Biology subjects

Chatterjee, S.

Publications and source records attributed to Chatterjee, S..

At least 19 recordsLinked to original sources

bioRxiv2026

Sequence architecture of RNA reveals key molecular signatures driving RNA phase separation

Biomolecular condensates are dynamic membraneless assemblies that organize various cellular processes through liquid-liquid phase separation (LLPS). RNA is an active regulator of biomolecular condensates and influence their formation through sequence-encoded features. Despite its established role in condensate formation, no computational framework exists to identify underlying signatures to predict LLPS-associated RNAs. We develop an interpretable hybrid framework to distinguish reviewed, experimentally supported LLPS-associated RNAs from background RNAs. We uncover biologically meaningful sequence properties associated with condensate participation. Each RNA is represented by 167 handcrafted descriptors capturing composition, k-mer usage, sequence complexity, repeat organization and dinucleotide autocorrelation together with 640-dimensional contextual embeddings from RNA-FM. These representations are integrated through cross-validated stacking with neural-network meta-learner. The framework achieves an AUC-ROC of 0.935, AUC-PR of 0.944 and MCC of 0.782. Feature statistics, ablation analysis and SHAP interpretation reveal a distributed sequence architecture dominated by altered local k-mer usage with additional contributions from low-complexity burden, repeat-associated organization and long-range dinucleotide pattern. Biological case studies including MALAT1 and TMPO-AS1 further connect these patterns with experimentally characterized modes of multivalent RNA-protein assembly. Together, the results show how interpretable machine learning can move beyond prediction to identify sequence features that generate mechanistic hypotheses for RNA-mediated condensation.

bioinformatics↗

bioRxiv2026

Recurrent leukaemia stem cell states define the antigenic landscape of paediatric Acute Myeloid Leukaemia

Paediatric acute myeloid leukaemia (pAML) remains a leading cause of childhood cancer mortality, with disease heterogeneity representing a major obstacle to effective immunotherapy. To enable rational immunotherapy design accounting for such heterogeneity, we combined single-cell transcriptomics and surface proteomics (CITE-seq). Using an integrated framework for malignant cell identification and unbiased gene program identification, we resolved three conserved leukaemia stem cell (LSC) subtypes, primitive (P-LSC), monocytic (M-LSC), and erythroid-like (E-LSC), that frequently coexist within individual patients in varying proportions and represent distinct stem-cell states with characteristic immunophenotypes and transcriptional programmes. Quantitative surface antigen profiling revealed that no single target achieved full LSC coverage. CLEC12A, an antigen currently being evaluated clinically, was expressed across P-LSC and M-LSC but was largely absent from E-LSC. In contrast, CD84 provided complementary coverage in the P and M groups and served as the primary target in the E-LSC population. The combination of CLEC12A and CD84 provided broad coverage across all three LSC subtypes, while sparing healthy haematopoietic stem cells. Validation across independent single-cell and bulk cohorts confirmed the robustness of this combination. These findings establish a paediatric-specific framework for antigen prioritisation in AML, identify CLEC12A/CD84 as a robust dual-targeting strategy across heterogeneous LSC states, and provide a blueprint for the rational design of next-generation CAR T-cell combinations.

cancer biology↗

bioRxiv2026

Slow Ionic Dynamics Reshape Bistability in a Biophysical Mean-Field Model of Brain Activity

Brain states such as sleep, seizures, and resting wakefulness are often described in terms of transitions between distinct population states. Biophysically inspired mean-field models that couple neuronal firing statistics to slow ionic homeostasis provide a mechanistic bridge between detailed single-neuron physiology and macroscopic brain activity. Here we examine this issue in a biophysical mean-field model of cortical populations driven by potassium exchange and compare its dynamical repertoire with a matched spiking network across six physiological and pathological regimes. The fast subsystem contains a substantial region in which low- and high-activity fixed points coexist, but this conditional bistability is not inherited by the physiological resting branch of the complete slow-fast system. A generic fast-slow calculation identifies how feedback through a dynamical ionic variable changes the stability conditions of the fast subsystem, and an exact equilibrium reduction of the KIonEx-MF equations yields a single equilibrium on the physiological resting branch over the range examined. This resting state is excitable: perturbations generate intermittent synchronized events in both the mean-field and spiking-network descriptions. The results show how slow ionic dynamics can reshape conclusions drawn from a frozen fast subsystem and provide noise-driven excitability as an alternative route to spontaneous population transitions.

