Biology subjects

Yadav, M.

Publications and source records attributed to Yadav, M..

At least 37 records · Page 2Linked to original sources

bioRxiv2025

The mitochondrial unfolded protein response and metabolic reprogramming promote PASMC proliferation in response to sphingosine kinase-1/sphingosine-1-phosphate signaling

Proliferation and vasoconstriction of the intimal smooth muscle layer of the pulmonary artery are pathogenic characteristics of pulmonary arterial hypertension (PAH). Altered mitochondrial function, i.e. glycolysis, ROS generation and fission, are known potentiators of vascular remodeling. However, most current therapeutic interventions fail to effectively address the proliferation of the pulmonary artery smooth muscle cells (PASMCSs) lining the pulmonary vasculature and highlight the importance of identifying novel pathways to target for intervention. The Sphk1/S1P/S1P2 signaling axis is upregulated in PAH patients and is known to induce PASMC proliferation during hypoxia-mediated pulmonary hypertension (HPH). Interestingly, Sphk1 modulates mitochondrial function in that it regulates dynamics, cell growth and survival and in C. elegans, it induces activation of the unfolded protein response (UPRmt). We aimed to investigate if the Sphk1/S1P/S1P2 signaling axis promotes vascular remodeling in PAH via activation of the UPRmt. PASMCs isolated from IPAH patients were subjected to RNAseq analysis. The effect of Sphk1 or S1P was interrogated in hPASMC cell lines and the HPH model was used to assess the effect of the UPRmt on PAH pathogenesis. RNAseq analysis revealed that pathways involved in mitochondrial respiration were among the top 20 most significantly regulated pathways. Furthermore, ATF-5, the transcription factor that mediates the UPRmt was significantly upregulated. In hPASMCs, Sphk1/S1P lead to decreased respiration, increased glycolysis, fission, ROS and UPRmt activation. Pharmacological inhibition of the UPRmt mediator, mtHSP70, mitigated the Sphk1 induced increase in hPASMC proliferation. Furthermore, mtHSP70 inhibition was protective in hypoxia-mediated pulmonary hypertension (HPH) as we observed a decrease in right ventricular systolic pressure, right ventricular hypertrophy and vascular remodeling. These data suggest that the UPRmt promotes vascular remodeling in PAH and may present a novel pathway to target for pharmaceutical intervention.

cell biology↗

bioRxiv2025

Homeorhetic regulation of cellular phenotype

How cells translate growth factor (GF) signals into context-specific phenotypes remains a fundamental question in cell biology. The classical view holds that cells translate a constant concentration of a GF with specific chemical identity to a steady state activation of the underlying signaling pathway, resulting in a defined phenotypic response. However, recent findings suggest that even a single GF, when presented in a pulsatile manner, drives differential phenotypic responses depending on the frequency of stimulation. To reconcile these views, we introduce a novel conceptual framework of "signaling homeorhesis". Unlike homeostasis, homeorhesis describes the stable evolution of signaling trajectories over time. Defining this concept quantitatively using a dynamical systems framework, we use mathematical models of the Epidermal Factor Growth Receptor (EGFR) and the Tropomyosin receptor kinase A (TrkA) networks, as well as available experimental temporal protein activity recordings in PC-12 cells to demonstrate that cells classify GF signals to unique signaling trajectories that encode for distinct cell phenotypes, irrespective of the GF identity. We thereby propose that the cellular phenotype is determined in real-time, as the cell actively interprets the growth factor signals from its environment.

cell biology↗

bioRxiv2025

Circulating Biomarkers for Therapeutic Response to Immune Checkpoint Inhibitor Therapy in Patients with Advanced Lung Cancer

