Biology subjects

Wang, C.

Publications and source records attributed to Wang, C..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

The uplift of the Qinghai-Tibetan Plateau reshaped genome architecture and diversification of Asian torrent catfishes

Tectonic uplift and mountain building are major drivers of species diversification and adaptation, yet how they reshape genome architecture and promote evolutionary innovation remains poorly understood. Here, we generated multiple chromosome-level genomes for Asian torrent catfishes (Sisoridae) and performed phylogenomic and comparative genomic analyses. Our results support an Asian origin of Sisoridae and provide a refined phylogenetic topology for catfishes. Comparative analyses revealed extensive chromosomal rearrangements during sisorid evolution, indicating highly dynamic genome architectures. The timing of sisorid diversification overlaps with major phases of regional tectonic change, and analyses of phylogenetic discordance indicate heterogeneous contributions from incomplete lineage sorting and introgression. Elevational distribution was associated with variation in estimated molecular evolutionary rates, while exploratory scans identified lineage-specific candidates for selection and convergent evolution. Candidate coding and non-coding changes occur near genes with known roles in fin development, body patterning, and liver biology, but their effects on sisorid traits remain to be tested. Together, our results demonstrate how tectonic uplift reshaped genome architecture and diversification in Asian torrent catfishes and provide new insights into the genomic basis of adaptation in mountainous freshwater ecosystems.

evolutionary biology↗

bioRxiv2026

AREION: A Foundation Model for Atlas-Agnostic Representation Learning of Brain Connectome

Brain foundation models have shown promising advances in learning generalizable representations from functional magnetic resonance imaging (fMRI) data. However, existing models are typically tied to specific brain atlases and cannot be applied to fMRI data represented using different atlases without full retraining, thereby severely limiting their broader utility across neuroimaging studies. To address this bottleneck, we introduce AREION, atlas-agnostic representation learning of brain connectomes. AREION overcomes atlas dependency through two integrated innovations. First, a Brain Region Contextualizing technique maps brain regions and connectivity entries from diverse atlases into a unified representation space based on their spatial, functional, and morphological characteristics. Second, a Hierarchical Brain Transformer Encoder processes region-specific connectivity profiles as variable-length token sequences and jointly captures local functional structure and global brain functional organization, conditioned on brain regional context, without assuming a fixed number of regions. Together, these two techniques enable the learning of generalizable representations across brain atlases with different parcellation resolutions and connectivity dimensions. AREION is pretrained on a large-scale multi-atlas cohort of fMRI data via self-supervised modeling and evaluated across diverse downstream tasks. Extensive experiments show that it outperforms strong supervised baselines and fMRI foundation models while using substantially fewer parameters, demonstrating strong transferability to atlases unseen during pretraining, generalization to external datasets, and excellent interpretability at the brain regional level.

neuroscience↗

bioRxiv2026

Evidence Scaling for Zero-Shot Protein Reasoning with Large Language Models

Large language models (LLMs) show emerging zero-shot capability for protein variant prediction, yet still lag behind specialized protein models. We ask whether this gap can be reduced by scaling access to biological evidence rather than adapting model parameters. We introduce BioEvidence, a training-free and model-agnostic interface that converts structural and evolutionary information from standard biological tools into compact evidence for frozen LLMs. On the ProteinGym benchmark, we observe evidence scaling: performance improves as evidence becomes richer. Structural and evolutionary evidence each improve performance, and combining them yields further gains, while mismatching the same evidence to the wrong variants degrades performance below the no-evidence baseline. Notably, BioEvidence enables zero-shot ranking to reach strong specialized protein predictors on matched evaluations, and the improvement persists on post-cutoff data released after the model's knowledge cutoff. Evidence also interacts with conventional scaling: for GPT-5.6 Sol, evidence at low reasoning effort outperforms the no-evidence condition at medium effort, while a six-model analysis associates stronger no-evidence performance with larger margins over evolutionary rank fusion. These results identify external evidence as a complementary scaling axis for scientific prediction alongside model capability and inference effort.

