Biology subjects

Saha, A.

Publications and source records attributed to Saha, A..

At least 37 records · Page 2Linked to original sources

bioRxiv2026

Snapshots of Internal Protein Crystal Architecture at the Nanoscale

Macromolecular crystallography has historically inferred models of internal crystal architecture from reciprocal-space measurements of Bragg reflections. Nevertheless, direct real-space visualization of crystallographic disorder remains elusive, particularly at the nanoscale. Using a 15-nanometer probe, here we apply both ambient-temperature and cryogenic four-dimensional scanning transmission electron microscopy (4D-STEM) to map the topography of coherently diffracting domains (CDDs) in lysozyme and myoglobin microcrystals at length scales 100x finer than conventional X-ray and electron beams. Virtual dark-field reconstructions from individual Bragg reflections reveal that each peak arises from spatially distinct subvolumes. Subdomain analysis demonstrates that these CDDs behave as orientationally monolithic units analogous to single mosaic blocks. Under sustained irradiation, protein CDDs undergo continuous rearrangements spanning several micrometers of internal movement. Furthermore, pinpoint high-dose "impact crater" experiments reveal delocalized radiolytic damage propagating hundreds of nanometers from primary irradiation sites, behavior similar to small-molecule crystals but amplified in both rate and magnitude. Together, these results establish macromolecular microcrystals as dynamic assemblies whose internal architecture continuously reorganizes during irradiation, laying the foundation for realistic models of mosaicity directly informed by both real-space and reciprocal-space observations.

biophysics↗

bioRxiv2025

Fus depleted oligodendrocytes reduce neuronal damage and attenuate AD progression in the AppNL-G-F mouse

AbstractOligodendrocytes (OL) and myelin abnormalities have emerged as important contributors to the pathogenesis of Alzheimers Disease (AD). OL maintain neuronal health through myelin axon interactions and by supplying neurotrophic and metabolic support. To gain insight on how OL and myelin may improve neuronal deficits associated with AD, we have generated a novel mouse model (AD/cKO) by crossing the AppNL-G-F mouse which carries three human AD mutations in the mouse App gene with the FusOLcKO, which has thicker myelin associated with greater cholesterol biosynthesis. The spatial working memory deficits manifested by the aged AD mouse were fully rescued by the FusOLcKO. This outcome was associated with reduced neuronal oxidative damage, preserved presynaptic structures at the plaque niches and a shift in microglia state at the niches in both hippocampus and cortex. In contrast, plaque burden and microglia density were decreased in the hippocampus but not in cortex, uncoupling the neuronal and microglia effects from the amyloid burden. Single cell transcriptomics of AD/cKO hippocampal OL revealed upregulation of energy metabolism and antioxidant genes, suggesting a role of OL enhanced energy metabolism in protecting neurons and affecting microglia state in AD pathology.

neuroscience↗

bioRxiv2025

STELAR-X: Scaling Coalescent-Based Species Tree Inference to 100,000 Species and Beyond

Summary methods reconstruct species trees from collections of gene trees while accounting for gene tree discordance and provide a statistically consistent framework for phylogenomic inference under the multispecies coalescent model. While existing triplet- and quartet-based approaches such as ASTRAL and STELAR have provable statistical consistency, their running time and memory usage restrict their applicability to ultra-large datasets. We introduce STELAR-X, a statistically consistent and highly scalable triplet-based phylogenetic inference algorithm that achieves an asymptotically optimal memory complexity of $O(nk)$ for \textit{n} species and \textit{k} gene trees, essentially matching the input size and allowing analyses to remain feasible as long as the input trees fit in memory, while also substantially reducing running time. STELAR-X achieves this through a compact integer tuple-based encoding of tree bipartitions, efficient precomputation of bipartition weights, and GPU parallelism. These innovations substantially reduce computational overhead in the underlying dynamic programming framework. Experiments demonstrate that STELAR-X achieves unprecedented scalability. On simulated datasets with 10,000 taxa and 1,000 gene trees, STELAR-X runs 3,576$\times$ faster than ASTRAL-MP (the most scalable variant of ASTRAL) while using 13.9$\times$ less CPU memory. STELAR-X analyzed a dataset of 100,000 taxa and 1,000 genes in 34.37 minutes using 58.40 GB RAM, and a 100,000-gene dataset with 1000 taxa in just 3.32 minutes using 74.10 GB RAM, scales that were previously intractable for statistically consistent summary methods. Moreover, applying STELAR-X to two large-scale avian datasets produced trees highly consistent with established bird phylogenies, demonstrating its robustness on biological data.

