Biology subjects

Mukherjee, S.

Publications and source records attributed to Mukherjee, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Interplay of Cullin5-HECTD3 ubiquitin ligases regulates stability of CRAF mutant associated with hypertrophy

Proteostatic imbalance caused by CRAF (Raf1) kinase mutation alters MAPK signaling and contributes to RASopathies. CRAF proteostasis is maintained by chaperones, Hsp90 which aids in folding, maturation, and activation; whereas Hsp70 recruits ubiquitin ligase CHIP for proteasomal degradation. However, the proteostasis of disease-associated CRAF mutants remains undefined. Here, we identify HECTD3, a HECT-ubiquitin ligase in promoting degradation of hypertrophic CRAF mutants. Interestingly, increased Hsp90 binding to CRAF plays a determinant factor in degradation via HECTD3. Transient increase in Hsp90-CRAF association upon Hsp90 inhibition promote ubiquitination, whereas prolonged inhibition stabilizes mutant CRAF, indicating temporally distinct chaperone functions. Notably, HECTD3 undergoes proteosomal degradation under stress via Cullin-RING ubiquitin ligase Cul5 in a neddylation-dependent manner. Overexpression of Cul5 thus reduces HECTD3 level resulted in stabilization of CRAFD486N, while promoting degradation of wild-type CRAF. Therefore, modulation of the Cul5-HECTD3 axis alters hypertrophic signaling in cardiomyocyte cells. These results establish a hierarchical proteostasis mechanism in which Hsp90 binding primes substrate for HECTD3-mediated ubiquitination, and Cul5-controlled ligase turnover collectively determine mutant CRAF fate.

cell biology↗

bioRxiv2026

Predicting Autopsy-Confirmed Neuropathology across Clinical, Neuroimaging, and CSF Biomarkers using Machine Learning

Accurate in vivo prediction of neuropathology is critical for advancing diagnosis and treatment of Alzheimers disease and related dementias (ADRDs). As many individuals with ADRDs have mixed pathologies ({beta}-amyloid, pathologic tau, cerebrovascular disease, vascular brain injury, pathologic TDP-43, hippocampal sclerosis, Lewy bodies), there is interest in determining how accurately we can infer these pathologic changes from clinical data, biofluid assays (e.g., CSF), and neuroimaging. Here we evaluated automated machine learning models trained on data curated by the AD Sequencing Project Phenotype Harmonization Consortium (N=7,894 individuals), to predict 26 autopsy-confirmed neuropathological outcomes. Predictors included in vivo clinical and cognitive composite scores, brain measures from 3D structural MRI and diffusion tensor imaging, image-derived measures of white matter hyperintensities (WMH), and CSF biomarkers. Predictive models were trained using ensemble learning with stratified cross-validation. We assessed performance using Spearmans rank correlation and Matthews correlation coefficient, to accommodate co-occurring pathologic changes. The added value of neuroimaging and CSF versus clinical features alone was quantified. Braak stage was among the most consistently predicted outcomes. CSF biomarkers best predicted {beta}-amyloid and tau pathology, but diffusion MRI metrics best captured vascular brain injury and white matter injury, and outperformed clinical and cognitive measures and anatomical MRI in predicting Lewy body disease. Anatomical measures from structural MRI outperformed standard clinical assessments in assessing neurodegeneration and hippocampal sclerosis, and WMH complemented cognitive measures in predicting TDP-43 pathology. These results establish a baseline for comparing modalities for inferring neuropathology.

neuroscience↗

bioRxiv2026

Histopathology-inferred spatial transcriptomics characterizes the tumor microenvironment in 1,500 head and neck tumors and predicts clinical outcomes

