Biology subjects

Savin, C.

Publications and source records attributed to Savin, C..

At least 19 recordsLinked to original sources

bioRxiv2026

Yersinia pestis lipoprotein SlyB promotes plague pathogenesis via envelope stress tolerance

Yersinia pestis, the etiological agent of plague, persists in an enzootic cycle involving mammals and fleas, requiring constant outer membrane (OM) adaptation to disparate host environments. One such pathway involves the glycine zipper 2TM domain-containing protein SlyB, a central component of the OM stress response and PhoPQ virulence pathway. While the OM is critical for virulence, the role of the OM lipoprotein SlyB in Y. pestis ecology and pathogenesis remains unknown. We show by phylogenetic analyses that slyB paralogs expanded in environmental bacteria, whereas the canonical slyB gene was under negative selective pressure during Y. pestis speciation from Yersinia pseudotuberculosis. Using rodent and flea infection models recapitulating Y. pestis natural history, we demonstrate that SlyB is specifically required to resist the mammalian immune system at 37{degrees}C, including neutrophil-mediated antimicrobial activity during lymph node colonization, but is dispensable in septicemic plague in rodents. Strikingly, SlyB is not required for flea colonization and resistance to the antimicrobial-peptide-based immunity of arthropods at lower temperatures. SlyB-dependent OM stress tolerance reveals a mechanism by which Y. pestis establishes bubonic plague, in line with its critical lipopolysaccharide structural switch. Our findings identify SlyB as an evolutionarily fine-tuned component of the Y. pestis envelope that mediates immune escape upon infection of mammalian hosts through maintenance of structural integrity.

microbiology↗

bioRxiv2026

Temporal Structure of Reward Availability and Sensory Uncertainty Modulate Allocation Dynamics in Naturalistic Foraging

Adaptive foraging requires animals to combine uncertain sensory cues with predictions about when rewards are likely to occur. While theoretical models describe how animals should allocate their effort under variable-interval reward schedules, it remains unclear how the timing or rewards and the reliability of sensory cues affects behavior. We developed a continuous foraging task in which freely moving macaque monkeys navigated among three reward patches. Rewards became available at unpredictable times, with their availability signaled by a visual cue of varying reliability. We also varied the schedule of reward availability: in some conditions, rewards were equally likely to become available at any moment (exponentially distributed intervals), while in others the interval distribution was more concentrated around a particular mean (gamma-distributed intervals) which increased the cost of premature responses. Under exponential schedules, monkeys eventually allocated their time at different patches according to reward schedules, and cue reliability had only modest effects. Under gamma-distributed intervals, monkeys more quickly learned to differentiate between patches. Their choices were more strongly dependent on predicted reward timing, particularly when sensory cues were highly reliable. These results show that both the timing of rewards and reliability of sensory cues shape how animals allocate their time and effort in continuous naturalistic foraging tasks.

animal behavior and cognition↗

bioRxiv2026

A corticostriatal circuit updates subjective beliefs about latent task states

Beliefs about states of the world profoundly impact decision-making and learning, but little is known about how neural circuits represent and update beliefs. We performed projection-specific recordings and perturbations from neurons in the orbitofrontal cortex (OFC) projecting to the intermediate or rostral cau-date putamen (CPi/CPr) in rats performing a task with hidden reward states. Stimulating OFC[->]CPi neurons biased rats beliefs towards high reward states. Recordings from optogenetically-tagged OFC[->]CPi neurons showed that they encoded categorical evidence for high reward states, shaped by a saturating non-linearity in neural responses. Downstream neurons could, in principle, decode the full belief distribution over reward states as rats deliberated about deci-sions. Finally, projection-specific perturbations disrupted encoding of hidden states within OFC. These findings reveal the circuit implementation of a core cognitive computation, updating subjective beliefs about abstract latent states of the environment.