bioinformatics↗

bioRxiv2025

MExConn: A Mechanistically Interpretable Multi-Expert Framework for Multi-Organelle Segmentation in Connectomics

Electron microscopy (EM) provides subcellular resolution which has made it a critical tool in fields such as cellular biology and connectomics. However, manual annotation of subcellular organelles in these EM images is extremely labor-intensive and impractical at scale. While computational segmentation methods have been developed, most existing approaches are limited to segmenting a single organelle at a time, neglecting the inherent shared information present in EM images containing multiple organelles. To address this, we present MExConn, the first known interpretable multi-expert U-Net architecture in the connectomics field that employs a shared encoder and multiple decoder heads to simultaneously segment multiple organelles from the same input EM image. MExConn significantly outperforms five baselines, including single-organelle model and four state-of-the-art connectomics segmentation models in all evaluation metrics, reducing the Variation of Information by up to 33.54% on average across organelles. A key novelty of our approach is that MExConn offers mechanistic interpretability by revealing that the shared encoder learns shared representations essential for accurately segmenting multiple organelles. Through systematic analysis of encoder gradients with respect to each decoder output, we identify channel-wise importance profiles and reveal that many encoder channels are jointly essential for all organelles, while others are organelle-specific. Rigorous experiments on three connectomics datasets demonstrate the effectiveness of MExConn in both segmentation performance and interpretability, establishing it as a principled approach for multi-organelle analysis in connectomics. The source code is publicly available at https://github.com/abrarrahmanabir/MExConn.

neuroscience↗

bioRxiv2025

Blind Prediction of Complex Water and Ion Ensembles Around RNA in CASP16

Biomolecules rely on water and ions for stable folding, but these interactions are often transient, dynamic, or disordered and thus hidden from experiments and evaluation challenges that represent biomolecules as single, ordered structures. Here, we compare blindly predicted ensembles of water and ion structure to the cryo-EM densities observed around the Tetrahymena ribozyme at 2.2-2.3 [A] resolution, collected through target R1260 in the CASP16 competition. 26 groups participated in this solvation cryo-ensemble prediction challenge, submitting over 350 million atoms in total, offering the first opportunity to compare blind predictions of dynamic solvent shell ensembles to cryo-EM density. Predicted atomic ensembles were converted to density through local alignment and these densities were compared to the cryo-EM densities using Pearson correlation, Spearman correlation, mutual information, and precision-recall curves. These predictions show that an ensemble representation is able to capture information of transient or dynamic water and ions better than traditional atomic models, but there remains a large accuracy gap to the performance ceiling set by experimental uncertainty. Overall, molecular dynamics approaches best matched the cryo-EM density, with blind predictions from bussilab_plain_md, SoutheRNA, bussilab_replex, coogs2, and coogs3 outperforming the baseline molecular dynamics prediction. This study indicates that simulations of water and ions can be quantitatively evaluated with cryo-EM maps. We propose that further community-wide blind challenges can drive and evaluate progress in modeling water, ions and other previously hidden components of biomolecular systems.

biophysics↗

bioRxiv2025

Bhlhe40 Coordinates T Cell Programs with Distinct CD4 and CD8 T Cell Requirements for Anti-PD-1 Versus Anti-CTLA-4

