Abstract

Several studies have shown the ubiquitous presence of bacteria in hospital surfaces, staff, and patients. Frequently, these bacteria are related to HAI (healthcare-associated infections) and carry antimicrobial resistance (AMR). These HAI-related bacteria contribute 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 identification of AMR genes, as well as whole genome sequencing (WGS), are biotechnological tools that allow multiple-sample screening for a diversity of bacteria. In this paper, we used these methods to perform a one-year cross sectional profiling of bacteria and AMR genes in adult and neonatal intensive care units (ICU and NICU) in a Brazilian public, tertiary hospital. Our results showed high abundances of HAI-related bacteria such 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. Whole genome sequencing (WGS), 16S rRNA oligotypes, and AMR identification allowed a high-resolution characterization of the hospital microbiome profile.

Highlights

  • Hospital indoor environment including surfaces, staff and patients are the focus of major recent investigations regarding the microbiome and its bacterial composition [1,2,3,4]

  • In the log10 scale, patient and healthcare environment median reads in intensive care unit (ICU) and neonatal intensive care unit (NICU) reflects the scales of microbial load in the samples (Fig 1)

  • Considering quality reads that passed through our bioinformatics pipeline, 98.74% of reads could be classified as bacteria, 97.84% were classified at family level, 89.14% at genus level, and 67.28% at species level

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Summary

Introduction

Hospital indoor environment including surfaces, staff and patients are the focus of major recent investigations regarding the microbiome and its bacterial composition [1,2,3,4]. One year cross-sectional study of bacterial profiles and resistance genes in the ICU and NICU

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