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1.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-337278

ABSTRACT

Background: The exchange of microbes between humans and the built environment is a bidirectional and dynamic process that has significant impact on health. Most studies exploring the microbiome of the built environment have been predicated on improving our understanding of pathogen emergence, persistence, and transmission. Previous studies have demonstrated that SARS-CoV-2 presence significantly correlates with the proportional abundance of specific bacteria on surfaces in the built environment. However, in these studies, SARS-CoV-2 originated from infected patients. Here we perform a similar assessment for a clinical microbiology lab while staff were handling SARS-CoV-2 infected swab samples for RT-qPCR analysis. The goal of this study was to understand the distribution and dynamics of microbial population on various surfaces within different sections of a clinical microbiology lab during a short period of 2020 Coronavirus disease (COVID-19) pandemic. Results: : We sampled floors, benches and sinks in three sections of an active clinical microbiology lab (bacteriology, molecular microbiology, and COVID) over a 3-month period. Although floor samples harbored SARS-CoV-2, it was rarely identified on other surfaces, and bacterial diversity was significantly greater in floor samples than sinks and benches. The floor-associated microbiota comprised greater proportions of bacteria commonly associated with natural environments (e.g., soils), and benchtops harbored a greater proportion of human-associated microbes, including Staphylococcus and Streptococcus , which may have originated from either laboratory staff or clinical samples. Finally, we show that the microbial composition of these surfaces did not change over time and remained stable. Conclusion: Despite of finding viruses on the floors, no lab-acquired infections were reported during the study period, which suggests that lab safety protocols and sanitation practices were sufficient to prevent pathogen exposures. Like other BEs and health care facilities the most common bacteria colonizing the surfaces in a clinical microbiology lab primarily consist of bacterial taxa of environmental and human origin. Although our analysis here does not identify the source of infection in any given case, it does help to elucidate microbes that colonize these surfaces and have the potential to cause LAIs.

2.
mSystems ; 7(3): e0141121, 2022 Jun 28.
Article in English | MEDLINE | ID: covidwho-1846330

ABSTRACT

Monitoring severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces is emerging as an important tool for identifying past exposure to individuals shedding viral RNA. Our past work demonstrated that SARS-CoV-2 reverse transcription-quantitative PCR (RT-qPCR) signals from surfaces can identify when infected individuals have touched surfaces and when they have been present in hospital rooms or schools. However, the sensitivity and specificity of surface sampling as a method for detecting the presence of a SARS-CoV-2 positive individual, as well as guidance about where to sample, has not been established. To address these questions and to test whether our past observations linking SARS-CoV-2 abundance to Rothia sp. in hospitals also hold in a residential setting, we performed a detailed spatial sampling of three isolation housing units, assessing each sample for SARS-CoV-2 abundance by RT-qPCR, linking the results to 16S rRNA gene amplicon sequences (to assess the bacterial community at each location), and to the Cq value of the contemporaneous clinical test. Our results showed that the highest SARS-CoV-2 load in this setting is on touched surfaces, such as light switches and faucets, but a detectable signal was present in many untouched surfaces (e.g., floors) that may be more relevant in settings, such as schools where mask-wearing is enforced. As in past studies, the bacterial community predicts which samples are positive for SARS-CoV-2, with Rothia sp. showing a positive association. IMPORTANCE Surface sampling for detecting SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19), is increasingly being used to locate infected individuals. We tested which indoor surfaces had high versus low viral loads by collecting 381 samples from three residential units where infected individuals resided, and interpreted the results in terms of whether SARS-CoV-2 was likely transmitted directly (e.g., touching a light switch) or indirectly (e.g., by droplets or aerosols settling). We found the highest loads where the subject touched the surface directly, although enough virus was detected on indirectly contacted surfaces to make such locations useful for sampling (e.g., in schools, where students did not touch the light switches and also wore masks such that they had no opportunity to touch their face and then the object). We also documented links between the bacteria present in a sample and the SARS-CoV-2 virus, consistent with earlier studies.

