Biology subjects

Anand, A.

Publications and source records attributed to Anand, A..

At least 19 recordsLinked to original sources

bioRxiv2026

Genome-wide LD scores enable robust heritability and genetic correlation estimation from summary statistics across genetic ancestries

Our knowledge of human complex trait architecture across diverse populations remains limited. Estimating SNP heritability and genetic correlation from GWAS summary statistics - successful in revealing genetic architecture in homogeneous cohorts - is challenging in structured and admixed populations due, in part, to the difficulty of representing long-range LD. We present SUMMIT, a statistical framework that combines genome-wide LD scores, efficiently estimated using random projections, with GWAS summary statistics to estimate genome-wide and annotation-specific heritability and genetic correlation. In simulations that explore diverse aspects of genetic architecture across European (EUR), South Asian (SAS), and admixed African-European cohorts (AFR) in the UK Biobank (UKB), SUMMIT had increased accuracy and reduced bias compared to prior methods, with the largest gains in non-European ancestries reflecting improved modeling of long-range LD. Across 40 UKB traits, SUMMIT produced estimates of genome-wide common-SNP heritability (h_g^2) and heritability enrichments in genomic annotations that were broadly concordant across ancestries with the SUMMIT h_g^2 estimates more closely matching recent whole-genome sequencing based estimates. SUMMIT substantially improved genetic correlation analysis recovering more significant findings across ancestries (23 SAS and 3 AFR at FDR < 0.05 compared with none and two for cov-LDSC) with the non-European discoveries showing concordant effects in Europeans suggesting that, like heritability, global patterns of pleiotropy are largely shared across ancestries. By combining accurate genome-wide LD and efficient moment estimation, SUMMIT enables investigation into how heritability and genetic correlation vary across populations and genomic annotations, including in structured and admixed cohorts, at the genome-wide, annotation-specific, and cross-trait levels.

genomics↗

bioRxiv2026

Trust, but Verify: Epistemic Uncertainty-Gated Pseudo-Labeling for Safer Semi-Supervised Malaria Screening

Background. Deep learning could make malaria microscopy more accessible in low-resource settings, but training it usually needs thousands of expert-labeled images. Semi-supervised learning (SSL) reduces this need by also learning from unlabeled images. However, methods such as FixMatch accept pseudo-labels using a fixed confidence threshold, and lowering that threshold to use more data can teach the model to make confident mistakes. These silent failures are dangerous because they are never flagged for expert review. Methods. We added an uncertainty check to SSL pseudo-labeling. Each unlabeled image is passed through the model ten times with Monte Carlo dropout active; its pseudo-label is used only if the normalized predictive entropy of the averaged prediction is below 0.2, and it is then weighted by a sigmoid function of model confidence. We trained a ResNet-18 on the public Malaria Cell Images dataset (27,558 cell images; 70:10:20 split) using labels for only 20% of the training images. Over six random seeds, we compared the method with a supervised baseline and with FixMatch at thresholds of 0.95 and 0.80, measuring accuracy, AUC and silent failure rate (SFR), the share of predictions that are wrong despite confidence above 0.95. Results. Compared with FixMatch at a threshold of 0.80, our method lowered the mean SFR from 2.28% to 1.52%, a 33.2% relative reduction (paired t-test, t = 4.29, p = 0.0078), and the SFR was lower in all six runs. Accuracy (96.6% vs. 96.4%) and AUC (0.991 for both) were unchanged. The mean SFR was also below that of FixMatch at 0.95 (1.97%) and of the supervised baseline (2.01%). Conclusions. Checking epistemic uncertainty before accepting pseudo-labels reduced confident errors in semi-supervised malaria cell classification without lowering accuracy. Patient-level and external validation on whole-slide images are still needed before clinical use.

bioinformatics↗

bioRxiv2026

Microbial persistence beneath temporal restructuring in university wastewater metagenomes

