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10.1371/journal.ppat.1004874 | Experimental Evolution of an RNA Virus in Wild Birds: Evidence for Host-Dependent Impacts on Population Structure and Competitive Fitness | Within hosts, RNA viruses form populations that are genetically and phenotypically complex. Heterogeneity in RNA virus genomes arises due to error-prone replication and is reduced by stochastic and selective mechanisms that are incompletely understood. Defining how natural selection shapes RNA virus populations is critical because it can inform treatment paradigms and enhance control efforts. We allowed West Nile virus (WNV) to replicate in wild-caught American crows, house sparrows and American robins to assess how natural selection shapes RNA virus populations in ecologically relevant hosts that differ in susceptibility to virus-induced mortality. After five sequential passages in each bird species, we examined the phenotype and population diversity of WNV through fitness competition assays and next generation sequencing. We demonstrate that fitness gains occur in a species-specific manner, with the greatest replicative fitness gains in robin-passaged WNV and the least in WNV passaged in crows. Sequencing data revealed that intrahost WNV populations were strongly influenced by purifying selection and the overall complexity of the viral populations was similar among passaged hosts. However, the selective pressures that control WNV populations seem to be bird species-dependent. Specifically, crow-passaged WNV populations contained the most unique mutations (~1.7× more than sparrows, ~3.4× more than robins) and defective genomes (~1.4× greater than sparrows, ~2.7× greater than robins), but the lowest average mutation frequency (about equal to sparrows, ~2.6× lower than robins). Therefore, our data suggest that WNV replication in the most disease-susceptible bird species is positively associated with virus mutational tolerance, likely via complementation, and negatively associated with the strength of selection. These differences in genetic composition most likely have distinct phenotypic consequences for the virus populations. Taken together, these results reveal important insights into how different hosts may contribute to the emergence of RNA viruses.
| Viruses are constantly emerging into new areas and pose significant challenges to public health. Chikungunya and West Nile viruses (WNV), both mosquito-borne RNA viruses, are quintessential examples of how increased globalization has facilitated the expansion of viruses into new territories. Rapid evolution of both of these agents has contributed to their rapid spread and health burden. Thus, characterizing how selection shapes zoonotic RNA viruses in their natural hosts is important to understand their emergence. As an ecological generalist able to infect hundreds of bird species, WNV is an excellent tool to study how different animal hosts can differentially drive virus evolution. We examined the genetic composition and fitness of WNV produced during replication in wild-caught American crows, house sparrows and American robins, species that range in mortality following WNV infection (crows the highest, robins the lowest). We demonstrate host-dependent effects on WNV population structure and fitness. Our study provides insights on how different virus-animal interactions can influence the success of a virus in the next host and ultimately the success of virus emergence into new host systems.
| RNA viruses pose some of the most complex, persistent and challenging problems facing public health and medicine. The ongoing outbreaks of avian influenza A(H7N9) virus (Orthomyxoviridae) in China [1], Ebola virus (Filoviridae) in West Africa [2], and chikungunya virus (CHIKV, Togaviridae, Alphavirus) and West Nile virus (WNV, Flaviviridae, Flavivirus) in the Americas [3,4] highlight the health and societal impacts imposed by RNA virus-induced diseases. Several factors contribute to the emergence of these agents and the continued burdens they impose on human health. Among these is their ability to undergo rapid evolution in new and/or changing environments. Well documented examples of RNA virus evolution leading to increased virus transmission include WNV and CHIKV. In both cases, small, conservative amino acid substitutions (residues with similar physiochemical properties) to the viral envelope proteins resulted in more efficient transmission by mosquito vectors [5,6]. Adaptive changes to RNA virus genomes first arise as minority components within a genetically complex population of related but non-identical virus variants. The genetic diversity present in naturally occurring RNA virus populations has been clearly shown through a large and expanding body of observational and experimental studies to be critical to their biology. For example, several studies have demonstrated that the diversity of an intrahost viral population, rather than the fitness of individual variants, correlates with pathogenesis, disease progression and therapeutic outcome [7–9]. Moreover RNA viruses have the capacity for rapid evolutionary change because within infected hosts, all single nucleotide mutations may be generated.
This has been particularly clear in the case of WNV, an arthropod-borne virus (arbovirus) that persists in nature in enzootic cycles between ornithophilic mosquitoes (mainly Culex spp.) and birds. After its initial identification in the New York City area in 1999, WNV spread throughout the continental United States, producing the largest outbreaks of flaviviral encephalitis ever recorded in North America. The explosive spread of the virus was accompanied by the displacement of the introduced genotype by a derived strain that is more efficiently transmitted by local Culex mosquitoes [10]. Studies of intrahost population dynamics of WNV demonstrated that genetic diversity is greater in mosquitoes than in birds [11]. The selective basis for the host-specific patterns of WNV genetic diversity is that the strong purifying selection that predominates in birds is relaxed in mosquitoes [11,12]. In addition, the RNA interference-based antiviral response in mosquitoes creates an environment where negative frequency-dependent selection may drive rare variants to higher population frequency [13]. Moreover, WNV maintains both adaptive plasticity and high fitness by alternating between hosts that impose different selective forces on the virus population [14].
Nonetheless, important gaps remain in our understanding of how error-prone replication interacts with selective and stochastic reductions in viral genetic diversity under natural conditions. This is particularly the case for arboviruses, which tend to cause acute infection in vertebrates, with transmission occurring before the development of a neutralizing antibody response. Therefore, well-described mechanisms of immune selection such as those that occur during chronic hepatitis C and human immunodeficiency virus infections are comparatively weak during acute arbovirus infection of vertebrates. Thus, the ways that ecologically relevant, natural hosts can influence arbovirus genetic diversity remain poorly understood. WNV in particular provides an excellent experimental system to study the influences of natural vertebrate hosts on viral evolution. The virus infects a large number of wild bird species [15] with a wide-range of infection outcomes [16]. In addition, several studies have provided evidence that particular WNV variants may arise through adaptation to birds [17,18].
Therefore, we sought to determine whether different wild bird species may have distinct impacts on WNV population structure. Specifically, we allowed WNV to replicate in wild-caught American crows (Corvus brachyrhynchos), house sparrows (Passer domesticus), and American robins (Turdus migratorius), bypassing the mosquito portion of the arbovirus cycle in order to focus on the impact of different vertebrate environments on virus populations during acute infection. Virus was passaged in individuals of each species five times in order to amplify host-specific patterns of selection that may remain cryptic after a single passage. Bird species were selected on the basis of ecological relevance and resistance to WNV-induced mortality. American crows experience high viremia and mortality following inoculation with WNV [19] and can directly transmit virus to roost mates without mosquito involvement [20]; house sparrows experience high viremia and intermediate mortality [21] and are frequently involved in WNV perpetuation [22]; and American robins experience intermediate viremia but very low mortality [23] and can be drivers for human WNV risk [24]. Virus populations were characterized using next generation sequencing (NGS) and through in vivo fitness competition studies in birds and mosquitoes. Our findings demonstrate that relevant vertebrate hosts with varying levels of disease susceptibility differentially shape WNV population structure with direct impacts on fitness during host shifts.
The WNV used in these studies was derived from an infectious clone of the NY99 genotype and is described in detail elsewhere [25]. Clone-derived WNV was passaged five times in wild-caught American crows, house sparrows and American robins. To avoid systematically selecting high- or low-replicating strains and population bottlenecks during passage, and since titers are highly variable in wild-caught birds, the sera from the individuals with the intermediate viral load were passed into the next cohort at a standard dose of 1000 plaque forming units (PFU). Virus titer was variable but did not change significantly or consistently during the course of passage (Fig 1A). Further, five passages in wild birds did not alter viremia production or mortality in crows and sparrows (S1A and S1B Fig). WNV replication and fitness after passage was assessed using young chickens and Culex quinquefasciatus mosquitoes to directly compare the viral populations in hosts not used for passaging and to remove the variability of wild-caught birds (e.g. age and infection history) (Fig 1B and 1C). Passaged virus (p5) was similar to the WNVic (p0) in peak viremia production in chickens (i.e. at 2 and 3 dpi) (Fig 1B).
Fitness assays were used to directly compare passaged viruses to a standard reference WNV in head-to-head competition. These assays can detect subtle fitness differences that are inapparent in comparative studies. Competitive fitness of all wild-bird p5 WNV was significantly enhanced in chickens. Crow-passaged virus had the smallest fitness gains and robin-passaged virus the largest (Fig 1C). Fitness studies conducted in wild birds produced the same results as those in chickens (S1C Fig). Competitive fitness was slightly increased in mosquitoes, but no bird-specific differences were noted (Fig 1C, S1D Fig).
At each passage virus was examined by NGS to determine whether the consensus sequence changed during passage and to characterize the diversity of intrahost viral populations (S1 Table, S2 Fig). WNV genome coverage was variable across the genome and between samples (S2A Fig), and positively correlated with viral population size (S2C Fig). The lower relative WNV genome coverage from robin sera can in part be explained by smaller intrahost viral population sizes and smaller virus to host RNA ratios. Approximately 68%, 29% and 7% of NGS reads aligned to the WNV genome from crow, sparrow and robin sera, respectively. Comparatively, 20% and 0.5% of the NGS reads aligned to the WNV genome from chicken sera and mosquito bodies, respectively.
Three nucleotide mutations that led to consensus amino acid substitutions were detected though passaging in birds, but none became fixed (i.e. frequency = 1) in the population. In contrast, three consensus amino acid substitutions were detected after a single mosquito passage. All intrahost single nucleotide variants (iSNVs) > 0.02 frequency are listed in S2 Table.
We estimated intrahost variation from NGS data to determine whether WNV population diversity was bird species-dependent. The mean number of unique iSNVs in each virus population was relatively constant between passages, but differences were apparent among bird species (Fig 2A). WNV populations passaged in crows five times (p5) had significantly more unique iSNVs than WNV passaged in sparrows and robins. In addition, the frequency of individual iSNVs increased during passage in a species-dependent manner: The mean iSNV frequency after p5 in robins was significantly higher than after p5 in crows or sparrows (Fig 2B). Despite these differences, the viral populations had similar Normalized Shannon entropies (SN), Hamming distances (i.e. SNVs per coding sequence) and amino acid substitutions per coding sequence after p5 in different species (Fig 2C).
We examined the ratio of viral genome equivalents (GE) to PFUs and intrahost single nucleotide length variants (iLVs, including both insertions and deletions) to assess defective viral genomes in WNV populations during passage. Crow-passaged WNV had the highest GE:PFU ratio (Fig 3A) and the most unique iLVs (Fig 3B). In addition, a greater proportion of the iLVs in crows were found in subsequent passages compared to sparrows and robins (Fig 3C). The number of iLVs per coding sequence was positively correlated with the titer of infectious virus (Fig 3D). We then evaluated the possibility that greater levels of iLV carry though in crows, which can only occur via complementation (Fig 3C), were due to sampling artifacts. To do this, we used a hypergeometric test implemented in R that indicated that selecting 400 common iLVs in two samples of 600 from the total pool of available single-nucleotide iLVs (n = 51,490) was 0. Simulation studies confirmed that it is extremely unlikely that random sampling produced the observed data.
Evidence for natural selection was assessed in WNV populations using intrahost neutrality tests. The proportion of mutations in each population that were nonsynonymous (pN) and the ratios of nonsynonymous to synonymous variants per site (dN/dS) were highest in the input p0 WNV population and decreased significantly during passage in each bird species (Table 1). Separate analysis of dN and dS shows that dN did not significantly increase during passage while dS increased significantly at p5 in all bird species, a hallmark of purifying selection. The Fu and Li’s F and Fay and Wu’s H statistics were obtained from reconstructed haplotypes. The F statistic at p1 and p5 was consistently negative, indicating that the haplotypes contained excessive amounts of rare SNVs, again indicative of purifying selection (Table 1). The H statistic measures an excess of high compared to intermediate frequency SNVs. The insignificant H values suggest that the deviations from neutrality were due to natural selection rather than selective sweeps (Table 1).
Analysis of reconstructed haplotypes that arose during passage and high frequency iSNVs (i.e. frequency > 0.02) was conducted to minimize the impact of differences in sequencing coverage and to assess positive selection. 0.02 was selected as a cutoff for “high frequency” mutations because it includes the top 5% of a gamma distribution of all VPhaser2-accepted iSNVs. The proportion of iSNVs that were high frequency after p5 was the greatest within robin-passaged WNV populations (16.5%) compared to sparrows (4.9%) and crows (4.8%) (Fig 4A). Reconstructed haplotypes from high frequency iSNVs were then used to assess the selective pressures that lead to haplotype replacement during passage (Fig 4B). The ancestral p0 virus population was composed of a single dominant haplotype that remained dominant after a single passage in all bird species. After p5, the ancestral haplotype remained dominant in crows, but not in sparrows and robins. Furthermore, high frequency iSNVs from crows contributed significantly fewer amino acid substitutions per coding sequence compared to robins after p5 (Fig 4C). Examination of dN/dS, amino acid diversity and high frequency nonsynonymous iSNVs across the WNV genome demonstrated that, in general, selection was the strongest in the structural protein coding regions (Fig 4D and 4E). Specifically, passage in robins imposed significant selective pressures on the envelope (E) protein coding region that heavily targeted ectodomains (ED) I and II. The apparent selection of the nonstructural protein 4B (NS4B) from sparrow passaging is the result of a single high frequency nonsynonymous iSNV (S2 Table). Individual high frequency iSNVs fluctuated in frequency through passaging and all nonsynonymous high frequency iSNVs were unique to its passage lineage (i.e. no “signature mutations” were detected that served as markers for replication in any particular bird species, see S2 Table).
The standardized variance in iSNV frequencies (FST) was then estimated from the coding sequence to determine the degree of genetic divergence among replicates within a passage and between passages (Fig 5). Viral populations from robins were more divergent compared to those from crows and sparrows. FST from WNV passaged once in young chickens was similar to wild-caught birds, but WNV passaged once in mosquitoes was much more divergent. These results are supported by analysis of haplotypes (S3 Fig). The p0 haplotype was still dominant in chicken p1 populations with a small minority of haplotypes containing single iSNVs, similar to wild birds (Fig 4B). In mosquitoes the ancestral haplotype became a minority after a single passage.
We examined WNV genetic diversity during the course of passage in birds that experience varying mortality due to WNV infection to assess how different hosts influence virus population structure and fitness. Passage in each host was accomplished in three concurrent biological replicates in order to control for the impact of individual wild-caught birds that may vary in several ways that could impact virus replication. Titers during passage were highly variable between individuals. However, mean titers did not significantly change during the course of passage, indicating that replication competence was retained and that overt increases in competitive fitness were not selected through our passage strategy.
Wild-bird passaged virus was similar to unpassaged WNV in viremia production. Only when more sensitive in vivo competitive fitness assays (i.e. comparative replication of the passaged and reference WNV in the same host) were conducted were changes apparent. Note that our definition of fitness here is restricted to the specific competition environment (within the bird or mosquito) and does not consider the larger ecological fitness required for maintenance in a complex arbovirus transmission cycle. Passage in all birds resulted in significant competitive fitness gains during replication in chickens. Interestingly, the fitness gains were smallest after WNV was passaged in the host that experiences the most mortality (crows), and largest in the most disease-resistant avian host (robins). Fitness gains were far less clear when virus competition was measured in mosquitoes. A limitation to our mosquito studies is that competition was conducted via intrathoracic inoculation, which bypasses the midgut, a major physiological barrier in mosquitoes. Intrathoracic inoculation was used because the volume of blood available and the virus titers would have likely made oral infection highly inefficient. Importantly, our results on WNV replication and fitness are supported by previous observations [14] indicating that high fitness is maintained through purifying selection in vertebrates, and that no tradeoff occurs when the virus is re-introduced into mosquitoes. Moreover, replicative fitness increases occur during passage in ecologically relevant wild birds, and these gains occur in a species-specific manner.
To investigate the viral genetic and population determinants of the observed fitness gains, we characterized WNV at each passage using NGS. Our data suggests that although the overall complexity of the virus population was similar among different bird species, its composition, and the selective pressures that produced it appear to be bird species-dependent. Interestingly, WNV replication in the most disease-susceptible bird species seems to be positively associated with the number of unique iSNVs (i.e. mutational tolerance) and negatively associated with iSNV frequency (i.e. strength of selection). This observation requires further investigation using additional resistant and susceptible birds, but may provide important insights into which bird species are most likely to drive virus evolution toward fitness gains. Our data thus far suggests that more disease resistant birds such as robins would be most likely to fill this role as long as they produce sufficiently high titers to infect mosquitoes.
In this study we used various neutrality tests to determine whether intrahost WNV populations from each bird species were evolving non-randomly through purifying selection. While these tests all measure slightly different aspects of genetic diversity, all clearly demonstrate purifying selection in birds. This result confirms previous studies of WNV passaged in young chickens [11], and indicates that our approaches to sequencing and analysis, although they differ significantly from those reported previously, produce results consistent with other methods.
Our studies also provide some evidence for positive selection during bird infection. We found that WNV passage in robins resulted in more amino acid substitutions that reach high frequency compared to crows. In addition, the ancestral haplotype tended to be displaced by novel mutants that arose during passage in sparrows and robins. These data suggest that positive selection within hosts is stronger in less susceptible bird species [26].
Examination of patterns of variation across the WNV genome provides additional evidence for differences in host selective environment. We found, consistent with previous reports on dengue virus populations [27], the highest variant frequencies in ectodomains I and II of the E coding sequence of WNV passaged in robins. The mechanisms that lead to the emergence of these variants are not currently clear. Although the E protein contains most neutralizing epitopes, the earliest neutralizing antibody responses observed in birds generally occur at around 5 to 7 days post infection [23,28]. Other mechanisms that could impact selection on the E protein include resistance to the early antiviral states induced by type I interferon [29,30] and alternate methods for virus entry and uncoating of the viral RNA [31]; though these mechanisms need further investigation, especially in birds. Our results suggest that in relatively resistant hosts, novel variants may rise to high frequency within the context of purifying selection. The notion that positive selection occurs in robins is further supported by our data showing that virus diverged most during replication in them. It is, however, balanced by a lack of evidence of a selective sweep, i.e. a rapid reduction in genetic diversity as a novel variant becomes very prominent in the population. Clearly further studies are needed to confirm whether and how positive selection contributes to WNV population structure in birds.
Compared to other RNA viruses, arboviruses have low long-term rates of amino acid substitution [32]. This is at least partially due to the fact that most mutations are deleterious because of evolutionary constraints on arbovirus genomes [33]. We provide evidence that accumulation of deleterious mutations, or defective viral genomes, is unequal between hosts; WNV populations replicating in wild-caught crows accumulate the most defective genomes, and WNV replicating in robins accumulate the least. Defective genomes are often found during laboratory and natural virus infections [17,34] and can persist through multiple rounds of transmission [35,36]. Using both bioassays (i.e. GE:PFU) and sequencing data (i.e. iLVs per coding sequence), we found that the accumulation of WNV defective genomes during infection was positively correlated with viral load. This apparent density-dependent selection of deleterious mutations likely occurs via functional complementation, which becomes more efficient as effective multiplicity of infection (MOI, i.e. intrahost viral load) increases [37,38]. In addition, high MOI environments tend to tolerate neutral mutations that can become deleterious in a new environment [39]. Taken together, these studies provide a framework to understand how WNV replication in high-viremic crows leads to a broader network of potentially deleterious mutations and limited selection for adaptive amino acid substitutions, especially when compared to WNV replication in robins. The rather modest fitness gains experienced by crow-passaged WNV support this observation.
