Biology subjects

Ramachandran, S.

Publications and source records attributed to Ramachandran, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

An Integrated Decarbonising Approach to Mitigate Methane Emissions and Enhance Productivity in Rice Cultivation

Flooded rice paddies contribute approximately 12% of global anthropogenic methane emissions, accounting for 1.5% of the total warming effect from all greenhouse gases. With the rising global demand for rice due to population growth, the need for effective methane mitigation strategies in rice cultivation is increasingly critical. This study investigates the combined impact of irrigation methods, fertiliser combinations, and varietal differences on productivity, water use and methane emissions in rice. Field trials were conducted across five land parcels covering 8 Ha in the Sathyamangalam region of Tamil Nadu, India, from October 2024 to January 2025. Results revealed that drip irrigation significantly reduced seasonal methane emissions by up to 68% (128 kg/ha/season) compared to continuous flood irrigation (402.32 kg/ha/season) offering a sustainable solution to address climate change. Furthermore, our modified package of practices coupled with tailored fertiliser combination, led to a 28% reduction in methane emissions (222 kg/ha/season) relative to continuous flooding methods used by the farmers in the region (309 kg/ha/season). Methane emission differences of up to 23.8% were also evident across rice varieties ADT-45 (229.7 kg/ha/season and BPT-5204 (301.7 kg/ha/season) for. Although flood irrigation yielded a 5-6% higher grain productivity than drip irrigation, the TLL fertiliser package under flood irrigation still provided distinct benefits with a yield increase of 5.4%. Notably, water usage under drip irrigation was 42.5% lower on average across the five locations, with minimal impact on yield, resulting in a marked improvement in water use efficiency (0.62 kg.m-3 under drip vs. 0.39 kg.m-3 under flood irrigation). Our findings highlight the value of integrating modern irrigation techniques, optimizing fertiliser management, and appropriate varietal selection with higher environmental sustainability and improved farm productivity to mitigate climate impact in rice cultivation.

plant biology↗

bioRxiv2025

Epigenetically regulated p53 activity maintains intestinal regulatory T cell identity to prevent inflammation

Regulatory T cells (Tregs) are critical guardians of immune homeostasis that must operate in diverse and often inflammatory conditions. However, the mechanisms that Tregs use to maintain their stability and function, especially in response to the stresses of distinct microenvironments, remain incompletely understood. Previous work identified the repressive chromatin modification histone 3 lysine 27 trimethylation (H3K27me3) as a rheostat for Treg function. Here, we find that loss of H3K27me3 in Tregs activates the tumor suppressor p53. Stabilization of p53 using the MDM2 inhibitor Nutlin-3 protected Tregs from losing their master transcription factor Foxp3 in vitro when cultured with the Th17 cytokines IL-6 and IL-1{beta}, while p53 deficiency rendered Tregs more prone to Foxp3 loss. Treg-specific p53 deficiency resulted in accumulation of cells that had lost Foxp3 expression ("ex-Tregs") and reduction of suppressive markers on Tregs specifically in the colon. Additionally, these mice exhibited inflammation in the colon at homeostasis and increased severity of induced colitis. These results demonstrate a specific role for p53 in the maintenance of Treg stability in Th17-polarizing environments and present a possible target for improving Treg-based immunotherapies for diseases defined by intestinal inflammation, such as inflammatory bowel disease (IBD).

immunology↗

bioRxiv2025

The Data Distillery: A Graph Framework for Semantic Integration and Querying of Biomedical Data

The Data Distillery Knowledge Graph (DDKG) is a framework for semantic integration and querying of biomedical data across domains. Built for the NIH Common Fund Data Ecosystem, it supports translational research by linking clinical and experimental datasets in a unified graph model. Clinical standards such as ICD-10, SNOMED, and DrugBank are integrated through UMLS, while genomics and basic science data are structured using ontologies and standards such as HPO, GENCODE, Ensembl, STRING, and ClinVar. The DDKG uses a property graph architecture based on the UBKG infrastructure and supports ontology-based ingestion, identifier normalization, and graph-native querying. The system is modular and can be extended with new datasets or schema modules. We demonstrate its utility for informatics queries across eight use cases, including regulatory variant analysis, tissue-specific expression, biomarker discovery, and cross-species variant prioritization. The DDKG is accessible via a public interface, a programmatic API, and downloadable builds for local use.

bioinformatics↗

bioRxiv2025

Early detection of oxidative stress in mammary epithelial cells by using secreted Cyclophilin A as a marker in the milk.