Temporal changes in wastewater microbiomes can reflect shifts in microbial abundance, detectable membership, and genome recovery. We paired genome-resolved and read-based metagenomics to distinguish these signals in 25 spatially pooled university wastewater samples collected during wet and dry periods. The workflow recovered 203 wet-period and 230 dry-period metagenome-assembled genomes (MAGs). Community composition differed between periods in both MAG-derived presence/absence profiles (Jaccard PERMANOVA, R2 = 0.548, p = 0.001) and read-based relative-abundance profiles (BrayCurtis PERMANOVA, R2 = 0.167, p = 0.001). Greater dry-period read-based richness persisted after rarefaction but disappeared under more stringent abundance thresholds, indicating a substantial contribution from low-abundance detections. Of 57 period-associated core species in the MAG-derived profiles, 14 had exact species-level matches in the read-based dataset. All 14 remained detectable at >=90% prevalence in the opposite period, and 13 had higher relative abundance in the period corresponding to their MAG-based association. Continued species detection therefore accompanied changes in community composition and MAG-based representation. Perfect/Strict CARD/RGI resistance-associated annotations occurred in 94.1% of wet-period and 92.2% of dry-period MAGs and were distributed across shared-core and period-associated taxa. These findings reveal repeated detection of a matched subset of microbial taxa beneath temporal community restructuring, together with widespread resistance-associated genetic potential among recovered genomes. Combining read-based and genome-resolved profiles helps distinguish changes in detectable membership from changes in the genomic characterization available for wastewater surveillance.

microbiology↗

bioRxiv2026

Cross-Dataset Reanalysis of Mouse Alzheimer Disease Single-Cell RNA-Sequencing Data Reveals a Reproducible Innate Immune Activation Signature

Single-cell RNA sequencing (scRNA-seq) studies of Alzheimer disease (AD) mouse models have proliferated across independent laboratories, brain regions, and platforms, yet the cross-study reproducibility of transcriptional signatures derived from such data remains underexplored. We reanalyzed six publicly available mouse brain scRNA-seq datasets (GSE140399, GSE140510, GSE143758, GSE208683, GSE214244, and GSE296027; 360,620 cells, 102 annotated clusters) using a standardized pipeline (Figure 1) comprising quality control, Leiden clustering, confidence-tiered marker-based cell-type annotation, sample-level pseudobulk differential expression, cross-dataset consistency analysis, and pathway enrichment. Pseudobulk differential expression, performed on 32 samples (16 AD, 16 Control) from five of the six datasets, identified 301 significant genes (FDR-adjusted p < 0.05) out of 20,629 tested, of which 290 (96.3%) were upregulated and 11 (3.7%) downregulated in AD. The upregulated set was dominated by innate immune and interferon-response genes (Ccl3, Ccl4, Ccl6, Itgax, Cst7, Tlr4, Trem2) and showed extremely strong enrichment for immune system and innate immune system pathways (Reactome, p {equiv} 1.9 x 10-43 and 2.1 x 10-29 respectively), phagosome and osteoclast differentiation (KEGG), and interferon alpha/beta signaling. Of the 301 significant genes, 235 (78%) showed the same direction of effect across all datasets in which they were tested. The sixth dataset, GSE296027, was excluded from differential expression analysis due to a gene-identifier corruption artifact introduced during pseudobulk aggregation (detailed in Methods and Limitations) but contributed valid cell-type composition and microglial subclustering data, independently recovering a disease-associated microglia-like state. These findings indicate that a reproducible, strongly immune/interferon-skewed transcriptional signature, rather than a balanced up/down transcriptional shift, characterizes the mouse AD models analyzed here.

bioinformatics↗

bioRxiv2026

Slice, Subtract, Segment: Efficient 2D and Physiologically Informed 3D Brain Tumor Segmentation

Background. Automated segmentation of glioma subregions on multiparametric MRI can be improved by changing either the network architecture or the information presented to the network. These two design levers are usually studied together, which makes their individual contributions difficult to see. We present an integrated analysis of two completed, independent studies, each of which isolates one lever. Methods. In the architecture-level study (Slice), SIBA-UNet - a 2D U-Net combining depthwise separable convolution, inverted-bottleneck blocks and attention-guided skip fusion - was trained on 128 x 128 multimodal slices from BraTS 2020 with a patient-level split, and a sigmoid decision threshold was selected on validation data. In the representation-level study (Subtract), CMSR-3D augmented the four standard MRI sequences with four voxel-wise cross-modal subtraction maps (T1-T1CE, T2-FLAIR, FLAIR-T1CE, T2-T1CE) and evaluated 4-, 6- and 8-channel inputs with an identical 3D U-Net on 1,251 BraTS-GLI 2023 cases (1,001/125/125 split). Results. SIBA-UNet reached an overall validation Dice of 0.8601 at a validation-selected threshold of 0.51, with reported subregion Dice of 0.8795 (necrotic core), 0.8501 (edema) and 0.9125 (enhancing tumor); the source ablation was only partially reported. With the architecture held fixed, the 8-channel CMSR-3D configuration gave the highest mean Dice among the evaluated inputs (0.8699 vs. 0.8534 for the 4-channel baseline) and the lowest mean HD95 (5.9859 vs. 8.2308), whereas either two-map subset alone changed mean Dice by at most 0.0037. Conclusions. Architecture design and input-representation design are separable levers for brain tumor segmentation. The controlled representation ablation indicates that the complete set of subtraction maps was more informative than either subset under a fixed 3D U-Net. Both studies were evaluated internally on their respective datasets, and their numerical results are not directly compared because the datasets, dimensionality and evaluation protocols differ.

