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Fanconi Anemia (FA) is a rare autosomal recessive disorder characterized by hypersensitivity to inter-strand crosslinks (ICLs). FANCD2, a central factor of the FA pathway, is essential for the repair of double strand breaks (DSBs) generated during fork collapse at ICLs. While lesions different from ICLs can also trigger fork collapse, the contribution of FANCD2 to the resolution of replication-coupled DSBs generated independently from ICLs is unknown. Intriguingly, FANCD2 is readily activated after UV irradiation, a DNA-damaging agent that generates predominantly intra-strand crosslinks but not ICLs. Hence, UV irradiation is an ideal tool to explore the contribution of FANCD2 to the DNA damage response triggered by DNA lesions other than ICL repair. Here we show that, in contrast to ICL-causing agents, UV radiation compromises cell survival independently from FANCD2. In agreement, FANCD2 depletion does not increase the amount of DSBs generated during the replication of UV-damaged DNA and is dispensable for UV-induced checkpoint activation. Remarkably however, FANCD2 protects UV-dependent, replication-coupled DSBs from aberrant processing by non-homologous end joining, preventing the accumulation of micronuclei and chromatid aberrations including non-homologous chromatid exchanges. Hence, while dispensable for cell survival, FANCD2 selectively safeguards chromosomal stability after UV-triggered replication stress.
Fanconi anemia (FA) is a rare recessive disorder characterized by increased spontaneous rearrangements of chromosomes, tumorigenesis and cell death [1,2]. Initial signs of FA include bone or skeleton defects, renal dysfunction, short stature and very frequently abnormal hyper- and hypo-pigmentation of the skin and café_au_lait spots [3]. FA is characterized by bone marrow failure and high risk of developing myeloid leukemias and squamous cell carcinomas [4]. Cells derived from FA patients are strikingly sensitive to DNA interstrand crosslinks (ICLs), i. e. cross-links between two DNA strands. Consequently, much of our current understanding of FA comes from studies that utilize ICL-causing agents, such as mitomycin C (MMC), diepoxybutane or cisplatin, as sources of DNA damage [1,2]. To date, 17 genes with described mutations in patients were defined as components of the FA pathway that are all required for ICL repair [5]. ICL removal is generally accomplished when the replication fork abuts the DNA lesion. ICL-stalled replication forks undergo a programmed collapse, which is regulated by all FA proteins [6]. Firstly, FANCD2 is loaded onto the ICL, a process that requires the FA core complex, the D2 partner FANCI and D2 monoubiquitination [7]. Indeed, FANCD2-FANCI bind preferentially to a variety of branched DNA structures formed by ICL repair intermediates [8,9]. Moreover, the crystal structure of FANCI with DNA suggests that the ID2 complex could accommodate the X-shaped DNA structures formed by replication forks that collide with ICLs [10]. Secondly, FANCD2 recruits the XESS nuclease complex (including the nucleases XPF-ERCC1 and SLX1 and the scaffold protein SLX4) and the FAN1 and SNM1A nucleases [8]. Thirdly, these enzymes co-ordinately incise the DNA 3´and 5´of the lesion, thus unhooking the ICL. Finally, FANCD2 masters the resolution of such DNA repair intermediate by coordinating the activation of translesion DNA synthesis (TLS), homologous recombination repair (HRR) and possibly Nucleotide Excision Repair (NER) [1,2]. Collectively, solid evidence demonstrates that FANCD2 is crucial to ICL repair. Upon γIR, a source of replication-independent DSBs, ATM activates FANCD2 by phosphorylation [11]. However, FANCD2-deficient cells are only moderately sensitive to γIR and X-rays, another source of replication-independent DSBs [12–15]. In addition, FANCD2 does not play a predominant role in the repair of DSBs generated by restriction enzymes, but it is key to the resolution of ICL-dependent replication-coupled DSBs [16]. These results led to the assumption that FANCD2 is specifically required for the resolution of all replication-coupled but not direct DSBs. However, it is yet unclear whether FANCD2 resolves DSBs generated at replication forks stalled by lesions others than ICLs. It has been shown that the activation of FANCD2 during unperturbed S phase [17] suggests that FANCD2 participates in mechanisms unrelated to DSB repair. Indeed, FANCD2 prevents the nucleolytic degradation of nascent DNA triggered by hydroxyurea (HU) or aphidicolin (APH) and promotes fork restart immediately after drug removal [18–22]. Hence, FANCD2 not only promotes DSB repair by HRR but also attenuates DSB formation by protecting persistently stalled replication forks and promoting their reactivation. Intriguingly, FANCD2 is activated by UV irradiation, a DNA-damaging agent which rarely causes ICL accumulation [23,24] with no persistent stalling of replication forks at doses of 20 J/m2 or lower [25,26]. In contrast to ICL repair, the removal of UV-induced lesions does not require coordination between TLS and NER as both processes can occur independently from each other in UV-treated cells [27]. Moreover, NER efficiency is not altered in FA-defective backgrounds [28]. Importantly, FANCD2-deficient cells show normal spontaneous and UV-C-induced point mutation frequency [29] and null or very low sensitivity to UV-light [30–33]. Nonetheless, it is intriguing that the hypo/hyperpigmentation and the café_au_lait spots that characterize the FA disease are skin-associated defects. We thus reasoned that the function of FANCD2 after UV irradiation could be revealed by exploring processes that may not necessarily trigger cell death. We found that the UV irradiation of FANCD2-depleted cells with doses as low as 1. 5 J/m2 cause a striking increase of genomic instability markers, such as aberrant chromatid exchanges and micronuclei (MN) formation. The generation of both aberrations require DSBs [34,35]. While UV irradiation is not expected to directly cause DSBs, replication-associated one-ended DSBs (also known as double strand ends–DSEs) could accumulate when elongating forks encounter UV lesions [36,37]. Our results demonstrate that FANCD2 does not majorly modulate DSB accumulation. On the contrary, FANCD2 guarantees the correct processing of replication-coupled DSBs after UV irradiation. In particular, FANCD2 promotes the recruitment of the HRR factor RAD51 to UV-damaged DNA and the resolution of replication-associated DSBs by HRR. When FANCD2 is depleted, unleashed non-homologous end joining (NHEJ) increases genomic instability after UV irradiation. Hence, FANCD2 operates beyond ICL processing, and such function might apply to all replication-coupled DSBs generated after different genotoxic insults.
As reported by others [23,38], UV irradiation induces focal organization (S1A and S1B Fig) and monoubiquitination (S1C and S1D Fig) of FANCD2, both in U2OS and PD20 cells expressing FANCD2 (PD20+D2). However, FANCD2 depletion (Fig 1A) did not alter the cell cycle distribution after UV irradiation (whereas it did alter the cell cycle profile after MMC treatment, Fig 1B). Moreover, both the transient depletion of FANCD2 in U2OS cells (Fig 1A higher panel) and the permanent loss of FANCD2 in PD20 cells obtained from patients (Fig 1A lower panel) did not affect cell survival both in short (2 days) and long (8–10 days) term assays (however we observed hypersensitivity to MMC in FANCD2-depleted samples, Fig 1C–1D). To corroborate that the doses of UV radiation used can impact the clonogenic potential of U2OS cells, we depleted Pol η (to impair TLS). We observed that TLS-Pol η-depletion reduced the colony formation ability of UV-irradiated cells (S1E Fig), therefore demonstrating that UV hypersensitivity can be revealed in our settings. The undetectable contribution of FANCD2 to UV resistance is in agreement with four previous reports that found no effect of FANCD2 depletion on cell survival after UV irradiation [30–33] and other manuscripts that showed similar results when depleting FA core proteins (see Discussion). We reasoned that, while not affecting cell survival, FANCD2 depletion could jeopardize the stability of the genome after UV irradiation. To evaluate this possibility, we first analyzed MN formation at the lowest dose required to achieve a detectable difference between untreated and UV-irradiated samples (5 J/m2). Strikingly, when depleting FANCD2, the frequency of MN increased in UV-irradiated U2OS (Fig 2A and 2B) and in PD20 cells, when compared to control GM00637 fibroblasts or PD20 reconstituted counterparts, respectively (Fig 2C and 2D). MN are formed when DSB are processed in a manner that excludes fragments of chromosomes from nuclei during/ after karyokinesis and before cytokinesis [34]. Although not widely accepted, UV irradiation has been reported as a source of DSB formation [39–41]. We therefore inferred that the increase in MN in UV-treated FANCD2-depleted cells results from an increase in the number of DSBs and/or because of aberrant DSB processing. After UV irradiation, the most likely sources of DSBs are replication-coupled, one-ended double-strand ends generated at collapsed replication forks. The deficient resolution of replication-coupled DSBs increases replication-derived chromatid aberrations, which are specifically generated in S phase [42]. Thus, we evaluated the role of FANCD2 on chromatid aberrations after UV irradiation. We first determined the lowest dose required to upregulate these aberrations in control samples (1. 5 J/m2, Fig 2E and 2F). Interestingly, despite modest FANCD2 ubiquitination at low UV doses (S1F Fig), chromatidic breaks/gaps were upregulated in such conditions when FANCD2 was depleted (Fig 2E). Moreover, aberrations such as chromatid exchanges (mono and poly-radial chromosomes), which have been exclusively associated to replication-coupled DSBs [35,42] robustly increased in FANCD2-depleted but not in control cells (Fig 2F). Importantly, only chromatid (generated in S/G2 phase) but not chromosome (generated in G1/G0) exchanges [42] accumulated in UV-irradiated FANCD2-depleted samples (S2 Fig). Altogether, Figs 2 and S2 indicate that FANCD2 activation is required to avoid aberrant processing of replication-coupled DSBs after UV irradiation. The afore-mentioned results indicate that FANCD2 either prevents DSB formation or regulates their processing once they are formed. To explore the first possibility, we first analyzed PCNA monoubiquitination and Pol η recruitment to replication factories, two hallmarks of UV-triggered TLS, a well-characterized mechanism that aids DNA replication across UV-triggered DNA lesions and could thus prevent UV-induced DSB formation [43]. [43]. It has been previously demonstrated that FA core components [29,44] but not FANCD2 [29] promote TLS events after UV irradiation. However one report indicates that FANCD2 depletion reduces the ratio of Pol η focus formation over total Pol η signal in UV-irradiated (20 J/m2) Hela cells [45]. Based on these previous reports, we reasoned that the depletion of FANCD2 could modulate TLS markers in our settings. When analysing PCNA ubiquitination in FANCD2-depleted samples and PD20 cells (Figs 3A and S3A), alterations were not evident at time points (6 hours) in which TLS events are expected to be fully active [46] or at later (24hrs) time points at doses used in MN formation and induction of chromosomal aberrations (≤5 J/m2 –Figs 1 and 2). To further explore a potential modulation of TLS activity after FANCD2 knockdown we also evaluated the recruitment of TLS Pol η to replication factories, which is another parameter of TLS activation [47]. Here we observed that the proportion of cells with Pol η foci was not modulated by FANCD2 depletion in our experimental settings at 5 J/m2 (Fig 3B). This is in agreement with the previously reported negligible contribution of FANCD2 to PCNA ubiquitination, Rev1 recruitment to replication factories and the unaltered TLS-dependent mutagenesis of UV-irradiated FANCD2-depleted samples [29,48]. Hence, two central TLS parameters were not modulated by FANCD2 knockdown at UV doses such as 5 J/m2, which do alter the genomic stability of FANCD2-depleted samples. We then explored checkpoint activation, which is up-regulated by replication fork stalling and/or by increased DSBs levels. Chk1 phosphorylation is readily induced after low doses of UV irradiation [49] and increases when FA core components are depleted, possibly as a consequence of TLS defects [44]. In contrast, Chk1 phosphorylation at Ser 345 was transiently reduced 6hs -but not 24hs- post-UV in FANCD2-depleted U2OS and in PD20 cells (Figs 3C and S3B). Moreover, the extent and the timing of p53 activation and p21 downregulation after UV irradiation [50] were not modified when FANCD2 was depleted (Fig 3C). Together, these results suggest that there is no persistent reprogramming of TLS and Chk1 signals in FANCD2-depleted cells. We then asked whether the total number of DSBs increases in UV-irradiated samples after FANCD2 transient or permanent knockdown. Supporting the notion of a constant number of DSBs, we found that the activating phosphorylation of the histone variant H2AX (γH2AX—S139) [51] increased in a manner that depended on the UV dose but not on the levels of FANCD2 (Fig 4D). Moreover, when specifically focusing on the 5 J/m2 dose, the intensity of the γH2AX signal modestly increased with respect to sham-irradiated controls with no significant changes after FANCD2 depletion (Fig 4A). The percentage of cells with γH2AX foci (Figs 4B, S4A and S4C) and the number of γH2AX foci per cell (Fig 4C) were also unaffected by FANCD2 depletion. These results are opposite to those obtained when we analyzed FANCD2-depleted cells treated with the ICLs inducer, MMC (S4B and S4C Fig). Since γH2AX foci can be formed in the absence of DSBs [52] we evaluated other markers of DSBs such as the phosphorylation of ATM kinase at S1981 or of KAP1 at S824 [7,53]. p-ATM did not increase and rather decreased in FANCD2-depleted samples (U2OS in Fig 4D and PD20 cells in S3C Fig). Similarly, pKAP1 levels did not increase in UV-irradiated FANCD2-depleted samples (Figs 4D and S3C). Our results are thus in agreement with a recent report from the Vaziri group showing Tunnel negative staining of FANCD2-depleted samples [54]. Collectively, these data suggest that FANCD2 depletion does not increase the levels of DSBs both before and after UV irradiation. To confirm this hypothesis, we set up a Pulse Field Gel Electrophoresis (PFGE) analysis to directly measure DSB formation. We observed no significant differences between control and FANCD2-depleted samples both 6 and 24 hours post-UV irradiation (Fig 4E). Similar results were obtained in PD20 cells (S4C Fig). While it might be argued that PFGE might have low sensitivity to detect small amounts of DSBs, our experimental setup proved to be sensitive enough to detect DSBs even at the lowest doses of UV irradiation (Fig 4E). Moreover, as a control of our PFGE experimental setup, we confirmed that FANCD2 prevents DSB accumulation in MMC-treated (S4E Fig) but not in UV-irradiated samples (S4D Fig). Collectively, the experiments in Figs 3 and 4 and S3 and S4 suggest that the infrequent DSBs that accumulate after UV irradiation are not upregulated by FANCD2 depletion. Rad51 is a highly conserved protein that promotes homology search and strand invasion events during HRR [55]. Rad51 recruitment to chromatin is thus a hallmark of HRR activation. We therefore analyzed the local recruitment of Rad51 to unshielded regions within UV irradiated nuclei to explore the FAND2 contribution to UV-dependent HRR (Fig 5A–5C). Interestingly, transient or permanent depletion of FANCD2 in U2OS and PD20 cells impaired Rad51 recruitment to unshielded nuclear regions (Fig 5B and 5C). To evaluate the functional contribution of FANCD2 to UV-induced HRR, we explored the frequency of homologous recombination events evidenced as the exchange of large DNA regions between sister chromatids (sister chromatid exchange-SCE) [56]. The defective accumulation of SCEs indicates defects in HRR activation at replication-associated DSBs [57]. Notably, the number of SCE decreased in UV-irradiated FANCD2-depleted samples (Fig 5D). This result suggests that FANCD2 directs the processing of UV-triggered DSBs generated at collapsed forks into HRR resolution. Cells choose to repair DSBs by HRR or NHEJ mainly depending on its replicative status [58]. Therefore, we evaluated the effect of FANCD2 depletion on the recruitment to γH2AX foci of a factor that is recruited to DSBs committed to NHEJ, the BRCT-containing protein 53BP1 [59,60]. Interestingly, the percentage of 53BP1 foci colocalizing with γH2AX foci was upregulated in UV-irradiated FANCD2-depleted samples (Fig 5E). Consistently, the total number of cells with 53BP1 foci increased in UV-treated FANCD2-depleted samples, albeit less markedly than after MMC treatment (to allow an easier comparison, the percentages of cells with 53BP1 foci in UV and MMC treated-cells are shown as overlapped bars in Fig 5F). Moreover, the cells with increased 53BP1 foci were almost exclusively those that were transiting S phase at the time of UV irradiation (S5A–S5C Fig), demonstrating that FANCD2 may prevent NHEJ events in S-phase. It is important to mention that other functions of 53BP1 such as the shielding of fragile DNA in G1 phase were recently documented [61,62]. Such 53BP1 structures are generated because of defective chromosomal segregation and are characterized by fewer but larger 53BP1 foci in G1 [61,62]. To evidence such 53BP1 foci we performed an EdU incorporation right before fixation and focused our analysis in EdU negative samples (S5D Fig). In such experimental settings, the percentage of cells with 53BP1 foci were unaffected by UV-irradiation in cells depleted from FANCD2 (S5E Fig). Hence, FANCD2 promotes the recruitment of HRR factors but not of NHEJ factors to UV-damaged DNA in cells transiting S phase. To evaluate the contribution of NHEJ to the genomic instability of FANCD2-depleted cells, we transiently downregulated the NHEJ core component XRCC4 [63]. The depletion of XRCC4 in U2OS cells (S6A Fig) had no effect on the number of cells with 53BP1 foci (S6B Fig), the levels of DSBs (Figs 6A and S6C), the clonogenic potential (S6D Fig) or the accumulation of chromosomal abnormalities (Fig 6B–6D) in sham- or UV-irradiated samples. As NHEJ is a pathway that resolves replication-independent DSBs [15], this result indicates that UV is not a source of such DSBs, while UV might trigger replication-coupled DSBs. The simultaneous depletion of XRCC4 and FANCD2 did not affect DSB accumulation (Figs 6A and S6C) in comparison to FANCD2- or sham-depleted samples, thus reinforcing the notion that FANCD2 depletion does not contribute to DSB formation. Cell survival was also unaffected by simultaneous depletion of XRCC4 and FANCD2 (S6D Fig). However, the percentage of cells with 53BP1 foci increased (S6B Fig), thus suggesting a potential delay in the processing of DSB at such foci in XRCC4- and FANCD2-depleted cells. Remarkably, XRCC4 depletion rescued the accumulation of chromatid aberrations and MN formation caused by FANCD2 depletion (Fig 6B–6D). Similarly, XRCC4 depletion rescued MN accumulation in PD20 cells (S7A–S7C Fig). Importantly, the prevention of MN accumulation after UV irradiation depended predominantly on FANCD2 ubiquitination as PD20 cells expressing the FANCD2 K561R mutant (PD20+D2 KRo) had MN levels similar to those in PD20 cells (S7B and S7C Fig). Moreover, the increased UV-associated genomic instability of PD20 cells expressing FANCD2 K561R was also rescued by XRCC4 depletion (S7B and S7C Fig). Finally, MN accumulated primarily in EdU-positive cells (S7D and S7E Fig), i. e. cells transiting S phase at the time of UV irradiation (see timeline in S7D Fig). Altogether, these results demonstrate that FANCD2 is crucial to the repair of replication-derived DSBs generated independently from ICLs. In contrast to FANCD2 function during ICL repair, FANCD2-dependent DSB repair pathway choice after UV irradiation is irrelevant to cell survival but it is key to safeguarding genomic stability.
It has been previously reported that the elimination of the FA pathway has a modest or null effect on UV sensitivity. In fact, with the exception of FANCM, cells deficient in FANCC, FANCA, FANCE, FANCL, FANCD2 and FANCJ are not or modestly hypersensitive to UV light ([23,30–33,44,64–67] and this work). Remarkably however, we have unveiled a function of FANCD2 after UV irradiation. In particular, we show that FANCD2 preserves genomic stability by modulating the correct processing of DSBs generated during the replication of UV-damaged DNA. Whereas DSBs are not caused directly by UV irradiation [68], the accumulation of DSBs have been previously reported after 8–10 J/m2 [39–41]. Indeed, we demonstrate herein that DSBs are formed at UV doses of ≤5 J/m2. For example, UV doses as low as 1. 5 J/m2 induce SCE in control samples and complex aberrations (radials) in FANCD2-depleted samples. The formation of SCEs, aberrant chromatid exchanges and MN in binucleated cells require not only DSBs, but also DNA replication [69]. Therefore, UV-triggered DSBs are most likely generated as a consequence of DNA replication across damaged DNA. In fact, ATM phosphorylation after UV irradiation takes place predominantly in S phase [41]. Moreover, 53BP1 foci and MN in FANCD2-depleted cells accumulated almost exclusively in cells transiting S-phase at the time of UV irradiation (see S5 and S7 Figs). Thus, UV irradiation generates DSBs, most likely at collapsed replication forks. It should be noted that occasional ICLs, which depend on an alternative conformation of DNA that approximates pyrimidines from different strands, were also reported after UV irradiation [70–72]. In fact, when irradiating plasmidic DNA in vitro, a dose of 1000 J/m2 (260 nm) was required to accumulate ~0. 07 ICLs/kbp [24]. While we cannot formally discard their contribution, it is unlikely that such a sporadic event could predominate over other types of fork collapses (at frequent UV lesions such as unrepaired cyclobutane pyrimide dimers and 6–4 photoproducts). Moreover, FANCD2 differentially contributes to the replication of UV- and MMC-damaged DNA (see next section), thus reinforcing a difference in the fork-collapsing event after both treatments. Despite their increased genomic instability, FANCD2-depleted cells did not show increased DSB levels. In fact, PFGE did not reveal substantial changes in the accumulation of DSB in FANCD2–depleted samples. Consistently, KAP1 phosphorylation (a DSB marker) was not upregulated, and ATM and Chk1 phosphorylation were transiently downregulated. These results indicate that FANCD2 might process DNA repair intermediates at collapsed forks, generating substrates for ATM and Chk1 activation. Such speculation is supported by recent results indicating that after ICLs, DNA ends are resected into HRR-proficient substrates that promote robust ATM activation [73]. While we cannot further speculate on the signals leading to impaired ATM and Chk1 activation in UV-irradiated FANCD2-depleted samples, it is evident that in agreement with our PFGE results, the lack of upregulated phosphorylation of KAP1, ATM and Chk1 argues against a role of FANCD2 in the prevention of DSB accumulation after UV irradiation. Our results indicate that the main role of FANCD2 after UV irradiation is to direct DSBs into HRR repair (Figs 2 and 6). This implies that FANCD2 may be crucial to the repair of replication-coupled DSBs that arise from sources other than ICLs. Indeed, our results suggest that the functions of FANCD2 in the cellular response to UV irradiation and ICL accumulation partially overlap. However, the responses are not equivalent. This conclusion is supported by the following observations: A) FANCD2 depletion does not trigger cell death after UV irradiation, which is strikingly different from the significant increase in cell death observed after MMC treatment in FANCD2-depleted cells. Moreover, while NHEJ deficiency either rescues or exacerbates cell death in FANCD2 deficient samples treated with ICL inducers [74–76], we revealed an insignificant effect of XRCC4 depletion in the survival of UV-irradiated FANCD2-depleted cells. B) NHEJ depletion abrogates all the chromatid aberrations caused by UV irradiation in FANCD2-depleted cells. While similar results were reported in other systems using MMC [74,75], the simultaneous elimination of FANCD2 and KU80 after MMC and cisplatin treatments in mammalian cells not only fails to abrogate, but instead further increases chromosomal instability [76]. Hence, while in response to UV- and ICL-damaged DNA FANCD2 facilitates HRR, the quality and/or quantity of DSBs may not be equivalent in both scenarios. In fact, HRR most likely takes place after the convergence of two opposite replication forks at the ICL [8]. Therefore, the HRR substrate during ICL repair may resemble a canonical double-ended DSB, which could be repaired by NHEJ without causing a massive chromosomal rearrangement. In contrast, fork collapse induced by UV irradiation may generate DSEs which, in FANCD2-depleted backgrounds, may induce gross chromosomal rearrangements when processed by NHEJ. Alternatively, different nucleases may be recruited to DSBs after UV irradiation or ICLs. In this respect, it should be mentioned that FANCD2 not only recruits nucleases to ICLs but also to DNA lesions generated by HU [21]. While the nuclease in charge of the processing of UV-triggered DSBs remains unidentified, we postulate that FANCD2 mediates the processing of collapsed forks into HHR-proficient substrates. In fact, as mentioned before, defective Chk1 activation may indicate defective processing of DNA in the absence of FANCD2. Since FA patients are not normally exposed to ICLs agents, a major concern of clinical relevance is to identify life-threatening sources of stress in FA patients. The group of K. Patel has elegantly shown that aldehydes are an endogenous source of ICLs [77] and that the enzyme Aldh2 is essential to prevent the accumulation of aldehyde-derived ICLs [78]. Tissues with low levels of Aldh2, e. g. the hematopoietic linage, rely heavily on the FA pathway to process ICLs generated from endogenous aldehydes [79,80]. Hence, endogenous ICLs represent important triggers for oncogenesis in FA patients. But whether they represent the sole trigger for genomic instability in FA patients is still unresolved. While previous studies have proposed that the contribution of FANCD2 to the resolution of DSBs might be specifically linked to inter-strand ICLs [12,14,16,81], our report demonstrates that replication-coupled DSBs unrelated to ICLs may require FANCD2 for their repair through the HRR pathway. In addition, unanticipated HRR-independent functions of FANCD2 have been recently identified. Pioneer work from K. Schlacher and M. Jasin showed that FANCD2 and BRCA2/FANCD1 prevent degradation of nascent DNA in HU-treated cells [18,19]. It has also been shown that after HU, and in a core-independent manner, FANCD2 in concert with the Bloom helicase (BLM) restart stalled replication forks while suppressing origin firing [20,22]. In FANCD2 depleted samples, increased aberrant rearrangements of chromosomes were reported in [18,19] and increased frequencies of MN where reported in [20,22]. It is therefore possible that the defects in chromosomal integrity observed after UV irradiation are the indirect consequence of DSB-independent functions of FANCD2 at replicating DNA after UV irradiation. However, a number of evidences disfavour such hypothesis. First, the DSBs-independent contribution of FANCD2 after HU has been associated with persistent fork stalling [19], which is not frequent event after UV irradiation doses used in this study [25,26]. Second, the chromosomal integrity of FANCD2-depleted cells after UV is restored when NHEJ is silenced, therefore suggesting that the main function of FANCD2 is related to the processing of DSBs rather than to DNA replication events taking place prior to DSB formation. Third, the events taking place prior to DSBs processing after HU are independent of FANCD2 ubiquitination [82] whereas the UV-triggered events, which take place after DSB formation, are dependent on FANCD2 ubiquitination (see S7 Fig). Moreover, it is also reasonable to speculate that after HU treatment, the accumulation of at least some aberrations in FANCD2-depleted cells, e. g. the non-homologous exchanges [19] require the elimination of the FANCD2-mediated facilitation of DSB resolution by HRR (in addition to the disruption of FANCD2 functions at nascent DNA). Hence, while it is conceivable that during the replication of UV-damaged DNA FANCD2 participates in more than one (HRR-dependent and independent) process, results in Fig 6 demonstrate that the inhibition of NHEJ is a function of FANCD2, which must obligatorily be disrupted to generate many -if not all- the chromosome aberrations observed after UV irradiation. Remarkably, uncontrolled NHEJ at replication-coupled DSBs might also be the source of the chromosomal abnormalities reported in FANCD2-depleted samples subjected to replication-stressing agents such as HPV 16 E6/E7 expression [83], HU/APH treatments [19,21,84], PARP inhibition [85], R-loop accumulation [86], and dysregulated Pol κ recruitment to replication forks [87]. It is unclear to us why genomic stability but not cell survival is affected by FANCD2 depletion after UV irradiation. Similar results were reported after HU treatment [19]. It is possible that the DSBs generated by UV irradiation and HU are infrequent and therefore only tangentially contribute to cell death. Alternatively, while unresolved DSBs could be extremely toxic, their resolution, even when aberrant (e. g. in a FANCD2 depleted sample), may suffice to prevent cell death. Indeed, our data reveals multiple backup mechanisms that promote resolution of DSBs. Hence, when forks collapse, resolution mechanisms that promote cell survival may prevail even when genomic stability is compromised with multiple rearrangements. Our results suggest that low levels of replication-associated DSBs may be an important oncogenic factor if FANCD2 is not available to direct them into an error free pathway. FANCD2 is also required for the spontaneous levels of SCEs in uveal melanoma [88], thus we speculate that even during unperturbed replication FANCD2 regulates the pathway choice for DSBs repair. We propose a surveillance role for FANCD2 that is required to resolve replication-associated DSBs arising from any stress source and which might be relevant for the etiology of cancer in FA patients.
The following cells were used: U2OS cells (ATCC), GM00637 (Coriell Repositories), FANCD2-deficient PD20 cells (GM16633—Coriell Repositories) and two reconstituted counterparts, PD20 + D2 (GM16634—Coriell Repositories, a microcell hybrid expressing low levels of wt FANCD2) and PD20 + D2O (PD20 cells expressing full-length FANCD2 cDNA), and PD20 K561R (overexpressed FANCD2 mutant with mutated K561 lysine). PD20, PD20 K561R and PD20 + D2 cells were a gift from J. Surralles (Universidad de Barcelona, Spain) and PD20 + D2O from T. Huang (New York University). All cells were grown in Dulbecco’s modified Eagle’s medium (Invitrogen) supplemented with 10% fetal calf serum. Transfections were performed using Jet Prime (Polyplus). GFP-Pol η was a gift from A. Lehmann. UVC irradiation was performed using a CL-1000 ultraviolet cross-linker equipped with 254 nm tubes (UVP) or a XX-15S UV bench lamp from UVP. For local irradiation, a polycarbonate filter with 5 μm pores (Millipore # TMTP01300) was positioned in direct contact with cells, which were then treated with 100 J/m2 -equivalent to a much lower dose than the one reported in [89]. siRNA duplexes (Thermo-Fisher Scientific) were the following: siFANCD2: 5-UUGGAGGAGAUUGAUGGUCUA-3 [90], siXRCC4: 5-AUAUGUUGGUGAACUGAGA-3 [91] siPol η: 5-CUGGUUGUGAGCAUUCGUGUA-3 has been recently described [92] and in our laboratory was designed by using the Invitrogen Block-iT RNAi Designer program validated with Dharmacon siRNA design software. siLuc: 5-CGUACGCGGAAUACUUCGA-3 [93]. For the immunodetection of FANCD2, Rad51,53BP1 and γH2AX, cells were fixed in 2% paraformaldehyde (PFA) /sucrose and permeablized with 0. 1% Triton X-100 in phosphate buffered saline (PBS). Well-assembled GFP- Pol η foci were quantified after fixation with ice-cold methanol followed by a 30-second incubation with ice-cold acetone as previously described by us [93]. EdU was detected following manufacturer’s instructions (Click-iT EdU kit– C10338). Blocking was performed overnight in PBS 2% donkey serum (Sigma). Coverslips were incubated for 1 h in primary antibodies: α FANCD2 (Novus), α Rad51 (Calbiochem), α γH2AX (Ser 139, Upstate), α 53BP1 (Santa Cruz). Secondary α-mouse/rabbit-conjugated Cy2/Cy3 antibodies (Jackson Immuno Research) and α -rabbit Alexa 488 (Invitrogen) were used. GFP-Pol η was detected by GFP auto-fluorescence. Nuclei were stained with DAPI (Sigma). Images were obtained with a Zeiss Axioplan confocal microscope or a Zeiss Axio Imager. A2. When quantifying GFP-pol η nuclear focal structures, cells with more than 10 foci were considered positive. When quantifying cells with Rad51 recruitment to locally irradiated areas of nuclei revealed by DAPI staining, only fields with γH2AX (+) staining were analyzed. Rad51 was always recruited to γH2AX (+) regions for all conditions tested. γH2AX staining was positive in 50% of the nuclei for all conditions tested. To quantify γ-H2AX intensity 100x images were analyzed with ImageJ. Approximately 30 pictures per condition were evaluated (300 cells); DAPI images were used as a pattern to define the position of nuclei on the images. The γ-H2AX intensity was determined in 300 nuclei/sample in arbitrary units, which were expressed as a fold increase with respect to the untreated control (siLuc non-irradiated). Western blots were performed using the following antibodies: α FANCD2 (Santa Cruz Biotechnology; FI17), α Ku70 (Santa Cruz Biotechnology; A9), α PCNA (Santa Cruz Biotechnology; PC10), α phospho- (S1981) -ATM (Millipore), α ATM (GeneTex 2C1), α phospho- (S345) -Chk1 (Cell Signalling), α Chk1 (Santa Cruz Biotechnology, G4), α p21 (Santa Cruz Biotechnology, C19), α p53 (DO-1 and 1801) and α γH2AX (Upstate). α phospho (S824) KAP1 (Bethyl Laboratories), α KAP1 (Bethyl Laboratories), α Pol η (Santa Cruz Biotechnology; H-300). Incubation with secondary antibodies (Sigma) and ECL detection (Amersham GE Healthcare) were performed according to the manufacturers' instructions. Western blot images were taken with Image QuantLAS4000 (GE Healthcare), which allows capture and quantification of images within a linear range. These images were then quantified with the ImageJ software. While U20S cells can be used in clonogenic assays, PD20 cells did not resist such harsh treatment in our experimental settings. Clonogenic assays performed in U2OS cells involved an initial siRNA transfection step in 35-mm dishes, followed by replating 200 cells per 60-mm plate (2 plates per condition) and UV irradiation 24 hours later. 8–10 days later, colony formation was visualized by crystal violet staining. Colonies with more than 40 cells were scored as positive. For PD20 (and U2OS) cells, a viability kit was used at earlier time points (up to 72 hours). Transfected or PD20 and PD20 + D2 cells were plated in 96-well plates; 24 hours later cells were UV irradiated or treated with Mitomicyn C (MMC, Roche). When using MMC, treatment was interrupted 15 hrs later and samples were washed and incubated with fresh growing medium. The analysis was performed at the indicated hours after release. PD20 cells were subjected to the Cell Viability Assay following manufacturer’s instructions (CellTiter-Glo Luminescent Cell Viability Assay G-7570, Promega). Cells were fixed with ice-cold ethanol and resuspended in PBS containing RNase I (100 mg/ml, Sigma) and propidium iodide (50 mg/ml, Sigma). Samples were subjected to fluorescence activated cell sorting (FACS, Calibur, Becton Dickinson), and data was analyzed using the Summit 4. 3 software (DAKO Cytomation). U2OS and PD20 cells were plated at low density, UV irradiated 24 hours later and incubated with cytochalasin B (4. 5 ug/ml, Sigma) for 40 h (U2OS) and 24 hrs (PD20). Cells were washed 1 min with hypotonic buffer (KCl 0. 0075 M), twice with PBS and fixed with paraformaldehyde (PFA) /sucrose 2% for 20 min. Phalloidin and DAPI staining served to visualize whole cells and nuclei respectively. 300 binucleated cells were analyzed and the frequency was calculated as MN/binucleated cells. Metaphase chromosome spreads were generated introducing minor modifications to protocols previously used by us [94]. Briefly, U2OS transfected cells were replated and UV irradiated (1. 5 J/m2). Before harvesting, cells were treated with Colcemid (0. 08 μg/ml, KaryoMAX, Invitrogen) for 20 h. Cell pellets were incubated in hypotonic buffer (KCl 0. 0075 M) at 37°C for 4 min, followed by fixation in Carnoy’s fixative (3: 1 methanol: glacial acetic acid). Cells were dropped onto slides and air-dried before staining with 6% w/v Giemsa in Sorensen’s buffer (2: 1 67 mM KH2PO4: 67 mM Na2HPO4, pH 6. 8) for 2 min. Samples were analyzed in an Applied Imaging Cytovision 3. 7. 50 metaphase spreads were used to quantify chromosomal gaps, breaks and exchanges. This protocol was set up to enrich samples with cells transiting the first cell cycle after UV irradiation. Transfected U2OS cells (with siLuc and siD2) were UV irradiated (1. 5 J/m2). To generate the differential staining of sister chromatids, cells were incubated with the thymine analogue 5-bromo-2´-deoxyuridine (BrdU, 20 μM, Becton Dickinson) for two complete cell cycles. Colcemid (0. 08 μg/ml, KaryoMAX, Invitrogen) was added 20 h before harvest. Metaphase chromosome spreads were prepared as mentioned above (see Chromosomal aberration analysis). Slides were air dried for 5 days, stained with Hoechst (5 μg/ml, Invitrogen), irradiated with a sun lamp (Ultra-Vitalux, OSRAM) for 7 min and finally stained with 6% w/v Giemsa in Sorensen’s buffer for 2 min. The treatment with Hoechst dye and Giemsa allows the newly synthesized DNA within a chromatid to be recognized, since BrdU incorporation results in much weaker staining. Sister-chromatid exchanges (SCE) were scored analysing chromosomes in 50 metaphase spreads. To prepare agarose plugs we used the protocol reported in [52] with minor modifications. Briefly, samples were UV irradiated, 6 or 24 h later 1 x 105 cells were melted into 1. 0% Pulsed Field Certified Agarose (Bio-Rad Laboratories). Agarose plugs were digested in 0. 5 M EDTA-1% N-laurylsarcosyl-proteinase K (1 mg/ml, Invitrogen) at 50°C for 48 h and washed four times in TE buffer and loaded onto a separation gel (1. 0% Pulsed Field Certified Agarose). Electrophoresis was performed on CHEF DR II equipment (Bio-Rad Laboratories) as previously described in [52]. A second electrophoresis protocol was also used [49], with minor modifications: 9 h, 120°, 5. 5 V/cm, 30–18 s switch time; 6 h, 120°, 4. 5 V/cm, 18–9 s switch time; 6 h, 120°, 4 V/cm, 9–5 s switch time, for 24 hr. A 2h-bleomycin (100 μg/mL, Gador) treatment was used as a positive control. Ethidium bromide–stained gels were visualized in a White Ultraviolet Transilluminator (UVP) or with Image Quant LAS4000, which allows capture and quantification of images within a linear range. PFGE images were then quantified with the ImageJ software. Cells were lysed and total RNA was extracted using Trizol Reagent (Invitrogen). 1 μg of total RNA was used as template for cDNA synthesis using ImProm-II Reverse Transcription System (Promega) and oligo-dT. Quantitative real-time PCR was performed in a MX3005P qPCR instrument (Stratagene) with Taq DNA polymerase (Invitrogen) and SyberGreen and ROX as reference dyes (Invitrogen). All amplification reactions approached 100% efficiency as determined by standard curves. Three independent biological samples were analyzed and one representative set of results is shown. Primers used for Quantitative Real Time PCR analysis: XRCC4 (f) 5′-AAGATGTCTCATTCAGACTTG-3′ (r) 5′ CCGCTTATAAAGATCAGTCTC-3′ [95]. GADPH: (f) 5’-AGCCTCCCGCTTCGCTCTCT-3’ (r) 5’-GAGCGATGTGGCTCGGCTGG-3’. [96] GraphPad Prism 5 software was used to analyse SCE, for cytogenetic experiments and foci formation experiments we used the Student' s t test. Other calculations and graphics were performed by using Microsoft Excel 2010. | Here we show that irradiation with low doses of UV light causes modest accumulation of replication-coupled double strand breaks (DSBs), i. e. collapsed forks. Remarkably, the Fanconi Anemia protein FANCD2 is central to prevent the aberrant processing of UV-triggered DSBs and the generation of micronuclei and chromosome fusions but is dispensable to modulate cell death. Specifically, FANCD2 promotes homologous recombination-dependent repair of UV-triggered DSBs, thus preventing their aberrant processing by non-homologous end joining. Hence, the homologous recombination-dependent tumor suppressor function of FANCD2 is not restricted to inter-strand crosslinks but instead extends to replication-coupled DSBs that arise from a broader range of genotoxic stimuli. | Abstract
Introduction
Results
Discussion
Materials and Methods | 2016 | Chromosomal Integrity after UV Irradiation Requires FANCD2-Mediated Repair of Double Strand Breaks | 11,806 | 213 |
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The use of the bacterium Wolbachia is an attractive alternative method to control vector populations. In mosquitoes, as in members of the Culex pipiens complex, Wolbachia induces a form of embryonic lethality called cytoplasmic incompatibility, a sperm-egg incompatibility occurring when infected males mate either with uninfected females or with females infected with incompatible Wolbachia strain (s). Here we explore the feasibility of the Incompatible Insect Technique (IIT), a species-specific control approach in which field females are sterilized by inundative releases of incompatible males. We show that the Wolbachia wPip (Is) strain, naturally infecting Cx. p. pipiens mosquitoes from Turkey, is a good candidate to control Cx. p. quinquefasciatus populations on four islands of the south-western Indian Ocean (La Réunion, Mauritius, Grande Glorieuse and Mayotte). The wPip (Is) strain was introduced into the nuclear background of Cx. p. quinquefasciatus mosquitoes from La Réunion, leading to the LR[wPip (Is) ] line. Total embryonic lethality was observed in crosses between LR[wPip (Is) ] males and all tested field females from the four islands. Interestingly, most crosses involving LR[wPip (Is) ] females and field males were also incompatible, which is expected to reduce the impact of any accidental release of LR[wPip (Is) ] females. Cage experiments demonstrate that LR[wPip (Is) ] males are equally competitive with La Réunion males resulting in demographic crash when LR[wPip (Is) ] males were introduced into La Réunion laboratory cages. These results, together with the geographic isolation of the four south-western Indian Ocean islands and their limited land area, support the feasibility of an IIT program using LR[wPip (Is) ] males and stimulate the implementation of field tests for a Cx. p. quinquefasciatus control strategy on these islands.
The last few years have witnessed an increasing interest in the alpha-proteobacterium Wolbachia (Rickettsiales) for the biological control of insect pest populations [for reviews see [1]–[5]. Wolbachia is the most common intracellular bacterium yet described [6], [7], present in more than 65% of insect species and found in all major insect families [8]. Some medically important mosquitoes are naturally infected by Wolbachia, such as the common house mosquito Culex pipiens [9], [10] and the Asian tiger mosquito Aedes albopictus [11], or can otherwise be artificially infected, such as the yellow fever mosquito Ae. aegypti [12]–[14]. Wolbachia is vertically inherited from a female host to its progeny through the egg cytoplasm, males being a dead end in terms of transmission [4], [15]. Wolbachia is usually termed a ‘reproductive parasite’ in the sense that it optimizes its transmission by manipulating its host' s reproductive biology [15], [16]. In mosquitoes, Wolbachia induces a form of embryonic death called cytoplasmic incompatibility (CI) [9]. This phenomenon results from sperm-egg incompatibility occurring when Wolbachia-infected males mate with uninfected females or females infected with an incompatible Wolbachia strain [17]. Therefore, CI has been investigated as a mechanism to control field populations [1], [18], [19], [20]–[22], or to drive transgenes into field populations [2], [3], [10], [23]. In addition, recent investigations showed that Wolbachia can affect virus transmission both by reducing the lifespan of the infected vector and by interfering with the arthropod-borne parasite [14], [24]–[26]. Mosquitoes of the Cx. pipiens complex are of special interest for Wolbachia-based control strategies. The most common members of the complex are the subspecies Cx. p. quinquefasciatus (Say) and Cx. p. pipiens (Linnaeus) (also considered as true species, depending on the authors), representing the southern and northern mosquito populations, which are ubiquitous in tropical and temperate regions, respectively [27]. This mosquito is the main vector of lymphatic filarial in Comoros and Madagascar [28] as well as a known vector for many arboviruses worldwide [29]. This is the case, for example, of the West Nile Virus (WNV), recrudescent in Mediterranean countries [30], [31] and in the United States where thousands of cases have been identified in the last decade [32], [33]. This species also transmits the Rift Valley Fever (RVF) virus, currently expanding in the Indian Ocean [34], [35]. Members of the Cx. pipiens complex are naturally infected with different Wolbachia strains, referred as wPip strains. The prevalence is high in natural populations with wPip infections near to fixation [10], [36], [37]. Recent multi-loci typing approaches revealed that the wPip strains cluster into five distinct phylogenetic groups (referred as wPip-I to V) which form a robust monophyletic clade within the B group of Wolbachia [38]. The Cx. pipiens complex exhibits the largest variation of CI crossing types observed in arthropods thus far [39]–[43]. When Cx. pipiens individuals are infected by different Wolbachia strains (here arbitrarily named wPip (1) and wPip (2) ), their crosses can be (a) compatible and produce viable offspring; (b) incompatible in both directions and produce infertile eggs (a phenomenon called bidirectional CI); or (c) incompatible in one direction only (unidirectional CI, e. g. the cross between wPip (1) males and wPip (2) females is incompatible, while the reciprocal cross is compatible). The presence of incompatible wPip infections in the Cx. pipiens system makes unnecessary the artificial introduction of exogenous Wolbachia strains, and encourages the development of a Wolbachia-based control strategy. Here, we examined the feasibility of an ‘Incompatible Insect Technique’ (IIT) strategy targeting Cx. pipiens natural populations. IIT derives from the ‘Sterile Insect technique’ (SIT) notably used in the control of the New World screwworm Cochliomyia hominivorax [44]. In both SIT and IIT, mating of released sterilizing males with native females leads to a decrease in the females' reproductive potential and ultimately, if males are released in sufficient numbers over a sufficient period of time, to the local elimination or eradication of the pest population [3], [20], [22], [45]. In the SIT program, males are sterilized with irradiation or chemicals, which might weaken the fitness of sterilized insects, making them less competitive than field males for mating [46], [47]. In the IIT strategy, Cx. pipiens males are infected by a wPip strain incompatible with the wPip strain (s) infecting field females. In this case, the released incompatible males are not expected to suffer any reduction in mating when competing with field males. The IIT strategy has been successfully applied in a field trial assay targeting Cx. pipiens populations in Burma [48] as well as in cage experiments with the Polynesian tiger mosquito Ae. polynesiensis [49] and the medfly Ceratitis capitata [19]. We focused on natural populations of Cx. p. quinquefasciatus collected on five islands in the south-western Indian Ocean (SWIO): La Réunion, Mauritius, Mayotte, Madagascar and Grande Glorieuse. Prior studies have demonstrated that Cx. p. quinquefasciatus lines from La Réunion are infected with closely related wPip strains which express complete CI (ca. 100% embryo mortality) with Cx. pipiens lines from distant geographic areas and infected by genetically different wPip strains [43]. The Cx. p. pipiens Is line from Turkey, infected by the wPip (Is) strain, is of particular interest: all crosses between Is males and females from La Réunion are incompatible and almost all reciprocal crosses are incompatible as well [43]. This complete bidirectional CI makes the wPip (Is) strain a good candidate for an IIT program. In this study, we obtained robust data that encourage the use of wPip (Is) -infected Cx. p. quinquefasciatus males in an IIT program which could be implemented on the SWIO islands. First, the regional genetic diversity of wPip infections is low as all identified wPip strains belong to the wPip-I group; this indicates that immigration of mosquitoes into the controlled area is unlikely to introduce a new wPip strain compatible with wPip (Is) -infected males. Second, the wPip (Is) strain, from the wPip- IV group, was introduced into the nuclear background of Cx. p. quinquefasciatus mosquitoes, leading to a line (LR[wPip (Is) ]) expressing complete CI with wild females sampled from all 5 SWIO Islands. Last, CI properties expressed by this line are optimal as (i) there is no effect of males ageing on CI expression, (ii) LR[wPip (Is) ] males show similar body size and longevity as males from La Réunion Island, suggesting good competitiveness of incompatible males vs. wild males, which was further confirmed in cage confrontations and (iii) LR[wPip (Is) ] mosquitoes are mainly bidirectionally incompatible with La Réunion, Mauritius, Mayotte and Grande Glorieuse field mosquitoes: this lowers the risk of Wolbachia replacement possibly induced by accidental releases of LR[wPip (Is) ] females.
Two laboratory lines of Cx. pipiens mosquitoes naturally infected by Wolbachia were used in the experiments: the isofemale line Is, a Cx. p. pipiens line from Turkey infected by the wPip (Is) strain, and the Cx. p. quinquefasciatus LR line, infected by the wPip (LR) strain, and established from several hundred field-caught larvae in La Réunion island (Table 1 and Figure 1). In addition, one uninfected line, LR-TC, was generated by curing Wolbachia of mosquitoes from the LR line with antibiotic, following the protocol described in [50]. Briefly, ca. 5,000 LR larvae were reared for three generations in a solution containing tetracycline hydrochloride at concentrations of 10−4,2×10−4 and 4×10−4 M for the first, second and third-instar larvae, respectively. Mosquitoes from LR-TC were next reared for at least two generations in the absence of tetracycline before experiments, to prevent any possible side-effects of the treatment. Field Cx. p. quinquefasciatus larvae and pupae were collected during the summers 2007–2011 in 29 natural breeding sites on five islands of the Indian Ocean: La Réunion (16 populations), Mauritius (four populations), Mayotte (three populations) Madagascar (five populations) and Grande Glorieuse (one population) (Table 1 and Figure 1). Specimens were brought to the laboratory for emergence and identification. Individuals were either directly stored in 70% EtOH for molecular analyses or kept alive for crossing experiments. All mosquitoes were reared in 65 dm3 cages kept at ca. 25±2°C with 12 h/12 h light/dark cycle. Larvae were fed ad libitum with a mixture of shrimp powder and rabbit pellets, and adults with a honey solution. Mosquito DNA was extracted using a CetylTrimethylAmmonium Bromide (CTAB) protocol [51]. The wPip infections were characterized through the analysis of one Wolbachia marker, the ankyrin domains encoding gene, ank2 [52] (primers are listed in Table S1). This marker differentiated wPip strains from groups I and IV on the basis of the size of the PCR amplified fragments: 313 bp and 511 bp fragment for group I and IV, respectively. For field samples, the ank2 PCR products from two specimens per sample site were sequenced to confirm their identity with La Réunion ank2 allele [Genbank AM397068; [43]]. The examination of the mosquito nuclear genome was assessed by PCR/RFLP tests based on Cx. pipiens ace-2 and Ester2 genes (primers are in Table S1). The ace-2 gene is located on chromosome I and encodes acetylcholinesterase 2 (AChE2) [53]. The Ester2 gene is located on chromosome II and encodes a carboxylester hydrolase [54]. A PCR/RFLP test on ace-2 using the ScaI restriction enzyme (37°C, 3 hours; see [55]) allows the discrimination between the Is (two fragments: 230 and 470 bp) and the LR (three fragments: 120,230 and 350 bp) nuclear genomes. We developed a PCR/RFLP test on Ester2 using the AvaII enzyme (37°C, 3 hours) that also generated different restriction fragments for the Is (three fragments: 37,519 and 544 bp) and LR (four fragments: 91,176,313 and 520 bp) nuclear genomes. All PCRs were performed with ca. 20 ng of genomic DNA solution in a 40 µl final volume reaction for 35 cycles (94°C, 5 min; 94°C, 30 sec; 52°C, 30 sec; 72°C, 1 min). Direct sequencing of PCR products was performed on an ABI Prism 3130 sequencer using the BigDye Terminator Kit (Applied Biosystems) after purification with the QIAquick gel extraction kit (QIAGEN, Valencia, CA). Sequence alignment and analyses were done using MEGA software [56]. The cytoplasm of the Is line, including the wPip (Is) strain, was introduced into the LR nuclear background through eight generations of backcrossing, a procedure that should result in at least 99% genome replacement of the Is line by the LR nuclear genome. A first cross was performed using 200 virgin Is females and 250 LR-TC males. For the following generations, 200 hybrid females were backcrossed with 250 LR-TC males. Using this protocol, we obtained the LR[wPip (Is) ] line which carries the LR nuclear genome and the wPip (Is) strain. We examined the crossing relationships between mosquito lines through crossing experiments. Mass crosses were carried out using 35–200 two-day-old males and an equivalent number of females that had been individually separated at the pupal stage (age was assessed from the emergence of adults; day 0 = emergence). We also tested the effect of male aging on CI by comparing crossing relationships of young males (two-day-old) to that of older males (24-day-old). For all crosses, females were allowed to blood feed 5 days after caging. Egg-rafts were collected and stored separately until hatching at 25°C±2°C. Hatching rates (HR) were scored 72 h after egg-raft collection to determine the CI phenotype. All unhatched egg-rafts were checked for fertilization through observation of embryonic development following the procedure of [57]. The longevity of the LR[wPip (Is) ] and LR males was compared. We obtained males from larvae reared in standardized laboratory conditions at ca. 25°C±2°C. For each line, three containers containing 300 first-instar larvae with 1 L of water were set up. The water of each container was changed every two days and food provided ad libitum. Pupae were randomly sampled from the three containers to minimize possible rearing bias. Pupae were placed separately in 5 mL vials for emergence. Freshly-emerged males were kept in their vials until they died, and mortality was checked twice a day. No food was provided to the adults but they had access to the water in their tube. Survival data were fitted to the Cox proportional hazards models (coxph, survival package) [58] and a ratio for each line was estimated as their instantaneous risk of death relative to each other. These analyses were performed using R software (www. r-project. org). One posterior leg was removed on dead specimens and the tibia was measured with a micrometer (NIKON Digital Counter CM-6S). Four cages were set up to compare the mating performance of both LR[wPip (Is) ] and LR males. Each cage contained an equal number of two-day-old virgin LR females and LR males (1∶1), as well as different numbers of two-day-old virgin LR[wPip (Is) ] males so that different ratios of the three types of mosquitoes could be tested (1∶1∶0,1∶1∶1,1∶1∶5 and 1∶1∶10). Thus the total number of adults for each of these confrontations was 200,300,350 and 600, respectively. For each confrontation, all the mosquitoes were introduced into the cage at the same time. Females were allowed to blood feed five days after caging and their egg-rafts were collected daily to score HR. To assess the stability of the expression of CI over the mosquito lifespan, a second blood meal was given to females 15 days after the first one, and new collections of egg-rafts were then made.
We first examined the genetic diversity of wPip strains found in natural populations of Cx. p. quinquefasciatus from La Réunion, Mauritius, Mayotte, Madagascar and Grande Glorieuse. The main purpose of this investigation was to assess the possibility of controlling mosquito populations in each of these four islands with wPip (Is) -infected males. We examined 650 Cx. p. quinquefasciatus field specimens from 29 populations: La Réunion (16 populations, n = 384 individuals), Mauritius (4 populations, n = 91 individuals), Mayotte (3 populations, n = 69 individuals), Madagascar (5 populations, n = 105 individuals) and Grande Glorieuse (1 population, n = 24) (Table 1 and Figure 1). The genotyping of wPip infections in these samples was performed using only the ank2 gene which was recently shown to discriminate wPip strains into five distinct phylogenetic groups (referred as wPip-I to wPip-V) [38]. PCR assays using ank2 indicated the occurrence of wPip infection in all Cx. p. quinquefasciatus field specimens, as observed in other geographic areas for this species [10], [36], [37], and all shared the same ank2 allele as indicated by the length of ank2 PCR products (313 bp). This similarity was further confirmed by sequencing the ank2 gene of two individuals per population from Mauritius, Mayotte, Madagascar and Grande Glorieuse. All sequences were found to be strictly identical to that found in the wPip strains infecting all 10 laboratory isofemale lines from La Réunion and to other wPip strains belonging to the wPip-I group [38]. This result shows that wPip strains from La Réunion, Mauritius, Mayotte, Madagascar and Grande Glorieuse are genetically closely related and are genetically different from the wPip (Is) strain belonging to the wPip-IV group. Males from the Is line belong to Cx. p. pipiens subspecies and may not be optimally adapted to the tropical environment of the Indian Ocean where Cx. p. quinquefasciatus is found. More specifically the two subspecies are known to differ by behavioral and physiological characters including mating behavior [27]. To circumvent this problem, we introduced the wPip (Is) strain into the Cx. p. quinquefasciatus nuclear background from La Réunion. First a LR line was established from a large number (>5,000) of field-caught Cx. p. quinquefasciatus from three localities of La Réunion in order to have a good representation of the local genetic diversity. This line was then cured of its Wolbachia by tetracycline treatment of larvae during three generations (LR-TC line). Finally wPip (Is) from the Is line was introduced into the nuclear background of the LR-TC line by successive backcrossing. The LR[wPip (Is) ] line thus created shares the same nuclear genetic background as the LR line but is infected by the wPip (Is) strain (Figure S1). This was verified by PCR/RFLP tests on ace-2 and Ester2 Cx. pipiens nuclear genes (Figure S2A and S2B) and by analyzing the allelic profiles of the ank2 gene of the infecting Wolbachia (Figure S2C). Crossing experiments between LR[wPip (Is) ] and Is lines were conducted to check that Cx. p. quinquefasciatus nuclear background has not altered the CI phenotype of the wPip (Is) strain. This aspect needs to be investigated since the host nuclear genome has been reported to affect the penetration of the CI phenotype induced by a Wolbachia strain [59]–[61]. Our data show that both lines behave similarly: LR[wPip (Is) ] and Is showed bidirectional CI with LR while LR[wPip (Is) ] and Is were mutually compatible (Table 2). The intensity of CI was very high, with 98–100% of the embryos that did not hatch in incompatible crosses. In addition, crosses between infected and uninfected lines showed unidirectional CI: males from all infected lines (LR[wPip (Is) ], Is and LR) induced complete CI (100% embryo mortality) when crossed with uninfected females (LR-TC), the reverse crosses (i. e. uninfected males and infected females) being always compatible. Overall, no significant difference of hatching rate (HR) was found when the LR[wPip (Is) ] and Is lines were compared (Wilcoxon test; all P>0. 14). This shows that the CI phenotype of the wPip (Is) strain was not altered by the LR genetic background, and that the CI phenotype is controlled by the wPip infection rather than by nuclear genes, which is in accordance with most studies involving species of the Cx. pipiens complex [43], [62]. The effect of male ageing on CI intensity was also tested as, in a few host species including some mosquitoes, CI intensity has been shown to decrease with male aging [63]–[67]. Such an effect could impede the use of LR[wPip (Is) ] males to sterilize field females. To investigate this aspect, we crossed two-day and 24-day old LR[wPip (Is) ] males with two-day old LR females. No viable embryo was obtained in incompatible crosses with both young and old LR[wPip (Is) ] males (Table 3). Thus CI is expressed with the same intensity throughout the LR[wPip (Is) ] males' lifespan, a result also observed in diverse Cx. pipiens laboratory lines [10], [68]. LR[wPip (Is) ] males were crossed with field females from five populations: Samuel (La Réunion; n = 75 females), Salines (Mauritius; n = 37), Tsoundzou (Mayotte; n = 75) Mada (Madagascar; n = 44) and Grande Glorieuse (Grande Glorieuse; n = 97 females). All crosses were incompatible, displaying >99% embryo mortality (Table 4). Thus, LR[wPip (Is) ] males express high CI intensity with field females from the four islands, as observed with females of the LR line. Crossing relationships between LR[wPip (Is) ] females and field males were also investigated to determine how the LR[wPip (Is) ] line may evolve in Cx. p. quinquefasciatus field populations in the case of accidental release of LR[wPip (Is) ] females. LR[wPip (Is) ] females were incompatible with all males from Samuel (n = 36 males), Salines (n = 37) and Grande Glorieuse (n = 40) (Table 4). This shows that LR[wPip (Is) ] expresses bidirectional CI with field specimens from these populations. However, males from Tsoundzou (n = 16) were polymorphic for their CI properties, the majority (n = 14) expressing complete CI with LR[wPip (Is) ] females and a few (n = 2) being compatible (HR = 0. 895±0. 035) (Table 4). This shows that LR[wPip (Is) ] expresses either bidirectional CI or unidirectional CI with field specimens from Tsoundzou. Thus, two crossing types coexist in Mayotte, but it is likely that the bidirectional CI crossing type is the most frequent one. Males from Mada were also polymorphic for their CI properties but, in contrast to Tsoundzou males, most Mada males were compatible with LR[wPip (Is) ] females (n = 18, HR = 0. 804±0. 283) while only two males expressed CI. So the unidirectional CI type was the most frequent in the Mada population. Inferior competitive ability of LR[wPip (Is) ] males compared with field males may limit the efficiency of an IIT program. Thus, the performances of LR[wPip (Is) ] and LR males, reared in standardized conditions, were examined for different life history traits. Longevity of LR[wPip (Is) ] and LR males (n = 154 and n = 238, respectively) was investigated in conditions where males had to survive by metabolizing nutritional reserves accumulated during their larval life (see material and methods) [69]. No significant difference was found (χ2 = 0. 04, P = 0. 84; Figure 2), suggesting that the infection by wPip (Is) did not alter mosquito metabolism. There was also no significant difference between LR[wPip (Is) ] and LR male tibia length (n = 30 and n = 30; Wilcoxon two-sided test, P = 0. 34; Figure 3), a parameter known to be positively correlated with mosquitoes' adult size and reproductive success [70]. This suggests that LR[wPip (Is) ] and LR males most probably exhibit similar mating performance. To further test this assumption, mating competition between LR[wPip (Is) ] and LR males was investigated in laboratory cages. Four cages containing different ratios of LR females to LR males to LR[wPip (Is) ] males (1∶1∶0,1∶1∶1,1∶1∶5 and 1∶1∶10) were set up. Note that as CI occurring between LR[wPip (Is) ] males and LR females is complete, it was easy to distinguish egg-rafts produced from compatible (LR males×LR females) or incompatible (LR[wPip (Is) ] males×LR females) crosses. Two successive collections of egg-rafts were obtained for each cage by giving females two distinct blood meals. There was no significant variation in the proportion of incompatible egg-rafts between the first and the second series of egg-rafts (Fisher exact test, all P>0. 57). As expected, when only LR males were present, all the egg-rafts were compatible (Table 5). In the other cages, no significant difference between LR[wPip (Is) ] and LR males' mating capacity was found. Indeed, the number of incompatible egg-rafts observed was not significantly different from expected values assuming an equal competitiveness of LR[wPip (Is) ] and LR males and random mating (Binomial test, all P>0. 18; Table 5). For instance, with an identical ratio of LR[wPip (Is) ] and LR males (1∶1), ca. 50% of the egg-rafts produced by LR females were incompatible. When the LR[wPip (Is) ] males' ratio was higher than that of LR males, i. e. at 1∶5 and at 1∶10, we observed ca. five and ten times more incompatible egg-rafts than compatible ones. Taken together, these results showed that LR[wPip (Is) ] males are as fit as LR males, at least in our laboratory conditions. These experiments also established that LR females cannot discriminate between compatible LR males and incompatible LR[wPip (Is) ] males, a result consistent with previous observations of random mating between Cx. pipiens mosquitoes infected by incompatible Wolbachia strains [37], [48], [71].
The study presented here supports the feasibility of an IIT strategy using the LR[wPip (Is) ] males and targeting field Cx. p. quinquefasciatus populations, a species of medical and veterinary concern in the SWIO islands. This method now needs to be further tested in semi-field conditions in order to optimize several key parameters, i. e. the number of males to be released as well as the timing of releases. Recently, new semi-field cages were developed to measure the impact of the life-shortening Wolbachia wMelPop strain on populations of Aedes aegypti [80]. Such cages provide a realistic transitional platform between laboratory and field conditions. The risk of accidental releases of females needs also to be limited by developing an efficient sexing method to prevent any unintentional Wolbachia replacement. | Mosquitoes of the Culex pipiens complex are important vectors of human pathogens including filarial parasites and many currently expanding arboviruses. The absence of effective vaccines and the evolution of insecticide resistance stress the urgent need for the development of novel control strategies. One strategy that is receiving increasing attention is based upon the use of the intracellular bacteria Wolbachia, which induce a form of sterility known as cytoplasmic incompatibility in mosquitoes. Here, we show that a Wolbachia strain, named wPip (Is) and naturally infecting Cx. p. pipiens from Turkey, can be used in the Incompatible Insect Technique (IIT) to sterilize Cx. p. quinquefasciatus females from several islands of the southwestern Indian Ocean (SWIO). The wPip (Is) strain was introduced into SWIO Cx. p. quinquefasciatus nuclear background leading to the LR[wPip (Is) ] line. Males from this latter line were found to sterilize all wild females tested, and no difference in mating competition was observed between LR[wPip (Is) ] and wild males. These results encourage the development of an IIT program based on the wPip (Is) strain to control mosquito populations in the SWIO. | Abstract
Introduction
Materials and Methods
Results
Discussion | vector biology
biology
microbiology | 2011 | Cytoplasmic Incompatibility as a Means of Controlling Culex pipiens quinquefasciatus Mosquito in the Islands of the South-Western Indian Ocean | 7,620 | 334 |
Rabies is a fatal zoonosis that still causes nearly 70,000 human deaths every year. In Europe, the oral rabies vaccination (ORV) of red foxes (Vulpes vulpes) was developed in the late 1970s and has demonstrated its effectiveness in the eradication of the disease in Western and some Central European countries. Following the accession of the three Baltic countries—Estonia, Latvia and Lithuania—to the European Union in 2004, subsequent financial support has allowed the implementation of regular ORV campaigns since 2005–2006. This paper reviews ten years of surveillance efforts and ORV campaigns in these countries resulting in the near eradication of the disease. The various factors that may have influenced the results of vaccination monitoring were assessed using generalized linear models (GLMs) on bait uptake and on herd immunity. As shown in previous studies, juveniles had lower bait uptake level than adults. For the first time, raccoon dogs (Nyctereutes procyonoides) were shown to have significantly lower bait uptake proportion compared with red foxes. This result suggests potentially altered ORV effectiveness in this invasive species compared to the red foxes. An extensive phylogenetic analysis demonstrated that the North-East European (NEE) rabies phylogroup is endemic in all three Baltic countries. Although successive oral vaccination campaigns have substantially reduced the number of detected rabies cases, sporadic detection of the C lineage (European part of Russian phylogroup) underlines the risk of reintroduction via westward spread from bordering countries. Vaccine induced cases were also reported for the first time in non-target species (Martes martes and Meles meles).
Rabies disease is a fatal mammalian encephalomyelitis caused by the rabies virus of the genus Lyssavirus (family Rhabdoviridae) [1]. The virus is distributed worldwide, with the exception of the Antarctic, Australia and several islands and although all species of mammals are susceptible to this virus, it infects principally carnivores and bats [2]. In Europe, the genus lyssavirus evolves through five virus species (four of them circulate in bats only): the classic rabies virus (RABV) affecting non-flying terrestrial mammals only, the european bat lyssaviruses type 1 and type 2 (EBLV-1 and EBLV-2) and the more recently detected Bokelo bat lyssavirus (BBLV) and Lleida bat lyssavirus not yet taxonomically assessed [3]. RABV has spread in Europe since antiquity as a dog and wolf-mediated disease [4]. In the 1940s, likely due to spillover from domestic animals, a new epizootic maintained by a single species, the red fox, emerged in Eastern Europe with an assumed ground zero in Kaliningrad [5]. The front moved from Poland to Germany spreading through Europe with a speed of approximately 30–60 km per year, reaching France in 1968 and Italy in 1980 [6]. Large rivers, lakes and high mountain chains acted as obstacles to the spread; bridges facilitated the crossing of rivers. Intensive fox destruction campaigns alone cannot stop the spread of the virus [7], prompting oral rabies vaccination (ORV) programs that rapidly proved to be the only efficient technique for controlling the disease. The first ORV field trial was conducted in 1978 in Switzerland [8] and was gradually extended to surrounding countries, such as Belgium, France and Germany. In the 1980s, fox rabies control in European Union became a public health issue. Since 1989, the European Commission has provided funding to Member States for national eradication programmes, thereby improving surveillance and encouraging regular implementation of oral vaccination campaigns on large scales in coordination with neighbouring countries. This strategy leaded to the successful elimination of rabies in most Western and Central European countries [9,10]. In Europe, approximately half of the historical rabies endemic countries are now free of rabies (Austria, Belgium, Czech Republic, Finland, France, Germany, Italy, Luxembourg, Switzerland and the Netherlands). In the Baltics, the three countries were recently officially recognized free of rabies according to OIE (World Organisation for Animal Health) criteria [11–13]. In the last three years, some sporadic cases have been reported in some countries (Bulgaria, Hungary, Slovakia and Slovenia) and the disease is still endemic in several Eastern European countries (eastern Poland, Romania, Ukraine, Belarus and Russia, source: http: //www. who-rabies-bulletin. org/Queries/Surveillance. aspx). In the Baltic States, represented by Lithuania, Estonia and Latvia, sylvatic rabies emerged in the 1950s-1960s [14]. Since this time, a surveillance of the disease were progressively implemented and positive cases have been observed mainly in red foxes and raccoon dogs [15–17]. Although the red fox is known to be highly susceptible to RABV and is the main reservoir and vector of rabies throughout Europe, the Baltic countries has the particularity to host a second vector and reservoir, i. e. the raccoon dog [14]. Raccoon dog is one of the most successful alien carnivores in Europe. Native to East of Asia, this species was introduced in the eastern part of Russia via fur industry during the first half of the 20th century and has spread throughout Europe, becoming common in the Baltics and some other northeastern European countries. After it was first observed in the 1950’s in the Baltics, ten years were required to colonize the entire countries [18]. Foxes and raccoon dogs are both opportunistic omnivores, often share the same habitats and overlap their home ranges increasing the probability of contacts between the two species. Moreover, their combined densities could allow rabies epizootics to persist in a certain area [19]. The existence of this important rabies transmitter in this area challenged health authorities and questioned on its potential impact on the success of conventional ORV method used to control rabies in Western Europe. ORV programs were experimented differently according to the Baltic State. While no ORV was implemented in Estonia until 2005, in Latvia, ORV was firstly initiated in 1991 using chicken head vaccine baits. ORV using manufactured baits started in 1998 and has been performed twice a year since 1999, but regular purchase of the necessary amount of vaccine baits for annual nationwide vaccination was not possible because of financial reasons. The vaccination area was enlarged every year to cover the whole territory by 2001–2003 and vaccines were distributed manually [20]. In Lithuania, ORV was tested for the first time in 1983 with fish or meat baits containing a vaccine made of a derived ERA (Evelyn Rokitnicki Abelseth) laboratory fixed virus strain produced in Russia. In 1993 ORV was occasionally assessed on three districts [21]. Between 1995 and 2000, following the Lithuanian National Rabies prevention programme, ORV was performed generally manually and a large range of vaccines was used (Street Alabama Duffering (SAD) Bern, SAD P5/88 (Rabifox), (Street Alabama Gif (SAG) 1) over variable geographic areas. Following the accession of three Baltic countries to the European Union in 2004, subsequent financial support allowed the implementation of regular oral vaccination campaigns in the three countries since 2006 and ORV are still ongoing. This paper reviews ten years of surveillance efforts and oral vaccination campaigns conducted in the frame of European Commission programmes. Through the epidemiological analysis of rabies surveillance in these countries and an in-deep analysis of the ORV monitoring results, this paper emphasizes determinants of success and draws lessons for the future. These findings could provide valuable insights into the strategy required for rabies elimination and may help guide future implementation of oral vaccination programmes.
Covering approximately 175,000 km2, the Baltic States lie in the northeastern part of Europe and comprise the countries of Estonia (45,227 km2), Latvia (64,589 km2) and Lithuania (65,303 km2) (Fig 1). The Baltic States are bounded on the west and north by the Baltic Sea, which gives the region its name, on the east by Russia (511 km of common border), on the southeast by Belarus (818 km), and on the southwest by Poland (104 km) and an exclave of Russia named Kaliningrad (255 km). The topography of this area is relatively flat (culminating points in the three countries are around 300 m), characterized by numerous lakes and ponds, especially in the north, and hills in Lithuania. The most commonly encountered landscape is the temperate forest covering between 35 and 50% of the territories. All suspect non-flying mammals exhibiting clinical signs suggestive of rabies or showing abnormal behaviour, animals found dead in the field including road kills and those to which humans have been exposed (bites, scratches, licking of wounds or contamination of mucous membranes with saliva) are defined as indicator animals and are submitted for diagnosis [19]. The sampling scheme focusing on these animals, covering the whole country territory, is herein defined by expert committees of the WHO (World Health Organization) and EFSA (European Food Safety Authority) as the surveillance system [2,19]. All collected samples were shipped and analyzed in the respective National Reference Laboratories of each Baltic country (Estonian Veterinary and Food Laboratory for Estonia; Institute of Food Safety, Animal Health and Environment" BIOR" for Latvia and National Food and Veterinary Risk Assessment Institute of Lithuania for Lithuania). Brain tissues were analyzed for viral antigens using the Fluorescent Anti-body Test (FAT) which is the gold standard technique for rabies diagnosis [22,23]. For all three countries, FAT-negative results of animals involved in human exposure and FAT-inconclusive results were confirmed using the rabies tissue culture infection test (RTCIT) [24], Reverse Transcription Polymerase Chain Reaction (RT-PCR) [25] or Real-Time Polymerase Chain Reaction (RT-qPCR) [26,27]. The first wildlife ORV campaign in Estonia was organized in autumn 2005 and covered 57% of Estonian lands in the northern part of the country as part of a PHARE Twining Light Project (Fig 1) [16]. Vaccination programmes covering the entire territory (excluding urban areas, roads, water bodies and wet fields) representing approximately 43,000 km2 were carried out from 2006 to 2010. Bait distribution was performed twice a year, in spring (May, early June) and in autumn (September, October) as recommended by WHO and EFSA [2,19]. Baits were distributed at a rate of 20 baits per km2 using small fixed-wing aircraft flying at an altitude of 100–150 m, speeds of 150–200 km/h and in parallel flight lines (global positioning system (GPS) routes followed by the plane) distanced of 600 m [16,28]. Since spring 2011, ORV campaigns have been conducted only in a buffer zone of 9,325 km2 adjacent to neighbouring infected countries (Russia and Latvia) to ensure a sufficient level of immunity among raccoon dog and red fox populations. No automatic dropping device was used in the airplanes and no additional manual distribution was carried out in the field. A single vaccine bait type was selected through a tendering process, the modified live attenuated SAG2 vaccine (RABIGEN, Virbac Laboratories, France) (Fig 2). In Latvia, following a PHARE Twinning Light project, ORV campaigns were carried out in 2005 for the first time via aircraft in half of the country (the size of vaccination area was 28,000 km2 and it was delimited by natural barriers) twice a year with 23 baits per km2. Starting from 2006, two vaccination campaigns were implemented in the entire territory (64,589 km2) (except in 2008 and autumn 2011 when ORV campaigns were incomplete and in spring 2014 where no ORV was carried out). Since 2006, between 21 and 31 baits per km2 have been distributed using flight line distances of 1000 m until 2008,1000 m and 500 m alternately between 2008 and 2011, and 500 m since 2011. An automatic dropping device has been used since 2007 to distribute the baits. The type of vaccine purchased varied according to the procurement procedure. In general, two vaccines were used within the period 2005–2011—SAD B19 vaccine (FUCHSORAL, IDT Biologica GmbH, Germany) and SAD Bern (LYSVULPEN, Bioveta, Czech Republic). Since 2012, only the Lysvulpen vaccine has been in use (Fig 2). In Lithuania, ORV programmes have been implemented since 2006 using aircrafts over the whole country (65,000 km2) except lakes, urban areas and the Ignalina nuclear power-station. The no-fly area surrounding the Ignalina power plant was covered by manual distribution of baits. Like in other countries, the vaccination strategy has been implemented biannually (one vaccination in spring between March and May and one vaccination in autumn between October and December). Parallel flight lines generally separated by 1000 m (since 2011,500 m in areas on the Belarus border) at an altitude of 150–200 m and speed 150–200 km/h were used to distribute 20 baits per km2 [29] (Fig 2). Since 2006, only the Lysvuplen vaccines have been distributed except in 2011 and 2012 when Fuchsoral vaccines were used. In addition to the sampling scheme designed for rabies surveillance, a second sampling plan defined as monitoring of ORV was set up in vaccinated areas to evaluate the efficacy of ORV campaigns in terms of bait consumption (bait-uptake) and herd immunity [2,19,30]. This sampling focused on the collection of animals (red foxes and raccoon dogs) targeted by oral vaccines. These animals sampled by hunter associations are therefore considered as not suspected for rabies. Herd immunity level was assessed by enzyme-linked immunosorbent assays (ELISAs) [31]. Two commercial anti-rabies ELISA kit were used within the study: the BioPro ELISA (BioPro, Czech Republic) and the Platelia Rabies II kit (Bio-Rad, France). Their technologies differ by their coating aspect. The BioPro ELISA is a blocking ELISA using the crude glycoprotein to coat the plates and a positivity threshold (expressed as a percentage of blocking) of 40% [32,33]. The Platelia Rabies II kit is an indirect test using a purified rabies glycoprotein for the coating [34]. Serum titers were expressed as Equivalent Units per milliliter (EU/mL) with a cut-off of positivity fixed at 0. 5 EU/mL in Estonia and Lithuania and 0. 125 EU/mL in Latvia. The BioPro Rabies ELISA Ab kit was used in Latvia only. Bait uptake was investigated by collecting red fox and raccoon dog jaws and by analysing the tetracycline (TTC) specific fluorescence in thin tooth sections under ultraviolet light [35,36]. Indeed, after its inclusion in the coating of the bait and its consumption by the targeted animal, the tetracycline molecule, used as a bait uptake marker, is incorporated into bones and teeth. This interaction creates a line that can be detected using epi-fluorescence microscopy. Each animal sampled for monitoring were analyzed for both serological analysis and tetracycline detection when possible (depending of the organs let intact by the shot of the hunter). Studied animals from surveillance and monitoring scheme were originated from the field, died of natural causes and during the hunting/vaccination program developed and launched by the ministry of each country. These sampling processes were realised in compliance with the legislation of each country and under the recommendations of international institution (WHO [2] and EFSA [19]). In Europe, such process does not require any specific ethical approval as animals are received only dead in laboratories. Hunting plans are organised in the frame of control programmes of the disease and organised by Member States. A panel of 165 field rabies viruses was collected in Baltic countries between 2004 and 2013 for this study. The isolates investigated from domestic and wild animals were extracted from brains of animals samples in Estonia (n = 43), Latvia (n = 42) and Lithuania (n = 80). The samples were isolated from 12 different wild and domestic animal species: Nyctereutes procyonoides (65), Vulpes vulpes (44), Canis familiaris (14), Bos taurus (11), Felis catus (ten), Procyon lotor (four), Meles meles (three), Equus caballus (two), Martes martes (two), Ovis aries (one), Canis (one), Lynx lynx (one) and six non-determined species (S1 Table). The samples were initially tested using the FAT prior to genetic characterization [23]. For all the samples, forward and reverse sequences were assembled and edited using the ContigExpress program of Vector NTI software, version 11. 5. 3. (Invitrogen, France). Alignments were edited using Genedoc software, version 2. 7. 000 [41]. The same software was used to translate the gene sequence. Percentage identities and similarity scores were determined using the BIOEDIT program version 7. 2. 5. [42]. After the alignment of sequenced amplified PCR products, 106 identical sequences (56 from Lithuania, 23 from Latvia and 27 from Estonia) showing 100% nucleotide identity for the N gene (460 nt) were removed from the phylogeny. Fifty-nine partial N gene sequences (24 from Lithuania, 19 from Latvia and 16 from Estonia) were available for subsequent analysis. The dataset contained 93 sequences (361 nucleotides, positions 109 to 470 compared with the challenge virus standard (CVS) -11 strain GenBank no. GQ918139). Fifty nine representative Baltic samples, eight isolates from neighbouring countries (six from Poland and two from Russia), two from Ukraine, seven from Europe, two fixed strains (D42112 and HQ829841), three representatives of rabies vaccine strains (EF206708, EF206709 and EF206719), six referenced Artic and Artic-like isolates and six reference strains used as outgroup were included in the dataset (S1 Table).
A total of 24,919 animals were diagnosed for rabies from 2005 to 2014 in the Baltics. Around 70 to 80% of all detected positive cases were found in red foxes and raccoon dogs (For Estonia, 35% foxes and 48% racoon dogs; for Latvia, 40% foxes and 30% raccoon dogs; for Lithuania 31% foxes and 40% raccoon dogs). In the three countries, the maximum number of detected rabies cases was observed during the 2005–2006 period (Fig 2). The highest number of detected cases was recorded at the same semester of the implantation of the first ORV in Estonia and Latvia, while one semester after the first ORV in Lithuania. The ORV induced indisputably a decrease of the number of positives cases in the three countries (excepted in Lithuania between the second semester of 2006 and the first semester of 2007). Regarding the maximum number of cases observed in each country, 90% reduction of detected cases was reached after two ORV campaigns in Estonia, eight in Latvia and four in Lithuania. The last rabies case (field strain) was notified in 2011 in Estonia, in 2012 in Latvia and in 2013 in Lithuania. When starting ORV, surveillance effort (number of indicator animals sampled per 100 km2 in the whole country) ranged from 1. 7 to 1. 3 in Estonia (2005 and 2006), 1. 7 to 1. 6 in Latvia (2005 and 2006) and 5. 8 in Lithuania (but caution must be taken in the interpretation of this number because animals collected for monitoring were also included for this latter country). Since no rabies cases were detected, the pressure of surveillance appeared also comparable between the three countries ranging from 0. 42–0. 30 in Estonia (2012–2014), 0. 42–0. 30 in Latvia (2013–2014) and 0. 48 in Lithuania (2014). These data thus support the comparability of the number of positive cases in the different countries in recent years. The two phylogenetic analyses of the partial N gene sequences performed using either PhyML or Mr Bayes produced trees with identical topology. The phylogenetic analysis showed that 163 of the 165 studied Baltic sequences belonged to the lineage formed by the classical rabies virus within the cosmopolitan lineage, with a bootstrap value of 86% (Fig 8). No Arctic or Arctic-like variants were identified in the panel of viruses studied from the Baltic States. The majority of the Baltic rabies isolates grouped with the North-East European lineage (NEE), forming one strongly supported group (bootstrap value of 83). The NEE group consisted of 52 samples from the Baltic States and 21 published viral sequences (S1 Table) [38,49–51]. Both wild and domestic species fell in the NEE group. The NEE Group showed less than 1% nucleotide divergence and 3% amino acid divergence among all Baltic isolates. Nucleotide sequence analysis showed 100% of nucleotide identity between a red fox sample (no. 11584) isolated in 2006 in Estonia and three samples from Lithuania (a red fox isolated in 2007, a raccoon dog and a cattle both isolated in 2009). The same perfect identity was obtained between the Estonian isolate no. 11584 and two samples from Latvia (a raccoon dog and a dog both isolated in 2008). Five sequences from the Baltic States clustered with C group [48] formed with two published sequences, one from Russia and one from Ukraine (bootstrap support of 96%). Four species were included in this group: red fox (n = 2), raccoon dog (n = 1), cattle (n = 1) and dog (n = 1). Within C group, sequences showed more than 99. 9% of nucleotide similarity. 100% nucleotide identity was shown between a red fox sample (MT3-TA11-00267) isolated in Estonia in 2011 and two samples from Lithuania; a dog (no. 864) in 2012 and a raccoon dog (no. 4740) isolated in 2010. The PhyML tree also showed that a badger (Meles meles) (no. DR 784) and a marten (Martes martes) (no. 24771) isolated in Latvia in 2013 and in Lithuania in 2008 respectively, belonged to the group formed by the rabies virus vaccines (bootstrap of 100) (Fig 8). The vaccine-induced case isolated in Lithuania was found in the Alytus district in the south of the country, an area vaccinated since 2006 with Lysvulpen baits, whereas the vaccine-induced case isolated in Latvia was found in the Aloja district, in the north of the country, an area also vaccinated with Lysvulpen baits since 2011. Nucleotide analysis of the partial N gene sequenced of the two isolates showed 100% of nucleotide identity with the two referenced SAD-derived laboratory vaccine virus strains (EF206719 and EF206709) and there was 99. 4% nucleotide similarity with the SAD Bern vaccine strain (EF206708). The case found in Latvia was located in an area vaccinated with the Lysvulpen baits 25 km away from Estonia where the Rabigen baits were used. As the partial N gene sequence analysis did not discriminate among the two SAD-derived laboratory vaccine virus strains, the amplification of partial G gene sequence on the DR784 isolate was undertaken to identify the vaccine strain. The comparison between DR784 isolate and three vaccine strains, SAD B19 (EF206709), SAG2 (EF206719) and SAD Bern (EF206708), showed 100% nucleotide identity with SAD B19 and 99. 8% of similarity with the SAG2 and SAD Bern vaccines. The isolate DR784 was characterized by the presence of arginine in codon 333 (G gene). The sequence was clearly distinct from SAG2 (EF206719), characterized by two mutations in codon 333 yielding glutamine (Gln) at this position instead of arginine (Arg).
Surveillance data indicated a drastic reduction (90%) in the number of detected cases following 1 to 4 years of ORV. These results corroborate those from other European countries where 90% reduction of rabies detected cases were observed within 10 years, and in many cases less than 5 years following first ORV [52–54]. Depending on the country, the time to complete elimination (i. e. remaining 10%) is more or less longer to achieve. While eradication requires an additional 10 or more campaigns until no more cases are detected in Freuling at al. [10] we found that 2 to 8 campaigns were necessary. Variation in the reduction of the number of cases detected after each ORV depends on multiple factors such as the geographical location of the infected country, the initial epidemiological situation, the tools and strategy used in the control programmes and indubitably the implementation of an appropriate surveillance scheme. As soon as ORV was implemented on the whole territories, the proportion of positive cases started to decrease in the three countries. As suggested previously in Brochier et al. [55], and Aubert [56] for fox rabies and Townsend et al. [57] for dog rabies, an inadequate vaccination area can compromise success and considerably extend the time to elimination. For Lithuania, the animals collected in vaccinated areas for the monitoring of ORV were also diagnosed for rabies. Because this sampling focuses on the animal population targeted by oral vaccines and not suspected for rabies (in contrary to classic rabies surveillance plans where only suspect animals are collected), Lithuanian surveillance data probably overestimates the number of negative samples compare to other countries. The comparison of the percentage of positive cases between countries became consequently hazardous. For this reason, combining data issued from surveillance sampling and monitoring sampling should, insofar as possible, be avoided [2,22]. Appropriate surveillance schemes focus on indicator animals collected at anytime, anywhere throughout the country and no sample size can be defined for proving the absence or the presence of rabies in wildlife regardless of the reservoir species. In contrast, the monitoring schemes are based on sampling foxes and raccoon dogs shot by hunters in vaccinated areas after ORV campaigns [30]. The oral vaccines used at the present time in Europe for raccoon dogs were developed to control rabies specifically in foxes. An experimental study evaluated the safety and efficacy of SAG 2 baits on caged raccoon dogs [58]. Either direct instillation or bait ingestion using a virus dose containing at least 10 times the field vaccine dose proved vaccine safety during the 60 days of observation of animals. More than 6 months after oral vaccination with the field dose, all animals were challenged with a street rabies virus. All vaccinated animals developed high rabies neutralizing antibody titers and survived a virulent challenge, demonstrating the effectiveness of the vaccine bait according to the European Pharmacopeia monograph. These results suggest that SAG2 vaccine baits are suitable for this species. Another study conducted on the SADP5/88 vaccine (derived from SAD Bern and no longer in use) in which two different doses of the vaccine were administrated showed satisfactory protection of challenged animals [59]. Paradoxically, to our knowledge, there are very few experimental studies using vaccines used in Baltic countries on raccoon dogs to assess their efficacy and safety prior to their release in the field. For the first time, bait uptake results suggest a significant difference in the frequency of uptake of red foxes and raccoon dogs, with a lower proportion of tetracycline-positive raccoon dogs compared with red foxes. This result can be attributed to the difference in behavior of the two species and particularly to the hibernation of raccoon dogs in the Baltics during the cold season (November–March) [60], which may influence the epidemiology of the disease and access to vaccines distributed during this period. The impact of hibernation was suggested in a model of rabies transmission in both raccoon dogs and red foxes [61]. As suggested by our results, strategies to control rabies in countries where this species is an important transmitter should better focus on the raccoon dog biology. As example, ORV could also target raccoon dogs after they emerge from hibernation. All countries implemented ORV according to the EU recommendations[19]. Bait uptake levels in Baltic countries rapidly reached 80% of the target population. Our study showed a constantly increasing bait uptake throughout the study period, suggesting cumulative exposure to distributed baits [19]. Data analysis in Estonia and Lithuania confirmed previous studies, showing a significantly lower bait uptake in juveniles than in adults [28,62,63]. As a matter of fact, difficulties in reaching juveniles during ORV campaigns were observed. This was observed especially in early spring [19] because cubs are in dens or cannot be vaccinated because too young to eat the bait. Latvia has used two types of vaccines, Lysvulpen and Fuchsoral vaccines. Analysis of factors that potentially affect bait uptake showed a significant influence of the type of bait used, with higher bait uptake when the vaccine Lysvuplen was used. The type of bait influence was independent from the year as further analysis, omitting the first years of vaccination with Fuchsoral baits, still considered the bait type as a significant variable explaining the TTC variations. Given that, according to the manufacturer’s specifications, both vaccines contain 150 mg of tetracycline in the bait matrix, the reason for this difference is unknown. More investigations on bait matrix composition and palatability are needed. Neutralizing antibodies are the most reliable parameter for assessing the efficacy of vaccination because they are closely correlated with protection against rabies infection [64]. The assessment of the rabies antibody level is theoretically the best means for evaluating vaccination coverage because individual variation in immune reactions is taken into account. ELISAs allow large-scale screening because they are rapid, easy to perform, do not require live rabies virus or cell culture, and can be performed in any laboratory. These tests have been demonstrated as particularly suitable for assessing the effectiveness of oral vaccination in field samples [31,65,66]. The evolution of herd immunity level did not show any specific pattern, showing an unsteady evolution in all three countries. The surprising absence of any immunological trend may reflect the lack of sensitivity or reliability of some commercial ELISA kits, as has already been demonstrated recently [34,67,68]. Although the overall average bait uptake in this study was 80%, seroconversion level was approximately 50%. The same large discrepancies observed between uptake and seroconverion were attributed the lack of sensitivity of a commercial kit on field samples compared to blood samples taken from experimentally infected foxes and raccoon dogs, probably due to the reduced quality of the sera (haemolysis, bacterial contamination due to field condition) [28,67,69]. Latvia was the only country that used two different kinds of ELISA kits (Bio-Rad and BioPro) to evaluate vaccination coverage in red foxes and raccoon dogs. Further analysis demonstrated that significantly different levels of seroconversion were found for the two different kits. BioPro ELISA results showed lower seroconversion level than those of the Bio-Rad ELISA kit. These discrepancies are inconsistent with previous studies in which the seroconverion were found lower using Bio-Rad compared to BioPro kits due to the lower sensitivity of the first test [33,70]. Our results may be explained by the fact that a different cut-off value from the 0. 5 conventional one’s was used for the Bio-Rad kit (0. 125 instead of the 0. 5 used in Wasniewski et al.). These results must be also nuanced by the fact that Latvia encountered specific events in the same period when using the Bio-Pro test in 2012, a year during which an epidemic sarcoptic mange occurred. Immunological reactivity due to sarcoptic mange could potentially have interfered with the rabies vaccination, leading to a lower response and a decrease in the level of rabies antibodies. A sharp decrease in the number of marked animals was observed in Estonia during the last four campaigns as soon as the ORV area was reduced to a buffer zone of 9 325 km2 (20 km along the Southern border and 30–50 km in eastern part of the country). This drop could be explained, inter alia, by an “edge effect” due to the small size of the vaccinated areas. The areas being small, the perimeter-to-surface ratio is higher and the probability of sampling an unvaccinated animal in bordering areas is higher than for a large ORV areas. Moreover, the proportion of raccoon dogs in the monitoring sample has increased every year, ultimately constituting more than ¾ of all animals tested. This example highlights the importance of considering the structure of the monitoring sample in the determinism of the overall and final bait uptake level. Thus, comparison of monitoring data between countries and their interpretation should be assessed by taking into account the species (raccoon dogs vs red foxes) and the age class (juvenile vs adult) of the sampled population. The molecular epidemiology of RABV in the Baltic countries showed the presence of three types of RABV variants in the Baltic States, the North-East European group (NEE) (158/165 isolates), the Russian group (C) (5/165 isolates) and two vaccine-induced rabies cases. These results confirm that the terrain for rabies hosts infected with Baltic variants is broad [71], ranging from Eastern to the Central Europe. More precisely, the NEE group has been reported in Eastern part of Russia and from Finland to Romania [49] including the Baltic States [28,72,73], Slovakia, Poland and Ukraine [38,48,74], while C group has been reported from the European part of Russia [48] to different parts of Ukraine [74]. Although the C group is the most widely reported RABV variant in Russia [75] including regions of western Siberia, Kazakhstan and Tuva, four other variants have been previously described in Russia [48]. This study is the first to report the presence of C variant in North-East Europe with three cases in Lithuania reported between 2009 and 2013, one case in Estonia in 2011 and one case in Latvia in 2012. The occurrence of the C variant in Baltic States could be the result of a westward spread of rabies-infected hosts from Russia or from Belarus to the Baltic States. Animal-to-animal transmission of rabies virus or human-mediated transports of latently infected animals could explain the movement of rabies infected hosts across borders. There are numerous studies illustrating rabies virus transmission by human-mediated animal movements [76], wildlife-mediated movement of rabies [50] or movements of infected animals a cross frozen seas [77]. In Russia, six wild canid species (red fox, raccoon dog, artic fox, steppe fox, jackal and wolf) are vector of the disease. In Eastern Europe and in north-eastern Europe, most wildlife cases are reported in red foxes and raccoon dogs. The NEE variant is particularly associated with raccoon dogs in north-western Russia and north-eastern Europe, while C group were previously associated with the red fox and the steppe fox in Russia [48]. In this study, no phylogenetic distinction was reported between the red fox and raccoon dog isolates, whatever the variant analysed (C and NEE groups) and whatever the phylogenetic method used. Perfect identity observed between one isolate (red fox) in Estonia in 2006 and five strains (two raccoon dogs, one fox, one cattle and a dog) isolated in Latvia and in Lithuania between 2007 and 2009 suggests that the variant circulating in fox and raccoon dog populations have the same origin. Dogs may have served as an early reservoir for interspecies rabies virus transmission generating viral lineages that then spread to other species [78]. Due to the risk of residual pathogenicity of oral rabies vaccines related to the viral strain’s attenuation level, all rabies virus samples isolated in areas where attenuated rabies virus vaccines are used should be typed in order to distinguish between vaccine and field virus strains [2,19,22]. For the first time, we demonstrated that two field Baltic isolates (a marten from Lithuania in 2008 and a badger from Latvia in 2013), clustered with the group forming the rabies vaccines, SAG2, SAD B19 and SAD Bern. Clearly, the two vaccine-induced rabies cases were closely related to SAD B19 strains, although both cases were found in an area vaccinated with SAD Bern Lysvulpen baits. Previous study results indicated that the SAD Bern Lysvulpen vaccine shows higher similarity to the strains belonging to the SAD B19 vaccine [79]. Such findings led to a change in the viral strain description for the national marketing authorization dossier of this vaccine, http: //www. uskvbl. cz/en/authorisation-a-approval/marketing-authorisation-of-vmps/list-of-vmps/authorised-by-national-and-mrdc-procedures. This is also the first reporting of a vaccine-associated virus detected in badgers and in martens. To date, few vaccine-induced rabies cases have been documented in target species. Muller et al. [80] reported six vaccine-induced rabies cases in foxes caused by SAD B19 and SADP5/88 in vaccinated areas in Germany and Austria, respectively. In Slovenia, a young fox was also shown closely related to SAD B19 in 2012 [81]. The most likely explanation for these vaccine associated cases isolated in non target species is either residual pathogenicity of the virus vaccine despite vaccine attenuation or reversion to virulence. RNA viruses are known to have high mutation rates due to the lack of proofreading by RNA polymerases and could have occasionally reversed to more virulent viruses. The second hypotheses would be a transmission from a red fox or raccoon dog initially infected by a vaccine strain. Potential transmission of vaccine strain has indeed been recently questioned when finding vaccine strain in salivary gland of a naturally infected fox [81]. | This paper reviews ten years of rabies epidemiology in the three Baltic countries. Both surveillance efforts and oral rabies vaccination campaigns have resulted in the near eradication of the disease. Multivariate analysis assessed with generalized linear models (GLM) suggested lower oral vaccination effectiveness in raccoon dogs compared with red foxes, highlighting the importance of adapting oral vaccination strategy to each vector of the disease. Although eradication of the disease is almost achieved, the detection of some cases belonging with the Russian rabies lineage emphasizes a risk of rabies reintroduction in the Baltic States due to westward spread from bordering countries. This study show also the first vaccine-induced cases detected in non-target species (Martes martes and Meles meles). | Abstract
Introduction
Materials and Methods
Results
Discussion | medicine and health sciences
pathology and laboratory medicine
pathogens
immunology
tropical diseases
microbiology
vertebrates
geographical locations
estonia
dogs
animals
mammals
viruses
vaccines
preventive medicine
rabies
raccoons
rna viruses
neglected tropical diseases
vaccination and immunization
rabies virus
public and occupational health
infectious diseases
foxes
latvia
zoonoses
medical microbiology
microbial pathogens
people and places
lyssavirus
viral pathogens
biology and life sciences
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europe
organisms | 2016 | Rabies in the Baltic States: Decoding a Process of Control and Elimination | 8,854 | 174 |
Spatial modeling is increasingly utilized to elucidate relationships between demographic, environmental, and socioeconomic factors, and infectious disease prevalence data. However, there is a paucity of studies focusing on spatio-temporal modeling that take into account the uncertainty of diagnostic techniques. We obtained Schistosoma japonicum prevalence data, based on a standardized indirect hemagglutination assay (IHA), from annual reports from 114 schistosome-endemic villages in Dangtu County, southeastern part of the People' s Republic of China, for the period 1995 to 2004. Environmental data were extracted from satellite images. Socioeconomic data were available from village registries. We used Bayesian spatio-temporal models, accounting for the sensitivity and specificity of the IHA test via an equation derived from the law of total probability, to relate the observed with the ‘true’ prevalence. The risk of S. japonicum was positively associated with the mean land surface temperature, and negatively correlated with the mean normalized difference vegetation index and distance to the nearest water body. There was no significant association between S. japonicum and socioeconomic status of the villages surveyed. The spatial correlation structures of the observed S. japonicum seroprevalence and the estimated infection prevalence differed from one year to another. Variance estimates based on a model adjusted for the diagnostic error were larger than unadjusted models. The generated prediction map for 2005 showed that most of the former and current infections occur in close proximity to the Yangtze River. Bayesian spatial-temporal modeling incorporating diagnostic uncertainty is a suitable approach for risk mapping S. japonicum prevalence data. The Yangtze River and its tributaries govern schistosomiasis transmission in Dangtu County, but spatial correlation needs to be taken into consideration when making risk prediction at small scales.