neuroscience↗

bioRxiv2026

SHERLOCK: Structured representation learning and causal inference of downstream perturbation effects

Understanding the effects of genetic, molecular, and experimental perturbations is essential for decoding cellular mechanisms and guiding biomedical interventions. Existing computational approaches are typically designed for individual tasks, such as predicting perturbation responses, characterizing downstream transcriptional effects, or modeling perturbation combinations, and therefore do not provide a unified framework for learning interpretable perturbation representations while enabling causal analysis of downstream effects and characterization of condition-dependent responses. We present SHERLOCK, an interpretable deep generative framework for single-cell perturbation analysis that represents perturbation effects as structured interventions on a latent baseline cellular state. SHERLOCK learns correlated and sparse perturbation representations that organize genetic and pharmacological perturbations according to shared transcriptional responses. % By formulating perturbations as interventions within a structural causal model, it enables counterfactual estimation of their downstream transcriptional effects under explicit identifiability assumptions. The same framework quantifies how perturbation responses vary across conditions and compositionally models combinatorial perturbations, enabling prediction of held-out combinations and classification of genetic interactions. Across genome-scale CRISPR, chemical, and spatial perturbation datasets, SHERLOCK recovers perturbation relationships concordant with known biological pathways and pharmacological properties, identifies condition-dependent responses, and predicts combinatorial perturbation effects. Together, SHERLOCK provides a unified framework for interpretable and causal analysis of perturbation effects across diverse single-cell perturbation experiments.

genomics↗

bioRxiv2026

Discovery of a Small-Molecule mTORC1 Pathway Activator that Enhances Adoptive T-Cell Therapy via Immuno-metabolic Reprogramming of CD8+ T Cells

Adoptive cell therapy (ACT) has transformed cancer immunotherapy; however, its clinical efficacy remains limited by progressive T cell dysfunction and inadequate metabolic fitness acquired during ex vivo expansion and within the tumor microenvironment. Here, we report the discovery of AS-3, a first-in-class small-molecule activator that enhances the therapeutic competence of CD8 T cells through RAPTOR-dependent mTORC1 activation. Identified by phenotypic screening of an in-house library of pharmacologically relevant scaffolds and subsequent medicinal chemistry optimization, AS-3 markedly increased effector cytokine production while preserving T cell viability. Mechanistically, AS-3 enhanced phosphorylation of mTORC1 downstream effectors, promoted glycolytic and mitochondrial metabolism, and sustained pathway activity under rapamycin-mediated inhibition. Transcriptomic profiling of activated human CD8 T cells revealed coordinated enrichment of mTORC1 signalling, oxidative phosphorylation, glycolysis, proliferative programs, and cytotoxic effector gene networks, consistent with comprehensive immunometabolic reprogramming. Genetic silencing of RAPTOR attenuated both mTORC1 signalling and cytokine induction, establishing pathway dependency. Ex vivo conditioning with AS-3 significantly improved antitumor efficacy in two independent adoptive T-cell therapy models, accompanied by enhanced persistence, reduced exhaustion, and superior effector function. Together, these findings establish pharmacological activation of the RAPTOR-mTORC1 axis as a strategy to generate metabolically resilient T cells and provide a clinically translatable approach to improving the durability and efficacy of next-generation ACT.

immunology↗

bioRxiv2026

Therapeutic-induced chromatin remodeling via AP-1/SWI-SNF enhances BK Polyomavirus replication in urothelial cells

Hemorrhagic cystitis (HC) caused by BK polyomavirus (BKPyV) reactivation is a serious complication in immunocompromised patients especially in hematopoietic stem cell transplant recipients, yet the effects of conditioning regimens on viral replication remain undefined. Current therapies for HC are largely supportive, and no specific antiviral drugs are approved for BKPyV reactivation, underscoring an urgent need for new interventions. Here, using a cellular model of HC, we provide the first mechanistic evidence that physiologic concentrations of genotoxic chemotherapy, immune-conditioning, and antiviral exposures commonly enhance BKPyV replication by reprogramming host chromatin remodeling machinery independently of immune suppression. Transcriptomic and epigenomic profiling of urothelial cells revealed that these treatments induce host and virus chromatin remodeling, specifically, the SWI/SNF ATP-dependent remodeling complex is activated and creates a regulatory landscape enriched for AP-1 transcription factor motifs, implicating the AP-1/SWI-SNF axis as a key regulator of viral replication. Functional inhibition of SWI/SNF with AU-15330 and FHD-286 consistently suppressed BKPyV replication across all tested therapeutic conditions. Patient urine samples and cellular experiments demonstrated these effects are independent of viral genomic changes. These findings suggest chromatin remodeling as the mechanistic driver of therapy-associated BKPyV reactivation and propose SWI/SNF inhibition as a translational therapeutic strategy to mitigate hemorrhagic cystitis.