Immune checkpoint inhibitors (ICIs) have demonstrated remarkable efficacy in the treatment of advanced lung cancer (ALC), but not all patients benefit. To identify responders, patient selection, categorization, and the identification of specific predictive biomarkers are crucial. Our research aims to identify circulating metabolites that could be used to stratify patients into potential responders prior to the initiation of ICIs and to monitor clinical response in real-time during treatment. In the discovery phase, plasma samples (n = 25) from ALC patients receiving ICIs were analyzed using unbiased metabolomics and validated in a distinct patient cohort (n = 39). Five potential biomarkers were identified (FC > 1.5, p 0.05, AUC 0.81-1), including Thiourea and a combined metabolite panel (CMP) consisting of sphingosine-1-phosphate, gentisic acid, glutathione, and 4-hydroxybutanone. Early on-treatment high plasma levels of Thiourea were significantly associated with 5-year progression-free survival [Hazard ratio (HR) = 0.038, 95% confidence interval (CI) = 0.013-0.107, p<0.001] and overall survival [HR = 0.048, 95% CI = 0.019-0.120, p<0.001]. Low levels of CMP early on treatment were significantly associated with progression-free survival [HR = 8.119, 95% CI: 3.767-17.501, p<0.001] and overall survival [HR = 7.367, 95% CI: 3.517-15.433, 3.517-15.433, p<0.001]. This predictive plasma metabolite panel could serve as promising circulating biomarkers for predicting the therapeutic response of ICIs in ALC patients.

cancer biology↗

bioRxiv2025

Expression of Tacr1 and Gpr83 by spinal projection neurons

Anterolateral system (ALS) projection neurons underlie perception of pain, itch and skin temperature. These cells are heterogeneous, and there have therefore been many attempts to define functional populations. A recent study identified two classes of ALS neuron in mouse superficial dorsal horn (SDH) based on expression of the G protein-coupled receptors Tacr1 or Gpr83. It was reported that cells expressing these receptors formed largely non-overlapping populations, and that [~]60% of ALS cells in SDH expressed Tacr1. An additional finding was that while Tacr1- and Gpr83-expressing ALS cells projected to several brain nuclei, their axons did not reach the ventral posterolateral (VPL) thalamic nucleus, which is reciprocally connected to the primary somatosensory cortex. These results were surprising, because we had reported that [~]90% of SDH ALS neurons in the mouse possess the neurokinin 1 receptor (NK1r), which is encoded by Tacr1, and in addition the VPL is thought to receive input from lamina I ALS cells. Here we use retrograde and anterograde labelling in Tacr1CreERT2 and Gpr83CreERT2 mice to reinvestigate the expression of the receptors by ALS neurons and to reassess their projection patterns. We find that [~]90% of ALS neurons in SDH express Tacr1, with 40-50% expressing Gpr83. We also show that axons of both Tacr1- and Gpr83-expressing ALS neurons reach the VPL. These results suggest that ALS neurons in the SDH that express these GPCRs show considerable overlap, and that they are likely to contribute to the sensory-discriminative dimension of pain through their projections to VPL.

neuroscience↗

bioRxiv2025

IAN: An Intelligent System for Omics Data Analysis and Discovery

IAN is an R package that addresses the challenge of integrating, analyzing and interpreting high-throughput "omics" data, using a multi-agent artificial intelligence (AI) system. IAN leverages popular pathway and regulatory datasets (KEGG, WikiPathways, Reactome, GO, ChEA) and the STRING database for protein-protein interactions to perform standard enrichment analysis. The individual enrichment results are then used to generate insightful summaries, for each of the datasets, using a large language model (LLM) through a multi-agent architecture. These summaries are then contextually integrated and interpreted by the LLM, guided by carefully engineered prompts and grounding instructions, to provide insightful explanations, system overview, key regulators, novel observations etc. We demonstrate IANs potential to facilitate biological discovery from complex omics data, by reanalyzing two already published data and evaluating the results. We also show remarkable performance of IAN, in terms of avoiding hallucination. IAN package, along with installation instructions and example usage, is available on https://github.com/NIH-NEI/IAN.

bioinformatics↗

bioRxiv2024

Anatomical characterisation of somatostatin-expressing neurons belonging to the anterolateral system

