Biology subjects

Ghosh, A.

Publications and source records attributed to Ghosh, A..

At least 19 recordsLinked to original sources

bioRxiv2026

FMNL1 polymerized actin filaments complete mitochondrial division downstream of Golgi-derived vesicles

Mitochondrial division includes contributions from several organelles yet the molecular machinery that facilitates the final Drp1-induced scission of the OMM is largely elusive. We elucidate that FMNL1, a formin family actin assembly factor, is recruited to the mitochondrial division sites through the TGN vesicles in a calcium dependent pathway to complete mitochondrial division. FMNL1 is activated specifically by Cdc42 that generates actin filaments to complete division of the OMM in Drp1 and actin-dependent pathway. Depletion of FMNL1 enhances early events in mitochondrial division pathway characterized by enhanced ER-mitochondrial contacts and increased Drp1 and TGN vesicles on mitochondria which still results in failed mitochondrial division.

cell biology↗

bioRxiv2026

Astrocytic sEH-EET signaling regulates microglial lysosomal function and suppresses the STING-Type I interferon pathway in Alzheimer's disease

Background: The development of {beta}-amyloid (A{beta}) pathology in Alzheimer's disease (AD) is accompanied by profound changes in astrocytes and microglia and associated neuroinflammation. Soluble epoxide hydrolase (sEH), which degrades anti-inflammatory epoxyeicosatrienoic acids (EETs), is elevated in the AD brain, yet how EETs restrain inflammation remains poorly understood. Methods: We performed single-nucleus RNA sequencing (snRNA-seq) on brains from wild-type, sEH knockout, 5xFAD, and 5xFAD; sEH knockout mice, and used primary mouse microglia and human induced pluripotent stem cell (iPSC)-derived microglia to define the underlying mechanism. To test cell-type-specific contributions, we generated astrocyte- and endothelial-specific she knockout mice and crossed them with 5xFAD mice. Results: Genetic disruption of sEH in 5xFAD mice markedly reduced the abundance of a type I interferon (IFN)-responsive microglial subcluster and lowered phospho-STING (pSTING) levels. In primary microglia, supplementation with 11,12-EET attenuated STING activation and IFN target gene expression; blocking lysosomal acidification abolished this effect and caused pSTING to accumulate, identifying lysosomal degradation as a critical route for terminating STING signaling. 11,12-EET also enhanced microglial lysosomal acidification and A{beta} phagocytosis. Astrocytic, but not endothelial, disruption of sEH recapitulated the reductions in A{beta} pathology and microglial STING activation seen in global sEH-deficient mice, identifying astrocytes as the major cellular source of EETs regulating this pathway. Conclusion: We define an astrocyte-microglia axis in which astrocytic sEH limits EET availability and thereby sustains microglial STING signaling. By promoting lysosomal clearance of pSTING, EETs suppress type I IFN signaling and enhance microglial A{beta} clearance, highlighting sEH inhibition as a therapeutic strategy targeting both neuroinflammation and lysosomal dysfunction in AD.

neuroscience↗

bioRxiv2026

A Computational Framework for Understanding HCV Infection and Associated Lipid Dynamics

Hepatitis C virus (HCV) infection is strongly intertwined with host lipid metabolism and is frequently associated with hepatic steatosis, particularly in genotype-specific cases where lipid accumulation reflects direct viral effects rather than host metabolic comorbidities. Despite extensive clinical and experimental evidence, a quantitative framework capturing the bidirectional coupling between viral dynamics and lipid metabolism remains lacking. In this work, we develop a comprehensive mathematical model that integrates HCV infection dynamics with intracellular lipid regulation. The framework combines a reaction diffusion system for spatial viral spread with a coupled metabolic module describing lipid influx. Numerical simulations highlight the role of lipid feedback in shifting infection outcomes toward persistence and recurrent oscillations, demonstrating that lipid accumulation acts as a critical driver of viral amplification. The model also highlights the critical role of immune memory to study acute and chronic phase and successfully reproduces observed viral RNA trajectories. Overall, the framework provides mechanistic insights into HCV dynamics and offers a general modeling approach for studying virus metabolism interactions in liver disease.

cell biology↗

bioRxiv2026

Early-life vancomycin and meropenem treatment exert distinct effects on microbiota-gut-brain axis signalling in zebrafish larvae

