Biology subjects

Shen, X.

Publications and source records attributed to Shen, X..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Multisensory integration of a host metabolite coordinates bacterial predation of macrophages

The crisis of antimicrobial resistance demands new strategies that circumvent conventional killing. Here, we show that Yersinia pseudotuberculosis intercepts host mesifurane, a mimic of quorum-sensing signal AI-2. Rather than acting through a single receptor, mesifurane is directly and independently sensed by three receptor classes, YcrA, NarX, and CusR, that converge on a "Sense, Arm, Recruit" program. YcrA drives chemotaxis toward host cells; NarX-NarP licenses T6SS-mediated killing; and CusR amplifies AI-2 production to recruit more bacteria. YcrA is conserved across Gram-negative pathogens, creating a therapeutic vulnerability. Suramin sodium, a repurposed drug blocking YcrA, disarms this circuit without inhibiting growth. In murine sepsis, suramin sodium conferred 80-90% survival against WHO critical-priority pathogens, including carbapenem-resistant A. baumannii, E. coli, and P. aeruginosa, even when delayed 8 hours post-infection, without selecting for resistance. These findings establish that disrupting sensory perception, rather than viability, provides an anti-infective strategy bypassing resistance while imposing minimal selective pressure.

microbiology↗

bioRxiv2026

From unsupervised clustering to atlas-guided annotation in cohort-scale spatial omics with HiCAT

Pathologist-annotated tissue regions provide a fundamental reference for examining spatial omics data, yet such annotations are available for a limited number of samples due to the substantial manual effort required. Moreover, these annotations are derived from morphology within individual histology images, which can overlook molecularly defined regions and obscure intra-sample heterogeneity. To address these limitations, we present HiCAT, a machine-learning framework that automatically generates pathologist-informed region annotations and characterizes regional heterogeneity in spatial omics data. Across seven datasets, HiCAT consistently outperforms state-of-the-art methods, achieving a median relative improvement of 107% in accuracy. Beyond transferring pathologist annotations, HiCAT uncovers molecularly informed regional heterogeneity not captured by original annotations, including tumor subregions associated with clinical outcomes and brain subregions aligned with spatiotemporal disease progression. By generating consistent, highly granular, and biologically informative region annotations across large cohorts, HiCAT enables scalable downstream analysis and provides training labels for foundation models in spatial biology.

genomics↗

bioRxiv2026

Rational Design of Resistance-Suppressing Phage-Antibiotic Cocktails via Receptor Tradeoffs

Bacteriophages (phages) are promising antibiotic alternatives, yet their utility is limited by rapid resistance evolution. Current phage-antibiotic combination strategies rely on empirical screening for efficacy in killing, which often fails to prevent resistance. Here, we establish a mechanistic framework to rationally design phage-antibiotic cotreatments that specifically suppress resistance by leveraging evolutionary tradeoffs. We show that traditional killing efficacy metrics do not predict resistance suppression. Instead, we identify predictable evolutionary trade-offs, including species-specific targets like TolC (Escherichia coli) and Type IV pili (Pseudomonas aeruginosa). We also identify a universal vulnerability for Gram-negative bacteria, lipopolysaccharide (LPS). We find that LPS-targeting phages are ubiquitous and that phage-steered LPS perturbation creates a predictable hypersensitivity to lipophilic antibiotics. This mechanistic trade-off, governed by physicochemical rules rather than drug-specific targets, directly correlates with resistance suppression. This framework shifts combination therapy from empirical screening to the a priori design of evolutionarily stable cocktails.

microbiology↗

bioRxiv2026

LagCI Enables Inference of Temporal Causal Relationships from Dense Multi-Omic Time Series

