Molecular Determinants of Antibiotic Resistance in the Costa Rican Pseudomonas aeruginosa AG1 by a Multi-omics Approach:A Review of 10 Years of Study

作     者：Jose Arturo Molina-Mora Fernando García 

作者机构：Centro de Investigación en Enfermedades Tropicales(CIET)&Facultad de MicrobiologíaUniversidad de Costa RicaSan JoséCosta Rica 

出 版 物：《Phenomics》 (表型组学（英文）)

年 卷 期：2021年第1卷第3期

页      面：129-142页

学科分类：0710[理学-生物学] 1002[医学-临床医学] 100214[医学-肿瘤学] 10[医学] 

基　　金：funded by projects B8114 B8152 B7124 B5113 B4658 B4657 B4504 B4094 B4059 and B4051 Vicerrectoría de Investigación Universidad de Costa Rica(period 2010-2020) 

主　　题：Pseudomonas aeruginosa PaeAG1 Antibiotic resistance Multi-omics High risk 

摘      要：Pseudomonas aeruginosa AG1(PaeAG1)is a Costa Rican strain that was isolated in 2010 in a major *** strain has resistance to multiple antibiotics such asβ-lactams(including carbapenems),aminoglycosides,and ***1 is considered critical(Priority 1)due to its resistance to carbapenems,and it was the first report of a *** isolate carrying both VIM-2 and IMP-18 genes encoding for metallo-β-lactamases(MBL)enzymes(both with carbapenemase activity).Owing to these traits,we have studied this model for 10 years using diverse approaches including *** this review,we summarize the main points of the different steps that we have studied in PaeAG1:preliminary analyses of this strain at the genomic and phenomic levels revealed that this microorganism has particular features of antibiotic *** the multi-omics approach,the genome assembly was the initial step to identify the genomic determinants of this strain,includ-ing virulence factors,antibiotic resistance genes,as well as a complex accessory ***,a comparative genomic approach was implemented to define and update the phylogenetic relationship among complete *** genomes,the genomic island content in other strains,and the architecture of the two MBL-carrying ***,the proteomic profile of PaeAG1 was studied after exposure to antibiotics using 2-dimensional gel electrophoresis(2D-GE).Fourth,to study the central response to multiple perturbations in ***,i.e.,the core perturbome,a machine learning approach was *** analysis revealed biological functions and determinants that are shared by different ***,to evaluate the effects of ciprofloxacin(CIP)on PaeAG1,a growth curve comparison,differential expression analysis(RNA-Seq),and network analysis were *** the results of the core perturbome(pathways that also were found in this perturbation with CIP),it was possible to identify the“exclusiveresponse and determina