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Microbiome ; 8(1): 86, 2020 06 08.
Artigo em Inglês | MEDLINE | ID: mdl-32513256

RESUMO

BACKGROUND: Inanimate surfaces within a hospital serve as a reservoir of microbial life that may colonize patients and ultimately result in healthcare associated infections (HAIs). Critically ill patients in intensive care units (ICUs) are particularly vulnerable to HAIs. Little is known about how the microbiome of the ICU is established or what factors influence its evolution over time. A unique opportunity to bridge the knowledge gap into how the ICU microbiome evolves emerged in our health system, where we were able to characterize microbial communities in an established hospital ICU prior to closing for renovations, during renovations, and then after re-opening. RESULTS: We collected swab specimens from ICU bedrails, computer keyboards, and sinks longitudinally at each renovation stage, and analyzed the bacterial compositions on these surfaces by 16S rRNA gene sequencing. Specimens collected before ICU closure had the greatest alpha diversity, while specimens collected after the ICU had been closed for over 300 days had the least. We sampled the ICU during the 45 days after re-opening; however, within that time frame, the alpha diversity never reached pre-closure levels. There were clear and significant differences in microbiota compositions at each renovation stage, which was driven by environmental bacteria after closure and human-associated bacteria after re-opening and before closure. CONCLUSIONS: Overall, we identified significant differences in microbiota diversity and community composition at each renovation stage. These data help to decipher the evolution of the microbiome in the most critical part of the hospital and demonstrate the significant impacts that microbiota from patients and staff have on the evolution of ICU surfaces. Video Abstract.


Assuntos
Biodiversidade , Microbiologia Ambiental , Arquitetura Hospitalar , Unidades de Terapia Intensiva , Microbiota , Bactérias/genética , Arquitetura Hospitalar/estatística & dados numéricos , Microbiota/genética , RNA Ribossômico 16S/genética , Fatores de Tempo
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