Author: Marotz, Clarisse; Belda-Ferre, Pedro; Ali, Farhana; Das, Promi; Huang, Shi; Cantrell, Kalen; Jiang, Lingjing; Martino, Cameron; Diner, Rachel E.; Rahman, Gibraan; McDonald, Daniel; Armstrong, George; Kodera, Sho; Donato, Sonya; Ecklu-Mensah, Gertrude; Gottel, Neil; Garcia, Mariana C. Salas; Chiang, Leslie Y.; Salido, Rodolfo A.; Shaffer, Justin P.; Bryant, MacKenzie; Sanders, Karenina; Humphrey, Greg; Ackermann, Gail; Haiminen, Niina; Beck, Kristen L.; Kim, Ho-Cheol; Carrieri, Anna Paola; Parida, Laxmi; Vázquez-Baeza, Yoshiki; Torriani, Francesca J.; Knight, Rob; Gilbert, Jack A.; Sweeney, Daniel A.; Allard, Sarah M.
Title: Microbial context predicts SARS-CoV-2 prevalence in patients and the hospital built environment Cord-id: 3t1g1nj4 Document date: 2020_11_22
ID: 3t1g1nj4
Snippet: Synergistic effects of bacteria on viral stability and transmission are widely documented but remain unclear in the context of SARS-CoV-2. We collected 972 samples from hospitalized patients with coronavirus disease 2019 (COVID-19), their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and contextualized the massive microbial diversity in this d
Document: Synergistic effects of bacteria on viral stability and transmission are widely documented but remain unclear in the context of SARS-CoV-2. We collected 972 samples from hospitalized patients with coronavirus disease 2019 (COVID-19), their health care providers, and hospital surfaces before, during, and after admission. We screened for SARS-CoV-2 using RT-qPCR, characterized microbial communities using 16S rRNA gene amplicon sequencing, and contextualized the massive microbial diversity in this dataset through meta-analysis of over 20,000 samples. Sixteen percent of surfaces from COVID-19 patient rooms were positive, with the highest prevalence in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples increasingly resembled the patient microbiome over time, SARS-CoV-2 was detected less there (11%). Despite viral surface contamination in almost all patient rooms, no health care workers contracted the disease, suggesting that personal protective equipment was effective in preventing transmissions. SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity across human and surface samples, and higher biomass in floor samples. 16S microbial community profiles allowed for high SARS-CoV-2 classifier accuracy in not only nares, but also forehead, stool, and floor samples. Across distinct microbial profiles, a single amplicon sequence variant from the genus Rothia was highly predictive of SARS-CoV-2 across sample types and had higher prevalence in positive surface and human samples, even compared to samples from patients in another intensive care unit prior to the COVID-19 pandemic. These results suggest that bacterial communities may contribute to viral prevalence both in the host and hospital environment.
Search related documents:
Co phrase search for related documents- Try single phrases listed below for: 1
Co phrase search for related documents, hyperlinks ordered by date