Mycobacterial Metabolic Model Development for Drug Target Identification

Abstract

ABSTRACTAntibiotic resistance is increasing at an alarming rate, and three related mycobacteria are the source of widespread infections in humans. According to the World Health Organization,Mycobacterium leprae, which causes leprosy, is still endemic in tropical countries; Mycobacterium tuberculosis is the second largest infectious disease killer worldwide after COVID-19;Mycobacteroides abscessus, a group of non-tuberculous mycobacteria, causes lung infections and other health-care-associated infections in humans. Due to the rise in resistance to common antibacterial drugs, it is critical to develop alternatives to traditional treatment procedures. Furthermore, an understanding of the biochemical mechanisms underlying pathogenic evolution is important for the treatment and management of these diseased conditions.In this study, metabolic models have been developed for two bacterial pathogens,M. leprae, andM. abscessus, and a new computational tool has been used to identify potential drug targets, which are referred to as bottleneck reactions. The genes, reactions, and pathways in each of these organisms have been highlighted; the potential drug targets can be further explored as broad-spectrum antibacterials and the unique drug targets to each pathogen are significant for precision medicine initiatives.The models and associating datasets are available in GigaScience and the following repositories:M. abscessusBiomodels:https://www.ebi.ac.uk/biomodels/MODEL2203300002https://www.patmedb.org/Bacteria/MabscessusM. lepraeBiomodels:https://www.ebi.ac.uk/biomodels/MODEL2203300001https://www.patmedb.org/Bacteria/Mleprae