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Network integrative genomic and transcriptomic analysis of carbapenem-resistant Klebsiella pneumoniae strains identifies genes for resistance and virulence

ABSTRACT: With the global increase in the use of carbapenems, several gram-negative bacteria have acquired carbapenem resistance, thereby limiting treatment options. Klebsiella pneumoniae is one of such notorious pathogen that is being widely studied to find novel resistance mechanisms and drug targets. These antibiotic-resistant clinical isolates generally harbor many genetic alterations, and identification of causal mutations will provide insights into the molecular mechanisms of antibiotic resistance. We propose a method to prioritize mutated genes responsible for antibiotic resistance, in which mutated genes that also show significant expression changes among their functionally coupled genes become more likely candidates. For network-based analyses, we developed a genome-scale co-functional network of K. pneumoniae genes, KlebNet (www.inetbio.org/klebnet). Using KlebNet, we could reconstruct functional modules for antibiotic-resistance, and virulence, and retrieved functional association between them. With complementation assays with top candidate genes, we could validate a gene for negative regulation of meropenem resistance and four genes for positive regulation of virulence in Galleria mellonella larvae. Therefore, our study demonstrated the feasibility of network-based identification of genes required for antimicrobial resistance and virulence of human pathogenic bacteria with genomic and transcriptomic profiles from antibiotic-resistant clinical isolates.

ORGANISM(S): Klebsiella pneumoniae

PROVIDER: GSE115539 | GEO | 2018/06/10

REPOSITORIES: GEO

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Project description:Pseudomonas aeruginosa is a major opportunistic pathogen causing a wide range of infections and one of the most problematic bacteria regarding antibiotic resistance, with an increasing incidence of multidrug and extensively-drug resistant strains, including resistance to last resource antibiotics such as carbapenems. Resistances are often due to complex interplays of naturally and acquired resistance mechanisms which are enhanced by its remarkably large regulatory network. Thus, the use of non-targeted shotgun methodologies such as mass spectrometry-based proteomics is crucial to understand these interplays and to reveal possible strain and species-specific novel mechanisms of antibiotic resistance. The aim of this study was to determine the proteomic response of two carbapenem-resistant and extensively-drug-resistant P. aeruginosa strains to subminimal inhibitory concentrations (sub-MICs) of meropenem. The strains belonged to high-risk clones ST235 and ST395, one carrying a class 1 integron-encoded VIM-4 metallo-β-lactamase and one carrying no acquired antibiotic resistance genes. Each strain was cultivated with three different sub-MICs of meropenem, and a quantitative shotgun proteomic approach was applied, using tandem mass tag (TMT) isobaric labeling followed by nano-liquid chromatography tandem-mass spectrometry, to determine significantly up- or down-regulated proteins and enriched groups of proteins and pathways. Cultivation of both strains with ½ and ¼ of the MIC, resulted in hundreds of differentially regulated proteins, including several β-lactamases, transport-related proteins (including multiple porins and efflux pumps), proteins associated with peptidoglycan metabolism and cell wall organization and dozens of regulatory proteins. Remarkably, all components of the H1 type VI secretion system were up-regulated in one of the strains. Enrichment analyses revealed that multiple metabolic pathways were affected. Additionally, numerous proteins of unknown function were also differentially-regulated in each strain. In conclusion, high subminimal-inhibitory concentrations of meropenem cause massive changes in the proteomes of carbapenem-resistant P. aeruginosa strains, involving a wide range of common and strain-specific mechanisms and proteins, many still uncharacterized which might potentially play a role in the susceptibility of P. aeruginosa to meropenem.

Project description:Background: Antimicrobial resistance is generally studied using a combination of growth inhibition measurements, sometimes in combination with DNA detection methods. However, the actual proteins that cause resistance such as enzymes, efflux pumps and a lack of porins cannot be detected by these methods. Improvements in liquid chromatography (LC) and mass spectrometry (MS) enabled easier and more comprehensive proteome analysis. In the current study, these three methods are combined into a multi-omics approach to analyze resistance against frequently used antibiotics within the beta-lactam, aminoglycoside and fluoroquinolone group in E. coli and K. pneumoniae. Objectives: We aimed to analyze which currently known antimicrobial resistance genes are detected at the protein level using liquid chromatography-mass spectrometry (LC-MS/MS) and to assess whether these could explain beta-lactam, aminoglycoside, and fluoroquinolone resistance in the studied isolates. Furthermore, we aimed to identify significant protein to resistance correlations which have not yet been described and to correlate the abundance of different porins to resistance. Methods: Whole genome sequencing, high-resolution LC-MS/MS and antimicrobial susceptibility testing by broth microdilution were performed for 187 clinical E. coli and K. pneumoniae isolates. Resistance genes and proteins were identified using the Comprehensive Antibiotic Resistance Database (CARD). All proteins were annotated using the NCBI RefSeq database and Prokka. Results & Conclusion: Proteins of small spectrum beta-lactamases, extended spectrum beta-lactamases, AmpC beta-lactamases, carbapenemases, and proteins of 16S ribosomal RNA methyltransferases and aminoglycoside acetyltransferases can be detected in E. coli and K. pneumoniae by LC-MS/MS. The detected mechanisms could explain phenotypic resistance in most of the studied isolates. Differences in the abundance and the primary structure of other proteins such as porins also correlated with resistance. LC-MS/MS is a different and complementary method which can be used to characterize antimicrobial resistance in detail as not only the primary resistance causing mechanisms are detected, but also secondary enhancing resistance mechanisms.

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Network integrative genomic and transcriptomic analysis of carbapenem-resistant Klebsiella pneumoniae strains identifies genes for resistance and virulence

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