The results presented here shed light on the selective forces that shape WNV populations in nature. We demonstrate that selective pressures that control WNV populations seem to occur in a species-specific manner (Fig 6). All three bird species evaluated have been suggested to be significant drivers of WNV outbreaks, with robins receiving particular attention due to findings indicating that this species is more frequently fed upon by mosquito vectors [24]. During intrahost WNV replication, our studies suggest that disease-susceptibility is positively associated with mutational tolerance and negatively associated with the strength of selection. This means that robins also may better maintain high fitness in WNV populations than do birds that are more susceptible to disease. While it is tempting to speculate that robins are significant generators of WNV genetic diversity, we also confirm herein that mosquitoes are much more efficient in generating mutational diversity in the WNV system. Moreover, these data suggest that intrahost virus evolutionary dynamics are associated with host resistance to disease in several ways and provide an important insight towards the genetic and ecological factors that influence RNA virus emergence.
Wild birds were collected from under US Fish and Wildlife Service (#MB91672A-0) and Colorado Parks and Wildlife (#13TRb2106) permits and with permissions from landowners. No endangered or protected species were caught or harmed during the study. Experiments involving animals were conducted in accordance with protocols approved by the Colorado State University (CSU) Institutional Animal Care and Use Committee (#12-3694A) and the recommendations set forth in the Guide for the Care and Use of Laboratory Animals of the National Institutes of Health.
A WNV infectious clone (WNVic) was previously constructed from an American crow kidney isolate collected during the 2000 outbreak in New York City [25,40]. The WNVic contains a naturally selected proline at amino acid site 249 in nonstructural protein 3 (NS3) allowing it to replicate to high titers in wild birds [18,41]. Wild birds were collected in Northern Colorado from 2013 to 2014 using mist nets (house sparrows and American robins) and cannon nets (American crows). All birds were bled prior to inoculation and serum was tested by plaque reduction neutralization test to confirm that all birds used for subsequent studies were WNV seronegative. The virus strain used to initiate the passage series was derived from a WNVic as previously described [25]. Virus was harvested from the supernatant of BHK cells transfected with linearized plasmid, stored at -80°C and used without further passage. Viruses were administered to birds by subcutaneous inoculation to the breast region with 1,000 WNV PFU/100 μl, a dose similar to mosquito transmission [42], in inoculation medium (endotoxin and cation-free phosphate buffered saline with 1% FBS). Birds were bled from the jugular vein at the time of peak viremia on 3 days post-infection (dpi). Serum was titered by standard plaque assay on African green monkey kidney cells (Vero, ATCC CCL-81) and stored at -80°C until used for subsequent passage or sequencing as described below. The first passage series utilized seven birds for each wild-caught species and the three birds with the median viral titers were used to start three independent replicate lineages, each including three naïve birds (i.e. replicates ‘a’, ‘b’, and ‘c’). From each group of three birds, the serum with the median viral titer was used to continue passaging to another cohort until five serial passages were completed. The WNVic derived virus was also passaged once in three young chickens for 3 dpi and two individual Cx. quinquefasciatus mosquitoes for 14 dpi to compare viral populations from commonly used laboratory vertebrate host and invertebrate vector models, respectively. See S1 Text for information about housing and care of wild-caught birds, chickens and mosquitoes.
The infection phenotype of each WNV lineage after five passages (p5) in wild-caught birds was compared to the unpassaged (p0) WNV in the same bird species as virus passage, young chickens (two-days old), and Cx. quinquefasciatus mosquitoes (4–7 days post emergence). Viremia and survival was measured from birds were inoculated with 1,000 PFU of p5 or p0 WNV (n = 4–5 birds/virus) for up to 6 dpi. As defined here, competitive fitness compares the replication of a competitor virus (i.e. serial passaged p5 WNV) and a standard WNV reference (WNV-REF) during infection of the same host. Competitive fitness is quantified by the proportion of competitor to WNV-REF genotypes using sequence chromatograms (i.e. quantitative sequencing) [43]. WNV-REF was generated from an infectious clone as described above and in S1 Text and is indistinguishable from the parental virus in replication in cells and relevant organisms [44]. Competitive fitness assays of co-inoculated birds and mosquitoes with equally mixed WNV-REF and p5 competitor virus was conducted as described in S1 Text.
Virus libraries were prepared for RNA sequencing on the Illumina HiSeq 2000 platform (Beckman Coulter Genomics, Danvers, MA) using the NuGEN Ovation RNA-Seq System V2 and Ultralow Library kit (San Carlos, CA) (See SI Text for more details). Fastq files containing read data were demultiplexed using CASAVA and custom scripts that impose high stringency (0 mismatches) in the barcode region of each read. The sequence of the input WNV strain was determined from three independent biological sequencing replicates of the input virus using the Trinity assembler [45]. 100 nt paired-end reads were then aligned to this “input” sequence using MOSAIK [46]. Duplicate reads were removed using the MarkDuplicates tool within Picard to limit the influence of PCR artifacts and multiply sequenced clusters on variant calling with Vphaser2 [47]. Variants with significant strand bias were removed to reduce the potential for false-positives [48]. Variants called using Vphaser2 were used for subsequent data analysis unless otherwise specified. Analysis was limited to the protein coding sequences; and iSNVs and iLVs (includes both insertions and deletions) were analyzed separately.
Hamming distances from the p0 “input” virus were calculated for each population by dividing the total number of polymorphisms by the average coding sequencing coverage. Mean viral population complexity was calculated by the SN at each site using the following equation [49]:
SN=−pi(Lnpi)+(1−pi)(Ln(1−pi))/LnN
where p is the frequency of the iSNV at site i and N is the coverage at that site. At a single nucleotide position, a SN score of 0 indicates a single nucleotide was present (i.e. no polymorphism) while a score of 1 represents maximum complexity (i.e. equal numbers of alternate nucleotides). The SN at all protein coding sequence nucleotides loci were averaged to estimate the viral population complexity.
High frequency iSNVs were subjected to an additional analysis to reduce the possibility that conclusions drawn from the complete dataset were dependent on extremely rare variants. To establish a threshold for “high frequency” iSNVs, all of the Vphaser2 accepted variants detected in this study (n = 6052) were log10 transformed, increased by 3.75 (to make all of the values positive) and fit to a gamma distribution, where α = μ2/s2 and β = E[μ]/s2, using R (data did not fit a beta distribution). An iSNV frequency >0.02 was determined to be in the upper 5% of the gamma distribution and was used to define high frequency SNVs detected through WNV passage in birds (n = 341 individual SNVs). The sequencing reads from p0, p1 and p5 were aligned to the WNV genome using mpileup from the VarScan2 software package [50] and haplotypes were reconstructed using QuasiRecomb 1.2 [51] with the flags ‘-r 97–10395’, to reconstruct haplotypes from the entire coding sequence with respect to reference genome numbering, ‘-K 1–10’, to use a bigger interval of generators and ‘-noRecomb”, to disable the recombination process because it was not expected from the viral population and to reduce the runtime. To increase haplotype specificity, the flag ‘-conservative’ was employed and analysis was restricted to haplotypes containing high frequency SNVs (i.e. >0.02).
pN and dN/dS were used to test for intrahost selection [33]. DnaSP (version 5) [52] was used to determine the number of nonsynonymous and synonymous sites to calculate dN/dS using the Nei-Gojorori method [53] with the following modifications for NGS data. Nd and Sd (i.e. the numbers of detected nonsynonymous and synonymous mutations, respectively) were calculated for each viral population by the sum of individual nonsynonymous and synonymous VPhaser2 accepted iSNV frequencies and the passage consensus sequence was used to determine the number of nonsynonymous and synonymous sites. The number of nonsynonymous (7843.67) and synonymous (2455.33) sites in the ancestral p0 consensus sequence were used to determine that pN prior to selection is ~ 0.76. In addition, 50 most frequent haplotypes reconstructed from p1 and p5 from each bird species were analyzed using the Fu and Li’s F [54] and Fay and Wu’s H [55] statistical tests of neutrality in DnaSP with a window length of 100, a step size of 25 and the p0 consensus sequence as an outgroup to infer the ancestral nucleotide state.
FST was used to estimate the extent of interhost genetic divergence using a scale between 0 and 1, and the extent of FST change between populations represents the degree of genetic divergence. Specifically, in-house FORTAN scripts were used to calculate FST using equations 1, 2 and 4 by Fumagalli et al. [56]. Intrahost SNV frequencies determined by mpileup and readcounts from the VarScan2 software package [50] were used to estimate the per site heterozygosity in biological replicates compared to the total population (e.g. all biological replicates within passage) at a single passage (i.e. intra-passage) and the per site heterozygosity between passage replicates (i.e. inter-passage).
For estimation of the probability of resampling for the iLV data, we used the phyper command in R (www.R-project.org). We calculated that a total of 51,490 single nucleotide iLVs were possible by multiplying the length of the coding sequence (10,299 nt) by the 5 different kinds of iLVs that could occur at each site (one deletion and four different nt insertions). We then used phyper to obtain the probability of sampling overlap of 400 iLVs out of 600 sampled (reflecting a reasonable approximation of our observed data for crows) given that 51,490 iLVs are possible. Simulation studies were conducted in R by randomly sampling 600 individuals, with replacement, from a set of 51,490 and comparing the sets. T-tests, Kruskal Wallis tests, and correlation statistics were obtained using R and GraphPad Prism (La Jolla, CA).
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10.1371/journal.pntd.0007210 | Evaluation of a novel West Nile virus transmission control strategy that targets Culex tarsalis with endectocide-containing blood meals | Control of arbovirus transmission remains focused on vector control through application of insecticides directly to the environment. However, these insecticide applications are often reactive interventions that can be poorly-targeted, inadequate for localized control during outbreaks, and opposed due to environmental and toxicity concerns. In this study, we developed endectocide-treated feed as a systemic endectocide for birds to target blood feeding Culex tarsalis, the primary West Nile virus (WNV) bridge vector in the western United States, and conducted preliminary tests on the effects of deploying this feed in the field. In lab tests, ivermectin (IVM) was the most effective endectocide tested against Cx. tarsalis and WNV-infection did not influence mosquito mortality from IVM. Chickens and wild Eurasian collared doves exhibited no signs of toxicity when fed solely on bird feed treated with concentrations up to 200 mg IVM/kg of diet, and significantly more Cx. tarsalis that blood fed on these birds died (greater than 80% mortality) compared to controls (less than 25% mortality). Mosquito mortality following blood feeding correlated with IVM serum concentrations at the time of blood feeding, which dropped rapidly after the withdrawal of treated feed. Preliminary field testing over one WNV season in Fort Collins, Colorado demonstrated that nearly all birds captured around treated bird feeders had detectable levels of IVM in their blood. However, entomological data showed that WNV transmission was non-significantly reduced around treated bird feeders. With further development, deployment of ivermectin-treated bird feed might be an effective, localized WNV transmission control tool.
| West Nile virus (WNV) is a mosquito-borne virus that causes significant disease and death every year in humans, domesticated animals, and wildlife. Control of WNV transmission is focused on controlling the mosquito vector through applications of insecticides directly to the environment. In this study, we evaluate a novel control strategy for WNV transmission by targeting the main mosquito bridge vector in the Great Plains region, Culex tarsalis, through its blood feeding behavior. Because Culex tarsalis favor taking blood meals from particular bird species, our strategy aims to target these bird species with endectocide-treated bird feed that will result in lethal blood meals for Cx. tarsalis. In this study, we developed a safe and effective formulation of ivermectin-treated diet that resulted in increased mortality for Cx. tarsalis blood fed on birds consuming this treated diet as compared to mosquitoes feeding on control birds. We also conducted a pilot field trial in Fort Collins, Colorado to test this strategy in a natural transmission cycle, which demonstrated promising results.
| West Nile virus (WNV) is an arthropod-borne flavivirus, and the leading cause of domestically acquired arboviral disease in the United States [1,2], resulting in significant disease and death every year in humans, domesticated animals, and wildlife. From 1999–2017, >48,000 cases of human WNV disease and >2000 deaths were reported to the CDC [3], but the total number of individuals in the U.S. who have been made ill from WNV is estimated to be greater than 1 million, or approximately 1 of every 5 persons infected (>5 million infected individuals) [4]. Control of WNV transmission remains focused on vector control through larvicide and adulticide applications [5]. Larvicide applications are generally preferred to adulticide applications as they are more cost-effective and less environmentally-damaging due to more direct and efficient targeting of mosquitoes [6,7]. While previous studies have demonstrated the effectiveness of larvicide applications to catch basins, a common Culex larval habitat, in reducing the number of mosquitoes [8,9], the efficacy may vary significantly with suboptimal catch basin design or environmental conditions [10,11]. Aerial spraying can be costly [12], but is effective in reducing target mosquito populations [13–16], and has been linked to reductions in human WNV cases in a treated area relative to an untreated area [15] and in entomological measures of WNV risk [16]. Similar ground ultra-low volume application of adulticides may reduce target mosquito populations under ideal conditions, but studies have provided inconclusive data on their effect on WNV infection rates in mosquitoes or subsequent virus transmission [17–20]. Additionally, off-target effects can occur despite optimal calibration of adulticide applications to host-seeking and active times for target vector species [21–23]. Insecticide applications also often face community opposition due to environmental and toxicity/allergenicity concerns [24–28] and are often restricted to urban and semi-urban communities that can afford to fund them [29,30].
WNV is maintained in an enzootic cycle between Culex mosquitoes and avian hosts. The highest WNV disease incidence occurs along the Great Plains region of the United States [31], as the irrigated agriculture provides a supportive habitat for the main WNV bridge vector of the region, Culex tarsalis [32].Therefore, blood meals by Cx. tarsalis from often-bitten avian species may be utilized to selectively target adult females through their blood feeding behavior. Given that the majority of Cx. tarsalis blood meals on the northern Colorado plains may come from select species during the WNV transmission season [33], effective targeting of these preferred hosts with endectocide-treated bird feed could result in control of WNV transmission.
Previous studies have assessed the use of systemic endectocides provided to wild animals to control tick vector populations. Pound et al. evaluated ivermectin (IVM)-treated corn that was fed to white-tailed deer (Odocoileus virginianus) in a treatment pasture to control tick populations [34]. Amblyomma americanum collections from treatment pastures showed a 83.4% reduction in adults, 92.4% in nymphs, and 100.0% in larvae compared to control pastures [34]. IVM-treated feed provided to O. virginianus, which is the definitive host for the reproductive stage of Ixodes scapularis, has also been explored as a method for controlling this vector of Lyme disease. Rand et al. provided an island community of white-tailed deer with IVM-treated corn for 5 consecutive spring and fall seasons [35]. A treatment effect was observed in island deer that reached target IVM sera concentrations resulting in reductions in adult tick density, engorgement, and oviposition rates as well as reduced rates of larval eclosion from any laid eggs compared to collections from untreated deer on a control island [35]. Dolan et al. also conducted a field study that targeted the rodent reservoirs of Lyme disease to reduce the infection prevalence of Borrelia burgdorferi and Anaplasma phagocytophilum with antibiotic-treated bait. Between treated and control areas, they found that B. burgdorferi prevalence was reduced by 87% and A. phagocytophilum by 74% in small mammals, and in questing nymphal ticks, B. burgdorferi prevalence was reduced by 94% and A. phagocytophilum by 92% [36]. A field study testing the passive application of topical acaricide during bait consumption showed reductions of 68% and 84% of nymphal and larval I. scapularis found on white-footed mice, accompanied by a 53% reduction in the B. burgdorferi infection rate of white-footed mice and a 77% decrease in the questing adult I. scapularis abundance between control and treated properties [37].
Rodent baits with feed-through and systemic insecticide activity have also been evaluated to control the phlebotomine sand fly vectors of zoonotic cutaneous leishmaniasis and visceral leishmaniasis. A wide variety of insecticides have been tested for efficacy against multiple phlebotomine sand fly species using larval and adult blood feeding bioassays in multiple rodents. Methoprene, pyriproxyfen, novularon, eprinomectin, ivermectin, and diflubenzuron have been tested for efficacy within the lab [38–41], while fipronil has been additionally tested in field studies [40,42,43]. Systemic insecticides have also been used to target plague transmission, where field trials have assessed imidalcloprid-treated bait for controlling flea populations in California ground squirrels (Spermphilus beechyi), black-tailed prairie dogs (Cynomys ludovicianus), and other rodents [44–46]. To our knowledge, this strategy of endectocide-treated baits has not been evaluated in birds for arbovirus control.
IVM use in birds is primarily off-label; however, IVM has been administered to treat multiple species of parasites that infest birds, including falcons, cockerels, and chickens [47–50]. Moreno et al. characterized the pharmacokinetics, metabolism, and tissue profiles of IVM in laying hens (Gallus gallus) with IVM delivered using intravenous (IV) and oral routes [51]. For both IV and oral routes, expected pharmacokinetic profiles and tissue distributions consistent for a highly lipophilic drug were observed [51]. Bennett et al. demonstrated transfer of IVM through crop milk when adult pigeon pairs were given 3.3 μg/mL IVM dosed in drinking water and housed with brooding squab, and IVM was subsequently detected in squabs following 3 days of daily adult pigeon IVM dosing [52].
In this present study, we evaluated endectocide-treated bird feed as a systemic endectocide to target Cx. tarsalis. 50% lethal concentrations for selamectin, eprinomectin, and ivermectin were determined in artificial blood meals. IVM-treated bird feed was evaluated for safety and consumption rates in chickens. Mosquitocidal effects in Cx. tarsalis fed on IVM-treated birds were also characterized. Lastly, we present the results of a pilot field trial conducted in Fort Collins, CO in 2017 that examined the safety of IVM-treated bird feed in the field and efficacy on entomological indices of WNV transmission.
Animal research was done under CSU IACUC study protocol 16-6552A. Animal euthanasia was applied using sodium pentobarbital as approved in the IACUC study protocol. Field research was done under Colorado Parks and Wildlife Scientific Collection License #17TRb2104 and Fort Collins Natural Areas Permit #914–2017.
Cx. tarsalis (Bakersfield colony) were reared in standard insectary conditions (28 ˚C, 16:8 light cycle). Approximately 150 larvae were reared in roughly 3 gallons of water and fed 2.5 grams of powdered Tetramin fish food daily until pupation. Adults were housed at approximately 300 per cage and fed ad libitum sugar and water until separated for bioassays. Mosquito bioassays were performed to determine the lethal concentrations resulting in 50% mortality (LC50) by adding drug (eprinomectin, selamectin, and IVM) into defibrinated calf blood (Colorado Serum Company) at serial dilutions for artificial membrane feeding. Following blood feeding, Cx. tarsalis were knocked down with CO2, and fully-engorged females were collected and held for 5 days in the same insectary conditions. For all bioassays, mosquito mortality was recorded every 24 hours and analyzed using Kaplan-Meier survival curves and compared using Mantel-Cox (log-rank) test. LC50 values were calculated using a nonlinear mixed model with probit analysis [53].
