Biology subjects

Sharma, P.

Publications and source records attributed to Sharma, P..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Hypoxia-Induced Cardiopulmonary Remodeling and Recovery: Critical Roles of the Proximal Pulmonary Artery, Macrophages, and Exercise

Hypoxemia impairs cardiopulmonary function. We investigated pulmonary artery remodeling in mice exposed to chronic hypoxia for up to five weeks and quantified associated changes in cardiac and lung function, without or with subsequent normoxic recovery in the absence or presence of exercise or pharmacological intervention. Hypoxia-induced stiffening of the proximal pulmonary artery stemmed primarily from remodeling of the adventitial collagen, which resulted in part from altered inter-cellular signaling associated with phenotypic changes in the mural smooth muscle cells and macrophages. Such stiffening appeared to precede and associate with both right ventricular and lung dysfunction, with changes emerging to similar degrees regardless of the age of onset of hypoxia during postnatal development. Key homeostatic target values of the wall mechanics were recovered by the pulmonary arteries with normoxic recovery while other values recovered only partially. Overall cardiopulmonary dysfunction due to hypoxia was similarly only partially reversible. Remodeling of the cardiopulmonary system due to hypoxia is a complex, multi-scale process that involves maladaptations of the proximal pulmonary artery.

physiology↗

bioRxiv2025

State or personality trait: Determinants of boldness and shoal size preference in adult zebrafish

Animals adjust their behavior in response to physiological states to optimize the trade-off between energy acquisition and survival. A key question in animal personality research is whether behavioral variation is driven by consistent physiological state differences or stable personality traits. This study evaluates boldness and shoal size discrimination in adult male zebrafish (Danio rerio) across three hunger states: same-day feeding (H0), 24-hour food deprivation (H1), and 48-hour food deprivation (H2). Behavioral assessments were conducted over two testing cycles, with each individual undergoing every test twice for each hunger state within each cycle. The assays comprised the Open Field Test (OFT), Emergence Test (ET), and Social Preference Test (SPT), with the SPT conducted under binary (4 vs. 2 fish) and ternary (4 vs. 2 vs. 1 fish) choice conditions. Hunger significantly reduced emergence latency, but did not affect exploratory behavior in the OFT. Hunger also enhanced preference for larger shoals above chance in the binary SPT during the second testing cycle, though this effect was absent in ternary choices. Testing cycle effects revealed habituation-driven increases in boldness in both the tests and a progressive shift toward larger shoal preferences in the binary SPT. Among all assays, only the OFT showed significant repeatability, making it a reliable measure of boldness. However, it did not show consistent individual differences in plasticity due to hunger. These results highlight the crucial role of labile physiological states, such as hunger and habituation, in driving behavioral variation and underscore the importance of designing studies that disentangle state-dependent behaviors from stable personality traits in animal personality research.

animal behavior and cognition↗

bioRxiv2025

A Multi-Model Ensemble Reveals Soil Carbon Gains from Regenerative Practices in the U.S. Midwest Cropland

Process-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification (MMRV) frameworks of carbon markets, but their application suffers from model-specific differences that keep any one model from working well across all combinations of soils, climates, crops, and agronomic practices at varying scales. Multi-model ensemble (MME), successfully used to quantify soil, management and climate impact on crop productivity, provide an opportunity to better estimate changes in soil organic carbon (SOC) outcomes for agronomic practices that have the potential to mitigate SOC loss at scale. We used an MME across 46 million hectares of US Midwest cropland at a resolution of 4- km2 to assess the aggregate ability of different regenerative practices to sequester SOC at this scale compared to their dynamic baselines. MME was validated with long-term experimental data and compared to its constituent CSMs, showing greater accuracy and lower uncertainty. The results show that adopting no-till combined with cover crops increased SOC stocks by 0.36 {+/-} 0.12 Mg ha-1 yr-1 aggregated across the entire U.S. Midwest cropland. At the regional scale, this corresponds to a net SOC gain of 16.4 Tg C yr-1 compared to business-as-usual baselines. These benefits are approximately halved when each management change is practiced individually, and the modest gains are only fully realized when continued over the long-term in soils with low initial carbon stock. Results demonstrate the power of MMEs run at high resolution for providing robust estimates of environmental outcomes following agricultural practice change, and for pinpointing locations for most effective intervention. This approach can alleviate many producer carbon market participation barriers and help address market issues while ultimately supporting large-scale regenerative agriculture initiatives.