bioinformatics↗

bioRxiv2026

An AI-powered cloud biofoundry for autonomous biological research

Autonomous experimentation, where an automated system designs, performs, analyzes, and iteratively improves experiments with minimal human intervention represents a transformative scientific research paradigm. However, it remains hampered by the disconnect between computational design and experimental execution. Here we present iCloudBiofoundry, a cloud-accessible, scalable, and self-evolving platform that bridges this divide. A scientific multi-agent system, iBioGenie, plans research workflows by converting natural language research objectives into testable hypotheses and experimentally grounded protocols using literature, databases, and computational tools. A physical AI layer, BiofoundryAI, translates them into executable workflows that run autonomously on distributed robotic biofoundries, and collects the data for iterative design. We demonstrate the end-to-end capabilities of iCloudBiofoundry across three representative case studies spanning enzyme retrieval, protein engineering, and metabolic engineering. By integrating agentic AI with physical AI, iCloudBiofoundry provides a cloud accessible platform that unifies computational design and robotic execution, enabling autonomous biological research.

synthetic biology↗

bioRxiv2026

MHC restriction is structurally encoded by the T cell receptor germline

MHC restriction -- the requirement for {beta} T cell receptors (TCRs) to recognize Major Histocompatibility Complex (MHC) molecules when presenting peptide antigens -- is a pillar of adaptive immunity. Here, we provide direct structural evidence for TCR germline-encoded recognition of MHC molecules irrespective of antigenic peptide. We engineered "germline-like" TCRs to eliminate CDR3 specificity for peptide, and a molecular clamping strategy to trap ultra-low-affinity complexes with peptide-MHC for cryo-EM. We find that germline-like TCR/pMHC docking modes are identical to wild-type T cell receptors with intact CDR3 loops, across distinct peptide antigens and MHC alleles. Analysis of human TCR repertoires reveals enrichment of specific V genes and V-V{beta} pairing patterns associated with HLA-A*02 contexts. Thus, the TCR germline encodes the blueprint for MHC restriction, providing a sequence-based framework that could inform computational and AI-driven prediction of TCR specificity.

immunology↗

bioRxiv2026

A diverse family of protein antibiotics inhibits the BAM complex by β-signal mimicry

Lectin-like protein antibiotics (Llps) kill Pseudomonas by inhibiting BamA, the essential core of the beta-barrel assembly machinery (BAM). Llps are composed of one or two beta;-lectin domains and a C-terminal peptide, with characterisation to date centred on the two-domain L-type pyocins of P. aeruginosa, which bind BamA extracellular loop 6 and inhibit by delivering the C-terminal peptide to BamA beta;-strand 1. Whether this mechanism is general, and how Llps contend with BamA sequence differences across species, remained unknown. We screened 238 Pseudomonas Llps against 101 genome-sequenced isolates, showing susceptibility across the family is set by BamA extracellular loop 6. Loop 6 length varies, and Llps fall into three targeting modes: short-loop and long-loop specialists and broad-range dual targeters, which have arisen repeatedly. We determine the 2.66 angstrom cryo-electron microscopy structure of a two-domain LlpA bound to BAM, showing recognition has been relocated relative to the L-type pyocins, with loop 6 bound by a single face of the N-terminal beta-lectin domain rather than the inter-domain cleft. This explains how single-domain LlpBs retain BamA targeting and why the second lectin domain has been lost at least twice. We show that the BamA inhibition mechanism is shared across Llps, with a hypervariable C-terminal peptide binding BamA beta-strand 1, inhibiting the BAM insertase by mimicking the beta-signal of BamA substrates. Together, these data provide an atlas of Llp diversity and the mechanistic principles for engineering it, identifying Llps as a tuneable, multi-interface scaffold for BAM-directed precision antibacterials against pathogenic Pseudomonas, including economically important plant pathogens.