Artificial membrane blood feeds were also used to test the effects of IVM and WNV on Cx. tarsalis mortality. The WNV strain used was a 2012 Colorado isolate propagated in Vero cells. Negative controls were DMEM (Dulbecco’s Modified Eagle Media) and DMSO (dimethyl sulfoxide) at the same volumes as WNV and IVM, respectively. For the concurrent blood feed of WNV and IVM, IVM at 73.66 ng/mL (LC75) and WNV at low titer (5x105 PFU/mL) or high titer (107 PFU/mL) were fed in a membrane blood meal to Cx. tarsalis and mortality was observed as described above. For the WNV-exposure followed by an IVM blood feed, mosquitoes were fed a first blood meal containing 107 PFU/mL of WNV or DMEM for a mock-exposure. Fully engorged females were sorted and held for 10 days, then fed a second blood meal containing 73.66 ng/mL IVM, after which fully blood fed females were sorted and mortality observed.
4–6 weeks old white leghorn chickens were divided into groups (n = 4) that were housed separately, and which were provided clean water daily and control (untreated) diet consisting of a cracked corn mix (Chick Start and Grow, Northern Colorado Feeders Supply) mixed with any additives that were also added to IVM-treated diet for 3 or 7 consecutive days. IVM-treated diet consisted of two formulations: an Ivomec formulation where liquid Ivomec (Merial) was mixed directly into the cracked corn mix and a powder IVM formulation where powder IVM (Sigma-Aldrich) was mixed into all-purpose flour at 5% and then added to the cracked corn mixture to aid in even powder distribution. Chickens were fed ad libitum and feed consumed by each group was measured daily. Chickens were weighed daily and observed for clinical signs of toxicity, including diarrhea, mydriasis, ptosis, stupor and ataxia. The amount of chicken feed consumed was compared between groups using the students t-test and chicken growth rates were compared using linear regression. Blood was collected from these chickens through venipuncture at the end of their IVM diet regimen and for two days following IVM diet withdrawal. Serum was then isolated from the blood samples and stored at -80°C until further analysis.
Eurasian collared doves (Streptopelia decaocto) were captured by mist net in Wellington, CO and brought back to CSU. They were housed in groups of three and provided ad libitum clean water and either control diet or powder IVM formulation diet of 200 mg IVM/kg of diet for 10 days. Three doves were fed each control and powder IVM formulation diet and then used for mosquito bioassays.
Mosquito bioassays following blood feeding on birds were conducted on the last day of the IVM diet regimen for each group and for two days following IVM diet removal. For direct blood feeding on birds, the downy breast feathers were trimmed, and the exposed bird breast was placed on top of the mosquito cage. The birds were gently restrained for 30 minutes while the mosquitoes blood fed through the mosquito cage organdy. Given the difficulties of direct mosquito blood feeding on live chickens, supplemental serum-replacement membrane blood feeds were also performed, where frozen chicken serum was used in reconstituted blood meals using red blood cells from defibrinated calf blood [54,55].
All research with animals was reviewed and conducted under authorization by the Colorado State University Institutional Animal Care and Use Committee, protocol 16-6552A. Colorado State University Animal Care and Use is Public Health Service (PHS) and Office for Laboratory Animal Welfare (OLAW) assured (#A3572-01), United States Department of Agriculture (USDA) registered (#84-R-0003), and Association for Assessment and Accreditation of Laboratory Animal Care (AAALAC) accredited (#000834).
All chemicals used in derivatization were HPLC grade and purchased from Sigma-Aldrich. IVM was extracted from serum following methanol precipitation [56]. 400 μL of methanol was added to 100 μL serum and vortexed for 1.5 min. Methanol precipitation was carried out at -80˚C overnight. Samples were centrifuged for 30 min at 16,000 x g. Supernatants were transferred and evaporated to dryness using a Speedvac concentrator (Savant). The dry residue was dissolved in 20 μL acetonitrile. Samples were derivatized according to previously published literature [57].
A Waters 700 autosampler system was used to quantify IVM by high-performance liquid chromatography (HPLC)-fluorescence. A mobile phase of acetonitrile/water (3:1, v/v) was pumped through a C8 column (Waters, XBridge BEH C8 XP, 130 Å, 2.5 μm, 2.1x100 mm) at a rate of 0.45 mL/min. Excitation and emission spectra were 365 and 470 nm, respectively. 10 μL of derivatized sample was injected by the autosampler.
Precision was quantified as coefficient of variation (%CV). This was calculated interday and intraday, evaluating drug-free chicken serum samples (n = 5) spiked with IVM at 25, 50, and 100 ng/mL. Instrument CV was 6.11%. Intraday CV ranged between 4.36 and 9.77%. Interday reproducibility was 15.39%. Retention time CV was 1.77%.
The method was linear across the range of concentrations tested in the standard curve (3.125–100 ng/mL). Linear regression curves containing fortified IVM serum samples with concentrations of 3.125, 6.25, 12.5, 25, 50, and 100 ng/mL had a R-square value of 0.9974. Limits of detection and quantification were 1.56 ng/mL and 3.125 ng/mL, respectively.
For the 2017 pilot trial, field sites were located in urban and suburban areas in the City of Fort Collins (mainly in city open space areas and near water sources) that were weekly mosquito trapping sites used by the city for WNV surveillance efforts and have been maintained since 2006 (S1 Fig). Six field sites were chosen based on historical WNV surveillance data from all city trapping sites as those having the highest number of WNV-positive Cx. tarsalis pools since 2006, while excluding trap sites in neighborhoods that are regularly treated with adulticides or used as sentinel sites for the Colorado WNV surveillance system by the state department of health. The 6 chosen sites were all in east Fort Collins and were randomly placed into the treatment group (3 sites; mosquito traps surrounded by IVM-treated bird feed stations) or the control group (3 sites; mosquito traps surrounded by control un-treated bird feed stations). At each field site, an array of three bird feed stations was placed in an approximate triangular perimeter around the mosquito trap at a distance of 50 m (S1 Fig). IVM-treated bird feed was used at a concentration of 200 mg/kg of diet, and the diet was a mixture of white proso millet, cracked corn, and flour (47.5:47.5:5, v/v/v). IVM-treated bird feed was changed daily to account for any effects of IVM degradation due to exposure, which also allowed for daily monitoring of any obvious adverse effects of IVM in local fauna.
Motion-activated trail cameras were used to document bird visits to feeders, with each field site having a motion-activated trail camera placed at one of the three feeders. Photos were screened using the Sibley Guide to Birds [58]. Due to an overabundance of pictures, only a random sampling of 6 days from the 2017 season were counted. Bird trapping and sampling of their blood was performed at two IVM sites. Birds were caught using mist nets placed approximately 10 m from an IVM-treated bird feeder. Blood was collected from netted birds using jugular venipuncture and placed into serum separator tubes. Bird sera were analyzed using HPLC-fluorescence and a subset of samples was analyzed using LC-MS. Because 200 μL of blood could not be drawn from the sparrows as needed for HPLC-fluorescence quantification, IVM analysis for sparrows was only documented as presence or absence. Control sera from house sparrows caught in spring 2014 were used as negative controls. Serum from one IVM-positive grackle was also used in a serum-replacement blood feed with colony Cx. tarsalis for a mosquito survival bioassay.
Mosquitoes were processed as part of the Fort Collins WNV surveillance program according to established protocols [59]. Briefly, mosquitoes were collected weekly by Vector Disease Control International using miniature CDC light traps baited with CO2. Mosquitoes were sorted to species and pooled into groups of typically no more than 50. Mosquito pools were screened at CSU using qRT-PCR using the following primer sequences: forward 5’ 1160-TCAGCGATCTCTCCACCAAAG 3’, reverse 5’ 1209-GGGTCAGCACGTTTGTCATTG 3’, probe 5’ FAM-1186-TGCCCGACCATGGGAGAAGCTC 3’ [59].
Bird sampling was done under Colorado Parks and Wildlife Scientific Collection License #17TRb2104 and Fort Collins Natural Areas Permit #914–2017.
Chicken feed consumption was compared between groups using a t-test. Linear regression was done on chicken weights and the rate of weight gain was compared using Analysis of Covariance.
For mosquito bioassays, survival was analyzed using Kaplan-Meier survival curves and compared using Mantel-Cox (log-rank) test. LC50 values were calculated using a nonlinear mixed model with probit analysis [53]. IVM sera concentrations from chickens were compared using ANOVA. IVM sera concentrations from individual chickens were correlated to cumulative mosquito morality from bioassays conducted on the respective chickens using Spearman correlation.
The field trial utilized control and treatment sites located in the City of Fort Collins; however, it was an exploratory trial to test a new trial design and sites, and so was not powered for detecting differences in Cx. tarsalis abundance and WNV infection. Cx. tarsalis abundance from control and treatment sites were compared against each other using a generalized linear mixed model with negative binomial distribution that included site, week of trapping, and treatment. Cx. tarsalis abundance was also shown in comparison to historical data from 2006–2016 (which lacked any bird feed stations surrounding the traps). WNV infection rate was calculated as maximum likelihood estimate (MLE) using the Excel PooledInfRate Add In [60], but Fisher’s exact test was again used to compare the total number of WNV-positive and WNV-negative pools between control and treatment sites.
Statistical analyses were done in GraphPad Prism (Version 7) and R (Version 3.3.1).
Mosquitocidal concentrations of IVM, selamectin, and eprinomectin were determined with mosquito bioassays following blood feeds with serially diluted drug (S2 Fig). IVM had the lowest LC50 concentration at 49.94 ng/mL (Table 1) as compared to eprinomectin with a LC50 of 101.59 ng/mL and selamectin with a LC50 of 151.46 ng/mL. With the lowest effective concentrations, ivermectin was chosen for further characterization in birds.
Potential interactions of IVM and WNV on Cx. tarsalis mortality were assessed in a simultaneous blood meal containing IVM (LC75) and WNV. Feeding with IVM only resulted in significantly increased mortality compared to DMSO controls; however, the observed 41% and 83% mortality for IVM control groups (Fig 1A and 1B) reflect the variability of mosquito bioassays, especially for intermediate ranges of lethal concentrations. WNV (both low and high titer) exposure in the absence of IVM did not affect Cx. tarsalis mortality over 5 days immediately after the blood meal (Fig 1A and Fig 1B), or following a second untreated blood meal 10 days later (Fig 1C). On the other hand, Cx. tarsalis given a concurrent blood meal containing low-titer WNV and IVM exhibited significantly increased mortality at 51% compared to the control IVM group not fed WNV with 41% morality (p = 0.0268, χ2 = 4.904) (Fig 1A). However, there was no significant difference (p = 0.2529, χ2 = 1.307) in mortality between Cx. tarsalis fed a concurrent blood meal containing high titer WNV and IVM compared to the control (Fig 1B). Similarly, Cx. tarsalis given a first blood meal of either DMEM control or high titer WNV, and then a second blood meal containing IVM 10 days later, showed no significant differences in mortality (p = 0.1637, χ2 = 1.940) (Fig 1C).
Over 7 days of observation, there were no observable clinical signs of IVM neurotoxicity—diarrhea, mydriasis, ptosis, stupor, and ataxia–in groups that consumed either liquid Ivomec or powder formulations of IVM of 200 mg IVM/kg of diet.
For the Ivomec formulation diet, the chickens consumed an average 59.3 g of feed per chicken daily. This was significantly less than the corresponding control group which averaged 121.6 g of feed per chicken per day (p = 0.0045, t = 3.490). Consequently, there was also a significant difference (p <0.0001, F = 19.45) in the rate of weight gain between Ivomec and control groups (S3A Fig). For the powder IVM formulation diet, the IVM group consumed 60.97 g of feed per chicken each day, which was not significantly different from daily control group consumption of 55.2 g of feed per chicken (p = 0.2928, t = 1.100). This was also reflected in similar rates of weight gain between powder IVM and control groups (p = 0.0680, F = 4.022) (S3B Fig).
Cx. tarsalis mortality following blood feeding on IVM-treated chickens increased as IVM concentration within the diet increased (S4 Fig). There were significant differences in mosquito mortality following blood feeding on chickens given 50 mg IVM/kg of diet (p = 0.0132, χ2 = 6.146) and 100 mg IVM/kg of diet (<0.0001, χ2 = 86.48). However, the largest increase in mortality (p<0.0001, χ2 = 461.1) following blood feeding was at 200 mg IVM/kg of diet with 95.2% mortality in mosquitoes fed on IVM-treated chickens and 2.7% mortality in mosquitoes fed on control chickens. All subsequent experiments used IVM-treated feed at 200 mg IVM/kg of diet.
For the Ivomec formulation at 200 mg IVM/kg of diet, there was a significantly increased mortality in mosquitoes blood fed on chickens consuming Ivomec-diet for either 3 or 7 days as compared to mosquitoes blood fed on control chickens (Fig 2; left and right panels, respectively). On the last day of Ivomec feed administered, for both 3 or 7 days, there was a significant increase (p<0.0001, χ2 = 80.22 and χ2 = 76.41, respectively) in mortality between mosquitoes blood fed on chickens consuming an Ivomec diet with upwards of 80% mortality as compared to mosquitoes blood fed on control chickens with less than 40% mortality (Fig 2A and 2B). This difference in mosquito mortality between treatment and controls decreased when the blood feed occurred 1 day following the withdrawal of the Ivomec diet in the treatment group (Fig 2C and 2D). After 2 days following Ivomec diet withdrawal, there was no significant difference in mosquito mortality between those blood fed on Ivomec-consuming chickens as compared to mosquitoes blood fed on control chickens in the 3 day group, but there was a significant difference in the 7 day IVM group (p = 0.0117, χ2 = 6.354) which is likely due to the variability in mosquito bioassays (Fig 2E and 2F). In addition, the time administered Ivomec-treated diets (3 vs. 7 days) did not affect mosquito survival curves following direct blood feeding on chickens, regardless if the mosquitoes were blood fed on the last day of chicken time on the diets, or if the chickens were 1 or 2 days post withdrawal of the diets (Fig 2, left vs. right panels).
There was also significantly increased mosquito mortality in mosquitoes blood fed on chickens consuming the powder formulation of IVM (200 mg IVM/kg of diet) compared to mosquitoes fed on control chickens (S5 Fig). Because bioassays from the Ivomec formulation and a preliminary powder formulation indicated no differences between mosquitocidal effects for groups given IVM for 3 or 7 days, these and subsequent experiments focused on the 7 day time point. A direct blood feed of mosquitoes on chickens given a powder IVM diet for 7 days resulted in 92.3% mosquito mortality as compared to 25.7% mosquito mortality from those blood fed on control chickens (p<0.0001, χ2 = 41.23) (S5A Fig), while an indirect, serum-replacement blood feed using sera from chickens given a powder IVM diet for 7 days resulted in 79.0% mosquito mortality as compared to 16.7% mortality from those blood fed on control chicken serum (p<0.0001, χ2 = 42.83) (S5B Fig). Furthermore, the mosquito survival curves between those blood fed directly on IVM-treated chickens as compared to sera from IVM-treated chickens were significantly different (red lines in S5A Fig vs. S5B; p<0.0001; hazard ratio 2.007). At 1 day post-powder IVM diet withdrawal, there was still a significant difference (p = 0.001, χ2 = 10.86) in mosquito mortality between those directly blood fed on IVM-diet vs control-diet chickens (S5C Fig; 90.9% vs. 0% mortality). However, this mosquitocidal effect was not apparent in a serum-replacement blood feed derived from chicken blood taken 1 day after IVM diet withdrawal (p = 0.7445, χ2 = 0.1062) (S5D Fig). As above, the mosquito survival curves between those blood fed directly vs. indirectly on treated chickens 1 day post-diet withdrawal were also significantly different (red lines in S5C Fig vs. S5D; p<0.0001; hazard ratio 6.742). At 2 days post-IVM diet withdrawal, blood/serum from treated chickens was no longer mosquitocidal in either direct blood feeding (p = 0.8402, χ2 = 0.04065) or serum-replacement (p = 0.1792, χ2 = 1.804) assays (S5E and S5F Fig).
Direct blood feeds of Cx. tarsalis were also conducted on six wild caught Eurasian Collared Doves fed either a powder IVM formulation diet of 200 mg IVM/kg or control diet in the laboratory (Fig 3). There was a significant difference in mosquito mortality (p<0.0001, χ2 = 60.34) with 88.5% mortality in Cx. tarsalis fed on IVM-treated doves as compared to 14.3% mortality from mosquitoes blood fed on control doves. Additionally, there were no clinical signs of IVM toxicity observed in this treated bird species.
Neither the IVM formulation nor the time for which the chickens consumed IVM-treated diet resulted in significant differences in average IVM serum concentrations (p = 0.2715, F = 1.472) (Fig 4A, blue vs. green bars). On the last day of IVM diet, the average IVM serum concentrations (with SD) were 88.575 (±43.613) ng/mL for 3-day Ivomec, 45.255 (±70.051) ng/mL for 3-day powder IVM, 21.910 (±20.914) ng/mL for 7-day Ivomec, 45.745 (±33.852) ng/mL for 7-day powder IVM. Chicken IVM serum concentrations decreased following withdrawal of the IVM diet and were nearly undetectable at 2 days post-withdrawal, which corresponded with mosquito bioassay results showing decreases in mosquitocidal activity following IVM-diet removal. Additionally, IVM serum concentrations were correlated to resulting mosquito mortality from blood feeding on these corresponding IVM-powder fed chickens (Fig 4B). There was a higher correlation between IVM serum concentrations and mortality from serum-replacement feeds with a Spearman r of 0.8629 (P = 0.0007), while the correlation between IVM serum concentrations and mortality from direct blood feeds was 0.4153 (p = 0.3062).
For a pilot trial testing IVM feed in a natural transmission cycle, feeder stations were placed in urban and suburban areas within the City of Fort Collins (S1 Fig) and randomized to treatment or control sites. Bird visits to IVM feeders at all sites were dominated by grackles with infrequent visits by house (Passer domesticus) and sagebrush sparrows (Artemisiospiza nevadensis) and black-capped chickadees (Poecile atricapillus) (Table 2). There were also two visits by blue jays (Cyanocitta cristata), and a few other birds which could not be identified from the photographs. A more homogenous mix of grackles, house and brewers (Spizella breweri) sparrows, blue jays, black-capped chickadees, bushtits, and squirrels visited control feeders (Table 2).
Birds were also caught by mist net and their sera assayed for IVM at the end of the field season. Ten grackles and 5 sparrows were caught over 4 mornings of sampling on August 30th and September 2nd, 3rd, and 7th. Most birds had been observed feeding from the IVM-treated feeder immediately preceding mist net capture. Nine grackles and 4 sparrows (87% of tested sera) had detectable levels of IVM within their serum, and the negative control sparrow serum from 2014 had no detectable IVM (Table 3). Serum from grackle #5 (Table 3) was plentiful and thus further used in a LC-MS assay to confirm the presence of IVM, and also tested in a serum-replacement bioassay. Interestingly, even though the IVM serum concentration in grackle #5 was measured as 5.7 ng/mL, there was strong mosquitocidal effect from this serum (100% mortality within 2 days; p<0.0001, χ2 = 54.15) compared to control mosquitoes fed on control calf serum (Fig 5).