ecology↗

bioRxiv2025

SARS-CoV-2 infection of the brain: the K18-hACE2 mouse model to illustrate the role and response of the vasculature in neurotropic viral infection

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) primarily affects the respiratory tract and lungs; however, the associated disease, coronavirus disease 2019 (COVID-19), can involve the central nervous system (CNS) in both its acute and long-term (Long COVID) clinical manifestation. The pathomechanisms underlying neurological impairments in COVID-19 are not yet fully understood, hence experimental studies to clarify the direct effect of SARS-CoV-2 in the brain can provide further insight. In the present study we used the K18-hACE2 model, intranasally challenged with SARS-CoV-2 ancestral and Delta isolates at low or medium doses, to address the hypothesis that the inflammatory response raised in the brain of infected mice is secondary to neuronal infection. Our data confirmed that the virus reaches the brain even after low dose (102 PFU/mouse, Delta isolate) infection where it targets the neurons without overt neuropathic effect, sparing the blood vessels. In situ investigation of the resulting inflammatory response showed the recruitment of leukocytes via postcapillary venules, with their accumulation in the perivascular space and occasional migration into the neuroparenchyma, without targeting and/or damage to the vessel wall. These changes were reflected in the brain transcriptome and proteome which showed positive enrichment of pathways and up-regulation of genes involved in the inflammatory response including the recruitment (including adhesion and migration) and activity of leukocytes. Additionally, morphological and transcriptome/proteome changes suggest minimal associated blood-brain barrier dysfunction. The brain metabolome and lipidome showed minimal changes; these were consistent with oxidative stress and inflammatory and immune/antiviral responses. The results obtained from our model indicate that SARS-CoV-2 infection of the neurons can result in limited neuroinflammation. These data can help to understand more fully the reaction of the CNS in COVID-19 patients, and neurotropic virus infections in general.

pathology↗

bioRxiv2025

Learning single-cell spatial context through integrated spatial multiomics with CORAL

Cellular organization is central to tissue function and homeostasis, influencing development, disease progression, and therapeutic outcomes. The emergence of spatial omics technologies, including spatial transcriptomics and proteomics, has enabled the integration of molecular and histological features within tissues. Analyzing these multimodal data presents unique challenges, including variable resolutions, imperfect tissue alignment, and limited or variable spatial coverage. To address these issues, we introduce CORAL, a probabilistic deep generative model that leverages graph attention mechanisms to learn expressive, integrated representations of multimodal spatial omics data. CORAL deconvolves low-resolution spatial data into high-resolution single-cell profiles and detects functional spatial domains. It also characterizes cell-cell interactions and elucidates disease-relevant spatial features. Validated on synthetic data and experimental datasets, including Stero-CITE-seq data from mouse thymus, and paired CODEX and Visium data from hepatocellular carcinoma, CORAL demonstrates robustness and versatility. In hepatocellular carcinoma, CORAL uncovered key immune cell subsets that drive the failure of response to immunotherapy, highlighting its potential to advance spatial single-cell analyses and accelerate translational research.

bioinformatics↗

bioRxiv2025

Identification of Antituberculars with Favorable Potency and Pharmacokinetics through Structure-Based and Ligand-Based Modeling

Drug discovery is inherently challenged by a multiple criteria decision making problem. The arduous path from hit discovery through lead optimization and preclinical candidate selection necessitates the evolution of a plethora of molecular properties. In this study, we focus on the hit discovery phase while beginning to address multiple criteria critical to the development of novel therapeutics to treat Mycobacterium tuberculosis infection. We develop a hybrid structure- and ligand-based pipeline for nominating diverse inhibitors targeting the {beta}-ketoacyl synthase KasA by employing a Bayesian optimization-guided docking method and an ensemble model for compound nominations based on machine learning models for in vitro antibacterial efficacy, as characterized by minimum inhibitory concentration (MIC), and mouse pharmacokinetic (PK) plasma exposure. The application of our pipeline to the Enamine HTS library of 2.1M molecules resulted in the selection of 93 compounds, the experimental validation of which revealed exceptional PK (41%) and MIC (19%) success rates. Twelve compounds meet hit-like criteria in terms of MIC and PK profile and represent promising seeds for future drug discovery programs.

