Biology subjects

Kushwaha, A.

Publications and source records attributed to Kushwaha, A..

4 recordsLinked to original sources

bioRxiv2026

Preferential recruitment of PML isoform II by incoming HPV16 genome transport vesicles facilitates early stage of infection

The interplay between promyelocytic leukemia nuclear bodies (PML NBs) and viral infections is complex and multifaceted, with viruses often engaging in a delicate balance of exploitation and evasion of host immune responses. It is well-established that incoming human papillomavirus (HPV) virions associate with PML NBs; however, the mechanism by which HPV targets PML NBs to facilitate early transcription and replication remains elusive. We have shown that HPV genomes are delivered to the nucleus inside membrane-bound vesicles during mitosis and that PML proteins are recruited to HPV-harboring nuclear vesicles prior to egress. Herein, we demonstrate that the PML isoform II (PMLII), but not other PML isoforms, is selectively attracted to incoming HPV still residing in transport vesicles. Using individual PML NB isoform and HPV16 minor protein, L2, over-expression experiments in HeLa cells, we conclude that PML II binds to the lipids of the HPV harbouring membrane-bound vesicles rather than L2. This is in line with previous observations that PML II is the only isoform binding to lipid droplets in the nucleus. We observed that the association of PML NBs with the HPV16 viral genome was transient and lost over time. We also found that nuclear Phospholipase C {beta}4 and {gamma}1 colocalize with PML II-L1 complexes in infected cells. Our data support a model in which PML II contributes to the establishment of early HPV16 infection by organizing host lipid regulatory factors at incoming viral transport vesicles.

cancer biology↗

bioRxiv2026

HPV16 Utilizes Phospholipase C(s) for its Genome Egress

Nuclear delivery of human papillomavirus (HPV) requires infected cells to undergo mitosis. Incoming HPV DNA is protected by a transport vesicle structure, which becomes unstable post-mitosis. We have previously shown that HPV genome egress takes on average 4 hours post-mitosis completion; thus, we propose that an enzymatic process is involved in degrading this transport vesicle to allow genome egress. Several phospholipase C (PLC) isoforms, including PLC{delta}3, PLC{zeta}1, and PLCL1, have been previously implicated in HPV infection in large-scale siRNA screens, and the parvovirus VP1 capsid protein has phospholipase enzymatic activity. Therefore, we hypothesized that cellular phospholipases residing in the nucleus mediate egress of the HPV genome from transport vesicles. We utilized siRNA-mediated knockdown and CRISPR/Cas9 knockout techniques to target specific PLC isoforms in both HeLa and HaCaT cell lines. We found that targeting PLC isoforms PLC{beta}1, {beta}4, {delta}3, {delta}4, and {gamma}1 significantly decreased HPV infection in both HeLa and HaCaT cells, as measured using a luciferase-based reporter assay. We also discovered a novel interaction between HPV16 minor protein L2 and PLCs {beta}1, {beta}4, {delta}1, {delta}3, and {delta}4. Furthermore, we observed that knockout of PLC{beta}4 and {delta}4 delayed egress of the HPV genome from nuclear membrane-bound vesicles after infection of HeLa cells. We propose that HPV utilizes phospholipase Cs to achieve genome egress from its protective vesicular structure after nuclear delivery.

microbiology↗

bioRxiv2025

IMGT(R) at scale: FAIR, Dynamic and Automated Tools for Immune Locus Analysis

IMGT(R), the international ImMunoGeneTics information system(R), has advanced its comprehensive platform for the analysis of immunoglobulin (IG) and T cell receptor (TR) genes through the development of new automated and scalable tools. This article presents major updates aligned with IMGTs three axes of research. Axis I introduces dynamic resources such as IMGT/GeneTables, IMGT/AssemblyComparison, and IMGT/StatAssembly, enabling real-time access to annotated genomic data and quality assessment of assemblies. Axis II enhances repertoire analysis with a redesigned IMGT/GeneFrequency tool and new customization features in IMGT/V-QUEST, supporting flexible exploration of IG and TR gene expression. Axis III improves the accurate prediction of peptide-MHC thanks to IMGT/RobustpMHC. Additionally, the IMGT Knowledge Graph (IMGT-KG) and its therapeutic extension, IMGT/mAb-KG, provide semantically structured access to more than 100 million immunogenetic triplets, integrating IMGT databases and linking IMGT content to external biomedical resources. These developments promote standardization, interoperability, and integrative analysis across immunogenetics and clinical applications, reinforcing IMGTs role as a core reference in the era of FAIR data and personalized medicine.

bioinformatics↗

bioRxiv2023

IMGT/RobustpMHC: Robust Training for class-I MHCPeptide Binding Prediction

The accurate prediction of peptide-MHC class I binding probabilities is a critical endeavor in immunoinformatics, with broad implications for vaccine development and immunotherapies. While recent deep neural network based approaches have showcased promise in peptide-MHC prediction, they have two shortcomings: (i) they rely on hand-crafted pseudo-sequence extraction, (ii) they do not generalise well to different datasets, which limits the practicality of these approaches. In this paper, we present PerceiverpMHC that is able to learn accurate representations on full-sequences by leveraging efficient transformer based architectures. Additionally, we propose IMGT/RobustpMHC that harnesses the potential of unlabeled data in improving the robustness of peptide-MHC binding predictions through a self-supervised learning strategy. We extensively evaluate RobustpMHC on 8 different datasets and showcase the improvements over the state-of-the-art approaches. Finally, we compile CrystalIMGT, a crystallography verified dataset that presents a challenge to existing approaches due to significantly different peptide-MHC distributions.

bioinformatics↗