Cx. tarsalis abundance over time in 2017 at the urban and suburban field sites was similar to historical data collected from the same traps for 10 years prior (Fig 6A). A generalized linear mixed model with negative binomial distribution did not find a significant difference between Cx. tarsalis abundance at IVM sites compared to control sites (p = 0.161, z = 1.401) (Fig 6B). The low number of WNV infections did not allow for robust statistical analysis, although MLE was calculated (Fig 6C). A combined Fisher’s Exact Test of all 6 field sites showed a non-significant decrease in the proportion of WNV-positive pools to WNV-negative pools among control and treatment traps (p = 0.2081) (Fig 6D).
This study presents a novel characterization of IVM-treated bird feed as a systemic endectocide to control WNV transmission. Lab studies characterized the effects of IVM-treated bird feed in both domestic and wild birds, especially mosquitocidal effects in Cx. tarsalis blood fed on birds consuming this IVM-containing diet. In addition, a pilot field trial was performed over a WNV season to gather preliminary efficacy data on the effects of IVM-treated bird feed within a natural WNV transmission cycle between wild birds and mosquitoes.
IVM was determined to be the most effective endectocide tested with the lowest lethal concentrations for Cx. tarsalis. In addition, there did not appear to be a synergistic effect of IVM and WNV on Cx. tarsalis mortality in either a simultaneous blood feed of IVM and high titer WNV or sequential blood feeds, the first containing WNV and the second containing IVM. There was a statistical difference between survival curves of Cx. tarsalis fed a concurrent blood meal of a low WNV titer IVM compared to Cx. tarsalis fed only IVM. However, this increased mortality was likely due to the variable survival response of mosquitoes to IVM particularly at intermediate lethal concentrations, rather than a biologically significant interaction between WNV and IVM as there was no mortality difference between mosquitoes fed a concurrent higher titer WNV+IVM blood meal compared to mosquitoes fed DMEM+IVM. There was also no difference between mosquitoes previously exposed to WNV and then fed IVM as compared to mosquitoes unexposed to WNV and then fed IVM. While there is a study suggesting that IVM can inhibit WNV replication by targeting NS3 helicase activity, this was an in vitro cell-culture study using mammalian cells, and the concentration of IVM needed to inhibit 50% of the RNA synthesis in the Vero cells infected with WNV was considerably higher than what was achieved in our chickens following IVM feed consumption [61].
No clinical signs of toxicity were observed in any of the birds consuming either formulation of IVM feed. This was not surprising as IVM is given therapeutically in bird species in a wide range of doses (0.2 mg/kg to 2 mg/kg), depending on route of administration. However, more detailed studies of IVM toxicity should be conducted in multiple bird species in future controlled experiments. Previous studies have identified neurotoxic effects in pigeons following long-term consumption of a diet containing avermectin [62,63], of which IVM is a safer derivative [64]. Specifically, Chen et al. observed clinical signs of neurotoxicity, ranging from reduced activity and food intake following avermectin consumption for 60 days on a 20 mg/kg diet, to ataxia and spasms following avermectin consumption for 30 days on a 60 mg/kg diet [63]. On the other hand, a characterization of IVM pharmacokinetics, metabolism, and tissue distribution in laying hens treated intravenously (400 μg/kg) or consuming IVM-treated water (400 μg/kg/day) for 5 days did not report any ill effects in the birds [51]. Following the intravenous injection of the hens, the highest IVM plasma concentrations (739.6 ± 50.2 ng/mL) were 30 minutes after administration and plasma concentrations remained below 10 ng/mL after 24 hours [51]. Mean IVM concentrations in our chickens fed exclusively on an IVM-containing diet for 3 and 7 days were approximately 45 ng/mL, and similarly we did not observe any neurotoxicity. It remains to be determined if these results vary among different bird species or longer times on the diet. However, in the field studies, it is unlikely that the IVM-treated bird feed was the sole or even primary source of food for the wild birds visiting the feeders given the abundance of alternative food sources during summer.
While chickens on the powder IVM and control diets consumed equivalent quantities of food, there was a significant difference in feed consumption among chicken fed the Ivomec diet and their controls. This may be a result of the glycerol formal and propylene glycol carriers in Ivomec that could give an unpleasant taste, as propylene glycol has been identified as a unpleasant and unpalatable feed additive in cattle [65]. Consequently, the decreased Ivomec feed consumption relative to control feed consumption is likely responsible for the significantly reduced rate of weight gain in the Ivomec group as compared to controls.
Chickens that consumed either a powder IVM or Ivomec diet reached mosquitocidal levels of IVM in their blood within 3 days, as demonstrated by both the IVM serum concentrations in the chickens as well as the significant difference in survival curves of mosquitoes blood fed on IVM-treated chickens compared to controls. There were no notable differences between either IVM diet formulations in mosquitocidal efficacy when considering either time to achieve a mosquitocidal effect and IVM persistence in chicken serum following IVM withdrawal. Furthermore, the time the chickens were placed on the two IVM diets (3 and 7 days) did not significantly affect mosquito mortality, serum concentrations, or the elimination time of IVM from serum following feed withdrawal. This is corroborated by the similar IVM serum concentrations at all time points among the different IVM administration times and formulations. A mosquitocidal effect, but no observable bird toxicity, was demonstrated for wild-caught Eurasian collared doves following consumption of the 200 mg IVM/kg diet, indicating similar mosquitocidal efficacy of the approach in one other bird species and thus potential application to other wild bird species in field settings.
The mosquito mortality in control groups had a greater variation for direct blood feeds (17.75% CV) relative to control groups for serum-replacement blood feeds (3.57% CV), indicating that direct blood feeds results in more inherent variability in mosquito mortality. This increased variability could be a result of increased mosquito handling and rougher conditions during direct blood feeding on birds. It is also possible this higher variability is partly due to smaller sample sizes from the direct blood feeds due to the low success of our colony mosquitoes imbibing full blood meals from live chickens. Regardless, the higher variability among direct blood feed data led to a weaker correlation between IVM serum concentrations and mosquito mortality compared to that from serum-replacement blood feed data. However, despite this higher variability, cumulative mosquito mortality from these direct blood feeds was higher (consistently above 75%) compared to that from the serum-replacement feeds, and mostly independent of measured IVM concentration in the chickens’ sera. One likely possibility for this discrepancy is that the IVM concentration within serum extracted from venous blood may not always be an accurate representation of the IVM concentration in subdermal capillary blood on which mosquitoes blood feed. It has been previously proposed that because IVM is extremely lipophilic and sequestered in fatty tissues, there may exist a concentration gradient of higher IVM or IVM metabolite concentrations in adipose tissue and blood of the surrounding capillaries compared with venous blood [66]. This is also one explanation for the observation that the IVM serum concentrations in chickens correlated with higher cumulative mosquito mortality than would be predicted from the LCx values calculated using artificial membrane feeds. A useful future analysis would be to compare mosquito mortality results from direct skin blood feeding on chickens, membrane blood feeds using venous blood drawn from the chickens, and serum replacement blood feeds using unfrozen serum from the same chickens.
The mosquitocidal effect from chickens on an IVM-containing diet did not extend past one day after IVM-feed withdrawal, and this corresponded with the IVM serum concentrations that were generally below detectable limits by two days post-IVM feed withdrawal. This could potentially be a concern for applying this strategy in the field as it would suggest that frequent bird visits would be necessary to maintain their mosquitocidal blood concentrations of IVM. However, our field data indicated that wild birds were visiting the bird feeders and did have detectable levels of IVM within their sera during multiple days throughout the trial. In addition, one grackle from our 2017 field trial had strongly mosquitocidal serum as assessed in a bioassay, even though the IVM concentration in that serum was surprisingly low. It is promising that a majority of the birds tested had detectable levels of IVM within their sera, indicating that there was an unexpectedly high coverage of IVM in captured birds. However, the placement of mist nets at roughly a 10 m distance from an IVM feeder may have biased the sampling towards birds that visited the feeder, so future studies should more intensively sample birds at wider radii from the feeders. Understanding IVM coverage and persistence within wild birds is an important component of determining the efficacy of this strategy and should be supplemented with detection of IVM in wild-caught blood fed Cx. tarsalis in future field seasons. This could also be coupled with mosquito survival bioassays using wild bird sera to assess mosquitocidal activity as we performed here.
This use of IVM-treated feed as a systemic endectocide to control WNV transmission is based on targeting Cx. tarsalis by medicating its preferred host species. Previous studies in California implicate Cx. tarsalis as a regionally adaptive, opportunistic blood feeder with a preference for avian hosts, and the diversity of available blood meal sources is reflected in the composition of its blood meals [67–71]. Important avian hosts for Cx. tarsalis in small rural towns within Weld County, which is adjacent to our Fort Collins field site area, include American Robins, doves, and other Passeriformes [33]. American Robins are an important Cx. tarsalis blood meal source and WNV amplification host that does not frequent bird feeders and would not be targeted by this current strategy [33,72,73]. However, doves and passerines are preferred blood meal sources of Cx. tarsalis and contribute to the cumulative number of WNV-positive Cx. tarsalis at estimated rates of approximately 30% in June, 60% in July, and 85% in August [33]. This represents a large proportion of Cx. tarsalis blood meal sources and WNV-positive contributions from birds that consume grain and seed that could be targeted throughout the summer season. However, our trail camera data did not show a large proportion of visits from these species identified as regionally important. For example, grackles were predominantly visiting our IVM-treated feeders, while control feeders were visited mostly by grackles, blue jays, brewer’s sparrows, and squirrels. However, the single trail camera we employed per site may not have fully documented bird visits to other feeders at the field site. Camera placement was limited to tree-filled areas where a feeder could be placed with a camera locked to a tree across from the feeder, and this may have biased the camera data against bird species that feed in open space or brush rather than among trees. This limitation of the field camera data is illustrated by our detection of IVM in house sparrows caught by mist net, but we had no documentation of sparrow visits on the trail camera for this specific field site. An important future direction will also be to gather a more updated understanding of the Cx. tarsalis blood meal sources within urban and suburban area of the City of Fort Collins, which might allow for specific targeting of these bird species with attractive bird feed compositions and an optimized bird feeder design.
In addition to a better characterization of avian blood meal sources for Cx. tarsalis, a more complete understanding of bird and Cx. tarsalis spatial dynamics is also important for determining the best placement for the IVM-treated feeders. Because our field sites were chosen based on historical mosquito and WNV surveillance, we did not account for crucial bird parameters that may have influenced mosquito sampling. For example, birds may have fed at the IVM-treated feeders and returned to their communal roosts where they would have been blood fed on by Cx. tarsalis [33,70,74], representing a treatment effect in a different population of Cx. tarsalis than sampled at our traps. Accounting for these bird-mosquito spatial dynamics by placing IVM-treated feeders near communal roosts of granivorous birds and sampling mosquitoes within close range may show the greatest entomological treatment effect, especially as Kent et al. gives an example of a house sparrow roost serving as both a major blood meal and amplification source of WNV-positive Cx. tarsalis [33]. While communal bird roosts could present a critical target, this strategy should continue to be tested in areas of increased human use such as parks and backyards. This highlights that future studies should also consider the best placement of bird feeders in the context of both human land use, and bird and mosquito interactions.
Our pilot field trial was ultimately inconclusive and did not find a significant difference in Cx. tarsalis abundance or WNV infection due to IVM treatment. This is likely due to three field sites for each trial arm being underpowered to observe a significant effect. However, these preliminary field data will serve as important effect size variables with which to properly power future field trials. In addition, this strategy of controlling vector pathogen transmission with an endectocide like IVM is based on shifting the mosquito population age structure in a treatment area from older, infectious mosquitoes to younger, non-infectious mosquitoes, and is less dependent on reducing total mosquito abundance. This has been modeled, as well as observed with empirical data, in trials testing IVM for malaria transmission control [75,76]. We would also expect to see a shift in the age structure of the population to fewer older, infectious Cx. tarsalis and more uninfected, younger mosquitoes. However, our preliminary results from ovary dissections and parity scoring according to Detinova [77] showed consistently high parous rates within the field-caught Cx. tarsalis. This suggested that autogeny, or the ability to develop a batch of eggs without imbibing a blood meal, could be present among the Cx. tarsalis in our study area and confounded our data, and we chose to not conduct further parity scoring during our pilot field trial. As determining age structure of the wild Cx. tarsalis population would be additional way to evaluate this control strategy, future studies should integrate other age-grading techniques such as near infrared spectroscopy (NIRS) [78,79].
Our characterization of IVM as a systemic endectocide in birds demonstrates its feasibility to be developed into a novel WNV transmission control tool. We have demonstrated that birds readily consume IVM-treated feed in the lab and field with our formulation and concentration, while not displaying any observable clinical signs of toxicity following consumption. Furthermore, Cx. tarsalis mosquitoes blood feed on these IVM-treated birds and often die as a result. Our pilot field trial testing IVM-treated feed in natural transmission cycles within wild birds and mosquitoes was ultimately inconclusive, but did provide critical effect size variables to inform future trial design. Important future directions will be to optimize treated bird feed formulations for the field and better characterize the pharmacokinetics and pharmacodynamics of this diet within multiple bird species, especially in relation to mosquitocidal activity and physiological/clinical signs of toxicity. In addition, a more-updated, regionally-specific understanding of the blood meal host preferences of Cx. tarsalis across urban, suburban and rural habitats would allow for better targeting of these preferred host species through the design of an attractive bird feed composition, discriminating bird feeders, and optimized bird feeder location for application to different geographic areas. Finally, our field study provides an important template for future field studies across multiple WNV seasons that will be adequately-powered for measuring effect sizes in entomological and other outcomes.
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10.1371/journal.pntd.0005622 | Rapid deployment of a mobile biosafety level-3 laboratory in Sierra Leone during the 2014 Ebola virus epidemic | Ebola virus emerged in West Africa in December 2013. The high population mobility and poor public health infrastructure in this region led to the development of the largest Ebola virus disease (EVD) outbreak to date.
On September 26, 2014, China dispatched a Mobile Biosafety Level-3 Laboratory (MBSL-3 Lab) and a well-trained diagnostic team to Sierra Leone to assist in EVD diagnosis using quantitative real-time PCR, which allowed the diagnosis of suspected EVD cases in less than 4 hours from the time of sample receiving. This laboratory was composed of three container vehicles equipped with advanced ventilation system, communication system, electricity and gas supply system. We strictly applied multiple safety precautions to reduce exposure risks. Personnel, materials, water and air flow management were the key elements of the biosafety measures in the MBSL-3 Lab. Air samples were regularly collected from the MBSL-3 Lab, but no evidence of Ebola virus infectious aerosols was detected. Potentially contaminated objects were also tested by collecting swabs. On one occasion, a pipette tested positive for EVD. A total of 1,635 suspected EVD cases (824 positive [50.4%]) were tested from September 28 to November 11, 2014, and no member of the diagnostic team was infected with Ebola virus or other pathogens, including Lassa fever. The specimens tested included blood (69.2%) and oral swabs (30.8%) with positivity rates of 54.2% and 41.9%, respectively. The China mobile laboratory was thus instrumental in the EVD outbreak response by providing timely and reliable diagnostics.
The MBSL-3 Lab significantly contributed to establishing a suitable laboratory response capacity during the emergence of EVD in Sierra Leone.
| A Mobile Biosafety Level-3 Laboratory (MBSL-3 Lab) and a well-trained diagnostic team were dispatched to Sierra Leone to assist in Ebola virus disease (EVD) diagnosis when the largest outbreak of EVD to date emerged in West Africa in 2014. This setup allowed for the diagnosis of suspected EVD cases in less than 4 hours from the time of sample receiving. The laboratory was composed of three container vehicles and was equipped with advanced ventilation system, communication system, electricity and gas supply system. Multiple safety precautions were strictly applied to reduce exposure risks. A total of 1,635 suspected EVD cases were evaluated from September 28 to November 11, 2014, and none of the staff members was infected with Ebola virus or other pathogens. The China mobile laboratory was thus instrumental in the EVD outbreak response by providing timely and accurate diagnostics. Therefore, the MBSL-3 Lab played a significant role in establishing a suitable laboratory response capacity during the emergence of EVD in Sierra Leone.
| Ebola virus belongs to the Filoviridae family of enveloped viruses and contains a non-segmented negative-strand RNA genome [1,2]. Infection in humans can cause Ebola hemorrhagic fever, with exceptionally high case-fatality rates of more than 50% [3,4]. The incubation period of Ebola virus disease (EVD) is 2 to 21 days [5]. The clinical signs and symptoms are extremely similar to those of the Marburg virus and include fever, body aches, vomiting, diarrhea, rash and, in some cases, both internal and external bleeding [5]. Patients usually die of multiple-organ failure or hypovolemic shock. No licensed therapeutic or prophylactic treatments are currently available.
The largest outbreak of EVD has been ongoing in West Africa since December 2013. As of April 15, 2015, 25,826 cases (10,704 deaths [41.4%]) had been reported by the World Health Organization (WHO) [6]. Although direct contact is the main route of transmission [7–10], EVD is still easily contagious, and healthcare workers have constituted a considerable proportion of all cases. In particular, by April 11, 2015, 864 healthcare workers (503 deaths [58.2%]) had been infected [6].
Ebola virus is classified as a biosafety level-4 agent. Clinical specimen inactivation should be performed in a biosafety level-3 laboratory, and subsequent to this step, routine testing can be performed in a biosafety level-2 laboratory. However, at the time of the outbreak, West Africa had few high-level biosafety facilities, so scientists had to work under difficult and dangerous conditions associated with potential exposure risks [11]. It would take a fairly long time, a large staff and many resources to construct a new fixed biosafety facility, thus delaying prevention and control of the epidemic. Therefore, a mobile unit [12,13] with both biosafety and flexibility was urgently needed to manage epidemics and emergent public health incidents such as the EVD outbreak.
In September 2014, China responded to the appeal made by the United Nations and WHO and offered assistance to the government of Sierra Leone. A truck-based mobile biosafety level-3 laboratory (MBSL-3 Lab) and a well-trained diagnostic team were then dispatched and deployed to the Sierra Leone-China Friendship Hospital, in one of the hardest-hit areas, near Freetown, to assist in EVD diagnosis. The team members and aid supplies arrived on September 17, 2014. It took approximately one week to rebuild part of the hospital into multiple functional regions to meet the specimen testing requirements, including a specimen-receiving region, a supply-storage region, a waste-incineration region, a nucleic-acid-detection region, and a staff-rest area, among others. The MBSL-3 Lab was transported by an airlift jet aircraft (Antonov An-124 Ruslan, Russia) from Beijing Capital International Airport on September 24, 2014, at 03:00 (Beijing time) to Freetown International Airport on September 25, 2014, at 14:00 (Freetown time), with a flight duration of 43 h. It took another three and a half hours to drive the MBSL-3 Lab to the Sierra Leone-China Friendship Hospital. With strict training and standard operating procedures (SOPs), clinical specimen testing began within 60 h after the arrival of the MBSL-3 Lab, enabling the diagnosis of suspected EVD cases in less than 4 hours from the time of sample receiving. In total, 1,635 suspected EVD cases (824 positive [50.4%]) were tested from September 28 to November 11, 2014, and none of the staff members was infected with Ebola virus or other pathogens. Here, we provide a brief overview of the MBSL-3 Lab and the biosafety precautions applied to manage the EVD outbreak.
This Ebola outbreak response was a humanitarian aid mission. The SOPs used were approved by the WHO and the Sierra Leone Ministry of Health and Sanitation (MoHS). The diagnostic results were released immediately after the specimen analyses were completed.