Schistosomiasis japonica is a zoonotic disease caused by the digenetic trematode Schistosoma japonicum. Historically, the disease was endemic in 12 provinces of the People' s Republic of China, with more than 10 million individuals infected [1]–[3]. Sustained control efforts implemented over the past 50 years have confined S. japonicum to seven provinces and brought down the number of infected people to less than 1 million [1]–[3]. The mean infection intensity has also decreased significantly [2]. However, surveillance and interventions are still warranted in 435 counties according to the 2005 annual report on the epidemiologic status of schistosomiasis in the People' s Republic of China [4]. Geographic information system (GIS) and remote sensing technologies are increasingly utilized for risk mapping and prediction of schistosomiasis [5], [6]. Over the past decade, several studies have explored the relationship between the occurrence of schistosomiasis, its intermediate host snails and environmental factors, particularly land surface temperature (LST) and normalized difference vegetation index (NDVI) [7]–[14]. Socioeconomic factors and water contact patterns were also studied [11], [15]–[18]. The flexibility in modeling and parameter estimation renders Bayesian spatial modeling particularly attractive for risk factor analysis and mapping [19]–[21]. Early statistical methods employed for data analysis followed independent rather than spatially-correlated approaches. More recently, spatial modeling using Bayesian Markov chain Monte Carlo (MCMC) simulation-based inference has been applied to estimate the relation between environmental predictors, socioeconomic factors, and schistosomiasis. This approach allows the prediction of the prevalence and intensity of infection at non-sampled locations, taking into account the spatial correlation present in the data [11], [12], [21]–[25]. However, none of the above-mentioned studies pertaining to the spatial or spatio-temporal distribution of disease risk has taken into account the uncertainty of the diagnostic technique. In the case of schistosomiasis japonica, both serological (e. g. , enzyme-linked immunosorbent assay (ELISA), indirect hemagglutination assay (IHA) [26]) and parasitological methods (e. g. , Kato-Katz technique [27], miracidium hatching test [28]) are used in epidemiologic surveys. None of these diagnostic approaches has 100% sensitivity, however [28]–[31]. Although an enhanced sampling effort (e. g. , multiple stool examinations) and simultaneous use of different diagnostics improve the sensitivity [32], [33] this strategy is not feasible in routine surveys due to logistic and financial constraints. In the early 1990s, the Chinese schistosomiasis control programme embarked on a two-pronged diagnostic approach. Local residents in S. japonicum-endemic areas are first screened with a serological test, followed by stool examination of seropositive individuals [29]. According to expert opinion, the sensitivity of ELISA ranges from 90% to 95%, and the specificity from 85% to 90%. In the case of the Kato-Katz technique, the estimated sensitivity and specificity are 20–70%, and 95–100%, respectively [32]. In this study, we employed a Bayesian approach to investigate the spatio-temporal patterns of S. japonicum infection, and to identify environmental and socioeconomic risk factors. In our models, we explicitly took into account the diagnostic uncertainty.
The study was carried out in Dangtu, one of 14 S. japonicum-endemic counties in Anhui province, southeastern part of the People' s Republic of China. The first local case of schistosomiasis japonica was confirmed in 1953. Dangtu is situated on the lower reaches of the Yangtze River and stretches from 118°22′ to 118°53′E longitude and from 31°17′ to 31°42′N latitude. All three commonly recognized S. japonicum ecotypes are found in Dangtu, i. e. , (i) plains with waterway networks, (ii) marshlands and lakes, and (iii) hilly and mountainous regions. S. japonicum prevalence data were obtained from the annual county reports, covering the period from 1995 to 2004. Each year in September, field teams of the schistosomiasis control station in Dangtu sampled and surveyed the 114 schistosome-endemic villages as part of the national control program of schistosomiasis, which was approved by the institutional review board of the National Institute of Parasitic Diseases, Chinese Center for Disease Control and Prevention in Shanghai. The sampling frequency was in accordance with the prior classification of the respective village. Hence, villages with ongoing transmission were surveyed annually, villages where transmission was under control (prevalence <1%) were sampled every 2–3 years, and villages which had reached the criteria for transmission interruption (no human or animal cases within the past 5 years, no intermediate host snails observed in the previous year) were only surveyed if new snail habitats had been identified. During the 10-year surveillance period covered here, between 43 (in 1999 and 2002) and 68 (in 1998) villages were surveyed annually (median: 49). In sampled villages, all residents aged 5 to 65 years were invited to participate. One of the study requirements was that at least 80% of the eligible individuals should be tested. A two-pronged diagnostic approach was adopted; individuals were first screened by the IHA, followed by stool examination of seropositives. Parasitological diagnosis usually relied on the Kato-Katz technique [27]. Those found with S. japonicum eggs in their stool were treated with praziquantel. The median number of IHA tests performed per village was 778 (lower and upper quintiles: 302 and 1250). In this study, data from the Kato-Katz thick smear examinations were not used for further analysis, since some of the seropositives were not followed-up by the Kato-Katz technique due to recent treatments with praziquantel, and lack of compliance. The geographic coordinates of the village committee houses in the S. japonicum-endemic villages were collected using hand-held global positioning system (GPS) receivers (Garmin Corp. ; Olathe, KS, USA) and used as a proxi for the location of the village. Figure 1 shows the 114 S. japonicum-endemic villages in Dangtu county in relation to identified water bodies. Most endemic villages are located in the vicinity of water bodies or in the marshlands. Only four villages are situated in the northeastern hilly and mountainous region. A SPOT5 image with a spatial resolution of 2. 5 m and covering the whole study area, taken on February 9,2004, was purchased from China Remote Sensing Satellite Ground Station (Beijing, People' s Republic of China). This image was chosen because of its high quality (e. g. , cloud cover <10%). With regard to water bodies, no major changes occurred from 1995 to 2004. Water bodies were identified using an unsupervised classification function of ERDAS IMAGINE version 8. 6 (ERDAS LLC. ; Atlanta, GA, USA). The shortest straight-line distance between each village and the closest water body was calculated in ArcGIS version 8. 3 (ESRI; Redlands, CA, USA). For each year, one cloud-free Landsat-5 TM image with a spatial resolution of 30 m was purchased from China Remote Sensing Satellite Ground Station, covering the period from 1995 to 2004 (4 scenes were acquired in April, 3 in March, 2 in June, and 1 in August). LST and NDVI were extracted using the tools offered by ERDAS (http: //gi. leica-geosystems. com). For each scene, the mean LST and NDVI within a 2-km buffer zone around the centroids of the study villages were calculated in ArcGIS. Village-specific socioeconomic data were obtained from the annually-updated village registries. The available indices included annual average per-capita income and the proportion of households with tap water and improved sanitation. Dangtu county was partitioned into 0. 25×0. 25 km grid cells for the generation of a smooth prediction map for 2005. The minimum distance from each grid cell centroid to the nearest water body was calculated in ArcGIS. For each cell, the mean LST and the mean NDVI were extracted from the 2005 Landsat scene. LST and NDVI data were standardized by subtracting the arithmetic mean calculated from data within a 2-km buffer zone around the centroids of the study villages for each scene and then dividing the standard deviation using SAS version 8. 0 (SAS Institute Inc. ; Cary, NC). Villages were stratified into five wealth quintiles, based on the annual average per-capita income. The relationship between S. japonicum seroprevalence and village-specific environmental and socioeconomic surrogate measures was examined using scatter plots. A Bayesian approach was utilized to explore the spatio-temporal patterns of the S. japonicum seroprevalence data. The relationship between seroprevalence and environmental and socioeconomic covariates was also examined. We applied two different model specifications. The first set of models assumed no diagnostic error of the IHA. The second set of models explicitly took into account the diagnostic error, thus correcting for the estimated ‘true’ sensitivity and specificity of the IHA. For 2005, we created a smoothed predictive map of the S. japonicum prevalence. Let nit and zit be the number of examined and positive subjects by IHA, respectively, of village i (i = 1, …, N) in year t (t = 1, …, T). We assumed that zit follows a binomial distribution, that is zit ∼ Binomial (pit, nit), where pit is the seroprevalence following the standard formulation of the logistic regression model. We introduced covariate effects on the logit transformation of pit, that is, where α is the intercept, βk denotes a regression coefficient, and Xitk is the environmental or socioeconomic covariate. The standard assumption of this formulation is that the observations are independent. However, our data are spatially correlated because common environmental factors concurrently influence the infection risk in neighboring villages. Similarly, the data are temporally correlated because they have been obtained through repeated cross-sectional surveys. Ignoring these correlations, we would overestimate the significance of the covariates. To account for the spatio-temporal correlation, we introduced village-specific and year-specific random effects, ui and vt, respectively, as follows: . We defined a latent stationary and isotropic spatial process [34] on ui, by assuming that u = (u1, u2, …, uN) T has a multivariate normal distribution with variance-covariance matrix Σ, that is, u∼MVN (0, Σ). We defined Σ by an exponential correlation function, i. e. , Σlm = σ2exp (−ϕdlm), where dlm is the shortest straight-line distance between villages l and m, σ2 models the geographic variability, and ϕ is a smoothing parameter controlling the rate of decline of the spatial correlation with distance throughout the study period. For the exponential correlation function we have adopted the minimum distance at which correlation becomes less than 5%, which is defined by 3/ϕ and expressed in meters. Similar to previous spatio-temporal modeling of schistosomiasis [12], we defined a first-order autoregressive process (AR (1) ) on vt, assuming that temporal correlation ρ exists only with the preceding year [35]. An alternative spatio-temporal structure was modeled by assuming that spatial correlations evolve over time (space-time interaction) that is, where ut = (u1t, u2t, …, uNt) T is the spatio-temporal random effect such that with the parameter ϕt controlling the rate of decline of spatial correlation with distance in year t. We assessed the significance of covariates by including only environmental, or only socioeconomic, or both types of covariates. The model detailed before was based on the assumption that the IHA reliably diagnoses a S. japonicum infection, i. e. , its sensitivity and specificity are 100%. However, since IHA and other diagnostic tests have shortcomings [29], we made an attempt to incorporate the diagnostic error of IHA into our modeling framework. Expert opinions on the diagnostic performance of IHA were gathered by means of a questionnaire survey, as described elsewhere [32]. The experts' consensus was that the sensitivity and specificity of IHA is 80–95% and 70–80%, respectively. These values were fed into the model as prior information. Let πit be the underlying true prevalence of S. japonicum infection for village i in year t, and pit the observed prevalence of infection. Following the model specifications of Booth and colleagues [33] and Wang et al. [32], we assumed that the number of seropositives zit has a binomial distribution that is zit ∼ Binomial (pit, nit), and related the observed and true prevalence via the equation pit = πitsjt + (1−πit) (1−cjt). This equation is derived from the law of total probability, where sjt and cjt are the sensitivity and specificity of IHA for village j (j = 1, …, J) in year t, respectively, where j is a group of adjacent villages. The models described previously were fitted, but with underlying prevalence πit instead of the seroprevalence pit. The same database was used throughout the study. We randomly selected 93 out of the 114 S. japonicum-endemic villages (82%), and used the surveys conducted between 1995 and 2004 for fitting the models, employing 408 out of the available 508 surveys. The remaining 100 surveys carried out in the other 21 villages over the same period served for model validation. In a first step, we compared the goodness-of-fit of the models by using the deviance information criterion (DIC) [36]. The model with the smallest DIC value was considered the best-fitting one. Next, we evaluated the predictive abilities of different models by calculating five different Bayesian credible intervals (BCIs) with probability coverage equal to 5%, 25%, 50%, 75%, and 95% of the posterior predictive distribution at the test locations, as suggested elsewhere [19]. Models with a high percentage of records falling into the narrowest BCIs were considered to have good predictive abilities. Following a Bayesian model formulation, we adopted vague normal prior distributions for each regression coefficient βk and intercept α, vague inverse gamma priors for variances, and a uniform prior ranging from −1 to 1 for temporal correlation ρ. Informative beta prior distributions derived from expert opinion that is, beta (67. 18,9. 60) and beta (224. 25,74. 75), were used for sensitivity sjt and specificity cjt, respectively. We assumed that the prior for the spatial correlation ranged from 0. 01 to 0. 99 at the minimal distance between villages (0. 6 km) and from 0 to 0. 2 at maximal distance (49 km), thus uniform priors ranging from 0. 017 to 7. 675 were used for the spatial decay parameters ϕ and ϕt. Two-chain MCMC was used for parameter estimation. Model convergence was assessed by visually inspecting the time series plot for each parameter, and Gelman-Rubin statistics [37]. The inference of the parameters was based on 15,000 iterations of both chains after the burn-in phase. Model fit was carried out in WinBUGS 1. 4. 1 (Imperial College and MRC, London, UK).
Figure 2 shows the observed seroprevalence in the study villages, according to survey year. Commonly, high seroprevalences were observed in villages located in close proximity to large rivers. In 27% of the village surveys the seroprevalence was zero, whereas a mean seroprevalence ≥10% was found in 41% of the surveys. Table 1 summarizes the goodness-of-fit and the predictive ability of the models which did not take into account the diagnostic error of IHA. The smaller DIC values of the spatio-temporal models indicate that they fitted the data better than the non-spatial ones. The predictive ability of the models could be improved significantly by considering spatio-temporal random effects. Moreover, the percentage of testing records falling into smaller BCIs of the posterior predictive distribution was considerably higher in the spatio-temporal models than in the non-spatial ones. Models considering the temporal evolution of spatial correlation also appeared to better fit the data than those assuming independent spatial and temporal processes. Considering also socioeconomic information did not further improve the model. Hence, the model with environmental covariates and variable spatial correlation was considered the best-fitting one. As shown in Table 2, incorporating the sensitivity and specificity of IHA as model parameters, resulted in smaller DIC values in the annual differences in the spatial correlation. When models also considered socioeconomic information there was no further improvement. Actually, the percentages of testing records falling into smaller BCIs were larger in a similar model that only considered environmental covariates. Thus, the model without explicit consideration of socioeconomic data was considered the best-fitting one. However, its predictive ability was inferior to that of the best-performing model which did not take into account the diagnostic error of IHA (4% versus 31% of the test records falling into the 5% BCI). Table 3 summarizes the results of the best-fitting spatio-temporal models regarding the observed S. japonicum seroprevalence and the ‘true’ infection prevalence. The prevalence increased with the mean LST (regression coefficients: 0. 201 and 0. 669 for seroprevalence and ‘true’ infection prevalence, respectively), and was negatively correlated with the mean NDVI (regression coefficient: −0. 327 and −1. 044, respectively). The seroprevalence was also inversely related to the distance to the closest water body (regression coefficient: −0. 277 and −1. 069, respectively). The estimated variances using the model with adjusting for the diagnostic error were larger, as suggested by larger 95% BCIs. The relationship between the serostatus and socioeconomic covariates was not further explored since the selected variables neither improved the goodness-of-fit nor the prediction ability of the models. The best-fitting spatio-temporal models indicated that the spatial correlation structures of the observed seroprevalence and the ‘true’ prevalence differed from one year to another, albeit not significantly (Table 3). Generally, the spatial correlation of the seroprevalence declined at a slower pace than that of the ‘true’ prevalence (smaller values of the parameter ϕ indicate a slower decay of the correlation with distance). For the measured seroprevalence, the shortest distance at which the spatial correlation was below 5% was determined in 1995 (5. 9 km; 95% confidence interval (CI): 0. 5–17. 8 km). The maximum value of 55. 6 km (95% CI: 21. 0–144. 4 km) was modeled for 2003. For the underlying ‘true’ prevalence, the respective distances were 0. 7 km (95% CI: 0. 4–3. 0 km in 2001) and 3. 7 km (95% CI: 0. 4–20. 7 km in 1999; Figure 3). The model for the measured seroprevalence further indicated a fast decline of the spatial correlation with distance in 1995,1998, and 2001, and a slower decay over the respective ensuing two years. The S. japonicum prevalence in Dangtu county was predicted for 2005, based on the spatial correlation structures observed in the preceding year. The predicted seroprevalence in the county ranged from 0. 05% to 22. 9% (posterior median). Most of the predicted high-seroprevalence areas are located in close proximity to water bodies, especially the Yangtze River, and in the southeast of the county (data not shown). The predicted ‘true’ S. japonicum prevalence ranged from nil to 3. 7% (posterior median). The locations for which a relatively high ‘true’ prevalence was predicted are again located in the vicinity of water bodies (Figures 4a and 4c). The distribution of the prediction error is depicted in Figures 4b and 4d.
In this study, we estimated the ‘true’ S. japonicum prevalence in a schistosome-endemic county of the People' s Republic of China by explicitly taking into consideration the diagnostic error of a widely used serological test, i. e. IHA. Additionally, we explored the spatial distribution over time, and produced a predictive risk map for the year 2005. Since antibody-based immunological tests, such as IHA and ELISA, cannot distinguish between an active and a recently cleared infection, these techniques result in low specificity in areas where chemotherapy is provided on a regular basis [31]. Thus, the analysis of uncorrected seroprevalence data would only be suggestive of the overall infection pressure [38]. In order to better understand the epidemiologic characteristics of schistosomiasis japonica, we accounted for the lack of sensitivity and specificity of the standard serological test employed in our study setting by using a Bayesian approach, and compared the outcome with that of the uncorrected model that assumed 100% sensitivity and specificity. In recent years, significant progress has been made with Bayesian spatio-temporal models. Thus our understanding of the epidemiology of infectious diseases in general [39], [40], and schistosomiasis in particular [22], has been improved. We used two types of spatio-temporal models; one assumed independent spatial and temporal random effects, and the second assumed that spatial correlations evolved over time (space-time interaction). Similar approaches have been successfully employed before [12], [41], [42]. We considered a stationary spatial process, although recent investigations suggest that non-stationarity is a more reasonable approach [19], [21]. The reasons were as follows. First, Dangtu county is small, spanning 50 km at most. Second, the local environment in this setting is rather uniform, and the study area mainly consists of plain regions with waterways, marshlands and lakes. In future analyses, it would be interesting to investigate anisotropic processes. Remotely-sensed environmental data are increasingly utilized in schistosomiasis research [5], [11], [43], [44]. Temperature and vegetation coverage are among the most frequently investigated environmental features, as they can be readily derived from satellite images. Their utility for an enhanced understanding of the local epidemiology of schistosomiasis has been demonstrated extensively [8], [11], [44]. In this study, LST and NDVI were extracted from Landsat-5 TM images, and averaged values for each village for individual survey years were calculated for 2-km buffer zones around the centroid of each village. The 2-km buffer zone approximately corresponds to an average village in Dangtu, and most daily activities take place within such a range. Prevailing weather conditions did not allow us to obtain all remotely-sensed data in the same month, i. e. , April, the first month of the local transmission season [12]. To remedy this issue, we standardized the indices. Three important findings emerged from our study. First, LST was positively associated with S. japonicum prevalence, whereas the NDVI and distance to water bodies were negatively associated. These observations are consistent with previous findings [12], [23]. However, the non-spatial models revealed that the prediction ability of these covariates was poor whether or not the diagnostic error of IHA was taken into account. It is thus conceivable that the environmental factors explained the local S. japonicum prevalence to a small degree only. The effects of socioeconomic factors such as the annual average per-capita income, the proportion of households with piped water supply, and the proportion of households with access to improved sanitation were even smaller, contrasting results for S. mansoni in Côte d' Ivoire [11], [45]. Possible explanations for this finding are that socioeconomic factors could be disconnected from the epidemiology of schistosomiasis at small spatial scales, and improved water supply and sanitation do not necessarily change the water contact pattern of villagers [15]. A model incorporating socioeconomic variables measured at the individual level rather than at the village level as done here, might result in a better fit. Second, the spatial correlation of the seroprevalence and the estimated ‘true’ prevalence of S. japonicum occurred over greater distances for the former than the later. Our study is the first to compare the range of spatial correlation of the seroprevalence with that of the underlying prevalence. Additional investigations in different settings are warranted to verify this finding and explore possible reasons. Spatial correlation has also been documented for S. haematobium and S. mansoni in different African settings [11], [23]. The importance of the spatial correlation was underscored by the finding that the predictive ability of the model was greatly improved when spatio-temporal random effects were incorporated. The inclusion of the uncertainty about IHA sensitivity and specificity lowered the predictive ability, and increased the prediction errors since additional sources of errors were considered and the spatial correlation occurred over shorter distances. Whilst the spatial correlation varied from one year to another, no strong temporal trend was observed in our study. One possible reason is that the duration of our inquiry (i. e. , 10 years) is not long enough for capturing prevailing temporal patterns. Third, smoothed risk maps for 2005 were created based on the spatial correlation found in the preceding year. Since no significant temporal trend was detected from 1995 to 2004, it was decided to use the most recent data only. It is evident that most human infections were predicted to occur in close proximity to the Yangtze River and its tributaries. It has already been noted before that Oncomelania hupensis in the waterways connected to the Yangtze River are difficult to eliminate, and that snails can readily re-colonize cleared areas [2]. The prediction maps highlighted the areas (villages) at high risk of S. japonicum infection, and emphasized the important role of the Yangtze River in the transmission of schistosomiasis in Dangtu county. Implications for the local schistosomiasis control program are that control measures should be targeted to those villages at highest risk. One limitation of our study is that about 20% of the eligible population (aged 5–65 years) in the sampled villages was not surveyed. It is hard to predict whether non-compliance biased our risk profiles. Another limitation is that non-surveyed villages were excluded from the analysis in the corresponding year (s) and their effects on the estimates were not taken into consideration in the models, since there might be too many parameters to be estimated. In conclusion, we have presented an in-depth study on the spatio-temporal pattern of S. japonicum within a single county. Importantly, we explicitly took into account the diagnostic error of the serological screening test, and employed a Bayesian modeling approach, through which the underlying ‘true’ prevalence of S. japonicum infection could be estimated and predicted. There is considerable spatial correlation and annual variability of S. japonicum infection. Hence, for small-scale prediction, accounting for the spatial correlation seems more important than considering the risk factors included in our study. Finally, the Yangtze River and its tributaries play an essential role in the local epidemiology of schistosomiasis japonica. | Schistosomiasis is a serious public health problem in the People' s Republic of China and elsewhere, and mapping of risk areas is important for guiding control interventions. Here, a 10-year surveillance database from Dangtu County in the southeastern part of the People' s Republic of China was utilized for modeling the spatial and temporal distribution of infections in relation to environmental features and socioeconomic factors. Disease surveillance was done on the basis of a serological test, and we explicitly considered the imperfect sensitivity and specificity of the test when modeling the ‘true’ infection prevalence of Schistosoma japonicum. We then produced a risk map for S. japonicum transmission, which can assist decision making for local control interventions. Our work emphasizes the importance of accounting for the uncertainty in the diagnosis of schistosomiasis, and the potential of predicting the spatial and temporal distribution of the disease when using a Bayesian modeling framework. Our study can therefore serve as a template for future risk profiling of neglected tropical diseases studies, particularly when exploring spatial and temporal disease patterns in relation to environmental and socioeconomic factors, and how to account for the influence of diagnostic uncertainty. | Abstract
Introduction
Materials and Methods
Results
Discussion | infectious diseases/neglected tropical diseases
public health and epidemiology/epidemiology
infectious diseases/helminth infections
public health and epidemiology/social and behavioral determinants of health
mathematics/mathematical computing
infectious diseases/tropical and travel-associated diseases
public health and epidemiology/environmental health
infectious diseases/epidemiology and control of infectious diseases | 2008 | Bayesian Spatio-Temporal Modeling of Schistosoma japonicum Prevalence Data in the Absence of a Diagnostic ‘Gold’ Standard | 6,875 | 263 |
Staphylococcus aureus is a human commensal that can also cause systemic infections. This transition requires evasion of the immune response and the ability to exploit different niches within the host. However, the disease mechanisms and the dominant immune mediators against infection are poorly understood. Previously it has been shown that the infecting S. aureus population goes through a population bottleneck, from which very few bacteria escape to establish the abscesses that are characteristic of many infections. Here we examine the host factors underlying the population bottleneck and subsequent clonal expansion in S. aureus infection models, to identify underpinning principles of infection. The bottleneck is a common feature between models and is independent of S. aureus strain. Interestingly, the high doses of S. aureus required for the widely used “survival” model results in a reduced population bottleneck, suggesting that host defences have been simply overloaded. This brings into question the applicability of the survival model. Depletion of immune mediators revealed key breakpoints and the dynamics of systemic infection. Loss of macrophages, including the liver Kupffer cells, led to increased sensitivity to infection as expected but also loss of the population bottleneck and the spread to other organs still occurred. Conversely, neutrophil depletion led to greater susceptibility to disease but with a concomitant maintenance of the bottleneck and lack of systemic spread. We also used a novel microscopy approach to examine abscess architecture and distribution within organs. From these observations we developed a conceptual model for S. aureus disease from initial infection to mature abscess. This work highlights the need to understand the complexities of the infectious process to be able to assign functions for host and bacterial components, and why S. aureus disease requires a seemingly high infectious dose and how interventions such as a vaccine may be more rationally developed.
Staphylococcus aureus is a leading opportunistic human pathogen renowned for its ability to evade the immune system and cause a variety of different infections [1]. S. aureus infections can vary from superficial skin lesions, through deep seated abscesses to life threatening sepsis [1]. The diversity of disease modalities has made an understanding of the underlying principles of infection challenging. S. aureus primarily occurs as a human commensal, mostly in the nares from whence it is able to seed infection. Many S. aureus infections are iatrogenic, and these are commonly associated with the colonisation of indwelling medical devices [2]. Typically during an infection, after invasion, an immune reaction is initiated by macrophages and these release cytokines to summon neutrophils [3]. Fibrosis also occurs, as well as the death of many of the invading immune cells leading to the pus filled abscesses associated with S. aureus infections. S. aureus can also regularly escape local infection sites and disseminate further. If it enters the bloodstream this can lead to sepsis as well as invasion of other organs whereby further local infections can occur. Thus S. aureus infection is a highly dynamic process with broad dissemination and repeated metastases. Phagocytosis by professional phagocytes such as macrophages and neutrophils is the primary mode by which S. aureus is controlled by the immune system. However, S. aureus has multiple mechanisms to subvert the immune response [4,5], including the production of a variety of specific toxins, the ability to survive intracellularly within immune cells and the capacity to evade capture by phagocytes. As S. aureus is effectively ubiquitous in the human environment, our immune systems are exposed to this organism as evidenced by the significant bloodstream titre of antibodies against a variety of S. aureus antigens [4,6–8], however these do not necessarily afford protection against infection. It is therefore the subject of much debate as to what are the key immune factors that control S. aureus due to the variety of possible infections as well as the many immune components involved [9,10]. This is of great translational importance as the correlates of protection against infection will determine crucial developments such as a vaccine to prevent disease [9,10]. In order to develop the knowledge base to underpin such an intervention it is necessary to first understand the correlates of disease, which in itself is dependent on mapping disease progression from initial infection to resolution in favour of the host or the pathogen. To understand the factors that are important for disease progression it is first necessary to determine the population, spatial and temporal dynamics of the infectious agent within the host. This will highlight the immune breakpoints through which the pathogen must pass to achieve a productive infection. A key way to demonstrate this has been through the creation of multiple tagged variant strains of the pathogen of equivalent fitness and passaging them, at specific ratios, through the relevant host model of disease [11–15]. Subsequent analysis of overall pathogen numbers and the ratios of the tagged strains allows determination of the within host population dynamics. Coupling this with temporal and spatial (specific organ) analysis provides a map of the spread and proliferation of the infectious agent, and highlights the potential for population bottlenecks from which clonal expansion may occur. In model animal systems this can also be combined with the manipulation of the host and/or pathogen to determine the role of multiple factors in disease. This type of study has been very revealing for a range of pathogens such as Streptococcus pneumoniae, Yersinia pseudotuberculosis and Salmonella enterica [12,14,16]. We have used this approach with S. aureus to demonstrate a population bottleneck during systemic infection in murine and zebrafish embryo models [13,17]. An initial discovery in the zebrafish model was used to inform the design of murine experiments. Using an intravenous administration of a mix of 3 antibiotic resistance marker tagged S. aureus Newman HG (NewHG) clones it was found that the bacteria are initially largely sequestered in the liver and spleen. Bacterial numbers subsequently slowly decreased in the liver with concomitant increasing numbers in the kidneys. In the liver and spleen the initial ratio of strains is apparent but surprisingly there is a significant alteration in strain ratio in the kidneys consistent with individual bacteria founding the characteristic abscesses [13]. This clonal expansion increases in all organs during infection but is most pronounced in the kidneys. These results show that a population bottleneck can occur in the mouse alluding to a metastatic spread of bacteria from a primary site of infection to the kidneys. In zebrafish, manipulation of professional phagocytes demonstrated the population bottleneck to be likely neutrophil mediated (with the involvement of macrophages) [17,18]. Since it is mediated by immune cells we would also define this population bottleneck as an immune bottleneck. This provides an initial framework onto which to map within host population dynamics and the influence of host immune defences. The basis for key developments in our understanding of disease relies on the use of animal models, the aim of which is to reflect facets of human disease. There are a multiplicity of S. aureus infection models available, ranging from insects (e. g. Drosophila & Galleria), to zebrafish and mammals (e. g. mice and rabbits) [9,17,19,20]. Mammalian models are considered the most apposite for S. aureus infections as they share several important characteristics with humans, for instance body temperature, innate and adaptive immune systems and disease pathology. However mammalian models typically require a high initial inoculum to ensure disease initiation and many S. aureus virulence determinants are human specific [9,21]. Consequently, it is difficult to equate animal model data with the human situation, particularly in the translational context where for instance, despite promising animal model data, vaccine trials have failed in the clinic [9,10]. Given these caveats, animal models are still important conduits for discovery of basic disease parameters. However it is important to evaluate the relative merits of the available models before relying on them to make useful conclusions. In this study we have used 3 models of systemic disease: firstly the zebrafish model to provide initial data to inform murine studies and then the mouse sepsis and survival models (15,18–20). The sepsis model is well established and gives a clear progression of bacterial population dynamics [22]. The survival model has been standard for many studies and is fundamentally similar to the sepsis model in that bacteria are commonly injected in to the bloodstream. However the dose is relatively much higher to cause the subjects to succumb to infection rather than survive and resolve as in the sepsis model [23]. The survival, or lethal challenge model, has been in general use and is of regulatory importance [21,23,24]. Here, we have evaluated infection dynamics in the above systemic models of infection with a suite of otherwise isogenic, antibiotic resistant variants of a range of S. aureus strains. This has revealed population bottlenecks within organ pathogen spatial distribution and established the role of specific immune effector cells in the dynamics of infection. This has led to the formulation of a new conceptual model for disease progression.
To evaluate potential strain-specific and generic pathogenesis parameters the population dynamics of a range of different S. aureus strains (Newman, NewHG, SH1000 and USA300) in the zebrafish embryo systemic model was first determined. Three matched antibiotic resistant S. aureus strains in the USA300 (JE2) strain background: erythromycin/lincomycin-resistant, EryR (EPPS1); kanamycin-resistant, KanR (EPPS2); and tetracycline-resistant, TetR (EPPS3), and the Newman strain background EryR (EPPS4), KanR (EPPS5), TetR (EPPS6) were produced by transduction of the relevant markers from the previously constructed NewHG strains [13]. The established zebrafish embryo model of systemic disease was then used [17], whereby a 1: 1: 1 mixture of the variants of each strain was injected into embryos 30 hours post fertilisation (c. 1500 CFU (colony forming units) in total), followed by monitoring of host survival. Bacteria were harvested from embryos and their total numbers and proportions of each S. aureus strain variant determined. Each marked variant was equally likely to predominate (group variation was not significantly different, Bartlett’s test for equal variance USA300: p = 0. 1252, Newman: p = 0. 2364), demonstrating that there were no relative fitness costs associated with the individual antibiotic resistance markers which would undermine the analysis [11] (S1 Fig). The proportion of the different strains was used to generate the species evenness index for the population [25], which defines how evenly matched different populations of organisms are within an environment. A population evenness of 1 for a given population (whether it was a host or organ) means the strain variants are evenly distributed (1: 1: 1 ratio) whereas 0 means the entire population consists of one strain variant. We chose the population evenness metric as it is a commonly accepted in ecological studies [26,27]. It is suitable as it is based on Shannon’s diversity index which is equally sensitive to very rare and very common species in a sample. Our samples inherently had these properties as the populations varied from evenly mixed to completely dominated by 1 variant. We found that the variants which randomly came to predominate readily occurred in both the Newman and USA300 infected hosts, i. e. the population evenness of the injected population started at near 1 and became 0 over the course of the experiment (Fig 1). Additionally, there was a statistically significant correlation between time of death and decreasing population evenness for both strain backgrounds (linear regression, USA300: P<0. 0001, F = 57. 39, R2 = 0. 3766, Newman: p = 0. 0006, F = 13. 69, R2 = 0. 2504, Fig 1). The decrease in population evenness showed that the population had an increased chance of being clonal over time. This meant that the bacterial population in those zebrafish had passed through a likely population bottleneck. This corresponds to the previous observation of clonality in SH1000 and NewHG in the zebrafish model. The marked strains were then used for determination of the population dynamics in the established murine sepsis model of infection [22]. A total infectious dose of approximately 1x107 CFU was injected intravenously via the tail for each combination of marked variants in the 4 strain backgrounds (Newman, USA300, SH1000 and NewHG constructed here and previously [13]). Mice were culled at 2,18,48 and 72 hours post infection. The heart, lungs, spleen, left and right kidneys and liver were extracted from each subject, homogenised and the CFUs (colony forming units) of the different marked variants determined. As for the zebrafish model the species evenness index was determined. Overall the occurrence of the TetR, EryR and KanR populations was not significantly different in the mice regardless of strain (S1 Fig, Bartlett’s test for equal variance, SH1000: p = 0. 5598, NewHG: p = 0. 8478, Newman: p = 0. 9631 and USA300: p = 0. 9330), demonstrating that in all strain backgrounds the antibiotic resistance markers did not impart a fitness cost in the mouse model. The occurrence and distribution of S. aureus for NewHG, Newman, SH1000 and USA300 are shown in Figs 2 and S2. As the liver is likely the source of within host dissemination, how is this mediated? Previously we have postulated that phagocytes form the focus for the population bottleneck and it has been demonstrated that macrophages and neutrophils are required for the control of S. aureus infections in the mouse and zebrafish models [17,28,29]. In particular, it has been shown that after iv injection, S. aureus is initially phagocytosed by Kupffer cells (liver macrophages) [30]. Neutrophils have also been demonstrated to act a potential “Trojan horses” carrying viable bacteria within themselves [5]. Macrophages were depleted using clodronate vesicles [31] and, as expected, mice are consequently more susceptible to S. aureus infection and so the dose was reduced to 1x105 CFU of 1: 1: 1 labelled NewHG. Treated mice had a significantly higher bacterial burden in the liver compared to the control vesicle treated subjects (ANOVA, p<0. 0001 Multiple comparisons show that the clodronate treated is significantly different from the blank controls, Fig 4). An additional replicate produced similar results (S5 Fig). Occasionally other organs, including the kidneys, were colonised. Interestingly, population evenness was significantly increased compared to the control (Kruskal-Wallis, p = 0. 0002, Multiple comparisons show that the clodronate treated group is significantly different from the blank controls). This increased population evenness is due to the formation of multiple small abscesses visible on the liver rather than a single clone emerging. Similarly, to macrophage depletion, neutropenia (generated using anti-Ly6G antibodies) resulted in greatly increased susceptibility to S. aureus infection with an inoculum of 5x105 CFU being used (Fig 4). Neutropenic mice demonstrated detectable bacteria almost exclusively in the liver and in contrast to macrophage depletion these populations showed no difference in population evenness compared to the control, indicating clonal expansion (Kruskal-Wallis, p = 0. 0002, Multiple comparisons show that the anti-Ly6G treated group is significantly different from the clodronate groups but not the blank controls). The infected livers appeared pale with no observable surface abscesses. We initially tried a lower dose of 1x105 CFU, although there was neutrophil depletion, the resulting CFUs were no greater than the controls (again only the livers contained S. aureus by day 3 post infection) so we increased the dose used to the 5x105 CFU results presented (additional results are shown in S5 Fig). We also depleted the neutrophils using cyclophosphamide and an inoculum of 1x105 CFU. This again showed pale livers, increased CFU in the livers and mostly clonal in contrast to the macrophage depletion study (S5 Fig) and supporting our anti-Ly6G results (Liver CFU ANOVA, p<0. 0001, Multiple comparisons show that the cyclophosphamide treated group is significantly different from both the blank controls and clodronate). However, the depletion of neutrophils was not as complete (cyclophosphamide is generally toxic and although it depletes neutrophils in particular it also affects lymphocytes, monocytes and other fast growing cells) so the anti-Ly6G mediated depletion was preferred for demonstrating the effect of neutrophils. Whilst both macrophages and neutrophils are required for host defence compared to the control and their loss results in greater bacterial loads (ANOVA, P<0. 0001 Multiple comparisons show that the clodronate and anti-Ly6G treated groups are significantly different from the blank controls) the macrophages, and not neutrophils, appear to be the basis for clonal expansion as their depletion results in increased population evenness. Macrophage depletion also results in greater bacterial loads than neutrophil loads when the same amount of S. aureus is administered, further indicating that macrophages are the likely bottleneck. Conversely, neutrophils appear to be involved in the seeding of organs from an already derived clonal population within the liver. Kidney abscesses in the sepsis model are largely clonal in that they are derived from an individual founding cell [13,18]. However, outwardly the kidneys can show a multi-lobed abscess structure (Fig 5A). Two methods of within-organ analysis were used, both using a mixed population of differentially labelled bacteria to allow clonality to be determined post hoc. Firstly mice were injected with a 1: 1 ratio of 1x107 CFU NewHG GFP KanR/NewHG mCherry EryR, and at 5 days post infection (the time by which kidney abscesses had developed), the mice were sacrificed. Infected kidneys were serially and sequentially sectioned for CFU determination, histology and microscopy analysis of labelled bacterial populations (Fig 5B). This allowed a reconstruction of the 3D abscess architecture. Sample organs were sectioned every 300μm and 3x8μm sections of tissue were stained with either DAPI or Hematoxylin and Eosin (Fig 5F and 5G). The 300μm of tissue in between these sections was homogenised and plated for CFU determination (Fig 5D). Secondly, an optical clearing technique was employed to reveal the in situ distribution of fluorescently labelled bacteria within the organ (Fig 5H and S1 Video). Here lightsheet microscopy allowed a 3D rendering of the bacterial distribution to be determined [32,33]. Overall the histological sectioning revealed that there was an uneven distribution of bacteria within organs, with distinct foci that correlated with both CFU and visualisation of fluorescent bacteria (Fig 5). The foci of infection consist of solid aggregates of S. aureus or scattered individuals that co-localise with areas of neutrophil infiltration (S7 Fig). Where mature abscesses were present they almost exclusively consisted of one fluorescent variant (Fig 5C and 5D). However, this technique resulted in the destruction of the tissue and we used new techniques to confirm the distribution of S. aureus in the kidneys. We used lightsheet microscopy combined with the optical clearing of the organs, which maintains the fluorescence of the bacteria whilst making an abscess observable in 3D. Organ clearing and lightsheet microscopy has been used in other systems to great effect due to preserving structures in situ and we anticipate this technique will be of great use in S. aureus research. The lightsheet microscopy additionally showed (beyond the details revealed by histology) that within abscesses the solid aggregates in the kidneys were following the structure of kidney tubules in the cortex whilst the neutrophil infiltration sites were outside the tubules (Fig 5H and S1 Video). This would not have been demonstrated by histology alone. Based on these observations it seems likely the S. aureus is trapped in the tubules, grows into solid aggregates and then some can subsequently escape into the regions between the tubules where neutrophils engage the bacteria. Even in infected organs that contain abscesses that overall are formed from more than one marked strain, there is a clear differential distribution of clones suggesting that pervasive abscesses which have multiple foci are seeded from a single bacterium which has divided and spread to form extended foci of infection in the surrounding tissue. The mouse survival model has been used widely to test the efficacy of novel treatments, prophylaxis and the role of bacterial and host factors in disease [21,23,34–36]. It is technically similar to the mouse sepsis model but primarily differs in that an increased dose is given leading to mortality as a primary output. Strains NewHG, Newman, SH1000 and USA300 were compared using the survival model. For all strains a high inoculum was used (around 1x108 CFU except USA300 which is similarly lethal at a lower dose of 3x107 CFU), made up of equal proportions of the 3 antibiotic resistant marked variants in each case (Figs 6 and S3). Infection became systemic in every subject, with bacteria across multiple organs, and typically resulted in mouse cull within 2–3 days. Clonality (low population evenness) was much rarer at these high doses in all organs, in all subjects, and across all 4 bacterial strains (Fig 6). It was also notable that the hearts, lungs and spleens now had high numbers of S. aureus. To determine whether the sepsis and survival model were ends of a spectrum or independent of each other, intermediate doses of the strains were administered to delay, and reduce, the number of subjects reaching the morbidity endpoint (for all strains around 3x107 CFU except USA300 which is similarly lethal at a lower dose of 1x107 CFU). This resulted in a lower rate of mortality (S4 Fig), with those subjects culled up to and including day 5 having more systemic infections, whereas after this time only the liver and kidneys had bacterial loads as the infection resolves. Lower dose survival treatments had much greater levels of clonality than the equivalent higher dose survival treatment. Both kidneys are more frequently concurrently infected as well. Overall there is a significant correlation between increasing initial dose of S. aureus and the decreasing occurrence of clonality (linear regression, p = 0. 0386, F = 6. 959, R2 = 0. 5370, Fig 7). There is a significant correlation between increasing clonality and increased survival by day 4 (linear regression, p=0. 0049, F=18. 82, R2=0. 7583, Fig 7). There is also a significant correlation between increasing initial dose of S. aureus and decreasing survival (linear regression, p = 0. 0196, F = 9. 982, R2 = 0. 6246). The order of increasing virulence in the survival model was SH1000, Newman, NewHG and USA300 consistent with previous reports [37–39].
As an opportunistic pathogen, S. aureus is able to cause a wide range of human diseases from the superficial to potentially life threatening. There are multiple animal models of S. aureus infection that all aim to recapitulate those events that shape the interaction between the pathogen and the human host. However, increasingly there is evidence that many of the virulence determinants are human specific and thus are not relevant to the widely used animal models. Also the route and mode of human infection is difficult to replicate in models. Murine models of S. aureus infection are commonplace and have been one of the main tools in developing our understanding of the disease processes. Models of sepsis (bacteraemia) are well-established and are characterised by kidney abscesses as a primary outcome [21,23,24]. Establishment of sepsis requires a high inoculum as is apparent in other murine models. This has been suggested to be due to a bolus of bacteria being required to initiate disease [13,15]. Recently we have shown that, in fact, there is a population bottleneck whereby likely single bacteria found kidney abscesses [13,18]. This therefore requires an explanation as to what the series of events that precedes abscess formation are, and the mechanism (s) involved. The individual bacteria that found lesions occur randomly from the population in that they do not have a genetic advantage [13,18]. Thus the initiation of abscesses is a stochastic event that is enhanced by a large inoculum. Here we aimed to investigate within-host population dynamics and determine the cellular basis of bottlenecks in S. aureus infection models. The temporal and spatial dynamics of sepsis in zebrafish and murine models have been determined using sets of marked strains in a range of backgrounds. This enabled a model for the dynamics of infection in the mouse to be established (Fig 8). We found for all strains that the liver was the key destination organ for the initial mixed population inoculum. Previously S. aureus has been shown to be phagocytosed by Kupffer cells in the liver and these form a primary immunological defence (2,22). Subsequently expansion of individual clones occurs in the liver or the bacterial load is cleared. Kupffer cells are effective agents for the control of S. aureus but if this immunological bottleneck fails then bacteria are able to grow to form abscesses. Depletion of Kupffer cells results in greatly increased host susceptibility to S. aureus infection manifested by abscesses mostly in the livers, but also in the kidneys. Kidney abscesses develop during the infection but these organs are not an initial colonisation site. Interestingly kidneys do not have mixed populations that then become clonal but rather this happens at abscess initiation suggesting that they are founded by single organisms or that the founders were already clonal. Given the complex population dynamics in the liver we suggest that it is the transfer of S. aureus from the liver that gives rise to kidney colonisation. But how therefore do the bacteria traffic between organs? A clue to this comes from the generation of neutropenia within the mouse. Interestingly loss of neutrophils results in no loss of clonality within the liver. Thus the neutrophils are not the primary bottleneck within the liver. However, subsequent abscess formation was abrogated within the kidneys. The importance of neutrophils for dissemination correlates with other research that shows that S. aureus can live intracellularly within phagosomes and be transported by them in the blood, forming a mobile reservoir to infect other organs [5,40,41]. Also, treatment with antibiotics that do not penetrate the neutrophil phagosome do not prevent internal dissemination of S. aureus [30,42]. However, conventionally neutrophils that mature and enter infected tissue do not re-enter the blood stream [28,43]. The most parsimonious explanation is that neutrophils that are already circulating in the blood (whose population greatly increases in response to infection) take up S. aureus that escape into the blood stream from the lesions in the liver. This could be due to abscesses/microlesions shedding S. aureus into the blood stream, as is known to occur in clinical infections [44]. Kidney CFU alone is used as a readout in many studies of S. aureus disease, for which one might express caution as if bacteria have passed through the liver bottleneck then they can clonally expand and so the subtleties of S aureus infection prior to this point will be lost. Liver CFU provides a useful adjunct to kidney numbers. It might seem surprising that a kidney with many apparent surface abscesses could in fact be seeded by an individual founder. It is also important to note that it is unlikely that apparently clonal organs are founded by multiple bacteria of the same type as left and right kidneys are often clonal but with different clones. In order to determine how a single organism could establish a disseminated abscess throughout a kidney we began to map the 3D architecture of the abscess. We developed two methods to address this conundrum. Serial organ sectioning revealed foci of infection with the characteristic abscess structure of infiltration of phagocytes but these extended throughout the kidney forming a seemingly linked series of lesions. Organ clearing is a new approach to study infecting organisms within host tissue and here it revealed a pervasive spread of S. aureus as solid aggregates within cortex tubules and as diffuse groupings with infiltration of phagocytes outside these tubules [33,45]. The scheme presented in Fig 8 suggests the presence of two immunological bottlenecks within the murine sepsis model. Firstly, at the level of Kupffer cells in the liver and then at the neutrophils when disseminating from the liver. Zebrafish embryos do not have Kupffer cells at the time of infection. In the zebrafish the population bottleneck occurs in the phagocytes but is mainly believed to be due to the neutrophils[18]. Our mouse models therefore apparently diverge from the zebrafish model on the relative importance of the two major classes of professional phagocytes. This study provides data that phagocytes present a key breakpoint during infection in that these cells are absolutely required for host resistance but also permit proliferation as “Trojan Horses” as has been previously proposed [40]. The question arises however as to whether this hypothesis translates into a human infection both in terms of the immune system and the occurrence of population bottlenecks. The murine sepsis model shares several characteristics that are known to occur within human infections such as how S. aureus can disseminate in the blood stream to different organs from an initial infection site and the formation of localised abscesses in separate organs. It is known that professional phagocytes are key to controlling S. aureus infections but that S. aureus can also hide intracellularly [5,28]. What we have found correlates with human infections. In our model both neutrophils and macrophages are important for controlling S. aureus infection and the same is true in humans as shown by various genetic disorders in these can result in increased S. aureus infections [46]. This is however more commonly associated with neutrophil disorders (which may reflect how macrophages are generally less dispensable as they are required for tissue development and homeostasis). One particular point is that our model shows that the liver is the site of the primary bottleneck. Generally, in humans, the liver is not a site particularly associated with S. aureus infection (compared to soft tissue infections or deep infections such as osteomyelitis) so it would seem unlikely it would have the same role in humans. However, patients with chronic granulomatous disease (lacking the respiratory burst part of phagocytosis) have a particularly high risk of staphylococcal liver abscesses [46,47]. This implies that in normal people S. aureus can be cleared from the liver as a normal process, which would be by the action of Kupffer cells, the resident professional phagocytes. Our results suggest that the killing activity of macrophages on S. aureus should be worthy of further study but also the ability of neutrophils to transfer S. aureus between organs should also be of great interest as has been shown by other methods [5,30]. Genome studies have shown that there are repeated genetic population bottlenecks and that these occur both during transmission and the shift from colonisation to disease [48–50]. In human infections, population bottlenecks would be interacting with the inherent variation of the naturally colonising S. aureus population as infections tend to be derived from the previous resident S. aureus [48]. The existence of stochastic niches and resource limitation (here access to host nutrients) according to ecological studies are intrinsically supposed to maintain increased population diversity particularly if they are better at competing for different resources [51]. Population bottlenecks, as the host is infected, would form stochastic niches and the exact site would exert different selection pressures. They could therefore work to maintain population diversity and increased strain divergence as the population bottleneck would randomly exclude different subpopulations upon each infection. This may be reflected in the diversity of virulence factors that different strains of S. aureus possess and the maintenance of different clones of S. aureus [52]. Population bottlenecks would also favour variants that are better at getting through it rather than selecting for mutants fitter after subsequent diversification. This concurs with the diversity seen in Young during colonisation and the more limited subsequent diversification [48]. A population bottleneck results in a notable distribution of the observable population. There are members of the administered dose that pass through and come to dominate the population and then there are those that are excluded, which ultimately means there tends to be two groups of data: mixed populations that have not yet passed through the bottleneck and populations that have become, or are rapidly becoming, clonal (as one strain is expanding relative to the others). This can be seen in our data as organs with a mixed population with all 3 strains present and organs with clonal populations. It is reasonable to make assessments based on the proportion of a population that was mixed or clonal as we have done but it would be much harder to assess if one population was becoming clonal more quickly than another (e. g. if one strain or another was better at expanding out of the macrophage bottleneck). Population bottlenecks during infection represent key breakpoints for interventions. Despite apparent success in animal models, vaccine development for S. aureus has not translated into successful human trials [10,53]. Active vaccination is by its nature prophylaxis and thus the target should be to prevent the ability of S. aureus to pass through bottlenecks and proliferate. The knowledge that intracellular organisms form this nexus within phagocytes provides a key parameter from which to design future vaccine formulations. Recent evidence highlighting the targeting of intraphagocytic S. aureus supports such an approach [42]. This is consistent with what has been found previously, in that S. aureus can survive within neutrophils; and treating mice with antibiotics that do not affect intracellular S. aureus does not prevent dissemination [5,30]. Our work, as well as highlighting the cellular locations of immunological bottlenecks also sheds light on the role of the infectious dose on the outcome of infection and the population dynamics therein. The survival challenge model is a standard in the field and has been used in many studies [21,24]. Measuring population dynamics within this model showed a clear diminution of population bottlenecks correlating with an increased infectious dose leading to host morbidity. High infectious doses result in systemic infections across all major organs. The relevance of this model is therefore bought into question as clearly those immunological processes that control the dynamics of infection have been overwhelmed. This observation is therefore of great importance for the design of intervention studies where one is modelling human infection and not uncontrolled bacteraemia. Using lower doses is more realistic as well as allowing population bottlenecks to occur as infectious doses of S. aureus are likely to be inherently lower in humans compared to our mouse models. In Grice et al punch biopsies were used which gave total bacterial numbers of at least 106 CFU/cm2[54]. In a study of vascular catheters, a range of bacteria were found with numbers up to 107 CFU [55]. In a given infection it is likely that only a fraction of these would be able to disseminate from the skin or implant. This is reflected in bacteraemia where the count is typically <10 CFU per ml [56]. The number of bacteria that can transfer to infect organs is much less than >5 x 107 CFU per ml murine blood if 108 CFU is injected (assuming 1. 5 ml of blood per 25g mouse). The threat of antimicrobial resistance to human healthcare is real and increasing. Disease is a complex and dynamic interplay between host and a population of infectious agent. Here we have highlighted key parameters of how S. aureus disease progresses and provide a framework for determination of efficacy of new interventions.
Animal work (both mice and zebrafish) was carried out according to guidelines and legislation set out in the UK Animals (Scientific Procedures) Act 1986, under Project Licenses PPL 40/3699 and PPL 40/3574. Ethical approval was granted by the University of Sheffield Local Ethical Review Panel. Staphylococcus aureus strains (S1 Table) were grown using brain heart infusion (BHI) liquid or solid medium (Oxoid) at 37°C, supplemented with the following antibiotics where appropriate: kanamycin 50 μg/ml, tetracycline 5 μg/ml or erythromycin 5 μg/ml plus lincomycin 25 μg/ml (Sigma-Aldrich). S. aureus TetR, EryR and KanR strains used included those constructed previously [13]. The resistance markers were transferred into further strain backgrounds using ϕ11 transduction [57]. ϕ11 variants of suicide vector pMUTIN4 were used to integrate various antibiotic resistance cassettes downstream of the lysA gene in S. aureus in the original strains [13]. The genomic region surrounding lysA is conserved in the Newman and USA300 genomes. The suicide vector pKASBAR (and pKASBARkan) was used to integrate constitutive GFP and mCherry fluorescence markers with promoter Pma1M from the E. faecalis pmv158GFP and pmv158mCherry plasmids into the S. aureus lipase gene in RN4220 [58,59]. The fluorescent markers were then transferred into SH1000, Newman, NewHG and USA300 by ϕ11 transduction. This resulted in strains which were GFP KanR or mCherry TetR. A fragment of c. 1200 bp containing the GFP encoding gene and its promoter sequence was amplified by PCR from pMV158GFP plasmid using the following primers: The PCR fragment was cloned into pKASBARkan by Gibson assembly, with the plasmid cut by EcoRI and BamHI [58]. The resulting plasmid pKASBARGFPkan was introduced into E. coli NEB5-alpha by electroporation with selection for ampicillin resistance. The correct plasmid was confirmed by sequencing and used to transform S. aureus competent cells RN4220 containing a helper plasmid pCL112Δ19 and then selected for with Kanamycin[60]. The marker was then transferred into the NewHG strain (and other backgrounds) by ϕ11 transduction. A fragment of c. 1200 bp containing the mCherry encoding gene and its promoter sequence was amplified by PCR from pMV158mCherry plasmid using the following primers: The PCR fragment was cloned into pKASBAR by Gibson assembly with the plasmid cut by EcoRI and BamHI[58]. The resulting plasmid pKASBARmCherry was introduced into E. coli NEB5-alpha by electroporation with selection for ampicillin resistance. The correct plasmid was confirmed by sequencing and used to transform S. aureus competent cells RN4220 containing a helper plasmid pCL112Δ19 and then selected for with tetracycline [60]. The marker was then transferred into NewHG (and other backgrounds) by ϕ11 transduction. The generated strains however showed only weak tetracycline resistance and were therefore supplemented by EryR from SJF3673 strain collection (lysA: : ery lysA+) by ϕ11 transduction. Transductants with supplemented EryR were verified by PCR. London wild-type (LWT) zebrafish embryos (bred in the MRC CDBG aquarium facilities at the University of Sheffield; see Ethics Statement) were used for all experiments and were incubated in E3 medium at 28. 3°C according to standard protocols [61]. Anaesthetized embryos at 30 hours post fertilization were embedded in 3% w/v methylcellulose and injected individually using microcapillary pipettes filled with bacterial suspension of known concentration into the blood circulation, as previously described [17]. Following infection, embryos were kept individually in 100 μl E3 medium, and observed frequently up to 90 hours post infection; dead embryos removed and CFU from these embryos recorded at each time point. 6–7 week old Female BALB/c mice were purchased from Envigo (formerly Harlan (UK) ) and maintained at the University of Sheffield using standard husbandry procedures. The mice were acclimatised for 1 week. The mice were then inoculated in the tail vein with 100 μl of S. aureus suspension in endotoxin-free PBS (Sigma) diluted from frozen stocks. Viable bacteria in the inoculum were plated on TSB (plus appropriate antibiotics) after serial decimal dilution to confirm the accuracy of the bacterial dose. Mice were monitored and sacrificed at various time-points according to experimental design. All mice were injected with 1x107 CFU S. aureus consisting of a 1: 1: 1 ratio of KanR, EryR & TetR variants of the different strains (SH1000, Newman, NewHG, USA300). 5 mice were sacrificed at the following time points post infection: 2hrs, 18hrs, 48hrs, 72hrs (end of procedure) The mice were injected with the following doses of S. aureus to reflect different levels of challenge that result in both low and high levels of mice that reach the severity limits. The higher dose set: SH1000: 1x108 CFU, NewHG: 1x108 CFU, Newman: 9x107 CFU, USA300: 3x107 CFU The lower dose set: SH1000: 3x107 CFU, NewHG: 3x107 CFU, Newman: 3x107 CFU, USA300: 1x107 CFU. Macrophages were depleted using clodronate liposomes following previously published protocols (NvR, http: //www. clodronateliposomes. org/) [30,31]. The mice were injected iv with 1ml of liposomes per 100g on day 1. The mice were then injected with 1x105 CFU S. aureus on day 2. Mice were sacrificed on day 5 (3 days post infection). Blank liposomes were used as a control. Macrophage depletion was confirmed in pilot studies using histology sections of the liver stained with F4/80 from Serotec AbD Serotec MCA497, followed by an anti-rat red fluorophore. The results confirming macrophage depletion are shown in S6 Fig. Neutrophils were depleted using anti-Ly6G mouse antibodies following previously published protocols [62]. For antibody based neutrophil depletion Invivo anti-Ly6G mouse antibody (1A8, BioXcell) was used [62]. The mice were injected with 1. 5mg/mouse (200ul per mouse) on day 1 with the mice being injected with S. aureus on day 2. Mice were sacrificed on day 5 (3 days post infection). For cyclophosphamide depletion mice were injected intraperitoneally with 150mg/kg cyclophosphamide monohydrate (Sigma, also known as Cyclophosphamide & Cytoxan) on day 1 and 100mg/kg cyclophosphamide intraperitoneally on day 4. The mice were injected with 20mg/ml cyclophosphamide reconstituted in etox free water. The mice were then injected with S. aureus on day 5. Mice were sacrificed on day 8 (3 days post infection). Neutrophil depletion was confirmed using flow cytometry. 100μl of blood was collected via tail bleeding at the same time as S. aureus was injected and 100μl was collected at the end of the experiment via terminal anaesthesia and heart puncture. These blood samples were each mixed with 20μl of Heparin. The blood samples were stained with APC Rat Anti-Mouse Ly6G antibody (BD biosciences, cat. No: 560599) according to the BD bioscience protocol for Immunofluorescent Staining of Mouse and Rat Leukocytes and Fixation with fixation buffer (cat. No: 554655). (http: //www. bdbiosciences. com/eu/resources/s/mouseratleukocytes). The samples were then processed using the BD LSRII flow cytometer. The results confirming neutrophil depletion are shown in S6 Fig. In order to recover bacteria from host tissues, whole zebrafish embryos or mouse organs were individually homogenized in a suitable volume of PBS using the PreCellys 24-Dual (Peqlab) [13]. Homogenates were serially diluted in PBS and plated on TSB (S. aureus) or TSB supplemented with appropriate antibiotics (tetracycline, erythromycin or kanamycin) to determine bacterial numbers. The limit of detection was defined as <100 CFU as defined previously and these results were treated as 0 CFU [13]. Mice were injected with a 1: 1 ratio of 1x107 CFU NewHG GFP KanR/NewHG mCherry EryR, and at 5 days post infection the mice were sacrificed, organs with notable abscesses were sectioned and histology performed. The selected organs were sectioned evenly throughout. Every 300μm, 3 sections (8μm each) of tissue were stained with either DAPI, Hematoxylin and Eosin, or Gram stain. The 300μm sections in between were homogenised separately and plated out for bacterial enumeration as described above. DAPI stained tissue sections were analysed using a Nikon Dual Cam fluorescent microscope whilst the Hematoxylin and Eosin or Gram stained slides were analysed using an Aperio digital microscope slide scanner. Other organs were optically cleared using the ScaleS protocol and were visualised using a Zeiss Z1 lightsheet microscope [33]. Survival experiments were evaluated using the Kaplan-Meier method. Comparisons between curves were performed using the log rank test. For comparisons between CFU groups, a two-tailed, unpaired ANOVA was used. For comparisons of strain ratios where 3 strains were tested (e. g. TetR, EryR and KanR), species evenness was calculated per sample (Species evenness is Shannon’s diversity index H divided by the natural logarithm of species richness ln (S) ) and then compared using a (non-parametric) Kruskal-Wallis test. Bartlett’s test for equal variance was used to test if the mixed strains were equally fit (population spread should be equal). For comparing correlations linear regression was used and the mean was presented on corresponding graphs. All statistical analysis was performed using Prism version 6. 0 (GraphPad) and statistical significance was assumed at p<0. 05. Error bars indicate mean ± One Standard Deviation. | Staphylococcus aureus is a major human pathogen that causes a wide variety of infections. In animal infection models, high doses of S. aureus are generally required to establish infections. We have recently shown in animal models that this is due to very few bacteria within the infecting population going on to cause disease. This population bottleneck during infection is an ideal target for treatment development. Here we have shown that this bottleneck is common to a range of different S. aureus types and infection models. The mouse survival model is commonly used for testing antistaphylococcal treatments. We show that the large infectious dose it requires diminishes the bacterial population bottleneck. This suggests the host immune system is simply overwhelmed and brings into question the applicability of such a model. We found that both macrophages and neutrophils are important for resistance to S. aureus infection but these affect the population bottleneck differently. Macrophages in the liver mediate the initial population bottleneck whereas neutrophils enable the subsequent spread of bacteria to other organs. This has allowed a model of S. aureus disease progression to be established and our study gives insights into how novel treatments could be established to counter it. | Abstract
Introduction
Results
Discussion
Materials & methods | blood cells
medicine and health sciences
fish
liver
immune cells
pathology and laboratory medicine
pathogens
immunology
microbiology
vertebrates
staphylococcus aureus
animals
animal models
osteichthyes
model organisms
signs and symptoms
experimental organism systems
kidneys
bacteria
neutrophils
bacterial pathogens
research and analysis methods
abscesses
white blood cells
animal cells
staphylococcus
medical microbiology
microbial pathogens
mouse models
zebrafish
eukaryota
diagnostic medicine
anatomy
cell biology
biology and life sciences
cellular types
renal system
macrophages
organisms | 2018 | Staphylococcus aureus infection dynamics | 11,327 | 269 |
Novel drugs are required for the elimination of infections caused by filarial worms, as most commonly used drugs largely target the microfilariae or first stage larvae of these infections. Previous studies, conducted in vitro, have shown that inhibition of Hsp90 kills adult Brugia pahangi. As numerous small molecule inhibitors of Hsp90 have been developed for use in cancer chemotherapy, we tested the activity of several novel Hsp90 inhibitors in a fluorescence polarization assay and against microfilariae and adult worms of Brugia in vitro. The results from all three assays correlated reasonably well and one particular compound, NVP-AUY922, was shown to be particularly active, inhibiting Mf output from female worms at concentrations as low as 5. 0 nanomolar after 6 days exposure to drug. NVP-AUY922 was also active on adult worms after a short 24 h exposure to drug. Based on these in vitro data, NVP-AUY922 was tested in vivo in a mouse model and was shown to significantly reduce the recovery of both adult worms and microfilariae. These studies provide proof of principle that the repurposing of currently available Hsp90 inhibitors may have potential for the development of novel agents with macrofilaricidal properties.
Infections caused by the parasitic filarial nematodes Wuchereria bancrofti, Brugia malayi and Onchocerca volvulus remain a significant cause of pathology in the tropics. The adult stages of these pathogens are extremely difficult to kill with currently available drugs. Treatment relies upon two compounds, ivermectin (IVM) or diethylcarbamazine (DEC), both of which largely target the larval stage of the life cycle (the microfilariae, Mf). In the Global Campaign for the Elimination of Lymphatic Filariasis, either DEC or IVM is combined with albendazole. While this approach effectively disrupts transmission [1], Mf repopulate the circulation, necessitating the repeated administration of drug. As the reproductive life span of the adult female worm is estimated to be around 10 years for the lymphatic species [2] and longer for Onchocerca volvulus [3], programs aimed at eradication of these parasites are faced with a considerable challenge, as treatment must be continued over this long timescale. At least for O. volvulus, the repeated administration of ivermectin over many years is associated with treatment failures [4], although whether these truly reflect resistance remains the subject of debate. Consequently, drugs that target adult filarial worms would be a major advantage in control programs aimed at eliminating these parasites [5]. Heat shock protein 90 (Hsp90) has emerged in recent years as a validated target for the therapy of various tumors [6], resulting in the development of many Hsp90-specific small molecule inhibitors. Hsp90 is essential in all eukaryotes and several recent studies have demonstrated the activity of specific inhibitors against a variety of tropical pathogens, such as Plasmodium [7], [8], Trypanosoma sp [9] Leishmania sp [10] and the filarial worm Brugia [11], [12]. The repurposing of compounds designed for one purpose to control of tropical infections is an attractive proposition [13], generating considerable enthusiasm in the pharmaceutical industry. Starting the search for new therapeutics for these diseases with drug-like molecules offers several short cuts, as these have already passed the basic criteria for development, have usually been optimized for their drug-like qualities and have often undergone toxicity testing. Here we compare the efficacy of several classes of Hsp90 inhibitor against the lymphatic filarial nematode Brugia. The prototype Hsp90 inhibitor is geldanamycin (GA), a fermentation product of Streptomyces species that binds at the N-terminal ATP domain of Hsp90 disrupting its function [14]. Hsp90 acts as a molecular chaperone helping to fold and stabilize a variety of different proteins, the so-called ‘client’ proteins, many of which are involved in signal transduction [6]. The realization that Hsp90 client proteins, such as those encoded by oncogenes, were unable to attain their active conformation and were degraded following exposure to GA led to studies in animal models of various cancers. However, GA suffers from several target-unrelated limitations as an in vivo chemotherapeutic agent because of its chemical structure, as it contains a benzoquinone ring, rendering it hepatotoxic [15]. GA has been extensively modified to limit these liabilities and some of the resulting derivatives are still undergoing clinical assessment (reviewed in [16]). However, most recent efforts have been directed at developing synthetic small molecule inhibitors of distinct chemical scaffold, such as the purine-scaffold series [17], that bind at the same site as GA but lack the target-unrelated liabilities. These molecules have undergone considerable modification and one compound, PU-H71, shows potential in the clinic [18], [19]. Several additional N-terminal Hsp90 inhibitors have been identified in high throughput screens, including the pyrazole, isoxazole and triazole resorcinol classes such as VER-50589, NVP-AUY922 and STA-9090 (ganetespib), respectively [20], [21]. NVP-AUY922 is progressing through Phase I/II clinical trials while STA-9090 has advanced to Phase III [22], [23]. An additional class of compound, the Serenex series, also progressed to phase I/II clinical trials (reviewed in [22]). In this paper we report the efficacy of five inhibitors, representing four different classes of compound, on adult Brugia in vitro and compare the results with those from screens based on Mf viability and a fluorescence polarization assay. We focus on the most active compound, NVP-AUY922, and describe its in vitro effects on three life cycle stages of Brugia and its efficacy against adult worms in vivo.
All animal protocols were carried out in accordance with the guidelines of the UK Home Office, under the Animal (Scientific Procedures) Act 1986, following approval by the University of Glasgow Ethical Review Panel. Experiments were performed under the authority of the UK Home Office, project numbers 60/4448 and 60/3792. The Brugia pahangi life cycle was maintained by serial passage through mosquitoes (Aedes aegypti, Refm) and jirds, Meriones unguiculatus, as described previously [24]. Adult worms of B. pahangi were obtained from infected jirds after 3–4 months, exactly as described previously [11] and were frozen in liquid nitrogen, ground in a pestle and mortar to a fine powder and re-suspended in an appropriate volume of HFB assay buffer (20 mM HEPES, pH 7. 3,50 mM KCl, 5 mM MgCl2,20 mM Na2MoO4,1% NP40). Protein concentrations were estimated using the BioRad protein assay. At this point lysates were freeze-dried for shipping to the USA. The FP assay was set up essentially as described previously [12], [25]. In brief, assays were performed in black 96-well half-volume non-binding microtiter plates (Corning #3686) in a total volume of 50 µl per well. Assay buffer (HFB2) contained 20 mM HEPES, pH 7. 3,50 mM KCl, 2 mM EDTA, 0. 01% Triton-X100,0. 1 mg/ml bovine gamma globulin (Sigma #G5009, Saint Louis, MO), 2 mM DTT (Sigma, Saint Louis, MO) and protease inhibitor cocktail (Roche #11836170, Indianapolis, IN). The equilibrium binding of Cy3B-GA and recombinant human Hsp90α (Enzo Life Sciences, Farmingdale, NY USA) or parasite lysate was determined by creating a two-fold dilution series of protein/extract for an eleven-point curve with the first column containing no protein. The dilution series was incubated with 6 nM Cy3B-GA in triplicate at 4°C with gentle shaking for different periods of time and FP measurements taken on a Safire2 plate reader (Tecan, San Jose, CA) with excitation and emission wavelengths of 530 nm and 585 nm, respectively, and a bandwidth of 20 nm. All FP values are expressed in millipolarization (mP) units with the mP value of free Cy3B-GA probe set to 50. Equilibrium binding constants were determined by nonlinear regression using a one-site binding model (GraphPad Prism software). The relative binding affinities of inhibitors to human or parasite-derived Hsp90 was determined using competitive FP binding assays. Human Hsp90 was used at a concentration resulting in 50% maximal binding of 6 nM Cy3B-GA (2. 4 nM for human Hsp90α). For parasite-derived Hsp90, an amount of parasite lysate resulting in 50% of maximal Cy3B-GA binding was used. The drugs tested in the FP assay were GA and 17-AAG, CCTC018159, VER-49009, VER-50589, NBP-AUY922, NVP-BEP800, CAY 10607, BIIB021, PU-H71, SNX-2112, SNX-9203 and HSP990. Stock solutions of each compound were prepared in DMSO at a concentration of 10 mM and 3-fold serial dilutions prepared in DMSO for eleven point curves. Drugs were then diluted 100-fold into HFB2 assay buffer containing 12 nM Cy3B-GA in 96-well storage plates to create 2X drug solutions. Drug solutions (25 µl/well) were then transferred in duplicate to 96-well black assay plates (Corning#3686) containing 25 µl HFB2 with 2X the final desired concentration of Hsp90. The final concentration of Cy3B-GA was 6 nM and the final DMSO concentration in all wells was 0. 5%. Free Cy3B-GA (mP set to 50) and buffer only (background) wells were included as controls on each plate. Plates were incubated at 8°C with gentle shaking for 20 h. FP measurements were taken and the inhibitor concentration at which 50% of bound Cy3b-GA was displaced (IC50) was determined using nonlinear regression with a four parameter logistic equation (GraphPad Prism software). The five new compounds selected for in vitro testing on B. pahangi were NVP-AUY922, NVP-BEP800, SNX-2112, SNX-9203 and BIIB021. GA was used as a positive control in some experiments. All compounds were supplied by Selleck Chemicals (www. selleckchem. com), with the exception of GA, which was supplied by MBL International Corporation (Woburn, MA). Drugs were dissolved in DMSO to give a stock solution of 10 mM, then aliquoted and stored at −20°C. Working concentrations of drugs were prepared on the day of use by dilution in tissue culture medium. For in vivo studies, NVP-AUY922 was purchased from LC Laboratories (www. LCLabs. com) and dissolved in DMSO at 50 mg/ml. As adult Brugia worms are limited in numbers, initial experiments assessed the effect of each drug on Mf viability. Mf were purified from infected animals essentially as described previously [26]. In brief, following lavage of the peritoneal cavity of an infected animal with Hanks Balanced Salt Solution (HBSS) pre-warmed to 37°C, Mf were collected by centrifugation and then purified from host cells by centrifugation through lymphoprep (Sigma). This procedure was repeated twice. Mf were collected from the pellet, washed twice in HBSS and once in worm culture medium (WCM) which comprised RPMI 1640, (Invitrogen Cat No: 52400), containing 5% heat inactivated fetal calf serum, 1% glucose, 100 units/ml penicillin and 100 µg/ml streptomycin (all Invitrogen). Mf were then dispensed into the wells of a 24-well plate to give approximately 200 Mf in 2. 0 ml, using a single well for each drug concentration. All procedures were carried out using aseptic techniques. The five novel compounds, plus GA and medium alone controls, were tested three times against Mf over the full range of concentrations. For adult worm assays, adult female B. pahangi, 3–4 months old, were incubated individually in 2. 0 ml of WCM overnight in 24-well plates and pre-screened for Mf production. Any worms that failed to produce Mf overnight were discarded. For the drug experiments, six female worms of B. pahangi for each concentration of drug were cultured individually in 24-well plates in 2. 0 ml of WCM containing drug, or carrier alone (DMSO) at a concentration equal to that in the highest concentration of drug. In some experiments, GA was used as a positive control. Initially, all five compounds were tested over selected concentrations starting at 2 µM to 100 nM (see Results for details). For Hsp90 inhibitors, Mf output by individual female worms is a sensitive indicator of adult worm viability and, in most experiments, was assessed at 72 h. In addition, adult worms were examined microscopically on a daily basis for 7–10 days to determine whether lower concentrations of drugs had any effects over a longer period of incubation. Results are expressed as mean Mf output ± SD over a 72 h period. Statistical significance between groups was calculated using the Mann Whitney test with P values<0. 05 being considered significant. In two additional experiments, adult worms were exposed to a short 24 h incubation in 250,25 or 10 nM NVP-AUY922 or DMSO in medium alone, using six worms per concentration as described above. After 24 h in drug, adult worms were removed, washed out of drug and incubated in medium alone. Mf output was counted after 24 h in drug and again after 24 h or 48 h in medium alone. Plates were maintained for up to 10 days and the condition of adult parasites noted at regular intervals. In one experiment the effect of GA on Mf output by adult B. malayi worms was compared with B. pahangi. B. malayi worms were kindly provided by Prof. R. Maizels (University of Edinburgh). In this experiment, Mf were counted after 48 h of culture in GA at 2. 0 µM and 1. 0 µM GA. In all in vitro experiments, plates were viewed daily and the motility and condition of the parasites noted by two independent observers, of whom one was unaware of the contents of the well. L3 stages were harvested from mosquitoes nine days post-infection. L3 were picked individually with a fine glass pipette, counted and washed three times in HBSS containing 1000 units/ml of penicillin and 1000 µg/ml streptomycin by sedimentation at room temperature. 20–30 L3 per well were plated out in duplicate in 24-well plates in 2. 0 ml of WCM containing drug, or carrier alone (DMSO) and cultured at 37°C for up to 7 days. NVP-AUY922 was tested at a range of concentrations: 500,250,100,50,25,10,5. 0,1. 0,0. 5 and 0. 1 nM. This experiment was repeated twice. Adult worms were removed from the peritoneal cavity of infected jirds and rinsed in HBSS. 10 adult female worms were transplanted into the peritoneal cavity of each of ten male BALB/c mouse using standard methods [27], [28]. Adult worms were transferred into the peritoneal cavity of anaesthetized mice using a blunted glass hook. Not all mice received the full quota of 10 worms (see Table 1). The stock solution of drug was diluted to 5 mg/ml in sterile PBS containing Tween 20, to a final concentration 5%, and DMSO to a final concentration of 10%, as detailed previously [29]. Five mice were treated with 50 mg/Kg NVP-AUY922 and five with sterile PBS/Tween 20/DMSO by intra-peritoneal injection at three time points: day 0 (7 days post-transplantation), day 3 and day 7. This dose was selected on the basis of previous studies in a mouse xenograft model [29]. Adult worms and Mf were recovered 9 days after the last dose of drug by peritoneal lavage with pre-warmed HBSS. The condition of any adult worms recovered was noted. Mf in the first 12 ml of peritoneal washings were pelleted by centrifugation and fixed in 2% formalin in water and stored at 4°C until counted. Mice were weighed at each time point to monitor any possible weight loss.
Several classes of inhibitor were screened against B. pahangi or B. malayi lysates, as well as human Hsp90α, using the FP assay originally developed as a high throughput screen for Hsp90 inhibitors in tumor cells, as previously applied to Brugia [12]. This assay is based on the ability of small molecules to inhibit the binding of Cy3B labeled GA to Hsp90. Table 2 shows the range of IC50 values for the binding of selected compounds to B. pahangi, B. malayi or human Hsp90α. In general, most compounds bound to parasite-derived and human Hsp90 with broadly similar affinities. Several compounds bound worm Hsp90 with high affinity, including NVP-AUY922 and VER-50589, each of which bound Brugia Hsp90 at low nanomolar concentrations (IC50 1–2 nM). A second group of compounds including GA, PU-H71, SNX-2112, SNX-9203, BIIB021 and VER-49009 bound Brugia Hsp90 with an IC50 in the range of 10–20 nM. Most drugs bound to Hsp90 from both species of Brugia with broadly similar affinity; CAY10607 was an exception in this respect, showing a 10-fold higher affinity for B. pahangi Hsp90 compared to B. malayi Hsp90. We initially compared the efficacy of Hsp90 inhibitors against Mf as this life cycle stage is extremely abundant, while the numbers of adult worms are more restricted. In these experiments six drugs, representing five different chemotypes were selected including NVP-AUY922, NVP-BEP800, SNX-2112, SNX-9203, BIIB021 and GA (see Fig. 1 for drug structures), were tested over ten doubling dilutions from 4. 0 µM to 0. 976 nM and compared with the DMSO vehicle. The results of these experiments were clear-cut: NVP-AUY922 was by far the most effective compound tested, killing 100% of Mf by day 7 at all concentrations down to and including 1. 95 nM. At the lowest concentration of NVP-AUY922 tested (0. 976 nM), ∼75% of the Mf were dead after 7 days incubation. In contrast, a concentration of 500 nM NVP-BEP800 was required to kill the majority of Mf by day 7, with ∼50% death at 250 nM. Lower concentrations of NVP-BEP800 affected Mf motility but did not kill substantial numbers of worms. For the SNX compounds, SNX-2112 killed approximately 50% of Mf at 500 nM by day 7, while at 250 nM, Mf were very sluggish but still alive. SNX-9203 was slightly more effective at lower concentrations, killing ∼90% of Mf at 500 nM after 7 days exposure, while at 250 nM most worms were alive but were much less motile than controls. Finally, BIIB021 was active only at 4. 0 µM, while lower concentrations affected worm motility but did not kill the worms within a 7-day period. In comparison, GA killed ∼90% of the Mf at 31. 25 nM, while at 15. 6 nM ∼50% of the Mf died, similar to the effective dose reported previously [11]. Thus, NVP-AUY922 was the most efficient inhibitor of Hsp90 as judged by Mf killing followed by GA, while BIIB021 was the least effective and the SNX compounds and NVP-BEP800 had broadly similar effects on Mf viability (see Table 3 for summary). We have previously described a sensitive assay to record the effect of GA and the purine scaffold inhibitors on adult worm viability that involves counting Mf output over a designated time of exposure to inhibitor [11], [12]. In initial experiments, all five new compounds were screened against adult female worms at concentrations ranging from 2. 0 µM to 100 nM and Mf output and adult worm viability monitored over a 7-day period (data not shown). Three of the five compounds tested (NVP-AUY922, NVP-BEP800 and SNX-9203) had a significant effect on Mf output at all doses tested including 100 nM, while SNX-2112 was significant only at 500 nM and BIIB021 at 2. 0 µM. In additional experiments, NVP-BEP800 and the SNX compounds were further titrated from 500 nM to 1. 0 nM to estimate the minimal effective concentration. For all three drugs a concentration of 500 nM was required to consistently show a significant effect on Mf output by adult worms in replicate experiments. Further experiments dealt only with the most effective compound NVP-AUY922, which was titrated over a range of concentrations from 500 nM to 1. 0 nM. Following 72 h of exposure to all concentrations from 500 nM to 10 nM NVP-AUY922, a significant inhibitory effect on Mf output was observed (P = 0. 0087 for 10 nM vs DMSO, see Fig. 2). Continuing the cultures for a further three days in the presence of drug resulted in a significant decrease in Mf output at 5. 0 nM (P = 0. 0043) but not at 1. 0 nM. By 6 days of exposure all adult worms were dead at concentrations of 100 nM NVP-AUY922 and above, and, in a typical experiment (shown in Fig. 2), 4/6 worms were dead at 50 nM drug and 3/6 were dead at 25 nM drug. The remaining worms although alive, were extremely sluggish. Although the motility of the adult worms was affected by exposure to lower concentrations of NVP-AUY922 (10 and 5. 0 nM), they did not die at these concentrations. Worms that were dying tended to burst and release their uterine contents and wells contained many embryonic stages in addition to Mf. Confirmation that NVP-AUY922 has a direct macrofilaricidal effect was obtained by exposing male worms to a range of concentrations from 5. 0 µM to 100 nM. By day 7 of exposure 100% of male worms exposed to 100 nM drug were dead. While for human filarial parasites, drugs that target adult worms are the priority, it was of interest to determine whether NVP-AUY922 also killed the infective form of the parasite, the L3. In these experiments, L3 were harvested directly from mosquitoes, washed and exposed to varying concentrations of NVP-AUY922 from 500 nM to 0. 1 nM in WCM. After 6 days exposure to drug, 100% of L3 were dead at all concentration down to and including 10 nM. At 5. 0 nM approximately 30% of parasites were dead and the remainder were moving very slowly. At this time point there was no significant mortality in control wells and, at concentrations of 1 nM or below, no effect on the L3 was observed. Thus NVP-AUY922 is toxic to L3 stages at relatively low concentrations. In the experiments described above, adult worms or Mf were continuously exposed to drug and viability assessed. However, as any drug that might be used against filarial worms in vivo would be required to exert its effect over a limited period of time, we carried out two additional experiments to determine the outcome of exposing adult female worms to NVP-AUY922 for a 24 h period only. In these experiments six adult female worms per group were cultured individually with 250,25 or 10 nM NVP-AUY922 or the appropriate concentration of DMSO alone for 24 h. Worms were then washed free of drug and cultured in medium alone for a further 7–9 days. After 24 h in drug, significantly fewer Mf were produced at 250 nM and at 25 nM NVP-AUY922 (P = 0. 0043 for both concentrations) but no significant difference was observed in Mf output in worms incubated with 10 nM drug. After 24 h in drug and 24 h in medium alone, Mf production was almost completely inhibited from worms cultured in 250 nM drug (mean of 11±23 Mf) or 25 nM drug (mean of 100±60 Mf) compared to DMSO controls (1658±198, P<0. 05 for both 250 nm and 25 nM drug). Although worms exposed to 10 nM drug for 24 h produced fewer Mf (mean 910±674 Mf) than DMSO controls this difference failed to reach significance (P = 0. 0635). However following 24 h in drug and 48 h in medium alone, adult worms exposed to 10 nM NVP-AUY922 for 24 h produced significantly fewer Mf than control worms (P = 0. 0317) (see Fig. 3). Adult worms were clearly affected by a short-term exposure to 250 nM NVP-AUY922, being much less motile than control worms after 24 h in medium alone. By 48 h they were elongate and by 9 days in medium alone, they were barely moving, but they were still alive. Worms exposed to 25 nM NVP-AUY922 were also noticeably more sluggish than control worms at day 9, while no obvious difference was observed between those incubated in 10 nM drug and DMSO controls. The experiment was discontinued at this point. Most of our experiments have been carried out using B. pahangi, a close relative of the human parasite, B. malayi. We compared the efficacy of GA at two concentrations (1. 0 and 2. 0 µM) on B. malayi in parallel experiments with B. pahangi. Not surprisingly, given the degree of amino acid identity between Hsp90 in the two species (93. 5% identical), both were equally sensitive to Hsp90 inhibition. In this experiment, the reduction in Mf output at any one concentration of drug was almost identical: at 2. 0 µM GA, there was a 93% reduction in Mf output in B. malayi and 92% with B. pahangi while at 1. 0 µM, there was a 74% reduction in Mf output with B. malayi and a 78% reduction with B. pahangi after 48 h of drug exposure (P = 0. 0043 for all concentrations of GA versus DMSO control). As NVP-AUY922 appeared to be extremely active at low concentrations after a short exposure in vitro, it was pertinent to determine whether it would have activity in vivo against adult worms transplanted into the peritoneal cavity of BALB/c mice. Three animals in the treated group were given 10 adult worms, while the remaining two mice received 9 worms, while in the control group, one animal received 9 worms, one received 8 worms and the remaining three mice received 10 worms. Following adult worm transplant, mice were randomly assigned to a treatment group (five per group) and received either 50 mg/Kg NVP-AUY922 at three time points by intra-peritoneal injection or an injection of PBS/Tween 20/DMSO. Mice were weighed at each treatment and prior to recovery of adult worms, but no weight loss was observed in drug-treated animals over the time course of the experiment. Adult worms were recovered 9 days after the last injection of drug, at which point there was a significant reduction in worm recovery from treated mice compared to control animals (P = 0. 0109) (see Table 1). All control animals contained live, motile adult worms with recoveries varying from 30–78% of transplanted worms (see Table 1 for details). In contrast, very few live worms were recovered from NVP-AUY922 treated mice (recovery of live worms ranged from 0–11%, Table 1). Adult parasites recovered from all animals were placed in HBSS at 37°C for 2–3 hours and examined again. There was no evidence to suggest that the adult worms recovered from drug-treated animals regained their motility over this time period. In three out of five treated animals, only a few dead Mf were observed in the peritoneal washings, while the remaining two animals contained low numbers of Mf that were very slow moving (P = 0. 0079, NVP-AUY922 versus control).
In this paper we extend our observations on the effect of Hsp90 inhibitors on adult Brugia worms in vitro and in vivo. A panel of commercially available Hsp90 inhibitors, all designed and optimized for binding to human Hsp90, was profiled in FP binding assays. The broadly similar binding affinities between human and parasite proteins highlight the evolutionarily conserved structure of the nucleotide-binding domain that is targeted by these inhibitors. Selectivity towards parasite Hsp90 would obviously be preferable, but this endeavor would require a structure-based design effort, as recently described for trypanosome Hsp83 (Hsp90) [30]. In the spirit of exploring the potential for a direct repurposing strategy, the translation from parasite Hsp90 binding to filaricidal activity was examined. Five clinically viable compounds belonging to four different drug classes were tested in vitro for their ability to kill Mf and inhibit Mf output from adult female worms. The results from all three systems were reasonably consistent and highlight the efficacy of one specific inhibitor, NVP-AUY922. This compound showed significant activity against adult female worms at a concentration of 25 nM after 6 days exposure, significantly inhibiting Mf output and killing 50% of adult worms. Although lower concentrations of NVP-AUY922 (down to 5. 0 nM) showed a significant effect on Mf output, adult worms were not killed at this concentration over the time scale of the experiment. NVP-AUY922 showed a high affinity for Brugia Hsp90 in the FP screen, further validating the application of this assay as a high throughput screen. It was also the most active compound tested in the Mf killing assay. As a single infected animal can produce millions of Mf, these results indicate that using Mf could provide a simple, inexpensive and relatively high throughput pre-screen for compounds with macrofilaricidal activity, while acknowledging that not all compounds that effect Mf will also kill adult worms. The translation from Brugia Hsp90 binding to micro- and macro-filaricidal activity depends upon the chemotype being tested and this is evident in the compounds used here. While NVP-AUY922 bound Brugia Hsp90 at ∼1 nM and had an EC50 against Mf viability in the same range, the other compounds exhibited variable translation between the two assays. For example, NVP-BEP800 bound quite well to Brugia Hsp90 (∼7 nM IC50) but required much higher concentrations to kill microfilaria (∼250 nM EC50) during an extended 7-day incubation. There are many possible explanations for this discrepancy, including failure of the compound to fully equilibrate within the microfilariae during the experiment. It is possible that this particular compound does not penetrate well or is actively exported from the parasites. As more detailed studies would be required to address this issue, we continued to focus on compounds with the best activity against live parasites. We assessed the effect of these inhibitors on adult female worms by quantifying Mf output, as a measure of worm viability. Mf output is an active process in filarial worms and relies on the presence of live Mf in utero and on the activity of the vulva, a muscular opening close to the anterior end of the worm. When Hsp90 is inhibited, cessation of Mf output is a sensitive surrogate measure of adult female worm health and appears to be one of the first signs that worm viability is compromised. Once Mf production ceases following exposure to Hsp90 inhibitors, it does not resume, at least over the time scale of our in vitro experiments. In addition, previous studies [11] demonstrated that embryogenesis in adult B. pahangi was disrupted upon inhibition of Hsp90 with GA. When RNAi was used to knockdown hsp90 (daf-21) in the free-living nematode Caenorhabditis elegans, one of the most penetrant phenotypes observed was a protruding vulva and sterility in the F1 generation [31]. In C. elegans, the vulva is a complex structure, the development of which is dependent upon a number of signaling pathways (reviewed in [32]). The vulva is innervated by neurons and egg-laying in C. elegans (the equivalent of Mf release in filarial worms) is regulated by multiple factors and molecules, including neuropeptides, kinases and members of the TGF-β signaling pathway [33]. Much less is known of the factors that regulate Mf production in filarial nematodes, but the vulva may be particularly sensitive to Hsp90 inhibitors, perhaps acting on various kinases required for signaling in this structure. Alternatively, the rapid inhibition of Mf output observed (within 24 h at high concentrations of inhibitor) may reflect a general demise in adult female worms upon inhibition of Hsp90. In the related filarial nematode O. volvulus, ivermectin is reported to inhibit Mf output, while not killing the adult worm. In cattle infected with O. ochengi, embryogenesis is disrupted by treatment with ivermectin and an accumulation of dead and dying Mf are observed [34], similar to that described for female Brugia exposed to GA [11]. However, the results of the present study show that inhibition of Hsp90 by NVP-AUY922 not only affects Mf release but also directly affects the viability of adult worms. This property was clearly demonstrated following in vitro exposure of both male and female adults to the inhibitor and in vivo administration of the inhibitor to mice following transplant of female worms. Hsp90 functions in a complex with other proteins to fold and/or stabilize a wide variety of client proteins, most of which have been identified from mammalian cells or yeast. A list of Hsp90 client proteins is curated by the Picard Lab (http: //www. picard. ch). However, we know little about the key client proteins clients in Brugia, except by homology with known interacting proteins identified from other systems. A better understanding of the Hsp90 interactome in Brugia may help explain the effects observed upon chemical inhibition of Hsp90. As all our previous studies have focused on B. pahangi, we also tested B. malayi in this study and showed that GA had very similar effects upon both species. Similar data was recently published [35] showing that GA and four derivatives of GA, were active in vitro on adult B. malayi and the trematode parasite Schistosoma japonicum. In that study, the lowest concentration tested was 500 nM, but encouragingly all compounds were active against adult B. malayi at this concentration. Interestingly, NVP-AUY922 also showed potent activity against the L3 stage of B. pahangi. While drugs that target the L3 stage of filarial nematodes are not the highest priority for human use, they are of significant interest in the veterinary field, where prophylaxis of the dog heartworm, Dirofilaria immitis, is a major area of concern in veterinary practice. Here, the macrocyclic lactones, such as ivermectin and moxidectin, have been the mainstay of control for many years. Given the recent observation on treatment failures with ivermectin in some dogs in the Southern states of the USA [36], there is a clear need for the development of novel compounds to protect susceptible animals. As a preliminary to in vivo testing, we investigated whether a short exposure to the most effective compound identified, NVP-AUY922, affected adult worm viability in vitro. These experiments showed that Mf output was significantly reduced following a 24 h exposure to all concentrations of drug including 10 nM (the lowest concentration tested in this study), although it required an additional 48 h incubation in medium alone to detect this effect. However, although Mf output was significantly different between drug exposed and control worms, a direct effect was observed at 250 nM concentration after a 24 h exposure, with adult female worms being almost motionless after 9 days in culture. While a 24 h exposure to 25 nM NVP-AUY922 resulted in a significant decrease in motility, the adult female worms were still alive at day 9. Whether such motility-impaired worms would be viable in vivo in an immuno-competent host is doubtful. These data also highlight one of the characteristics of Hsp90 inhibitors: the time taken to kill adult worms. They do not kill rapidly, which may be a useful attribute for in vivo use, as some of the pathogenesis of lymphatic filariasis is associated with death of the adult worms, and the subsequent release of antigen and the Wolbachia endosymbiont [37]. NVP-AUY922 belongs to the isoxazole resorcinol class of Hsp90 inhibitors and has shown some promise as an anti-tumor agent in a mouse xenograft tumor model [29], [38]. In the first of these studies, pharmacokinetic analysis showed that the plasma levels of drug reached a maximum of 52,506 nM at 0. 25 h post-dosing following a single dose of 50 mg/Kg delivered by the intra-peritoneal route. As a 24 h exposure to 250 nM NVP-AUY922 had a significant deleterious effect on adult female worms, we were encouraged to test this compound in vivo, using an adoptive transplant system in which viable adult worms are transplanted into the peritoneal cavity of mice [27], [28]. In previous experiments with NVP-AUY922 administered in a similar dosing regimen to nude mice containing xeno-grafted tumors, weight loss was observed [38]. However our immune-competent animals showed no loss in weight or other obvious deleterious effects over the time scale of the experiment. Adult worms were recovered nine days after the last dose of drug, as the in vitro data indicated that it might take some time for the drug to act. Additionally, previous studies with suramin, one of the few compounds with activity against adult filarial worms, demonstrated that it took approximately 6 weeks to reduce adult worm recovery in the jird model [39]. A total of eight out of 48 transplanted female worms were recovered from drug treated animals, but of these only two were healthy with the others being coated in cells, indicating that they were in the process of being cleared by the immune system. In contrast, 26 female worms out xof 47 transplanted were recovered from animal treated with vehicle alone. Moreover, only two of the drug-treated mice contained live Mf, and these appeared very sluggish compared to controls. Further studies will be required to examine alternative routes of drug administration and to explore in more detail the mechanism by which these inhibitors exert their macrofilaricidal effect. The clinically viable Hsp90 inhibitors tested here are targeted and potent towards human Hsp90 and thus may have unwanted side effects. In this respect, the therapeutic potential of any of these inhibitors for filarial disease will depend on the pharmacodynamic differences between host toxicities and parasite killing. There are pharmacokinetic data in both animals and humans available for many of the Hsp90 inhibitors. We have used this data in combination with in vitro worm killing assays to predict the doses of NVP-AUY922 that would be successful in killing parasites in vivo. While efficacy in cancer treatment likely requires chronic dosing of near maximum tolerated doses, the treatment of parasitic diseases would ideally necessitate a short course of treatment. It is not currently clear whether a short treatment course with current inhibitors would be able to clear parasites, while maintaining appropriate safety margins. Additional studies will be required to carefully delineate the therapeutic window of short treatment courses. As noted earlier, the development of parasite-selective inhibitors with reduced potential for host toxicity would be of enormous benefit and should also be pursued. The ubiquitous nature of Hsp90 in normal as well as transformed cells, has led some to question the potential of this molecule as a drug target. However, for the past 20 years, the National Cancer Institute has advocated Hsp90 as a drug target, since GA was first shown to exhibit anti-tumor properties. There are currently seventeen Hsp90 inhibitors in clinical trials and a growing arsenal of novel Hsp90 inhibitors, of structurally diverse scaffold (reviewed in [40]). Current emphasis is on combination therapies in which Hsp90 inhibitors are combined with other anti-tumor drugs [41]. Whether a similar approach would further enhance the activity of these inhibitors against adult filarial parasites remains to be determined. However, we believe that these studies provide data to further strengthen the contention that inhibition of Hsp90 is a valid target for the chemotherapy of lymphatic filariasis, while acknowledging that a significant medicinal chemistry effort would be required to optimize the activity of these inhibitors. | Adult filarial worms are long-lived nematode parasites that have proved very difficult to kill with existing drugs. Current campaigns for the control or elimination of these parasites are largely based on treatment with drugs such as diethylcarbamazine or ivermectin, that preferentially kill the first stage larvae of the parasite, the microfilariae. As microfilariae repopulate the body from unaffected adult worms, repeated dosing with these drugs is required over the long reproductive life span of the worm. The availability of compounds with macrofilaricidal activity would help facilitate the goal of controlling filarial infections. Hsp90 is a recognized target in tumor cells: consequently many oncology programs have developed small molecule inhibitors of Hsp90, several of which are commercially available. Here we provide proof of principle that inhibition of Hsp90 is lethal to adult Brugia worms in vivo, as well as in vitro, suggesting that these compounds may have potential for further development as macrofilaricidal drugs. | Abstract
Introduction
Methods
Results
Discussion | oncology
medicine
chemotherapy and drug treatment
cancer treatment
biology
microbiology
parasitology | 2014 | A Repurposing Strategy for Hsp90 Inhibitors Demonstrates Their Potency against Filarial Nematodes | 10,291 | 251 |
Spikelets are small spike-like depolarizations that can be measured in somatic intracellular recordings. Their origin in pyramidal neurons remains controversial. To explain spikelet generation, we propose a novel single-cell mechanism: somato-dendritic input generates action potentials at the axon initial segment that may fail to activate the soma and manifest as somatic spikelets. Using mathematical analysis and numerical simulations of compartmental neuron models, we identified four key factors controlling spikelet generation: (1) difference in firing threshold, (2) impedance mismatch, and (3) electrotonic separation between the soma and the axon initial segment, as well as (4) input amplitude. Because spikelets involve forward propagation of action potentials along the axon while they avoid full depolarization of the somato-dendritic compartments, we conjecture that this mode of operation saves energy and regulates dendritic plasticity while still allowing for a read-out of results of neuronal computations.