microbiology↗

bioRxiv2025

YY1 protein is essential for the promotion of Muller glia reprogramming and retina regeneration

Unlike mammals, the Muller glia reprogramming in zebrafish retina restores vision after an acute retinal injury. Here, we explored the Ying yang (Yy1) protein and its multi-faceted roles in different phases of retina regeneration. We show that the acetylation and deacetylation status of Yy1 contribute to its transcriptional activation and repression functions on various target genes, including regeneration-associated genes (RAGs). Yy1 is regulated positively by TGF-{beta} and negatively through Delta-Notch signaling in the injured retina. Yy1-knockdown caused reduced retinal progenitor induction and regeneration, while the opposite was seen in its overexpression. Yy1 collaborates with histone deacetylases, BAF complex, and the effector of TGF-{beta} signaling, pSMAD3, to target the genome differentially. Lastly, the whole transcriptome analysis of the Yy1-debilitated retina revealed differential expression of various RAGs and BMP-signaling. Yy1 facilitates the BMP pathways genes through the downregulation of noggin3. Our study unravels how a single transcription factor, Yy1, could influence many important regulatory steps of retina regeneration.

cell biology↗

bioRxiv2025

Recurrent oncogenic ZC3H18 mutations stabilize endogenous retroviral RNA

Endogenous retroviral (ERV) RNA is highly expressed in cancer, although the molecular causes and consequences remain unknown. We found that ZC3H18 (Z18), a component of multiple nuclear RNA surveillance complexes, has recurrent truncating mutations in cancer. We show that Z18trunc mutations are oncogenic and that Z18 plays an evolutionarily conserved role in nuclear RNA surveillance of ERV RNA. In zebrafish, Z18trunc expedited melanoma onset and promoted a specific accumulation of ERV RNA. Z18 mutant human cell lines from the Cancer Cell Line Encyclopedia also expressed higher levels of ERV RNA. In engineered human melanoma cells, Z18trunc enhanced ERV RNA accumulation more than loss of one Z18 copy, indicating dominant negative activity. Z18trunc directly bound and stabilized ERV RNA. Notably, expression of ERV RNA was sufficient to expedite oncogenesis in a zebrafish model, which is the first evidence of which we are aware that ERV transcripts can play a functional role in cancer. Our work illuminates a mechanism for elevated ERV transcripts in cancer and supports that aberrant RNA accumulation is broadly oncogenic.

cancer biology↗

bioRxiv2025

Regulation of the lncRNA malat1/Egr1 Axis by Wnt, Notch and TGF-β signaling: A Key Mechanism in Retina Regeneration

Adult zebrafish retinas rely on the resident Muller glia to maintain homeostasis and enable regeneration. Retina regeneration remains incomplete in mammals despite extensive efforts to emulate zebrafish regenerative conditions. Many studies have examined the reprogramming of zebrafish Muller glia cells, which is necessary for regeneration driven by regeneration-associated gene expression. Here, we show that the lncRNA malat1, crucial for many biological functions, plays essential roles during retina regeneration. We demonstrate that malat1 functions through an Egr-dependent axis, modulated by Wnt, Notch, and TGF-{beta} signaling pathways, and is necessary for effective retina regeneration. Moreover, we uncover that the antisense lncRNA talam1, which regulates malat1 availability, is differentially regulated in zebrafish and mice, highlighting species-specific gene regulatory mechanisms after retinal injury. Cells with active TGF-{beta} signaling stabilize Malat1 in mice while the same signaling destabilizes malat1 in zebrafish. Taken together, our work uncovers a new role for the malat1/Egr1 axis in necessitating retina regeneration, which may have important implications for differential regenerative ability in vertebrates.

cell biology↗

bioRxiv2025

An ultra-long heavy chain bovine antibody neutralizes SARS-CoV-2 and reacts broadly with sarbecoviruses.

