Network Integrative Genomic and Transcriptomic Analysis of Carbapenem-Resistant Klebsiella pneumoniae Strains Identifies Genes for Antibiotic Resistance and Virulence

Abstract

Global increases in the use of carbapenems have resulted in several strains of Gram-negative bacteria acquiring carbapenem resistance, thereby limiting treatment options. Klebsiella pneumoniae is a common carbapenem-resistant pathogenic bacterium that is widely studied to identify novel antibiotic resistance mechanisms and drug targets. Antibiotic-resistant clinical isolates generally harbor many genetic alterations, and the identification of responsible mutations would provide insights into the molecular mechanisms of antibiotic resistance. We propose a method to prioritize mutated genes responsible for antibiotic resistance on the basis of expression changes in their local subnetworks, hypothesizing that mutated genes that show significant expression changes among the corresponding functionally associated genes are more likely to be involved in the carbapenem resistance. For network-based gene prioritization, we developed KlebNet (www.inetbio.org/klebnet), a genome-scale cofunctional network of K. pneumoniae genes. Using KlebNet, we reconstructed the functional modules for carbapenem resistance and virulence and identified the functional association between antibiotic resistance and virulence. Using complementation assays with the top candidate genes, we were able to validate a novel gene that negatively regulated carbapenem resistance and four novel genes that positively regulated virulence in Galleria mellonella larvae. Therefore, our study demonstrated the feasibility of network-based identification of genes required for antibiotic resistance and virulence of human-pathogenic bacteria. IMPORTANCE Klebsiella pneumoniae is a major bacterial pathogen that causes pneumonia and urinary tract infections in human. K. pneumoniae infections are treated with carbapenem, but carbapenem-resistant K. pneumoniae has been spreading worldwide. We are able to identify antimicrobial-resistant genes among mutated genes of the antibiotic-resistant clinical isolates. However, they usually harbor many mutated genes, including those that cause weak or neutral functional effects. Therefore, we need to prioritize the mutated genes to identify the more likely candidates for the follow-up functional analysis. For this study, we present a functional network of K. pneumoniae genes and propose a network-based method of prioritizing the mutated genes of the resistant clinical isolates. We also reconstructed the network-based functional modules for carbapenem resistance and virulence and retrieved the functional association between antibiotic resistance and virulence. This study demonstrated the feasibility of network-based analysis of clinical genomics data for the study of K. pneumoniae infection.

Integrated Co-functional Network Analysis on the Resistance and Virulence Features in Acinetobacter baumannii

“…Identification of resistance and virulence factor by traditional molecular technologies is normally labor intensive. Network analysis has been successfully used to analyze the antibiotic resistance and virulence in selected bacteria (Lee et al, 2019). Here, we use the integrated network analysis to construct a cofunctional network to investigate the resistance and virulence factors in A. baumannii, one of the most threatening bacterial pathogens to humans currently because of its widespread antibiotic resistance.…”

“…In general, analyzing the network structure and understanding the topological properties could discover novel nodes in the complex biologic system and provide new insights for elucidation of the molecular mechanism (Yan et al, 2018). For example, through a genome-scale co-functional network analysis, Lee et al successfully identified several novel genes associated with antibiotic resistance or virulence in Klebsiella pneumoniae (Lee et al, 2019).…”

Transcriptome-based design of antisense inhibitors re-sensitizes CREE. colito carbapenems

“…However, carbapenem resistance is not often studied at a transcriptomic level, and, when it is, the research almost exclusively examines basal expression levels. 30–35 In this work, we profiled the short-term transient transcriptomic responses of a partially carbapenem-resistant clinical isolate of E. coli and used our FAST platform to design PNA that uncovered the importance of multiple systems in the development of this phenotype, including the regulators flhC , hycA , and bolA . Furthermore, by inhibiting hycA , bolA , and dsrB with FAST PNA, we were able to re-sensitize the clinical isolate to sub-MIC carbapenem concentrations.…”

“…30, 31 Four recent studies that examined transcriptomic profiles of CRE —Enterobacter cloacae , K. pneumoniae (2), and Escherichia coli —identified less consistent responses, although downregulation of porin genes and upregulation of cell survival and β-lactamase genes were observed. 32–35 Of this prior research, only one study 32 attempts to evaluate the transcriptomic response of a resistant Enterobacteriaceae strain under antibiotic challenge, the majority examining only the constitutive gene expression levels of an untreated resistant pathogen.…”

Antibody-recruiting protein-catalyzed capture agents to combat antibiotic-resistant bacteria

“…12 Compounding the general problem of antibiotic resistance are challenges in developing and approving new antibiotics. 13 This has spurred research into understanding resistance mechanisms, 14,15 host defenses, [16][17][18] diagnostics 19 and antibiotic generation. 20,21 Ultimately, without a rapid and perhaps general method to develop new targeted antibiotics, therapies might relapse towards those of the pre-antibiotic era.…”