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Search indexed bioRxiv preprints in genomics, neuroscience, cell biology and bioinformatics. Read source abstracts and check manuscript versions; preprints are not peer reviewed.

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bioRxiv2026

The Microbiota Dictates Vendor-Derived Differences in a Murine Clostridioides difficile Infection Model

Clostridioides difficile infection (CDI) is the leading cause of healthcare-associated infectious diarrhea and remains a major burden to healthcare systems worldwide. The development of novel therapeutics for CDI requires robust and reproducible preclinical models. However, the microbiota has emerged as a major source of variability in animal studies. Here, we found that genetically similar mice obtained from two commercial vendors, Jackson Laboratory (JAX) and Charles River Laboratories (CRL), exhibited marked differences in susceptibility to CDI, with JAX mice developing fulminant disease and CRL mice remaining resistant. Using full-length 16S rRNA gene sequencing, we show that JAX and CRL mice harboured distinct gut microbiota, and that cohousing susceptible JAX mice with resistant CRL mice was sufficient to shift the JAX microbiota toward the CRL community structure and confer resistance to CDI. Differential abundance analysis identified taxa distinguishing resistant and susceptible mice, providing candidates for future mechanistic investigation. These findings demonstrate that vendor-derived variation in the gut microbiota drives differential susceptibility to CDI in mice, and that this phenotype is transferable via cohousing, highlighting the importance of accounting for the microbiota when designing and interpreting animal models of infectious disease.

microbiology↗

bioRxiv2026

A configuration-resolved benchmark of differential abundance analysis methods for human gut 16S rRNA microbiome data

Tools for differential abundance testing of 16S rRNA data are conventionally treated as discrete methods, and benchmarks have accordingly sought to determine which tool performs best. However, each tool offers an array of configurations based on different normalisation, transformation, reference choice, and sensitivity filtering methods, and the specific impact of these configurations on performance has rarely been systematically investigated. We benchmarked five widely used tools (MaAsLin 2, MaAsLin 3, edgeR, ALDEx2, and ANCOM-BC2) across 18 configurations, using simulated communities and human gut profiles with implanted signals, at two taxonomic resolutions and across several design factors. Configuration accounted for as much performance variation as the choice of tool itself, with the ranking of two tools depending on which of their settings are compared. Individual parameters behaved as switches between opposite error regimes rather than as graded adjustments, and the settings carrying this weight are identifiable in advance. These behaviours were reproducible across data sources and resolutions. Our results define a configuration-aware framework for matching a tool and its settings to the cohort, study design, and feature resolution, establishing that a differential abundance result is interpretable only if the configuration used for the analysis is reported.

microbiology↗

bioRxiv2026

Membrane voltage and connexin expression work together to enhance tumor growth and metastasis in cancer

There is strong evidence of tumors manipulating their resting membrane potential (Vmem). While most fully-differentiated cells have a Vmem of roughly -70mV, tumor cells are generally depolarized, with Vmem {approx}-30mV, which more closely resembles the Vmem of stem cells. This is often believed to serve the purpose of accelerating the cell cycle and hence advantaging tumor proliferation. But when the tumor becomes invasive, its cells sometimes revert to a hyperpolarized Vmem with no obvious reason why. Separately, it is well accepted that solid tumors that are not yet invasive greatly underexpress connexins relative to healthy tissue; connexins, for our purpose, form gap junctions (GJs), small connecting tubes between nearby cells. Tumors that are invasive, by contrast, overexpress connexins. There is very little explanation for the paradox that connexins are first underexpressed and then overexpressed. However, it has long been known that Vmem electrically gates GJs; specifically, that homotypic GJs conduct best when the two cells they connect have a similar Vmem. Our in-silico model results explain this phenomenon, showing that when considered together, tumors' electrical and connexin-expression behaviors form a unified and effective strategy to control communication between the tumor and its healthy neighbor cells. This has implications for the emerging field of cancer bioelectrics, potentially leading to more precisely-targeted therapies.

cancer biology↗

bioRxiv2026

TheCellVision.org repository: expansion with high-content cell imaging projects on eukaryotic intracellular organization and DUB biology