Brain functions rely on computations in single neurons, but some basic features of neural processing still remain unclear. Here, we focus on spikelets, which are brief, spike-like depolarizations of small amplitude (< 20 mV). Spikelets can be measured in somatic intracellular recordings in diverse neuron types, including cortical interneurons (e. g. , [1]) and pyramidal cells [2–4]. Due to their all-or-none appearance and spike-like shape, spikelets are considered to reflect action potentials (APs) occurring in electrotonically distinct compartments. These APs might originate either in the dendrites or in the axon of the same cell, or in another neuron that is either coupled ephaptically or through gap junctions. Since spikelets influence somatic voltage dynamics, including AP generation [2], identifying the origin of spikelets is important for understanding neural computations. The origin of spikelets in hippocampal [2,3, 5] and neocortical [4] pyramidal neurons is not well understood. The original hypothesis of spikelets resulting from dendritic spikes [6] could not be supported by subsequent studies [7]. Instead, axo-axonal [8,9] and somato-dendritic [10,11] gap-junction coupling of pyramidal neurons has been suggested as the spikelet origin, however, the supporting experimental evidence is scarce, raising the question whether there are other mechanisms for generating spikelets in pyramidal neurons. In vitro, somatic spikelets can be evoked with distal axonal stimulation if an antidromically propagating AP [12] does not suffice to activate the somatic sodium channels. This can happen because of somatic hyperpolarization, (prolonged) somatic depolarization, or fast repeated axonal stimulation [13–16]. However, in-vivo inputs are usually considered to arrive at the soma orthodromically. Indeed, spontaneous antidromic spikelets (also called “ectopic”) have been identified mainly under pathological conditions, such as epilepsy [17]. Additionally, antidromic spikelets are expected to occur when neurons would be coupled through axo-axonal gap junctions [8]. Here, we present a novel hypothesis for the origin of spikelets in pyramidal neurons. Using a computational approach, we demonstrate that spikelets can be evoked orthodromically with somato-dendritic inputs, which initiate APs at the distal axon initial segment (AIS). Under certain conditions, these APs in the AIS fail to fully activate the soma and appear there as spikelets. Consequently, the possibility of a forward propagating AP without it propagating back to the soma and into the dendrites presents a powerful mechanism for control of dendritic plasticity while ensuring the read-out of neural computations.
To investigate mechanisms underlying spikelet occurrence, we first used a previously published multi-compartmental model of a reconstructed layer V pyramidal neuron ([16]; Fig 1A). This model includes a detailed sodium channel distribution at the AIS and a hyperpolarized voltage shift of 13 mV in the activation and inactivation functions of the low-threshold NaV1. 6 channels, present in the AIS and axon. To increase the incidence of spikelets, we modestly reduced the density of sodium channels (see Methods for details). The model cell was stimulated at the soma with stochastic excitatory and inhibitory synaptic point conductances [18] representing in vivo-like background activity. The resulting somatic voltage traces (Fig 1B, top) showed both APs and spikelets (stars). All APs were shoulder-APs (sh-APs; [2]) characterized by two components in the rising phase. The first component (the shoulder) was slower and resembled the waveform of spikelets (Fig 1C); the second, faster component included the peak of the AP. To reveal the origin of spikelets and sh-APs in our model, we compared voltage traces in the soma and the AIS (Fig 1B). The APs and spikelets recorded at the soma were initiated as full APs at the distal AIS (Fig 1D). Accordingly, both the shoulders of the sh-APs and the spikelets reflected axonal APs invading the soma [14,19]. Next, we aligned APs to the times of crossing a voltage threshold in the soma, and spikelets to the times of crossing the same voltage threshold in the AIS (Fig 1E, see also Methods). This alignment revealed a variable delay between the shoulder and the peak of the AP (Fig 1E, left) and demonstrated the all-or-none nature of the spikelet waveform (Fig 1E and 1F), as observed experimentally (Fig 1G; [2]). To understand why APs initiated at the AIS sometimes failed to elicit a somatic AP, we calculated both AP-triggered and spikelet-triggered averages of the synaptic input (Fig 1H). Excitation slowly increased ca. 5 ms before the onset of both APs and spikelets but dropped sharply prior to spikelet initiation; inhibition was stronger during spikelets compared to APs (Fig 1H2). Together, this input resulted in a weaker and briefer depolarizing synaptic drive for the initiation of spikelets compared to APs (Fig 1H3). We found that fast sodium channel inactivation, known to modulate spiking thresholds [20], was not a major factor influencing spikelet generation in our model (S1 Fig). Spikelets can thus be generated in a computational model of a single pyramidal neuron experiencing in vivo-like synaptic input: APs initiated at the AIS may fail to activate the soma and appear there as spikelets. Failure of AP propagation from the AIS to the soma (Fig 1) suggests that there is a strong voltage attenuation from axon to soma such that the somatic voltage does not reach the spiking threshold. To identify cell properties that could underlie such attenuation, we mathematically analyzed a passive-membrane model consisting of an axonal cable connected to a single somato-dendritic compartment (Fig 2A; see Methods for details). In particular, we computed the attenuation for sinusoidal input currents at several frequencies as a function of all model parameters (Fig 2B–2G; see Methods for equations). A central factor influencing signal attenuation is the electrotonic distance between the soma and the AIS. Attenuation thus increases with increasing physical distance (Fig 2B), increasing axial resistivity (Fig 2C), and decreasing axonal diameter (Fig 2D). Importantly, the attenuation is typically much larger in the antidromic (axon-to-soma) than in the orthodromic (soma-to-axon) direction because the large somato-dendritic compartment provides a substantially stronger current sink for the passively propagated signal than the thin axon, i. e. , there is a strong impedance mismatch between the two. Consistently, increasing the somato-dendritic surface area increased the attenuation of the antidromic signal whereas it did not affect the orthodromic propagation (Fig 2E). However, this did not reveal the nature of the current sink since the membrane resistance and the membrane capacitance are co-varied when changing the surface area. The specific membrane resistance, when varied separately in a range realistic for a pyramidal neuron (> 1 kΩ cm2), did not influence the antidromic attenuation for frequencies > 100 Hz (Fig 2F); in contrast, the antidromic attenuation of high-frequency (> 100 Hz) inputs was strongly influenced by the membrane capacitance (Fig 2G). For a fast, transient signal such as an AP, particularly the high-frequency components determine its shape. Indeed, in our model, the axon-to-soma attenuation of an AP waveform (black dashed lines in Fig 2B–2G) was very similar to the attenuation of a 300 Hz sine wave. Hence, apart from the electrotonic distance between soma and AIS, the capacitance of the somato-dendritic compartment strongly influences the attenuation of APs propagating from axon to soma. In general, the attenuation is asymmetric, i. e. , much larger in the axon-to-soma than in the soma-to-axon direction, which constitutes a favorable condition for spikelet generation. We next tested whether the asymmetric voltage attenuation is indeed a key component underlying the generation of spikelets through somato-dendritic input. For this, we turned to a model consisting of a dendrite, a soma, and an axon that all expressed active conductances (Fig 3A; see Methods for details). Similarly to the detailed compartmental model in Fig 1, the sodium channels at the distal AIS and in the axon were set to activate and inactivate at more hyperpolarized voltages than the sodium channels in the dendrite, the soma, and the proximal AIS [16,21]. However, the model in Fig 3 is much simpler than the complex model in Fig 1, which enabled us to explore its parameter space. To study the response of the model neuron with a simple stimulus, we applied rectangular current pulses (50 ms) to the soma for a range of input strengths. When an AP at the AIS was evoked, the corresponding somatic maximum response amplitude was recorded and plotted in a continuous color code (Fig 3B–3H). However, the somatic response amplitudes typically appeared in three well-separated clusters (examples in Fig 3B and S2 Fig B): (i) Spikelets (yellow) resulted from the weakest inputs that generated APs at the AIS but failed to evoke a somatic AP. (ii) The sh-APs (red) were evoked by larger somatic inputs and resulted from APs at the AIS that evoked a somatic AP. The shoulders of the sh-APs matched the spikelet waveform (see phase plots in Fig 3B, right). (iii) Finally, strong enough inputs could lead to full-blown APs (fb-APs; orange), which did not display a shoulder. The fb-APs resulted from AP initiation at the soma before or concurrent with AP initiation at the AIS. Consequently, fb-APs lacked the rapid onset (“kink”) typical for spikelets and sh-APs (Fig 3B, right) and the fb-AP amplitudes (from maximum curvature to maximum voltage) appeared smaller than the amplitudes of sh-APs because the maximum curvature occurred at higher voltages (Fig 3B, right). So similarly to the detailed model from Fig 1, input amplitude determined whether a spikelet or an AP was generated at the soma (see also S2 Fig): passive somatic depolarization from the input current added up to the somatic depolarization due to the AP propagated from the AIS, and if it reached the (fixed) somatic threshold, an AP was generated at the soma. Otherwise, a somatic spikelet appeared. To quantify how the somatic response type (spikelet, sh-AP, or fb-AP) depends on the somatic stimulus amplitude and the model parameters, we performed extensive numerical simulations of the active model with reduced morphology (Fig 3C–3H). These simulations indicated that the occurrence of spikelets required a certain degree of electrotonic separation between the soma and the AIS (Fig 3C and 3D) to allow for sufficient attenuation from axon to soma, as was suggested by the analytical results from the passive-membrane model (see Fig 2B–2D). Furthermore, spikelet generation needed a high enough somatic input capacitance (Fig 3E), in agreement with the analytical result that membrane capacitance was the primary current sink for APs propagating from AIS to soma (Fig 2F and 2G). Also as predicted, spikelet activity depended only weakly on the membrane resistance in a range that is plausible for pyramidal neurons (Fig 3F). Besides the passive membrane characteristics, also active properties of sodium channels were fundamental to the generation of somatic spikelets (Fig 3G and 3H). Lowering somato-dendritic sodium channel densities increased the somatic firing threshold and thereby promoted spikelet occurrence (Fig 3G). This result is in agreement with the reduced sodium channel densities boosting spikelet generation in the multi-compartment model in Fig 1. Another way to increase the firing-threshold difference between the soma and the AIS and thereby facilitate spikelet occurrence was to introduce a voltage shift in the activation function between the somato-dendritic and the axonal sodium channels (Fig 3H). The voltage shift had to be large enough such that an AP initiated at the AIS did not reach the voltage threshold in the soma. In summary, the simulation results of the active model with reduced morphology confirm that spikelets can be evoked through sufficiently small somatic input. In addition to strong and asymmetric voltage attenuation, the generation of spikelets requires a substantially lower AP threshold in the AIS compared to the soma. Spikelets of axonal origin can be evoked with distal axonal stimulation when the antidromically propagating AP does not suffice to cross the somatic spiking threshold. Such antidromic spikelets could also result from axo-axonic coupling by gap junctions [8]. Since the antidromic spikelets have different functional consequences than the orthodromic spikelets shown in Figs 1 and 3, it is important to be able to distinguish the two phenomena. To compare the properties of orthodromic and antidromic spikelets, the detailed model neuron with fluctuating somatic inputs from Fig 1 was additionally stimulated with brief current pulses to the distal axon (Fig 4A), which evoked axonal APs propagating antidromically towards the soma. The resulting spikelets were classified as antidromic (evoked with the distal axonal stimulus) and orthodromic (evoked with the somatic stimulus). Classification was based on the relative timing of the AP occurring at the distal AIS and in the axon (Fig 4B; see Methods). The two spikelet types were similar in shape and amplitude (Fig 4B and 4C), but the averaged antidromic spikelet displayed a more hyperpolarized somatic threshold and started abruptly from the baseline without a preceding depolarization (Fig 4C1), which is also typical for experimentally recorded antidromic APs [15]. For the antidromic spikelets in our computational model, the somatic excitatory and inhibitory conductances as well as the effective synaptic reversal potential did not show any modulation, which is in line with its distal axonal origin and its independence from somatic activity (Fig 4C2 and 4C3). Although the physiological occurrence of antidromic spikelets is disputed [22], we hypothesized that spikelets with similar properties can occur in pyramidal cells when the axon is attached to a dendrite instead of the soma [23]. To simulate this scenario, we adapted the morphology of the detailed model cell used in Figs 1 and 4 (Fig 5; see Methods), and excitatory postsynaptic conductances (EPSGs) were delivered to the axon-carrying dendrite, additionally to the somatic fluctuating inputs (Fig 5A). The resulting spikelets (Fig 5B) were classified according to the relative timing of the spikelet and the EPSG (see Methods). Both types of spikelets had comparable shapes and phase plots (Fig 5B). Spikelets evoked with stimuli to the axon-carrying dendrite exhibited a hyperpolarized average onset; nevertheless, some depolarization preceding these spikelets was visible in the somatic traces because the underlying input was located close enough to the soma (≈ 25 μm). However, spikelets evoked with stimuli to the axon-carrying dendrite were basically independent of somatic synaptic conductances (Fig 5C), and these spikelets are therefore reminiscent of the antidromic spikelets described in Fig 4. Alternatively, when the model presented in Fig 1 was additionally stimulated with brief current pulses at the proximal apical dendrite, the thresholds and waveforms of spikelets resulting from the dendritic stimulus were virtually identical to spikelets triggered by the fluctuating background stimulus applied to the soma (Fig 6). The average background conductances (Fig 6C2) and the effective synaptic drive (Fig 6C3) were less modulated for the dendritically evoked spikelets than for the spikelets evoked with the background stimulus. The number of dendritically evoked spikelets was substantially smaller than for inputs located at the distal axon or at the axon-attached dendrite because of an interplay between the dendritic and somatic stimulus in spikelet generation: The dendritic stimulus added to the background somatic input and triggered spikelets if the soma had the right level of depolarization. If the soma was too depolarized at the time point when the dendritic stimulus arrives, somatic APs were evoked; if the soma was too hyperpolarized, the compound input did not suffice to trigger an AP at the AIS. To summarize our results, spikelets can be generated within a single pyramidal neuron in three ways (Fig 7A, Sp1–Sp3). Each type of spikelet has characteristic features, which may allow to infer the origin of spikelets in experimental somatic voltage traces. Two key distinguishing features of spikelets are the somatic voltage threshold (Fig 7B) and the slope of the voltage a few milliseconds before the threshold is reached (Fig 7C). As a reference we consider the orthodromic APs, which exhibit the highest somatic firing threshold and are preceded by the steepest depolarization compared to the three types of spikelets: Orthodromic spikelets (Sp1) show a slightly smaller threshold and are preceded by a less steep depolarization, consistent with the finding that they required weaker inputs than APs. Antidromic spikelets (Sp2), which were evoked in our simulations with distal axonal stimulation, are characterized by the lowest thresholds and the highest somatic threshold variability. They arise abruptly at the soma: the averaged voltage trace shows no preceding depolarization. Finally, spikelets evoked by inputs to the axon-carrying dendrite (Sp3) lie somewhere in between the orthodromic and antidromic spikelets, regarding the average somatic threshold and the preceding depolarization; their orthodromic-like versus antidromic-like appearance depends on the electrotonic separation of the soma and the axon-carrying dendrite.
Action potentials are the basis of neural function, yet some of their fundamental features are still not well understood, as highlighted by the recent focus on the rapidness of the AP onset [19,24,25]. It is generally assumed that an AP initiated in the AIS of a pyramidal neuron always leads to an AP in the soma. We argue here that this view needs to be corrected. Under certain conditions, APs initiated in the AIS by somato-dendritic inputs fail to fully activate the soma and appear there as spikelets. In simulations we showed that spikelets can result from APs that were evoked at the AIS with somato-dendritic inputs and propagated down the axon, but that did not trigger a somato-dendritic AP. This AP failure occurred for a sufficiently large difference in spiking thresholds between the soma and the AIS, together with a strong impedance mismatch (causing asymmetric voltage attenuation) and some degree of electrotonic separation between the soma and the AIS. In this way, a weak depolarizing input could pass through the soma and initiate an AP at the AIS, which, in turn, was not able to depolarize the soma to the firing threshold. Thus, a spikelet appeared at the soma instead of an AP. This mechanism reproduced several key features of spikelets reported in the experimental literature [2,4, 5]: the fast dynamics and rapid onset of spikelets as well as the match between the spikelet waveform and the shoulder of a sh-AP. This single-cell mechanism is also in line with the observation that APs and spikelets recorded in a single hippocampal place cell exhibit virtually identical place fields [2]. In contrast, in the electrotonic-coupling (gap junction) scenario of pairs of pyramidal cells [8–10], the place fields of spikelets and APs measured in a single cell are expected to differ due to lack of topography in hippocampus [26]. We found that the fast dynamics and amplitudes of spikelets observed in pyramidal neurons can be compatible with gap junction coupling only if the somato-dendritic gap junctions are very strong and located at proximal sites (S3 Fig). In previous experimental studies, spikelets could be evoked with dendritic stimulation or dendritic EPSPs [4,6], which led the authors to conclude that somatic spikelets arise from dendritic spikes. However, our modelling results suggest that although spikelets can be evoked with somato-dendritic inputs, they rather originate in the axon. Depending on the state of the proximal axonal sodium channels, the AP is initiated either in the AIS, as we considered in this study, or further down the axon. Consistently, a recent experimental study demonstrated an axonal origin of spikelets occurring during dendritic plateau-driven complex spiking in CA1 pyramidal neurons [27]. Also in other central neurons, spikelets occurring during somatic bursts can originate in the axon, for example, in inferior olivary neurons [28] and in cerebellar Purkinje neurons [29]. Antidromic spikelets also result from axonal APs, but these are evoked by distal axonal inputs [30] or by APs propagating through putative axo-axonal gap junctions [8]. Compared to the orthodromic spikelets, antidromic spikelets are characterized by hyperpolarized thresholds and they arise abruptly without a preceding depolarization (Fig 4C1). However, the best experimental distinguishing criterion is the fact that, because of their distal origin, they survive moderate levels of somatic hyperpolarization, as has been demonstrated, for example, in layer V pyramidal neurons in vitro [16]. Orthodromic spikelets do not occur when the somatically injected hyperpolarizing current is larger than the synaptic driving current measured at the soma, since the synaptic depolarizing input has to pass through the soma to trigger an AP at the AIS. In contrast, antidromic spikelets can be evoked even when the synaptic driving current is somewhat smaller than the somatically injected hyperpolarizing current. Spikelets evoked by inputs to the axon-carrying dendrite (Fig 5) would also be abolished by a certain level of somatic hyperpolarization, because of the relatively small electrotonic distance between the soma and the axon origin [23]. Consistent with an orthodromic origin of spikelets is the experimental observation that spikelets are suppressed by hyperpolarizing somatic current injections, leading to the conclusion that spikelets “are not generated far from the soma” [4]. Our proposed spikelet hypothesis relies on AP initiation at the AIS. Indeed, APs in hippocampal [31] and neocortical pyramidal neurons [16,32] are typically initiated in the distal portion of the AIS, about 20 − 40 μm away from the axon hillock. This site is preferred for AP initiation because of its decreased capacitive load from the soma [33] and increased sodium channel density, especially of the NaV1. 6 channel subtype [34], which activates at more hyperpolarized membrane potentials than the somatic sodium channel subtype NaV1. 2 [21]. However, it is still disputed whether the axonal sodium channel density is substantially higher (up to 50-times higher, [35]) than the somatic sodium channel density or whether the axonal and somatic sodium channels have similar densities [21,36]. The model neuron used in Figs 1 and 4–6 is characterized by a high ratio between the axonal and somatic sodium channel densities (up to a factor 40, [16]), which contributes to the large threshold difference between the axon and the soma, thus favoring spikelet generation. The question then arises how spikelet generation is affected when the sodium channel density ratio is smaller. The model used in Fig 3 employed a much smaller density ratio of 5 between the soma and the distal AIS (0. 02 and 0. 1 S/cm2, respectively). Fig 3G illustrates that spikelets occurred when the somatic sodium channel density was less than half the value at the distal AIS (i. e. , < 0. 05 S/cm2). In vivo, a fraction of somatic sodium channels is inactivated due to ongoing activity, which decreases the effective sodium channel density and promotes spikelet occurrence. However, the range of density ratios that support spikelet generation is not absolute, but depends on other parameters influencing somatic voltage threshold, like the voltage shift between the activation of somatic and axonal sodium channels (Fig 3H). In the present study, we used the standard sodium channel models that were fitted to neocortical (Figs 1 and 4–6, [16]) and hippocampal (Fig 3, [37]) pyramidal neurons. However, the dynamics of these model channels is slow compared to what has been found in more recent experiments [38,39]. Interestingly, simulations by Fleidervish et al. demonstrated that the faster, more realistic, sodium channel activation generated larger axo-somatic delays and larger voltage gradients than the classic, slower, sodium channel models [36]. As this axo-somatic gradient is vital for spikelet generation, we expect faster Na-channel gating to support spikelet generation. Experimental recordings featuring spikelets typically contain two types of APs: shoulder-APs with an initial slower phase corresponding to the spikelet, and full-blown APs, characterized by a single rising phase without a shoulder [2]. The shoulder of sh-APs is considered to result from the AP evoked at the AIS (e. g. , [19]). Then, the question about the origin of fb-APs arises. In our detailed compartmental model (Fig 1), all APs are evoked at the AIS and exhibit a shoulder. In the simple model shown in Fig 3, fb-APs can be generated with strong stimuli and for large electrotonic distances between the soma and the AIS, which allows somatic AP initiation to precede or co-occur with AP initiation at the AIS. However, unlike experimentally recorded fb-APs, they arise smoothly from the subthreshold depolarization and do not exhibit a rapid onset that is present in simulated and experimentally recorded spikelets and sh-APs. According to the “compartmentalization hypothesis of AP initiation” [25], the AP onset rapidness is caused by axonal AP initiation. This suggests that experimentally recorded fb-APs with rapid onset are not generated at the soma. Consistently, somatic AP initiation due to serotonin inhibition of AIS channels can result in gradually rising APs without a rapid onset [40]. Therefore, we hypothesize that fb-APs are either generated at the AIS and the shoulder is “masked” by fast somato-dendritic activation or they are initiated in the apical dendrites and no shoulder is visible because of the smooth morphologic transition between the primary apical dendrite and the soma. An intriguing issue concerns the rare observation of spikelets in vitro. Our analyses suggest that pyramidal neurons are positioned at the edge of a regime that allows spikelet generation. In the complex model from [16] used in Figs 1 and 4–6 for example, a modest decrease in sodium channel density strongly increased spikelet occurrence. One reason for such a decrease in functional sodium channel availability might be slow sodium channel inactivation [41]. In vitro, there is less slow sodium channel inactivation: a larger fraction of sodium channels might be available for spiking due to a lower average membrane potential and a lower firing activity, which keeps the fraction of inactivated sodium channels low. Additionally, sodium channel availability is regulated by various neuromodulators, acting via activity-dependent phosphorylation [42]. This might be especially relevant in vivo, where a variety of homeostatic mechanisms are expected to maintain spiking activity in neural circuits [43]. In our models, fast sodium channel inactivation was not a main factor influencing spikelet generation (S1 and S2 Figs). It cannot be ruled out, however, that fast sodium inactivation does play a significant role in real neurons under certain in vivo conditions. Another important factor for spikelet generation is the somato-dendritic current sink, which is reduced in brain slices because of “dendritic pruning”, i. e. , dendritic processes cut by the slicing procedure [44]. The typical thickness of slices is a few hundred microns (e. g. , 300 μm, [8,16]), which roughly matches the spatial extent of a pyramidal neuron’s dendritic tree (e. g. , [45]). For patch-clamp recordings, cells close to the slice surface are preferentially used, which is where one expects significant damage to proximal dendrites [44]. A pyramidal cell’s input capacitance is in the range of hundreds of picofarads [46], and considerable changes of this value are predicted to strongly affect spikelet occurrence (Fig 3E). In contrast, an artificial capacitance increase of about 4—10 pF by an uncompensated patch electrode [47] is small compared to a pyramidal cell’s input capacitance and, thus, should not influence spikelet incidence significantly. The presented hypothesis predicts that all-or-none somatic spikelets in pyramidal neurons are associated with APs at the AIS or further down in the axon [27]. This mechanism could be tested experimentally with simultaneous recordings of the somatic and axonal membrane voltages, which, however, might be difficult in vivo. An alternative would be to establish a reliable spikelet model in vitro. We propose to recreate in vitro a state of a pyramidal cell that retains the in vivo properties of sodium channels, for example by prolonged stimulation with fluctuating inputs and/or application of relevant neurotransmitters and neuromodulators naturally present in the cerebrospinal fluid in vivo [48]. Additionally, it might be necessary to record from neurons located in the middle of a slice, to minimize the dendritic loss and the resulting decrease in the somato-dendritic current sink. Interestingly, unlike in mammalian cells, spikelets are easily evoked in turtle pyramidal neurons in vitro with weak somatic or dendritic stimuli [49,50]. The amplitudes and waveforms of these spikelets closely resemble those in mammalian pyramidal neurons. Dual somatic and axonal recordings suggested an axonal origin of these spikelets [50]. We hypothesize that there might be two important differences between turtle and mammalian neurons that support in vitro spikelet firing in turtles. First, the slower and wider APs in turtles suggest that the effective (peri-) somatic sodium channel densities might be smaller in turtle than in mammalian pyramidal neurons. Second, the somata of turtle neurons are substantially larger than the somata of mammalian neurons, and most of the dendrites are single branches extending from the soma [50]. This might result in an increased capacitive somato-dendritic current sink and augment the impedance mismatch between the axon and the soma. The spikelets we described here are APs that propagate forward down the axon but not backward into the soma and the dendrites. What could be a functional role of such “output-only APs”? From an energetic point of view, spikelet firing saves energy since it avoids activation of sodium currents in the soma and the dendritic tree. Output-only APs thus minimize their contribution to activity-dependent metabolism [51,52]. Moreover, spikelets might be a means of reading out the result of neuronal computations without triggering dendritic plasticity through backpropagating APs [53]. Hence, spikelets potentially represent a mode of operation that is functionally highly relevant. To further unravel the role spikelets may play in neural computations, more theoretical and experimental studies are needed. Developing a CA1 pyramidal neuron model with a realistic AIS composition incorporating state-of-the-art sodium channel models is vital for a quantitative study of spikelet generation and properties, as the prevailing experimental work on spikelets has been carried out in these neurons. In order to construct such a model, further experimental studies of AIS composition and function in CA1 pyramidal neurons are necessary. Future studies could also address the putative role of axo-axonic synapses in spikelet generation, which provide powerful inhibition at the proximal AIS that can prevent antidromically evoked APs from invading the soma [12]. It would be important to see whether these synapses can control the propagation of orthodromically initiated APs and give rise to somatic spikelets, given the small distances between the soma and the distal AIS and the requirement for precise timing of inhibition: Too early inhibition would shunt the subthreshold depolarization and prevent AP initiation in the first place, whereas too late inhibition would be ineffective to stop the propagating AP (see also [54]). Also the influence of sodium channel neuromodulation on spikelet occurrence [42] and generation of full-blown APs in cells exhibiting spikelets are important topics for our understanding of spikelets in pyramidal neurons. This knowledge should allow to assess the computational consequences of spikelet firing at the single-cell and network level.
For the results in Figs 1,4, 5 and 6 we used a previously published detailed model of a reconstructed layer V pyramidal neuron [16, ModelDB accession number 123897], implemented in NEURON [55]. Compared to the original model, we made two modifications. First, a small geometrical discontinuity at the AIS was corrected. In the original model, the AIS tapers from 1. 7 μm to 1. 22 μm. However, the diameter at the end of the axon hillock, i. e. , at the hillock-AIS boundary, is 1. 3 μm. We removed this sudden jump in the diameter so that the diameters at the end of the axon hillock and at the beginning of the AIS are equal at a value of 1. 3 μm (then tapering smoothly to 1. 22 μm, at the end of AIS). Second, the density of the NaV1. 2 subtype was decreased in soma, axon hillock, and AIS to 80%, and in dendrites to 60% of the original values. These changes only weakly influenced the AP properties and firing patterns (Table 1). The largest effects were observed for spikelet frequency and maximum AP slope. The decrease in maximum AP slope was desired, as it reflects the smaller AP slopes reported in vivo. Overall, the properties of APs generated in this model (Table 1) fit well into the range reported for pyramidal neurons in the experimental literature [2,5, 24,32,56]. The compartmental model cell was stimulated with two fluctuating synaptic point conductances placed at the soma [18] with the following parameters (values given in parentheses): reversal potential of the excitatory (Ee = 0 mV) and inhibitory (Ei = −75 mV) conductance, average excitatory (ge0 = 0. 01 μS) and inhibitory (gi0 = 0. 0573 μS) conductance, standard deviation of the excitatory (stde = 0. 014 μS) and inhibitory (stdi = 0. 02 μS) conductance and time constant of the excitatory (τe = 2. 728 ms) and inhibitory (τi = 10. 49 ms) conductance. As a result, the somatic membrane voltage fluctuated with a standard deviation of 8. 09 mV, producing a somatic AP firing rate of 5. 79 s−1 and a spikelet firing rate of 0. 63 s−1 (Fig 1). The somatic APs and spikelets were detected using a voltage-threshold criterion at the AIS and at the soma (both − 10mV). For both types of events, the threshold at the AIS had to be crossed. If the threshold at the soma was crossed within a time window from 1 ms before to 5 ms after the AIS threshold crossing, such an event was classified as an AP. Otherwise, the event was a spikelet. We also used a double-threshold criterion for the somatic voltage derivative (dV/dt) to confirm that no event was missed by the above voltage-threshold criterion and that indeed all somatic APs and spikelets were associated with an AP at the AIS: events that crossed the first threshold (20 V/s), but not the second threshold (100 V/s) were classified as spikelets, whereas somatic APs had to cross both thresholds within 2 ms. In Fig 1E, the APs were aligned in time to the point of crossing a somatic voltage threshold of -10 mV, whereas spikelets were aligned to the point of crossing a voltage threshold of -10 mV at the AIS. In Fig 1H, all events were aligned to the point of crossing the voltage threshold at the AIS to allow for a comparison of inputs between APs and spikelets. In Fig 1H, the effective synaptic reversal potential was calculated as (ge (t) Ee + gi (t) Ei) / (ge (t) + gi (t) ), i. e. , the excitatory and inhibitory reversal potentials weighted with the respective conductances. In Fig 4, in addition to the somatic conductance inputs as in Fig 1, the model cell was also stimulated with brief current pulses (0. 5 nA for 2 ms) delivered every 500 ms at the most distal axonal compartment. Somatic spikelets were classified as orthodromic (i. e. , evoked with somatic inputs) or antidromic (i. e. , evoked with distal axonal inputs) based on the relative timing of the AP at the distal AIS and in the axon. For orthodromic spikelets, the AP at the distal AIS preceded the AP in the axon; for antidromic spikelets, the AP at the distal AIS followed the AP in the axon. In Fig 5, the morphology of the model cell was altered: the axon hillock was omitted and the AIS was attached to a basal dendrite (“dendrite3[2] (0. 5) ”) 20. 5 μm away from the soma. In addition to the somatic conductance inputs as in Fig 1, an EPSG (τrise = 0. 5 ms, τdecay = 2 ms, peak conductance = 0. 02 μS, Esyn = 0 mV) was delivered every 500 ms to the axon-carrying dendrite, distally to the AIS-connecting site (“dendrite3[3] (0. 1) ”). Spikelets evoked with dendritic EPSGs were distinguished from the orthodromic spikelets (evoked with somatic inputs) as spikelets occurring within a 2 ms window after the dendritic EPSG. In Fig 6, in addition to the somatic conductance inputs as in Fig 1, the model cell was also stimulated with a brief current pulse (2 nA for 1 ms) delivered every 20 ms at the proximal apical dendrite (“dendrite11[2] (0) ”) 47 μm away from soma. In 200 s of simulation, 2,106 somatic APs and 91 somatic spikelets were generated. We classified the spikelets as evoked with the dendritic input if the somatic spikelet was evoked within 2 ms from dendritic stimulus onset (N = 43); if the spikelet occurred 10 ms or later after the onset of the dendritic stimulus, the spikelet was classified as triggered by the somatic background stimulus (N = 41). In S3 Fig, we simulated two identical cells (as in Fig 1) coupled by a gap junction. The gap junction was modelled as an ohmic resistor, allowing to transmit voltage changes between the coupled cells [57]. In cell 1, an AP was evoked with a somatic current step (2 nA applied for 15 ms), and a spikelet was recorded in cell 2. The strength of the gap junction was varied between 22 and 82 MΩ in 5 MΩ steps (corresponding to gap junctional conductance of 12–45 nS). The gap junction was placed at the soma or at several positions along the main apical dendrite (at a distance of ≈ 8,24,47,78, or 109 μm from soma). The leak reversal and initial membrane voltages were set to -80 mV instead of the original leak reversal of -70 mV because otherwise the closest and strongest gap junctions could only generate an AP and not a spikelet in cell 2. The amplitude of spikelets was measured from the maximum of the 2nd derivative (the “kink”) to the maximum amplitude. We mathematically analyzed a model consisting of a semi-infinite cable with an RC-circuit as a boundary condition, representing the axon and the entire somato-dendritic compartment, respectively (Fig 2). The system is mathematically equivalent to the lumped-soma model introduced by Rall [58]. Our model describes the dynamics of the voltage V along the axon at distance x from the soma in response to current input at location x = y using the linear cable equation: λ 2 δ 2 δ x 2 V (x, t) - τ δ δ t V (x, t) - V (x, t) = g (x, t) for x > 0 (1) where τ is the membrane time constant (in ms), λ is the axonal length constant (in cm), and g (x, t) is the input to the model. The boundary condition to include the somato-dendritic compartment at x = 0 is τ δ δ t V (0, t) = λ ρ δ δ x V (0, t) - V (0, t) (2) where the dimensionless parameter ρ denotes the ratio of the total somato-dendritic membrane resistance to the input resistance of the axon. The semi-infinite cable boundary condition is lim x → ∞ V (x, t) = 0. (3) For notational convenience we consider the resting potential in this linear system to be 0 mV. The parameters τ, λ, and ρ are determined by physiological parameters. Setting the specific membrane resistance Rm = 104 Ω cm2, specific membrane capacitance Cm = 1 μF/cm2, axial resistivity Ra = 150 Ω cm, surface area of the somato-dendritic compartment Asd = 2 ⋅ 10−4 cm2 and diameter of the axon da = 10−4 cm yields τ = RmCm = 10 ms, λ = R m d a 4 R a = 0. 041 cm and ρ = π d a 3 / 2 2 A s d = 0. 064. The purpose of the mathematical model was to compute the frequency-dependent attenuation of voltage signals between the axon and the somato-dendritic compartment. One approach is to use a complex-valued input current in the original partial differential equation and solve for the voltage responses of the axon and the somato-dendritic compartment. Here, we will instead proceed using a real-valued input current and use the Fourier transforms of the above partial differential equation and boundary conditions: λ 2 δ 2 δ x 2 V ^ (x, ω) - b (ω) 2 V ^ (x, ω) = g ^ (x, ω) for x > 0 (4) with the boundary conditions δ δ x V ^ (0, ω) - b (ω) 2 λ ρ V ^ (0, ω) = 0 (5) and lim x → ∞ V ^ (x, ω) = 0, (6) where V ^ (x, ω) and g ^ (x, ω) are the Fourier transforms of V (x, t) and g (x, t), respectively, ω = 2πf with frequency f (in Hertz), and b (ω) 2 = 1 + iωτ. We next calculated the voltage response of the model to the real-valued sinusoidal input current at location x = y: g (x, t) = R m π d a I 0 cos (ω 0 t) δ (x - y) (7) with radial frequency ω = ω0 ≥ 0 and amplitude I0. The Fourier transform of the input term is g ^ (x, ω) = R m π d a I 0 δ (ω - ω 0) δ (x - y), (8) where we neglected the negative-frequency terms. We then solved the above second-order, nonhomogeneous ODE by first considering solutions of the form V ^ h (x, ω) = c 1 exp (− b (ω) x / λ) + c 2 exp (b (ω) x / λ) for the homogeneous version of the ODE and use this to find a particular solution V ^ n h (x, ω) for the nonhomogeneous ODE; subsequently the constants c1 and c2 were determined by considering the boundary conditions [59, section 6. 2]. The sinusoidal voltage response at location 0 ≤ x ≤ y is V ^ (x, ω 0) = I 0 R ∞ b 0 ρ cosh (b 0 x / λ) + b 0 sinh (b 0 x / λ) (b 0 + ρ) exp (b 0 y / λ), (9) and for x ≥ y it is V ^ (x, ω 0) = I 0 R ∞ b 0 ρ cosh (b 0 x / λ) + b 0 sinh (b 0 x / λ) (b 0 + ρ) exp (b 0 y / λ) - sinh (b 0 (x - y) / λ) (10) where b0 = b (ω0) is the principal square root (i. e. , with positive real part) of 1 + i ω 0 τ and R ∞ = 2 π d a - 3 / 2 R m R a is the input resistance of a semi-infinite cable. The steady-state voltage attenuation from axon to soma is then given by the ratio of the voltage response amplitude at the axonal injection site to the somatic voltage response amplitude: A a x o n → s o m a (y, ω 0) = V ^ (y, ω 0) V ^ (0, ω 0) = cosh (b 0 y / λ) + b 0 ρ sinh (b 0 y / λ), (11) where |z| denotes the absolute value of the complex number z. Similarly, the frequency-dependent voltage attenuation from soma to axon for a somatic input (i. e. , y = 0 and x ≥ y) can be computed, which is equal to the attenuation in an (semi-) infinite cable: Asoma→axon (x, ω0) =| V^ (0, ω0) V^ (x, ω0) |=| exp (b0x/λ) |. (12) In Fig 2B–2G, the natural logarithm of the attenuation was plotted. The axonal stimulation/recording site was y = 50 μm away from the soma (except in Fig 2B where it was varied). The passive-membrane model was also simulated numerically with the NEURON module embedded in Python [60] to compare the antidromic (axon-to-soma) attenuation of pure sine waves with the attenuation of an AP waveform. Here, identical parameters were used as in the analytical calculations (see above). The axon length was set to 2 mm, corresponding to an electrotonic length of 4. 9 λ. The AP waveform was delivered via a voltage clamp at a 1 μm long axonal compartment located 50 μm away from the soma. We used an AP waveform recorded at the AIS of the detailed model (Fig 1D, middle). The input capacitance in Fig 2G was calculated from a small, prolonged voltage-clamp step by dividing the integrated transient charge by the voltage-clamp step size [61]. Results presented in Fig 3 used an active compartmental model of a simplified neuron morphology. The model consisted of a dendritic cable (length × diameter: 900 μm × 6 μm), an axonal cable (1,060 μm × 1 μm), and a cylindrical somatic compartment (40 μm × 20 μm). The axonal cable included a proximal AIS (30 μm), a distal AIS (30 μm), and the axon (1,000 μm). The passive model properties were uniform along the model neuron: specific membrane capacitance 1 μF/cm2, specific membrane resistance 10 kΩ cm2, and axial resistivity 150 Ω cm. The resting membrane potential equaled the leak reversal potential, which was set to -70 mV. The active model properties included transient sodium and delayed rectifier potassium conductances. Channel models were taken from [37, ModelDB accession number 2796], with parameter values corresponding to hippocampal pyramidal neurons. Active currents were present in all compartments (densities given in parentheses): Na-channel conductance in the soma and the dendrite (0. 02 S/cm2), in the proximal AIS and the axon (0. 04 S/cm2), and in the distal AIS (0. 1 S/cm2); K-channel conductance in the soma and the dendrite (0. 05 S/cm2), in the proximal and distal AIS (0. 25 S/cm2), and in the axon (0. 125 S/cm2). Additionally, the activation and inactivation curves of the Na-channels in the distal AIS and in the axon were shifted by 10 mV in hyperpolarizing direction compared to the activation and inactivation curves of Na-channels in the dendrite, the soma, and the proximal AIS. To elicit spiking activity in the model, rectangular current stimuli of 50 ms duration were applied at the soma. The resulting somatic event amplitude was measured from the voltage at the maximum of its second derivative (i. e. , maximum curvature) to the peak voltage. However, if there was no AP occurring at the AIS (detected as not crossing a voltage threshold of -20 mV), the somatic amplitude was not plotted (white regions in the heat maps). The input capacitance (Fig 3E) was calculated in the same way as in the passive-membrane model (see above). Voltage traces shown in S2 Fig were generated in a model with default parameters, except the length of the proximal AIS, which was set to 100 μm instead of the default 30 μm, so that all event types (spikelet, sh-AP, fb-AP) could be produced. In S2C Fig, the dynamics of sodium channel inactivation was “frozen” to the steady-state value at -70 mV by setting the time constant of inactivation to a very large value (105 ms). Numerical simulations were performed using the NEURON simulation environment [55], with the NEURON module embedded in Python [60]. | Action potentials (APs) are digital, all-or-none signals by which neurons communicate with each other. Therefore, APs are the basis of neural function, yet some of their fundamental features are still not well understood. Here we focus on pyramidal cells, which are the principal neurons in neocortex and hippocampus. According to textbook knowledge, an AP in pyramidal neurons is initiated at the axon initial segment and propagates along the axon to the next cell. Concurrently, the AP also propagates back to the soma and into the dendrites where it might trigger synaptic plasticity, which is the basis of learning and memory. However, besides APs, pyramidal cells sometimes also show somatic spikelets—small depolarizations with an AP-like shape—whose origin remains unclear. Here, we propose that spikelets occur when an AP initiated at the axon initial segment only propagates down the axon, but fails to activate sodium currents in the soma and dendrites. As a result, spikelet firing saves energy, and moreover, might be a means to control synaptic plasticity and thereby control learning and memory. | Abstract
Introduction
Results
Discussion
Methods | cell physiology
medicine and health sciences
action potentials
nervous system
depolarization
membrane potential
junctional complexes
electrophysiology
neuroscience
gap junctions
ion channels
nerve fibers
neuronal dendrites
sodium channels
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neurophysiology | 2017 | Spikelets in Pyramidal Neurons: Action Potentials Initiated in the Axon Initial Segment That Do Not Activate the Soma | 13,246 | 276 |
The bloodstream forms of Trypanosoma brucei, the causative agent of sleeping sickness, rely solely on glycolysis for ATP production. It is generally accepted that pyruvate is the major end-product excreted from glucose metabolism by the proliferative long-slender bloodstream forms of the parasite, with virtually no production of succinate and acetate, the main end-products excreted from glycolysis by all the other trypanosomatid adaptative forms, including the procyclic insect form of T. brucei. A comparative NMR analysis showed that the bloodstream long-slender and procyclic trypanosomes excreted equivalent amounts of acetate and succinate from glucose metabolism. Key enzymes of acetate production from glucose-derived pyruvate and threonine are expressed in the mitochondrion of the long-slender forms, which produces 1. 4-times more acetate from glucose than from threonine in the presence of an equal amount of both carbon sources. By using a combination of reverse genetics and NMR analyses, we showed that mitochondrial production of acetate is essential for the long-slender forms, since blocking of acetate biosynthesis from both carbon sources induces cell death. This was confirmed in the absence of threonine by the lethal phenotype of RNAi-mediated depletion of the pyruvate dehydrogenase, which is involved in glucose-derived acetate production. In addition, we showed that de novo fatty acid biosynthesis from acetate is essential for this parasite, as demonstrated by a lethal phenotype and metabolic analyses of RNAi-mediated depletion of acetyl-CoA synthetase, catalyzing the first cytosolic step of this pathway. Acetate produced in the mitochondrion from glucose and threonine is synthetically essential for the long-slender mammalian forms of T. brucei to feed the essential fatty acid biosynthesis through the “acetate shuttle” that was recently described in the procyclic insect form of the parasite. Consequently, key enzymatic steps of this pathway, particularly acetyl-CoA synthetase, constitute new attractive drug targets against trypanosomiasis.
Trypanosoma brucei is a unicellular eukaryote, belonging to the protozoan order Kinetoplastida that causes sleeping sickness in humans and economically important livestock diseases [1]. This parasite undergoes a complex life cycle during transmission from the bloodstream of a mammalian host (bloodstream forms of the parasite - BSF) to the alimentary tract (procyclic form - PF) and salivary glands (epimastigote and metacyclic forms) of a blood feeding insect vector, the tsetse fly. In the bloodstream of the mammalian host, the pleomorphic BSF strains proliferate as “long-slender” BSF (LS-BSF) and differentiate into the non-proliferative “short-stumpy” trypanosomes (SS-BSF), which are preadapted for differentiation into PF in the insect midgut [2]. The environmental changes encountered by the parasite require significant morphological and metabolic adaptations, as exemplified by important qualitative and quantitative differences in glucose metabolism between BSF and PF [3], [4]. PF living in the tsetse fly midgut – where glucose is scarce or absent – have developed an elaborate energy metabolism based on amino acids, such as proline. However, when grown in standard glucose-rich conditions, they prefer glucose to proline as a carbon source [5], [6]. PF converts glucose into the partially oxidized and excreted end-products, acetate and succinate, with most of the glycolysis taking place in specialized peroxisomes called glycosomes [7]. In the course of glycolysis, phosphoenolpyruvate (PEP) is produced in the cytosol, where it is located at a branching point to feed the glycosomal ‘succinate branch’ and the mitochondrial ‘acetate and succinate branches’ (see Fig. 1). For the “succinate branches”, PEP must re-enter the glycosomes where it is converted into malate and succinate within that compartment. Malate, which moves from the glycosomes into the mitochondrion, can also be converted into succinate therein. Additionally, PEP can be converted in the cytosol into pyruvate to feed the ‘acetate branch’ (steps 1–4 in Fig. 1). In the mitochondrion, pyruvate is converted by the pyruvate dehydrogenase complex (PDH, EC 1. 2. 4. 1, step 1) into acetyl-CoA and then into acetate by two different enzymes, i. e. acetate∶succinate CoA transferase (ASCT, EC 2. 8. 3. 8, step 2) and acetyl-CoA thioesterase (ACH, EC 3. 1. 2. 1, step 3) [8]–[10]. In PF, acetate production plays an important role for mitochondrial ATP production by the ASCT/SCoAS cycle (steps 2 and 4), while ACH is not involved in ATP production [10]. Acetate can also be produced from threonine, a major carbon source of PF present in the in vitro medium [6], [11], [12]. This amino acid is converted into acetate by threonine-3-dehydrogenase (TDH, EC 1. 1. 1. 103, step 5), acetyl-CoA∶glycine C acetyltransferase (EC 2. 3. 1. 29, step 6) and probably ASCT and/or ACH. We recently showed that PF uses a new metabolic pathway only observed in PF trypanosomes so far, named the “acetate shuttle”, which transfers acetyl-CoA from the mitochondrion to the cytosol to feed the essential cytosolic fatty acid biosynthesis [13]. In this shuttle, acetate produced in the mitochondrion from acetyl-CoA is exported in the cytosol and converted back into acetyl-CoA by the cytosolic acetyl-CoA synthetase (AMP-dependent enzyme, AceCS, EC 6. 2. 1. 1, step 7). In contrast to PF, BSF trypanosomes rely only on glucose for their energy production, with a 5- to 10-fold higher rate of glucose consumption [14]. It is generally accepted that the proliferative LS-BSF grown under aerobiosis convert glucose exclusively into pyruvate [15], [16], although excretion of trace amounts of other incompletely oxidized end-products such as glycerol, succinate and alanine have been reported [14], [17]. These minor glycolytic end-products are thought to be produced by “contaminating” non-proliferative SS-BSF trypanosomes that have developed a more elaborated central metabolism with a number of PF traits, including production of acetate and succinate from glycolysis [18], [19]. Consequently, recent reports consider that LS-BSF trypanosomes do not produce acetate from glucose. In the seventies, acetate production was reported from the threonine degradation in both PF and BSF trypanosomes [12], however, this metabolic pathway was not further investigated. Here we investigated the role of glucose and threonine degradation in acetate production in the monomorphic 427 BSF strain, which proliferates as LS-BSF trypanosomes and has lost the ability to differentiate into non-proliferative SS-BSF [20], [21]. This BSF cell line produces and excretes acetate, as a minor end-product of glucose metabolism, with a metabolic flux in the same range as observed for PF. Glucose and threonine contribute almost equally to acetate production, which is essential for the viability of proliferative BSF trypanosomes, as demonstrated by reverse genetics approaches. Our data reveal unexpected metabolic similarities between PF and LS-BSF trypanosomes.
The bloodstream form of T. brucei 427 90-13 (TetR-HYG T7RNAPOL-NEO), a 427 221a line (MiTat 1. 2) designed for the conditional expression of genes, was cultured at 37°C in IMDM (Iscove' s Modified Dulbecco' s Medium, Life Technologies) supplemented with 10% (v/v) heat-inactivated fetal calf serum (FCS), 0. 25 mM ß-mercaptoethanol, 36 mM NaHCO3,1 mM hypoxanthine, 0. 16 mM thymidine, 1 mM sodium pyruvate, 0. 05 mM bathocuprone and 2 mM L-cysteine [22]. To prepare threonine-depleted IMDM medium all the compounds constituting the medium, except threonine, were purchased from Sigma-Aldrich. The procyclic form of T. brucei EATRO1125 was cultured at 27°C in SDM79 medium containing 10% (v/v) heat-inactivated fetal calf serum and 35 µg/mL hemin [23]. Replacement of the threonine-3-dehydrogenase (TDH: Tb927. 6. 2790) by the puromycin (PAC) and blasticidin (BSD) resistance markers via homologous recombination was performed with DNA fragments containing a resistance marker gene flanked by the TDH UTR sequences. The TDH knock out was generated in the 427 90-13 BSF parental cell line, which constitutively expresses the T7 RNA polymerase gene and the tetracycline repressor under the control of a T7 RNA polymerase promoter for tetracycline inducible expression (TetR-HYG T7RNAPOL-NEO) [24]. Transfection and selection of drug-resistant clones were performed as previously reported using the Nucleofactor system [25]. The first and second TDH alleles were replaced by puromycin- and blasticidin-resistant genes, respectively. Transfected cells were selected in IMDM medium containing hygromycin B (5 µg/mL), neomycin (2. 5 µg/mL), puromycin (0. 1 µg/mL) and blasticidin (10 µg/mL). The selected cell line (TetR-HYG T7RNAPOL-NEO Δtdh: : PAC/Δtdh: : BSD) is called Δtdh. Accession numbers (http: //www. genedb. org/genedb/tryp/) of genes targeted by RNAi, acetyl-CoA synthetase (AMP-dependent enzyme, AceCS) and E2 subunit of the pyruvate dehydrogenase complex (PDH-E2), are Tb927. 8. 2520 and Tb927. 10. 7570, respectively. RNAi-mediated inhibition of gene expression in the 427 90-13 BSF parental cell line was performed by expression of stem-loop “sense/anti-sense” RNA molecules of the targeted sequences introduced into the pHD1336 (kindly provided by C. Clayton, ZMBH, Heidelberg, Germany, cclayton@zmbh. uni-heidelberg. de). The AceCS-SAS and PDH-E2-SAS “sense/anti-sense” constructs were first generated in the pLew100 vector (kindly provided by E. Wirtz and G. Cross) [24] as described before [5], [13]. Then the AceCS-SAS and PDH-E2-SAS HindIII-BamHI cassettes extracted from the pLew100 plasmids were inserted in HindIII-BamHI digested pHD1336 vector, which contains the blasticidin resistance gene. The RNAi-harboring RNAiAceCS and RNAiPDH single mutant cell lines were produced by transfection of the 427 90-13 cell line with the NotI-linearized pHD-AceCS-SAS and pHD-PDH-E2-SAS plasmids, respectively, and selected in IMDM medium containing hygromycin B (5 µg/mL), neomycin (2. 5 µg/mL) and blasticidin (10 µg/mL). For transfection of the Δtdh cell line with the pLew-PDH-E2-SAS construct, all of the four antibiotics used to select the Δtdh cell line, in addition to phleomycin (2. 5 µg/mL), were included in the medium to select double mutant cell lines. A recombinant fragment containing the full-length TDH gene was inserted into the NdeI and BamHI restriction sites of the pET28a expression vectors (Novagen) to express in BL21 Escherichia coli the TDH protein preceded by a N-terminal histidine tag (6 histidine codons). Cells were harvested by centrifugation, and recombinant proteins purified by nickel chelation chromatography (Novagen) from the insoluble fraction according to the manufacturer' s instructions. The anti-TDH immune serum was raised in rabbits by five injections at 15-day intervals of 100 µg of TDH-His recombinant nickel-purified proteins, emulsified with complete (first injection) or incomplete Freund' s adjuvant (Proteogenix S. A.). Antibodies raised against the T. brucei TDH protein expressed in E. coli recognize a single 36. 5 kDa protein in western blots, corresponding to the calculated TDH molecular weight (36. 96 kDa). Total protein extracts of bloodstream or procyclic forms of T. brucei (5×106 cells) were separated by SDS PAGE (10%) and immunoblotted on Immobilon-P filters (Millipore) [26]. Immunodetection was performed as described [26], [27] using as primary antibodies, the mouse anti-sera against AceCS diluted 1∶100 [13], PDH-E2 diluted 1∶500 [28] or the heat shock protein 60 (hsp60) diluted 1∶10,000 [29], or the rabbit anti-sera against TDH diluted 1∶500, acetate∶succinate CoA-transferase (ASCT) diluted 1∶100 [9], acetyl-CoA thioesterase (ACH) diluted 1∶500 [10] or glycerol-3-phosphate dehydrogenase (GPDH, EC 1. 1. 1. 8) diluted 1∶100 [30]. Goat anti-rabbit Ig/peroxidase (1∶10,000 dilution) or goat anti-mouse Ig/peroxidase were used as secondary antibody and revelation was performed using the SuperSignal West Pico Chemiluminescent Substrate as described by the manufacturer (Thermo Scientific). Images were acquired and analyzed with a KODAK Image Station 4,000 MM and quantitative analyses were performed with the KODAK MI application. Cells were washed in PBS and lysed by sonication (5 sec at 4°C) in hypotonic lysis buffer (5 mM Na2HPO4,0. 3 mM KH2PO4). Determination of TDH and PDH enzymatic activities was performed using a spectrophotometric assay as described before [12], [31], [32]. To stain mitochondria of the wild-type cell lines, 200 nM MitoTracker Red CMXRos (Invitrogen) were added to the culture, followed by a 20 min incubation and washes in PBS. Then wild-type cells were fixed with 4% formaldehyde in PBS, permeabilized with 1% Triton X-100, and spread on poly-L-lysine-coated slides. The slides were then incubated for 45 min in PBS containing 5% BSA, followed by incubation in PBS with 2% BSA and the primary antiserum, 1∶50 diluted rabbit anti-TDH, mouse anti-AceCS or mouse anti-PDH-E1α. After washing with PBS, the slides were incubated with 2 µg/mL Alexa 594 anti-rabbit IgG conjugate or Alexa Fluor 594 anti-mouse IgG conjugate (Molecular Probes). Slides were then washed and mounted in the SlowFade antifade reagent (Invitrogen). Cells were visualized with a Leica DM5500B microscope, and images were captured by an ORCA-R2 camera (Hamamatsu) and Leica MM AF Imaging System software (MetaMorph). The bloodstream forms (2. 5×107 cells, ∼0. 25 mg of proteins) or procyclic form (5×107 cells, ∼0. 25 mg of proteins) of T. brucei were collected by centrifugation at 1,400 g for 10 min, washed once/twice with phosphate-buffered saline (PBS) and incubated for 5 h at 37°C in 2. 5 mL of incubation buffer (PBS supplemented with 5 g/L NaHCO3, pH 7. 4), with [U-13C]-glucose (4 mM) in the presence or the absence of threonine (4 mM). The same experiments were performed with regular 12C glucose as the only carbon source. The integrity of the cells during the incubation was checked by microscopic observation. 50 µL of maleate (20 mM) were added as internal reference to a 500 µL aliquot of the collected supernatant and proton NMR (1H-NMR) spectra were performed at 125. 77 MHz on a Bruker DPX500 spectrometer equipped with a 5 mm broadband probe head. Measurements were recorded at 25°C with an ERETIC method. This method provides an electronically synthesized reference signal [33]. Acquisition conditions were as follows: 90° flip angle, 5,000 Hz spectral width, 32 K memory size, and 9. 3 sec total recycle time. Measurements were performed with 256 scans for a total time close to 40 min. Before each experiment, the phase of the ERETIC peak was precisely adjusted. Resonances of the obtained spectra were integrated and results were expressed relative to ERETIC peak integration. The linear production of pyruvate and acetate throughout the experiment was confirmed by 1H-NMR quantification of the end-products excreted by the wild type trypanosomes incubated for 6 h in PBS containing 4 mM [U-13C]-glucose (data not shown). Cells in the late exponential phase (5×107 cells) were incubated for 16 h in 10 mL of modified IMDM medium without threonine, pyruvate, leucine, isoleucine, valine, containing 25 mM glucose, 100 µM acetate and 40 µCi of [1-14C]-acetate (55. 3 mCi/mmol). Cells were checked microscopically for viability several times during incubation. Subsequently, lipids were extracted by chloroform∶methanol (2∶1, v/v) for 30 min at room temperature, and then washed three times with 0. 9% NaCl. The washed lipid extracts were then evaporated and lipids were dissolved in 1 mL of methanol∶H2SO4 (40∶1, v/v). Trans-esterification of the fatty acids of the lipids was performed at 80°C for 60 min. After cooling the samples, 400 µL of hexane (99% pure) and 1. 5 mL of H2O were added, and the mixture was homogenized vigorously for 20 sec. The samples were then centrifuged for 5 min at 1,000 g to separate the phases, and the hexane upper phases containing fatty acid methyl ester (FAMEs) were recovered without contact with the lower phases. FAMEs were loaded onto HPTLC plates developed in hexane/ethylether/acetic acid (90∶15∶2, v/v) and were separated (RF 0. 90). They were identified by co-migration with known standards. Their radio-labeling was then determined with a STORM 860 (GE Healthcare). The values were normalized with the amounts of total esters in each sample and detected by densitometry analysis using a TLC scanner 3 (CAMAG, Muttenz, Switzerland) as already described [13]. Eight- to ten-week-old female BALB/c mice bred at the SAS Centre d' Elevage Depré (Saint Doulchard, France) were housed under conventional conditions, with food and water administered ad libitum, according to institutional guidelines. Twelve mice per group were immunocompromised by intraperitoneal injection of 300 mg/kg Endoxan 48 h prior to infection and then infected with a single intraperitoneal injection of 104 parasites suspended in 0. 3 mL of fresh IMDM medium. Where appropriate, 1 mg/mL doxycycline and 50 g/L saccharose were added every 48 h to the drinking water starting three days prior to infection. Four experimental groups were studied: animals infected with wild-type parasites without (group 1) or with doxycycline (group 2) in the drinking water, animals infected with the c RNAiPDH. ni cell line (group 3) and animals infected with the RNAiPDH. i cell line cultured for 48 h in the presence of doxycycline to pre-induce down-regulation of PDH-E2 expression and then kept with doxycycline in the drinking water (group 4). To prevent the phenotypic reversion commonly observed in BSF mutants, the injected RNAiPDH. i cell line was selected from a fresh transfection and maintained in vitro up to 4 weeks post-transfection before injecting the animals. Efficient down-regulation of PDH-E2 expression was confirmed by western blot and the threonine-dependency of the selected cell line was confirmed in vitro. The health status of the animals was monitored on a daily basis and parasitaemias were counted daily. Experiments, maintenance and care of mice complied with guidelines of the European Convention for the Protection of Vertebrate Animals used for Experimental and other Scientific Purposes (CETS n°123). Experiments were approved by the Department for the protection of animals and plants of the Préfecture de la Gironde (Identification number A33-063-324).
PF depend on acetate produced in the mitochondrion to feed fatty acid biosynthesis through the essential enzyme AceCS [13]. A western blot analysis showed that AceCS (74 kDa) was expressed at the same level in the BSF and PF, and an immunofluorescence analysis using the anti-AceCS immune serum showed a homogeneous diffuse pattern characteristic of a cytoplasmic localization (Fig. 2), suggesting that this pathway may also exist in BSF. AceCS is essential for BSF viability, as demonstrated by the death of the RNAiAceCS. i cell line three days post-induction of down-regulation of the AceCS gene expression (. ni and. i stands for uninduced and tetracycline-induced, respectively) (Fig. 3A). To investigate the role of AceCS, radiolabel incorporation into fatty acids from [1-14C]-acetate was measured for the parental and RNAiAceCS cell lines incubated in the IMDM medium. Label incorporation into fatty acids was reduced 2. 1- and 8. 1-fold one and two days after tetracycline addition, respectively, which correlates with the reduction of AceCS expression (Fig. 3B). Altogether these data demonstrate that proliferative BSF require acetate to feed the essential fatty acid biosynthetic pathway, as previously observed in PF [13]. The IMDM medium does not contain acetate, except the minor contribution of the 10% FCS supplement (∼5 µM) [34]. Consequently, LS-BSF may produce acetate from the catabolic pathways previously identified in PF, i. e. mitochondrial production of acetyl-CoA from glucose and threonine degradation through PDH and TDH, respectively [3], followed by conversion of acetyl-CoA into acetate by two mitochondrial enzymes, ASCT [9] and ACH [10]. A western blot analysis showed that ASCT (54 kDa), ACH (40. 5 kDa), PDH-E2 (E2 subunit of PDH, 49. 6 kDa) and TDH (39. 5 kDa) are expressed in the 427 BSF strain, which has lost the ability to differentiate into SS-BSF (Fig. 2A). This was confirmed by determination of the PDH and TDH activities in LS-BSF, which were 4-fold and 6. 7-fold lower than PF, respectively (Fig. 2A). Immunofluorescence analyses revealed colocalization of PDH-E1α (E1α subunit of PDH) and TDH with the mitochondrion-specific dye MitoTracker Red CMXRos (Invitrogen) (Fig. 2B). The mitochondrial localization of TDH is consistent with a 24-amino-acid N-terminal mitochondrial targeting signal predicted by MitoProt (http: //ihg. gsf. de/ihg/mitoprot. html) with a high probability (0. 82). Since BSF express the whole set of enzymes required for acetate production, we then used a combination of reverse genetics on PDH-E2 and TDH and metabolic profiling by NMR to investigate mitochondrial acetate production in BSF. It is widely considered that LS-BSF excrete only pyruvate from glucose metabolism, while PF mainly produce acetate and succinate. To compare glucose metabolism in these two forms, 2. 5×107 LS-BSF and 5×107 PF (equivalent to 0. 25 mg of proteins) were incubated in 2. 5 mL of PBS containing 4 mM glucose (Fig. 4) or [U-13C]-glucose (Fig. 5A and Table 1). 13C-enriched end-products excreted in the medium from [U-13C]-glucose metabolism were quantified by 1H-NMR (Table 1). It is to note that quantification errors are significant, in particular for molecules representing less than 5% of all excreted end-products. As expected, BSF mainly converted glucose into pyruvate (7761 nmol/h/108 cells), which accounts for 85. 1% of the excreted end-products. In addition, BSF excreted significant amounts of alanine, acetate and succinate, which represent 9. 2%, 4. 9% and 0. 8% of the excreted end-products from glucose metabolism, respectively (Table 1). Surprisingly, the rate of excretion of 13C-enriched acetate and succinate from [U-13C]-glucose was only 2-fold lower in BSF than in PF (446 versus 789 nmol of acetate/h/108 cells and 71 versus 156 nmol of succinate/h/108 cells, respectively) (Table 1, see Fig. 4). The unexpected similar rate of acetate and succinate excretion in both trypanosome forms is probably due to the ∼10-fold higher glycolytic rate in BSF (the rate of glycolytic end-product excretion was 9. 4-fold higher in BSF compared to PF - Table 1). Consequently, the high glycolytic rate in BSF combined with the dominant conversion of glucose into pyruvate (85. 1% of the excreted end-products) may have led to underestimation of the role of acetate and succinate production in LS-BSF, although their rate of production were in the same range in PF. To confirm acetate production from glucose metabolism by LS-BSF, we conducted RNAi-mediated down-regulation of expression of the PDH-E2 gene. The RNAiPDH. i cell line showed no growth phenotype upon tetracycline induction (Fig. 6A), although the PDH-E2 protein was no longer detectable by western blot two days post-induction (Fig. 6A, inset). Metabolite profiling of the RNAiPDH. i cell line incubated in the presence of 4 mM of [U-13C]-glucose showed a 13. 7-fold reduction of acetate production from glucose compared to the RNAiPDH. ni cells (55 versus 755 nmol/h/108 cells) (Table 1). It is to note that, for unknown reasons, the uninduced RNAiPDH. ni cell line produces ∼1. 7-times more acetate from glucose than the parental cells. Since both BSF and PF have been reported to produce acetate from threonine [12], which is present in the IMDM medium (0. 9 mM), we investigated the threonine degradation pathway in BSF. Incubation of the parasites in threonine-depleted medium, which contains only ∼15 µM of the amino acid coming from FCS [35], did not affect growth of the wild-type and RNAiPDH. ni cells, while growth of the RNAiPDH. i mutant was abolished (Fig. 6D). To confirm that glucose and threonine degradations contribute to acetate production, both pathways were interrupted by down-regulating PDH-E2 expression in the TDH null background (Δtdh/RNAiPDH cell line). First, both TDH alleles were replaced by the puromycin (PAC) and blasticidin (BSD) markers in the Δtdh cell line, with no effect on growth rate (Fig. 6C). Deletion of both TDH alleles was confirmed by PCR analyses (Fig. 6B), western blot analyses and enzymatic assays (insets of Fig. 6C). Second, RNAi-mediated down-regulation of PDH-E2 was performed in the Δtdh background. Growth of the Δtdh/RNAiPDH. i cell lines was abolished three days post-induction before cell death seven days later (Fig. 6E). Addition of 4 mM acetate in the medium does not rescue growth of the Δtdh/RNAiPDH. i mutant (data not shown) suggesting that acetate and/or acetyl-coA need to be produced inside the mitochondrion to feed the essential mitochondrial fatty acid pathway, may be through the production of the precursor butyryl-CoA [36]. This result confirms that abolition of mitochondrial acetyl-CoA/acetate production from both glucose and threonine is lethal for BSF grown in standard medium. To address this question we developed a metabolite profiling assay based on the ability of 1H-NMR spectrometry to distinguish 13C-enriched molecules from 12C ones. Cells were incubated in PBS with equal amounts (4 mM) of [U-13C]-glucose and unenriched threonine in order to perform a quantitative analysis of threonine-derived and glucose-derived acetate production by 1H-NMR. When [U-13C]-glucose was the only carbon source in the incubation medium, the excreted [13C]-acetate (annotated A13 in Fig. 5) was represented by two doublets with chemical shifts at around 2. 0 ppm and 1. 75 ppm, respectively (see Fig. 5A). It is to be noted that threonine metabolism cannot be analyzed independently since glucose is essential for BSF. Addition of threonine to the [U-13C]-glucose/PBS medium induced production of threonine-derived [12C]-acetate (386 nmol/h/108 cells) in addition to [13C]-glucose-derived [13C]-acetate (532 nmol/h/108 cells) (Fig. 5B and Table 2). This shows that in the presence of equal amounts of both carbon sources, glucose contributes ∼1. 4-fold more than threonine to acetate production. 1H-NMR metabolite profiling of the single and double mutants confirmed the involvement of both glucose and threonine in acetate production. As expected, production of [13C]-glucose-derived [13C]-acetate was ∼50-times lower in the RNAiPDH. i than in the RNAiPDH. ni cells (16 versus 847 nmol/h/108 cells), while threonine-derived acetate production was not affected. Conversely, production of threonine-derived acetate was abolished in the Δtdh mutant, while [13C]-glucose-derived [13C]-acetate was not affected (Table 2 and Fig. 5C–D). Finally, production of acetate from both carbon sources was affected in the Δtdh/RNAiPDH. i double mutant cell line (Table 2 and Fig. 5E). BALB/c mice immunocompromised by Endoxan treatment were injected with wild-type and RNAiPDH cells and kept with or without doxycycline, a stable tetracycline analog, in the drinking water to down-regulate expression of PDH-E2. Animal survival and the blood parasite levels were monitored. No differences were observed between the four groups of animals, in which parasite density started to rise at day three post-infection. All mice were dead at days 6–7 post-infection (data not shown). This shows that acetate production from glucose is not necessary for the viability of T. brucei in vivo, suggesting that a possible acetate source (threonine) that is present in the blood is absent in the threonine-depleted in vitro culture medium. As mentioned above, mammalian blood contains approximately 150 µM threonine [35], [37], which is 10-times higher than in the threonine-depleted IMDM medium. The RNAiPDH. i cell line died in IMDM medium containing 15,37. 5 and 75 µM threonine, while addition of 150 µM of the amino acid restored its growth in vitro (Fig. 6D), suggesting that the homeostatic threonine blood concentration (150 µM) is sufficient to provide BSF with the required acetyl-CoA/acetate molecules. Altogether, this demonstrates that BSF trypanosomes have developed two complementary and self-sufficient ways to maintain the essential production of acetate in the blood of mammalian hosts.
LS-BSF trypanosomes are well known for their glucose-dependency to satisfy ATP requirements [38]. Indeed, net production of all cellular ATP is fulfilled by the last glycolytic step catalyzed by pyruvate kinase, which produces pyruvate, the excreted glycolytic end-product. Excretion of significant amounts of other partially oxidized end-products of glycolysis, such as glycerol, succinate and alanine, has been previously reported [14], [17], [39], [40]. However, in the late seventies emerged a general dogma whereby pyruvate was considered the exclusive glycolytic end-product excreted from LS-BSF under aerobic conditions [15], [16], because the minor end-products were assigned to either non-growing conditions or contamination with non-dividing SS-BSF [18], [19]. Here, we used as an experimental model the 427 BSF strain, which has lost the ability to differentiate into SS-BSF, in order to focus our analysis of glucose metabolism on LS-BSF trypanosomes. This laboratory-adapted monomorphic strain is insensitive to the stumpy inductor factor, but, it successfully differentiates in vitro into bona fide SS-BSF, for instance when expression of the protein kinase target of rapamycin (TOR4) is inhibited [41]. This suggests that the 427 strain can be considered as a slender-like BSF that has lost the ability to respond to the stumpy inductor factor, and as such is the relevant model to study the metabolism of proliferative BSF. Our metabolic analyses showed that LS-BSF can produce almost as much succinate and acetate from glucose as PF incubated in the same conditions. This suggests that most, if not all, enzymes involved in the “succinate and acetate branches” previously characterized in PF are also expressed in LS-BSF. To produce acetate, PDH (step 1 in Fig. 1) converts pyruvate into acetyl-CoA, which is the substrate of ASCT (step 2) and ACH (step 3) for acetate production. ASCT expression is low in BSF (Fig. 2 and [19]), while ACH is relatively abundant (Fig. 2) with an ACH activity ∼2-fold higher than PF (data not shown). Three of the four PDH subunits have been investigated so far and are expressed in BSF (PDH-E1α and PDH-E2, see Fig. 2; PDH-E3, [42]), with a PDH enzymatic activity only 4-fold lower than in PF (Fig. 2). This relatively high PDH activity is in agreement with a recent comparative SILAC proteomics analysis showing that PDH-E1α, PDH-E1ß, PDH-E2 and PDH-E3 are 5. 3-, 7. 6-, 5. 2- and 8. 1-fold more abundant in PF than LS-BSF, respectively [43]. The same proteomics analysis in LS-BSF also detected most, if not all, of the enzymes involved in succinate production from phosphoenolpyruvate, although at a lower level of expression than in PF (between 3- and 20-fold). Altogether, this clearly demonstrates that LS-BSF have maintained the capacity to produce and excrete acetate and succinate from glycolysis. The relatively high rate of acetate and succinate production (only ∼2-fold higher in PF), while the enzymes involved in the corresponding metabolic pathways are 5- to 20-times more abundant in PF, may be due to the considerably higher glycolytic flux in BSF. We determined that the excretion rate of glycolytic end-products is 9. 5-fold higher in BSF than in PF (9115 versus 968 nmol of excreted end-products/h/108 cells), which is consistent with the previously measured 5- to 10-fold difference in glycolytic flux [14]. A recent analysis of the glycolytic flux in the same BSF strain incubated in growing conditions (IMDM containing 20 mM glucose) showed a higher rate of pyruvate production compared to our analysis performed in PBS containing 4 mM glucose and threonine (19. 2 versus 12. 0 µmol/h/108 cells) [44]. The reduced glycolytic flux observed in PBS conditions certainly reflects the difference between non-growing conditions (PBS) and exponential growth (IMDM) with a doubling time in the range of 5 h [44]. Also, the 35% reduction in total end-product fluxes for the wild type cells depending on the available substrates (PBS/glucose versus PBS/glucose/threonine) shows that metabolic fluxes are dependent on the exact context of substrates present (Table 1). It is important to note that our experimental procedures do not reflect physiological conditions, since trypanosomes were incubated at high density in PBS containing 4 mM glucose. Consequently, these minor glycolytic end-products might be excreted at a lower rate, or not at all, by LS-BSF trypanosomes in vivo. A recent quantitative analysis of the fate of glucose in exponentially growing 427 LS-BSF in vitro (the same strain analysis here) showed that pyruvate is the only excreted glycolytic end-product [44]. Glucose, pyruvate and glycerol were analysed in that study. Although they report an almost complete carbon balance between glucose uptake and pyruvate excretion, their analysis leaves room for small fluxes towards products they did not analyse such as acetate and succinate. We here report these end-products, with fluxes to acetate and succinate together representing ∼5% of the excreted glycolytic end products. The exact fraction of total carbon going to these end-products is difficult to assign, due to the errors in quantification of fluxes and because our results did not enable the calculation of a carbon balance between carbon uptake and excretion. Whatever the rate of acetate excretion from glucose metabolism in exponentially growing LS-BSF is, its production is essential for growth, as exemplified by the death of the RNAiPDH. i cell line incubated in the absence of threonine, the other acetate source. This was confirmed by inducing cell death upon blocking acetate production from both carbon sources in the Δtdh/RNAiPDH. i double mutant, while growth of the corresponding single mutants in standard IMDM medium was not affected (Fig. 6). The relevance of acetate production from glycolysis for LS-BSF is further strengthened by (i) the same high rate of growth of the wild-type parasite, even in the absence of threonine (Fig. 6), as recently observed by the development of a new minimal medium that supports growth of BSF [37] and (ii) the impossibility to rescue growth of the Δtdh/RNAiPDH. i double mutant by addition of sodium acetate in the medium, which cannot substitutes glucose-derived acetate production. The above-mentioned reverse genetic experiments combined with 1H-NMR metabolic analyses also clearly demonstrate that glucose and threonine are the only significant carbon sources contributing to the essential production of acetate in the 427 BSF strain. To our knowledge, this is the first report showing acetate production from glucose in LS-BSF, while threonine has been described before as an acetate-source in BSF [12], [45]. Inhibition of a single acetate-production pathway in the RNAiPDH. i and Δtdh cell lines grown in standard IMDM medium does not affect growth of LS-BSF, indicating that a single active pathway is sufficient for growth in vitro. This is probably also true in vivo, since (i) glucose concentration is higher in the blood than in our experimental conditions (5 versus 4 mM) and (ii) the relatively low homeostatic concentration of threonine in mammalian blood (150 µM) is sufficient for acetate production, as demonstrated by the absence of growth effect of the RNAiPDH. i mutant in medium containing at least 150 µM threonine (Fig. 6D). When incubated with equal amounts of threonine and glucose (4 mM), the parasite produces ∼1. 4-fold more acetate from glycolysis. Mammalian blood contains ∼30-fold more glucose than threonine (5 mM versus 150 µM), which strengthens the view that the contribution of glucose to acetate production is relevant in vivo. This contrasts with an equivalent recent analysis performed on the procyclic form of T. brucei, which prefers threonine for acetate and fatty acid productions, with a ∼2. 5-fold higher contribution of threonine compared to glucose when incubated with 4 mM of both carbon sources [46]. In PF trypanosomes, the mitochondrial production of acetate is essential to feed de novo fatty acid biosynthesis through the “acetate shuttle” [13]. In this shuttle, acetate produced in the mitochondrion reaches the cytosol, where a part of it is converted by AceCS into acetyl-CoA to produce malonyl-CoA, the elongator for fatty acid biosynthesis. It is noteworthy that both the microsomal elongase-dependent and mitochondrial type II fatty acid synthase pathways use malonyl-CoA to elongate fatty acids [47]. As observed in PF, AceCS is essential for incorporation of [1-14C]-acetate into LS-BSF fatty acids (Fig. 3), indicating that AceCS is required for de novo fatty acid synthesis. In addition, Gilbert et al. previously showed that both glucose and threonine are used as carbon sources for fatty acid synthesis [47]. Altogether, this demonstrates that, like PF, proliferative BSF trypanosomes use the “acetate shuttle” to feed fatty acid biosynthetic pathways. The essential role of mitochondrial fatty acid synthesis has been documented in BSF, however, RNAi-mediated down regulation of elongase genes involved in the microsomal fatty acid biosynthesis does not affect growth of the parasite [36], [48], [49], [50]. Consequently, the lethal phenotype observed for the LS-BSF RNAiAceCS mutant is probably due to the dramatic reduction of cytosolic malonyl-CoA production required to feed mitochondrial fatty acid biosynthesis, which contribute to ∼10% of cellular fatty acid production [36]. As mentioned above, our detection of several “minor” glycolytic end-products excreted by BSF trypanosomes is consistent with most, if not all, early reports [14], [17], [39], [40] and the recent quantitative flux analysis in BSF 427 [44]. The high glycolytic flux combined with the almost exclusive conversion of glucose into pyruvate has probably caused the community to overlook these minor end-products and the metabolic pathways leading to their production, although their biosynthesis may be essential for the parasite, as described here for acetate. For instance, we also observed that LS-BSF excretes alanine from glucose (twice more than acetate, Table 1), as reported before [17]. Alanine is produced from pyruvate by transfer of an amino group coming from various possible amino acid sources. A recent metabolomic analysis showed that glutamate and hydrophobic keto acids accumulate in the BSF spent media, suggesting that glutamine and hydrophobic amino acids are possible substrates of alanine aminotransferase for alanine production [37]. The relevance of alanine production from glycolysis is strengthened by the reported accumulation of hydrophobic keto acids in the plasma and urine of infected rodents [51], [52] and the requirement of alanine aminotransferase activity for in vitro growth of the parasite [53]. Succinate production from glycolysis may also be of importance for biosynthetic pathways in LS-BSF, as exemplified by the requirement of fumarate for de novo synthesis of pyrimidine through the unusual fumarate-dependent dihydroorotate dehydrogenase [54]. Altogether, this highlights the need to reconsider and further investigate the metabolic pathways leading to minor glycolytic end-products, which are still considered negligible compared to the total carbon flux from glucose [44], in order to reveal new essential metabolic pathways that could be targeted to develop new trypanocidal molecules. Beyond glycolysis, other overlooked metabolic pathways of the central metabolism need to be revisited in LS-BSF, as exemplified by the recent observation that RNAi down-regulation of the tricarboxylic acid enzyme succinyl-CoA synthetase induces one of the most spectacular death phenotypes observed in BSF, with 100% cell death within less than 20 h post-induction [55], while this pathway is considered repressed in BSF. | Many protists, including parasitic helminthes, trichomonads and trypanosomatids, produce acetate in their mitochondrion or mitochondrion-like organelle, which is excreted as a main metabolic end-product of their energy metabolism. We have recently demonstrated that mitochondrial production of acetate is essential for fatty acid biosynthesis and ATP production in the procyclic insect form of T. brucei. However, acetate metabolism has not been investigated in the long-slender bloodstream forms of the parasite, the proliferative forms responsible for the sleeping sickness. In contrast to the current view, we showed that the bloodstream forms produce almost as much acetate from glucose than the procyclic parasites. Acetate production from glucose and threonine is synthetically essential for growth and de novo synthesis of fatty acids of the bloodstream trypanosomes. These data highlight that the central metabolism of the bloodstream forms contains unexpected essential pathways, although minor in terms of metabolic flux, which could be targeted for the development of trypanocidal drugs. | Abstract
Introduction
Materials and Methods
Results
Discussion | 2013 | Revisiting the Central Metabolism of the Bloodstream Forms of Trypanosoma brucei: Production of Acetate in the Mitochondrion Is Essential for Parasite Viability | 11,653 | 258 |
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DNA molecules are highly charged semi-flexible polymers that are involved in a wide variety of dynamical processes such as transcription and replication. Characterizing the binding landscapes around DNA molecules is essential to understanding the energetics and kinetics of various biological processes. We present a curvilinear coordinate system that fully takes into account the helical symmetry of a DNA segment. The latter naturally allows to characterize the spatial organization and motions of ligands tracking the minor or major grooves, in a motion reminiscent of sliding. Using this approach, we performed umbrella sampling (US) molecular dynamics (MD) simulations to calculate the three-dimensional potentials of mean force (3D-PMFs) for a Na+ cation and for methyl guanidinium, an arginine analog. The computed PMFs show that, even for small ligands, the free energy landscapes are complex. In general, energy barriers of up to ~5 kcal/mol were measured for removing the ligands from the minor groove, and of ~1. 5 kcal/mol for sliding along the minor groove. We shed light on the way the minor groove geometry, defined mainly by the DNA sequence, shapes the binding landscape around DNA, providing heterogeneous environments for recognition by various ligands. For example, we identified the presence of dissociation points or “exit ramps” that naturally would terminate sliding. We discuss how our findings have important implications for understanding how proteins and ligands associate and slide along DNA.
DNA is a charged, semi-flexible polymer, carrying two elementary negative charges per base-pair. Mobile counterions screen the inter-strand electrostatic repulsion, hence, stabilizing the double helix. Moreover, since DNA molecules are highly rigid, mobile ions also influence DNA’s mechanical properties, for example, favoring bending and substantially influencing DNA’s conformational preferences [1,2]. The ionic atmosphere around DNA is distinctly nonhomogeneous, where different counterions preferentially associate, for example, with the DNA grooves or the strands [3–5]. The helical nature of DNA plays a critical role in determining the distribution of counterions, providing a variety of local environments. For example, the minor groove enhanced electrostatic potential provides binding sites to positively charged ligands. Furthermore, the width of the minor groove, which is highly correlated with its electrostatic potential, is a readout mechanism determined by the sequence dependent geometry of the DNA molecule [6]. The organization and dynamics of condensed ions can also give rise to complex interactions between DNA molecules, that lead, for example, to aggregation [7–10]. Despite substantial prior work on elucidating the counterionic atmosphere around DNA, the topography and roughness of the energy landscape for ligand binding to DNA are still not well understood. However, such binding landscape features are important, since they determine how binding partners, such as counterions, drugs or proteins, move around the DNA chain. In the eukariotic cell nucleus, DNA molecules associate with a variety of counterions, proteins and other molecules. By associating with these molecules, the DNA chain condenses into organized chromatin structures. In this compact state, a twofold challenge needs to be overcome: the DNA-binding proteins need to associate tightly to their targets, while also being able to seek out the specific site in an efficient way among a myriad of non-specific decoys. Even though numerous studies have shed light on the molecular basis of specific protein-DNA complex formation, much less is known regarding the mechanisms allowing DNA-binding proteins to find their specific targets. Experimental [11–13], theoretical [14,15] and computational [16–20] studies have suggested that some of the processes involved in the search procedure are: 1) one-dimensional sliding of the protein along DNA (intramolecular translocation), 2) direct transfer from one DNA segment to another and 3) jumping from one DNA segment by dissociation and re-association [11,21–23]. The first process, protein sliding or translocation, corresponds to a one-dimensional diffusion process where proteins or other ligands first associate non-specifically to DNA molecules, followed by thermally induced motions along the DNA chains. For the term sliding to make sense, the protein needs to move significant distances on a DNA surface (in either direction) before dissociating. This basically necessitates relatively low free energy barriers with respect to the longitudinal motions along DNA and relatively high (or moderate) free energy barriers to prevent dissociation [14,15]. Recent studies allowed visualization of single transcription factors sliding along extended DNA molecules, offering a step towards understanding the one dimensional translocation or diffusion search processes [22,24,25]. These experiments indirectly suggest that the protein’s translocation motion is coupled to the rotation along the DNA’s axis. It is believed that, while sliding, an ensemble of rapidly fluctuating nonspecific protein-DNA interactions allow the ligand to maintain continuous contact with the major groove, minor groove, or both [26,27]. These interactions are presumably mostly electrostatic, however, as the protein finds its DNA target site, they switch to sequence specific interactions, such as hydrogen bonding and van der Waals interactions. For example, insertion of arginine residues into the narrow minor groove, where the electrostatic potential is strongly enhanced, is a widely used mode of non-specific protein-DNA recognition [28,29]. In DNA regulatory processes, which are thought to be highly dynamic, the helical symmetry of the DNA segment plays a critical role in providing a unique physico-chemical environment for ligand binding to a specific DNA sequence. These different environments are widely exploited by proteins and other regulatory molecules in order to tightly regulate transcription and translation. Unlike most previous modeling efforts, the current study focuses on how counterions and charged residues might move along the DNA, where its local helical geometry is emphasized and fully taken into account. Our computational approach uses molecular dynamics (MD) simulations to determine the three dimensional potential of mean force (3D-PMF) of these charged ligands. For this purpose, we developed a helical coordinate system that allowed us to constrain the ligand to track the minor groove. We studied two small charged ligands known to localize to the minor groove: a Na+ ion and methyl-guanidinium, an arginine side chain analog. In prior works, tracking of helical paths was used as reaction coordinate [20]. However, a helical coordinate system tiling the three-dimensional space is introduced in this work for the first time, to the best of our knowledge, . Focusing on two small ligands allowed us to achieve two goals: 1) investigate the accuracy and efficiency of 3D-PMF simulations when using the newly introduced helical coordinates, and, furthermore, 2) map out the fine-scale roughness of the binding free energy landscape of the minor grove. The latter investigation would be difficult to carry out with protein size probes, that would introduce significant disturbances into the minor groove. Fine-grained mapping of the binding free energy landscape provides important mechanistic information about the role of non-specific interactions in protein sliding [30,31], as elaborated below. The computed free energy landscapes directly illustrate the binding sites and energetic barriers that may be encountered by mobile ligands or proteins. The helical coordinate system presented in this work makes it possible to straightforwardly compare the energetics of association and dissociation processes to those of sliding motions along the helical path. Furthermore, we determined the changes in the solvent structure at the interface between the ligand and the DNA molecule, highlighting the rapidly fluctuating nature of DNA-solvent-ligand nonspecific interactions. Overall, our simulation results shed light on the way the roughness of the free-energy landscape in the vicinity of a DNA segment modulates binding and diffusion of ligands.
Using all-atom umbrella sampling (US) MD simulations with the above-mentioned helical coordinate system, we calculated the PMF for a Na+ ion tracking the DNA’s minor groove to probe the roughness of the binding free energy landscape (Fig. 2). Notably, the free-energy landscape varies significantly along one helical turn, indicating a rough free energy surface, with large energy barriers and free energy minima. For example, in most cases, the sites of lowest free-energy are deeply buried in the minor groove (i. e. closer to the DNA’s axis). However, large free energy barriers were also identified (≳ 5 kcal/mol), possibly due to steric hindrance, as the ligands comes closer to the DNA’s axis or backbone. The large free-energy barrier in the first-quadrant (i. e. ϕ in the range from 0 to 90o) are due to the deformation of the DNA which causes a steric clash between the Na+ cation and the backbone between T5 and C6 of the 3’ to 5’ strand (S4 Fig.). On the other hand, at intermediate radii from the DNA’s axis (∼ 12 Å), the energy landscape becomes smoother (Fig. 3. A). Binding sites along the studied region are not necessarily well localized and can extend for several base pairs (Fig. 3. A). For the specific DNA sequence studied in this work, the computed energy landscape suggests that the Na+ ions localize to a 5 base-pair segment. Previous studies have determined that Na+ ions bind to AT rich regions for periods of 50 ns [3]. These binding sites are the main contributors to slowly exchanging Na+ ions between the DNA’s minor groove and the surrounding bulk solvent [33]. Our calculations are in agreement with these findings, but suggest that once buried into the minor groove, Na+ ions may easily slide along the helical path, moving slightly away from the helical axis during sliding, when needed. The radial distribution function (gOW−Na+) of water oxygens around the Na+ ions (Fig. 3. B) shows that the minor groove is able to accommodate hydrated Na+ ions. The Na+ ions probed inside the minor groove maintain most of their first hydration shell (first peak, Fig. 3. B) and are characterized by partial dehydration of the second hydration shell (second peak, Fig. 3. B). This result suggests that the water molecules mediate the interactions between the Na+ cations and the DNA molecule and, consequently, contribute to the localization of the ions to the minor groove. This is consistent with having a shared hydration spine along the minor groove [34], where the water coordination of the Na+ and the DNA molecules allows the movement of the cations along the helical path, without necessarily unbinding and rebinding. We computed the 3D-PMF for the arginine analog, methyl guanidinium, to illustrate the positional free-energy of this ligand in the minor groove. At first sight, the 2D projection of the 3D-PMF (top view, Fig. 4. A) shows that the surface of the minor groove represents an intricate landscape with various local free-energy minima, with free-energy barriers of up to 5 kcal/mol. The 1D-PMFs computed at different angular locations (Fig. 4. B) show that the free-energy barriers to removing the ligand from the minor groove can vary significantly, ranging from 1. 5 to 5 kcal/mol. These free-energy differences can be interpreted as the unbinding energies at different locations. On the other hand, the free-energy profiles of the ligand sliding along the helical path (Fig. 5. A) show energy barriers ranging from 0. 5 to 1. 5 kcal/mol. Additionally, the minimum free energy path along the studied turn (Fig. 5. B) indicates that a small free ligand, such as methyl guanidinium, would localize to a free energy minimum having a depth of 1. 5 kcal/mol. Notably, the free-energy profiles vary significantly at different radii, indicating that, at an intermediate radius (i. e. ∼ 9. 3 Å) the free-energy profile for sliding has the smallest barriers (≲ 0. 8 kcal/mol). Consequently, in general, the energy barriers are smaller in the angular direction than in the radial direction, making sliding the preferred mechanism for moving methyl guanidinium along the DNA chain. Fig. 6. A shows the 2D projections of the electrostatic potential inside the minor groove along one DNA turn, analogous to the 2D projections of the 3D-PMF (Fig. 5. B). The Pearson’s correlation between the free-energy (Fig. 4. A) and potential energy (Fig. 6. A) is r≃0. 91. This result supports the view that the enhanced electrostatic potential in the minor groove is a key determinant of the free-energy landscape. Furthermore, the computed DNA’s minor groove width (Fig. 6. B) shows that, along the studied turn, there are two narrower segments. Qualitatively, the location and depth of the free-energy minima (Fig. 5. B) correlate with the narrow regions of the minor groove (correlation coefficient r≃0. 82, Fig. 6. B) and electrostatic potentials (Fig. 6. A), in agreement with Honig and co-workers [28,35]. However, at some different radii, the free energy profiles (Fig. 5. A) do not correlate well with the widths of the minor groove. This might have important implications for proteins binding and sliding along DNA, as further elaborated below. In addition, in the studied spatial region around the DNA segment, the ranges of the free energy differences and the electrostatic potentials differ from each other, being 5. 3 kcal/mol and 3. 5 kcal/mol, respectively. This range difference is most likely associated with the inaccurate treatment of complex hydration effects in the minor groove when using continuum electrostatic approaches, as well as the importance of non-electrostatic interactions. Given the high charge density of the DNA backbone, it is expected that the binding free-energy (Fig. 5) and electrostatic potential (Fig. 6) landscapes are not completely smooth at large distances (≳ 12 Å). Our simulations indicated that the presence of the methyl-guanidinium ligand did not noticeably affect the DNA’s minor groove geometry. However, it may be possible that the timescale for groove deformations is significantly longer than the simulated time for each of our US windows. As the methyl-guanidinium ligand is removed from the minor groove, the head group shows partial dehydration, as shown by the radial distribution function gOW−cation (Fig. 7). This non-trivial hydration profile suggests that the largest dehydration occurs at an intermediate range of radii between 11 and 12 Å off the DNA’s axis (Fig. 7. B), which coincides with the position of the DNA’s phosphate groups. Consequently, the methyl-guanidinium ligands become partially dehydrated as they get into the minor groove, but once further buried into the minor groove, water molecules relocalize to the first hydration shell. Fig. 7. A also indicates partial dehydration of the second hydration shell for methyl-guanidinium cations buried in the minor groove. These hydration patterns reveal the presence of water mediated interactions [36,37] between the methyl-guanidinium ligand and the DNA molecule. These observations suggest that the free-energy barriers of radial ligand movement not only depend on the electrostatic potential inside the minor groove but also on the sizes and the hydration levels of the ligand. The methyl-guanidinium ligand is capable of forming direct and water-mediated hydrogen bonds with the DNA molecule. We determined that, on average, the ligand forms ∼ 0. 7–1 direct hydrogen bonds with DNA, having an average life time of ∼ 25 ps. The number of hydrogen bonds decreases slightly as the ligand is removed from the minor groove, and is higher at the intermediate radii (i. e. ρ ∼ 9. 3 − 10. 0 Å). Water mediated hydrogen bonds were found to be very short lived, with an average lifetime of ∼ 2. 8 ps. These results corroborate the idea that protein-DNA interactions in the minor groove are non-specific and rapidly fluctuating. In proteins, this may allow the ligand to maintain contact with the DNA molecule without the entropic cost of fixing the conformation of the side chains [27,38]. By computing the 3D-PMFs discussed above, we have characterized the physicochemical environment of the minor groove for two small charged ligands: Na+ and methyl-guanidinium. These maps can be used to shed light on how proteins might slide along the DNA axis while searching for their binding target. For example, the calculated PMFs show that, even for very small ligands, the surface of the minor groove is very rough and that the fine structure of the landscape varies notably at different locations. For example, smoother free energy profiles were obtained at intermediate radii (Figs. 3. A and 5. A). It is expected that small ligands, such as the studied here, will localize to the sites of lowest free energy (Fig. 5. B), even if these binding sites are buried deep inside the minor groove. However, this scenario would change for larger ligands or proteins, where the inner binding sites might not be accessible due to steric or geometrical constraints. For particular systems, such as glycosylases, experimental evidence support the concept that a single ‘wedge residue’ can be used to scan DNA [31]. In the case of sliding proteins, having a smooth free energy landscape would prove advantageous and favor moving along the helical path rather than dissociation and re-association. The methods presented here can be used to study proteins, such as transcription factors, sliding along DNA. Defining a reaction coordinate to track the minor or major grooves, or both, is natural and simple in the helical coordinate systems. Furthermore, using a coordinate system that is congruent with the geometry of DNA allows for straightforward studying of the preferred paths for proteins and other ligands. Additionally, our work corroborates that the pre-existing geometry of the minor groove, determined mainly by the sequence, is a major determinant of the presence of binding sites for positively charged ligands. We identified that the binding sites are located in the narrow AT rich regions, where the electrostatic potential is strongly enhanced. Therefore, in the context of charged ligands bound to the DNA’s minor groove, a sliding mechanism can be described as follows: the roughness of the free energy landscape strongly depends on 1) the degree to which the ligand is buried and 2) the geometry of the minor groove. In particular, if the ligand is constrained to move at the intermediate radii, the height of the free energy barriers are comparable to the thermal fluctuations and, consequently, sliding along DNA helical path, rather than dissociation, is energetically favorable. In the current implementation, it is required that the DNA’s axis is aligned to the z-axis, thus not being applicable in situations that require DNA translation or bending. For applications that require allowing the DNA molecules to translate or bend, our approach can be straightforwardly generalized in such a way that the helical coordinate system is defined locally, based on the instantaneous orientation of the axis of some DNA segment, while at the same time allowing for dynamic adjustment of this orientation during the simulation time course.
