Biology subjects

Patil, K. R.

Publications and source records attributed to Patil, K. R..

At least 19 recordsLinked to original sources

bioRxiv2026

Network-scale disruption of RNA-protein interactions by a bioaccumulating small-molecule drug

Many small-molecule drugs accumulate in both host and gut microbial cells. Yet, the molecular consequences of intracellular drug accumulation are largely unknown. Here we show that the antidepressant duloxetine broadly disrupts RNA-protein interactions revealing a previously unrecognized mode of drug effect. Across phylogenetically diverse bacteria and human intestinal cells, duloxetine consistently reduced RNA-binding capacity, with approximately 80% of RNA-binding proteins responding to duloxetine in bacteria (E. coli IAI1) and human (Caco-2) cells. As a mechanistic example, we show how duloxetine disrupts interactions between the pyrimidine biosynthesis enzyme PyrB and transcripts encoding metabolically linked functions. Biochemical and structural analyses show that duloxetine competes with aspartate, the natural substrate of PyrB, weakening the enzymes binding with 3' UTR-localized stem-loop structures in its RNA partners. Overall, our results uncover the off-target disruption of RNA-protein interactions due to drug accumulation and have implications for understanding molecular basis of variation in drug efficacy and toxicity.

systems biology↗

bioRxiv2026

Laboratory evolution enhances resilience of a symbiont yeast and its honeybee host against agrochemical exposure

Yeasts are key microbial members of several ecosystems. Yet, the impact of widespread chemical pollutants on yeasts is only sparsely studied. Here we report the effect of >1000 chemical pollutants on fourteen diverse yeast species spanning the Saccharomycotina subphylum. Starmerella bombicola, a symbiont of various bee species, was the most sensitive and inhibited by several fungicides as well as by non-fungicides. To identify the molecular basis of this ultra-sensitivity, we selected resistant lineages against nine chemicals using adaptive laboratory evolution. Whole-genome-sequencing uncovered convergent evolution on YBP1, a key regulator of oxidative stress. Proteomic analysis confirmed the protective role of oxidative stress response pathways, including proteins encoded by horizontally transferred bacterial genes. We find that the evolved S. bombicola stably colonized the bee gut and ameliorated the negative effect of paclobutrazol, a plant hormone regulator, on gut microbes, sucrose responsiveness, and learning. Our findings demonstrate how laboratory evolution can be used to mitigate the negative impact of chemical pollutants on pollinators.

microbiology↗

bioRxiv2026

CarveMe-GutMicrobes: Automated Metabolic Model Reconstruction for Gut Microbial Species and Communities

Genome-scale metabolic models (GSMMs) are important aids towards system-level understanding of the metabolic physiology of the gut microbes and for rational microbiome engineering. While large-scale repositories of GSMMs for gut-associated bacteria are available, strain-level variability and the continuous discovery of novel taxa through metagenomics and culturomics underscore the need for scalable, ab initio reconstruction tools. Here, we present CarveMe-GutMicrobes, a client-side framework for rapid reconstruction of metabolic models directly from (meta)genomic input. Building upon the original CarveMe framework, CarveMe-GutMicrobes incorporates an expanded, gut-microbe-centric biochemical database that includes reactions, metabolites, and gene-protein-reaction (GPR) associations curated specifically for Bacteria and Archaea inhabiting the human gut. The tool supports taxonomic restriction of the reference database to improve context-specific accuracy. CarveMe-GutMicrobes models demonstrated high predictive performance performance against gene essentiality and metabolite secretion datasets. By integrating curated resources, extending reaction coverage, and offering new empirical datasets, CarveMe-GutMicrobes provides a scalable platform for high-resolution metabolic reconstruction towards broader adoption of GSMMs in gut microbiome research.

bioinformatics↗

bioRxiv2026

How to Catch a Blank Mind? Brain Similarities and Differences between Self- and Probe-Caught Mind Blanking