ObjectiveTo investigate the secretion and expression of cyclophilin A (CypA) in mammary epithelial cells in vitro under oxidative stress conditions and to evaluate its potential as a biomarker of oxidative stress in dairy cows. MethodsPrimary mammary epithelial cells isolated from goat mammary gland, luminal epithelial cells isolated from goat milk and mouse mammary epithelial cells were cultured and treated with hydrogen peroxide (H2O2) and tert-butyl hydroperoxide (t-BHP) to induce oxidative stress. Cell viability, intracellular reactive oxygen species (ROS) levels, lipid peroxidation, and antioxidant enzyme activity were measured to assess the oxidative status of cells. CypA gene expression was quantified using quantitative reverse transcription polymerase chain reaction and the secreted CypA levels were measured by using enzyme linked immunosorbent assay and immunoblotting. Milk samples from various cow breeds were also analysed for somatic cell count, catalase activity and CypA levels. ResultsThe primary mammary epithelial cells culture displayed typical epithelial cell morphology. Oxidative stress induced by 200 {micro}M of both H2O2 and t-BHP and an exposure duration of 1 hour was observed to be optimum in inducing oxidative stress. A significant increase in ROS levels and lipid peroxidation index was observed across all cell types. Catalase activity was also elevated in the treated cells. An upregulation of CypA gene expression was observed in response to oxidative stress with a significant increase in CypA protein levels. Milk samples from the various cattle breeds revealed varying somatic cell counts with the highest in Kankrej and lowest in Holstein Friesian. ConclusionThese findings demonstrate that CypA is secreted from the mammary epithelial cells in response to oxidative stress and may serve as a potential biomarker for oxidative stress in dairy cows.

cell biology↗

bioRxiv2025

Genome-wide analysis reveals pathways important for the development and maturation of excitatory synaptic connections to GABAergic neurons

A high degree of cell and circuit-specific regulation has presented challenges for efforts to precisely define molecular mechanisms controlling synapse formation and maturation. Here, we pursue an unbiased forward genetic approach to identify C. elegans genes involved in the formation and maturation of cholinergic synaptic connections with GABAergic motor neurons as indicated by the distribution of GFP-tagged postsynaptic acetylcholine receptors (AChR) on GABAergic dendrites. We identified mutations in 3 genes that identify key processes in synapse/circuit maturation. Mutation of the RUN domain (RPIP8, UNC-14, and NESCA) cargo adaptor gene unc-14 dramatically impacts overall GABAergic neuron morphology and dendritic spines. Mutation of the nicotinic acetylcholine alpha subunit gene unc-63 causes a failure in AChR assembly in GABAergic neurons but does not significantly alter dendritic spine structure or abundance. Finally, a mutation in the Liprin- synaptic scaffold gene syd-2 severely disrupts both dendritic spines and AChR localization. The identification of these three genes from our screen highlights how mechanisms for cargo trafficking, receptor assembly, and synapse structural organization each make distinct contributions to synapse assembly and circuit connectivity.

neuroscience↗

bioRxiv2025

AAV gene therapy for GBA-PD and Gaucher Disease

Mutations in GBA1, the gene encoding glucocerebrosidase (GCase), are the most common risk factor for Parkinsons Disease (PD). GBA-PD patients are a genetic subpopulation of PD carrying heterozygous mutations in GBA1. Additionally, bi-allelic mutations in GBA1 cause Gaucher Disease (GD), a lysosomal storage disorder. Loss of GCase activity, a lysosomal enzyme leads to the accumulation of lipid substrates, disrupting lipid homeostasis and promoting cellular toxicity. Here, we report an AAV-mediated GBA1 replacement strategy to treat GD and GBA-PD by a one-time infusion via intravenous (GD Type 1) or intra-CSF (GBA-PD) route of administration. We engineered human GCase to be readily secretable to facilitate broad cross-correction. We developed CBE (conduritol {beta}-epoxide) induced lipid accumulation models to assess efficacy in mice and non-human primates (NHPs) to assess efficacy of our engineered constructs. Based on data across species, across different routes of administration, we nominated AAV.GMU01 SS3-GBA1 as our lead candidate. SS3-GBA1 is robustly secreted, cross-corrected across tissues and promotes lipid clearance. By comparing human GCase levels in AAV-treated NHP brains to healthy human donor brains, we demonstrate that AAV.GMU01 SS3-GBA1 replenishes the GCase deficit seen in GBA-PD patients, thus, restoring GCase to near-physiological levels Importantly, AAV.GMU01 SS3-GBA1 is well-tolerated with no adverse findings. Collectively, we establish a therapeutic strategy for the treatment of Gaucher Disease and GBA-PD with a single gene therapy product. One Sentence SummaryA novel gene therapy strategy for GBA1-PD and Gaucher disease with an engineered payload that robustly cross-corrects enhancing therapeutic footprint