The transcriptional programs enabling T cells to mediate anti-tumor immunity remain incompletely defined. Here, we identify Bhlhe40 as a key transcriptional regulator that coordinates both CD4 and CD8 T cell effector programs, revealing divergent cell-specific requirements during anti-PD-1 versus anti-CTLA-4 immune checkpoint therapy (ICT). Using conditional knockout mice, we show that anti-PD-1 efficacy depends on CD8 T cell-intrinsic Bhlhe40, whereas anti-CTLA-4 remains effective through Bhlhe40-dependent CD4 T cell Th1 programs that buffer impaired effector function in Bhlhe40-deficient CD8 T cells. Mechanistically, loss of Bhlhe40 reduces IFN-{gamma} production and skews CD8 T cells toward TCF-1-expressing progenitor exhausted/stem-like states at the expense of effector differentiation, impairing glycolytic fitness under both therapies and mitochondrial function during anti-PD-1 treatment, thereby revealing a Bhlhe40-dependent coupling between effector differentiation, cytokine production, and metabolic fitness that is particularly critical for anti-PD-1 efficacy. CD8 T cell-intrinsic Bhlhe40 also promotes critical ICT-induced remodeling from M2-like CX3CR1 macrophages to inflammatory iNOS macrophages. Analysis of human cancer datasets supported our preclinical observations, revealing that BHLHE40 is enriched in tumor-reactive and activated/exhausted CD8 T cells, where its expression is inversely correlated with TCF7 (TCF-1) and positively associated with TOX, GZMB, and IFNG. Moreover, persistent CD8 T cell clones from basal cell carcinoma responders exhibited significantly higher BHLHE40 expression at pre-treatment than those from non-responders to PD-1 blockade. Together, these findings establish Bhlhe40 not only as a transcriptional coordinator of T cell effector programs, but also as a therapy-specific, subset-dependent determinant that differentially governs CD4 and CD8 T cell contributions to anti-PD-1 and anti-CTLA-4 efficacy.

immunology↗

bioRxiv2025

MACS: Multi-Domain Adaptation Enables Accurate Connectomics Segmentation

Connectomics aims to map the brains neural wiring by segmenting cellular structures from high-resolution electron microscopy (EM) images. Manual labeling and proofreading remain a major bottleneck for accurate extraction of microstructures. While computational models have advanced automated segmentation, they typically require training from scratch on each dataset, demanding substantial annotated data. Domain adaptation methods address this by transferring knowledge from a labeled source to a less-annotated target. However, existing approaches are limited to adaptation from a single source domain. This overlooks the potential benefits of integrating information from multiple diverse domains, motivating the development of multidomain adaptation. To address this, we propose MACS, the first known multi-domain adaptation framework that combines knowledge from multiple heterogeneous source domains to learn segmentation in the target domain, and employs active learning to efficiently select the most informative target samples for annotation. MACS uses information-theoretic weighting to combine source domains, and introduces a novel and efficient Bayesian Laplace approximation for uncertainty estimation. Our extensive experiments across nine connectomics datasets demonstrate that MACS consistently and substantially outperforms state-of-the-art models, even under limited annotation budgets, with a mean improvement of 5.89% at the lowest annotation budget and 27.72% at the highest annotation budget. In-depth analyses further reveal that MACS offers mechanistic interpretability by quantifying and explicitly upweighting the most transferable source domains for each target. The preprocessed datasets and the source code of MACS are publicly available at http://github.com/abrarrahmanabir/MACS.

neuroscience↗

bioRxiv2025

Lifestyle-associated variation in type IV secretion systems between phytopathogenic and environmental Ralstonia