High-content cell imaging approaches enable the systematic characterization of cellular function through the acquisition of multimodal information from large cohorts of live single cells. Yet, due to their scale and complexity, data acquired via such approaches are often challenging to meaningfully share across laboratories and effectively use for independent studies. Since its inception, the main purpose of TheCellVision.org repository has been to fill this gap, providing the research community with access to large-scale, multimodal single-cell datasets, in a structured, intuitive, and user-friendly way. Here, we report on the third major update of TheCellVision.org, which involves the expansion of the repository with the addition of data from two single-cell phenomics projects; the Intracellular Organization Dynamics project, which quantitatively maps changes in the morphology of 21 major subcellular structures in live yeast cells elicited by the systematic inhibition of essential genes, and the DUB Biology project, which describes changes in the concentration and localization of the budding yeast proteome in mutants of key deubiquitination enzymes (DUBs). With these additions, the repository now hosts six complementary high-content imaging projects which collectively explore the dynamics of intracellular organization and the proteome during changes in cell state and in response to environmental and genetic perturbations.

cell biology↗

bioRxiv2026

Environmental sensing capacity predicts bacterial ecological strategies and environmental preferences

The ability to sense environmental variation is a prerequisite for ecological success. Sensor domains enable bacteria to detect nutrients, neighboring organisms, and physicochemical conditions, but whether variation in these sensing systems reflects ecological specialization remains unresolved. Here, we analyzed sensor domains across 51,343 bacterial genomes and 255 soil metagenomes spanning a climatic gradient to determine whether sensory repertoires encode bacterial ecological strategies and environmental preferences. Sensory repertoires exhibited strong phylogenetic conservatism and revealed signatures of genome streamlining, indicating that environmental sensing reflects trade-offs associated with maintaining sensory complexity. Taxa occupying environmentally heterogeneous habitats, particularly free-living aerobic generalists, encoded the largest sensory repertoires, consistent with selection for expanded environmental information processing. To link sensory function with ecological adaptation, we mapped experimentally-characterized ligand-binding motifs (LBMs) across genomes and metagenomes. Distinct LBM profiles discriminated host-associated and free-living taxa, aerobic and anaerobic lineages, and generalists and non-generalists, revealing a tight coupling between sensory capacity and ecological strategy. Across soil communities, motifs associated with osmoprotection and oxygen sensing were consistently enriched under increasing aridity, linking sensory function to environmental filtering in natural ecosystems. These findings identify environmental sensing as an important organizational axis of bacterial trait-based ecology that integrates evolutionary history, ecological lifestyle, and adaptation to local conditions. Environmental sensing should be considered for predicting microbial niches and responses to environmental change.

ecology↗

bioRxiv2026

BioIMA: a one-click desktop tool for standardized extraction of phenotypic traits from biological images

Standardized extraction of quantitative phenotypes from images is increasingly important across plant biology, from ecological and evolutionary studies to genetics, breeding, and functional genomics. However, as large image datasets are increasingly used for trait analysis, many biologically relevant traits, including size, shape, color, and spatial patterning, are still measured manually or using fragmented semi-automated workflows. These limitations reduce throughput, reproducibility, and accessibility, especially for researchers without computational expertise. Here, we present BioIMA, an open-source desktop tool for rapid and standardized phenotyping from biological images. BioIMA integrates foundation model-based segmentation with automated trait computation, allowing users to extract quantitative measurements from images through an intuitive graphical interface and without model training. To validate its performance, we quantified a set of knot morphological traits in two Populus species, as these measurements are typically time-consuming to perform manually. Automatic measurements showed strong agreement with manual ImageJ-based measurements (R2 > 0.95), while reducing per-image processing time by approximately 75% (from ~15 s to ~4 s). BioIMA was further applied to diverse plant datasets, including Helianthus and Rhododendron images with varying morphologies and background conditions. Although developed for plant phenotyping, BioIMA may also be extended to other biological samples where region-based size, shape, or color traits are of interest. By combining accessibility and standardization in a lightweight local application, BioIMA provides a practical community resource for image-based phenotyping in ecological and evolutionary studies.

bioinformatics↗

bioRxiv2026

Abundance and trends of harbor seals (Phoca vitulina richardii) in Alaska, 1996-2023