3.
Sci Rep ; 12(1): 5077, 2022 03 24.
Article in English | MEDLINE | ID: covidwho-1815587

ABSTRACT

Throughout the COVID-19 pandemic, massive sequencing and data sharing efforts enabled the real-time surveillance of novel SARS-CoV-2 strains throughout the world, the results of which provided public health officials with actionable information to prevent the spread of the virus. However, with great sequencing comes great computation, and while cloud computing platforms bring high-performance computing directly into the hands of all who seek it, optimal design and configuration of a cloud compute cluster requires significant system administration expertise. We developed ViReflow, a user-friendly viral consensus sequence reconstruction pipeline enabling rapid analysis of viral sequence datasets leveraging Amazon Web Services (AWS) cloud compute resources and the Reflow system. ViReflow was developed specifically in response to the COVID-19 pandemic, but it is general to any viral pathogen. Importantly, when utilized with sufficient compute resources, ViReflow can trim, map, call variants, and call consensus sequences from amplicon sequence data from 1000 SARS-CoV-2 samples at 1000X depth in < 10 min, with no user intervention. ViReflow's simplicity, flexibility, and scalability make it an ideal tool for viral molecular epidemiological efforts.


Subject(s)
COVID-19 , Software , COVID-19/epidemiology , Genome, Viral/genetics , Humans , Pandemics , SARS-CoV-2/genetics
5.
EuropePMC; 2022.
Preprint in English | EuropePMC | ID: ppcovidwho-329062

ABSTRACT

Monitoring wastewater samples at building-level resolution screens large populations for SARS-CoV-2, prioritizing testing and isolation efforts. Here we perform untargeted metatranscriptomics on virally-enriched wastewater samples from 10 locations on the UC San Diego campus, demonstrating that resulting bacterial taxonomic and functional profiles discriminate SARS-CoV-2 status even without direct detection of viral transcripts. Our proof-of-principle reveals emergent threats through changes in the human microbiome, suggesting new approaches for untargeted wastewater-based epidemiology.

6.
EuropePMC;
Preprint in English | EuropePMC | ID: ppcovidwho-327336

ABSTRACT

Accurate, high-resolution environmental monitoring of SARS-CoV-2 traces indoors through sentinel cards is a promising approach to help students safely return to in-person learning. Because SARS-CoV-2 RNA can persist for up to a week on several indoor surface types, there is a need for increased temporal resolution to determine whether consecutive surface positives arise from new infection events or continue to report past events. Cleaning sentinel cards after sampling would provide the needed resolution, but might interfere with assay performance. We tested the effect of three cleaning solutions (BZK wipes, wet wipes, RNase Away) at three different viral loads: "high" (4 x 10 4 GE/mL), "medium" (1 x 10 4 GE/mL), and "low" (2.5 x 10 3 GE/mL). RNAse Away, chosen as a positive control, was the most effective cleaning solution on all three viral loads. Wet wipes were found to be more effective than BZK wipes in the medium viral load condition. The low viral load condition was easily reset with all three cleaning solutions. These findings will enable temporal SARS-CoV-2 monitoring in indoor environments where transmission risk of the virus is high and the need to avoid individual-level sampling for privacy or compliance reasons exists.

7.
2021.
Preprint in English | Other preprints | ID: ppcovidwho-294133

ABSTRACT

Cell interactions determine phenotypes, and intercellular communication is shaped by cellular contexts such as disease state, organismal life stage, and tissue microenvironment. Single-cell technologies measure the molecules mediating cell-cell communication, and emerging computational tools can exploit these data to decipher intercellular communication. However, current methods either disregard cellular context or rely on simple pairwise comparisons between samples, thus limiting the ability to decipher complex cell-cell communication across multiple time points, levels of disease severity, or spatial contexts. Here we present Tensor-cell2cell, an unsupervised method using tensor decomposition, which is the first strategy to decipher context-driven intercellular communication by simultaneously accounting for multiple stages, states, or locations of the cells. To do so, Tensor-cell2cell uncovers context-driven patterns of communication associated with different phenotypic states and determined by unique combinations of cell types and ligand-receptor pairs. We show Tensor-cell2cell can identify multiple modules associated with distinct communication processes (e.g., participating cell-cell and ligand receptor pairs) linked to COVID-19 severities. Thus, we introduce an effective and easy-to-use strategy for understanding complex communication patterns across diverse conditions.