Inferring causal relationships from time-series data is critical for uncovering the dynamics of biological regulation. However, in multi-omics studies, this task is often hampered by sparse temporal sampling and the limitations of existing methods. To address this, we developed Lagged-Correlation Based Causal Inference (lagCI), a computational framework designed to identify time-lagged associations by combining comprehensive lag-correlation profiling with a robust statistical filtering scheme. Rather than relying on simple cross-correlation, lagCI analyzes the entire correlation profile and applies a quality-scoring system to filter out spurious associations that often plague high-dimensional datasets. We first tested lagCI on wearable physiological data, where it successfully captured the well-known causal link between physical activity and heart rate, even accounting for variations in lag times between individuals. Moving to high-frequency human multi-omics, we used lagCI to build a directed network of 1,624 molecules connected by over 157,000 predicted interactions. This network didnt just mirror established biology (such as cytokine-hormone crosstalk); it also pointed to specific molecular hubs that seem to orchestrate the timing of metabolic and immune responses. Overall, lagCI provides a data-driven way to extract temporal insights from dense longitudinal omics. Weve made the tool available as an R package with multiple interfaces to ensure its accessible for both bioinformaticians and clinicians.

bioinformatics↗

bioRxiv2026

Discovering Novel Circuit Mechanisms in Higher Cognition through Factor-Centric Recurrent Neural Network Modeling

Recurrent neural networks (RNNs) have transformed how systems neuroscientists generate hypotheses about circuit mechanisms in higher cognition. Yet their promise has been constrained by a fundamental limitation: conventional RNNs are neuron-centric and therefore often difficult to interpret mechanistically. Here we introduce Restricted-RNN, a factor-centric RNN modeling framework developed to uncover interpretable circuit mechanisms. By formalizing factor communication through subpopulations, the dual of neuron communication through subspaces, Restricted-RNN departs fundamentally from standard neuron-centric RNN models and provides a distinct framework for describing circuit mechanisms. Using this approach, we identify novel circuit mechanisms underlying sequence working memory control and the counterintuitive firing-rate reversal observed in perceptual decision-making, with key predictions supported by neurophysiological recordings from monkey frontal and parietal cortex. More importantly, factor-centric RNN modeling reveals a unified low-dimensional neural control state space that links seemingly disparate phenomena across tasks, providing a geometric framework for understanding the pervasive role of control in higher cognition.

neuroscience↗

bioRxiv2026

Complementary multiphoton tools to create 3D architectures in soft hydrogels for epithelial tissue engineering.

Curvature provides essential mechanical cues for epithelial cells, playing a key role in cell differentiation and morphology. Repeatable manufacture of precisely controlled curvature in soft hydrogel materials is therefore essential to study epithelial mechanobiology and function. Multiphoton (MP) based biofabrication holds promise due to its high resolution and three-dimensional design flexibility. Here, we leverage MPs advantages while increasing print speed to develop two complementary tools based on replica molding and multiphoton ablation. These can provide scalable hydrogel curvatures with tunable surface properties relevant for epithelial tissue engineering. In replica molding, MP prints are transferred into PDMS used to pattern centimeter scale arrays in hydrogels. In multiphoton ablation, hydrogels are locally degraded to generate precisely controlled curvatures and surface topography. With both methods, we repeatably guide epithelial cells into alveolar and duct-like shapes. Concave alveolar-like surfaces are shown to enhance the formation of thicker epithelial layers. We observe that surface properties, controlled by both tools, could enhance cytoskeletal organization. Using these biofabrication techniques, individual effects of curvature, surface properties, hydrogel composition, and bulk stiffness on epithelial cells can be studied. Both approaches offer high curvature control and throughput, providing a viable alternative to traditional 3D culture and other printing methods.

bioengineering↗

bioRxiv2026

Ovarian extracellular matrix mechanics regulate oocyte-follicle interactions during female reproductive aging

Female reproductive aging is associated with ovarian functional decline, leading to infertility. During aging, biochemical and biophysical changes in the ovarian extracellular matrix (ECM) occur, yet how these properties affect follicle growth and oocyte quality remains poorly understood. Here we describe spatiotemporal changes in the ovarian ECM with age using mass spectrometry, immunohistochemistry, and nanoindentation. While follicle stiffness remains unchanged, stromal matrix remodeling is associated with a [~]2.5-fold increase in stiffness. To understand how this increase in stromal stiffness affects age-related follicular dysfunction, isolated young follicles were cultured in soft and stiff hydrogels mimicking young and aged ovarian stromal stiffness, respectively. Higher stiffness leads to a decrease in granulosa cell (GC) proliferation, oocyte quality, and GC-oocyte interactions mediated via transzonal projections (TZPs). RNA-seq revealed TGF-{beta} signaling as a major pathway affected by stiffness, and activation of TGF-{beta} signaling through Mongersen treatment rescued TZP formation and oocyte quality in stiff matrix. These findings provide mechanistic insight into how changes in ECM mechanics contribute to ovarian aging functional decline and reveal potential therapeutic targets to counter fertility loss associated with tissue aging and fibrosis.