neuroscience↗

bioRxiv2024

Global evolutionary patterns of Yersinia pestis and its spread into Africa

The zoonotic pathogen Yersinia pestis, the etiologic agent of plague, has caused three major pandemics and diversified in different lineages currently established in endemic areas worldwide1-3. However, some regions like continental Africa have been poorly covered within the global diversity and epidemiological history of this pathogen2,4-6. Here, we report the whole-genome sequences of 1,124 Y. pestis isolates collected from endemic areas worldwide over 116 years, nearly doubling the available genomic data for the species. By integrating population genomics and historical research, we retrace the introduction of multiple Y. pestis lineages into continental Africa, revealing the diversity of the 1.ANT lineage, its historical emergence and its spread to and within Africa since the late 17th century. We identify key mechanisms of genome evolution, including signatures of adaptive evolution present in virulence and biofilm-related genes such as RovA, a master virulence regulator, which likely play a role in the pathogens adaptation and endemic persistence. Additionally, our findings reveal an increased trajectory of genome degradation and expansion of IS elements in different lineages. This trend appears especially pronounced in 1.ANT genomes, promoting the remarkable genomic variation within this lineage. Taken together, our findings shed light on the introduction and evolutionary history of plague in Africa and provide a comprehensive framework for understanding the global diversity and genome evolution of Y. pestis, revealing potential factors contributing to its long-term adaptation in endemic areas.

microbiology↗

bioRxiv2024

Neural dynamics in the orbitofrontal cortex reveal cognitive strategies

While the orbitofrontal cortex (OFC) is implicated in learning and inferring latent states, the precise computation performed by OFC for state inference is unclear. Here we show that rat OFC updates beliefs about states, and this process is decipherable from OFC dynamics in rats performing state inference, but not alternative strategies. We trained rats to perform a temporal wagering task with hidden reward states. Well-trained rats used state inference when deciding how long to wait for rewards, and OFC inactivations impaired belief updating about states. Electrophysiology and novel population analysis methods identified latent neural factors reflecting inferred states in rats performing inference, but not other strategies. Neural firing rates and latent population factors showed abrupt changes following trials that were informative of state transitions. These results identify a precise computation performed by OFC, and reveal neural signatures of inference.

neuroscience↗

bioRxiv2024

Hippocampal neuronal activity is aligned with action plans

Neurons in the hippocampus are correlated with different variables, including space, time, sensory cues, rewards, and actions, where the extent of tuning depends on ongoing task demands. However, it remains uncertain whether such diverse tuning corresponds to distinct functions within the hippocampal network or if a more generic computation can account for these observations. To disentangle the contribution of externally driven cues versus internal computation, we developed a task in mice where space, auditory tones, rewards, and context were juxtaposed with changing relevance. High-density electrophysiological recordings revealed that neurons were tuned to each of these modalities. By comparing movement paths and action sequences, we observed that external variables had limited direct influence on hippocampal firing. Instead, spiking was influenced by online action plans modulated by goal uncertainty. Our results suggest that internally generated cell assembly sequences are selected and updated by action plans toward deliberate goals. The apparent tuning of hippocampal neuronal spiking to different sensory modalities might emerge due to alignment to the afforded action progression within a task rather than representation of external cues.

neuroscience↗

bioRxiv2024

A type IVB secretion system contributes to the pathogenicity of Yersinia pseudotuberculosis strains responsible for the Far East scarlet-like fever