Specimens were delivered to our worksite daily from two sources: the emergency operations center jointly established by the Sierra Leone MoHS and the China medical aid team who accompanied us and was also deployed to the Sierra Leone-China Friendship Hospital.
When picking up the specimens, the staff wore one layer of personal protective equipment (PPE), including a protective suit (Lakeland INC or DuPont, USA), an N95 mask (3M, USA), an anti-impact goggle (3M, USA), two pairs of latex gloves with the inner pair taped to the protective suit and a pair of dedicated shoes and waterproof shoe covers (S1 Fig). The surface of the specimen bucket and the packing bag were disinfected by spraying with 0.25% chlorine-containing disinfectants.
The staff extracted RNA in the BSL-3 Lab wearing two layers of PPE. The inner PPE included a protective suit, an N95 mask, a pair of inner gloves and a pair of dedicated shoes and waterproof shoe covers (S1 Fig). The external PPE included a HEPA filter-equipped powered air purifying respirator (3M, USA), a disposable sterilized surgical gown, a pair of external gloves and waterproof shoe covers (S1 Fig). The specimen bucket was opened within the biosafety cabinet. As Buffer AVL in the QIAamp Viral RNA Mini Kit (Qiagen, Germantown, MD, USA) was insufficient to inactivate samples [14], a combination of physical and chemical inactivation was performed to enhance the inactivation efficiency. The specimens were first inactivated by incubation in a water bath at 62°C for 1h before opening the tube cap to pipette the samples and were then further inactivated by the addition of Buffer AVL to the samples.
RNA was extracted using the QIAamp Viral RNA Mini Kit (Qiagen, Germantown, MD, USA) according to the manufacturer’s protocol. All waste was first chemically inactivated (with 0.25% chlorine-containing disinfectant), then sterilized using a double-leaf autoclave and finally incinerated.
Quantitative real-time PCR (Q-RT-PCR) assays were performed using a set of published primers and probes [15], targeting regions of the glycoprotein gene (F: 5’-TGGGCTGAAAAYTGCTACAATC-3’; R: 5’-CTTTGTGMACATASCGGCAC-3’; Probe: FAM-5′-CTACCAGCAGCGCCAGACGG-3′-TAMRA). RNA was amplified using the One Step PrimeScript RT-PCR Kit (TaKaRa, Japan), and 40-cycle Q-RT-PCR assays were run on the LightCycle 96 System (Roche, Switzerland). Melt curve analysis was performed to confirm the identity of the amplification products. The specimens were considered positive if there was an apparent logarithmic phase in the amplification curve, with melting point confirmed amplification products and the Ct value≤36 (Ct value<26, intense positive; 26≤Ct value≤ 36, weak positive). In contrast, the specimens were considered negative if there was no apparent logarithmic phase, with the Ct value undetermined, and they were considered suspect when 36<Ct value≤40.
The MBSL-3 Lab was equipped with a -20°C freezer and a -80°C freezer, and there was another -80°C freezer outside the MBSL-3 Lab. As a result, we could store a total of 1500–2000 specimens. For short-term storage, namely, within 1 day, we stored the specimens at -20°C. For long-term storage, we stored the specimens at -80°C. The specimens were well packed and surface disinfected with 0.25% chlorine-containing disinfectant before storage. The Sierra Leone-China Friendship Hospital was guarded by the military guard of Sierra Leone, and the freezers were well locked.
Every patient was assigned a unique Outbreak Case ID by the emergency operations center jointly established by the MoHS. Each time a sample was collected, the patient was asked to complete a “VIRAL HEMORRHAGIC FEVER CASE INVESTIGATION FORM”. The sample tube and the investigation form were marked with the Outbreak Case ID and patient name and were then delivered to us. Therefore, the Outbreak Case ID provided a unique number for tracking the patient, the specimen and the test result. The information in our testing report included the Outbreak Case ID, the Ct value yielded by Q-RT-PCR and the confirmed result (Yes/No/Suspect).
According to an agreement with the MoHS, we usually did not contact hospitals directly. Instead, we submitted the testing report to the WHO and the MoHS, which was in charge of delivering the results to hospitals. In particular, the China medical aid team who came with us and was also deployed to the Sierra Leone-China Friendship Hospital could get testing results from us directly.
The China MBSL-3 Lab arrived in Sierra Leone on September 25, 2014, and specimen tests were carried out within 60 h of its arrival. The worksite layout was shown in Fig 1. After receiving specimens, scientists sent them to the MBSL-3 Lab, where RNA was extracted. One room in the hospital was rebuilt and used for subsequent Q-RT-PCR analysis. The MBSL-3 Lab was powered by alternate use of 200kW diesel generators. Lab and household trash was incinerated away from the lab or structures in a pit. There were surveillance cameras all around the worksite and inside every experimental room, and scientists could watch real-time surveillance video and communicate with the experimenters in the laboratory.
An overview of the composition of the China mobile laboratory diagnostic team and the team members’ tasks was shown in Table 1. One scientist was in charge of contacting the MoHS to coordinate issues such as sending specimens and releasing analysis results. In addition, eight scientists engaged in virus detection. Technical support personnel were in charge of the operation of the MBSL-3 Lab, including overseeing the water and electricity supply, maintenance and repair of equipment, sterilization and incineration of lab trash as well as watching and recording the daily experimental process. Two medical doctors monitored the health conditions of every staff member.
The MBSL-3 Lab was composed of three container vehicles. The container encompassing the BSL-3 laboratory was called the main container (L×W×H: 9125×2438×2896mm); the second container, of the same size, was used for personnel cleaning and technology support and was called the auxiliary container; and the third container was the command container (L×W×H: 6300×2460×2100mm). As shown in Fig 2, the main and auxiliary containers were connected by an airtight soft connection and together formed a complete BSL-3 Lab. From the entrance to the inside, in order, there was the outside locker room (0-5Pa), the inside locker room (Buffer room-2, -10Pa), the semi-contaminated channel (-20±5Pa), the air lock room (Buffer room-1, -45±5Pa) and the BSL-3 laboratory (-70±10Pa). The doors were interlocking.
The checklist for the different workplaces and instruments in the MBSL-3 Lab was listed in S1 Table. The MBSL-3 Lab provided triple protection for humans, specimens and the environment. The main performance of the MBSL-3 Lab was detailed as follows.
“Four Flows” management were the key elements of biosafety measures in the MBSL-3 Lab (Fig 4).
To assess the aerosol exposure risk when working in or around the MBSL-3 Lab, air samples were collected from the BSL-3 lab, locker rooms, water treatment room, equipment room, exhaust outlet and command container and were concentrated for EVD detection every 15 days (S1 Fig). Fortunately, all results were negative.
We also collected swabs from the surfaces of potentially contaminated objects to determine whether there was an existing exposure risk (S2 Table). On one occasion, the pipette used to pipette samples from the blood-collection tubes tested positive for EVD, with a Ct value of 27.75.
The diagnostic algorithm for laboratory testing and the rationale for positive/negative/suspect test results were presented in Fig 5. We repeated the testing of the suspect and negative cases and strongly recommended collecting specimens again if collection was performed <3 days post onset of symptoms. We found no evidence of RNA contamination during the entire operation. We added positive and negative controls to every experiment, and all controls produced the expected results.
Overall, 1,635 suspected EVD specimens were tested from September 28 to November 11, 2014, primarily blood/serum samples (69.2%) and oral swabs (30.8%). The sample sources and test results were presented in Table 2. In total, 824 cases (50.4%) were identified as positive, and the positive rate of the swab samples (41.9%) was slightly lower than that of the blood samples (54.2%).
The number of various paroxysmal public health events has been growing, and most have occurred in poverty-stricken areas. However, the resources for medical treatment, outbreak management and laboratory research are concentrated in developed regions, and substantial expenditure would be required to build new medical systems in these areas. Because epidemic situations are always urgent, scientists thus work under inadequate conditions and face exposure risks. Therefore, rapid, safe and flexible outbreak response capacity is urgently needed [17]. A mobile laboratory unit can easily be promptly deployed when needed and can provide a safe working environment, which will be a vital part of the outbreak response to emerging public health events or bioterrorism acts and will make great contributions to lessening and controlling epidemics. Several mobile units have previously been used in natural disaster scenarios [18,19], in health surveys [20,21], during the outbreak of severe infectious diseases [22–24] and in military campaigns [25].
Our MBSL-3 Lab meets the requirements of on-site collection, isolation, cultivation and detection of emergent infectious pathogens. This laboratory also protects humans as well as the environment and specimens, and it was designed to be functional in a field setting, even without logistical support. The major challenges in a remote location may be power supply and water supply, but there are ways to overcome them. There was an 80kVA (≈70kW) diesel generating set in the auxiliary container of the MBSL-3 Lab. Full fuel in the oil box can power the MBSL-3 Lab in continuous operation for 24h. We can bring as much fuel with us as possible using oil tanks, and wherever the MBSL-3 Lab can arrive, a refueling truck could also arrive. The MBSL-3 Lab is also equipped with a water storage tank and a water softener, and water can be re-supplied with water from a well or clear stream. If the experimenters could do not take a shower in the MBSL-3 Lab, the water requirement is not large, approximately 200L per day. In addition, the MBSL-3 Lab is equipped with a leveling system, but it still needs a 20m×8m level ground. This was the first time that we executed a mission in Africa. In total, 1,635 specimens were tested from September 28 to November 11, 2014, accounting for more than one quarter of the nation’s specimen volume during the same period. In all, 824 (50.4%) specimens were EVD-positive, representing 33.3% of the total number of confirmed cases reported in Sierra Leone during the same period. The maximum number of specimens that we could reasonably process in one day is approximately 120–150.
We developed strict SOPs, adopted comprehensive protective measures and used comprehensive medical and logistical support systems to ensure safe and orderly performance of the virus diagnosis task. In particular, the “Four Flows” biosafety protocol was strictly followed. We monitored the exposure risk during clinical specimen testing. Air samples were collected from every workspace, and the test results were all negative, indicating that the working environment was relatively safe. The surfaces of potentially contaminated objects were also swabbed. On one occasion, the pipette used to pipette samples from blood-collection tubes tested positive. Given that a portion of the specimens contained only a small sample volume, the pipette had to be placed deep into the tubes and was easily contaminated by touching the inner wall. Therefore, it was suggested that the barrel of the pipette should be disinfected with disinfectant-containing gauze after pipetting each sample to avoid personnel infection and cross-contamination of samples.
The test results played an important role in the disposal of symptomatic individuals and might, in a sense, determine their fates. For positive cases, the patients would be properly isolated and treated without visiting family members, and traditional religious funerals for the dead were forbidden. For negative cases, the patients would be separated from the positive cases and kept in an observation ward for follow-up testing or discharge to relieve the limited wards. Hence, the accuracy of the test results was crucial. False-positive results might lead to the individual being infected by positive patients, whereas false-negative results might lead to the spread of EVD to families and even the community. Our diagnostic algorithm suggested a suspect conclusion when 36<Ct value≤40 and strongly recommended resampling and considering clinical information and epidemiological links. Q-RT-PCR is now a preferred method for pathogen diagnosis due to its rapid and sensitive features [26], but it is prone to contamination and may result in false-positive results. Therefore, we conducted every experiment in the biosafety cabinet. The cabinet and PCR room were exposed periodically to ultraviolet radiation to eliminate nucleic acid contamination. Additionally, PCR tubes were never opened. Every control included in the PCR assays produced the expected result, indicating high experimental accuracy. Moreover, the MoHS was in charge of retrospective look at the disease progresses of the patients, and to date, we have not received any feedback regarding a false diagnostic case from the MoHS.
We have shown that the positive rate of oral swabs was lower than that of blood samples. The technique and efficiency of swabbing might be one of the most important factors. Swab samples should be obtained by vigorous sampling to acquire sufficient biologic material for testing [27]. A quality-control PCR target (housekeeping gene target), such as Beta 2 Microglobulin (B2M), should be added for sample integrity assessment in the future.
Our MBSL-3 Lab continuously worked for six months and managed 4,867 specimens for EVD diagnostics. During that time, the China CDC established a fixed BSL-3 Lab near the Sierra Leone-China Friendship Hospital for long-term surveillance and to serve as the public health system for future outbreaks and epidemics. Currently, the EVD epidemic situation is under effective control, and our MBSL-3 Lab has been proven to be an important force for disease control and emergency disposal.
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10.1371/journal.ppat.0030058 | Identification of a CCR5-Expressing T Cell Subset That Is Resistant to R5-Tropic HIV Infection | Infection with HIV-1 perturbs homeostasis of human T cell subsets, leading to accelerated immunologic deterioration. While studying changes in CD4+ memory and naïve T cells during HIV-1 infection, we found that a subset of CD4+ effector memory T cells that are CCR7−CD45RO−CD45RA+ (referred to as TEMRA cells), was significantly increased in some HIV-infected individuals. This T cell subset displayed a differentiated phenotype and skewed Th1-type cytokine production. Despite expressing high levels of CCR5, TEMRA cells were strikingly resistant to infection with CCR5 (R5)–tropic HIV-1, but remained highly susceptible to CXCR4 (X4)–tropic HIV-1. The resistance of TEMRA cells to R5-tropic viruses was determined to be post-entry of the virus and prior to early viral reverse transcription, suggesting a block at the uncoating stage. Remarkably, in a subset of the HIV-infected individuals, the relatively high proportion of TEMRA cells within effector T cells strongly correlated with higher CD4+ T cell numbers. These data provide compelling evidence for selection of an HIV-1–resistant CD4+ T cell population during the course of HIV-1 infection. Determining the host factors within TEMRA cells that restrict R5-tropic viruses and endow HIV-1–specific CD4+ T cells with this ability may result in novel therapeutic strategies against HIV-1 infection.
| HIV-1 infection profoundly perturbs the immune system and is characterized by depletion of CD4+ T cells and chronic immune activation, which lead to AIDS. Although HIV-1 targets CD4+ T cells, it also requires a second receptor in order to infect the target cells. The majority of HIV-1 strains that are transmitted use a cell surface molecule called CCR5, which is expressed on a portion of T cells. In this manuscript we identify a subset of human CD4+ T cells, which we termed TEMRA cells, that express CCR5 but still remain resistant to infection. We show that HIV-1 infection is blocked in TEMRA cells after entry of the virus, but before it has a chance to integrate into the cellular genome. TEMRA cells are present at low frequency in HIV-1 uninfected individuals but greatly increase in some HIV-infected individuals, which correlates with higher CD4+ T cell numbers. These findings provide the basis for future studies to understand the role of TEMRA cells during HIV-1 infection and identify the host factors that could restrict the virus. This knowledge may be used to endow susceptible T cells with the ability to resist infection and result in novel vaccine or therapeutic strategies against HIV-1 infection.
| Chronic immune activation and homeostatic disturbance of T cell subsets that accompany viral replication are hallmarks of HIV-1 infection [1–4]. The cause and implications of these profound quantitative and qualitative changes in CD4+ memory T cell subsets during HIV-1 infection are still not well understood [2]. Elucidating the causal relationships between perturbed naïve and memory T cell compartments during the course of HIV-1 infection could be critical in understanding its pathogenesis.
Human T cells are categorized as naïve (TN) and memory (TM) subsets based on expression of CD45RA and CD45RO isoforms, respectively [5–8]. It is now known that memory T cells are comprised of distinct subsets that can be identified based on other surface markers and effector functions [9]. Sallusto and colleagues defined two CD4+ memory T cell subsets, termed central memory (TCM) and effector memory (TEM) cells [8]. TEM cells have low expression levels of the chemokine receptor CCR7 and lymph node homing receptor CD62L, express receptors for migration to inflamed tissues, and display immediate effector functions [8,10]. In contrast, TCM cells express high levels of CCR7 and lack potent effector functions. It has been proposed that TCM cells are responsible for maintaining long-term memory, and upon re-exposure to antigens, differentiate into TEM cells with effector functions. Prior studies indicated that HIV-1 preferentially infects memory, rather than naïve CD4+ T cells [11–16], possibly because of exclusive expression of the HIV-1 coreceptor CCR5 on memory T cells. Within the memory population, TEM cells are enriched for expression of CCR5 relative to other CD4 memory cells [17,18], suggesting that they may be primary targets for CCR5-tropic (R5-tropic) viruses that predominate in most infected persons.
Because chronic HIV-1 infection disrupts the balance between naïve and memory T cell subsets [19], we characterized the distribution of these cells during HIV-1 infection. We found that a small subset of CD4+ TEM cells, which we called CD4+ TEMRA cells, were greatly increased in some HIV-infected individuals relative to uninfected individuals. Remarkably, CD4+ TEMRA cells displayed a specific post-entry block to R5-tropic HIV-1, despite expressing high levels of CCR5. Accumulation of this effector memory CD4+ T cell subset during chronic HIV infection could have important implications in understanding intrinsic resistance to the virus and perturbation of T cell compartments in infected individuals.
The dynamics of T cell changes were studied in HIV-infected and HIV-uninfected individuals by staining their peripheral blood mononuclear cells (PBMCs) with monoclonal antibodies against CD3, CD4, CCR7, and CD45RO cell surface molecules. In most uninfected individuals, this analysis divides CD4+ T cells into three subsets that can be readily quantified: naïve T cells (TN; CD45RO−CCR7+), central memory T cells (TCM; CD45RO+CCR7+), and effector memory T cells (TEM; CCR7−) (Figure 1A, left panel). However, in HIV-uninfected individuals, a fourth subset (CD45RO−/dullCCR7−) was also observed (Figure 1A), albeit with a low frequency (0.5%–3%). This subset was greatly increased in some of the HIV-infected individuals (Figure 1A, right panel). Because these cells resembled a previously defined CD8+ T cell subset (called CD8+ TEMRA cells) with effector functions that expressed CD45RA with effector functions [20], we tentatively termed them CD4+ TEMRA cells (referred to as TEMRA cells hereafter). Conversely, we denoted the CD45RO+CD45RA−CCR7− effector memory CD4+ T cell subset as TEMRO cells. The relationship between TEMRA cells and HIV-1 infection was studied in 33 HIV-infected and 30 HIV-uninfected individuals (Figure 1B). The proportion of TEMRO and TEMRA subsets was significantly increased in HIV-infected individuals (Figure 1B). On the other hand, the proportion of TN cells was significantly decreased in HIV-infected individuals, while the proportion of TCM cells remained similar in both groups (Figure 1B).
The high proportion of TEMRA cells found in HIV-infected individuals prompted further analysis of this subset. We hypothesized that TEMRA cells are a subset of effector memory CD4+ T cells, analogous to a subset recently described for CD8+ T cells with the same surface marker phenotype [20]. The four subsets of CD4+ T cells (TN, TCM, TEMRO, and TEMRA) obtained from HIV-infected and HIV-uninfected individuals were analyzed for expression of cell surface molecules known to be expressed differentially in naïve, memory, and effector T cells. All TN cells expressed CD28, CD27, CD7, and CD62L, with progressively less expression on CD4+ TCM, TEMRO, and TEMRA cells (Figure 2). In contrast, expression of CD11b, CD57, and HLA-DR were increased on TEMRO and TEMRA cells compared to CD4+ TN and TCM cells (Figure 2). In contrast to TCM and TEMRO cells, TEMRA cells also expressed high levels of CD45RA, similar to TN cells (Figure 2, top panel). This profile suggested that TEMRA cells are a subset of CD4+ effector memory T cells with a peculiar CD45RA+CD45RO−/dull phenotype.