biochemistry↗

bioRxiv2026

Gap-free telomere-to-telomere haplotypes assembly of the hybrid grouper 'Yushuban' (Cromileptes altivelis female x Epinephelus fuscoguttatus male)

The hybrid grouper 'Yushuban' (Cromileptes altivelis [female] x Epinephelus fuscoguttatus [male]) has shown promising performance in aquaculture trials, yet no complete reference genome has been available for this hybrid. We generated two gapless, telomere-to-telomere (T2T) haplotype-resolved genome assemblies of a single individual by integrating short-read, PacBio HiFi, Oxford Nanopore ultralong-read and Hi-C data. The maternal (Yushu_Calti_1.0) and paternal (Yushu_Efusc_1.0) haplotypes are 1,077.33 Mb and 1,083.36 Mb in length, with N50 values of 45.46 Mb and 45.55 Mb, respectively. Across all platforms, over 99.4% of reads mapped to each assembly, and Merqury-based quality values reached 57.7413 and 59.2068 (PacBio). BUSCO recovered 99.78% and 99.75% of complete core genes. We predicted 27,248 and 27,566 protein-coding genes, of which 98.52% and 99.23% were functionally annotated, and annotated telomeric motifs and repetitive elements (46.12% and 47.18% of each genome). These assemblies fill a gap in grouper genomic resources and provide a foundation for genetic dissection, parental genome comparison and molecular breeding of this hybrid.

genomics↗

bioRxiv2026

Selfing-aware demographic inference highlights local population structure and bottlenecks in Hawaiian Caenorhabditis elegans

Demographic inference based on sequentially Markovian coalescent (SMC) model is widely used for disentangling the evolutionary history of species and populations. However, the genetic effects of self-fertilization, including the expected reduction of population-level genetic diversity and hence effective population size (Ne), are often ignored in demographic inference, despite the fact that selfing is a common reproductive mode in both invertebrates and plants. To investigate how self-fertilization could bias demographic inference, we apply eSMC2, a selfing-aware demographic inference method, to Hawaiian populations of Caenorhabditis elegans, a predominantly self-fertilizing nematode. Using an expanded dataset that contains more Hawaiian strains than in previous studies, we recovered previously reported genetic groups, including one largely consisting of strains from the Big Island. Population substructure is also detected among these Big Island subpopulations, highlighting the importance of identifying subgroups to avoid misinterpretations of demography. For different Big Island subpopulations, we estimate high selfing rates compatible with previous studies and infer consistent population declines. Population sizes inferred using eSMC2 are smaller than those inferred using PSMC', which does not account for selfing. However, rescaling PSMC' parameters to account for self-fertilization produces a similar demographic trajectory as eSMC2 inference. Our study thus demonstrates how one can account for effects of selfing when using SMC-based methods. It also indicates that the Hawaiian group shows population declines similar to those previously found outside Hawaii.

evolutionary biology↗

bioRxiv2026

Rising water is an underappreciated driver of forest mortality

Forests are known to burn and desiccate under a changing climate; less appreciated is that they also drown. Across much of the globe, a warming atmosphere is amplifying the length and intensity of both droughts and floods. Whereas massive die-offs from drought and fire are widely studied as consequences of climate change on forests, inundation-induced mortality remains poorly quantified. Using approximately 1 m resolution aerial imagery and deep learning, we tracked over 260 million dead trees across the United States' Great Lakes and ocean coastlines from 2012 to 2023. Within 10 km of the coasts, more than half of mapped mortality was concentrated in just 10% of forests, primarily in high-elevation inland wetlands and low-lying forests prone to inundation. Mortality rates doubled within a decade around expanding freshwater lakes and in inland wetlands experiencing intensifying regional-scale precipitation, while tripling in low-lying coastal forests where salinization compounded inundation in sea-level rise hotspots. Our findings identify rising waters as a widespread, underappreciated driver of forest die-off that can extend far inland, underscoring the need to reassess the impacts of climate change on the functioning, demography, and carbon-methane budgets amongst the world's most carbon-rich forests as seas rise and hydroclimate shifts globally.

