Biology subjects

Wang, C.

Publications and source records attributed to Wang, C..

At least 163 records · Page 9Linked to original sources

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

A Conserved Geometric Code: Extracellular Matrix Curvature Directs Cell Migration Strategy via Nuclear Mechanosensing

Cells navigate complex tissue microenvironments defined by intricate physical cues, yet how they interpret the three-dimensional geometry of the extracellular matrix (ECM) remains an open question. Current models often fail to account for the tortuous architectures found in physiological tissues. Here, we demonstrate that ECM curvature functions as a tissue-specific geometric code read by the cell nucleus. By mapping collagen architectures across cancers and tissues, we find unique curvature fingerprints preserved during metastasis. Using micro-engineered substrates, we show that high curvature imposes localized nuclear bending stress, triggering a Lamin A/C-cPLA2-Ca2+ mechanotransductive cascade. This sensor rewires the cytoskeleton from longitudinal stress fibers to a cortical actomyosin network, driving a sharp transition from fast mesenchymal migration to a slower, exploratory amoeboid phenotype. We term this "nuclear curvotaxis", establishing a physical principle linking static geometry to dynamic strategy, with implications for predicting metastatic risk, understanding immune exclusion, and designing bio-instructive scaffolds for tissue engineering.

biophysics↗

bioRxiv2026

Adaptive immunity shapes baseline physiology of M. tuberculosis in high-dose versus low-dose infection BALB/c mouse drug treatment models

Preclinical tuberculosis (TB) drug evaluation relies heavily on mouse infection models. Drug efficacy varies depending on inoculum and the timing of treatment initiation. These differences reflect, in part, physiological adaptations of Mycobacterium tuberculosis (Mtb) to host immune pressure. We used novel molecular markers of pathogen health (RS ratio and SEARCH-TB) to contrast Mtb phenotypes in the BALB/c high dose aerosol (HDA) subacute TB and low dose aerosol (LDA) chronic TB infection models, focusing on the transition from innate to adaptive immunity. We found that the onset of adaptive immunity coincided with a rapid reprogramming of Mtb physiology, characterized by suppressed respiration, metabolism, and biosynthesis, together with induction of stress and nutrient acquisition pathways. Changes in key Mtb processes were concordant with changes in host expression of canonical features of adaptive immunity. Our results also explain key model-specific differences in drug efficacy: when used for drug evaluation, the HDA model begins treatment during the innate immune phase when Mtb are metabolically active, whereas the LDA model initiates therapy after host adaptive immunity has already activated and the bacterial population is immune-constrained. The HDA model is shown to be a mixed model, spanning immune phases with initial treatment acting on replicating bacteria and later treatment acting on immune-constrained populations. Together, the two models offer complementary perspectives on therapeutic activity across the spectrum of bacterial states and provide a framework for designing regimens that are effective against both active and immune-constrained Mtb.

genomics↗

bioRxiv2026

Population Structure and Antimicrobial Resistance Gene Transfer of Respiratory Escherichia coli Isolated from Swine in China