Head and neck squamous cell carcinoma (HNSC) is a prevalent malignancy associated with poor prognosis despite recent therapeutic advances. We hypothesized that a comprehensive understanding of the spatial heterogeneity and organization of the tumor microenvironment (TME) can substantially improve risk stratification and prediction of treatment response in HNSC. As spatial transcriptomics (ST) remains labor-intensive and costly, we developed HEiST (H&E-Inferred Spatial Transcriptomics), a deep learning framework that predicts spatially resolved gene expression profiles directly from routine hematoxylin and eosin (H&E)-stained histology slides. After rigorous validation across two independent external ST cohorts, we applied HEiST to infer spatial transcriptomes across 1,500 HNSC patient tumors spanning two publicly available datasets and two newly generated cohorts, one treated with concurrent chemoradiotherapy (CCRT) and one with immunotherapy. This large-scale analysis uncovered reproducible spatial clusters characterizing the HNSC TME, defining two distinct prognostic Spatiotypes, Immune-Exhausted and Immune-Activated, with significantly distinct survival outcomes. Critically, spatial cluster composition accurately predicts HPV status and yields treatment response predictors for both CCRT/radiotherapy and immunotherapy that outperform costly gene-expression and direct image-based approaches. Notably, the ST cluster-based predictor of immunotherapy response markedly surpasses the performance of commonly used FDA-approved biomarkers, including CPS, TPS, and their combination. To the best of our knowledge, this represents the first virtual spatial profiling effort and the most comprehensive large-scale spatial TME analysis in HNSC to date. HEiST thus introduces a scalable, low-cost, and spatially grounded biomarker discovery for precision oncology in HNSC.

cancer biology↗

bioRxiv2026

Dynamic s-acylation of schizophrenia-linked antioxidants explicate the redox flexibility of human microglia during inflammation.

Cysteine proteome essentially regulates cellular adaptability during stress. Proteomic cysteines are reversibly modified to avoid loss through oxidation. Reversible cysteine-modifications beneficially preserve cellular stress-response mechanisms by regulating the transient activation of substrate proteins. Cysteine acylation (or s-acylation) is one such extensively documented reversible protein modification. Inflammation-responsive changes in s-acylation facilitate the plasticity of immune-partitioned brains by dynamically determining the utilization of stress-buffering (substrate) cysteine-proteins in microglia, the primary immune-reactive brain cells. However, the inflammation-responsiveness of cysteine-acylation in microglia is not elaborately measured at a large-scale. Therefore, we observed the differential (quantitative) s-acylation of proteins in cultured human (HMC3) microglia by implementing comparative MLCC-based chemoproteomic workflows. Parallelly, we characterized the molecular consequences of HMC3 cell treatment with 2-bromopalmitate, a general s-acylation inhibitor, by performing immunocytochemistry and proteomic experiments. We also identified the s-acylation-dependent microglial inflammatory responses through live spatiotemporal tracking and confocal microscopy, following treatment of microglia with PAMPs (LPS or IFNy). Finally, from our proteomic studies of postmortem human brain tissues, we confirmed major protein-causals of schizophrenia, a redox-related brain disorder, to undergo inflammation-responsive s-acylation. This report provides a first comprehensive library of cysteine-proteins differentially processed through inflammation-responsive acylation in microglia. It also outlines the inflammation-responsive s-acylation of key NRF2-antioxidants, including peroxiredoxins (especially PRDX2) and glutathione synthetase (GSS), as a biochemical signature of early-stage inflammation and oxidative-stress in microglia. More importantly, the innovative proteo-informatic workflows designed for this research work can be reliably repurposed to identify bifunctional theragnostic protein markers of many complex disorders and diseases.

biochemistry↗

bioRxiv2026

DCN1 inhibitor induces fetal hemoglobin through self-limited regulation of CUL3 neddylation

Few genetic loci are as well-characterized as the globin gene locus, and the substitution of healthy {gamma}-globin (HbF) for missing or mutated {beta}-globin (HbB) is an established therapeutic strategy for {beta}-hemoglobinopathies including sickle cell disease (SCD) and {beta}-thalassemia. Although substantial progress has been made in understanding HbF derepression and globin switching, many current therapeutic strategies involving small molecules increase HbF through broad epigenetic perturbations or cytotoxic stress, raising concerns about dose-limiting cytopenias and off-target effects. By coupling single-cell transcriptomics, genetic perturbations, and functional genomics, we identified an unknown role of neddylation in the regulation of fetal hemoglobin (HbF). Partial impairment of neddylation of cullin ubiquitin ligase 3 (CUL3) through defective in cullin neddylation 1 (DCN1) inhibition leads to highly selective chromatin changes, histone demethylation, and globin locus binding of known activators of HbF transcription. Further, DCN1 inhibition drives globin switching and HbF increases in vitro and in vivo with minimal off-target transcriptional effects and no evidence of cytotoxicity or stress erythropoiesis. To therapeutically target this axis, we report the discovery and characterization of CLY-124, a first-in-class, covalent DCN1 inhibitor with favorable pharmacology properties. In a humanized mouse model, CLY-124 showed a dose-dependent increase in HbF as monotherapy and in synergy with hydroxyurea (HU), a current standard of care. Collectively, these findings highlight the power of single-cell transcriptomics to elucidate undiscovered biologic insights with therapeutic potential, and the promise of DCN-1 inhibitors like CLY-124 to address {beta}-hemoglobinopathies. With an appropriate nonclinical safety profile, a first-in human study of safety, pharmacokinetics and HbF assessments in healthy volunteers and participants with SCD is ongoing for CLY-124. One-sentence SummaryDCN1 is a promising target for {beta}-hemoglobinopathies