Differentiated effector memory T cells have a reduced proliferative capacity [8,20]. To assess the relative proliferative capacity of the different CD4+ T cell subsets, each subset was purified from an HIV-uninfected individual according to CCR7 and CD45RO expression as shown in Figure 1A, and stimulated with dendritic cells (DCs) pulsed with superantigen (staphylococcal enterotoxin B [SEB]). Activated T cells were counted at day 12 (Figure 3A). DC-mediated activation caused robust cell division of TN and TCM cells (Figure 3A), whereas TEMRO cells and TEMRA cells divided fewer times (Figure 3A).
The reduced proliferative capacity of effector T cells correlates with a decrease in telomere length and with an increased propensity to undergo apoptosis [9]. To determine whether TEMRA cells undergo apoptosis similar to effector T cells, all T cell subsets were stained with a marker of apoptosis (Annexin V) before and after cells were stimulated through the T cell receptor (TCR) by anti-CD3 plus anti-CD28 antibodies for 18 h. A higher proportion of effector T cells underwent apoptosis compared to TN and TCM cells (Figure 3B). Levels of apoptosis were comparable between TEMRO and TEMRA cells before and after TCR stimulation (Figure 3B).
A hallmark of TEM cells is secretion of greater quantities of cytokines when stimulated through the TCR, as compared to TN and TCM cells [8,10]. We therefore explored cytokine profiles of TEMRO and TEMRA subsets. As expected, [8,10] TEMRO cells secreted greater amounts of most cytokines assayed (IL-4, IL-5, IL-10, TNF-α, and IFN-γ) compared to TN and TCM cells (Figure 3C). TEMRA cells secreted high levels of IFN-γ, but much lower levels of IL-4, IL-5, or IL-10 compared to TEMRO cells (Figure 3C). This cytokine profile suggested that the TEMRA subset is skewed towards a Th1 phenotype. Recently, a cell surface molecule called CRTH2 was shown to be highly expressed on Th2 but not on Th1 cells [21]. To confirm Th1 skewing of TEMRA cells, we analyzed the surface expression of CRTH2. In agreement with the cytokine profile, significantly fewer TEMRA cells expressed CRTH2 compared to TEMRO or TCM subsets (Figure S1). Taken together, we conclude that TEMRA cells are differentiated effector memory T cells that are skewed toward a Th1 phenotype.
Because TEMRA cells were proportionately increased in some HIV-infected individuals, we next investigated the susceptibility of these cells to HIV-1 infection. For these experiments, TN, TCM, TEMRO, and TEMRA cells purified from PBMCs of HIV-infected and HIV-uninfected individuals were activated through the TCR to render them susceptible to infection. The activated T cells were then infected with either R5-tropic replication-competent HIV (R5.HIV), CXCR4 (X4)–tropic replication-competent HIV (X4.HIV), or replication-defective viruses that only undergo a single round of replication and are pseudotyped with vesicular stomatitis virus glycoprotein G (VSV-G.HIV). Each virus used here encoded green fluorescent protein (GFP) that was used to quantify infection by flow cytometry at specific time points after inoculation [22].
Prior to the infectivity assay, we analyzed the expression of HIV-1 co-receptors CCR5 and CXCR4 on TN, TCM, TEMRO, and TEMRA cells isolated from an HIV-uninfected individual (Figure 4A). TEMRA and TEMRO cells expressed the highest levels of CCR5, while all four subsets expressed high levels of CXCR4 (Figure 4A). In addition, the median CCR5 expression was quantitated from 20 HIV-infected individuals, and the similar subset expression trends were confirmed (Figure S2). When each T cell subset isolated from an HIV-uninfected individual was challenged with R5.HIV, CD4 TCM and TEMRO cells were more susceptible to infection than TN cells (Figure 4B), most likely reflecting high CCR5 surface expression levels on these memory T cells (Figure 4A). In contrast, TEMRA cells were resistant to a high multiplicity challenge with R5.HIV (Figure 4B, top panel). This was an unexpected finding given the high cell surface CCR5 levels on TEMRA cells (Figure 4A). At day 12 post-infection, R5.HIV spread through the cultures, producing more infected TN, TCM, and TEMRO cells as compared to 5 d post-infection. Even at this late time point, TEMRA cells remained almost completely refractory to infection (Figure 4B, second panel). In contrast, TEMRA cells were similarly susceptible to infection with X4.HIV, as well as other T cell subsets (Figure 4B, third panel). Surprisingly, TEMRA cells were also 5- to 10-fold less susceptible to VSV-G.HIV infection than other T cell subsets (Figure 4B, bottom panel).
We then sought to determine whether over time the TEMRA subset would progressively become more susceptible to infection post-activation, or whether these cells were being killed in culture by rapidly replicating virus. For this experiment, T cells were infected with R5.HIV or X4.HIV for 2 d at different multiplicities of infection (MOIs) and then washed to remove input virus. Infection was quantified based on GFP expression at different time points after inoculation (Figure 5A), and viral replication was assessed by quantifying HIV p24 protein in culture supernatants. R5.HIV replicated efficiently in TN, TCM, and TEMRO cells, but there was little or no replication in TEMRA cells (Figure 5B). In contrast, X4.HIV infected and replicated efficiently in all four subsets and rapidly killed most of the T cells (Figure 5A and 5B, right panels; unpublished data). Similar results were observed when primary HIV-1 isolates, utilizing different R5-tropic, X4-tropic, and R5X4-dual tropic HIV-1 envelopes that also express nef, were used (Figure 5C). The infectivity of TEMRA cells activated with SEB-pulsed DCs also remained identical (unpublished data).
The surface marker CD57 identifies terminally differentiated cells [23], and expansion of CD57+ cells occurs in HIV-infected individuals [24]. Because TEMRA cells were enriched in CD57+ cells (Figure 2), we asked whether CD57+ T cells were differentially susceptible to R5-tropic or X4-tropic viruses. For this experiment, TEMRA and TEMRO cells were further subdivided into CD57+ and CD57− subsets by flow cytometry cell sorting. Both CD57+ and CD57− subsets of TEMRA cells were resistant to infection by R5-tropic virus, whereas both CD57+ and CD57− subsets of TEMRO cells remained susceptible to R5-tropic virus infection (Figure 6, top panel). However, the CD57+ and CD57− subsets of both TEMRO and TEMRA cells were similarly susceptible to X4-tropic viruses (Figure 6, bottom panel). Thus, the relative resistance of TEMRA cells to R5-tropic HIV was not attributable to enrichment with the CD57+ subset.
We next investigated where in the HIV-1 life cycle R5-tropic infection of TEMRA cells was blocked. Because large numbers of cells were required for these experiments, we expanded TN, TCM, TEMRO, and TEMRA cells purified from PBMCs of HIV-uninfected individuals using SEB-pulsed DCs for 12 d in IL-2–containing medium. In order to verify that CCR5 expression levels were maintained on expanded T cell subsets and that TEMRA cells remained resistant to R5-tropic infection, CCR5 expression was determined post-activation and expansion (Figure 7A, top panel). The expanded subsets were then reactivated with SEB-pulsed DCs and subsequently infected with R5.HIV. Although the TEMRA cells maintained very high CCR5 expression, they remained resistant to R5-tropic infection (Figure 7A, bottom panel).
We first asked whether the block of R5-tropic infection was at the level of fusion. For this experiment, we employed a recently developed reporter assay to quantify HIV particle entry [25]. Expanded TCM, TEMRO, and TEMRA cells were infected with either R5.HIV, X4.HIV, or VSV-G.HIV. Fusion of these three viruses with TEMRA cells was similarly efficient, whereas fusion was inhibited in both TN and Jurkat cells, which do not express CCR5, or when cells were pre-treated with T20, a fusion inhibitor (Figure 7B). Collectively, these data indicate that the R5.HIV infection block in TEMRA cells is post-fusion.
We next conducted analysis of the stage in the HIV-1 life cycle at which R5-tropic and VSV-G pseudotyped virus replication was blocked in the TEMRA subset. Late reverse transcripts in cells infected with VSV-G.HIV, R5.HIV, and X4.HIV were analyzed. Infection was blocked at the level of reverse transcription in TEMRA cells infected with R5.HIV and VSV-G.HIV, suggesting an early block to infection in these cells that did not affect X4.HIV (Figure 7C).
Because we did not see the accumulation of late reverse transcription products, we wanted to understand whether earlier steps in reverse transcription were impaired. Therefore, we investigated the initiation of reverse transcription of R5-tropic and VSV-G pseudotyped virus in TEMRA cells. Early reverse transcription was assessed by the presence of strong-stop, minus-strand viral DNA (R/U5 DNA) by quantitative real-time PCR. Early transcripts were not formed in TEMRA cells infected with R5.HIV or VSV-G.HIV (Figure 7D). These data suggest that the block in the HIV-1 life cycle occurs at or prior to the initiation of reverse transcription.
Our findings that TEMRA cells are expanded in a portion of HIV-infected individuals and are highly resistant to R5-tropic infection prompted us to examine relationships between high TEMRA cells and CD4 numbers. Among HIV-infected individuals, the TN cell percentage correlated positively with absolute CD4+ T cell numbers (Figure 1B). Conversely, the total TEM cell (TEMRO + TEMRA) percentage correlated negatively with CD4+ T cell numbers (Figure 1B; unpublished data). To further delineate the association between TEMRO and TEMRA cell proportions and CD4 numbers, we subdivided infected individuals into three groups based on their total TEM cells (Figure 8). Infected individuals in whom the TEM percentage of their CD4+ T cells was similar to healthy individuals (bottom group) had high CD4+ cell numbers (Figure 8; unpublished data). In contrast, the group with a very high TEM cell percentage had low CD4+ T cell numbers, and all of these individuals had high levels of TEMRO cells (Figure 8, top group). Importantly, however, when we subdivided the infected individuals with median levels of TEM cells (Figure 8, middle group), a highly significant association between higher TEMRA cell percentage and higher CD4+ T cell numbers and higher TN cells was established (Figure 8). These results imply that a greater proportion of TEMRA cells within the effector T cell subset may identify individuals with better preservation of CD4+ cell numbers, and possibly slow HIV-1 disease progression.
Our investigation of memory T cell subsets during HIV-1 infection led to the discovery of a unique subset of CD4+ T cells called CD4+ TEMRA cells. We found that these cells are highly susceptible to infection by X4-tropic HIV-1 but are almost completely resistant to R5-tropic HIV-1 despite high levels of cell surface CCR5 expression. These cells are also relatively resistant to infection by VSV-G pseudotyped HIV-1. Our findings are consistent with a recent ex vivo analysis of T cell subsets from HIV-infected individuals, which demonstrated that CD4+CD57+ effector memory T cells were associated with approximately ten times fewer copies of viral DNA than TCM cells [23]. Although both CD57+ and CD57− subsets of TEMRA cells displayed the same R5-tropic HIV-1 infection (Figure 5C), overall, CD57+ cells are more enriched within TEMRA cells (Figure 2). Thus, TEMRA cells represent the first unique subpopulation of CD4+ T cells that are uniquely resistant to HIV-1 infection and may emerge as a consequence selection during infection.
Further studies are required to elucidate how TEMRA cells can be resistant to R5-tropic infection despite high levels of CCR5 expression, yet remain susceptible to X4-tropic viruses. In order to exclude that this restriction was at the level of post-entry and not because of downregulation or block of CCR5 by beta-chemokines, we showed that 1) TEMRA cells permitted entry of R5-tropic HIV-1 as measured by the BlaM-Vpr virion fusion assay, 2) TEMRA cells continued to express high levels of CCR5 at the time of infection, 3) and TEMRA cells were partly less susceptible to VSV-G pseudotyped viruses that bypass the coreceptor requirement. Taken together, these results indicate that the post-entry pathway followed by R5-tropic HIV-1 may differ in TEMRA cells compared to other CD4+CCR5+ T cell subsets and to X4-tropic HIV-1–infecting TEMRA cells. It is conceivable that either signaling or the entry pathway through the CXCR4 receptor elicits intracellular events needed for HIV replication or bypasses mechanisms that otherwise restrict HIV-1 in TEMRA cells.
Elucidating cellular mechanisms that determine why some, but not all, CCR5-expressing CD4+ T cells are permissive to R5-tropic HIV-1 infection could provide clues to identify natural cellular HIV-1 barriers. Our findings suggest that at least one subset of primary human T cells display intrinsic restriction that limits HIV-1 infection. The presence of differentiated TEMRA cells in HIV-1 infected individuals and in uninfected individuals, albeit at lower frequency, suggests that these cells expand and survive during the course of the normal immune response. These findings also pose several important questions: How do TEMRA cells arise? Are they repeatedly stimulated memory T cells? What aspect of the TEMRA cell differentiation program renders them resistant to HIV-1 infection? For example, TEMRA cells displayed a preferential Th1 phenotype and exhibited a reduced proliferative capacity as well as a cell surface marker and cytokine profile characteristic of highly differentiated T cells. A subset of CD8+ T cells that are CD45RA+CD27− (CD8+ TEMRA cells) has been shown to display similar phenotypic features to CD4+ TEMRA cells characterized here [8,20,26]. It is not yet clear whether CD4+ TEMRA cells are functionally similar to CD8+ TEMRA cells or what role these subsets play during chronic viral infections. The homeostatic mechanisms that induce and maintain CD4+ TEMRA cells also remains to be determined.
Our finding that TEMRA cells correlate with higher CD4+ T cell numbers in a portion of HIV-infected individuals suggests that virus infection may positively drive selection for HIV-resistant cells in vivo, a phenomenon previously observed only in cell culture but usually involving loss of CD4 expression. Studies using animal models for HIV-1 infection may aid in determining whether there is a causal relationship between virus infection and selective enrichment of the TEMRA subset. Remarkably, HIV-infected individuals whose TEM cells were composed mostly of TEMRA cells were significantly associated with higher CD4+ T cell and TN cell levels. How TEMRA cells accumulate or expand in HIV patients, and whether they have a protective role against progression of disease, remains to be determined. Memory and effector T cells are enriched for CCR5 expression [17,18], suggesting that they are targets for HIV-1, especially T cells resident in the gut tissue [27–30]. It is conceivable that after continuous destruction of susceptible TEMRO cells, an HIV-resistant subset of TEMRA cells is selected. Alternatively, TEMRA cells may have a protective role against HIV-1 infection, perhaps because HIV-specific T cells are enriched in this subset. If TEMRA cells contain a high proportion of HIV-specific effector T cells, this would overcome a potential Achilles' heel of the immune response during HIV-1 infection; that is, CD4+ T cells that are activated by HIV-1 antigens themselves become highly susceptible targets for the virus [31]. Conferring an HIV-resistant ability to HIV-1–specific CD4+ T cells could lead to novel strategies aimed at potentiating a protective immune response against HIV-1 infection.
During the primary and asymptomatic phases of HIV-1 infection, R5-tropic viruses predominate, whereas X4-tropic viruses are found in about 50% of infected individuals at late stages of HIV disease [32–34]. A more rapid decline in total CD4+ T cell counts is often associated with a switch from R5-tropic to X4-tropic HIV or R5/X4 HIV variants [35]. At present, it is unclear whether the switch to X4-tropic viruses is a cause or a consequence of the collapse of the immune system. Because TEMRA cells remain highly susceptible to X4-tropic viruses, it would be expected that these cells would also be rapidly depleted when an X4-tropic switch occurs. If TEMRA cells contain HIV-specific T cells or play some other protective role against infection, then elimination of these cells by X4-tropic viruses would further weaken the immune response against HIV-1 and facilitate immunological deterioration.
In summary, our results demonstrate that CD4+ TEMRA cells are present at a higher frequency in HIV-infected than uninfected individuals and are resistant to R5-tropic HIV infection, but not to X4-tropic HIV-1 infection. Studies focused on emergence of these effector memory T cell subsets will contribute to a better understanding of HIV-1 pathogenesis and the role of these cells during normal immune responses. Decoding the precise molecular mechanism of the intrinsic resistance of TEMRA cells to R5-tropic infection may have significant implications for developing novel approaches to endow this unique phenotype on HIV-1–susceptible T cells.
PBMCs were separated from blood of HIV-uninfected and HIV-infected individuals through Ficoll-Hypaque (Pharmacia, http://www.pfizer.com). Resting CD4+ T cells were purified as previously described [22] and were at least 99.5% pure as determined by post-purification FACS analysis. To purify naïve, central, and effector memory subsets, purified CD4+ cells were stained with CCR7 and CD45RO antibodies, and CD45RO−CCR7+ (TN), CD45RO+CCR7+ (TCM), CD45RO+CCR7− (TEMRO), and CD45RO−CCR7− (TEMRA) subsets were sorted using the flow cytometer (FACSAria; BD Biosciences, http://www.bdbiosciences.com). The culture medium used in all experiments was RPMI (Cellgro, http://www.cellgro.com) and prepared as described before [22]. All cytokines were purchased from R&D Systems (http://www.rndsystems.com). In some experiments, TEMRO and TEMRA subsets were further subdivided into CD57+ and CD57− subsets by flow sorting by staining purified CD4+ T cells with CCR7, CD45RO, and CD57 antibodies. Monocyte-derived DCs were generated as previously described [22]. The superantigen SEB (Sigma, http://www.sigmaaldrich.com) was used to stimulate resting T cells in the presence of DCs [36].
Uninfected individuals were adults (ages 21–64, mean age was 32) with no history of HIV infection. Whole blood samples from adult participants with HIV infection were obtained during routine primary care visits. Among the HIV-infected individuals, 76% were Caucasian, 82% were male, the median (range) age was 41 (28–59) years, and 79% were receiving potent antiretroviral therapy. Median (IQR) CD4+ T cell and log10 plasma HIV-1 RNA values were 380 (270–592) cells/mm3 and 2.7 (2.6–3.8) copies/ml plasma, respectively, and 50% had fewer than 400 HIV-1 RNA copies/ml in plasma. There were no selection criteria based on race or sex. All participants provided written informed consent that was approved by the Vanderbilt Institutional Review Board.
VSV-G pseudotyped replication-incompetent HIV were generated as previously described [36]. R5-tropic and X4-tropic replication-competent viruses were prepared similarly by transfecting 293T cells with HIV that encodes either R5-tropic (BaL) or X4-tropic (NL4–3) envelope and EGFP (Clontech, http://www.clontech.com) in place of the nef gene as previously described [37]. Wild-type virus (NL4–3) with X4-tropic or with R5-tropic envelope (BaL) and virus (R8) encoding heat stable antigen (HSA) in place of vpr [38] with intact nef gene were obtained from Chris Aiken (Vanderbilt University). Additional viruses used in this study were as follows. NL4–3–based proviral constructs encoding Env genes from R5-tropic proviral 92MW965.26, NL JRFL, NL YU2, and dual-tropic NL89.6 were obtained from Paul Bieniasz (Aaron Diamond AIDS Research Center) and have been previously described [39]. R5-tropic virus JRCSF and X4-tropic virus R9 were obtained from Vineet KewalRamani (National Cancer Institute [NCI]). Typically, viral titers ranged from 1 × 106 to 5 × 106 IFU/ml for replication-competent viruses and 10 × 106 to 30 × 106 IFU/ml for VSV-G pseudotyped HIV, as titered on CCR5-expressing Hut78 T cell lines (gift of Vineet KewalRamani, NCI). Viral replication in T cell cultures was determined by measuring p24 levels within supernatants by an ELISA.
