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Autor(en) / Beteiligte
Titel
Diversity and trends in population structure of ESBL-producing Enterobacteriaceae in febrile urinary tract infections in children in France from 2014 to 2017
Ist Teil von
  • Journal of antimicrobial chemotherapy, 2020-01, Vol.75 (1), p.96-105
Ort / Verlag
England: Oxford University Press
Erscheinungsjahr
2020
Quelle
Oxford Journals 2020 Medicine
Beschreibungen/Notizen
  • Abstract Background The population structure of extraintestinal pathogenic Escherichia coli evolves over time, notably due to the emergence of antibiotic-resistant clones such as ESBL-producing Enterobacteriaceae (ESBL-E). Objectives To analyse by WGS the genetic diversity of a large number of ESBL-E isolated from urinary tract infections in children from paediatric centres across France between 2014 and 2017 and collected by the National Observatory of febrile urinary tract infection (FUTI) caused by ESBL-E. Methods A total of 40 905 Enterobacteriaceae-positive urine cultures were identified. ESBL-E were found in 1983 samples (4.85%). WGS was performed on 251 ESBL-E causing FUTI. STs, core genome MLST (cgMLST), serotype, fimH allele, ESBL genes and presence of papGII key virulence factor were determined. Results E. coli and Klebsiella pneumoniae were found in 86.9% (218/251) and 11.2% (28/251) of cases, respectively. Several STs predominate among E. coli such as ST131, ST38, ST69, ST73, ST95, ST405, ST12 and ST1193, while no ST emerged in K. pneumoniae. E. coli ST131, ST38 and ST1193 increased during the study period, with a heterogeneity in papGII prevalence (64.5%, 35% and 20% respectively). Most isolates harboured the CTX-M type (97%) with a predominance of blaCTX-M-15. blaCTX-M-27, an emerging variant in E. coli, is found in various STs. cgMLST enabled discrimination of clusters within the main STs. Conclusions The predominance of ST131, and the emergence of other STs such as ST38 and ST1193 combined with ESBL genes deserves close epidemiological surveillance considering their high threat in infectious disease. cgMLST could be a discriminant complementary tool for the analyses.

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