microbiology↗

bioRxiv2026

Single-cell informed metabolic modeling reveals organ-specific metabolic adaptations in breast cancer organotropism

Breast cancer organotropism is driven by interactions between tumor cells and organ-specific microenvironments that support metastatic growth. To better understand the metabolic basis of organ-specific metastasis, we integrated single-cell transcriptomics with constraint-based systems biology to generate context-specific metabolic models of breast cancer metastasis to the liver, bone, and brain. Our analysis identified both common and organ-specific metabolic changes, suggesting that metastatic cells share a core metabolic program while also adapting to the metabolic environment of each target organ. Primary tumors with metastatic potential showed early alterations in nucleotide metabolism, transport reactions, and energy-related pathways, indicating metabolic changes before metastatic spread. Metabolic transformation analysis identified key metabolic regulators involved in the tricarboxylic acid (TCA) cycle, oxidative phosphorylation, redox balance, and metabolite transport. Integration with CRISPR gene essentiality data further highlighted metabolically important genes as potential therapeutic targets. In addition, analysis of organ-specific secreted metabolites revealed distinct metabolic signatures associated with metastatic colonization of the liver, bone, and brain. Overall, our single-cell-informed metabolic modeling approach shows that breast cancer organotropism is associated with both shared and organ-specific metabolic adaptations. The study provides a framework for identifying potential metabolic vulnerabilities that could be targeted to treat metastatic breast cancer.

systems biology↗

bioRxiv2026

APP and APLP2 Kunitz Domains Are Potent Endogenous Inhibitors of TMPRSS2 and Respiratory Virus Infection

Respiratory viruses depend on host proteases for activation of viral fusion proteins, making these enzymes attractive targets for broad-spectrum antiviral strategies. We previously identified Trypstatin, a human Bikunin-derived Kunitz domain, as a potent endogenous inhibitor of the airway serine protease TMPRSS2. Here, we investigated whether TMPRSS2 inhibition is shared by additional human Kunitz domains. Kunitz domains with high sequence similarity to Trypstatin were synthesized, refolded, and functionally characterized. Domains derived from amyloid precursor protein (APP) and amyloid precursor-like protein 2 (APLP2) potently inhibited TMPRSS2, with APP displaying subnanomolar activity comparable to camostat mesylate. APP and APLP2 selectively blocked SARS-CoV-2 Spike-mediated entry without affecting VSV-G-mediated entry or cell viability and inhibited infection by multiple coronaviruses and influenza viruses, but not TMPRSS2-independent rhinovirus. In primary human airway epithelial cultures, APP and Trypstatin reduced replication of SARS-CoV-2, endemic coronaviruses, and influenza A virus, and remained stable in airway mucus. These findings identify APP and APLP2 Kunitz domains as potent endogenous inhibitors of TMPRSS2-dependent respiratory virus infection and promising scaffolds for host-directed broad-spectrum antivirals.

microbiology↗

bioRxiv2026

Targeting Tumor-derived Sphingosine Kinase 2 Unleashes Antitumor Immunity and Improves Survival of Mice with Group 3 Medulloblastoma

