Biology subjects

Pokharel, S.

Publications and source records attributed to Pokharel, S..

9 recordsLinked to original sources

bioRxiv2026

A dynamic molecular glue targets a plastic MDA5 filament interface to stimulate innate immunity

Innate immune signaling is a double-edged sword: uncontrolled activation drives autoinflammatory diseases, while controlled activation enhances antiviral and antitumor immunity. MDA5, a cytosolic dsRNA sensor that activates type I interferon signaling, mediates both immunopathology and protective immunity, yet small-molecule modulators have remained elusive. Here we report MA2, a first-in-class selective MDA5 agonist that acts as a molecular glue. MA2 binds a cryptic inter-protomer pocket within MDA5 filaments that undergoes ATPase-associated conformational remodeling. Rather than rigidly locking the interface, MA2 remains bound while accommodating and reshaping these structural transitions, strengthening MDA5-dsRNA and inter-protomer interactions and attenuating ATP hydrolysis. MA2 does not induce new filament assembly but potentiates pre-existing filaments, enabling context-dependent activation in dsRNA-enriched cells. MA2 enhances antiviral activity and synergizes with chemotherapeutic agents and natural killer cells to promote tumor cell killing. These findings establish dynamic molecular glues as a strategy for targeting conformationally plastic interfaces previously considered undruggable.

immunology↗

bioRxiv2026

Learning Shared Residue Backgrounds and Modification-Specific Offsets for PTM Site Prediction

Post-translational modifications (PTMs) are chemical changes added to proteins after translation. These changes affect protein function and regulation, and their disruption is linked to disease-associated mechanisms. Because experimentally validating all possible modification sites is impractical, many computational predictors have been developed for PTM site prediction. In this work, we study whether a shared model can represent common residue-background patterns while learning modification-specific background-to-positive offsets. This framing is especially relevant for residues such as lysine (K), which can be acetylated, ubiquitinated, methylated, or sumoylated depending on the surrounding protein context. We propose an anchor-guided rectified flow matching framework for multi-type PTM site prediction from protein language model embeddings. For each PTM--residue pair, the model builds residue-background anchors from PTM-compatible unannotated residues and positive anchors from experimentally annotated modified residues. Given a candidate residue and target modification type, the model compares the residue embedding with these anchor sets and uses a rectified flow module to estimate a modification-conditioned background-to-positive offset. This offset is combined with anchor-based features and used for site scoring. We evaluate the framework on a dbPTM-derived benchmark covering six commonly studied PTMs: phosphorylation, acetylation, ubiquitination, methylation, sumoylation, and N-linked glycosylation. In the shared-model setting, our approach achieves a macro AUPRC of 0.4195, improving over the gated multi-anchor baseline of 0.4154, while independently trained per-modification models achieve 0.4353. These results suggest that multi-type PTM prediction can be modeled within a single shared framework by combining residue-background anchors with modification-conditioned offset features.

bioinformatics↗

bioRxiv2026

Single-nucleus RNA sequencing reveals cell type-specific responses to heat stress in bovine mammary gland

BackgroundHeat stress (HS) poses a major challenge to the dairy industry by reducing milk production, yet its cell type-specific effects in the bovine mammary gland remain incompletely defined. In this study, we recorded production traits and collected mammary biopsies from cows under thermoneutral (TN), HS, and pair-fed (PF) conditions. ResultsClinical measurements confirmed HS-induced physiological alterations. Compared with TN cows, HS cows exhibited reduced dry matter intake (DMI), milk yield, and yields of fat, protein, and lactose, along with increased water intake and milk urea nitrogen. The use of PF controls indicated that decreased DMI accounted for 45% of the milk-yield reduction, whereas direct HS effects accounted for the remaining reduction. We applied single-nucleus RNA-seq (snRNA-seq) on mammary biopsies to generate cell-resolved HS responses. We identified 14 distinct cell clusters, including epithelial, immune, and stromal populations. Under the TN condition, casein genes (e.g., CSN1S1, CSN2) were broadly expressed across luminal cells but were attenuated under HS, whereas luminal alveolar cells showed relative upregulation. Heat shock protein genes were strongly induced by HS, primarily in epithelial clusters. Gene-set enrichment analyses revealed increased ribosomal activities across HS-responsive clusters and enrichment of protein folding and metabolic pathways in luminal alveolar cells, suggesting elevated proteostasis demands under stress. Pseudotime analysis positioned luminal cells along a progenitor-to-secretory trajectory under TN, accompanied by increased casein gene expression, whereas under HS, mature luminal cells shifted toward a homeostasis regulatory state. Cell-cell communication analysis demonstrated HS-induced remodeling of interepithelial signaling, including altered ERBB4-mediated signaling from luminal hormone-sensing to alveolar lineages. Finally, transcription factor activity profiling highlighted cell type-specific HS-activated regulators and their downstream target genes. ConclusionsTogether, this cell type-resolved atlas delineates how HS alters bovine mammary epithelial function, developmental state, and intercellular crosstalk. These findings point to proteostasis pressure, disrupted signaling pathways, and rewired regulatory networks as mechanistic contributors to reduced lactational performance under HS, offering insights for improving heat resilience in dairy cattle.