Pacific harbor seals (Phoca vitulina richardii) were surveyed throughout their range along Alaska coasts over a 28-year period. Twelve management stocks, delineated on the basis of evidence for demographic independence, were monitored for abundance and trends. We employed a two-stage Bayesian hierarchical analysis that integrated aerial survey counts with satellite-linked bio-logger haul-out timelines to account for the proportion of seals in the water and not visible to survey observers and cameras. Overall, harbor seals were abundant (201,122 seals in 2023) but, during the span of our study the population (stock) trends varied. The first half of our study was characterised primarily by growth, with a peak abundance of approximately 225,000 seals in 2015. Since then trends have been variable, with some stocks (e.g., Bristol Bay) showing continued growth while others (e.g. Prince William Sound, South Kodiak) declined. The recent regional declines coincided with observed climate anomalies (e.g., marine heatwaves) and the rapid retreat of tidewater glaciers. Our results provide a basis for managing this species in Alaska, which is protected under the Marine Mammal Protection Act; a vital nutritional and cultural resource for Alaska Native communities; and an important sentinel of change in the Northeast Pacific marine ecosystem.

ecology↗

bioRxiv2026

Proteomic analysis of Stony Coral Tissue Loss Disease demonstrates coral-algal dysbiosis during disease progression

Stony Coral Tissue Loss Disease (SCTLD) has devastated Caribbean reefs, yet the host molecular response to infection is poorly understood. Previous gene expression studies of diseased corals identified shifts in the immune response, apoptosis, and coral-algal dysbiosis. Here, we characterized the proteomic response of Diploria labyrinthiformis to SCTLD by comparing protein abundance in healthy tissue from uninfected colonies and apparently healthy and neighboring diseased tissue from infected colonies. These results were compared with existing metagenomic data from the same samples that previously demonstrated significant shifts in the coral microbiome due to SCTLD. We identified 480 differentially abundant proteins when comparing diseased lesion and healthy tissues, but only 12 between apparently healthy and healthy tissues. Pathway-level analysis provides evidence of immune suppression in apparently healthy tissue, suggesting that host molecular responses precede visible disease progression. Diseased lesion tissues showed wound-healing responses combined with a decreased abundance of proteins involved in symbiosome maintenance and increased oxidative stress responses, consistent with host-algal dysbiosis. This result correlates with the previous metagenomic analysis of these samples which found that infected colonies exhibit distinct algal symbiont communities dominated by Symbiodinium necroappetens, whereas healthy colonies are dominated by Durusdinium trenchii and Breviolum spp. Comparison with existing transcriptomic studies revealed both shared and distinct molecular responses, underscoring the importance of integrating multi-omics approaches to understand coral diseases. Our results suggest that SCTLD in D. labyrinthiformis is associated with early immune suppression, coral-algal dysbiosis, oxidative stress, and subsequent wound-healing responses.

ecology↗

bioRxiv2026

Constructing microbiome co-occurrence networks with confidence: A conditional, nonparametric, inference-based approach

Constructing microbial association networks is a common strategy for exploring relationships among taxa in microbiome studies. Although marginal correlation methods are easy to implement and allow formal inference, they can produce spurious edges driven by indirect associations through other taxa. Conditional graphical-modeling methods aim to recover direct associations, but many rely on Gaussian or linear assumptions and often provide limited uncertainty quantification. We propose a conditional, nonparametric approach based on the scaled expected conditional covariance (SEcov). SEcov measures population-level conditional association by residualizing each taxon with respect to the remaining taxa and scaling the resulting expected conditional covariance. The resulting estimator can incorporate flexible machine-learning methods for conditional-mean estimation and admits asymptotic normal inference, enabling p-values and confidence intervals for taxon-pair associations. We demonstrate through simulation studies that our proposed approach improves network recovery relative to other methods, and we illustrate the new method via construction of a co-occurrence network for the vaginal microbiome during pregnancy. IMPORTANCEHigh-throughput sequencing has made it possible to characterize microbial communities at large scale, and network analysis is widely used to summarize relationships among taxa. However, networks based on marginal correlations may include indirect associations, whereas many conditional graphical models rely on assumptions that may be difficult to justify for sparse, zero-inflated, compositional microbiome data. SEcov offers a practical alternative by estimating conditional associations nonparametrically and attaching inferential uncertainty to individual edges. This allows investigators to construct microbiome networks using statistically interpretable evidence for taxon-pair associations, rather than relying solely on arbitrary correlation cutoffs or regularization tuning parameters.