ABSTRACPorcine respiratory diseases caused by extraintestinal pathogenic Escherichia coli (ExPEC) pose a severe threat to swine production and public health; however, research on respiratory tract-isolated ExPEC remains limited. This study comprehensively analyzed the genomic characteristics and antibiotic resistance gene (ARG) transfer potential of 441 ExPEC strains isolated from porcine lungs across 21 Chinese provinces (including 53 newly isolated strains from 2022-2024 and 388 NCBI-deposited strains). Phylogenetic analysis revealed that 84% of the isolates belonged to phylogroups A, B1, and C, with ST410, ST101, and ST88 as the predominant STs. The strains exhibited extensive ARG diversity, harboring 111 distinct ARG subtypes, with sul2 (81.4%), floR (73.5%), and tet (A) (68.0%) being the most prevalent. Importantly, critical "last-resort" antibiotic resistance genes (e.g., blaNDM-1/5, the mcr family, and tet (X4)) were also detected. Notably, 77.2% of the ARGs presented horizontal transfer potential, with plasmids (especially IncF family replicons) serving as core vectors, followed by integrons and transposons. Cooccurrence network analysis identified aph (3)-Ib, aph (6)-Id, sul2, and floR as core subnetworks driving multidrug resistance dissemination. Pangenomic analysis confirmed an open genome architecture, with core genes accounting for only 6%, reflecting the strains capacity to acquire exogenous genetic material via horizontal transfer. From the One Health perspective, these transferable ARGs can spread to the environment and humans through fecal discharge and the food chain. These findings underscore the importance of monitoring and controlling ExPEC infections in swine, as such strains can as reservoirs of ARGs, pose potential risks to human health, and may even act as sources of pathogenic agents responsible for human infections. IMPORTANCEPorcine respiratory ExPEC-induced diseases threaten swine production and public health, yet respiratory tract-isolated ExPEC research remains scarce. This study comprehensively analyzed 441 porcine lung ExPEC strains across 21 Chinese provinces, uncovering their dominant phylogroups, high ARG diversity (111 subtypes) and the presence of "last-resort" antibiotic resistance genes. We identified 77.2% of ARGs with horizontal transfer potential, plasmids (especially IncF family) as core vectors, and a core ARG subnetwork driving multidrug resistance. The open pangenome (6% core genes) highlights ExPECs strong capacity to acquire exogenous genes. These findings fill the research gap of respiratory ExPEC, clarify ARG transmission mechanisms in swine ExPEC, and provide critical genomic data for One Health-based AMR surveillance and control, guiding targeted strategies to mitigate ARG spread from swine to humans and the environment.

microbiology↗

bioRxiv2026

Mucosal Inflammation Shapes Human Neutrophil States in Tissue and Circulation

The oral mucosa is a prototypical human barrier reliant on neutrophils for homeostasis, as both neutrophil deficiency and excessive activation are linked to immunopathology. Yet, whether neutrophils acquire tissue-specific states in health or disease remains unclear. We incorporated single-cell RNA sequencing, spectral flow cytometry, and spatial proteomics across tooth-associated oral mucosa (gingiva) and interconnected compartments of blood and oral cavity to define neutrophil tissue specification in healthy individuals and patients with periodontitis, a neutrophil-dominated inflammatory disease. In health, mucosal neutrophils adopt discrete immunoregulatory states despite constant microbial exposure and mechanical injury. Periodontitis disrupts these programs through infiltration of blood-like neutrophil subsets, increased transcriptional noise, and heightened effector activation. Strikingly, oral inflammation systemically imprints on circulating neutrophils, marked by the expansion of a Rho-GTPase regulatory program that is shared across diverse human inflammatory conditions. Together, these findings establish a framework for understanding how localized tissue inflammation affects both neutrophil plasticity at barrier surfaces and conditioning of systemic neutrophil states with broad implications for inflammatory disease pathogenesis.

immunology↗

bioRxiv2026

A feed-forward loop between niche adenosine and Gzmk⁺ CD8 T cells propagates systemic inflammaging

The causal link between the aging microenvironment and T cell aging remains elusive. Here, we demonstrate that adenosine within aging tissues actively reprograms CD8+ T cells into a pro-aging Granzyme K+ (Gzmk+) population. Mechanistically, senescent cells create an adenosine-rich niche via p16-dependent CD39 upregulation, triggering A2aR signaling to induce Gzmk+ T cell differentiation. Once released, Gzmk promotes systemic inflammaging through PAR1 and complement activation. Crucially, targeting this axis--either via genetic Gzmk ablation or pharmacological A2aR blockade--reverses multi-organ aging phenotypes and significantly extends healthy lifespan in mice. Human analysis reveals age-dependent Gzmk+ T cell accumulation in multi organs, while coffee intake (an A2aR antagonist) inversely correlates with plasma Gzmk levels. Our findings uncover how metabolic niche changes drive T cell aging and establish the adenosine-Gzmk axis as a pivotal therapeutic target for combating age-related diseases.