genomics↗

bioRxiv2025

Defying Salinity, Drought, and pH Extremes: A Multifunctional Rhizobacterium, Burkholderia gladioli ST3M-39a, Matches Fertilizer Efficacy in Wheat via Phosphate Solubilization

Global phosphorus scarcity and the environmental impacts of chemical fertilizers necessitate sustainable microbial alternatives for agriculture. We characterized Burkholderia gladioli ST3M-39a, a maize rhizosphere isolate, as a multifunctional plant growth-promoting rhizobacterium with exceptional climate resilience. The strain achieved rapid phosphate solubilization (177.96 {+/-} 5.26 {micro}g/mL within 24 h; molybdenum-antimony assay), zinc solubilization, and ammonia production, EPS production, and produced stress-alleviating enzymes (cellulase and protease). Crucially, it maintained robust growth and phosphate-mobilizing capacity under extreme abiotic stresses: pH 4.5-8.5, 7.5% NaCl salinity, and drought-mimicking low water activity (aw 0.950, 32% sorbitol). In wheat trials, ST3M-39a inoculation significantly increased the growth parameters (p < 0.05 vs. those of the uninoculated controls), resulting in 85-92% of the biomass stimulation observed with diammonium phosphate (DAP) fertilizer. This multifunctional stress tolerance, coupled with its near-fertilizer efficacy, positioned ST3M-39a as a transformative bioinoculant for degraded soils. Field validation of its agricultural deployment and ecological impact is now pivotal.

microbiology↗

bioRxiv2025

Reversible therapeutic resistance in EGFR mutant lung cancer caused by RB1 loss induced lineage plasticity

Treatment with EGFR tyrosine kinase inhibitors (EGFR TKI) is standard of care for patients with lung cancer initiated by activating mutations in the EGFR gene. While EGFR TKI treatment is effective, virtually all patients progress on therapy. Loss of function mutations in the RB1 tumor suppressor gene are associated with poor EGFR TKI outcomes, but underlying mechanisms remain unclear. Analysis of genetically engineered experimental models and human clinical specimens described here demonstrates RB1 loss has minimal impact on initial cell cycle responses to EGFR TKI but markedly accelerates acquired resistance over time. RB1 loss promotes transcriptional plasticity that enables rare cells to spontaneously assume reversible, resistance-conferring lineage states. These findings highlight the importance of non-genetic adaptations in driving acquired EGFR TKI resistance, advance our understanding of how RB1 impacts cancer, and identify opportunities to improve EGFR TKI treatment outcomes by targeting reversible epigenetic resistance mechanisms.

cancer biology↗

bioRxiv2024

pLM-DBPs: Enhanced DNA-Binding Protein Prediction in Plants Using Embeddings From Protein Language Models

DNA-binding proteins (DBPs) play critical roles in gene regulation, development, and environmental response across various species, including plants, animals, and microorganisms. While various machine learning and deep learning models have been developed to distinguish DNA-binding proteins (DBPs) from non-DNA-binding proteins (NDBPs), most available tools have focused on human and mouse datasets. As a result, there are limited studies specifically addressing plant-based DNA-binding proteins, which restricts our understanding of their unique roles and functions in plant biology. Developing an efficient framework for improving DBP prediction in plants would enhance our knowledge and enable precise gene expression control, accelerate crop improvement, enhance stress resilience, and optimize metabolic engineering for agricultural advancement. In this work, we developed a tool that uses a protein language model (pLM) pre-trained on millions of sequences. We evaluated several leading models, including ProtT5, Ankh, and ESM-2, and leveraged their high-dimensional, information-rich representations to improve the accuracy of DNA-binding protein prediction in plants significantly. Our final model, pLM-DBPs, a feed-forward neural network classifier utilizing ProtT5-based representations, outperformed existing approaches with a Matthews Correlation Coefficient (MCC) of 83.8% on the independent test set. This represents a 10% improvement over the previous state-of-the-art model for plant-based DBP prediction, highlighting its superior performance compared to the existing approaches.

bioinformatics↗

bioRxiv2024

CaLMPhosKAN: Prediction of General Phosphorylation Sites in Proteins via Fusion of Codon Aware Embeddings with Amino Acid Aware Embeddings and Wavelet-based Kolmogorov Arnold Network