8.
mSystems ; 6(6): e0113621, 2021 Dec 21.
Article in English | MEDLINE | ID: covidwho-1494994

ABSTRACT

Environmental monitoring in public spaces can be used to identify surfaces contaminated by persons with coronavirus disease 2019 (COVID-19) and inform appropriate infection mitigation responses. Research groups have reported detection of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) on surfaces days or weeks after the virus has been deposited, making it difficult to estimate when an infected individual may have shed virus onto a SARS-CoV-2-positive surface, which in turn complicates the process of establishing effective quarantine measures. In this study, we determined that reverse transcription-quantitative PCR (RT-qPCR) detection of viral RNA from heat-inactivated particles experiences minimal decay over 7 days of monitoring on eight out of nine surfaces tested. The properties of the studied surfaces result in RT-qPCR signatures that can be segregated into two material categories, rough and smooth, where smooth surfaces have a lower limit of detection. RT-qPCR signal intensity (average quantification cycle [Cq]) can be correlated with surface viral load using only one linear regression model per material category. The same experiment was performed with untreated viral particles on one surface from each category, with essentially identical results. The stability of RT-qPCR viral signal demonstrates the need to clean monitored surfaces after sampling to establish temporal resolution. Additionally, these findings can be used to minimize the number of materials and time points tested and allow for the use of heat-inactivated viral particles when optimizing environmental monitoring methods. IMPORTANCE Environmental monitoring is an important tool for public health surveillance, particularly in settings with low rates of diagnostic testing. Time between sampling public environments, such as hospitals or schools, and notifying stakeholders of the results should be minimal, allowing decisions to be made toward containing outbreaks of coronavirus disease 2019 (COVID-19). The Safer At School Early Alert program (SASEA) (https://saseasystem.org/), a large-scale environmental monitoring effort in elementary school and child care settings, has processed >13,000 surface samples for SARS-CoV-2, detecting viral signals from 574 samples. However, consecutive detection events necessitated the present study to establish appropriate response practices around persistent viral signals on classroom surfaces. Other research groups and clinical labs developing environmental monitoring methods may need to establish their own correlation between RT-qPCR results and viral load, but this work provides evidence justifying simplified experimental designs, like reduced testing materials and the use of heat-inactivated viral particles.

9.
ACS Sens ; 6(11): 3957-3966, 2021 11 26.
Article in English | MEDLINE | ID: covidwho-1493024

ABSTRACT

The development of an extensive toolkit for potential point-of-care diagnostics that is expeditiously adaptable to new emerging pathogens is of critical public health importance. Recently, a number of novel CRISPR-based diagnostics have been developed to detect SARS-CoV-2. Herein, we outline the development of an alternative CRISPR nucleic acid diagnostic utilizing a Cas13d ribonuclease derived from Ruminococcus flavefaciens XPD3002 (CasRx) to detect SARS-CoV-2, an approach we term SENSR (sensitive enzymatic nucleic acid sequence reporter) that can detect attomolar concentrations of SARS-CoV-2. We demonstrate 100% sensitivity in patient-derived samples by lateral flow and fluorescence readout with a detection limit of 45 copy/µL. This technology expands the available nucleic acid diagnostic toolkit, which can be adapted to combat future pandemics.


Subject(s)
COVID-19 , SARS-CoV-2 , Humans , Nucleic Acid Amplification Techniques , RNA, Viral , Ruminococcus
10.
mSystems ; 6(4): e0079321, 2021 Aug 31.
Article in English | MEDLINE | ID: covidwho-1350006