Anterolateral system (ALS) spinal projection neurons are essential for pain perception. However, these cells are heterogeneous, and there has been extensive debate about the roles of ALS populations in the different pain dimensions. We recently performed single-nucleus RNA sequencing on a developmentally-defined subset of ALS neurons, and identified 5 transcriptomic populations. One of these, ALS4, consists of cells that express Sst, the gene coding for somatostatin, and we reported that these were located in the lateral part of lamina V. Here we use a SstCre mouse line to characterise these cells and define their axonal projections. We find that their axons ascend mainly on the ipsilateral side, giving off collaterals throughout their course in the spinal cord. They target various brainstem nuclei, including the parabrachial internal lateral nucleus, and the posterior triangular and medial dorsal thalamic nuclei. We also show that in the L4 segment Sst is expressed by [~]75% of ALS neurons in lateral lamina V and that there are around 120 Sst-positive lateral lamina V cells on each side. Our findings indicate that this is a relatively large population, and based on projection targets we conclude that they are likely to contribute to the affective-motivational dimension of pain.

neuroscience↗

bioRxiv2024

miRNA Biomarkers in Prostate Cancer: Leveraging Machine Learning for Improved Diagnostic Accuracy

Prostate cancer (PCa) diagnosis often relies on prostate-specific antigen (PSA) testing, but its high false-positive rates often lead to unnecessary biopsies. MicroRNAs (miRNAs) have emerged as promising non-invasive biomarkers for cancer detection due to their stability in biological fluid and disease specificity. Despite their potential, the clinical translation of miRNAs as non-invasive cancer biomarkers is hindered by several challenges - population-based variability, environmental Factors, methodological Inconsistencies, lack of standardization, normalization Issues, and complexity of the biological System. These factors significantly impact the consistency of miRNA expression readouts, particularly in terms of Ct-values, across different studies, which in turn affects the determination of cutoff values that are crucial in a diagnostic setup. This preliminary study offers a pilot demonstration for integrating miRNA biomarker expression with machine learning (ML), which can help identify patterns and improve classification, potentially reducing the reliance on fixed cutoff values in certain contexts and pave the path to wider clinical translation. We analyzed the expression of key miRNAs (miR-21-5p, miR-221-3p, and miR-141-3p) in blood samples from patients with PCa and benign prostatic hyperplasia (BPH). Utilizing a Random Forest classifier, we achieved an accuracy of 77.42%, a precision of 86.21%, a recall of 71.43%, and an AUC-ROC score of 0.78. The application of ML enabled us to leverage complex features, such as combinations and ratios of miRNA expression data, which enhanced the robustness and reliability of the diagnostic model. Additionally, bioinformatics analysis of the preferential features identified by the ML model confirmed the biological relevance of these miRNAs in PCa-related pathways, further supporting their potential as clinical biomarkers. In the future, ML is poised to significantly enhance diagnostic performance compared to traditional linear analyses of a limited set of biomarkers. While our study did not explore multiple populations or the effects of methodological variables, it highlights the potential of ML by demonstrating improved accuracy and eliminating the need for cutoff values. This capability could broaden the applicability of miRNA-based diagnostics, making them more reliable and actionable in clinical settings. However, to fully realize this potential, further validation with larger and more diverse cohorts is essential. Overall, this study lays the groundwork for utilizing ML-enhanced miRNA panels as powerful tools for the early and non-invasive diagnosis of PCa in future clinical practice. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=130 SRC="FIGDIR/small/618146v1_ufig1.gif" ALT="Figure 1"> View larger version (38K): org.highwire.dtl.DTLVardef@2eddd9org.highwire.dtl.DTLVardef@e6d6c8org.highwire.dtl.DTLVardef@11eea0forg.highwire.dtl.DTLVardef@989c15_HPS_FORMAT_FIGEXP M_FIG C_FIG

genomics↗

bioRxiv2024

AyurPhenoClusters define common molecular roots for rare diseases and uncover ciliary dysfunctions in syndromic conditions

