Miracle-dz/UniFAR-FTUs huggingface dataset:
Co-infection of Ehrlichia with B. burgdorferi drives emergency myelopoiesis and promotes Lyme arthritis

Lyme disease is caused by the extracellular pathogen Borrelia burgdorferi (Bb), transmitted by the Ixodes scapularis tick. Approximately one-third of infected individuals develop arthritis of weight-bearing joints, though it is unclear why some patients develop arthritis and severe systemic disease while others do not. C57BL/6 (B6) mice are susceptible to Bb infection but do not develop arthritis, providing an in vivo model to evaluate mechanisms regulating development of Lyme arthritis. We demonstrate here that co-infection of B6 mice with the tick-borne pathogens Bb and Ehrlichia muris (Em) induced significant arthritis. Although co-infection did not impact bacterial burden or growth of either pathogen, the resultant Lyme arthritis in co-infected mice correlated with significant hematologic disturbances. Whereas single Bb infection elicited no overt hematologic changes, Em infection resulted in thrombocytopenia, lymphopenia, monocytosis, and granulocytosis, which was consistently observed in mice co-infected with both Bb and Em. Hematologic changes correlated with profound changes to the hematopoietic stem and progenitor cell (HSPC) populations in Em-infected mice. Most notable were dramatic reductions in populations of HSPCs committed to myeloid-biased differentiation. Co-infection resulted in persistent hematologic changes and bone marrow inflammation. Our data demonstrate for the first time that B6 mice, resistant to developing Lyme arthritis, exhibit severe joint pathology in the presence of a second pathogen, correlating with persistent emergency myelopoiesis. Our data support the conclusion that pathogen burden is not sufficient for disease and specific inflammatory signals and cells regulate the development of Lyme arthritis. Importance Tick-borne illnesses, historically relegated to specific geographic areas, are increasing in prevalence and distribution. Borrelia burgdorferi causes Lyme disease, the most common tick-borne illness in North America, characterized by debilitating arthritis, carditis, and neurologic complications. It remains unclear why certain infected individuals develop severe disease while others are only mildly symptomatic. Human monocytic ehrlichiosis (HME) is another tick-borne disease that often results in profound illness and severe hematological disturbances. We show here that co-infection of B6 mice, resistant to Lyme arthritis, with Borrelia burgdorferi and Ehrlichia muris, used to model HME, results in the development of severe arthritis and emergency myelopoiesis. Our work suggests that immune activation driven by co-infection contributes to the development of Lyme arthritis.
Pathogen transmission modes determine contact network structure, altering other pathogen characteristics

Pathogen traits can vary greatly and impact the ability of a pathogen to persist in a population. Although this variation is fundamental to disease ecology, little is known about the evolutionary pressures that drive these differences, particularly where they interact with host behavior. We hypothesized that host behaviors relevant to different transmission routes give rise to differences in contact network structure, constraining the space over which pathogen traits can evolve to maximize fitness. Our analysis of 232 contact networks across mammals, birds, reptiles, amphibians, arthropods, fish, and mollusks found that contact network topology varies by contact events, most notably in networks that are representative of fluid-exchange transmission. Using infectious disease model simulations, we showed that these differences in network structure suggest pathogens transmitted through fluid-exchange contact events will need traits associated with high transmissibility to successfully proliferate, compared to pathogens that transmit through other types of contact. These findings were supported through a review of known traits of pathogens that transmit in humans. Our work demonstrates that contact network structure may drive the evolution of compensatory pathogen traits according to transmission strategy, providing essential context for understanding pathogen evolution and ecology.
Isolation and structure of the fibril protein, a major component of the internal ribbon for Spiroplasma swimming