neuroscience↗

bioRxiv2025

Integration of Alzheimer's GWAS, 3D genomics, and single-cell CRISPRi non-coding screen implicates causal variants in a microglial enhancer regulating TSPAN14.

While GWAS have been successful in providing variant-to-trait associations for human complex diseases, functional dissection of the discovered loci has lagged behind. Here, we describe a variant-to-gene (V2G) mapping effort for Alzheimers disease (AD) to implicate causal variants and effector genes from the most recent AD GWAS meta-analyses (101 loci). We leveraged our genomics datasets comprising high-resolution promoter Capture C, ATAC-seq, and RNA-seq from brain-relevant cell types to fine-map AD GWAS variants, identifying 89 candidate causal SNPs and 69 effector genes. We then designed a single-cell CRISPRi screen to perturb candidate regulatory regions (n=74) and assess the transcriptional response in the human microglial cell line, HMC3. Our screen across [~]97,000 cells identified 19 regulatory regions and 19 effector genes. We then elected to functionally dissect our top hit, the TSPAN14 locus, and we show that an intronic region containing AD-associated SNPs rs7080009, rs1870138, and rs1870137 is a microglia-specific enhancer, with the AD risk haplotype increasing its activity. CRISPR precise genomic deletion of this region decreases TSPAN14 expression, alters specific cellular pathways including cell adhesion, and decreases secreted levels of pro-inflammatory cytokines IL-6 and IL-8, which are known biomarkers of aging and AD. Our work provides a systematic framework to map GWAS signals to their effector genes for AD and other brain-related disorders, and provides robust leads to follow up with in-depth functional investigations.

genetics↗

bioRxiv2025

AAV-mediated ARSA replacement for the treatment of Metachromatic Leukodystrophy

Metachromatic leukodystrophy (MLD) is an autosomal recessive neurodegenerative disorder caused by mutations in the arylsulfatase A (ARSA) gene, resulting in lower sulfatase activity and the toxic accumulation of sulfatides in the central and peripheral nervous system. Children account for 70% of cases and become progressively disabled with death occurring within 10 years of disease onset. Gene therapy approaches to restore ARSA expression via adeno-associated viral vectors (AAV) have been promising but hampered by limited brain biodistribution. We report the development of a novel capsid AAV.GMU01, demonstrating superior biodistribution and transgene expression in the central nervous system of non-human primates (NHPs). Next, we show that AAV.GMU01-ARSA treated MLD mice exhibit persistent, normal levels of sulfatase activity and a concomitant reduction in toxic sulfatides. Treated mice also show a reduction in MLD-associated pathology and auditory dysfunction. Lastly, we demonstrate that treatment with AAV.GMU01-ARSA in NHPs is well-tolerated and results in potentially therapeutic ARSA expression in the brain. In summary, we propose AAV.GMU01-ARSA mediated gene replacement as a clinically viable approach to achieve broad and therapeutic levels of ARSA.

neuroscience↗

bioRxiv2025

ML-MAGES: A machine learning framework for multivariate genetic association analyses with genes and effect size shrinkage