We have presented in this work a helical coordinate system, which facilitates studying the physicochemical environments surrounding DNA molecules, allowing natural tracking of DNA’s minor and major grooves. This coordinate system is fully congruent with the helical symmetry of DNA molecules and is general enough for studying the energetics of ligand or protein interactions with various DNA segments in molecular detail. As a key advantage, the helical coordinates can be used to directly obtain 3D-PMFs of ligand association to DNA, in order to determine whether sliding or unbinding is more energetically favorable at each spatial location. The 3D-PMFs can be used to determined the preferred paths of diffusive proteins and other ligands in the DNA’s vicinity. The computed PMFs indicate that the spatially resolved binding landscapes around DNA chain segments are far from smooth, even for small ligands, showing rich fine structures at different positions. We determined that ligands need to overcome free energy barriers of up to ∼ 5 kcal/mol when dissociating. On the other hand, while sliding, ligand encounter free energy barriers of up to ∼ 1. 5 kcal/mol. Consequently, in general, sliding is favored over dissociation. Nevertheless, due to the roughness of the energy landscape and the non-homogeneity of the energy barrier locations, we hypothesize that variations in the geometry of the minor groove can be exploited to create dissociation points or “exit ramps”, to halt sliding. We found that the smallest free energy barriers are encountered by ligands that slide at the intermediate radii from the DNA axis, with the barriers being less than 1. 5 and 0. 8 kcal/mol for Na+ and methyl guanidinium, respectively. We also confirmed prior suggestions that DNA’s free energy landscape is highly modulated by its electrostatic potential, the latter being mostly determined by the sequence-dependent geometry of the minor groove. Additionally, we found that both ligands were only partial dehydrated inside the minor groove and that water-mediated interactions between the ligands and the DNA may play a critical role in favoring sliding over dissociation. Our study provides a general framework for characterizing the free energy landscapes surrounding DNA molecules and for making quantitative predictions of the energetics and molecular basis of different types of diffusive motions in the proximity of DNA chains.
All of our simulations were carried out using the LAMMPS MD software [39], the amber parmbsc0 forcefield for nucleic acids [40], the Joung and Cheatham ions parameters [41] and the TIP3P water model. Starting from a canonical B-form 20-base pair DNA oligomer, [d (CGCGAGGTTTAAACCTCGCG) ]2, we solvated the system in a 50 × 50 × 70 Å box of water with periodic boundary conditions, that were applied throughout all the simulations. In addition, each strand of the DNA molecule was covalently liked to itself over the periodic boundaries of the system [42,43]. This setup allowed us to suppress all deformation modes whose wavelengths were bigger than the system size. Na+ and Cl− ions were added to compensate charge and to represent a 0. 15 M concentration that mimics the physiological environment. The total number of atoms in the system was 15,000. The system was first minimized by 2000 cycles while constraining the DNA heavy atoms followed 1000 steps of unconstrained energy minimization using the steepest descent method. The system was then heated to 300K for 1 ns. This was followed by a round of MD simulations at constant pressure (NPT) for 1 ns using a Langevin piston pressure control to obtain a pressure of 1 atm for density equilibration. After density equilibration, the average size of the box was 48. 4 × 48. 1 × 67. 1 Å. The final round of equilibrations was performed at 300K for 50 ns to ensure the equilibration of the ions. All equilibration and production runs were performed at constant volume, using the average volume measured in the NPT simulations. To maintain a constant temperature, a Langevin thermostat was applied with a damping constant of 0. 2 ps−1. In equilibration and production runs the SHAKE algorithm was applied to constrain all bonds involving hydrogen atoms. Electrostatic interactions were modeled using the Particle Mesh Ewald (PME) method [44] and van der Waals interactions were truncated at 12 Å. The production run time-step was set to 2 fs and frames were saved every 2 ps. Prior works have shown that, for comparable systems (15,000—19,000 atoms), 50 ns are enough to equilibrate the NaCl atmosphere around the DNA molecule [1,5]. During the equilibration, the DNA molecules remained in the B-form conformation. A second model included a charged arginine side chain analog, methyl-guanidinium, bound to DNA. This ligand was modeled using the amber ff99SB* force-field [45,46] for the arginine residue. The initial coordinates of the arginine analog were obtained from the conserved -N terminal structure of the Antennapedia homeodomain (pdb access code 9ANT) [26]. Taking advantage of the helical symmetry of the DNA molecules, we constructed a helical coordinates system (ρ, ϕ, ξ) that specifies the relative position of the ligands with respect to a DNA molecule. The DNA’s axis was aligned to the z-axis, such that the ρ and ϕ coordinates are equivalent in magnitude to the r and θ coordinates used in cylindrical coordinates (r, θ, z). ξ is the family of helical surfaces given by ξ = z−pϕ/2π, with p the pitch of the helical system (Fig. 1. A). It is also useful to define the pitch angle α such that tanα = p/2πρ (Fig. 1. A) and p ¯ =p/2π. This coordinate system was initially introduced by Waldron [47] for applications in electromagnetic theory and takes the helix to be right-handed. In helical coordinates, at ρ = constant, the components of a vector V = (Vρ, Vϕ, Vξ), are expressed in the following way, V ϕ = V θ sec α (1) V ξ = V z − V θ tan α (2) through the corresponding cylindrical components (Vr, Vθ, Vz) (Fig. 1. B). It is important to note that the radial component of the vector Vρ is perpendicular to Vϕ and Vξ, but Vϕ and Vξ coordinates are not orthogonal. Analogously, the transformation between helical and cartesian (x, y, z) coordinates systems is given by: ρ = x 2 + y 2 (3) ϕ = tan − 1 (y / x) (4) ξ = z − p ¯ tan − 1 (y / x) (5) For the helical coordinate system we define a covariant basis (eρ, eϕ, eξ) and a contravariant basis (bρ, bϕ, bξ). The scale factors are given by: hρ = 1, hϕ = ρ/ cos α and hξ = 1. The covariant basis vectors are defined as: e ρ = (cos ϕ, sin ϕ, 0) (6) e ϕ = (− cos α sin ϕ, cos α cos ϕ, sin α) (7) e ξ = (0,0, 1) (8) The (non-unit) contravariant basis vectors are given by: b ρ = (cos ϕ, sin ϕ, 0) (9) b ϕ = (− sin ϕ cos α, cos ϕ cos α, 0) (10) b ξ = (tan α sin ϕ ρ, − tan α cos ϕ ρ, 1) (11) Following the definition of the gradient, ∇ Ψ = 1 h i ∂ Ψ ∂ q i b i (12) we expressed the helical coordinates gradient as, ∇ Ψ = b ρ ∂ ρ Ψ + b ϕ cos α ρ ∂ ϕ Ψ + b ξ ∂ ξ Ψ (13) Note that Eq. 13 becomes the gradient in cylindrical coordinates in the limit α → 0. The helical coordinate system described above was implemented in LAMMPS. We used potential of mean force (PMF) umbrella sampling [48] techniques to characterize the free energy surface governing how counterions and charged residues move along the minor groove. To restrain the ligand’s center of mass, we introduced the potential: Ψ (ρ, ϕ, ξ) = k ρ 2 (ρ − ρ 0) 2 + k ϕ 2 (ρ ϕ − ρ 0 ϕ 0) 2 + k ξ 2 (ξ − ξ 0) 2, (14) where ρ, ϕ and ξ correspond to the coordinates of the center of mass, ρ0, ϕ0 and ξ0 are the target positions and kρ, kϕ and kξ the respective force constants. For this potential, the force (F) acting on the center of mass of the ligands were obtained by using the gradient in helical coordinates (Eq. 13), F = −∇Ψ. For each ligand we computed the PMF for one full turn (ϕ = 2π) around the DNA molecule, equivalent to a rotation along 10. 5 base pairs. From the simulated segment, we computed the binding free-energy map for the mid-section (underlined sequence): [d (CGCGAGGTTTAAACCTCGCG) ]2. The Na+ center of mass was constrained using force constants of kρ = 25 kcal/mol/Å2, kϕ = 2. 5 kcal/mol/ (rad2 ⋅Å2) and kξ = 10 kcal/mol/Å2. Umbrella increments were set to 0. 4 for ρ and 0. 25 rad for ϕ, for ρ ranging from 10 to 15 Å and ϕ ranging from 0 to 2π. The methyl-guanidinium center of mass was constrained using forced constants of kρ = 10 kcal/mol/Å2, kϕ = 1 kcal/mol/ (rad2 ⋅Å2) and kξ = 5 kcal/mol/Å2. Umbrella increments were set to 0. 4 Å for ρ, 0. 25 rad for ϕ for ρ ranging from 8. 6 to 12. 8 Å and ϕ ranging from 0 to 2π. Force constants were chosen to ensure the proper overlap of the histograms (see S2 Fig.) and that energy contributions associated with the restraining potential in each of the three coordinates (ρ, ϕ, ξ) are comparable. For Na+, US production runs were 5 ns long for each window. For methyl-guanidinium the US production runs were 8 ns for each window. The 3D-PMF maps were obtained from the US simulations using the WHAM algorithm [49] extended to three dimensions to account the for the helical coordinate system. The PMF’s were calculated considering only the translational degrees of freedom of the ligand’s center of mass restrained in the helical coordinate system (ρ, ϕ, ξ). The rotational degrees of freedom, as well as the DNA’s and solvent’s degrees of freedom were averaged in the PMF. To test the convergence of the binding free-energy estimates, we repeated the WHAM calculations using only fraction of the US trajectories (S3 Fig.). The free-energy errors were estimated as integrated standard deviations of the mean using the bootstrap algorithm [50]. In each case we generated 2000 bootstraps. For visualization purposes, the 3D-PMF’s were projected into 2D-PMF’s by, at every angular position, obtaining the free energies to a “ribbon” passing through the middle of the minor groove’s solvent accessible volume (S1 Fig.). It is important to note that the helical coordinate system is not periodic. This is, for a probe with coordinates (ρ, ϕ, ξ), after a 2π rotation, the coordinates are (ρ, ϕ, ξ + p). The geometry of the DNA molecule was analyzed using the program Curves [51], which allowed us to obtain the width of the minor groove along the studied turn. The electrostatic potential inside the minor groove was determined from the solutions of the non-linear Poisson-Boltzmann equation using the Adaptive Poisson-Boltzmann (APBS) software [52] at 0. 15 M salt concentration. The atomic partial charges and radii were obtain from the Amber force field [40]. A 129 × 129 × 193 grid was used, with a grid spacing of 1. 5 Å. A dielectric value of ϵ = 2. 00 was assigned to the interior of the DNA molecule (calculate with a 1. 4 Å probe sphere), whereas a dielectric value of ϵ = 78. 54 was assigned to the solvent. Boundary condition values were determined using the Debye-Hückel approximation. To compute the correlation between the binding free-energy and the electrostatic potential we first used interpolation [53] to build a grid with a 0. 13 Å spacing, equivalent to the one from the free-energy maps. The Pearson’s correlation coefficient was computed between the maps with equivalent spacing. We identified all of the methyl-guanidinium and DNA’s minor groove hydrogen bond donors and acceptors and recorded all hydrogen bonds formed within every 2 picosecond frame along each trajectory. A geometric definition of a hydrogen bond was used: two heavy atoms are considered to be bonded if (1) their donor-acceptor distance is less than 3. 5 Å and (2) the acceptor-donor-hydrogen angle is less than 60o. Additionally, we computed the radial distribution function (g (r) ) between the Na+ ions and the oxygen atoms of the water molecules as well as the g (r) between the polar head of the methyl-guanidinum (defined as the center of mass of the NE, CZ, NH1, and NH2 atoms) and the oxygen atoms of the water molecules. For Na+ we computed the g (r) of cations localized to the minor groove via the umbrella potentials and for cations in the bulk in all trajectories. The hydration number of these ligands was determined by integrating, over volume, the water molecules in the first hydration shell, which is equivalent to integrating the first peak in the g (r). | Protein-DNA and ion-DNA interactions are key for many essential biological activities such as DNA condensation, replication, transcription and repair. All these processes require DNA-binding proteins to associate tightly to their specific targets, while also being able to find these sites in an efficient way. To facilitate the search of their DNA targets, DNA-binding proteins often first interact non-specifically with DNA molecules and then slide along the DNA. In this paper, we quantitatively describe the energetics of sliding and binding of two small ligands to the DNA’s minor groove. We show that the minor groove geometry shapes the free-energy landscape surrounding the DNA molecule providing heterogeneous binding environment that can be exploited by DNA-binding proteins in this search for their specific recognition sites. | Abstract
Introduction
Results
Discussion
Materials and Methods | 2015 | DNA Exit Ramps Are Revealed in the Binding Landscapes Obtained from Simulations in Helical Coordinates | 8,018 | 167 |
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Theileria parasites invade and transform bovine leukocytes causing either East Coast fever (T. parva), or tropical theileriosis (T. annulata). Susceptible animals usually die within weeks of infection, but indigenous infected cattle show markedly reduced pathology, suggesting that host genetic factors may cause disease susceptibility. Attenuated live vaccines are widely used to control tropical theileriosis and attenuation is associated with reduced invasiveness of infected macrophages in vitro. Disease pathogenesis is therefore linked to aggressive invasiveness, rather than uncontrolled proliferation of Theileria-infected leukocytes. We show that the invasive potential of Theileria-transformed leukocytes involves TGF-b signalling. Attenuated live vaccine lines express reduced TGF-b2 and their invasiveness can be rescued with exogenous TGF-b. Importantly, infected macrophages from disease susceptible Holstein-Friesian (HF) cows express more TGF-b2 and traverse Matrigel with great efficiency compared to those from disease-resistant Sahiwal cattle. Thus, TGF-b2 levels correlate with disease susceptibility. Using fluorescence and time-lapse video microscopy we show that Theileria-infected, disease-susceptible HF macrophages exhibit increased actin dynamics in their lamellipodia and podosomal adhesion structures and develop more membrane blebs. TGF-b2-associated invasiveness in HF macrophages has a transcription-independent element that relies on cytoskeleton remodelling via activation of Rho kinase (ROCK). We propose that a TGF-b autocrine loop confers an amoeboid-like motility on Theileria-infected leukocytes, which combines with MMP-dependent motility to drive invasiveness and virulence.
Cellular transformation is a complex, multi-step process and leukocyte transformation by Theileria is no exception, as parasite infection activates several different leukocyte-signalling pathways, the combination of which leads to full host cell transformation [1]. However, Theileria-induced leukocyte transformation is unusual in that it is rapid and appears to be entirely reversible with the host cell losing its transformed phenotype upon drug-induced parasite death [2]. Just like most cancer cells however, Theileria-induced pathogenesis (virulence) is associated with the invasive capacity of transformed leukocytes, which is lost upon attenuation of vaccine lines [3]. Attenuation of virulence has been ascribed to decreased matrix-metallo-proteinase-9 (MMP9) production and loss of AP-1 transcriptional activity [4]. Consistently, functional inactivation of AP-1 resulted in reduced tumour formation, when infected and transformed B cells were injected into Rag2gC mice [5]. Host leukocyte tropism differs with T. parva infecting all subpopulations of lymphocytes whereas T. annulata infects monocytes/macrophages, dendritic cells and B lymphocytes [1]. Despite this, the diseases they cause (called tropical theileriosis with T. annulata infection and East Coast fever with T. parva infection) are both severe, as susceptible animals usually die within three weeks of infection. The geographical distribution of their respective tick vector species determines areas where disease is widespread. Tropical theileriosis affects over 250 million animals and extends over the Mediterranean basin, the Middle East, India and the Far East, whereas East Coast fever is prevalent in eastern, central and southern Africa. It is noteworthy that in endemic areas indigenous breeds of cattle are more resistant to disease. For example, when Bos indicus Sahiwals are experimentally infected with T. annulata they exhibit fewer clinical symptoms and recover from a parasite dose that is fatal in the European Holstein-Friesian (HF) B. taurus breed [6]–[7]. Theileria-infected leukocytes are capable of producing IL-1 and IL-6 [8], as well as GM-CSF [9] and TNF [10]. Nonetheless, no differences in the level of expression of the pro-inflammatory cytokines TNF, IL-1b, or IL-6 were detected between disease-resistant Sahiwal- versus HF-infected macrophages [11]. Some additional inherent genetic trait of Sahiwal animals must therefore underlie their disease-resistance. Although transcriptome analysis of 3–5 times passaged Sahiwal and HF macrophages following infection with T. annulata revealed significant breed differences in both the resting and infected gene expression profiles, no clear candidate genetic trait was revealed [12]. Transforming growth factor beta (TGF-b) is a family of cytokines and both TGF-b1 and TGF-b2 can bind with high affinity to the TGF-b type II receptor (TGF-RII) leading to the recruitment of TGF-RI. The constitutive kinase activity of TGF-RII phosphorylates and activates TGF-RI, which in turns recruits and activates Smad2 and Smad3, which bind Smad4, and the whole complex translocates to the nucleus and induces the transcription of target genes [13]. The TGF-b signalling pathway can be negatively regulated [14] and an increasing number of non-Smad-mediated TGF-b signalling pathways have been described [15]. TGF-b can also regulate cytoskeleton dynamics via transcription-dependent and transcription-independent processes [16]. It is likely that all these different pathways contribute in different ways to the pleiotropic effects of TGF-b (see http: //www. cell. com/enhanced/taylor). TGF-b can exert opposite effects on cell growth: in most non-transformed cells TGF-b is usually growth inhibitory, but it can increase motility of certain mesenchymal cells and monocytes, but however, at some point in the transformation process TGF-b becomes pro-metastatic [17]–[18], for example in ovarian cancer [19]. We show here that TGF-b plays a role in infected host leukocyte invasiveness. Importantly, the high level of TGF-b2 production by Theileria-infected HF-transformed macrophages renders them more invasive than those of disease-resistant Sahiwal animals. In addition, vaccination against tropical theileriosis uses live attenuated T. annulata-infected macrophages and attenuation leads to the loss of both TGF-b2 transcription and alteration in the expression of a set of TGF-b-target genes, and a drop in TGF-b-mediated invasion. Thus, Theileria-dependent TGF-b2 induction is a virulence trait that underscores susceptibility to tropical theileriosis.
As Theileria-transformed leukocytes are known to secrete a number of different cytokines we examined whether infection by T. annulata sporozites of the same parasite strain (Hissar) could induce TGF-b in macrophages 72h post-invasion, as described [12]. Prior to infection both Sahiwal and HF macrophages produced low levels of TGF-b transcript with slightly higher amounts of TGF-b1 (Fig. 1A). Interestingly, Theileria infection induces preferentially TGF-b2 in both Sahiwal and HF macrophages, and importantly, the induction after 72h is much greater in disease-susceptible HF cells. We next examined the levels of TGF-b transcripts in a series of T. annulata-transformed cell lines derived from Sahiwal and HF animals. Again, TGF-b1 and TGF-b2 mRNA could be detected in all 10 transformed cell lines (Fig. 1B). Similar to freshly invaded cells the relative mRNA levels of TGF-b1 did not differ significantly across the T. annulata infected cell lines and there was no evidence of a breed-specific difference in TGF-b1 expression (Fig. 1B grey bars, p = 0. 710). In contrast, the relative TGF-b2 mRNA levels exhibit statistically significant differences (Fig. 1B black bars, p<0. 001), with TGF-b2 mRNA levels being higher in HF cell-lines. Additional qRT-PCR experiments revealed that the levels of expression of TGF-RI, TGF-RII and TGF-RIII were equivalent in HF versus Sahiwal T. annulata-infected cell lines (data not shown). Thus, disease susceptibility correlates to the level of TGF-b2 transcripts that are expressed 7-fold (p<0. 001) more by T. annulata-transformed macrophages of HF origin. In T. parva-transformed B cells a TGF-b-mediated signalling pathway is active and invasion is partially TGF-b-dependent (Fig. S1). We therefore compared the invasive capacity of T. annulata-transformed HF versus Sahiwal macrophages (Figure 2). We found that disease-susceptible HF macrophages displayed 30% greater capacity (p<0. 005) to traverse Matrigel than infected Sahiwal macrophages and that traversal is again TGF-b-dependent (Fig. 2A). The invasive capacity of the H7 cell line was reduced to levels equivalent to S3 cells upon treatment with the TGF-R inhibitor (Fig. 2A) and conversely, when S3 cells were stimulated with conditioned medium from H7 cultures, S3 cells displayed increased invasiveness (Fig. 2B). Moreover, the reduced invasive capacity of disease-resistant S3 macrophages could be restored to above virulent levels by addition of either TGF-b1, or TGF-b2 (Fig. 2C), demonstrating that the TGF-b signalling pathways are intact in these cells. Theileria infection therefore preferentially induces up-regulation of TGF-b2 and increased invasiveness of transformed leukocytes. T. annulata-infected cell lines can be attenuated for virulence by multiple in vitro passages to generate live vaccines that are used to protect against tropical theileriosis [3]. The molecular basis of attenuation is not known, but our above observations on preferential TGF-b2 induction and augmented host cell invasiveness suggest that attenuation might be lead to reduced TGF-b2 transcription and TGF-b2-mediated invasion. To directly test this prediction we examined the Ode vaccine line derived from an infected HF cow in India [20] and estimated the level of TGF-b2 transcripts and TGF-b-target gene transcription in virulent (early passage) and attenuated (late passage) infected macrophages (Figure 3). As predicted, attenuation leads to a significant decrease in the amount of TGF-b2 message and surprisingly, a slight increase in TGF-b1 transcripts (Fig. 3A). This strongly suggests that upon attenuation the parasite' s ability to induce host cell TGF-b2 has been impaired. Reduced levels of TGF-b2 should lead to an alteration in the transcription profiles of known TGF-b-target genes and to see if this is indeed the case, we performed microarray analyses and hierarchical clustering of transcript levels. The microarray representing 26,751 bovine genes included 1,158 targets of TGF-b (http: //www. netpath. org/) and 76 of these genes were identified as differentially expressed upon attenuation. The heat-map, where low gene expression level is depicted as blue, intermediate as yellow and high expression as red, is present in Fig. 3B. Among the down-regulated TGF-target genes, five were chosen at random and their expression verified by qRT-PCR using mRNA from early and late passage Ode (Fig. 3C). In each case their transcription was reduced upon attenuation and could be restored by adding exogenous recombinant TGF-b2. Consistently, their expression was high in disease-susceptible infected HF macrophages that produce more TGF-b2 (see Fig. 1) and low in Sahiwal macrophages, but could be augmented by exogenous TGF-b2 stimulation (Fig. S2). Attenuation of virulence therefore, leads to ablation of TGF-b2 signalling and an alteration in the profile of expression of a set of TGF-target genes. The observation that early passage Ode cells express higher levels of TGF-b2 message and have altered expression of 76 TGF-b-target genes led us to compare early with late passage Ode and examine the contribution of TGF-b to their invasive capacity (Figure 4). As previously described [4], attenuation of Ode leads to a significant drop in invasive capacity (***p<0. 005) and receptor blockade by SB431542 gives an estimate (***p<0. 005) of the contribution of TGF-b to early passage Ode virulence (Fig. 4A). The potential contribution of TGF-b to virulence has been ablated by attenuation, since the invasive capacity late passage Ode is insensitive to receptor blockade (Fig. 4A, right). When conditioned medium from early passage Ode is given to late passage Ode there is a marked (**p<0. 05) regain in invasion (Fig. 4B). Virulent Ode therefore, secretes factors into the medium that contribute to invasiveness, one of which is clearly TGF-b2, and this capacity is lost upon attenuation. The partial inhibition of invasion by early passage Ode by SB431542 might also suggest that although virulent following 65/70 in vitro passages some attenuation of TGF-b2 induction might be occurring. We next studied whether the TGF-b-mediated invasion programme might have a consequence on cellular adhesion and invasion structures such as lamellipodia, podosomes and membrane blebs. We first investigated by time-lapse video microscopy lamellipodia morphology of T. annulata-infected macrophages cultured without (control), or with SB431542 (Fig. S3 and Movies S1 and S2) and found that the size of lamellipodia (shown boxed) decreased upon SB431542 treatment (Fig. S3A). Visualisation of the actin cytoskeleton with Texas red-labelled phalloidin showed that decreased lamellipodia size correlated with reduced actin dynamics (Fig. S3B and C) and suggested that TGF-controls cortical actin dynamics in infected macrophages. We next compared the basal and central cortical actin cytoskeleton of S3 and H7 cells cultured on a gelatin/fibronectin matrix, which facilitates adhesion of these cells. In S3 cells, we observed only small podosomal adhesion structures that were rarely clustered and no actin-rich membrane blebs (Fig. 5A). In contrast, in H7 cells podosomal adhesion structures were markedly enlarged and clustered and the majority of cells displayed actin-rich membrane blebs. Membrane blebbing was confirmed by live-cell imaging (Fig. S4A), which highlights the dynamics of bleb formation. Individual blebs expand within one to three seconds and persist for approximately 30–120 seconds, which is a time frame typically observed in bleb formation and retraction [21]. Reducing the serum concentration from 10% to 0. 5% (starvation) resulted in a significant decrease in the number of membrane blebs (Fig. 5B and C). Membrane blebbing in starved cells was rescued by the exogenous addition of TGF-b2. The TGF-b-induced membrane blebs were blocked by the Rho-kinase (ROCK) inhibitor H-1152 and in the presence of serum the formation of actin-rich membrane blebs was significantly reduced after treatment with the TGF-R inhibitor, but completely blocked in the presence of H-1152 (Fig. 5C). Thus, one consequence of increased TGF-b2 production is increased cortical actin dynamics, which likely gives rise to enhanced podosomal adhesion structures (invadosomes) and membrane blebs in macrophages derived from disease susceptible HF cattle. We next investigated the functional significance of membrane blebs for cell motility in 3-D matrices. In the low rigidity fibrillar collagen or high-density Matrigel matrices, H7 macrophages acquired an amoeboid pattern of motility with characteristic polarized formation of membrane blebs (Fig. 5D and Fig. S4B and C). Membrane bleb formation required ROCK activity and inhibition of ROCK prevents local contractibility, polarized bleb formation and forward movement of the cell. Taken together, these data show that exposure of H7 macrophages to TGF-b2, results in ROCK-dependent membrane blebbing that drives motility in 3-D matrices.
We have shown here that Theileria-induced leukocyte transformation results in the constitutive induction of a TGF-b autocrine loop that augments the invasive potential of infected leukocytes. We could find no evidence for a contribution of TGF-b signalling to host cell survival, or proliferation (data not shown), implying that leukocyte infection by Theileria essentially confers on TGF-b a pro-metastatic role. Smads and p53 are known to associate and collaborate in the induction of a subset of TGF-b target genes [22]. Recently, p53 has been described as being sequestered in the cytosol of Theileria-transformed leukocytes, as part of a parasite-induced survival mechanism [23]. Although not addressed by Haller et al it is possible that cytosol located p53 might ablate nuclear translocation of Smads, thus counteracting the anti-proliferative affect of TGF-b in Theileria-transformed leukocytes? Importantly, comparison of disease-susceptible HF transformed macrophages to disease-resistant Sahiwal ones, showed that the degree to which Theileria (the same parasite strain) induces TGF-b2 influences the invasive potential of the infected and transformed host cell. The likelihood of developing a life-threatening cancer-like disease therefore appears to be due in part to the inherent genetic propensity of HF macrophages to produce high levels of TGF-b2 upon infection that might render the transformed macrophages more invasive. T. annulata-transformation of HF macrophages leads to the induction of higher amounts of TGF-b2 the levels of induced TGF-b1 mRNA being the same as in Sahiwal macrophages. As TGF-RI and -RII and -RIII [24] are expressed to the same extent in the two types of macrophages (data not shown) it suggests that only the amount of TGF-b2 is crucial. The predisposition of Theileria transformation to induce TGF-b2 over TGF-b1 in HF versus Sahiwal macrophages implies that there could be disease-associated sensitivity to infection linked to TGF-b2 over-production. Species-specific promoter differences, or some other unknown breed difference may explain the greater propensity of Theileria to induce TGF-b2 over TGF-b1 transcripts in HF compared to Sahiwal cattle. However, promoter sequence differences seem unlikely to underlie Theileria' s ability to induce TGF-b2 over TGF-b1 transcripts, or explain the drop in TGF-b2 levels upon attenuation of the Ode vaccine line as here, both virulent and attenuated infected macrophages are of HF origin [20]. Loss of virulence of the Ode vaccine line upon long-term in vitro passage is clearly associated with a decrease in TGF-b2 transcripts and it would appear that the parasite' s ability to specifically activate host cell transcription of TGF-b2 is impaired and one possibility is that attenuation is associated with altered epigenetic regulation of TGF-b2 promoter activity. Microarray analyses indicate that upon attenuation of virulence, not only do TGF-b2 levels drop, but also 76 TGF-b-target genes display altered transcription. It would appear then that preferential TGF-b2 induction following Theileria infection initiates a host cell genetic programme that contributes to more aggressive invasiveness of transformed HF macrophages. We believe the same TGF-b2-initiated genetic programme also contributes to the invasiveness, albeit reduced, of disease-resistant Sahiwal macrophages, as Theileria infection also preferentially induces TGF-b2, just to a lesser extent. We have used fluorescence and time-lapse video microscopy to examine the morphology of Theileria-infected Sahiwal and HF infected macrophages and the effect of TGF-b and Rho kinase (ROCK) on actin dynamics and lamellipodia formation. Theileria infected, disease-susceptible HF macrophages show increased actin dynamics in their lamellipodia and podosomal adhesion structures and a remarkable propensity to develop membrane blebs. Figure 5D shows the dynamic behaviour of infected cells embedded in 3-D matrices (see also Fig. S3 and movies S3 and S4), where either fibrillar collagen, or matrigel was used giving two 3-D matrices of low (collagen) and high (matrigel) rigidity. Membrane blebbing of motile H7 cells occurs in both matrices in a polarized fashion at the leading edge, clearly suggesting that membrane blebbing is required for infected cell motility in 3-D. Movie S3 shows bleb-driven membrane protrusions, which results in forward movement of the cell (see also kymographs of movie S3, Fig. 5D). Moreover, ROCK activity is required, because inhibition of ROCK with H-1152 impairs polarized bleb formation and forward movement in fibrillar collagen and matrigel. Spatio-temporal control of Rho-ROCK activity is also required for cell polarization and lamellipodia formation in 2-D [25]. Since TGF-b acts upstream of Rho-ROCK in infected cells, we would therefore predict that spatio-temporal activation of Rho-ROCK – controlled by TGF-b signalling – is required for lamellipodia formation as well. Combined, increased bleb and lamellipodia formation could give rise to more invadosomes on infected virulent macrophages in a similar manner to TGF-b-mediated increased adhesion of immortalised hepatocyte cell lines [26]. We showed that augmented invasiveness by TGF-b2 in disease-susceptible HF macrophages has a transcription-independent element that relies on cytoskeleton remodelling via activation of Rho and its downstream target ROCK [27]–[28]. Given the important role played by ROCK in increased blebbing of infected host cells and the recent description that Rho/ROCK signals amoeboid-like motility [29], it is tempting to speculate that the TGF-b autocrine loop confers on Theileria-infected leukocytes an amoeboid-like motility that contributes to invasiveness and makes them more virulent. However, since prolonged TGF-b stimulation can result in decreased Rho activity due to the action of p190RhoGap [30], Theileria infected cells must have developed a mechanism to balance TGF-b-induced RhoGAP activities. It is possible that the parasite might also regulate the expression, activity or localization of Rho-family GEFs, as the Rho activator GEF-H1/Lfc has been shown to be a TGF-b1 target gene [31] and an analogous mechanism involving TGF-b2 might be exploited by Theileria parasites? Alternatively, the parasite could function by excluding negative regulators of Rho from specific subcellular compartments, analogous to the exclusion of the RhoGAP Myo9b from lamellipodia of macrophages [25]. Whatever the underlying mechanism of inducing TGF-b2 levels in Theileria-infected leukocytes, its induction and the genetic programme it initiates is clearly correlated with the invasive phenotype of transformed macrophages of disease-sensitive hosts. This implies that overall invasiveness of Theileria-transformed leukocytes is made up of amoeboid (TGF-b- & ROCK-dependent) and mixed amoeboid/proteolytic (MMP-dependent [4]) motility; reviewed in [32]. These Theileria-based observations also suggest that in some cases the propensity of human leukaemia patients to develop life-threatening cancer could be due to the inherent genetic predisposition of their tumours to produce high levels of TGF-b2, rather than TGF-b1, and the genetic programme this initiates on promoting an additional amoeboid-like invasive phenotype of their tumours.
TpMD409. B2 is a T. parva Muguga-infected B-cell clone (B2) and its B-cell characteristics have been previously confirmed [33]. The cell lines S1–S5 and H7–H10 have been described previously [6]. In vitro infection of uninfected S and H cells by Theileria sporozoites was done as described [12]. The characterisation of the Ode vaccine line has been reported [20] and in this study virulent/early Ode corresponds to passage 65–70 and attenuated to passage 318–322. It is possible that passages 65–70 have already become slightly attenuated. All cultures were maintained in RPMI-1640 medium supplemented with 10% foetal calf serum (FCS) and 50 uM b-mercaptoethanol. Cell cultures were passaged 24h before harvesting to maintain the cells in the exponential growth phase. The TGF-bRI/ALK5 inhibitor SB431542 (Sigma #S4317) was added at 10uM for 18h. The Rho kinase (ROCK) inhibitor H-1152 (Alexis Biochemicals, #ALX-270-423) was added at 10uM. Recombinant bovine TGF-b1 and TGF-b2 (rboTGF-b1 and rboTGF-b2; both NIBSC, Potters Bar. UK) were added in the culture media at 10ng/ml and incubated for different times (15 min or 30 min). All transfections were carried out by electroporation as previously described [34]. The CAGA-luc (the Smad 3/4 binding element-luciferase construct) was transiently transfected into B2 cells with the inhibitory Smad7 plasmid (Flag-Smad7-pcdef3), or an empty vector (pcdef3). The major late minimal promoter (MLP - a minimal promoter consisting of the TATA box and the initiator sequence of the adenovirus major late promoter) was cloned into pGL3 (Promega) to generate the MLP-luc plasmid that was used as minimal promoter negative control [35]–[36]. Efficiencies of transfections were normalized to renilla activity by co-transfection of a pRL-TK renilla reporter plasmid (Promega #E6241). Luciferase assay was performed 24h after transfection using the Dual-Luciferase Reporter Assay System (Promega, #E1980) in a microplate luminometer (Centro LB 960, Berthold). Relative luminescence was represented as the ratio firefly/renilla luminescence. Nuclear extracts of from T. parva-infected (B2) cells were prepared as described [37]. 20ug of proteins were separated in a denaturing 8% SDS-PAGE gel and electro-transferred onto a nitrocellulose membrane (Scheicher and Schuell). Antibodies used in immuno-blotting were as follows: anti-phospho-Smad2 (Cell Signaling #3101), anti-Smad2 (BioVision, #3462-100), anti-PARP (Clone C2-10, Pharmingen #556362). Total RNA was isolated from each of the T. annulata infected cell lines using the RNeasy mini kit (Qiagen) according to the manufacturer' s instructions. The quality and quantity of the resulting RNA was determined using a Nanodrop spectrophotometer and gel electrophoresis and for microarray screens on an Agilent 2100 Bioanalyser (Agilent Technologies). mRNA was reverse transcribed to first-strand cDNA and the relative levels of each transcript were quantified by real-time PCR using SYBR Green detection. The detection of a single product was verified by dissociation curve analysis and relative quantities of mRNA calculated using the method described by [38]. GAPDH, HPRT1 and C13orf8 relative quantities were used to normalise mRNA levels. For list of primers used, see Table 1. Host gene expression was investigated using a custom-designed microarray (Roche NimbleGen Inc. , Madison, WI), which represented every bovine RNA reference sequence currently deposited in the NCBI database (n = 26,751). Each gene was represented by two identical sets of five 60-mer-oligonucleotide probes that were isothermal with respect to melting temperature. cDNA was generated from 10 ug total RNA using oligo (dT) primer and tagged with 3′-Cy3 dye and labelled cDNA was hybridised to the array. Gene expression values were calculated from an RMA-normalised dataset [39] and differentially expressed genes were identified using Rank Product Analysis [40]. Genes were defined as differentially expressed using the criteria of a false discovery rate of less than 5% and a fold change of greater than two. Selected gene sets were subjected to hierarchical clustering based on Euclidean distance between expression values and the results were illustrated using a heat-map (ArrayStar3, DNASTAR Inc. , Madison, WI). The invasive capacity of the bovine leukocytes was assessed using in vitro Matrigel migration chambers, as described [5]. After 26h of incubation at 37°C, filters were washed twice in PBS and the Matrigel was eliminated. In some cases, during this 12h period cells were also incubated with the TGF-b inhibitor SB431542 (10uM), or with recombinant TGF-b protein (10ng/ml). When added TGF-b was maintained in the top chamber, meaning that overall cells were incubated with TGF-b for 36h. Cells were then counted under the microscope (40× objective) to obtain a statistically significant mean number of cells per field (at least 10 fields per filter). The experiment was performed at least in triplicate. Time-lapse imaging using video microscopy was performed with cells growing on glass bottom culture dishes (Willco Wells, the Netherlands) using a Nikon Eclipse TE2000-U inverted microscope equipped with a climate-controlled chamber. Data acquisition and image processing was performed using NIS software of Nikon Instruments. DIC images were acquired in intervals ranging from 0. 5 msec to 1 min for 30 min and assembled in movies; acceleration of movies is approximately 600-fold. Kymographs were acquired along a one pixel wide line using NIS software. A 40× Plan Achromat Objective of Nikon was used for longworking distance image acquisition in Matrigel. Theileria-infected macrophages were seeded onto glass coverslips, or glass bottom culture dishes (Willco Wells, the Netherlands) and maintained in growth medium for 48h without or with 10uM SB431542 (SIGMA). SB431542 was replenished after 24h. Cells were either processed for live cell imaging or fixed in 3. 5% formaldehyde, 15 min. Actin cytoskeletons of fixed and Triton X-100 permeabilized cells were visualized with Texas red-labelled phalloidin. Lamellipodia area and integrated fluorescence intensities in lamellipodia were determined using photoshop CS3 software. Glass coverslips were coated with 0. 1% poly-L-lysine for 15 min at room temperature and then fixed with 0. 5% glutharaldehyde for 15min. After 3 washes with PBS, coverslips were inverted onto droplet containing 2mg/ml (0. 2%) gelatin (MERCK) in H2O for 15min. After 3 washes with PBS, coverslips were inverted onto droplet containing 25ug/ml bovine plasma fibronectin (SIGMA) in PBS and then incubated 1h at room temperature. Coverslips were then transferred into 24 well plate washed once with PBS and kept in PBS until seeding of 50,000 cells per well. After 18h cells were fixed in 3. 5% formaldehyde, 15min. Embedding in collagen: 3×105 cells in 50ul medium were added to a mixture of 68µl sodium bicarbonate (7. 5%, SIGMA), 240ul 10× PBS and 2ml PureCol (3mg/ml, Inamed). The resulting gelatin solution with the concentration of 2. 4mg gelatin/ml was distributed into live-cell imaging wells or dishes and transferred to 37°C for collagen polymerization. Embedding in Matrigel: 1×105 cells in medium were mixed on ice with 250ul growth factor reduced Matrigel (BD biosciences) and was distributed into live-cell imaging wells or dishes and transferred to 37°C for polymerization. | Theileria annulata causes tropical theileriosis that is endemic in cattle in North Africa, the Middle East, India and China. T. parva causes East Coast fever that is prevalent in East and Southern Africa. In endemic countries indigenous cattle are more resistant to pathology, but produce little meat and milk and attempts to improve output by importing European and American breeds have failed due to a high susceptibility to these diseases that are often rapidly fatal. We examined T. annulata-transformed macrophages isolated from disease resistant Sahiwal compared to disease-susceptible Holstein-Friesian (HF) cattle, for their capacity to traverse synthetic extra-cellular matrix in vitro. The invasive capacity of all transformed macrophages was TGF-b dependent, but those of disease-susceptible HF animals invaded better i. e. they were more aggressive. The greater invasive capacity of HF transformed macrophages matched their increased production of TGF-b2, since levels of TGF-b1, and all three TGF-b receptors, were the same as in transformed macrophages isolated from disease-resistant Sahiwal animals. TGF-b2 production therefore likely renders Theileria-transformed leukocytes more pathogenic and consistently, in a live attenuated line used to vaccinate against tropical theileriosis transcripts of TGF-b2 and those of a significant number of TGF-target genes drop and consequently, TGF-b-mediated invasiveness decreases. | Abstract
Introduction
Results
Discussion
Materials and Methods | infectious diseases/protozoal infections
cell biology/extra-cellular matrix
cell biology/leukocyte signaling and gene expression | 2010 | TGF-b2 Induction Regulates Invasiveness of Theileria-Transformed Leukocytes and Disease Susceptibility | 8,155 | 350 |
No-go Decay (NGD) is a process that has evolved to deal with stalled ribosomes resulting from structural blocks or aberrant mRNAs. The process is distinguished by an endonucleolytic cleavage prior to degradation of the transcript. While many of the details of the pathway have been described, the identity of the endonuclease remains unknown. Here we identify residues of the small subunit ribosomal protein Rps3 that are important for NGD by affecting the cleavage reaction. Mutation of residues within the ribosomal entry tunnel that contact the incoming mRNA leads to significantly reduced accumulation of cleavage products, independent of the type of stall sequence, and renders cells sensitive to damaging agents thought to trigger NGD. These phenotypes are distinct from those seen in combination with other NGD factors, suggesting a separate role for Rps3 in NGD. Conversely, ribosomal proteins ubiquitination is not affected by rps3 mutations, indicating that upstream ribosome quality control (RQC) events are not dependent on these residues. Together, these results suggest that Rps3 is important for quality control on the ribosome and strongly supports the notion that the ribosome itself plays a central role in the endonucleolytic cleavage reaction during NGD.
The elongation phase of translation is an imperfect process, during which the ribosome moves with irregular speed along the mRNA template [1]. By and large the elongation speed is determined by sequence and structural features of the coding sequence. For instance, the identity of the A-site codon is known to have a drastic effect on the rate of protein synthesis depending on the availability of its partner tRNA and the nature of the codon-anticodon base-pairing interaction [2,3]. Furthermore, the chemical characteristics of the locally-encoded amino acids have been shown to regulate the rate of protein synthesis based on the manner they interact with the exit tunnel of the ribosome [4]. mRNAs are also known to harbor local secondary structures that can slow down the ribosome as it unwinds them [5,6]. Regardless of the underlying mechanism, the fluctuating rate of protein synthesis along an mRNA molecule appears to serve important biological functions such as promoting appropriate co-translational protein folding and ensuring that the encoded protein is targeted to the correct destination in the cell [7–12]. In contrast to this “programmed” regulation of ribosome traffic, the ribosome often encounters unwanted obstacles that severely hinder its progression and in some cases stall protein synthesis all together [13,14]. Most of these impediments are typically associated with defects in the mRNA, including stable secondary structures, stretches of rare and inhibitory codons, as well as truncations and chemical damage [3,15–17], [18]. Because multiple ribosomes are typically translating a single mRNA at any given point, one stalled ribosome is likely to impede the progression of multiple upstream ribosomes. As a result, if left unresolved, these stalling events have the potential to severely reduce cellular fitness. Notably, the stalling of the ribosome itself is not such a detriment to the cell as is the loss of valuable ribosomes from the translating net pool [13,14]. In eukaryotes, the evolutionary solution to this predicament was No-Go Decay (NGD) [15] as a means to dissociate stalled ribosomes [19–21]. It is thought that over time, this mechanism was expanded on to include mRNA surveillance to dispose of the aberrant mRNA. In particular, the mRNA undergoes an endonucleolytic cleavage upstream of the stall site. The resulting deadenylated 5’-end and uncapped 3’-end pieces are then rapidly degraded by the exosome and Xrn1, respectively [3,15–17]. Initial studies on NGD in yeast focused on the two factors Dom34 (Pelota in mammals) and Hbs1 [15,22,23]. These factors are homologs of the termination factors eRF1 and eRF3, respectively. Early reports of NGD hinted at a role for the factors in mediating the endonucleolytic cleavage of the mRNA near the stalled ribosome [15,24]. However, later studies by the same group and others showed the cleavage to take place in the absence of the factors [22] leaving the question of the role of the factors in the process unanswered. Interestingly prior to the discovery of NGD, genetics studies suggested that Dom34 and Hbs1 are important in maintaining ribosome homeostasis of the cell [25]. To this end, both factors become essential or near-essential when ribosomes are depleted either by knocking down certain ribosomal proteins or under conditions when ribosomes are sequestered [25–27]. These observations are consistent with biochemical studies using a yeast translation reconstituted system, which showed the factors to be responsible for dissociating ribosomes into their respective subunits [18]. This splitting activity of Dom34-Hbs1 was also found to be much more efficient in the presence of Rli1 (ABCE1 in mammals) [20,21]. In vivo data also supported this model for the role of the three factors in dissociating ribosomes [16]. Hence, this rescuing/recycling activity of these factors rationalizes the effect of their deletion on ribosome availability, especially under stress conditions. In addition to ribosome rescue and degradation of the aberrant RNA, NGD is closely linked to a newly discovered protein-quality-control process termed ribosome quality control (RQC). This process is responsible for degrading the incomplete nascent protein resulting from stalled translation [28–34]. RQC proceeds after the splitting action of Dom34-Hbs1-Rli1, which results in a peptidyl-tRNA-associated large-ribosome subunit. This atypical form of the 60S subunit is recognized by the E3 ligase Ltn1 (Listerin in mammals) alongside Rqc2 (formerly Tae2) [30,33,35]. Ltn1 ligates ubiquitin chains to the nascent peptide as it is attached to the tRNA on the large subunit. The ubiquitinated nascent peptide is then extracted and delivered to the proteasome for degradation through the action of Rqc2 and Cdc48 (and its adaptor proteins Ufd1 and Npl4). Two additional factors, the ribosome-associated Asc1 and the E3 ligase Hel2 (Rack1 and Znf598 in mammals, respectively), also appear to be important for proper RQC function. Both factors are important for ribosomal protein ubiquitination and appear to play a role during stalling [36,37]. In particular, deletion of either factor results in increased readthrough of stall sequences [38,39]. How regulatory ribosomal protein ubiquitination interconnects with RQC and NGD is currently poorly understood. Even though the consequences of ribosome stalling in eukaryotes was initially described in the context of its impact on mRNA steady state levels [15], as detailed above we know far more about its entanglement with ribosome rescue and quality control of the associated nascent peptide. More specifically, degradation of the mRNA is initiated by endonucleolytic cleavage, but the identity of the endonuclease remains elusive. This in turn has precluded further critical mechanistic dissections of NGD. Some of these outstanding important questions are: 1) How does the endonuclease recognize stalled ribosomes? 2) Is it associated with the ribosome? 3) Does it have a specificity for certain mRNAs 4) How is its function activated? 5) Can NGD be used to regulate gene expression? Work from our group recently provided some clues about the cleavage reaction. Using reporters and genetic manipulation of yeast we showed that the physical act of ribosome collision is important for initiating the process of RNA degradation and ribosome rescue during no-go decay (NGD) [40]. High-resolution mapping of the cleavage products also provided some important clues about the potential role of the ribosome in the reaction. Namely, cleavage appears to take place well upstream of the lead stalled ribosome with the closest most prominent one being ~45 nt upstream of the stall site. As ribosomes are likely to be stacked on the mRNA, this suggested the possibility that the cleavage is taking place inside the ribosome [18,41]. Multiple regions of the ribosome make intimate contact with the mRNA. Most noteworthy among these is the mRNA entry tunnel, which encompasses residues of the ribosomal proteins Rps3/uS3 and Rps2/uS5 [42]. In eukaryotes additional contacts are made by helices 18 and 14 of the 18S rRNA, whereas in bacteria these contacts are carried out by Rps4/uS4 (orthologous to Rps9 in yeast and humans) [42–44]. In the entry tunnel, Rps3’s contacts with the mRNA stand out because they appear to be almost universally conserved and form an integral part of the helicase domain of the ribosome [42]. Furthermore, the protein has been implicated in translation initiation during the rearrangement of the small subunit that allows for the opening of the ribosomal mRNA binding channel and subsequent scanning of the mRNA [45] as well as start-codon selection [46]. Here we show the entry tunnel of the ribosome to play an important role during NGD. Mutation of the residues of RPS3 that form part of the entry tunnel, which have also been implicated in the helicase activity of the ribosome, were found to significantly reduce the accumulation of cleavage products. This effect on cleavage efficiency to a large extent was independent of the identity of the stall site. Combining these mutations with factors involved in other aspects of NGD revealed that the entry tunnel is also likely to be important in ribosome rescue. Our findings provide new insights into how quality control mechanisms evolved to integrate into fundamental biological machines.
To address a potential role for Rps3 in the cleavage reaction, we introduced a number of mutations to the protein and assessed their effect on cleavage of stalling reporters. Our choice of residues for the mutations was motivated by three criteria: they had to be conserved, made intimate contacts with the mRNA and have basic or acidic side chains (Fig 1A and 1B). This led us to Arg116 (R116) and Arg117 (R117). In addition to these, we also analyzed two residues that have been suggested to be important for Rps3’s extra-ribosomal activity in DNA repair [47–51], Asp154 (D154) and Lys200 (K200). Mutation of these residues abolishes the 8-oxoguanosine glycoslase and AP/endonuclease activities of the protein [51]. The variant-yeast strains were generated by introducing mutations to the chromosomal copy of RPS3 (see Methods) in different backgrounds of deletions and mutations. All in all, we generated the following mutants: Arg116 and Arg117 were substituted by Ala residues (R116A/R117A), Asp154 was substituted by an Ala residue (D154A), Lys200 was substituted by an Asn residue (K200N) and finally we generated a double mutant D154A/K200N. Of these the R116A/R117A mutation was notable as the side chain of these residues are projected into the entry tunnel of the ribosome and make electrostatic interactions with the mRNA (Fig 1B). Next, we assessed the effect of these mutations on the cleavage of NGD substrates. We initially used an NGD reporter, which harbors a stable stem loop in the PGK1 coding sequence and was originally designed by Parker and colleagues. The stem loop presents a robust obstacle for the ribosome and is subject to an endonucleolytic cleavage as evidenced by the accumulation of 5’ and 3’ fragments when the exosome and Xrn1 are inactivated, respectively [15]. Indeed, similar to what was observed by us and others [15,16,40], in the ski2Δ strain- which is defective for 3’-5’ mRNA degradation- northern analysis of cells expressing PGK1-SL revealed substantial accumulation of 5’-fragments (Fig 1C). The D154A and K200N mutations in RPS3, which have been suggested to be important for an AP endonuclease activity [51], had no observable effect on the cleavage efficiency and appear to play no role in NGD. In contrast, the R116A/R117A mutations appear to reduce the accumulation of cleavage fragments and also increased heterogeneity among these products (Fig 1C). Interestingly, the mutations also appear to affect the steady-state levels of endogenous PGK1 transcript (Fig 1C). Regardless, these observations suggest that residues of Rps3 that interact with the mRNA in the entry tunnel are important during NGD. The effects of the R116A/R117A mutations on the cleavage reaction were further studied in the context of other deletions that alter different aspects of NGD. Namely, we introduced these mutations into dom34Δ and xrn1Δ strains in addition to the wild-type parent strain. As expected, expression of the PGK1-SL in these strains does not result in the accumulation of 5’-fragments and the R116A/R117A mutations have no effect. As a control, these fragments were seen in the ski2Δ background and the rps3 mutations significantly reduced their levels (Fig 1D). Production of the 3’-fragments, as expected, was seen in the absence of XRN1 and their levels diminished in the presence of the RPS3 mutations, albeit to a lower extent than that seen for the 5’ fragments (Fig 1E). These latter observations suggested that the R116A/R117A mutations do not completely inhibit cleavage and that they may affect other aspects of NGD. To provide further support for a role for the entry tunnel residues of Rps3 during NGD, we next examined the effect of the mutations on the stability of the PGK1-SL mRNA. Our reporters are expressed under the control of the GAL1 promoter, and as a result transcriptional-shutoff by shifting cells to glucose-containing media was used to measure the decay rate of the reporter mRNAs. As a control, we initially measured the decay rate of a non-NGD reporter (PGK1), which does not harbor any stalling sequence. The mutations were found to have little effect on the decay rate of the PGK1 mRNA reporter (Fig 2A); we measured half-lives of 28 ± 1. 9 and 26 ± 4. 4 minutes in the WT and the RPS3-mutant stains, respectively. As expected, the PGK1-SL mRNA decays with a faster rate relative to its PGK1 parent (Fig 2B). Its half-life of 4. 7 ± 0. 2 minutes is similar to previously published reports [15]. Here the RPS3 mutations result in a moderate but reproducible increase in reporter half-life to 6. 0 ± 1. 3 minutes, suggesting greater stabilization of the PGK1-SL mRNA (Fig 2B). Hence, these findings add additional support for the entry tunnel of the ribosome playing a role in mRNA-surveillance during NGD, whereby loss of interactions with the mRNA leads to stabilization of mRNAs harboring stalls. So far, our analysis has focused on one type of stall—a stable RNA secondary structure in the form of a stem loop. Since the mutations under investigation here are important for the helicase function of the ribosome, any effect we saw on the cleavage reaction could be explained by defects in the unwinding activity of the ribosome and not in NGD. To rule out this potential explanation, we used two other reporters that had 12 stretches of the inhibitory arginine CGA or lysine AAA codons. Both are known to efficiently block translation and are not predicted to form secondary structures [3,15,23]. These new reporters were introduced to wild-type or mutant RPS3 yeast strains in the ski2Δ background. As expected, the CGA and AAA reporters accumulated 5’-fragments in the wild-type RPS3 strain, whereas the control UUU reporter did not (Fig 3). Similar to what we observed for the SL reporter, the R116A/R117A mutations significantly reduced the 5’-fragments levels for the CGA and AAA reporters, suggesting that the entry tunnel residues affect the accumulation of cleavage fragments independent of the type of stall (Fig 3). Interestingly, however, unlike the SL reporter, for which we observe an almost complete loss of cleavage products when RPS3 was mutated, cleavage fragments resulting from the CGA and AAA reporters were still visible but instead were heterogeneous in nature (Fig 3). This also made it difficult to perform any meaningful quantification. This is likely due to cleavage fragments produced by inefficient initial cleavage reactions, which lead to ribosome queuing upstream of the lead stalled ribosome. Ski7, a component of the exosome in yeast, has been implicated in non-stop decay (NSD) [52–54]; given the similarities between NSD and NGD, the mutations in RPS3 could potentially affect the function of Ski7. To address this possibility, we deleted SKI7 from the wild-type, dom34Δ and ski2Δ stains in the absence and presence of the RPS3 mutations and assessed its effect on NGD efficiency from the SL reporter. We observed no significant changes to the accumulation of the 5’-fragments due to the SKI7 deletion suggesting that the entry tunnel residues do not affect the function of the factor (S1 Fig). As mentioned earlier, in addition to Rps3, the mRNA entry tunnel of the small subunit also encompasses conserved residues of the ribosomal protein Rps2 [42,55]. Namely the side-chain of Glu120 of the yeast protein protrudes into the entry tunnel and is likely to interact with the mRNA downstream of the A site (S1 Fig). Consequently, we determined whether this residue contributes to NGD or not. We mutated Glu120 to Ala in the ski2Δ strain and evaluated its effect on NGD cleavage efficiency. In contrast to the RPS3 mutations, the RPS2 mutation had no noticeable effect on the cleavage reaction; we observed comparable levels of 5’-fragments accumulation from the SL reporters in the RPS2 wild-type and mutant strains (S1 Fig). It thus appears that the changes to NGD we observe in the presence of the RPS3 mutations are the result of Rps3-dependent effects, and likely not from general alterations to the mRNA-entry tunnel. Initial reports of NGD suggested that Dom34 plays a role in the cleavage reaction due to the loss of the cleavage products accumulation when the factor is deleted [15,24]. Later studies, however, showed that the protein together with Hbs1 and ABCE1 dissociates stalled ribosomes [19]. In its absence ribosomes pile up on the mRNA leading to multiple cleavage events upstream of the lead stalled ribosome, which run as a long smear on a gel that appears to result in loss of cleavage efficiency [16]. Furthermore, overexpression of certain ribosomal proteins restored cleavage in the absence of DOM34, suggesting that the protein is involved in maintaining ribosome homeostasis [22]. To gain further insights into the role of the entry-tunnel residues in ribosome rescue, we deleted DOM34 from our RPS3-mutant strains and assessed its effect on the accumulation of 5’-fragments from the PGK1-SL reporter. As had been seen by others, deletion of DOM34 appeared to result in a loss of cleavage [16]. Interestingly the same deletion in the presence of the R116A/R117A mutations appears to restore cleavage with one caveat; the fragments are much more heterogeneous relative to those observed under normal conditions (Fig 4A). In particular, the products were observed to form a long smear on agarose gels. It seems that, under conditions where ribosome rescue is inhibited, mutation of the entry tunnel residues leads to a spreading of cleavage events well upstream of the stall site. To provide further support for this notion, we examined the effect of mutations in ASC1 on cleavage in conjunction with the RPS3 mutations. Asc1 is a ribosome-associated protein that has been implicated in multiple aspects of ribosome quality control processes including NGD [38,56–58]. For instance, cryoEM structures of a Dom34-Hbs1-bound ribosome revealed the factor to interact with Dom34 suggesting that it is critical for NGD [59,60]. In addition, recent data from the Inada group showed that the factor is important for sequential endonucleolytic cleavage during non-stop decay (NSD) in the absence of DOM34 [58]. Instead of deleting ASC1- which harbors a snoRNA gene in its intron- from our rps3 strains, we opted to introduce the R38D/K40E mutations into the chromosomal copy of the gene. These mutations are known to affect the association of the factor with the ribosome and phenocopy its deletion in NGD [61]. Similar to the effect we saw in the dom34Δ background, the ASC1 mutations resulted in the accumulation of heterogeneous 5’-fragments from the PGK1-SL NGD substrate in the presence of the R116A/R117A mutations (Fig 4B). To verify that the effect on NGD we observe with the RPS3 mutants are not due to decreased association of Asc1 with the ribosome, we carried out polysome analysis and used western analysis to look at the binding of Asc1 to ribosomes. As can be seen in Fig 4C, ribosomal occupancy by wild-type Asc1 is not significantly altered by the mutations in RPS3; similar to the wild-type, the protein was found to primarily associate with the polysomes in the presence of the RPS3 mutation (top panels). As a control, the R38D/K40E mutant was observed in the light fractions of the sucrose gradient, that is not ribosome-associated, regardless of RPS3 status (bottom panels). We should note, though, Asc1 participates in a multitude of processes on the ribosome including translation of short ORFs, stall clearance and ribosomal protein ubiquitination [37,38,56–58,62]. As a result, any interpretation of its consequence on NGD is likely to be complicated by the larger context of its effect on ribosome function. How inhibition of ribosome rescue either by deletion of DOM34 or mutation of ASC1 restores cleavage efficiency to entry-tunnel mutants, albeit with a distinct signature of heterogeneous product accumulation, is difficult to interpret. One plausible explanation is that the R116A/R117A mutations inhibit the accumulation of cleavage fragments and under normal conditions ribosome rescue is fast enough to dissociate stalled ribosomes, which results in the observed disappearance of cleavage products. When rescue slows down due to reduced cleavage kinetics, ribosomes accumulate on the mRNA, initiating cleavage further upstream of the stall sequence. Our Northern analysis of the NGD-cleavage products suggested that the R116A/R117A mutations affect cleavage fragments accumulation and result in ribosome queueing upstream of the stall site. This pile-up of ribosomes, in turn, results in cleavage reactions even farther upstream leading to diffusion of the NGD intermediates. We provided further support for these ideas by conducting high-throughput sequencing to map the 3’-end of the 5’-NGD fragments. Briefly, total RNA was isolated from strains harboring either the RPS3 mutants, dom34Δ, or ASC1 mutants in the ski2Δ background, each expressing one of the three NGD reporters- SL, (CGA) 12 and (AAA) 12. An adenylated DNA oligonucleotide was ligated to the 3’-end of the RNA samples, which was used to prime reverse transcription. The resulting cDNA was then amplified using a PGK1-specific 5’-primer and subjected to high-throughput sequencing using the Illumina Hiseq 2500 platform (GEO accession: GSE117652). Similar to what we have reported earlier [40], for otherwise wild-type cells, the 5’-fragments resulting from the PGK1-SL reporter mapped well upstream of the stall in all strains regardless of the mutational background (Fig 5). However, mapping of the fragments from the R116A/R117A mutant cells revealed extensive spreading of the cleavage events (Fig 5B). More specifically, whereas in the wild-type RPS3 background we observe one predominant peak near the ~150-nt upstream mark, in the rps3 mutant background, no predominant peak was observed (Fig 5B). Instead, fragments mapped throughout a 500-nt region upstream of the stall site and multiple peaks were observed with a near 30-nt periodicity. Interestingly, in the dom34Δ and the asc1 cells, the fragments displayed distinct mapping patterns relative to the wild-type and rps3 cells as well as to each other. Similar to what was observed for the rps3 mutant cells, in the dom34Δ cells the predominant peak at ~150-nt is lost, but here the distance between the peaks increased to 40–60 nt (Fig 5C). This is consistent with the role of Dom34 in rescuing ribosomes that run to the end of the transcript following endonucleolytic cleavage on NGD reporters. Since multiple ribosomes appear to be required for efficient cleavage, the reaction would be expected to occur every ~45-nt- with the lead ribosome protecting 15-nt, while the one behind protects 30-nt. In clear distinction to both the rps3 and the dom34Δ cells, mapping of the 5’-fragments from the SL reporter was not as diffuse in the asc1 mutant cells. Instead, only one additional predominant peak (relative to the wild-type cells) was observed at ~250 nt upstream (Fig 5D). Differences in cleavage patterns from the WT, rps3 and dom34Δ cells were also evident for 5’-fragments obtained from the (CGA) 12 reporter, and to a lesser extent for (AAA) 12 reporter (S2 Fig). We note that for both the (CGA) 12 and (AAA) 12 reporters, fewer reads were mapped in the rps3 cells, presumably due to decreased cleavage efficiency. These differences between the R116A/R117A mutant, and the DOM34 and ASC1 mutants suggest that the entry tunnel of Rps3 affects different aspects of NGD relative to these factors. It is also consistent with our model that these residues are important for the endonuclease function. Recently we showed that ribosome collision appears to play an important role in initiating NGD during stalling [17]. In particular, decreasing ribosome concentration, and hence ribosome density per mRNA, by deleting certain ribosomal protein paralogues was found to reduce cleavage of NGD targets [40]. As a result, we wondered whether the mutations of the entry tunnel residues had similar effects on ribosome density. To address this potential explanation, we compared the polysome profile of the rps3 cells to the wild-type ones. Our analysis revealed that the mutations in RPS3 had little effect on ribosome density (Fig 6). The ratio of polysomes to monosomes in the mutant is largely similar to that observed in the wild-type background. In contrast, similar analysis of the dom34Δ cells- as has been seen before [27]- revealed elevated levels of 80S monosomes relative to polysomes (Fig 6). The finding that the RPS3 mutations do not seem to affect ribosome density has two immediate ramifications: 1) the observed inhibition of NGD in the presence of these mutations does not result from changes to ribosome collisions; 2) consistent with our mapping analysis, the mutations are not likely affecting the function of Dom34. As discussed earlier, ubiquitination of ribosomal proteins by Hel2 (Znf598 in humans) has recently been recognized as an important feature of ribosome stalling. This modification promotes stalling on inhibitory codons as deletion of HEL2 results in significant bypassing of stalls by the ribosome [36–38,63,64]. Relevant to our studies is the observation that Rps3 is one of the targets for Hel2-mediated ubiquitination on K212, but it is currently unclear if its modification is important for stalling [64]. Nevertheless, if the entry tunnel mutations somehow affect Hel2 function, this could in principle explain their effect on NGD. As a result, we set out to assess stalling-induced ribosomal protein ubiquitination in the presence of R116A/R117A mutations. We took advantage of our previous observation that the addition of cycloheximide to an intermediary concentration, whereby ribosome collisions presumably occur at a global level, results in robust ribosomal protein ubiquitination [62]. We added cycloheximide to a final concentration of 2 μg/mL to wild-type, rps3 R116A/R117A, dom34Δ and double mutant cells; and isolated ribosomes. Ubiquitination patterns of ribosomal proteins resulting from cycloheximide addition, as assessed by western-blotting, was nearly identical among all strains (Fig 7). However, we noted that deletion of DOM34 had a discernible effect on the ubiquitination levels suggesting that Dom34 might affect Hel2 function (Fig 7). The rps3 mutations on their own, however, had no observable effect on the efficiency of ribosomal proteins ubiquitination. Hence, it is very unlikely that the effect of the entry-tunnel mutations on NGD are due to differences in ribosomal protein ubiquitination during stalling. We reasoned that if the entry-tunnel residues of Rps3 are affecting NGD, then mutating them should result in increased sensitivity to cycloheximide especially at intermediate concentrations, at which ribosome collisions will occur and hence NGD is triggered. Growth of the rps3 strain was compared to the wild-type one in the presence of varying concentrations of cycloheximide (Fig 8A and 8B). To distinguish between effects on the growth rate versus lag time, we determined the first derivative of the growth curve to measure the instantaneous growth rate. The maxima of the resulting curves report on the maximal growth rate, whereas the distance between the maxima reports on the lag. As expected, the mutations had no effect on the growth rate or lag period in the absence of the drug and at very low and high concentrations (S3 Fig). In contrast and in agreement with our model, the addition of cycloheximide at intermediate concentrations (0. 02–0. 32 μg/mL) significantly increased the lag period for the R116A/R117A mutant. This effect was most noticeable at the 0. 16 μg/mL concentration, for which we observed a lag-time difference between the wild-type and the mutant cells of more than 4 hours (S3 Fig). Our data suggests that the entry-tunnel residues are important for dealing with intermittent collision events, and likely the ensuing process of ribosome rescue. Previous work from our lab revealed that RNA oxidation strongly stalls translation in vitro [17]. In particular, the introduction of a single 8-oxoguanosine adduct to the mRNA reduced the rate of peptide-bond formation by almost three orders of magnitude in a bacterial reconstituted system and prevented the formation of full-length protein products in wheat-germ and rabbit-reticulocyte extracts. We also provided evidence that showed oxidized mRNA is subject to NGD. Because our rps3 mutations appear to affect NGD, they should also in principle result in increased sensitivity to agents that react with RNA to produce adducts such as 8-oxoguanosine. We used the chemical 4-Nitroquinoline 1-oxide (4NQO), a UV mimetic and known to produce reactive oxygen species, to introduce 8-oxoguanosine into RNA [65] in living yeast. Wild-type and rps3-mutant cells were grown to mid-logarithmic before being challenged with 5 μg/mL of 4NQO for 30 minutes. Cells were washed with fresh media, diluted and their growth monitored. In the absence of any drugs, the rps3 mutant displayed a growth rate nearly identical to that of the wild-type (6. 6 ±0. 23 versus 6. 3 ±0. 07 hours). After incubation with 4NQO, the mutant displayed a notable lag in its growth of 1. 4 hours (10. 4 ±0. 18 versus 9. 0 ±0. 79) (Fig 9A and 9B). We note that although the effects we saw are modest, they are reproducible and suggest that mutations of the entry-tunnel residues render cells sensitive to damaging agents. These effects are also reminiscent of the effects that we and others have documented for dom34Δ and xrn1Δ strains [17]. These findings together with the observation that mutations in RPS3 result in increased sensitivity towards cycloheximide provide further support for a role for the factor in NGD.
NGD is a conserved eukaryotic process that responds to stalled ribosomes [14]. The process is characterized by an endonucleolytic cleavage of the aberrant mRNA upstream of the lead ribosome [15] and as yet the identity of the culprit endonuclease remains unknown. As a result, there is a critical gap in our understanding of some of the mechanistic details of the process. Nonetheless, multiple studies have provided important hints about the enzyme. For instance, mapping experiments suggested that the endonuclease is ribosome-associated [40,41]. In particular, cleavage takes place in frame with the ribosome and is phased by ~30 nt, the mRNA-length protected by the ribosome. Furthermore, the reaction appears to likely take place between stacked ribosomes [40]. These studies hinted at a role for the ribosome itself in activating or recruiting the endonuclease. Here we provided further evidence for this notion. More specifically, we find the entry tunnel of the ribosomal protein Rps3 to be important for the cleavage reaction. Mutation of the key-entry-tunnel residues Arg116 and Arg117 were found to drastically affect the outcome of the cleavage event; we observe a significant reduction in the accumulation of 5’-fragments from a number of NGD reporters when these residues are mutated to Ala. Consistent with these findings, although subtle, the half-life of the SL reporter increases in the presence of the mutations suggesting that these mutations may stabilize NGD reporters. Mapping of the cleavage products also revealed spreading of the cleavage reaction in the presence of the mutations. We note that Rps3 is known to interact with two key NGD factors: Dom34 and ribosome-associated Asc1 [60,66]. Although deletion or mutation of these factors affects the cleavage pattern in the rps3 background, as evidenced by northern analysis, the effect of the mutations on NGD do not appear to phenocopy those observed in the dom34Δ and asc1 strains, which is apparent in the high-throughput mapping data. Furthermore, the mutations do not alter Asc1 occupancy on the ribosome. Collectively our data suggests that the entry-tunnel region of Rps3, and hence the ribosome, has a function in NGD upon stalling. In agreement with this proposal, mutations of this region render cells sensitive to intermediate concentrations of cycloheximide and the nucleic-acid damaging agent 4NQO; both stall the ribosome and likely trigger NGD. Apart from the decoding center nucleotides, the Arg116 and Arg117 residues of the entry tunnel of the ribosome come closest to the mRNA. Indeed, some of the first studies on this region showed it to be important for unwinding the mRNA and make up part of the helicase domain of the ribosome [42]. While our data do not show the residues to be required for cleavage to take place–we still observe accumulation of NGD fragments in the presence of the mutations–they clearly affect the pattern of the cleavage reaction. It is feasible that the electrostatic interaction between the side chains and the phosphodiester backbone of the mRNA is important for locking the mRNA in place for the endonuclease to carry out its cleavage reaction. When these residues are mutated to Ala residues, the mRNA is more dynamic and its accessibility to the enzyme’s active site is severely affected. Alternatively, these residues might be important for recruiting or activating the endonuclease and as a result, changing their identities inhibits the cleavage reaction, although it is not clear how residues buried deep in the ribosome could be used efficiently to recruit exogenous protein factors. Instead, we favor a model whereby the endonuclease is intimately associated with the ribosome and it is activated upon stalling. In agreement with this, previous work has indicated that during non-stop decay, when the ribosome runs to the end of an mRNA, the endonucleolytic cleavage takes place near the exit tunnel of the ribosome [16,41,67] as evidenced partly by the accumulation of 15–18 nt fragments. Similarly, during a novel form of mRNA degradation termed ribothrypsis, it was suggested that an endonucleolytic cleavage event takes place near the exit tunnel [68]. Interestingly, recent structural data from human cells has revealed the position of multiple ribosomal proteins and associated factors at collided di-ribosomes–events that trigger NGD [69]. It appears that this higher order structure brings an entry- and exit-tunnel face of adjacent ribosomes in close proximity, which could potentially allow for interactions between otherwise distally positioned components. These include RACK1/Asc1 on the stalled ribosome with uS3, eS10, and uS10 on the collided ribosome, as well as eS26 and eS28 facing uS4 and rRNA helix 16 on the stalled and collided ribosomes, respectively. It will be exciting to see how modifications to these factors may affect endonuclease activity. In an endonuclease-independent consequence, the residues and their interaction with the mRNA could play a role in recruiting Dom34 and Hbs1 to the ribosome. Biochemical and structural studies have suggested that Hbs1 is recruited to a ribosome with little to no mRNA downstream of the A site [20,21,66,70]. The N-terminal of Hbs1 binds in the RNA entry tunnel, interacting with Rps3 [66]. It was hypothesized that Hbs1 cannot bind in the presence of mRNA in the entry tunnel [19,20,60,66]. Additional recent structural studies also revealed a potential role for Dom34 in sensing the mRNA channel, whereby it uses a unique β-loop to protrude into the mRNA channel to sense its absence [60]. Together these two mechanisms ensure that ribosome dissociation only occurs when the ribosome reaches the end of the mRNA, such as during NSD or on the behind ribosomes following cleavage during NGD. It is possible that the mutations in the entry tunnel of Rps3 make the mRNA more dynamic, preventing a clash with Dom34 and Hbs1. In turn, this allows the factors to bind and dissociate the ribosomes before cleavage could take place. In agreement with this model, deletion of DOM34 in the presence of the rps3 mutations restores cleavage efficiency, and with increased heterogeneity, as expected, due to widespread ribosome queueing. This model, however, does not explain why the cleavage patterns in the double mutant do not look similar to those observed in the dom34Δ mutant. Therefore, the effects of the rps3 mutations appear to be more complex and they are likely to alter different aspects of NGD including the cleavage and the dissociation reactions. In contrast, the mutations do not appear to affect the RQC pathway, as we observe comparable ribosomal protein ubiquitination patterning and efficiency upon inducing ribosome collisions regardless of the status of Rps3. Perhaps not surprising given its proximity to the mRNA, Rps3 plays a number of roles on the ribosome during translation. It has been shown to be important for providing the helicase activity to the ribosome; in bacteria Rps3/uS3, together with Rps4/uS4 and Rps5/uS5, encircle the incoming mRNA within the entry tunnel. When Arg131 and Arg132 in bacteria (corresponding to Arg116 and Arg117 in yeast) were mutated to Alanine, the efficiency of unwinding an RNA duplex by the ribosome was reduced [42]. Residues of Rps4 were also shown to contribute to helicase activity, but the process overall is coupled to and dependent on movements during translocation [71]. Rps3 is known to interact with other ribosomal proteins, including ribosome-bound Asc1/RACK1 [60,66]. In addition to its aforementioned role in NGD, Asc1 is known to be involved in preventing readthrough of inhibitory codons and reading-frame maintenance [72]. In eukaryotes, the C-terminal tail of Rps3 lies further inside the mRNA channel, proximal to Asc1 [43]. It is tempting to speculate that conformational changes that involve Rps3 could be communicated to Asc1, which then may initiate additional steps in NGD. However, the convergence of phenotypes among Rps3, Asc1 and Dom34 highlight the potential for redundancy or simply subtle differences of function between these and related factors. This is also evident during non-functional 18S rRNA decay (NRD), where both Asc1 and Rps3 have recently been identified as players in the pathway [73]. The post-translationally modified C-terminal tail of Rps3 is required for 18S NRD and, as Asc1 can collaborate with either Dom34 or Hbs1, it was suggested that multiple overlapping pathways function to deal with damaged rRNA. At another step in the translation cycle, Rps3 also contributes to stabilizing the incoming mRNA during initiation. Again, yeast residues Arg116 and Arg117 were shown to promote binding of the mRNA to eIF3 dependent pre-initiation complexes (PICs) and in particular, when the exit channel is empty, they were absolutely required [46]. This demonstrates the diverse functionality of Rps3 that is likely due in part to its position at the entry tunnel where it interacts with and can survey incoming transcripts. Collectively our findings provide further evidence for the central role of the ribosome in mRNA-surveillance pathways beyond just recognizing the aberrant mRNA and initiating the downstream events. The observation that mutations deep into the ribosome lead to dramatic changes to NGD bolsters arguments by us and others that the endonuclease is likely to be an integral part of the machine. This in turn could explain why it has been difficult to identify the endonuclease. It would be interesting to examine how quality control mechanisms evolved to integrate into fundamental biological machines. Further delineation of the details of this mechanism will also contribute to the understanding of how cells identify and degrade defective biological molecules. Finally, similar to NMD, NGD is likely to have been coopted to regulate gene expression. Indeed, recent reports have shown conditional deletion of Pelota (the human orthologue of Dom34) results in abnormal cellular differentiation [74]. The identification of the endonuclease is more than likely to provide further and important appreciation of the pervasiveness of this mode of gene regulation through NGD.
Cells were grown at 30°C in YPD or in defined media when expressing reporter plasmids. Yeast strains were made using standard PCR-based disruption techniques in the background BY4741 (MATa (his3Δ1 leu2Δ0 met15Δ0 ura3Δ0). SKI7 knockout strains were generated with a LEU2 cassette, amplified using oligos complementary to the insertion site. RPS3 mutant strains were constructed by first cloning a fragment encoding RPS3-HIS3-rpS3 3’UTR, generated by fusion PCR, into the BamHI/XhoI sites in pPROEX-HTb. Point mutations in RPS3 were introduced by site directed mutagenesis and a cassette encoding the entire region was PCR amplified and used to transform the target yeast strains. RPS2 (E120A) strains were made using the same method and ASC1 (R38D, K40E) strains were made similarly, except using BamHI/XbaI sites in pET28a. HIS3 and LEU2 coding regions were amplified from plasmids pFAGa-6xGLY-FLAG-HIS3 and pAG415 [75] respectively. Plasmids encoding the PGK1 gene or PGK1-SL under control of the GAL1 promoter were obtained from R. Parker [15]. PGK1- (CGA) 12, PGK1- (AAA) 12 and PGK1- (UUU) 12 were made by annealing complementary oligos and ligating them to XbaI digested PGK1 plasmid [40]. Culture was grown overnight in a defined media (-Ura) with glucose. Cells were washed twice in media containing 2% Raffinose and 2% galactose, diluted to OD 0. 1 in the same media and grown to an OD of 0. 5–0. 8 to permit expression of the gal-driven reporters. RNA was isolated using hot phenol extraction followed by two sets of chloroform extraction and ethanol precipitation. 2μg of total RNA was resolved on 1. 2% formaldehyde agarose gel, followed by transfer to positively-charged nylon membrane (GE Lifesciences) using a vacuum blotter (Biorad). Next, nucleic acids were UV cross-linked to the membrane and baked at 80°C for 15 minutes. Membranes were then pre-hybridized in Rapid-Hyb buffer (GE Lifesciences) for 30 minutes in a hybridization oven. Radiolabeled DNA probe, which was labeled using polynucleotide kinase and [γ-32P]ATP, was added to the buffer and incubated overnight. Membranes were washed with nonstringent buffer (2 × SSC, 0. 1% SDS) three times, in some cases followed by three washes in stringent buffer (0. 2 × SSC, 0. 1% SDS), all at hybridization temperature. Membranes were exposed to a phosphorimager screen and analyzed using a Biorad Personal Molecular Imager. All Northern analyses were performed using at least three biological replicates. Representative images are shown. Cells expressing PGK1-SL were grown overnight in defined media (-Ura) plus glucose. Cultures were then washed in -Ura media, resuspended at OD 0. 1 in 50 mL -Ura plus galactose, and grown for 18–20 hours to allow expression of the reporter plasmid. Cells were collected at OD 0. 5–0. 6, washed once and resuspended in 11 mL pre-warmed -Ura media. A 1 mL aliquot was saved for the t0 timepoint and 1 mL 40% glucose added to the remainder. Cells were incubated at 30°C while shaking and aliquots taken at the indicated timepoints. For each sample, cells were pelleted, media was removed, and tubes were frozen on dry ice. RNA was isolated using a hot phenol method followed by two rounds of chloroform extraction and ethanol precipitation. 2 μg of total RNA for each sample was analyzed by Northern blot. Yeast cultures were grown to mid-log phase before addition of cycloheximide to a final concentration of 100 μg/mL. The culture was chilled by adding an equal volume of ice and centrifuged at 4°C. Cells were then resuspended in polysome lysis buffer (20 mM Tris pH 7. 5,140 mM KCl, 5 mM MgCl2,0. 5 mM DTT, 1% Triton-100,100 μg/mL cycloheximide, 200 μg/mL heparin), washed once and lysed with glass beads using a FastPrep (MP Biomedical). Supernatant from cleared lysate corresponding to 1 mg of total RNA was layered over a 10–50% sucrose gradient and centrifuged at 37,000 rpm for 160 min in an SW41Ti (Beckman) swinging bucket rotor. Gradients were fractionated using a Brandel tube-piercing system combined with continuous absorbance reading at A254 nm. Proteins were precipitated by the addition of TCA to 10% after a twofold dilution with water, and resuspended in HU buffer (8 M Urea, 5% SDS, 200 mM Tris pH 6. 8,100 mM DTT). Proteins were resolved on 15% SDS PAGE gels and transferred to PVDF membranes using a semi-dry transfer apparatus (BioRad). The membranes were blocked with milk in PBST for ~ 30 minutes at room temperature followed by incubation with primary antibody overnight at 4°C. After washing with PBST, the membrane was incubated with the appropriate HRP-conjugated secondary antibody for ~ 1hr at room temperature before washing 3–4 × with PBST. Detection was carried out on a GE ImageQuant LAS 4000 using the Pierce SuperSignal West Pico Chemiluminescent Substrate. The following antibodies were used: mouse anti-PGK1[22C5D8] (ab113687) and rabbit anti-rpS9 (ab117861) from Abcam; rabbit anti-ASC1 was a gift from Wendy Gilbert (Yale University) [61]; mouse anti-rpL4 was a gift from Heather True (Washington University in St. Louis); goat anti-mouse IgG HRP (31430) and goat anti-rabbit IgG HRP (31460) from Thermo Scientific. Total RNA from the indicated strains was ligated to a short adenylated DNA oligonucleotide, 5' rAppCTGTAGGCACCATCAAT/3ddC/ 3' , at its 3’ end using truncated T4 RNA ligase 2 (NEB). For each sample, total RNA from at least two biological replicates was included. Reverse transcription using a primer complementary to the adaptor was performed, and then cDNA was amplified with a 5’-primer that annealed at position 585 of PGK1. Primers were designed for the Illumina HiSeq platform and samples were column purified to remove primers before sequencing. Single-read HiSeq 2500 sequencing was performed by the Genome TechnologyAccess Center (GTAC) at Washington University. Raw data was analyzed for quality using the Fastx toolkit (http: //hannonlab. cshl. edu/fastx_toolkit/index. html), trimmed using cutadapt [76] and aligned to our reference reporter sequence using NovoAlign (http: //www. novocraft. com/). Sequencing results are available at GEO (accession #GSE117652). Sensitivity assays were conducted essentially as described [74]. Yeast cells were grown to mid-log-phase (OD600 of 0. 5–0. 7), collected, washed and resuspended in YPD to a final density of OD 0. 8. 5 μl of the cell suspension was added to 195 μl of YPD with CHX at various concentrations, from 0–10 μg/mL. All samples were prepared in biological triplicates as well as technical duplicates in 96-well polystyrene microplates. The plate was incubated at 30°C with shaking on a microplate scanning spectrophotometer (Biotek). Cell density was monitored every 10 min over 24–48 h at 600nm. To assay sensitivity to 4NQO, after growing cells to mid-log (OD 0. 5–0. 7) cultures were treated with and without 5 μg/mL 4QNO for 30 minutes. Cells were collected, washed and adjusted to OD 0. 8. Samples were plated and growth monitored as above. | In all organisms, optimum cellular fitness depends on the ability of cells to recognize and degrade aberrant molecules. Messenger RNA is subject to alterations and, as a result, often presents roadblocks for the translating ribosomes. It is not surprising, then, that organisms evolved pathways to resolve these valuable stuck ribosomes. In eukaryotes, this process is called no-go decay (NGD) because it is coupled with decay of mRNAs that are associated with ribosomes that do not ‘go’. This decay process initiates with cleavage of the mRNA near the stall site, but some important details about this reaction are lacking. Here, we show that the ribosome itself is very central to the cleavage reaction. In particular, we identified a pair of residues of a ribosomal protein to be important for cleavage efficiency. These observations are consistent with prior structural studies showing that the residues make intimate contacts with the incoming mRNA in the entry tunnel. Altogether our data provide important clues about this quality-control pathway and suggest that the endonuclease not only recognizes stalled ribosomes but may have coevolved with the translation machinery to take advantage of certain residues of the ribosome to fulfill its function. | Abstract
Introduction
Results
Discussion
Methods | northern analysis
deletion mutation
molecular probe techniques
messenger rna
polyribosomes
mutation
fungi
molecular biology techniques
cellular structures and organelles
gel electrophoresis
research and analysis methods
electrophoretic techniques
proteins
ubiquitination
molecular biology
ribosomes
yeast
biochemistry
rna
eukaryota
cell biology
nucleic acids
post-translational modification
genetics
biology and life sciences
organisms | 2018 | Interactions between the mRNA and Rps3/uS3 at the entry tunnel of the ribosomal small subunit are important for no-go decay | 13,105 | 303 |
Viruses in the Flavivirus genus of the Flaviviridae family are arthropod-transmitted and contribute to staggering numbers of human infections and significant deaths annually across the globe. To identify cellular factors with antiviral activity against flaviviruses, we screened a cDNA library using an iterative approach. We identified a mammalian Hsp40 chaperone protein (DNAJC14) that when overexpressed was able to mediate protection from yellow fever virus (YFV) -induced cell death. Further studies revealed that DNAJC14 inhibits YFV at the step of viral RNA replication. Since replication of bovine viral diarrhea virus (BVDV), a member of the related Pestivirus genus, is also known to be modulated by DNAJC14, we tested the effect of this host factor on diverse Flaviviridae family members. Flaviviruses, including the pathogenic Asibi strain of YFV, Kunjin, and tick-borne Langat virus, as well as a Hepacivirus, hepatitis C virus (HCV), all were inhibited by overexpression of DNAJC14. Mutagenesis showed that both the J-domain and the C-terminal domain, which mediates self-interaction, are required for anti-YFV activity. We found that DNAJC14 does not block YFV nor HCV NS2-3 cleavage, and using non-inhibitory mutants demonstrate that DNAJC14 is recruited to YFV replication complexes. Immunofluorescence analysis demonstrated that endogenous DNAJC14 rearranges during infection and is found in replication complexes identified by dsRNA staining. Interestingly, silencing of endogenous DNAJC14 results in impaired YFV replication suggesting a requirement for DNAJC14 in YFV replication complex assembly. Finally, the antiviral activity of overexpressed DNAJC14 occurs in a time- and dose-dependent manner. DNAJC14 overexpression may disrupt the proper stoichiometry resulting in inhibition, which can be overcome upon restoration of the optimal ratios due to the accumulation of viral nonstructural proteins. Our findings, together with previously published work, suggest that the members of the Flaviviridae family have evolved in unique and important ways to interact with this host Hsp40 chaperone molecule.
The Flavivirus, Pestivirus and Hepacivirus genera of the Flaviviridae family each include important human and/or animal pathogens [1]. A major human pathogen hepatitis C virus (HCV) is a member of the Hepacivirus genus, while Pestiviruses bovine viral diarrhea (BVDV), border disease and classical swine fever viruses each have significant economic consequences in the livestock industry. Within the Flaviviridae family, members of the Flavivirus genus, which includes over 50 viral species, have perhaps the most significant impact on human health [2], [3]. Viruses in this genus, including yellow fever (YF), dengue (DEN), West Nile (WN), Japanese encephalitis (JE) and tick-borne encephalitis (TBE) viruses, contribute to staggering numbers of human infections and significant death rates across the globe. Viruses in this genus are usually transmitted via arthropod vectors and as such human infection depends on climate and geographical factors affecting the ranges of the transmitting arthropod and the likelihood of arthropod-human contact. Rising global temperatures, increased human population densities, human movement and increased dispersal of ticks and mosquitoes have contributed to increased numbers of epidemics in new geographical locations; this trend is likely to continue. While successful vaccines have been developed for prevention of YFV, JEV and TBEV infection, none are available for other pathogenic flaviviruses. Efforts to create and implement such vaccines have been hampered by the presence of multiple serotypes (DEN), the large geographical areas involved, and the sporadic nature of infection [4], [5]. Even for vaccine-preventable flavivirus infections, the cost associated with immunizing all at-risk people is enormous. Moreover, there are currently no drugs available for the specific treatment of any flaviviral disease. While several viral proteins are attractive targets for the development of small molecule inhibitors, the potential for rapid evolution of the flavivirus RNA genome suggests that resistance may be a significant problem. Disrupting critical interactions of viral proteins with host factors, or inducing expression of host proteins able to inhibit viral replication, are alternative approaches to developing effective anti-flaviviral therapies, and may limit the emergence of escape mutants. Unfortunately our understanding of host factor involvement in promoting or inhibiting flaviviral replication remains incomplete. Members of the Flavivirus genus share a common genome organization and replication strategy [1]. After virion entry and fusion of the viral and host membranes within the endosome, the ∼11,000 nt viral positive sense genomic RNA is translated in association with host cell membranes to form a single polyprotein which is co- and post-translationally cleaved by both host and viral proteases. The structural proteins, C, prM and E, are located in the N-terminal region of the polyprotein, followed by the nonstructural proteins, NS1, NS2A, NS2B, NS3, NS4A, NS4B and NS5. After appropriate cleavage and assembly of replication complexes, the genomic RNA is replicated by NS5, the viral RNA-dependent RNA polymerase, in association with other viral nonstructural and host proteins to generate new progeny genomes. Virion morphogenesis then follows via encapsidation and budding into the ER lumen. Virions mature during transport through the secretory pathway and are released into the extracellular milieu via exocytosis. Given the common replication strategy of the Flavivirus genus members, different species may exploit or be susceptible to many of the same host factors or environmental conditions. We hypothesized that identification of a cellular antiviral factor with activity against one flavivirus species may provide information on targets for broad-spectrum therapeutics. In order to identify antiviral cellular factors active against YFV, we conducted an iterative screen of a cDNA library from interferon-α treated cells. We identified DNAJC14, an Hsp40 family member, as able to mediate protection from YFV-induced cell death. Further studies demonstrate that DNAJC14 is recruited to YFV replication complexes and that its overexpression inhibits viral RNA accumulation. The C-terminus of DNAJC14, which mediates its multimerization, is required for antiviral activity. Furthermore, we found that silencing of endogenous DNAJC14 inhibits YFV replication. Overall our findings suggest that DNAJC14 plays an important role in regulating YFV replication complex assembly.