Spiroplasma, which are known pathogens and commensals of arthropods and plants, are helical-shaped bacteria that lack a peptidoglycan layer. Spiroplasma swim by alternating between left- and right-handed helicity. Of note, this system is not related to flagellar motility, which is widespread in bacteria. A helical ribbon running along the inner side of the helical cell should be responsible for cell helicity and comprises the bacterial actin homolog, MreB, and a protein specific to Spiroplasma, fibril. Here, we isolated the ribbon and its major component, fibril filament, for electron microscopy (EM) analysis. Single-particle analysis of the fibril filaments using the negative-staining EM revealed a three-dimensional chain structure composed of rings with a size of 11 nm wide and 6 nm long, connected by a backbone cylinder with an 8.7 nm interval with a twist along the filament axis. This structure was verified through EM tomography of quick-freeze deep-etch replica sample, with a focus on its handedness. The handedness and pitch of the helix for the isolated ribbon and fibril filament agreed with those of the cell in the resting state. Structures corresponding to the alternative state were not identified. These results suggest that the helical cell structure is supported by fibril filaments; however, the helical switch is caused by the force generated by the MreB proteins. The isolation and structural outline of the fibril filaments provide crucial information for an in-depth clarification of the unique swimming mechanism of Spiroplasma.
Characterizing control of memory CD8 T cell differentiation by BTB-ZF transcription factor Zbtb20

This work characterizes the transcriptional and epigenetic control of memory CD8 T cell differentiation by the BTB-ZF family transcription factor Zbtb20 using single cell RNA and ATAC sequencing and identifies direct genomic targets of Zbtb20 using CUT&RUN. Members of the BTB-ZF transcription factor family regulate the immune system. Our laboratory identified that family member Zbtb20 contributes to the differentiation, recall responses, and metabolism of CD8 T cells. Here, we report a characterization of the transcriptional and epigenetic signatures controlled by Zbtb20 at single-cell resolution during the effector and memory phases of the CD8 T cell response. Without Zbtb20, transcriptional programs associated with memory CD8 T cell formation were up-regulated throughout the CD8 T response. A signature of open chromatin was associated with genes controlling T cell activation, consistent with the known impact on differentiation. In addition, memory CD8 T cells lacking Zbtb20 were characterized by open chromatin regions with overrepresentation of AP-1 transcription factor motifs and elevated RNA- and protein-level expressions of the corresponding AP-1 components. Finally, we describe motifs and genomic annotations from the DNA targets of Zbtb20 in CD8 T cells identified by cleavage under targets and release under nuclease (CUT&RUN). Together, these data establish the transcriptional and epigenetic networks contributing to the control of CD8 T cell responses by Zbtb20.
An outbreak of SARS-CoV-2 in big hairy armadillos (Chaetophractus villosus) associated with Gamma variant in Argentina three months after being undetectable in humans

The present pandemic produced by SARS-CoV-2 and its variants represents an example of the one health concept in which humans and animals are components of the same epidemiologic chain. Animal reservoirs of these viruses are thus the focus of surveillance programs to monitor their circulation and evolution in potentially new hosts and reservoirs. In this work, we report the detection of SARS-CoV-2 Gamma variant infection in four specimens of Chaetophractus villosus (big hairy armadillo/armadillo peludo) in Argentina. In addition to the finding of a new wildlife species susceptible to SARS-CoV-2 infection, the identification of the Gamma variant three months after its last detection in humans is a noteworthy result, raising the question of potential unidentified viral reservoirs.
Changes in social position predict survival in bottlenose dolphins

Social bonds and social structure are important features of animal systems that impact individual fitness. Few studies have examined how temporal dynamics in individual social bonds predict fitness outcomes. This is critical to understand given the high variation in types of social structures and strategies within populations of social mammals, both across time and among individuals. If individually-differentiated social bonds are important, it might be the change in bonds which has fitness consequences, not the absolute number of bonds nor their strength. We investigated how network dynamics predict survival in a wild population of bottlenose dolphins using a 35-year longitudinal study. In particular, we were interested in two sex-specific measures of the “widowhood effect”, as well as a more general investigation into the predictability of mortality from changes in higher-order social network metrics. We used two inferential frameworks to provide complimentary evidence for or against hypotheses; namely, a gradient-boosting predictivist approach with relative importance measures, and an inclusion probabilities approach based on stability-selection. We found evidence of a widowhood effect among males but not females. Surprisingly, the most robust predictor of survival was closeness-centrality, whereby the loss of closeness centrality preceded death. This finding, that absolute network position may not be as relevant to survival as changes in network status, is consistent with a large social-psychological literature in humans on the impacts of loss of social capital, dissolution of close friendships, and loss through death of partners (widowhood effect). This study highlights the critical nature of social connections and how its disruption can be a matter of life and death.
Structural remodeling of Coxiella burnetii during its biphasic developmental cycle revealed by cryo-electron tomography