Yersinia pseudotuberculosis is a food-borne pathogen responsible for a self-limiting gastrointestinal disease in humans known as mesenteric lymphadenitis. A phylogenetically distinct Y. pseudotuberculosis cluster from lineages 1 and 8 is associated to a specific syndrome called the Far East scarlet-like fever (FESLF), characterized by skin rash, hyperemic tongue and desquamation. Genome sequencing of FESLF strains previously revealed the presence in the plasmid pVM82 of dot/icm genes, homologous to those known to encode a T4BSS in the intracellular pathogens Legionella pneumophila and Coxiella burnetii. In the present article, we characterized the genomic features and functionality of the Y. pseudotuberculosis T4BSS (yT4BSS). We found higher dot/icm gene identity between Y. pseudotuberculosis and Pseudomonas putida genes than with those of L. pneumophila or C. burnetii. We validated the presence of all essential dot/icm genes required for the structure of a T4BSS. We then evaluated the conditions required for yT4BSS gene expression in vitro and identified an influence of temperature, with higher expression at 37{degrees}C, which mimicks the mammalian host temperature. The yT4BSS is also expressed in cellulo during the Y. pseudotuberculosis intracellular life cycle and in vivo during mouse infection. Although T4BSS functions are well characterized in the intracellular life cycle of L. pneumophila and C. burnetii, the yT4BSS appears to not be required for the intracellular survival nor for the establishment of a replication niche within cells of Y. pseudotuberculosis. Interestingly, the yT4BSS is implicated in Y. pseudotuberculosis FESLF strain pathogenicity when orally inoculated to mice but not during intravenous inoculation. Despite a role in virulence during oral infection, the yT4BSS does not influence organ colonization. However, the yT4BSS appears to be implicated in induction of important necrosis lesions in mesenteric lymph nodes and caeca of mice. Cytokine profil analyses revealed an induction of production of innate immunity related cytokines and chemokines depending on the yT4BSS in cellulo using a mouse bone marrow-derived macrophages infection model. Thus, the yT4BSS modulates cytokine responses of the host innate immune system during oral infection. In conclusion, the yT4BSS is a newly characterized virulence factor implicated in pathogenicity of Y. pseudotuberculosis strains from lineage 8 responsible for FESLF.

microbiology↗

bioRxiv2024

In-host evolution of Yersinia enterocolitica during a chronic human infection

Following a pacemaker implantation, a 75-years-old patient suffered from five successive bacteremia episodes between in 1999 and 2013 despite long-term antibiotic treatment, with intermittent vegetation apparition on the device atrial lead. Four blood isolates, identified as Yersinia enterocolitica bioserotype 4/O:3, were further genetically and phenotypically characterized. Phylogenetic reconstruction showed that the patient was chronically infected by the same strain, which evolved within the host for 14 years. Single-nucleotide polymorphism (SNP) analysis indicates that the last two isolates evolved in parallel and formed two independent lineages within the host. Pan-genome analysis and genome comparison showed that their common evolution was characterized by 41 small insertion/deletion events, loss of three large DNA fragments and mutations in 140 genes. A phylogenetic analysis by maximum likelihood identified two genes presenting a positive selection signal, suggesting that these mutations provided a survival advantage to bacteria during chronic infection. Quinolone resistance in the last two isolates was acquired through a so far undescribed deletion in the gyrA gene. Mass-spectrometry analysis revealed a strong proteome remodeling in the last two isolates which was correlated with a truncation in the stringent response regulator DksA. A reduced carbon, energy and purine metabolism supports their severe growth defects in vitro. 3rd-generation cephalosporin resistance of the last isolate was correlated with a truncation of OmpF, the main porin translocating antibiotics through the outer-membrane, as well as an increased production of BlaA and AmpC {beta}-lactamases. This is the first report of genetic and phenotypic changes associated to within-host adaptation of a pathogenic Yersinia species under antibiotic pressure.

microbiology↗

bioRxiv2024

A common computational and neural anomaly across mouse models of autism

Computational psychiatry has suggested that humans within the autism spectrum disorder (ASD) inflexibly update their expectations (i.e., Bayesian priors). Here, we leveraged high-yield rodent psychophysics (n = 75 mice), extensive behavioral modeling (including principled and heuristics), and (near) brain-wide single cell extracellular recordings (over 53k units in 150 brain areas) to ask (1) whether mice with different genetic perturbations associated with ASD show this same computational anomaly, and if so, (2) what neurophysiological features are shared across genotypes in subserving this deficit. We demonstrate that mice harboring mutations in Fmr1, Cntnap2, and Shank3B show a blunted update of priors during decision-making. Neurally, the differentiating factor between animals flexibly and inflexibly updating their priors was a shift in the weighting of prior encoding from sensory to frontal cortices. Further, in mouse models of ASD frontal areas showed a preponderance of units coding for deviations from the animals long-run prior, and sensory responses did not differentiate between expected and unexpected observations. These findings demonstrate that distinct genetic instantiations of ASD may yield common neurophysiological and behavioral phenotypes.