Retroviral vectors pV1, pV1-GFP, pTrip-EGFP and pTrip-TagRFP have been described [6], [7], [8], [9]. Derivatives were generated using standard methods; all polymerase chain reaction (PCR) generated sequences were verified by sequencing and primer sequences are available upon request. Derivatives of pV1 were constructed to express human DNAJC14 (hDNAJC14) and mutants, each containing a carboxyl-terminal myc tag; the myc tag (EQKLISEEDL) was introduced during PCR by inclusion of myc-encoding nucleotide sequences in the antisense primers. DNAJC14- or truncation mutant-encoding DNA was amplified, using the Expand Long Template PCR System (Roche), from hDNAJC14 cDNA plasmid (Open Biosystems), and after digestion with SfiI was cloned into similarly digested pV1. Plasmid pV1-hDNAJC14-FL encodes full-length hDNAJC14 (amino acids 1–702) with a carboxyl-terminal myc tag. The human N-terminal truncation mutant (NT1) corresponding to the truncated hamster cDNA isolated in the screen starts from the amino acid corresponding to residue 305 of hDNAJC14, and was designed to have the identical amino terminus as the hamster sequence (305MVQFLSQS—); the corresponding human wildtype sequence has a phenylalanine residue at position 306. Additional mutants generated include NT2: 250AGFWWLIE—; NT3: 291MGVWTGRL—; NT4: 320FTRFLKLL—; NT5: 349LVGLGDRL— and as necessary contained an extra methionine residue for translation initiation. C-terminal truncated mutants end at the following amino acids prior to the myc epitope tag: CT1: —HISFGSRI625; CT2: —DLKEAMNT534; CT3: —EEVARLLT433; CT4: —RFLVGLGD354; CT5: —AEELCQLG248. The NT5CT1 mutant contains both the NT5 and CT1 truncations. Point mutations were introduced using site directed mutagenesis with the appropriate oligos by standard techniques. Plasmids pTrip-EGFP-hDNAJC14-NT5 and pTrip-RFP-hDNAJC14-FL or pTrip-RFP-hDNAJC14-NT1 were generated by PCR amplification of the NT5, full-length (FL) or NT1 hDNAJC14 sequences. After BsrG1 and XhoI digestion the sequences were ligated into similarly digested pTRIP-EGFP or pTRIP-TagRFP. These plasmids express hDNAJC14 (or mutants) fused in frame to the C-terminus of EGFP or RFP. To generate a doxycycline-inducible cell line expressing hDNAJC14-NT5, sequences encoding NT5 were generated by PCR and were inserted into pcDNA4/TO/myc-His B (Invitrogen) via HindIII and XbaI digestion to generate pcDNA4/TO/hDNAJC14-NT5. Plasmid pTrip-RFP-hNZAP was generated by cloning DNA encoding amino acids 1 to 252 of human zinc-finger antiviral protein [10], generated by PCR, as an in frame fusion with the carboxyl terminus of RFP in the pTrip-TagRFP vector. Plasmids pFlag-HCV-NS2-3-WT or pFlag-HCV-NS2-3-H171A were described previously [11] and express Flag-tagged HCV NS2-3181 or the inactive H171A mutant form of the NS2 protease, respectively. Plasmids pFlag-YF-NS2-3 (181) -WT or pFlag-YF-NS2-3 (181) -S138A were generated by amplification of YFV NS2-3 fragments from plasmids pACNR-YF17D [12] and pET-BS (+) /Sig2A-5356-R2107/2506E, S1622A [13], respectively, and cloning the KpnI/XhoI digested products into similarly digested pcDNA3. 1. The sense primer contained appropriate sequences to encode a Flag epitope tag on the N-termini of the respective proteins. The plasmids express Flag-tagged YFV NS2-3181 or the inactive S138A form of the NS3 protease, respectively. Plasmids pACNR-FLYF17Dx [12] and pACNR-FLYF17Da [14] contain the sequences of YFV 17D downstream of the SP6 promoter with XhoI and AflII linearization sites, respectively. Plasmid pACNR-FLYF-Asibi (the details of which will be described in another paper) contains the sequences of YFV Asibi downstream of the SP6 promoter. Plasmid pYF17D (5′C25Venus2AUbi) was constructed by inserting Venus, a variant of yellow fluorescent protein (YFP), into the YFV 17D open reading frame (ORF) using standard molecular techniques. All generated PCR products and plasmids were verified by restriction digests and by sequencing (primers available upon request). First, the Venus cassette was amplified from plasmid Venus/pCS2 (kindly provided by Dr. Atsushi Miyawaki) and cloned in frame after the first 25 amino acids of the YFV Capsid in pNEB193/YF5′ [15] using the SacI and AgeI sites. Next, the foot-and-mouth disease virus (FMDV) 2A peptide, which mediates cleavage following its own carboxy-terminus, and a ubiquitin (Ubi) monomer were amplified from pTM3-HCV-Ubi-NS5B (C. Lin and C. M. Rice, unpublished) and inserted downstream of Venus in pNEB193/YF5′ by assembly PCR. YFV 17D amino acids 1–514, containing silent mutations in sequences encoding the first 25 amino acids to avoid recombination, were similarly assembled downstream of FMDV 2A in pNEB193/YF5′. Finally, to generate pYF17D (5′C25Venus2AUbi), Venus and YFV 17D sequences were removed from pNEB193/YF5′ using SrfI and NsiI and cloned into pCC1-YF17D [16], which contains the entire YFV genome. Thus in pYF17D (5′C25Venus2AUbi), the Venus/2AUbi cassette is inserted in frame after the first 25 amino acids of Capsid, followed by the complete YFV polyprotein. The presence of FMDV 2A and Ubi downstream of Venus ensures complete cleavage from the YFV polyprotein, thereby ensuring the authentic YFV amino terminus. This strategy has the potential advantage of allowing expression of foreign inserts without disrupting the YFV 17D polyprotein, which may have unpredictable deleterious effects on replication. YFV replicon plasmids pYF-R. luc2A-RP and pYF-luc-IRES-RP-ΔDD [17] were kindly provided by Richard J. Kuhn (Purdue University). Plasmid pYF-R. luc2A-RP-ΔDD (expressing a polymerase defective YFV luciferase-expressing replicon) was constructed by swapping the NdeI/XhoI fragment from pYF-luc-IRES-RP-ΔDD into pYF-R. luc2A-RP. All cell lines were maintained at 37°C in humidified chambers containing 5% CO2. SW13 (human adrenal carcinoma) cells were cultured in Minimum Essential Medium (MEM) Alpha Medium (MEMa, Invitrogen) supplemented with 10% fetal bovine serum (FBS, Invitrogen). Huh7. 5 cells [18] were cultured in Dulbecco' s Modified Eagle Medium (DMEM, Invitrogen) supplemented with nonessential amino acids (Invitrogen) and 10% FBS. HEK293T and Vero cells were cultured in DMEM supplemented with 10% FBS. T-REx-293-LacZ cells inducibly expressing myc-tagged LacZ were previously described [19]. T-REx-293-NT5 cells inducibly expressing hDNAJC14-NT5 were obtained by transfection of T-REx-293 cells with pcDNA4/TO/hDNAJC14-NT5 and selection in medium containing zeocin. The selected bulk population was then cultured in DMEM supplemented with 10% FBS, 5 µg/ml blasticidin, and 0. 5 mg/ml zeocin. For induction, doxycycline was added to a final concentration of 1 µg/ml. BHK-J cells, a previously described [20] line of BHK-21 hamster kidney cells were cultured in MEM supplemented with 7. 5% FBS and BHK/NZAP-Zeo cells [21] were maintained in the same medium with the addition of 200 µg/ml zeocin. Anti-Myc mouse monoclonal antibody 9E10 (ATCC CRL1792 hybridoma) was used in Western and immunofluorescence or immunoprecipitation at 2. 5 and 16 µg/ml, respectively. Anti-Flag antibody (Sigma M2 mouse monoclonal) was used in Western analysis at 1∶1000 dilution. Yellow fever NS3 rabbit polyclonal antiserum was previously described [22] and utilized at 1∶5000 dilution for Western analysis, and 1∶500 for immunofluorescence. Rabbit polyclonal anti-GFP antiserum was generated as described [23] and utilized at 1∶20,000 dilution in Western and 1∶1000 in immunoprecipitation. Mouse monoclonal anti-calnexin antibody (BD Biosciences, 610523) was used in Western and immunofluorescence at 1∶250 and 1∶50 dilution, respectively. Mouse monoclonal anti-actin (Sigma, A5441) antibodies were utilized in Western analyses at 1∶5000 dilution. Rabbit polyclonal anti-DNAJC14 antibody (Sigma, HPA017653) was used in Western and immunofluorescence at 1∶2000 and 1∶200 dilution, respectively. Mouse monoclonal anti-double stranded RNA (dsRNA) J2 antibody (English & Scientific Consulting, Bt. Szirák, Hungary), kindly provided by Dr. Elena Frolova (University of Alabama at Birmingham), was used at 1∶200 dilution. Alexa Fluor 488 donkey anti-mouse IgG (A-212020) and Alexa Fluor 594 goat anti-rabbit IgG (A-11012, Invitrogen) were utilized in immunofluorescence at 1∶000 dilution. YF 17D neutralizing mouse monoclonal antibody 8A3 [24] ascitic fluid was kindly provided by Jack Schlesinger (University of Rochester). A dilution of 1∶100 was found to efficiently neutralize up to 105 pfu of YFV (data not shown). HRP-conjugated secondary anti-mouse (Jackson ImmunoResearch, 115-035-146) and anti-rabbit (Pierce, 31462) IgG antibodies were utilized at 1∶20,000 dilution. Normal rabbit IgG used in immunoprecipitations was from Santa Cruz Biotechnology, Inc. YFV stocks were generated by electroporation of BHK-J cells as previously described [25] with in vitro transcribed YFV RNA. Plasmids pACNR-FLYF17Dx [12], pYF17D (5′C25Venus2AUbi), and pACNR-FL-YF-Asibi were used for generation of YF 17D, YFV-Venus or YF Asibi, respectively. All work with YF Asibi was conducted under Biosafety level 3 containment conditions. Virus stocks and samples were titered by infection of BHK-J cells with 10-fold serial dilutions in MEM with 2% FCS. Two hundred µl of diluted virus was added to each 35 mm well and after 1 h of infection the well was overlaid with 0. 6% agarose in MEM supplemented with 2% FBS. Plaques were enumerated by crystal violet staining after 72 h. For YFV infections, multiplicity of infection (moi) was based on titers obtained on BHK-J cells. HCVcc (Jc1FLAG2 (p7-nsGluc2A) ) a cell culture-derived HCV expressing Gaussia luciferase was prepared by electroporation of Huh7. 5 cells as described previously [26]. Stocks of Kunjin (derived from infectious clone FLSDX 250pro) were propagated on Vero cells as described [27], [28]. Langat (TP21 strain) was propagated on Vero cells as described [29]. Titrations of stocks and samples were performed by focus forming assay, as previously described [30], [31]. Briefly, Vero cells were infected with 10-fold serial dilutions and after the 1 h adsorption the wells were overlaid with 0. 8% methylcellulose in DMEM containing 2% FBS. After 4 d the monolayers were fixed with 100% methanol and plaques were visualized by incubation with polyclonal mouse antibody cross-reactive to Langat (hyperimmune mouse ascites fluid, clone Russian Spring Summer Encephalitis VR79; ATCC) or polyclonal mouse anti-West Nile virus E protein (obtained from Dr. Robert Tesh, World Reference Center for Emerging Viruses and Arboviruses) followed by secondary goat anti-mouse peroxidase-labelled polymer (DAKO Envision Systems) and application of peroxidase substrate containing 0. 4 mg/ml 3,3′ diaminobenzidine and 0. 0135% hydrogen peroxide in PBS. To bypass entry steps, SW13 cells were electroporated essentially as described [32] with in vitro transcribed RNA generated from plasmid pACNR-FLYF17Da, YF-R. luc2A-RP, or pYF-R. luc2A-RP-ΔDD. Stocks containing VSV-G pseudotyped lentiviral particles were generated essentially as described [7] by cotransfection using Fugene 6 (Roche) of 293T cells with plasmids encoding VSV-G, HIV gag-pol and the lentiviral provirus plasmid at a ratio of 1∶4∶4 µg. Medium overlaying the cells was harvested at 48–72 h after transfection, filtered through a 0. 45 µM filter, aliquoted and stored at −80°C. Transductions were performed by incubating cells with the pseudoparticles in the presence of 8 µg/ml polybrene. The tissue culture 50% infectious dose (TCID50) was determined essentially as described [33] by titration on the TZM HeLa cell derivative [34], which expresses β-galactosidase under the control of the HIV LTR. Comparison of the TCID50 of a VSV-G pseudotyped V1-GFP stock, as determined on TZM cells, to the number of GFP-positive cells obtained after transduction of the target cell line with the same V1-GFP stock allowed for calculation of the appropriate TCID50 to utilize to achieve the desired transduction efficiency. For protein expression, transduction efficiency was typically in the range of 70–95%. A cDNA library was generated as described [7] from mRNA isolated from a BHK-21 derivative cell line, designated BHK/NZAP-Zeo [21], expressing the amino terminal fragment of the rat zinc-finger antiviral protein, after treatment for 6 h with 100 U/ml Universal type I IFN (PBL Biomedical Laboratories). Briefly, total RNA was harvested with Trizol (Invitrogen) and mRNA isolated by oligo dT selection (Oligotex mRNA Maxi Kit, Qiagen) according to the manufacturer' s recommendations. The cDNA synthesis was carried using the method of the SMART cDNA Library Construction Kit (Clontech) with the outlined modifications [7] which utilized Superscript III (Invitrogen) for first strand synthesis and TaqPlus Long PCR System (Stratagene) for second strand synthesis and amplification, SfiI digestion and size fractionation with cDNA Size Fractionation Columns (Invitrogen). After ligation to the minimal HIV provirus V1 vector that had been SfiI-digested, and electroporation of DH10B cells (Invitrogen), the library was divided into two sub-libraries (L1 and L2), each with >3,000,000 clones, for amplification. Plasmid DNA was isolated from the amplified libraries using a Qiagen MaxiPrep Kit, and VSV-G pseudotyped particles expressing the library cDNAs were generated as described above. Library L1 contained insert sizes ranging from ∼400 to ∼2,400 nt and was utilized for these studies. The L1 cDNA library was screened for cDNAs able to confer resistance to YFV 17D-mediated cell death using a previously described iterative approach [7] and as outlined in Figure 1. SW13 cells (18 million) were transduced with the L1 library of lentiviral particles (0. 45 TCID50/cell) and two days later were challenged with YFV 17D (moi = 5). After maintenance in MEM with 2% FBS for 7 d, the surviving Round 1 (Rd 1) cells were pooled and expanded in growth medium. The cDNA clones present in the surviving Rd 1 cells were rescued by transfection of cells in two 10 cm dishes with 15 µg VSV-G- and 5 µg HIV gag-pol-encoding plasmids diluted in OptiMem containing 40 µl Lipofectamine 2000 (Invitrogen) -according to the manufacturer' s recommendations. The medium overlying the cells was collected 2 d later, pooled, filtered through a 0. 45 µM filter, aliquoted and stored at −80°C. For subsequent steps, the rescued lentiviral stocks were treated for 2 h at room temperature with a 1∶100 dilution of mouse monoclonal 8A3 YFV neutralizing antibody prior to transduction of naïve SW13 cells in order to prevent cell death mediated by residual YFV in the lentiviral stock. Each rescued stock was utilized undiluted for subsequent transductions. Two additional rounds of transduction and challenge were performed to generate Rd 2 and Rd 3 cells and rescued lentiviral stocks. Rd 2 was performed on ∼4×106 SW13 cells, (0. 0003 R1 TC1D50/cell), and a YFV 17D challenge (moi = 5) 2 d later. Rescue was performed on the surviving Rd 2 cells in three 35 mm dishes, using Lipofectamine 2000-mediated transfection as described above (13 µl reagent, with 3 µg VSV-G- and 1 µg HIV gag-pol-encoding plasmids per dish). Rd 3 was performed on ∼2×106 SW13 cells (0. 07 R2 TC1D50/cell) and a YFV 17D challenge (moi = 1) 2 days later. A large number of cells survived the challenge compared to cells transduced with V1-GFP and challenged in parallel (see Figure 2A) and these Rd 3 cells were expanded for further testing. Rescue was performed as in Rd 2. A repeat experiment using the same Rd 2 rescued lentiviral stock gave similar results and an additional selection round using particles rescued from the Rd 3 cells also yielded many surviving Rd 4 cells (not shown). The predominant cDNA present in the Rd 3 cells was isolated by PCR. Rd 3 cellular DNA was isolated using the DNeasy Blood and Tissue Kit (Qiagen) and amplified using the Expand High Fidelity PCR System (Roche) and primers flanking the cDNA insert in the V1 vector (5′-GATTGTAACGAGGATTGTGGAACTTCTGGG-3′ and 5′-GATCCACAGATCAAGGATATCTTGTCTTCTTTGGG-3′). The PCR product was digested with SfiI, recloned into the V1 vector and sequenced using the above primers, as well as with primers designed to bind within the DNAJC14 sequence (5-TTGAAGCCACAGCATCC-3′ and AAGTCTACAGCTGCTCGAG-3′). Blast analysis demonstrated high homology with murine and human DNAJC14 with the cDNA insert predicted to express an amino-terminally truncated form of the protein. The nucleotide sequence of the truncated hamster DNAJC14 cDNA was submitted to GenBank (BankIt1399336 DNAJC14 HQ415606). To demonstrate DNAJC14 self interaction, HEK293T cells were seeded 16 h before transfection onto 60 or 100 mm tissue culture dishes at a density of 1. 6×106 or 4×106 cells, respectively. The cells were co-transfected using Fugene 6 (Roche) with 2 (60 mm dish) or 4 (100 mm dish) µg each of pTrip-EGFP-hDNAJC14-NT5 and pV1-hDNAJC14-FL or mutants. Forty-eight hours post transfection, cells were scraped into ice-cold PBS and solublized with lysis buffer (10 mM HEPES, pH 7. 5,150 mM KCl, 3 mM MgCl2,0. 5% NP-40,1×Proteinase inhibitor cocktail (Roche) ), using 300 or 600 µl for 60 or 100 mm dishes, respectively. After disruption by passing through a 27G needle 5 times and clarification by centrifugation at 15,000×g for 10 min at 4°C, 300 µl of the soluble fraction was incubated overnight at 4°C with anti-myc, anti-GFP or control antibody. Pre-equilibrated protein A/G-agarose beads (Santa Cruz) were then added, and after 2 h of incubation, were collected by centrifugation and then washed four times with 600 µl washing buffer (10 mM HEPES, pH 7. 5,150 mM KCl, 3 mM MgCl2,0. 05% NP-40). The bound proteins were eluted by boiling in sodium dodecyl sulfate (SDS) sample buffer and were subjected to Western analysis. To demonstrate the NS3-DNAJC14 interaction, SW13 cells were transduced with lentivirus expressing the myc tagged CT1 hDNAJC14 mutant and 2 d later were infected with YFV (moi = 1). After 2 d the cells were harvested and immunoprecipitation performed as described above except that the lysis and wash buffer contained 1% NP-40. Cells were directly lysed with 2×SDS loading buffer (100 mM Tris-Cl pH 6. 8,20% Glycerol, 4% SDS, 3% β-mercaptoethanol, 0. 02% bromophenol blue) and boiled for 5 min. Proteins were separated by SDS-polyacrylamide gel electrophoresis (PAGE) and transferred to a Hybond ECL Nitrocellulose Membrane (GE Healthcare Life Sciences). The membrane was incubated in blocking buffer (PBS, 0. 05% Tween 20,5% dried milk) for 2 h, and then incubated with primary antibody diluted in blocking buffer at 4°C overnight. The membrane was washed 3 times in PBS supplemented with 0. 05% Tween 20 and incubated for 2 h at room temperature with HRP-conjugated secondary antibody. After 3 washes, the membrane was visualized by ECL Supersignal West Pico (or Femto) Chemiluminescent substrate (Thermo scientific). Cells were fixed with 4% formaldehyde in PBS and permeablized with 0. 2% Triton X-100 in PBS for 5 min at room temperature. After being washed with PBS, samples were then blocked and incubated overnight with primary antibody in 3% BSA in PBS at 4°C After three washes with PBS, samples were incubated at 37°C for 1 h with Alex488- or Alex594-conjugated secondary antibody. Coverslips were finally mounted with Mowiol Mounting Media [0. 1 M Tris-HCl, pH 8. 5,25% glycerol, 10% Mowiol 4–88 (Calbiochem 475904) ] and observed by Leica LSM510 confocal laser with a 100×NA 1. 3 oil immersion objective. Images were captured using the LSM software and processed using ImageJ. Cells were harvested by trypsinization, resuspended in PBS with 1% BSA, and then fixed in 2% formaldehyde in PBS. Samples were analyzed for expression of RFP and Venus using a BD LSR II flow cytometer, analyzing 10,000 events per sample. Data were processed using the FlowJo software. For the luciferase activity assay, transduced and infected Huh7. 5 cells were washed twice with PBS and lysed with 1× Passive Lysis Buffer (Promega) according to the manufacture' s recommendations. Luciferase activity was measured using the Renilla Luciferase Assay system (Promega) using a Lumat LB9507 Luminometer (Berthold). Triplicate wells of SW13 cells transduced with V1-GFP control or DNAJC14-expressing lentiviruses were seeded in 24 well plates at 1×105 cells per well in the presence of 60 nM Stealth RNAi siRNA Negative Control Med GC (12935-300) or DNAJC14-targeting Stealth siRNA (CCGAGGAACUAUGUCAACUUGGACA) and Lipofectamine RNAiMAX (Invitrogen) according to the manufacturer' s reverse transfection protocol. The siRNA transfection was repeated 2 d later, using forward transfection with 60 nM siRNA. After an additional 2 d incubation, the cells were infected with YFV (moi = 5) and 24 h later the medium was collected for virus titration. For each condition, cells from one of the triplicate wells were harvested for Western blot analysis, while the remaining 2 wells were pooled for RNA harvest. RNA was purified using the RNeasy minikit (Qiagen) and each sample was reverse transcribed in triplicate using random primers and the Superscript III first strand synthesis kit (Invitrogen). Quantitative PCR was performed using the QuantiTect SYBR Green PCR Kit (Qiagen) and a LightCycler 480 (Roche) for detection as previously described [35]. Qiagen QuantiTect primers (QT00197043) were used for DNAJC14 amplification; levels were normalized to those of GAPDH, using a GAPDH primer set (sense: CCCACTCCTCCACCTTTGAC, antisense: CATACCAGGAAATGAGCTTGACAA) as described [36].
To identify cellular factors with antiviral activity against flaviviruses, we initiated a screen for host proteins that could inhibit cell death caused by YFV infection. We reasoned that a cDNA expression library generated from cells treated with interferon (IFN) -α to increase expression of antiviral factors would represent both IFN induced and constitutively expressed factors, some of which might have a protective effect against YFV. For this study, we utilized a cDNA library that we had generated (for other unrelated studies) from a BHK-21 cell derivative previously shown to develop dramatic resistance to Sindbis virus infection upon treatment with IFN [21]. Although we had some concerns regarding possible species incompatibilities for the function of hamster proteins in cells of other species, we thought it likely that factors influencing YFV, which has conserved replication strategies in both vertebrate and invertebrate cells, would function in a broad range of cells. We transduced YFV-susceptible human SW13 cells with the expression library, challenged these cells with YFV (vaccine strain 17D), and identified the cDNA (s) expressed in cells that survived the infection. During initial screens, we encountered several challenges, including difficulty cloning out rare surviving cells, and the presence of multiple library integrants. In order to overcome these obstacles, we expressed the cDNA library using a lentiviral vector (V1) in cells that are amenable to repackaging, as has been previously described [7]. Transfection of cells surviving the YFV challenge with helper plasmids expressing HIV gag-pol and an envelope glycoprotein (VSV-G) allows packaging of the lentiviral genomes, generating a lentivirus stock enriched for genes that confer a selective advantage (Figure 1). This approach obviates the need to clone individual cells, and allows iterative cycles of library transduction, YFV challenge, and rescue of sequences conferring survival. A YFV neutralization step of the selected, rescued lentiviral particles was used to prevent cell death mediated by residual virus during transduction of the naïve SW13 cells. After multiple rounds, the pool of cDNA-expressing lentiviruses will have markedly reduced complexity and active cDNA clones will be highly enriched. After two rounds of selection, transduction of SW13 cells with the enriched library of lentiviral constructs resulted in extensive resistance to YFV-induced cell killing (Figure 2A). These “Round 3” (Rd 3) cells were expanded, retested for their susceptibility to YFV-induced cytopathicity and found to be resistant at several multiplicities of infection (moi, Figure 2B). DNA was harvested from the Rd 3 cells, and the cDNA inserts were amplified using primers specific for the V1 vector (Figure 2C). The single major PCR product (∼2. 5 kb) was cloned, sequenced and found by BLAST analysis to show high homology to a murine (as well as human) Hsp40 family member, DNAJC14. The cDNA was predicted to express an N-terminally truncated version of the protein, which, based on the human sequence, lacked the first 304 amino acids of the 702 amino acid protein. DNAJC14 and the truncated hamster clone are shown schematically in Figure 2D. To test whether the DNAJC14 sequence obtained by PCR could confer resistance to YFV-mediated cell death in naïve cells, the PCR product was cloned back into the V1 lentiviral vector. Five individual clones (designated 1-1,1-2,1-3,1-4, and 1-5) were packaged and the VSV-G pseudotyped lentiviral particles were used to transduce naïve SW13 cells, which were challenged with YFV. Clone 1-1 was unable to confer resistance to YFV-mediated cell death, while each of the remaining four clones resulted in protection (data not shown). Sequencing of clones 1-1 and 1-2 indicated that both encoded a 398 amino acid protein (equivalent to human DNAJC14 aa 305–702) but clone 1-1 encoded a leucine to proline mutation at position 466, likely introduced during PCR amplification. This leucine is within the highly conserved J domain and is conserved amongst human, chimp, dog, cow, mouse and rat sequences. We conclude from these studies that expression of amino acids 305–702 of hamster DNAJC14 is able to confer resistance to YFV-mediated cell death. Because our screen used cDNA from IFN-α-treated cells, we tested whether interferon treatment of SW13 cells results in upregulation of DNAJC14 mRNA levels. After treatment for 8 h with IFN-α, DNAJC14 RNA levels were quantified by real time RT-PCR. No significant differences in DNAJC14 RNA levels were found in cells treated with doses of IFN-α ranging from 0 to 1000 IU/ml (data not shown). Detection of eIF2α phosphorylation by Western blot demonstrated that IFN was active in these cells (data not shown). Although we cannot exclude that the gene may be upregulated in response to IFN-α in some cell types, DNAJC14 appears to be constitutively expressed in SW13 cells. Our screen utilized protection from viral-mediated cell death as an endpoint for the isolation of host proteins with activity against YFV. Survival could be due to inhibition of virus replication or prevention of activation and/or blocking of cell death pathways. To test whether expression of DNAJC14 resulted in inhibition of viral growth, we infected the Rd 3 cells with YFV and quantified virus production (Figure 3A). Compared to naïve cells, YFV propagation was markedly reduced in DNAJC14 expressing cells, with a greater than 2 log reduction in infectious titers at 48 h, and virus production continuing to decrease over time. In contrast, robust replication occurred at 48 h in the naïve cells, with infectious titers decreasing at 5 d, at which time the cells displayed massive cytopathic effect. To determine whether the decreased infectious titers were a result of decreased intracellular viral replication, we performed Western blot analysis (Figure 3B) on YFV-inoculated cells transduced with V1 vector containing the clone 1-2,1-3,1-4 and 1-5 inserts. We found reduced levels of the viral NS3 protein in the cells expressing hamster DNAJC14 compared to control cells transduced to express GFP. These results demonstrate that truncated hamster DNAJC14 blocks YFV infection and/or replication, which results in prolonged cell survival. The truncated hamster DNAJC14 isolated in our screen is highly homologous to murine and human DNAJC14 proteins (89% identical and 93% similar to the corresponding region of the proteins). We therefore determined if expression of the 702 amino acid human DNAJC14 protein, also designated dopamine receptor interacting protein (DRIP78), could also confer protection against YFV-mediated cell death. We generated V1 lentiviral expression constructs to for both the full-length hDNAJC14 (hDNAJC14-FL) as well as an amino terminal truncation mutant (designated NT1) expressing amino acids 305–702 of human DNAJC14 (hDNAJC14-NT1), which corresponds to the hamster protein identified in our screen. A C-terminal myc epitope tag was engineered in the constructs to allow detection of the proteins. After packaging, the lentiviral pseudoparticles were used to transduce SW13 cells, which were then challenged with YFV (Figure 3C). Both the full-length and truncated versions of DRIP78 inhibited intracellular YFV NS3 accumulation. These studies demonstrate that the human DNAJC14 homolog is able to inhibit YFV infection and/or replication, as well as show that the addition of a C-terminal epitope tag does not interfere with the inhibitory activity. Bovine DNAJC14 (also known as J-domain protein interacting with viral protein, or Jiv) has previously been implicated in regulation of pestivirus (BVDV) replication. Intriguingly, cytopathic strains of the virus can contain insertions of DNAJC14 within their genome [37], [38], [39]. A portion of the Jiv protein (Jiv90) is required for the substrate interaction and activity of the viral autoprotease (NS2) and the subsequent establishment of replication complexes [40], [41], [42]. We therefore wondered how expression of DNAJC14 would affect other members of the Flavivirus genus, as well as the Hepacivirus genus member HCV. We first compared the ability of DNAJC14 to inhibit YFV 17D (vaccine strain) and the prototype virulent Asibi strain isolated from a young Ghanaian patient in 1927 [43]. Measuring of infectious virus production by transduced cells indicated that both the vaccine and Asibi YFV strains were susceptible to inhibition by the truncated or full-length hDNAJC14 (Figure 4A and B). Kunjin, a more distantly related mosquito-borne Flavivirus genus member (from the Japanese encephalitis serocomplex group) was also found to be susceptible to hDNAJC14-mediated inhibition (Figure 4C). A representative of the tick-borne encephalitis group, Langat virus, was similarly susceptible to hDNAJC14' s inhibitory effects (Figure 4D). It therefore seems likely that DNAJC14 broadly affects members of the Flavivirus genus. To establish whether hDNAJC14 also has effects on the Hepacivirus genus, we used HCV Jc1FLAG2 (p7-nsGluc2A), a cell-culture infectious virus (HCVcc) expressing a luciferase reporter [26]. Again, both the full-length DNAJC14 and NT1 truncation mutant, corresponding to our isolated hamster clone, inhibited viral propagation. Taken all together, these results suggest that DNAJC14 modulates the replication of many or all members of the Flaviviridae family. Since DNAJC14 regulates dopamine D1 receptor transport [44], it is possible that inhibition of YFV is the result of disrupting the transport of a cell surface receptor (s) utilized by the virus. We introduced the YFV genomic RNA into cells by electroporation in order to bypass entry and to determine if downstream steps are affected by DNAJC14. We found that DNAJC14 was still able to mediate inhibition of YFV protein expression when entry steps are bypassed; infectious virion production was also reduced (Figure 5A and B). The reduced protein levels and virion production might be due to decreased translation, RNA replication, assembly and/or egress. Using a YFV replicon (Figure 5C) expressing luciferase in place of the structural proteins [17], we tested whether DNAJC14 results in reduced expression of viral protein. The results (Figure 5D, wildtype replicon) demonstrate that YFV translation levels are reduced at later time points in the DNAJC14-expressing cells. Since the replicon does not express the structural proteins and is incapable of spread, the results suggest that DNAJC14-mediated inhibition can occur at a step after entry and prior to assembly, egress and spread. Interestingly, luciferase expression at early time points after electroporation was similar in the control (V1-GFP) and DNAJC14-expressing cells, suggesting that genome translation is not inhibited by DNAJC14. At later times (after 8 h) increased luciferase activity was detected in the control cells, suggesting that new RNA had been synthesized for translation. Use of a replicon containing a mutation abolishing RNA-dependent RNA polymerase activity (ΔDD) demonstrates that translation of the genomic RNA is similar in DNAJC14 overexpressing and control cells. Taken together the results indicate that a step after entry and translation and before assembly and egress is affected by DNAJC14. To ascertain determinants of DNAJC14 inhibitory function, we generated deletion and point mutants and tested their ability to inhibit YFV infection. A schematic of the deletion mutants is shown in Figure 6A. Expression levels, as determined by Western blot detecting the C-terminal myc tag on each of the constructs, were variable (Figure 6B), although immunofluorescence analysis verified almost 100% percent transduction efficiency for each of the mutants (data not shown). DNAJC14 has been proposed to reside in the ER membrane with both its N and C termini located within the cytoplasm [44]. This predicted topology was based on the interaction of DNAJC14 with the C terminus of the dopamine D1 receptor, as well as on DNAJC14 hydrophobicity plots and the absence of a signal peptide. Topology prediction programs suggest three potential regions that may serve as transmembrane (TM) domains. The truncated hamster mutant identified in our screen (NT1) contains an amino terminal deletion and is predicted to have one TM domain. Of the N terminal deletion mutants, NT3, NT4 and NT5 (lacking one, two or all three potential TM domains) exhibited similar antiviral activity to the full-length protein, while NT1 (lacking two) and NT2 (containing all three TM domains) exhibited the most potent activity (Figure 6C). Thus while the most inhibitory mutants contained at least one putative TM domain, the presence of a TM domain is not strictly required for inhibition. The C terminal deletion series were uninformative with respect to the role of the TM domains, since deletion of the C terminal 77 amino acids of DNAJC14 (mutant CT1), and various further deletions (mutants CT2, CT3, CT4, and CT5, which lacks all 3 TM domains) all resulted in a protein devoid of antiviral activity (Figure 6C). This suggests the carboxyl terminal 77 amino acids of DNAJC14 are required for antiviral activity. Although mutants CT3, CT4, and CT5 all contained deletions of the J domain, they also were not informative as to the role of the J domain in antiviral activity, since they also lacked the important C terminal domain. We utilized the NT5 mutant, which has robust expression and inhibitory activity equivalent to wildtype hDNAJC14, as the backbone to test several point mutations for their affect on YFV inhibition (Figure 6B, C). Our initial hamster clone 1-1 construct contained a presumed PCR-induced mutation at leucine 466 (to proline) within the J domain and was unable to confer resistance to YFV (not shown). We tested the L466P mutation in the context of hDNAJC14-NT5 and found that it abrogated the antiviral activity against YFV, suggesting a role for the J domain in the inhibitory process. Within the J domain, the conserved HPD motif is important for accelerating the ATPase activity of Hsp70 [45] and mutation of this motif (mutant H471Q) resulted in a noninhibitory protein. Studies on the interaction of rat DNAJC14 with the dopamine receptor [44] implicate the zinc fingers within the Jiv90 domain as important to the dopamine receptor-DNAJC14 interaction; mutation of cysteine 536 (537 in human DNAJC14, Figure 6), to serine abolished the DNAJC14-dopamine receptor interaction. We therefore generated mutations in two of the conserved Jiv90 cysteine residues, predicted to be involved in zinc coordination. Interestingly, mutants C537S and C559S could still inhibit YFV infection. We also mutated two residues (Y617A, I619A) that are required for maximal bovine Jiv90-mediated stimulation of BVDV NS2-3 cleavage [40]. Interestingly, these two mutants also displayed potent anti-YFV activity. Taken all together, the results suggest that the J domain and C-terminal domain are important for DNAJC14' s inhibitory effects on YFV. Both the DNAJC14 determinants important for modulation of pestivirus and flavivirus replication, as well as the result of DNAJC14 overexpression differ for viruses in these two Flaviviridae genera. Hsp40 family members are categorized into three classes [45], [46], [47]. Type I proteins contain the J domain at the N terminus followed by a glycine/phenylalanine rich region, four zinc finger motifs and a peptide binding fragment, with a C-terminal dimerization domain. Type II proteins contain an amino terminal J domain, and C-terminal peptide binding fragment, but lack the zinc-finger motifs, while Type III proteins are variable, with the J domain localized anywhere in the protein. DNAJC14 would thus be categorized as a Type III Hsp40, although the presence of two zinc-finger motifs downstream of the J domain suggests some similarities to the Type I members. Structural and functional analyses of several Type I and Type II Hsp40 members [45], [46] demonstrate that the C-terminal domains mediate dimerization. We therefore investigated whether DNAJC14 was capable of self-interaction. Using the NT5 mutant, which contains the C-terminal region, we tested its ability to interact with itself and with full-length DNAJC14. SW13 cells were cotransfected with plasmids expressing GFP and myc tagged DNAJC14 proteins and immunoprecipitations were performed using anti-myc antibodies. GFP-tagged NT5 co-purified with myc-tagged DNAJC14 or NT5 during myc-mediated immunoprecipitation, demonstrating self-interaction (Figure 7A). The NT5 self-interaction was verified by the reciprocal immunoprecipitation using anti-GFP antibodies (Figure 7B, left panel). However, mutant NT5 lacking the C-terminal 77 amino acids (NT5CT1) failed to co-purify in the immunoprecipitation (Figure 7B, right panel). Thus, similar to the Type I Hsp40 members, DNAJC14 multimerizes, and the self-interaction is mediated by the C-terminal 77 amino acids. Since the CT1 mutant also fails to inhibit YFV, it is possible that multimerization (likely dimerization) is important for DNAJC14' s antiviral activity. DNAJC14 is a required cofactor for the BVDV NS2 protease, which mediates autoproteolytic cleavage of NS2-3 as a necessary prerequisite for RNA replication [40]. Overexpression of DNAJC14 enhances cleavage at the 2/3 site, RNA replication and cytopathogenicity, but results in reduced infectious virion production due to a requirement for uncleaved NS2-3 for late life cycle events [48]. In contrast, in the case of YFV, DNAJC14 overexpression inhibits RNA replication (Figure 5D). Based on this apparent opposite effect, we wondered if DNAJC14 might inhibit (rather than enhance) YFV NS2B-3 cleavage and result in reduced levels of subsequent RNA replication. It is of interest that for YFV, cleavage at the NS2B/3 site is mediated by the viral NS3 protease, while for HCV the cleavage of the NS2/3 site is mediated by NS2. Since the effects of DNAJC14 on cleavage at the NS2/3 site of BVDV was successfully determined by coexpression of DNAJC14 and viral fragments capable of self-cleavage [39], we took a similar approach to test whether DNAJC14 inhibited YFV NS2B-3 cleavage. We first generated a doxycycline-inducible cell line expressing hDNAJC14 mutant NT5 with a C-terminal myc tag (Figure 8A). As expected, YFV replication was reduced in this cell line when treated with doxycycline to induce hDNAJC14-NT5 expression (Figure 8B). Using transfection, we expressed Flag-tagged self-cleavage competent YFV NS2B-3181 as well as a form incapable of cleavage due to a S138A active site mutation within NS3 [49] and monitored cleavage in doxycycline treated (expressing hDNAJC14-NT5) or non-induced control cells by Western blot. Similarly, we expressed Flag-tagged self-cleavage competent HCV NS2-3 protease, as well as a form incapable of autocleavage due to a H143A active site mutation within NS2 [11]. A plasmid expressing GFP was cotransfected to monitor transfection efficiency. As shown in Figure 8C, wildtype NS2B-3 or NS2-3 was efficiently processed resulting in similar levels of NS2 in the presence or absence of DNAJC14-NT5. The low levels of cleavage incompetent HCV NS2B-3 are likely due to the previously described rapid degradation of uncleaved NS2-3 [50]. Thus, contrary to our prediction, DNAJC14 does not grossly inhibit YFV, or HCV polyprotein cleavage. However, due to the sensitivity of this assay, subtle inhibition of processing efficacy would likely not be detected. Moreover, given the efficiency of cleavage in cells not induced to express DNAJC14, we cannot exclude an enhancement effect, similar to that seen with BVDV NS2-3 processing, of DNAJC14 on YFV NS2B-3 or HCV NS2-3 cleavage. Since DNAJC14 does not inhibit YFV genome translation yet blocks RNA replication, we wondered if it might interfere with the formation of functional replication complexes, which assemble on ER-derived membranes. Studies to investigate whether hDNAJC14 colocalizes with replication complexes in YFV infected cells are complicated by the fact that DNAJC14 expression inhibits YFV replication. To determine whether hDNAJC14 colocalizes with YFV replication complexes, we made use of the non-inhibitory DNAJC14 mutants H471Q and CT1 and monitored their colocalization with YFV NS3. SW13 cells transduced with lentiviruses expressing hDNAJC14 mutants were infected with YFV and the localization of NS3 and hDNAJC14 was examined by confocal microscopy (Figure 9A). As a control, we examined the localization of calnexin and demonstrated that YFV infection results in a redistribution of this ER marker to colocalize with NS3 in infected cells (Figure 9A). Full-length DNAJC14 containing the J domain mutation H471Q (FL-H471Q) and mutant CT1 both colocalized with NS3 in infected cells. The results are consistent with the known ER reorganization that occurs during YFV replication complex formation and suggest that DNAJC14 proteins associated with the ER membrane redistribute to replication complexes during YFV infection. Expression levels of the CT1 mutant, which is recruited to sites containing NS3 (Figure 9A) without blocking replication (Figure 6C), are similar to expression levels of the inhibitory full-length protein (Figure 6B). This makes a nonspecific process, such as the induction of ER stress due to protein overexpression, unlikely for the inhibitory mechanism. To assess further whether DNAJC14 associates with the viral replication complexes, we looked for a physical interaction using coimmunoprecipitation. Cells transduced (or not) to express the myc epitope tagged noninhibitory CT1 mutant were infected with YFV. CT1 and associated proteins were isolated from lysates using anti-myc antibody. As can be seen in Figure 9B, NS3 was coimmunoisolated with CT1, while the ER marker calnexin was not. Thus while both calnexin and CT1 colocalize with NS3 in immunofluorescence assays (Figure 9A), NS3, but not calnexin, was found to be in a physical complex with CT1. We utilized antibodies directed against dsRNA as another means to identify replication complexes and assess whether endogenous DNAJC14 is present (Figure 9C). Using anti-DNAJC14 antibody, we found that in uninfected cells, endogenous DNAJC14 in the cytosol predominantly displayed a diffuse pattern with occasional punctate staining. In infected cells the endogenous DNAJC14 demonstrated a more punctate staining pattern and the dsRNA was found colocalized with these punctate sites of staining. These findings demonstrate that both endogenous DNAJC14 and overexpressed non-inhibitory DNAJC14 mutants are recruited to YFV replication complexes, which suggests that endogenous DNAJC14 may facilitate replication complex formation. To test whether DNAJC14 might be required for, or facilitate virus replication, we used siRNA-mediated silencing to reduce levels of endogenous DNAJC14 and tested the ability of YFV to replicate. To evaluate replication capacity across a range of DNAJC14 levels, we used cells transduced with vector as well as cells transduced with lentivirus expressing DNAJC14 and subjected them to silencing with a control irrelevant siRNA or siRNA targeting DNAJC14 mRNA within the protein coding region. It should be noted that the absolute level of DNAJC14 RNA in normal cells (vector-transduced cells treated with control siRNA) is low, with DNAJC14 RNA levels more than 1000 fold lower than GAPDH mRNA levels (data not shown). Reducing levels of DNAJC14 mRNA by ∼2 fold, as measured by quantitative RT-PCR (Figure 10A), resulted in a ∼4 fold statistically significant (p<0. 0001) reduction in YFV titer (Figure 10B, compare vector cells treated with the control and DNAJC14 siRNAs). Western blot analysis using anti-DNAJC14 antibody demonstrates a reduction upon silencing at the protein level as well (Figure 10C). Although no protein band is apparent in the vector cells treated with the DNAJC14-targeting siRNA, given that mRNA was still detectable, a low level of residual protein could account for the modest reduction in viral replication. Despite multiple attempts we were unable to reduce the DNAJC14 mRNA levels lower than ∼2 fold (data not shown). Interestingly, cells transduced with lentivirus expressing DNAJC14 had a >300 fold increase in the level of DNAJC14 mRNA (Figure 10A,) and a corresponding increase in DNAJC14 protein levels (Figure 10C), which resulted in a ∼15 fold inhibition of YFV virion production (Figure 10B, compare vector and DNAJC14 cells treated with the control siRNA). Silencing of DNAJC14 in the DNAJC14-overexpressing cells resulted in intermediate mRNA (Figure 10A) and protein (Figure 10C) levels, although the RNA levels remained ∼50–60 fold higher than endogenous levels (compare DNAJC14 siRNA-treated DNAJC14 cells to control siRNA-treated vector cells). This residual intermediate level of DNAJC14 was less inhibitory than the high levels present in DNAJC14 overexpressing cells treated with the control siRNA, but still resulted in a 4. 7 fold inhibition of YFV replication compared to vector cells treated with the control siRNA (Figure 10B). Thus decreasing DNAJC14 levels by ∼2 fold or increasing levels by ∼50 fold each had a similar (∼4 fold) inhibitory effect towards YFV. Thus maximal YFV replication requires an optimal DNAJC14 concentration; levels too low or too high result in inhibition. A requirement for an optimal level of DNAJC14 and the ability of overexpressed wildtype DNAJC14 to inhibit YFV replication could be explained by DNAJC14 facilitating YFV replication complex formation in a stoichiometric process such that increased levels might function in a dominant negative fashion to inhibit replication complex formation. There is precedent for this, since DNAJC14 modulates BVDV NS2-3 cleavage in a temporal manner due to a stoichiometric mechanism [40], [41]. After translation of the BVDV polyprotein, NS2-3 autoprocessing is mediated in cis by the cysteine protease residing in NS2 [41], which requires DNAJC14 in a 1∶1 ratio [40]. RNA replication is dependent on this cleavage, due to a requirement for free NS3 for the formation of functional replication complexes [41]. Limiting amounts of cellular DNAJC14 thus limit processing and result in downregulation of RNA replication at later time points, allowing viral persistence [40]. Overexpression of DNAJC14 results in increased cleavage at NS2/3, increased RNA replication, and increased cytopathogenicity [39]. We wondered if inhibition of YFV might exhibit similar properties, in which the ratio of DNAJC14 to viral substrate is critical for its antiviral activity. If so, then inhibition would be expected to be dose-dependent, and continued translation of the incoming genome over time might restore the appropriate stoichiometry and thus allow replication to begin. Consistent with this hypothesis, we noticed that the antiviral activity of DNAJC14 diminished at later times after infection or electroporation (Figures. 4A, 5B). To test this hypothesis, we monitored the antiviral activity of DNAJC14 at the single cell level by flow cytometry. Cells transduced with RFP-tagged DNAJC14 (full-length and NT1 mutant) were infected with a YFV variant expressing Venus, and both virus replication (Venus) and DNAJC14 expression (RFP) were monitored. As shown in Figure 11A, the YFV signal was dramatically reduced in RFP-DNAJC14-FL- and -NT1-expressing cells compared to levels seen in cells expressing ZAP, an anti-Sindbis virus protein with no effect on YFV [10], [51]. In addition, the NT1 mutant demonstrated more potent inhibitory activity than full-length DNAJC14, which may be due to higher expression levels of NT1 as reflected by the RFP signal. Interestingly, both full-length and the NT1 mutant inhibited YFV in a dose dependent manner (Figure 11A), with lower YFV (Venus) signal seen in cells expressing higher levels of DNAJC14 (RFP). We next investigated the antiviral activity of mutant NT1 at various time points after infection (Figure 10B). At late time points (4 d), substantial YFV (Venus) signal was detected in RFP-positive cells. Even at this late time, when substantial YFV replication was occurring, the inhibition mediated by NT1 was still dose-dependent. To verify that increased Venus expression was due to increased replication, in a separate experiment we monitored infectious virus production in cells expressing RFP-DNAJC14-NT1 compared to nontransduced cells. Virion production on day 4 was found to be equivalent (Figure 10C), despite the fact that the DNAJC14 overexpressing cells were more resistant to cell death as monitored by crystal violet staining (data not shown). To exclude the possibility that the increase in virus replication seen after 3 to 4 d is due to the generation and replication of escape mutants, we collected the culture medium from cells after 4 d of infection and re-infected new cells expressing RFP-DNAJC14-NT1. Infection with this virus resulted in a similar early inhibition with a time-dependent increase in virus replication (data not shown). These results demonstrate that not only is DNAJC14-mediated inhibition dependent on the level of DNAJC14, but with time, levels that initially blocked YFV replication no longer are inhibitory. The failure to observe YFV replication in the Rd 3 cells (Figure 3A) is likely due to the fact that these cells had undergone prior infection and selection, resulting in a population of cells with maximal inhibitory properties.
DNAJC14 (also designated DRIP78, Jiv and HDJ3) is a member of the Hsp40 family of protein chaperones [45], [52]. Proteins in this family contain a 70 amino acid motif, designated the J-domain, which recruits Hsp70 family members and stimulates the ATP hydrolysis step of the chaperone process. J-domain containing proteins are involved in diverse cellular processes. The human DNAJC family has 23 members with the presence of the J domain being the single common feature. Although not extensively studied, involvement of these proteins in mitochondrial import, translation, endocytosis and exocytosis has been noted [45]. DNAJC14 has previously been implicated in the life cycle of a member of the Flaviviridae. The bovine homolog of this factor, Jiv, is essential for the polyprotein cleavage and replication of the pestivirus BVDV. Jiv acts as a required co-factor for the viral NS2 autoprotease, influencing its cleavage from NS3 and modulating RNA replication, virus production and cytopathogenicity of this pestivirus [38], [39], [42]. In contrast to our findings with YFV, increased expression of Jiv results in higher levels of BVDV RNA replication and virus-induced cell death. Interestingly, some cytopathic biotypes of BVDV are naturally occurring recombinant viruses, which have insertions of DNAJC14 in the NS2-3 coding region. A 90 amino acid domain common to all of the Jiv-containing cytopathic BVDV isolates is designated Jiv90 (see Figure 2D). This sequence is distinct from the J-domain and contains two conserved CXXCXXXH motifs. DNAJ proteins regulate the ATPase cycle of Hsp70 via their J domain, with the HPD motif critical in accelerating the Hsp70 ATPase activity, while the substrate-binding domain loads the substrate onto Hsp70 [53], [54]. Our studies with mutant H471Q suggest that the critical HPD motif within the J domain is required for DNAJC14 antiviral function, suggesting that ATP-driven Hsp70 chaperone activity may be involved in the process of RNA replication and its inhibition. Since Hsp70 chaperone activity occurs via a stoichiometric mechanism, with a single Hsp70 monomer per substrate [54] it seems likely that DNAJC14/Hsp70 chaperone activity is required for YFV replication complex assembly and that overexpression of DNAJC14 disrupts the chaperone/substrate complex. Dimerization of some Hsp40 family members is evolutionarily conserved and required for their function [45], [53]. The CT1 mutant lacks the ability to multimerize (Figure 8) and fails to inhibit YFV (Figure 6) as well as HCV (data not shown). Thus multimerization is likely critical for DNAJC14' s antiviral function. In our studies, we demonstrated that DNAJC14 noninhibitory mutants are found in YFV replication complexes, as measured by colocalization and coprecipitation with NS3 (Figure 10A and B). Moreover, endogenous DNAJC14 rearranges upon YFV infection and is found colocalized with active replication complexes, as determined by the presence of dsRNA (Figure 10C). This suggests that YFV replication complexes assemble at a specific ER membrane site where DNAJC14 is located, and that DNAJC14 (and likely Hsp70) is specifically recruited to facilitate formation of the viral replication complex. DNAJC14 overexpression would then result in disrupted chaperone/substrate stoichiometry and inhibit replication complex assembly. Alternatively, YFV may hijack DNAJC14-containing membranes for its replication complex assembly, and overexpression may inhibit the distribution and recruitment of other host factors localized to this membrane microdomain and required for replication complex formation. We realized that the inhibitory effect of DNAJC14 on YFV was diminished at later time points post infection and that inhibition was dose dependent, with higher levels of DNAJC14 resulting in lower levels of virus replication (Figure 11). One possible explanation is that at early time points, overexpressed DNAJC14 is in vast excess to its substrates (viral proteins) and this inappropriate stoichiometry results in inhibition of replication complex formation. Since DNAJC14 does not inhibit virus genome translation (Figure 5D), nor polyprotein processing (Figure 8C), viral protein would be predicted to accumulate with time. At some point, the level of viral protein (s) would result in an appropriate DNAJC14 to substrate ratio to allow the chaperone process to occur and thus overcome DNAJC14' s inhibitory effect. This is not dissimilar to the scenario occurring with BVDV, in which the DNAJC14 Jiv90 domain interacts with BVDV NS2-3 at a ratio of 1∶1. This stoichiometric mechanism might be a common requirement for normal DNAJC14 cellular function, as either overexpression or sequestration of DNAJC14 inhibits dopamine D1 receptor transport [44]. We found that multiple Flaviviridae were inhibited under conditions of DNAJC14 overexpression and wondered whether viruses from other families might be similarly affected. We tested DNAJC14' s effects on Sindbis virus, a positive strand RNA virus from the Alphavirus genus. In contrast to the flaviviruses, we found that DNAJC14 overexpression had no effect on viral replication, as measured by expression of a fluorescent reporter from the viral subgenomic RNA (data not shown). Thus replication complex formation for Sindbis virus is not likely affected by DNAJC14 overexpression. Interestingly, however, Sindbis virion production was reduced by DNAJC14 overexpression (data not shown). Thus a step in Sindbis virus assembly, such as glycoprotein maturation and transport from the ER-Golgi to the plasma membrane, where Sindbis budding occurs, may require DNAJC14-containing membrane microdomains and chaperone function. In addition, overexpression of DNAJC14 reduced VSV virion production (data not shown), suggesting an effect on VSV glycoprotein ER-golgi transport. Since it has been reported that DNAJC14 is involved in dopamine D1 receptor transport [44], it is likely that DNAJC14 facilitates specific membrane processes including vesicle transport and viral replication complex assembly. It is possible that many virus families have specific requirements for chaperone processes at various steps in their life cycle. Understanding these requirements and identifying the chaperones and proteins undergoing the chaperone process may lead to insights into similarities and differences between different virus families in these critical life cycle steps. DNAJC14 can both facilitate and inhibit YFV replication. Based on all of our findings, we propose the following model (Figure 12): Translation of the incoming YFV RNA and subsequent polyprotein processing generates the viral proteins necessary for the viral RNA replication process. DNAJC14 functions as a chaperone system, most likely with involvement of Hsp70, to facilitate a step in the YFV membrane-associated multiprotein complex assembly that is critical for the formation of replication complexes. The TM domains within DNAJC14 target the protein to a specific subcellular ER membrane location, wherein substrate selection and YFV replication complex formation occurs. Multimerization of DNAJC14 via its C-terminus is likely required for assembly of the chaperone/substrate complex. It is possible that each DNAJC14 monomer binds a substrate and together they promote the proper folding and interaction of the substrate pair, which might be different sites on the same protein, two different YFV proteins, or a viral protein and host protein necessary for viral replication. Newly generated viral RNA is produced, which after translation generates new substrate for the chaperone process, and the formation of additional replication complexes. Overexpression of DNAJC14 mutants that fail to multimerize (CT1, CT2, CT3, CT4 or CT5), or contain mutations in the critical J domain (L466P, H471Q, Figure 12A) has no effect on virus replication; these mutants fail to interact with and disrupt the normal chaperone components and therefore exhibit no antiviral activity. Expression of full-length (wildtype) DNAJC14 results in an excess of DNAJC14 relative to the substrate, and complexes with an inappropriate stoichiometric ratio are formed, disrupting the chaperone process (Figure 12 B). The N-terminal truncation mutants, which contain the C terminal multimerization motif and an intact J domain, also interact with the chaperone components, disrupting the proper chaperone/substrate stoichiometry. With time, continued translation of the incoming viral genome (or genome generated by very low levels of viral replication) results in the accumulation of viral proteins. Once the optimal substrate/chaperone ratio is established, the restored chaperone process results in replication complex formation and viral RNA replication. Further studies are required to address the viral and cellular substrate (s) for DNAJC14 and to determine if other host factors (for example, Hsp70) participate in this important chaperone process. | Viruses in the Flavivirus genus are transmitted by arthropods and cause significant disease burden across the globe. We undertook a screening approach to select for and identify host factors that provide resistance to death caused by infection with the mosquito-transmitted Flavivirus, yellow fever virus (YFV). We identified the host factor DNAJC14, an Hsp40 chaperone protein family member, as able to inhibit replication of the vaccine strain of YFV, and the virulent parental Asibi strain. We found that DNAJC14 also inhibits several other members of the Flavivirus genus, including Kunjin and the tick-borne Langat virus. Moreover, the Hepacivirus hepatitis C virus is also inhibited, suggesting a role for DNAJC14 in modulating the replication of all three genera of the Flaviviridae family. By probing the mechanism of the YFV inhibitory process, we determined that DNAJC14 inhibits at a post entry step, and most likely prevents the formation of functional replication complexes. We determined that DNAJC14 is required for YFV replication and that expression of inappropriately high levels of this protein results in a disruption of a process critical for viral RNA replication. Understanding how host factors inhibit or contribute to Flavivirus replication steps may identify new targets for antiviral drug development. | Abstract
Introduction
Materials and Methods
Results
Discussion | cell biology/membranes and sorting
virology/viral replication and gene regulation
virology/mechanisms of resistance and susceptibility, including host genetics | 2011 | Identification and Characterization of the Host Protein DNAJC14 as a Broadly Active Flavivirus Replication Modulator | 18,306 | 308 |
The population genetic perspective is that the processes shaping genomic variation can be revealed only through simultaneous investigation of sequence polymorphism and divergence within and between closely related species. Here we present a population genetic analysis of Drosophila simulans based on whole-genome shotgun sequencing of multiple inbred lines and comparison of the resulting data to genome assemblies of the closely related species, D. melanogaster and D. yakuba. We discovered previously unknown, large-scale fluctuations of polymorphism and divergence along chromosome arms, and significantly less polymorphism and faster divergence on the X chromosome. We generated a comprehensive list of functional elements in the D. simulans genome influenced by adaptive evolution. Finally, we characterized genomic patterns of base composition for coding and noncoding sequence. These results suggest several new hypotheses regarding the genetic and biological mechanisms controlling polymorphism and divergence across the Drosophila genome, and provide a rich resource for the investigation of adaptive evolution and functional variation in D. simulans.
Given the long history of Drosophila as a central model system in evolutionary genetics beginning with the origins of empirical population genetics in the 1930s, it is unsurprising that Drosophila data have inspired the development of methods to test population genetic theories using DNA variation within and between closely related species [1–4]. These methods rest on the supposition of the neutral theory of molecular evolution that polymorphism and divergence are manifestations of mutation and genetic drift of neutral variants at different time scales [5]. Under neutrality, polymorphism is a “snapshot” of variation, some of which ultimately contributes to species divergence as a result of fixation by genetic drift. Natural selection, however, may cause functionally important variants to rapidly increase or decrease in frequency, resulting in patterns of polymorphism and divergence that deviate from neutral expectations [1,2, 6]. A powerful aspect of inferring evolutionary mechanism in this population genetic context is that selection on sequence variants with miniscule fitness effects, which would be difficult or impossible to study in nature or in the laboratory but are evolutionarily important, may cause detectable deviations from neutral predictions. Another notable aspect of these population genetic approaches is that they facilitate inferences about recent selection—which may be manifest as reduced polymorphism or elevated linkage disequilibrium—or about selection that has occurred in the distant past—which may be manifest as unexpectedly high levels of divergence. The application of these conceptual advances to the study of variation in closely related species has resulted in several fundamental advances in our understanding of the relative contributions of mutation, genetic drift, recombination, and natural selection to sequence variation. However, it is also clear that our genomic understanding of population genetics has been hobbled by fragmentary and nonrandom population genetic sampling of genomes. Thus, the full value of genome annotation has not yet been applied to the study of population genetic mechanisms. Combining whole-genome studies of genetic variation within and between closely related species (i. e. , population genomics) with high-quality genome annotation offers several major advantages. For example, we have known for more than a decade that regions of the genome experiencing reduced crossing over in Drosophila tend to show reduced levels of polymorphism yet normal levels of divergence between species [7–10]. This pattern can only result from natural selection reducing levels of polymorphism at linked neutral sites, because it violates the neutral theory prediction of a strong positive correlation between polymorphism and divergence [5]. However, we have no general genomic description of the physical scale of variation in polymorphism and divergence in Drosophila and how such variation might be related to variation in mutation rates, recombination rates, gene density, natural selection, or other factors. Similarly, although several Drosophila genes have been targets of molecular population genetic analysis, in many cases, these genes were not randomly chosen but were targeted because of their putative association with phenotypes thought to have a history of adaptive evolution [11,12]. Such biased data make it difficult to estimate the proportion of proteins diverging under adaptive evolution. In a similar vein, the unique power of molecular population genetic analysis, when used in concert with genome annotation, could fundamentally alter our notions about phenotypic divergence due to natural selection. This is because our current understanding of phenotypic divergence and its causes is based on a small and necessarily highly biased description of phenotypic variation. Alternatively, a comprehensive genomic investigation of adaptive divergence could use genome annotations to reveal large numbers of new biological processes previously unsuspected of having diverged under selection. Here we present a population genomic analysis of D. simulans. D. simulans and D. melanogaster are closely related and split from the outgroup species, D. yakuba, several million years ago [13–15]. The vast majority of D. simulans and D. yakuba euchromatic DNA is readily aligned to D. melanogaster, which permits direct use of D. melanogaster annotation for investigation of polymorphism and divergence and allows reliable inference of D. simulans–D. melanogaster ancestral states over much of the genome. Our analysis uses a draft version of a D. yakuba genome assembly (aligned to the D. melanogaster reference sequence) and a set of light-coverage, whole-genome shotgun data from multiple inbred lines of D. simulans, which were syntenically aligned to the D. melanogaster reference sequence.
Seven lines of D. simulans and one line of D. yakuba were sequenced at the Washington University Genome Sequencing Center (the white paper can be found at http: //www. genome. gov/11008080). The D. simulans lines were selected to capture variation in populations from putatively ancestral geographic regions [16], recent cosmopolitan populations, and strains encompassing the three highly diverged mitochondrial haplotypes previously described for the species [17]. These strains have been deposited at the Tucson Drosophila Stock Center (http: //stockcenter. arl. arizona. edu). A total of 2,424,141 D. simulans traces and 2,245,197 D. yakuba traces from this project have been deposited in the National Center for Biotechnology Information (NCBI) trace archive. D. simulans syntenic assemblies were created by aligning trimmed, uniquely mapped sequence traces from each D. simulans strain to the euchromatic D. melanogaster reference sequence (v4). Two strains from the same population, sim4 and sim6, were unintentionally mixed prior to library construction; reads from these strains were combined to generate a single, deeper, syntenic assembly (see Materials and Methods), which is referred to as SIM4/6. The other strains investigated are referred to as C167. 4, MD106TS, MD199S, NC48S, and w501. Thus, six (rather than seven) D. simulans syntenic assemblies are the objects of analysis. Details on the fly strains and procedures used to create these assemblies, including the use of sequence quality scores, can be found in Materials and Methods. The coverages (in Mbp) for C167. 4, MD106TS, MD199S, NC48S, SIM4/6, and w501, are 56. 9,56. 3,63. 4,42. 6,89. 8, and 84. 8, respectively. A D. yakuba strain Tai18E2 whole-genome shotgun assembly (v2. 0; http: //genome. wustl. edu/) generated by the Parallel Contig Assembly Program (PCAP) [18] was aligned to the D. melanogaster reference sequence (Materials and Methods). The main use of the D. yakuba assembly was to infer states of the D. simulans–D. melanogaster ancestor. For many analyses, we used divergence estimates for the D. simulans lineage or the D. melanogaster lineage (from the inferred D. simulans–D. melanogaster ancestor) rather than the pairwise (i. e. , unpolarized) divergence between these species. These lineage-specific estimates are often referred to as “D. simulans divergence, ” “D. melanogaster divergence, ” or “polarized divergence. ” A total of 393,951,345 D. simulans base pairs and 102,574,197 D. yakuba base pairs were syntenically aligned to the D. melanogaster reference sequence. Several tens of kilobases of repeat-rich sequences near the telomeres and centromeres of each chromosome arm were excluded from our analyses (Materials and Methods). D. simulans genes were conservatively filtered for analysis based on conserved physical organization and reading frame with respect to the D. melanogaster reference sequence gene models (Materials and Methods). We took this conservative approach so as to retain only the highest quality D. simulans data for most inferences. The number of D. simulans genes remaining after filtering was 11,466. Ninety-eight percent of coding sequence (CDS) nucleotides from this gene set are covered by at least one D. simulans allele. The average number of lines sequenced per aligned D. simulans base was 3. 90. For several analyses in which heterozygosity and divergence per site were estimated, we further filtered the data so as to retain only genes or functional elements (e. g. , untranslated regions [UTRs]) for which the total number of bases sequenced across all lines exceeded an arbitrary threshold (see Materials and Methods). The numbers of genes for which we estimated coding region expected heterozygosity, unpolarized divergence, and polarized divergence were 11,403,11,439, and 10,150, respectively. Coverage on the X chromosome was slightly lower than autosomal coverage, which is consistent with less X chromosome DNA than autosomal DNA in mixed-sex DNA preps. Variable coverage required analysis of individual coverage classes (n = 1–6) for a given region or feature, followed by estimation and inference weighted by coverage (Materials and Methods). The D. simulans syntenic alignments are available at http: //www. dpgp. org/. An alternative D. simulans “mosaic” assembly, which is available at http: //www. genome. wustl. edu/, was created independently of the D. melanogaster reference sequence. One of the main goals of large-scale investigations of sequence divergence is to characterize the many biological factors influencing variation in substitution rates throughout the genome. Most analyses of Drosophila data focus on variation in functional constraints or directional selection as the main cause of heterogeneity in substitution rates across genes or functional elements [20,21]. However, the available data have been too sparse to detect any patterns of increasing or decreasing divergence along chromosome arms. Centromere proximal regions tend to be more divergent than distal regions (Figure 1, Figure S4, and Table S5). This pattern is more consistent for D. simulans than for D. melanogaster. Proximal euchromatic regions tend to have lower inferred ancestral GC content compared with distal regions of chromosome arms (Figure S4 and Table S5), which is consistent with the observation that D. simulans divergence was negatively correlated with inferred ancestral GC content (Materials and Methods) (50-kb windows, Spearman' s ρ = −0. 23, p = 1. 4 × 10−26) [30]. The correlation between ancestral GC content and divergence was much weaker and only marginally significant for D. melanogaster (Spearman' s ρ = −0. 05, p = 0. 03). However, while chromosomal gradients of divergence were observed for most chromosome arms (Figure S4 and Table S5), inferred ancestral GC content tends to show a less-consistent pattern. For example, some arms showed a more U-shaped distribution, with euchromatic regions near centromeres and telomeres tending to have higher estimated ancestral GC content (Figure S5). More proximal and distal regions also tend to have reduced crossing-over [39], which is consistent with the observation that inferred ancestral GC content is negatively correlated with cM/kb (Materials and Methods) on the X chromosome (Spearman' s ρ = −0. 33, p = 0. 0002) [59], the only chromosome arm for which we investigated correlates of recombination rate variation (see below). The neutral model of evolution predicts that gradients of divergence along chromosome arms are explained by gradients of functional constraint or mutation rates. For example, higher divergence in regions near centromeres could be explained if such regions harbor a lower density of functional elements (e. g. , genes). However, with the exception of chromosome arm 2L (Spearman' s ρ = −0. 19, p = 6 × 10−5), variation in coding sequence density (CDS bases per 50-kb window) showed no significant chromosomal proximal–distal trend, suggesting that variation in constraint that is associated with coding density plays, at best, a small part in explaining chromosomal gradients of divergence. More generally, the expectation of a negative correlation between coding density and nucleotide divergence in D. simulans was not met. This seemingly counterintuitive result probably reflects the fact that exons constitute a relatively small fraction of the genome and were not dramatically less diverged (0. 016) compared with intergenic DNA (0. 027). If proximal–distal gradients of decreasing divergence along chromosome arms result from variation in mutation rates, then the neutral theory predicts that we should observe similar gradients of polymorphism. This is the case for some chromosome arms but not others (Figure 1 and Table S5), after regions of reduced πnt in the most distal/proximal regions are excluded (Materials and Methods; this result is robust to variation in the extent of proximal and distal chromosomal regions removed from the analysis). Thus, variable neutral mutation rates alone is an insufficient explanation for the overall genomic patterns of variation. Below we address the possibility that recombination rate variation contributes to variation in D. simulans πnt and divergence across chromosome arms. There was considerable variance of polymorphism and divergence across chromosome arms, even when regions of severely reduced heterozygosity near centromeres and telomeres were excluded. Figure 1 clearly shows that variance in polymorphism and divergence is not randomly arranged, but rather appears to be spatially structured on the scale of several tens of kilobases. These qualitative visual assessments were supported by significant statistical autocorrelations (Materials and Methods) for nucleotide heterozygosity and divergence across all chromosome arms (Table S6) [60]. Furthermore, the strength of this autocorrelation appeared to differ across arms, because X and 3L show evidence of stronger correlations over longer distances (Figure 1). The strength of autocorrelation is consistently higher for heterozygosity than for divergence. Under the neutral theory, fluctuations in polymorphism and divergence could be the result of variation in gene density, with windows that have more exons per kb showing lower polymorphism and divergence. This expectation was not met. Indeed, for 50-kb autosome windows (but not X-linked windows), divergence is positively correlated with coding density (Spearman' s ρ = 0. 12, p < 0. 0001). This is consistent with an important role of directional selection on coding sequence to genome divergence, a point we will revisit in several analyses below. In contrast to the positive correlation between coding density and divergence, we found a negative correlation between coding density and D. simulans πnt (autosome Spearman' s ρ = −0. 10, p < 0. 0001; X Spearman' s ρ = 0. 29, p < 0. 0001). Overall, the contrasting correlations between coding density and polymorphism versus divergence suggest that directional selection in exon-rich regions generates greater divergence and reduced polymorphism due to hitchhiking effects [3,6, 61]. The analyses presented above, especially for the X chromosome data, strongly suggest that hitchhiking effects contribute to shaping patterns of polymorphism across the D. simulans genome. To provide a more quantitative assessment of the physical extent, magnitude, and biological basis of these hitchhiking effects, we carried out a genomic analysis of polymorphism and divergence in the context of the Hudson-Kreitman-Aguade (HKA) test [2] (Materials and Methods). The analysis should be thought of as a method for identifying unusual genomic regions rather than as a formal test of a specific model, since our data violate the assumptions of the simple neutral model (neutral alleles sampled from a single, equilibrium, panmictic population). The results (Figure 1, Datasets S6, S16–S20) statistically support our earlier contention and previous reports [7,8, 10,34,36], that Drosophila chromosomes show greatly decreased polymorphism, relative to divergence, in both telomere- and centromere-proximal regions. The fact that corrected X chromosome heterozygosity was not significantly different from autosomal heterozygosity, although X chromosome divergence was significantly higher than autosomal divergence, supports a role for hitchhiking effects reducing nucleotide variation on the X chromosome. Our previously mentioned result, that coding density is positively correlated with divergence and negatively correlated with polymorphism, suggested that hitchhiking effects of directional selection are more common in exonic sequence. The HKA-like analysis supports this contention. We identified regions of the genome that had either two or more consecutive, nonoverlapping 10-kb windows with p < 1 × 10−6 or four such windows with p < 0. 01. The number of coding nucleotides per 10 kb in these “hitchhiking windows” (n = 378 windows, mean coding density = 2,980 bp) was much higher than coding density in other windows (n = 9,329, mean coding density = 1,860 bp) (Mann-Whitney U, p < 0. 0001). An alternative hypothesis for the strong correlation between recombination and polymorphism and the high density of coding sequence in regions showing reduced heterozygosity-to-divergence ratios is background selection, a phenomenon whereby the removal of deleterious mutations reduces polymorphism at linked sites [1]. To address this possibility, we calculated Fay and Wu' s H [56] for 10-kb windows across the genome using only sites with a coverage of five alleles and windows not located in extended regions of reduced heterozygosity near the distal and proximal ends of chromosome arms (Materials and Methods). Hitchhiking effects of beneficial mutations are expected to cause an excess of high-frequency derived alleles (and a more-negative H statistic) relative to neutral theory predictions, while background selection predicts no such excess [1,72]. We compared the average H statistic for regions of the genome showing four or more consecutive 10-kb windows with an HKA-like test of p < 0. 01 versus 10-kb windows from the rest of the genome. For each chromosome arm, the H statistic was significantly more negative in windows showing a reduced heterozyogsity-to-divergence ratio (Mann Whitney U, p < 10−4 for each arm), which strongly supports the proposition that hitchhiking effects of beneficial variants is a major cause of the fluctuations in heterozygosity across the genome. Note, however, that this analysis does not rule out a contribution of background selection [1]. Several factors can generate lineage differences in divergence. For example, higher divergence in a lineage (relative to the lineage of its sister species) could be due to higher mutation rates, shorter generation times, or stronger directional selection. Investigating which classes of mutations or functional elements tend to show different levels of divergence in two lineages can inform our understanding of the causes of rate variation. Previously collected data from coding regions suggest that D. melanogaster evolves faster than D. simulans [89,90]. We found a similar pattern in that dN and dS are greater in D. melanogaster (median = 0. 0045 and 0. 0688) than in D. simulans (median = 0. 0036 and 0. 0507) (Table 1 and S3). This pattern has been interpreted as reflecting the reduced efficacy of selection against slightly deleterious variants in D. melanogaster, supposedly resulting from its smaller effective population size relative to D. simulans [89]. However, a different pattern is observed on a genome-wide scale, as median D. simulans divergence (50-kb windows; 0. 025), though only slightly greater than D. melanogaster (50-kb windows; 0. 022), is consistently greater across a large proportion of windows (Wilcoxon sign rank test, p = 1. 8 × 10−275). We consider the genomic faster D. simulans finding as provisional due the potential biases associated with D. melanogaster-centric alignments. For example, genomic regions that are evolving quickly only in D. melanogaster may drop out of the D. melanogaster–D. yakuba alignment, whereas regions evolving quickly only in D. simulans may be retained because of the relatively short D. melanogaster–D. simulans branch. Analysis of rate variation across site types (Table 1 and Table S3) reveals a more complex pattern. For example, D. simulans shows greater divergence than D. melanogaster for intergenic, intron, and 3′ UTR sites, whereas D. melanogaster shows greater divergence than D. simulans for 5′ UTRs, nonsynonymous sites, and synonymous sites. A decades-old issue in population genetics is the extent to which directional selection determines protein divergence. Several analytic strategies for investigating the prevalence of adaptive protein divergence between closely related species have been proposed (reviewed in [91]). Here we focused on two approaches. First, we used comparisons of synonymous and nonsynonymous polymorphic and fixed variants in individual genes to test the neutral model. Second, we identified proteins that show very different divergence estimates in D. simulans versus D. melanogaster. The same logic originally proposed in the MK test using nonsynonymous and synonymous variation can be extended to any setting in which variant types can be categorized, a priori. We tested variation in individual noncoding elements (introns, UTRs, and intergenic sequences) relative to variation at tightly linked synonymous sites (Materials and Methods) using the same criteria described for the MK tests; we present only polarized analyses (Datasets S2–S5). The proportion of tests (Materials and Methods) that rejected (p < 0. 05) the null model for 5′ UTR, 3′ UTR, intron, and intergenic sites are 0. 13,0. 13,0. 12, and 0. 17, respectively. However, unlike the case for the nonsynonymous versus synonymous polarized MK tests, of which only 6% of the significant tests deviated in the direction of excess polymorphism (relative to synonymous sites), a much greater proportion of noncoding MK tests deviated in this direction—0. 13,0. 24,0. 28, and 0. 28 for 5′ UTR, 3′ UTR, intron, and intergenic regions, respectively. Thus, the proportion of noncoding elements showing evidence of adaptive evolution for 5′ UTR, 3′ UTR, intron, and intergenic sites is 0. 12,0. 10,0. 08, and 0. 12, respectively, which is similar to the proportion of coding sequences inferred (by polarized MK tests) to be under direction selection (0. 14). It would be tempting to conclude from this result that intergenic variants are as likely to be under directional selection as nonsynonymous variants. However, such an interpretation ignores the fact that the number of variants per element for each MK test is much greater for intergenic sequence (median = 87) compared to the numbers for coding regions (median = 42), 5′ UTRs (median = 34), 3′ UTRs (median = 35), or introns (median = 64). Thus, there is more power to reject the neutral model for intergenic sequence and introns than for exonic sequence. The fact that MK p-values are significantly negatively correlated with the total number of observations per test is consistent with this explanation. There was no evidence of different proportions of significant versus nonsignificant tests for X-linked versus autosomal elements. Tables S22–S24 report data from the ten most highly significant MK tests (average coverage > 2) indicative of directional selection on 5′ UTRs, 3′ UTRs, and intron sequences, respectively. Among the most unusual 5′UTRs are those associated with genes coding for proteins associated with the cytoskeleton or the chromosome, categories that also appeared as unusual in the MK tests on protein variation. Two of the top-ten 3′ UTRs are associated with the SAGA complex, a multi-subunit transcription factor involved in recruitment of RNA Pol II to the chromosome [111]. Among the extreme introns, two are from genes coding for components of the ABC transporter complex and two are from genes coding for centrosomal proteins, again pointing to the unusual evolution of genes associated with the cytoskeleton and chromosome structure and movement. As previously noted, a large number of significant UTRs deviate in the direction of excess polymorphism (relative to synonymous mutations). Given the potential importance of the UTRs in regulating transcript abundance and localization, translational control, and as targets of regulatory microRNAs [112], such UTRs could be attractive candidates for functional investigation. Contingency tests of significant versus nonsignificant MK test for amino acids versus each of the noncoding elements yielded p-values of 0. 65,0. 04, and 0. 07 for 5′ UTRs, 3′ UTRs, and introns, respectively. Thus, there is weak evidence that genes under directional selection on amino acid sequences tend to have 3′ UTRs and introns influenced by directional selection as well. Up to this point, our analyses have investigated various attributes of polymorphism and divergence based on windows or genes. An alternative approach for understanding the causes of variation and divergence is to analyze polymorphism and divergence across site types. Table 2 shows whole-genome counts of polymorphic and polarized fixed variants for UTRs, synonymous sites, nonsynonymous sites, introns, and intergenic sites. We also provide data for polarized, synonymous preferred or unpreferred variants. Almost all preferred versus unpreferred codons in D. melanogaster end in GC versus AT, respectively [113]; thus, preferred versus unpreferred codons can be thought of as GC-ending versus AT-ending codons. Nonsynonymous sites showed the smallest ratio of polymorphic-to-fixed variants, which is consistent with the MK tests and supports the idea that such sites are the most likely to be under directional selection. Nonsynonymous polymorphisms also occur at slightly lower frequency than do noncoding variants (Table S25). Synonymous sites have the highest ratio of polymorphic-to-fixed variants, which supports the previously documented elevated ratio of polymorphic-to-fixed unpreferred synonymous variants in D. simulans [89]. The confidence intervals of the ratio of polymorphic-to-fixed variants among site types are nonoverlapping with the exception of intron and intergenic sites. If preferred synonymous mutations are, on average, beneficial [89,114], then the smaller polymorphic-to-fixed ratio for nonsynonymous and UTR variants versus preferred variants implies that a large proportion of new nonsynonymous and UTR mutations are beneficial. Using similar reasoning, the data in Table 2 suggest that directional selection plays a larger role in nonsynonymous and UTR divergence compared to intron and intergenic divergence [20,115,116]. These conclusions are consistent with estimates of α [11,117], the proportion of sites fixing under directional selection (assuming that synonymous sites are neutral and at equilibrium) for different site types. Determining the relative contributions of various mutational and population genetic processes to base composition variation and inferring the biological basis of selection on base composition remain difficult problems. Much of the previously published data on base composition variation in D. simulans have been from synonymous sites [55,89,90,118]. Several lines of evidence [55,89,90,113,118] suggest that on average, preferred codons have higher fitness than unpreferred codons, with variation in codon usage being maintained by AT-biased mutation, weak selection against unpreferred codons, and genetic drift [23,114]. However, the possibilities of nonequilibrium mutational processes and/or natural selection favoring different base composition in different lineages have also been addressed [119]. The D. simulans population genomic data allow for a thorough investigation of the population genetics and evolution of base composition for both coding and noncoding DNA [59,120]. The analyses discussed below use parsimony to polarize polymorphic and fixed variants. Complete genomic and gene-based data are available as Datasets S9 and S10. The genomic analysis of polymorphism and divergence based on alignments to a reference sequence is poised to become a central component of biological research. Here we have demonstrated that such analysis can be based on high-quality whole-genome syntenic assemblies from light shotgun sequence data; accounting for variable coverage and data quality is fundamentally important. Several, noteworthy new results have been reported here. First, our genome-level investigation of adaptive protein evolution has revealed a large number of proteins and biological processes that have experienced directional selection, setting the stage for a general analysis of functional protein divergence under selection in Drosophila. Second, we identified several UTRs, introns, and intergenic sequences showing the signature of adaptive evolution. The functional biology of such noncoding elements and their connections to adaptive protein and gene expression evolution is open to investigation. Third, D. simulans populations exhibit large-scale chromosomal patterning of polymorphism and divergence that is poorly explained by current genome annotations. Variation in recombination rates across chromosomes may contribute to these patterns. Fourth, the population genetics of the X chromosome differs in several ways from that of the autosomes. It evolves faster, harbors less polymorphism, and shows a different spatial scale of variation of polymorphism and divergence compared to the autosomes. Finally, base composition is evolving in both coding and noncoding sequences, for reasons that are as of yet unclear. This project is, in many ways, a first step toward population genomics in general, and in the Drosophila model specifically. For example, the average number of alleles sampled per base is too small for investigating many interesting properties of variation. Some genomic regions have been excluded due to low coverage, their repetitive nature, or very high divergence from D. melanogaster. Many aspects of biological annotation have not been investigated here, and many new Drosophila annotations will be produced in the near future as comparative and functional annotations of the D. melanogaster genome move forward. Nevertheless, the data are a stunningly rich source of material for functional and population genetic investigation of D. simulans polymorphism and divergence. It will be interesting to compare the processes determining polymorphism and divergence in D. simulans to those controlling variation in D. melanogaster (http: //www. dpgp. org) and in other species, such as humans. Such comparisons are likely to result in new insights into the genetic, biological, and population genetic factors responsible for similarities and differences among species in the genomic distribution of sequence variation.
D. simulans 4 (males and females). This strain was established by ten generations of sibling mating from a single, inseminated female collected by D. Begun in the Wolfskill orchard, Winters, California, USA, summer 1995. D. simulans 6 (males and females). This strain was established by ten generations of sibling mating from a single, inseminated female collected by D. Begun in the Wolfskill orchard, Winters, California, summer 1995. D. simulans w501 (males and females). This strain carries a white (eye color) mutation. It has been in culture since the mid 20th century, likely descended from a female collected in North America. The strain used for sequencing was sib-mated for nine generations by D. Barbash at UC Davis. Libraries for sequencing were prepared from DNA isolated from embryos. D. simulans MD106TS (males and females). This strain was descended from a single, inseminated female collected by J. W. O. Ballard in Ansirabe, Madagascar on 19 March 1998. It has the siII mitochondrial genotype, and was cured of Wolbachia by tetracycline. The strain was sib-mated for five generations in the Ballard lab, followed by an additional five generations of sib-mating by D. Begun. D. simulans MD199S (females). This strain was descended from a single, inseminated female collected by J. W. O. Ballard in Joffreville, Madagascar on 28 March 1998. It has the siIII mitochondrial genotype, and probably lost Wolbachia infection. The strain was sib-mated for five generations in the Ballard lab, followed by an additional five generations of sib-mating by D. Begun. All-female DNA was made to assist in assembly of the Y chromosome by comparison to mixed-sex libraries of other lines. D. simulans NC48S (males and females). This strain was descended from a collection by F. Baba-Aissa in Noumea, New Caledonia in 1991. It has the siI mitochondrial genotype, and was sib-mated for five generations in the Ballard lab, followed by an additional five generations of sib-mating by D. Begun. D. simulans C167. 4 (males and females). This strain was descended from a collection in Nanyuki, Kenya. It is unusual in that can produce fertile females when hybridized to D. melanogaster. The line used for genome project was obtained from the Ashburner laboratory via D. Barbash, and was subjected to a total of 13 generations of sib- mating. D. yakuba Tai18E2 (males and females). This strain derives from a single inseminated female captured in 1983 by D. Lachaise in the Taï rainforest, on the border of Liberia and Ivory Coast. This line was sib-mated for ten generations by A. Llopart and J. Coyne. Inspection of 21 salivary gland polytene chromosomes showed no chromosomal rearrangements segregating within the strain. Therefore, Tai18E2 appears homokaryotypic for the standard arrangement in all chromosome arms, save 2R, which is homokaryotypic for 2Rn. DNA preparations for sequencing all lines except w501 and Tai18E2 were made from adults. Drosophila nuclei were isolated following Bingham et al. [121]. For all lines except w501 and Tai18E2, DNA was isolated by phenol/chloroform extraction of nuclei followed by ethanol precipitation. For lines w501 and Tai18E2, embryos were collected using standard procedures [122] followed by DNA isolation on CsCl gradients [121]. Sequence data were obtained from paired-end plasmids and fosmids (Table S32) using standard Washington University Genome Sequencing Center laboratory protocols (http: //genome. wustl. edu). A highly automated production pipeline using a 384-well format ensured the integrity of the paired-end data. We determined the nucleotide-level accuracy by reviewing the quality values of the D. yakuba consensus assembly and by comparison to manually edited D. yakuba sequence. More than 97% of the D. yakuba genome sequence had quality scores of at least 40 (Q40), corresponding to an error rate of ≤10−4. Further, we extracted reads from two local fosmid-sized regions (68 kb, defined by fosmid-end sequence pairs, one on chromosome X and one on chromosome 3L) of the assembly and reassembled using Phrap (P. Green, unpublished data). The resulting “fosmids” were manually reviewed and edited. Comparison of the sequence to these manually edited regions revealed a high-quality discrepancy rate of 2 × 10−4 substitutions and 1 × 10−4 insertion/deletion errors, consistent with the above estimates based on consensus base quality. We also found no evidence of misassembly when comparing the WGS assembly to these projects. Repetitive content was estimated both in D. yakuba and D. melanogaster using RECON to generate the repeat families and RepeatMasker to then identify those repeats in the genomes. The D. yakuba genome was ∼27% repetitive overall (of which ∼2. 5% is simple sequence repeats/low complexity sequence) and 8% in the euchromatic portion of the genome. The D. melanogaster genome was ∼11% repetitive overall (of which 2. 3% is simple sequence repeats/low complexity sequence) and ∼7% in the euchromatic portion of the genome. The first step in creating D. yakuba chromosomal fasta files was to align the D. yakuba WGS assembly data against the D. melanogaster genome. D. yakuba supercontigs were artificially broken into 1,000-bp fragments and aligned against the D. melanogaster genome using BLAT [123]. An alignment was defined as “unique” if its best scoring match had a score of at least twice that of its next best scoring alignment. Of the 139. 5 Mb of D. yakuba supercontigs that uniquely aligned to the D. melanogaster genome (4. 2 Mb of which aligned uniquely to D. melanogaster unlocalized sequence, chrU), only 16 supercontigs totaling 15. 1 Mb contained unique assignments to more than one chromosome arm. Eleven of these involved alignments to heterochromatin where only less than ∼5% of the supercontig aligned uniquely to the D. melanogaster genome. These contigs were assigned to either chrU or the heterochromatic portion of the chromosome for cases where the contig aligned to both the heterochromatic and nonheterochromatic portion of the same chromosome. One 200-kb contig had only 6. 2 kb that uniquely mapped to the D. melanogaster genome, 3. 8 kb mapping to chr2R, and 2. 4 kb mapping to chrX. This supercontig was assigned to chrU. The remaining four supercontigs were alignments to chromosome arms 2L and 2R, the location of a known pericentric inversion between D. melanogaster and D. yakuba. The D. yakuba contigs were initially ordered by their position along the assigned D. melanogaster chromosomes. Because there are rearrangements in D. yakuba as compared to D. melanogaster, we allowed one portion of a D. yakuba supercontig to align to one region of a chromosome and the remaining portion to align elsewhere along that chromosome. For example, four supercontigs aligned to both chromosome arms 2L and 2R. However, these 2L/2R cross-overs and other interspecific nonlinearities are expected given the known chromosome inversions [124] between D. yakuba and D. melanogaster. This initial ordering for 2L, 2R, 3L, 3R, and X was used as the starting point for manually introducing inversions in the D. melanogaster-ordered D. yakuba supercontigs. The goal was to minimize the total number of inversions required to “rejoin” all D. yakuba supercontigs previously assigned to distant chromosomal regions based on D. melanogaster alignments (L. Hillier, unpublished data). Inversions were only introduced between contigs and not within contigs. Using this process, we created the final chromosomal D. yakuba sequence. Sequence data were obtained from paired-end plasmids from the various D. simulans strains using standard laboratory protocols (http: //genome. wustl. edu). A genomic assembly was also created. We began by generating an ∼4× WGS assembly of D. simulans w501 using PCAP [18]. The w501contigs were initially anchored, ordered, and oriented by alignment with the D. melanogaster genome in a manner similar to that described above for alignments between the D. yakuba and D. melanogaster genome. The assembly was then examined for places where the w501 assembly suggested inversions with respect to the D. melanogaster assembly. One major inversion was found, confirming the already-documented inversion found by [124]. Six other D. simulans lines (C167. 4, MD106TS, MD199S, NC48S, SIM4, and SIM6) were also assembled using PCAP with ∼1× coverage. Using the 4× WGS assembly of the D. simulans w501 genome as a scaffold, contigs and unplaced reads from the 1× assemblies of the other individual D. simulans lines were used to cover gaps in the w501 assembly where possible. Thus, the resulting assembly is a mosaic containing the w501 contigs as the primary scaffolding, with contigs and unplaced reads from the other lines filling gaps in the w501 assembly (L. Hillier, unpublished data). The D. simulans w501 whole-genome shotgun assembly can be accessed at GenBank. The goal was to align unique D. melanogaster reference sequence assembly v4 to orthologous D. simulans sequence. The D. melanogaster genome was preprocessed to soft mask all 24mers that were not unique, as such sequences were not expected to have a discriminating effect during mapping of D. simulans reads. Transposable elements in the reference sequence were also masked. The D. simulans WGS reads were quality trimmed prior to assembly based on their phred-score derived error probability. These error probabilities were used to trim the read back to the longest contiguous interval with an average probability of error less than 0. 005. Each end was then examined and trimmed until its terminal 10 bp had an average probability of error less than 0. 005. If the read was less than 50 bp after this process, it was discarded. These criteria resulted in 164,480 discarded reads from a total 2,424,141 reads. See Table S33 for read and trim statistics. A dynamic programming algorithm was used to create a maximum-likelihood description of the evolutionary path between sequences from the two species with respect to the standard alignment model, which was extended to incorporate the possibility of sequencing error. To improve the accuracy of the alignments, optimal parameters were estimated with respect to the overall expected evolutionary distance between the two species. This was done from a first-pass assembly using the method described in [129]. Because dynamic programming is not feasible on a genomic scale, we determined candidate locations for each read using the MegaBLAST (http: //www. ncbi. nlm. nih. gov/BLAST/docs/megablast. html) algorithm. A read was then realigned to each candidate location as a single contiguous alignment using a derivative of the Smith-Waterman algorithm, which was adapted to incorporate the expected divergence and the error probabilities provided by Phred quality scores. Alignments were ranked by score. Reads were considered unambiguously mapped if their alignment covered at least 90% of the sequence and showed more than two high-quality differences between the putative best orthologous location and a possible secondary candidate location. Reads were incorporated into the assembly on a clone-by-clone basis only if both mate-pairs were unambiguously mapped with the proper orientation and appropriate distance from each other. For each D. simulans line, the aligned reads were coalesced into syntenic contigs using their overlap with respect to the D. melanogaster genome. Note that “overhanging” or unaligned sequence that may represent transposable elements, other repetitive sequence, or highly diverged sequence, was not considered. This “master–slave” multiple alignment contains reads that are aligned “optimally” with respect to the D. melanogaster reference sequence. However, this does not ensure that the reads are optimally aligned with respect to each other. For instance, small, identical insertion or deletion variants may not be mapped to precisely identical locations in all D. simulans reads. To address this problem, the D. melanogaster reference sequence was set aside, and the method of Anson and Meyers [125] was used to optimize the alignment of each component read of each D. simulans line with respect to a D. simulans–only consensus sequence. This method, which minimizes the sum of differences between each of the reads and the consensus sequence, belongs to the class of expectation maximization algorithms [125]. The round robin, align-and-update algorithm converges on a consensus sequence and alignment that most parsimoniously describe the differences between each read and the consensus. This has the effect of coalescing deletions and aligning insertions. The end result of the assembly is a multi-tiered alignment with associated quality scores for (i) the trimmed reads, (ii) the assembled sequences within lines, and (iii) a species consensus sequence, all aligned to the D. melanogaster reference sequence. A reference sequence was produced for each D. simulans line by concatenating the syntenically assembled contigs that were padded with respect to the D. melanogaster reference sequence. The result is a set of D. simulans genomes onto which D. melanogaster annotation can be directly mapped. Nine regions, including coding and noncoding DNA, were chosen to cover a range of polymorphism levels as predicted by an early version of the syntenic assembly. These regions were amplified from lines C167. 4, MD106TS, NC48S, and w501, and sequenced at UNC-Chapel Hill High-Throughput Sequencing Facility. Sequences were assembled using Consed; a minimum quality score of 30 was required. Approximately 27,500 bp were sequenced per line. The per-base discrepancy between these sequences and the current syntenic assembly (insertions, deletions, and masked bases omitted) was estimated as 0. 00043. An orthology map (with respect to the D. melanogaster reference sequence) of D. yakuba assembly (v1. 0) was generated by the Mercator program (http: //rd. plos. org/pbio. 0050310a). The MAVID [126] aligner was run on each orthologous segment in the map. MAVID uses protein-coding hits reported by Mercator to anchor its alignment of each segment. It recursively finds additional anchors and then runs the Needleman-Wunsch algorithm in between the anchors to obtain a single, global alignment of the entire orthologous segment. These regions were filtered based on manual examination of the density of annotated repetitive sequence in the centromere and telomere proximal regions of the five large arms. The transition from the “typical” euchromatic density of large repeats to the typical “beta heterochromatic” pattern is obvious. The “euchromatic/heterochromatic boundaries” were drawn roughly at the edges of the first annotated gene within each euchromatic arm. The following regions were excluded from analysis: (i) X 1 to 171944 AND 19740624 to END; (ii) 2L 1 to 82455 AND 21183096 to END; (iii) 2R 1 to 2014072 AND 20572063 to END; (iv) 3L 1 to 158639 AND 22436835 to END; and (v) 3R 1 to 478547 AND 27670982 to END. The sequence for each line is derived from the multiple alignment of reads to the D. melanogaster reference assembly (v4). For each line and each column (nucleotide position) corresponding to a D. melanogaster base, a likelihood model was used to determine the quality score for each of the four bases. The quality score was calculated as −10log (1 – probability base is correct). To compute the probability a base call is correct, we assume that each read is an observation of a random variable with equal likelihoods for all four bases with some probability of error. From the definition of a phred score, the probability of error for a particular observed call is: 10 (phred score/–10). We assumed that a base in error is equally likely to be any one of the three other bases. Then, for a given position A, Bayes theorem implies the probability (Pr) that the call is correct is Where Pr[A] = 1/4, Pr[Observations|A is correct] = likelihood of A observations being correct and non-A observations being incorrect, and Pr[Observations] = likelihood of seeing observed values given frequency and error rates. Quality scores were truncated at 90. The sequences for each line were investigated for regions containing unusually high densities of high-quality discrepancies, which are due to residual heterozygosity, duplication, and erroneous sequence. These regions were filtered from subsequent analysis (see below). For each line, the support for each alternative (A, G, C, and T) at each aligned base was the sum of the qualities, with the highest quality base assigned as the base for that line/position. Implicit in this approach is that a base is called only if the highest quality base has a quality score that is 30 or more greater than that of the next highest quality base. The combined SIM4/SIM6 consensus was also treated in this manner. Residual heterozygosity within lines or duplications present in D. simulans but not D. melanogaster can lead to regions with excess high-quality discrepancies between reads within lines. We refer to these as single-nucleotide discrepancies. We derived a distribution of the number of discrepancies per site over each chromosome for each D. simulans line. We based the distributions on counts of within-line discrepancies per site in 500-bp windows that had 250-bp overlap. We took the conservative approach of filtering windows in all the lines that fell into the top 0. 5% of the distribution in any single line. In other words, a window with a high-quality discrepancy in one line was filtered from the entire dataset, even if the other lines had no discrepancy. Overall, 334,500 base pairs were filtered from the genome. The number of sites filtered for each chromosome arm were 39 kb for 2L, 86. 5 kb for 2R, 58 kb for 3L, 73 kb for 3R, and 78 kb for X. One large inversion on chromosome arm 3R distinguishes the two species. Phylogenetic analysis of the cytogenetic data suggested that the inversion fixed in the D. melanogaster lineage [39]. Thus, D. simulans 3R is rearranged with respect to the D. melanogaster reference sequence. We used D. melanogaster/D. simulans alignments provided by the UC Santa Cruz Genome Browser to locate the putative breakpoints of the inversion as Chr3R: 3874907 and 17560827. All features were defined in the D. melanogaster v4. 2 annotation (http: //flybase. org). For each gene, the longest isoform (i. e. , the isoform the with greatest number of codons) was chosen for analyses. Exons that were not part of the longest isoform were excluded from all feature-based analyses, but were included in window analyses. The analyzed introns correspond to these longest isoforms; all introns were included in window analyses. Intronic sequences within annotated UTRs or that overlapped any coding sequence were excluded. UTRs investigated for this paper were restricted to those inferred from “Gold Collection” genes with completely sequenced cDNAs (http: //www. fruitfly. org/EST/gold_collection. shtml). All annotated CDS sequences were used regardless of the associated empirical support. Intergenic regions were defined as noncoding segments between annotated genic regions (UTRs, coding sequence, and noncoding RNAs) regardless of strand. Defined intergenic regions from v4. 2 annotation were checked against all known coding and UTR coordinates; any nucleotides that overlapped a genic region were removed from the intergenic set before analysis. We established a conservative gene set for analyses (base composition analyses excepted) by including only genes for which the start codon (ATG or otherwise), splice junctions (canonical or otherwise), and termination codon position agreed with the D. melanogaster reference sequence. We took the conservative approach of excluding from the gene-based analysis any gene for which any of the six D. simulans gene models disagreed with the D. melanogaster gene model. Long insertions and deletions (indels) are difficult to identify using only aligned reads. As indel length increases, the likelihood that indels are missed increases because they are either too long or occur near the end of a read, which compromises alignment. Furthermore, indel error probabilities are difficult to estimate. These considerations led us to restrict our analysis to indels of 10 bp or less and to restrict our analysis of divergence to the D. simulans versus D. melanogaster comparison. Variants were classified as insertions or deletions relative to the D. melanogaster reference sequence. The quality score for an insertion was the average quality score of sequence in that insertion; the quality score for a deletion was the minimum of qualities of the two flanking nucleotides. Qualities were determined this way to provide a metric of overall sequence quality in the region of a putative indel, thereby allowing a quantitatively defined cutoff for inferring indel variants; only indels of high quality (over phred 40) were considered in the analysis. Light, variable coverage of each line requires that statistical estimation and inference account for coverage variation. When appropriate (e. g. , contingency tables of frequency variation), counts of variants within a coverage category were used. In other estimation and inference settings, the familiar estimators were applied to each coverage class and then averaged, weighting by the proportion of total covered base pairs in the window or other feature. Heterozygosity. The expected nucleotide, insertion, and deletion heterozyogsity was estimated as the average pairwise differences between D. simulans alleles as follows: πi is the coverage-weighted average expected heterozygosity of nucleotide variants (i = nt), deletions (i =Δ) or insertions (i = ▿) per base pair. “Expected heterozygosity” assumes the six sequenced genomes were drawn from a single, randomly mating population. Variable coverage over sites led us to extend the typical calculation of expected heterozygosity [127,128] to the following: where nc is the number of aligned base pairs in the genomic region (e. g. , gene feature or window) with sequencing coverage c. kcj is the number of sites in this region with coverage c at which the derived state (nt, ▵, or ▿) occurs in j out of the c sequences. This estimator was used for 10-kb windows, 50-kb windows, 30-kb sliding windows (10-kb increments), 150-kb sliding windows (10-kb increments), and 210-kb windows (10-kb increments), including all windows for which coverage was >200 bp. Expected heterozygosity was also estimated for genomic features (exons, introns, UTRs, and intergenic sequence) that had a minimum size and coverage [i. e. , n (n – 1) × s ≥ 100, where n = average number of alleles sampled and s = number of sites]. For coding regions, the numbers of silent and replacement sites were counted using the method of Nei and Gojobori [129]. The pathway between two codons was calculated as the average number of silent and replacement changes from all possible paths between the pair. The variance of pairwise differences in sliding windows (150-kb windows, 10-kb increments) was used as a method of summarizing the magnitude of linkage disequilibrium across the D. simulans genome. For each window, we calculated coverage weighted variance of the expected heterozygosity (see above) for all pairs of alleles. Divergence. Unpolarized (i. e. , pairwise) divergence between D. simulans and D. melanogaster was estimated for 10-kb windows, 50-kb windows, 30-kb sliding windows (10-kb increments), 150-kb sliding windows (10-kb increments), 210-kb windows (10-kb increments), and genomic feature that had a minimum number of nucleotides represented [i. e. , n × s > 100, with n and s as above in calculations of π. Unpolarized divergence was calculated as the average pairwise divergence at each site, which was then summed over sites and divided by the total number of sites. A Jukes-Cantor [130] correction was applied to account for multiple hits. For coding regions, the numbers of silent and replacement sites were counted using the method of Nei and Gojobori [129]. The pathway between two codons was calculated as the average number of silent and replacement changes from all possible paths between the pair. Estimates of unpolarized divergence over chromosome arms were calculated for each feature with averages weighted by the number of sites per feature. Lineage-specific divergence was estimated by maximum likelihood using PAML v3. 14 [131] and was reported as a weighted average over each line with greater than 50 aligned sites in the segment being analyzed. Maximum likelihood estimates of divergence were calculated over 10-kb windows, 50-kb windows, 30-kb sliding windows (10-kb increments), 150-kb sliding windows (10-kb increments), 210-kb windows (10-kb increments), and gene features (exons, introns, and UTRs). PAML was run in batch mode using a BioPerl wrapper [132]. For noncoding regions and windows, we used baseml with HKY as the model of evolution to account for transition/transversion bias and unequal base frequencies [133]; for coding regions, we used codeml with codon frequencies estimated from the data. Insertion and deletion divergence was calculated as divi, the coverage-weighted average divergence of deletions (i = ▵) or insertions (i = ▿) per base pair. where nc is the number of aligned base pairs in the genomic region (e. g. , gene feature or window) with sequencing coverage c. kcj is the number of sites in this region with coverage c at which the derived state with respect to the D. melanogaster reference sequence (▵ or ▿) occurs in j out of the c sequences. Unpolarized MK tests [4] used D. simulans polymorphism data and the D. melanogaster reference sequence for counting fixed differences. Polarized MK tests used D. yakuba to infer the D. simulans/D. melanogaster ancestral state. For both polarized and unpolarized analyses, we took the conservative approach of retaining for analysis only codons for which there were no more than two alternative states. For cases in which two alternative codons differed at more than one position, we used the pathway between codons that minimized the number of nonsynonymous substitutions. This is conservative with respect to the alternative hypothesis of adaptive evolution. Polymorphic codons at which one of the D. simulans codons was not identical to the D. melanogaster codon were not included. To reduce multiple testing problems, we filtered the data to retain for further analysis only genes that exceeded a minimum number of observations; we required that each row and column in the 2 × 2 table (two variant types and polymorphic versus fixed) sum to six or greater. Statistical significance of 2 × 2 contingency tables was determined by Fisher' s Exact test. MK tests were also carried out for introns and Gold Collection UTRs by comparing synonymous variants in the associated genes with variants in these functional elements. For intergenic MK tests, we used synonymous variants from genes within 5 kb of the 5′ and/or 3′boundary of the intergenic segment. For some analyses, we restricted our attention to MK tests that rejected the null in the direction of adaptive evolution. This categorization was determined following Rand and Kann [134]. Polarized 2 × 2 contingency tables were used to calculate α, which under some circumstances can be thought of as an estimate of the proportion of variants fixing under selection [11]. Bootstrap confidence intervals of α and of the ratio of polymorphic-to-fixed variants for each functional element (Table 2) were estimated in R using bias correction and acceleration [135]. Our approach takes overall rate variation among lineages into account when generating expected numbers of substitutions under the null model and allows for different rates of evolution among chromosome arms (e. g. , a faster-X effect). For example, the number of substitutions for all X-linked 50-kb windows was estimated using PAML (baseml), allowing different rates for each lineage. All D. simulans lines were used, with the estimated substitution D. simulans rate for each window being the coverage-weighted average. This generated an empirically determined branch length of the X chromosome for the average over each of the D. simulans lines (from all three way comparisons with D. melanogaster and D. yakuba) weighted by the number of bases covered. We carried out a relative rate test for windows or features in D. simulans and D. melanogaster by generating the expected number of substitutions for each window/feature/lineage based on the branch length of the entire chromosome in each lineage (PAML) and the coverage of the window/feature in question in each lineage. We then calculated the deviation from the expected number of substitutions as (observed – expected substitutions) 2/expected substitutions for any window/feature/lineage. For each GO term associated with at least five MK tests, we calculated the proportion of significant (p < 0. 05) tests. We then randomly selected n p-values from the set of all MK p-values, where n is the number of tests in the ontology category. We repeated this procedure 10,000 times to get the empirical distribution of the proportion significant p-values for each GO term. The relative rate χ2 for dN was calculated for each gene as described above. Genes showing a significant (p < 0. 05) acceleration of dN in the D. simulans lineage were identified as described in the previous section. The probabilities of observing as many, or more, significant relative rate χ2 tests for dN were determined by permutation as described in the previous section. We retrieved ontology terms associated with genes that fell under windows of interest in linked selection analyses. Then, for each term, we divided the number of instances that the term was represented in the windows of interest by the total number of genes in the genome that are associated with the ontology term. This gave us a proportional representation of each GO term in windows of interest. We compared this proportion for each GO term with the empirical distribution of proportions derived from permuted datasets. For each permuted dataset, we randomly picked a nonoverlapping set of windows that were the same size in numbers of base pairs as the observed windows. Each window was guaranteed to contain at least one gene, given that windows of interest have higher-than-average gene density. We then retrieved the ontology terms associated with the genes under the random set of windows. We next calculated the proportion of each term as described above for the observed windows. We repeated this procedure 1,000 times to obtain an empirical distribution of proportions of each term in random windows. The proportion of each GO term in the original observed windows of interest was compared to this empirical distribution to obtain a probability of observing that proportion of each term in windows of interest. We wanted to know whether ontology terms were clustered in the genome. We tested whether each ontology term was significantly clustered by calculating the coefficient of variation based on occurrence in 1-Mb, nonoverlapping windows and compared that to the coefficient of variation from permuted datasets in which we randomized the locations of genes on each chromosome arm. Genes were assigned to expression categories, with the goal of determining whether certain categories had a greater proportion of significant MK tests for adaptive protein divergence than expected by chance. Two types of data, expressed sequence tag (EST) collections and microarray experiments, were used. Genes associated with EST collections from D. melanogaster (head, ovary, and testis from Flybase and spermatheca from Swanson et al [136]) were assigned to that tissue expression category. Female-mating responsive genes were those defined by microarray experiments [137]. Male- and female-biased genes were defined based on microarray experiments of Parisi et al. [138] and Arbeitman et al. [139]. Male- and female-biased genes from Parisi et al. [138] were obtained directly from their Tables S41 and S42. Arbeitman et al. [139] measured expression over the D. melanogaster life cycle for adult males and females. We averaged expression for each gene over the time points taken for each stage. For example, there were 30 time point measurements during the egg stage; we used the average expression over those 30 time points. We repeated this for larvae, metamorph, adult female, and adult male stages. Each gene was provisionally designated as having biased expression for the stage with the maximum average expression, which we will call the biased stage. For each gene, we calculated the average difference between the biased stage expression value and the other stage expression values. This generated a distribution of differences for each comparison of stages. A gene was finally determined to have biased expression if the average difference between the biased stage and the other stages fell into top half for that stage distribution. This procedure resulted in 592,374,223,466, and 296 stage-biased genes for egg, larvae, metamorph, adult male, and adult female stages, respectively. We calculated the proportion of genes in a group (e. g. , male-biased) that had significant MK tests (p < 0. 05). We used permutation testing to determine whether the proportion of significant polarized MK tests deviating in the direction of adaptive protein evolution exceeded the 95% tail of the empirical distribution, based on 10,000 datasets of randomly selected MK tests, sampled without replacement. We tested whether pairs of proteins that interact with one another were more likely to show evidence of adaptive protein divergence than random pairs of proteins with no evidence of interaction. Data were from Giot et al. [140]. We considered pairs of genes to have a significant interaction if the probability of interaction was greater than 0. 5. We calculated the proportion of interacting pairs where both members had significant evidence of adaptive evolution (MK p-values < 0. 05). We compared this proportion to the distribution of proportion generated from permuted datasets generated by randomly drawing pairs of genes without replacement from the Giot et al. [140] dataset. Hudson, Kreitman, and Aquadé [2] proposed a test of the neutral theory of molecular evolution in which the numbers of polymorphic and (fixed) divergent sites are contrasted between two independent loci (genomic regions). The distribution of a χ2-like test statistic can be determined by simulation for any assumed values of recombination within each locus. However, given the small sample size here and the genomic scale of the data, we used an analogous statistic for polymorphisms and fixations on the D. simulans lineage in various sizes of sliding windows, combined over coverage classes. First, the average proportion of segregating sites in D. simulans and parsimony-inferred fixed differences for each chromosome arm in D. simulans was determined for each coverage class over a range of sliding window sizes (10 kbp to 510 kbp). The test statistic is a simple two-cell χ2, in which the observed numbers (summed over coverage classes) of segregating and fixed sites are contrasted with their expected numbers (summed over coverage classes, the chromosome arm average for each coverage class times the total numbers of segregating and fixed sites in that class). Only sites for which unambiguous, parsimony-inferred D. simulans/D. melanogaster ancestral states could be determined were included in the analysis. In a number of figures, χ[–log10 (p) ] is plotted; –log10 of p, critical value for this χ2, was given the sign of the difference, observed numbers of segregating site – expect number of segregating sites. As expected (Figure 1), there is a clear tendency for the level of polymorphism (both πnt and proportion of segregating sites) to decline proximal to the telomeres and centromeres. Therefore, the test statistics discussed in this section were determined by generating expected values as described above, but only including the “central euchromatic” regions. These were defined as the regions bounded by the first and last position on each chromosomes arm for which the proportion of segregating sites was greater than or equal to the chromosome arm average in a 510-kbp window. While this makes deviations in the centromere and telomere proximal regions appear greater, it removes the obvious bias toward positive deviations (i. e. , excess polymorphism) that would be created by including large genomic regions known to show reduced polymorphism when generating expectations. Minimum values for the expected numbers of segregating and fixed sites were one (unless otherwise indicated). Windows with coverage <200 bp were dropped (unless otherwise indicated). Expected nucleotide heterozygosity and polarized divergence were calculated for 10-kb and 50-kb nonoverlapping windows spanning each chromosome arm as described above. For each arm, autocorrelation between successive windows was calculated as: where there are n windows along an arm, and xt represents the value of nucleotide heterozyogsity or divergence for the t-th window. Significance of r for all arms for both polymorphism and divergence was calculated by permutation. All calculations were carried out in R (http: //www. r-project. org). We set out to find putative selective sweeps that occurred concomitantly with migration by D. simulans out of Africa/Madagascar. We expect the signature of these sweeps to be low variation in New World (NW) lines, defined here as w501 and SIM4/6, compared to Old World (OW) lines, defined here as C167. 4, MD199S, and MD106TS. The method described here addresses the issue of autocorrelated loci. Our approach was to simulate datasets with the same degree of autocorrelation as that of the observed data, and to determine whether there are longer runs of windows with disproportionately low NW π in the actual data than one would expect by chance. All data manipulation, calculations, and simulations were carried out in R using functions available within the “base” and “stats” packages. Mean nucleotide diversity (π) from 10-kb nonoverlapping windows throughout the genome from the two NW and three OW lines were used. Adjacent 10-kb windows were averaged (weighted by coverage) to obtain 20-kb windows. Remaining windows for which no estimate of π was available were conservatively estimated by interpolation. There were no gaps in the 20-kb window data longer than three consecutive windows in either population. For each window, the ratio of NW π: OW π (π NW: πOW) was measured. Maximum likelihood estimates of first-order coefficients of autocorrelation for each of the chromosome arms were found (all were significant). Monte Carlo simulations of the ratio πNW: πOW were performed according to the following procedure. We first randomly sampled ratios of π NW: πOW from the data with replacement for each arm separately; this ensures that our simulated data has the same mean and variance as the actual data. A first-order autoregressive filter was then applied to the randomly sampled data using the estimate of autocorrelation for the given chromosomal arm, according to the following relationship: where parameter μ is the mean of the sampled data, ρ is the autocorrelation, Xi – 1 is previous value in the series, and Xi is the original sampled measure for the ith window. This filter imposes the observed autocorrelation onto the sampled data to mimic the observed autocorrelation, resulting in a new value, Xi*, for each window. Variance and estimated first-order autocorrelation of the simulations were similar to those of the empirical data without altering this procedure. A lower threshold of π NW: πOW, below which 5% of the empirical data points reside, was determined. Significance of runs of windows below this threshold was determined by comparison to the distribution of the run lengths in 10,000 Monte Carlo simulation runs for each chromosome arm, performed as described above. P-values for each arm were corrected for multiple comparisons conservatively via Bonferroni correction (Dunn-Sidak corrections did not result in an increased number of significant sweeps). Parsimony was used to infer D. simulans/D. melanogaster ancestral states; D. yakuba was the outgroup. Only codons with one synonymous variant among the three species were included in these analyses. The preferred codon set was defined following Akashi [113]. For some analyses, preferred and unpreferred substitution rates were determined by dividing the number of substitutions of each type by the number of ancestral codons of the appropriate ancestral state (unpreferred ancestors for the preferred substitution rate and preferred ancestors for the unpreferred substitution rate), all inferred by parsimony. In principle, excess unpreferred polymorphisms at synonymous sites could erroneously lead one to infer directional selection on other sites. However, the ratio of preferred-to-unpreferred polymorphisms is not significantly different (pooled across genes or gene-by-gene) for UTRs that had significant versus nonsignificant MK tests in contrasts of synonymous and UTR sites. For introns that showed a significant MK test versus synonymous sites, there was a slightly larger ratio of unpreferred-to-preferred polymorphisms compared to the ratio for introns that were not significant. However, this was seen only in the pooled analysis and not in the gene-by-gene analysis. We found that significant intron and UTR MK tests had more similar coverages (e. g. , 5′ UTR versus synonymous) compared to tests that were not significant, suggesting that the large number of significant noncoding versus synonymous tests cannot be explained by relatively small coverage differences across site-types. Overall, these data suggest that most of the highly significant MK tests of noncoding DNA are not explained by excess unpreferred polymorphisms or coverage variation. Base composition analyses on noncoding DNA were carried out in a similar fashion, with parsimony being used to infer the D. simulans/D. melanogaster ancestor. Only unambiguous parsimony-inferred sites were used in these analyses. All X-linked genes for which Flybase reported genetic and physical locations (first nucleotide of the gene in Flybase annotation of D. melanogaster v4. 2) were used. Genetic and physical distances were determined for 12-gene intervals, sliding one gene at a time; estimates of cM/kb per interval were used as estimates of recombination rate per physical length. Mean physical and genetic distances per interval were 1. 55 Mb and 5 cM, respectively. Two intervals with negative estimates of cM/kb, indicative of discordant genetic and physical data were removed, leaving estimates of cM/kb for 150 intervals. The physical location of the interval was defined as the midpoint between physical locations of the first and last gene. For analyses investigating correlations of 50-kb windows of polymorphism and divergence with crossing-over, midpoints were rounded to the nearest 50,000. If multiple intervals were rounded to the same number, the distal interval was used in the analyses. Cloned elements. The “hanging ends” of well-mapped plasmid clones that were not fully aligned to D. melanogaster were examined by BLAST for extensive (100 bp or greater), high-quality (90% or greater) sequence similarity to known transposable elements of D. melanogaster (v 9. 2, http: //www. fruitfly. org/p_disrupt/TE. html). The coordinates are slightly rounded to facilitate finding duplicates slightly off in alignment. Clustered elements. This analysis used plasmid clones for which only one mate pair mapped uniquely and unambiguously to the genome according to the method described previously. The other mate pair was compared to the D. melanogaster transposable element database v9. 2. If the read mapped uniquely and unambiguously to a transposable element (90% coverage, 90% identity, at least two high quality differences to a secondary candidate), a transposable element was considered as mapped to the general genomic location of its mate pair. The estimated location begins at the end of the mate pair read and ends 10 kb away in the appropriate direction determined by the direction of the alignment. Transposable elements from the same family located within 5 kb of each other in the same D. simulans line were considered the same element, and therefore, were clustered.
