Dual transcriptome based reconstruction of Salmonella-human integrated metabolic network to screen potential drug targets

Abstract

Salmonella enterica serovar Typhimurium (S. Typhimurium) is a highly adaptive pathogenic bacteria with a serious public health concern due to its increasing resistance to antibiotics. Therefore, identification of novel drug targets for S. Typhimurium is crucial. Here, we first created a pathogen-host integrated genome-scale metabolic network by combining the metabolic models of human and S. Typhimurium, which we further tailored to the pathogenic state by the integration of dual transcriptome data. The integrated metabolic model enabled simultaneous investigation of metabolic alterations in human cells and S. Typhimurium during infection. Then, we used the tailored pathogen-host integrated genome-scale metabolic network to predict essential genes in the pathogen, which are candidate novel drug targets to inhibit infection. Drug target prioritization procedure was applied to these targets, and pabB was chosen as a putative drug target. It has an essential role in 4-aminobenzoic acid (PABA) synthesis, which is an essential biomolecule for many pathogens. A structure based virtual screening was applied through docking simulations to predict candidate compounds that eliminate S. Typhimurium infection by inhibiting pabB. To our knowledge, this is the first comprehensive study for predicting drug targets and drug like molecules by using pathogen-host integrated genome-scale models, dual RNA-seq data and structure-based virtual screening protocols. This framework will be useful in proposing novel drug targets and drugs for antibiotic-resistant pathogens.

Improved production of Taxol® precursors in S. cerevisiae using combinatorial in silico design and metabolic engineering

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Uncovering the Effect of SARS-CoV-2 on Liver Metabolism via Genome-Scale Metabolic Modeling for Reprogramming and Therapeutic Strategies

“…In the alveolar macrophage part, nitric oxide production was increased, but ATP production and nucleotide synthesis were decreased. In another study, Salmonella-infected HeLa cells were investigated using integrated pathogen-host genome-scale metabolic network and dual transcriptome data . Subsequent to drug target prioritization procedure, pabB was selected as the putative drug target, and docking simulations were performed to predict candidate compounds inhibiting pabB.…”

“…The infectious coronavirus disease 2019 (COVID- 19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus and has affected millions of people around the world since its outbreak in December 2019. World Health Organization declared a global emergency on January 30, 2020 and a global pandemic on March 11, 2020.…”

“…In another study, Salmonella -infected HeLa cells were investigated using integrated pathogen-host genome-scale metabolic network and dual transcriptome data. 19 Subsequent to drug target prioritization procedure, pabB was selected as the putative drug target, and docking simulations were performed to predict candidate compounds inhibiting pabB. Similar to bacterial pathogens, GEMs are also used in viral infection modeling in which the virus is represented by a pseudoreaction called virus biomass objective function (VBOF) based on its constituents.…”