To determine apoptosis, T cells were stimulated with α-CD3 (OKT-3, ATCC)–coated plates in the presence of soluble α-CD28 (1 μg/ml; Pharmingen, http://www.bdbiosciences.com) for 18 h. T cell apoptosis was measured by PE-conjugated Annexin V according to manufacturer's instructions (BD Biosciences). Cytokines (IL-2, IL-4, IL-5, IL-10, TNF-α, IFN- γ) in the supernatants were assayed using a commercially available cytometric bead assay (CBA) (BD Biosciences) [40], and analyzed using CBA 6-bead analysis software (BD Biosciences).
T cells were stained with the relevant antibody on ice for 30 min (chemokine receptor staining performed at room temperature for 20 min) in PBS buffer containing 2% FCS and 0.1% sodium azide. Cells were then washed twice, fixed with 1% paraformaldehyde, and analyzed with a FACSCalibur or FACSAria flow cytometer. Live cells were gated based on forward and side scatter properties, and analysis was performed using FlowJo software (Tree Star, http://www.treestar.com). The following anti-human antibodies were used for staining: CD3, CD4, CD8, CD45RO, CD45RA, CD28, CD27, CD11b, CD57, CD7, CD62L, HLA-DR, CCR5 (all from BD Biosciences), CCR7, and CCR4 (R&D Systems). The CRTH2 antibody used for these experiments has been previously described [41]. Secondary goat-anti-mouse antibodies were conjugated with allophycocyanin or PE (BD Biosciences). For the intracellular p24 stain, fixation and permeabilization was performed using a commercial kit (BD Biosciences) according to the manufacturer's instructions. Subsequently, cells were stained with anti-p24 for 1 h, followed by goat-anti-mouse conjugated to allophycocyanin for 30 min.
HIV fusion assays were performed essentially as previously described [25]. Briefly, viruses carrying a β-lactamase reporter protein fused to the amino terminus of the virion protein Vpr (BlaM-Vpr) were added to expanded T cell subsets at 37 °C for 2 h to allow virus–cell fusion. CCF2/AM (20 μM; Aurora Biosciences Corporation, http://www.vrtx.com) was added, and the cultures were incubated for 14 h at room temperature. Cells were pelleted and resuspended in PBS, and the fluorescence was measured at 447 and 520 nm with a microplate fluorometer after excitation at 409 nm. Uncleaved CCF2 fluoresces green, due to fluorescence resonance energy transfer between the coumarin and fluorescein groups; however, cleavage by BlaM results in the dissociation of these fluorophores, and the emission spectrum shifts to blue. Thus, the ratio of blue to green cellular fluorescence is proportional to the overall extent of virus–cell fusion. Fluorescence ratios were calculated after subtraction of the average background fluorescence of control cultures containing no virus (blue values) and wells containing PBS (green values).
Viral DNA was quantified by real-time PCR using an ABI 7700 instrument (PE Biosystems, http://www.appliedbiosystems.com) with SYBR Green chemistry. The reaction mixtures (25 μl total volume) contained 2.5 μl of infected lysate, 12.5 μl of 2x SYBR Green PCR Master Mix (PE Biosystems), and 50 nM of each primer. A standard curve was prepared from serial dilutions of HIV plasmid DNA. The reactions were amplified and analyzed as previously described [42]. The sequences of primers (R and U5) specific for early products were 5′-GGCTAACTAGGGAACCCACTGCTT (forward) and 5′-CTGCTAGAGATTTTCCACACTGAC (reverse). The late-product primer sequences (R and 5NC) were 5′-TGTGTGCCCGTCTGTTGTGT (forward) and 5′-GAGTCCTGCGTCGAGAGAGC (reverse), as previously described.
Statistical analyses were performed using Stata version 9.0 (http://www.stata.com). T cell subset and clinical data are presented as means (standard deviation). Statistical significance between groups was determined by Wilcoxon rank sum test. Differences were considered significant at p < 0.05. |
10.1371/journal.ppat.1007876 | Structural mechanism for guanylate-binding proteins (GBPs) targeting by the Shigella E3 ligase IpaH9.8 | The guanylate-binding proteins (GBPs) belong to the dynamin superfamily of GTPases and function in cell-autonomous defense against intracellular pathogens. IpaH9.8, an E3 ligase from the pathogenic bacterium Shigella flexneri, ubiquitinates a subset of GBPs and leads to their proteasomal degradation. Here we report the structure of a C-terminally truncated GBP1 in complex with the IpaH9.8 Leucine-rich repeat (LRR) domain. IpaH9.8LRR engages the GTPase domain of GBP1, and differences in the Switch II and α3 helix regions render some GBPs such as GBP3 and GBP7 resistant to IpaH9.8. Comparisons with other IpaH structures uncover interaction hot spots in their LRR domains. The C-terminal region of GBP1 undergoes a large rotation compared to previously determined structures. We further show that the C-terminal farnesylation modification also plays a role in regulating GBP1 conformation. Our results suggest a general mechanism by which the IpaH proteins target their cellular substrates and shed light on the structural dynamics of the GBPs.
| Shigella flexneri is a Gram-negative bacteria that causes diarrhea in humans and leads to a million deaths every year. Once inside the cell, S. flexneri injects the host cell cytoplasm with effector proteins to suppress host defense. The guanylate-binding proteins (GBPs) have potent antimicrobial functions against a number of pathogens including S. flexneri. For successful infection, S. flexneri relies on an effector protein known as IpaH9.8, a unique ubiquitin E3 ligase to target a subset of GBPs for proteasomal degradation. How these GBPs are specifically recognized by IpaH9.8 was unclear. Here, using a combination of structural and biochemical approaches, we reveal the molecular basis of GBP-IpaH9.8 interaction, and show that subtle differences in the seven human GBPs can significantly impact the targeting specificity of IpaH9.8. We also show that the GBPs have considerable structural flexibility, which is likely important for their function. Our results provide further insights into S. flexneri pathogenesis, and laid the groundwork for future biophysical and biochemical studies to investigate the functional mechanism of GBPs.
| The guanylate-binding proteins (GBPs) play critical roles in cell-autonomous immunity against a diverse range of bacterial, viral, and protozoan pathogens. The charter member of this family is GBP1, which was identified as a protein that is strongly induced by the interferons and can specifically bind to the guanylate affinity column [1, 2]. There are seven GBPs in human (GBP1-7), which share 52%-88% sequence identity between each other [3]. GBP1, GBP2, and GBP5 contain C-terminal CaaX box sequences that allow them to be prenylated in cells. GBP1 is farnesylated, which is important for its localization to membrane structures such as the Golgi apparatus [4, 5]. The farnesylation modification, together with a nearby triple-arginine motif, is also required for the localization of GBP1 to cytosolic bacteria [6, 7]. Once on the bacterial surface, GBP1 is able to recruit other GBPs via heterodimerization and oligomerization [7, 8]. A unique property of GBP1 is its ability to hydrolyze GTP first to GDP and then to GMP in a processive manner [9, 10]. In contrast, GBP2 only converts ~10% GTP to GMP, whereas GBP5 hydrolyzes GTP only to GDP [11, 12]. The physiological significance of the unusual enzyme activity of GBP1, as well as the biochemical differences between different GBPs, remains unclear. Mechanistically, the GBPs belong to the dynamin superfamily of GTPases, which often mediate membrane fission or fusion [13, 14]. By analogy, the GBPs could also function in the membrane remodeling processes. For example, they may contribute to the lysis of pathogen-containing vacuoles. Other reported functions of the GBPs include promoting autophagy, initiating inflammasome assembly, and inhibiting bacterial motility (for recent reviews, see [15–20]). However, our understanding towards the functions of these important proteins is still in its infancy.
The GBPs have complex structural dynamics. Crystal structures have been determined for the full-length GBP1 in the monomer state and the isolated GTPase domain of GBP1 in the dimer state [10, 21, 22]. GBP1 contains an N-terminal large GTPase (LG) domain and a C-terminal helical region, which can be further divided into a middle domain (MD) that contains the α7-α11 helices and a GTPase effector domain (GED) that consists of the α12-α13 helices. The GED folds back and interacts with LG and MD, which is important to maintain GBP1 at the resting state [21, 23]. Binding of GTP induces the release of GED from the rest of the protein, resulting in an extended conformation that was previously interpreted as a “dimer” based on size-exclusion chromatography analyses [24]. Unlike the isolated LG domain that readily dimerizes under several guanine nucleotide conditions, full-length GBP1 only forms a stable dimer in the presence of GDP-AlFx that mimics the catalytic transition state [10, 24]. Due to the extended conformation of the GED domain, the dimer of the full-length protein has a large hydrodynamic radius and was long regarded as a “tetramer”. Dimerized full-length GBP1 can cause the tethering of unilamellar vesicles in vitro, and this activity depends on the C-terminal farnesylation modification [25]. Furthermore, the farnesylated GBP1 can form a transient ring-like oligomer that is reminiscent of dynamin and related proteins such as the Mx (Myxovirus resistance) proteins [25]. Whether these properties are related to the cellular functions of GBP1 remains to be investigated.
Pathogens often antagonize key cellular proteins to evade host defense. Due to the important functions of the GBPs in innate immunity, it is not a surprise that some pathogens have evolved strategies to counter their activity. The IpaH family of proteins are unique E3 ubiquitin ligases that are only found in bacteria, especially pathogenic bacteria such as Shigella and Salmonella [26]. They all contain an N-terminal Leucine-rich repeat (LRR) domain and a C-terminal novel E3 ligase (NEL) domain. Although the NEL domain is structurally unrelated to the HECT family of E3 ligases, it also catalyzes the ubiquitination reaction by forming a ubiquitin-thioester intermediate via an invariant Cys in the CxD motif [27, 28]. IpaH9.8 from Shigella flexneri, an intracellular bacterium that causes bacillary dysentery, is one of the most extensively studied member of the IpaH family. In fact, it is one of the first IpaH proteins that is demonstrated to be an E3 ligase [26]. Recent studies have discovered that IpaH9.8 ubiquitinates and degrades a subset of GBPs, which is important for S. flexneri to suppress host defense and replicate in the cells [6–8].
To delineate how the GBPs are targeted by IpaH9.8 and gain further insights into GBP-mediated immunity, we have first determined the crystal structure of IpaH9.8LRR in complex with GBP1LG-MD, which explains the specific recognition of select GBPs by IpaH9.8. Mutating the GBP1-binding residues in IpaH9.8 diminish its ability to degrade the GBPs. By comparing with other IpaH protein structures, we have identified interaction hot spots in the LRR domains of this unique family of bacterial ubiquitin ligases. A large rotation of GBP1MD is observed in our structure, revealing that the elastic α7 helix plays an important role in regulating the structural dynamics of GBP1. Finally, we determined the structure of farnesylated full-length GBP1 and show that the farnesylation modification is involved in restraining GBP1 conformation.
The IpaH proteins are modular enzymes that all contain a LRR domain and a NEL domain. The NEL domains are highly conserved, and therefore the substrate specificity is largely dictated by the variable LRR domains. Indeed, IpaH9.8LRR binds to GBP1 [6]. Swapping the LRR domains of IpaH4 and IpaH7.8 to IpaH9.8LRR enables the chimera IpaHs to degrade the GBPs (Fig 1a).
To elucidate the molecular basis of how IpaH9.8LRR recognizes GBP1, we sought to determine their complex structure. We first crystallized full-length GBP1 in complex with IpaH9.8LRR. However, the crystal diffracted to only ~10 Å and could not be improved despite extensive attempts. We subsequently crystallized the LG-MD region of GBP1 (GBP1LG-MD) in complex with IpaH9.8LRR and determined the structure at 3.6 Å (Table 1, Fig 1b). The moderate resolution is likely caused by a high solvent content of the crystal (73.4%). Nevertheless, the electron density map generated from the molecular replacement solution is of high quality and allows unambiguous model building (S1 Fig).
The LG domain of GBP1 features a canonical globular GTPase fold that highly resembles GBP1LG in the full-length GBP1 structure [21, 22]. Superimposing it to the full-length structure generates a root mean square deviation (rmsd) of 1.0 Å for 257 Cα atoms. The MD domain features two three-helix bundles that spiral around the common α9 helix and also resembles the corresponding region in the full-length structure. Superimposing the MD domain from our structure to the corresponding region in full-length GBP1 yields a rmsd of 1.9 Å for 169 Cα atoms. However, the arrangement of the LG and MD in our structure is different from that in the full-length structure, and a large swing of the MD is observed (S2a Fig). IpaH9.8LRR is very similar to the previously determined IpaH9.8LRR alone structure [29], and contains eight LRR motifs (LRR1-LRR8) that are organized into a slightly curved solenoid. In the complex structure, it engages GBP1LG using the concave surface of the solenoid (Fig 1b). Three regions in GBP1LG are involved in interacting with IpaH9.8LRR: the P-loop, the switch II region, and the α3 helix (Fig 1b). These regions are located on the opposite side of the GED domain in the full-length GBP1 structure, so the GED domain, which is not present in our structure, would not interfere with the binding (S2a Fig). On the other hand, these regions are involved in forming the dimer interface in the LG dimer structure [10], and therefore binding of IpaH9.8 would lead to the disruption of the GBP1LG dimer (S2b Fig). This is consistent with our previous observation that IpaH9.8 disrupts the GBP1 “tetramer” in the presence of GDP-AlFx [6].
In the structure, seven out of the eight LRR modules in IpaH9.8LRR contribute residues to interact with GBP1 (S1b Fig, Fig 2). In LRR1, Arg629.8 (superscripts 9.8 and G indicate residues in IpaH9.8 and GBP1, respectively) forms bidentate interactions with Glu105G in the Switch II region of GBP1. Asp649.8 forms a hydrogen bond with Tyr47G, and Arg659.8 interacts with Tyr47G via a cation-π interaction. Asn679.8 forms a hydrogen bond with Gln137G. In LRR2, Asn839.8 forms a hydrogen bond with Glu105G.Tyr869.8 forms a hydrogen bond with the main chain carbonyl group of Gly102G, at the same time forms van der waals interactions with Tyr47G. Gln889.8 appears to stabilize the position of Lys1089.8 in LRR3, which in turn forms a salt bridge with Asp140G. Other residues in LRR3 that interact with GBP1 include Tyr1039.8, which packs against the aliphatic region of Glu105G. His1269.8 from LRR4 interacts with Tyr143G via cation-π and van der waals interactions. In LRR5, Asn1439.8 forms a hydrogen bond with Asn109G, and Tyr1469.8 hydrogen bonds with Glu147G. Arg1669.8 from LRR6 forms a salt bridge with Glu147G. Arg1909.8 from LRR7 may form a hydrogen bond with His150G. The residues involved in binding GBP1 are unique to IpaH9.8 (S3 Fig), explaining the fact that only IpaH9.8, but not other IpaH proteins, specifically degrades the GBPs [6, 8].
The seven human GBPs are highly homologous to each other. However, only a subset of GBPs such as GBP1, GBP2, GBP4, and GBP6 are efficiently targeted and degraded by IpaH9.8 [6, 8]. GBP3 and GBP7 are particularly resistant (Fig 3a). Careful examination reveals subtle differences in their Switch II and α3 helix regions. For example, GBP3 contains a Lys (Lys105) in its Switch II that aligns with Glu105 in GBP1 (S4 Fig), which lies at the center of GBP1LG-MD/IpaH9.8LRR interface and makes critical interactions with several IpaH9.8 residues (Fig 2). Mutation of this residue to Glu allows the GBP3 mutant (GBP3-M) to be efficiently degraded by IpaH9.8 (Fig 3a). GBP3-M also binds strongly to IpaH9.8-C337A, an IpaH9.8 mutant that has abolished E3 ligase activity (Fig 3b). The α3 helix of GBP5 is slightly different when compared with GBP1 (S4 Fig). Gly137, Leu141, and His143 replace GBP1 residues Gln137, Gln141, and Tyr143, respectively. These differences likely reduce the interaction between GBP5 and IpaH9.8, and make GBP5 a suboptimal substrate that requires higher amounts of IpaH9.8 for degradation (Fig 3a). A double mutant of GBP5, G137Q/L141Q (GBP5-M), is degraded more efficiently by IpaH9.8 (Fig 3a). Several residues in the Switch II and α3 helix region of GBP7 are different compared to GBP1, including Met104 that replaces Val104 in GBP1 and His143 like in GBP5 (S4 Fig). The bulkier Met104 may hinder the binding of IpaH9.8. Furthermore, molecular dynamics simulation study suggests that the α3 helix region of GBP7 prefers to adopt a loop rather than a helical conformation (S5 Fig), caused partly by the presence of Ser111, instead of an Asn in other GBPs, at the end of its Switch II (S4 Fig). Ser111 appears to stabilize a hydrogen bond interaction between Ser113 and Glu147, which causes the α3 helix to unfold. Swapping the GBP7 Switch II-α3 region (residues 104–151) to the corresponding segment in GBP1 renders the GBP7 mutant (GBP7-M) susceptible to IpaH9.8-mediated degradation (Fig 3a). GBP7-M also shows a stronger interaction with IpaH9.8-C337A (Fig 3b).
To further verify our structure, we mutated several IpaH residues that are involved in binding to GBP1, including Tyr86, Gln88, His126, Tyr146, and Arg190. When these mutations are generated in combination with C337A, the resulting mutants IpaH9.8-Y86A/Q88A/C337A, IpaH9.8-H126A/R190A/C337A, and IpaH9.8-Y146A/R190A/C337A all display greatly reduced interaction with GBP1, as shown by the co-immunoprecipitation experiments (Fig 4a). Mutating Tyr86 and Gln88 together generates the strongest effect. Similarly, IpaH9.8-Y86A/Q88A/C337A also failed to interact with other GBPs, including GBP2, GBP4, and GBP6 (Fig 4a).
To validate the physiological relevance of these GBP-binding residues, we performed cell imaging experiments as we previously described [6]. We made mutations to IpaH9.8 that are fused with 10 tandem repeats of the SUperNova tags (SunTags) [30]. We then expressed these IpaH9.8 mutants in the S. flexneri ΔipaH9.8 strain and used these bacteria to infect HeLa cells stably expressing RFP-GBP1 and scFv-GCN4-GFP. GCN4 is a single chain antibody that specifically recognizes the SunTag. In uninfected cells, GCN4-GFP display a dispersed pattern in the cell (Fig 4b). When infected with S. flexneri expressing wild-type IpaH9.8-10xSunTag, the GFP signals are enriched in the cytoplasm due to the delivery of IpaH9.8 by the bacteria, and the RFP signal is largely diminished due to the degradation of GBP1 (Fig 4b). In contrast, RFP-GBP1 is not efficiently degraded by the bacterial strains expressing IpaH9.8-Y86A/Q88A, IpaH9.8-H126A/Y146A, or IpaH9.8-Y146A/R190A. In these cells, the RFP signal is most bright around the bacteria, due to the localization of GBP1 to the bacterial surface (Fig 4b). Together, these results demonstrate that an intact GBP-binding surface in IpaH9.8LRR is critical for the function of IpaH9.8 in vivo.
