Biofilms on Hospital Shower Hoses: Characterization and Implications for Nosocomial Infections

Abstract

Although the source of drinking water (DW) used in hospitals is commonly disinfected, biofilms forming on water pipelines are a refuge for bacteria, including possible pathogens that survive different disinfection strategies. These biofilm communities are only beginning to be explored by culture-independent techniques that circumvent the limitations of conventional monitoring efforts. Hence, theories regarding the frequency of opportunistic pathogens in DW biofilms and how biofilm members withstand high doses of disinfectants and/or chlorine residuals in the water supply remain speculative. The aim of this study was to characterize the composition of microbial communities growing on five hospital shower hoses using both 16S rRNA gene sequencing of bacterial isolates and whole-genome shotgun metagenome sequencing. The resulting data revealed a Mycobacterium-like population, closely related to Mycobacterium rhodesiae and Mycobacterium tusciae, to be the predominant taxon in all five samples, and its nearly complete draft genome sequence was recovered. In contrast, the fraction recovered by culture was mostly affiliated with Proteobacteria, including members of the genera Sphingomonas, Blastomonas, and Porphyrobacter.The biofilm community harbored genes related to disinfectant tolerance (2.34% of the total annotated proteins) and a lower abundance of virulence determinants related to colonization and evasion of the host immune system. Additionally, genes potentially conferring resistance to β-lactam, aminoglycoside, amphenicol, and quinolone antibiotics were detected. Collectively, our results underscore the need to understand the microbiome of DW biofilms using metagenomic approaches. This information might lead to more robust management practices that minimize the risks associated with exposure to opportunistic pathogens in hospitals.

FIG 1

Taxonomic composition of the shower hose biofilms based on 16S rRNA gene fragments recovered from the metagenomes and isolates. The relative abundances (y axis) of the 16S rRNA gene-containing reads recovered from the metagenomes (normalized by the total number of classified 16S rRNA gene-containing reads in each metagenome) and the cultured fraction (normalized by the number of isolates; last column) for the major genera present in each sample (x axis) are shown.

FIG 2

Phylogenetic relationships and relative abundance of the populations recovered in the shower hose metagenomes. The tree shows all 30S ribosomal protein S9 sequences assembled from the metagenomes and selected reference sequences from publicly available genomes (denoted by complete species names). The radius of the pie charts indicates the number of reads mapping to the specific protein sequence related to the node, and the colors represent the five different data sets (see figure key). Roseobacter denitrificans was used as an outgroup. The phylogenetic tree was constructed using the neighbor-joining algorithm with 1,000 bootstrap replicates in MEGA5 (91). The scale bar represents the number of substitutions per site.

FIG 3

Relative abundance of functional genes in the shower hose metagenomes. (Top to bottom) The heat map on the left is composed of 7 proteins involved in antibiotic resistance, 12 proteins involved in disinfectant resistance mechanisms and EPS production, and the 30 most abundant proteins annotated with UniProt DB (rows) for each sample (columns). The small heat map on the right represents a magnification of the main heat map, focusing on the antibiotic resistance genes (note the difference in scale). Relative abundance of a gene/function was defined as the fraction of total annotated proteins with the particular function. The antibiotic class denotes the classification of the antibiotics based on WHO ATC code J01 (WHO Collaborating Centre for Drug Statistics Methodology [http://www.whocc.no/atc_ddd_index/]). The cladogram was constructed using complete linkage hierarchical clustering with Euclidean distance, as implemented on gplot package in R (92). A detailed description of all the proteins plotted in the heat map is in Table S4 in the supplemental material.