immunology↗

bioRxiv2026

X-Cell: Scaling Causal Perturbation Prediction Across Diverse Cellular Contexts via Diffusion Language Models

Causal models of cellular systems hold the promise to empower broad biological discovery, including the systematic identification of novel targets for drug discovery. Predicting how genetic and pathway perturbations reshape gene expression across diverse cellular contexts is a prerequisite for building generalizable cellular foundation models. However, current methods typically fail to extrapolate beyond their training distributions because they rely predominantly on observational expression atlases rather than interventional perturbation data. We present X-Atlas/Pisces, the largest genome-wide CRISPRi Perturb-seq compendium to date, comprising 25.6 million perturbed single-cell transcriptomes across 16 biologically diverse contexts, including widely used cell lines, induced pluripotent stem cells (iPSCs), resting and CD3/CD28 activated Jurkat T lymphoma cells, and multi-lineage differentiating iPSCs. Leveraging this resource, we develop X-Cell, a diffusion language model that predicts perturbation responses by iteratively refining control-to-perturbed state transitions through cross-attention to multi-modal biological priors derived from natural language, protein language models, interaction networks, genetic dependency maps, and morphological profiles. X-Cell outperforms existing state-of-the-art models by up to five-fold on key metrics such as Pearson{Delta} (correlation between predicted and observed perturbation-induced log-fold changes), and demonstrates zero-shot prediction of T cell inactivating perturbations in stimulated Jurkat cells. We scale X-Cell to 4.9 billion parameters (X-Cell-Ultra), the largest causal perturbation model to date. We demonstrate for the first time that perturbation prediction follows power-law scaling with an exponent matching large language models. X-Cell-Ultra demonstrates zero-shot generalization to novel biological contexts, including unseen iPSC-derived melanocyte progenitors and primary human CD4+ T cells from multiple donors, and outperforms all baselines after self-supervised test-time adaptation. These results demonstrate that coordinated scaling of causal perturbation data and model capacity yields foundation models capable of generalizable perturbation prediction across cellular contexts, with potential applications for improving computational target identification, validation, and context-specific therapeutic prioritization.

systems biology↗

bioRxiv2026

Trem2hi macrophages bridge inflammation resolution and fibrosis initiation after ischemia-reperfusion injury in the kidney

Maladaptive repair of acute kidney injury (AKI) may lead to the development of chronic kidney disease (CKD) characterized by renal fibrosis. Macrophages play roles in AKI-to-CKD progression; however, the interplay between inflammation and fibrosis after AKI remains controversial and the precise role of the distinct macrophage subsets remains elusive. In the present study we identified a unique population of Trem2hi macrophages derived from the bone marrow as a mediator bridging inflammation resolution and fibrosis establishment after kidney injury. Trem2 deficient mice exhibited mitigated renal fibrosis after ischemia-reperfusion injury (IRI) while the renal injury and inflammation persisted. Mechanistically, Trem2 promoted renal inflammation resolution by facilitating macrophage efferocytosis to remove apoptotic tubule cells and reshaping the macrophage cytokine production profile. Loss of Trem2 expression led to excessive cholesterol accumulation in macrophages via Lxr-Abca1/Abcg1 axis and thus sustained pro-inflammatory cytokines production. Moreover, Trem2hi macrophages orchestrated the pro-fibrotic tubular epithelial cells and the activation of myofibroblasts through SPP1 to promote the establishment of renal fibrotic niche. Based on our findings, Trem2hi macrophages may serve as a potential therapeutic target for AKI-to-CKD in combination with anti-inflammatory remedies.

immunology↗

bioRxiv2026

Spatio-temporal mapping of immune cell dynamics during human sequential lymph node metastasis