Group 3 medulloblastomas (G3MB) carry the worst prognosis among medulloblastoma subtypes, yet molecularly targeted therapies remain elusive. Standard treatments cause severe long-term morbidity in survivors. Here, we identify tumor-derived sphingosine kinase 2 (SPHK2) as an essential driver of G3MB initiation and progression. SPHK2 exacerbates local immunosuppression by suppressing cytotoxic T-cell and NK-cell activity while promoting regulatory T-cell infiltration. Genetic or pharmacologic SPHK2 inhibition using Opaganib attenuates pro-survival tumor signaling and restores anti-tumor immunity, significantly improving survival in syngeneic G3MB mouse models. Combining Opaganib with fractionated low-dose radiation (f-LDRT) further enhances antigen presentation and reprograms tumor-associated myeloid cells toward an anti-tumor phenotype. This combination therapy markedly prolongs survival without inducing significant toxicity. Overall, our study establishes SPHK2 as a previously unrecognized therapeutic target and presents a safe, effective, microenvironment-reprogramming regimen for G3MB. One Sentence SummaryDirect inhibition of tumor-derived SPHK2 overcomes local immunosuppression and downregulates pro-survival signaling in Group 3 medulloblastoma, while combination with fractionated low-dose radiation further enhances anti-tumor immunity and significantly improves survival.

cancer biology↗

bioRxiv2026

Multiomic Integration Reveals Transposable Element-Embedded Regulatory Variants Underlying Brain Aging

Genome-wide association studies (GWAS) have identified thousands of variants associated with brain aging, most in noncoding regions whose regulatory effects remain poorly understood. Transposable elements (TEs) constitute a major, understudied component of brain regulatory DNA. To interpret noncoding brain-aging variants through TE-derived regulatory architecture, we integrated brain-aging GWAS variants with TE annotations, ENCODE candidate cis-regulatory elements (cCREs), single-nucleus ATAC-seq accessibility maps, HOMER motif analysis, experimental enhancer-promoter interaction maps, and multiomic variant-to-gene resources. Of 6,323 genome-wide-significant variants, 633 (10.0%) localized within 367 TE-derived cCREs. These elements were predominantly enhancer-like and frequently carried transcription factor-associated annotation. Alu-derived elements formed the largest family component, followed by L1, L2, MIR and ERVL-MaLR elements. Single-nucleus accessibility maps resolved these variants across brain cell types, including a TcMar-Tigger-associated signal in oligodendrocytes, and motif analysis of SINE-associated cCREs identified reproducible nuclear-receptor, immune (PU.1:IRF8) and chromatin-regulatory (RFX-family) signatures. Because this localization reflects correlated variants within a limited number of independent loci rather than independent enrichment signals, we prioritized candidate regulatory variants and their target genes using the Brain Aging Genetic ScoreCard, which integrates 27 orthogonal evidence layers across independent, LD-defined loci and identified 25 loci with TE-derived regulatory support. The chromosome 17q21.31 MAPT locus emerged as the top candidate genome-wide, where a MIR-derived enhancer shows convergent evidence linking it to MAPT, a prioritization robust to locus-size effects. Overall, our study provides an integrative framework for interpreting noncoding GWAS variation through TE-derived regulatory architecture.

genomics↗

bioRxiv2026

HiBASIL: Hierarchical Bayesian Source Inference and Localization for Spatial Epidemiology

O_LIIdentifying spatial origins of biological invasions, disease outbreaks, or environmental contaminants is critical for timely intervention. However, existing methods struggle to resolve overlapping signals from multiple sources or account for extreme zero/one inflation in bounded data. C_LIO_LIWe developed HiBASIL (Hierarchical BAyesian Source Inference and Localization), a Bayesian framework that jointly infers source coordinates and mechanistic dispersal kernels from zero-one-inflated spatial observations. We systematically tested HiBASIL across 2,500 simulations spanning localized to long-distance dispersal regimes, various foci weight mixtures (0.5/0.5 to 0.95/0.05), and varying sample sizes (N = 50 to 500) to evaluate geometric sensitivity, spatial robustness, parameter recovery capability, and multi-focal resolution. We applied HiBASIL in tracking cucurbit downy mildew dispersal in field experiments including non-inoculated control, single-focus, and two-foci treatments arranged in a randomized complete block design. To demonstrate broad applicability, we validated HiBASIL with historical London cholera epidemic data to determine whether it could accurately localize the epicenter. C_LIO_LIHiBASIL achieved 100% accuracy in kernel identification under correct model specification, 100% and 98% (2% predictive equivalence) in under- and over-parameterization scenarios, and maintained appropriate parsimony in null scenarios. Source localization was highly precise, with a median bias of 0.11 m, successfully resolving minority sources contributing only 5% of the observations. Importantly, the framework provides intrinsic self-diagnostics, signaling model complexity mismatch through posterior bimodality (under-parameterization) or parameter collapse (over-parameterization). HiBASIL is applicable in various epidemic scenarios, including diffused long-distance dispersal. Under an isotropic process, HiBASIL achieved sub-meter mean errors on two-source localization in cucurbit downy mildew field tests, effectively isolating transmission signals from landscape noise despite sparse sampling. Despite confounding influence of underlying network processes in the historical cholera data, the posterior localized the epicenter to within [~] 33m, demonstrating portability beyond plant disease epidemiology. C_LIO_LIIn summary, HiBASIL can accurately localize multiple sources across various epidemic scenarios, extremely unbalanced foci mixtures, and sparse sampling conditions. HiBASIL also demonstrates wide applicability across agricultural and human disease epidemic systems. By providing an open-source Python implementation, HiBASIL enables rigorous inverse spatial inference for ecology, epidemiology, and environmental monitoring, transforming how discrete transmission sources are identified in complex landscapes. C_LI