molecular biology↗

bioRxiv2026

scVIP: personalized modeling of single-cell transcriptomes for developmental and disease phenotypes

Single-cell transcriptomics resolves cellular heterogeneity within individuals, but connecting molecular states to individual-level phenotypes requires frameworks that explicitly bridge these scales. We present scVIP, a generative model that links gene expression, cell-type composition, and phenotypic measurements within a single probabilistic model, which enables accurate phenotype prediction and interpretable trajectory inference. A cell-type-aware multi-instance learning architecture learns donor embeddings that capture progression while localizing phenotype-associated signals to specific cell populations. Applied across four settings, scVIP accurately predicts cortical developmental age (Pearson r = 0.95), characterizes Huntingtons disease progression (concordance correlation coefficient = 0.90), integrates two Alzheimers disease cohorts recovering disease-relevant microglial and astrocytic programs, and distinguishes healthy from ACPA-positive individuals and non-progressors from early RA individuals, identifying inflammatory T cell programs associated with disease. scVIP enables principled analysis of how cellular states collectively shape organism-level phenotypes across development and disease.

bioinformatics↗

bioRxiv2026

State-Dependent Organization of Microscale Functional Circuitry in Visual Cortex

How the cortex organizes directed functional interactions among individual neurons and how this microscale circuitry maps onto cell types and the underlying anatomy remains poorly understood. Here, we construct one of the largest single-neuron-resolution directed functional circuit maps in mouse visual cortex from calcium imaging of more than 57,000 active neurons across four visual areas and five cortical layers. We infer directed connections with a time-aware causal-inference method (CITS) that is specifically designed for neural time-series. In the co-registered electron-microscopy connectome, CITS-inferred pairs are 3.6-fold more likely to be synaptically connected than unconnected pairs, which is significantly more than Granger causality (1.1-fold) or lagged correlation (1.6-fold). We found that our inferred functional circuits organization aligns with synaptic connectivity at areal, laminar, and cell-type levels. Among intra-areal connections, anterolateral area (AL) had the highest density, and among inter-areal connections, the AL{leftrightarrow}rostrolateral area (RL) axis formed the strongest pathway. At the cell-type level, layer 6 recurrence dominated the aggregate network in low arousal, whereas layer 6-to-layer 5 output connections dominated in high arousal. Spatial extent expanded with inter-neuron distance in high arousal, for both excitatory-to-excitatory and excitatory-to-inhibitory connections. Finally, in stimulusdriven response prediction, neuron pairs with stronger functional connections exhibited more similar predictive performance in both high-arousal and low-arousal states, with performance varying by layer and cell type. Overall, our findings establish, at single-neuron resolution, the multi-scale organization of directed functional circuitry in mouse visual cortex across brain states.

neuroscience↗

bioRxiv2026

Modeling cis-regulatory variation in human brain enhancers across a large Parkinson's Disease cohort

Genome-wide association studies (GWAS) have linked more than a hundred non-coding genomic loci to Parkinsons disease (PD) risk. Deciphering their functional impact on gene regulation requires cell type-aware modeling approaches to assess the effects of sequence variation on enhancer function and target gene expression. To address this challenge, we generated a comprehensive matched dataset from 190 human donors (115 controls and 75 PD), comprising long-read whole-genome sequencing alongside single nucleus multiome atlases (snATAC-seq and snRNA-seq for 3.1 and 1.1 million nuclei respectively) of the anterior cingulate cortex and substantia nigra. By integrating chromatin accessibility quantitative trait loci (caQTL), DNA methylation QTL (meQTL), and allele-specific chromatin accessibility (ASCA), we identified 53,841 high-confidence cis-acting genetic variants that modulate cell type-specific enhancer accessibility in one or both brain regions. We further demonstrate that sequence-to-function models can accurately predict the impact of these variants directly from the genomic sequence. Novel explainability approaches allowed stratifying these variants according to their regulatory function, with the majority disrupting specific transcription factor binding sites in a cell type specific manner. Integrating these "enhancer variants" (EV) with eQTL mapping and gene locus modeling linked a subset of EVs to their target genes. Finally, we applied these models to prioritize regulatory variants at known PD GWAS loci, bypassing statistical limitations in rare disease-relevant populations like dopaminergic neurons. All together, we establish a unique resource and new sequence modeling strategies to interpret functional non-coding variation in the human brain.

