Biology subjects

Tyagi, R.

Publications and source records attributed to Tyagi, R..

5 recordsLinked to original sources

bioRxiv2025

AI-Guided Design and AKT3 Degradation Synergize to Enhance Bispecific and Trispecific CAR-T Cell Persistence and Overcome Antigen Escape

The structural design of chimeric antigen receptors (CARs) is critical for achieving robust and durable anti-tumor responses, particularly when targeting multiple antigens to prevent tumor antigen escape. However, increasing CAR complexity can introduce structural vulnerabilities, leading to antigen-independent T cell activation, activation-induced cell death, and reduced CAR-T cell persistence. To overcome these challenges, we designed 10,824 CAR molecules across diverse formats and screened 1,452 constructs in-vitro to develop an artificial intelligence model, termed CAR-Mediated Self-Destruction (CARMSeD), which predicts CAR designs susceptible to self-activation and dysfunction. Guided by CARMSeD and structural CAR-CAR interaction modeling, we identified optimized CAR architectures incorporating ICOS and 4-1BB co-stimulatory domains. Humanized bispecific CARs targeting CD20/CD19 and CD22/CD19 demonstrated superior anti-tumor efficacy and persistence both in-vitro and in various xenograft mice models. To further extend CAR-T cell persistence, we engineered bispecific CARs integrated with an AKT3-targeted PROTAC strategy. Targeted degradation of AKT3 enhanced anti-tumor potency, promoted memory T cell formation, and enabled sustained responses even under tumor rechallenge and CD19 antigen-loss conditions. Mechanistically, these effects were mediated by metabolic reprogramming involving FOXO4; notably, FOXO4-deficient CAR-T cells exhibited impaired long-term persistence. Leveraging these mechanistic insights, we developed a trispecific CAR-T cell platform incorporating a bispecific T cell engager (BiTE) targeting CD22/CD3, combined with AKT3 PROTACs. These trispecific CAR-T cells achieved potent tumor eradication, even against malignancies lacking both CD19 and CD20 expression. Collectively, this study presents a comprehensive strategy combining structure-based design, AI-guided screening, and targeted protein degradation to engineer next-generation bi and trispecific CAR-T cells with enhanced persistence, broad antigen coverage, and superior therapeutic durability.

cancer biology↗

bioRxiv2022

Protein Language Model for Prediction of Subcellular Localization of Protein Sequences from Gram-negative bacteria (ProtLM.SCL)

The prediction of bacterial protein Sub-Cellular Localization (SCL) is critical for antigen identification and reverse vaccinology, especially when determining protein localization in the lab is time consuming, expensive and not possible for all species. While PSORTb is one of the most widely used tool for predicting SCL, it has several limitations, including the tendency to label a large number of proteins as Unknown. To address these shortcomings, we present a protein language model capable of predicting the subcellular localization of a given protein (ProtLM.SCL) from gram-negative bacteria. By performing 10-fold cross validation on the PSORTb public data set, we demonstrate that ProtLM.SCL is more accurate and precise than PSORTb. When compared to empirically validated published data, our models also outperformed PSORTb, particularly when categorizing difficult occurrences.

bioinformatics↗

bioRxiv2020

Reprogramming the endogenous type III-A CRISPR-Cas system for genome editing, RNA interference and CRISPRi screening in Mycobacterium tuberculosis