bioengineering↗

bioRxiv2026

Adaptive respiratory bypass restores oxidative metabolism in NADH dehydrogenase-deficient Escherichia coli

Nicotinamide adenine dinucleotide is central to the cellular redox network and continuously cycles between its oxidized (NAD) and reduced (NADH) forms. Membrane-bound NADH dehydrogenases are the primary NADH-oxidizing enzymes and principal entry point for reducing equivalents into the bacterial respiratory chain. While maintaining optimal balance of this redox cofactor is among the most fundamental biochemical constraints on living systems, how cells adapt when the primary NADH oxidation route is lost remains poorly understood. Here we show that Escherichia coli lacking both NADH dehydrogenases initially compensates through costly fermentative lactate secretion, potentially to maintain redox and energy homeostasis, but at the cost of impaired growth and oxidative metabolism. Using adaptive laboratory evolution across four independent lineages, we found that all evolved populations derepressed malate:quinone oxidoreductase by disrupting an ArcA-binding site. This gain-of-function mutation establishes an alternative pathway that funnels electrons directly into the quinone pool, restoring respiratory oxygen consumption to wild-type level. Multi-omics and genome-scale metabolic modeling reveal that this bypass drives broad reorganization of central carbon metabolism, reinstates tricarboxylic acid cycle flux, and shifts cells toward a higher, more oxidative aero-type. These findings uncover a previously unrecognized metabolic buffering capacity that enables bacteria to circumvent loss of canonical respiratory entry points.

microbiology↗

bioRxiv2026

MAFA drives pancreatic islet maturation through coordination of cell growth, metabolic maturation, and resilience to stress.

Stem cell-derived islets (SC-islets) are a promising source for replacing the loss of insulin-secreting {beta} cells in insulin-dependent diabetes patients, but compared to their primary human counter parts, SC-islets are considered functionally immature and do not immediately regulate blood glucose after transplantation. To better understand the molecular underpinnings of {beta} cell maturation, we genetically engineered human pluripotent stem cells (hPSCs) to control the induction of the {beta} cell-maturing transcription factor MAFA or a MAFA S64F mutant variant associated with premature {beta} cell aging and senescence in SC-islets. We employ a combination of in vitro assays, multi-omics analyses, and murine in vivo transplantation studies to demonstrate that MAFA remodeling of the SC-islet transcriptional landscape promotes SC-islet biogenesis and metabolic maturation giving rise to greater SC-islet resilience and insulin secretory capacity. Parallel MAFA S64F studies highlight the importance for compensatory mechanisms for sustaining accelerated oxidative metabolism and enhanced insulin secretion without inducing intracellular stress responses and islet dysfunction. Overall, these results reveal MAFA-governed transcriptional changes that drive SC-islet functional maturation, which provides the foundation for maturing SC-islets in vitro, preserving {beta} cell integrity, and improving SC-islet cell replacement therapies.

cell biology↗

bioRxiv2026

Early-life stress-induced gut dysbiosis is ameliorated by nicotinamide treatment

Early life stress (ELS) in the form of adverse experiences in childhood results in multiple psycho-physiological pathologies during adulthood and accelerates aging. Such pathologies are recently observed to be alleviated upon nicotinamide treatment in a maternal separation model of ELS. We report a nicotinamide-driven amelioration of gut dysbiosis in middle-aged rodents with a history of neonatal maternal separation.

microbiology↗

bioRxiv2026

Mechanical History and Substrate Stiffness Shape Integrin-Mediated Endothelial Cell Behavior on Bioactive Hydrogels