The microbiota-gut-brain axis is a bidirectional communication pathway between the gastrointestinal tract, gut microbiota and the central nervous system, that influences host neurobiology, metabolism and behaviour. Although germ-free and antibiotic-treated animals demonstrate a role for microbial signalling in mood and behaviour, mechanisms linking microbiome disruption to altered neural signalling during early development remain incompletely understood. Here, we investigated the impact of antibiotic-induced perturbations of the gut microbiota on behaviour, neurotransmitter levels as well as central and peripheral metabolism in 5 dpf zebrafish larvae, an established neurodevelopmental model. Larvae were exposed to the broad-spectrum antibiotic meropenem, the Gram-positive-directed antibiotic vancomycin, or their combination, and assessed gut microbiota composition, behaviour, neurotransmitter levels and metabolite profiles. All treatments altered microbial community composition, although the extent differed markedly, with pronounced restructuring after meropenem and combination treatment and more subtle changes after vancomycin. Behavioural analysis using the light-dark transition assay revealed reduced centre locomotion during the dark phase in all treated groups, without a general reduction in swimming activity, consistent with anxiety-like behaviour. These behavioural changes were accompanied by reduced expression of serotonergic genes and widespread central and peripheral metabolic disruptions in all antibiotic-treated groups. Treatment- and tissue-specific effects included suppression of the arginine-polyamine pathway in the brain following vancomycin treatment and increased peripheral glutamate, GABA and L-DOPA levels after meropenem exposure. Together, these findings demonstrate that early-life microbiome perturbation reshapes behaviour, neurotransmitter levels, and host metabolism in zebrafish larvae. In addition, we identified candidate metabolic pathways through which the microbiome may influence neurodevelopment.

neuroscience↗

bioRxiv2026

Root exudates enhance the ecological fitness of a non-native PGPR and reshape rhizosphere microbiome assembly

Root exudates play critical roles in rhizosphere microbiome assembly. Nevertheless, the molecular mechanisms by which plant growth-promoting rhizobacteria (PGPR) perceive these signals, adapt to the rhizosphere, and influence native microbial communities remain poorly understood. Here, using maize (Zea mays cv. Early Golden Bantam) and the rhizobacterium Priestia aryabhattai AB211, we took a multi-omics approach combining metabolomics, bacterial transcriptomics and proteomics, and rhizosphere metagenomics to elucidate the mechanism underlying this process. Maize root exudates were enriched in diverse carbon and nitrogen metabolites that promoted bacterial growth and induced extensive molecular reprogramming of pathways involved in nutrient acquisition, chemotaxis, motility, stress adaptation, and plant growth promotion, thereby enhancing rhizosphere competence. In field-conditioned soil, AB211 persisted as a core member of the maize rhizosphere microbiome, promoted early seedling growth, and reshaped microbial community composition and function. Root exudates-primed (RE-primed) AB211 further enhanced the enrichment of microbial functions associated with nutrient cycling, quorum sensing, plant growth promotion, and rhizosphere fitness, highlighting the role of root exudates in modulating the rhizosphere-adaptative potential of beneficial bacteria. These findings establish a mechanistic framework linking root exudates composition with PGPR adaptation and microbiome assembly, providing a foundation for engineering ecologically adapted microbial inoculants to improve crop productivity and sustainable agriculture.

microbiology↗

bioRxiv2026

Ligand binding remodels the oligomeric state and active site of Klebsiella pneumoniae azoreductase

Azo dyes are widespread in the environment, and humans ingest a range of these dyes present in food and drugs. The human gut microbiome significantly impacts the fate of ingested azo dyes primarily through the reduction of the azo bond (R-N=N-R'). Flavin-dependent azoreductases have been considered the key enzymatic drivers of this process. To challenge this paradigm, we constructed a sequence similarity network of known azoreductases and focused on AzoA of Klebsiella pneumoniae, a central representative within the gut microbiome cluster. Unexpectedly, K. pneumoniae AzoA displayed relatively low in vitro activity against a range of azo compounds. While the physiological implications remain unclear, these findings are consistent with the possibility that non-enzymatic mechanisms contribute substantially to azo compound reduction in the gut. Furthermore, structural characterization of AzoA, as a holoenzyme and in its substrate-bound state, revealed a previously unrecognized ligand-coupled mechanism involving remodeling of the active site and oligomeric state.

