SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment
Abstract Background SARS-CoV-2 is an RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Viruses exist in complex microbial environments, and recent studies have revealed both synergistic and antagonistic effects of specific bacterial taxa on viral prevalence and infectivity....
| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2021-06-01
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| Series: | Microbiome |
| Subjects: | |
| Online Access: | https://doi.org/10.1186/s40168-021-01083-0 |
| _version_ | 1819012263016660992 |
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| author | Clarisse Marotz Pedro Belda-Ferre Farhana Ali Promi Das Shi Huang Kalen Cantrell Lingjing Jiang Cameron Martino Rachel E. Diner Gibraan Rahman Daniel McDonald George Armstrong Sho Kodera Sonya Donato Gertrude Ecklu-Mensah Neil Gottel Mariana C. Salas Garcia Leslie Y. Chiang Rodolfo A. Salido Justin P. Shaffer Mac Kenzie Bryant Karenina Sanders Greg Humphrey Gail Ackermann Niina Haiminen Kristen L. Beck Ho-Cheol Kim Anna Paola Carrieri Laxmi Parida Yoshiki Vázquez-Baeza Francesca J. Torriani Rob Knight Jack Gilbert Daniel A. Sweeney Sarah M. Allard |
| author_facet | Clarisse Marotz Pedro Belda-Ferre Farhana Ali Promi Das Shi Huang Kalen Cantrell Lingjing Jiang Cameron Martino Rachel E. Diner Gibraan Rahman Daniel McDonald George Armstrong Sho Kodera Sonya Donato Gertrude Ecklu-Mensah Neil Gottel Mariana C. Salas Garcia Leslie Y. Chiang Rodolfo A. Salido Justin P. Shaffer Mac Kenzie Bryant Karenina Sanders Greg Humphrey Gail Ackermann Niina Haiminen Kristen L. Beck Ho-Cheol Kim Anna Paola Carrieri Laxmi Parida Yoshiki Vázquez-Baeza Francesca J. Torriani Rob Knight Jack Gilbert Daniel A. Sweeney Sarah M. Allard |
| author_sort | Clarisse Marotz |
| collection | DOAJ |
| description | Abstract Background SARS-CoV-2 is an RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Viruses exist in complex microbial environments, and recent studies have revealed both synergistic and antagonistic effects of specific bacterial taxa on viral prevalence and infectivity. We set out to test whether specific bacterial communities predict SARS-CoV-2 occurrence in a hospital setting. Methods We collected 972 samples from hospitalized patients with 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 used these bacterial profiles to classify SARS-CoV-2 RNA detection with a random forest model. Results Sixteen percent of surfaces from COVID-19 patient rooms had detectable SARS-CoV-2 RNA, although infectivity was not assessed. The highest prevalence was in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples more closely resembled the patient microbiome compared to floor samples, SARS-CoV-2 RNA was detected less often in bed rail samples (11%). SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity in both human and surface samples and higher biomass in floor samples. 16S microbial community profiles enabled 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 strongly predicted SARS-CoV-2 presence across sample types, with greater prevalence in positive surface and human samples, even when compared to samples from patients in other intensive care units prior to the COVID-19 pandemic. Conclusions These results contextualize the vast diversity of microbial niches where SARS-CoV-2 RNA is detected and identify specific bacterial taxa that associate with the viral RNA prevalence both in the host and hospital environment. Video Abstract |
| first_indexed | 2024-12-21T01:41:16Z |
| format | Article |
| id | doaj.art-9cbfb3750bf44967a2ef40936b47350e |
| institution | Directory Open Access Journal |
| issn | 2049-2618 |
| language | English |
| last_indexed | 2024-12-21T01:41:16Z |
| publishDate | 2021-06-01 |
| publisher | BMC |
| record_format | Article |
| series | Microbiome |