ecology↗

bioRxiv2026

ACAN regulates VSMC mitochondrial homeostasis through the YAP1/TAZ pathway and contributes to the onset and progression of aortic dissection

Objective: Aortic dissection (AD) is a serious, life-threatening cardiovascular crisis. While vascular proteoglycans normally buffer hemodynamic stress, their aberrant accumulation in the AD aorta predisposes to rupture. Aggrecan (ACAN) is among the most frequently elevated proteoglycans in this setting, yet its pathogenic relationship to AD remains undefined. This study aimed to investigate the role of ACAN in AD and identify potential therapeutic targets. Approach and Results: We employed human tissues, animal models, and cell cultures. Western blotting and immunohistochemistry (IHC) were performed on aortic samples from AD patients and controls to assess contractile markers, MMPs, ACAN, and SOX9. In vivo, AD was induced in mice using {beta}-aminoisobutyric acid (BAPN) and Ang II, with AAV-mediated ACAN knockdown in VSMCs. Histological staining confirmed model validity and enabled assessment of AD incidence, mortality, and protein expression changes. In vitro, human aortic vascular smooth muscle cells (HAVSMCs) were stimulated with Ang II, and SOX9 and ACAN were silenced via siRNA to evaluate the functional impact of ACAN downregulation. In human AD aortas, elevated ACAN and its upstream transcription factor SOX9 drove VSMC phenotypic switching and ECM degradation. In mice, ACAN knockdown corrected AD-induced medial structural disruption, elastin fragmentation, and collagen deposition, markedly reducing incidence and mortality while curbing excessive mitochondrial fission and rescuing functional integrity. ACAN silencing attenuated Ang II-induced mitochondrial damage in HAVSMCs via the RNA-seq-identified YAP1/TAZ pathway, and Verteporfin restored homeostasis. Conclusion: ACAN is aberrantly expressed in AD and murine aortas. ACAN downregulation delays disease progression by preserving mitochondrial homeostasis and function via the YAP1/TAZ pathway.

pharmacology and toxicology↗

bioRxiv2026

Distinct RNA-RNA spatial interaction sub-networks of transcription factors in hepatic cells

We applied the latest RIC-seq technology to study the RNA-RNA interactions in human liver HepG2 cells. Integrating ChIP-seq data with the RIC-seq data, we clas-sified vari ous transcription factors (TFs) into two distinct clusters based on the in-teraction enrichment scores of the uaRNA (RNA transcribed in promoter regions) and eRNA (RNA tran scribed in enhancer regions) potentially transcribed by the TF binding sites. We went on to compare the genomic features and clinical significance across different clusters, by further integrating Hi-C, ATAC-seq, and clinical data from liver cancer patients. Our results showed that Cluster 1 exhibited low spatial interaction (RIC-seq derived RNA-RNA interactions between regulatory RNA ele-ments) and high tissue specificity (high proportion of binding sites covered by shared peaks between two different cell lines for each histone modification marker), showed higher associations with the B compartments and nucleoli, contained less densely clustered TF binding sites, and is more correlated with clinical outcomes. In contrast, Cluster 2 has higher spatial interaction, is more likely to be found in the A compartments and nuclear speckles, contained more densely clustered TF binding sites, and is more prone to form loops. These findings suggested that these transcrip-tion factors might play critical roles in regulating gene expression and serve as po-tential biomarkers and therapeutic targets with significant implications for cancer prognosis and treatment. In summary, groups of TFs could occur as distinct sub-networks based on spatial proximity of non-coding RNAs transcribed by the TF binding sites. These sub-networks appear to be related to regulatory differences for the TF groups and may partially explain the chromosome compartments/domains.

genomics↗

bioRxiv2026

A single nuclei expression resource for exploring dog brain cell transcriptomic diversity

