Constraint-based modeling identifies new putative targets to fight colistin-resistant A. baumannii infections

Abstract

Acinetobacter baumannii is a clinical threat to human health, causing major infection outbreaks worldwide. As new drugs against Gram-negative bacteria do not seem to be forthcoming, and due to the microbial capability of acquiring multi-resistance, there is an urgent need for novel therapeutic targets. Here we have derived a list of new potential targets by means of metabolic reconstruction and modelling of A. baumannii ATCC 19606. By integrating constraint-based modelling with gene expression data, we simulated microbial growth in normal and stressful conditions (i.e. following antibiotic exposure). This allowed us to describe the metabolic reprogramming that occurs in this bacterium when treated with colistin (the currently adopted last-line treatment) and identify a set of genes that are primary targets for developing new drugs against A. baumannii, including colistin-resistant strains. It can be anticipated that the metabolic model presented herein will represent a solid and reliable resource for the future treatment of A. baumannii infections.

iCN718, an Updated and Improved Genome-Scale Metabolic Network Reconstruction of Acinetobacter baumannii AYE

“…However, one issue that has limited the use of this and other reconstructions is the lack of standardization in identifiers for metabolites and reactions ( Ebrahim et al, 2015 ). Since the publication of AbyMBEL891 in 2010, numerous studies have produced new data ( Farrugia et al, 2013 ; Gallagher et al, 2015 ; Presta et al, 2017 ) that provide an opportunity to update this A. baumannii reconstruction, allowing for more accurate representations of its physiology. One such study was a high-quality reconstruction of A. baumannii ATCC 19606, iLP844, that served as a valuable resource for model improvements ( Presta et al, 2017 ).…”

Systems-level analysis of NalD mutation, a recurrent driver of rapid drug resistance in acute Pseudomonas aeruginosa infection

“…In this study, we investigated the secondary effects of the NalD mutation by integrating metabolic modeling and transcriptomics data. Over the last decade, metabolic network analysis that combines genome-scale metabolic models and omics data have been applied to study antibiotic resistance in bacteria and to suggest therapeutic targets [46][47][48][49][50]. Although the molecular (primary) function of the NalD mutation has been widely studied, our work adds to our limited understanding of its secondary effects.…”

Network-Based Metabolism-Centered Screening of Potential Drug Targets in Klebsiella pneumoniae at Genome Scale

“…To do so, the essential pathogen proteins were subjected to BLASTp search against human protein sequences in Refseq database (Pruitt et al, 2007) at an expected value (E-value) cut-off of 1 × 10 −4 (Jamal et al, 2017;Presta et al, 2017). The proteins having <30% sequence identity with their human counterparts were considered as non-homologous (Presta et al, 2017). Hence, a putative drug target list consisting of the nonhomologous essential K. pneumoniae proteins was compiled.…”

“…When FBA is used to simulate gene deletion phenotypes, it provides significant quantitative insights about the bacterial metabolism, pathway activities, and potential drug targets (Cesur et al, 2018). To date, this approach has been commonly used in drug target discovery process at systems-level for different pathogens (Raman et al, 2008;Plata et al, 2010;Perumal et al, 2011;Ahn et al, 2014;Larocque et al, 2014;Presta et al, 2017). GMN models are available for different K. pneumoniae strains (Liao et al, 2011;Henry et al, 2017;Ramos et al, 2018;Norsigian et al, 2019).…”