genomics↗

bioRxiv2026

The Alternative Polyadenylation Factor CFIm25 Orchestrates Macrophage Antibacterial Immunity by Amplifying TAB2-Mediated MAPK and NF-κB Signaling During Salmonella Infection

Macrophage antimicrobial programs are regulated not only by transcriptional networks but also by RNA processing mechanisms affecting signal transduction and effector responses. One such mechanism, alternative polyadenylation (APA), determines mRNA fate by changing the length of the 3' UTR. However, our understanding of the impact of APA on antibacterial functions and how we can manipulate it to influence infection outcomes remains limited. In this study, we identify the APA regulator CFIm25 (NUDT21) as a promoter of macrophage defense against Salmonella enterica serovar Typhimurium (STM). STM infection is known to drive macrophages toward an M2-like immunosuppressive state conducive to bacterial survival. Concurrent with this transition, the CFIm25 level is reduced, and the 3 UTRs of CFIm25 targets encoding key immune proteins, such as TAB2 and TBL1XR1, are lengthened, suggesting a role for APA changes in the response to STM. Overexpression of CFIm25 in infected macrophages blocks these Salmonella-induced 3 UTR changes, leading to greater mRNA and protein expression. Significantly, the increase in CFIm25 suppresses infection, thereby creating a more antimicrobial intracellular environment, improving macrophage survival, and reducing M2 properties that support bacterial replication. Specifically, CFIm25 enhances production of the antibacterial peptide LL-37, increases reactive oxygen species and nitric oxide levels, suppresses arginase activity and lactate production, and stimulates release of pro-inflammatory cytokines while inhibiting anti-inflammatory cytokines. Depletion studies show TAB2 mediates CFIm25s antibacterial effects by activating both MAPK and NF-kB pathways. Our findings highlight APA regulation as a potential target for boosting immune defenses and developing treatments for chronic bacterial infections.

immunology↗

bioRxiv2026

Estimation of Absolute Protein-DNA Binding Free Energy using Streamlined Geometric Formalism

Protein-DNA complexes are involved in vital cellular functions like gene regulation, replication, transcription, packaging, rearrangement, and damage repair. In this work, streamlined geometric formalism for computing the absolute binding free energy was used to obtain chemical accurate in silico estimation of binding free energy of three Protein-DNA complexes. Additionally, molecular interactions between Protein and DNA involved hydrogen bonds, electrostatic, van der Waals, and hydrophobic interactions. Using this formalism, researcher can obtain the absolute binding free energy for a Protein-DNA complex with remarkable accuracy and modest computational cost.

biophysics↗

bioRxiv2026

A Functional Placenta-On-Chip Model For Maternal-Fetal Transport

The human placenta functions as a highly specialised barrier that integrates trophoblast differentiation, endocrine activity, and regulated transport of molecules to sustain fetal development. Experimental interrogation of placental barrier function remains challenging due to limited access to human placental tissue and the complexity of existing in vitro models. Here, we report a static, two-chamber placenta-on-chip platform designed to recapitulate key structural and functional attributes of the human placental barrier within an experimentally accessible format. The device design prioritises open maternal compartmentalisation and diffusion-dominated transport, reflecting the haemochorial nature of human placentation. It also remains compatible with standard multi-well plate formats for parallel experimentation. In this two-chambered device, separated by an extracellular matrix-loaded/coated microporous membrane, the trophoblast supports trophoblast syncytialisation, sustained {beta}-human chorionic gonadotropin secretion, and selective barrier function. The engineered barrier restricts macromolecular transport while permitting controlled diffusion of small solutes. Glucose transport across the device is strongly dependent on cellular configuration, with inclusion of the endothelial layer significantly modulating nutrient flux and yielding fetal-to-maternal glucose ratios comparable to those reported in vivo. The platform further supports directional transfer of urea from the fetal to the maternal compartment, demonstrating bidirectional metabolite exchange relevant to placental waste clearance. Under hyperglycemic conditions, glucose transport across the barrier increases without evidence of barrier breakdown, indicating sensitivity to metabolic perturbation. This scalable design of a placenta-on-chip platform provides a robust framework for studying placental transport, metabolic regulation, and barrier integrity. It offers broad application in placental biology, pregnancy-associated pathologies, and screening for pregnancy-safe drugs.