biochemistry↗

bioRxiv2026

Soluble guanylyl cyclase subunits act as Hsp90 co-chaperones to ensure the expression and functional maturation of hemeproteins in mammalian cells

The cofactor Fe-protoporphyrin IX cofactor (heme) performs many functions in biology. Animal cells must stabilize their newly generated heme-free (apo)-hemeproteins and deliver mitochondrial heme to them so they can mature to functional form. Glyceraldehyde 3-phosphate dehydrogenase (GAPDH) typically accomplishes the heme deliveries, and for many apo-hemeproteins, heat shock protein 90 (Hsp90) drives their heme insertions. We previously observed hemeproteins express poorly in a cell line (COS-7) that does not express soluble guanylyl cyclase (sGC), a heme-binding enzyme that typically functions through its cGMP generation. To understand sGC involvement, we expressed four hemeproteins, Hemoglobin beta (Hb{beta}), Myoglobin (Mb), Indoleamine 2,3-dioxygenase 1 (IDO1), and Tryptophan 2,3-dioxygenase (TDO) in a cell line expressing sGC (HEK293) or in two cell lines (COS-7, DU145) that do not. We assessed hemeprotein expression levels, their abilities to acquire heme, and when relevant if these facets could be rescued by co-expressing individual sGC subunits, including variants with defects in either sGC heme binding, Hsp90 association, heterodimerization, or cGMP production. We found that co-expression of either sGC subunit was essential for three of the four apo-hemeproteins to accumulate in the COS7 and DU145 cells and acquire heme. This did not involve heme binding, heterodimer formation, or cGMP generation by the sGC subunits, and instead depended on a subunits ability to recruit Hsp90 and GAPDH to the apo-hemeproteins via their own Hsp90 binding. Recruiting Hsp90 and GAPDH to apo-hemeprotein clients to ensure they can accumulate and mature to functional form broadens our understanding of sGC and Hsp90 functions in biology.

cell biology↗

bioRxiv2026

ASAREE: An Analytical Sandbox for Agentic AI Research, Engineering, and Experimentation

Summary: Agentic AI platforms enable the engineering of autonomous workflows but are not designed for experimentation and hypothesis testing. ASAREE (Analytical Sandbox for Agentic AI Research, Engineering, and Experimentation), is an open-source platform to address this gap. ASAREE creates agents, connects to MCP servers and tools, and designs factorial experiments through a visual interface or Python SDK. It records a full provenance trace for every run and routes all model calls through a provider-agnostic bridge that supports local deployments, ensuring data privacy. As a use-case, we use ASAREE to evaluate key design choices in a mutli-agent machine learning pipeline. Across a 2 x 2 x 2 factorial design, more advanced models, greater reasoning effort, and critic agent use significantly increased compute time, token use, cost, and feature count without improving predictive performance. The lowest-cost baseline, Claude Sonnet 5 with medium effort and no critic, achieved the highest mean PR AUC while Claude Opus 5 with extra high effort and a critic agent cost 15.5x more (USD) and ran 13.1x longer while performing worse on average. These findings highlight ASAREE as a robust framework for evaluating agentic system performance and resource efficiency.

bioinformatics↗

bioRxiv2026

Loss of PTPRB function remodels VEGFR1 activation in tumors overexpressing the receptor tyrosine kinase

The VEGF Receptor-1 (VEGFR1) is a deceptive receptor tyrosine kinase (RTK). In early embryonic development, VEGFR1 negatively regulates angiogenesis by acting like a decoy receptor. Ligand binding transiently phosphorylates the receptor and induces a weak activation, even at high receptor density. Yet, in multiple cancers, overexpression of VEGFR1 plays a central role in tumor vascularization and growth. Unlike many pro-oncogenic RTKs, extensive patient data analysis revealed no somatic mutation in VEGFR1 that may spontaneously activate the tyrosine kinase. The mechanism by which VEGFR1 is activated in cancers has remained an open question for more than two decades. Here, we evaluated the multi-omics profiles of VEGFR1 and its regulators in a pan-cancer database. We observed an inverse correlation between VEGFR1 and PTPRB phosphatase expression in KIRC patients and disease outcome. We observed that patients overexpressing VEGFR1 and deficient in PTPRB expression have a lower likelihood of survival. Using super-resolution single-cell imaging, we discovered that inhibiting PTPRB spontaneously activates VEGFR1 by inducing ligand-independent dimerization, possibly by shifting the equilibrium toward the active state. PTPRB inhibition induces sustained, ligand-dependent phosphorylation of VEGFR1, which may promote tumor vascularization. We conclude that a subtle phosphatase imbalance is fundamental in determining VEGFR1s role in pathological angiogenesis in tumors.