The GenBank (http: //www. ncbi. nlm. nih. gov/Genbank/) accession number for D. yakuba is AAEU01000000 (version 1) and for the D. simulans w501 whole-genome shotgun assembly is TBS-AAEU01000000 (version 1). | Population genomics, the study of genome-wide patterns of sequence variation within and between closely related species, can provide a comprehensive view of the relative importance of mutation, recombination, natural selection, and genetic drift in evolution. It can also provide fundamental insights into the biological attributes of organisms that are specifically shaped by adaptive evolution. One approach for generating population genomic datasets is to align DNA sequences from whole-genome shotgun projects to a standard reference sequence. We used this approach to carry out whole-genome analysis of polymorphism and divergence in Drosophila simulans, a close relative of the model system, D. melanogaster. We find that polymorphism and divergence fluctuate on a large scale across the genome and that these fluctuations are probably explained by natural selection rather than by variation in mutation rates. Our analysis suggests that adaptive protein evolution is common and is often related to biological processes that may be associated with gene expression, chromosome biology, and reproduction. The approaches presented here will have broad applicability to future analysis of population genomic variation in other systems, including humans. | Abstract
Introduction
Results/Discussion
Materials and Methods
Supporting Information | computational biology
evolutionary biology
genetics and genomics | 2007 | Population Genomics: Whole-Genome Analysis of Polymorphism and Divergence in Drosophila simulans | 18,941 | 244 |
In both humans and Drosophila melanogaster, UDP-galactose 4′-epimerase (GALE) catalyzes two distinct reactions, interconverting UDP-galactose (UDP-gal) and UDP-glucose (UDP-glc) in the final step of the Leloir pathway of galactose metabolism, and also interconverting UDP-N-acetylgalactosamine (UDP-galNAc) and UDP-N-acetylglucosamine (UDP-glcNAc). All four of these UDP-sugars serve as vital substrates for glycosylation in metazoans. Partial loss of GALE in humans results in the spectrum disorder epimerase deficiency galactosemia; partial loss of GALE in Drosophila melanogaster also results in galactose-sensitivity, and complete loss in Drosophila is embryonic lethal. However, whether these outcomes in both humans and flies result from loss of one GALE activity, the other, or both has remained unknown. To address this question, we uncoupled the two activities in a Drosophila model, effectively replacing the endogenous dGALE with prokaryotic transgenes, one of which (Escherichia coli GALE) efficiently interconverts only UDP-gal/UDP-glc, and the other of which (Plesiomonas shigelloides wbgU) efficiently interconverts only UDP-galNAc/UDP-glcNAc. Our results demonstrate that both UDP-gal and UDP-galNAc activities of dGALE are required for Drosophila survival, although distinct roles for each activity can be seen in specific windows of developmental time or in response to a galactose challenge. By extension, these data also suggest that both activities might play distinct and essential roles in humans.
Galactose is an essential component of glycoproteins and glycolipids in metazoans, and as a constituent monosaccharide of the milk sugar, lactose, also serves as a key nutrient for mammalian infants. Galactose is also found in notable quantities in some fruits, vegetables, and legumes. Galactose is both synthesized and catabolized in all species via the Leloir pathway, which is highly conserved across branches of the evolutionary tree [1]. The reactions of the Leloir pathway are catalyzed by the sequential activities of three enzymes: (1) galactokinase (GALK) which phosphorylates alpha-D-galactose to form galactose-1-phosphate (gal-1P), (2) galactose-1-phosphate uridylyltransferase (GALT), which transfers uridine monophosphate (UMP) from uridine diphosphoglucose (UDP-glc) to gal-1P, forming UDP-galactose (UDP-gal) and releasing glucose-1-phosphate (glc-1P), which can proceed to phosphoglucomutase and the glycolytic pathway, and (3) UDP-galactose 4′-epimerase (GALE) which interconverts UDP-gal and UDP-glc [1]. In addition to a role in the Leloir pathway, metazoan GALE enzymes also interconvert UDP-N-acetylgalactosamine (UDP-galNAc) and UDP-N-acetylglucosamine (UDP-glcNAc) (Figure 1). Because it catalyzes reversible reactions, GALE therefore not only contributes to the catabolism of dietary galactose, but also enables the endogenous biosynthesis of both UDP-gal and UDP-galNAc [2], [3] when exogenous sources are limited. Deficiency in any of the three Leloir enzymes in humans results in a form of the metabolic disorder galactosemia, although the symptoms and clinical severity differ according to which enzyme is impaired and the extent of the impairment. Profound loss of hGALE results in generalized epimerase-deficiency galactosemia, an autosomal recessive and potentially severe disorder. To date, however, no patient has been reported with complete loss of GALE, and even the most severely affected demonstrate at least 5% residual enzyme activity [4]. Previous studies have indicated that different patient mutations impair hGALE to different extents [5]–[9]. Further, while some mutations impair both GALE activities similarly, others do not. For example, the hGALE allele V94M, which leads to severe epimerase-deficiency galactosemia in the homozygous state, encodes an enzyme that retains ∼5% residual activity toward UDP-gal but ∼25% residual activity toward UDP-galNAc [8], [9]. Disparities such as this have raised the question of whether the pathophysiology of epimerase deficiency galactosemia results from the loss of GALE activity toward UDP-gal/UDP-glc, or toward UDP-galNAc/UDP-glcNAc, or both. To address this question, we applied a Drosophila melanogaster model of GALE deficiency [10]. Using this model, we have previously established that GALE is essential in Drosophila; animals completely lacking endogenous dGALE succumb as embryos, and conditional loss of dGALE in larvae results in death within two to four days of knockdown. Finally, partial loss of dGALE leads to galactose sensitivity in larvae, and transgenic expression of human GALE (hGALE) rescues each of these negative outcomes [7]. Here we have applied our transgenic Drosophila model to uncouple and examine the individual roles of GALE separately. Toward that end, we generated flies that lacked endogenous dGALE and expressed either of two prokaryotic transgenes, one encoding E. coli GALE (eGALE) which exhibits an approximately 8,000-fold substrate preference for UDP-gal/UDP-glc over UDP-galNAc/UDP-glcNAc [11], and the other encoding P. shigelloides wbgU, which exhibits an approximately 2,000-fold substrate preference for UDP-galNAc/UDP-glcNAc over UDP-gal/UDP-glc [12]. By expressing these prokaryotic transgenes individually or in combination in dGALE-deficient Drosophila we determined that both GALE activities are required for survival of embryos and larvae. We also found that restoration of one activity or the other in later development rescued some phenotypes. Combined, these results provide insight into the varied roles of dGALE in Drosophila development and homeostasis, and by extension, suggest that hGALE may play similarly complex and essential roles in humans.
Human and other mammalian GALE enzymes efficiently interconvert both UDP-gal/UDP-glc and UDP-galNAc/UDP-glcNAc (e. g. [13]–[15]). Previously, we reported that Drosophila GALE interconverts the first of these substrate pairs (UDP-gal/UDP-glc) [10], but did not address whether dGALE could also interconvert the second. Here we demonstrate that dGALE from wild-type adult flies efficiently interconverts both substrate sets (left most bar, Figure 2). Of note, while purified human GALE [15] and dGALE each interconvert both UDP-gal/UDP-glc and UDP-galNAc/UDP-glcNAc, the apparent specific activity of both human and fly enzymes toward UDP-gal is significantly higher than toward UDP-galNAc. To generate flies with epimerase activity toward only UDP-gal/UDP-glc or only UDP-galNAc/UDP-glcNAc, we created transgenic lines expressing eGALE (UAS-eGALE) or wbgU (UAS-wbgU), respectively, each in a conditionally dGALE-impaired background. Each of these prokaryotic GALE genes has been demonstrated previously to encode epimerase activity toward only one of the two sets of epimer pairs (e. g. [11], [12]). To minimize background, activities of the encoded eGALE and WbgU enzymes toward UDP-gal and UDP-galNAc were assayed in flies knocked down for endogenous dGALE; results for the transgenes that demonstrated activities closest to those seen in wild-type Drosophila, eGALE62A and wbgU19A, are presented in Figure 2. As expected, lysates from dGALE knockdown flies expressing the eGALE transgene demonstrated strong activity toward UDP-gal, but not UDP-galNAc, and lysates from dGALE knockdown flies expressing the wbgU transgene demonstrated strong activity toward UDP-galNAc, but not UDP-gal. As a control we also tested lysates from dGALE knockdown flies expressing a human GALE transgene; as expected, those samples demonstrated very strong activity toward both substrates. Previously, we created and characterized two dGALE-deficient alleles, dGALEf00624. 4 and dGALEΔy, which allowed us to demonstrate that GALE is essential for survival in Drosophila [10]. To examine the requirement for the two different epimerase activities separately, we set up crosses which allowed for the expression of eGALE or wbgU, individually or in combination, driven by Act5C-GAL4 in an otherwise dGALE-deficient background (dGALEf00624. 4/dGALEΔy). Table 1 shows the observed to expected ratios of surviving transgenic offspring that eclosed from these crosses. As presented in Table 1, neither eGALE alone nor wbgU alone was sufficient to rescue survival of the dGALE-deficient animals; however, expression of both eGALE and wbgU, in combination, was sufficient. These results demonstrate that GALE activities toward both UDP-gal and UDP-galNAc are essential for survival of D. melanogaster. To rule out the possibility that rescue with eGALE plus wbgU in combination occurred not because both GALE activities are essential but rather because neither individual transgene expressed sufficient enzyme, we also tested additional eGALE and wbgU transgenes that individually demonstrated higher levels of expression; none was sufficient to rescue (data not shown). Of note, there also was no apparent over-expression phenotype; for example, animals expressing either eGALE or wbgU in addition to endogenous dGALE, and animals dramatically over-expressing human GALE, remained viable, fertile, and appeared morphologically normal (data not shown). Previously, we described an approach that achieves conditional knockdown of dGALE in Drosophila using a UAS-RNAidGALE transgene (12030-R2, National Institute of Genetics Fly Stock Center, Mishima, Shizuoka, Japan) in combination with a temperature sensitive allele of yeast GAL80 (GAL80ts) ([10] and Figure 3A). Using this system, we found that dGALE is required from embryogenesis through pupation, and that loss of dGALE during pupation leads to defects in fecundity and perhaps also a shortened life span [10]. Here we have expanded the GAL80tsconditional dGALE knockdown system to include different GAL4-dependent GALE transgenes and have applied this expanded system to test the ability of each transgene, or pair of transgenes, to compensate for the loss of endogenous dGALE. By using age-synchronized cohorts of animals and shifting from the permissive (18°C) to the restrictive temperature (28–29°C) at different times we also were able to test the ability of each GALE transgene, or pair of transgenes, to sustain survival and fecundity at different stages of development. At 18°C these animals expressed endogenous dGALE, but not their transgenes, and at 28–29°C these animals expressed their transgenes but not dGALE (Figure 3A). Specifically, we tested Drosophila that carried no GALE transgene, an eGALE transgene, a wbgU transgene, both eGALE and wbgU transgenes, or an hGALE transgene. As expected from prior results ([10] and Table 1), animals expressing no GALE transgene succumbed when shifted to the restrictive temperature as larvae, while animals expressing either human GALE or both eGALE plus wbgU remained viable and fertile (Figure 3C). Surprisingly, expression of either eGALE or wbgU alone was also sufficient to rescue survival, albeit to a lesser extent. The fact that the individual prokaryotic transgenes were sufficient to rescue dGALE knockdown animals, but not animals genetically null for dGALE (Table 1), suggests that trace residual dGALE expression in the knockdown animals lowered the threshold of transgene function required for rescue. Of note, while dGALE knockdown animals encoding either eGALE or wbgU remained viable following a shift to the restrictive temperature in early to mid-development (Figure 3C), these survivors were not entirely healthy. Specifically, these animals demonstrated either partial or complete loss of fecundity as adults. To test whether the degree of dGALE knockdown was comparable between males and females, and therefore not a confounding factor in differential outcome, we performed GALE and GALT enzyme assays on newly eclosed and three day old male and female knockdown adults that carried no GALE transgene and that had been switched to the restrictive temperature as early to mid-stage pupa. The degree of GALE knockdown in both males and females was profound and comparable (Figure 3B). As expected, the level of GALE activity was even lower in the older animals, presumably because any GALE synthesized prior to the temperature switch had three additional days to decay. Also as expected, GALT activity was normal and apparently unaffected by the dGALE knockdown in all samples tested (data not shown). To examine fecundity, we collected and sequestered newly eclosed virgin female and male flies from each surviving cohort, crossed them to an equal number of wild-type flies of the opposite sex, and counted the numbers of viable offspring resulting from each cross. Crosses resulting in large numbers of viable offspring (>50) were scored as “normal fecundity”. Crosses resulting in fewer than 10 viable offspring were scored as “reduced fecundity, ” and crosses resulting in no viable offspring were scored as “loss of fecundity” (Figure 3C). For example, when dGALE knockdown was initiated during early to mid-stage pupal development, animals of both sexes displayed diminished fecundity. Expression of eGALE alone, but not wbgU alone, rescued the male defect, whereas expression of both prokaryotic transgenes in combination, or hGALE alone, was required to rescue the female defect. These results indicate that GALE activity toward UDP-gal is both necessary and sufficient for male fecundity, but that GALE activities toward both UDP-gal and UDP-galNAc are required for female fecundity. We have previously demonstrated that Drosophila expressing a hypomorphic allele of dGALE are viable but sensitive to galactose exposure [10]. To assess the roles of the two GALE activities in coping with environmental galactose, we collected adult flies in which dGALE knockdown coupled with hGALE, eGALE, wbgU, or eGALE plus wbgU transgene expression was initiated using the GAL80ts system during late larval or early-to-mid-pupal development. These animals were allowed to develop on a standard molasses-based food, and were then transferred as newly eclosed adults to food containing either 555 mM glucose as the sole sugar, or 555 mM glucose plus 175 mM galactose. We assessed the lifespan of each cohort of animals on both foods; as a control, knockdown animals expressing no GALE transgene were also monitored (Figure 4). In the absence of galactose, all cohorts showed similar longevity profiles, although females (Figure 4C) showed greater variability than males (Figure 4A). In the presence of galactose, however, both males and females expressing either no GALE transgene, or only the wbgU transgene, demonstrated a dramatic reduction in life span (p<0. 0001, Figure 4B and 4D). Females expressing eGALE alone exhibited a slight decrease in life span that was independent of diet. Animals expressing hGALE or eGALE+wbgU had lifespans comparable to control animals expressing endogenous dGALE, regardless of diet. These data implicate loss of UDP-gal activity as responsible for the galactose-dependent early demise of adult dGALE-impaired Drosophila. As one approach to explore the pathophysiology underlying the different galactose-dependent outcomes observed in Drosophila deficient in GALE activity toward UDP-gal or UDP-galNAc we measured the levels of gal-1P, UDP-gal, and UDP-galNAc in lysates prepared from galactose-exposed third instar larvae expressing different GALE transgenes. As illustrated in Figure 5, galactose exposed animals deficient in both GALE activities (bars marked “KD” for knockdown) accumulated abnormally high levels of gal-1P (Figure 5A and 5D) and UDP-gal (Figure 5B and 5E). Animals deficient only in GALE activity toward UDP-gal (bars marked “wbgU” in Figure 5) also demonstrated elevated gal-1P (Figure 5A and 5D) and UDP-gal (Figure 5B and 5E). In contrast, galactose exposed larvae deficient only in GALE activity toward UDP-galNAc (bars marked “eGALE” in Figure 5C and 5F) demonstrated no extraordinary metabolic abnormalities, although, as expected, the absolute level of UDP-galNAc was diminished in these animals independent of diet relative to the “no knockdown” control (Figure 5C). Also as expected, animals expressing either hGALE or both eGALE plus wbgU demonstrated no clear metabolic abnormalities (Figure 5).
The disparate metabolic profiles observed in GALE-impaired flies exposed to galactose provide a window of insight into potential mechanisms behind the outcomes observed. For example, gal-1P accumulates to abnormal levels in animals missing GALE activity toward UDP-gal but not UDP-galNAc, and only those animals demonstrate substantially reduced lifespan when exposed to galactose as adults. This metabolic result is expected, since only GALE activity toward UDP-gal should impact the Leloir pathway, and this outcome result implies that gal-1P might contribute to the early demise of these animals. However, the gal-1P result also implies that the negative outcomes observed in Drosophila deficient in GALE activity toward UDP-galNAc, e. g. compromised survival in embryos and compromised fecundity in adult females, do not result from gal-1P accumulation. This is an important point because it challenges the common supposition that gal-1P underlies pathophysiology in both classic and epimerase deficiency galactosemias. Clearly there must be another basis for the negative outcomes observed in these animals. It is also interesting to note that while loss of GALE activity toward UDP-galNAc in developing animals has phenotypic consequences, at least for female fecundity, it does not appear to negatively impact the “global” level of UDP-galNAc in animals exposed to galactose. The explanation for this apparent disparity might involve subtle or tissue-specific differences below the threshold of detection of our experimental approach. The implications of this work for patients with epimerase deficiency galactosemia are two-fold. First, these results demonstrate that both GALE activities are essential for health of flies, and possibly also people. To our knowledge clinical laboratories that test patient samples for GALE activity only test activity toward UDP-gal. While this practice is certainly understandable, given that mutations may impact the two GALE activities differently [18]–[20], the results presented here raise the possibility that rare patients with GALE deficiency limited to UDP-galNAc activity could be missed. Second, given the impact of GALE-loss on both male and female fecundity in flies, these results suggest that long-term studies of both male and female reproductive issues in epimerase-deficiency galactosemia patients might be warranted.
The Drosophila stocks used in this study are listed in Table S1. Stocks were maintained at 25°C on a molasses-based food that contained 43. 5 g/l cornmeal, 17. 5 g/l yeast extract, 8. 75 g/l agar, 54. 7 ml/l molasses, 10 mls propionic acid and 14. 4 ml/l tegosept mold inhibitor (10% w/v in ethanol). For experiments in which the levels and types of sugar were to be varied, we used a glucose-based food [5. 5 g/l agar, 40 g/l yeast, 90 g/l cornmeal, 100 g/l glucose, 10 ml/l propionic acid and 14. 4 ml/l tegosept mold inhibitor (10% w/v in ethanol) ] [21] supplemented with galactose, as indicated. UAS-eGALE and UAS-wbgU transgenes were generated by subcloning the eGALE and wbgU coding sequences, respectively, as EcoRI/XhoI fragments, into pUAST [22] using the EcoRI and XhoI sites in the pUAST polylinker region. The wbgU sequence was amplified from a plasmid generously provided by Peng George Wang (Ohio State University). Resulting plasmids were confirmed by sequence analysis. UAS-eGALE stocks were generated using standard transgenic techniques following injection of the transgene into embryos by the fly core of the Massachusetts General Hospital, Charlestown, MA. UAS-wbgU stocks were generated using standard transgenic techniques following injection of the transgene into embryos by Genetic Services, Inc. , Cambridge, MA. Transformants were selected by the presence of the white gene within pUAST. Expression of functional eGALE or wbgU was confirmed by enzymatic assay of lysates from transformants. Lysates were prepared and assays for GALK, GALT and GALE with UDP-gal as the substrate were performed (n≥3) as described previously [10]. Activity was calculated from the conversion of UDP-galNAc to UDP-glcNAc. The initial reaction mixture concentrations were: 100 mM glycine pH 8. 7,1. 6 mM UDP-galNAc and 0. 5 mM NAD. Enzyme assays were performed as described in Sanders et al. [10] except for the following changes: To start each reaction, 7. 5 µl of diluted protein and 5 µl of a cocktail of substrates and cofactors were combined. Reaction mixtures were incubated at 25°C for 30 minutes and then quenched by the addition of 112. 5 µl of ice-cold high-performance liquid chromatography (HPLC) -grade water (Fisher). Lysates were diluted 1∶4, except for those prepared from animals with RNAi knockdown, which were undiluted, and those prepared from animals overexpressing hGALE or wbgU transgenes, which were diluted to a greater extent. Lysates from Act5C>hGALE22C animals were diluted 1∶60. Lysates from Act5C>wbgU19A animals were diluted 1∶20. Generation of animals in which GALE knockdown was initiated at 24-hour intervals throughout development was achieved as described previously [10]. A stock homozygous for both P{tubP-GAL80ts}10 and 12030R-2 was used in all crosses. These flies were then crossed to the appropriate genotypes to obtain offspring expressing various transgenes; for: no transgene, P{Act5C-GAL4}25FO1; +/T (2; 3) TSTL, Tb, Hu; eGALE only, P{Act5C-GAL4}25FO1, UAS-eGALE62A/CyO; wbgU only, P{Act5C-GAL4}25FO1/CyO; P{Act5C-GAL4}25FO1/CyO; UAS-wbgU19A/TM6B; eGALE plus wbgU, P{Act5C-GAL4}25FO1, UAS-eGALE62A/CyO; UAS-wbgU19A/TM6B; hGALE, P{Act5C-GAL4}25FO1/CyO; UAS-hGALE22C/TM6B. Adult flies eclosing from the vials were scored for the presence or absence of humeral and/or curly, as appropriate for each cross. Animals in which dGALE knockdown with concurrent transgene expression was achieved throughout development were obtained as described above. These animals were maintained on standard molasses medium until eclosion. Within 24 hours after eclosion, approximately 20 virgin male or female flies were placed in fresh vials of food containing 555 mM glucose only or 555 mM glucose plus 175 mM galactose. Flies were transferred to fresh food every 2–3 days, and the number of dead flies in each vial was recorded every other day. Log rank and Wilcoxon tests were used for statistical analysis using the program JMP (http: //www. jmp. com/). Cohorts of newly hatched larvae raised at 18°C were transferred to vials of food containing either 555 mM glucose only or 555 mM glucose plus 175 mM galactose. The larvae were maintained at 18°C for one additional day, then transferred to 28°–29°C and allowed to develop for another four days prior to harvest. Metabolites were extracted and quantified as described previously [10], and were separated and quantified using a Dionex HPLC, as described previously [23] with the following changes: UDP-gal and UDP-galNAc were separated using a high salt isocratic procedure with a flow rate of 0. 5 mL/min and buffer concentrations of 45% A and 55% B (0–61 min), followed by washing with a linear increase of B to 95% (61–80 min). For all samples, 20 µl were injected into a 25 µl injection loop. Ratios of the level of each metabolite on food containing galactose over the level on food containing glucose only were calculated, and 95% confidence intervals were determined using Fieller' s theorem. | In this manuscript we apply a fruit fly model to explore the relative contributions of each of two different activities attributed to a single enzyme—UDP-galactose 4′-epimerase (GALE); partial impairment of human GALE results in the potentially severe metabolic disorder epimerase deficiency galactosemia. One GALE activity involves interconverting UDP-galactose and UDP-glucose in the Leloir pathway of galactose metabolism; the other activity involves interconverting UDP-N-acetylgalactosamine and UDP-N-acetylglucosamine. We have previously demonstrated that complete loss of GALE is embryonic lethal in fruit flies, but it was unclear which GALE activity loss was responsible for the outcome. Using genetically modified fruit flies, we were able to remove or give back each GALE activity individually at different times in development and observe the consequences. Our results demonstrate that both GALE activities are essential, although they play different roles at different times in development. These results provide insight into the normal functions of GALE and also have implications for diagnosis and intervention in epimerase deficiency galactosemia. | Abstract
Introduction
Results
Discussion
Materials and Methods | developmental biology
model organisms
genetics
biology
molecular cell biology
genetics and genomics | 2012 | UDP-Galactose 4′-Epimerase Activities toward UDP-Gal and UDP-GalNAc Play Different Roles in the Development of Drosophila melanogaster | 6,673 | 272 |
The identification and characterization of antigens expressed in Trypanosoma cruzi stages that parasitize mammals are essential steps for the development of new vaccines and diagnostics. Genes that are preferentially expressed in trypomastigotes may be involved in key processes that define the biology of trypomastigotes, like cell invasion and immune system evasion. With the initial aim of identifying trypomastigote-specific expressed tags, we constructed and sequenced an epimastigote-subtracted trypomastigote cDNA library (library TcT-E). More than 45% of the sequenced clones of the library could not be mapped to previously annotated mRNAs or proteins. We validated the presence of these transcripts by reverse northern blot and northern blot experiments, therefore providing novel information about the mRNA expression of these genes in trypomastigotes. A 280-bp consensus element (TcT-E element, TcT-Eelem) located at the 3′ untranslated region (3′ UTR) of many different open reading frames (ORFs) was identified after clustering the TcT-E dataset. Using an RT-PCR approach, we were able to amplify different mature mRNAs containing the same TcT-Eelem in the 3′ UTR. The proteins encoded by these ORFs are members of a novel surface protein family in T. cruzi, (which we named TcTASV for T. cruzi Trypomastigote, Alanine, Serine and Valine rich proteins). All members of the TcTASV family have conserved coding amino- and carboxy-termini, and a central variable core that allows partitioning of TcTASV proteins into three subfamilies. Analysis of the T. cruzi genome database resulted in the identification of 38 genes/ORFs for the whole TcTASV family in the reference CL-Brener strain (lineage II). Because this protein family was not found in other trypanosomatids, we also looked for the presence of TcTASV genes in other evolutionary lineages of T. cruzi, sequencing 48 and 28 TcTASVs members from the RA (lineage II) and Dm28 (lineage I) T. cruzi strains respectively. Detailed phylogenetic analyses of TcTASV gene products show that this gene family is different from previously characterized mucin (TcMUCII), mucin-like, and MASP protein families. We identified TcTASV, a new gene family of surface proteins in T. cruzi.
Trypanosoma cruzi, a kinetoplastid protozoan parasite, is the causative agent of the American trypanosomiasis, also known as Chagas' disease, a zoonotic disease that affects about 8 million individuals in Latin America [1]. The disease is a chronic illness, which symptoms appear 10 or more years after the beginning of the infection, being the most common clinical forms the digestive megas and heart failure, which can lead to death. Currently, there is no effective therapy nor vaccine for the treatment or prevention of the disease [1], [2]. The identification and characterization of proteins expressed in the mammalian stages of T. cruzi (amastigotes and trypomastigotes) are key to drug and vaccine development [3]. The genome of the CL-Brener clone of T. cruzi was already sequenced by 2005 [4], but its final assembly has only been partially completed recently, mainly because of the high number of repetitive sequences [5]. Although 90% of the genes were assembled in 41 chromosomes, the remaining 10%, the majority of which belong to multigene families, are still excluded from the assembly, as they have not been assigned to any chromosome. Moreover, 64% of the predicted genes have been annotated as hypothetical proteins –their function and/or expression is unknown-, and it is possible that other genes may not have been annotated as genes at all. Therefore, the generation of expressed sequence tags (ESTs, single pass reads obtained from randomly selected cDNA clones) is still a valuable approach to map the location of genes, to obtain experimental evidence about their expression, to identify stage-specific transcripts, and to identify their untranslated regions (UTRs). Previously, we reported the sequencing and analysis of two full-length cDNA libraries constructed from trypomastigotes and amastigotes [6]. Because those libraries were not normalized and were prepared under similar conditions, we were able to identify a number of EST clusters that showed a significantly biased composition in the number of sequences derived from either the trypomastigote and/or the amastigote cDNA libraries. However, only one cluster corresponded to a case of apparent increased expression in trypomastigotes. In the present work, we focused our attention on the identification of mRNA transcripts over-represented in the mammalian trypomastigote stage as compared to the vector-associated epimastigote stage, using a subtractive PCR approach [7]. Molecules that are differentially expressed in the trypomastigote stage may be involved in the extracellular survival, dissemination to different organs and cell invasion that are the hallmarks of of this parasite stage. Besides finding a large proportion of novel and differentially expressed mRNAs in trypomastigotes (most of them with an unknown function), we discovered a novel protein family, which we denominated TcTASV. The expression profile and the genetic mapping of TcTASVs in the CL-Brener, Dm28 and RA T. cruzi strains were also investigated in this work.
All procedures requiring animals were performed in agreement with the guidelines of the Animal Ethics Comitee of our Institution. The CL-Brener clone (reference strain), RA (lineage II) and Dm28 (lineage I) strains of T. cruzi were used [8], [9], [10]. Trypomastigotes and amastigotes were obtained in vitro by infection of Vero cells grown in Minimum Essential Medium (MEM) -3% foetal bovine serum. For the library construction essentially pure CL-Brener trypomastigotes (with less than 3% amastigote forms) were used. Epimastigotes were obtained from axenic cultures, as previously described [11]. Total RNA was isolated from trypomastigotes and epimastigotes with TRIzol (Gibco-BRL) and mRNA purified with polyA-Tract mRNA isolation system (Promega). The PCR-Select cDNA Subtraction kit was used for library construction following the selective subtractive hybridization protocol provided by the manufacturers (CLONTECH). First strand cDNA synthesis was performed with 2 µg of polyA+ of each T. cruzi stage (trypomastigote and epimastigote), oligo dT primer with a 5′ RsaI site and Superscript II reverse transcriptase (Gibco-BRL). Second strand cDNA synthesis was performed with T4 DNA polymerase. After RsaI digestion of double stranded cDNA, two different sets of adaptors were ligated to the tester cDNA (trypomastigotes) but not to the driver cDNA (epimastigotes). Two rounds of subtractive hybridization in the presence of an excess of driver cDNA were performed, thus leading to the enrichment of differentially expressed sequences in the tester cDNA population that were the templates for further suppressive PCR amplification performed with adaptor-specific primers [7]. The subtraction efficiency was verified by monitoring the PCR amplification of the T. cruzi histone 2A transcript in subtracted and unsubtracted samples (H2_3′: tcttggacgccttcttcgct; H2_5′: gtgatgccgagcctgaacaa). PCR products enriched for tester differentially expressed sequences -higher than 100 bp- were cloned into the pGEM T-Easy vector (Promega). E. coli DH5α cells were transformed with ligations; white colonies were randomly picked and the TcT-E library plated in 384-well microplates. Template preparation of clones for sequencing was carried out as previously described [12]. Sequencing reactions were performed in a Perkin Elmer 9600 thermal cycler by using a Dye Terminator Cycle sequencing Ready Reaction Kit with AmpliTaq DNA polymerase according to the protocols supplied by the manufacturer (Applied Biosystems). Single-pass sequencing was performed on an ABI 377 automated sequencer. Bases were called by PHRED and an automated protocol for the analysis of the data was used to assess sequence quality and trim vector, adaptors and unreliable data from sequences [6]. Sequences longer than 100 bases were further analyzed. Sequence similarity searches against in-house databases were run locally using the BLAST suite of programs as distributed by the NCBI in a PC computer running Linux. Sequences were also compared against the NCBI non-redundant protein or nucleotide databases by using BLASTX or BLASTN programs respectively (cut off values: BLASTN p<10e-40; BLASTX p<10e-5) [12], [13]. For Northern blot, total RNA (20 µg/lane) from trypomastigotes and epimastigotes was electrophoresed on 1. 5% agarose formaldehyde gels and transferred to nylon membranes (Zeta-Probe, BioRad). All TcT-E clones used as probes were labeled with 32P by PCR using adaptor-specific primers (Nest_2R: agcgtggtcgcggccgaggt; Nest_1: tcgagcggccgcccgggcaggt). Hybridization and washing were performed at 63°C following standard procedures [14]. The complete ORF Tcruzi_1863-4-1211-93 (TriTrypDB. org) was amplified by PCR from the clone G53E20 (GenBank Acc AZ050960) from a random genomic library DNA [12], labeled by PCR and used as probe in northern and southern blot experiments. For reverse northern blots, clones of the TcT-E library were picked, grown in LB-ampicillin in 96-well plates and subjected to colony-PCR using 1 µl of culture and primers Nest_2R and Nest_1 [15]. The sizes of the inserts were checked on a 2% agarose gel and PCR products were then denatured and dotted in duplicate onto nitrocellulose membranes. Filters were hybridized with cDNA probes synthesized from total RNA of trypomastigotes and epimastigotes by reverse transcription using 32P-dCTP. Plasmids containing tubulin and SAPA (shed acute phase antigen) T. cruzi genes were dotted on membranes as positive controls, whereas a plasmid containing a non-related (mouse) gene was used as a negative control. For southern blots, DNA was prepared from epimastigotes of the CL-Brener strain by using the conventional Proteinase K phenol-chloroform method and digested with the indicated restriction enzymes. Electrophoresis, hybridization and washing were performed by standard procedures [14]. The complete TcT-E element (TcT-Eelem) was obtained from CL-Brener genomic DNA by PCR using Pfu DNA polymerase and the primers TcT-Ee_pp_Hind (taaagcttccgggcaggtacagtat) and TcT-Ee_pp_Xho (atctcgagtgagaatcccgcaggact). Mature mRNA transcripts containing both the TcT-Eelem and the different upstream open reading frames (ORFs) were identified by RT-PCR and sequencing in the CL-Brener strain. RNA was treated with RQ1 DNase (Promega Corp. , Madison, USA) and first strand cDNA synthesized using an oligo dT primer. PCR was performed using a 5′ primer specific for the T. cruzi miniexon containing an EcoRI site (cccgaattcaacgctattattgatacagtttctgt) and a 3′ antisense primer corresponding to the 3′ region of the TcT-Eelem (TcT-Ee_int_R: aagaaatgattcggcaggaa). PCR products were gel- excised, purified using QIAex II (Qiagen) and cloned. Alternatively, after first strand cDNA synthesis, PCR was performed with primers corresponding to the 5′ and 3′ conserved regions of the majority of the ORFs (CDS_desc_L: gtcgagcgactctacgacg; CDS_desc_R: acagcagcacagacaaggg) or with the 5′ CDS_desc_L and the 3′ T-Ee_int_R primers. Bands were also gel-excised, cloned and sequenced. Conceptually translated proteins corresponding to the cloned CDS were aligned by the Clustal method. To search for TcTASV in other T. cruzi strains, genomic DNA from Dm28 (lineage I, currently T. cruzi I) and RA (lineage II, currently T. cruzi VI) was amplified by PCR using primers CDS_desc_L and CDS_desc_R [8], [9], [10]. The bands obtained were gel-purified, cloned and sequenced on both strands on an ABI 3130. The sequences of each clone were assembled using the program DNAbaser. Phylogenetic trees were constructed from amino acid alignments using the Neighbour Joining method, and bootstrapped using 1000 permutations. The trees were rooted using 6 sequences as outgroups, and were visualized with the TreeView program (http: //taxonomy. zoology. gla. ac. uk/rod/treeview. html). The nucleotide sequence AF080220 (GenBank Accession number) was used to carry out a BLASTN search against the TcT-E database. A multiple sequence alignment was computed using the Clustal Method [16]. The consensus sequence of the TcT-E element (TcT-Eelem) was used as bait to search the unassembled whole genome shotgun sequences (GSSs) of T. cruzi at TIGR (http: //tigrblast. tigr. org/er-blast/index. cgi? project=tca1). GSSs identified in this way were assembled into contigs, that were then visualized and edited in Artemis to identify in silico additional TcTASVs [17]. Motif scanning for signal peptide, cleavage sites (SignalP) and Ser, Thr, and Tyr phosphorylation sites (NetPhos) was performed in the ExPASy proteomics server at http: //www. expasy. org/. The prediction of glycosylphosphatidylinositol (GPI) anchor addition sites, was performed using DGPI (run locally) and FragAnchor (http: //navet. ics. hawaii. edu/~fraganchor/NNHMM/NNHMM. html) [18]. The peptide RQ28 (GKLRWRFQGEKDWRKC) comprising amino acids 57 to 72 of TcTASV-A1 (GenBank AM492199) was purchased from Sigma-Genosys. This sequence was chosen because it is present in the conserved, noncleaved N-terminal region of the protein family which is also predicted not to be glycosylated or modified. The KLH coupled peptide was used to develop an anti-TcTASV-A specific serum in rabbit. Total IgG from anti-RQ serum was purified with protein G columns (HiTrap, GE Healthcare Life Sciences) and specific anti-TcTASV-A antibodies were purified by column affinity with SulfoLink Kits coupled with the RQ28 peptide (Thermo Scientific). Antibodies were used at 0. 1 µg/ml. Protein extracts of T. cruzi epimastigotes, trypomastigotes and amastigotes were resuspended in cracking buffer (60 mM Tris-HCl pH 6. 8; 2% SDS, 0. 1% glycerol, 5% â-mercaptoethanol) in the presence of protease inhibitors at a density of 1–2×106 parasites/µl. Conventional SDS-PAGE was performed on 12% polyacrylamide gels, and proteins were then transferred to nitrocellulose filters. Blots were incubated with anti-TcTASV-A antibodies, washed, incubated with an anti-rabbit secondary antibody labelled with horseradish-peroxidase (DAKO) and developed with chemiluminescence. Note: Nucleotide sequence data reported in this paper have been submitted to the EMBL/GenBank/DDBJ databases with the accession numbers AM492199–AM492211, GW883555–GW883875, HO052091–HO052172 and FN599093–FN599167.
To gain information about the genes that are differentially expressed in the trypomastigote (circulating stage in mammals) but not in the epimastigote (replicative stage in the insect vector) of T. cruzi, we built a library of trypomastigote cDNA subtracted with epimastigote cDNA (TcT-E library). Partial sequencing of this library provided high-quality sequences of 403 clones (GenBank Acc GW883555–GW883875 and HO052091–HO052172). With this set of data sequence (BLAST) analyses were performed against various databases of trypanosomatid ESTs (T. cruzi trypomastigotes, T. cruzi epimastigotes, ESTs of all kinetoplastids) and against protein databases (nr at GenBank and SwissProt) (Fig. 1A). The BLAST reports for all searches can be accessed online at http: //genoma. unsam. edu. ar/projects/tct-e/tct-e. p. html (Table S1). Briefly, more than 46% of the TcT-E dataset do not have any known mRNA or protein homologue and only two clones give positive hits against all databases (Fig. 1A). The comparison of the TcT-E dataset against T. cruzi ESTs showed that (a) only 3. 5% of them corresponded to trypomastigote-specific tags that were identified prior to this work and (b) 38% of TcT-E clones have significant matches with epimastigote sequences (Fig. 1A). The latter was expected in part because of the high number of epimastigote ESTs available in public databases. This could also indicate that these transcripts, although present in both stages, might be expressed at a higher level in trypomastigotes than in epimastigotes, since our library had been subtracted with epimastigote cDNA. By Northern blot (Fig. 1B) and reverse Northern blot on 86 randomly picked TcT-E clones (data not shown), we were able to confirm that even in those cases were a TcT-E clone had identity with ESTs obtained from epimastigotes, the mRNA levels were consistently higher in trypomastigotes than in epimastigotes. Sixty-eight (16. 9%) clones had similarity to known proteins (nr and SwissProt databases) and 33 of them matched previously described trypomastigote antigens like the flagellum-associated surface protein FL-160 (gb|AAA30196) or sialidase homologues (AF051695 and AF051696) (Table S1). The top 50 hits against SwissProt and GenBank (nr) are provided in Table S2. The whole TcT-E dataset can be searched by blast at http: //genoma. unsam. edu. ar/projects/tct-e/. To compensate for sequencing errors and to obtain longer sequences, we next generated a non-redundant TcT-E EST set by clustering (using the blastclust tool from the NCBI C Toolkit), which was composed of 23 clusters containing 261 sequences and 142 singletons (ESTs with no similarity against any other EST) (Table S3). EST clones belonging to clusters with the largest number of sequences as well as other clones that showed significant similarity to SwissProt and/or GenBank nr databases were selected to analyze their expression by reverse northern blot (Fig. 1C). We observed that most of the TcT-E clones were actually overexpressed in trypomastigotes, which again confirms the correct subtraction of the library, and that the sequences generated provide information about the transcripts differentially expressed in the trypomastigote stage. The larger groups of sequences in the clustered TcT-E EST dataset contained sequences that had no similarity against sequences in other databases. To further characterize these sequences, we then attempted to find any motif or conserved sequence in these contigs. By lowering the cut off value for BLASTN (e≤10e-5), we found that some contigs in cluster 1 showed similarity with a 100-bp region in the 3′ untranslated region (UTR) of the flagellar T. cruzi FL-160-2 gene (GenBank Acc AF080220) [19], [20]. By computing a multiple sequence alignment of the TcT-E clones that presented identity in these 100 bases, we reconstructed a consensus sequence of 280 bp (Fig. 2A). We named this 280-bp element TcT-E element (TcT-Eelem) because of its high representation in the subtractive TcT-E library. The first 27 and last 17 bases of the TcT-Eelem (bold in Fig. 2A) are polypyrimidine tracts and bases 66 to 165 (in italic) correspond to those similar to the 3′ UTR of FL-160-2. Another feature of the TcT-Eelem is the presence of a variable number (between 3 and 5) of TTA repeats (bold underlined in Fig. 2A). By southern blot, we found a pattern indicative of multiple genomic copies of the TcT-Eelem since several bands were detected, even though none of the restriction enzymes used are predicted to cut into the probe (Fig. 2B). Because the similarity of the TcT-Eelem to the 3′ UTR of the FL-160 gene was limited to 100 bp out of the 280 bp of the TcT-Eelem, we reasoned that TcT-Eelem might be associated to other genes (i. e. be present in gene contexts other than FL-160 genes). The sequence of the TcT-Eelem was used to search the T. cruzi genome raw data (unassembled whole genome shotgun sequences, or contigs assembled by the genome project) and the position of the TcT-Eelem relative to upstream open reading frames (ORFs) was determined. Interestingly, the polypyrimidine tracts contained within the TcT-Eelem were always found 30–70 bases downstream of the stop codon of a coding region (CDS), in different contigs. The close proximity of the TcT-Eelem to the end of the upstream coding sequence strongly suggested that the TcT-Eelem was part of the 3′ UTR of the gene. By southern blot, using a probe corresponding to the complete ORF of a predicted protein associated with the TcT-Eelem (currently identified as ORF Tcruzi_1863-4-1211-93, TriTrypDB database [21]), we observed a hybridization pattern similar to that obtained using the TcT-Eelem as probe (Fig. 2B), thus reinforcing the genetic linkage between the TcT-Eelem and the identified ORFs (data not shown). By northern blot analysis we confirmed that, like most of the ESTs from the TcT-E library, this ORF was also differentially expressed in the trypomastigote stage (Fig. 2C). Interestingly, fragments of several of the CDSs found associated with the TcT-Eelem in this bioinformatic analysis were also represented in the TcT-E library (for example clones TcT-E01p24 and TcT-E01k23, corresponding to GenBank GW883736 and HO052122, respectively, Fig. 1C). A schematic diagram of the CDS - TcT-Eelem arrangement found by in silico analysis is shown in Figure 2D. Although different coding sequences were located upstream of the TcT-Eelem, we observed that the amino- and carboxy–termini of those conceptually translated proteins were conserved, suggesting that these ORFs are members of the same family. Besides, we detected three bands by northern blot when using the clone TcT-E01k23 (GenBank HO052122) as probe, which corresponds to the last 270 nucleotides of one TcT-Eelem-associated ORF (not shown). Thus, both in silico and experimental observations suggested the presence of a new protein family sharing conserved amino- and carboxy-termini and the 3′ UTR of the mRNA (TcT-Eelem). To further investigate this hypothesis we looked for the presence of full-length transcripts, by performing RT-PCR experiments using a reverse primer specific for the 3′ end of the TcT-Eelem (TcT-Ee-intR) and a forward primer specific for the T. cruzi miniexon (ME) that is added by trans-splicing to all RNA PolII transcripts in T. cruzi [22]. In parallel, other RT-PCR reactions were designed to amplify the CDSs codifying for this new protein family irrespectively of their untranslated region, using the primers indicated in Figure 2D. Bands of ∼1500 bp and ∼900 bp obtained with primers ME/ TcT-Ee-intR as well as the three bands obtained in trypomastigotes with CDS-L/CDS-R primers (Fig. 2E) were cut from the gel, cloned and sequenced. Thirteen different transcripts were identified and deposited at GenBank with the accession numbers AM492199–AM492211. The coding region of the transcripts was conceptually translated and aligned, confirming that they belong to a multigene family with conserved amino- and carboxy-termini and a variable central core (Fig. 3A). The proteins are enriched in Ala, Ser and Val residues, and therefore, the family was named TcTASV (for Trypomastigote Alanine Serine Valine rich protein). According to the length of the central region, we were able to define three subfamilies (A, B and C, see Fig. 3A), with a conserved Glu-Ala-Pro motif in the variable region (asterisks in Fig. 3A). A visualization of the alignment in Fig. 3A using the partial order multiple sequence alignment visualizer POAVIZ (Fig. 3B) [23] helps to define the overall structure of how sequences match and diverge in the alignment, and facilitates the identification of complex branching structures, such as domains or large-scale insertions/ deletions. Aligned regions are joined together in the partial order graph whereas regions that are unaligned are separated, clearly showing the shared and divergent regions of the 3 TcTASV subfamilies, schematically represented in light blue (TcTASV-A), green (TcTASV-B) and orange (TcTASV-C) (Fig. 3B). The predicted molecular weights of the subfamilies are 18 kDa, 27 kDa and 36 kDa for the A, B and C apoproteins respectively. All proteins had a predicted signal peptide (arrows above and below the alignment in Fig. 3A show the predicted cleavage site) and a consensus sequence for the addition of a GPI anchor (red box in alignment), suggesting that the proteins could be located at the parasite surface. A high proportion of Ser and Thr that could be glycosylated (as found for other surface proteins of T. cruzi) were also identified [24], [25]. Surprisingly, many TcTASVs genes were not annotated as genes in the T. cruzi genome (available at http: //TriTrypDB. org) [4], [5], [21]. For example, only the TcTASV-A 2,4 and 8 genes (GenBank AM492200, AM492209 and AM492210, respectively) were annotated as protein coding genes (hypothetical), while all other TcTASVs-A were found as unannotated ORFs in the data base (Table S4). Besides, most TcTASVs-A have been annotated starting in an ATG codon (Met residue) located ∼145 aa upstream of the one we identified here as the site of trans-splicing, based on the amplification of mature mRNAs using a primer specific for the 5′ spliced leader. The best hits found in TriTrypDB for each TcTASV gene and the corresponding additional information (assigned gene number, contig, identity and other observations about the annotation of these genes is presented in Table S4. TcTASV genes are only present in T. cruzi. Sequence similarity searches revealed no orthologues in the genomes of T. brucei and Leishmania spp, and in ESTs obtained from T. rangeli, the most closely-related trypanosomatids. Based on this observation it is possible to hypothesize that TcTASVs may be involved in T. cruzi-specific strategies of survival and/or immune evasion. Although we obtained experimental evidence supporting the presence of 13 TcTASVs in CL-Brener (nine TcTASVs-A, two TcTASVs-B and two TcTASVs-C), it is likely that the TcTASV family is composed by a higher number of members. Recently, Arner et al. developed a public database specifically designed for the identification of repeated genes in the T. cruzi genome [26], the assumption being that the genes present in high copy numbers were collapsed during the assembly. By using this resource, the estimated number of genes was predicted to be 14 for TcTASVs-A, 6 for TcTASVs-B and 22 for TcTASVs-C. Our own detailed inspection of the T. cruzi data base allowed us to identify 20 TcTASVs-A, 5 TcTASVs-B and 13 TcTASVs-C members, giving a total number of 38 genes for the TcTASV family (Table S5, additional material). In the case of TcTASV-A and B families, when predicted as genes, they were annotated as hypothetical proteins. However, 6 out of 7 TcTASV-C genes were annotated as mucin-like genes. The mucin-like family is another family of surface proteins in T. cruzi and, as currently annotated in TriTrypDB, is composed of 28 genes [21]. Although the overall structure of mucin-like genes (conserved amino- and carboxy-termini, predictions for signal peptide and GPI anchor addition) resembles the one for TcTASV genes, mucin-like and TcTASV have very different amino acid composition. The hypotheses that (a) TcTASV is a protein family different from the mucin-like gene family, and (b) the genes that we identified here as TcTASV-C (but were annotated as mucin-like) are indeed members of the TcTASV family and not of the mucin-like family, were tested by a phylogenetic analysis. Starting with an alignment that included all TcTASV and mucin-like genes, we computed a neighbor-joining phylogenetic tree (Figure S1). The tree clearly shows two major branches: one for mucin-like genes and another for TcTASVs genes (including these 6 incorrectly annotated mucin-like genes). On the other hand, the monophyletic origin of TcTASVs in relation to other structurally similar protein families (TcMUCII, mucin-like, and MASP), was also tested through a phylogenetic analysis of 15 sequences from each family (Figure S2) [4], [27], [28], [29]. The limited phylogenetic distribution of the TcTASV family (so far only detected in T. cruzi), prompted us to investigate the presence of TcTASV genes in T. cruzi strains from other evolutionary lineages (T. cruzi I and II). For this, we amplified the genes of the TcTASV family from two representative strains (Dm28 and RA, respectively) using primers specific for the 3′ and 5′ conserved regions. Each of the amplicons obtained for each strain and for each TcTASV subfamily, was cloned to build a mini-library, in order to identify as many members as possible. We obtained 73 clones from the RA strain and 41 from Dm28 strain, but, for further analysis, we selected only those who presented unique sequences for each strain (RA: 48; Dm28: 28; GenBank Acc FN599093–FN599167) (Fig. 4, Table). The 76 unique sequences obtained for RA and Dm28, together with 8 sequences of CL-Brener (TcTASV-A: 4, TcTASV-B: 2 and TcTASV-C: 2) were used to compute a phylogenetic tree, using sequences of other T. cruzi glycoprotein families (mucin-like, TcMUCII and MASP) as outgroups (Fig. 4). All three (TcTASV-A, B and C) subfamilies were identified in this dataset. We also identified a new subgroup composed of six Dm28 and one RA sequences with mixed characteristics that could constitute a new TcTASV subfamily with some characteristics shared with members of the A subfamily (amino acid sequence) and others shared with members of the C subfamily (length) (Fig. 4, gray box). As in the case of the CL-Brener strain, the subfamilies with most members were TcTASV-A and TcTASV-C and, interestingly, we noted the absence of the TcTASV-B subfamily in the Dm28 strain, which could be explained either by the absence of TcTASV-B genes in this strain or by the accumulation of mutations that prevented the amplification of members of this subfamily in our PCR experiments. Another distinguishing characteristic between the two evolutionary lineages of T. cruzi is that proteins of the subfamily C found in lineage II (RA and CL-Brener) are longer than the same proteins found in lineage I (Dm28) (Fig. 4, Table). To assess the expression of TcTASV family, we took advantage of proteomic data, available in TcruziDB/TriTrypDB, together with experimental data obtained in this work. Mass spectrometry data strongly suggest the differential expression in trypomastigotes of al least 1 out of 4 TcTASV-A genes -Tc00. 1047053506337. 80, Tc00. 1047053506337. 100, Tc00. 1047053510717. 10 and, Tc00. 1047053510717. 20- that share a peptide that was detected only in this parasite stage (KPGEYESVTDDCAR, 2 spectra) (Table S5) [28], [30]. On the other hand, proteomic evidence of the expression of the TcTASV-A8 gene (GenBank AM492210; Tc00. 1047053506573. 5) has been reported for trypomastigotes (five mass spectra) and amastigotes (one spectrum) [28] and can be accessed through TcruziDB. org [30]. The peptide identified is also 100% identical to amino acids 89–104 of other TcTASV gene products (A9: GenBank AM492211, A7: GenBank AM492202 and A5: GenBank AM492201). Moreover, the peptide is completely conserved (15/16 identical aa) in all the other TcTASV-A members. The expression pattern of members of the TcTASV-A subfamily was also analyzed using affinity-purified antibodies that had been generated against a peptide that is conserved throughout the subfamily (see Methods). We were able to find TcTASV-A proteins only in cell-derived trypomastigotes, detecting two bands of ∼18 kDa by western blot (Figure S3).
Our first goal in this work was the identification of genes preferentially expressed in the trypomastigote stage of Trypanosoma cruzi, the etiological agent of Chagas' disease. To achieve this goal we followed an approach based on the sequencing of a subtractive cDNA library. Most of the clones of this TcT-E library represent mRNAs that are preferentially expressed in trypomastigotes, as confirmed by northern and reverse northern blots (Fig 1). The sequence information derived from the TcT-E library allowed us to identify genes that were not previously described in T. cruzi. For example, we found several clones with similarity to proteins that have been proposed to function in processes such as rRNA processing, ribosome assembly and the control of cell cycle in other eukaryotic organisms (Bop1, Nop56, BEM, Cwf17; see Tables S1 and S2) [31], [32], [33], [34]. Little is known in T. cruzi about these checkpoints in the cell cycle and it is interesting to note that the preferential expression of these mRNAs was detected in a non-replicative stage of the parasite. The lack of transcriptional control in trypanosomatids is well known, and, therefore, stage-specific differences in mRNA abundance are likely to be the result of selective mRNA stabilization and/or the absence of degradation mechanisms for those transcripts [22]. Therefore, one possibility is that these transcripts are being accumulated for the production of the corresponding proteins once the trypomastigote differentiates into the replicating amastigote within the host cell, or when the trypomastigote differentiates into epimastigotes upon entering the insect vector. After clustering the TcT-E dataset we identified a sequence that was found to be over-represented in trypomastigotes and that has a subregion of 100 bp with high similarity to the 3′ UTR of the T. cruzi flagellar antigen FL-160-2. This observation called our attention because the FL-160-2 gene is a member of a numerous family that is differentially expressed on the surface of trypomastigotes and is involved in parasite virulence [19], [20]. All these facts suggested that the 100 bp region could be part of a longer conserved region, and, indeed, we reconstructed a 280 bp element by multiple sequence alignment of TcT-E clones that matched the 100-bp motif that we named TcT-E element (TcT-Eelem), because of its high representation in the TcT-E library. Although we ended up associating the TcT-Eelem with the 3′ UTR of the new TcTASV family, we also observed that part of the TcT-Eelem (∼120–150 nt) is also found downstream of genes that do not belong to this family. For example, some hypothetical proteins, trans-sialidase genes or other coding sequences harbouring part of the TcT-Eelem were identified (Tc00. 1047053507875. 70, Tc00. 1047053504533. 40, Tc00. 1047053507491. 20). Interestingly, in all those cases, the 120–150-bp subregion of the TcT-Eelem is farther downstream from the stop codon than in the case of TcTASVs genes. Post-transcriptional cis-acting elements conserved among different genes and included into more extended 3′ UTRs have been previously identified. The existence of a regulatory region of 770 bp that is specific for amastin genes and that contains a 450-bp zone shared by amastin and other developmentally-regulated mRNAs has been reported in Leishmania [35]. This 450-bp sub-region (currently known to be part of the LmSIDER1 subfamily) mediates the translational regulation of mature transcripts in response to elevated temperature, the main environmental change that the parasite encounters upon its transmission from the vector to the mammalian host [36], [37]. Taking this into account, it could be hypothesized that a general stage-specific regulation of genes can be achieved in a similar way in T. cruzi. The 120–150-bp motif that is shared by different genes preferentially expressed in trypomastigotes, such as FL-160, TS and TcTASVs, could be involved in this stage-specific expression, probably forming part of a post-transcriptional regulon that allows the coordinated expression of these genes [38]. The new TcTASV gene family described in this work is composed of 38 members in the CL-Brener strain, none of which show significant similarity to other surface proteins in T. cruzi. A meticulous comparative analysis between sequences of TcTASV, MASPs, TcMUCII and mucin-like genes, shows that each of the families diverge in a diferent branch of the computed phylogenetic tree, thus reinforcing the idea that these are indeed different protein families. After the recent re-assembly of the genome of T. cruzi [5], previously annotated genes that we have now identified as TcTASVs could be found in 5 chromosomes, with a high proportion of TcTASVs-A on chromosome 16 and almost all annotated TcTASV-Cs on chromosome 24. TcTASV genes are apparently not arranged in tandem and most of them are surrounded by other hypothetical proteins (they are not TcTASVs). However, the majority of the TcTASV genes were not annotated by the genome-sequencing consortium and are still left out of the final genome assembly (they are only present as ORFs identified in unassembled or small partially assembled contigs). This is highly suggestive of assembly problems that occur frequently when highly similar genes are present in a moderate to high copy numbers. Therefore, it is possible that the copy number of TcTASVs genes in the CL-Brener genome could have been underestimated because of the collapse of repeated genes into fewer copies during assembly. However, the identification of a similar number of members of the TcTASV family in another type II strain (RA) of T. cruzi probably indicates that for lineage II the number of TcTASV genes is around 45, whereas those for lineage I is probably around 30, i. e. , the lowest number. These conclusions were derived from PCR experiments using oligonucleotides designed on highly conserved regions. Therefore, there is still the possibility that other TcTASV genes could not be amplified by these primers. Complex glycoproteins cover the surface of all the developmental stages of trypanosomatid human pathogens [2], [39]. Among the species-specific families, the best-studied ones are probably the mucins of T. cruzi and the proteophosphoglycans (PPGs) of Leishmania spp. Both protein families are rich in Ser, Thr and Pro residues, are retained in the membrane by GPI anchors and can be released from the parasite. In the case of TcTASVs, the amino acid composition is different, being enriched in Ala, Ser and Val. Regarding their expression, different groups of mucins and proteophosphoglycans are developmentally expressed, i. e. TcMUC I and II are expressed in the mammalian stages of T. cruzi, whereas TcSMUGs are only found in insect-derived stages ([40] and reviewed in [41], [42], [43]). In Leishmania, filamentous PPGs are secreted by promastigotes and have been implicated in protection from digestive enzymes in the insect midgut and in the formation of a plug in the sandfly digestive tract, which causes an increased frequency of feeding and correlates with parasite invasion and virulence [44], [45], [46]. On the other hand, membrane-bound PPGs have been implicated in parasite binding and invasion of macrophages [47], [48], [49]. For both mucins and PPGs several mechanisms leading to immune system evasion have also been demonstrated [41], [42], [49], [50], [51], [52], [53]. Therefore, it is clear that the parasite expresses different kind of mucins or PPGs, even with a differential cellular localization, in the different developmental stages in order to invade and persist in the parasitized host. In this work we demonstrate that TcTASV-A are expressed in trypomastigotes and could not be detected in other stages, suggesting that the TcTASV population could undergo developmental regulation. However, we cannot completely rule out the possible expression in other parasite stages, because we did not analyze the expression of the TcTASV-B nor TcTASV-C subfamilies and used only one peptide to obtain anti-TcTASV-A antibodies. Related to this, after following a proteomic approach Atwood et al. were able to identify a peptide in trypomastigote and amastigote extracts that is completely conserved (100% identity) in the TcTASV-A subfamily. The expression of TcTASV-A in amastigotes, though, probably occurs at very low levels since we were unable to detect TcTASV-A proteins in this parasite stage. Moreover, only one spectrum was detected by Atwood et al. in amastigotes (vs. 5 in trypomastigotes) [28]. Based on computational analyses, we predicted a signal peptide in the amino terminus and a potential site for the addition of a GPI anchor at the carboxy terminus of TcTASVs. However, at this moment, we cannot rule out the possibility that some members of TcTASV have a membrane-associated expression and others a cytosolic or secreted form. In summary, in the present work we have identified and partially characterized a new surface protein family in T. cruzi wich we named TcTASV. All TcTASV members have a conserved 3′ untranslated region (the TcT-Eelem, also identified for the first time here), conserved amino- and carboxy- termini, and could be grouped into three subfamilies according to the relative molecular mass of the predicted proteins. The presence of a high number of Ser and Thr susceptible to glycosylation as well as a signal peptide and a consensus sequence for the addition of a GPI anchor were predicted. The expression of the TcTASV-A subfamily in trypomastigotes was demonstrated. One other interesting characteristic of the TcTASV family is the lack of orthologues in other trypanosomatids. Finally, we would like to emphasize that TcTASV is a new gene family in T. cruzi, which so far had remained unnoticed (unannotated or missing from the assembled genome). We have worked closely with other groups to make sure that this is solved in future releases of T. cruzi genome databases. However, given the still draft nature of the T. cruzi genome, the possibility exists that this can happen for other genes. Moreover, by means of a genetic vaccination approach, one of the members of TcTASV (formerly TcYASP) has been found as part of a protective pool of antigens [3], which suggests that they are possible good vaccine candidates. | Chagas' disease, caused by the kinetoplastid protozoan parasite Trypanosoma cruzi, is endemic in Latin America. At present there are neither vaccines for prevention nor totally effective drugs for the treatment of the disease. T. cruzi has a complex life cycle alternating between a reduviid insect (the vector) and a mammalian host, where different parasite stages are found. Differentially expressed genes are the hallmark of the specialized biology of each life cycle stage. The aim of this work was to identify genes expressed in the trypomastigote stage (a blood-circulating stage that invades new cells and spreads the infection in different organs of the mammalian host) that could be used to develop new vaccines or diagnostics. An initial screening of trypomastigote transcripts was performed by sequencing of an epimastigote-subtracted trypomastigote cDNA library. Besides identifying a large proportion of differentially expressed mRNAs, we discovered a novel protein family, which we denominated TcTASV. | Abstract
Introduction
Methods
Results
Discussion | genetics and genomics/gene discovery
genetics and genomics/gene expression
infectious diseases/neglected tropical diseases
microbiology/parasitology
infectious diseases/protozoal infections
genetics and genomics/bioinformatics | 2010 | TcTASV: A Novel Protein Family in Trypanosoma cruzi Identified from a Subtractive Trypomastigote cDNA Library | 11,733 | 252 |
The interaction of Mycobacterium tuberculosis (Mtb) with host cell death signaling pathways is characterized by an initial anti-apoptotic phase followed by a pro-necrotic phase to allow for host cell exit of the bacteria. The bacterial modulators regulating necrosis induction are poorly understood. Here we describe the identification of a transcriptional repressor, Rv3167c responsible for regulating the escape of Mtb from the phagosome. Increased cytosolic localization of MtbΔRv3167c was accompanied by elevated levels of mitochondrial reactive oxygen species and reduced activation of the protein kinase Akt, and these events were critical for the induction of host cell necrosis and macroautophagy. The increase in necrosis led to an increase in bacterial virulence as reflected in higher bacterial burden and reduced survival of mice infected with MtbΔRv3167c. The regulon of Rv3167c thus contains the bacterial mediators involved in escape from the phagosome and host cell necrosis induction, both of which are crucial steps in the intracellular lifecycle and virulence of Mtb.
Apoptosis is a major programmed cell death pathway but now it is well established that necrosis can also be induced via defined signal transduction pathways [1,2]. The importance of apoptosis in host defense against pathogens is well described [3,4]. In contrast, the function of programmed necrosis in host resistance or susceptibility to pathogens is still an open question in many cases and may depend upon the context of the infection and the pathogen [5]. For instance, the RIPK1/3 necrosis pathway acts as a back-up mechanism of death induction in cells infected with viruses that are able to inhibit host cell apoptosis [6]. Consequently, programmed necrosis is associated with increased host resistance against viral pathogens in the case of vaccinia virus, adenovirus and MCMV [5,6]. Nevertheless, for the influenza A virus, programmed necrosis leads to increased pathology and host susceptibility [7]. Limited results are available for interaction of bacterial pathogens with host cell necrosis pathways but similar to viral pathogens the role of programmed necrosis may vary depending upon the pathogen. Enteropathogenic Escherichia coli can inhibit RIPK3-dependent necrosis via the glycosyl transferase NleB and this activity is important for bacterial virulence [8,9]. In contrast, IRF-3-dependent necrosis induction by Listeria monocytogenes promotes pathogen dissemination and virulence [10]. The interaction of wild-type Mycobacterium tuberculosis (Mtb) with its host cell in regard to cell death signaling is complex [11–13]. According to one model, virulent strains of Mtb are capable of inhibiting host cell apoptosis during the early phase of the infection to allow for intracellular replication but the bacteria induce necrosis in order to exit the host cell at a later stage [14]. The discovery of Mtb genes that inhibit host cell apoptosis such as nuoG [15], pknE [16], secA2 [17], Rv3654c [18], and ndk [19] supports this model. Furthermore, the Mtb nuoG mutant is attenuated in the mouse model of tuberculosis, thus illustrating the importance of host cell apoptosis inhibition for Mtb virulence [15]. Consistently, mice with reduced host cell apoptosis induction upon Mtb infection are more susceptible [20]. The mechanisms leading to increased host resistance include an increase in efferocytosis of apoptotic host cells leading to killing of the bacteria [21,22]. In addition, there are various lines of evidence that increased host cell apoptosis will lead to a more rapid and increased cytolytic T-cell response [17,23,24]. In contrast to apoptosis, host cell necrosis induction is associated with increased host susceptibility and virulence of Mtb as well as Mycobacterium marinum (Mm) in mice and in zebrafish [20,25]. Several studies demonstrated the central role of host cell eicosanoids lipoxin A4 (LXA4) and prostaglandin E2 (PGE2) in the regulation of host cell apoptosis versus necrosis induction and their importance for bacterial virulence and host resistance [24,26,27]. The enzyme Leukotriene A4 hydrolase (LTA4H) regulates synthesis of the eicosanoids LXA4 and leukotriene B4 (LTB4); excessive production of either lipid mediator leads to macrophage necrosis [28]. Polymorphisms in LTA4H in humans are associated with hypersusceptibility to mycobacterial infections [29]. Lysosomal destabilization and macrophage necrosis was found to occur following accumulation of about 20 or more intracellular bacteria [30,31]. The escape of Mtb from the phagosome to the cytosol precedes necrosis and exit from the host cell [32–34]. The Mtb type VII secretion systems, ESX-1 and ESX-5, are implicated in host cell necrosis induction. The deletion of the Mtb ESX-1 secretion system leads to a reduced induction of host cell necrosis and dissemination of the mutant mycobacteria [35–37], this could be due the inability of mutant strains to escape from the phagosome [33,34,38]. The Mtb ESX-5 system is involved in mediating cell necrosis after the bacteria have escaped the phagosome [39]. The PE25/PP41 complex secreted via ESX-5 may be one of the effectors of ESX-5-mediated host cell necrosis as addition of the purified protein complex induced necrosis of macrophages [40]. Host cell necrosis induction by Mtb is important for cell exit and dissemination but the molecular mechanisms involved are still poorly understood. Here we describe the discovery of a tetracycline repressor family protein, Rv3167c, which negatively regulates the capacity of the bacteria to induce host cell necrosis. Infection of macrophage with the Rv3167c deletion strain (MtbΔRv3167c) led to a rapid increase in host cell necrosis via a novel host cell signaling pathway that involves the reduced activation of the protein kinase Akt leading to an increase in mitochondrial reactive oxygen species (mROS). Interestingly, we discovered that MtbΔRv3167c escape the phagosome in higher numbers than wild-type Mtb, which most likely triggers the host cell necrosis signaling. Finally, aerosol infection of mice demonstrated the increased virulence of MtbΔRv3167c. In conclusion, we find that Rv3167c regulates the escape of Mtb from the phagosome, which marks the beginning of the host cell exit program of the Mtb intracellular life cycle.
We previously performed a gain-of-function genetic screen and identified a genomic region in Mtb H37Rv containing anti-apoptotic genes (S1A Fig) [15]. A series of deletion mutants spanning several genes within this region was generated and tested for loss of apoptosis inhibition. THP1 cells were infected with wild-type Mtb (Mtb) and the deletion mutants and stained for genomic DNA fragmentation using TUNEL assay. Two deletion mutants, one being the single gene nuoG mutant [15], and the other a five gene deletion mutant designated 7/10, induced higher levels of cell death compared to the Mtb control (S1B Fig). Screening of genes within the 7/10 region revealed that deletion of Rv3167c had the maximal effect on loss of cell death inhibition. Infection with the deletion mutant MtbΔRv3167c (MtbΔ) resulted in almost a 3-fold increase in TUNEL-positive THP1 cells compared to infection with the control Mtb strain (S1C Fig). Both southern blotting and RT-PCR confirmed deletion of Rv3167c (S2A–S2C Fig). Increased cell death induction by MtbΔRv3167c was also observed in primary human monocyte derived macrophages (hMDMs) by hypodiploid staining which measures loss of genomic DNA content following cell death (Fig 1B). Cell death induction by the complement strain MtbΔRv3167c-C (MtbΔC) was comparable to Mtb (Fig 1A and 1B), thus confirming that Rv3167c is required for Mtb-mediated host cell death inhibition. Replication of MtbΔ is similar to Mtb; both, in infected THP1 cells and in growth media (S2D and S2E Fig). Rv3167c is most likely a member of the tetracycline-like family of regulators (TFR) since 89% of the Rv3167c amino acid sequence can be modeled with 99. 9% confidence to the highest scoring template, the TFR SCO0332 of Streptomyces coelicolor, using Phyre2 software. Although TUNEL staining has been historically used for detection of apoptotic DNA fragmentation, recent studies have shown that necrotic cells can also be TUNEL positive [41–43]. A characteristic feature of apoptotic cells is preservation of cell membrane integrity [3]. To determine whether cell death induced by MtbΔRv3167c is accompanied by cell membrane damage, we tested for the presence of adenylate kinase, normally located within healthy cells, in the supernatants of THP1 cells using the Toxilight assay. At 24 and 48h, a 3-fold higher level of adenylate kinase activity was detected in supernatant from MtbΔRv3167c-infected cells compared to uninfected controls (Fig 1C). Mtb-infected cells also undergo necrosis albeit at lower levels compared to MtbΔRv3167c-infected cells. Mtb has been previously shown to induce necrosis in a dose and time dependent manner and our data supports this observation [44]. It is important to note that the Toxilight assay cannot differentiate between primary necrosis or secondary necrosis of apoptotic cells and consequently further analysis into the nature of the induced cell death was required. Execution of apoptotic cell death requires the cleavage and activation of the effector caspases-3, -6 and -7 [2]. We infected wild type (WT) and Casp3-/- bone marrow derived macrophages (BMDMs) and performed TUNEL staining to confirm that MtbΔRv3167c does not induce apoptotic cell death. No differences in TUNEL-positive cells were observed between MtbΔRv3167c-infected WT and Casp3-/- BMDMs (Fig 1D and 1E). To ensure that the lack of death inhibition in Casp3-/- BMDMs is not due to redundancy of caspase-3 with other effector caspases, the pan-caspase inhibitor zVAD-FMK was added to MtbΔRv3167c-infected cells. Inclusion of zVAD-FMK did not inhibit MtbΔRv3167c-induced cell death in both WT and Casp3-/- BMDMs (Fig 1E) although it did inhibit apoptosis induced by camptothecin (S3A Fig). We also did not observe cleavage of the DNA repair enzyme PARP, another feature of apoptosis, in Mtb or MtbΔRv3167c-infected THP1 cells (Fig 1F). Furthermore, the zVAD-FMK inhibitor was added to infected Ripk3-/- cells and had no effect on MtbΔRv3167c-induced cell death (S3D Fig). These results show that Rv3167c is required for inhibition of Mtb-induced necrotic host cell death. Next, we investigated the involvement of programmed necrosis pathways in cell death mediated by MtbΔRv3167c. In conditions where caspase-8 expression and activation are inhibited, the serine threonine protein kinases RIPK1 and RIPK3 induce necrosis downstream of TNF-receptor ligation via increased reactive oxygen species (ROS) generation, mitochondrial fission and formation of plasma membrane pores [45–48]. RIPK1 and RIPK3 have also been implicated in TNF-mediated necrosis in Mm-infected zebrafish [49]. We investigated the involvement of RIPK1 and RIPK3 in MtbΔRv3167c-induced cell death by using Ripk3-/- BMDM’s and the RIPK1 inhibitor necrostatin1 (Nec1). Similar levels of PI-positive cells were observed in MtbΔRv3167c-infected Ripk3-/- BMDMs and Nec1 treated cells compared to WT BMDMs and solvent control-treated cells respectively (Figs 2A and S3B). Nec1 efficacy was confirmed by its ability to inhibit LPS and zVAD FMK induced RIPKI dependent cell death (S3C Fig) [50]. Necrosis induction following TNF treatment has been reported to change to apoptosis in the absence of RIPK1 and consequently, the absence of an effect on cell death induction by MtbΔRv3167c could be due to an increase in apoptosis in cells deficient in RIPK1/3 signaling [1]. Addition of zVAD-FMK to Ripk3-/- cells did not affect MtbΔRv3167c-induced cell death thereby ruling out a switch between apoptosis and necrosis in MtbΔRv3167c-infected cells (S3D Fig). Infection of Tnfr1-/- BMDMs established that MtbΔRv3167c-induced necrosis was independent of TNF signaling (S4A Fig). The DNA repair enzyme PARP1 has been implicated in necrosis induction via ATP depletion and nuclear translocation of mitochondrial apoptosis inducing factor in response to DNA alkylating agents and infection with BCG and enterovirus71 [51–53]. Necrosis induction by MtbΔRv3167c is independent of PARP1 since similar levels of necrosis were observed in infected Parp1-/- BMDMs and WT control cells (Fig 2B). The pro-inflammatory caspases, caspase-1 and caspase-11 have been shown to be involved in necrosis induction in response to several bacterial pathogens [54,55]. The role of these caspases in MtbΔRv3167c-induced necrosis was excluded by PI staining of Casp1/11-/- BMDMs (Fig 2C). NLRP3-dependent but caspase-1-independent necrosis has been reported to occur in response to infection with Mtb and Shigella flexneri [56,57]. Using immortalized NLRP3-deficient BMDMs we ruled out involvement of NLRP3 in MtbΔRv3167c-induced necrosis (S4C Fig). Silencing of the inflammasome component ASC did not inhibit MtbΔRv3167c-induced necrosis as measured by the toxilight assay, rather necrosis was increased in MtbΔRv3167c-infected THP1shASC cells compared to control cells (S4D Fig). Involvement of IFNβ signaling (S4E and S4F Fig) and TLR signaling (S5A–S5C Fig) was also ruled out in necrosis induction by MtbΔRv3167c. These data indicate that MtbΔRv3167c does not engage the pathways of programmed necrosis currently described in the literature to induce host cell death. Lysosomal membrane permeabilization (LMP) and the subsequent release of lysosomal contents into the cell cytosol leads to cell death [58,59]. Moderate lysosomal permeabilization leads to apoptosis while more severe damage precedes necrosis [60]. Lysosomal permeabilization and cathepsin release into the cytosol has been previously observed in cells infected with Mtb at high MOI [61]. To investigate whether LMP contributes to MtbΔRv3167c-induced cell death, we used the dye acridine orange (AO) that accumulates within lysosomes. A two-fold increase in the number of cells with loss of AO staining was observed as early as 8h post infection in MtbΔRv3167c-infected THP1 cells compared to Mtb-infected controls (Fig 2D). After 20h of infection the difference was even more pronounced with only about 8% of Mtb-infected cells showing low AO-staining compared to about 25% in mutant infected cells (Fig 2D). This indicates that LMP precedes necrosis induction by MtbΔRv3167c and is not merely a consequence of the disintegration of the cell triggered via a different mechanism. Autophagy is a catabolic process that allows for cell survival via recycling of cellular contents and contributes to pathogen elimination [62]. However, autophagy induction can also lead to cell death [63]. Therefore, we investigated whether MtbΔRv3167c could induce autophagy in macrophages. First, we analyzed recruitment of LC3 into aggregates, an indicator of autophagy, by confocal microscopy [64]. THP1 cells expressing GFP-tagged LC3 (THP1 LC3GFP) were infected with AF647-NHS stained bacteria and at 8h, the percentage of cells showing aggregation of LC3 was estimated. A two-fold increase in autophagosome formation was observed in MtbΔRv3167c-infected cells compared to Mtb-infected control cells (Fig 3A). Previous studies have shown that Mtb induces xenophagy resulting in co-localization of bacteria with autophagosomes and bacterial killing [65,66] However, we observed minimal colocalization of both Mtb and MtbΔRv3167c (<1%) with autophagosomes (Fig 3A). This was confirmed by examination of infected THP1 cells by transmission electron microscopy (TEM) (Fig 3B). Next, we measured conversion of cytosolic LC3I to autophagosomal membrane bound LC3II, another hallmark of autophagy [64]. Uninfected and infected THP1 LC3GFP cells were washed with saponin-containing buffer leading to removal of cytosolic LC3I-GFP. Retention of autophagosomal membrane-bound LC3II-GFP was examined by flow cytometry [67]. A two-fold increase in autophagy induction was observed in MtbΔRv3167c-infected cells compared to those infected with Mtb and MtbΔRv3167c-C (Fig 3C). Increased conversion of both GFP tagged and endogenous LC3I to LC3II in MtbΔRv3167c-infected cells was also seen by immunoblotting (Fig 3D). Autophagy induction by MtbΔRv3167c was confirmed using 3-methyladenine (3-MA), a classical autophagy inhibitor [64]. Inclusion of 3-MA inhibited LC3II formation by MtbΔRv3167c in THP1 LC3GFP cells (Fig 3E). Increased accumulation of LC3II can be attributed either to an increase in autophagosome formation or to a decrease in LC3II degradation due to inhibition of autophagosome-lysosome fusion and maturation [64]. Addition of the vacuolar H+ ATPase inhibitor bafilomycin A1 (BafA1) that inhibits autophagosomal degradation to MtbΔRv3167c-infected THP1 LC3GFP cells led to a further increase in LC3II levels (S6A Fig). Autophagosome maturation leads to the degradation of LC3GFP to yield free GFP [64]. GFP was detected only in MtbΔRv3167c-infected cells by immunoblotting (S6B Fig). These data indicate that MtbΔRv3167c-induced autophagy but did not inhibit the maturation of the autophagosome. Finally to determine whether necrotic death of MtbΔRv3167c-infected cells was a consequence of autophagy induction, we measured adenylate kinase release from Atg5fl/fl LysM Cre+ (Atg5-/-) and Atg5fl/fl LysM Cre- (Atg5+/+) BMDMs. We observed no differences in necrosis induction by MtbΔRv3167c in autophagy-deficient Atg5-/- cells compared to the Atg5+/+ controls (Fig 3F). Additionally, the inclusion of 3-MA did not result in inhibition of MtbΔRv3167c-induced cell death in THP1 cells (S6C Fig). Therefore, while MtbΔRv3167c-infected cells undergo macroautophagy, this does not contribute to their death via necrosis. The concept that Mtb resides within phagosomal compartments at all times has been challenged by recent studies demonstrating bacillary escape to the cytosol both ex vivo and in vivo [32–34,38]. Necrosis induction by Mtb and Mm was shown to closely follow escape to the cytosol [33,68]. We examined cytosolic escape by MtbΔRv3167c using a fluorescence resonance energy transfer (FRET) based assay [33,34,69]. Uninfected and infected THP1 cells differentiated for three days with PMA were loaded with CCF4-AM. Intact CCF4-AM emits green fluorescence (535nm) due to FRET between the fluorescent moieties. Cleavage of CCF4-AM by β-lactamase expressed by cytosolic bacteria leads to FRET loss and a shift in the emission wavelength to 450nm that was measured by flow cytometry. Cells were co-stained with Live/Dead Fixable Red stain to restrict analysis to live cells only. While minor increases in fluorescence emission at 450nm were observed in Mtb-infected cells compared to uninfected cells at 48h, the largest shift in the CCF4 emission spectrum was seen in MtbΔRv3167c-infected cells (Fig 4A and 4B). A three-fold increase was observed in MFI450nm of cells infected with MtbΔRv3167c compared to Mtb-infected controls. Increased cytosolic escape of MtbΔRv3167c was reversed following complementation (Fig 4A–4C). The pro-necrotic phenotype of MtbΔRv3167c was preserved in these macrophages (Fig 4D). Bacterial β-lactamase activity was not affected by either deletion of Rv3167c or gene complementation (S7 Fig). To confirm the increased cytosolic escape by MtbΔRv3167c, we examined infected THP1 cells by TEM and quantified cytosolic bacteria in a double-blinded fashion by examining for absence of phagosomal membranes in healthy cells (Fig 4E, above). Increased presence of MtbΔRv3167c was observed in the cytosol at 8h compared to controls although statistical significance was not achieved. At 24h, 60% of MtbΔRv3167c were found to be cytosolic compared to 20% of Mtb corroborating the increased cytosolic escape by MtbΔRv3167c observed with the CCF4-AM assay (Fig 4E, below). A reduction of cytosolic escape was observed in cells infected with the complemented MtbΔRv3167c-C strain (Fig 4E, below). These data suggest that Rv3167c negatively regulates Mtb escape from the phagosome to the cytosol, an event that has been shown to be followed by induction of host cell necrosis [33,34]. Next we investigated the molecular mechanisms underlying autophagy induction by MtbΔRv3167c. The mitogen activated protein kinases (MAPKs) JNK and p38 have been implicated in autophagic responses of cells infected with Mtb following exposure to cytokines and vitamin D3 [70,71]. Mtb Eis has been shown to inhibit autophagy induction by suppressing JNK activation [72]. Hence we examined MAPK activation in response to MtbΔRv3167c infection by immunoblotting for phosphorylated forms in whole cell lysates prepared from infected THP1 LC3GFP cells at the indicated times. JNK activation was not observed at 0h, however increased JNK phosphorylation was detected in MtbΔRv3167c-infected cells compared to those infected with Mtb and MtbΔRv3167c-C at 18h (Fig 5A). In contrast to JNK, increased p38MAPK activation was observed in MtbΔRv3167c-infected cells at 0h. However by 18h, p38MAPK phosphorylation in MtbΔRv3167c-infected cells was similar to control cells infected with Mtb and MtbΔRv3167c-C (Fig 5A). Consistent results were observed in human monocyte-derived macrophages (hMDMs) as well; however, elevated JNK activation could be detected earlier at 0h in MtbΔRv3167c-infected cells (Fig 5B). We then determined whether JNK and p38MAPK contributed to autophagy induction by MtbΔRv3167c. THP1 LC3GFP cells were pre-treated and infected with JNK (SP600125) or p38MAPK (SB203580) inhibitors prior to infection with MtbΔRv3167c; the percentage of autophagic cells was measured by flow cytometry. Inclusion of the JNK inhibitor led to a partial, dose-dependent decrease in autophagy induction by MtbΔRv3167c while the p38MAPK inhibitor exerted no effects (Fig 5C). Neither of the inhibitors reversed the pro-necrotic phenotype of MtbΔRv3167c, instead a modest increase in PI-positive cells was observed in both cases (Fig 5D and 5E). The serine threonine protein kinase Akt functions as a critical negative regulator of autophagy at the initiation stage by activating mTOR and at the nucleation step by phosphorylating Beclin1 [73,74]. Inhibition of Akt activation has been implicated both in macroautophagy induction in response to nutritional stresses as well as selective autophagy-induction in response to pathogens such as Toxoplasma gondii and Salmonella typhimurium [73,75,76]. To determine role of Akt in autophagy-induction by MtbΔRv3167c, we examined Akt phosphorylation by immunoblotting. A complete loss of Akt activation was observed in MtbΔRv3167c-infected cells compared to the controls (Fig 5F). Consistently, the Akt activator, sc-79, inhibited autophagy induction by MtbΔRv3167c in a dose-dependent manner (Fig 5G) [77]. Additionally, Akt inhibition exerts effects on MtbΔRv3167c-mediated necrosis as well, since sc-79 significantly reduced MtbΔRv3167c-induced necrotic cell death (Fig 5H). Mtb-mediated suppression of reactive oxygen species (ROS) generated by the host phagocytic NADPH oxidase complex (NOX2) has been shown to inhibit host cell apoptosis [78]. Conversely, necrosis-induction by Mm has been shown to require mitochondrial ROS generation [49]. To determine whether necrosis-induction by MtbΔRv3167c involves ROS, we first measured ROS levels in cells infected by MtbΔRv3167c. Uninfected and infected BMDMs were stained with the either 2’7’-dichlorofluorescein diacetate (DCFDA) or MitoSOX Red for measurement of cytosolic and mitochondrial ROS respectively. At 0h, similar levels of ROS were observed in all infected cells compared to the uninfected controls (Fig 6A and 6B). However by 24h, approximately three-fold higher levels of both cytosolic and mitochondrial ROS were detected in MtbΔRv3167c-infected cells compared to those infected with Mtb and MtbΔRv3167c-C (Fig 6A and 6B). Next we examined whether increased ROS levels contribute to necrosis induction by MtbΔRv3167c using the flavoprotein inhibitor diphenylene iodonium (DPI) and the ROS scavengers glutathione and N-acetyl cysteine (NAC). Inclusion of these inhibitors and scavengers reversed necrosis induction by MtbΔRv3167c to levels observed in uninfected cells (S8A and S8B Fig). Thus, elevated ROS levels in MtbΔRv3167c-infected cells contribute to their necrotic cell death. Furthermore, addition of DPI to MtbΔRv3167c-infected THP1 LC3GFP cells completely abrogated autophagy induction compared to control cells (S8C Fig). As ROS in eukaryotic cells may be derived from the NOX2 complex or mitochondria, we sought to determine which of these sources is implicated in necrosis-induction by MtbΔRv3167c. Similar levels of necrosis induction by MtbΔRv3167c were detected in WT and Nox2-/- BMDMs by PI staining (Fig 6C). However, a complete inhibition of MtbΔRv3167c-mediated cell death was observed in mCAT BMDMs obtained from transgenic mice overexpressing mitochondrial targeted human catalase (Fig 6D). Increased mitochondrial ROS generation was also accompanied by a time dependent loss of mitochondrial membrane potential as measured by DIOC6 staining of MtbΔRv3167c-infected cells (S8D Fig). Increased mROS generation in MtbΔRv3167c-infected cells was found to be attributable to reduced Akt activation as inclusion of the Akt activator sc-79 inhibited mROS generation (Fig 6E). Taken together, our data reveal Akt and mitochondrial ROS to be critical regulators of MtbΔRv3167c-mediated necrosis and autophagy. We assessed the contribution of Rv3167c to Mtb virulence in vivo by performing a survival study of C57Bl/6 mice infected with approximately 100 CFU of Mtb, MtbΔRv3167c and MtbΔRv3167c-C via the aerosol route. Increased mortality was observed in MtbΔRv3167c-infected mice (median survival time—33 weeks) compared to those infected with Mtb or MtbΔRv3167c-C (median survival times– 59 and 60 weeks respectively) (Fig 7A). Decreased survival following MtbΔRv3167c infection was also observed in immunodeficient SCID mice (S9A Fig). Lung bacterial burden on day one after infection was similar for all three strains indicating comparable initial inoculum of infection in both C57Bl/6 and SCID mice (Figs 7B and S9B). Relative to control mice, the lung bacillary burden was 10-fold higher in MtbΔRv3167c-infected animals at14 and 28 days, and this difference was magnified by day 56 following aerosol infection (Fig 7B). Increased bacterial burdens also were observed in the liver and spleen of MtbΔRv3167c-infected mice relative to control mice (Fig 7C and 7D). Higher levels of pro-inflammatory cytokines (TNF, IL1α and IL6) (Fig 7E) and chemokines (CCL3, CCL5 and MMP9) (Fig 7F) were detected in the lung tissues of mice infected with MtbΔRv3167c. Comparison of lung histopathology revealed a two-fold increase in cellular infiltration in MtbΔRv3167c-infected animals (Fig 7G). Consistent with the findings in the mouse model of chronic TB infection, increased bacterial burdens were observed in the lungs of guinea pigs infected with MtbΔRv3167c relative to controls at 28 days following aerosol infection with similar bacterial loads (S9C and S9D Fig). MtbΔRv3167c was also found to induce cell death in ex vivo infection of guinea pig alveolar macrophages by TUNEL staining (S9E Fig). Collectively, these results show that Rv3167c negatively regulates Mtb virulence.