bioinformatics↗

bioRxiv2026

PhageTAILor leverages machine learning for phage tail-like elements detection and classification in plant-associated bacteria

Phage tail-like elements (PTEs) -- tailocins, bacterial type VI secretion systems (T6SS), and extracellular contractile injection systems (eCIS) -- are contractile nanomachines that bacteria use to kill their neighbors and compete within their micro-ecosystems. PTEs help shape microbial community composition. Most PTE detection tools only detect a single PTE class. Moreover, most tailocin detection methods are largely restricted to Pseudomonas, leaving a key part of tailocin diversity uncharacterized. In this work, we present PhageTAILor (https://github.com/hjcho-bio/PhageTAILor), an integrative and fully automated pipeline that detects and classifies prophages and 3 PTE classes from bacterial genomes. PhageTAILor combines a 6-detector homology-based candidate search (geNomad, tail-gene, PHROGs-tail, SecReT6, eCIStem, and a divergence-tolerant tail-HMM detector) with a LightGBM classifier comprising 1 multiclass and 3 binary heads, trained on 6,501 bacterial genomes carrying 13,082 prophages and PTEs. A phylogeny-free feature matrix used in our model keeps predictions reproducible between model construction and user inference. PhageTAILor performs strongly at the genome level and generalizes beyond its Pseudomonas-rich training set. On a 76-strain cross-clade benchmark, PhageTAILor detected tailocins at F1 = 0.955. Furthermore, it identified 12 of 13 experimentally validated tailocins spanning five genera versus 2 of 13 for a Pseudomonas-restricted tool TattleTail. PhageTAILor also demonstrated sensitivity equivalent to viral detection tool geNomad while avoiding its higher false-positive rate. Applied to 7,925 plant- and soil-associated bacterial isolates, PhageTAILor showed that prophages in the phyllosphere and tailocins in plant-associated bacteria, whereas eCIS are enriched in soil. PhageTAILor is distributed as an open-source, modular pipeline with a command-line interface.

microbiology↗

bioRxiv2026

Why are fishers retaining manta and devil ray bycatch?

Increasing fishing pressure, including from small-scale fisheries, has caused declines in more than one-third of all elasmobranch species. Tackling conservation issues in small-scale fisheries requires interdisciplinary approaches due to the coastal community's interdependence on marine resources. To support inclusive policy change and fisher engagement, an understanding of the motivations driving fishers' operational choices (i.e., the retention of elasmobranch bycatch) is needed. We assess the motivational drivers behind bycatch retention of one of the slowest-growing and most vulnerable elasmobranch groups, manta and devil rays (collectively, mobulids), through a case study in India, their largest fishery in the world. We conducted a best-worst scaling survey in the fishery-intensive states of Tamil Nadu and Andhra Pradesh, which make significant contributions to mobulid landings on India's east coast. Our results suggest that fishers exhibit varied motivations for retaining mobulid bycatch across states. Financial motivation to sell mobulids for additional revenue was the most important motivator for bycatch retention in both states. In Tamil Nadu, the top three motivators were all financially driven, whereas in Andhra Pradesh, the top three motivators included both financial and non-financial attributes, such as nutritional importance and storage optimisation. As the first socio-economic study of mobulid fisheries in India, we show that motivations underlying bycatch retention decisions vary geographically and may be influenced by cultural differences between states and the socio-economic characteristics of decision makers. Based on identified fisher motivations, we provide context-specific recommendations to align conservation strategies with the values fishers derive from the mobulid fishery and encourage participation in conservation. These include subsidies for net repair to encourage mobulid release; promotion of a minimum price measure for sustainably sourced alternative species; quality improvement of target species; and increased awareness of national and international regulatory obligations (e.g., CITES, CMS, IOTC).

ecology↗

bioRxiv2026

Stepping-stone population structure and sidespread clonality of the mesophotic octocoral Swiftia exserta in the warm temperate northwest Atlantic