biochemistry↗

bioRxiv2026

Mitochondrial phosphate carrier-dependence of mitochondrial calcium chelation and respiration in skeletal muscle

The past decade has seen remarkable progress in the molecular resolution of the influx and efflux components of mitochondrial Ca2+ handling, but little progress in matrix Ca2+ chelation that is central to mitochondrial calcium signaling. Among possible chelators, inorganic phosphate (Pi) is dynamic, and its uptake can lessen during Ca2+ uptake the rundown of the membrane potential, the primary driving force for Ca2+ uptake. Thus, PiC, the major mitochondrial Pi transporter, is well-positioned to regulate mitochondrial Ca2+ handling. To test this, we depleted (KD) PiC in murine skeletal muscle. We show that PiC depletion enhances the matrix free Ca2+ rise across a range of Ca2+ uptake activities, and surprisingly, causes elevated mitochondrial Ca2+ uptake, which seems to arise from an increased abundance of the mitochondrial Ca2+ uniporter. With protein levels of non-mitochondrial Ca2+ handling proteins unaltered, the greater mitochondrial Ca2+ uptake may drive a suppressed cytoplasmic Ca2+ response to tetanic stimulation, via lesser Ca2+-mediated positive feedback on Ca2+ release channels, contributing to an exercise deficit in KD mice. Alternatively, less buffering of matrix Ca2+ might be beneficial. We test these possibilities by lowering MCU, the uniporters pore forming subunit, in skeletal muscle of adult PiC KD mice, and find a worsened exercise deficit. This study establishes the requirement for PiC to maintain a bound fraction of Ca2+ in the matrix, and reveals a fitness benefit for elevated [Ca2+]m in striated muscle depleted of PiC.

biochemistry↗

bioRxiv2026

Macronutrient balance generates distinct nutritional optima for growth, immune function and stress responses in the specialist herbivore Plutella xylostella

Nutrition plays a fundamental role in insect physiology, yet how variation in dietary macronutrient balance shapes multiple physiological functions remains poorly understood. Using the Geometric Framework for Nutrition, we examined how dietary protein and carbohydrate composition influence growth, immunity and stress physiology in the specialist herbivore Plutella xylostella. Growth depended jointly on protein and carbohydrate availability, whereas immune and oxidative stress traits showed distinct response surfaces across the tested nutrient landscape. Total hemocyte counts and phenoloxidase activity were highest at intermediate protein levels, and survival following Bacillus thuringiensis challenge was likewise associated primarily with protein availability, pointing to a shared nutritional basis for immunity and pathogen resistance. Antioxidant and detoxification enzymes showed trait-specific nutrient responses, indicating that different physiological systems are favored by different macronutrient combinations. No single protein-carbohydrate ratio within the tested landscape simultaneously supported growth, immune performance, and oxidative homeostasis, highlighting trade-offs associated with nutrient allocation across physiological systems. These findings advance understanding of how nutrient-dependent mechanisms coordinate and constrain multiple physiological functions in a specialist herbivore.

ecology↗

bioRxiv2026

A large-scale crowd-sourced annotated acoustic dataset of Indian fauna

Global rates of biodiversity loss warrant conservation action and monitoring at large geographic scales. Conservation technologies such as acoustic monitoring in conjunction with deep learning now enable us to monitor wildlife simultaneously across space and time. However, for a significant proportion of biodiversity in tropical regions, we cannot yet rely on automated recognition approaches because we lack acoustic templates to robustly train deep learning algorithms. In this paper, we relied on a novel participatory approach, enlisting researchers, conservation practitioners, and nature enthusiasts to create a unique crowd-sourced, open-access dataset of acoustic annotations across taxonomic groups for biodiversity in India. Our dataset comprises 3311 minutes of strongly labelled data (bounding boxes or annotations for a species vocalization) and 2504 minutes of weakly labelled data (indicating the presence of a species within an audio file but lacking bounding boxes) for 518 species across India, spanning 25 of 36 states and union territories. We present metadata and code for data processing and highlight the strengths of a participatory approach to biodiversity monitoring.