Coxiella burnetii is an obligate zoonotic bacterium that targets macrophages to cause a disease known as Q fever. It has a biphasic developmental lifecycle where the extracellular and metabolically inactive small cell variant (SCV) transforms, under host acidic environment, into the vegetative large cell variant (LCV). However, the details about the morphological and structural changes that accompany this biphasic cycle are still lacking. Here, we used cryo-electron tomography to image the different cell variants of C. burnetii grown either under axenic conditions in different pH or purified directly from host cells revealing the major developmental, morphological and structural transitions. We show that SCVs are characterized by equidistant stacks of inner membrane that presumably allow a smooth transition to LCV, a transition coupled with the expression of the Dot/Icm type IVB secretion system (T4BSS). A class of T4BSS particles were associated with extracellular densities including a tubular structure possibly involved in host interaction or effector delivery. Also, SCVs and cells in the transition state contained spherical multilayered membrane structures of different sizes and locations suggesting that they are not related to a sporulation process as once assumed.
Accuracy of non-parametric species richness estimators across taxa and regions

Non-parametric species richness estimators are efficient and widely used when sampling is incomplete. There is little consensus on which of the available estimators works best across taxa and regions. Until now no work compared existing algorithms with multiple datasets encompassing contrasting scenarios. We used data from 62 inventories worldwide at different spatial scales, including 20 vertebrate, 22 invertebrate and 20 plant datasets, and compared the accuracy of the most used non-parametric estimators (Chao and Jackknife) and improvements to their original formulations. Our results highlight the good performance of the Jackknife estimators for incidence data, especially the P-corrected first order jackknife estimator (Jack1inP). This algorithm ranked most often the best or among the best performing estimators using two measures of accuracy that measure deviation from expectation along the accumulation curve. We argue that Jack1inP can be considered a universal estimator for species richness, regardless of taxon, temporal and spatial scales, or completeness of the sampling. More research should however be directed towards finding the precise contexts when each estimator might perform best.
Vimentin intermediate filaments provide structural stability to the mammalian Golgi apparatus

The Golgi apparatus comprises a connected ribbon of stacked cisternal membranes localized to the perinuclear region of most vertebrate cells. The position and morphology of this organelle depends upon interactions with microtubules and the actin cytoskeleton. In contrast, we know relatively little about the relationship of the Golgi apparatus with intermediate filaments. In this study we show that the Golgi is in close physical proximity to vimentin intermediate filaments (IFs) in cultured mouse and human cells. We also show that the trans-Golgi network coiled-coil protein GORAB can physically associate with IFs. Although loss of vimentin and/or GORAB does not have major effects upon Golgi morphology at steady-state, the Golgi undergoes more rapid disassembly upon chemical disruption with the drug brefeldin A, and slower reassembly upon drug washout, in vimentin knockout cells. Moreover, loss of vimentin causes reduced Golgi ribbon integrity when cells are cultured on high stiffness hydrogels, which is exacerbated by loss of GORAB. These results indicate that vimentin IFs contribute to the structural stability of the Golgi apparatus, and suggest a role for GORAB in this process.
An accessible and versatile deep learning-based sleep stage classifier