Mind Blanking (MB) is a mental state characterized by the experience of a seemingly empty mind. This apparent emptiness challenges the theoretical view of a continuous and content-full stream of thought, leading to the question of how it is possible to capture MB events in the first place. MB research has relied largely on probe-caught experience-sampling, during which participants are interrupted at random times to report their mental state. This approach risks missing some MB events as they may occur between probes. Self-caught paradigms, on the other hand, allow participants to report MB upon spontaneously realizing it, relying on meta-awareness. To date, it is not clear whether these two methods capture the same phenomenon neuronally. Here, we investigated whether probe-caught MB (pMB) and self-caught MB (sMB) converge on their behavioral properties and brain correlates. Twenty-two participants underwent 3T fMRI scanning while performing both a pMB and a sMB experience-sampling task. We compared the behavioral properties, BOLD activations and time-varying functional connectivity (FC) across the two approaches. We found that reporting frequencies of pMB and sMB were significantly correlated across individuals, and both MB reports were uniformly distributed over time, pointing towards a behavioral convergence across approaches. However, we observed a divergence in BOLD activations, as sMB recruited significantly greater activation in the dorsal anterior cingulate cortex (dACC) compared to pMB, likely reflecting the meta-awareness and metacognitive monitoring required for self-detecting a MB. Lastly, time-varying FC analysis revealed a convergence, with both pMB and sMB FC resembling a hyperconnectivity pattern compared to other content-full mental states, pointing towards low arousal FC. Together, our results show that sMB and pMB converge on overlapping neurobehavioral correlates. This positions the self-caught method as a complementary tool for studying MB without external interruption, while highlighting the role of meta-awareness in self-report detection.

neuroscience↗

bioRxiv2026

Oxygen gradients reshape cross-feeding through emergent spatial organization of gut commensal bacteria

Microbial interactions unfold within environments structured by physical transport and chemical gradients. Yet most mechanistic studies rely on well-mixed systems that mask the reciprocal influences of environmental heterogeneity on metabolism and ecology. Here, we investigate how the physical environment modulates the interaction between the gut commensal Bacteroides thetaiotaomicron and Escherichia coli. In anoxic liquid culture, cell-resolved isotope imaging and genetic perturbations reveal exploitative cross-feeding, where E. coli consumes diffusible sugars released by B. thetaiotaomicron during starch degradation. When exposed to intestinal-like oxygen gradients in microfluidics, the interaction is restructured by spatial organization. The species self-organize into complementary niches: E. coli locally depletes sugars and oxygen, thereby expanding the anoxic niche required by B. thetaiotaomicron. A reactive transport model confirms that this organization arises from coupled feedback between physical transport and metabolic reaction rates. Together, our results reveal how physical structure and chemical gradients convert an exploitative cross-feeding interaction into a dynamic niche-construction process that generates emergent spatial organization and stabilizes coexistence.

microbiology↗

bioRxiv2026

Linking human brain functional connectivity to underlying neurotransmission

The human brain is organized into interacting functional systems. Their underlying neurobiological mechanisms remain difficult to study in vivo. Here, we adopt a topological framework to quantify the association between neurobiology and brain functional connectivity derived from both resting-state fMRI and MEG. Across six healthy adult cohorts (n = 19-112), regional variation in fMRI connectivity robustly aligns with the distribution of neurotransmitter receptors and transporters. These patterns are present in every single subject, replicate across all cohorts, and are mirrored in MEG. Most prominently, noradrenergic modulation of connectivity in a sensorimotor-insular network is consistently detected across individuals and linked to autonomic arousal. In pharmacological and clinical samples, associations are sensitive to neurotransmitter system manipulation and are altered in early psychosis, aligning with clinical symptomatology. These findings provide biological insight into typical and atypical functional organization of the human brain using a framework linking underlying neurobiology to the functional connectome (NEOFC).

neuroscience↗

bioRxiv2026

YBX3 overexpression in mesothelioma drives aberrant cell proliferation

Malignant pleural mesothelioma (MpM) is a lethal tumour closely linked to asbestos exposure and is a cancer of unmet clinical need with no known oncogenic drivers. Recent advancements in technologies to identify RNA-binding proteins (RBPs) has uncovered an emerging role for RBP-RNA interactions in cancer progression and we therefore assessed changes in the RBPome of patient-derived MpM cell lines. We identify over 350 RBPs showing altered RNA binding, with functions consistent with key cancer hallmarks, and discovered YBX3 as a potential oncoprotein driving cell proliferation in MpM. Mechanistically we show the impact of YBX3 on cell growth is achieved through its control of the expression of the amino acid transporter SLC7A5/LAT1, with increased amino acid uptake increasing protein synthesis rates. Notably, we show the inhibition of cell growth by YBX3 deletion is recapitulated by the clinically-relevant SLC7A5/LAT1 inhibitor JPH203. Finally, we demonstrate that JPH203 sensitizes MpM cells to radiotherapy, which could provide a promising therapeutic strategy for MpM. TeaserHigher levels of YBX3 expression in mesothelioma increases cell proliferation and protein synthesis rates by upregulation of amino acid uptake.