Domesticated dogs present a unique case in nature where mutualism with and selective breeding by humans has led to profound changes in their environment, physiology, and behaviour compared to their wolf-like ancestors. Dog tameness, sociability, and trainability have likely evolved due to significant alterations to brain function. Exploring the effects of domestication on the dog brain will be facilitated by the characterisation of dog brain cell diversity, a task which is not yet complete. To fill this gap, we use single-nucleus RNA sequencing and survey cell types across the dog brain. We present transcriptomes from almost 60,000 cells sampled from the cerebellum, thalamus, and three regions of the cerebrum. Our analysis identified 24 major clusters representing 21 broad cell types, and 131 subclusters revealing regional variation. Comparisons with human and mouse datasets revealed a high level of conservation in neurons across mammalian brains, and greater divergence in glial cells, particularly oligodendrocytes. We demonstrate the utility of the dataset for interrogating specific gene expression patterns across the brain, including genes implicated in dog domestication, behavioural traits, and disease. We discover distinct differences in the expression of opioid receptors in the brains of dogs, compared to humans and mice, providing a potential explanation for dogs' higher tolerance and lower risk of severe adverse effects of opioid drugs. The data from this project are released via a web application for use by the wider community.

genomics↗

bioRxiv2026

A rational design strategy and validation for protease-resistant fusion-inhibitor antiviral peptides

Peptide-based fusion inhibitors are promising pharmaceuticals in the fight against enveloped viruses relying on membrane fusion for host infection. However, peptide therapeutic applications have long been hindered by their poor stability in vivo. Here, we discovered that peptide inhibitors with the wildtype sequence of the heptad repeat 2 (HR2) domain of the SARS-CoV-2 spike protein are efficiently cleaved by Transmembrane Protease, Serine 2 (TMPRSS2), a key protease involved in the SARS-CoV-2 virus-cell fusion pathway. We then identified the corresponding cleavage sites and designed three protease-resistant peptides using ranking based on deep mutational scanning and natural occurrence. The three candidates all exhibit inhibitory activity in a cell-cell fusion assay. A high-resolution cryo-EM structure of the top candidate, HR2-NHN, bound to its HR1 target reveals the molecular basis for its potent activity. The top candidate of the cell-based screening assay significantly improved efficacy relative to the wildtype peptide when administered 12 h before infection in both an authentic virus-cell infection assay and a mouse assay. More broadly, our results suggest that the design strategies for protease-resistant peptides could be applied to a broad spectrum of other enveloped viruses and pave the way for the development of safe, prophylactic antivirals that can be administered before exposure.

microbiology↗

bioRxiv2026

Diffusion MR Microscopy of the Human Hippocampus at 50 μm Resolution at 14.1 T for 3D Virtual Histology

Bridging the gap between macroscopic neuroimaging and microscopic histology remains a challenge in neuroscience. Here, we present a technical feasibility study of diffusion MR microscopy (dMRM) in the ex vivo human hippocampus using a 14.1 T ultrahigh-field MRI system. Mid-hippocampal blocks from control and Alzheimers disease (AD) patients were acquired at 50 x 50 x 100 {micro}m3, representing, to our knowledge, the highest resolution reported for human brain diffusion MRI. At a spatial scale approaching cellular dimensions, dMRM maps and tractography showed close correspondence with immunohistological markers of axons and dendrites. The acquired data delineated six hippocampal laminae, distinguished the inner and outer molecular layers, and preserved short, lamina-specific trajectories that became attenuated or blurred at 100 {micro}m resolution. Tractography further depicted the major components of the hippocampal tri-synaptic circuit--the perforant path, mossy fibers, and Schaffer collaterals in 3D. In the AD specimen, dMRM revealed reduced laminar contrast, local discontinuities, and altered radial and tangential fibers that were paralleled by pathological staining. With the 3D nondestructive characterization of human brain microstructure and circuitry, ex vivo dMRM showed its potential toward the goal of 3D virtual histology.