The ongoing threat of new SARS-CoV-2 variants and other sarbecoviruses has driven efforts to develop broadly neutralizing monoclonal antibodies (mAbs). This study used immunized cattle, known for producing antibodies with ultra-long CDRH3 domains, to generate 33 mAbs, ten of which had ultra-long CDRH3s (>50 amino acids). Of these, mAbs P7 and 99, demonstrated broad and potent neutralization. Notably, mAb P7 neutralized all tested variants, including SARS-CoV-1, with IC50 values between 0.05 and 9.2 {micro}g/mL, and showed cross-reactivity with RBDs from various sarbecoviruses. Structural analysis revealed that mAb 99 binds the spike proteins RBD at the ACE2 binding site. Although the exact binding of P7 wasnt resolved, evidence suggests it targets a hidden epitope, promoting spike trimer dissociation via its extended CDRH3. In Syrian hamsters, both mAbs significantly reduced lung viral loads. These results support the potential of bovine-derived mAbs, particularly those with ultra-long CDRH3s, for future antiviral therapies.

immunology↗

bioRxiv2024

LBR and LAP2 mediate heterochromatin tethering to the nuclear periphery to preserve genome homeostasis

In most eukaryotic cells, euchromatin is localized in the nuclear interior, whereas heterochromatin is enriched at the nuclear envelope (NE). This conventional chromatin organization is established by heterochromatin tethering to the NE, however its importance for cellular homeostasis is largely unexplored. Peripheral heterochromatin localization relies on redundant NE-tethering systems. One tether is constituted by the lamin B receptor (LBR) in mammals, but the enigmatic nature of the other tethers has hampered functional analyses. Here we demonstrate that the downregulation of abundant, ubiquitous NE proteins can induce the global detachment of heterochromatin from the NE. Among these factors, we identify LBR and LAP2 as major players in bulk heterochromatin attachment to the NE in pluripotent and differentiated mammalian cells. Their loss leads to repositioning of heterochromatin to the nuclear interior, changes in chromatin accessibility, deregulation of gene expression including activation of antiviral innate immunity, and defects in cell fate determination.

cell biology↗

bioRxiv2024

Spatial Transcriptomics Reveals Inflammation and Trans-differentiation States of Acute Myeloid Leukemia in Extramedullary and Medullary Tissues

Acute myeloid leukemia (AML) is a heterogeneous disease of the bone marrow (medullary) but can also involve extramedullary tissues. While single cell dynamics of AML in suspension are previously explored, a comprehensive spatial transcriptomic assessment in AML remain underexplored. Here, we used Visium spatial transcriptomics to resolve medullary and extramedullary AML environments. We reveal spatial co-localization of monocytes and granulocyte-monocyte progenitors with leukemic populations in the bone marrow, sharing molecular signatures with extramedullary sites. Cell-cell communication via the CXCL12- CXCR4 axis correlated with PI3K/AKT/mTOR signaling in high inflammatory niches. Trans- differentiation states were concentrated in AML-infiltrated regions, with committed-like AML populations present in inflammatory niches and away from the trabeculae, while primitive-like AML cells localized near the endosteal niche. We validated these findings in GeoMx-based Digital Spatial profiling (DSP). Our study applied multimodal spatial transcriptomic approaches to characterize the spatial hierarchy and microenvironmental dynamics of AML differentiation states. We also demonstrated the feasibility of applying Visium-based spatial transcriptomics in decalcified bone tissues.

cancer biology↗

bioRxiv2024

An Accessible 3D HepG2/C3A Liver Spheroid Model Supporting the Complete Intrahepatocytic Lifecycle of Plasmodium falciparum

