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Callahan C, Lee RA, Lee GR, Zulauf K, Kirby JE, Arnaout R. Nasal Swab Performance by Collection Timing, Procedure, and Method of Transport for Patients with SARS-CoV-2. J Clin Microbiol 2021; 59:e0056921. [PMID: 34076471 PMCID: PMC8373031 DOI: 10.1128/jcm.00569-21] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2021] [Accepted: 04/30/2021] [Indexed: 12/23/2022] Open
Abstract
The urgent need for large-scale diagnostic testing for SARS-CoV-2 has prompted interest in sample collection methods of sufficient sensitivity to replace nasopharynx (NP) sampling. Nasal swab samples are an attractive alternative; however, previous studies have disagreed over how nasal sampling performs relative to NP sampling. Here, we compared nasal versus NP specimens collected by health care workers in a cohort of individuals clinically suspected of COVID-19 as well as SARS-CoV-2 reverse transcription (RT)-PCR-positive outpatients undergoing follow-up. We compared subjects being seen for initial evaluation versus follow-up, two different nasal swab collection protocols, and three different transport conditions, including traditional viral transport media (VTM) and dry swabs, on 307 total study participants. We compared categorical results and viral loads to those from standard NP swabs collected at the same time from the same patients. All testing was performed by RT-PCR on the Abbott SARS-CoV-2 RealTime emergency use authorization (EUA) (limit of detection [LoD], 100 copies viral genomic RNA/ml transport medium). We found low concordance overall, with Cohen's kappa (κ) of 0.49, with high concordance only for subjects with very high viral loads. We found medium concordance for testing at initial presentation (κ = 0.68) and very low concordance for follow-up testing (κ = 0.27). Finally, we show that previous reports of high concordance may have resulted from measurement using assays with sensitivity of ≥1,000 copies/ml. These findings suggest nasal-swab testing be used for situations in which viral load is expected to be high, as we demonstrate that nasal swab testing is likely to miss patients with low viral loads.
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Affiliation(s)
- Cody Callahan
- Department of Radiology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Rose A. Lee
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Division of Infectious Diseases, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Ghee Rye Lee
- Department of Surgery, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Kate Zulauf
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - James E. Kirby
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
| | - Ramy Arnaout
- Department of Pathology, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Division of Clinical Informatics, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
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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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3
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Minich JJ, Power C, Melanson M, Knight R, Webber C, Rough K, Bott NJ, Nowak B, Allen EE. The Southern Bluefin Tuna Mucosal Microbiome Is Influenced by Husbandry Method, Net Pen Location, and Anti-parasite Treatment. Front Microbiol 2020; 11:2015. [PMID: 32983024 PMCID: PMC7476325 DOI: 10.3389/fmicb.2020.02015] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2020] [Accepted: 07/30/2020] [Indexed: 12/19/2022] Open
Abstract
Aquaculture is the fastest growing primary industry worldwide. Marine finfish culture in open ocean net pens, or pontoons, is one of the largest growth areas and is currently the only way to rear high value fish such as bluefin tuna. Ranching involves catching wild juveniles, stocking in floating net pens and fattening for 4 to 8 months. Tuna experience several parasite-induced disease challenges in culture that can be mitigated by application of praziquantel (PZQ) as a therapeutic. In this study, we characterized the microbiome of ranched southern Bluefin Tuna, Thunnus maccoyii, across four anatomic sites (gill, skin, digesta, and anterior kidney) and evaluated environmental and pathological factors that influence microbiome composition, including the impact of PZQ treatment on microbiome stability. Southern bluefin tuna gill, skin, and digesta microbiome communities are unique and potentially influenced by husbandry practices, location of pontoon growout pens, and treatment with the antiparasitic PZQ. There was no significant relationship between the fish mucosal microbiome and incidence or abundance of adult blood fluke in the heart or fluke egg density in the gill. An enhanced understanding of microbiome diversity and function in high-value farmed fish species such as bluefin tuna is needed to optimize fish health and improve aquaculture yield. Comparison of the bluefin tuna microbiome to other fish species, including Seriola lalandi (yellowtail kingfish), a common farmed species from Australia, and Scomber japonicus (Pacific mackerel), a wild caught Scombrid relative of tuna, showed the two Scombrids had more similar microbial communities compared to other families. The finding that mucosal microbial communities are more similar in phylogenetically related fish species exposes an opportunity to develop mackerel as a model for tuna microbiome and parasite research.
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Affiliation(s)
- Jeremiah J. Minich
- Marine Biology Research Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States
| | - Cecilia Power
- Centre for Environmental Sustainability and Remediation, School of Science, RMIT University, Bundoora, VIC, Australia
| | - Michaela Melanson
- Marine Biology Research Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States
| | - Rob Knight
- Department of Pediatrics, School of Medicine, University of California, San Diego, La Jolla, CA, United States
- Department of Computer Science and Engineering, University of California, San Diego, La Jolla, CA, United States
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, United States
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, United States
| | - Claire Webber
- Australian Southern Bluefin Tuna Industry Association, Port Lincoln, SA, Australia
| | - Kirsten Rough
- Australian Southern Bluefin Tuna Industry Association, Port Lincoln, SA, Australia
| | - Nathan J. Bott
- Centre for Environmental Sustainability and Remediation, School of Science, RMIT University, Bundoora, VIC, Australia
| | - Barbara Nowak
- Centre for Environmental Sustainability and Remediation, School of Science, RMIT University, Bundoora, VIC, Australia
- Institute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS, Australia
| | - Eric E. Allen
- Marine Biology Research Division, Scripps Institution of Oceanography, University of California, San Diego, La Jolla, CA, United States
- Center for Microbiome Innovation, University of California, San Diego, La Jolla, CA, United States
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, United States
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