Manual sleep analysis for research purposes and for the diagnosis of sleep disorders is labor-intensive and often produces unreliable results, which has motivated many attempts to design automatic sleep stage classifiers. With the recent introduction of large, publicly available hand-scored polysomnographic data, and concomitant advances in machine learning methods to solve complex classification problems with supervised learning, the problem has received new attention, and a number of new classifiers that provide excellent accuracy. Most of these however have non-trivial barriers to use. We introduce the Greifswald Sleep Stage Classifier (GSSC), which is free, open source, and can be relatively easily installed and used on any moderately powered computer. In addition, the GSSC has been trained to perform well on a large variety of electrode set-ups, allowing high performance sleep staging with portable systems. The GSSC can also be readily integrated into brain-computer interfaces for real-time inference. These innovations were achieved while simultaneously reaching a level of accuracy equal to, or exceeding, recent state of the art classifiers and human experts, making the GSSC an excellent choice for researchers in need of reliable, automatic sleep staging.
Evolution of scapula size and shape in Carnivora: locomotor habits and differential shape scaling

The effect of size, phylogeny, and locomotor habit, on shape was tested in 213 scapulas from 101 carnivoran species using 3D geometric morphometric methods. The sampled species spanned the whole size range and locomotor patterns in Carnivora. The results of the present study indicate that, in this order, scapula shape responds to the complex interaction of allometric, phylogenetic, and functional effects. Furthermore, evidence for differential scaling in the shape of the carnivoran scapula was found, which might be related to scaling differences among carnivoran families. Additionally, most allometric shape variation in the carnivoran scapula was related to size changes along phyletic lines. Locomotor-related shape differences were assessed using canonical variate analysis. Most locomotor habits could be significantly separated from each other based on scapula shape, although high misclassification rates were obtained when comparing semiarboreal and semifossorial carnivorans to other locomotor types. Locomotor indicators in the scapula shape of extant carnivorans seemed independent of size or shared ancestry and could be related to muscular function. These locomotor indicators were then used to infer the locomotor habits of several internal nodes of the carnivoran phylogeny, whose scapular size and shape was reconstructed using weighted square-change parsimony. According to scapula size and shape, the carnivoran ancestor was a medium-sized scansorial animal (i.e., it spent most of its time on the ground, but was a good climber).
Human social learning biases in immersive virtual environments

Social learning strategies describe what, when, and from whom individuals choose to learn. Evidence suggests that both humans and animals are capable of strategic social learning. However, human research generally lacks ecological and spatial realism, making it difficult to understand the importance of our use of social information in an evolutionary context. In this study, we use virtual reality to simulate three novel tasks inspired by the animal literature (Container, Route Choice and Foraging tasks) within complex, three-dimensional environments. In each experiment, combinations of demonstrators with different characteristics gave opposing solutions to the task to determine from whom participants preferentially learned. Importantly, participants were able to freely navigate the environment and attempt the task in any way they chose by using or ignoring social information. We found that participants displayed an overall bias towards learning asocially (independently) rather than socially. Asocial learning was favoured more strongly during complex tasks that spanned larger spatial scales, potentially due to the difficulties in keeping track of social information in such scenarios. When learning from others, participants displayed a bias towards learning from the majority over the minority (positive frequency-dependent social learning) and towards learning from the most successful demonstrators (payoff-based social learning), which supports the findings of previous, lab-based experiments. There was no apparent bias with respect to demonstrator dominance status, gender and body size. Our findings are the first to show a variation in the use of social learning across task and environmental complexities in humans, to carry out a comprehensive evaluation of hypothetical human learning biases, and to provide a methodological link between non-human and human social learning experiments. As demonstrated here, immersive virtual environments have great potential for research into human social evolution and we strongly encourage future research to adopt a similar approach.
Targeting Neuroinflammation with Abscisic Acid Reduces Pain Sensitivity in Females and Hyperactivity in Males of an ADHD Mice Model