molecular biology↗

bioRxiv2025

Unveiling the Multifaceted Networks of the Left DLPFC for Precision TMS Targeting

The left dorsolateral prefrontal cortex (lDLPFC) is the standard transcranial magnetic stimulation (TMS) target for treatment-resistant depression (TRD), yet non-response rates remain high. TMS efficacy has been linked to the stimulation sites functional connectivity, particularly its anti-correlation with the subgenual cingulate cortex (SGC). While this pragmatic strategy has demonstrated clinical utility, it offers limited insight into how the lDLPFCs network interactions contribute to site-dependent variability in treatment response. Here, we used connectivity-based parcellation within a region of interest encompassing common TMS targets in the left prefrontal cortex (TMS-PFC) to delineate functionally distinct subregions and characterize their large-scale network connectivity and behavioral associations. Our results revealed a hierarchical organization: a coarse two-pole antagonism between anterior-central and superior-posterior subregions and a finer nine-cluster architecture exposing the heterogeneity along anterior-posterior and ventral-dorsal axes within TMS-PFC. Anterior-central areas were strongly anti-correlated with SGC and default-mode network, positively connected with salience, dorsal attention, and control networks, and associated with cognitive control. In contrast, superior-posterior subregions displayed the inverse pattern, while ventral clusters engaged somatomotor and visual networks, and language-related processes. Central and superior-anterior clusters showed differentiated profiles, including associations with inhibition, social cognition, and perceptual functions. To aid clinical translation, we derived a likelihood map integrating granularities, highlighting the anterior-central subregion as the strongest TMS candidate given its connectivity and behavioral relevance in depression, while indicating that neighboring subregions have distinct functions. These findings underscore the hierarchical and heterogeneous organization of TMS-PFC and provide a network-informed reference for developing individualized, symptom-specific TMS interventions. HighlightsO_LITMS targets within the left PFC encompass nine functionally distinct subregions C_LIO_LISubregions differ in SGC, DMN, salience, attention, and control network connectivity C_LIO_LIAnterior-central and superior-posterior subregions show antagonistic profiles C_LIO_LIA likelihood map identifies the anterior-central subregion as optimal TMS target C_LIO_LIFindings provide a network-informed reference for symptom-specific TMS targeting C_LI

neuroscience↗

bioRxiv2025

A toolkit for transposon libraries and functional genomics in intestinal Bacteroidales

Members of the order Bacteroidales include some of the most prevalent and abundant bacterial species in the healthy human gut microbiota. Yet, most of the functions encoded in their genomes remain poorly characterized, limiting our understanding of the different roles they play in the human gut microbiome. Towards addressing this gap, we developed tools and methods for genome-wide transposon mutagenesis in Bacteroidales, including broad-range transposon vectors with several antibiotic selection markers, a dual conjugation-cloning donor strain, and protocols for convenient library generation in liquid media. We then created saturated, barcoded, insertion mutant libraries in the type strains of three key representatives of the main genera within Bacteroidales: Bacteroides uniformis (ATCC 8492), Phocaeicola vulgatus (ATCC 8482) and Parabacteroides merdae (ATCC 43184). Based on the dense transposon insertion profiles and a workflow for comparing essentialomes across species, we identified 275 core essential genes shared across the three species, and 163 species-specific essential genes, some of which could be explained by functional redundancy and alternative metabolic pathways. We further identified essential non-protein coding elements and essential protein domains with known and unknown functions. Finally, using insertion directionality bias, we could map potential toxic modalities in the three genomes, including toxin-antitoxin pairs, mobile elements encoding toxic products and enzymes leading to toxic metabolic intermediates. Overall, the tools, workflows and genome-wide resources reported here expand the experimental repertoire for characterizing genes in key bacteria of the human gut microbiome, and pave the way for the establishment of similar genetic toolkits for other gut bacteria.

microbiology↗

bioRxiv2025

Bacteroides-driven metabolic remodelling suppresses Clostridioides difficile toxin expression in mixed biofilm communities