The heterogeneity of underlying causes and the variability of symptoms across Multiple organs in rare diseases present significant challenges when approached from an organ-centric perspective. Ayurveda, however, takes a multisystem perspective, assessing diseases through kinetic (Vata:V ), metabolic (Pitta:P ), and structural (Kapha:K ) dimensions, each with distinct phenotypic and molecular correlates. This study explores rare diseases from a systems perspective by integrating Ayurveda and unifying terminologies from both disciplines using Human Phenotype Ontology (HPO). Experts categorized 10,610 HPO terms into Ayurvedic phenotypic groups (V/P/K ) and applied the Expectation Maximization (EM) algorithm to cluster 12,678 diseases. This yielded six distinct clusters, termed AyurPhenoClusters, with 2,814 diseases uniquely classified and enriched for V/P/K phenotypes. Functional annotation of these, highlighted key biological processes: (i) embryogenesis and skeletal morphogenesis, (ii) endocrine and ciliary functions, (iii) DNA damage response and cell cycle regulation, (iv) inflammation and immune response, (v) immune function, hemopoiesis, and telomere aging, and (vi) small molecule metabolism and transport. Notably, the K predominant cluster had the highest ciliary gene enrichment (43%), followed by the V predominant cluster (16%), suggesting potential ciliopathies in V cluster. This systems-based approach enhances the understanding of rare diseases by bridging Ayurveda with modern medicine, for improved diagnostics and therapeutics

genetics↗

bioRxiv2024

Diabetic liver-enriched secretory dipeptidyl peptidase 4 (DPP4) fuels gut inflammation via attenuation of autophagy

The recurrent pathological inflammation of the gut is a major concern in diabetic patients. With the failure of anti-inflammatory or diabetic drugs to limit relapse of colon inflammation demands the unearthing of mechanistic details underlying higher incidences of colitis in diabetic patients. Here we report the enrichment of DPP4 in the livers and blood samples of diabetic humans and mice models of diabesity that is in parallel to the development of colitis. Overexpression of DPP4 exacerbates or hepatic silencing of DPP4 impairs experimental colitis induced by DSS and STM. Mechanistically, we identified liver DPP4 attenuates gut-autophagic response to trigger enteric cell apoptosis, reduced mucin secretion, and compromised gut barrier leading to high infiltration of immune cells secreting inflammatory cytokines establishing pathological gut inflammation. Thus, liver-DPP4-mediated gut autophagy inhibition is a key pathway in diabesitic colitis.

physiology↗

bioRxiv2024

PRMT5 is required for full-length HTT expression by repressing multiple proximal intronic polyadenylation sites

Expansion of the CAG trinucleotide repeat tract in exon 1 of the Huntingtin (HTT) gene above a threshold of [~]36 repeats causes Huntingtons disease (HD) through the expression of a polyglutamine-expanded form of the HTT protein. This mutation triggers wide-ranging cellular and biochemical pathologies leading to cognitive, motor, and psychiatric symptoms in HD patients. As accurate splicing is required to produce the full-length HTT protein of [~]348 kDa, targeting HTT splicing with small molecule drugs is a compelling approach to lower HTT protein levels to treat HD, and splice modulators are being tested in the clinic. Here, we identify PRMT5 as a novel regulator of HTT mRNA splicing and alternative polyadenylation. PRMT5 inhibition disrupts the splicing of HTT introns 9 and 10, leading to activation of multiple proximal intronic polyadenylation sites within these introns and promoting premature termination, cleavage and polyadenylation (PCPA) of the HTT mRNA, thus lowering total HTT protein levels. We also detected increasing levels of these truncated, intron-containing HTT transcripts across a series of neuronal differentiation samples which correlated with lower PRMT5 expression. Notably, PRMT5 inhibition in glioblastoma (GBM) stem cells potently induced neuronal differentiation. We posit that PRMT5-mediated regulation of intronic polyadenylation, premature termination and cleavage of the HTT mRNA modulates HTT expression and plays an important role during embryonic development and neuronal differentiation.