cell biology↗

bioRxiv2026

eBiota: Designing microbial communities from large seed pools with desired function using rapid optimization and deep learning

Designing microbial communities to generate target products is crucial for biotechnology, agriculture, and disease treatment. However, rationally designing such communities from large seed pools has become a major challenge, as the rapidly expanding number of complete microbial genomes greatly expands the search space and sharply increases the required screening time and computational cost. Here, we introduce eBiota, a platform for ab initio design of microbial communities from a pool of 21,514 strains to generate target products. eBiota not only identifies optimal strain combinations but also simulates community behaviors, including microbial interactions and relative abundances. eBiota integrates three modules: CoreBFS, a graph-based search algorithm that rapidly screens for bacteria with complete metabolic pathways related to the target product; ProdFBA, an extended flux balance analysis that identifies microbial consortia with maximal production efficiency; and DeepCooc, a deep learning model trained on 23,323 microbiome samples across various environments to infer co-occurrence patterns. We validated eBiotas capabilities in microbial community design and production efficiency calculation using public microbiome datasets, ranging from single strains to six-member consortia. Further in vitro experiments involving 94 strains confirmed eBiotas ability to identify species that inhibit pathogen growth and to accurately model the relative abundances within complex microbial communities. As an initial digital twin, eBiota provides a powerful platform for the rational design of functional microbial communities, offering new opportunities for metabolic engineering and synthetic biology.

bioengineering↗

bioRxiv2026

Harmonizing brain rhythms: cortex-wide neuronal dynamics underpin quasi-periodic patterns in resting-state fMRI

Functional magnetic resonance imaging (fMRI) captures whole-brain activity fluctuations non-invasively in humans and animals. Beyond task/stimuli-locked responses, fMRI measures large-scale patterned activity during rest. Among these, quasi-periodic patterns (QPPs) represent recurring waves of activity that unfold over seconds and exhibit consistent spatiotemporal characteristics. Notably, certain fMRI-QPPs are well-preserved across species and altered in various neuropsychiatric and neurodegenerative diseases. Yet, our collective understanding of their neural underpinnings is limited given the indirect nature of blood-oxygen-level dependent (BOLD) fMRI signals. Simultaneous measures of local field potentials have provided some affirmation that fMRI-QPPs have neural origins, but these point-measurements are limited to a handful of sites. Here, we use a unique multimodal implementation of simultaneous wide-field calcium (WF-Ca2+) imaging and fMRI to investigate the neural origins of fMRI-based QPPs. We uncover a robust time-locked correlation between QPPs detected by cortex-wide fluorescent WF-Ca2+ imaging of neural activity and QPPs of BOLD-fMRI. These data validate the hypothesis that BOLD-fMRI QPPs derive from preceding slow waves of neural activity with regional and temporal precision.

neuroscience↗

bioRxiv2026

Complete Genomes of Cultivated Gut Bacteria Reveal Mobile Genetic Element-Driven Functional Diversity with Therapeutic Implications

Cultivated bacterial isolates are essential for elucidating gut microbiota functions, yet reliance on fragmented draft genomes and limited mobile genetic element (MGE) annotation has constrained high-resolution analyses. Here, we present the Cultivated Complete Genome Reference (CCGR), a comprehensive compendium of 1,150 fully circularized human gut bacterial genomes. Overcoming draft limitations, CCGR achieves chromosome-scale resolution and reveals distinct evolutionary strategies shaping gene topological organization in response to bacterial growth. Furthermore, we decode the dynamic landscape of MGEs, demonstrating that broad-host-range phages follow strict positional patterns by integrating at conserved chromosomal hotspots flanked by nutrient transporter loci. Importantly, we provide mechanistic in vivo evidence that accessory genomic elements drive strain-level functional heterogeneity. Specifically, the plasmid-encoded scrK gene in Levilactobacillus brevis involved in fructose catabolism is required to mitigate fructose-diet-exacerbated colitis. Collectively, CCGR establishes a framework linking chromosomal architecture and MGEs to bacterial evolution and host health, enabling precise, strain-resolved functional investigations.