ecology↗

bioRxiv2026

Coupled Cell-Intrinsic and Microenvironmental Heterogeneity Drives Divergent Trajectories in Castration-Resistant Prostate Cancer

Castration-resistant prostate cancer emerges from coupling between cell-intrinsic heterogeneity and microenvironmental constraints. Mechanistically dissecting this coupling, rather than either factor in isolation, is the central aim of this study. To systematically study the effect of intrinsic and extrinsic spatial axes on disease trajectories, we developed an integrated multiscale framework: a cellular signaling model (MHS) parameterized with TCGA genomic data from control, biochemical recurrence (BR), and treatment-resistant (TR) cohorts, coupled to a spatial agent-based model (ABM). Machine learning surrogates trained on the MHS model identified PTEN, MDM4, and AR as dominant intrinsic drivers, using SHAP-based feature ranking. Clinical validation via Kaplan-Meier and Cox regression across cBioPortal cohorts confirmed these rankings: AR alterations (median OS 20 vs. 86 months), PTEN loss (54 vs. 77 months), and MDM4 amplification (33 vs. 75 months) predicted poor overall survival outcomes independently. At the tissue scale, ABM simulations were run to study the effect of microenvironmental (cell-extrinsic) factors such as physical confinement, androgen uptake kinetics, and adhesion-motility strength, on disease progression. This spatiotemporal analysis revealed that identical genetic alterations produce varied selection outcomes depending on microenvironmental context. Extending this coupling logic to the individual patient level, we parameterized the MHS model using gene expression profiles from 14 patients in the EUREKA1 prospective registry. Patient-specific androgen sensitivity ratios, the ratio of net cell growth under high versus low testosterone, stratified patients by model-predicted androgen dependence without requiring longitudinal PSA observations and showed that PTEN deletion shifts the proliferative response toward androgen independence in a patient-specific magnitude set by the broader expression background. This provides a model-based route from genomic data at diagnosis to personalized prediction of ADT resistance risk. Together, these findings establish that CRPC emergence is an emergent property of the intrinsic-extrinsic coupling, that neither molecular nor spatial analyses in isolation can predict clinical trajectories, and that mechanistic integration of both is required for accurate patient stratification.

systems biology↗

bioRxiv2026

amR: an R package suite to predict antimicrobial resistance in bacterial pathogens

MotivationIdentifying bacterial antimicrobial resistance (AMR) is critical for diagnostics and treatment, but resistance is a complex trait arising from myriad mechanisms spanning multiple molecular scales. Existing computational approaches often function as black boxes and rarely explore cross-species or multi-drug patterns. We developed amR, an integrated R package suite that provides a complete framework from bacterial genome data curation to interpretable AMR predictions, enabling identification of resistance mechanisms across species and drugs. ResultsThe amR R package suite contains three modular packages. amRdata downloads genomes and paired antimicrobial susceptibility testing data from BV-BRC and processes them, constructs pangenomes, and extracts features at gene/protein cluster, protein domain, annotated Clusters of Orthologous Groups and ResFinder AMR-associated features, and structural variant scales; data are stored in memory-efficient formats (Parquet, DuckDB). amRml trains interpretable machine learning models per species-drug combination, calculates feature importance and performance metrics, and provides rich ground for hypothesis generation and mechanism discovery. amRviz provides an interactive Shiny dashboard to explore metadata distributions and model performance across species and drugs, visualize top predictive AMR features, and analyze cross-model patterns across geographic/temporal strata. We apply the suite to Shigella sonnei, achieving a median Matthews Correlation Coefficient of 0.89 across 23 drugs and drug classes. With thousands of genomes, multi-scale features, and interpretable models, amR provides an accessible, comprehensive framework for AMR research. The amR package suite is installable via GitHub (https://github.com/JRaviLab/amR; BSD-3-Clause license).

bioinformatics↗

bioRxiv2026

Pharmacological Stratification of Public Bioactivity Databases: A Reusable, OECD-Anchored Curation and Benchmarking Framework Demonstrated for Opioid Receptors