neuroscience↗

bioRxiv2024

A resource to enable chemical biology and drug discovery of WDR Proteins

Protein class-focused drug discovery has a long and successful history in pharmaceutical research, yet most members of druggable protein families remain unliganded, often for practical reasons. Here we combined experiment and computation to enable discovery of ligands for WD40 repeat (WDR) proteins, one of the largest human protein families. This resource includes expression clones, purification protocols, and a comprehensive assessment of the druggability for hundreds of WDR proteins. We solved 21 high resolution crystal structures, and have made available a suite of biophysical, biochemical, and cellular assays to facilitate the discovery and characterization of small molecule ligands. To this end, we use the resource in a hit-finding pilot involving DNA-encoded library (DEL) selection followed by machine learning (ML). This led to the discovery of first-in-class, drug-like ligands for 9 of 20 targets. This result demonstrates the broad ligandability of WDRs. This extensive resource of reagents and knowledge will enable further discovery of chemical tools and potential therapeutics for this important class of proteins.

biochemistry↗

bioRxiv2024

Huntingtin is an RNA-binding protein and participates in NEAT1-mediated paraspeckles

AbstractHuntingtin protein, mutated in Huntington disease, is implicated in nucleic acid- mediated processes, yet evidence for direct huntingtin-nucleic acid interaction is limited. Here we show wildtype and mutant huntingtin co-purify with nucleic acids, primarily RNA, and interact directly with G-rich RNAs in in vitro assays. Huntingtin RNA immunoprecipitation sequencing from patient-derived fibroblasts and neuronal progenitor cells expressing wildtype and mutant huntingtin revealed NEAT1 as a significantly enriched transcript. Altered NEAT1 levels were evident in Huntingtons disease cells and postmortem brain tissues, and huntingtin knockdown decreased NEAT1 levels. Huntingtin co-localized with NEAT1 in paraspeckles, and we identified a high-affinity RNA motif preferred by huntingtin. This study highlights NEAT1 as a novel huntingtin interactor, demonstrating huntingtins involvement in RNA-mediated functions and paraspeckle regulation. One-Sentence SummaryHTT is an RNA-binding protein that interacts with G-rich sequences, including those in the paraspeckle lncRNA NEAT1.

cell biology↗

bioRxiv2024

PPARγ mediated enhanced lipid biogenesis fuels Mycobacterium tuberculosis growth in hepatocytes.

Mycobacterium tuberculosis (Mtb) infection of the lungs, besides producing prolonged cough with mucus, also causes progressive fatigue and cachexia with debilitating loss of muscle mass. While anti-tuberculosis (TB) drug therapy is directed toward eliminating bacilli, the treatment regimen ignores the systemic pathogenic derailments that probably dictate TB-associated mortality and morbidity. Presently, it is not understood whether Mtb spreads to metabolic organs and brings about these impairments. Here we show that Mtb creates a replication-conducive milieu of lipid droplets in hepatocytes by upregulating transcription factor PPAR{gamma} and scavenging lipids from the host cells. In hepatocytes, Mtb shields itself against the common anti-TB drugs by inducing drug-metabolizing enzymes. Infection of the hepatocytes in the in vivo aerosol mice model can be consistently observed post-week 4 along with enhanced expression of PPAR{gamma} and drug-metabolizing enzymes. Moreover, histopathological analysis indeed shows the presence of Mtb in hepatocytes along with granuloma-like structures in human biopsied liver sections. Hepatotropism of Mtb during the chronic infectious cycle results in immuno-metabolic dysregulation that could magnify local and systemic pathogenicity, altering clinical presentations.

microbiology↗

bioRxiv2024

Molecular basis of ligand promiscuity, structural mimicry, and atypical dimerization in the chemokine receptors