The IpaH proteins have diverse substrates in the host [31]. In particular, two IpaH proteins from Salmonella, SspH1 and Slrp, use their LRR domains to target the host PKN1 kinase and Trx1 thioredoxin, respectively [32, 33]. Crystal structures have been determined for SspH1LRR in complex with a coiled-coil region of the PKN1 kinase [34], and Slrp in complex with Trx1 [35]. Comparing these structures with the GBP1LG-MD/IpaH9.8LRR complex reveals both differences and common features (Fig 5).
Like IpaH9.8, SspH1 binds its target using the concave surface of its LRR domain. While the N-terminal region of IpaH9.8LRR mediates the majority of the interactions with GBP1, the contact site for PKN1 is more focused on the C-terminal half of SspH1LRR (Fig 5a and 5b). Nonetheless, the edge of the concave surface that are pointed by the LRR strands are important for the binding in both structures. In IpaH9.8LRR, Asn67 from LRR1, Gln88 from LRR2, Lys108 from LRR3, His126 from LRR4, Tyr146 from LRR5, Arg166 from LRR6, and Arg190 from LRR7 form a continuous surface patch that are critical for GBP1 binding (Fig 5a). In SspH1LRR, a similar edge is formed by Leu247 from LRR3, Asn266 from LRR4, Asn286 from LRR5, Asn326 from LRR7, His346 from LRR8, Asp368 from LRR9, and His392 from LRR10 (Fig 5b). When SspH1LRR is compared with IpaH9.8LRR, SspH1 residues Leu247, Asn266, Asn286, and Asn326 align exactly with IpaH9.8 residues Lys108, His126, Tyr146, and Arg190, respectively (S3 Fig).
In the crystal structure of Slrp/Trx1, Slrp interacts with Trx1 using two interfaces [35]. The so-called type I binding site highly resembles the GBP1 binding site in IpaH9.8LRR (Fig 5a and 5c). This site is formed by the first six LRR modules of SlrpLRR, and also involves the concave surface. Trx1 binding residues Arg184, Lys186, Ile187, Ile205, Asn208, Tyr226, Gln231, Ile250, and His271 all align with IpaH9.8 residues Arg62, Asp64, Arg65, Asn83, Tyr86, Tyr103, Lys108, His126, and Tyr146 (S3 Fig). Although the physiological significance of the type I binding site in Slrp remains to be explored, these analyses suggest that the IpaH family proteins could generally bind their target proteins using the LRR concave surfaces. In particular, residues located at positions corresponding to Lys108 in IpaH9.8-LRR3, His126 in IpaH9.8-LRR4, and Tyr146 in IpaH9.8-LRR5 are important for binding in all three complexes (Fig 5, S3 Fig), suggesting that these three positions could function as “hot spots” to mediate the interaction between the IpaH proteins and their cellular targets.
The dynamin superfamily proteins are considered mechanochemical enzymes that convert the energy from GTP binding and hydrolysis to mechanical force. The conformational dynamics of GBP1 is likely at the heart of its function but remains poorly understood. In the previously determined structures, the GED folds back and locks the conformation of GBP1 (Fig 6a). However, biophysical studies suggest that the GED domain is unleashed during the GTPase reaction cycle and the C-terminal region of GBP1 undergoes large degree of conformational change. In our structure, since the GED domain is not present, the MD domain is free to adopt a relaxed conformation. The α7 helix, which is forced to bend in the apo structure due to the interaction between the GED and the LG-MD domains, springs back to the straightened state (Fig 6b). Starting from a highly conserved Gln321 (S4 Fig), the C-terminal half of the α7 helix rotates ~13°, and this conformational change is transmitted toward the rest of the protein, causing an ~20° en bloc rotation of the α8-α11 helices (Fig 6c, S2a Fig). Due to the unfavorable geometry of the α7 helix in the “GED on” state, this conformational change likely also occurs in the full-length protein when the GED domain is set free during GBP1 function.
The conformational change seen above prompted us to further investigate the conformation dynamics of GBP1. GBP1 is farnesylated at Cys589, and this modification is important for its localization to the Golgi apparatus and recruitment by various pathogens [4–7]. Despite this modification, GBP1 is primarily a cytosolic protein until the cells are infected by pathogens [4, 5], suggesting that the farnesyl group is probably not exposed at the resting state. The farnesylation modification changes the behavior of GBP1 on hydrophobic chromatography column and reduced its ability to hydrolyze GTP to GMP, suggesting that it impacts the conformation of GBP1 [36].
To assess how the farnesyl group affects GBP1 structure, we followed a previously described protocol [36] and prepared farnesylated GBP1 (GBP1F) by co-expressing GBP1 with the farnesyltransferase in E. coli. Successful modification is confirmed by mass spectrometry analyses of the purified protein (S6a Fig). We subsequently determined the crystal structure of GBP1F (Table 1). Interpretable electron density is present for the farnesyl group, as well as the entire C-terminal tail of GBP1 (S6b Fig). The farnesyl group is accommodated in a pocket formed by His378, Gln381, Lys382, Ala385 from the α9 helix and Tyr524, His527, Leu528, Leu531 from the α12 helix (Fig 7a). These interactions pull the α12 helix towards the α9 helix, and cause the GED domain to become more tightly fastened to the rest of the protein. In this conformation, the α7 helix remains bent; while the N-terminal half the α12 helix, as well as the majority of the MD domain, undergoes a ~10° rotation when compared to the previously determined full-length GBP1 structure (Fig 7b).
Despite the fact that GBP1 was identified more than 30 years ago as one of the most prominent proteins that are induced by the interferons, its precise function remains elusive. Recent studies suggest that GBP1 inhibits intracellular bacterial replication by translocating to the bacterial surface, hindering their actin-dependent motility, and blocking their cell-to-cell spread [6–8]. Clearly, GBP1 plays an important role in cell-autonomous immunity, and poses a major threat to cytosolic bacteria such as S. flexneri. In the arms race between the bacteria and the host, S. flexneri has acquired the ability to eliminate a subgroup of GBPs through the action of its virulence E3 ligase IpaH9.8. To provide insight into the interaction between IpaH9.8 and the GBPs, we have solved the crystal structure of the LRR domain of IpaH9.8 in complex with a major fragment of GBP1. Our results show that the residues involved in interacting with GBP1 are unique to IpaH9.8, elucidating how IpaH9.8, but not other IpaH family proteins, can specifically target the GBPs. Due to the differences in the Switch II and α3 helix regions, GBP3, GBP5, and GBP7 are not efficiently degraded by IpaH9.8. Mutating relevant residues in these GBPs makes the mutant proteins more susceptible to IapH9.8-mediated degradation. By comparing our structure with other IpaH proteins in complex with their target molecules, we further reveal interaction hot spots in the LRR domain of this unique family of bacterial effectors. These results provide a deeper understanding on the pathogenesis of S. flexneri, and may facilitate the investigation of other IpaH proteins in the future.
Our results also shed light on the structural dynamics of GBP1. Previously, GBP1 without the farnesyl moiety has been crystallized in the apo state and in complex with GMP-PNP, a nonhydrolyzable analog of GTP [21, 22]. However, the two structures are largely similar and have not provided sufficient insights into the conformational change of GBP1. Through the examination of the GBP1LG-MD and GBPF structures determined in this study, we uncovered two new conformations of GBP1. In a way, the GBP1F structure likely reflects GBP1 at its most tense state. By creating additional interactions between the GED domain and the MD domain, the farnesyl group appears to function as the second tier of bolt to lock the GED domain to the rest of the protein. A bending of the α7 helix is forced in this conformation. In contrast, the GBP1LG-MD structure likely reflects GBP1 at its most relaxed state. We envision that when the structural restraints imposed by the GED domain and the farnesyl group are relieved upon GBP1 activation, the α7 helix would become straight, and this would cause the C-terminal region to rotate like seen here in the GBP1LG-MD structure. How the GED domain and the farnesyl moiety are arranged in the active state, and how these conformational changes are translated to the function of GBP1, remain important questions to be addressed. In this regard, it is worth noting that, GBP5ta, a splicing variant of GBP5 that is associated with the T-cell lymphoma tissues, naturally lacks the GED domain [37]. GBP3ΔC, a splicing variant of GBP3 that does not have the α13 helix, has also been reported [38]. The functional significance of these GBP variants are unclear, but they would be more prone to adopt a relaxed conformation compared to full-length GBP5 and GBP3.
Primers used in this study are listed in Supplementary Table 1. IpaH9.8LRR (residues 22–252) [6] and GBP1LG-MD (residues 1–479) were expressed as His6-SUMO fusion proteins in E. coli BL21(DE3). The bacterial cultures were grown at 37 °C in the Luria-Bertani (LB) medium to an OD 600 of 0.6–0.8 before induced with 0.5 mM isopropyl β-D-1-thiogalactopyranoside (IPTG) at 18 °C for overnight. The cells were collected by centrifugation and were resuspended in a lysis buffer containing 50 mM Tris-HCl, pH 8.0, 500 mM NaCl, 10 mM imidazole, 5 mM β-mercaptoethanol, and 1 mM phenylmethylsulfonyl fluoride (PMSF). The cells were then disrupted by sonication, and the insoluble debris was removed by centrifugation. The supernatant was applied to a Ni-NTA column (GE Healthcare). The column was then washed extensively with a wash buffer containing 50 mM Tris-HCl, pH 8.0, 500 mM NaCl, 30 mM imidazole, and 5 mM β-mercaptoethanol, and eluted with an elution buffer containing 50 mM Tris-HCl, pH 8.0, 150 mM NaCl, 250 mM imidazole, and 5 mM β-mercaptoethanol. Next, the eluted proteins were digested with the ULP1 protease to cleave the N-terminal His6-SUMO fusion tag. The protein samples were then passed through another Ni-NTA column to remove the His6-SUMO fusion tag and the ULP1 protease. Untagged IpaH9.8LRR and GBP1LG-MD were further purified by gel filtration chromatography using a Superdex 200 column (GE Healthcare), and eluted in the final buffer containing 25 mM Tris-HCl, pH 8.0, 20 mM NaCl, and 2 mM Dithiothreitol (DTT).
To obtain the farnesylated GBP1 (GBP1F), full-length GBP1 was cloned into a vector that is kanamycin resistant and expresses GBP1 as a His6-SUMO fusion protein. The two subunits of the farnesyltransferase (FTase α and β, respectively) were cloned into the pACYCDuet-1 (Novagen) vector that is chloramphenicol resistant. His6-SUMO-GBP1 was then co-expressed with the FTase α/β in E. coli BL21(DE3). The bacterial cultures were supplemented with both kanamycin (50 μg/ml) and chloramphenicol (25 μg/ml), and were induced with 0.5 mM IPTG at an OD 600 of 0.8. The cells were then cultured at 20°C for 18h and were collected by centrifugation. The GBP1F was then purified similarly as described above for the GBP1LG-MD protein.
To obtain the IpaH9.8LRR/GBP1LG-MD complex, purified IpaH9.8LRR and GBP1LG-MD were incubated overnight on ice using a 1.5:1 molar ratio. The mixtures were then passed through a Superdex 200 column and eluted using the final buffer described above. The protein complex was concentrated to 18 mg/ml for crystallization. Crystals were grown at 20°C using the sitting drop vapor diffusion method. The crystallization solution contains 1.6 M sodium/potassium phosphate, pH 6.5. Crystals grew to full size in several days and were transferred to a cryo solution containing 1.6 M sodium/potassium phosphate, pH 6.5, and 38% sucrose before flash-cooled in liquid nitrogen.
GBP1F was crystallized using the sitting drop vapor diffusion method at a concentration of 15 mg/ml. Crystals appeared overnight in 20 mM citric acid, 80 mM Bis-Tris propane, pH 8.8, and 16% (w/v) Polyethylene glycol 3,350. For data collection, the crystals were transferred to a solution containing 20 mM citric acid, 80 mM Bis-Tris propane, pH 8.8, 16% Polyethylene glycol 3,350, and 20% ethylene glycol before flash-cooled in liquid nitrogen.
The diffraction data were collected at Shanghai Synchrotron Radiation Facility (SSRF) beamline BL17U. The diffraction data were indexed, integrated, and scaled using HKL2000 (HKL Research). The structure was determined by the molecular replacement method using the published structure of IpaH9.8LRR (PDB ID:5B0N) and GBP1 (PDB ID:1DG3) as the search models. The structure modeling was performed in Coot [39] and refined using Phenix [40]. Structural validation was performed with MolProbity [41]. Composite omit map was generated with Phenix [42].
The structure models of GBP6 and GBP7 were obtained by homology modeling using MODELLER [43] with GBP1 structure as the template. The molecular dynamics simulations were carried out using the GROMACS 5.1.2 package (http://www.gromacs.org) [44].
HEK293T and HeLa cells, originally obtained from ATCC, were grown in a humidified incubator with 5% CO2 at 37 °C in Dulbecco's modified Eagle's medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 100 μg/ml penicillin/streptomycin (GIBCO). All cell lines were tested to be free of mycoplasma by the standard PCR method.
The mammalian expression plasmids have been previously described [6]. Mutations were introduced into plasmids by a PCR-based method. For the immunoprecipitation experiments, a catalytically dead mutant of IpaH9.8 (IpaH9.8-C337A) was used, since wild-type IpaH9.8 would lead to quick degradation of co-expressed GBPs. HEK293T cells were grown in 10 cm dishes to 70%-80% confluency. They were then co-transfected with 5 μg IpaH9.8-C337A and 10 μg indicated GBP plasmids using Polyethylenimine (PEI). The cells were harvested 18–24 hours later, washed with the phosphate-buffered saline (PBS) buffer, and lysed in a buffer containing 25 mM Tris-HCl, pH 8.0, 2 mM MgCl2, 1 mM GTP, 1 mM PMSF, and 0.5% Triton X-100. The cell lysates were cleared by centrifugation, and then incubated with the Flag M2 beads (Sigma, A2220) for 2 hours. The beads were spun down and then washed three times with the wash buffer (25 mM Tris-HCl, pH 8.0, 2 mM MgCl2, 1 mM GTP, and 0.2% Triton X-100). The immunoprecipitated proteins were eluted from the beads using the 3x Flag peptides (NJPeptide, NJP50002) and analyzed by SDS-PAGE and western blotting. Purified GBP1 protein interacts strongly with purified IpaH9.8 under all nucleotide conditions (apo, GMP, GDP, GppNHp, and GDP-AlFx) [6]. Also, no nucleotide is required for the formation of the IpaH9.8LRR/GBP1LG-MD complex. However, we observed more consistent binding between GBP1 and IpaH9.8 co-expressed in cells when we included GTP in the lysis buffer. The reason for this is not entirely clear. We noticed that GBP1 tends to form puncta/aggregates when overexpressed in HEK293T cells, and we hypothesized that GTP may help to solubilize these aggregates.
For the degradation experiments, HEK293T cells were grown to 70%-80% confluency in 6-well plates, and were transfected with indicated plasmids using PEI. 18–24 h after transfection, the cells were harvested, washed, and then lysed in a lysis buffer containing 25 mM Tris-HCl, pH 8.0, and 0.5% Triton X-100. The cell lysates were cleared by centrifugation and then analyzed by western blot using antibodies for HA (Sigma, H3663), c-Myc (HuaxingBio, HX1802), Flag (Sigma, F3165), and β-tubulin (TransGen, HC101).
The IpaH9.8 gene with indicated mutations were cloned into the pME6032-10x SunTag plasmid as previously described [6]. S. flexneri ΔipaH9.8 2a strains were then transformed with these plasmids, and single colonies were picked up for each individual plasmid. The bacterial strains were cultured overnight at 37°C in the LB broth, before diluted 1:100 in fresh LB broth, and grown to an OD 600 of 0.8 in the presence of IPTG.
The HeLa cell line stably expressing RFP-GBP1 and scFv-GCN4-GFP was described previously [6]. The cells were seeded onto glass coverslips in 24-well plates and cultured for 16 h before infection. The infection (MOI, 50) was facilitated by centrifugation at 800 g for 5 min at room temperature, and cultured for another hour at 37°C in a 5% CO2 incubator. Cells were washed three times with PBS. Fresh DMEM containing 100 μg/ml gentamycin was then added to kill the extracellular bacteria. Two hours later, infected cells were washed three times with PBS, fixed with 4% paraformaldehyde for 30 min at room temperature, and then place in the mounting medium (ZSGB-BIO, ZLI-9556) for imaging. Cell images were recorded using the Zeiss LSM 510 Meta confocal microscope and processed with the LSM software package.
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10.1371/journal.pgen.1003185 | Genetic Disruption of the Copulatory Plug in Mice Leads to Severely Reduced Fertility | "Seminal fluid proteins affect fertility at multiple stages in reproduction. In many species, a male(...TRUNCATED) | "Male reproductive fitness is strongly affected by seminal fluid. In many animals, the male's ejacul(...TRUNCATED) | "The non-sperm component of an ejaculate can have large effects on male reproductive fitness. In int(...TRUNCATED) |
10.1371/journal.pbio.2006601 | Heterogeneity and longevity of antibody memory to viruses and vaccines | "Determining the duration of protective immunity requires quantifying the magnitude and rate of loss(...TRUNCATED) | "Immunological memory, mediated by antibodies, is a hallmark of immunity. A key problem for determin(...TRUNCATED) | "Immune memory is a cardinal feature of the adaptive immune response of vertebrates and is the princ(...TRUNCATED) |
10.1371/journal.ppat.1002062 | Bacteria-Induced Dscam Isoforms of the Crustacean, Pacifastacus leniusculus | "The Down syndrome cell adhesion molecule, also known as Dscam, is a member of the immunoglobulin su(...TRUNCATED) | "Invertebrate animals lack an adaptive immune system and have no antibodies. Vertebrate antibodies b(...TRUNCATED) | "The immunoglobulin super family (IgSF) is composed of proteins that contain at least one immunoglob(...TRUNCATED) |
10.1371/journal.ppat.1005075 | "Nanoformulations of Rilpivirine for Topical Pericoital and Systemic Coitus-Independent Administrati(...TRUNCATED) | "Vaginal HIV transmission accounts for the majority of new infections worldwide. Currently, multiple(...TRUNCATED) | "When taken consistently, PrEP has been shown to reduce the risk of HIV infection by up to 92% in pe(...TRUNCATED) | "Although the annual number of new HIV infections continues to decline, the global HIV-1 pandemic re(...TRUNCATED) |
10.1371/journal.ppat.1002361 | Signal Transduction through CsrRS Confers an Invasive Phenotype in Group A Streptococcus | "The CsrRS (or CovRS) two component system controls expression of up to 15% of the genome of group A(...TRUNCATED) | "Group A Streptococcus (S. pyogenes or GAS) is exclusively a human pathogen that can inhabit the hum(...TRUNCATED) | "Human beings are thought to be the principal if not exclusive host for group A Streptococcus (S. py(...TRUNCATED) |
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in Dataset Viewer.
This is the dataset used in the paper "Readability Controllable Biomedical Document Summarization" by Zheheng Luo, Qianqian Xie, Sophia Ananiadou. Every instance in the dataset contains a technical summary(abstract), a plain language summary, and the whole article text. All the data are from the PLOS journals.
Detailed format is as following:
{
"doi": str, # unique doi identifier
"title": str, # title
"abstract": str, # abstract
"plain language summary": str, # plain language summary
"article": str # whole text
}
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