Biology subjects

Salhotra, A.

Publications and source records attributed to Salhotra, A..

4 recordsLinked to original sources

bioRxiv2026

PepCL: A replay-based continual learning framework for updating peptide-MHC models

Understanding peptide-major histocompatibility complex (MHC) class I binding is critical for effective vaccine and immunotherapy design but is a combinatorially complex challenge for which prediction models have become essential. MHC ligands are typically identified at scale via untargeted mass spectrometry (MS), and this has built a strong base for peptide-MHC model training. However, MS incompletely captures the vast peptide-MHC space due to technical, sampling, and biological biases. Although recently developed experimental assays have queried such blind spots yielding complementary information, existing peptide-MHC predictors have not yet incorporated these orthogonal data and are not designed to be updated as new data are generated. Here, we introduce PepCL (Peptide-MHC Continual Learning), a continual learning framework for updating peptide-MHC predictors with new assay data while explicitly preserving prior MS knowledge. To enable PepCL, we also develop MHCPrime, a new state-of-the-art pan-allelic peptide-MHC prediction model, trained on publicly available MS data, that can be effectively updated under our framework. We demonstrate that PepCL allows MHCPrime to learn previously unseen, assay-specific information while preventing catastrophic forgetting that is typically observed with conventional fine-tuning. We evaluate PepCL and MHCPrime in a variety of biological contexts, including infectious disease and cancer, and show improved peptide-MHC prediction that transfers across alleles for broader applicability in clinical settings. Overall, our results establish PepCL as a flexible framework for extending the utility of peptide-MHC models by improving their predictive performance as immunopeptidomics assays continue to evolve and new data become available.

bioinformatics↗

bioRxiv2021

Integrated spatial multi-omics reveals fibroblast fate during tissue repair

In the skin, tissue injury results in fibrosis in the form of scars composed of dense extracellular matrix deposited by fibroblasts. The therapeutic goal of regenerative wound healing has remained elusive in part because principles of fibroblast programming and adaptive response to injury remain incompletely understood. Here, we present a multimodal -omics platform for the comprehensive study of cell populations in complex tissue, which has allowed us to characterize the cells involved in wound healing across both time and space. We employ a stented wound model that recapitulates human tissue repair kinetics and multiple Rainbow transgenic lines to precisely track fibroblast fate during the physiologic response to injury. Through integrated analysis of single cell chromatin landscapes and gene expression states, coupled with spatial transcriptomic profiling, we are able to impute fibroblast epigenomes with temporospatial resolution. This has allowed us to define the mechanisms controlling cell fate during migration, proliferation, and differentiation following tissue injury and thereby reexamine the canonical phases of wound healing. These findings have broad implications for the study of tissue repair in complex organ systems.

bioinformatics↗

bioRxiv2020

Optimized single molecule fluorescence sheds light on elusive enzymatic mechanisms

Single molecule enzymology using fluorescent substrate requires truly minimal amounts of proteins. This is highly beneficial when the protein source is either advanced expression systems or samples from humans/animals with ethical and economic implications. Further benefits of single molecule analysis is the potential to reveal phenomena hidden in ensemble studies. However, dye photophysics and fluorescent contaminants complicate interpretation of the single molecule data. We here corroborate the importance of such complexities using fluorescent Alexa647 ATP to study ATP turnover by myosin and actomyosin. We further show that the complexities are largely eliminated by aggressive surface cleaning and use of a range of triple state quenchers and redox agents with minor effects on actin-myosin function. Using optimized assay conditions, we then show that the distributions of ATP binding dwell times on myosin are best described by the sum of 2 to 3 exponential processes. This applies in the presence and absence of actin and in the presence and absence of the drug para-aminoblebbistatin. Two of the processes are attributable to ATP turnover by myosin and actomyosin, respectively. A remaining process with rate constant in the range 0.2-0.5 s-1 is consistent with non-specific ATP binding to myosin and bioinformatics modelling suggests that such binding may be important for accelerated ATP transport to the active site. Finally, we report studies of the actin-activated myosin ATP turnover under conditions with no sliding between actin and myosin, as in isometrically contracting muscle, revealing heterogeneity in the ATP turnover kinetics between different molecules.

biophysics↗

bioRxiv2019

Spen links RNA-mediated endogenous retrovirus silencing and X chromosome inactivation

Dosage compensation between the sexes has emerged independently multiple times during evolution, often harnessing long noncoding RNAs (lncRNAs) to alter gene expression on the sex chromosomes. In eutherian mammals, X chromosome inactivation (XCI) in females proceeds via the lncRNA Xist, which coats one of the two X chromosomes and recruits repressive proteins to epigenetically silence gene expression in cis1,2. How Xist evolved new functional RNA domains to recruit ancient, pleiotropic protein partners is of great interest. Here we show that Spen, an Xist-binding repressor protein essential for XCI3-7, binds to ancient retroviral RNA, performing a surveillance role to recruit chromatin silencing machinery to these parasitic loci. Spen inactivation leads to de-repression of a subset of endogenous retroviral (ERV) elements in embryonic stem cells, with gain of chromatin accessibility, active histone modifications, and ERV RNA transcription. Spen binds directly to ERV RNAs that show structural similarity to the A-repeat of Xist, a region critical for Xist-mediated gene silencing8-9. ERV RNA and Xist A-repeat bind the RRM3 domain of Spen in a competitive manner. Insertion of an ERV into an A-repeat deficient Xist rescues binding of Xist RNA to Spen and results in local gene silencing in cis. These results suggest that insertion of an ERV element into proto-Xist may have been a critical evolutionary event, which allowed Xist to coopt transposable element RNA-protein interactions to repurpose powerful antiviral chromatin silencing machinery for sex chromosome dosage compensation.

genomics↗