Current liver-stage Plasmodium falciparum models are complex, expensive, and largely inaccessible, hindering research progress. Here, we show that a 3D liver spheroid model grown from immortalized HepG2/C3A cells supports the complete intrahepatocytic lifecycle of P. falciparum. Our results demonstrate sporozoite infection, development of exoerythrocytic forms, and breakthrough infection into erythrocytes. The 3D-grown spheroid hepatocytes are structurally and functionally polarised, displaying enhanced albumin and urea production and increased expression of key metabolic enzymes, mimicking in vivo conditions - relative to 2D cultures. This accessible, reproducible model lowers barriers to malaria research, promoting advancements in fundamental biology and translational research.

microbiology↗

bioRxiv2024

Loss of KDM6A-mediated genomic instability and metabolic reprogramming differentially regulates responses to immune checkpoint therapy and chemotherapy in bladder cancer.

Mutations in genes encoding critical epigenetic regulators are frequently noted in bladder cancer, however, the impact of these mutations on therapeutic efficacy is unclear. One of the most common driver mutations in bladder cancer occurs in the KDM6A gene, which encodes a histone demethylase that promotes gene transcription. Retrospective analyses of patients with bladder cancer demonstrated that KDM6A mutations correlate with improved overall survival (OS) with immune checkpoint therapy (ICT), while they are associated with lower OS in patients undergoing cisplatin-based chemotherapy. Mechanistic studies utilizing CRISPR-Cas9 mediated deletion of Kdm6a showed reduced expression of DNA mismatch repair (MMR) and DNA double-stranded base repair (DSBR) genes in tumor cells with improved response to anti-PD-1 therapy and attenuated sensitivity to cisplatin-based chemotherapy in preclinical models of bladder cancer. Additionally, the loss of Kdm6a-mediated reduction in glycolysis and intratumoral lactate accumulation impaired histone 3 lysine 9 lactylation (H3K9la) and histone 3 lysine 18 lactylation (H3K18la) in Tregs with concurrent decrease in the expression of key genes including Foxp3, Tgfb and Pdcd1 and their immune-suppressive function. Further, reduced expansion of PD-1hi Tregs improved the ratio of cytotoxic T cells to Tregs and response to anti-PD-1 therapy in Kdm6a deficient tumor-bearing mice. Collectively, this study provided key insights into the role of KDM6A-mediated epigenetic regulation of DNA repair and metabolic reprogramming which potentially govern response to chemotherapy and ICT thus highlighting the utility of KDM6A mutation status for patient stratification and development of personalized treatment algorithms.

immunology↗

bioRxiv2024

WhaleLM: Finding Structure and Information in Sperm Whale Vocalizations and Behavior with Machine Learning

Language models (LMs), which are neural sequence predictors trained to model distributions over natural language texts, have come to play a central role in human language technologies like machine translation and information retrieval. They have also contributed to the scientific study of human language itself, enabling progress on long-standing questions about the learnability, optimality, and universality of key features of human languages. Many analogous questions exist in the study of communication between non-human animals--for which, in many cases, we have only a preliminary understanding of signals structure and use. Can neural sequence models help us understand these animal communication systems as well? We use these models to characterize the structure and information content of sperm whale vocalizations. Sperm whales (Physeter macrocephalus) engage in complex, coordinated behaviours like foraging and navigation in the darkness of the ocean while exchanging sequences of rhythmic clicks known as codas. However, little is known about whether there are any systematic patterns governing coda production, or how codas influence group decision-making and behaviour. To begin to answer these questions, we first train a neural sequence model (a sperm whale language model) to predict whales future vocalizations from their conversational history. By systematically manipulating the information available to this model, and measuring the change in predictive accuracy, we show that sperm whale vocalizations exhibit order dependence, long-range dependencies on up to the past eight codas in an exchange, and predictable turn-taking. Second, we train the sequence model to predict whales behaviour from their vocal exchanges, and find that both current behavioural context and future actions are predictable, with accuracies of 72% and 86% respectively, from coda sequences. Our study provides the first evidence that sperm whale vocalizations contain information that could be used to coordinate behaviour. More generally, it offers a framework for using modern machine learning tools for hypothesis generation and to assist in investigating the structure and function of unknown communication systems.