Regional lymph node (LN) metastasis critically influences distant metastatic progression, anti-tumour immunity, and patient prognosis. While tumour-induced immune modulation in tumour-draining LNs (TDLNs) has been extensively studied using murine models, the systematic reconstruction of the immune system from primary tumours through TDLNs and subsequent lymph nodes in human cancer progression remains understudied. Here, we utilised integrated multi-omics approaches, including imaging mass cytometry, single-cell RNA sequencing, Visium and Xenium spatial transcriptomics, and multi-colour immunofluorescence to systematically characterise immune cell dynamics across 147 paired primary tumours, sentinel TDLNs (S-TDLNs), and secondary axillary LNs (ALNs) obtained from 50 treatment-naive triple-negative breast cancer patients with different progression statuses. Our comprehensive profiling revealed critical immune alterations, such as decreased type-2 conventional dendritic cells (cDC2), naive T cells, and B cells, along with an increase in immunosuppressive macrophages. Developing a novel single-cell transformer model, we identified substantial alterations in various immune cell populations, notably MARCO+ macrophages, which strongly correlated with breast cancer patient survival outcomes. Spatial analysis combined with our newly integrated cell-cell interaction platform revealed diminished immune cell communication and impaired priming interactions among dendritic cells, B cells, and T cells within metastatic lymph nodes and primary tumour sites. In an independent neoadjuvant immunotherapy cohort of 36 TNBC patients with 52 lymph node samples, we found preservation of CD1c cDC2 in lymph nodes predicted pathological complete response and longer event-free survival, highlighting cDC2 as a potential biomarker and therapeutic target. Collectively, this systematic mapping of immune landscape alterations during human sequential LN metastasis provides essential insights for understanding cancer metastasis mechanisms and paves the way for innovative immunotherapeutic strategies.

immunology↗

bioRxiv2026

Bacillus velezensis-derived muropeptide promotes growth of zebrafish via NOD2-mediated induction of IGF1 signaling

The role of gut microbiome in regulating vertebrate metabolism has been well-recognized. However, the effects of gut bacteria on growth have been less studied. Bacillus is a prevalent genus in the gut microbiota of human and animals. In this study, the effect of gut-derived Bacillus velezensis T23 on growth was investigated in zebrafish. B. velezensis T23 improved the growth of zebrafish and promoted IGF1 production in the liver and muscle, with a concomitant activation of the AKT/mTOR signaling pathway. The growth-promoting effect of B. velezensis T23 was not dependent on lipopeptides and polyketides. Cell wall peptidoglycan isolated from B. velezensis T23, as well as muramyl dipeptide (MDP), was sufficient to stimulate IGF1 signaling and growth. Further, the effect of B. velezensis T23 on growth and IGF1 production was abrogated in nod2-/- zebrafish, confirming that B. velezensis T23 promoted growth via MDP-NOD2 signaling. Gut transcriptomic analysis indicated that B. velezensis T23 promoted renewal and differentiation of intestinal cells, suggesting an involvement of gut-liver axis in the effect of B. velezensis T23 on systemic IGF1 production. Together, our results revealed an effect of gut Bacillus-derived muropeptide on growth via NOD2-IGF1 signaling, and provided novel mechanistic insights in the beneficial effect of Bacillus spp. as probiotics.

microbiology↗

bioRxiv2026

High-Fidelity Long-term Whole-embryo Lineage and Fate Reconstruction by Iterative Tracking with Error Correction

