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Kayani, M. U. R.

Publications and source records attributed to Kayani, M. U. R..

2 recordsLinked to original sources

Integrative metagenomics and structural bioinformatics identify explainable gut microbial variants associated with Crohns disease

Metagenomics has revealed disease-associated shifts in microbial taxa and functions in inflammatory bowel disease (IBD) patients. However, the role of genomic variation in gut commensals remains poorly understood. Here, we integrated metagenomic profiling, variant calling, and structural bioinformatics to identify disease-associated variants in the gut microbes. Crohns disease (CD) and ulcerative colitis (UC) showed significant negative associations with Bacteroides uniformis, Bacteroides vulgatus, and Eubacterium rectale. These bacteria exhibited 190,712 single-nucleotide polymorphisms, including 479 CD-specific and 235 UC-specific variants. Variant prioritization identified a CD-specific Val170Leu substitution in the conserved starch-binding domain of the Starch Utilization System D (SusD) protein in B. uniformis. Structural modeling and cyclodextrin docking indicated reduced binding affinity in the mutant, while 200-ns molecular dynamics simulations showed stable ligand retention only in the wild type. These findings suggest that impaired starch metabolism driven by SusD variation may contribute to B. uniformis depletion in CD and demonstrate the value of integrating metagenomics with structural analyses to identify functionally relevant microbial variants.

bioinformatics↗

MiCK: a database of gut microbial genes linked with chemoresistance in cancer patients

Cancer remains a global health challenge, with significant morbidity and mortality rates. In 2020, cancer caused nearly 10 million deaths, making it the second leading cause of death worldwide. However, the emergence of chemoresistance becomes a major hurdle in successfully treating patients. Human gut microbes have been recognized for their role in modulating drug efficacy through their metabolites, ultimately leading to chemoresistance. The available databases are currently limited to knowledge regarding the interactions between gut microbiome and drugs. However, a database containing the human gut microbial gene sequences, and their effect on the efficacy of chemotherapy for cancer patients has not yet been reported. To address this challenge, we present the Microbial Chemoresistance Knowledgebase (MiCK), a comprehensive database cataloging microbial gene sequences associated with chemoresistance cancers. MiCK contains 1.6 million sequences of 29 gene types linked to chemoresistance and drug metabolism, curated manually from recent literature and sequence databases. The database supports efficient data retrieval and analysis, providing a user-friendly web interface for sequence search and download functionalities. MiCK aims to facilitate the understanding and mitigation of chemoresistance in cancers by serving as a valuable resource for researchers. Database URLhttps://microbialchemreskb.com/

bioinformatics↗