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

ABSTRACT: Pseudomonas aeruginosa AG1 (PaeAG1) is a Costa Rican strain that was isolated in 2010 in a major Hospital. This strain has resistance to multiple antibiotics such as β-lactams (including carbapenems), aminoglycosides, and fluoroquinolones. PaeAG1 is considered critical (Priority 1) due to its resistance to carbapenems, and it was the first report of a P. aeruginosa 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 multi-omics. In 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 resistance. In the multi-omics approach, the genome assembly was the initial step to identify the genomic determinants of this strain, including virulence factors, antibiotic resistance genes, as well as a complex accessory genome. Second, a comparative genomic approach was implemented to define and update the phylogenetic relationship among complete P. aeruginosa genomes, the genomic island content in other strains, and the architecture of the two MBL-carrying integrons. Third, 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 P. aeruginosa, i.e., the core perturbome, a machine learning approach was used. The analysis revealed biological functions and determinants that are shared by different disturbances. Finally, to evaluate the effects of ciprofloxacin (CIP) on PaeAG1, a growth curve comparison, differential expression analysis (RNA-Seq), and network analysis were performed. Using the results of the core perturbome (pathways that also were found in this perturbation with CIP), it was possible to identify the “exclusive” response and determinants of PaeAG1 after exposure to CIP. Altogether, after a decade of study using a multi-omics approach (at genomics, comparative genomics, perturbomics, transcriptomics, proteomics, and phenomics levels), we have provided new insights about the genomic and transcriptomic determinants associated with antibiotic resistance in PaeAG1. These results not only partially explain the high-risk condition of this strain that enables it to conquer nosocomial environments and its multi-resistance profile, but also this information may eventually be used as part of the strategies to fight this pathogen.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-021-00016-z.

SUBMITTER: Molina-Mora J

PROVIDER: S-EPMC8210740 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Pseudomonas aeruginosa is an opportunistic pathogen that thrives in diverse environments and causes a variety of human infections. Pseudomonas aeruginosa AG1 (PaeAG1) is a high-risk sequence type 111 (ST-111) strain isolated from a Costa Rican hospital in 2010. PaeAG1 has both blaVIM-2 and blaIMP-18 genes encoding for metallo-?-lactamases, and it is resistant to ?-lactams (including carbapenems), aminoglycosides, and fluoroquinolones. Ciprofloxacin (CIP) is an antibiotic commonly used to treat P. aeruginosa infections, and it is known to produce DNA damage, triggering a complex molecular response. In order to evaluate the effects of a sub-inhibitory CIP concentration on PaeAG1, growth curves using increasing CIP concentrations were compared. We then measured gene expression using RNA-Seq at three time points (0, 2.5 and 5 h) after CIP exposure to identify the transcriptomic determinants of the response (i.e. hub genes, gene clusters and enriched pathways). Changes in expression were determined using differential expression analysis and network analysis using a top-down systems biology approach. A hybrid model using database-based and co-expression analysis approaches was implemented to predict gene-gene interactions. We observed a reduction of the growth curve rate as the sub-inhibitory CIP concentrations were increased. In the transcriptomic analysis, we detected that over time CIP treatment resulted in the differential expression of 518 genes, showing a complex impact at the molecular level. The transcriptomic determinants were 14 hub genes, multiple gene clusters at different levels (associated to hub genes or as co-expression modules) and 15 enriched pathways. Down-regulation of genes implicated in several metabolism pathways, virulence elements and ribosomal activity was observed. In contrast, amino acid catabolism, RpoS factor, proteases, and phenazines genes were up-regulated. Remarkably,?>?80 resident-phage genes were up-regulated after CIP treatment, which was validated at phenomic level using a phage plaque assay. Thus, reduction of the growth curve rate and increasing phage induction was evidenced as the CIP concentrations were increased. In summary, transcriptomic and network analyses, as well as the growth curves and phage plaque assays provide evidence that PaeAG1 presents a complex, concentration-dependent response to sub-inhibitory CIP exposure, showing pleiotropic effects at the systems level. Manipulation of these determinants, such as phage genes, could be used to gain more insights about the regulation of responses in PaeAG1 as well as the identification of possible therapeutic targets. To our knowledge, this is the first report of the transcriptomic analysis of CIP response in a ST-111 high-risk P. aeruginosa strain, in particular using a top-down systems biology approach.

Project description:The intrinsic resistance of Pseudomonas aeruginosa to many antibiotics limits treatment options for pseudomonal infections. P. aeruginosa's outer membrane is highly impermeable and decreases antibiotic entry into the cell. We used an unbiased high-throughput approach to examine mechanisms underlying outer membrane-mediated antibiotic exclusion. Insertion sequencing (INSeq) identified genes that altered fitness in the presence of linezolid, rifampin, and vancomycin, antibiotics to which P. aeruginosa is intrinsically resistant. We reasoned that resistance to at least one of these antibiotics would depend on outer membrane barrier function, as previously demonstrated in Escherichia coli and Vibrio cholerae This approach demonstrated a critical role of the outer membrane barrier in vancomycin fitness, while efflux pumps were primary contributors to fitness in the presence of linezolid and rifampin. Disruption of flagellar assembly or function was sufficient to confer a fitness advantage to bacteria exposed to vancomycin. These findings clearly show that loss of flagellar function alone can confer a fitness advantage in the presence of an antibiotic.IMPORTANCE The cell envelopes of Gram-negative bacteria render them intrinsically resistant to many classes of antibiotics. We used insertion sequencing to identify genes whose disruption altered the fitness of a highly antibiotic-resistant pathogen, Pseudomonas aeruginosa, in the presence of antibiotics usually excluded by the cell envelope. This screen identified gene products involved in outer membrane biogenesis and homeostasis, respiration, and efflux as important contributors to fitness. An unanticipated fitness cost of flagellar assembly and function in the presence of the glycopeptide antibiotic vancomycin was further characterized. These findings have clinical relevance for individuals with cystic fibrosis who are infected with P. aeruginosa and undergo treatment with vancomycin for a concurrent Staphylococcus aureus infection.

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

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