Synthetic blood contacting devices frequently fail due to the lack of requisite biochemical and biomechanical cues needed to support transanastamotic endothelialization. During transanastomotic endothelialization, endothelial cells experience dynamic changes in extracellular mechanical cues as they migrate from compliant native vessels onto stiffer blood contacting device surfaces. However, how substrate stiffness and mechanical memory from prior mechanical environments influence temporal integrin remodeling and downstream endothelialization processes necessary to establish a stable endothelial layer remains poorly understood. In this study, human coronary artery endothelial cells (HCECs) were cultured on substrates spanning physiologically relevant stiffnesses to determine how substrate mechanics regulate collagen binding integrins and endothelialization. Increasing substrate stiffness promoted time dependent upregulation of 2{beta}1 integrin expression, whereas 1{beta}1 expression remained unchanged. Enhanced 2{beta}1 expression on stiff substrates was accompanied by increased vinculin associated focal adhesion maturation and accelerated endothelialization, characterized by increased proliferation, migration, and progression to confluence prior to reaching quiescence after 1 week. To better model transanastomotic migration and investigate mechanical history effects, cells initially expanded on compliant hydrogels were transferred to stiff substrates. Although these cells exhibited transient reductions in 2{beta}1 expression at early timepoints compared with tissue culture polystyrene expanded controls, no persistent differences in focal adhesion maturation, proliferation, migration, confluence, or quiescence were observed. Collectively, these findings demonstrate that substrate stiffness is a primary regulator of the early endothelialization processes required to establish a stable endothelial monolayer, whereas the influence of mechanical history is transient and ultimately superseded by the current mechanical environment. These findings also identify 2{beta}1 mediated mechanotransduction as a potential design target for blood contacting biomaterials that promote rapid endothelialization while supporting long-term endothelial cell quiescence.

bioengineering↗

bioRxiv2026

Kappa opioid receptors (KORs) in the anterior paraventricular nucleus of the thalamus (aPVT) mediate morphine withdrawal-, anxiety-, fear-, and KOR agonist-induced aversion-like behaviors in mice

PVT is involved in stress responses, fear, anxiety, arousal, aversion and reward. Anterior and posterior PVT (aPVT and pPVT) have different neuronal connections, molecular contents, and functional roles. PVT expressed a high level of KOR. Herein we mapped the projection targets of aPVT KOR(+) neurons and explored the behavioral significance of aPVT KOR. Using KOR-iCre mice and Cre-dependent anterograde tracer, we found that KOR(+) glutamatergic neurons in aPVT primarily projected to NAc, CeA, BNST, PFC, and reticular nucleus of the thalamus (RT). 3-D images showed the pathway emanating from aPVT to the ventral RT, through NAc, and out to the other regions, indicating widespread axonal collateralization. We conditionally knock-downed KOR (KOR cKD) in aPVT by injection of AAV-eGFP-Cre or AAV-eGFP (control) into aPVT of Oprk1lox/lox mice. [3H]U69,593 receptor autoradiography revealed substantial KOR cKD in aPVT. In both male and female mice, the KOR cKD in aPVT significantly reduced anxiety-like behaviors in the elevated plus-maze test, cue-induced freezing after fear conditioning and naloxone-precipitated morphine withdrawal-associated jumps. KOR cKD attenuated U50,488H-induced conditioned place aversion in males only, while having no effect on forced swim immobility or the U50,488H-induced visceral analgesic and antipruritic effects in either sex. Thus, our results reveal for the first time that KOR-mediated inhibition of aPVT neurons may mediate morphine withdrawal, anxiety, and cue-induced fear in both sexes but contribute to KOR agonist-induced aversion only in males. Notably, our findings reveal a previously unrecognized role for aPVT in regulating morphine withdrawal, acting in a manner distinct from pPVT.

neuroscience↗

bioRxiv2026

A Facile and Versatile Technique for Creating Antifibrotic Coatings on Biomedical Implants