Type IV secretion systems (T4SSs) are versatile machines with variable functions including DNA uptake and release, protein translocation, and DNA conjugation. However, the diversity, distribution, and functional roles of the T4SS in the Ralstonia genus remain poorly understood. The Ralstonia solanacearum species complex (RSSC) comprises three species of plant-pathogenic bacteria that cause bacterial wilt disease. The Ralstonia genus also includes non-RSSC species that are primarily environmental bacteria and rare opportunistic human pathogens. This study compared the diversity and phylogenetic distribution of T4SSs in the RSSC phytopathogens vs. non-RSSC environmentals. Phylogenetic analysis of VirB4 sequences and synteny analysis revealed 16 distinct T4SS clusters in Ralstonia, with ten clusters found in RSSC phytopathogen genomes, twelve in non-RSSC environmental genomes, and six clusters in both groups. Collectively, these gene clusters were more prevalent in non-RSSC environmental genomes. The presence of type IV coupling protein and relaxase genes suggests that at least 14 of these T4SS gene clusters could be putative DNA conjugation systems. The clusters were encoded on accessory plasmids of various sizes or as integrative and conjugative elements (ICEs) on the chromosome or megaplasmid. The putative regions of transfer for T4SS gene clusters in the RSSC phytopathogen genomes often contained type III effectors, type VI secretion toxin/antitoxin clusters, and hemagglutinin gene clusters. In contrast, the non-RSSC environmentals were enriched in heavy metal metabolism and resistance genes. One of the 16 T4SS clusters, cluster i, exhibited evidence of specialization for the RSSC phytopathogens. These findings shed light on the eco-evolutionary differences in the Ralstonia genus. Impact statementThe Ralstonia genus contains the Ralstonia solanacearum species complex (RSSC), a group of globally important plant pathogens that impact food security. These pathogens are known to have an expansive, open pangenome with high levels of gene flow. To shed light on the eco-evolutionary differences between RSSC phytopathogens and closely related environmental species, we explored the potential role of type IV secretion systems (T4SSs) in horizontal gene flow within the Ralstonia genus. Surprisingly, these mobile genetic elements were less common in the phytopathogens than the environmentals. Nevertheless, we identified a particular T4SS gene cluster encoded on an accessory plasmid that appears to be specialized to the pathogenic lifestyle of the RSSC. This specialized cluster harbors genes that drive RSSC host range (type III effectors) and others that likely allow these pathogens to antagonize the plant microbiota (type VI secretion toxins and hemagglutinin two partner secretion systems). Moreover, this study sheds light on the cryptic lifestyles of the poorly studied environmental Ralstonia species, revealing that their conjugative T4SSs frequently carry heavy metal metabolism and resistance genes. Overall, this study provides a foundation to investigate the functional roles of T4SS clusters and their cargo genes in the fitness of phytopathogenic and environmental Ralstonia. Data summarySupplemental Table S1 lists details of the RSSC phytopathogen, non-RSSC environmental, and Burkholderiaceae family genomes used in this study. Supplemental Table S2A is the final list of 501 VirB4 sequences collectively identified in 636 RSSC phytopathogen genomes and 143 non-RSSC environmental genomes. Supplemental Table S2B includes the annotations and NCBI accessions for every gene and protein sequence in reference clusters a-p. Supplemental Table S2C is the list of putative T4SS cargo genes identified in complete Ralstonia genomes. Supplemental Table S2D is the list of putative T4SS cargo genes identified in cluster i regions from draft and complete Ralstonia genomes. Supplemental File S1 is the multiple sequence alignment (MSA) input for HMMER, made from the 753 VirB4 protein sequences from the Burkholderiaceae family genomes. Supplemental Files S2 and S3 are PDF-format versions of the species trees displaying the presence of T4SS gene clusters in RSSC phytopathogens and non-RSSC environmentals, respectively. Supplemental File S4 is the species tree displaying the presence of RSp0179 and RSp1521 in the Ralstonia genus. Supplemental File S5 is the MSA input for FastTree 2, made from the VirB4 protein sequences from Ralstonia genomes. Supplemental Files S6-S9 are various formats of the VirB4 protein tree in Figure 1. Supplemental Files S10-S25 are the GBK files for reference clusters a-p. Supplemental File S26 is the clinker output comparing the reference clusters. Supplemental Files S27-S36 are the clinker outputs comparing the putative regions of transfer of T4SSs in complete Ralstonia genomes. Supplemental File S37 is an MSA analysis comparing RSp1521 to AcvB homologs. Supplemental File S38 is the clustered average nucleotide identity (ANI) matrix for the putative regions of transfer of cluster i T4SSs in draft and complete Ralstonia genomes. Supplemental File S39 is the clinker output comparing the cluster i regions in draft and complete Ralstonia genomes. All Supplemental Tables and Files are available through Zenodo (DOI: 10.5281/zenodo.14873518). O_FIG O_LINKSMALLFIG WIDTH=199 HEIGHT=200 SRC="FIGDIR/small/675681v2_fig1.gif" ALT="Figure 1"> View larger version (43K): org.highwire.dtl.DTLVardef@1640850org.highwire.dtl.DTLVardef@5de6f5org.highwire.dtl.DTLVardef@e605feorg.highwire.dtl.DTLVardef@1937bac_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOFigure 1.C_FLOATNO Sequence diversity of the T4SS marker VirB4 in the Ralstonia genus. VirB4 protein sequences (n=496) were identified by a custom hidden Markov model (HMM) search, and an approximately-maximum-likelihood tree was built with FastTree 2 from a MUSCLE multiple sequence alignment (MSA) of the VirB4 sequences. Bootstrap values (0 to 1) from 1,000 resamples are shown for key nodes. The unrooted tree was visualized in iTOL and labeled using Affinity Designer. The 16 distinct T4SS gene clusters (a-p) are outlined and labeled. Circles denote clusters that are present in the RSSC phytopathogens and triangles denote clusters that are present in the non-RSSC environmentals. Colored clusters were found in RSSC phytopathogen genomes, and clusters with dashed outlines were not found in the RSSC phytopathogens. Supplemental files contain the virB4 gene list (Supplemental Table S2A), the VirB4 protein sequence MSA (Supplemental File S5), the Newick file for the tree (File S6), a PDF of the unrooted tree with branch labels (File S7), and PDFs of the rectangular tree with branch labels, without and with colors (Files S8 and S9). C_FIG This studys newly sequenced genomes, Gazipur 4 and Gazipur 5, are available on NCBI with the following accessions: GCF_049860735.1 and GCF_049860725.1, respectively. The two contigs containing the cluster j T4SS were submitted to NCBI through the Third Party Annotation (TPA) section of the DDBJ/ENA/GenBank databases with the following accessions: BK072068-BK072069. These contigs were assembled from SRA reads under the accession: SRR18649448.