microbiology↗

bioRxiv2026

Endocardial TIE1 synergizes with TIE2 to regulate the atrial internal muscular network assembly

Atrial cardiomyopathy is characterized by altered atrial structures, yet its underlying genetic basis remains inadequately explored. TIE1 mutations are reported in lymphedema patients, but whether they exhibit cardiac defects alongside lymphatic abnormalities remains unknown. Here, single-cell RNA sequencing showed high Tie1 and Tek expression in atrial endocardial cells. TIE1 deficiency severely disrupted atrial morphogenesis, with only minor ventricular defects. Bulk RNA-seq showed reduced transcripts for endothelial development and cardiac trabeculation in Tie1 mutants. Separate RNA-seq analysis of the atria and ventricles further confirmed these findings, revealing a more pronounced downregulation of trabecular genes, including Tek, in the atria upon Tie1 loss. Endothelial deletion of Tek impaired trabeculation, particularly in atria. Consistently, Tie1 loss combined with a single null Tek allele disrupted both atrial and ventricular trabeculation. Strikingly, atrial morphogenesis defects appeared within 48 hours of induced endothelial Tie1 loss coupled with Tek heterozygous deletion, implying a critical endocardial role in organizing the atrial muscular network. The synergy of TIE1 and TIE2 in remodeling atrial trabeculae was confirmed postnatally, whereas TIE1 insufficiency alone had no effect. Together, TIE1 is differentially required for atrial versus ventricular development, acting synergistically with TIE2 to regulate endocardial cell-coordinated assembly of atrial internal muscular network.

developmental biology↗

bioRxiv2026

Insulin resistance modifies longitudinal multi-omics responses to habitual diet

How habitual diet influences the gut microbiome and plasma metabolome across insulin resistance states remains unclear. We conducted year-long multi-omics profiling of 71 deeply phenotyped adults, integrating repeated assessments of diet, metabolome, gut microbiome, clinical laboratory measures, and inflammatory markers. Using gold-standard insulin suppression tests and machine learning-derived dietary patterns, we examined how dietary patterns relate to metabolic and microbial landscapes by insulin resistance status. Insulin-sensitive individuals exhibited stronger and more numerous diet-omics associations than insulin-resistant individuals, identifying metabolic flexibility as a central determinant of dietary responsiveness. Parabacteroides emerged as a candidate microbial mediator between refined carbohydrate-rich dietary patterns and host metabolic signatures. Integrated into a cardiovascular risk prediction model, diet, metabolites, microbial taxa, and immune markers each contributed to 10-year atherosclerotic cardiovascular disease risk. These findings show that inter-individual variation in cardiometabolic risk partly reflects differences in molecular responsiveness to habitual diet, informing precision nutrition and cardiovascular prevention.

molecular biology↗

bioRxiv2026

Oxidation-Driven mtDNA B-Z Transition Activates ZBP1 to Mediate Acetaminophen Hepatotoxicity

Acetaminophen (APAP) overdose induces mitochondrial damage in hepatocytes, leading to secondary toxicity that resists to N-acetylcysteine (NAC) treatment and culminates in hepatocyte death and acute liver failure (ALF)1. The underlying mechanisms remain poorly understood, often necessitating liver transplantation2. Here, we identify oxidative modification-driven B-to-Z transitions in mtDNA as the central pathological driver of APAP-induced ALF. Upon APAP exposure, oxidized mtDNA fragments leak into the cytosol, activating ZBP1 signaling via its Z domain. Genetic inhibition of ZBP1 mitigates liver damage and improves survival. Using synthetic 12-bp dGdC duplexes, we demonstrate that 8-oxoG substitution, even under physiological salt concentrations, is sufficient to induce Z-DNA formation, enabling specific ZBP1 binding through its Z domain. The 8-oxoG repair enzyme OGG13, activated by TH107854, removes 8-oxoG modifications and reverses Z-DNA to B-DNA conformation. In mice with lethal APAP toxicity, delayed NAC treatment results in 50% mortality. In contrast, TH10785 monotherapy increases survival to 90%, while its combination with NAC achieves 100% survival. These results define the oxidized mt Z-DNA-ZBP1 axis as a critical driver of APAP hepatotoxicity, providing fundamental insights into DNA conformational dynamics and therapeutic opportunities in drug-induced liver failure.