Isolated mesophotic banks form spatially discrete networks of patchy ecosystems along continental shelves. Their long-term persistence depends on connectivity among populations of the dominant coral species that structure these communities. Yet the scale of larval-mediated gene flow across these networks remains poorly characterized. Similarly, the extent to which clonal propagation shapes local population dynamics is unresolved, leaving the relative contributions of sexual and asexual reproduction to population maintenance an open question. Here, population genomics and high-resolution (1km) biophysical larval dispersal modeling are integrated to resolve the genetic connectivity and clonal dynamics of Swiftia exserta, a key habitat-forming octocoral, across 13 mesophotic banks spanning the U.S. Gulf and eastern coast within the Warm Temperate Northwest Atlantic (WTNWA) coastal and shelf biogeographic province. Genome-wide SNP markers derived from Restriction-site Associated Sequencing (RADseq) were genotyped across 288 individuals. About 40% of individuals belonged to clonal genets confined to single banks within meters of one another, indicating that asexual propagation sustains local density but plays no detectable role in inter-bank connectivity. Population genetic analyses pointed to isolation by distance as the primary structuring force, with the majority of molecular variance residing within rather than among populations. The west-most population, East Flower Garden Banks, was the most differentiated population in the WTNWA Northern Gulf ecoregion, reflecting its peripheral position within the bank network. The Edisto population from the WTNWA Carolinian ecoregion, was distinct from all others, implicating the Florida Peninsula as a phylogeographic barrier. Biophysical particle-tracking simulations independently recovered the same spatial structure, with modeled larval exchange consistent with the genomic signal across the bank network. These findings reveal that S. exserta persists across the northern WTNWA province through a dual reproductive strategy of clonality at the bank scale and episodic larval exchange at the network scale, with implications for the conservation and management of mesophotic octocoral metacommunities.

ecology↗

bioRxiv2026

Burning down the mouse: Effects of wildfire and post-fire reseeding on Sin Nombre virus prevalence in its reservoir host

Worldwide, physical habitats and biological communities are being reshaped by wildfire. Such changes have obvious potential to alter pathogen ecology, yet few studies, outside of those focused on ectoparasites, have tested the effects of wildfire on pathogen prevalence in wildlife. Even fewer have focused on the impacts of strategies for post-fire remediation on pathogen circulation. Here, we investigated the effect of wildfire and wildfire mitigation on the prevalence and viral load of Sin Nombre virus (SNV) infection in its reservoir host, the western deer mouse, using a study design of matched burned, unburned, and post-burn reseeded sites in northern New Mexico. In total, we screened 411 individual deer mice for SNV via RT-qPCR and analyzed the effect of wildfire and wildfire mitigation on relative mouse abundance, individual infection probability, site-level prevalence and viral load. Relative abundance was highest at reseeded sites, and model selection indicated that habitat structure, particularly the gradient from closed canopy to open-herbaceous habitat, was consistently associated with increased relative abundance. Similarly, SNV prevalence was significantly higher in reseeded sites than either burned or unburned sites but did not differ in burned versus unburned sites. Viral load did not differ between burn history types, and zero-inflated gamma hurdle models did not identify any strong predictors of viral load. Serendipitously, we were also able to investigate the impacts of an El Nino Southern Oscillation (ENSO) cycle on patterns of infection in a subsample of sites that were studied during and one year after an ENSO year and found that SNV prevalence increased significantly post-ENSO. Both reseeding and ENSO deliver resource pulses that can support increases in mouse density and thereby enhance SNV transmission. The impacts of post-fire management practices on SNV prevalence in its reservoir host that were revealed in this study should be considered when implementing such strategies and when utilizing treated areas.

ecology↗

bioRxiv2026

Design and Validation of New Primers for Specific and Sensitive Real-time PCR Detection and Quantification of Seven Botulinum Encoding Genes (Serotype A-G) of Clostridium botulinum

Botulinum neurotoxins (BoNTs) comprise a highly diverse group of seven serotypes (from A-G) and over 40 subtypes worldwide. Previous primer- and probe-based nucleic acid amplification tests (NAATs) for detection of BoNT encoding genes are challenged by high levels of nucleotide polymorphism both across and within subtypes. In this study, multiple BoNT gene sequences were aligned to identify highly conserved regions for the design of new primers that enable the detection of all seven serotypes under the same conditions. Specific primer sets were designed and validated using in silico, conventional and real-time PCR with constructed plasmids carrying the target fragments and spiked food matrices. The established procedure achieved highly specific and sensitive detection of BoNT serotypes A-G with sensitivity of 10 copies/reaction and a total turnaround time of approximately 1.5 hours. The procedure also eliminated the carryover PCR product by using uracil-N-glycosylase in combination with dUTP in the assay reaction mix. This study provides an alternative NAAT with higher coverage and compliments the traditional mouse bioassays in enhancing global botulism surveillance capabilities.