microbiology↗

bioRxiv2025

Quantifying the role of pre-existing tissue resident cellular immunity in limiting respiratory virus transmission

Viral transmission from infected donors to uninfected recipients is the key event underlying the spread of viral pathogens at the level of a host population. Successful viral transmission from a donor to a recipient depends on several factors including the infectiousness of the donor. Donor infectiousness in turn can depend on the viral kinetics and viral load of the donor, donor behavior and symptoms, and donor immunity. Here, we use a mouse model of murine respirovirus (otherwise known as Sendai virus SeV) infection to quantitatively explore donor determinants of respiratory virus transmission. The experimental transmission studies we analyze are specifically designed to address the effect that pre-existing donor immunity may have on transmission potential by studying SeV transmission from both immunized and control (placebo-immunized) donors to naive recipients. We specifically focus on the impact of tissue resident memory (TRM) CD8 T cells on donor transmission potential by considering immunization strategies that primarily generate CD8 T cell immunity. Through quantitative analyses of these experiments, we find that pre-existing CD8 TRMs act to reduce donor transmission potential. This reduction can be in part explained by a reduction in total infection load in immunized donors. However, even once differences in infection load between immunized and control donors are accounted for, immunized donors still have reduced infectiousness relative to control donors. We explore possible reasons for this unexpected pattern using a mathematical model that integrates within-host viral dynamics and between-host transmission occurrences. Analysis of model simulations, along with observations from knock-out experiments, suggests that interferon gamma (IFN-{gamma}) may be partly responsible for the observed differences in infectiousness between control and pre-immune donors. Future experimental transmission studies should consider measuring IFN-{gamma} levels when interpreting transmission outcomes in the context of host immunity.