A fundamental goal of genetics is to identify which and how genetic variants are associated with a trait, often using the regression results from genome-wide association (GWA) studies. Important methodological challenges are accounting for inflation in GWA effect estimates as well as investigating more than one trait simultaneously. We leverage machine learning approaches for these two challenges, developing a computationally efficient method called ML-MAGES. First, we shrink the inflation in GWA effect sizes caused by non-independence among variants using neural networks. We then cluster variant associations among multiple traits via variational inference. We compare the performance of shrinkage via neural networks to regularized regression and fine-mapping, two approaches used for addressing inflated effects but dealing with variants in focal regions of different sizes. Our neural network shrinkage outperforms both methods in approximating the true effect sizes in simulated data. Our infinite mixture clustering approach offers a flexible, data-driven way to distinguish different types of associations--trait-specific, shared across traits, or spurious--among multiple traits based on their regularized effects. Clustering applied to our neural network shrinkage results also produces consistently higher precision and recall for distinguishing gene-level associations in simulations. We demonstrate the application of ML-MAGES on association analyses of two quantitative traits and two binary traits in the UK Biobank (genetic and phenotypic data from 500,000 residents of the UK). Our identified associated genes from single-trait enrichment tests overlap with those having known relevant biological processes to the traits. Besides trait-specific associations, ML-MAGES identifies several variants with shared multi-trait associations, suggesting putative shared genetic architecture.

genetics↗

bioRxiv2025

Cutaneous lupus features specialized stromal niches and altered retroelement expression

Cutaneous Lupus is an inflammatory skin disease causing highly morbid inflamed skin and hair loss. In order to investigate the pathophysiology of cutaneous lupus, we performed single-cell RNA and spatial sequencing of lesional and non-lesional cutaneous lupus skin compared to healthy controls. Pathway enrichment analyses of lesional keratinocytes revealed elevated responses to type I interferon, type II interferon, tumor necrosis factor, and apoptotic signaling. Detailed clustering demonstrated unique fibroblasts specific to lupus skin with likely roles in inflammatory cell recruitment and fibrosis. We also evaluated the association of retroelement expression with type I interferons in the skin. We observed increased retroelement expression which correlated with interferon-stimulated genes across multiple cell types. Moreover, we saw elevated expression of genes involved in RIG-I and cGAS-STING pathways, which transduce elevated nucleic acid signals. Treatment of active cutaneous lupus with Anifrolumab reduced RIG-I and cGAS-STING pathways in addition to the most abundant retroelement family, L2b. Our studies better define type I interferon-mediated immunopathology in cutaneous lupus and identify an association between retroelement expression and interferon signatures in cutaneous lupus.

immunology↗

bioRxiv2025

The CFDE Workbench: Integrating Metadata and Processed Data from Common Fund Programs

The NIH Common Fund Data Ecosystem (CFDE) program was established to facilitate data accessibility and interoperability across multiple Common Fund (CF) programs and promote collaborations and new discoveries by combining data from different CF programs. The CFDE Data Resource Center (DRC) was tasked with developing two web-based portals: an Information Portal to serve information about the CFDE, and a Data Portal to host harmonized metadata and processed data contributed by participating CF Data Coordination Centers (DCCs) and other sources. To achieve these goals, the CFDE DRC developed the CFDE Workbench, a web-based platform that hosts highly processed data, metadata, tools, use cases, and analyses developed by the CFDE. The Crosscut Metadata Model (C2M2) and several other processed data formats are hosted by the CFDE Workbench, including set libraries (XMTs), Knowledge Graph (KG) assertions, and attribute tables. These processed data formats make information derived from CF programs more findable, accessible, interoperable, and reusable (FAIR) and artificial intelligence (AI)-ready for cross-DCC knowledge discovery. In addition to these processed data formats, several other assets are served by the Workbench, including Extract Transform Load (ETL) pipelines, OpenAPI-documented and SmartAPI-registered Representational State Transfer (REST) Application Programming Interfaces (APIs), entity pages such as gene, drug, disease, or tissue landing pages, Playbook Workflow Builder (PWB) metanodes which are codified workflow steps involving DCC APIs, and chatbot specifications which are prompts helping chatbots to use DCC APIs to answer a wide range of user queries. Besides serving data, metadata, and code assets, the CFDE Workbench also has several tools that use these data, metadata, and code assets to enable cross-CF-program knowledge discovery use cases. Overall, the CFDE Workbench is a platform that consolidates efforts toward making CF programs funded resources harmonized, FAIR, and AI-ready. The CFDE Workbench website is available from: https://cfde.info/.