Reconstructing the complete cell lineages and fate maps of a living embryo has remained a central challenge in developmental biology. Here we introduce ITEC (Iterative Tracking with Error Correction), a fully unsupervised method that automatically reconstructs the lineage of every cell in the embryo with high fidelity. ITEC was validated with manually annotated lineages on four cross-species datasets including zebrafish, mouse, and Drosophila. We reconstructed the developmental lineages of a zebrafish embryo from terabyte-scale data of total 18.5 million cells with an estimated accuracy of over 99.7%. With ITEC, we revealed spatiotemporal dynamics of key morphogenetic processes such as somite boundary formation, demonstrated the various patterns of spatial sorting among adjacent organs or anatomical regions, and identified associations between cellular movement and spatial transcriptomics. ITEC provides a powerful platform for retrospective fate mapping and systematic exploration of developmental dynamics at the cellular scale and single-embryo level.

bioinformatics↗

bioRxiv2026

Context-dependent genetic regulation of gene expression in pigs

Production livestock provide a natural system for studying gene regulation under physiologically demanding conditions shaped by rapid growth, environmental exposure, and immune challenges. Using farm pigs from the PigGTEx resource as a model, we applied quantile regression to uncover latent, context-dependent genetic effects on gene expression across tissues. This approach identifies quantile-specific expression quantitative trait loci (eQTLs) that are not detected by standard linear regression and are enriched in distal regulatory elements and three-dimensional genome architectural features rather than promoter-proximal regions. Genes with quantile-dependent eQTLs are more intolerant to loss-of-function variants and exhibit stronger enrichment in GO functional categories, indicating their likely functional significance. Cross-species comparisons reveal substantial overlap between pig and human eGenes across tissues, indicating conservation of regulatory architecture. Notably, many quantile-specific eQTLs influence tail expression states and involve genes relevant to human disease. For example, we identify a cis-eQTL affecting the conserved transcriptional regulator BCL6B in pig blood that modulates enhancer activity and reduces expression at lower quantiles. In contrast, BCL6B is minimally expressed in resting human blood and lacks detectable cis-regulatory variation under baseline conditions, consistent with its reported induction during immune activation. These findings demonstrate that pig eQTL maps can reveal context-dependent regulatory variation at loci that remain silent or weakly variable in human cohorts.

bioinformatics↗

bioRxiv2026

Metabolic reprogramming and stress mitigation of Chlamydomonas reinhardtii using protective metal-phenolic networks

Single-cell encapsulation is widely used in biotechnology to protect highly sensitive living cells from environmental stress. However, the impact of encapsulation on biological function and metabolism remains rarely explored despite its importance for understanding stress response and modulating the production of valuable metabolites. Herein, we show that coating individual cells with protective metal-phenolic networks not only improves survival against stress, but also modifies cellular metabolism. Importantly, this encapsulation technique induces a reversible state of quiescence, which enables accumulation of high-energy-density compounds through selective nutrient diffusion and the resulting carbon flux redistribution. Specifically, light exposure favors the accumulation of nearly eightfold higher starches, while incubation in darkness leads to twofold higher lipid accumulation compared to native cells. This metabolic engineering approach via individual cell encapsulation expands the cell editing toolbox and will facilitate applications in synthetic biology, bioengineering, and cell-based therapeutics. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=184 SRC="FIGDIR/small/711231v2_ufig1.gif" ALT="Figure 1"> View larger version (60K): org.highwire.dtl.DTLVardef@d27478org.highwire.dtl.DTLVardef@dc73baorg.highwire.dtl.DTLVardef@131dcaeorg.highwire.dtl.DTLVardef@8f3dc4_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2026

Volume regulation of cancer cells during osmotic pressure variation

Osmotic pressure is a fundamental physical determinant of cellular homeostasis, and its perturbation is recognized as a critical factor in cancer progression and therapy. However, whether cancer cells and normal cells respond to osmotic pressure changes differently remains unclear. Here, we subjected cancer and normal cells to osmotic shocks and compared their volume and traction force changes. Under hypotonic conditions, cancer cells recovered their volume and forces much more slowly than normal cells, although both cell types responded similarly to hypertonic shock. We found that actin-based cortical tension controlled the recovery speed; whereas myosin-mediated contractility tuned the volume change extent. Substrate stiffness also influenced the recovery process by altering cytoskeletal constraint. A theoretical model integrating adhesion energy, ion and water transport, and surface tension was developed. The results matched the experimental observations. Our work uncovered the distinct mechanobiological behaviors of cancer cells upon hypotonic shock, providing a mechanical framework for understanding cancer mechanisms that may inform the development of cancer therapeutics.