Selectivity of natural agonists for their cognate receptors is one of the hallmarks of the members of GPCR family, and it is crucial for the specificity of downstream signal-transduction. However, this selectivity often breaks down in the chemokine receptor subfamily, wherein a high degree of promiscuity is observed with one receptor recognizing multiple chemokines and one chemokine binding to multiple receptors. The molecular determinants of such a striking promiscuity for natural ligands in the chemokine-chemokine receptor system remain mostly elusive and represent an important knowledge gap in our current understanding. Here, we carry out a comprehensive transducer-coupling analysis, testing all known C-X-C chemokines on every C-X-C type chemokine receptor, to generate a global fingerprint of the selectivity and promiscuity encoded within this system. Taking lead from our finding, we determined cryo-EM structures of the most promiscuous receptor, CXCR2, in complex with every interacting chemokine, and deciphered the conserved molecular signatures and distinct binding modalities. While most chemokines position themselves on the receptor as a dimer, CXCL6 exhibits a monomeric binding pose induced by a previously unanticipated reorientation of its carboxyl-terminal -helix, leading to disruption of the dimer interface. Surprisingly, one of the chemokines, CXCL5, induces a ligand-swapped dimer of CXCR2, the first of its kind observed in class A GPCRs, wherein each protomer of the ligand engages its own receptor without any discernible receptor-receptor interface. These unique observations provide a possible structural mechanism for inherent functional specialization encoded in chemokines despite their convergence to a common receptor. Furthermore, we also determined cryo-EM structures of CXCR3 in complex with G-protein-biased and {beta}-arrestin-biased small molecule agonists that elucidate distinct allosteric modulations in the receptor driving their divergent transducer-coupling bias. Guided by structural analysis and experimental validation, we discover that in contrast to previously held notion, small molecule agonists of CXCR3 display robust agonism at CXCR7, an intrinsically biased, {beta}-arrestin-coupled receptor, making them first-in-class dual agonists for chemokine receptors with exclusive {beta}arr-bias at CXCR7. Taken together, our study provides molecular insights into ligand promiscuity and signaling bias at the chemokine receptors, and also demonstrates a proof of principle that naturally encoded structural mimicry can be recapitulated using synthetic pharmacophores with potential implications for developing novel therapeutics.

biochemistry↗

bioRxiv2023

gQuant: A Robust and Generalizable Algorithm for Identifying Normalizer Genes in qRT-PCR Data: A Case Study on Urinary Exosomal miRNAs

The emergent role of nucleic acid-based biomarkers, such as microRNAs (miRNAs), long non-coding RNAs (lncRNAs), and messenger RNAs (mRNAs), is becoming increasingly prominent in the realms of disease diagnostics and risk assessment. Quantitative reverse transcription PCR (qRT-PCR) is the primary analytical method for quantitative measurement of biomarkers. Yet, the relative infancy of non-coding RNAs (ncRNAs) recognition as biomarkers poses a challenge due to the absence of a consensus on a universally accepted normalizer gene, which is pivotal for accurate quantification. Current tools for selecting normalizer genes in qRT-PCR are fraught with limitations, including inadequate handling of null values, reliance on elementary statistical tools, use of a biased integrated approach, outlier sensitivity, and suboptimal graphical user interface for data visualization. These deficiencies underscore the necessity for a more nuanced and algorithmically balanced tool tailored to handle qRT-PCR datasets and facilitate the discernment of the most appropriate normalizer gene for specific datasets. Addressing the identified challenges, we have developed gQuant, a tool crafted to address the limitations present in existing methods. In gQuant we employed voting classifiers as an ensemble technique that combines predictions from multiple statistical methods to make more accurate rankings than any individual statistical measures. The tools efficacy was substantiated through rigorous validation against datasets from the Gene Expression Omnibus (GEO) database and corroborated with experimental data derived from urinary exosomal miRNAs. Comparative analysis with existing tools revealed that their integrated methodologies could skew the ranking of normalizer genes, whereas gQuant consistently yielded rankings characterized by lower standard deviation, reduced covariance, and enhanced kernel density estimation (KDE) values. Given gQuants promising performance, normalizer gene identification will be greatly improved, improving the precision of gene expression quantification in a variety of research scenarios.

molecular biology↗

bioRxiv2023

Telomeres control regulation of the human Telomerase (hTERT) gene through non-telomeric TRF2 and independent of Telomere looping