Public bioactivity databases are heterogeneous not only in measurement type, where binding affinities and functional potencies are reported on different scales, but in pharmacology: the same compound and target can carry agonist, antagonist, or inhibitor records measured through binding displacement, cAMP, {beta}-arrestin, or [35S]GTP{gamma}S readouts that quantify different biological events. Pooling these records produces models whose output is detached from any coherent pharmacological claim. Prior work has standardized bioactivity at scale and quantified the noise from mixing measurement types, but pharmacological mechanism and assay-readout class have not been treated as a primary axis of large-scale curation. This study presents an auditable, OECD-anchored framework that stratifies public records by action type and assay readout before modeling, converting heterogeneous data into externally validated, interpretable QSAR tasks that compose with existing standardization resources rather than replacing them. The framework is demonstrated on the four opioid receptors (MOR, DOR, KOR, and nociceptin/orphanin FQ, NOP). Four public sources were reconciled into 72,148 merged records and 50,977 curated measurements spanning 19,585 compounds, each carrying auditable attributes for source agreement, endpoint meaning, pharmacology class, assay readout, and trust tier. Receptor-level binding tasks formed a compact benchmark with strong locked external performance, including KOR pK (R2 = 0.79, n = 798) and DOR pK (R2 = 0.77, n = 736). Pharmacology- and readout-resolved functional endpoints yielded externally validated strata that pooled labels would obscure, including a MOR antagonist functional-inhibition endpoint (R2 = 0.86, n = 110) and agonist potency endpoints for DOR, KOR, and MOR (R2 up to 0.81). Comparison against a fully pooled baseline shows that pooled models either match stratified models on coherent endpoints or reach a deceptively high R2 on functional-IC50 endpoints by training predominantly on binding-displacement records, so the pooled number predicts affinity rather than functional activity. SHAP attribution indicates that binding and functional potency encode partially distinct structure-activity signals. The dataset contract, not model performance alone, defines the validity and scope of a QSAR claim, and stratification is a precondition for a functional model to support a defensible claim. Curation logic, derived tables, frozen data, and reproducibility artifacts are released.

bioinformatics↗

bioRxiv2026

Passive acoustic monitoring of Ensiferan calling diversity in a sub-tropical forest of Northeast India.

Ensiferans are nocturnal insects (Order Orthoptera) that produce mating advertisement calls using stridulatory organs on modified forewings. These calls, typically made by males, are species-specific and serve as indicators of forest health. In biodiverse ecosystems like the subtropical forests, caller density is high, and ecological constraints such as intra- and interspecific acoustic competition, masking interference, and predation pressure can influence calling behavior. These pressures lead to variation in call structures and differences in spatiotemporal acoustic space use, leading to variations in community call type composition across the seasons. Passive Acoustic Monitoring (PAM), a non-invasive and cost-effective technique, is widely used for long-term monitoring in vertebrate taxa, but is less commonly applied to terrestrial invertebrates. In this study, we employed PAM to quantify acoustic diversity, acoustic space use, separation of different call types, seasonal calling patterns, and seasonal variation in call type composition among nocturnal Ensiferan callers. Year-round recordings were conducted using AudioMoth devices in the Khasi Hills of Meghalaya, part of the Indo-Burma Biodiversity Hotspot, at a 48 kHz sampling rate. Acoustic samples were processed using Raven Pro software. We identified 33 distinct call types, mutually distinctly differing in spectral, temporal, or both parameters. Principal Component Analysis revealed fine-scale separation of call types. While there were seasonal shifts in call types, with the dry season having the least number of callers, overall call type composition remained stable across pre-monsoon and monsoon seasons. Acoustic Space Use (ASU) analysis indicated greater use of lower frequency bands consistent with ground cricket presence, as well as seasonal variation in spectral occupancy. This foundational study is the first of its kind in Northeast India and demonstrates the potential of PAM in studying invertebrate soundscapes.

zoology↗

bioRxiv2026

Quorum-Sensing Stimulation and Phytochemical Quenching Reshape Biofilm-Associated Gene Expression in Salmonella enterica