Aims Attention deficit/hyperactivity disorder (ADHD) is a neurodevelopmental syndrome characterized by dopaminergic dysfunction. In this study, we aimed to demonstrate the link between dopaminergic deficit and neuroinflammation underlying ADHD symptoms. Subjects and Treatment We used a validated ADHD mice model, that involves perinatal 6-OHDA lesion. Animals were treated with 20mg/L (drinking water) of Abscisic acid (ABA) for one month. We tested behaviour (learning and memory, anxiety, social interactions, and pain) in both females and male mice, in all eight groups (control and lesioned, with/without ABA). Postmortem, we analyzed microglia morphology and Ape1 expression in specific brain areas related to the descending pain inhibitory pathway. Results In females, dopaminergic deficit increased pain sensitivity, but not hyperactivity, in contrast to males. This behaviour was associated with inflammatory microglia and lower Ape1 levels in the anterior cingulate cortex (ACC) and posterior insula cortex (IC). ABA treatment reduced inflammation and alleviated pain. In males, ABA reduced hyperactivity, but had no significant effect on inflammation. Conclusions This is the first study proving a sex-dependent association between dopamine dysfunction and inflammation in specific brain areas, leading to different behavior outcomes in a mouse model of ADHD. These findings provide new clues for potential treatments.
Genome-wide prediction of disease variants with a deep protein language model

Distinguishing between damaging and neutral missense variants is an ongoing challenge in human genetics, with profound implications for clinical diagnosis, genetic studies and protein engineering. Recently, deep-learning models have achieved state-of-the-art performance in classifying variants as pathogenic or benign. However, these models are currently unable to provide predictions over all missense variants, either because of dependency on close protein homologs or due to software limitations. Here we leveraged ESM1b, a 650M-parameter protein language model, to predict the functional impact of human coding variation at scale. To overcome existing technical limitations, we developed a modified ESM1b workflow and functionalized, for the first time, all proteins in the human genome, resulting in predictions for all ∼450M possible missense variant effects. ESM1b was able to distinguish between pathogenic and benign variants across ∼150K variants annotated in ClinVar and HGMD, outperforming existing state-of-the-art methods. ESM1b also exceeded the state of the art at predicting the experimental results of deep mutational scans. We further annotated ∼2M variants across ∼9K alternatively-spliced genes as damaging in certain protein isoforms while neutral in others, demonstrating the importance of considering all isoforms when functionalizing variant effects. The complete catalog of variant effect predictions is available at: https://huggingface.co/spaces/ntranoslab/esm_variants.
Characterization of a novel estrogen- and progesterone-responsive endometrial cancer cell line: HCI-EC-23

Most endometrial cancers express the hormone receptor estrogen receptor alpha (ER) and are driven by excess estrogen signaling. However, evaluation of the estrogen response in endometrial cancer cells has been limited by the availability of hormonally responsive in vitro models, with one cell line, Ishikawa, being used in most studies. Here, we describe a novel, adherent endometrioid endometrial cancer (EEC) cell line model, HCI-EC-23. We show that HCI-EC-23 retains ER expression and that ER functionally responds to estrogen induction over a range of passages. We also demonstrate that this cell line retains paradoxical activation of ER by tamoxifen, which is also observed in Ishikawa and is consistent with clinical data. The mutational landscape shows that HCI-EC-23 is mutated at many of the commonly altered genes in EEC, has relatively few copy-number alterations, and is microsatellite instable high (MSI-high). In vitro proliferation of HCI-EC-23 is strongly reduced upon combination estrogen and progesterone treatment. HCI-EC-23 exhibits strong estrogen dependence for tumor growth in vivo and tumor size is reduced by combination estrogen and progesterone treatment. Molecular characterization of estrogen induction in HCI-EC-23 revealed hundreds of estrogen-responsive genes that significantly overlapped with those regulated in Ishikawa. Analysis of ER genome binding identified similar patterns in HCI-EC-23 and Ishikawa, although ER exhibited more bound sites in Ishikawa. This study demonstrates that HCI-EC-23 is an estrogen- and progesterone-responsive cell line model that can be used to study the hormonal aspects of endometrial cancer.