The mapping from codon to amino acid is surjective due to the high degeneracy of the codon alphabet, suggesting that codon space might harbor higher information content. Embeddings from the codon language model have recently demonstrated success in various downstream tasks. However, predictive models for phosphorylation sites, arguably the most studied Post-Translational Modification (PTM), and PTM sites in general, have predominantly relied on amino acid-level representations. This work introduces a novel approach for prediction of phosphorylation sites by incorporating codon-level information through embeddings from a recently developed codon language model trained exclusively on protein-coding DNA sequences. Protein sequences are first meticulously mapped to reliable coding sequences and encoded using this encoder to generate codon-aware embeddings. These embeddings are then integrated with amino acid-aware embeddings obtained from a protein language model through an early fusion strategy. Subsequently, a window-level representation of the site of interest is formed from the fused embeddings within a defined window frame. A ConvBiGRU network extracts features capturing spatiotemporal correlations between proximal residues within the window, followed by a Kolmogorov-Arnold Network (KAN) based on the Derivative of Gaussian (DoG) wavelet transform function to produce the prediction inference for the site. We dub the overall model integrating these elements as CaLMPhosKAN. On independent testing with Serine-Threonine (combined) and Tyrosine test sets, CaLMPhosKAN outperforms existing approaches. Furthermore, we demonstrate the models effectiveness in predicting sites within intrinsically disordered regions of proteins. Overall, CaLMPhosKAN emerges as a robust predictor of general phosphosites in proteins. CaLMPhosKAN will be released publicly soon.

bioinformatics↗

bioRxiv2023

High prevalence of Bovine Tuberculosis reported in Cattle and Buffalo of Eastern Nepal

Livestock farming, specifically of cattle and buffalo, is crucial to Nepals economy, with more than 66% of the population involved in agriculture and animal husbandry. Animal tuberculosis (TB) caused by Mycobacterium bovis is a chronic disease that affects these animals and results in economic losses due to reduced milk and meat productivity, fertility and mortality. M. bovis also infects humans, non-human primates, goats and other mammals, and can afflict both cattle and buffalo. Our study is a part of routine surveillance of prevalent diseases, including M. bovis, in cattle and buffalo. We collected blood samples (n=400, 100 samples from each district) from selected eastern districts of Nepal. We used a Rapid Bovine TB Test Kit to test these samples for presence of M. bovis. Of the 400 samples collected, 74 animals (18.75%) tested positive for M. bovis, with the majority of positive samples coming from cattle (n=71, 17.75%) and only three from buffalo (<1%). Among the screened breeds of cattle and buffalo, Holstein Friesian cattle (HF) (n=43, 58%), Jersey-cross cattle (JX) (n=20, 27%), Local buffalo (n=8, 10.8%) and Murra breed buffalo (n=3, 4.1%) were found to carry M. bovis. The majority (50%) of infected animals were between 3-6 years old. Morang (n= 24 positive in cattle; n=1 positive in buffalo) and Jhapa (n= 22 positive in cattle; n=2 positive in buffalo) had the highest prevalence of M. bovis, while all the positive cases in Sunsari (n=19) and Udaypur (n=6) were in cattle. The fact that over 18% of the samples tested positive for M. bovis is of great concern. It is critical to thoroughly test animal products from these livestock prior to human consumption. To prevent and mitigate M. bovis-related infections in Nepal, a more comprehensive screening strategy coupled with more effective animal husbandry practices needs to be adapted.

microbiology↗

bioRxiv2022

Cdc42 prevents precocious Rho1 activation during cytokinesis in a Pak1-dependent manner

Cytokinesis consists of a series of coordinated multi-step events that partition a dividing cell. Accurate regulation of cytokinesis is essential for proliferation and genome integrity. In fission yeast, these coordinated events ensure that the actomyosin ring and septum start ingressing only after chromosome segregation. How cytokinetic events are coordinated remains unclear. The GTPase Cdc42 is required for the delivery of certain cell wall-building enzymes while the GTPase Rho1 is required for activation of these enzymes. Here we show that Cdc42 prevents early Rho1 activation during cytokinesis. Using an active Rho-probe, we show that even though the Rho1 activators Rgf1 and Rgf3 localize to the division site in early anaphase, Rho1 is not activated until late anaphase, just before the onset of ring constriction. We find that loss of Cdc42 activation enables precocious Rho1 activation in early anaphase. Furthermore, this inhibition of Rho1 activation is dependent on the downstream Cdc42 effector Pak1 kinase. Disrupting pak1 function results in early Rho1 activation accompanied by precocious septum deposition and ring constriction. We provide functional and genetic evidence which indicates that Pak1 regulates Rho1 activation likely via the regulation of its GEF Rgf1. Our work proposes a mechanism of Rho1 regulation by active Cdc42 to coordinate timely septum formation and cytokinesis fidelity.

cell biology↗