neuroscience↗

bioRxiv2026

Spatial Logic and Evolutionary Innovation in Human Placentation

Human pregnancy unfolds in a unique mosaic tissue context. Embryonic/fetal placental and maternal uterine cells (decidua basalis) coalesce, forming the basal plate where immune tolerance is coordinated and the utero-placental circulation is initiated. The remaining approximately 70% of the maternal-fetal interface is comprised of the chorionic membranes, an epithelial-like layer of placental cells that lies adjacent to but does not coalesce with the overlying decidua capsularis and parietalis. It is unknown how these two regions of the maternal-fetal interface, which are comprised of seemingly similar cell types, diverge anatomically and functionally. Likewise, it is unknown whether the molecular characteristics of the maternal-fetal interface vary across human populations, potentially contributing to population disparities in pregnancy complications. Here, we generated large-scale paired single-nucleus RNA-seq and chromatin-accessibility profiles of the basal plate and chorionic membranes-associated decidual compartments from diverse-ancestry pregnancies, integrated with spatial transcriptomics and multiplexed protein imaging. We show that the two interfaces share a conserved cytotrophoblast differentiation hierarchy, which is deployed differently resulting in the observed distinct architectures. In the chorionic membranes, progenitor, early, and mature extravillous cytotrophoblast (EVT) states form an epithelial-like laminar shell. In the basal plate, this hierarchy is elaborated upon to enable deep placentation: EVTs that arise early in pregnancy invade the farthest into the uterus, while mature EVTs accumulate superficially to sculpt the local maternal immune microenvironment. Comparative analysis identified DSC4, a decidual stromal cell subtype, as an anti-invasive barrier that is densely enriched adjacent to the chorionic membranes but substantially reduced at the basal plate. Population-resolved analysis further identified the DSC4 marker NID2, which encodes the basement-membrane glycoprotein nidogen-2, as an ancestry-associated rheostat of EVT invasion. A specific NID2 promoter haplotype arose on the modern-human lineage, is absent from available archaic-human genomes, and shows evidence of positive selection in Eurasian populations. This haplotype is associated with reduced local chromatin accessibility and lower NID2 expression in DSC4 cells. Consistent with this genetic association, extracellular NID2 directly suppressed the invasion of primary human cytotrophoblasts in vitro. Together, these findings reveal how a shared developmental program is spatially reconfigured across distinct regions of the maternal-fetal interface and identify a recent modern-human regulatory innovation that modulates maternal decidual restraint of fetal trophoblast invasion across populations.

genomics↗

bioRxiv2026

Pyroptotic cell-derived factors promote osteoclast differentiation

The NLRP3 D301N substitution, the murine ortholog of the human D303N variant, causes NLRP3 constitutive activation (NLRP3CA) and inflammasome assembly. Here, we show that priming signals induced by lipopolysaccharide (LPS) are sufficient to trigger GSDMD-dependent pyroptosis in NLRP3CA-expressing bone marrow-derived macrophages (BMDMs), but not in wild-type (NLRP3WT) cells. NLRP3CA mice exhibit elevated IL-1{beta} secretion and LDH release in bone marrow supernatants under both basal and LPS-challenged conditions. Other cytokines (e.g., TNF-) increased comparably between genotypes, indicating that NLRP3CA specifically amplifies inflammasome-dependent responses. Conditioned medium (CM) from LPS-treated NLRP3CA BMDMs significantly enhanced osteoclast (OC) differentiation in vivo and in vitro compared to NLRP3WT CM, as did bone marrow supernatants from NLRP3CA mice. This osteoclastogenic activity was largely independent of IL-1{beta}, as demonstrated by experiments using IL-1{beta}-deficient NLRP3CA BMDMs, IL-1{beta}-neutralizing antibodies, and genetic deletion of the IL-1 receptor. The osteoclastogenic factors were primarily soluble proteins, as heat inactivation and proteinase K digestion markedly reduced OC formation. Extracellular vesicles (EVs) from NLRP3CA CM modestly promoted OC differentiation, but EV-depleted supernatants retained full activity, indicating that the primary mediators are soluble proteins not carried within EVs. Together, these findings establish NLRP3CA as a well-controlled model for studying pyroptosis and demonstrate that pyroptotic cells release soluble proteins that drive osteoclastogenesis independently of IL-1{beta}.

