ABSTRACT: Metagenomics analysis revealing the characterization of antibiotic resistance genes and their relationship with the pathogen in aquaculture ponds
Project description:Infectious pancreatic necrosis (IPN) is a serious viral disease that causes significant economic losses in salmon aquaculture. To characterize the host-pathogen relationship in IPN, we analysed transcriptional profiles of salmon head kidney (SHK-1) cells infected with infectious pancreatic necrosis virus (IPNV) at three timepoints over six days (at 1, 3 & 6 days post infection. The transcriptome was investigated using the TRAITS / SGP 16950-feature Atlantic salmon cDNA microarray, which is enriched for genes with functions related to the immune response.
Project description: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.