neuroscience↗

bioRxiv2024

Curriculum learning inspired by behavioral shaping trains neural networks to adopt animal-like decision making strategies

1Recurrent neural networks (RNN) are ubiquitously used in neuroscience to capture both neural dynamics and behaviors of living systems. However, when it comes to complex cognitive tasks, training RNNs with traditional methods can prove difficult and fall short of capturing crucial aspects of animal behavior. Here we propose a principled approach for identifying and incorporating compositional tasks as part of RNN training. Taking as target a temporal wagering task previously studied in rats, we design a pretraining curriculum of simpler cognitive tasks that reflect relevant sub-computations. We show that this pretraining substantially improves learning efficacy and is critical for RNNs to adopt similar strategies as rats, including long-timescale inference of latent states, which conventional pretraining approaches fail to capture. Mechanistically, our pretraining supports the development of slow dynamical systems features needed for implementing both inference and value-based decision making. Overall, our approach is an important step for endowing RNNs with relevant inductive biases, which is important when modeling complex behaviors that rely on multiple cognitive computations.

neuroscience↗

bioRxiv2023

Complex priors and flexible inference in recurrent circuits with dendritic nonlinearities

Despite many successful examples in which probabilistic inference can account for perception, we have little understanding of how the brain represents and uses structured priors that capture the complexity of natural input statistics. Here we construct a recurrent circuit model that can implicitly represent priors over latent variables, and combine them with sensory and contextual sources of information to encode task-specific posteriors. Inspired by the recent success of diffusion models as means of learning and using priors over images, our model uses dendritic nonlinearities optimized for denoising, and stochastic somatic integration with the degree of noise modulated by an oscillating global signal. Combining these elements into a recurrent network yields a dynamical system that samples from the prior at a rate prescribed by the period of the global oscillator. Additional inputs reflecting sensory or top-down contextual information alter these dynamics to generate samples from the corresponding posterior, with different input gating patterns selecting different inference tasks. We demonstrate that this architecture can sample from low dimensional nonlinear manifolds and multimodal posteriors. Overall, the model provides a new framework for circuit-level representation of probabilistic information, in a format that facilitates flexible inference.

neuroscience↗

bioRxiv2023

Probing learning through the lens of changes in circuit dynamics

Despite the success of dynamical systems as accounts of circuit computation and observed behavior, our understanding of how dynamical systems evolve over learning is very limited. Here we develop a computational framework for extracting core dynamical systems features of recurrent circuits across learning and analyze the properties of these meta-dynamics in model analogues of several brain-relevant tasks. Across learning algorithms and tasks we find a stereotyped path to task mastery, which involves the creation of dynamical systems features and their refinement to a stable solution. This learning universality reveals common principles in the organization of recurrent neural networks in service to function and highlights some of the challenges in reverse engineering learning principles from chronic population recordings of neural activity.

neuroscience↗

bioRxiv2023

Context-invariant beliefs are supported by dynamic reconfiguration of single unit functional connectivity in prefrontal cortex

Natural behaviors occur in closed action-perception loops and are supported by dynamic and flexible beliefs abstracted away from our immediate sensory milieu. How this real-world flexibility is instantiated in neural circuits remains unknown. Here we have macaques navigate in a virtual environment by primarily leveraging sensory (optic flow) signals, or by more heavily relying on acquired internal models. We record single-unit spiking activity simultaneously from the dorsomedial superior temporal area (MSTd), parietal area 7a, and the dorso-lateral prefrontal cortex (dlPFC). Results show that while animals were able to maintain adaptive task-relevant beliefs regardless of sensory context, the fine-grain statistical dependencies between neurons, particularly in 7a and dlPFC, dynamically remapped with the changing computational demands. In dlPFC, but not 7a, destroying these statistical dependencies abolished the areas ability for cross-context decoding. Lastly, correlation analyses suggested that the more unit-to-unit couplings remapped in dlPFC, and the less they did so in MSTd, the less were population codes and behavior impacted by the loss of sensory evidence. We conclude that dynamic functional connectivity between prefrontal cortex neurons maintains a stable population code and context-invariant beliefs during naturalistic behavior with closed action-perception loops.

