Nationwide genome surveillance of carbapenem-resistant Pseudomonas aeruginosa in Japan
Yano, H.; Hayashi, W.; Kawakami, S.; Aoki, S.; Anzai, E.; Kitamura, N.; Hirabayashi, A.; Kajihara, T.; Kayama, S.; Sugawara, Y.; Yahara, K.; Sugai, M.
Show abstract
Japan is a country with an approximate 10 % prevalence rate of carbapenem-resistant Pseudomonas aeruginosa (CRPA). Currently, a comprehensive overview of the genotype and phenotype patterns of CRPA in Japan is lacking. Herein, we conducted genome sequencing and quantitative antimicrobial susceptibility testing for 382 meropenem-resistant CRPA isolates that were collected from 78 hospitals across Japan from 2019 to 2020. CRPA exhibited susceptibility rates of 52.9%, 26.4%, and 88.0% against piperacillin-tazobactam, ciprofloxacin, and amikacin, respectively, whereas 27.7% of CRPA isolates were classified as difficult-to-treat resistance P. aeruginosa. Of the 148 sequence types detected, ST274 (9.7%) was predominant, followed by ST235 (7.6%). The proportion of urine isolates in ST235 was higher than that in other STs (P = 0.0056, chi-square test). Only 4.1% of CRPA isolates carried the carbapenemase genes: blaGES (2) and blaIMP (13). One ST235 isolate carried the novel blaIMP variant blaIMP-98 in the chromosome. Regarding chromosomal mutations, 87.1% of CRPA isolates possessed inactivating or other resistance mutations in oprD, and 28.8% showed mutations in the regulatory genes (mexR, nalC, and nalD) for the MexAB-OprM effux pump. Additionally, 4.7% of CRPA isolates carried a resistance mutation in the PBP3-encoding gene ftsI. The findings from this study and other surveillance studies collectively demonstrate that CRPA exhibits marked genetic diversity and that its multidrug resistance in Japan is less prevailed than in other regions. This study contributes a valuable dataset that addresses a gap in genotype/phenotype information regarding CRPA in the Asia-Pacific region, where the epidemiological background markedly differs between regions.
Matching journals
The top 3 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Novel quinolone resistance determinant, qepA8, in Shigella flexneri isolated in the United States, 2016 97%
- Genomic Insights into Ceftazidime Resistance in Burkholderia pseudomallei: Discovery of A172T Mutation, and Palindromic GC-Rich Repeat Sequences Facilitating penA Duplication and Amplification. 96%
- Inter-phylum circulation of a beta-lactamase - encoding gene: a rare but observable event 96%
Similar papers in this journal
- Global dissemination of tet(X3) and tet(X6) among livestock-associated Acinetobacter is sporadically mediated by highly diverse plasmidomes 97%
- Mutations in ampD cause hyperproduction of AmpC and CphA beta-lactamases and high resistance to beta-lactam antibiotics in Chromobacterium violaceum 96%
- Clinical and genomic epidemiology of mcr - 9 -carrying carbapenem-resistant Enterobacterales isolates in Metropolitan Atlanta, 2012-2017 96%
Similar papers in this journal
- Population genomic molecular epidemiological study of macrolide resistant Streptococcus pyogenes in Iceland,1995-2016: Identification of a large clonal population with a pbp2x mutation conferring reduced in vitro beta-lactam susceptibility 96%
- Transmission and antibiotic resistance of Achromobacter in cystic fibrosis 94%
- A novel platform to accelerate antimicrobial susceptibility testing in Neisseria gonorrhoeae using RNA signatures 94%
Similar papers in this journal
- Within-host genotypic and phenotypic diversity of contemporaneous carbapenem-resistant Klebsiella pneumoniae from blood cultures of patients with bacteremia 96%
- Population structure and antimicrobial resistance patterns of Salmonella Typhi and Paratyphi A amid a phased municipal vaccination campaign in Navi Mumbai, India 95%
- Identification of a novel LysR-type transcriptional regulator in Staphylococcus aureus that is crucial for secondary tissue colonization during metastatic bloodstream infection 94%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.