Bacterial colonization and succession in a newly opened hospital

The microorganisms that inhabit hospitals may influence patient recovery and outcome, although the complexity and diversity of these bacterial communities can confound our ability to focus on potential pathogens in isolation. To develop a community-level understanding of how microorganisms colonize...

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Bibliographic Details
Published in:	Science translational medicine Vol. 9; no. 391
Main Authors:	Lax, Simon, Sangwan, Naseer, Smith, Daniel, Larsen, Peter, Handley, Kim M, Richardson, Miles, Guyton, Kristina, Krezalek, Monika, Shogan, Benjamin D, Defazio, Jennifer, Flemming, Irma, Shakhsheer, Baddr, Weber, Stephen, Landon, Emily, Garcia-Houchins, Sylvia, Siegel, Jeffrey, Alverdy, John, Knight, Rob, Stephens, Brent, Gilbert, Jack A
Format:	Journal Article
Language:	English
Published:	United States 24-05-2017
Subjects:	Bacteria - genetics Bacteria - isolation & purification Bayes Theorem Hospitals Humans Microbiota Propionibacterium - genetics Propionibacterium - isolation & purification Staphylococcus - genetics Staphylococcus - isolation & purification
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Summary:	The microorganisms that inhabit hospitals may influence patient recovery and outcome, although the complexity and diversity of these bacterial communities can confound our ability to focus on potential pathogens in isolation. To develop a community-level understanding of how microorganisms colonize and move through the hospital environment, we characterized the bacterial dynamics among hospital surfaces, patients, and staff over the course of 1 year as a new hospital became operational. The bacteria in patient rooms, particularly on bedrails, consistently resembled the skin microbiota of the patient occupying the room. Bacterial communities on patients and room surfaces became increasingly similar over the course of a patient's stay. Temporal correlations in community structure demonstrated that patients initially acquired room-associated taxa that predated their stay but that their own microbial signatures began to influence the room community structure over time. The α- and β-diversity of patient skin samples were only weakly or nonsignificantly associated with clinical factors such as chemotherapy, antibiotic usage, and surgical recovery, and no factor except for ambulatory status affected microbial similarity between the microbiotas of a patient and their room. Metagenomic analyses revealed that genes conferring antimicrobial resistance were consistently more abundant on room surfaces than on the skin of the patients inhabiting those rooms. In addition, persistent unique genotypes of and were identified. Dynamic Bayesian network analysis suggested that hospital staff were more likely to be a source of bacteria on the skin of patients than the reverse but that there were no universal patterns of transmission across patient rooms.
ISSN:	1946-6242
DOI:	10.1126/scitranslmed.aah6500