biophysics↗

bioRxiv2026

FishMamba-1: A Linear-Complexity Foundation Model for Deciphering Polyploid Cyprinid Genomes

The Cypriniformes order, comprising essential aquaculture species like carps and minnows, presents unique genomic challenges due to complex whole-genome duplication (WGD) events and extensive repetitive elements. Conventional annotation tools and Transformer-based foundation models often struggle to capture long-range dependencies in these expanded genomes due to quadratic computational complexity. Here, we introduce FishMamba-1, the first genomic foundation model tailored for the aquatic clade, built upon the selective state-space model (SSM) architecture. By leveraging Mamba-2s linear scaling efficiency, FishMamba-1 processes context windows of 32,768 base pairs (32k)--significantly surpassing the 4-6k limit of standard DNA Transformers--enabling the modeling of distal regulatory patterns on a single GPU. We curated Cypri-24, a comprehensive dataset comprising 28.8 Gb of high-quality genome assemblies from 24 representative species, to pre-train FishMamba-1 on 15 billion tokens. Subsequent fine-tuning for genome segmentation (FishSegmenter) demonstrates the models capability to annotate gene structures at single-nucleotide resolution with remarkable precision. Evaluation on a held-out test set reveals that FishMamba-1 achieves a precision of 64.6% in exon identification, effectively distinguishing coding regions from the vast non-coding background without relying on RNA-seq evidence. Furthermore, interpretability analysis confirms that the model captures biological syntax such as splice acceptor motifs. FishMamba-1 provides a scalable, open-source framework for decoding the complex genomes of non-model organisms, providing a scalable computational resource to support downstream applications in molecular breeding and ecological monitoring. The complete source code, pre-trained model weights, and datasets are freely available at https://github.com/lu1000001/FishMamba. Additionally, the FishMamba Hub, a web-based inference platform, is accessible at https://huggingface.co/spaces/lu1000001/FishMamba-Hub to facilitate real-time genomic segmentation for the aquatic research community. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=112 SRC="FIGDIR/small/710409v1_ufig1.gif" ALT="Figure 1"> View larger version (71K): org.highwire.dtl.DTLVardef@f5ee02org.highwire.dtl.DTLVardef@1dcfd31org.highwire.dtl.DTLVardef@1729ef8org.highwire.dtl.DTLVardef@22e4f1_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2026

MetaSAG: A Tool for Multi-level Exploration and Taxonomic Analysis of Microbial Single-Amplified Genomes

Microbial single-amplified genome (SAG) sequencing technologies have elevated microbial research resolution to the single-cell level. However, neither upstream data processing nor downstream analysis has been fully developed, greatly limiting the research in strain level. Herein, we developed MetaSAG (Multi-level Exploration and Taxonomic Analysis of microbial Single-Amplified Genomes), which enables accurate and rapid taxonomic classification of microbial SAGs. MetaSAG outperforms existing method in species classification certainty, computational efficiency, and sensitivity of low abundance species identification. In addition, MetaSAG enables species-level functional analysis, as well as strain-level evolutionary analysis. With the help of MetaSAG, we discovered the parasitic relationship between phages and bacteria, identifying multiple susceptible bacteria and a broad spectrum of phages. Furthermore, we developed MetaK-Lytic (k-mer-based meta-learning framework to predict phage lytic ability) to achieve accurate prediction of phage lytic activity based on 31-mer short sequences, which is well adapted to the characteristics of incomplete SAG sequences. Overall, we offer a comprehensive integrated tool that can parse microbial SAG data from raw data to the strain level to decipher the functional ecology of microbial dark matter, with broad implications for microbial ecology and phage therapy (https://github.com/liangcheng-hrbmu/MetaSAG). Significance StatementThis work provides a comprehensive framework for high-resolution SAG data analysis. The developed pipeline improves taxonomic annotation sensitivity and speed. Strain-level tracking enables dynamic evolutionary and functional insights, while single-cell bacterial-virus network reconstruction reveals precise interaction patterns. The novel annotation-free short sequence-based MetaK-Lytic facilitates functional prediction of uncharacterized phage sequences. Integrated into the MetaSAG platform, these tools deliver a streamlined, multi-level solution for interpreting SAG data, advancing studies in microbial ecology, evolution, and virology.