Foreign body response is a common yet serious challenge for biomedical implants. It can trigger inflammation and eventually lead to the formation of a fibrotic capsule, which compromises device function. Although significant efforts have been made to develop antifibrotic surface coatings for implantable materials, developing broadly applicable solutions remains challenging due to the diversity of materials used in biomedical implants. Here, we propose a simple and versatile strategy to develop antifibrotic coatings for biomedical implants. Photoreactive benzophenone groups are incorporated into designer polymers to enable covalent attachment to various substrates. The effect of benzophenone group density within polymer chains on surface coating efficiency was investigated, and an optimal BP incorporation ratio was identified. Polymers incorporating varying ratios of an anti-fibrotic small molecule and anti-fouling zwitterionic moieties were synthesized and successfully attached to silicone implants. In vivo evaluation of these implants in C57BL/6 mice identified an optimized polymer composition that reduced fibrotic capsule thickness by around 60%. Coating of commercial medical catheters with this optimized polymer reduced collagen deposition by over 3.5-fold following 4 weeks of implantation in the peritoneal space of C57BL/6 mice. Finally, we demonstrated that the optimized polymer coating can be readily applied to a variety of commonly used biomedical materials using this straightforward method, highlighting the versatility of the approach. This work provides a facile and broadly applicable strategy for developing antifibrotic coatings, which has the potential to expand the design of surface modifications aimed at improving the performance of biomedical implants.

bioengineering↗

bioRxiv2026

Alternative respiratory electron transport pathways drive differential aminoglycoside susceptibility

The bacterial electron transport system (ETS) is a highly branched and modular network that interfaces directly with the proton motive force (PMF) to drive ATP synthesis, solute transport, and cellular homeostasis (1-5). Distinct ETS branches differ in their capacities for proton translocation, redox balancing, and membrane polarization. The rewiring of cellular energetics has emerged as a recurrent strategy through which bacteria attenuate drug efficacy by shifting metabolic states, reducing membrane potential, and suppressing reactive oxygen species-linked killing mechanisms (6, 7). Here, we probe the interplay between respiratory routes and antibiotic susceptibilities.

microbiology↗

bioRxiv2026

Generative Augmentation Reveals Previously Overlooked Signals in Transcriptomic Datasets

Identifying robust gene expression signatures from transcriptomic studies with small sample sizes remains one of the most persistent challenges in computational biology. Gene expression datasets have thousands of features but only a handful of biological samples. This presents the classic p >> n imbalance, which limits statistical power and makes it difficult to discover reliable biomarkers. In imaging, generative models such as GANs, VAEs, and diffusion models have demonstrated promising applications in data augmentation, but their usefulness for omics data has not been systematically tested. More importantly, no existing framework integrates synthetic data generation, stability-aware signature discovery, and multi-source biological validation into a single pipeline. In this work, we present GeneLift, with the hypothesis that a computational pipeline of generative data augmentation, stability testing, and evaluating biological evidence will aid novel gene-signature discovery in small-cohort transcriptomic studies. We tested this hypothesis across 36 microarray datasets covering five diseases: sepsis, breast cancer, ovarian cancer, tuberculosis, and diabetes. A component-wise testing of GeneLift revealed that Gaussian Mixture Models (GMMs) outperformed deep generative approaches and faithfully reproduced gene-level distributions. By a novel approach of titrating the level of augmentation, we identified biologically meaningful gene candidates that did not appear in the original, underpowered analyses. We also developed BayesScore, a Bayesian posterior probability of gene-disease association computed from PubMed co-occurrence, which both recovers well-characterised disease genes missed by standard differential expression and surfaces candidates whose disease relevance was independently confirmed in subsequent publications, with lead times of up to 18 years between the source dataset and the first disease-specific citation. GeneLift is freely available at tavlab-iiitd/GeneLift. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=103 SRC="FIGDIR/small/720348v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@13c8aeeorg.highwire.dtl.DTLVardef@1c5277corg.highwire.dtl.DTLVardef@a35664org.highwire.dtl.DTLVardef@17cdc48_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2026

One-Pot NADH-Mediated Physiological Redox-Controlled Synthesis of Papain-Stabilized Copper Nanoclusters with Preserved Bioactivity for Efficient Drug Delivery

