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Marotz C, Belda-Ferre P, Ali F, Das P, Huang S, Cantrell K, Jiang L, Martino C, Diner RE, Rahman G, McDonald D, Armstrong G, Kodera S, Donato S, Ecklu-Mensah G, Gottel N, Garcia MCS, Chiang LY, Salido RA, Shaffer JP, Bryant M, Sanders K, Humphrey G, Ackermann G, Haiminen N, Beck KL, Kim HC, Carrieri AP, Parida L, Vázquez-Baeza Y, Torriani FJ, Knight R, Gilbert JA, Sweeney DA, Allard SM. Microbial context predicts SARS-CoV-2 prevalence in patients and the hospital built environment. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.11.19.20234229. [PMID: 33236030 PMCID: PMC7685343 DOI: 10.1101/2020.11.19.20234229] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
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 ICU 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 in a 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 throughout their stay, SARS-CoV-2 was less frequently detected there (11%). Despite surface contamination in almost all patient rooms, no health care workers providing COVID-19 patient care contracted the disease. 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 classifier accuracy for SARS-CoV-2 status in not only nares, but also forehead, stool and floor samples. Across these 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 when comparing to samples from patients in another intensive care unit prior to the COVID-19 pandemic. These results suggest that bacterial communities contribute to viral prevalence both in the host and hospital environment.
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Affiliation(s)
- Clarisse Marotz
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Pedro Belda-Ferre
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Farhana Ali
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Promi Das
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Shi Huang
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Kalen Cantrell
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Department of Computer Science and Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Lingjing Jiang
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Division of Biostatistics, University of California, San Diego, La Jolla, California, USA
| | - Cameron Martino
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Bioinformatics and Systems Biology Program, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Rachel E Diner
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Gibraan Rahman
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Bioinformatics and Systems Biology Program, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Daniel McDonald
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - George Armstrong
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Bioinformatics and Systems Biology Program, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Sho Kodera
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Sonya Donato
- Microbiome Core, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Gertrude Ecklu-Mensah
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Neil Gottel
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Mariana C Salas Garcia
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
| | - Leslie Y Chiang
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Rodolfo A Salido
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Justin P Shaffer
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - MacKenzie Bryant
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Karenina Sanders
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Greg Humphrey
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Gail Ackermann
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
| | - Niina Haiminen
- IBM, T.J Watson Research Center, Yorktown Heights, New York, USA
| | - Kristen L Beck
- AI and Cognitive Software, IBM Research-Almaden, San Jose, California, USA
| | - Ho-Cheol Kim
- AI and Cognitive Software, IBM Research-Almaden, San Jose, California, USA
| | | | - Laxmi Parida
- AI and Cognitive Software, IBM Research-Almaden, San Jose, California, USA
| | - Yoshiki Vázquez-Baeza
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Francesca J Torriani
- Infection Prevention and Clinical Epidemiology Unit at UC San Diego Health, Division of Infectious Diseases and Global Public Health, Department of Medicine, UC San Diego, San Diego CA, USA
| | - Rob Knight
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Department of Computer Science and Engineering, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
- Department of Bioengineering, University of California San Diego, La Jolla, California, USA
| | - Jack A Gilbert
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
- Center for Microbiome Innovation, Jacobs School of Engineering, University of California San Diego, La Jolla, California, USA
| | - Daniel A Sweeney
- Division of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of California San Diego, La Jolla, California, USA
| | - Sarah M Allard
- Department of Pediatrics, School of Medicine, University of California San Diego, La Jolla, California, USA
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, California, USA
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