molecular biology↗

bioRxiv2026

Structural basis for catalytic and inhibitory divergence between archaeal and bacterial ammonia monooxygenases

Ammonia oxidation initiates nitrification and is closely linked to microbial N2O production. Ammonia monooxygenase (AMO) catalyzes the first and rate-limiting step of nitrification and is widespread across evolutionarily distinct ammonia-oxidizing archaea (AOA) and bacteria (AOB). The ocean is the largest biome for AOA and AOB, which have distinct ecological niches and markedly different sensitivities to nitrification inhibitors. However, the lack of archaeal AMO structures and inhibitor-bound AMO complexes has hindered mechanistic understanding of the architectural, catalytic, and inhibitory divergence between these two enzyme systems. Here, we report high-resolution cryo-electron microscopy (cryo-EM) structures of marine archaeal AMO captured in active and inactivated states within its native membrane environment, together with inhibitor-bound structures of estuarine bacterial AMO. Archaeal AMO forms an unexpected cup-shaped homotrimer composed of eight subunits per protomer and exhibits substantial architectural divergence from bacterial AMO. Integrated structural, biochemical, kinetic, and computational analyses reveal distinct periplasmic architectures, copper-center organization, and hydrophobic channels between archaeal and bacterial AMOs for ammonium acquisition, catalysis and inhibitor response. These findings provide a structural and mechanistic framework for understanding how archaeal and bacterial AMOs have diverged to distinct ammonia-oxidizing strategies and inhibitor susceptibilities across environmentally important ammonia oxidizers.

molecular biology↗

bioRxiv2026

A 28-color panel for classical and non-classical T lymphocytes in decidua and PBMC in rhesus macaques

This 28-color panel was developed to identify classical and non-classical T lymphocytes in decidual leukocytes and peripheral blood mononuclear cells (PBMC) of pregnant rhesus macaques. By profiling these T lymphocytes, we can investigate how maternal immunity balances tolerance to fetal antigens with protection against vertically transmitted pathogens. The selected markers define memory populations and characterize tissue residency, activation, proliferation, cytotoxicity, trafficking, and exhaustion status. This panel also delineates B lymphocytes and NK cells to confirm expected frequencies. The utility of this panel is aimed at evaluating cellular immune correlates of protection against congenital infections at the maternal-fetal interface and PBMC in rhesus macaques.

immunology↗

bioRxiv2026

Motor planning and execution establish distinct feedforward and feedback motor histories

Movements are systematically affected by the recent motor history. These history effects may be induced either by reused motor plans or from lingering tuning of the previous movements' execution. We dissociated planning and execution using four experimental manipulations across two complementary motor paradigms. We isolated planning by preventing execution with stop signals and mechanical blocks, and execution by moving participants' hand passively using a robot manipulandum. History effects emerged in feedforward movement aspects - reaction time and early movement kinematics - following isolated planning. In contrast, they were absent or markedly reduced for isolated execution. History effects emerged also in late movement aspect that involves sensory feedback during execution - movement accuracy and precision - but only when movements were both planned and executed. Feedforward effects generalized across hands, whereas feedback effects were effector specific. Thus, prior motor planning and execution make distinct and complementary contributions in shaping future motor behavior.

neuroscience↗

bioRxiv2026

Feature-based valuation and its impairment in people with compulsive and addictive symptoms

Effective decision-making requires evaluating options based on relevant features while reducing attention to those that are not. However, how attention prioritizes one source of information over another during value-based decisions remains unknown. Across 7 experiments, we show that irrelevant features both constructively and destructively interfered with how values are assigned to choice options. When relevant and irrelevant features agreed, choice accuracy and speed were facilitated; when they conflicted, accuracy decreased and choices slowed in proportion to the value of the irrelevant feature. We modeled this interference as a weighted sum of relevant and irrelevant feature values. This model explained individual differences in choice behavior and, critically, tracked psychiatric symptom severity related to substance abuse and obsessive-compulsive disorder. This suggests that these symptoms may, in part, reflect an impaired ability to weigh relevant against irrelevant information when assigning value to choice options - a process we term feature-based valuation.

neuroscience↗