ecology↗

bioRxiv2026

scINTILLA: Single-Cell Integrated Inference, Labelling, and Landscape Analysis for Cell-Type Annotation Quality Assessment

Single-cell RNA sequencing has enabled the construction of comprehensive cell atlases, yet the quality and coherence of the cell-type annotations within these atlases remain largely unexamined. When a label is applied to a transcriptionally heterogeneous population, the downstream analyses that depend on it, and automated label transfer in particular, become unreliable. We present scINTILLA (Single-Cell Integrated Inference, Labelling, and Landscape Analysis), a computational framework that combines supervised and unsupervised machine learning to score the learnability and internal consistency of cell-type labels in single-cell datasets. The unsupervised arm benchmarks a broad panel of clustering algorithms and derives a neighbourhood confusion score for every cell, whilst the supervised arm trains up to twelve classifiers and extracts prediction agreement, entropy, and confidence. These signals are normalised and aggregated into a single composite score per cell type, where a low score flags label ambiguity or concealed heterogeneity. As a by-product, scIN-TILLA also reports which clustering and classification algorithms perform best on a given dataset, offering practical guidance for downstream label transfer. We applied it to five Human Cell Atlas datasets spanning the adult brain, lung, eye, and two organoid atlases, and recovered clear differences in the learnability and internal consistency of annotations across atlases that were not driven by the number of annotated cell types. Focused re-analysis of lowscoring populations in the lung and endoderm-organoid atlases resolved biologically coherent sub-populations, in some cases with context-specific enrichment, much of it recovered from cells that had been assigned broad or catch-all labels. scINTILLA is advisory rather than prescriptive, guiding principled, data-driven re-annotation at atlas scale.

bioinformatics↗

bioRxiv2026

Orthogonal perturbation of sulfur availability reveals antibiotic-induced synthetic lethality in Mycobacterium tuberculosis

Despite its essential role in growth, the impact of sulfur limitation on mycobacterial physiology and antibiotic responsiveness remains poorly understood. Here, we combined chemical-genetic perturbations and infection models to investigate the consequences of sulfur limitation in Mycobacterium tuberculosis (M. tuberculosis). We report that sulfur limitation restricted bacterial growth by rewiring metabolism, resembling nutrient starvation. CRISPR interference of the sulfate transporter (ST) revealed severe vulnerability and sensitised M. tuberculosis to anti-TB drugs. Inhibition of H2S production in macrophages further compromised the fitness of ST-deficient M. tuberculosis, indicating that the bacteria depend on host-derived sulfur during infection. Importantly, preventing sulfur acquisition attenuated both the drug-sensitive H37Rv and the drug-resistant clinical strain of M. tuberculosis, while enhancing the efficacy of Isoniazid (INH) in the murine model, resulting in sterilisation of infected lung tissues. Combined, our findings suggest that restricting sulfur uptake highlights a therapeutic vulnerability that enhances the efficacy of existing anti-TB drugs.

microbiology↗

bioRxiv2026

GIGYF2/4EHP-Mediated Translational Attenuation Maintains Cellular Homeostasis Following Ionizing Radiation