Protein-protected copper nanoclusters are promising candidates for bioimaging and therapeutic applications. However, harsh reducing conditions required for their synthesis, compromising the proteins structural integrity and bioactivity. Here, we report a one-pot, physiologically compatible aqueous synthesis for papain-protected copper nanoclusters (Pap-CuNCs) with blue photoluminescence and excellent photostability using nicotinamide adenine dinucleotide (NADH) as a biological reducing agent. The mild conditions (ambient temperature, neutral pH) enable the simultaneous formation of a metallic Cu0 core while stabilizing the helical content of the protein. This approach introduces a physiologically redox-controlled strategy for nanocluster formation, establishing physiological redox chemistry as a governing principle for controlling nanoscale structure and protein conformational stability. Spectroscopic and microscopic studies have demonstrated the presence of crystalline nanoclusters with a protein corona that undergoes -helical stabilization as revealed by circular dichroism. Notably, atomistic simulation studies reveal preferential binding of the copper core in the proteins active site, enhancing the -helical content of papain, consistent with experimental observations. Functionally, the Pap-CuNCs possess biocompatibility and serve as an effective delivery platform for 5-fluorouracil, leading to a 50-fold decrease in IC50 for HeLa cells without causing cytotoxicity to normal cells. This establishes a generalizable framework for bio-integrated nanocluster design under biologically compatible conditions. TOC Text O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=44 SRC="FIGDIR/small/719779v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1ca9292org.highwire.dtl.DTLVardef@5cd82aorg.highwire.dtl.DTLVardef@173ed2forg.highwire.dtl.DTLVardef@1d8c30c_HPS_FORMAT_FIGEXP M_FIG C_FIG NADH-mediated physiological redox synthesis of papain-stabilized copper nanoclusters with enhanced -helical stability. This bio-integrated nanoplatform facilitates drug loading and delivery, resulting in a [~]50-fold increase in cytotoxicity in cancer cells while maintaining excellent biocompatibility toward normal cells.

bioengineering↗

bioRxiv2026

A biobank-scale method for learning modulators of gene-environment interaction underlying human complex traits from multiple environmental exposures

It is increasingly recognized that genetic effects on complex traits and diseases are shaped by environmental context. Biobanks that measure diverse environmental exposures alongside genotypes and phenotypes at scale enable systematic study of gene-environment (GxE) interactions. Existing approaches, however, are limited in their ability to accurately model polygenic GxE involving many exposures across genome-wide genetic variants. It is unclear which exposure combinations are relevant for a given trait while distinguishing true interactions from environment-dependent heteroskedastic noise. To address these challenges, we develop Efficient multi-eNvironmental Gene-environment Interaction iNference Estimator (ENGINE), a supervised variance-component framework that learns an embedding that combines multiple environmental exposures while jointly estimating additive, GxE, and heteroskedastic noise components. To enable biobank-scale inference, ENGINE makes a single pass over the genotype matrix to cache genotype-dependent summaries, then assembles normal-equation components and gradients at each iteration. In simulations, ENGINE controls type I error rates, achieves high power, and accurately recovers the environmental embedding while remaining efficient at biobank-scale. Applied to five complex traits paired with lifestyle exposures in N = 291,273 unrelated white British individuals and M = 454,207 common SNPs (MAF> 0.01) from the UK Biobank, ENGINE recovered GxE variance that was on average 1.4-fold larger than that captured by a single exposure and 5.5-fold larger than that captured by the first principal component of the exposures.

genetics↗

bioRxiv2026

Cost adjusted hierarchical defense strategies enables stratified oxidative stress tolerance

Organisms employ diverse adaptive strategies to withstand environmental stresses, yet how bacteria tailor their responses to different magnitudes of the same stressor remains poorly understood. This question is particularly salient for oxidative stress, which varies substantially across physiological niches and exerts distinct selection pressures on colonizing bacterial populations. Here, we used four separate adaptive laboratory evolutions of Escherichia coli across multiple paraquat concentrations and genetic backgrounds to dissect how cells adapt to varying levels of superoxide stress. Integrating multi-omic analyses with tailored genome-scale metabolic modeling, we identify two fundamentally distinct tolerance strategies based on flux control and cellular resource optimization. Under low superoxide stress, blocking polyamine transporter that is hijacked for paraquat influx suffices to maintain redox balance. In contrast, higher stress levels activate an energetically demanding program involving enhanced detoxification of reactive radicals and active efflux that allows cells to maintain higher aerotype. We further demonstrate that flux regulation establishes a primary defense layer, upon which metabolic repair systems act to provide additional fitness advantages. Together, our findings reveal how E. coli differentially engages modular stress-response programs depending on stress magnitude, offering generalizable insights into the principles governing dynamic bacterial adaptation.

microbiology↗

bioRxiv2025

The anti-retroviral therapy emtricitabine affects skeletal muscle DNA methylation and transcriptome patterns in a male HIV mouse model