The intracellular location of bacteria has important consequences for their recognition by the host and the generation of innate and adaptive immune responses. Mtb was thought to restrict itself to a modified host cell phagosomal compartment after infection [79,80]. However, electron microscopy studies performed on infected macrophages and dendritic cells provided evidence that Mtb and other mycobacterial species are present in the cytosol and that phagosomal escape is dependent upon the ESX-1 secretion system [32,38]. This was confirmed by a FRET-based method dependent on β-lactamase production by Mtb in ex vivo-infected cells as well as in pulmonary phagocytic cells obtained from infected mice [33,34]. We report in the current study that the mycobacterial gene Rv3167c negatively regulates the escape of Mtb from the phagosome to the cytosol (Fig 4). Our study is the first to suggest that Mtb can exert temporal control on phagosomal escape as MtbΔRv3167c was found in the cytosol as early as 24h after infection while Mtb has been reported to access the cytosol much later in the infection process (4–5 days) [33]. We hypothesize that Rv3167c represses cytosolic escape at early stages when the bacterial load is low, favoring Mtb replication and establishment of infection. Genes involved in cytosolic escape could be induced once bacterial numbers reach about 20 per cell which seems to be an important threshold to switch on the cell escape program of Mtb [30]. Gene deletions resulting in increased cytosolic translocation from vacuolar compartments have been reported for other bacteria; for example, the sdhA (a Dot/Icm-secreted effector) mutant of Legionella pneumophila and the sifA (an SPI2-secreted effector) mutant of Salmonella typhimurium [81,82]. Deletion of the secreted phospholipase A abrogated the early escape of the L. pneumophila sdhA mutant [81]. The Mtb genome encodes four phospholipases (plc A-D), which could potentially contribute to the early escape of MtbΔRv3167c. The mechanisms involved in Mtb escape from the phagosome and eventual induction of host cell necrosis to exit the cell are difficult to study because of the slow kinetic of the process. Consequently, the early induction of cytosolic escape and necrosis by MtbΔRv3167c make it a useful model to study the host cell escape mechanisms of Mtb. The escape of Mtb from the phagosome to the cytosol is closely followed by necrotic death of the host cells [32,33,83]. Consistently, we measured higher levels of cell death by necrosis in MtbΔRv3167c-infected cells (Figs 1A, 1B and S9E). Mtb may induce necrosis via the manipulation of host cell lipid mediators by favoring the production of the eicosanoid LXA4 [27]. In addition, the activation of the NLRP3-inflammasome was also shown to induce necrosis after Mtb infection [56]. We found that NLRP3 is dispensable for MtbΔRv3167c-mediated necrosis (S4C Fig). The regulation of cell death is complex and recently there have been major discoveries of signal transduction pathways for the regulation of programmed necrosis [1]. Using a combination of inhibitors and macrophages from knock-out mice, we screened for host factors required for MtbΔRv3167c-induced necrosis and ruled out the involvement of known programmed necrosis pathways (Figs 2, S4 and S5). Redundancy between the various necrosis-signaling modules may explain this result. For instance, both RIPK1-RIPK3 and caspase-1 activation are required for S. tymphimurium-induced necrotic cell death and blocking either one of the signaling pathways led only to a marginal inhibition of the death phenotype [43]. However, we found elevated mitochondrial ROS (mROS) to be required for the pro-necrotic phenotype of MtbΔRv3167c (Fig 6). Elevated mROS production could lead to increases in cytosolic ROS levels that may via lipid oxidation cause lysosomal permeabilization and cell death [1,84]. Lysosomal permeabilization has been implicated previously in necrosis induction by high bacillary loads of Mtb [61]. It is possible that MtbΔRv3167c may exploit a similar mechanism to kill host cells as increased lysosomal permeabilization was observed in cells infected with the mutant bacteria (Fig 2D). The Mm-mediated induction of necrosis after zebrafish infection also requires an increase in mROS [49]. Nevertheless, in contrast to our data (Figs 2A, S3B and S4A), Mm signals through the TNF/RIPK3 pathway to induce an increase of mROS and necrosis. The differences may reflect the variations in molecular pathogenesis pathways engaged by the human pathogen Mtb and the fish pathogen Mm. Our data indicates involvement of diminished Akt activation in mitochondrial ROS generation in MtbΔRv3167c–infected cells (Fig 6E). The augmented phagosomal escape observed in MtbΔRv3167c-infected cells may allow for previously sequestered Mtb proteins to target mitochondria and trigger an increase in mROS generation. The mycobacterial type VII secretion system, ESX-5, is involved in the secretion of proteins containing Pro-Pro-Glu (PPE), Pro-Glu (PE) and polymorphic GC-rich sequences (PGRS) and has been implicated in cell lysis after Mtb escapes from the phagosome [39,85]. Interestingly, the ESX-5 substrates PE25 and PPE41 form a complex and induce necrosis [39,40]. Furthermore, the Mtb PE_PGRS33 protein, when ectopically expressed in a eukaryotic cell, localizes to the mitochondria and induces apoptotic and necrotic cell death [86]. The importance of these proteins in the context of infection with live bacteria has not been demonstrated yet. Another compelling target could be the secreted Mtb toxin CpnT which induces RIPK1-independent necrosis in Mtb-infected macrophages [87] via its NAD+ glycohydrolase activity [88]. It is possible that both mitochondrial localization of mycobacterial proteins and inhibition of Akt activation via Mtb proteins may both contribute to elevated mitochondrial ROS levels seen observed in MtbΔRv3167c-infected cells. Autophagic clearance is a defense mechanism employed by host cells following detection of cytosolic pathogens. While macroautophagy (hereafter referred to as autophagy) is defined as the engulfment of cytosol by the autophagosome, selective autophagy describes the process in which autophagosome formation is directed towards a specific organelle, protein complex or microorganism by cargo receptor proteins (p62, NDP52, NBR1, Optineurin) [89–91]. Selective autophagy augments killing of intracellular mycobacteria, since reduced bacterial viability was seen following autophagy induction with IFNγ treatment of BCG-infected macrophages [92]. The relevance of selective autophagy for host defense against Mtb was demonstrated by the dramatically increased susceptibility of Atg5-/- mice when compared to wild-type mice [66,93]. It was thus unexpected that MtbΔRv3167c was hypervirulent in the mouse model (Fig 7A) even though increased autophagy induction was observed in MtbΔRv3167c-infected cells compared to Mtb-infected controls (Fig 3C and 3D). We found that while MtbΔRv3167c induces autophagy, there was no increase in selective autophagy, as very few mycobacteria (both wild-type and mutant) co-localized with autophagosomes (Fig 3A and 3B). Previous studies have shown that Mtb has evolved mechanisms to avoid recruitment into the autophagosome [66,72,94–96]. Our results support this observation and show that this immune evasion strategy remains intact in MtbΔRv3167c. The increased autophagy seen in MtbΔRv3167c-infected cells is most likely a host stress response to an increased number of cytosolic bacteria [66]. Autophagy may dampen inflammation by negative regulation of the inflammasome and via the degradation of danger associated molecular patterns during host cell necrosis [97,98]. Atg5-/- mice have higher basal level of inflammation when compared to wild-type mice [93] and Mtb-infected Atg5-/- mice had increased levels of pulmonary pro-inflammatory cytokines and exhibited increased lung tissue damage [66,99]. It is thus possible that in the absence of autophagy induction, the increased inflammatory response seen in MtbΔRv3167c-infected mice (Fig 7E and 7F) would have been even stronger. Unlike apoptosis, which benefits the host by reducing mycobacterial viability, Mtb-induced necrosis is beneficial to the pathogen allowing it to exit from infected cells and to disseminate [14,100]. Consistent with this concept was our finding that the necrosis-inducing MtbΔRv3167c strain was hypervirulent in mice and guinea pig. The hypervirulence of various clinical Mtb strains and Mtb deletion mutants has been reported previously [101]. For example, the Beijing strain HN878 was found to be more virulent than another member of the same family in immunocompetent mice [102]. Deletion of the mce1 operon, two component response regulators KdpDE, tcrXY and the serine threonine protein kinases pknH, pknE and pknI rendered Mtb hypervirulent in mouse studies [103–107]. The presence of multiple anti-virulence genes in Mtb gives rise to the question: why would Mtb encode genes that suppress its virulence? While virulence may be defined as the ability of a pathogen to cause disease, an important aspect of virulence is successful transmission between hosts [108]. As Mtb has probably co-evolved with humans for more than 50,000 years, moderation of its virulence would have prevented elimination of the early existent small host populations thus maximizing transmission opportunities and improving persistence of the pathogen [109,110].
THP1 monocytes were obtained from ATCC (TIB 202). GFP tagged LC3 expressing THP1 monocytes (THP1 LC3GFP) were provided by Dr. John Kehrl (NIH). THP1shASC and THP1shcontrol cells were obtained from Dr. Jenny Ting (University of North Carolina). C57Bl6, Nox2-/-, Casp3-/- and mCAT transgenic mice were obtained from Jackson Laboratories. Ripk3-/- mice were obtained from Genentech. Casp1/11-/- mice were provided by Dr. Denise Monack (Stanford School of Medicine). Parp1-/- mice were obtained from Dr. Ted Dawson (Johns Hopkins University). Tnfr1-/-, Il1r1-/-, Irf3-/- and Ifnβ-/- mice were provided by Dr. Alan Sher (NIH). Immortalized wildtype, Nlrp3-/ and Trif-/-MyD88-/- BMDMs were provided by Dr. Igor Brodsky (University of Pennsylvania). Atg5fl/fl LysM Cre+ (Atg5-/-) and Atg5fl/fl LysM Cre- (Atg5+/+) mice were obtained from Dr. Herbert Virgin IV (Washington University School of Medicine). zVAD FMK, Necrostatin 1, MAPK inhibitors (SP600125, SB203580), Akt activator (sc-79) and DPI were purchased from Calbiochem. BafilomycinA1, glutathione and N-acetyl cysteine were sourced from Sigma. 3-MA was purchased from Tocris Biosciences. Rv3167c was deleted in M. tuberculosis H37Rv using a specialized phage transduction strategy described previously [111]. Gene deletion was confirmed by RT-PCR as well as by southern blotting. The probes used were labeled with biotin using BrightStar Psoralen-Biotin Kit. Genomic DNA was digested with EcoRI. The DNA fragments were separated by agarose gel electrophoresis, transferred to charged nylon membrane, and denatured with 0. 4N NaOH. The probe was denatured at 90°C for 10 min in the presence of 10mM EDTA and hybridized to the membrane at 55°C for 16h in hybridization buffer (AlkPhos Direct hybridization buffer with 0. 5M NaCl). The membrane was washed and the probe was detected using a BrightStar BioDetect Nonisotopic Detection Kit. For generating the complement strain, Rv3167c gene sequence including 60bp upstream was cloned into the episomal plasmid pMV261, electroporated into the Rv3167c mutant strain and plated on 7H10 plates with 40μg/ml kanamycin. Bacterial strains were grown in 7H9 medium supplemented with 10% ADC, 0. 5% glycerol and 0. 05% Tween 80. Hygromycin (50μg/ml) and kanamycin (40μg/ml) were added to the mutant and complement cultures respectively. For infection, cultures with an OD600 between 0. 6–0. 8 (corresponding to the late log phase of growth) were pelleted and resuspended in 0. 05% PBS-Tween 80 prior to addition to cells. To measure in vitro bacterial growth, bacteria were added to 7H9 medium to obtain a starting OD600 of 0. 01. OD600 measurements were made at 24h intervals until 7 days. Ex vivo bacterial growth was determined by infecting THP1 macrophages and lysing them at the indicated timepoints with 0. 1% Triton X 100. Appropriate dilutions were plated on 7H11 medium in triplicate. Inoculated plates were incubated at 37°C and colonies were counted approximately 2 weeks after plating. THP1 monocytes were maintained in RPMI 1640 supplemented with 10% heat inactivated FCS. Cells were differentiated with 20ng/ml PMA for 20–24 hours, washed and infected in growth medium containing 5% human serum. Bacteria were added to cells at MOI 3 for 4 hours at 37°C, extracellular bacteria were removed by PBS washes and chase medium containing 100μg/ml gentamicin was added. BMDMs were prepared from cells obtained from femurs and tibia of various mouse strains and cultured in DMEM supplemented with 10% heat inactivated FCS, 25% L929 supernatant and 1% Penicillin-Streptomycin. Growth medium was replaced with DMEM containing 10% non-heat inactivated FCS for 4h and cells were infected at MOI 10 in same medium in the manner described above. Chase media contained 10% L929 supernatant in order to avoid cell death induction due to cytokine withdrawal. Immortalized BMDMs were maintained in DMEM containing 10% heat inactivated FCS and infected in media similar to that used for primary BMDMs. Human monocyte derived macrophages (hMDMs) were prepared from elutriated monocyte fractions obtained from NIH blood bank. Monocyte fractions were seeded in serum free RPMI for one hour. Non-adherent cells were removed and adherent cells were differentiated in RPMI medium containing 5% off-the-clot AB human serum (Gemini) and 10ng/ml human MCSF (Peprotech) for 7 days. Inhibitors (with the exception of 3-MA) were added to cells one hour prior to infection and included in chase medium. 3-MA was added only to chase medium. For all experiments, 0h time point refers to end of infection period when cells have been exposed to bacteria for 4 hours. Cells were stained with 1μg/ml propidium iodide (PI) (Sigma-Aldrich) for 10 minutes at room temperature and analyzed by flowcytometry. For TUNEL stain, cells were fixed in 4% paraformaldehyde overnight, stained as per manufacturer’s instructions (Roche) and examined by either flow cytometry or fluorescence microscopy. Hypodiploid stain was performed using PI/RNase staining buffer (BD Pharmingen) following overnight fixation in 70% ethanol as per manufacturer’s instructions. For all flow cytometry analyses, at least 10,000 cells were acquired (BD Accuri C6). Toxilight assay to measure adenylate kinase release from cells was performed as per manufacturers instructions. Autophagy induction in THP1 LC3GFP expressing cells was analyzed as described previously [67]. Briefly, cells were permeabilized with 0. 05% saponin for 5 minutes, washed and resuspended in PBS containing 5% FCS. Permeabilization resulted in loss of cytosolic LC3I while LC3II bound to autophagosome membranes were retained, which was measured by flow cytometry (50,000 cells acquired, BD Accuri C6). For immunofluorescence analysis, bacteria were stained with 0. 4mg/ml AF647-NHS ester (Molecular Probes) in 0. 1M sodium bicarbonate solution for 30 minutes at 37°C and used for infecting cells on slides. At specified time points, cells were fixed with 4% paraformaldehyde overnight, stained with Hoechst 33342 and analyzed by confocal microscopy (Zeiss LSM710). Cell lysates were obtained by lysing cells with RIPA buffer containing protease (Complete, Mini EDTA free, Roche) and phosphatase inhibitor cocktails (PhosStop, Roche) followed by centrifugation at 12,000g for 5 minutes. Pierce BCA protein assay kit (Thermo Scientific) was used to measure protein concentrations to ensure equivalent loading. Antibodies against phosphorylated and total Akt and MAPKs, PARP, tubulin and GFP were purchased from Cell Signaling and used at 1: 1000 dilution. Anti LC3 antibody was purchased from Epitomics and used at 1: 2500 dilution. Densitometric analysis was performed using ImageJ software. To detect mycobacterial escape from the phagosome, the CCF4 FRET assay was performed as described previously [34]. Briefly, cells were stained with 8μM of CCF4 (Invitrogen) in EM buffer (120mM NaCl, 7mM KCl, 1. 8mM CaCl2,0. 8mM MgCl2 5mM glucose, 25mM Hepes, pH7. 3) containing 2. 5μM of probenecid (Sigma-Aldrich) for 1. 5 hours at room temperature. Live populations were distinguished from dead ones by addition of Live/Dead Fixable Red stain (Invitrogen) for 30 minutes at room temperature. After staining cells were fixed with 4% PFA overnight and analyzed by flow cytometry (BD FACS CantoII). 40,000 cells were acquired and post acquisition analysis done using FlowJo software (Treestar, OR). For estimation of bacterial β-lactamase activity, bacteria were resuspended in PBS containing 50μg/ml porcine esterase liver extract and 100nM CCF4-AM and incubated at 37°C for 12h. Fluoresence measurements were made using Biotek Synergy 4 microplate reader. For measurement of ROS levels in BMDMs, cells were infected as described previously [78]. At indicated time points after infection, cells were harvested and stained with 10μM CM-H2DCFDA (Molecular Probes) or 1. 25μM MitoSOX Red (Molecular Probes) for 30 minutes at 37°C in HBSS. Cells were analyzed by flow cytometry (at least 10,000 cells acquired, BD Accuri C6) after HBSS wash. Cells were stained with 40 nmol of DIOC6 stain (Molecular Probes) at 37°C for 15 minutes, washed and analyzed by flow cytometry (10,000 cells acquired, BD Accuri C6). THP1 cells were fixed in 2% gluteraldehyde and 2% paraformaldehyde in 0. 1M sodium cacodylate buffer pH7. 4 for 1 hour. They were carefully pelleted and re-suspended in 2% paraformaldehyde for several hours, followed by rinsing in 0. 1M sodium cacodylate buffer and pelleted in 2% agar in the same buffer. The samples were post fixed in 1% osmium tetroxide in 0. 1M sodium cacodylate buffer, rinsed in distilled water and, en bloc stained in 2% aqueous uranyl acetate for a further hour. They were then rinsed and dehydrated in an ethanol series (50% to 100%) followed by resin infiltration Embed 812 (Electron Microscopy Sciences) and baked overnight at 60°C. Hardened blocks were cut using a Leica UltraCut UC7. 60nm sections were collected on formvar/carbon coated nickel grids and contrast stained using 2% uranyl acetate and lead citrate. Grids were all viewed in a FEI Tencai Biotwin TEM at 80Kv. Images were taken using Morada CCD and iTEM (Olympus) software. Embedding and sectioning was performed at the electron microscopy core facility at the Yale School of Medicine. C57Bl/6 mice were infected with 100 CFU of each of the various bacterial strains grown to late log phase via the aerosol route using a Glas-Col full body inhalation exposure system. At the indicated time points, 3 mice per group were sacrificed and bacterial load was determined by homogenizing the organs in PBS and plating serial dilutions on 7H11 plates. Lung homogenate supernatants were used for cytokine analysis using the Luminex MAGPIX platform (R&D Bioscience). Superior lobes of the lungs were fixed in 10% buffered formalin for histopathology. Paraffin embedding, sectioning and hematoxylin and eosin (H and E) staining were performed by AML Labs, Baltimore. Total lung area and areas of inflamed regions in H and E stained lung sections were quantified using ImageJ. Female outbred Hartley guinea pigs (250-300g) were purchased from Charles River Labs (Wilmington, MA). Animals were infected with each of the three Mtb strains via aerosol using a Madison chamber aerosol generation device (University of Wisconsin, Madison, WI) calibrated to deliver ~3 log10 CFU in the lungs. Four animals from each group were sacrificed on day 1 and day 28 post-infection. The lungs were homogenized, as previously described, and the lung homogenates were plated on 7H11 Middlebrook agar and incubated at 37°C for 4 weeks before final CFU counts were determined [112]. Alveolar macrophages were harvested by bronchoalveolar lavage (BAL) as described previously [113]. Briefly, cold PBS with 3% FCS was instilled into the lungs following insertion into the trachea of an 18-gauge cannula fixed to a 20-ml syringe. The cells were pelleted by centrifugation at 380g for 10 min, washed twice with RPMI-1640 supplemented with 10% FCS, and 10μM 2-mercaptoethanol (RPMI complete medium), and resuspended in 1 ml RPMI complete medium. Following transport from Johns Hopkins to University of Maryland on ice, viable cells were enumerated by the trypan blue exclusion method and seeded in RPMI complete medium overnight. Adherent cells were infected in RPMI medium containing 5% FCS at specified MOI for 4 hours at 37°C, extracellular bacteria were removed by PBS washes and chase medium containing 100μg/ml gentamicin was added. Statistical analysis was performed using GraphPad Prism version 6. 0 software. Data is presented as mean ± S. E. M. of three independent experiments and one-way ANOVA with Tukey post-test was used unless mentioned otherwise in the figure legends. p-value significance is as follows—*- ≤0. 05, ** - ≤0. 01, *** - ≤0. 001, **** - 0. 0001. All animals were handled in accordance with the NIH guidelines for housing and care of laboratory animals and the studies were approved by the Institutional Animal Care and Use Committees at the University of Maryland, College Park (protocol no—R-12-55) and Johns Hopkins University School of Medicine (protocol no—GP12M88). | Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis, is a highly successful human pathogen. Following entry into host phagocytic cells, Mtb resides within a modified phagosomal compartment and inhibits apoptotic host cell death. Recent studies have demonstrated that Mtb eventually translocates from the phagosomal compartment to the cytosol. This event is followed by the induction of necrotic host cell death allowing the bacteria to exit the host cell and infect naive cell populations. Our study adds to this relatively unexplored aspect of Mtb pathogenesis by revealing that the transcriptional repressor Rv3167c of Mtb negatively regulates phagosomal escape and host cell necrosis. We furthermore demonstrate that the increased necrosis induction by the Mtb mutant strain deficient in Rv3167c required elevated reactive oxygen species levels within host cell mitochondria and reduced activation of the protein kinase Akt. In addition, the increased virulence of the Mtb mutant strain observed after aerosol infection of mice strengthens the link between the ability of the bacteria to induce host cell necrosis and virulence. The Mtb genes negatively regulated by Rv3167c are thus potential virulence factors that can be targeted for drug and vaccine development. | Abstract
Introduction
Results
Discussion
Materials and Methods | flow cytometry
cell death
medicine and health sciences
autophagic cell death
pathology and laboratory medicine
viral transmission and infection
cell processes
microbiology
signs and symptoms
bacteria
research and analysis methods
specimen preparation and treatment
staining
spectrum analysis techniques
necrotic cell death
actinobacteria
spectrophotometry
necrosis
cytophotometry
cell staining
diagnostic medicine
host cells
cell biology
mycobacterium tuberculosis
virology
apoptosis
biology and life sciences
organisms | 2016 | Identification of a Transcription Factor That Regulates Host Cell Exit and Virulence of Mycobacterium tuberculosis | 14,507 | 321 |
The agr quorum-sensing system of Staphylococcus aureus modulates the expression of virulence factors in response to autoinducing peptides (AIPs). Recent studies have suggested a role for the agr system in S. aureus biofilm development, as agr mutants exhibit a high propensity to form biofilms, and cells dispersing from a biofilm have been observed displaying an active agr system. Here, we report that repression of agr is necessary to form a biofilm and that reactivation of agr in established biofilms through AIP addition or glucose depletion triggers detachment. Inhibitory AIP molecules did not induce detachment and an agr mutant was non-responsive, indicating a dependence on a functional, active agr system for dispersal. Biofilm detachment occurred in multiple S. aureus strains possessing divergent agr systems, suggesting it is a general S. aureus phenomenon. Importantly, detachment also restored sensitivity of the dispersed cells to the antibiotic rifampicin. Proteinase K inhibited biofilm formation and dispersed established biofilms, suggesting agr-mediated detachment occurred in an ica-independent manner. Consistent with a protease-mediated mechanism, increased levels of serine proteases were detected in detaching biofilm effluents, and the serine protease inhibitor PMSF reduced the degree of agr-mediated detachment. Through genetic analysis, a double mutant in the agr-regulated Aur metalloprotease and the SplABCDEF serine proteases displayed minimal extracellular protease activity, improved biofilm formation, and a strongly attenuated detachment phenotype. These findings indicate that induction of the agr system in established S. aureus biofilms detaches cells and demonstrate that the dispersal mechanism requires extracellular protease activity.
Most bacteria have an inherent ability to form surface-attached communities of cells called biofilms [1]. The opportunistic pathogen Staphylococcus aureus can form biofilms on many host tissues and implanted medical devices often causing chronic infections [2]–[5]. The challenge presented by biofilm infections is the remarkable resistance to both host immune responses and available chemotherapies [6], [7], and estimates suggest that as many as 80% of chronic bacterial infections are biofilm associated [8]. In response to certain environmental cues, bacteria living in biofilms are capable of using active mechanisms to leave biofilms and return to the planktonic (free-living) state in which sensitivity to antimicrobials is regained [9]–[11]. Therefore an improved understanding of the molecular mechanism of biofilm detachment could facilitate the discovery of innovative treatment options. Studies on the opportunistic pathogen Pseudomonas aeruginosa indicate that cell-to-cell communication (often termed “quorum-sensing”) is required to make a robust biofilm under some growth conditions [12]. Surprisingly, the opposite is true in S. aureus, as the presence of an active quorum-sensing impedes attachment and development of a biofilm [13], [14]. The S. aureus quorum-sensing system is encoded by the accessory gene regulator (agr) locus and the communication molecule that it produces and senses is called an autoinducing peptide (AIP), which is an eight-residue peptide with the last five residues constrained in a cyclic thiolactone ring [15]. During growth, AIP is synthesized and secreted through a poorly understood mechanism that requires multiple peptidases [16], [17]. Once AIP reaches a critical concentration, it binds to a surface histidine kinase receptor, initiating a regulatory cascade that controls expression of a myriad of virulence factors, such as proteases, hemolysins, and toxins [18]. A recent study by Yarwood et. al. [19] raised the possibility that the agr quorum-sensing system is involved in biofilm detachment. This study demonstrated that bacteria dispersing from biofilms displayed high levels of agr activity, while cells in a biofilm had predominantly repressed agr systems. These findings correlate well with prior data indicating that agr deficient S. aureus strains form more robust biofilms compared to wild type strains [13], [14]. In the study presented here, we demonstrate that activation of the agr system in established biofilms is necessary for detachment. This activation could be accomplished with exogenous AIP addition or by changing nutrient availability to the biofilm. We also demonstrate that agr-mediated detachment requires the activity of extracellular proteases. Our findings suggest that agr quorum-sensing is an important regulatory switch between planktonic and biofilm lifestyles and may contribute to S. aureus dispersal and colonization of new sites.
Mutations in the agr quorum-sensing system are known to improve biofilm development [13], [14]. Based on these studies, it seemed probable that there is a correlation between agr activity and biofilm formation. Regassa et al. reported that growth on rich media containing glucose represses the agr system through the nonmaintained generation of low pH [20]. Interestingly, in most published flow cell biofilm studies, one commonality is the use of growth media containing or supplemented with glucose [9], [19], [21]–[24]. In our own efforts to grow S. aureus flow cell biofilms, we found a strict dependence on glucose supplementation. For the experimental setup, a once-through, continuous culture system was employed as previously described [19], [25], and S. aureus SH1000 constitutively expressing red fluorescent protein (PsarA-RFP, plasmid pAH9) was used as the testing strain. Using 2% TSB as the growth media, SH1000 cells did not attach and develop a biofilm (Figure 1A), instead passing right through the flow cell to the effluent. However, in the presence of 0. 2% glucose (TSBg), cells attached and a formed a robust biofilm (10–20 microns thick) after two days of growth, which was visually evident and monitored with confocal laser scanning microscopy (CLSM, Figure 1B). As expected, glucose strongly inhibited expression from the P3 promoter using a GFP reporter (Figure 1E), suggesting that repression of RNAIII is essential for attachment and biofilm formation. In broth culture and biofilm effluents, we observed a glucose-dependent pH decrease to the 5. 5 range similar as previously reported [20], [26]. As a control, flow cell biofilms were prepared with an agr mutant strain (SH1001, Δagr: : TetM) containing plasmid pAH9 (Figure 1C & D), and this strain developed a biofilm even in the absence of media supplementations (Figure 1C). As anticipated, the P3 promoter did not activate in the agr mutant (Figure 1E). Overall, these observations indicate that environmental conditions favoring low agr activity are essential for attachment and biofilm formation. To investigate the role of the agr system in established biofilms, we developed strategies to modulate level of agr activity within a biofilm. Initially, media supplementation experiments were performed using purified AIP signal in order to place the agr system under external control. We recently developed a new method for AIP biosynthesis [27], enabling the production of sufficient signal levels for flow cell experiments. Through exogenous AIP addition, we could test wild-type strains and avoid any potential complications of constructed agr deletion mutants. For this approach, established flow cell biofilms were prepared using S. aureus SH1000 constitutively expressing RFP with plasmid pAH9. The flow cell media was supplemented with glucose to attenuate agr expression [20], allowing cell attachment and biofilm development. After two days, either 1 mL of buffer (100 mM phosphate [pH 7], 50 mM NaCl, 1 mM TCEP; Figure 2A) or 1 mL of 20 µM AIP-I in buffer (Figure 2B and Video S1) was diluted 1000-fold (50 nM final concentration) into the growth media. Using our synthesized AIP-I in dose-response curves [27], we estimate the amount of AIP-I in supernatants of TSB broth cultures (OD600 1. 0–1. 3) reaches approximately 400 nM (data not shown), indicating the 50 nM level used for the biofilm experiments is within a relevant concentration range. Examination with CLSM showed that the AIP-I treated biofilm sloughed off the flow cell over a period of 1–2 days (Figure 2B and Video S1), suggesting that AIP-I activated a detachment mechanism. To confirm that AIP-I caused detachment, we counted viable S. aureus cells in the effluent media (Figure 2C). The concentration of bacteria in the effluent increased markedly 24–36 hours after AIP-I addition. In contrast, the number of bacteria in the biofilm effluent without AIP-I addition remained relatively constant. Computational analysis of the detachment phenotype indicated that 91. 3±4. 3% of the biomass dispersed within 48 hrs of AIP-I addition. Among S. aureus strains, there are four types of agr quorum-sensing systems. Each of these agr systems, referred to as agr-I through agr-IV, recognizes a unique AIP structure (AIP-I through AIP-IV). Through an intriguing mechanism of chemical communication, these varying quorum-sensing systems can be subdivided into three cross-inhibitory groups: agr-I/IV, agr-II, and agr-III. The activating signals of each group cross-inhibits the alternative signal receptors with surprising potency, a phenomenon termed “bacterial interference” [15]. Since AIP-I and AIP-IV differ by only one amino acid and function interchangeably [28], they are grouped together in the classification scheme, although this assignment has been controversial [29], [30]. To determine the generality of the detachment mechanism, we examined the effect of AIP addition using S. aureus strains representing different agr groups. The strains tested were (i) FRI1169, agr-I, toxic shock syndrome isolate [31]; (ii) SA502a (ATCC27217), nasal isolate and prototype agr-II strain [15], [32]; and (iii) ATCC25923, clinical agr-III isolate [9]. When the correct AIP signal was added to 2-day old biofilms of each strain (FRI1169, AIP-1; SA502a, AIP-II; ATCC25923, AIP-III), signal addition resulted in robust detachment of each biofilm over a period of 48 hours (Figure 3). These findings indicate biofilm detachment is a general S. aureus phenomenon that occurs in laboratory strains and clinical isolates, and functions across diverse agr systems. If AIP was promoting biofilm detachment via the agr system, we predicted that agr expression would be induced prior to detachment and an agr deficient mutant would not detach in response to AIP. To determine whether the agr system is activated prior to biofilm detachment, a dual fluorescent-labeled SH1000 strain was constructed with a constitutive RFP (PsarA-RFP, pAH9) and an agr responsive GFP reporter (PagrP3-GFP, pDB59). After two days of biofilm growth, we added AIP-I to the biofilm flow medium and this resulted in strong induction of the GFP reporter (Figure 4A), indicating activation of the agr system. As shown, the GFP reporter was clearly activated before dispersal of the biofilm cells. By the fourth day, all cells with detectable GFP expression detached from the biofilm. These observations provide convincing evidence that AIP activates the agr system prior to biofilm dispersal. To further investigate the role of the agr system, we utilized a mutant strain with a complete deletion of the agr locus (SH1001). Unlike the wild type strain (Figure 4A), the agr mutant biofilm harboring the same dual reporters did not respond to AIP-I treatment, as evidenced by a lack of GFP induction, and the mutant biofilm did not disperse (Figure 4B). Similarly, addition of an inhibitory AIP (50 nM AIP-II) to the dual-labeled SH1000 biofilm failed to induce GFP expression, and again, the biofilm did not disperse (Figure 4C). Taken together, these data demonstrate that an active agr quorum-sensing system is necessary for AIP-mediated biofilm dispersal. We have demonstrated that low agr activity is important for biofilm formation and that activation of the agr system in established biofilms induces detachment. Considering changes to the physiochemical environment may occur in vivo, we investigated whether an alteration in nutrient availability could reproduce the detachment phenotype. Again, two day flow cell biofilms were prepared with the dual-labeled strain (AH596) in TSBg (Figure 5A). The glucose was removed and significant activation of the P3 promoter was apparent by monitoring GFP levels using CLSM (Figure 5A), supporting our previous result (Figure 1A). Once the agr system was activated, robust detachment from the flow cell was observed and monitored with CLSM (Figure 5A). An agr deletion mutant did not respond to glucose depletion (Figure 5B), indicating the detachment phenotype was dependent upon a functional agr system. These findings demonstrated that glucose depletion can disperse an S. aureus biofilm and again the detachment occurred through an agr-dependent mechanism. These experimental observations mirrored those with AIP addition and further support the apparent inverse correlation between agr activity and biofilm formation. Biofilm growth of S. aureus increases resistance to antimicrobials when compared to the planktonic growth mode [9], [19]. This biofilm mediated resistance hinders treatment of many chronic S. aureus biofilm related infections, including endocarditis, osteomyelitis, and indwelling medical device infections [3], [33]. Therefore, we asked whether AIP-dispersed bacteria regained sensitivity to a clinically relevant antibiotic, rifampicin. To test this, we collected detached cells from an AIP-treated biofilm effluent and compared resistance to intact biofilms exposed to different levels of rifampicin. Similar to previous antibiotic susceptibility results [19], even at the highest concentration tested (100 µg/ml), the level of rifampicin killing was <2 log units of the biofilm biomass (Figure 6). In contrast, the viability of detached cells displayed a different antibiotic response. At 10 µg/ml rifampicin, a 6 log decrease of viable cells was detected, and at 100 µg/ml, complete killing of the detached cells was observed (Figure 6). The AIP-detached cells were more resistant than broth culture to comparable levels of rifampicin, suggesting parts of the detached biofilm may remain in emboli that are known to possess elevated antibiotic resistance [9]. These observations demonstrated that S. aureus cells detached from a biofilm regain susceptibility to a clinical antibiotic. S. aureus possesses the icaRADBC locus that is required to synthesize and generate an exopolysaccharide, which is referred to as the polysaccharide intracellular adhesin or PIA (also called PNAG). S. aureus is known to form biofilms through both ica-dependent and ica-independent mechanisms [34], [35]. To gain insight on the biofilm detachment mechanism, we sought to distinguish whether our S. aureus biofilms were dependent on PIA. In strain SH1000, we constructed an Δica: : Tet deletion mutant (strain AH595) using generalized transduction and confirmed the mutation with PCR and sequencing. In microtiter biofilm assays, we were unable to identify a biofilm phenotype (Figure 7A and 7B). Similarly in flow cell biofilms, we did not observe a defect in the ability of strain AH595 to form a biofilm (Figure 7C). No difference was observed compared to flow cell biofilms of SH1000 grown in parallel (data not shown). While SH1000 is a derivative of 8325-4, and there are reports that the ica locus is required for 8325-4 derived strains to make a biofilm [36], the ica locus was not required for biofilm formation under our experimental conditions. Similar to our observations, an ica mutant of the clinical S. aureus isolate UAMS-1 displays no defect in microtiter and flow cell biofilm assays [22]. In contrast, when proteinase K was added to SH1000, biofilms were unable to develop in the microtiter plate format (data not shown), indicating the biofilms are forming through an ica-independent mechanism. These findings suggest that PIA is unlikely to have a role in biofilm detachment in the SH1000 strain background. Knowing the agr system is essential for biofilm detachment, what agr regulated products are responsible for the dispersal phenotype? In S. aureus strains that produce ica-independent biofilms, proteinase K eliminates adherence and biofilm formation [35], [37]–[39], perhaps through cleavage of surface structures. S. aureus is coated with cell wall attached proteins that mediate adherence to a variety of substrates [40], and some of these adhesins, such as biofilm associated protein (BAP) and SasG are important for biofilm formation [41], [42]. It is also known that some surface adhesins, such as protein A and fibronectin-binding protein, are cleaved by the native S. aureus secreted proteases [43], [44]. Considering the agr system regulates the secreted proteases [45], [46], we hypothesized that increased expression of extracellular proteases could be responsible for biofilm detachment. If S. aureus proteases have a role in detachment, proteinase K should be able to disperse an established biofilm. To test this proposal, proteinase K (2 µg/mL) was added to a SH1000 biofilm and resulted in rapid detachment over 12 hrs (Figure 8A). With this preliminary observation, we measured the levels of protease activity in effluents from biofilms with and without AIP-I addition using Azocoll (azo dye impregnated collagen) reagent. As shown in Figure 8B, we detected a baseline level of protease activity in biofilm effluents without AIP-I addition and referenced other measurements to this baseline. With the addition of activating AIP-I, the protease activity increased approximately five-fold compared to a biofilm with no AIP-I treatment. As anticipated, addition of inhibitory AIP-II reduced the level of proteolytic activity in the effluent. Similarly, an agr mutant biofilm supplemented with activating AIP-I displayed very low levels of extracellular proteases (Figure 8B). There are 10 known extracellular proteases produced by most S. aureus strains and expression of all these enzymes is controlled by the agr system [18], [45], [46]. These 10 proteases include the metalloprotease aureolysin (aur), two cysteine proteases (scpA and sspB), and seven serine proteases (sspA (V8) and splABCDEF) [47]. To elucidate what class (es) of proteases are prevalent in AIP-treated biofilms, the effluent from a detaching biofilm was assayed for protease activity in the presence of protease inhibitors or activating agents. The addition of EGTA, an inhibitor of the metalloprotease aureolysin [16], had a negligible effect on overall protease activity (Figure 8C). The addition of PMSF, a potent serine protease inhibitor, however reduced overall protease activity to almost undetectable levels. Lastly, the addition of DTT, a reducing agent used to activate thiol proteases [48], did not significantly change protease activity in the effluents. These results suggest that serine proteases are the dominant, detectable secreted protease in AIP-treated biofilms. With our observation that serine proteases are abundant in detaching biofilms, we examined the effect of a serine protease inhibitor on AIP-mediated detachment. The addition of 10 µM PMSF in combination with AIP-I to an S. aureus biofilm significantly reduced the level of detachment compared with AIP-I alone (Figure 9A vs. B). However, 48. 8% (±5. 2) of the biomass still detached indicating that serine proteases are necessary but not sufficient for complete detachment. To further examine the mechanism, knock-out mutations were constructed in the genes encoding the V8 (SspA) and SplABCDEF serine proteases. Surprisingly, sspA: : Tet and Δspl: : Erm single mutants, and an sspA: : Tet Δspl: : Erm double mutant, all increased extracellular protease levels (Figure 10A) and eliminated biofilm formation under microtiter plate conditions (Figure 10B & 10C). To block other extracellular proteases, a mutation was constructed in the gene encoding aureolysin (Aur). Aur is a metalloprotease that is required to initiate a zymogen activation cascade [49], [50], starting with the V8 protease [51], which in turn activates the SspB cysteine protease [52]. The activation mechanism of the ScpA cysteine protease remains unresolved [49]. In contrast to the serine protease mutations, introduction of the Δaur deletion into S. aureus reduced extracellular protease levels (Figure 10A) and did not affect biofilm formation (Figure 10B). Interestingly, under conditions of high agr activity, the Δaur deletion displayed improved biofilm formation versus wild-type (Figure 10C). In biofilm detachment tests, the Δaur mutant reduced AIP-mediated detachment, but 54. 6% (±8. 1) of the biomass still detached (Figure 9C). Considering the Spl proteases are not zymogens [53], we examined the combined effects of the Aur cascade and the Spl proteases by constructing an Δaur Δspl: : Erm double mutant. The Δaur Δspl strain possessed very low levels of extracellular protease activity (Figure 10A) and had a minor enhancement in biofilm formation (Figure 10B). Similar to the Δaur mutant, the Δaur Δspl double mutant also displayed improved biofilm formation versus wild-type under conditions of high agr activity (Figure 10C). After AIP-I addition, only 21. 7% (±6. 6) of the Δaur Δspl mutant biomass detached in comparison to 91. 3 (±4. 3) of the wild-type strain (Figure 9D). These experiments indicate that the extracellular proteases have anti-biofilm properties and they demonstrate that agr-mediated biofilm detachment requires the activity of these proteases.
The majority of studies on biofilm detachment have focused on factors capable of initiating the process, such as nutrient availability [54], [55], nitric oxide exposure [56], oxygen tension [57], iron salts [58], chelators [59], and signaling molecules [60]–[63]. Alternatively, detachment studies have addressed effector gene products that contribute to the dissolution of the biofilm, including surfactants [10], [13], [64], [65], hydrolases [66], [67], proteases [37]–[39], and DNase [68]. Here were do both, by demonstrating that the increasing AIP levels or lowering available glucose can function as a S. aureus biofilm detachment signal by activating the agr quorum-sensing system, resulting in increased levels of extracellular proteases needed for the detachment mechanism. Importantly, agr-mediated detachment also restores antibiotic sensitivity to the released bacteria, suggesting the mechanism could be a target for treating biofilm infections. These results are in accord with previous studies showing that agr mutants have a propensity to form biofilms [13], [14] and that cells actively expressing agr leave biofilms at a high frequency [19]. Our findings also explain why S. aureus biofilm formation requires glucose supplementation to growth media. Unless the agr system is repressed or inactivated, or the enzymes mediating detachment are inhibited, S. aureus will remain in a planktonic state. The presence of glucose is known to represses RNAIII through a nonmaintained pH decrease to ∼5. 5 [20], resulting from the secretion of acidic metabolites. The RNAIII repression is not due to glucose itself, but results from the mild acid conditions [26] and can be mimicked with other carbon sources, such as galactose [20], that also lower the media pH. In microtiter biofilm experiments, we found these alternative pH-lowering carbon sources could substitute for glucose in facilitating biofilm formation (data not shown). The molecular mechanism through which low pH inhibits RNAIII expression remains to be determined. In the host, many niches colonized by S. aureus are maintained in lower pH ranges, such as the skin and vaginal tract [26], colonization sites that repress agr function could promote biofilm formation. Based on our findings, we propose that the S. aureus agr quorum-sensing system controls the switch between planktonic and biofilm lifestyles. When the agr system is repressed, cells have a propensity to attach to surfaces and form biofilms as detachment factors are produced at low levels. In our detachment model, dispersal of cells from an established biofilm requires reactivation of the agr system and occurs through a protease-mediated, ica-independent mechanism. Yarwood et al. demonstrated through time-course, flow cell studies that reactivation of agr does occur in a biofilm [19], presumably through autonomous AIP production that reaches local concentrations high enough to activate agr. Under these fixed conditions, the agr system may function primarily as a mechanism to detach clumps (also called emboli) that seed new colonization sites. In the experiments presented herein, we have employed growth conditions that tip the balance of the agr system, allowing an investigation into full agr reactivation within an established biofilm. This delicate balance can be offset with an increase in local AIP concentration or through changing environmental conditions, both situations that induce agr and result in massive dispersion of the cells. Biofilms are dynamic and dispersal is always operating [11], but accelerated detachment has been observed in response to changing environmental conditions, such as oxygen levels [57], [69], nutrient depletion [54], changing nutrient composition [55], or increased concentration of quorum-sensing signals [61]. An S. aureus biofilm growing in vivo is likely to encounter a changing physiochemical environment, which could serve as a cue to induce accelerated detachment through an agr-mediated mechanism. S. aureus has been reported to form biofilms through an ica-dependent mechanism suggesting that PIA could have a role in detachment [34], [36]. We observed no defect in microtiter or flow cell biofilm formation using an ica mutant of SH1000 (Figure 7). Our findings support the growing evidence that PIA is not a major matrix component of S. aureus biofilms, as exogenous addition of dispersin B, an N-acetyl-glucosaminidase capable of degrading PIA, has little effect on established biofilms of SH1000 and other S. aureus strains [70]. In contrast, dispersin B does detach S. epidermidis biofilms indicating a more significant role for PIA in the S. epidermidis matrix structure [70]. Our experiments with proteinase K and the S. aureus proteases indicate that some proteinaceous material is important for SH1000 biofilm integrity, and this result supports a number of recent studies demonstrating that proteases can inhibit biofilm formation or detach established biofilms from many S. aureus strains [35], [37]–[39]. It is not clear whether agr-mediated detachment will function in S. aureus strains that produce an ica-dependent biofilm. In this study, we document a role for the Aur and Spl proteases in biofilm detachment. Global expression analysis has shown that activation of the agr quorum-sensing system results in up-regulation of extracellular proteases (Aur, SplABCDEF, ScpA, SspAB) and down-regulation of many surface proteins [45], [46]. However, the target of these agr controlled proteases is not clear. One potential target is the surface adhesins, and possible candidates include the surface proteins Atl, Bap, and SasG, all of which have reported roles in biofilm formation [41], [42], [71]–[73]. Atl is additionally known to require proteolytic processing for activation, and this processing is PMSF inhibited [74]. Other possibilities include microbial surface components recognizing adhesive matrix molecules (MSCRAMMs), which are important for adherence to the extracellular matrices of mammalian cells [40]. Also, the S. aureus secreted proteases are known to activate lipase (Sal-1 and Sal-2) precursors [75] and process other secreted enzymes, such as staphylococcal nuclease [76], [77]. In addition to proteases, there may be other agr regulated factors that contribute to biofilm detachment. Surfactant-like molecules, such as δ-toxin, are induced by the agr system and may exert dispersal effects on biofilms [13], [78]. There is growing evidence that extracellular DNA (eDNA) is an important S. aureus biofilm matrix component [24], [70], and expression of staphylococcal nuclease is reported to be under control of the agr system [18]. Thus, while agr induced proteases are required for the detachment phenotype, the agr controlled expression of an array of factors (proteases, nuclease, surfactants) may also contribute to the biofilm detachment mechanism. There is increasing interest in understanding how bacteria detach from biofilms and initiate colonization of new surfaces. The regulation of quorum-sensing systems may be one mechanism by which many bacteria control biofilm formation and dispersal. Quorum-sensing has been implicated in dispersal of biofilms formed by Yersinia pseudotuberculosis [79], Rhodobacter sphaeroides [80], Pseudomonas aureofaciens [81], Xanthomonas capmestris [62], and Serratia marceascens [61]. However, homoserine lactone signals play a divergent role in Pseudomonas aeuruginosa [12], Pseudomonas fluorescens [82], and Burkholderia cepacia [83], where the active versions of these quorum-sensing systems are necessary for biofilm formation and robustness under some growth conditions. In both cases, it appears quorum-sensing plays a significant role in biofilm development and determining the environmental stimuli that modulate quorum-sensing activity will provide insight on bacterial colonization, detachment, and dispersal to new sites.
The bacterial strains and plasmids used in this study are described in Table 1. S. aureus or Escherichia coli were grown in tryptic soy broth (TSB) or on tryptic soy agar (TSA) with the appropriate antibiotics for plasmid selection or maintenance (erythromycin 10 µg/ml; chloramphenicol 10 ug/ml; tetracycline 5 ug/ml) and incubated at 37°C. Plasmid DNA was prepared from E. coli and transformed by electroporation into S. aureus RN4220 as described [84]. Plasmids were moved from RN4220 into other S. aureus strains by transduction with bacteriophage α80 [85] or by purifying the plasmid DNA and transformed by electroporation into appropriate strains. To move sspA and splABCDEF mutations into appropriate genetic backgrounds, phage transduction with α80 was used as described [85]. To construct the Δaur mutation, the pKOR1-aur plasmid was used as described [16]. Fluorescence measurements with S. aureus strains containing pDB59 were performed as previously described [27]. The sarA P1 promoter region was PCR amplified from SH1000 genomic DNA with oligonucleotides (for 5′-GTTGTTAAGCTTCTGATATTTTTGACTAAACCAAATGC-3′, rev 5′-GTTGGATCCGATGCATCTTGCTCGATACATTTG-3′), digested with HindIII and BamHI, and cloned into the erythromycin shuttle plasmid pCE107 [19]. The mCherry (RFP) gene was PCR amplified from pRSET-mCherry [86] with oligonucleotides incorporating a 5′ ribosome binding site and KpnI site and a 3′ EcoRI site (for 5′-GTTGGTACCTAGGGAGGTTTTAAACATGGTGAGCAAGGGCGAGGAGG-3′, rev 5′-GTTGAATTCTTACTTGTACAGCTCGTCCATGCC-3′). The mCherry fragment was cut with KpnI and EcoRI and cloned downstream of the sarA promoter to generate a constitutive RFP expressing plasmid called pAH9. Milk agar plates for detection of protease activity consisted of 3 g/L Tryptic Soy broth, 20 g/L non-fat dry milk, and 15 g/L agar. To determine relative protease activities of strains, assays were performed as described previously using the Azocoll (Calbiochem) reagent [48]. For measuring protease levels in biofilm effluents, 100 mL of effluent was collected on ice (∼12 hours) after AIP addition to the biofilm medium. Cells were removed from the effluents through centrifugation and filtering, and ammonium sulfate was added to 60% over one hour at 4°C to concentrate proteins. The precipitated proteins were pelleted by centrifugation at 19,000 rpm for 30 min, and the pellet was washed and resuspended in 1 ml with 10 mM Tris pH 7. 5. For the protease assay, the reaction mixture was supplemented with either 1 mM EGTA, 200 µM PMSF, or 1 mM DTT to gauge relative levels of protease classes. Microtiter plate biofilms were performed as described [87] except that the plates were incubated at 37°C with shaking at 200 rpm for 12 hours. For flow cell experiments, AIPs were generated using the DnaB intein method, and the AIP concentrations were determined as previously described [27]. AIPs stocks (∼20 µM) were stored in 100 mM phosphate [pH 7], 50 mM NaCl, 1 mM tris (2-carboxyethyl) phosphine (TCEP) and were diluted into the biofilm flow medium to a final concentration of 50 nM. When required, 5 µg/ml of erythromycin and/or chloramphenicol were added to the flow cell media to maintain plasmids. The growth medium for flow cell biofilms consisted of 2% TSB plus 0. 2% glucose unless otherwise indicated. Flow cell biofilm experiments and confocal microscopy were performed as previously described [19]. Flow cells were inoculated with overnight cultures diluted 1: 100 in sterile water and laminar flow (170 µl/min) was initiated after one hour incubation. Confocal microscopy was performed using a Radiance 2100 system (Biorad) with a Nikon Eclipse E600 microscope. Confocal images were processed using Velocity software (Improvision, Lexington, Mass.). Biofilm biomass was quantified with the COMSTAT program [88] and percent biomass detached was calculated by subtracting biomass present at day 4 from day 2. To quantitate the number of bacteria detaching from a biofilm, 1 ml of flow cell effluent was collected on ice at indicated time points. The collected effluent was vortexed and sonicated in a water bath for 10 minutes to break up clumps, and serial dilutions were plated on TSA plates to determine colony forming units (CFUs). For the Proteinase K detachment experiments, the enzyme (Sigma-Aldrich) was suspended in water and added to the media reservoir at a final concentration of 2 µg/ml. S. aureus biofilms were grown for two days in a flow chamber lined with removable polycarbonate coupons (Flow Cell FC271, Biosurface Technologies, Bozeman MT). Biofilm effluents were collected on ice ∼24 hours after AIP-I addition. In parallel, coupons with biofilm growth were removed from flow cells not exposed to AIP-I. Both detached bacteria and the biofilms were exposed to the indicated levels of rifampicin for six hours. Subsequently, cells were vortexed, and the coupons were sonicated in a water bath to break up the biofilm or cell clumps. Serial dilutions were plated on TSA to determine surviving CFU' s. | A biofilm is a surface-attached community of cells bound together by an extracellular matrix. In a bacterial infection, biofilm-encased cells are protected from antibiotic therapy and host immune response, and these encased cells can develop into a chronic infection. Staphylococcus aureus is a prominent bacterial pathogen known to form biofilms on many medical implants and host tissues. In this report, we demonstrate that repression of the S. aureus quorum-sensing system is required to form a biofilm, and quorum-sensing reactivation in established biofilms disperses the cells. Genetic and molecular analysis demonstrates that quorum-sensing is activated before and required for the detachment mechanism. Detachment is protease-mediated, as established biofilms are sensitive to a non-specific protease and quorum-sensing activation increases the production of extracellular proteases. Using mutations in the protease genes, we show that these secreted enzymes are required for the detachment mechanism. These findings denote that S. aureus quorum-sensing can function as a dispersal mechanism to colonize new sites, and our results suggest this mechanism could be modulated to treat recalcitrant biofilms. | Abstract
Introduction
Results
Discussion
Materials and Methods | infectious diseases/bacterial infections
microbiology/microbial growth and development
microbiology/cellular microbiology and pathogenesis
microbiology/medical microbiology
infectious diseases/antimicrobials and drug resistance | 2008 | agr-Mediated Dispersal of Staphylococcus aureus Biofilms | 9,606 | 319 |
Although malaria has been the leading cause of fever for many years, with improved control regimes malaria transmission, morbidity and mortality have decreased. Recent studies have increasingly demonstrated the importance of non-malaria fevers, which have significantly improved our understanding of etiologies of febrile illnesses. A number of non-malaria febrile illnesses including Rift Valley Fever, dengue fever, Chikungunya virus infection, leptospirosis, tick-borne relapsing fever and Q-fever have been reported in Tanzania. This study aimed at assessing the awareness of communities and practices of health workers on non-malaria febrile illnesses. Twelve focus group discussions with members of communities and 14 in-depth interviews with health workers were conducted in Kilosa district, Tanzania. Transcripts were coded into different groups using MaxQDA software and analyzed through thematic content analysis. The study revealed that the awareness of the study participants on non-malaria febrile illnesses was low and many community members believed that most instances of fever are due to malaria. In addition, the majority had inappropriate beliefs about the possible causes of fever. In most cases, non-malaria febrile illnesses were considered following a negative Malaria Rapid Diagnostic Test (mRDT) result or persistent fevers after completion of anti-malaria dosage. Therefore, in the absence of mRDTs, there is over diagnosis of malaria and under diagnosis of non-malaria illnesses. Shortages of diagnostic facilities for febrile illnesses including mRDTs were repeatedly reported as a major barrier to proper diagnosis and treatment of febrile patients. Our results emphasize the need for creating community awareness on other causes of fever apart from malaria. Based on our study, appropriate treatment of febrile patients will require inputs geared towards strengthening of diagnostic facilities, drugs availability and optimal staffing of health facilities.
Febrile illnesses due to different etiological agents are the common causes of morbidity and mortality in developing countries [1]. Malaria has been the leading cause of fever in sub- Saharan Africa for many years [2]. For instance, in Tanzania, malaria was contributing to about 42% of hospital diagnoses and 32% of hospital deaths in the last decade [3]. Accordingly, presumptive treatment of all febrile illnesses in children under five years with anti-malarial drugs was adopted as policy in many countries of sub-Saharan Africa [4]. However, in recent years, there has been gain in malaria control strategies which has led to decreased malaria prevalence particularly in endemic countries [5]–[7]. The decrease in malaria burden has also been indicated by the 2012 World Malaria Report where there is a good achievement in worldwide reduction of malaria transmission, morbidity and mortality [8]. The decline in malaria transmission is mainly a result of increased coverage of different malaria control strategies that have been implemented for several years. This includes the use of long lasting insecticide treated bed nets, indoor residual spraying, intermittent presumptive treatment of malaria during pregnancy or intermittent presumptive treatment of malaria to infants and treatment with effective anti-malaria drugs such as Artemisinin-based Combination Therapies [5], [9]. The decrease in malaria transmission led World Health Organization (WHO) to change its policy in 2010 where anti-malarial treatment is initiated after parasitological confirmation [10]. However, the decline in trend of malaria transmission in many malaria-endemic countries corresponds to an increasing proportion of febrile patients who are diagnosed as not having malaria [11], [12]. Recent studies have increasingly demonstrated the importance of non-malaria fevers, which have significantly improved our understanding of etiologies of febrile illnesses [13], [14]. In this regard, a reasonable proportion of febrile illnesses are now ascribed to be non-malaria febrile illnesses [13] and episodes of such diseases are reported to increase [12]. In Tanzania, diseases such as respiratory tract infections, urinary tract infections, typhoid fever and rotavirus infection are among non-malaria febrile illnesses that have been commonly affecting people particularly children [15]–[18]. A study conducted in Dar es Salaam and Ifakara had shown that among 1005 children, 498 (50%) had acute respiratory infection, while 54 (5. 4%) had urinary tract infections and 33 (3. 3) had typhoid fever [18]. Diseases such as Rift Valley Fever (RVF), dengue fever, Chikungunya virus infection, leptospirosis, tick-borne relapsing fever, Q-fever, rotavirus infection and brucellosis have also been reported in Tanzania [13], [14], [19]–[24]. A recent study conducted in northern Tanzania has reported the occurrence of 55 (7. 9%) cases of Chikungunya virus infection, 40 (33. 9%) cases of leptospirosis, 24 (20. 3%) cases of Q-fever and 16 (13. 6%) cases of brucellosis among 870 admitted febrile patients [13]. Some non-malaria febrile illnesses may contribute to high morbidity and mortality in humans. For instance, rotavirus takes the lives of more than 8,100 Tanzanian children under five each year [25]. Furthermore, the most recent outbreak of RVF in 2006/2007 which occurred in 10 regions of Tanzania mainland [26] and in other countries such as Kenya and Somalia were associated with widespread morbidity and mortality in humans [27]. The diagnosis of non-malaria febrile illnesses poses a challenge since many of these illnesses may have similar symptoms with malaria and thus making their clinical diagnosis difficult [28]. Also, non-malaria febrile illnesses could have common overlapping manifestations and therefore, this absence of specific symptoms make it difficult to distinguish several non-malaria febrile conditions that often occur in the same area [29]. Clinical overlap between diseases may result in inappropriate antimicrobial therapy and therefore, laboratory tests for differential diagnosis of causative agent are essential. Following a long tradition of regarding malaria as the leading cause of fever, it is important for the community to understand the other causes of fever apart from malaria particularly during this period when the episodes of malaria related fevers are reported to decrease [8], [11], [30]. Understanding the awareness of the community on non-malaria febrile illnesses is critical and relevant particularly in management and control of such illnesses. Despite their importance, only few studies aiming at assessing the awareness of the communities regarding non-malaria febrile illnesses have been conducted in Tanzania [31], [32]. Therefore, this study intended to contribute in filling the information gap by assessing the knowledge and attitude of the communities regarding non-malaria febrile illnesses. In addition, the study explored treatment seeking behaviors for febrile illnesses among community members. Following the longstanding practice of treating most fevers as malaria, health workers may still treat febrile patients with anti-malarial drugs even if the patients had a negative test results. Studies from Tanzania and other countries like Zambia, Uganda and Burkina Faso have indicated that febrile patients were prescribed anti-malarial drugs following negative mRDT/microscopy result [33]–[36]. Therefore, there is a need to know the management of febrile patients following the decline in the incidence of malaria. The current study also assessed health workers' practices related to diagnosis and treatment of febrile patients.
The study was conducted in Kilosa district which is one of the six districts in Morogoro region, located in eastern Tanzania. The district borders with Tanga and Manyara regions to the north and Mvomero district and Mikumi National Park to the east. On the western border are Dodoma and Iringa regions whereas to the south it borders with Kilombero district. The district lies between latitudes 6° south and 8° south and longitudes 36°30′ east and 38° west. The area has semi humid climate with an average rainfall of 800 mm annually. The early rains start in November and end in January followed by heavy rainfall between March and May. The district experiences a long dry season from June to October and the average annual temperature is 24. 6°C. The district has an area of 14,245 square kilometers and has a population of 438,175 people [37]. It consists of a mixture of different ethnic groups predominantly Kaguru, Sagara and Vidunda. The main economic activities are crop production and livestock keeping. More than 77% of people are subsistence farmers and major crops cultivated include maize, cassava, rice, paddy and sorghum whereas the major cash crops are sisal, sugarcane, cotton and oilseeds. Kilosa was selected due to its possession of intensive human activities with livestock as well as its proximity to wildlife from the Mikumi National Park (figure 1), what was expected to be a good interface for zoonotic diseases such as RVF and Brucellosis [38]. Administratively, Kilosa district is divided into 9 divisions, 37 wards and 164 villages [39]. In terms of health care services, Kilosa district has 71 health facilities and among these, there are 3 hospitals, 7 health centers and 61 dispensaries [40]. However, the number of villages exceeds the number of health facilities and hence most health facilities serve more than one village. Kilosa district is an area with holoendemic malaria transmission with seasonal peaks following the long and short rainy seasons [41]. According to Tanzania HIV and Malaria Indicator Survey, in 2007–2008 malaria prevalence was estimated to be 15. 7% in Morogoro region [42] and decreased to 13% in the year 2011–2012 [43]. The common non-malaria febrile illnesses that have been reported in Kilosa district include acute respiratory diseases, UTIs and typhoid fever [24]. Data from a platform for health monitoring and evaluation in Tanzania (Sentinel Panel of Districts) have shown that in the year 2011, acute respiratory diseases and UTIs comprised of 20% and 2. 5% respectively of total recorded illnesses (77,862) in outpatient department in children aged less than 5 years [44]. This study was specifically conducted in 6 divisions, namely Kimamba, Kilosa town, Magole, Masanze, Rudewa and Ulaya. Within these divisions, 12 wards namely Dumila, Chanzuru, Magomeni, Kilosa, Msowero, Zombo, Ulaya, Kimamba, Mkwatani, Kasiki, Masanze and Rudewa were purposively selected based on (i) geographical representation within the district e. g. Zombo is in the south western part of the district, whereas Dumila ward is in north-eastern part (figure 1), (ii) the presence of government health facilities (iii) connectivity of the wards and ease of accessibility by road. We conducted a cross-sectional study in which qualitative data collection methods were used. Focus group discussions (FGDs) with members of the communities were conducted to assess their knowledge, attitude and perception of community members on non-malarial febrile illnesses. In-depth interviews (IDIs) with health workers were conducted in order to obtain their views about practices related to diagnosis and management of non-malarial febrile illnesses. Parents, guardians or caregivers aged between 18–59 years for children of less than 10 years were eligible to participate in FGDs. This group of participants was targeted because febrile illnesses have been shown to be common in children and contribute to high proportion of hospital admissions globally, with significant morbidity and mortality [13], [18], [45]. The participants were recruited from different hamlets within the study wards with the assistance of local government and villages leaders. In total 12 FGDs were conducted in urban, peri-urban and rural areas in the selected wards of which 5 FGDs were with men and 7 involved women. Each FGD comprised 6–8 people, but women and men were separately interviewed to give the participants freedom to talk during the discussions. Two FGDs were conducted per day and each FGD took about 60 to 90 minutes. In each of Dumila, Rudewa, Chanzuru and Ulaya wards 2 FGDs were separately conducted for men and women. In Masanze and Zombo wards 2 FGDs were conducted with women and the remaining 2 FGDs (1with men and 1with women) involved participants selected from Kilosa, Kasiki and Magomeni wards. For IDIs, only health workers who were on duty and attended patients (prescribers) in the health facilities during the study period were eligible to participate into the study. Health workers from 12 health facilities located in Dumila, Chanzuru, Ulaya, Zombo, Kilosa, Magomeni, Msowero, Kimamba, and Mkwatani wards were interviewed. Two health workers were interviewed from each health facility and only one health worker was interviewed at a time. In-depth interviews with health workers on average lasted for one hour and 2 IDIs were conducted per day. Focus group discussions and IDIs were conducted by a skilled and experienced social scientist who was assisted by an observer and note taker. All discussions and interviews were conducted based on a prepared semi-structured interview guide that consisted of questions corresponding to the research topic. To ensure accuracy of the information, the data collection tool was translated from English to Kiswahili and then back-translated. The interview guide for FGDs consisted of questions about their knowledge on non-malaria febrile illnesses, health care seeking behaviors and their recommendations on non-malaria febrile illnesses (supporting information S1). Health workers were asked questions on the awareness of the communities on non-malaria febrile illnesses, communities' health seeking behaviors, how they perform diagnosis and treatment of febrile patients and their recommendations on proper management of non-malaria febrile illnesses (supporting information S1). During the interviews and discussions, notes were taken and conversations were digitally recorded. Field notes were expanded on the same day of the interview/discussion. All FGDs and IDIs were held in Swahili language which is the most widely spoken language by the community (national language). FGDs and interviews were transcribed verbatim and translated from Swahili to English. Thereafter, the transcripts were converted into rich text format and imported into MaxQDA, a software for qualitative data analysis [46]. Text files were independently reviewed by the two researchers (IM and CM) before agreeing on the different themes and categories. In case of differing interpretations, the discussion between the researchers took place until the final agreement was reached. The findings were also validated by the interviewing researcher (BC). The agreed themes and categories were then coded. The retrieved segments were analyzed using thematic content analysis and their respective codes were exported to Excel for quantitative analysis. Ethical approval was obtained from Institutional Review Board of Ifakara Health Institute (IHI/IRB/No: 01-2013) and Medical Research Coordinating Committee of Tanzania' s National Institute for Medical Research (NIMR/HQ/R. 8a/Vol. 1X/1472). A written informed consent was obtained from each respondent and participant prior to IDIs or FGDs. To protect identification of the respondents and FGD participants, all personal information that could identify the study participants were only used during the analysis and omitted from the final reports. The participants were assured of anonymity in the presentation and publishing of the data.
The study participants were asked to explain what they know about the term “fever” (“homa” in Swahili language). There were different levels of understanding among the participants. The responses provided by majority of the participants did not associate fever with high body temperature. They described fever as an illness condition such as malaria, colic, rheumatism and sleeping sickness or associated it with symptoms such as headache, coughing, rashes and body pain. Others reported that they did not know the exact meaning of the term fever. There were few participants who described fever as a raise of body temperature (hot body). When the participants were asked to mention the causes of fever in children, things such as change of weather (cold, high temperature) and sunlight were listed by many participants. The participants believed that exposure to a cold environment or prolonged stay under the sun by itself can lead to fever. Only a few participants mentioned the right cause of fever which included illnesses like measles, tuberculosis (TB), typhoid fever and UTIs and other participants associated fever with symptoms/clinical signs such as flu, coughing and diarrhea. Moreover, inappropriate beliefs were perceived as causes of fever by the participants. For example, the presence of false teeth (meno ya plastiki in Swahili language), breastfeeding after long-term sunlight exposure of the mother as well as cessation of pulsation in the fontanel were mentioned by some participants. When the FGD participants were asked to mention the causes of fever other than malaria, several of them listed diseases or symptoms which were neither associated with fever nor non-malaria febrile illnesses. The commonly reported diseases/symptoms were headache, colic, hernia and abdominal pain. However, some participants admitted to be unaware of such illnesses. Only a small number of the participants mentioned the correct non-malaria febrile illnesses such as typhoid fever, UTIs (dirty urine), pneumonia, measles and tuberculosis (TB) and sleeping sickness. Both men and women participants had similar level of knowledge, but participants older than 30 years were more knowledgeable than those who were younger. Moreover, the participants from FGDs conducted in rural areas had limited knowledge in comparison with participants from urban and semi-urban areas. It was also revealed that despite the decrease of malaria, the participants believed that most instances of fever were due to malaria. This was noted when several participants mentioned only malaria as the cause of fever. The participants explained that when their children get fever, they mostly associated it with malaria. This was also acknowledged when the participants were asked to describe the meaning of the term fever (theme 1). A considerable number of the participants explained fever is malaria: During the interviews, health workers were asked to give their views about the knowledge of the community members on non-malaria febrile illnesses. All health workers reported that majority of community members were not aware or had little knowledge on these illnesses. Health workers explained that fevers were perceived to be caused by malaria by several members of communities. This situation was reported to be a challenge to health workers particularly when they want to obtain a comprehensive history of illness from patients since patients explain to health workers that they are suffering from malaria. Health workers identified this wrong perception as an impediment to proper management of patients and emphasized the need for change of attitude. In our study the most common reason for unawareness of the community on non-malaria febrile illnesses reported by the majority of health workers was lack of health education. Health workers pointed out that health education is offered at health facilities but it has not reached a wider community. Several community members live in remote villages and they rarely visit health centres for health care. Health workers emphasized that health education on diseases associated with non malaria fevers will help to create awareness to members of the community. Findings from the FGDs revealed that community members from the study population sought treatment from both the health facilities and traditional healers. When queried on their health seeking behavior, the majority of the study participants reported sending their febrile children to the nearby health facility. However, when asked for any alternative treatment, almost half of the participants reported to seek treatment from the traditional healers. Therefore, this indicates that health facilities and traditional healers were both utilized by the participants. Even though several participants reported seeking treatment from health facilities, but interviewed health workers explained that community members rarely visit health facilities. They said the majority of community members live in remote areas and thus long distances pose as an impediment for visiting health facilities. In addition, health workers stated that the habit of seeking treatment from traditional healers was practiced by some members of the community. They further pointed out that sometimes children were sent to health facilities when they were terminally ill. Likewise, some parents/guardians admitted to health workers that delays to send their children to health facilities was due to prior consultations made from traditional healers. Our findings have also shown that seeking treatment from the traditional healers was sought when there was a persistent fever following treatment from health facilities. If children still had fever after completion of anti-malarial dosage, majority of the participants opted to consult traditional healers for further treatment. Only a few mentioned taking their children back to the health facilities. This study found that self-medication was commonly practiced by several participants. Many participants reported purchasing drugs from pharmacy/drug shops without prior medical prescription. They explained that they prefer using anti-malarial drugs for the treatment of fever in children. The practice of self-medication was reported by FGD participants from wards located near the health facilities as well as wards which were far off from health facilities. During the interviews with health workers, all of them acknowledged that self-medication was commonly practiced by members of the communities. Heath workers further pointed out that some members of the communities would still visit health facilities if they had found no improvement following self-medication. Health workers explained that the habit of self-medication delays provision of prompt and proper treatment and in most cases results into death. The common reported reasons which influenced many members of the community to opt for self-medication were poor health services from health facilities, shortages of drugs, lack of diagnostic facilities, long distance to the nearby health facility and inability to afford health care charges. In our study, we found that the diagnosis of febrile patients was mostly done by mRDTs or clinical symptoms/signs as presented by patients with the assistance of Integrated Management of Childhood Illness guidelines. Interviewed health workers explained that mRDTs were used to distinguish malaria from non-malaria fevers and the majority (10/14) prescribed anti-malarial drugs only to patients with mRDT positive result. When patients had negative mRDT result, health workers reported looking for other causes of fever based on clinical signs and history of the fever. Only a few health workers (4/14) stated initiating anti-malarial drugs even if patients had negative mRDT, as one health worker said: Moreover, when mRDTs were not available, majority of health workers relied only on clinical manifestations of the patient. When asked to describe symptoms or signs which guide them to make a conclusive diagnosis of febrile illnesses such as malaria, typhoid fever or urinary tract infections, most health workers (12/14) mentioned presence of fever, vomiting, headache, loss of appetite and diarrhea as typical symptoms of malaria. With regards to UTIs, pain during urination was mentioned by majority of health workers as a definitive symptom whereas fewer health workers (2/14) considered urine coloration (from yellowish to milky colour) and small urine volume as symptoms of UTIs. For typhoid fever, symptoms such as abdominal pain and diarrhoea were commonly listed by the majority of health workers. It was also revealed that when mRDTs were available many febrile patients tested negative and hence other causes of fever were very likely to be considered. However, in the absence of mRDTs, health workers said several febrile patients were suspected to have malaria and were treated with anti-malarial drugs. They considered that reliance on clinical signs and symptoms only, is prone to lead to misdiagnosis and over-prescription of anti-malarial drugs. Opinions of health workers towards management of persistent fevers following completion of anti-malarial dosage were quite divergent. While majority of health workers (10/14) reported opting for symptomatic diagnosis of non-malaria febrile illnesses and appropriate prescription of antibiotics following failed malaria treatment, however fewer health workers (4/14) reported to switch from first line anti-malarials (artemisinin-based combination therapy) to second line anti-malarial treatment (quinine). Proper management of non-malaria febrile illnesses is largely dependent on the capacity of the health facility to perform accurate diagnosis and treatment of these illnesses. Health workers in this study repeatedly reported lack of diagnostic facilities, shortage of trained health workers, and stock-out of medications as major barriers to proper management of non-malaria febrile illnesses. Our study revealed that from the 12 health facilities, only 2 had diagnostic facilities for a few febrile illnesses; the dispensary had Widal test for detection of typhoid and a microscope used in diagnosis of UTIs and mRDTs, while the health center only had a microscope. The remaining health facilities (10/12) had no diagnostic tests except mRDTs in few health facilities. Health workers explained that they experienced challenges in managing febrile patients without tools for laboratory investigation. Even though mRDT was named as the only diagnostic test which was used to rule out malaria from febrile patients, stock-out of mRDTs was mentioned as an ongoing problem. Health workers said that the supply of mRDTs from the government to the health facilities was normally done on a quarterly basis. However, all health workers repeatedly reported receiving inadequate mRDTs and there were frequent delays in supply of mRDTs. It was clearly stated by health workers that in most cases half way through a quarter, they experienced lack of mRDTs. Among 12 health facilities, only 4 had mRDTs available at the time of our visit. Health workers insisted need for diagnostic tools for malaria and non-malaria febrile illnesses. During the interview with health workers, stock-out of medication was mentioned as a common problem. Drug shortages were reported in most (9/12) health facilities although a few (3/12) had a few boxes of basic drugs such as ALU, antibiotics (amoxicillin, septrin and metronidazole) and pain killer (paracetamol). With regards to staffing, our study revealed significant shortage of health workers particularly in health facilities located in rural areas. Among visited health facilities, four (a hospital, two health centers and one dispensary) had more than two health workers at the level of clinical officers. The remaining eight health facilities each had only one clinical officer assisted by a nurse/midwife or medical attendant. Some of the interviewed health workers (medical attendants/nurses) explained that although they prescribe drugs to patients, they had inadequate skills to manage febrile patients. Moreover, health workers reported to work beyond normal working hours and thus attend more patients beyond the standard average number of patients per physician.
FGD participants were selected from different divisions, wards and hamlets, hence they were from diverse demographic backgrounds and their views were a representation of the general population in the district. Interviewed health workers were selected from different health care levels, dispensary to hospital levels. This was purposively done to grasp a wide scope of attitudes and practices by health care staff from the few health facilities which were visited. During focused group discussion with communities more discussions were done with women as compared to men, but this was purposively done because women are responsible for child care in the family hence their views were expected to give a balanced representation of the household health. However, the results of this study showed that both men and women had similar level of knowledge when it comes to perceptions of non-malaria febrile illnesses. It is also possible that some information was lost during the translation of the transcripts before analysis. This study has demonstrated that the awareness and level of knowledge of communities on non-malaria febrile illnesses was low. Knowledge from this and other similar studies will provide insights into better and practicable methods for improving the management of febrile patients. The wrong perception among communities, whereas fever is understood as being synonymous with malaria, as encountered in this study pose a challenge to the health sector and thus we emphasizes the need of creating public awareness regarding causes of fever other than malaria. Community misconceptions on fever and its causes must be addressed since such beliefs often distract or delay treatment seeking from health care facilities. It is also crucial that relevant authorities intervene against existing habits of self-medication and seeking treatment from traditional healers. Appropriate treatment of febrile patients will require inputs geared towards strengthening of diagnostic facilities, drugs availability and optimal staffing of health facilities. Therefore, it is advisable that the government and other stakeholders should take appropriate measures to improve health care services delivery. | Understanding the awareness of the community on non-malaria febrile illnesses is crucial, especially during the recent decline of malaria episodes of malaria. This study conducted focus group discussions with communities to assess their awareness of non-malaria febrile illnesses. In addition, in-depth interviews with health workers were conducted to explore their views and practices related to diagnosis and management of these illnesses. We identified that the awareness of the study participants on non-malaria febrile illnesses was low and the majority believed that most instances of fever are due to malaria. Moreover, the participants could not mention the right causes of fever and many had inappropriate beliefs about possible causes of fever. Health workers from our study looked for non-malaria febrile illnesses when a febrile patient had negative mRDT result or there was persistence of fever following completion of anti-malarial dosage. Shortages of diagnostic facilities were identified as one of the impediments to proper diagnosis of febrile illnesses. These findings indicate the need for creation of public awareness on causes of fever other than malaria. We recommend appropriate measures be taken by the government and other stake holders to improve health care services delivery particularly at primary health care facilities. | Abstract
Introduction
Methods
Results
Discussion | biology and life sciences
veterinary science
medicine and health sciences
social sciences | 2014 | Community Knowledge and Attitudes and Health Workers' Practices regarding Non-malaria Febrile Illnesses in Eastern Tanzania | 6,307 | 244 |
The simultaneous targeting of host and pathogen processes represents an untapped approach for the treatment of intracellular infections. Hypoxia-inducible factor-1 (HIF-1) is a host cell transcription factor that is activated by and required for the growth of the intracellular protozoan parasite Toxoplasma gondii at physiological oxygen levels. Parasite activation of HIF-1 is blocked by inhibiting the family of closely related Activin-Like Kinase (ALK) host cell receptors ALK4, ALK5, and ALK7, which was determined in part by use of an ALK4,5, 7 inhibitor named SB505124. Besides inhibiting HIF-1 activation, SB505124 also potently blocks parasite replication under normoxic conditions. To determine whether SB505124 inhibition of parasite growth was exclusively due to inhibition of ALK4,5, 7 or because the drug inhibited a second kinase, SB505124-resistant parasites were isolated by chemical mutagenesis. Whole-genome sequencing of these mutants revealed mutations in the Toxoplasma MAP kinase, TgMAPK1. Allelic replacement of mutant TgMAPK1 alleles into wild-type parasites was sufficient to confer SB505124 resistance. SB505124 independently impacts TgMAPK1 and ALK4,5, 7 signaling since drug resistant parasites could not activate HIF-1 in the presence of SB505124 or grow in HIF-1 deficient cells. In addition, TgMAPK1 kinase activity is inhibited by SB505124. Finally, mice treated with SB505124 had significantly lower tissue burdens following Toxoplasma infection. These data therefore identify SB505124 as a novel small molecule inhibitor that acts by inhibiting two distinct targets, host HIF-1 and TgMAPK1.
Toxoplasma gondii infects approximately one-third of the world' s population and causes disease primarily in developing fetuses or immunocompromised individuals [1]. Humans and other intermediate hosts are infected with Toxoplasma by digesting either sporozoite-containing oocysts that are shed in feline fecal matter or bradyzoite-laden tissue cysts in undercooked meat [2]. In the intestine, the parasites infect intestinal epithelial cells and then convert into the replicative form of the parasite called tachyzoites [3]. As tachyzoites disseminate through the host, they encounter various host defenses or pharmacological agents that in most cases kill the tachyzoites. However, some escape killing and transform into bradyzoites that go on to develop into tissue cysts. These tissue cysts cannot be detected by the host' s immune system and are impervious to most, if not all, currently prescribed drugs [3]–[8]. Thus, Toxoplasma is highly prevalent in humans, in large part, because tachyzoites have evolved to grow within its host until it is challenged and then respond by forming a life-long chronic infection. For tachyzoites to be able to grow, they must establish a replicative niche within their host cells and do so by inducing a number of changes to host cell signaling, transcription, and organellar/cytoskeletal organization [9]–[17]. One of these changes includes activation of the host cell transcription factor hypoxia-inducible factor 1 (HIF-1), which is important for parasite growth [18]. Toxoplasma activates HIF-1 by stabilizing the abundance of the HIF-1α subunit. HIF-1α stabilization is accomplished by the parasite down regulating the abundance and activity of the Prolyl Hydroxylase Domain 2 (PHD2) protein whose primary function is to target HIF-1α for proteasomal-dependent degradation [19], [20]. To down regulate PHD2, Toxoplasma requires signaling via a family of host serine/threonine kinase receptors named the activin-like kinases (ALK4, ALK5, and ALK7) [21]. SB505124 [2- (5-benzo[1,3]dioxol-5-yl-2-tert-butyl-3H-imidazol-4-yl) -6-methylpyridine hydrochloride], which is a highly selective ALK4,5, 7 competitive inhibitor, was one reagent used to demonstrate a role for ALK4,5, 7 signaling in HIF-1 activation [21], [22]. But besides inhibiting ALK4,5, 7/HIF-1, SB505124 also potently blocked parasite replication. Although supporting a role for ALK4,5, 7 signaling in Toxoplasma growth, these data were enigmatic because the drug' s effect on parasite growth was more severe than the loss of HIF-1α. For example, the drug significantly blocked parasite replication at 21% O2 (Figure 6 in [21]) whereas parasite growth was more modestly attenuated in HIF-101629226835445KO cells at this O2 tension (Figure 5 in [18]). Two plausible explanations exist to address this: first, ALK4,5, 7 signaling regulates not only PHD2/HIF-1 but other host pathways that are important for parasite growth. Second, the drug has a second target that may be either host- or parasite-encoded. These possibilities were addressed using a forward genetic screen to isolate and characterize SB505124 resistant parasites. This screen revealed that SB505124 inhibits Toxoplasma growth by not only inhibiting ALK4,5, 7/HIF-1 signaling but by targeting a parasite MAP kinase named TgMAPK1.
To define how SB505124 inhibited parasite growth, we developed a forward genetic screen to isolate SB505124-resistant (SBR) parasites. Wild-type RHΔHXGPRT (RHΔ) parasites were chemically mutagenized with N-Ethyl-N-nitrosourea (ENU) and SBR mutants were isolated by growth in the presence of SB505124. Three SBR mutants (SBR1, SBR2, and SBR3) were isolated from three independent mutagenesis screens and relative resistance of each mutant to SB505124 was determined by plaquing assays. SBR mutants displayed similar IC50 values ranging from 4. 9 µM to 5. 4 µM, which relative to the parental RHΔ strain represented ∼5-fold increases in resistance to SB505124 (Figure 1A). Unless stated otherwise, the remaining assays in this report were performed with SBR1. To define how SB505124 affected parasite growth, mock- or drug-treated parasites were stained with DAPI and anti-SAG1 antisera to assess DNA content and identify individual parasites by immunofluorescence. SAG1 staining revealed that, as we previously reported [21], 3 µM SB505124 caused parasites to arrest growth as single SAG1+ parasites (Figures 1B&C). However, DAPI staining indicated that most vacuoles, including the seemingly single SAG1+ parasites, contained irregular numbers (non-2n) of parasites/vacuole (Figure 1C “Irregular Vacuole”). Numbers of nuclei/parasite bodies of those parasites growing within the “Irregular Vacuoles” were quantified (Figure 1D). Approximately 65% of vacuoles from the drug-treated RHΔ parasites contained ≥2 nuclei/parasite body. We also noted that approximately 25% of the SB505124-treated vacuoles contained parasites that were SAG1+/DAPI−, which are denoted as <1 nucleus/parasite body. In contrast, SBR1 replication was neither affected by SB505124 nor did the drug trigger an accumulation of multinucleated parasites or irregular vacuoles (Figure 1C&D). These data suggest that SB505124 disrupts tachyzoite cell cycle progression. SB505124 is a substituted imidazole compound that was developed from the same structural scaffold as the p38 MAP kinase inhibitor SB203580 [22]. SB203580 inhibits Toxoplasma replication and does so presumably by targeting a SB203580-sensitive, parasite-encoded kinase [23], [24]. Even though SB505124 more potently inhibits ALK4,5, 7 than human p38 MAP kinases [22], it was possible that SB505124 reduced parasite growth by targeting the same kinase that SB203580 inhibits. A plaquing growth assay, however, revealed that SB203580 similarly inhibited RHΔ and SBR1 growth (IC50∼15 µM) (Supplemental Figure S1), which is consistent with earlier reports [23]. Thus, these two structurally related kinase inhibitors appear to inhibit Toxoplasma through distinct mechanisms and target proteins. The preceding assays were performed with RH strain parasites because it is the strain best suited for genetic manipulation. But one limitation of the RH strain is that it grows exclusively as tachyzoites and does not readily undergo bradyzoite differentiation either in vitro or in vivo as other parasite strains can. Before testing the effect of SB505124 on the ability of the other parasite strains to undergo bradyzoite development, we first assessed whether SB505124 inhibited their proliferation as tachyzoites. We therefore grew Pru (a Type II strain), CTG (a Type III strain), and GT-1 (a Type I strain that can form bradyzoites) tachyzoites in the presence of SB505124 and determined the drug' s IC50 towards each strain (Figure 2A). SB505124 blocked lytic replication of all 3 strains with IC50 values lower than RH' s IC50. To assess the impact of SB505124 on bradyzoite development, GT-1, Pru, and CTG tachyzoites were grown on coverslips in the presence of SB505124. After 72 hours, parasites were fixed and stained with Dolichos-FITC to detect bradyzoite-containing cysts. We found that 3 µM SB505124 induced the formation of Dolichos+ cysts (Figure 2B and Supplemental Figure S2). But unlike high pH-induced bradyzoites, SAG1 staining could still be detected in the encysted parasites. To further assess bradyzoite development, Pru parasites were grown for 72 h in human foreskin fibroblasts (HFFs) in the presence of 3 µM SB505124 and bradyzoite specific gene expression was assessed by real time PCR. The data indicated that SB505124 induced a several hundred-fold increase of the bradyzoite gene transcripts, BAG1, LDH2, and ENO1 (Figure 2C). While a down-regulated trend was observed for the tachyzoite-specific gene ENO2, decreases in its abundance were not statistically significant (Figure 2C). Thus, SB505124 treatment induces some, but not all, features of bradyzoite development in cystogenic strains of Toxoplasma. To identify the genetic basis for SB505124 resistance, genomic DNA purified from each SBR mutant and the parental RHΔ parasites were subjected to Illumina whole genome sequencing. The sequenced genomes were aligned to the GT-1 Toxoplasma gondii reference genome and compared to identify ENU-induced single nucleotide variants (insertions or deletions were not detected) (Supplementary Table S1). To prioritize testing of candidate SBR mutations, we searched for genes that were mutated in more than one SBR mutant. From this filter, only one gene, Toxoplasma MAP Kinase 1 (TgMAPK1; TGGT1_312570 @ www. toxodb. org), was mutated in all three SBR mutants (Figures 3A&B and Supplemental Table S1). These three mutations affected the translation of two amino acids (Leu162→Gln and Ile171→Thr or Asn) in exon 2 that are part of the kinase' s predicted ATP binding pocket within its catalytic domain. To determine whether these TgMAPK1 mutations were bona fide SBR alleles, we used an allelic replacement strategy to test whether replacing the wild-type TgMAPK1 allele with the mutant one conferred SB505124 resistance (Figure 3C). Thus, RHΔku80 parasites were transfected with TgMAPK1WT or TgMAPK1SBR1 allelic replacement constructs consisting of 900 bp fragments of the TgMAPK1 gene containing either WT or candidate SBR alleles. The transfected parasites were grown in the presence of 3 µM SB505124 and parasite growth was monitored visually. While we could not detect growth of those parasites that were transfected with TgMAPK1WT DNA, we found that parasites grew when they received any of the candidate SBR alleles (Figure 3D). To verify that the mutant TgMAPK1 alleles had properly integrated into the genome, we confirmed the presence of each SBR allele by sequencing a PCR fragment containing TgMAPK1 mutations (data not shown). Thus, single nucleotide mutations in exon 2 of TgMAPK1 were sufficient to rescue growth in SB505124. We hypothesized that if the function of TgMAPK1 was epistatic to ALK4,5, 7/HIF-1 then HIF-1 activation would be unimpaired in the presence of SB505124 and that growth of the SBR mutants would be restored in HIF-1 knockout cells. First, HIF-1 luciferase reporter-transfected host cells were infected for 18 h with wild-type RHΔ, SBR1, SBR2, or SBR3 parasites in the absence or presence of SB505124. The data indicated that HIF-1 was activated by all 4 strains and this activation was similarly inhibited by SB505124 (Figure 4A). Next, we used [3H]-uracil incorporation to measure SBR mutant growth in HIF-1α knockout cells at 3% O2 and found that growth of the SBR mutants were as reduced as wild-type parasites growing in the HIF-1αKO cells (Figure 4B). HIF-1 is activated by a diffusible factor released from extracellular tachyzoites [18]. We, therefore, needed to eliminate the possibility that SB505124 blocked HIF-1 activation due to a global inhibition of host cell responses to extracellular parasites. Thus, we tested whether SB505124 inhibited STAT3 activation since activation of this host cell transcription factor is due to ROP16, which is a polymorphic rhoptry-encoded kinase that is injected by Type I and III strain parasites into host cells independently of invasion [15]. We found that RH strain-induced STAT3 phosphorylation and nuclear localization was unaffected by SB505124 (Figure 4C). Together, these data indicate that SB505124 has two distinct targets in Toxoplasma-infected cells – TgMAPK1 and host HIF-1. SB505124 was identified as an ATP competitive inhibitor of ALK4,5, 7 kinase activity [22]. Although SB505124 does not inhibit host MAPKs [22], we tested whether TgMAPK1 was identified as an SBR gene due to the drug inhibiting the parasite kinase. Our (and others [25]) initial attempts to express in E. coli either full-length TgMAPK1 or the kinase' s N-terminal half containing the kinase domain resulted in a protein preparation of low purity and limited specific activity (not shown). Moreover, we were unable to eliminate the possibility that any activity we did detect was due to a bacterial kinase contaminating our preparations. We therefore developed a Toxoplasma strain in which the C-terminus of TgMAPK1 is epitope tagged at its endogenous chromosomal locus (Figure 5A). Western blotting whole cell lysates with anti-HA antibodies revealed a single immunoreactive band at ∼150 kDa, which is consistent with the predicted molecular weight of TgMAPK1-HAx3 of 141 kDa (Figure 5B). Unlike Brumlik et al [26], we failed to note the presence of smaller immunoreactive bands. Because TgMAPK1 target substrates have yet to be identified, we assessed its activity using an autokinase assay. Thus, HA-tagged TgMAPK1 was immunoprecipitated from Toxoplasma lysates and in vitro kinase assays were performed in the presence of γ32P-ATP. We found that TgMAPK1 was autophosphorylated (Figure 5B), indicative of an active kinase, and that this autokinase activity was not detected in immunoprecipitates from wild type non-transgenic controls (Figure 5C). Dose response curves revealed that SB505124 inhibited TgMAPK1 autokinase activity with an apparent IC50 of 125 nM (Figure 5D&E). To address the possibility that the TgMAPK1 immunoprecipitates contained a contaminating kinase whose activity was SB505124 sensitive, we attempted to ectopically express a kinase-dead TgMAPK1 mutant cDNA by mutating the conserved lysine140 in the catalytic domain to an arginine. Repeated attempts to either transiently or stably express this mutant were unsuccessful as were attempts to express SBR mutants that were epitope tagged as either transgenes or at the endogenous TgMAPK1 locus. We therefore turned our attention to a TgMAPK1 temperature sensitive mutant that was isolated independently of this study in a temperature sensitive growth screen (LE and MW; manuscript in preparation). To minimize potential misfolding of the TgMAPK1ts protein, autokinase activity was compared between parasites grown at 34°C (the permissive growth temperature for the ts mutant) that harbored either HA-tagged TgMAPK1WT or TgMAPK1ts alleles. Unlike TgMAPK1 kinase-dead and SBR mutants, TgMAPK1ts-HA could be stably expressed and similar amounts of TgMAPK1WT-HA or TgMAPK1ts-HA could be immunoprecipitated using anti-HA beads (Figure 5F). In contrast, significantly lower levels of autokinase activity could be detected in the TgMAPK1ts immunoprecipitates suggesting that the kinase activity in the immunoprecipitates was most likely dependent on TgMAPK1 and not a contaminating kinase (Figure 5G). Even though the wild-type and ts mutants grew at similar rates at 34°C we cannot fully rule out the possibility that potential misfolding of TgMAPK1ts at the permissive temperature may affecting binding of a contaminating kinase. The differences in autokinase activity between the wild-type and ts kinases and the fact that the SBR mutations are in the region of the ATP binding pocket where the SB class of kinase inhibitors interact with their target kinases [27]–[29] strongly suggests that TgMAPK1 is an active kinase that can be inhibited by SB505124. Our in vitro data suggests that SB505124 blocks Toxoplasma growth in an unusual manner by which both host and parasite pathways are simultaneously targeted. To assess whether SB505124 can limit parasite growth in vivo, C57Bl/6 mice were intraperitoneally infected with 103 GFP-expressing RH tachyzoites and then treated with daily intraperitoneal injections of either 10 mg/kg SB505124 or vehicle (DMSO). On Day 5 post-infection, mice were sacrificed and peritoneal exudate cells were stained with anti-CD45 (to identify infiltrating leukocytes) and analyzed by flow cytometry. Mice treated with SB505124 had significantly fewer numbers of infected cells (12. 8%) compared to the vehicle controls (25. 7%) as measured as GFP+/CD45+ events (p = 0. 0252) (Figures 6A, B). To determine whether the infected cells contained similar numbers of parasites, we measured the mean fluorescence intensity (MFI) of GFP in CD45+/GFP+ cells and found that infected cells from SB505124-treated mice displayed a 26. 8% reduction in relative GFP MFI compared to vehicle-treated control mice (p = 0. 0988) (Figure 6C). Though this decrease was not statistically significant, it is likely an underestimation as SB505124-treated parasites display enlarged, translationally active parasite bodies that could still produce high levels of GFP. The polyploidy phenotype induced by SB505124 precluded us from further assessing parasite burdens by qPCR analysis of genomic DNA. Since SB505124 inhibits TGFβ signaling, a known antagonist of IFNγ production [22], [30], it is possible that the effect of SB505124 on Toxoplasma in mice is due to enhanced IFNγ-driven immunity. However, IFNγ serum levels from the mice 5 days post infection were identical between SB505124 and vehicle-control treated mice (Figure 6D).