Translational regulation is a critical component of the cellular response to environmental stress. Ionizing radiation (IR) exists naturally at low doses (e.g., cosmic rays and radioactive materials) but is applied at much higher doses in clinical settings, where accelerated photons (X-rays) and particle beams (protons, ions etc) are utilized for the treatment of cancer. While the effects of IR on DNA damage and cell cycle are well established, its impacts on cellular RNA metabolism remains less understood. In particular, the role of the mRNA translation machinery in shaping the early cellular response to IR is largely unexplored. Here, we demonstrate that IR induces an acute and persistent translational repression. This acute repression is independent of the mTOR and Integrated Stress Response pathways, which are known regulators of mRNA translation in response to environmental cues. Instead, we discovered that the translational repression is, at least partially, mediated by the GIGYF2/4EHP translational repressor complex. We show that GIGYF2/4EHP recruitment to the mRNAs upon IR exposure is driven by rapidly enhanced interactions with RNA-binding proteins such as ZFP36 and components of the miRNA-Induced Silencing Complex (miRISC) that are poised on their target mRNAs. Importantly, the presence of the GIGYF2/4EHP complex is required for the maintenance of proteostasis and cell viability following irradiation. Together, our results establish mRNA translational control as a key determinant of cellular response to IR and identify GIGYF2/4EHP as a critical component of this adaptive mechanism.

cell biology↗

bioRxiv2026

Estrogen-Deficiency Degrades Left Ventricular Diastolic Function and Energy Metabolism in Hypertensive Female Mice

AimsHeart failure (HF) due to diastolic dysfunction (DD) but normal left ventricular (LV) ejection fraction (EF) is termed HF with preserved EF (HFpEF). Given its high prevalence in post-menopausal women, we hypothesized that 17{beta}-estradiol (E2) function is mechanistically linked to DD HF and investigated E2-deficiency in the etiology of DD in a mouse model. MethodsFemale C57BL/6J mice were divided into one group with hypertension induced by N({omega})-nitro-L-arginine methyl ester (L) and cardiac pressure overload induced by angiotensin II (A), collectively inducing DD, and one group with sham treatment. Groups were subdivided to receive an ovariectomy (OVX) to induce estrogen-deficiency and emulate menopause or sham surgery. During the next 21 days, mice were tested for cardiac function, food intake, response to E2 agonists, gene profiling, cardiomyocyte-contractility and elasticity, and cardiac mitochondrial function. ResultsOVX-associated E2-deficiency exacerbated DD in a time-dependent way without affecting EF or stroke volume, emulating a severe DD phenotype. These changes paralleled those for mitochondrial dysfunction, i.e., upregulation of genes associated with stress, energy metabolism, and fibrosis, as well as functional and structural defects in cardiomyocytes. Treatment of OVX + (L + A) with E2 or a G-protein-coupled estrogen receptor agonist normalized diastolic function, whereas estrogen receptor beta agonists did not. The OVX DD mice exhibited moderately impaired mitochondrial function, which delayed cardiomyocyte relaxation but not contraction, altered cardiac substrate utilization, reduced cardiomyocyte elasticity, increased production of reactive oxygen species, and potentiated extracellular fibrosis. ConclusionsOVX-induced E2-deficiency generates metabolic, structural, and functional changes in cardiomyocytes and the adjacent extracellular matrix, exacerbating the effects of L and A on diastolic function. This robust DD model revealed a role for E2 via ER in diastole-regulation in female mice and raised questions about similar mechanisms operative in postmenopausal women. HIGHLIGHTSO_LIOvariectomy (OVX)-induced estrogen-deficiency exacerbated diastolic dysfunction (DD) induced by hypertension and pressure overload with preserved ejection fraction in female C57BL/6J mice. C_LIO_LIIn post-OVX-treated DD mice, heart weight and fibrosis preceded other metrics of cardiac dysfunction. C_LIO_LIOVX-induced estrogen-deficiency increased the expression of genes associated with stress, energy metabolism, and especially fibrosis. C_LIO_LIMetabolic imaging of the heart by positron emission tomography revealed that DD with preserved ejection fraction was associated with mitochondrial dysfunction presenting as increased accretion of cardiac energy substrates, [18F]deoxyglucose and [11C]palmitate, effects that worsened following OVX. C_LIO_LIOVX increased cardiomyocyte stiffness and fibrosis and reduced cardiomyocyte lengthening and compliance in the context of female DD. C_LIO_LIImproved diastolic function following delivery of GPER agonists or estradiol to OVX DD female mice implicates estrogen receptor in the maintenance of normal cardiac function. C_LI

physiology↗

bioRxiv2026

Dietary fiber selectively regulates intestinal persistence of probiotic bifidobacteria

