SARS-CoV-2 detection status associates with bacterial community composition in patients and the hospital environment
This article has been Reviewed by the following groups
Listed in
- Evaluated articles (ScreenIT)
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.
Article activity feed
-
-
SciScore for 10.1101/2020.11.19.20234229: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Top 100 random forest importance ranks and GreenGenes taxonomy from nares, forehead, stool, and inside floor samples. GreenGenessuggested: (Greengenes, RRID:SCR_002830)Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:It is both a strength and a limitation of this study that standard of care environmental cleaning was performed and was not influenced or altered by the …
SciScore for 10.1101/2020.11.19.20234229: (What is this?)
Please note, not all rigor criteria are appropriate for all manuscripts.
Table 1: Rigor
Institutional Review Board Statement not detected. Randomization not detected. Blinding not detected. Power Analysis not detected. Sex as a biological variable not detected. Table 2: Resources
Software and Algorithms Sentences Resources Top 100 random forest importance ranks and GreenGenes taxonomy from nares, forehead, stool, and inside floor samples. GreenGenessuggested: (Greengenes, RRID:SCR_002830)Results from OddPub: Thank you for sharing your data.
Results from LimitationRecognizer: We detected the following sentences addressing limitations in the study:It is both a strength and a limitation of this study that standard of care environmental cleaning was performed and was not influenced or altered by the study team. The daily cleaning regimen can vary depending on staff and other variables (hospital room surface types and disinfection protocols are summarized in Table S1) which is representative of hospital environmental practices worldwide. SARS-CoV-2 was amplified from floor samples, albeit at a relatively low abundance based on Ct values, in rooms even without COVID-19 patients and after cleaning. This highlights the importance of maintaining effective cleaning practices to mitigate the risk of viral spread via fomites. Although transmission risk from the floor is likely negligible as discussed above, the relatively high positivity rate for floor samples allowed us to use them as a proxy to study how microbial communities are interrelated with shed virus. In the built environment, microbial load, human biomass and alpha-diversity were higher in floor samples positive for SARS-CoV-2. Floor samples also had the highest biomass of all the surface samples tested, including high-touch surfaces (e.g. bedrail, keyboard, door handles). This may help explain the higher prevalence of positive floor samples in COVID-19 patient rooms (39%) versus bed rail samples (11%), despite their distance from the patient. This is in agreement with previous research showing that bacterial- and viral load are positively correlated in built environm...
Results from TrialIdentifier: No clinical trial numbers were referenced.
Results from Barzooka: We did not find any issues relating to the usage of bar graphs.
Results from JetFighter: We did not find any issues relating to colormaps.
Results from rtransparent:- Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
- Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
- No protocol registration statement was detected.
-