Clostridioides difficile is a major cause of hospital-associated diarrhoea worldwide. The intricate interactions between C. difficile and the resident gut microbiota play a crucial role in determining the outcome of C. difficile infection (CDI), although the molecular mechanisms underlying many C. difficile-commensal interactions are not understood. Here we show that selected Bacteroides species can inhibit C. difficile growth within mixed biofilms. A transcriptomic analysis of C. difficile-Bacteroides biofilms showed significant metabolic shifts, with distinct changes in carbohydrate and amino acid metabolism and, interestingly, a downregulation of C. difficile toxin gene expression. A significant reduction in C. difficile toxin production was evident in C. difficile-Bacteroides cocultures, irrespective of the extent of C. difficile growth inhibition. Notably, Stickland fermentation of proline, which is known to repress toxin synthesis, was upregulated in C. difficile, while proline synthesis was induced in the cocultured species B. vulgatus and B. dorei. Furthermore, upregulation of proline reductase pathways and consequent toxin repression were evident within a synthetic 9-species gut commensal biofilm community containing multiple Bacteroides spp. Thus, leveraging multiomics approaches, we demonstrate a potential cross-feeding mechanism where proline produced by B. dorei and B. vulgatus is utilised by C. difficile through Stickland fermentation to drive toxin repression. Our study reveals a new mechanism of microbiota-mediated control of a key virulence factor involved in C. difficile pathogenesis while enabling pathogen co-existence within a polymicrobial commensal community. ImportanceC. difficile infection, characterised by severe diarrhoea and colitis, has a significant impact on healthcare settings globally due to the high rates of recurrence. CDI is closely associated with the gut microbiota status and the use of antibiotics, yet the mechanistic basis of interactions between the causative bacterium C. difficile and individual gut commensal species remains poorly defined. Here, we demonstrate inhibitory effects of Bacteroides species on C. difficile through nutrient competition and a cross-feeding mechanism between these abundant gut commensals and this pathogen which blocks expression of key C. difficile virulence factors. Our findings offer insights into the effective design of microbiota consortia to prevent and treat CDI.

microbiology↗

bioRxiv2025

Predicting Brain Volumes from Anthropometric and Demographic Features: Insights from UK Biobank Neuroimaging Data

Brain size measures are well-studied and often treated as a confound in volumetric neuroimaging analyses. Yet their relationship with body anthropometric measures and demographics remains underexplored. In this study, we examined those relationships alongside age- and sex-related differences in global brain volumes. Using brain magnetic resonance imaging (MRI) of healthy participants in the UK Biobank, we derived global measures of brain morphometry, including total intracranial volume (TIV), total brain volume (TBV), gray matter volume (GMV), white matter volume (WMV), and cerebrospinal fluid (CSF). We extracted these measures using the Computational Anatomy Toolbox (CAT) and FreeSurfer. Our analyses were structured in three approaches: across-sex analysis, sex-specific analysis, and impact of age analysis. Employing machine learning (ML), we found that TIV was strongly predicted by sex (across-sex r = 0.68), reflecting sexual dimorphism. On the other hand, TBV, GMV, WMV, and CSF were more sensitive to age, with higher prediction accuracy when age was included as a feature, highlighting age-related changes in the brain structure, such as fluid expansion. Sex-specific models showed reduced TIV prediction (r {approx} 0.25) but improved TBV accuracy (r {approx} 0.44), underscoring sex-specific body-brain relationships. Anthropometrics enhanced prediction but only subsidiary to age and sex. These findings advance our understanding of brain-body scaling relationships and underscore the necessity of accounting for age and sex in neuroimaging studies of brain morphology.

neuroscience↗

bioRxiv2025

Interspecies interactions drive bacterial proteome reorganisation and emergent metabolism

Species in microbial communities must respond to the presence of others to stave off resource competition or to capitalise on new resources that may become available due to additional metabolic activities. Such metabolic interactions manifest in growth effects such as competitive exclusion or cooperative growth boost. However, intra-cellular molecular changes that underpin these responses are very sparsely studied, preventing mechanistic insights into community function and dynamics. Here, we analyse meta-proteomics and metabolomic responses in 104 pairwise co-cultures of 15 diverse gut bacteria in a nutrient-rich medium. These co-cultures span a diversity of ecological interactions with competition, amensalism and exploitation being prominent, and with around one in five positive interactions. The species in co-cultures feature substantial molecular responses, with typically more than 60% of the proteome changing in response to at least one partner. Even closely related species and ortholog proteins show different expression profiles in response to the same partner indicating functional diversification at both protein and species level. We show that the magnitude of these responses is determined by genome size, species abundance, and pH. Small-molecule transport and carbon metabolism are among the most responsive processes indicating pervasive metabolic interactions. Using metabolomics, we identify likely cross-fed metabolites, emergent polyamine metabolism, and niche partitioning in amino acid utilisation. Overall, our study shows how bacteria respond to the presence of other species through extensive remodelling of their proteome and metabolome.