Quorum sensing (QS) influences biofilm formation, persistence and stress adaptation in Salmonella enterica. Although Salmonella does not synthesise acyl-homoserine lactones (AHLs), it can detect exogenous AHLs through the LuxR homolog SdiA, allowing it to respond to interspecies signalling cues in polymicrobial environments. This study investigated whether external QS stimulation and quorum-modulatory compounds reshape biofilm-associated transcriptional programmes in S. enterica serovar Enteritidis (SE) and S. Typhimurium ST14028. Biofilm formation was assessed using the crystal violet assay, while expression of QS-, biofilm-, adhesion-, motility- and invasion-associated genes (sdiA, csgD, flgG, fimA, rck, invA, bapA and hilA) was quantified using multiplex RT-qPCR and analysed by the {Delta}{Delta}Ct method, with 16S rRNA used for normalisation. In parallel, molecular docking was used to explore the predicted interaction of C8-HSL, established quorum-quenching agents and selected phytochemicals with the Salmonella SdiA ligand-binding region. Exposure to exogenous C8-HSL increased biofilm biomass and induced coordinated upregulation of QS- and biofilm-associated genes in both serovars, supporting the role of external AHL sensing in Salmonella biofilm regulation. In contrast, farnesol and furanone produced broad transcriptional repression accompanied by reduced biofilm biomass. Selected natural products, including epigallocatechin gallate (EGCG), thymoquinone, garlic extract, turmeric extract and aloe-emodin, produced moderate antibiofilm effects and partial downregulation of QS-associated transcriptional responses, suggesting possible interference with biofilm-regulatory signalling pathways. Molecular docking further supported this interpretation by identifying potential interactions between selected quorum-modulatory compounds and the predicted SdiA binding region, providing a plausible mechanistic basis for their observed biological effects. Notably, responses differed between SE and ST14028, indicating strain-dependent sensitivity to QS stimulation and quorum-modulatory treatments. Collectively, these findings suggest that exogenous AHL sensing contributes to strain-dependent transcriptional reprogramming of Salmonella biofilm-associated genes and that selected phytochemicals may act as preliminary quorum-modulatory candidates. This study supports further investigation of SdiA-mediated signalling as an anti-virulence target for reducing Salmonella persistence in food-associated and clinical environments.

microbiology↗

bioRxiv2026

Putative G-Quadruplex Structures in Cancer-Dysregulated Circulating lncRNAs and their G4-mediated Identification of Protein Interacting Partners

Circulating long non-coding RNAs (lncRNAs) have emerged as compelling cancer biomarkers. However, the structural features that mediate their extracellular stability and protein interactions remain largely unexplored. Here, we present the first systematic investigation of G-quadruplex (G4) motifs within cancer-dysregulated circulating lncRNAs and exploit these structures as molecular handles to identify associated RNA-binding protein (RBP) networks. From 283 circulating lncRNAs curated from the Lnc2Cancer 3.0 database, putative G-quadruplex-forming sequences (PQSs) were identified computationally using QGRS Mapper and G4Hunter, yielding four prioritized candidates -- AGAP2-AS1, LINC00683, DLG1-AS1, and KRTAP5-AS1 -- spanning 2G to 4G architectures. In vitro transcribed PQSs were validated for parallel G4 formation by circular dichroism spectroscopy, native polyacrylamide gel electrophoresis with thioflavin T staining, and reverse transcriptase stop assays, conducted under both standard buffer and simulated body fluid conditions to approximate the circulatory milieu. Electrophoretic mobility shift assays and isothermal titration calorimetry demonstrated nanomolar-affinity interactions between the G4-containing RNA and human serum albumin (HSA), the most abundant circulating protein. Cross-referencing G4-interacting proteins from the G4IPDB database with lncRNA-protein associations from LncTarD and NPInter, combined with RPISeq interaction predictions, identified ten candidate RBPs. A STRING-based protein-protein interaction (PPI) network was constructed at a confidence threshold of [≥]0.7 and refined iteratively using experimental stability data to exclude proteins associated exclusively with the structurally weaker KRTAP5-AS1. The resulting network, centered on ELAVL1, IGF2BP1, hnRNPA2B1, and FUS, highlights a coordinated post-transcriptional regulatory module relevant to oncogenesis. This work establishes a novel, experimentally validated framework wherein G4 motifs serve as entry points for decoding the protein interactome of circulating lncRNAs, with implications for cancer diagnostics and RNA-targeted therapeutic strategies. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=64 SRC="FIGDIR/small/728349v1_ufig1.gif" ALT="Figure 1"> View larger version (25K): org.highwire.dtl.DTLVardef@1bba7dborg.highwire.dtl.DTLVardef@1095a53org.highwire.dtl.DTLVardef@1092eddorg.highwire.dtl.DTLVardef@1e3b7e7_HPS_FORMAT_FIGEXP M_FIG C_FIG

biochemistry↗