bioengineering↗

bioRxiv2026

Global Metabolomic Analysis of Lytic KSHV Infection: Induced Host Nucleotide Metabolism is Required for Infectious Virus Production

Kaposis Sarcoma Herpes Virus (KSHV) is the etiological agent of Kaposis Sarcoma (KS) which is known to cause metabolic stress in infected host cells. KSHV reprograms host metabolic pathways for efficient viral replication and infectious virion production. Here, we report a time-course global metabolomics study conducted in the doxycycline-inducible iSLK.BAC16 cells to compare latent and lytic KSHV infection. Our data show that amino acid, central carbon, and nucleotide metabolic pathways are highly dysregulated upon reactivation to lytic replication. During lytic KSHV infection, pathway enrichment analysis shows that the top two most significantly impacted and dysregulated pathways are purine and pyrimidine metabolism. Further experiments have shown that nucleotide metabolism is required during lytic KSHV infection to produce maximal infectious virus. Treatment with the FDA-approved drug, methotrexate (MTX), a folate antagonist that inhibits cellular DHFR and decreases nucleotide metabolism by reducing tetrahydrofolate cofactors, significantly reduced KSHV late lytic viral gene expression upon reactivation compared to control. Additionally, titering cell-free supernatants from MTX-treated lytic KSHV-infected cells showed a significant reduction in infectious virion production. Furthermore, by adding folinic acid (FA), a downstream metabolite of the MTX-DHFR inhibition step, in the presence of MTX, late lytic gene expression and infectious virion production were significantly rescued. Furthermore, we observed a significant decrease in viral titer of murine herpesvirus 68 (MHV-68), a model virus to study gammaherpesvirus, after MTX treatment. Overall, our study demonstrates that metabolic inhibition during lytic gammaherpesvirus infection decreases productive infection and hence, serves as a potential therapeutic antiviral target.

microbiology↗

bioRxiv2026

Dark state-mediated photobleaching in mCherry-basedred fluorescent proteins

Developing bright and photostable red fluorescent proteins (RFPs) is one of the holy grails of the protein engineering community. Despite several attempts, finding such fluorescent proteins (FPs) has remained elusive. One bottleneck to engineering next generation RFPs is our lack of understanding of non-fluorescent or dark state properties in such constructs. Here, we develop a theoretical and experimental framework that describes how photobleaching decays in FPs relates to dark state conversion and ground state recovery. Our systematic photophysical investigation of mCherry and mCherry-d, an RFP with enhanced dark state behavior, showed the presence of photodestructive dark states in such FPs. Molecular dynamics simulations reveal enhanced fluctuation around the imidazolinone-end of the chromophore in mCherry-d, potentially facilitating conversion to non-fluorescent states. Collectively, this work quantifies dark state kinetics and gives insights into engineering dark states in RFPs to develop bright yet photostable molecular probes.

biophysics↗

bioRxiv2026

Myeloid PINK1 represses mtDNA release and immune signaling that impacts neuronal pathology in patient-derived idiopathic PD models