cell biology↗

bioRxiv2026

The hippocampus enables abstract structure learning without reward

Statistical learning (SL) allows organisms to infer latent structure from sensory input without instruction, feedback, or reward, yet how the brain accomplishes such abstract, unsupervised learning remains unknown. Here we show that mice, like humans, rapidly acquire multiple forms of statistical structure, including event frequency, sequence identity, and abstract structural rules, and that the hippocampus is essential for this capacity. Pupil dynamics provided a cross-species, implicit readout of expectation formation, revealing spontaneous sensitivity to these regularities during passive listening. In mice, pharmacological and temporally precise optogenetic inactivation of dorsal CA1 abolished all learning-related pupil signatures without affecting baseline pupil size, target-evoked responses, or task performance, demonstrating a causal requirement for the hippocampus in forming and updating internal models of sensory structure. High-density recordings further revealed that dCA1 ensembles track evolving statistical contexts while dynamically reorganising population activity into subspaces that separately encode sensory features and abstract rules, enabling generalisation across distinct but structurally equivalent sequences. Together, these results identify the hippocampus as a critical neural substrate for latent abstract structure learning and offer a mechanistic account of how internal models emerge from unsupervised experience.

neuroscience↗

bioRxiv2026

The genetic repertoire of the deep sea: from sequence to structure and function

The deep sea as the largest and maybe most hostile environment on Earth is still underexplored especially regarding its genetic repertoire. Yet, previous work has revealed significant habitat-specific deep-sea biodiversity. Here, we present an integrated deep-sea genetic dataset comprising 502 million nonredundant genes from 2,138 samples and 2.4 million predicted structures, and used it to link specific protein structures with genetic variants associated with life in the deep sea and to assess their biotechnology potential. Combining global sequence analysis with biophysical and biochemical measurements revealed unprecedented sequence diversity, yet substantial structural conservation of proteins. Especially proteins involved in replication, recombination, and repair were identified to be under rapid evolution and with specialized properties. Among these, a structurally divergent helicase exhibited advantages in controlling nanopore sequencing speed. Thus, our work positions the deep sea as a unique evolutionary engine that generates and hosts genetic diversity and bridges genetic knowledge with biotechnology.

bioinformatics↗

bioRxiv2026

Intranasal Delivery of HIV/SIV Antigens with NE/AS01B Adjuvants Enhances Cellular Immunity and Reduces Viral Loads in SHIV-Challenged Macaques

The primary route of HIV transmission is across mucosal tissues; therefore, developing a protective mucosal vaccine is a top priority. In a pilot study, using a macaque model, we delivered HIV gp140 envelope glycoprotein and SIVmac239 P55 Gag and Nef antigens using heterologous prime/boost via the intranasal route with a soybean oil-based nanoemulsion (NE) adjuvant and through the intramuscular route with the AS01B adjuvant system to generate enhanced cell-mediated immunity. We used a NE adjuvant to promote gut-homing cell-mediated immunity and the AS01B system to enhance humoral immune responses. Following intrarectal challenge with SHIV 4MTF.tHy, vaccinated macaques acquired the virus but experienced lower viral loads in plasma (P=0.003) and CSF (P=0.001), and potent polyfunctional gag-specific (CD107a+, IFN{gamma}, TNF+) responses across diverse lymph nodes. Significant antibody-dependent complement deposition (ADCD) and antibody-dependent cellular phagocytosis (ADCP) responses were induced, and gut-microbiome crosstalk could be modulated and showing reduced SHIV-dysbiosis. Notably, vaccination preserved mucosal all-trans retinoic acid levels (atRA) (p<0.05). However, no significant differences were observed for antibody responses between vaccinated and unvaccinated macaques. In summary, the induced gut-homing properties by the NE adjuvant are effective at generating cell-mediated immunity and reducing viral set points and warrant further investigations as a mucosal adjuvant in HIV vaccine design. ImportanceThree major non-mucosal vaccine trials (RV144, HVTN702, and 706) failed to reduce HIV infection rates. Therefore, new approaches in developing a mucosal vaccine remain an effective strategy to attempt to control HIV infection. Coherent vaccine approaches against HIV were focused on immune correlates related to viral loads, persistent reservoirs, and antibody responses. As a proof-of-principle, we developed a vaccine regimen consisting of AS01B and an adjuvanted oil-in-water NE cleaved HIV clade C gp140 protein and non-cleaved Gag, and nef particles administered through intranasal, subcutaneous, and intramuscular routes, followed by intrarectal challenge with clade C SHIV. This vaccine elicited strong ADCD and ADCP responses, modulated immune-microbiome crosstalk, and reduced susceptibility to SHIV-infection-associated dysbiosis. Additionally, it preserved mucosal all trans retinoic acid (atRA) levels, suggesting a potential role for this approach in HIV vaccine development.