The function of the human telomerase reverse transcriptase (hTERT) in the synthesis and maintenance of chromosome ends, or telomeres, is widely understood. Whether and how telomeres, on the other hand, influence hTERT regulation is relatively less studied. We found hTERT was transcriptionally altered depending on telomere length (TL). This resulted from TL-dependent binding of TRF2 between telomeres and the hTERT promoter. hTERT promoter-bound TRF2 was non-telomeric and did not involve the looping of telomeres to the hTERT promoter. Cell lines from different tissue types (fibrosarcoma (HT1080), colon cancer (HCT116), and breast cancer (MDA-MB-231), engineered for either telomere elongation/shortening gave increase/decrease in hTERT, respectively. Mechanistically, we show hTERT promoter-bound non-telomeric TRF2 recruits the canonical PRC2-complex inducing repressor histone H3K27-trimethylation in a TL-dependent fashion. This was further supported by TL-dependent promoter activity from an exogenously inserted hTERT reporter. Increase in TL over days followed by gradual decline, resulted in activation followed by repression of hTERT in a concerted manner, further implicating TL as a key factor for hTERT regulation. Notably on reprogramming primary fibroblasts to induced pluripotent stem cells (iPSCs), TRF2 loss from the hTERT promoter was evident along with telomere elongation and hTERT upregulation. Conversely, on telomere shortening in iPSCs, hTERT promoter-bound TRF2 was restored with marked reduction in hTERT further supporting the causal role of TL in hTERT transcription. Mechanisms of tight control of hTERT by TL shown here are likely to have major implications in telomere-related physiologies, particularly, cancer, ageing and pluripotency. TeaserTelomere length controls hTERT expression by modulating TRF2 distribution and PRC2-mediated repression, highlighting a self-regulatory mechanism in cancer.

cancer biology↗

bioRxiv2023

A hepatocyte-specific transcriptional program driven by Rela and Stat3 exacerbates experimental colitis in mice by modulating bile synthesis

Hepatic factors secreted by the liver promote homeostasis and are pivotal for maintaining the liver-gut axis. Bile acid metabolism is one such example wherein, bile acid synthesis occurs in the liver and its biotransformation happens in the intestine. Dysfunctional interactions between the liver and the intestine stimulate varied pathological outcomes through its bidirectional portal communication. Indeed, aberrant bile acid metabolism has been reported in inflammatory bowel disease (IBD). However, the molecular mechanisms underlying these crosstalks that perpetuate intestinal permeability and inflammation remain obscure. Here, we identify a novel hepatic gene program regulated by Rela and Stat3 that accentuates the inflammation in an acute experimental colitis model. Hepatocyte-specific ablation of Rela and Stat3 reduces the levels of primary bile acids in both the liver and the gut and shows a restricted colitogenic phenotype. On supplementation of chenodeoxycholic acid (CDCA), knock-out mice exhibit enhanced colitis-induced alterations. This study provides persuasive evidence for the development of multi-organ strategies for treating IBD and identifies a hepatocyte-specific rela-stat3 network as a promising therapeutic target.

immunology↗

bioRxiv2023

In-Silico analysis of Human Insulin Gene for Mirror repeat sequences

The genetic material contains all the instructions necessary for the development, functioning & regulation of biological processes. This is also considering as a regulatory molecule. The structure constitute by its unique pattern of bases make it unique for every living being consider from bacteria to human. The varied pattern of bases in genomes or genes represents different types of repeats. These repeats types constitute the major fraction of the genomes. Among varied types Mirror repeats (MRs) play crucial roles in the genome especially in formation of H-DNA structure by Non Watson pairing. Some studies suggest that mirror sequences responsible for neurological diseases also. Now days in modern era of technology in silico techniques were develop to extract any type of repeat sequences from any gene or genome. The major focus of current work is on identification of mirror repeats (MRs) from human insulin gene sequence using an in silico approach. The approach is refer to as FPCB (FASTA Parallel Complement Analysis) were utilized to extract MR sequences. From the current study a total no of 210 MR sequenced were identified in Human insulin gene. The identified repeats vary in their length and majority of them are imperfect in nature. The maximum no of MR were reported in the region 3 & minimum is in the region 8 (8). In the remaining regions the no of MR sequences were lies in between maximum & minimum values. These sequences may be helpful in many molecular level studies.

bioinformatics↗