animal behavior and cognition↗

bioRxiv2024

Duplex PCR assay to determine sex and mating status of Ixodes scapularis (Acari: Ixodidae), vector of the Lyme disease pathogen

Ticks are a major health threat to humans and other animals, through direct damage, toxicoses, and transmission of pathogens. An estimated half a million people are treated annually in the United States of America for Lyme disease, a disease caused by the bite of a black-legged tick (Ixodes scapularis Say) infected with the bacterial pathogen Borrelia burgdorferi. This tick species also transmits another six human-disease causing pathogens, for which vaccines are currently unavailable. While I. scapularis are sexually dimorphic at the adult life stage, the DNA sequence differences between male and female I. scapularis that could be used as a sex-specific marker have not yet been established. We determine the sex-specific DNA sequences for I. scapularis (male heterogametic system with XY), using whole-genome resequencing and restriction site-associated DNA sequencing. Then we identify a male-specific marker that we use as the foundation of a molecular sex identification method (duplex PCR) to differentiate the sex of an I. scapularis tick. In addition, we provide evidence that this molecular sexing method can establish the mating status of adult females that have been mated and inseminated with male-determining sperm. Our molecular tool allows the characterization of mating and sex-specific biology across development for I. scapularis, a major pathogen vector, which is crucial for a better understanding of their biology and controlling tick populations.

genomics↗

bioRxiv2024

p-ClustVal: A Novel p-adic Approach for Enhanced Clustering of High-Dimensional scRNASeq Data

This paper introduces p-ClustVal, a novel data transformation technique inspired by p-adic number theory that significantly enhances cluster discernibility in genomics data, specifically Single Cell RNA Sequencing (scRNASeq). By leveraging p-adic-valuation, p-ClustVal integrates with and augments widely used clustering algorithms and dimension reduction techniques, amplifying their effectiveness in discovering meaningful structure from data. The transformation uses a data-centric heuristic to determine optimal parameters, without relying on ground truth labels, making it more user-friendly. p-ClustVal reduces overlap between clusters by employing alternate metric spaces inspired by p-adic-valuation, a significant shift from conventional methods. Our comprehensive evaluation spanning 30 experiments and over 1400 observations, shows that p-ClustVal improves performance in 91% of cases, and boosts the performance of classical and state of the art (SOTA) methods. This work contributes to data analytics and genomics by introducing a unique data transformation approach, enhancing downstream clustering algorithms, and providing empirical evidence of p-ClustVals efficacy. The study concludes with insights into the limitations of p-ClustVal and future research directions.

bioinformatics↗

bioRxiv2024

BoMBR: An Annotated Bone Marrow Biopsy Dataset for Segmentation of Reticulin Fibers

Bone marrow reticulin fibrosis is associated with varied benign as well as malignant hematological conditions. The assessment of reticulin fibrosis is important in the diagnosis, prognostication and management of such disorders. The current methods for quantification of reticulin fibrosis are inefficient and prone to errors. Therefore, there is a need for automated tools for accurate and consistent quantification of reticulin. However, the lack of standardized datasets has hindered the development of such tools. In this study, we present a comprehensive dataset that comprises of 201 Bone Marrow Biopsy images for Reticulin (BoMBR) quantification. These images were meticulously annotated for semantic segmentation, with the focus on performing reticulin fiber quantification. This annotation was done by two trained hematopathologists who were aided by Deep Learning (DL) models and image processing techniques that generated a rough automated annotation for them to start with. This ensured precise delineation of the reticulin fibers alongside other cellular components such as bony trabeculae, fat, and cells. This is the first publicly available dataset in this domain with the aim to catalyze advancements the development of computational models for improved reticulin quantification. Further, we show that our annotated dataset can be used to train a DL model for a multi-class semantic segmentation task for robust reticulin fiber detection task (Mean Dice score: 0.92). We use these model outputs for the Marrow Fibrosis (MF) grade detection and obtained a Mean Weighted Average F1 score of 0.656 with our trained model. Our code for preprocessing the dataset is available at https://github.com/AI-in-Medicine-IIT-Ropar/BoMBR_dataset_preprocessing.

pathology↗