microbiology↗

bioRxiv2026

Comparison of extracellular vesicles and mechanically induced vesicles for structure determination of membrane proteins

The structural and functional characteristics of membrane proteins can be influenced by the composition of the membrane. Consequently, native membranes are most relevant for the study of receptors and other membrane proteins. In this study, we investigated two types of cell-derived vesicles: natively shed extracellular vesicles (EVs) and mechanically derived vesicles (MVs). To this end, we utilized the human breast cancer cell line SKBR3, which strongly overexpresses the receptor HER2. We designed a protocol based on designed ankyrin repeat proteins (DARPins) to purify EVs and MVs enriched in HER2, and to ensure the native orientation of the HER2 receptors within the vesicle. The isolated HER2-containing EVs and MVs were characterized by cryo-EM, cryo-electron tomography (cryo-ET) and mass spectrometry (MS), which revealed fundamental differences between the different vesicle types. Our study highlights the greater structural diversity of EVs over MVs. A single particle cryo-EM analysis and classification of all visible receptors on the vesicle surface yielded electron density consistent with HER2 at modest resolution. Taken together, our results suggest that MVs can serve better than EVs as a suitable platform for the structure determination of membrane proteins within their native membrane environments.

biochemistry↗

bioRxiv2026

Circadian phase and sex shape swimming exercise responses and stereotyped behaviors in mice

Exercise provides broad health benefits, including improved emotional well-being and cognitive function. Emerging evidence suggests that exercising at different times during the day can have differential effects. However, how circadian phase and sex influence behavioral and physiological responses to exercise remains unclear. To address this question, we examined male and female wild-type mice maintained in either regular (REG, lights on/off at 7AM/7PM) or inverted (INV, lights off/on at 10AM/10PM) light cycles. Mice were then subjected to daily 20-min group swimming exercise sessions at ZT2-3 for 3 weeks. Exercised and sedentary controls mice were then subjected to an open field test (OFT) and blood corticosterone (CORT) measurements 24 hours post-exercise. We quantified several behaviors during swimming: escape attempts, floating, climbing and collisions. We also identified a novel swimming behavior: floating with only nostrils-above-water events (NAWEs). We found that expression of these behaviors was differentially modulated by sex, light-cycle and their interaction. Notably, behavioral differences were more pronounced in REG mice (rest phase). REG mice also lost weight after exercise and had elevated CORT levels compared to mice kept in INV conditions (active phase). Interestingly, OFT behaviors showed significant differences primarily in INV mice, particularly females, when comparing exercised vs sedentary groups. Our novel findings reveal that circadian rhythms and sex significantly interact to shape swimming exercise and stereotyped behaviors in mice. This emphasizes the need to consider the animals circadian phase when designing preclinical studies to match intended behavioral and physiological outcomes. HIGHLIGHTSCircadian phase and sex jointly shape swimming behavior patterns. Newly identified swimming behavior is more prevalent during rest-phase Restphase exercise produced stronger behavioral and physiological effects. Rest-phase exercise resulted in weight loss and elevated stress markers. Active-phase exercised females showed the strongest open field behavioral differences.

physiology↗