immunology↗

bioRxiv2025

A Cryptic Binding Pocket Regulates the Metal-Dependent Activity of Cas9

Cas9 is a metal-dependent nuclease that has revolutionized gene editing across diverse cells and organisms exhibiting varying ion uptake, metabolism, and concentrations. However, how divalent metals impact its catalytic function, and consequently its editing efficiency in different cells, remains unclear. Here, extensive molecular simulations, Markov State Models, biochemical and NMR experiments, demonstrate that divalent metals - Mg2+, Ca2+, and Co2+ - promote activation of the catalytic HNH domain by binding within a dynamically forming divalent metal binding pocket (DBP) at the HNH-RuvC interface. Mutations in DBP residues disrupt HNH activation and impair the coupled catalytic activity of both nucleases, identifying this cryptic DBP as a key regulator of Cas9s metal-dependent activity. The ionic strength thereby promotes Cas9s conformational activation, while its catalytic activity is metal-specific. These findings are critical to improving the metal-dependent function of Cas9 and its use for genome editing in different cells and organisms.

biophysics↗

bioRxiv2025

A water-based platform test of paired or group social dominance and neural activity in male and female mice

Social hierarchy is an evolutionarily-conserved phenomenon determined by social dominance behavior that has profound influence on health and relevance in neuropsychiatric disorders. Despite this, the neural mechanisms underlying social dominance remain unclear and current behavioral tests are limited. Here, we describe a novel platform test of social dominance where mice compete for space on a small, elevated platform surrounded by cold water and rank is calculated by total time spent on platform. To validate this assay, we conducted tube test followed by platform test in cages of male and female mice. We observed stable rank in both sexes using the platform test and saw notable differences in overall cage hierarchy between tube and platform. Motivated behavior as measured by attempts to get on the platform was reduced over time. Cooperative behavior as measured by shared time on platform was observed across all ranks but predominantly demonstrated by subordinate mice. Corticosterone levels were significantly higher in females but showed no rank-specific differences. Neuronal activity in the prefrontal cortex was not rank-dependent, however activity in the habenula scaled with rank in both sexes and was significantly correlated with dominance in males. We also investigated group social dynamics using the platform test and identified stable hierarchies with more exaggerated dominance compared to paired platform testing. These results introduce the platform test as a novel method for assessing social dominance behavior in male and female mice, which can be used to further our understanding of the neurobiology underlying social hierarchy.

neuroscience↗

bioRxiv2025

PE11 promotes intracellular persistence of Mycobacterium tuberculosis by inhibiting autophagy and lysosomal biogenesis by targeting the FLCN-lactate-TFEB signaling axis

Mycobacterium tuberculosis (Mtb) employs multiple virulence factors, including cell wall-associated proteins, to evade host immune responses. PE11, a cell wall-localized esterase, contributes to Mtb persistence by facilitating cell wall remodelling and resistance to acidic and antibiotic stress. Herein we describe a novel role of PE11 in subverting host autophagy through disruption of TFEB-mediated lysosomal function. PE11 promotes FLCN-dependent depletion of intracellular lactate to destabilize TFEB and thereby downregulate genes essential for autophagic flux and lysosomal acidification. Using a PE11-deficient Mtb strain, we demonstrate that PE11 targets the FLCN-lactate axis to regulate TFEB stability. Exogenous lactate supplementation restored TFEB stability, enhanced lysosomal acidification, and significantly reduced intracellular bacterial burden. Lactate also synergized with frontline anti-tubercular drugs to improve Mtb clearance. These findings establish PE11 as a key immune evasion factor and highlight lactate as a promising host-directed therapeutic to enhance bacterial killing and reduce antibiotic-associated toxicity.

microbiology↗

bioRxiv2025

Deletion of major shell protein of ethanolamine utilization microcompartment reduces intrinsic antibiotic resistance, biofilm and intracellular survival of Salmonella Typhimurium