Our initial interest in SB505124 stemmed from finding that this compound blocked the parasite' s ability to activate HIF-1 via ALK4,5, 7 signaling [21]. This conclusion was supported by additional data showing that overexpression of SMAD7, which is an endogenous ALK4,5, 7 inhibitor, also blocked parasite activation of HIF-1 [21]. Additional unpublished work demonstrated that HIF-1 activity is increased in cells transfected with ALK4,5, 7 expression plasmids. But since parasite replication was more severely reduced in SB505124-treated cells than in HIF-1α knockout cells, these data suggested that in addition to the ALK4,5, 7/HIF-1 pathway the drug had at least one additional target that could be in either the host or parasite. Our forward genetic screen resolved this issue and identified SB505124 as the first compound that we are aware of that inhibits growth of an intracellular pathogen by acting on seemingly unrelated targets in both the host and parasite. We believe that collectively our data demonstrate that TgMAPK1 and ALK4,5, 7/HIF-1 are the two relevant SB505124 targets in parasite-infected cells. While we cannot rule out that the drug may have additional targets in Toxoplasma-infected cells, these targets would not be important for parasite growth. Although the catalytic domain of TgMAPK1 is homologous to other MAPKs, it has two unusual features that may facilitate TgMAPK1-specific agonist development. First, TgMAPK1 has 3 unique insertions within its catalytic domain with the most predominant one being a 93 amino acid insertion between the DFGLAR-motif that coordinates divalent cations. How the catalytic domain of the kinase can properly fold with this large insertion is currently unknown and cannot be easily predicted since the insertion prevents protein-modeling programs from using known MAPK structures as scaffolds (Brown and Blader, unpublished results). Second, TgMAPK1 has an ∼800 amino acid C-terminal extension that lacks conserved domains and has no homology to any known protein either in Toxoplasma or its host. Given that inhibition of TgMAPK1 induces multinucleated parasites (suggesting a cell cycle defect) and that the C-terminal extension facilitates its localization to mitotic structures (E. Suvorovo et al, manuscript in preparation) we hypothesize that TgMAPK1 functions in cell cycle regulation and our future work will define if and how TgMAPK1 regulates the cell cycle. TgMAPK1 was originally discovered based on its homology to human MAPKs [24]. It was assigned then as a p38 MAPK homolog, in part, because its catalytic activity was reported to be sensitive to SB203580. In our hands, TgMAPK1 activity was largely unaffected by this compound (Supplemental Figure S1B), although a general decrease in autokinase activity by low SB203580 levels was noted that may reflect reduced non-specific binding of ATP to the kinase. Regardless, higher amounts of SB203580 did not significantly decrease TgMAPK1 autokinase activity and SBR mutants are similarly sensitive to SB203580 (Supplemental Figure S1A&B). We believe that there are two primary reasons for differences in between our data and those of [24]. First, our experiments used endogenously epitope-tagged TgMAPK1 that was immunoprecipitated from tachyzoites. In contrast, Brumlik and colleagues used a bacterially expressed construct that only contained TgMAPK1' s catalytic domain and most of this protein was expressed in bacterial inclusion bodies (our unpublished observations) [24]. Even though we could purify the protein from the inclusion bodies under denaturing conditions, very weak kinase activity was detected after refolding and we could not verify whether this protein was properly folded. Attempts to purify the soluble protein resulted in a preparation of poor purity (as noted by [24]) whose activity appeared to be due to a contaminating bacterial kinase since recombinant expression of a catalytically inactive kinase mutant had the same rate of activity as the wild-type kinase (not shown). Recently, Sugi et al demonstrated that the SBR2 (Leu162→Gln) and SBR3 (Ile171→Asn) alleles conferred resistance to the effect of the bumped kinase inhibitor 1NM-PP1 on parasite replication [25]. TgMAPK1 resistance to 1NM-PP1 is independent of its well-described inhibition of Toxoplasma Calcium-Dependent Protein Kinase 1, whose activity is required for parasite invasion and egress [31]. xxx But unlike our work, Sugi et al. did not test whether 1NM-PP1 affects parasite replication by directly inhibiting TgMAPK1 or if resistance emerged because TgMAPK1 functions downstream of the protein (s) that 1NM-PP1 interacts with [25], [32]. It is also noteworthy that we were unable to successfully express a kinase-dead mutant of TgMAPK1 as a transgene either in transiently or stably transfected parasites. The most likely explanation for this is that expression of the kinase dead TgMAPK1 mutant has a dominant negative effect either by binding its upstream activating kinase or its downstream targets. The continuing emergence of antimicrobial resistance requires novel approaches to the design of new drugs and treatments. Although simultaneous inhibition of both host and parasite targets is an untested approach, one benefit would be that resistance to a compound that impacts a host cell target is less likely to develop [33]. As a proof of concept, we showed that SB505124 reduced tachyzoite burdens 5 days after mice were intraperitoneally infected. We did not examine later time points for three reasons. First, we demonstrated that SB505124 will induce bradyzoite development in vitro and therefore it is possible that long-term treatments with this drug would lead to increased cyst burden. Second, germline loss of functions mutations in HIF-1α causes an embryonic lethal phenotype in mice [34]. Thus, HIF-1α can only be deleted in specific cell types using cre-recombinase expressing mice. But, Toxoplasma infects and forms bradyzoites in multiple types of cells. Since tissues consist of heterogeneous populations of cells it would, therefore, be difficult to assess how a cell-specific loss of HIF-1α would impact bradyzoite development. Third, ALK5 is the TGFβ receptor and long-term inhibition of this key immunosuppressive cytokine could have a deleterious effect on mice independent of its role in regulating parasite growth. Parasites treated with SB505124 developed into bradyzoites under in vitro conditions. Given that the drug induces RH parasites to become multi-nucleated (suggesting a role for TgMAPK1 in cell cycle), these data are consistent with earlier observations that bradyzoite development represents an exit from the cell cycle during the transition between S to M phase (Toxoplasma lacks a G2 phase) [35], [36]. One implication of bradyzoite development being potentially triggered by TgMAPK1 inhibition is that it may open the door to two novel but not necessarily mutually exclusive approaches for treating toxoplasmosis. First, we hypothesize that compounds that either act as TgMAPK1 agonists or mimic the activities of TgMAPK1 substrates would be predicted to act as inhibitors of bradyzoite development. Because bradyzoites are impervious to both immune surveillance mechanisms and anti-parasitic compounds [3]–[8], these small molecules would maintain the parasite as tachyzoites, which is a growth state that would prolong their susceptibility to currently prescribed drugs. Second we will focus on identifying a compound (s) that specifically blocks parasites from activating ALK4,5, 7 or prevent these receptors from triggering HIF-1 activity. We believe that either of these approaches would be valid even if SB505124 induces bradyzoite development as a consequence of the drug activating a more generalized stress response. Our future analysis of TgMAPK1 regulation and substrate identification will resolve how TgMAPK1 influences bradyzoite differentiation. In summary, we used a forward genetic screen to demonstrate that a serine/threonine kinase inhibitor blocks Toxoplasma growth through two distinct targets and our future work will focus on this issue. Kinase inhibitors are particularly useful for dual-target screens because even though they are designed to inhibit human kinases their off target effects cannot be predicted [37]. For example, we showed that SB203580 does not inhibit TgMAPK1, which bears homology to p38 MAPKs. Rather TgMAPK1 is inhibited by SB505124 even though this compound does not appear to significantly affect p38 MAPK activity [22]. Our work, therefore, also highlights the utility of repurposing drugs and investigative compounds originally developed to target cancer and other diseases for the study and/or treatment of microbial infections [38]–[41].
Animal protocols (IACUC Protocol #11-075I) were approved by the University of Oklahoma Health Sciences Center IACUC. This study was carried out in strict accordance with the Public Health Service Policy on Humane Care and Use of Laboratory Animals and AAALAC accreditation guidelines. Toxoplasma RH, RHΔHXGPRT, RHΔ-GFP (kindly provided by Dr. Gustavo Arrizabalaga of Indiana University), RHΔ RHΔHXGPRTΔKu80 (kindly provided by Dr. David Bzik of Dartmouth University), GT-1, Pru, and CTG parasites were maintained in human foreskin fibroblasts in Dulbecco' s Modification of Eagle' s Medium (DMEM) (Mediatech; Manassas, VA) supplemented with 10% fetal bovine serum (Mediatech), 2 mM L-glutamine (Mediatech), and 100 IU/ml penicillin – 100 µg/ml streptomycin (Mediatech). The TgMAPK1ts-HA temperature sensitive (ts) TgMAPK1 mutant will be described in detail elsewhere (manuscript in preparation). Other host cell lines were maintained in the HFF growth medium. All host cell lines and parasites were routinely tested for Mycoplasma contamination with the MycoAlert Mycoplasma Detection Kit (Lonza, Basel, Switzerland) and found to be negative. Intracellular RHΔHXGPRT tachyzoites grown in T-75 flasks were mutagenized with 300 µg/ml ENU (Sigma; St. Louis, MO) in complete DMEM for 2 hours at 37°C as previously described [42], [43]. After ENU treatment, media was removed and the monolayer was washed four times with 1× phosphate-buffered saline. Mutagenized parasites were then released from host cells by scraping and syringe-lysis (27 g needle) and washed with 30 ml DMEM. Parasites were allowed to recover in fresh HFFs for 72 h and then grown in the presence of SB505124 (TGF-βRI Kinase Inhibitor III (EMD Millipore; Billerica, MA) ). After several rounds of selection in SB505124, individual clones were obtained by limiting dilution in 96 well plates of HFFs. SBR1 was isolated from a population after 4 passages in 3 µM SB505124 and 11 passages in 5 µM SB505124. SBR2 was isolated after 4 passages in 5 µM SB505124. SBR3 was isolated after 5 passages in 5 µM SB505124. Plaque assays were performed by adding 200 parasites to each well of a 24 well plate containing confluent HFFs. After 5–7 days, the monolayers were methanol-fixed and stained with 0. 1% crystal violet. Plaques were counted using 4× magnification on an inverted dissecting microscope. Uracil incorporation assays were performed by growing parasites in 24 well plates. After 66 h, 5 µCi 3H-uracil (MP Biomedical; Santa Ana, CA) was added to the wells for an additional 6 h of the assay. Wells were washed, precipitated with 10% trichloroacetic acid, and 3H-uracil counted by liquid scintillation. Parasites were grown in confluent HFFs until the host monolayer had completely lysed. The media containing the extracellular parasites were collected without further scraping, washed with serum-free DMEM, passed three times through a 27 g needle, and then filtered through a 3 µm pore size filter membrane. Genomic DNA was isolated using the Qiamp DNA mini kit (Qiagen; Valencia, CA) using the manufacturer' s protocol for cultured cells. qRT-PCR (not shown) determined that host DNA contamination was less than 0. 5% and this result was confirmed by the whole genome sequencing data. Sequencing libraries were prepared from genomic DNA (1 µg) using the Truseq DNA LT Sample Prep Kit v2 as per the manufacturer' s protocols (Illumina, San Diego, CA) and the libraries sequenced on an Illumina HiSeq 2000 instrument with 100 bp, paired-end reads. Between 30–37-fold coverage was achieved for all genomes. Genome sequences were aligned with the MOSAIK program [44], [45] using the type I parasite genome of GT-1 as a reference and single nucleotide variants identified with variant caller program FreeBayes [46]. For MOSAIK, the default parameters we used had a hash size of 14. For FreeBayes, we used the program' s default parameters with the exception that: ploidy (-p) was set to 1, a P value cutoff of 0. 9 (-P) was used, complex events were ignored (-u), and population priors were turned off (-no-population-priors) as they are not applicable to the Toxoplasma genome. A 944 bp fragment of TgMAPK1 was PCR amplified using Platinum Pfx polymerase (Invitrogen; Carlsbad, CA) from wild-type and SBR mutant parasites with forward (5′-TGCATGGCGATGAGTTTCTGAACG-3′) and reverse (5′- TCGTGTCGACGTTTCTTCTGTGGA-3′) primers. PCR reactions were incubated with Taq polymerase (Invitrogen) for 10′ to add 3′ A-overhangs. PCR products were gel purified and cloned into pCR2. 1 (Invitrogen) by TA ligation. Inserts were sequenced verified by conventional sequencing. Parasites were transfected with 50 µg of linearized plasmid resuspended in cytomix buffer (2 mM ATP, 5 mM glutathione). For each transfection, 2×107 RHΔHXGPRTΔKu80 tachyzoites were washed in cytomix buffer and resuspended in 0. 5 ml complete cytomix buffer. The plasmid DNA was added to the parasites in a BTX electroporation cuvette (0. 4 mm gap), and electroporated into the parasites at 2000 V, 50 ohm, 25 µF with a BTX ECM 360 (Holliston, MA). Parasites were then transferred to 75 cm2 flasks containing confluent HFF monolayers and after 72 h 3 µM SB505124 was added. Parasites receiving pCR2. 1: TgMAPK1WT failed to grow whereas those that received pCR2. 1: TgMAPK1SBR1-3 were able to be passaged indefinitely in 3 µM SB505124. Individual clones were isolated by limiting dilution as described above and single clones were named RH: MAPK1SBR1, RH: MAPK1SBR2, and RH: MAPK1SBR3. To ensure that the SBR mutation was incorporated into the endogenous MAPK1 locus, PCR fragments were generated from genomic DNA using primers that flanked the region of the amplicon. The amplicon was then gel purified and cloned into PCR2. 1. At least 5 independent transformants were sequenced via conventional Sanger sequencing using M13 forward and reverse universal primers. RHΔ or SBR1 tachyzoites were added to 24 well plates containing confluent HFFs on glass coverslips in the presence or absence of 3 µM SB505124. After 24 h, coverslips were methanol-fixed, blocked with 3% bovine serum albumin, and labeled with rabbit anti-SAG1 (1∶100000; kindly provided by Dr. John Boothroyd, Stanford University) followed by Alexa Fluor 488-conjugated goat anti-rabbit (Invitrogen). Coverslips were mounted to slides with Vectashield containing DAPI (Vector Lab; Burlingame, CA). One hundred randomly chosen vacuoles/coverslip were counted. Phospho-STAT3 was detected in HFFs infected with RH-GFP (MOI of 10) tachyzoites for 6 h in the absence or presence of 5 µM SB505124. Cells were fixed with 4% formaldehyde, permeabilized with ice-cold methanol for 5 minutes, blocked at room temperature for 2 h with 3% BSA, and incubated with rabbit anti-phosphoSTAT3 (Cell Signaling; Danvers, MA) overnight at 4°C. After washing, cells were stained with Alexa Fluor 594 conjugated goat anti-rabbit (Invitrogen) and mounted to slides with Vectashield containing DAPI. Bradyzoite cysts were detected in HFFs 72 h after adding either 3 µM SB505124 or pH 8. 1 media [47]. Monolayers were fixed with ice-cold methanol for 5′ and then stained to detect SAG1 as described above. Bradyzoite cyst wall was detected by staining with 5 µg/ml FITC-conjugated Dolichos (Vector Labs). The frequency of Dolichos+ vacuoles was quantified by examining a minimum of one thousand vacuoles per strain from three independent experiments using a Cytation 3 (Biotek Instruments, Inc. , Winooski, VT) cell imaging multi-mode reader at 20× magnification. To generate strains in which TgMAPK1 is epitope tagged at its C-terminus with three HA repeats (RHΔHXGPRTΔKu80: TgMAPK1-3XHA), a 1513 bp fragment was amplified from the 3′ end of TgMAPK1 using primers TgMAPK1-3XHAF and TgMAPK1-3XHAR and cloned into p3xHA-LIC-HXGPRT by ligation independent cloning to create pTgMAPK1-3XHA [48]. RHΔHXGPRTΔKu80 parasites were transfected with PacI-linearized TgMAPK1 plasmids and transfectants selected with mycophenolic acid/xanthine. Proper integration and expression was by PCR (not shown), Western blotting (Figure 5B), and immunofluorescence (E. Suvorova et al. , Manuscript in Preparation). RHΔHXGPRTΔKu80: TgMAPK1WT-HA, RHΔHXGPRTΔKu80: TgMAPK1ts-HA, or wild-type RHΔHXGPRTΔKu80 were grown overnight in confluent 75 cm2 flasks. Extracellular parasites were washed away and intracellular parasites were released by scraping and syringe lysis. The parasites were washed and lysed on ice with 200 µl modified RIPA buffer (50 mM Tris pH 7. 4,1% NP-40; 0. 1% SDS, 500 mM NaCl) supplemented with 1× EDTA-free Protease Inhibitor Cocktail (Roche; Indianapolis, IN) per 107 parasites. Lysates were centrifuged at 20,000×g for 15′ at 4°C to remove insoluble material and the supernatant was precleared with rabbit IgG-conjugated sepharose beads (Cell Signaling). Precleared lysates were added to 10 µl anti-HA-sepharose beads (Cell Signaling) and incubated overnight at 4°C, washed 3 times in modified RIPA buffer, and 1 time in kinase assay buffer (20 mM HEPES pH 7. 48,25 mM glycerophosphate, 25 mM MgCl2,0. 5 mM DTT, and 0. 1 mM Na3VO4). Immune complexes were then evenly distributed between sample tubes (the equivalent of 200 µg of precleared lysate was used for each sample) and incubated with 10 µCi γ32P-ATP (MP Biomedicals) in kinase assay buffer at 34°C for 1 hour. Kinase reactions were stopped by adding 5 µl 6× sample buffer and boiling the samples for 5′. Reactions were separated by SDS-PAGE (10% acrylamide) and gels were fixed for 20′ in acetic acid∶methanol∶H20 (1∶5∶4) and dried. The gels were exposed to film and analyzed using ImageJ software. We attempted to express kinase-dead TgMAPK1 (K140R) and SBR mutants as a transgenes by synthesizing full length wild-type and mutant constructs in frame with C-terminal 3× HA-tags (Genescript; Piscataway, NJ). The cDNA constructs were cloned into pSAGCAT by replacing the CAT gene with the TgMAPK1 gene [49]. The constructs were then transfected into RH strain parasites and 24 h later the parasites were harvested and transgenic TgMAPK1 expression assessed by Western blotting and activity by in vitro kinase reaction. We were only able to detect low levels of mutant TgMAPK1 protein even when 175 cm2 flasks were used for the transfection and this amount of kinase was not sufficient for the autokinase reactions (not shown). In contrast, 25 cm2 flasks were sufficient to detect and assay the wild-type kinase. We next cloned the TgMAPK1 alleles into ptubYFPYFP/sagCAT [48] by replacing the YFP genes with the kinase alleles. Using chloramphenicol selection, stable transformants could be isolated for those parasites receiving wild-type TgMAPK1 but we could not obtain transformants for parasites receiving mutant alleles. We also attempted to epitope tag the SBR mutants at their endogenous locus by cloning the 1. 2 kb 3′ most region (up to the stop codon) of the genomic region of the TgMAPK1 into pSF-TAP-LIC-HXG in frame with the SF-TAP tag [48]. This single construct is compatible with both the wild type and SBR strains since the 3′ region of homology is downstream of the SBR mutations. We linearized the vector with NcoI, a unique restriction site within the TgMAPK1 sequence giving 677 bp of homology to the endogenous TgMAPK1 allele, and transfected the DNA into RHΔKu80ΔHXGPRT: TgMAPK1SBR1 and the parental wild type strain. But, we were unable to recover viable SBR parasites from selection with MPA/xanthine even though we were able to do so for the wild-type parasites. Proteins were separated by SDS-PAGE and transferred to PVDF membranes. Membranes were blocked with 5% BSA-TBST. Rat anti-HA (Roche) was used at a concentration of 1∶500. Goat anti-rat HRP (Cell Signaling) was used at a concentration of 1∶2000 and detected using Supersignal West Pico ECL reagent (Thermo, Waltham, MA) with a gel doc system. RNA was isolated with the RNeasy Midi kit (Qiagen) using the manufacturer' s instructions for cultured cells. RNA quality and yield was assessed by UV spectrophotometry and horizontal electrophoresis. Total RNA was treated with DNAse I (Invitrogen) and converted to cDNA using Superscript III (Invitrogen) using random hexamer primers. Relative abundances of bradyzoite gene transcripts BAG1, LDH2, ENO1 and tachyzoite transcript ENO2 were calculated with the 2−ΔΔCt method [50] using Toxoplasma β-actin as an internal control (see Supplemental Table S2 for primer sequences). HIF-1 luciferase assays were performed as previously described [18]. Briefly, murine embryonic fibroblasts were transfected pHRE-luc and pTK-Rel (as a transfection efficiency control) and 24 h later 2×106 parasites were added to the wells in the presence or absence of SB505124. 18 hours later, luciferase activity was measured using the Dual-Glo luciferase assay kit (Promega, Madison, WI). C57Bl/6 female mice were infected intraperitoneally with 103 freshly purified RH-GFP parasites in a volume of 200 µl phenol-red-free DMEM. Beginning 1 h post infection, mice received 10 mg/kg SB505124 or DMSO alone intraperitoneally once daily. The drug had no apparent effect on the health of the animals during this time course. On day 5 post-infection, mice were sacrificed by CO2 asphyxiation and PECs collected in a 5 ml PBS-lavage. Cells were washed, stained with anti-mouse APC-conjugated CD45, and analyzed by flow cytometry using a FACSCalibur cytometer (BD Biosciences, San Jose, CA). 105 events were counted and subsequent analysis was performed using Summit (Dako, Carpinteria, CA). IFNγ was measured using Mouse IFNγ ‘Femto-HS’ High Sensitivity ELISA (eBioscience; San Diego, CA). | Understanding how a compound blocks growth of an intracellular pathogen is important not only for developing these compounds into drugs that can be prescribed to patients, but also because these data will likely provide novel insight into the biology of these pathogens. Forward genetic screens are one established approach towards defining these mechanisms. But performing these screens with intracellular parasites has been limited not only because of technical limitations but also because the compounds may have off-target effects in either the host or parasite. Here, we report the first compound that kills a pathogen by simultaneously inhibiting distinct host- and parasite-encoded targets. Because developing drug resistance simultaneously to two targets is less likely, this work may highlight a new approach to antimicrobial drug discovery. | Abstract
Introduction
Results
Discussion
Materials and Methods | signal transduction
medicine and health sciences
molecular cell biology
pathology and laboratory medicine
cell biology
host-pathogen interactions
genetic screens
medical microbiology
gene identification and analysis
gene expression
genetics
biology and life sciences
microbiology
pathogenesis
parasitology | 2014 | Forward Genetic Screening Identifies a Small Molecule That Blocks Toxoplasma gondii Growth by Inhibiting Both Host- and Parasite-Encoded Kinases | 11,758 | 158 |
We introduce a series of experimental procedures enabling sensitive calcium monitoring in T cell populations by confocal video-microscopy. Tracking and post-acquisition analysis was performed using Methods for Automated and Accurate Analysis of Cell Signals (MAAACS), a fully customized program that associates a high throughput tracking algorithm, an intuitive reconnection routine and a statistical platform to provide, at a glance, the calcium barcode of a population of individual T-cells. Combined with a sensitive calcium probe, this method allowed us to unravel the heterogeneity in shape and intensity of the calcium response in T cell populations and especially in naive T cells, which display intracellular calcium oscillations upon stimulation by antigen presenting cells.
Calcium ion acts as a universal second messenger in response to most cellular stimuli [1]. The pattern of the calcium response is biphasic, and primarily results from the production of inositol-3 phosphate (IP3) which triggers the release of calcium from the endoplasmic reticulum (ER store release) into the cytoplasm. This decrease is sensed by the stromal interaction molecules (STIM) that secondarily trigger the capacitative entry of extracellular calcium via the calcium release activated channels (CRAC) of the ORAI family [2]–[4]. Measuring the intracellular concentration of calcium is therefore of primary interest when analyzing transduction processes in living cells. Currently, this is achieved by methods which combine flow cytometry with intracellular diffusive fluorescent calcium-sensitive dyes in immunological relevant cells such as macrophages, NK cells, T or B cells. As an example, the calcium response is routinely monitored in T cells [5]–[15] as a functional read-out of the outside-in signal transduction subsequent to T-cell receptor (TCR) engagement by major histocompatibility complex (MHC) molecules with agonist peptide. However, when naive T cells encounter antigen-presenting cells (APC) and more generally when signaling is induced by intimate signaling-to-target cell-cell contact, flow cytometry approaches cannot fully recapitulate the physiological conditions of stimulation. In addition, recent works have demonstrated that TCR triggering by the MHC molecules follows unusual physico-kinetic parameters of serial engagement-disengagement [16], [17], which could be the molecular basis for the broad selectivity, high specificity, extreme sensitivity [18] and the capacity to induce a rapid intracellular response that characterize TCR triggering [19]. While soluble anti TCR or anti CD3 antibodies [20], antibody coated beads [21], [22], and phorbol myristate acetate/ionomycin [23] can all induce a productive calcium signal in T cells that ultimately leads to their activation, proliferation and cytokine production, the calcium elevation triggered by these strong irreversible stimuli is usually sustained. It may not therefore be representative of the response to physiological stimulations, which is more likely to consist in calcium spikes and oscillations [9], [24]–[26]. In order to capture the true calcium responses triggered during cell-cell contacts such as those occurring during T-cell and APC stimulation, video-imaging is compulsory in that it provides informative parameters on individual cell behavior (i. e. displacements, shape and intensity fluctuation) [27]. Obtaining such imaging data requires a complex custom-built experimental set-up usually dedicated to the detection of UV-excitable calcium probes and to the maintenance of physiological parameters for long-term recordings [9], [25], [28]. In any case cell tracking is mandatory and is often performed by manual approaches [28]–[30]; however, in addition to being time-consuming, manual analysis is prone to systematic errors due to subjective choice. Such pre-selection is an unavoidable step in any manual analysis. Automating the simultaneous tracking of hundreds of cells over hundreds of time frames would overcome these issues. Nevertheless, simultaneously tracking moving cells at high density represents a considerable challenge, particularly considering the need to correctly resolve interlaced tracks of stretching cells while providing valuable statistical confidence and robustness. While many software packages do incorporate a cell tracking module or plugins, the normalization of the calcium signal for each cell as well as the classification of calcium responses and any quantification generally have to be performed manually involving tedious excel datasheets [31]. Here we have developed a complete approach named Methods for Automated and Accurate Analysis of Cell Signals (MAAACS) which enables the simultaneous tracking of a population of individual moving cells (multiple target tracking, MTT) [32] and the automatic extraction of robust statistics on pertinent observables. The MAAACS program has been conditioned to synchronize, normalize and assemble the recorded cell traces to provide an at a glance calcium barcoding of a heterogeneous cell population and facilitate the a posteriori data mining and interpretation. We used MAAACS to examine the calcium responses induced in T cells upon interaction with APCs and with it were able to reveal the oscillatory calcium responses in mouse naive CD4+ T cells upon antigen recognition.
Aiming to establish an easy, robust, sensitive and reliable way of evaluating calcium fluctuations in T cells, we assessed many visible calcium indicators such as Fluo-4 AM, Fluo-3 AM, and Fluo-8. All displayed short term leakiness of the loading without membrane extruder blockers [33] (such as probenecid) [34] and subsequent intracellular compartmentalization, incompatible with unbiased calcium measurements [35]. In contrast, T-cell hybridomas (3A9) loaded with the calcium indicator BD PBX appeared to overcome most of these problems [36]. Compared to standard loading conditions, this procedure provided a stable loading of the fluorescent indicator (emission spectrum fully stackable with Fluo-4 AM; Figure 1A), without affecting cell viability (Figure S1A). We also documented that BD PBX fluorescence was photostable upon repetitive confocal illumination for 30 min, unlike Fura-red the fluorescence of which rapidly decreased (Figure S1B). This precluded us from performing BD PBX/Fura red ratiometric cytosolic calcium measurements [37], [38]. In addition, we investigated whether cytosolic calcium gradients could be visualized under such experimental conditions since few discrete hotspots were detectable among the homogenous fluorescence. BD PBX and mitotracker red loaded cells were imaged to decipher whether mitochondria would accumulate calcium indicator. In 3A9 T cells the two signals were not mutually exclusive (Figure S1. C, D) unlike in Jurkat cells or primary human T cells [35], [39]. Part of the signals was correlated under stimulation, most presumably caused by FRET between the two dyes (Figure S1. C, D). We detected no significant sequestration of the BD PBX calcium dye, unlike Fura-2 in Jurkat cells although this phenomenon had a limited impact on whole cell calcium measurement [35]. These inconsistencies with previous reports [34] motivated us to consider BD PBX as a close relative of Fluo-4 AM but harboring subtle differences, that required the dedicated loading buffer to avoid the dye leakage displayed by Fluo-4 AM (Figure S1A). Due to the lack of information about the BD PBX from the manufacturer, we thus determined the in vitro Kd of the BD PBX as described previously [40] (Figure 1B), which gave a consistent value for Kd of 312 nM±33, comparable to the Kd for Fluo-4 AM of 327±49 nM and that in the literature (Kd = 345 nM) [41] (see Materials and Methods). The great similarity between BD PBX and Fluo-4 AM led us to assume the in situ Kd of BD PBX to equal the reported in situ Kd value (1 µM) of Fluo-4 AM [34], deemed acceptable when accurate determination by electrophysiology is either not feasible or not available [28]. Based on this Kd value, we estimated that the intracellular calcium concentration in resting 3A9 T cell hybridomas would be around 90 nM and consistent with previously published values for these hybridomas [42] as well as leukemic cell lines Jurkat [39], mouse thymocytes [43] and human peripheral blood lymphocytes [35]. We used flow cytometry to compare the detection sensitivity of BD PBX with the ratiometric Indo-1 AM (routinely used in calcium assays, UV excitable). In terms of response pattern, T cell hybridomas loaded with BD PBX do not strictly speaking respond the same as those loaded with Indo-1 AM, as the non-ratiometric calcium indicator BD PBX does not allow the evaluation of intracellular free calcium concentration (Figure 1C). We therefore sought to estimate the intracellular calcium concentrations in BD PBX loaded T cell hybridomas. Upon various concentrations of ionomycin, we compared intracellular calcium elevation in BD PBX versus Indo-1 AM loaded 3A9 T cell hybridomas. As previously mentioned, the kinetics were not fully stackable and the calculated intracellular calcium concentration differed between the two methods due to Kd discrepancy and loss of linearity in the relationship linking calcium concentrations and high fluorescence amplitudes [40]. Indeed at such high fluorescence values under strong ionomycin concentrations, the calcium concentration was overestimated and is the reason for us reporting fluorescence amplitude instead of erroneous calcium concentrations throughout this manuscript. Nevertheless to our surprise, lower concentrations of ionomycin rapidly abrogated fluorescence elevations of indo-1 AM whereas BD PBX fluorescence elevation remained detectable even at subnanomolar ionomycin concentrations. This indicated that BD PBX is sensitive to low intracellular calcium elevation. Thapsigargin (Figure 1D) or the cross-linking of the TCR/CD3 complex by anti-CD3ε (2C11 biotin/streptavidin) induced in cells loaded with BD PBX responses similar to those induced by ionomycin. This method was extendable to naive primary CD4+ T cells labeled or not with an anti CD4 monoclonal antibody (Figure 1E). While surface receptor crosslinking with antibodies is a convenient way of stimulating calcium responses in T cells, it cannot physiologically reproduce the dynamics of TCR/MHC-antigen interactions in the context of T-cell/APC contacts. Our goal was to decipher calcium signals arising from cellular contacts and requiring imaging approaches. We chose to perform all recordings on a conventional argon laser equipped-confocal scanning microscope, widely found in laboratories. Considering the lack of available methods [44] able to combine automatic tracking of cells and calcium signal processing, we set up our own procedure to automatically track moving cells at high densities with a minimum of input parameters. It is a customized version of our previously developed MTT algorithm [32], originally dedicated to tracking single fluorophores coupled to plasma membrane molecules at high density. We built a plugin that converts cellular images into cell position images that are comparable with the single molecule images supported by MTT (Figure 2A & Figure S2). Raw fluorescence images were first passed through a median filter to eliminate the electronic noise emanating from detection and an appropriate mask, consisting of a disk of adequate radius (see Materials and Methods for details on mask size), was applied to identify cells as single objects. Each cell was thus defined by the xy coordinates of its centroid which then served to reconstruct the cell' s trajectory over the stack of images (Figure 2A & Videos S1, S2, S3, S4, S5, S6, S7). Noteworthy, more complex cellular shapes could be handled if using other appropriate detection schemes. Next, we generated synthetic images containing Gaussian peaks at the corresponding positions, with a radius optimized for the tracking performed by MTT and an intensity equal to the integrated cell signal, itself proportional to the intracellular calcium concentration. The resulting sequence of single molecule like images could then be treated by MTT (Videos S5, S6). Replacing each cell by a Gaussian peak of smaller size prevented the occurrence of two targets crossing over each other, initially a major concern for MTT, thus rendering the reconnection of traces during the MTT procedure far more efficient. Overlapping was then handled at the detection stage, where crossing cells presenting as a “peanut” shape were detected as two targets. However, strongly overlapping cells resulting in more of a spherical shape were detected as a single target and thus required z-stack acquisitions and appropriate analysis to recognize the occurrence of such crossing trajectories. MAAACS generates traces which are defined by the position of the detected cells over time and intrinsically calculates their instantaneous velocity and their fluorescence intensity. Given that the basal level varies from cell to cell due to differences in intracellular calcium concentrations, or due to heterogeneous efficiency in calcium indicator loading, we needed to accurately set a baseline of fluorescence that we defined as the median of fluorescence calculated until the maximum fluorescence value had been reached for each cell (Figure 2B). To establish the best mode of normalization, we analyzed for each cell in non-stimulating conditions how the mean signal amplitude was correlated with signal fluctuations. We found that this relationship was proportional, thus implying that the normalization can be performed by division. Calcium responses are highly diverse, both in terms of magnitude and oscillation (Figure S3). The amplitude of calcium mobilization varies according to the type of stimulus and the addition of inhibitors, but also within a cell population for a given stimulus/treatment. Moreover, the shape of these signals, their maintenance and their oscillations are also varied. We therefore defined analytical parameters to describe and characterize these response diversities (Figure 2C). For each cell, the response magnitude is described as the fluorescence amplitude (FA) of calcium mobilization, corresponding to the time-average of normalized intensities on the whole trace. The temporal fluctuations are deciphered by analyzing the persistence and the oscillations of the calcium signals. We defined as the response fraction (RF) the ratio of two phases: the time when the normalized intensity is greater than the threshold over the total time during which the intensity is detected. We also calculated the number of bursts/min (BPM) defining the number of peaks detected above the threshold divided by the duration of the detected trace (Table S1). In order to provide a global, comprehensive view of the calcium response in a substantial number of cells for any given condition, we color coded the normalized calcium intensities with a gradient of blue and orange for values below or above the threshold (see below), respectively. The resulting values, for each cell at each time-point, could then be pooled to generate a heat map, the dimensions of which hence corresponded to the cell number and time (Figure 2C left panel). Non-relevant pixels, either before or after detection of a given cell in the time-lapse movie, were left in black. This representation simultaneously depicts the global tendency, together with the intra-population variability of response [45]. Collectively, all calcium signal parameters are summarized on scatter dot plots where responding cells are represented by a single dot (Figure 2C right panel). By integrating these different parameters, the heterogeneous behavior of activated cells (maintained, oscillatory and unique) can be determined and inactive cells identified, the proportions of which are then represented in a pie chart diagram (see Materials and Methods for details on the classification). An endemic problem in automatic tracking approaches is reaching a level of completeness that manual tracking only can guarantee. We analyzed several videos in parallel by the automatic and by manual methods and determined the percentage of cells tracked by MAAACS compared to that by manual tracking in the observation field (detection percentage). 3A9 T cell hybridomas or naive CD4+ T-cells loaded with BD PBX were seeded onto a monolayer of COS-7 cells stably expressing the molecules of the major histocompatibility complex [46]. We chose experimental situations with high cell densities on a rough and irregular surface. We only considered tracked cells detected by MAAACS over more than 5 images. The superimposition of the trajectories obtained manually or with MAAACS (Figure 3A) illustrated the efficiency of our algorithm, the detection percentage of which was greater than 96% (N = 125). Surprisingly, more traces were generated by MAAACS than obtained manually. Consequently, the MAAACS cell traces were fragmented into several parts as shown in Figure 3B illustrated by the number of fragments needed to reconstitute the full length trajectories (1. 3 for primary T cell and 1. 9 for hybridomas, Figure 3B). The lower efficiency for the latter can be explained by significant cellular shape changes over time preventing their detection by the circular mask and thus their reconnection. To fully document the cell response over time and to improve the quantitative analysis of cell signaling, we implemented a program allowing the reconnection of fragments of trajectories (Figure 3C). First, the method selected among the set of trajectories terminating before the end of the acquisition (plotted in gray in Figure 3C) to be reconnected to traces starting after the breaking off (plotted in red and blue in Figure 3C). Then the algorithm classified the candidates for reconnection by minimizing the interval between the stop and start times (Δt), the distance between the final and initial positions (Δr) and the difference of the mean fluorescence amplitude of the fragments (ΔI). The user is free to decide whether the trajectories should be reconnected by consulting the original video. In this way, the tracked time percentage was clearly improved (95% for primary T cells and 83% for hybridomas, Figure 3D). Within the course of this study, we noticed that without specific stimulation, cytoplasmic calcium concentrations displayed spontaneous oscillations, the amplitude of which was almost negligible for T cell hybridomas but not for primary naive T cells [13]. To account for this, we performed a median filtering with a sliding window of 7 frame-size on each fluorescence amplitude to remove aspecific oscillations in the absence of any stimulus. It was then important to carefully define the threshold of peptide-specific activation. As mentioned by many authors [26], [42], [47] and in our observations (Figure 3), calcium signaling exhibits high diversity even within the same cell line and depends on the applied perturbations (stimulation, drug treatment or mutation). It should be noted that defining any biological threshold for activation could be misleading since it is highly dependent upon the experimental conditions. Moreover, the definition of a criterion for specific activation should respect the response heterogeneity without favoring a subset of responding cells. Accordingly, we set up a detector which compares the fluorescence amplitude to a threshold of activation in order to identify activated cells in our experiments (Figure S4). If the fluorescence amplitude is greater than the threshold, then the cell is declared as activated. To determine this threshold, we investigated the statistical properties of the fluorescence amplitude of cells in the absence of any stimulation compared to that in cells that have been activated as a result of stimulation. For a given probability of false alarm (PFA), an activation threshold could be deduced from the cell responses in the absence of any stimulation. The probability of detection (PD) could then be calculated as the percentage of activated cells revealed by the detector. We then aimed to identify threshold values that minimized false detections (low PFA) without decreasing the identification of activating cell (high PD). A robust method to objectively determine the activation threshold is to perform a receiver operating characteristic analysis (ROC curves in Figure S4A, B) to explore the values of activation threshold that maximize the overall score PD x (1-PFA). All activation thresholds are reported in Figure S4C. Surprisingly, the activation threshold was quite stable whatever the cell type (hybridoma or naive T cells) or stimulation process (antibody or APC). For T-cell hybridomas, this method exhibited very high PD (>0. 99) and low PFA (<0. 02). PD was also high in primary T cells (>0. 98) and the PFA was reasonable (<0. 08) though slightly higher due to a higher diversity in the cell signaling. To test our MAAACS algorithm, we analyzed a population of T hybridomas 3A9 loaded with BD PBX and seeded at the bottom of a well of a Lab-Tek before their stimulation with thapsigargin after 1 minute. We generated a sequence with a frequency of 1 confocal image every 7 seconds for 30 minutes. Fluorescence intensity was not affected by repetitive illuminations as previously mentioned (Figure S1B). No a priori assumption was made and raw recordings were subjected to MAAACS. To compare the calcium signals, we normalized the fluorescence intensities as a fold of the basal fluorescence. A mean curve of variations in fluorescence over time was obtained (Figure 4C) and compared to flow cytometry measurements (Figure 4B). Fluorescence rose immediately after thapsigargin addition, reaching a plateau 3 minutes after induction [48] before slowly decreasing (Figure 4C). This response was fully stackable with the kinetics monitored by flow cytometry (Figure 4B). We noted that the response/baseline ratio was higher according to imaging recordings, presumably due to a better sensitivity of detection on confocal photomultipliers. In this case the benefit of MAAACS is limited since all individual cells responded homogenously by a strong, sustained non-oscillating response (fluorescence amplitude, FA = 7. 93±0. 50; response fraction, RF = 0. 91±0. 02; bursts per minute, BPM = 0. 04±0. 001). In the presence of the CRAC channel blocker 2-aminoethoxydiphenyl borate (2-APB) [49], thapsigargin induced a weak elevation of fluorescence that was similar to Ca2+/Mg2+ deficient incubation conditions [48] (Figure 4A) and consistent between the two methods (Figure 4B, C). The analysis of the global tendency clearly masked the singularity of each individual cell. Through MAAACS analysis, while 50% of the cells displayed a unique rise of fluorescence as the average tendency would have suggested, the other half was equally composed of cells displaying sustained or oscillatory behavior. This implies that within a cell population and for any given stimulus, the observed differences in response are not limited to intensity dispersion but also to the mode of response. We sought to document this point using different experimental stimuli each producing their own calcium response in terms of shape, intensity and heterogeneity (Figure 5) [50]. Indeed, when the cells were seeded onto an activating surface (anti TCR antibody coated pits), while most responses were sustained (FA = 4. 4±0. 43, RF = 0. 62±0. 03, BPM = 0. 09±0. 01), heterogeneous responses were also observed. These heterogeneities were even more obvious when the 3A9 cells were stimulated by I-AK-HEL expressing COS-7 APCs. The asynchronous landing of the T cells and the heterogeneous MHC II agonist peptide expression levels are parameters that affect the calcium response in addition to irregular crawling and scanning activities of the T cells on an APC monolayer. Indeed, during the first 30 minutes, 50% of the cells displayed a specific calcium rise [15]. Most of these exhibited a maintained fluorescence amplification but which was weaker in term of intensity and response fraction as compared to that in response to the stimulating antibody (Figure 5C), supporting the notion that abundant, immobile, highly affine ligands are not strictly recapitulating the stimulation by the natural membrane ligand of the TCR. Supporting this view, we analyzed the cell motility by MAAACS, as an integral parameter of T cell activation [29], [42], [51]. MAAACS analysis of cell velocity showed that inducers of strong and sustained calcium responses (thapsigargin or anti TCR coated slides and to a lesser extent anti CD45 unstimulating surfaces) negatively impacted the motility of cells [12], since instant speed measurements did not exceed 2 µm/min in the few minutes after landing on the slide, indicating that the cells were almost immobile. In contrast, T-cells migrating on COS-7 I-AK-HEL displayed higher velocities (unactivated: 5. 1±2. 4 µm/min; activated: 3. 7±1. 2 µm/min) with a high mobile fraction (unactivated: 0. 48±0. 17; activated: 0. 56±0. 16). These velocities are fully consistent with 2-photon-microscopy measurements (Figure S5), where migratory T cells in lymph nodes, or thymus slices display mean velocities around 4 µm/min [9], [28], [52]–[54] or stimulating lipid bilayers [55]. Although experimental, COS-7 I-AK-HEL have been shown to efficiently simulate physiological situations of T cell activation by inducing productive calcium signals, in a context of immunological kinapses [56], [57] rather than stable immunological synapses leading to specific cytokine secretion such as Interleukin-2 (data not shown). Additionally, as previously demonstrated, a clear correlation exists between activation and motility since unactivated T cells appear to move faster than activated ones within the same population [58] and T cell hybridoma mobility appears to decrease rapidly after calcium rise and rounding of the cells [10], [12] (Figure S6A). MAAACS was conditioned to automatically analyze the velocity and shape of the cells in addition to fluorescence signals, although no link between these parameters was found that was as tight as previous reports in cell systems expressing co-stimulatory or specific adhesion molecules. In the presence of 2-APB, the fluorescence amplitudes upon either anti TCR (FA = 3. 26±0. 24) or COS-7 I-AK-HEL stimulation (FA = 1. 56±0. 06) were strongly reduced compared to CRAC active control conditions. However, although the response fraction and the number of bursts per minute were left unaffected (RF = 0. 56±0. 03, BPM = 0. 09±0. 02) (Figure 5C) upon anti-TCR T cell activation, short and low calcium oscillations [26] were predominant in most T-cells (RF = 0. 26±0. 01, BPM = 0. 14±0. 01) (Figure 5C and Figure S3B) seeded onto COS-7 I-AK-HEL. In this case, the lack of co-stimulatory or specific adhesion molecules that usually sustain T cell/APC interactions and signaling [59] suggested that following TCR engagement by MHC-peptide, signaling events would occur through waves such as displayed by the calcium oscillations [60]. We therefore titrated the TCR-dependent calcium signaling in the presence of 2-APB in T-cells as a function of the amount of peptide loaded onto COS-7 I-AK. As shown in Figure 6, the peptide-specific, 2-APB sensitive calcium response was dependent upon the amount of peptide presented by COS-7 I-AK. In the absence of peptide, about 5% of the cells displayed a weak but significant calcium response above threshold. The percentage of responding cells increased proportionally to the peptide concentration to reach a plateau at a HEL 46–61 peptide concentration of 50 nM (Figure 6A), while being constantly oscillatory (Figure 6E). The fluorescence amplitude of the responding cells was significantly higher than that observed in the absence of antigenic peptide, even at low antigen doses (down to 0. 5 nM). (Figure 6B) Surprisingly, the fluorescence amplitude, response fraction, and burst frequency were independent of the antigen concentration (except at higher antigen concentrations) (Figure 6B–D). These data show that, at least in 3A9 T cell hybridomas, the TCR-mediated antigen-dependent ER-store-operated calcium response is digitally triggered irrespective of the antigenic peptide concentration. This is consistent with results from an earlier study [42] focusing however on the global calcium responses in 3A9 T cells. The antigen-dependent calcium response of mouse primary T cells has previously been investigated in vivo by microscopy on explants or sections of lymphoid organs [9], [28], [53] or ex vivo on artificial activating surfaces [55]. However, most of these studies were performed on lymphoblasts obtained by continuous activation in the presence of IL-2 for several hours and which therefore differ from naive T cells [18], [47], [61]. Data from studies that have examined the calcium response of naive T cells suggest that the calcium homeostasis of naive CD4+ T cells ex vivo is complex and at least in part antigen-independent [13], [62]. We evaluated these calcium responses of T-cells with MAAACS (Figure 7). Naive 3A9 transgenic CD4+ T cells [63], [64] seeded onto a surface coated with anti TCR antibodies showed a strong increase in fluorescence (FA = 4. 61±0. 25) that was maintained over time (RF = 0. 71±0. 03, BPM = 0. 13±0. 01) similar to that observed with 3A9 hybridomas (Figure 7A, B, 5C). However, we also observed that when seeded onto non-stimulating I-AK expressing COS-7 cells, around 20% of naive T cells responded spontaneously with short weak calcium pulses (FA = 1. 23±0. 03, RF = 0. 13±0. 01; BPM = 0. 14±0. 01) reminiscent of those previously reported [13] and [9]. Peptide specific calcium signals in the presence of COS-7 I-AK-HEL were mostly oscillatory in more than 60% of the cells (FA = 2. 02±0. 09, RF = 0. 32±0. 02, BPM = 0. 22±0. 01), in contrast to those observed in hybridomas (Figure 7B) which were mainly sustained. Another fundamental difference with hybridomas is that we found no clear correlation between calcium fluxes and cell velocity (Figure S6B), which nevertheless was expected considering in vivo reports [65]. We then wondered whether these calcium responses in CD4+ naive T cells were sensitive to 2-APB. CRAC channel activity in T cells is characterized upon stimulation by thapsigargin or soluble anti-CD3 antibody (2C11), generating sustained calcium responses that are absent in patients suffering from an inherited form of severe combined immune deficiency (SCID) syndrome or upon 2-APB treatment [3] Indeed, upon 2-APB treatment, the thapsigargin-induced calcium response was drastically reduced. Equivalent kinetics (evaluated by flow cytometry) was obtained with 2C11 stimulation in the presence of 2-APB or EDTA (Figure S7A–B). No additive or competitive effect was detected under these experimental conditions (Figure 7C). In fact, 2-APB-treated naive T cells seeded onto anti TCR coated surfaces did show a calcium response (FA = 2. 00±0. 14, RF = 0. 32±0. 03, BPM = 0. 13±0. 01) that was greatly reduced compared to the native conditions without CRAC inhibitor (Figure 7A). More unexpectedly, 2-APB treatment did not induce a unique calcium peak suggesting that other calcium channels than SOCE mediate calcium entry in naive mouse T cells, since calcium oscillations are dependent upon calcium influx [66]–[68]. Similarly, we analyzed the calcium response to COS-7 I-AK-HEL in the presence of 2-APB. There was a moderate but significant decrease in the amplitude of the calcium response (FA = 1. 66±0. 07, RF = 0. 29±0. 01, BPM = 0. 16±0. 01) compared to conditions in absence of 2-APB, together with a slight decrease of the oscillation frequency (Figure 7A–C). In addition 2-APB on naive T-cells seeded onto COS-7 I-AK did not show any significant impact on calcium fluxes (FA = 1. 28±0. 05, RF = 0. 13±0. 02, BPM = 0. 15±0. 02), remaining lower to the calcium response in presence of antigenic peptides. Altogether upon blockade of the CRAC channel activity by 2-APB, we evidence that the SOCE dependent calcium entry plays a limited role in mouse naive T-cells upon TCR triggering by-MHC-peptide.
The first aim of this study was to significantly increase the sensitivity, accuracy, completeness and statistical reliability of video-microscopy approaches to record calcium fluxes, by combining a strong calcium probe with a robust algorithm for high density cell tracking coupled to an automated interface for rigorous post-acquisition analysis. The second objective was to use this method to describe the characteristic parameters of intracellular calcium fluxes within a population of T cells in response to different stimuli. We highlighted the heterogeneous nature and dynamics of these fluxes after TCR engagement by its natural ligand in a cell/cell context, which cannot be documented by flow cytometry. The TCR-MHC-peptide is a paradigm for unconventional intercellular receptor-ligand interaction [69] based upon successive cycles of engagement/release [16], [17]. However, more functional data supporting this current view are needed, taking care to account for the free motility of cells prospecting for cognate antigens supported by MHC molecules in a 2D cell membrane environment. Our goal was to develop experimental tools to contribute to the understanding of these mechanisms. The first challenge was finding a bright and stable fluorescent calcium probe in the visible range of the spectrum and that was easy to monitor both by cytometry and on conventional confocal microscopes. T cells dedicated to calcium imaging are usually loaded with calcium indicators the emitted fluorescence of which is UV-shifted upon calcium elevation thus allowing ratiometric measurements (such as Fura-2). The sensitivity of these probes can however be impacted by their intracellular compartmentalization (adsorption by proteins, interaction with membranes or sequestration by organelles e. g. mitochondria), or their extrusion by organic cation transporters. To overcome these technical issues, loading can be performed with diluents (pluronic acid) or transporter blockers (probenecid), although these compounds can be noxious to T-cells and thereby affect their response [38]. Despite these potential drawbacks, Fura-2 loaded T cells are routinely used for long experimental procedure followed by transcriptomics without limitations by reduced cell viability [25]. In our study, cells loaded with BD PBX were used over extended periods of time without any evidence of mortality, compartmentalization, or photobleaching which have been reported to affect Fluo-4 AM use [34]. Although they could be considered as anecdotic or trivial, such properties enable more reproducibility and the use of BD PBX in a greater number of experiments compared to other fluorescent visible probes. Our here proposed MAAACS method incorporates our previously reported MTT algorithm dedicated to single particle tracking [32] and nanoscopy [70], [71] set up to enable the detection, monitoring and reconnection of trajectories of moving T cells acquired by conventional confocal microscopy. The ability to simultaneously track a great number of targets is in itself a challenge but in particular encounters difficulties when tracks are interlaced or crossing over. The performance of MTT was found to be slightly superior compared to existing algorithms however the implementation of a program of assistance proposing candidate traces to be reconnected to aborted traces was a major breakthrough in terms of improving the accuracy and completeness. In addition, during the analysis process, MAAACS enabled the rejection if necessary of dead or dividing cells. Consequently, while MAAACS is not yet a fully unsupervised method, we speculate that 3D time lapse video-acquisition methods (on a spinning disk confocal microscope, for example) would greatly reduce the number of aborted traces due to focus loss that occurs on a 2D+time acquisition scheme such as that in this study (in particular for primary T cells). Completeness is a major issue in this kind of study, since the baseline calculation could be under-estimated or incorrect when the first time points after cell landing are missing. Here, the automated normalization of calcium signals facilitates their comparison among a population of cells. The MAAACS analysis makes simple the analysis and, more importantly, the quantification of signaling. MAAACS deciphers a video sequence in about 10 minutes, where manual tracking and analysis would take at least 2 hours (depending on the duration of the time lapse and the number of cells). Video microscopy records the behavior of individual cells over time and not just part of a population of anonymous cells. This allowed us to demonstrate that calcium oscillations are highly diverse among cells [15] both in terms of intensity and frequency; they are mostly transient oscillations in primary T cells in contact with antigen loaded APCs. This diversity in cell responses supports the notion that T-cell triggering is stochastically linked to heterogeneity in the T cell population [50]. This is conceivable for T-cell clones due to genomic drift, but may seem more surprising for primary CD4+ T cells. Literature reports that oscillatory calcium fluctuations are associated to effector function of T cells and proliferation [21] in contrast to memory T cells which display unique increases in calcium [72]. In addition, sustained calcium responses are observed mainly in apoptotic T cells [73]. Altogether, our approach would be able to reveal in a seemingly homogenous population, T cell diversity in terms of function or fate, based upon antigen dependent calcium response mode. Another interesting finding is that CRAC channel dependent activity does not support a sustained calcium response in naive T cells encountering APCs, and that the predominant calcium response modes in T cells are oscillations, in agreement with literature [5], [9], [25], [74], at least in part sensitive to 2-APB blockade. This result supports recent works showing an intriguing role of voltage dependent Ca2+ channels (Cav1. 4) [66]–[68] in the calcium influx into naive T cells. Our results also suggest that membrane calcium channel openings are tightly correlated to ER-calcium waves upon TCR triggering [75], [76], and that sustained calcium fluxes such as those triggered by stimulating antibodies and revealed by flow cytometry or video imaging are not strictly physiologic, at least not in naive T-cells. It could be valuable to consider our results in the light of recent evidence suggesting a role for cytoplasmic calcium sustained elevation in the orientation of the cytoplasmic domains of the CD3 chains of the TCR/CD3 complex upon activation [77]. As a major conclusion, the introduction of MAAACS emphasizes the urgent need to record the effects of cell-to-cell stimuli using real-time videos. We believe that MAAACS holds huge scope that could be easily adapted to study various kinds of targets (such as Qdots, vesicles, cells, animals) based on various types of emitted signal, however one immediate application would be to compare our in vitro results to 2-photon imaging of calcium indicator-loaded T cells migrating in lymph nodes [53], [65].
2-Aminoethoxydiphenylborate (2-APB) (10 µM final concentration used for hybridomas, 20 µM for naive T cells) and thapsigargin (1 µM final concentration) were purchased from Calbiochem, and Ionomycin (0. 1 µg/mL, final) from Sigma. The PBX calcium assay kit, the antibody against CD3ε (clone 145-2C11) (6. 5 µg/ml, final), 2C11 biot (10 µg/mL final) and the F23. 1 anti-TCR Vβ 8 1-3 antibody (10 µg/mL, final) were supplied by Becton Dickinson. The mitochondrion label, Mitotracker red CMX-Ros, and the calcium indicators Indo-1 AM, Fluo-4 AM and Fura Red AM were supplied by Life technologies (Molecular probes). Streptavidin (5 µg/mL) was supplied by Jackson Immunoresarch. C4H3 (anti I-Ak-HEL), GK1. 5 (anti CD4), and H193. 16. 3 (anti CD45) (10 µg/mL, final) monoclonal antibodies were produced and purified in the lab from hybridoma supernatants according to standard protocols. 3A9 hybridoma T CD4+ cells are specific for hen egg lysozyme peptide (HEL) bound to MHC II I-Ak molecules [78]. These cells were cultured in RPMI medium supplemented with 5% FCS, 1 mM sodium pyruvate and 10 mM Hepes. COS-7 cells were cultured in DMEM medium with 5% FCS, 1 mM sodium pyruvate and 10 mM Hepes. Experimental antigen-presenting cells (APCs) were generated by stably transfecting COS-7 cells (Amaxa, V solution, A024) with plasmid cDNAs coding for the α chain of MHC II and the β chain of MHC II I-AK alone or covalently fused to a peptide derived from HEL (provided by D. A. Vignali) [46]. Cells were sorted according to their positivity to surface labeling by C4H3 antibodies (Facsvantage, Becton Dickinson). APC monolayers were generated by seeding 5. 5 104 cells into poly-L-Lysine-coated 8-well Lab-Tek chamber (Nunc). Spleens and lymph nodes were recovered from CBA/J x C3H non-transgenic mice and 3A9 TCR transgenic mice [63], [64]. After the extraction of cells onto nylon membrane in DMEM F12 medium (Lonza), splenic erythrocytes were removed via NH4Cl lysis. CD4+ T cells were isolated by depleting the CD4 negative cells according to manufacturer instructions (Dynal Mouse CD4 Negative Isolation Kit, Invitrogen). The day before experiments, cells were overnight serum starved in DMEM-F12 medium supplemented with 1% of Nutridoma-SP (Roche). For COS-7 transfected by plasmid cDNAs coding for the α and β chains of MHC II (I-AK), HEL peptide was added to the culture medium the day before the experiment. Coated surfaces were obtained by incubation with the appropriate concentration of antibody 24 h before the experiment at 37°C. Cells were analyzed on a LSR I flow cytometer (Becton Dickinson) with Cell Quest software or LSR II (for Fura Red/BD PBX and Indo-1 AM acquisitions) using the FACSDiva software. PBX calcium indicator was observed over time on the FL1 channel with an excitation by an Argon laser 488 nm and a 530/30 nm emission filter at 37°C, maintained using a water bath. Data analysis was performed with FlowJo software and the median intensity of fluorescence was plotted vs. time after exclusion of dead cells and cell debris. Movies were made on a Zeiss LSM 510 Meta confocal microscope equipped with a 30 mW argon laser (25% output, 1% AOTF). Pictures were taken with a C-Apochromat 40×/1. 2 water immersion objective, using the 488 nm line of the argon laser, HFT UV/488 dichroic mirror and a 505 nm long pass filter at 37°C, maintained using a hot plate. Time-lapse movies were composed of 300 images (512×512 pixels; 8 bit; 225 µm×225 µm; pinhole set to 3 airy units) taken every 7 seconds. Additional observations were performed on an Ultraview VoX Perkin Elmer spinning disk confocal microscope. All scripts, including multiple target tracking (MTT) [32], were developed under Matlab (The Mathworks). The source code of MTT, deposited at the Agence pour la Protection des Programmes, n° IDDN. FR. 001. 270021. 000 S. P. 2008. 000. 31230, is freely available for research purposes at http: //www. ciml. univ-mrs. fr/lab/he-marguet. htm. Cell tracking and automated analysis of cell signals with MAAACS can be done either in command line (directly in Matlab) or using a graphical user interface (GUI). While the GUI is more intuitive it is limited to the analysis of a single acquisition whereas the command line solution permits the sequential analysis of several video-acquisitions. Spectra of BD PBX and Fluo-4 AM were performed on the Cary Eclipse spectrofluorimeter (Varian). In vitro Kd determinations were performed using the calcium calibration kit (Life technologies) according to the manufacturer' s instructions. All statistical analyses and normality tests were performed using GraphPad Prism 5. 00. To determine the normality of the data, we performed a D' Agostino-Pearson normality test. Since not all our data were normally distributed, we used a non-parametric statistical test (two-tailed Mann-Whitney test with an alpha level of 5%). | The adaptive immune response to pathogen invasion requires the stimulation of lymphocytes by antigen-presenting cells. We hypothesized that investigating the dynamics of the T lymphocyte activation by monitoring intracellular calcium fluctuations might help explain the high specificity and selectivity of this phenomenon. However, the quantitative and exhaustive analysis of calcium fluctuations by video microscopy in the context of cell-to-cell contact is a tough challenge. To tackle this, we developed a complete solution named MAAACS (Methods for Automated and Accurate Analysis of Cell Signals), in order to automate the detection, cell tracking, raw data ordering and analysis of calcium signals. Our algorithm revealed that, when in contact with antigen-presenting cells, T lymphocytes generate oscillating calcium signals and not a massive and sustained calcium response as was originally thought. We anticipate our approach providing many more new insights into the molecular mechanisms triggering adaptive immunity. | Abstract
Introduction
Results
Discussion
Materials and Methods | 2013 | Barcoding T Cell Calcium Response Diversity with Methods for Automated and Accurate Analysis of Cell Signals (MAAACS) | 10,727 | 202 |
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There is an ultimate need for efficacious vaccines against human cytomegalovirus (HCMV), which causes severe morbidity and mortality among neonates and immunocompromised individuals. In this study we explored synthetic long peptide (SLP) vaccination as a platform modality to protect against mouse CMV (MCMV) infection in preclinical mouse models. In both C57BL/6 and BALB/c mouse strains, prime-booster vaccination with SLPs containing MHC class I restricted epitopes of MCMV resulted in the induction of strong and polyfunctional (i. e. , IFN-γ+, TNF+, IL-2+) CD8+ T cell responses, equivalent in magnitude to those induced by the virus itself. SLP vaccination initially led to the formation of effector CD8+ T cells (KLRG1hi, CD44hi, CD127lo, CD62Llo), which eventually converted to a mixed central and effector-memory T cell phenotype. Markedly, the magnitude of the SLP vaccine-induced CD8+ T cell response was unrelated to the T cell functional avidity but correlated to the naive CD8+ T cell precursor frequency of each epitope. Vaccination with single SLPs displayed various levels of long-term protection against acute MCMV infection, but superior protection occurred after vaccination with a combination of SLPs. This finding underlines the importance of the breadth of the vaccine-induced CD8+ T cell response. Thus, SLP-based vaccines could be a potential strategy to prevent CMV-associated disease.
Human cytomegalovirus (HCMV) contributes substantially to morbidity in immunocompromised individuals. Organ or hematopoietic stem cell transplant recipients, people infected with HIV and patients with lymphocytic leukaemia are particularly vulnerable to HCMV-associated disease [1]. Moreover, congenital HCMV infection of unborn and new born children can lead to severe and permanent neurological symptoms [2]. Although currently available antivirals for HCMV are able to decelerate viral progression, thereby reducing the odds for major side effects, they require prolonged treatment periods and are accompanied with significant toxicity. Adoptive transfer of HCMV-specific T cells is an alternative treatment modality but is costly and laborious. The apparent burden of HCMV-associated disease and the paucity of cost-effective measures without side-effects have led to major efforts to develop effective HCMV vaccines but unfortunately no licensed vaccines are currently available [3,4]. There is accumulating evidence that effective control of persistent viral infections requires the induction of a balanced composition of polyfunctional T cell responses [5]. T cell immunity against CMV plays a critical role in controlling the primary viral infection and latency [6]. Whereas CMV-specific CD4+ T cells are important during the primary infection phase, CD8+ T cells are associated with greater benefits at the persistent infection phase and confer superior protection during reactivation and re-exposure [7–9]. Upon CMV infection, extra-ordinary large CD8+ T cell responses of diverge phenotype arise. CD8+ T cell response kinetics specific to most antigens follow the traditional course comprised by expansion after antigen encounter, rapid contraction, long-term maintenance at low levels and acquisition of a central-memory phenotype. Interestingly, CD8+ T cell responses to certain CMV antigens do not dwindle post-infection but inflate and exhibit a polyfunctional effector-memory phenotype [10–13]. In immunocompromised hosts, the balance between CMV and cellular immunity is apparently underdeveloped or lost, and therefore instigating the development and/or restoration of the T cell compartment specific for CMV would be particularly informative. The overarching aim of this study was to test a potential prophylactic vaccine platform against CMV based on synthetic long peptides (SLPs) containing immunodominant T cell epitopes. Previously, we reported that in therapeutic settings SLP-based vaccines can be successfully designed to stimulate effector and memory T cells against human papilloma virus-associated disease in mice and human [14–16]. As the efficacy of SLP-based vaccines is directly linked to the phenotypical and functional characteristics of the vaccine-induced CD8+ T cell response, we rigorously evaluated SLP-induced T cell responses. MCMV-specific SLP vaccines, assessed in two different mouse strains (C57BL/6 and BALB/c mice), lead to strong polyfunctional T cell responses, and combined SLP vaccines targeting different antigens provide a successful vaccine modality to control MCMV infection.
To assess the potential of SLP-based vaccines in eliciting protecting CD8+ T cell responses against MCMV infection, we designed SLPs containing immunodominant MHC class I T cell epitopes from MCMV encoded proteins, and evaluated this vaccine platform in two different immunocompetent mouse strains with different susceptibility to MCMV; the C57BL/6 strain (MHC haplotype H-2b) and the more MCMV-susceptible mouse strain BALB/c (MHC haplotype H-2d) (S1 Table). C57BL/6 mice are less susceptible to MCMV infection compared to BALB/c mice because C57BL/6 mice express the NK cell-activating receptor Ly49H, which recognizes the MCMV protein m157 at the surface of infected cells [17–20]. Mice were vaccinated subcutaneously with SLPs along with the TLR9 ligand CpG as adjuvant. The SLP vaccine administration was well tolerated without adverse events. At day 7 after SLP immunization, epitope-specific CD8+ T cell responses were detected in the blood but a booster vaccination was required for induction of vigorous CD8+ T cell responses (Fig 1A and 1B). Prime-boosting with SLP vaccines induced very high frequencies of circulating CD8+ T cells against the noninflationary epitopes M45985-993 and M57816-824 in C57BL/6 mice, and were even higher than the percentages of the circulating MCMV-induced CD8+ T cells at the peak of infection (day 7). Also the response against m139419-426, known to be non-inflationary during the early phase after MCMV and at later time points as inflationary, is strong. The response against the non-inflationary M45507-515 epitope in BALB/c mice was even much higher in the SLP-vaccinated group as compared to the MCMV infected mice. The frequencies of the circulating CD8+ T cells against the inflationary M38316-323 and IE3416-423 epitopes in C57BL/6 mice and the inflationary m164257-265 and IE1168-176 epitopes in BALB/c mice were comparable (Fig 1A and 1B). SLP vaccines containing MHC class I epitopes may comprise unidentified class II epitopes and linear B cell epitopes leading to CD4+ T cell and antibody responses. To exclude this possibility, we performed polychromatic intracellular cytokine staining with the SLPs and performed SLP-specific antibody ELISAs, respectively (S1 and S2 Figs). Neither MCMV-specific CD4+ T cells nor peptide specific Abs were detected in these assays, indicating that the designed SLPs lead exclusively to antigen-specific CD8+ T cell responses and that epitope-specific responses induced by SLP or MCMV can only be compared for CD8+ T cells. Longitudinal analysis of the antigen-specific CD8+ T cell responses revealed that all SLP-induced T cell responses in both mice strains contracted gradually over time after the booster immunization (Fig 1B). Two months after the booster vaccination, the SLP-induced responses to most epitopes were still clearly detectable in blood. During MCMV infection, the epitope-specific CD8+ T cell responses followed a different course, consistent with previous reports [10,11]. T cell responses to the non-inflationary epitopes M45985-993, M57816-824, and M45507-515 rapidly contracted after the peak response and were stably maintained in time while T cell responses to the epitopes M38316-323, m139419-426, m164257-265, IE1168-176 and IE3416-423 inflated (Fig 1B). These data indicate that the context of epitope expression determines the kinetics of the T cell responses, which is uniform for diverse epitopes after SLP vaccination but in the case of MCMV infection this results in a dichotomy of responses related to the chronic nature of this infection. At the peak after the booster SLP immunization (day 7–8), high frequencies of epitope-specific CD8+ T cells, analogous to the responses elicited by MCMV virus were observed in the spleen (Fig 1C). However, in absolute numbers, MCMV infection led to a higher T cell magnitude compared to SLP vaccination, which can be attributed to virus-associated inflammation leading to splenomegaly. At the memory phase (day 60), MCMV-specific T cell responses to the non-inflationary epitopes were significantly lower than the equivalent SLP vaccine-induced responses (Fig 1C). The MCMV-induced CD8+ T cell responses to the inflationary epitopes were of higher magnitude compared to those induced by SLP vaccination. Taken together, these results show that prime-boost vaccination with SLP vaccines containing MHC class I MCMV epitopes elicit in mouse strains with different susceptibility to MCMV high percentages of effector and memory CD8+ T cells that contract gradually in time. Next, we aimed to dissect the underlying mechanisms of the relatively low responses to some of the SLPs (i. e. M38 and IE3 in C57BL/6; M45 in BALB/c) compared to the other. First, we endeavoured to alter the SLP sequences by altering the C-terminal cleavage, which may improve the immunogenicity (S3 Fig). However, the altered M38316-323 SLP did not exhibit a significant improvement in the SLP-induced T cell response whilst the altered SLP containing the IE3416-423 epitope elicited responses that were actually reduced. Then we questioned if the differences in the magnitude of the T cell responses triggered by the various single SLP vaccines might be related to the functional avidity of the T cells, which is determined by the affinity of the peptide for MHC and the TCR affinity for the peptide-MHC complex (Fig 2A and 2B). The SLPs elicited T cells with different levels of functional avidity but no correlation was found with the strength of the CD8+ T cell response. Moreover, in both C57BL/6 and BALB/c mice the functional avidity of the T cells, elicited either by SLP vaccines or MCMV infection, were remarkably similar and remained stable in time as they were similar during the acute and memory phase of response. Thus, differences in TCR affinity are not involved in the observed difference in the magnitude of the T cell responses. The data presented above illustrated that factors other than peptide-MHC/TCR affinity are implicated in shaping the strength of SLP-induced T cell responses. Recently, it was shown that the precursor frequency of naive T cell populations can predict the immunodominance hierarchy of viral epitope specific CD8+ T cell responses [21]. To test whether the precursor frequency is predictive for the magnitude of SLP-induced T cell responses we determined the precursor frequency of all the epitopes included in this study in naive C57BL/6 and BALB/c mice (Fig 2C). In C57BL/6 mice, the precursor frequencies for the M45985-993 and M57816-824 epitopes were among the highest followed by the precursor frequencies to the m139419-426 epitope. The lowest precursor frequencies were detected to the M38316-323 and IE3416-423 epitopes, confirming a previous report [22]. In BALB/c mice, the highest precursor frequencies were observed for the m164257-265 and IE1168-176 epitopes whereas the frequency of M45507-515 specific T cells was lower (Fig 2C). Markedly, the average level of the precursor frequency of each epitope-specific CD8+ T cell population was proportional to the expansion of the antigen-specific populations found in mice following either SLP immunization or MCMV infection. Together, these results indicate that naive precursor frequencies rather than TCR avidity determine the magnitude of SLP vaccine-mediated CD8+ T cell responses. To assess the phenotypical and functional quality of MCMV-specific CD8+ T cells induced by either the SLPs or the virus, we determined the formation of the diverse T cell subsets that develop after antigenic challenge. Early after the booster, SLP vaccination resulted in the induction of a highly activated CD8+ T cell subset exhibiting an effector-like phenotype (CD62Llo, CD44hi, CD127lo, KLRG1hi), which completely resembled the MCMV-specific T cell phenotype during the acute phase of the infection (Fig 3A and 3B). In the memory phase, both SLP- and MCMV-induced T cell phenotypic traits diverged (Fig 3C and 3D). All SLP-induced CD8+ T cells exhibited a fairly mixed phenotype sharing features of both central-memory T cells (CD62Lhi, CD44lo, CD127hi, KLRG1lo), effector-memory T cells (KLRG1hi, CD44hi, CD127lo, CD62Llo) but also an intermediate phenotype (i. e. KLRG1hi, CD127hi). As expected, during MCMV infection, the non-inflationary M45985-993, M45507-515 and M57816-824-specific CD8+ T cells gained a predominant central memory-like phenotype while the inflationary M38316-323, m139419-426, IE3416-423, m164257-265 and IE1168-176-specific T cells appeared mostly effector-memory like. To assess the cytokine profiles of the SLP-induced CD8+ T cells, we performed intracellular cytokine staining for IFN-γ, TNF and IL-2 and compared these to MCMV-induced T cells. At the peak response after booster vaccination, SLP-induced T cells consisted mainly of single IFN-γ and double IFN-γ/TNF producing populations (Figs 4A and S4). The cytokine producing traits of the MCMV-induced effector CD8+ T cells matched in general with the SLP-elicited T cells. Except relatively more single IFN-γ producing CD8+ T cells after MCMV infection compared to SLP vaccination were found in the T cell populations reactive to the epitopes IE3416-423, IE1168-176, M45507-515 and m164257-265. At the memory phase, the SLP-specific CD8+ T cells gained the ability to co-produce the three cytokines, at the expense of single cytokine producing cells (Figs 4B and S4). This gain in triple cytokine production (IFN-γ/TNF/IL-2) during MCMV infection is mainly observed in the non-inflationary CD8+ T cells. Both during the acute and memory phase, the percentage of the total CD8+ T cell population producing IFN-γ, either in case of SLP vaccination or MCMV infection, corresponded to the percentage of MHC class I tetramers, indicating full differentiation of the elicited T cells. A hallmark of memory T cells is the ability to undergo secondary expansion upon antigenic challenge [23]. To assess this property of vaccine-induced memory T cells, we performed adoptive transfer experiments in which congenically marked (CD45. 1+) memory M45985-993 and m139419-426-specific CD8+ T cells from SLP vaccinated and MCMV infected mice were isolated and transferred into naive recipient mice, which were subsequently challenged with MCMV (Fig 5). SLP-induced M45985-993 and m139419-426-specific T cells expanded; albeit to a lesser extend as compared to the MCMV-induced (Fig 5). The MCMV-elicited M45985-993-specific T cells exhibited, corresponding to their central-memory phenotype, a superior capacity in expansion as compared to the MCMV-elicited m139419-426-specific T cells with an effector-memory phenotype. Of note, the expansion of the SLP-induced M45-specific T cells was comparable to the m139-specific T cells induced by MCMV, although the phenotype of SLP-induced cells were more central-memory like. This indicates that the instruction that T cells receive in different settings can result in cells with a different expansion potential despite a seemingly similar phenotype based on markers for central/effector memory cells. All together we conclude that SLP-based vaccines induce a heterogeneous pool of memory T cells with a secondary expansion potential that is somewhat lower as compared to memory T cells elicited by virulent virus. The various SLP vaccine formulations were evaluated for their capacity to confer protection against MCMV challenge (at day 60 after booster vaccination). In C57BL/6 mice, the viral load of unvaccinated (naive) mice challenged with MCMV was found to be significantly higher in spleen, liver and lungs, when compared to the viral load of MCMV re-challenged mice that successfully controlled a previous MCMV infection, indicating that pre-existing immunity to MCMV can clearly reduce the viral load upon re-infection (Fig 6A). All the different SLP vaccines resulted in a reduction in viral load in the spleen compared to unvaccinated mice, albeit less effective when compared to MCMV infected mice. Mice vaccinated with the SLPs containing the M38316-323 and m139419-426 epitopes display a significant reduction in viral titres in the liver and lungs. Also, the M57816-824 and IE3416-423 epitope containing SLPs were capable in reducing the viral replication in the liver after MCMV challenge, albeit to a lesser extent (Fig 6A). Re-challenge of MCMV infected BALB/c mice resulted in substantial protection of the m164257-265 epitope containing SLP vaccine in spleen and liver (Fig 6B). The M45507-515 and IE1168-176 epitope containing SLPs however did not induce protective immunity in vaccinated mice. These results indicate that certain SLPs but not all have the potency to elicit protective immunity against virus challenge, and that this protection is not necessarily correlating to the size of the SLP-induced CD8+ T cell response. Since vaccination with the m139419-426 and M38316-323 epitope containing SLPs was accompanied with some reduction of the viral load, we examined in C57BL/6 mice whether vaccination with these two, or even more, SLPs combined is able to exceed the protection efficacy of single SLP immunization. Strong and long-lived peptide-specific CD8+ T cell responses were measured in mice vaccinated with the mixture of the m139 SLP plus the M38 SLP and with a mixture of all 5 SLP vaccines (Fig 7A). Notably, the T cell response against each peptide epitope with the combined SLP vaccines was lower as compared to single SLP vaccination (except for the m139-specific response), indicating that competition among antigen-specific CD8+ T cell populations can occur in multivalent vaccines. Especially, altered were the responses to the epitopes in M57 and IE3 because these were not boosted (Fig 7A). Such competition among T cells during boosting has also been observed after viral infection [24]. The kinetics of the combined SLP vaccine-induced T cell responses was found to be similar to single SLP vaccines, and the phenotype (Fig 7B) and cytokine polyfunctionality of the T cells as well (S5 Fig). At day 60 post booster vaccination, mice were challenged with MCMV and 5 days later viral titres were measured in different organ tissues. The efficacy of the combined SLPs to protect upon acute MCMV challenge was remarkably improved compared to the single SLP vaccines, as all mice that received a mixed SLP vaccine exhibited significant reduction in the viral load, especially in the liver (Fig 7C), suggesting that the breadth of the response or the magnitude of the total anti-viral response is important. Remarkably, the combination of the m139 SLP with the M38 SLP was as efficacious as the combination with all 5 SLPs. To assess if superior viral control was related to the breadth of the response, we adoptively transferred 1 × 104 m139 SLP-induced CD8+ T cells, 1 × 104 M38 SLP-induced CD8+ T cells, or an equal total number of a pool of both m139 (0. 5 × 104) and M38 (0. 5 × 104) SLP-induced CD8+ T cells in naive recipient mice (Fig 7D). The transfer of SLP-induced CD8+ T cell populations with a dual specificity resulted in a significant reduction in viral titres, while the transfers of equal amounts of T cells with single specificity did not. Thus, combinations of at least two distinct SLP vaccines have an increased potency to protect compared to single SLP vaccines, indicating that the breadth of the vaccine-induced CD8+ T cell responses plays a crucial role in anti-viral immunity. We conclude that vaccination with single SLPs can be applied as a prophylactic vaccine strategy against CMV infection, but vaccination with combinations of different SLPs serve as a superior vaccine technology platform against viral challenge.
In this study we report that SLP-based vaccines are an effective modality against CMV infection. In a prime-boost vaccine regimen, SLPs containing single MCMV epitopes are highly immunogenic in both C57BL/6 and BALB/c mice, and generate long-lasting polyfunctional CD8+ T cell responses. Our study revealed three key findings. First, the magnitude and phenotype of the SLP-induced T cell responses initially resemble those evoked by a real viral infection. Second, the magnitude of the SLP-induced T cell response strongly correlated to the naive T cell precursor frequency, and third the protection against viral infection by SLP-induced memory CD8+ T cells was most pronounced when vaccination was performed with combinations of distinct SLPs leading to an increased breadth of the antigen-specific T cell response. In the last decades many vaccine strategies such as attenuated virus, DNA constructs, protein, and virally vectored vaccines targeting HCMV have been developed [3,4]. The focus of most of these vaccines was to generate protective antibodies. Our finding that SLP-based vaccines that solely provoke CD8+ T cell responses are efficacious suggests that the design of more efficient vaccines against CMV should incorporate the induction of CD8+ T cell immunity. Although we observed some epitope competition among SLP vaccine-induced CD8+ T cell responses, we anticipate that inclusion of CD4+ T cell and B cell epitopes will further improve the vaccine efficacy given that CD4+ T cells and antibodies have also antiviral actions against CMV. Moreover, SLP-based vaccines allow further refinement by different prime-booster regimens and by combinations with adjuvants, immunomodulatory antibodies or other vaccine platforms [25]. Conceivably, this will positively impact the phenotype and effectivity of the vaccine-induced T cells. As to date, the high CD8+ T cells responses elicited with the SLP vaccines encoding MCMV epitopes have not been observed before with other SLPs including those containing epitopes of human papilloma virus (HPV) [14], lymphocytic choriomeningitis virus (LCMV) [26], influenza [27] or model antigens [28]. This may be explained by the relatively high precursor frequency of T cells responding to some of the MCMV epitopes. Our study indicates that it is of interest for T cell-based vaccines to determine the antigen-specific T cell precursor frequencies as these correlate to the magnitude of the vaccine-induced antigen-specific response, allowing the selection of epitopes generating the most robust responses. This knowledge can be very useful for development of vaccines that are based on selection of epitopes. Nevertheless, the magnitude of the vaccine-induced T cell response appears not necessarily to correlate to protective immunity but seems to depend also on the specificity. For example, in C57BL/6 mice, the large vaccine-elicited responses to the M45985–993 and M57816-824 epitopes do not provide as good protection as the seemingly lower response to the M38316–323 epitope. Similarly, in BALB/c mice the m164 SLP confers immunity in liver and spleen whereas the IE1168-176 epitope containing SLP, which is analogous in magnitude, does not show protective effects. Previous studies using short peptide or DNA vaccination also reported that the strength of the vaccine-induced IE1-specific CD8+ T cell response does not necessarily correlate to protection [29–31], suggesting that the quality of the vaccine-induced T cell is more decisive. Dissimilarities in transcription of viral genes [32], which may even vary in different tissues, as well as the efficiency of peptide processing and presentation at the cell surface, may also be implicated in the differential efficacy of the T cell response to each particular epitope to confer resistance to MCMV. In this respect it is of interest to note that SLP vaccines containing “inflationary” epitopes (i. e. , M38 and m139) elicit better protection as compared to the non-inflationary epitopes. This may relate to differences in the presentation of the inflationary epitopes as compared to the non-inflationary epitopes by infected cells and/or by (cross-presenting) APCs. An important requirement for memory inflation is chronic antigenic exposure [12]. The fact that SLPs do not elicit inflation suggests that SLPs are broken down in such a manner that epitopes are not presented over a long period of time as occurs during persistent CMV infection. Other factors important for memory inflation during CMV infection, such as dependence on certain T cell costimulatory interactions (e. g. , CD27-CD70 [33]), are likely also not in place at late time points post SLP vaccination. In addition, a characteristic feature of inflationary T cells is their predominant effector-memory like phenotype. The SLP vaccine-induced T cells are not mostly effector-memory like, as may be expected because of the apparent absence of memory inflation. Although the expansion of the SLP-induced CD8+ T cells seems to be somewhat negatively influenced as compared to virus-induced T cells, it remains to be determined whether protection on a per-cell basis is influenced as well. Nevertheless, the SLP-induced T cells were well capable to reduce the viral load upon viral challenge, especially when a mixture of distinct SLPs was used for vaccination. The somewhat lesser expansion potential of the SLP-induced T cells might relate to some of the differences in the phenotype of the SLP and MCMV-elicited T cells. Although the effector T cells induced by either SLP boost vaccination or MCMV infection had an analogous phenotype (KLRG1hi, CD44hi, CD127low, CD62Llow, IL2+/-) and cytokine profile, the memory T cells elicited by SLPs displayed a mixed profile of effector-memory (KLRG1hi, CD127lo), central-memory (KLRG1lo, CD127hi) and double-positive T cells (KLRG1hi, CD127hi). In contrast, MCMV infection induces a more polarized phenotype: either a central-memory phenotype (mainly non-inflationary responses) or an effector-memory phenotype (mainly inflationary responses). Whether a lack of CD4+ T cell helper signals [34] or a lack of virus-associated inflammatory signals [26] is responsible for the observed SLP vaccine-associated phenotype and secondary expansion potential remains to be examined in future studies. We showed that the efficacy of SLP vaccines to protect against MCMV is primarily driven by the breadth of the CD8+ T cell responses rather than the magnitude of the individual SLP vaccine-induced T cell responses. A possible explanation is that viral infected cells are to a certain degree resistant to CD8+ T cell mediated killing due to sophisticated immune evasion mechanisms including downmodulation of MHC class I molecules and prevention of apoptosis [35–37]. Accordingly, it has been estimated that one effector CD8+ T cell kills only 2–16 MCMV-infected cells per day and the probability of death of infected cells increases for those contacted by more than two CTLs, which is indicative of CTL cooperation [38]. Our study suggests that multiple encounters with cytotoxic CD8+ T cells with different specificity result in more effective killing of infected cells. Overall, this study provided evidence that SLP-based vaccines eliciting memory CD8+ T cell responses have protective effects against acute MCMV infection with respect to lowering the viral load in tissues. These promising results highlight the need for additional studies to elucidate the role of vaccine-induced T cells against CMV and other persistent viral infections.
C57BL/6 mice and BALB/c mice were purchased from Charles River Laboratories (L' Arbresle, France). CD45. 1 (Ly5. 1) congenic mice on a C57BL/6 background were obtained from The Jackson Laboratory. Mice were maintained under specific-pathogen-free conditions at the Central Animal Facility of Leiden University Medical Center (LUMC), and were aged 8–10 weeks at the beginning of each experiment. The mice did not undergo any immunosuppressive treatments and were fully immunocompetent. All animal experimental protocols were approved by the LUMC Animal Experiments Ethical Committee in accordance with the Dutch Experiments on Animals Act and the Council of Europe (numbers 13156 and 14187). MCMV virus stocks were prepared from salivary glands of BALB/c mice infected with MCMV-Smith (American Type Culture Collection (ATCC) ). The viral titres of the produced virus stocks were determined by viral plaque assays with 3T3 mouse embryonic fibroblasts (MEFs) (ATCC). Age- and gender-matched C57BL/6 mice were infected with 5 × 104 PFU MCMV, and age- and gender-matched BALB/c mice with 5 × 103 PFU MCMV. Viruses were administered intraperitoneally (i. p) in a total volume of 400 μl in PBS. At 65 days post-booster vaccination or infection, SLP vaccinated or MCMV infected mice were (re) -challenged with 5 × 104 PFU MCMV. Determination of viral load was performed by real-time PCR as described previously [39]. Short (9–10 aa) and long (20–21 aa) peptides containing MHC class I-restricted T cell epitopes from MCMV encoded proteins in C57BL/6 and BALB/c mice were produced at the peptide facility of the LUMC (peptide sequences are described in S1 Table). The purity of the synthesized peptides (75–90%) was determined by HPLC and the molecular weight by mass spectrometry. Synthetic long peptide (SLP) vaccinations were administered subcutaneously (s. c.) at the tail base by delivery of 50 μg SLP and 20 μg CpG (ODN 1826, InvivoGen) dissolved in PBS in a total volume of 50 μl. Booster SLP vaccinations were provided after 2 weeks. Vaccination with a mixture of SLPs was done with 50 μg of each SLP and 20 μg CpG. Cell surface and intracellular cytokine stainings of splenocytes and blood lymphocytes were performed as described [40]. For examination of intracellular cytokine production, single cell suspensions were stimulated with short peptides for 5 h in the presence of brefeldin A or with long peptides for 8 h of which the last 6 h in presence of brefeldin A (Golgiplug; BD Pharmingen). MHC class I tetramers specific for the following MCMV epitopes: M45985–993, M57816–824, m139419-426, M38316–323, and IE3416–423 in C57BL/6 mice and M45507–515, m164257-265 and IE1168-176 in BALB/c mice were produced as reported [41]. Fluorochrome-conjugated mAbs were purchased from BD Biosciences, Biolegend or eBioscience. Flow cytometry gating strategies are shown in S6 Fig. Samples were acquired with the LSRFortessa cytometer (BD Biosciences) and analysed with FlowJo-V10 software (Tree star). A peptide dose-response titration was performed to determine and compare the TCR avidity of the CD8+ T cells induced after SLP vaccination and MCMV infection at the acute and memory phase. In brief, splenocytes were stimulated with various concentrations of short peptide in presence of 2 μg/ml brefeldin A for 5 h at 37°C. Subsequently, cell surface staining and an intracellular IFN-γ staining were performed. Responses were analysed using the same approach as described above. Blood was collected from the retro-orbital plexus and after brief centrifugation, sera were obtained and stored at −20°C. Specific immunoglobulin levels in serum were measured by ELISA as described [39]. Briefly, Nunc-Immuno Maxisorp plates (Fisher Scientific) were coated either with 2 μg/ml SLPs or with MCMV-Smith in bicarbonate buffer, and after blocking with skim milk powder (Fluka BioChemika) diluted sera were added. Next, plates were incubated with HRP-conjugated antibodies (SouthernBiotech) to detect different Ab isotypes. Plates were developed with TMB substrate (Sigma Aldrich) and the colour reaction was stopped by addition of 1M H2SO4. To serve as a positive control, a peptide from the M2 protein (eM2) of influenza A virus with identified ability to induce antibodies and corresponding serum was used. Optical density was read at 450 nm (OD450) using a Microplate reader (Model 680, Bio-Rad). To determine the endogenous naive precursor frequency of MCMV-specific CD8+ T cell populations in C57BL/6 and BALB/c mice, enrichment assays of antigen-specific CD8+ T cells were performed as described [42]. In short, single cell suspensions were generated from pooled spleen and lymph nodes (mesenteric, inguinal, cervical, axillary, and brachial) of individual mice. Cells were stained with PE and APC-labelled MHC class I tetramers for 0. 5 h at RT, then washed, labelled with anti-PE and anti-APC microbeads (Miltenyi Biotec), and passed over a magnetized LS column (Miltenyi Biotec). The tetramer-enriched fractions were stained with fluorochrome labelled Abs against CD3 (clone 500A2), CD4 (clone L3T4), CD8 (clone 53–6. 7) for 30 min at 4°C, and subsequently analysed. Samples were acquired with the LSRFortessa cytometer (BD Biosciences). The expansion capacity and vaccine efficacy of SLP vaccine and/or MCMV-induced antigen-specific CD8+ T cells was determined by adoptive transfers. Splenic CD8+ T cells from chronically (day 60) infected and SLP vaccinated CD45. 1+ mice were enriched with magnetic sorting using the CD8+ T cell isolation kit in accordance with the manufacturer’s protocol (Miltenyi Biotec). Next, cells were stained with MHC class I tetramers and with fluorochrome labelled antibodies against CD3 and CD8. Tetramer positive CD8+ T cells were sorted using a FACSAria II Cell Sorter (BD Biosciences) and 1 × 104 tetramer+ CD8+ T cells were transferred (retro-orbital in a total volume of 200μl in PBS) into naive CD45. 2+ C57BL/6 recipients. Recipients were subsequently (2 h later) infected with 5 × 104 PFU MCMV. At day 5 post viral challenge the viral titres were determined by qPCR and the number of donor-specific CD8+ T cells by flow cytometry. Statistical significance was assessed with Student’s t-test or ANOVA using GraphPad Prism software (GraphPad Software Inc. , USA). The level of statistical significance was set at P<0. 05. | The majority of infections with the betaherpesvirus human cytomegalovirus (HCMV) are clinically unnoticed, but in immunocompromised hosts HCMV infections can be severe and even fatal. Here we investigated in preclinical mouse models the efficacy and mechanisms of synthetic long peptide (SLP) -based vaccines eliciting mouse CMV (MCMV) -specific CD8+ T cells as a platform modality to protect against CMV infection. The percentages of MCMV-specific T cells in the circulation elicited by prime-booster SLP vaccination were equivalent or higher compared to those induced by the virus itself. We further show that the naive T cell precursor frequency rather than the functional avidity of T cells predicts the magnitude of SLP-induced CD8+ T cell responses. Superior protection against MCMV infection depends strongly on the combined use of distinct SLP vaccines leading to broader viral-specific responses. This finding highlights the importance of the breadth of vaccine-induced CD8+ T cell responses. | Abstract
Introduction
Results
Discussion
Materials and Methods | blood cells
innate immune system
medicine and health sciences
immune cells
immune physiology
cytokines
immunology
cytomegalovirus infection
vaccines
preventive medicine
developmental biology
clinical medicine
molecular development
cytotoxic t cells
vaccination and immunization
public and occupational health
infectious diseases
white blood cells
major histocompatibility complex
memory t cells
animal cells
t cells
immune system
cell biology
clinical immunology
physiology
biology and life sciences
cellular types
viral diseases | 2016 | The Breadth of Synthetic Long Peptide Vaccine-Induced CD8+ T Cell Responses Determines the Efficacy against Mouse Cytomegalovirus Infection | 9,075 | 239 |
Pervasive natural selection can strongly influence observed patterns of genetic variation, but these effects remain poorly understood when multiple selected variants segregate in nearby regions of the genome. Classical population genetics fails to account for interference between linked mutations, which grows increasingly severe as the density of selected polymorphisms increases. Here, we describe a simple limit that emerges when interference is common, in which the fitness effects of individual mutations play a relatively minor role. Instead, similar to models of quantitative genetics, molecular evolution is determined by the variance in fitness within the population, defined over an effectively asexual segment of the genome (a “linkage block”). We exploit this insensitivity in a new “coarse-grained” coalescent framework, which approximates the effects of many weakly selected mutations with a smaller number of strongly selected mutations that create the same variance in fitness. This approximation generates accurate and efficient predictions for silent site variability when interference is common. However, these results suggest that there is reduced power to resolve individual selection pressures when interference is sufficiently widespread, since a broad range of parameters possess nearly identical patterns of silent site variability.
Natural selection maintains existing function and drives adaptation, altering patterns of diversity at the genetic level. Evidence from microbial evolution experiments [1], [2] and natural populations of nematodes [3], fruit flies [4], [5], and humans [6], [7] suggests that selection is common and that it can impact diversity on genome-wide scales. Understanding these patterns is crucial, not only for studying selection itself, but also for inference of confounded factors such as demography or population structure. However, existing theory struggles to predict genetic diversity when many sites experience selection at the same time, which limits our ability to interpret variation in DNA sequence data. Selection on individual nucleotides can be modeled very precisely, provided that the sites evolve in isolation. But as soon as they are linked together on a chromosome, selection creates correlations between nucleotides that are difficult to disentangle from each other. This gives rise to a complicated many-body problem, where even putatively neutral sites feel the effects of selection on nearby regions. Many authors neglect these correlations, or assume |