cell biology↗

bioRxiv2026

ReTIF: Granularity-Aware Multitask Interaction Routing for RNA-Compound Interaction Prediction and Binding-Site Localization

RNA-targeted drug discovery requires both RNA-compound interaction prediction and nucleotide-level binding-site (BS) localization. These two tasks rely on different levels of interaction information: DTI prediction summarizes overall RNA-compound compatibility, whereas BS localization requires preserving nucleotide-level compound-associated signals. However, existing multitask models often use shared cross-modal representations for both tasks before task-specific prediction layers, which may limit their ability to preserve task-dependent interaction patterns. We therefore propose ReTIF (Relation-enhanced Task-specific Interaction Framework), which constructs separate cross-modal interaction representations for DTI prediction and BS localization before aggregation. ReTIF integrates multi-source RNA-compound representations from frozen RNA-FM, StructRFM, Mole-BERT, and MolFormer encoders, and builds separate interaction representations for DTI scoring and BS localization. The DTI branch captures global compatibility through aggregation, whereas the BS branch preserves nucleotide-compound resolution and enhances local evidence through relation-guided propagation with RNA structural and compound topological priors. An asymmetric DTI-derived compatibility signal provides global context to BS prediction while maintaining local evidence. Across five-fold evaluations under unseen pair, RNA, compound, and joint shifts with 13 baselines, ReTIF has the highest mean in 13 of 16 scenario-metric combinations, including BS AUPR in all four settings.

bioinformatics↗

bioRxiv2026

Chronic stress promotes sex-divergent Type 1, 2 and 17 responses in brain resident lymphocytes.

T helper cytokines such as IFN{gamma} and IL-17 are dysregulated in a subset of patients with depression and are associated with poor responses to treatment. Both IFN{gamma} and IL-17 have been shown to regulate neural circuits involved in behavioral changes implicated in depression. However, the cellular source and the regulatory mechanisms governing these cytokines in this context remain incompletely understood. We analyzed brain lymphocytes in response to unpredictable chronic mild stress (UCMS), a model of depression with strong face and construct validity. We confirmed that UCMS induced depressive-like behavior in both male and female mice. Interestingly, UCMS preferentially reduced regional synaptic density in female and neuron counts in male hippocampi. Using single cell RNAseq, we identified T helper cytokine signatures to be enriched in distinct lymphocyte lineages expressing tissue resident markers and are regulated by both sex and chronic stress. Female brain-resident {gamma}{delta}T cells are significantly enriched for type 2 and type 17 signatures and have higher expression of inflammasome genes such as Nlrp3 and Il1b whereas male {beta}T cells and NKT cells are enriched for type 1 signatures and have elevated Cxcr3 and Il27ra expression. Chronic stress amplified the sex differences and preferentially increased the type 1 response including IFN{gamma} production in males at both the transcriptome and protein level. Type 17 response (e.g. IL-17A and IL-17F production) is also increased in response to UCMS, however with sex-divergent polarization: IL-22 is decreased in female and increased in male brain lymphocytes. Mechanistically, we found that UCMS suppressed P4ha1 in male and Zfp36 in female brain tissue resident lymphocytes. P4HA1 was previously shown to restrict mitochondrial function and limit type 1 responses in CD8 T cells, whereas ZFP36 is a suppressor of inflammatory cytokine translation. Consistent with this finding, ex vivo CD3-dependent stimulation of brain immune cells showed stress-dependent increase in cytokine production with sex-specific effects. Our study provides the cellular and molecular framework for chronic stress-induced tissue resident lymphocyte dysregulation and its sex bias in the brain, with implications for depressive disorders marked by inflammation.

immunology↗