With the high rise in Salmonella infection and emergence of antibiotic-resistant variants, developing a novel strategy to control the pathogen is imperative. Earlier studies revealed that Salmonella deploys ethanolamine (EA) metabolic machinery to disseminate in the intestine. Salmonella with a defect in EA metabolism manifests with lower intestinal colonization efficiency. Remarkably, the potential of EA metabolism as a therapeutic target is yet to explore. Our study revealed that supplementation of EA and vitamin B12 in both rich and minimal media enhanced biofilm formation, increased motility, and increased tolerance of Salmonella to some antibiotics. Conversely, mutants deficient in EA metabolic enzymes exhibited no physiological fitness. In Salmonella, EA metabolic enzymes are localized within a proteinaceous microcompartment (MCP) shell composed of thousands of copies of shell proteins encoded by five genes from the eut operon. Fascinatingly, bacterial cells with defective MCP shell due to mutation in the major shell proteins showed enhanced susceptibility towards a number of antibiotics in minimal media. The mutants were unable to form biofilm, produced lower curli expression and were defective in flagellar motility. Also, mutation in one of the major shell proteins reduced intramacrophagic viability of Salmonella. Notably, phenotypes were restored upon ectopic expression of corresponding genes. It was evident that mutation in the MCP shell proteins downregulated the expression of genes related to pathogenicity. Overall, this study sheds new light on understanding the relationship between EA metabolism and bacterial physiology that would pave the way for developing novel therapeutic interventions against Salmonella.

microbiology↗

bioRxiv2025

PRMT5 activity sustains histone production to maintain genome integrity

Histone proteins package DNA into nucleosomes, forming chromatin and thereby safeguarding genome integrity. Proper histone expression is essential for cell proliferation and chromatin organization, yet the upstream regulators of histone supply remain incompletely understood. PRMT5--a cell essential type II protein arginine methyltransferase frequently overexpressed in cancer--catalyzes symmetric dimethylation of arginine residues. Using time-resolved nascent transcriptional profiling, quantitative proteomics, and imaging, we show that PRMT5 activity is required to sustain histone transcription and histone protein synthesis during S phase. PRMT5 inhibition or knockdown leads to rapid histone mRNA depletion, loss of histone proteins, and accumulation of replicationassociated nuclear abnormalities. We further show that soluble histone H4 accumulates at histone locus bodies (HLBs) upon PRMT5 inhibition, and that PRMT5-substrate H4 Arginine 3 mutants localize more robustly to HLBs than do wildtype H4. These findings support a model in which PRMT5-mediated methylation of histone H4 regulates histone transcription. Our findings establish PRMT5 as a central coordinator of histone homeostasis and provide a mechanistic rationale for its essential role in proliferating cells.

cell biology↗

bioRxiv2025

Developmental Plasticity and Stromal Co-option Shape a Pituitary Neuroendocrine Tumor Transcriptional Continuum

Pituitary neuroendocrine tumors (PitNETs) are common intracranial neoplasms with complex biology underpinned by unresolved cellular origins, molecular heterogeneity, and microenvironment interactions. Here, we employ single-nuclei RNA-sequencing (snRNA-seq) of 419,874 cells from human normal pituitaries and PitNETs with spatial transcriptomics to resolve these challenges. We identify multi-hormonal neuroendocrine cells in both normal and tumor tissues, originating as early pseudotime intermediates from pituitary stem cells, revealing an inherent plasticity that blurs traditional lineage boundaries. PitNETs exhibit a transcriptional continuum across subtypes, challenging their classification into discrete categories. Trajectory analysis uncovers divergent cellular origins: silent gonadotroph adenomas (SGAs), prolactinomas, silent corticotroph adenomas (SCAs), and Cushings adenomas are closely linked to differentiated neuroendocrine cells, while somatotroph and null cell adenomas (NCAs) appear to derive more directly from adult stem cells. Tumor cells co-opt robust cell-cell communication networks found in normal adult neuroendocrine cells. Spatial profiling further demonstrates that perivascular niches enhance tumorigenicity through angiogenic and epithelial-mesenchymal transition programs. Our work redefines PitNETs as ecosystems shaped by developmental plasticity and microenvironmental crosstalk, offering a roadmap for future therapies targeting lineage fluidity and stromal dependencies.