bioinformatics↗

bioRxiv2024

Metabolic Switch in Endocrine Resistant Estrogen Receptor Positive Breast Cancer

PurposeThe development of endocrine resistance remains a significant challenge in the clinical management of estrogen receptor-positive (ER+) breast cancer. Metabolic reprogramming is a prominent component of endocrine resistance and a potential therapeutic intervention point. However, a limited understanding of which metabolic changes are conserved across the heterogeneous landscape of ER+ breast cancer or how metabolic changes factor into ER DNA binding patterns hinder our ability to target metabolic adaptation as a treatment strategy. This study uses dimethyl fumarate (DMF) to restore tamoxifen (Tam) and fulvestrant (Fulv) sensitivity in endocrine-resistant cell lines and investigates how metabolic changes influence ER DNA-binding patterns. Experimental DesignTo address the challenge of metabolic adaptation in anti-endocrine resistance, we generated Tam and Fulv resistance in six ER+ breast cancer (BC) cell lines, representing ductal (MCF7, T47D, ZR75-1, and UCD12), lobular (MDA-MB-134--VI), and HER2 amplified (BT474) BC molecular phenotypes. Metabolomic profiling, RNA sequencing, proteomics, and CUT&RUN assays were completed to characterize metabolic shifts, transcriptional and protein changes, and ER DNA-binding patterns in resistant cells. Dimethyl fumarate was assessed for its ability to reverse Tam and Fulv resistance, restore tricarboxylic acid cycle (TCA) cycle function, and restore parental cell (endocrine sensitive) ER DNA binding patterns. ResultsTamoxifen-resistant (TamR) and fulvestrant-resistant (FulvR) cells exhibited disrupted TCA cycle activity, reduced glutathione levels, and altered nucleotide and amino acid metabolism. DMF treatment replenished TCA cycle intermediates and reversed resistance in both TamR and FulvR cells. DMF also increased mevalonate pathway enzyme expression in both TamR and FulvR cells, with TamR cells upregulating enzymes in the cholesterol synthesis phase and FulvR enhancing enzymes in the early part of the pathway. DMF restored ER DNA-binding patterns in TamR cells to resemble parental cells, re-sensitizing them to Tam. In FulvR cells, DMF reversed resistance by modulating ER-cofactor interactions but did not restore parental ER DNA-binding signatures. ConclusionsOur findings provide new insights into how metabolic reprogramming affects ER DNA-binding activity in endocrine-resistant breast cancer. We demonstrate how altering metabolism can reprogram ER signaling and influence resistance mechanisms by targeting metabolic vulnerabilities, such as TCA cycle disruptions. Additionally, our data provide a comprehensive metabolomic, RNA-seq, and CUT&RUN data set relevant to tumor metabolic adaptation leading to acquired endocrine resistance in highly utilized ER+ breast cancer cell lines. This study improves our understanding of how metabolic states alter ER function in endocrine-resistant breast cancer.

cancer biology↗

bioRxiv2024

Drip irrigation suppresses methane emissions by reshaping the rhizosphere microbiomes in rice

The rhizosphere microbiomes of rice plants under conventional flood irrigation consist of highly complex consortia of microorganisms and in particular methanogens purportedly associated with methane emissions therein. Controlled irrigation has been proposed as a cultivation method of choice over continuous flooding to reduce water and fertilizer usage in an aerobic environment. However, a systemic understanding of the assembly and function of microbiota in the rhizosphere under drip and flood irrigation remains unclear. Using empirical analyses, we report a significant reduction in methane emissions in controlled irrigation compared to the flooded environment. Genotypic or varietal differences did not influence such methane emissions under conventional flooded cultivation of rice. Using metagenomic sequencing and computational analyses, we provide a deeper understanding of how drip irrigation or continuous flooding affect the root-associated microbiomes in rice. Rhizosphere soil from two different rice varieties, Huanghuazhan and Temasek rice, grown under drip or flood conditions in a greenhouse was collected over 2 months post-transplantation for metagenomic analysis. Our results reveal that drip irrigation favours microbes involved in the nitrifying-denitrifying processes while continuous flooding enriches for methanotrophs and methanogenic archaea. Syntrophic microbiomes associated with methanogenesis were significantly reduced in drip irrigation. Several keystone taxa were evident in the co-occurrence network model related to methanogenic, methanotrophic, nitrifying, sulphur-oxidising and sulphur-reducing activities. Lastly, oxygen availability and redox potential were identified as key drivers that reshape rhizosphere microbiota and the associated metabolic functional differences observed between the two irrigation regimes leading up to the microbial mitigation of climate impact. IMPORTANCEUnlike previous studies in alternate wet-dry irrigation systems, this study characterised the rice microbiomes in a controlled drip irrigation settings where water levels were maintained at low levels and soil remained unflooded throughout the entire season in a greenhouse. A reduction of more than 90% in methane emissions was observed with drip irrigation compared to flood irrigation. Significant correlation was found between levels of methane emitted and mcrA gene copies detected with a Pearson correlation coefficient R of 0.77 and p-value of 2.3e-10. Methanogens are highly abundant in continuous flooded rice soil and are significantly reduced in drip-irrigated soil. Metagenomic profiling indicates that the shifts in microbial diversity under drip irrigation favour nitrifying microorganisms and is likely influenced by increased oxygen availability due to higher soil redox potential.

