Abstract
Klebsiella pneumoniae is an opportunistic bacterial pathogen leading to life-threatening nosocomial infections. Emergence of highly resistant strains poses a major challenge in the management of the infections by healthcare-associated K. pneumoniae isolates. Thus, despite intensive efforts, the current treatment strategies remain insufficient to eradicate such infections. Failure of the conventional infection-prevention and treatment efforts explicitly indicates the requirement of new therapeutic approaches. This prompted us to systematically analyze the K. pneumoniae metabolism to investigate drug targets. Genome-scale metabolic networks (GMNs) facilitating the systematic analysis of the metabolism are promising platforms. Thus, we used a GMN of K. pneumoniae MGH 78578 to determine putative targets through gene- and metabolite-centric approaches. To develop more realistic infection models, we performed the bacterial growth simulations within different host-mimicking media, using an improved biomass formation reaction. We selected more suitable targets based on several property-based prioritization procedures. KdsA was identified as the high-ranked putative target satisfying most of the target prioritization criteria specified under the gene-centric approach. Through a structure-based virtual screening protocol, we identified potential KdsA inhibitors. In addition, the metabolite-centric approach extended the drug target list based on synthetic lethality. This revealed the importance of combined metabolic analyses for a better understanding of the metabolism. To our knowledge, this is the first comprehensive effort on the investigation of the K. pneumoniae metabolism for drug target prediction through the constraint-based analysis of its GMN in conjunction with several bioinformatic approaches. This study can guide the researchers for the future drug designs by providing initial findings regarding crucial components of the Klebsiella metabolism.
Highlights
Klebsiella pneumoniae, originally discovered in the lung samples of pneumonia patients, is a gram-negative, facultative anaerobic bacterium within the Enterobacteriaceae family (Friedlander, 1882)
Body fluid cultures are frequently used for the detection of K. pneumoniae (Goroll and Mulley, 2009). Another growth medium mimicking the body fluids (i.e., human body fluid (HBF) medium; Hadi and Marashi, 2014) and a more generic host medium were integrated to the Genome-scale metabolic networks (GMNs) for more comprehensive overview of the host environment
Genome-scale metabolic networks of different K. pneumoniae strains have been developed so far (Liao et al, 2011; Henry et al, 2017; Ramos et al, 2018; Norsigian et al, 2019), but to our knowledge they were not used for drug target discovery via the constraint-based analysis coupled to bioinformatic prioritization steps
Summary
Klebsiella pneumoniae, originally discovered in the lung samples of pneumonia patients, is a gram-negative, facultative anaerobic bacterium within the Enterobacteriaceae family (Friedlander, 1882). Identification of novel drugs, use of synergistic drug combinations and drug repositioning remain areas of active investigation (Sun et al, 2016; Taneja and Kaur, 2016), pointing to the crucial role of postgenomic approaches to cope with Klebsiella infections (Bachman et al, 2015; Santajit and Indrawattana, 2016) In this context, the evaluation of whole metabolism of the pathogen at genome scale can provide comprehensive insight for the elucidation of more efficient drug targets and enable a deeper understanding of the pathogen phenotype
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