Mycobacterium tuberculosis (M.tb) causes the current leading infectious disease. Examination of the functional genomics of M.tb and development of drugs and vaccines are hampered by the complicated and time-consuming genetic manipulation techniques for M.tb. Here, we reprogrammed M.tb endogenous type III-A CRISPR-Cas10 system for simple and efficient gene editing, RNA interference and screening via simple delivery of a plasmid harboring a mini-CRISPR array, thereby avoiding the introduction of exogenous proteins and minimizing proteotoxicity. We demonstrated that M.tb genes were efficiently and specifically knocked-in/out by this system, which was confirmed by whole-genome sequencing. This system was further employed for single and simultaneous multiple-gene RNA interference. Moreover, we successfully applied this system for genome-wide CRISPR interference screening to identify the in-vitro and intracellular growth-regulating genes. This system can be extensively used to explore the functional genomics of M.tb and facilitate the development of new anti-Mycobacterial drugs and vaccines. SummaryTuberculosis caused by Mycobacterium tuberculosis (M.tb) is the current leading infectious disease affecting more than ten million people annually. To dissect the functional genomics and understand its virulence, persistence, and antibiotics resistance, a powerful genome editing tool and high-throughput screening methods are desperately wanted. Our study developed an efficient and a robust tool for genome editing and RNA interference in M.tb using its endogenous CRISPR cas10 system. Moreover, the system has been successfully applied for genome-wide CRISPR interference screening. This tool could be employed to explore the functional genomics of M.tb and facilitate the development of anti-M.tb drugs and vaccines.

microbiology↗

bioRxiv2019

De novo identification of toxicants that cause irreparable damage to parasitic nematode intestinal cells

Efforts to identify new drugs for therapeutic and preventive treatments against parasitic nematodes have gained increasing interest with expanding pathogen omics databases and drug databases from which new anthelmintic compounds might be identified. Here, a novel approach focused on integrating a pan-Nematoda multi-omics data targeted to a specific nematode organ system (the intestinal tract) with evidence-based filtering and chemogenomic screening was undertaken. Based on de novo computational target prioritization of the 3,564 conserved intestine genes in A. suum, exocytosis was identified as a high priority pathway, and predicted inhibitors of exocytosis were tested using the large roundworm (Ascaris suum larval stages), a filarial worm (Brugia pahangi adult and L3), a whipworm (Trichuris muris adult), and the non-parasitic nematode Caenorhabditis elegans. 10 of 13 inhibitors were found to cause rapid immotility in A. suum L3 larvae, and five inhibitors were effective against the three phylogenetically diverse parasitic nematode species, indicating potential for a broad spectrum anthelmintics. Several distinct pathologic phenotypes were resolved related to molting, motility, or intestinal cell and tissue damage using conventional and novel histologic methods. Pathologic profiles characteristic for each inhibitor will guide future research to uncover mechanisms of the anthelmintic effects and improve on drug designs. This progress firmly validates the focus on intestinal cell biology as a useful resource to develop novel anthelmintic strategies. Author summaryThe intestinal cells of parasitic nematodes are not known to regenerate, therefore disruption of essential processes that cause irreparable damage to intestinal cells is expected to promote worm expulsion. To facilitate improved methods of therapy we need to better understand the basic intestinal cell and tissue functions of this critical organ. To that end have undertaken a comprehensive analysis of multi-omics omics data and identify and prioritize intestinal genes/pathways with essential functions and associated drugs and established a foundational model of the STH intestinal system using the large roundworm Ascaris suum to test and validate inhibitors of these functions. We found 10 inhibitors to impacted motility, and seven of those showed severe pathology and an apparent irreparable damage to intestinal cells. Furthermore, five inhibitors were effective against the three phylogenetically diverse parasitic nematode species, indicating potential for a broad spectrum anthelmintics. Our results firmly validate the focus on intestinal cell biology as a useful resource to develop novel anthelmintic strategies.

pathology↗

bioRxiv2019

CoolBox: a interactive genomic data explorer for Jupyter Notebook

SummaryCoolBox is a Python package for interactive genomic data exploration based on Jupyter notebook. It provides a ggplot2-like Application Programming Interface (API) for genomic data visualization, and a Jupyter/ipywidgets based Graphical User Interface (GUI) for interactive data exploration. CoolBox is a versatile multi-omics explorer supporting most types of data formats generated by various sequencing technologies like RNA-Seq, ChIP-Seq, ChIA-PET and Hi-C.\n\nAvailability and implementationCoolBox is purely implemented with Python, and the GUI widget in Jupyter notebook is based on the ipywidgets package. It is open-source and available under GPLv3 license at https://github.com/GangCaoLab/CoolBox.

bioinformatics↗