cancer biology↗

bioRxiv2025

LIMD1 Loss Confers a GPX4-Dependent Cell State in Lung Cancer

LIMD1 (LIM domains containing 1) is a bona-fide tumour suppressor gene frequently lost during the early stages of non-small cell lung cancer (NSCLC) development, resulting in a worse outcome for LIMD1-deficient patients. LIMD1 deficiency is present in approximately 50% of NSCLC cases, representing at least 21,000 patients in the United Kingdom and 1.2 million worldwide. During cancer progression, cells can accumulate genetic changes that render them more dependent on certain genes for their survival. By performing CRISPR-Cas9 dropout screens, we identified GPX4 as a novel vulnerability in LIMD1 deficient LUAD cells. By targeting GPX4 using RNA interference (RNAi) and pharmacological intervention in our isogenic LUAD lines along with a non-transformed lung cell line, we validated GPX4 as a novel dependency in LIMD1 deficient cells. GPX4 is a key defence mechanism against ferroptosis, an iron-dependent form of regulated cell death. This state of increased ferroptosis susceptibility upon LIMD1 loss is due to increased basal reactive oxygen species levels and lipid peroxidation. Importantly, targeting GPX4 with ferroptosis inducing agents in NSCLC patients with LIMD1 loss may represent a novel therapeutic strategy.

cancer biology↗

bioRxiv2025

Linker Histone H1.5 Contributes to Centromere Integrity in Human Cells

Mammalian H1 linker histones comprise a group of 11 non-allelic variants which have key roles in modulating chromatin. H1 variant specific genomic distribution contributes to fine tuning regulation of gene expression and chromatin architecture. Contradictory reports on the presence and role of H1 histones at centromeres led us to further investigate whether H1s impact centromeric chromatin. In this study, we focused on H1.5 and by in vitro assays we showed that H1.5 directly interacts with centromeric-protein A (CENP-A) mononucleosomes. Notably, our in vitro findings revealed that H1 variants H1.0 and H1.2 can also bind CENP-A nucleosomes, although with differing affinities and signatures, asserting centromeric localization may not be unique to H1.5. In human cells, H1.5 localized to the centromere and chromatin immuno-precipitation revealed an interaction between H1.5 with CENP-A nucleosomes. Knocking down of H1.5 resulted in the loss of centromeric -satellite transcription, reduction in loading of new CENP-A, and the accumulation of mitotic defects. These data point to an unreported role for histone H1 in the regulation of mitotic integrity in human cells. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=120 SRC="FIGDIR/small/657682v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@26a35borg.highwire.dtl.DTLVardef@aecc44org.highwire.dtl.DTLVardef@1e49939org.highwire.dtl.DTLVardef@107a485_HPS_FORMAT_FIGEXP M_FIG Graphical AbstractProposed model of H1.5 function at the centromere. When H1.5 is bound to the CENP-A nucleosomes at the centromere, the centromeric chromatin allows RNAPII based transcription to generate -satellite transcripts, which in turn allows for de novo CENP-A loading. The absence of H1.5 blocks this transcription, leading to an accumulation of mitotic defects. C_FIG

biochemistry↗

bioRxiv2025

Combining structural modeling and deep learning to calculate the E. coli protein interactome and functional networks

We report on the integration of three methods that are computationally efficient enough to predict, on a proteome-wide scale, whether two proteins are likely to form a binary complex. The methods include PrePPI, which uses three-dimensional structure information as a basis for predictions, Topsy-Turvy which analyzes sequences using a protein language model, and ZEPPI which uses evolutionary information to evaluate protein-protein interfaces. We demonstrate how these methods can be integrated and validate the performance of the integrated method and its separate components at predicting E. coli protein-protein interactions through testing on the HINT high-quality literature-curated database of binary interactions. The integrated method identifies more high-confidence (FPR [≤] 0.001) interactions ([~]20K) than any of the component methods. The AF3Complex algorithm was used to predict the structures of 400 protein-protein interactions, and 78% of the integrated method predictions resulted in models deemed accurate by the AF3Complex evaluation score. Notably, essentially all AF3Complex models have at least partially overlapping interfaces with PrePPI models of the complexes. Finally, we clustered the high-confidence E. coli interactome and obtained 385 subnetworks which have high functional coherence defined by enrichment of Gene Ontology Biological Process terms, thus, illustrating that our methods which contain no explicit functional information provide biologically meaningful protein interactions. Biological insights derived from the subnetworks, including the annotation of proteins of unknown function, are discussed in detail. Overall, independent validations support the accuracy of the comprehensive E. coli interactome we have presented.

systems biology↗