microbiology↗

bioRxiv2024

The NHGRI-EBI GWAS Catalog: standards for reusability, sustainability and diversity

The NHGRI-EBI GWAS Catalog serves as a vital resource for the genetic research community, providing access to the most comprehensive database of human GWAS results. Currently, it contains close to 7,000 publications for more than 15,000 traits, from which more than 625,000 lead associations have been curated. Additionally, 85,000 full genome-wide summary statistics datasets - containing association data for all variants in the analysis - are available for downstream analyses such as meta-analysis, fine-mapping, Mendelian randomisation or development of polygenic risk scores. As a centralised repository for GWAS results, the GWAS Catalog sets and implements standards for data submission and harmonisation, and encourages the use of consistent descriptors for traits, samples and methodologies. We share processes and vocabulary with the PGS Catalog, improving interoperability for a growing user group. Here, we describe the latest changes in data content, improvements in our user interface, and the implementation of the GWAS-SSF standard format for summary statistics. We address the challenges of handling the rapid increase in large-scale molecular quantitative trait GWAS and the need for sensitivity in the use of population and cohort descriptors while maintaining data interoperability and reusability.

genetics↗

bioRxiv2024

High-Complexity Barcoded Rabies Virus for Scalable Circuit Mapping Using Single-Cell and Single-Nucleus Sequencing

Single cell genomics has revolutionized our understanding of neuronal cell types. However, scalable technologies for probing single-cell connectivity are lacking, and we are just beginning to understand how molecularly defined cell types are organized into functional circuits. Here, we describe a protocol to generate high-complexity barcoded rabies virus (RV) for scalable circuit mapping from tens of thousands of individual starter cells in parallel. In addition, we introduce a strategy for targeting RV-encoded barcode transcripts to the nucleus so that they can be read out using single-nucleus RNA sequencing (snRNA-seq). We apply this tool in organotypic slice cultures of the developing human cerebral cortex, which reveals the emergence of cell type- specific circuit motifs in midgestation. By leveraging the power and throughput of single cell genomics for mapping synaptic connectivity, we chart a path forward for scalable circuit mapping of molecularly-defined cell types in healthy and disease states.

neuroscience↗

bioRxiv2024

Oxidative Phosphorylation Inhibition in Different Prostate Cancer Models and the Interplay with Androgen Receptor Signaling

IntroductionIn prostate cancer (PCa), androgen receptor signaling stimulates both glycolysis and oxidative phosphorylation (OxPhos). Early-stage prostate cancer is particularly reliant on OxPhos for its bioenergetic needs. OxPhos inhibitors have entered clinical trials. Here we investigated their interplay with androgens in different PCa cell lines. MethodsWe investigated the effects on PCa cell viability of an ATPase inhibitor (oligomycin) and a complex 1 inhibitor (IACS-010759) in the presence or absence of low testosterone concentrations in vitro. Both androgen-sensitive and insensitive PCa cell lines were used. The effects were assessed using MTT assay, flow cytometry and cell morphology. ResultsTreatment with oligomycin resulted in massive apoptotic death of VCAP cells in castrate conditions within 48 hours, but the simultaneous addition of low testosterone levels restored VCAP cell viability. However, complex 1 inhibition with IACS-010759 increased cell viability, which was further promoted in the presence of testosterone. Both oligomycin and IACS-010759 dramatically decreased viability in LNCaP cells, while testosterone had a small but statistically non-significant effect. The antitumor effect of OxPhos inhibitors was smaller in LNCaP-C4-2B compared to LNCaP cells. OxPhos inhibitors slightly decreased proliferation rates in androgen-independent PC3 cells and HEK293 cells. Oligomycin on LNCaP-C4-2B and PC3 cells resulted in an increased number of cells in G0-G1 phase and decreased in S-phase and G2M phase, rather than massive apoptosis. ConclusionThere is an interplay between androgen signaling and OxPhos in androgen-dependent PCa cells. Complex 1 inhibitors should be used with caution, given potential pro-tumorigenic effects in subsets of PCa cells.