Bifidobacteria dominate the gut microbiota of breast-fed infants, and are strongly associated with human health, including immune regulation, colonization resistance, and protection against inflammation. However, bifidobacteria persist at high abundance after weaning in only a subset of individuals, and the factors that regulate intestinal persistence of bifidobacteria are poorly understood. Using gnotobiotic mouse models, we identified a common dietary fiber, raffinose, as a critical determinant of bifidobacterial persistence during microbial transitions associated with weaning. Bifidobacterial persistence depends on an intact raffinose utilization operon and is associated with disease resistance and restrained inflammation in adult mice. Specific dietary fiber recommendations commencing at weaning are a potential strategy to maintain bifidobacteria persistence beyond infancy, with potential long-term benefits for host resilience and reduced risk of inflammatory disease.

microbiology↗

bioRxiv2026

Sustained presence of metabolically active mesophiles in the boiling vent-water of a low-salinity, slightly-alkaline, sulfate-rich geothermal spring characterized by an inequitable ecology of hyperthermophiles and thermophiles

Geothermal vent-heads exclusively support the proliferation of (hyper)thermophilic microorganisms. However, diverse mesophiles are stochastically thrust into these ecosystems by local geodynamic forces, and their population-level responses to the unfamiliar stressor hold critical implications for lifes intrinsic resilience to biophysical adversities. Here, we report a time-course exploration of the boiling vent-water of a Trans-Himalayan geothermal spring to determine the population dynamics, in situ functionalities, and potential ecological roles of mesophilic incomers in the context of indigenous (hyper)thermophiles. The temporally-consistent (hyper)thermophilic core-community, predominated in turn by a few Aquificia and Thermoproteota, was delineated as metagenome-assembled genomes. Mesophiles/moderate-thermophiles were identified as MAGs and/or pure-cultures, and whether temporally-consistent/inconsistent, had far lower prevalence. Overall, in situ transcriptional activity and prevalence had significant positive correlation; but many species exhibited high activity despite low prevalence and vice versa, implicating the decoupling of global metabolism from growth/proliferation. Bulked metatranscriptomic signatures identified the (hyper)thermophiles as primary producers of the ecosystem. Populations of mesophiles and moderate-thermophiles were apparently active, but not growing, in situ, with some being engaged in environment detoxification, and production of nutrients, metabolites and protective-biomolecules wanting in the (hyper)thermophiles. The findings engender an unprecedented portrayal of geothermal-vents as multi-community ecosystems where unfamiliar immigrants provide critical metabolic services.

microbiology↗

bioRxiv2026

De-Novo Designed Antibacterial N95 Facial Mask: Comprising a Nano-Garden Using ZnO Nanoflower

Nowadays N95 facial mask has gain huge attention due to COVID19 pandemic situation and it serves as the prime PPE. Though the microbes can be restricted to get inside the human body due to the presence of mask temporarily, but over the time, bacteria and other microbes may get entrapped into the threads of the mask itself and thus acting as a storage chamber of microbes. It is necessary to eliminate them from the mask surface. To do so different floral structured Nano-ZnO with variable oriented arrangement of petals were fabricated on the surface of the N95 mask and further characterized through instrumentations including XRD, FTIR,UV-Vis, Fluorescence-Spectroscopy, SEM, DLS. The average crystallite size calculated for synthesized four different ZnO nanoflower were 25.19 nm, 23.46 nm, 27.27 nm and 31.78 nm (for glycerol, PEG, EDTA, Chitosan assisted) respectively. The antimicrobial activity was investigated by standard microbial broth dilution assay and Kirby-Bauer test which assured the inhibition of the bacterial growth. The MIC-MBC value of ZnO nanoflowers for E.coli and B. subtilis were found to be effective at dilution of 250 {micro}g/ml and 100 {micro}g/ml. Additionally a modified Kirby-Bauer assay has been designed to investigate the killing efficiency of the bacteria (E.coli). O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=145 SRC="FIGDIR/small/719592v1_ufig1.gif" ALT="Figure 1"> View larger version (35K): org.highwire.dtl.DTLVardef@a76030org.highwire.dtl.DTLVardef@9bf1b3org.highwire.dtl.DTLVardef@19232forg.highwire.dtl.DTLVardef@54fe68_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFig. - Graphical AbstractC_FLOATNO C_FIG

microbiology↗