neuroscience↗

bioRxiv2022

Transformation of acoustic information to sensory decision variables in the parietal cortex

The process by which sensory evidence contributes to perceptual choices requires an understanding of its transformation into decision variables. Here, we address this issue by evaluating the neural representation of acoustic information in auditory cortex-recipient parietal cortex while gerbils either performed an auditory discrimination task or while they passively listened to identical acoustic stimuli. During task performance, decoding performance of simultaneously recorded parietal neurons reflected psychometric sensitivity. In contrast, decoding performance during passive listening was significantly reduced. Principal component and geometric analyses each revealed the emergence of decision-relevant, linearly separable manifolds, but only during task engagement. Finally, using a clustering analysis, we found subpopulations of neurons that may reflect the encoding of separate segments during task performance: stimulus integration and motor preparation or execution. Taken together, our findings demonstrate how parietal cortex neurons integrate and transform encoded auditory information to guide sound-driven perceptual decisions.

neuroscience↗

bioRxiv2022

Phylogenetic analysis of the origin and spread of plague in Madagascar

BackgroundPlague is a zoonotic disease caused by the bacterium Yersinia pestis, highly prevalent in the Central Highlands, a mountainous region in the center of Madagascar. After a plague-free period of over 60 years in the northwestern coast city of Mahajanga, the disease reappeared in 1991 and caused several outbreaks until 1999. Previous research indicates that the disease was reintroduced to the city of Mahajanga from the Central Highlands instead of reemerging from a local reservoir. However, it is not clear how many reintroductions occurred and when they took place. Methodology/Principal findingsIn this study we applied a Bayesian phylogeographic model to detect and date migrations of Y. pestis between the two locations that could be linked to the re-emergence of plague in Mahajanga. Genome sequences of 300 Y. pestis strains sampled between 1964 and 2012 were analyzed. Four migrations from the Central Highlands to Mahajanga were detected. Two resulted in persistent transmission in humans, one was responsible for most of the human cases recorded between 1995 and 1999, while the other produced plague cases in 1991 and 1992. We dated the emergence of the Y. pestis sub-branch 1.ORI3, which is only present in Madagascar and Turkey, to the beginning of the 20th century, using a Bayesian molecular dating analysis. The split between 1.ORI3 and its ancestor lineage 1.ORI2 was dated to the second half of the 19th century. Conclusions/SignificanceOur results indicate that two independent migrations from the Central Highlands caused the plague outbreaks in Mahajanga during the 1990s, with both introductions occurring during the early 1980s. They happened over a decade before the detection of human cases, thus the pathogen likely survived in wild reservoirs until the spillover to humans was possible. This study demonstrates the value of Bayesian phylogenetics in elucidating the re-emergence of infectious diseases. Author summaryIn 1991 human cases of plague were reported in the city of Mahajanga, located in the west coast of Madagascar, after 60 years without human cases. Existing evidence suggests that Yersinia pestis, the causal agent of the disease, was reintroduced to the city from a mountainous region known as the Central Highlands. We performed a phylogeographic analysis on 300 Y. pestis genome sequences to determine how many migrations of the pathogen between the two locations were related to the reappearance of the disease in Mahajanga. The results revealed that two migrations from the Central Highlands were the cause of the outbreaks of plague in the west coast of the country during the 1990s. We also aimed to date the emergence of the Y.pestis variant that circulates in Madagascar and is also present in Turkey. To do this, we conducted a molecular dating analysis using an extended data set of 445 sequences, which contained sequences from Turkey and India (the country from which the pathogen was exported to Madagascar for the first time). The analysis indicated that this particular variant emerged in the first decade of the 20th century.

