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One year cross-sectional study in adult and neonatal intensive care units reveals the bacterial and antimicrobial resistance genes profiles in patients and hospital surfaces

Authors :
Luiz Felipe Valter de Oliveira
Ana Andrea dos Reis
Ana Paula Christoff
Fernando Gatti de Menezes
Giuliano Netto Flores Cruz
Vanessa Leitner Silva
Telma Priscila Lovizio Raduan
Andrea dos Santos Pereira Marques
Aline Fernanda Rodrigues Sereia
Renata Gonçalves Viessi
Bianca Silva Braga
Camila Hernandes
Daniela Carolina de Bastiani
Ana Paula Metran Nascente
Marines Dalla Valle Martino
Source :
PLoS ONE, Vol 15, Iss 6, p e0234127 (2020), PLoS ONE
Publication Year :
2020
Publisher :
Public Library of Science (PLoS), 2020.

Abstract

Several studies have shown the ubiquitous presence of bacteria in the hospital environmental surfaces, staff, and patients. Frequently, these bacteria are related to HAI (healthcare-associated infections) and carry antimicrobial resistance (AMR). These HAI-related bacteria contributes to a major public health issue by increasing patient morbidity and mortality during or after hospital stay. Bacterial high-throughput amplicon gene sequencing along with AMR genes identification and whole genome sequencing (WGS) are new biotechnological tools that allow multiple-sample screening for a diversity of bacteria. In this paper, we used these methods to perform an one-year cross sectional profiling of bacteria and AMR genes in adult and neonatal intensive care units (ICU and NICU) in a Brazilian public hospital. Our results showed high abundances of HAI-related bacteria as S. epidermidis, S. aureus, K. pneumoniae, A. baumannii complex, E. coli, E. faecalis and P. aeruginosa in patients and hospital surfaces. Most abundant AMR genes detected throughout ICU and NICU were mecA, blaCTX-M-1 group, blaSHV-like and blaKPC-like. We found that NICU environment and patients were more widely contaminated with pathogenic bacteria than ICU. Patient samples, despite the higher bacterial load, have lower bacterial diversity than environmental samples in both units. Finally, we also identified contamination hotspots in the hospital environment showing constant frequencies of bacterial and AMR contamination throughout the year. WGS sequencing, 16S rRNA oligotypes and AMR identification allowed a high-resolution data analysis for bacterial characterization and its distributions along the hospital microbiome profile.

Details

Language :
English
ISSN :
19326203
Volume :
15
Issue :
6
Database :
OpenAIRE
Journal :
PLoS ONE
Accession number :
edsair.doi.dedup.....4f7f0a9871cb0c6113535b8f06e85c27