cancer biology↗

bioRxiv2024

Population genetics meets ecology: a guide to individual-based simulations in continuous landscapes

Individual-based simulation has become an increasingly crucial tool for many fields of population biology. However, continuous geography is important to many applications, and implementing realistic and stable simulations in continuous space presents a variety of difficulties, from modeling choices to computational efficiency. This paper aims to be a practical guide to spatial simulation, helping researchers to implement individual-based simulations and avoid common pitfalls. To do this, we delve into mechanisms of mating, reproduction, density-dependent feedback, and dispersal, all of which may vary across the landscape, discuss how these affect population dynamics, and describe how to parameterize simulations in convenient ways (for instance, to achieve a desired population density). We also demonstrate how to implement these models using the current version of the individual-based simulator, SLiM. We additionally discuss natural selection - in particular, how genetic variation can affect demographic processes. Finally, we provide four short vignettes: simulations of pikas that shift their range up a mountain as temperatures rise; mosquitoes that live in rivers as juveniles and experience seasonally changing habitat; cane toads that expand across Australia, reaching 120 million individuals; and monarch butterflies whose populations are regulated by an explicitly modeled resource (milkweed).

evolutionary biology↗

bioRxiv2024

Anti-diabetic and anti-adipogenic effects of polyherbal formulation Varanadi kashayam with a focus on incretin modulation

BackgroundFrontiers of health science increasingly emphasizes systems and network medicine approaches for managing complex lifestyle diseases such as diabetes. In this context, systemic targets like incretin hormones and their modulators - particularly DPP4 inhibitors - have gained prominence. Ayurveda, the Indian System of Medicine (ISM), with its clinically validated multicomponent formulations offers a valuable resource for integrative therapeutic strategies with systemic mode of action. PurposeThe study investigates the incretin modulatory effect of Varanadi Kashayam (VA), an Ayurveda polyherbal formulation used in the clinical management of diabetes and its comorbidities. Experimental approachA high-fat diet induced Sprague-Dawley (SD) rat model was used to study the anti-diabetic, GLP-1 secretory, and anti-obesity effects of VA. In vitro studies using GLUTag cells assessed the GLP-1 secretion and DPP4 gene expression modulation; and studies using 3T3-L1 fibroblasts examined the anti-adipogenic effects. Computational methods including molecular docking and molecular dynamic simulations were used to identify the phytochemicals responsible for DPP4 inhibition. ResultsVA administration significantly improved fasting blood glucose and oral glucose tolerance in experimental animals, along with enhanced GLP-1 secretion. The in vitro results showed inhibition of DPP4 enzyme activity, increase in GLP-1 secretion and downregulation of DPP4 gene expression in GLUTag cells, and suppression of adipogenesis in 3T3-L1 fibroblast cells. Computational analyses ascertained Chebulinic acid, Chebulagic acid and Terchebin as top ranked phytochemicals responsible for DPP4 inhibition effect. ConclusionCombining in vitro, in vivo and in silico findings, this study provides valuable insight into the incretin modulatory effect of VA in treating diabetes and associated metabolic diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=89 SRC="FIGDIR/small/601306v2_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1d424fcorg.highwire.dtl.DTLVardef@c84555org.highwire.dtl.DTLVardef@40094borg.highwire.dtl.DTLVardef@225272_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIVaranadi Kashayam (VA) improved blood glucose and GLP-1 levels in diabetic rats. C_LIO_LIInhibited DPP4 activity and gene expression in GLUTag cells. C_LIO_LISuppressed adipogenesis and adipogenic markers in 3T3-L1 cells. C_LIO_LIChebulinic acid, Chebulagic acid, and Terchebin identified as key DPP4 inhibitors. C_LI

cell biology↗