microbiology↗

bioRxiv2022

First description of a Yersinia pseudotuberculosis clonal outbreak in France, confirmed using a new core genome multilocus sequence typing method

Yersinia pseudotuberculosis is an enteric pathogen causing mild enteritis that can lead to mesenteric adenitis and septicemia in elderly patients. Most cases are sporadic, but outbreaks have already been described in different countries. We report for the first time a Y. pseudotuberculosis clonal outbreak in France, that occurred in 2020. An epidemiological investigation pointed towards the consumption of tomatoes as the likely source of contamination. The Yersinia National Reference Laboratory (YNRL) developed a new cgMLST scheme with 1,921 genes specific to Y. pseudotuberculosis that identified the clustering of isolates associated to the outbreak and allowed to perform molecular typing in real time. In addition, this method allowed to retrospectively identify isolates belonging to this cluster from earlier in 2020. This method, which does not require specific bioinformatic skills, is now used systematically at the YNRL and proves to display an excellent discriminatory power and is available to the scientific community.

microbiology↗

bioRxiv2021

Recurrent neural circuits overcome partial inactivation by compensation and re-learning

1Technical advances in artificial manipulation of neural activity have precipitated a surge in studying the causal contribution of brain circuits to cognition and behavior. However, complexities of neural circuits challenge interpretation of experimental results, necessitating theoretical frameworks for system-atic explorations. Here, we take a step in this direction, using, as a testbed, recurrent neural networks trained to perform a perceptual decision. We show that understanding the computations implemented by network dynamics enables predicting the magnitude of perturbation effects based on changes in the networks phase plane. Inactivation effects are weaker for distributed network architectures, are more easily discovered with non-discrete behavioral readouts (e.g., reaction times), and vary considerably across multiple tasks implemented by the same circuit. Finally, networks that can "learn" during inactivation recover function quickly, often much faster than the original training time. Our framework explains past empirical observations by clarifying how complex circuits compensate and adapt to perturbations.

neuroscience↗

bioRxiv2021

Flexible neural coding in sensory, parietal, and frontal cortices during goal-directed virtual navigation

We do not understand how neural nodes operate and coordinate within the recurrent action-perception loops that characterize naturalistic self-environment interactions. Here, we record single-unit spiking activity and local field potentials (LFPs) simultaneously from the dorsomedial superior temporal area (MSTd), parietal area 7a, and dorsolateral prefrontal cortex (dlPFC) as monkeys navigate in virtual reality to "catch fireflies." This task requires animals to actively sample from a closed-loop virtual environment while concurrently computing continuous latent variables: (i) the distance and angle travelled (i.e., path integration) and (ii) the distance and angle to a memorized firefly location (i.e., a hidden spatial goal). We observed a patterned mixed selectivity, with the prefrontal cortex most prominently coding for latent variables, parietal cortex coding for sensorimotor variables, and MSTd most often coding for eye-movements. However, even the traditionally considered sensory area (i.e., MSTd) tracked latent variables, demonstrating path integration and vector-coding of hidden spatial goals. Further, global encoding profiles and unit-to-unit coupling (i.e., noise correlations) suggested a functional subnetwork composed by MSTd and dlPFC, and not between these and 7a, as anatomy would suggest. We show that the greater the unit-to-unit coupling between MSTd and dlPFC, the more the animals gaze position was indicative of the ongoing location of the hidden spatial goal. We suggest this MSTd-dlPFC subnetwork reflects the monkeys natural and adaptive task strategy wherein they continuously gaze toward the location of the (invisible) target. Together, these results highlight the distributed nature of neural coding during closed action-perception loops and suggest that fine-grain functional subnetworks may be dynamically established to subserve (embodied) task strategies.

neuroscience↗