Parkinsons disease (PD) is a neurodegenerative disorder marked by the development of cardinal motor deficits preceded by a protracted prodromal period of non-motor symptoms often involving the gastrointestinal (GI) tract. There is an emerging consensus that both the peripheral immune system and local neuroinflammation play key roles in the etiology of PD. We previously demonstrated a critical function for the Parkinsons related proteins PINK1 and Parkin as repressors of the innate to adaptive immune response in cultured cells and mouse models of infection. However, it remained unclear whether these processes were conserved in patient-derived models, and precisely how immune signaling may ultimately drive the death of dopaminergic neurons. Here we show that GI infection of PINK1 knockout (KO) mice triggered acute neurodegeneration which was evident early in the enteric nervous system. Treating wild type enteric or dopaminergic neurons with conditioned medium from immune-stimulated PINK1 KO macrophages was sufficient to promote neuronal disruption in both mouse and human neurons in vitro. Within immune-activated macrophages, we reveal that loss of PINK1 led to an enhanced release of mitochondrial DNA (mtDNA) within mitochondrial derived vesicles, leading to the activation of cGAS/STING pathways. These changes were seen in both mouse/human in vitro models and in PD patient-derived primary macrophages. Notably, pharmacological modulation using a PINK1 activator with high therapeutic potential attenuated pro-inflammatory profiles elicited by the mtDNA-dependent STING/NF-{kappa}B pathway in idiopathic patient-derived macrophages. Ultimately, our study lays the foundation for understanding PINK1-related peripheral macrophage mechanisms in idiopathic PD and provides a target for further development to treat the disease at early stages. Graphical abstractPINK1-related immune mechanisms of Parkinsons disease and associations with early neurodegenerative events. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/694713v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@6f6488org.highwire.dtl.DTLVardef@13139aaorg.highwire.dtl.DTLVardef@c0d4d1org.highwire.dtl.DTLVardef@1d41e25_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2025

A multiscale modeling approach to study the role of mechanics and inflammation in pathophysiology of articular cartilage

Mechanical loading regulates chondrocyte health in articular cartilage. While physiological stimuli maintain homeostasis, supra-physiological stimuli from joint injuries disrupt it, leading to osteoarthritis (OA). OA is a prevalent degenerative joint disease affecting millions worldwide. OA progression involves complex mechanical and biochemical interactions across multiple length scales, which are challenging to investigate experimentally. In silico models provide an effective framework to explore these mechanisms. This study developed an integrated multiscale modeling framework for articular cartilage. It combined finite element (FE) models at tissue and cellular scales with an intracellular gene/protein regulatory network. The network incorporated key chondrocyte mechanotransduction and inflammatory pathways. A Hills function was used to link cellular forces from the FE model to a mechanical loading input to the regulatory network. Hills function constants were calibrated using a genetic algorithm approach. Calibration was performed by matching experimental and simulated expressions of COL-II and ADAMTS5 of cartilage explants under 20% dynamic compression. As a validation step, model simulations were performed at 10% dynamic compression of cartilage explants. COL-II and ACAN were overestimated, and ADAMTS5 was underestimated compared with experimental data. Furthermore, predicted sGAG loss matched the trend of experimental data. Simulated chondrocyte responses for varying spatial locations revealed spatial heterogeneity of chondrocyte activity. Over-all, the multiscale modeling workflow developed in this study provides a first step towards a powerful tool to increase the understanding of the complex interplay of mechanics and inflammation in articular cartilage. By integrating tissue, cellular, and intracellular scales, it offers a comprehensive framework for studying cartilage mechanobiology and guiding future therapeutic strategies. HighlightsO_LIDeveloped an integrated multiscale model linking tissue, cellular mechanics, and gene regulation in articular cartilage. C_LIO_LICoupled cellular mechanical forces to gene regulatory networks using Hills function approach. C_LIO_LICalibrated Hills function parameters via genetic algorithm using experimental cartilage explant compression data. C_LIO_LIPredicted spatial heterogeneity of chondrocyte activity and cartilage biomarker expression under dynamic compression C_LIO_LIEstablished computational framework can be used for studying cartilage mechanobiology and osteoarthritis therapeutic strategies C_LI