microbiology↗

bioRxiv2025

Impact of low-calorie sweeteners on gut bacteria is modulated by common xenobiotics

The gut microbiota is implicated in adverse effects associated with low-calorie sweeteners. Yet, the direct impact of sweeteners on gut bacteria remains largely uncharacterized. Here we report interactions between 25 phylogenetically diverse gut bacterial strains and 39 commercially used sweeteners. We tested these sweeteners individually and in combination with four commonly co-consumed compounds, viz., advantame, caffeine, vanillin, and duloxetine. Three quarters of the tested sweeteners individually impacted growth of at least one bacterial strain. Further, over 100 interactions were found between sweeteners and the four co-consumed compounds. Isosteviol, a commonly used sweetener, and duloxetine, an antidepressant, synergistically inhibited Roseburia intestinalis, a bacterium previously linked to glucose homeostasis, and Parabacteroides merdae, a prevalent commensal linked to healthy microbiota. Proteomic, metabolomic, and genetic analyses indicate altered small molecule transport underpinning this sweetener-drug synergy. The isosteviol-duloxetine combination also modulated metabolism of a synthetic gut bacterial community leading to increased toxicity to HeLa cells and altered secretion of inflammation modulatory cytokines IL-6 and IL-8 by Caco-2 cells. Together, our data bring forward the prevalence of interactions between low-calorie sweeteners and common xenobiotics.

microbiology↗

bioRxiv2025

Obligate cross-feeding of metabolites is common in soil microbial communities

Many microorganisms are refractory to laboratory cultivation. One possible explanation, known as the great plate count anomaly, is metabolic dependencies among community members. However, systematic studies of these interactions in communities like soil are missing, hindering advances in understanding these ecologically important ecosystems. Here, we address this issue by systematically analysing 6,931 bacterial isolates of 27 soil microbial communities. We find that the growth of up to 50% of all community members depended essentially on supplementation with amino acids, vitamins, or nucleotides. In 73% of cases, supplementation with multiple amino acids was necessary. Genomic analysis of 62 strains revealed that accumulation of insertion sequences and specific gene loss was associated with the observed auxotrophies. Finally, genome-scale metabolic models, computational analyses, and cocultivation experiments demonstrated that other co-occurring genotypes complemented the metabolic needs of auxotrophs, thus facilitating their growth. Our results demonstrate that soil bacteria exist within integrated metabolic networks, which hampers their cultivation.

microbiology↗

bioRxiv2024

Voxel-wise or Region-wise Nuisance Regression for Functional Connectivity Analyses: Does it matter?

Removal of nuisance signals (such as motion) from the BOLD time series is an important aspect of preprocessing to obtain meaningful resting-state functional connectivity (rs-FC). The nuisance signals are commonly removed using denoising procedures at the finest resolution, i.e. the voxel time series. Typically the voxel-wise time series are then aggregated into predefined regions or parcels to obtain a rs-FC matrix as the correlation between pairs of regional time series. Computational efficiency can be improved by denoising the aggregated regional time series instead of the voxel time series. However, a comprehensive comparison of the effects of denoising on these two resolutions is missing. In this study, we systematically investigate the effects of denoising at different time series resolutions (voxel- and region-level) in 370 unrelated subjects from the HCP-YA dataset. Alongside the time series resolution, we considered additional factors such as aggregation method (Mean and first eigenvariate [EV]) and parcellation granularity (100, 400, and 1,000 regions). To assess the effect of those choices on the utility of the resulting whole-brain rs-FC, we evaluated the individual specificity (fingerprinting) and the capacity to predict age and three cognitive scores. Our findings show generally equal or better performance for region-level denoising with notable differences depending on the aggregation method. Using mean aggregation yielded equal individual specificity and prediction performance for voxel- and region-level denoising. When EV was employed for aggregation, the individual specificity of voxel-level denoising was reduced compared to region-level denoising. Increasing parcellation granularity generally improved individual specificity. For the prediction of age and cognitive test scores, only fluid intelligence indicated worse performance for voxel-level denoising in the case of aggregating with the EV. Based on these results, we recommend the adoption of region-level denoising for brain-behavior investigations when using mean aggregation. This approach offers equal individual specificity and prediction capacity with reduced computational resources for the analysis of rs-FC patterns.