BackgroundAlthough antiretroviral therapies (ART) have substantially reduced HIV-associated mortality, the increased lifespan achieved by widespread ART deployment has revealed that HIV infection is linked to an unexplained earlier onset and increased incidence of aging-associated conditions like sarcopenia. Complex syndromes, like sarcopenia, often arise from a combination of genetic and environmental factors, so in this study, we investigated effects of short-term treatment with emtricitabine (2,3-dideoxy-5-fluoro-3-thiacytidine; FTC), an FDA approved ART, on skeletal muscle DNA methylation patterns and transcriptome-wide responses in a male murine model of HIV phenotypic biology (Tg26 mice). MethodsWe treated 6 month old male Tg26 (+/-) mice or wildtype (WT) littermates on a C57BL/6 genetic background with FTC in the drinking water for one month; control groups received drinking water vehicle alone (VEH). Muscle function and body composition were measured longitudinally. Skeletal muscle methylation patterns, transcriptional changes, and histological features were quantified at sacrifice. ResultsAlthough neither gross structural nor functional muscle deficits were observed in this short-term study with ART usage, relative decreases in muscle endurance measured by hang time over the study were 2-fold more severe in the Tg26 as compared to WT mice (p=0.0453), and markers of myogenic cell maturation (Myf5, Myf6) were disrupted in the Tg26 HIV model as compared to WT littermates in a manner exacerbated by FTC treatment. Fat mass, measured by DXA, also tended (p=0.085) to be uniquely increased by FTC treatment in the Tg26 mice over the study. Differential methylation patterns and pathway enrichment data suggested that the presence of an HIV phenotype and exposure to an ART regimen altered the methylation status in skeletal muscle genes such as Camk2B, Pcolce2 and Lima1 in a manner consistent with promoting eventual functional impairment in muscle. Additionally, RNAseq revealed differential gene expression profiles and key regulatory pathways including cellular differentiation, regulation of lipid metabolism, and neuroactive ligand-receptor interactions. Lipodystrophy-related genes including LEP, ADIPOQ and PPAR involved in fat distribution and metabolism along with skeletal genes related to regulation of muscle strength were affected by the presence of an HIV phenotype and ART treatment. ConclusionsThe current study provides insights into mechanisms by which a clinically relevant ART may influence DNA methylation and transcriptome changes in skeletal muscle in the context of HIV biology. The differentially regulated pathways suggest novel targets for understanding, and eventually abrogating, the harmful effects of long-term ART use in PLWH on skeletal muscle mass and function.

cell biology↗

bioRxiv2025

Native Olympia Oysters in San Francisco Bay: Microbiome and Antimicrobial Resistance Derived Insights Into Restoration

Restoration of Olympia oyster (Ostrea lurida) reefs can deliver ecological and public-health co-benefits. Characterization of the microbiome can provide valuable insights towards reef health but remains underused especially in San Francisco Bay. To overcome this gap, we applied shotgun metagenomics to oyster tissue, water, sediment, and biofilm collected from five San Francisco Bay sites (Loch Lomond, Point San Quentin, Brickyard Park, China Camp, Dunphy Park; Nov 2023) to profile community structure, Vibrio diversity, and antimicrobial-resistance (AMR) potential. Evaluating beta-diversity based on Bray-Curtis dissimilarities, we saw strong clustering by sample type (PERMANOVA R2 = 0.645, p = 0.001) and no significant clustering by location (R2 = 0.068, p = 0.937). Alpha diversity (Shannon) differed by matrix (Kruskal-Wallis p = 0.000416), with sediment and water highest and oyster tissues lowest. Vibrio taxa occurred at low relative abundance across matrices but were slightly enriched in biofilms and tissues; several Vibrio phages were also detected, consistent with potential (but unconfirmed) top-down control. Resistome profiling revealed a long-tailed distribution dominated by the tetracycline efflux pump tet(C) (70,049 reads) and APH(3)-Ia (4,498 reads), alongside multidrug efflux components (acrAB/-D, mdtABC/H/F/P, mdfA, MexF/MexW). Biofilms were AMR hotspots, while oyster tissues uniquely harbored Vibrio cholerae varG (Subclass B1 {beta}-lactamase). Collectively, our results indicate that matrix, not geography, structures reef microbiomes, that Vibrio is present but scarce, and that biofilms concentrate AMR potential. We propose a microbiome-integrated monitoring approach that stratifies by matrix, prioritizes biofilm resistome tracking, and targets Vibrio surveillance in oysters to align restoration performance with ecosystem-health safeguards.

genomics↗