bioengineering↗

bioRxiv2025

DRP1-mediated mitochondrial dynamics orchestrate EMT in glioblastoma cells

BackgroundEpithelial to mesenchymal transition (EMT), a differentiation process, frequently imparts invasive properties in Glioblastoma Multiforme (GBM), which leads to a poor prognosis. Cells lose apical-basal polarity, cell-cell connections, and/or chemo-resistance during EMT, which can result in the spread of cancer and the acquisition of additional stem cell-like traits. It is unclear how organelle dynamics influence EMT in this respect. The interaction between cytoskeletal and mitochondrial regulators governing GBM cell EMT is explored in this article. Results and DiscussionIn GBM cells, we observed that TGF-{beta}-induced EMT led to a proliferative arrest, which was accompanied by a fragmented mitochondrial morphology, elevated expression of fission markers such as DRP1, MFF, and FIS1, and most importantly, localization of mitochondria near the cell boundaries. An increase in mitochondrial ROS accompanied this, but their functional status was indicated by a higher oxygen consumption rate (OCR). Additionally, cytoskeleton re-distribution and EMT reversal were the outcomes of si-RNA-mediated elimination of the fission-marker DRP-1 or pharmacological inhibition of fission by Mdivi-1. On the other hand, drugs that disrupt the cytoskeleton, shifted the spatial distribution of mitochondria to the perinuclear area, which had an adverse effect on EMT. Notably, it was shown that RhoA, a protein that helps organize the actin cytoskeleton, co-immunoprecipitates with DRP1 and governs both cytoskeletal dynamics and mitochondrial fission in its presence. ConclusionOur research sheds substantial insight on the current interactions between the cytoskeleton and mitochondrial spatial dynamics that control EMT in GBM cells, which may have significant therapeutic implications. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=164 SRC="FIGDIR/small/694080v1_ufig1.gif" ALT="Figure 1"> View larger version (41K): org.highwire.dtl.DTLVardef@81b796org.highwire.dtl.DTLVardef@3bec9aorg.highwire.dtl.DTLVardef@2a79c3org.highwire.dtl.DTLVardef@9ff14a_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2025

Phase separation as a concentrating mechanism of protein/peptide hormones for the secretory granule storage

Protein/peptide hormones in the regulated secretory pathway are stored within secretory granules (SGs) as densely packed aggregates for extended periods of time until their stimulated release. These aggregated dense cores are reported as functional amyloids for several pituitary hormones. However, the molecular events initiating hormone aggregation and SG biogenesis remain poorly understood. Using a diverse set of protein/peptide hormones with different sizes and structures, we demonstrated that all these hormones undergo phase separation in trans-Golgi network (TGN)-relevant conditions (including low pH, the presence of glycosaminoglycans, etc.), which rapidly transitioned into solid-like structures and eventually form amyloid fibrils. Further, the cellular model expressing two protein hormones (GH-EGFP and PRL-EGFP) showed the highly dynamic, liquid-like condensate formation at the TGN volume, which was transported via microtubule to the cellular periphery/tips and formed a ready pool of mature SGs containing amyloid-rich hormone aggregates. Importantly, both in vitro and cellular studies confirmed that solid-like amyloid aggregates are reversible and can release bioactive monomeric hormones, recapitulating regulated exocytosis. Together, our findings suggest hormone phase separation at the TGN as a common molecular principle for concentrating cargo, driving rapid functional aggregation, and ensuring efficient storage within SGs.

biochemistry↗

bioRxiv2025

Genomic characterization of type I-E* CRISPR-Cas systems in Klebsiella pneumoniae: association of spacer diversity and antimicrobial resistance

BackgroundKlebsiella pneumoniae, known to acquire antimicrobial resistance genes (ARGs) through horizontal gene transfer, possess type I CRISPR-Cas systems. This study investigated the association of multidrug resistance (MDR) and CRISPR-Cas in septicemic K. pneumoniae, along with comparative analysis of CRISPR-positive global K. pneumoniae. MethodsArchived K. pneumoniae from septicemic neonates (2008-2020) were assessed for CRISPR-Cas system, cas gene expression and correlation with ARG carriage. Whole-genome sequencing was performed and diversity of spacers, protospacers adjacent motifs (PAMs), targeted plasmids, were evaluated. Comparative analyses were performed for CRISPR-positive global K. pneumoniae. ResultsTwenty-five percent of study K. pneumoniae possessed complete type I-E* CRISPR-Cas comparable to 22% of global K. pneumoniae, which were distributed equally to type I-E & I-E*. CRISPR-positive study strains (83%) were MDR, and exhibited no significant association of CRISPR-Cas with MDR phenotype. Spacers noted in non-MDRs were diverse, showed increased average count and identified more diverse PAMs compared to spacers from MDR strains. Plasmids harboring ARGs such as blaNDM, blaCTX-M, qnrS1, mcr-8, etc. were frequently targeted by spacers from non-MDRs. Presence of CRISPR-Cas system in epidemic MDR clones such as ST14/15/23 in I-E* (local, global) and ST147 in I-E (global), indicated a lineage-specific association with CRISPR-Cas subtypes. ConclusionThis study demonstrated the co-existence of CRISPR-Cas systems within both MDR and non-MDR K. pneumoniae, with no significant correlation with either group. However, presence of diverse spacers in non-MDR strains that identified more PAMs and targeted ARG-bearing plasmid implied role of CRISPR-Cas system in limiting ARG acquisition.

genomics↗