| spelling | doaj.art-9cbfb3750bf44967a2ef40936b47350e2022-12-21T19:20:09ZengBMCMicrobiome2049-26182021-06-019111510.1186/s40168-021-01083-0SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environmentClarisse Marotz0Pedro Belda-Ferre1Farhana Ali2Promi Das3Shi Huang4Kalen Cantrell5Lingjing Jiang6Cameron Martino7Rachel E. Diner8Gibraan Rahman9Daniel McDonald10George Armstrong11Sho Kodera12Sonya Donato13Gertrude Ecklu-Mensah14Neil Gottel15Mariana C. Salas Garcia16Leslie Y. Chiang17Rodolfo A. Salido18Justin P. Shaffer19Mac Kenzie Bryant20Karenina Sanders21Greg Humphrey22Gail Ackermann23Niina Haiminen24Kristen L. Beck25Ho-Cheol Kim26Anna Paola Carrieri27Laxmi Parida28Yoshiki Vázquez-Baeza29Francesca J. Torriani30Rob Knight31Jack Gilbert32Daniel A. Sweeney33Sarah M. Allard34Department of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San DiegoCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoMicrobiome Core, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoInfection Prevention and Clinical Epidemiology Unit at UC San Diego Health, Division of Infectious Diseases and Global Public Health, Department of Medicine, UC San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoIBM, T.J Watson Research Center, Yorktown HeightsAI and Cognitive Software, IBM Research-AlmadenAI and Cognitive Software, IBM Research-AlmadenIBM Research UK, The Hartree CentreIBM, T.J Watson Research Center, Yorktown HeightsCenter for Microbiome Innovation, Jacobs School of Engineering, University of California San DiegoInfection Prevention and Clinical Epidemiology Unit at UC San Diego Health, Division of Infectious Diseases and Global Public Health, Department of Medicine, UC San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoDivision of Pulmonary, Critical Care and Sleep Medicine, Department of Internal Medicine, University of California San DiegoDepartment of Pediatrics, School of Medicine, University of California San DiegoAbstract Background SARS-CoV-2 is an RNA virus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Viruses exist in complex microbial environments, and recent studies have revealed both synergistic and antagonistic effects of specific bacterial taxa on viral prevalence and infectivity. We set out to test whether specific bacterial communities predict SARS-CoV-2 occurrence in a hospital setting. Methods We collected 972 samples from hospitalized patients with 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 used these bacterial profiles to classify SARS-CoV-2 RNA detection with a random forest model. Results Sixteen percent of surfaces from COVID-19 patient rooms had detectable SARS-CoV-2 RNA, although infectivity was not assessed. The highest prevalence was in floor samples next to patient beds (39%) and directly outside their rooms (29%). Although bed rail samples more closely resembled the patient microbiome compared to floor samples, SARS-CoV-2 RNA was detected less often in bed rail samples (11%). SARS-CoV-2 positive samples had higher bacterial phylogenetic diversity in both human and surface samples and higher biomass in floor samples. 16S microbial community profiles enabled 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 strongly predicted SARS-CoV-2 presence across sample types, with greater prevalence in positive surface and human samples, even when compared to samples from patients in other intensive care units prior to the COVID-19 pandemic. Conclusions These results contextualize the vast diversity of microbial niches where SARS-CoV-2 RNA is detected and identify specific bacterial taxa that associate with the viral RNA prevalence both in the host and hospital environment. Video Abstracthttps://doi.org/10.1186/s40168-021-01083-0Built environmentSARS-CoV-216S rRNAMicrobiomeCOVID-19 |
| spellingShingle | Clarisse Marotz Pedro Belda-Ferre Farhana Ali Promi Das Shi Huang Kalen Cantrell Lingjing Jiang Cameron Martino Rachel E. Diner Gibraan Rahman Daniel McDonald George Armstrong Sho Kodera Sonya Donato Gertrude Ecklu-Mensah Neil Gottel Mariana C. Salas Garcia Leslie Y. Chiang Rodolfo A. Salido Justin P. Shaffer Mac Kenzie Bryant Karenina Sanders Greg Humphrey Gail Ackermann Niina Haiminen Kristen L. Beck Ho-Cheol Kim Anna Paola Carrieri Laxmi Parida Yoshiki Vázquez-Baeza Francesca J. Torriani Rob Knight Jack Gilbert Daniel A. Sweeney Sarah M. Allard SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment Microbiome Built environment SARS-CoV-2 16S rRNA Microbiome COVID-19 |
| title | SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment |
| title_full | SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment |
| title_fullStr | SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment |
| title_full_unstemmed | SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment |
| title_short | SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment |
| title_sort | sars cov 2 detection status associates with bacterial community composition in patients and the hospital environment |
| topic | Built environment SARS-CoV-2 16S rRNA Microbiome COVID-19 |
| url | https://doi.org/10.1186/s40168-021-01083-0 |
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