microbiology↗

bioRxiv2026

cloneXplorer: A high-throughput clone discovery platform based on conical microwell arrays

Antigen-specific T cell populations are of great value for studying immune recognition but tedious to generate by limiting dilution or cloning. Here, we develop a streamlined approach to generate antigen-specific T cell clones directly from peripheral blood using the cloneXplorer, a live-cell analysis and clone isolation platform based on conical microwell arrays. This platform continuously monitors cell proliferation, cytokine secretion, and surface markers in up to 100,000 single cell co-cultures, enabling the identification of rare, functionally defined T cells, which can be recovered for clonal expansion or sequence analysis. We benchmark the platform by performing several key demonstrations. First, we show that this platform can efficiently generate monoclonal cell populations from cell lines and human T cells. Next, we demonstrate that antigen-specificity can be identified at single cell resolution using a co-culture of Jurkat cells expressing NFAT-GFP, CD8, and a T cell receptor and K562 antigen presenting cells (APC) expressing a peptide library. Thereafter, we show that immune activation in mouse and human primary samples can be monitored by time lapse analysis of Interferon gamma (IFN-{gamma}) secretion in individual microwell co-cultures using a fluorescent sandwich assay. Finally, we combine these capabilities in a proof-of-concept demonstration, which uses IFN-{gamma} secretion and the presence of CD8 surface markers as hierarchical gates to isolate and expand antigen-specific T cells from human peripheral blood, and we verify their specificity by tetramer staining. Together, these results showcase potential applications of the cloneXplorer platform in cell line development, and in screening and validating immune receptor interactions with specific antigens. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/699323v1_ufig1.gif" ALT="Figure 1"> View larger version (48K): org.highwire.dtl.DTLVardef@1aafc29org.highwire.dtl.DTLVardef@91272dorg.highwire.dtl.DTLVardef@1a306eeorg.highwire.dtl.DTLVardef@1bfd54_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2026

Functional Convergence of Genetically Diverse B-Cell Receptors in Simian-HIV Infected Rhesus Macaques

Germline-targeting or lineage-design vaccine strategies are being used to induce HIV broadly neutralizing antibody (bnAb) responses. These strategies assume that genetically diverse individuals respond similarly to the same immunogen by mobilizing comparable germline precursors, although outcomes vary across bnAb epitopes. Here we explored this premise using a simian-HIV infection model in rhesus macaques. Antigen-unbiased Env- reactive B-cell populations were profiled, followed by systematic analysis of antibody function and B-cell receptor (BCR) genetics. We find that while global Env-reactive B-cell response profiles and antibody functional properties are similar across individuals, underlying BCR genetics are diverse, particularly among non-bnAbs. These results indicate that functional convergence of Env-reactive antibody responses does not necessarily require genetic convergence and suggest that specific germline-targeting may not be an absolute prerequisite for successful vaccine design. These findings support an epitope-focused framework in which bnAb epitopes are engineered to enhance population-level immunogenicity, with potential applicability to other challenging pathogens.

immunology↗