neuroscience↗

bioRxiv2024

Procrustes Alignment in Individual-level Analyses of Functional Gradients

Functional connectivity (FC) gradients provide valuable insights into individual differences in brain organization, yet aligning these gradients across individuals poses challenges. Procrustes alignment is often employed to standardize gradients across multiple subjects, but the choice of the number of gradients used in alignment introduces complexities that may impact individual-level analyses. In this study, we systematically investigate the impact of varying gradient counts in Procrustes alignment on the principal FC gradient, using data from four resting state fMRI datasets, including the Human Connectome Project (HCP-YA), Amsterdam Open MRI Collection (AOMIC) PIOP1 and PIOP2, and Cambridge Centre for Ageing and Neuroscience (Cam-CAN). We find that increasing the number of gradients used in alignment enhances identification accuracy but can reduce differential identifiability, as additional gradients risk introducing nuisance signals such as motion back into the principal gradient. To further probe these effects, machine learning to predict fluid intelligence and age, and a motion prediction analysis, revealing that higher alignment gradient counts may leak information from lower gradients into the principal gradient for individual-level analyses. These findings highlight the trade-off between alignment precision and the potential reintroduction of noise. Key PointsO_LIGradient count used in Procrustes alignment impacts identification accuracy and differential identifiability obtained using the principal gradient C_LIO_LIThe magnitude of the Procrustes transformation correlates with motion measures, and this correlation increases with higher gradient count used in alignment. C_LIO_LIGradient count used in Procrustes alignment impacts prediction of fluid intelligence and age C_LI

neuroscience↗

bioRxiv2024

Extensive PFAS accumulation by human gut bacteria

Per- and polyfluoroalkyl Substances (PFAS) - the so-called forever chemicals - are a major cause of environmental and health concern due to their toxicity and long-term persistence1,2. Yet, no efficient mechanisms for their removal have been identified. Here we report bioaccumulation of PFAS by several gut bacterial species over a wide range of concentrations from nanomolar up to 500 M. For bioaccumulating Bacteroides uniformis, a highly prevalent species, we estimate intracellular PFAS concentration in the mM range - above that of most native metabolites. Despite this high bioaccumulation, B. uniformis cells could grow appreciably up to 250 M perfluorononanoic acid (PFNA) exposure. Escherichia coli, which accumulated PFAS to a much lesser extent, substantially increased PFAS bioaccumulation when lacking TolC efflux pump indicating trans-membrane transport in PFAS bioaccumulation. Electron microscopy and cryogenic Focused Ion Beam-Secondary Ion Mass-spectrometry revealed distinct morphological changes and intracellular localisation of PFNA aggregates. Bioaccumulation of PFAS and transmembrane transport is also evident in proteomics, metabolomics, thermal proteome profiling, and mutations following adaptive laboratory evolution. In an in vivo context, mice colonized with human gut bacteria showed, compared to germ-free controls or those colonized with low-bioaccumulating bacteria, higher PFNA levels in excreted feces. As the gut microbiota is a critical interface between exposure and human body, our results have implications for understanding and utilizing microbial contribution to PFAS clearance.

microbiology↗

bioRxiv2024

Off-purpose activity of industrial and agricultural chemicals against human gut bacteria

Contamination by industrial and agricultural chemicals like pesticides are a cause of great concern due to the risk to human and environmental health. While these chemicals are often considered to have restricted activity and are labelled as such, there are concerns over a broader toxicity range. Here we report the impact of 1076 pollutants spanning diverse chemistries and indicated applications on 22 prevalent commensal gut bacteria. Our systematic investigation uncovered 588 interactions involving 168 chemicals, the majority of which were not previously reported to have antibacterial properties. Fungicides and industrial chemicals showed the largest impact with circa 30% exhibiting anti-commensal properties. We find that the sensitivity to chemical pollutants across species surprisingly correlates with that to human-targeted drugs, suggesting common susceptibility mechanisms. Using a genome-wide chemical-genetic screen, we identified membrane transport and fatty acid metabolism as major modulators of the off-target toxicity of chemicals. Mutants exhibiting chemical resistance include those defective in producing human-health-relevant metabolites like branched short-chain fatty acids, indicating that chronic exposure could lead to selection against production of beneficial metabolites. Toxicokinetic modelling suggested gut bacteria could be used as more sensitive in vitro toxicity indicators for chemicals of concern than animal models. Together, our data uncovers the off-target activity of industrial and agricultural chemicals with widespread exposure against human gut bacteria. Impact on the structure and function of the microbiota should therefore be considered in assessing chemical safety.

microbiology↗