ABSTRACT

Wastewater-based surveillance has gained prominence and come to the forefront as a leading indicator of forecasting COVID-19 (coronavirus disease 2019) infection dynamics owing to its cost-effectiveness and its ability to inform early public health interventions. A university campus could especially benefit from wastewater surveillance, as universities are characterized by largely asymptomatic populations and are potential hot spots for transmission that necessitate frequent diagnostic testing. In this study, we employed a large-scale GIS (geographic information systems)-enabled building-level wastewater monitoring system associated with the on-campus residences of 7,614 individuals. Sixty-eight automated wastewater samplers were deployed to monitor 239 campus buildings with a focus on residential buildings. Time-weighted composite samples were collected on a daily basis and analyzed on the same day. Sample processing was streamlined significantly through automation, reducing the turnaround time by 20-fold and exceeding the scale of similar surveillance programs by 10- to 100-fold, thereby overcoming one of the biggest bottlenecks in wastewater surveillance. An automated wastewater notification system was developed to alert residents to a positive wastewater sample associated with their residence and to encourage uptake of campus-provided asymptomatic testing at no charge. This system, integrated with the rest of the "Return to Learn" program at the University of California (UC) San Diego-led to the early diagnosis of nearly 85% of all COVID-19 cases on campus. COVID-19 testing rates increased by 1.9 to 13× following wastewater notifications. Our study shows the potential for a robust, efficient wastewater surveillance system to greatly reduce infection risk as college campuses and other high-risk environments reopen. IMPORTANCE Wastewater-based epidemiology can be particularly valuable at university campuses where high-resolution spatial sampling in a well-controlled context could not only provide insight into what affects campus community as well as how those inferences can be extended to a broader city/county context. In the present study, a large-scale wastewater surveillance was successfully implemented on a large university campus enabling early detection of 85% of COVID-19 cases thereby averting potential outbreaks. The highly automated sample processing to reporting system enabled dramatic reduction in the turnaround time to 5 h (sample to result time) for 96 samples. Furthermore, miniaturization of the sample processing pipeline brought down the processing cost significantly ($13/sample). Taken together, these results show that such a system could greatly ameliorate long-term surveillance on such communities as they look to reopen.

11.
Cell ; 184(19): 4939-4952.e15, 2021 09 16.
Article in English | MEDLINE | ID: covidwho-1330684

ABSTRACT

The emergence of the COVID-19 epidemic in the United States (U.S.) went largely undetected due to inadequate testing. New Orleans experienced one of the earliest and fastest accelerating outbreaks, coinciding with Mardi Gras. To gain insight into the emergence of SARS-CoV-2 in the U.S. and how large-scale events accelerate transmission, we sequenced SARS-CoV-2 genomes during the first wave of the COVID-19 epidemic in Louisiana. We show that SARS-CoV-2 in Louisiana had limited diversity compared to other U.S. states and that one introduction of SARS-CoV-2 led to almost all of the early transmission in Louisiana. By analyzing mobility and genomic data, we show that SARS-CoV-2 was already present in New Orleans before Mardi Gras, and the festival dramatically accelerated transmission. Our study provides an understanding of how superspreading during large-scale events played a key role during the early outbreak in the U.S. and can greatly accelerate epidemics.


Subject(s)
COVID-19/epidemiology , Epidemics , SARS-CoV-2/physiology , COVID-19/transmission , Databases as Topic , Disease Outbreaks , Humans , Louisiana/epidemiology , Phylogeny , Risk Factors , SARS-CoV-2/classification , Texas , Travel , United States/epidemiology
12.
PLoS Comput Biol ; 17(6): e1009056, 2021 06.
Article in English | MEDLINE | ID: covidwho-1282290

ABSTRACT

In October of 2020, in response to the Coronavirus Disease 2019 (COVID-19) pandemic, our team hosted our first fully online workshop teaching the QIIME 2 microbiome bioinformatics platform. We had 75 enrolled participants who joined from at least 25 different countries on 6 continents, and we had 22 instructors on 4 continents. In the 5-day workshop, participants worked hands-on with a cloud-based shared compute cluster that we deployed for this course. The event was well received, and participants provided feedback and suggestions in a postworkshop questionnaire. In January of 2021, we followed this workshop with a second fully online workshop, incorporating lessons from the first. Here, we present details on the technology and protocols that we used to run these workshops, focusing on the first workshop and then introducing changes made for the second workshop. We discuss what worked well, what didn't work well, and what we plan to do differently in future workshops.


Subject(s)
COVID-19 , Computational Biology , Microbiota , Computational Biology/education , Computational Biology/organization & administration , Feedback , Humans , SARS-CoV-2
13.
Microbiome ; 9(1): 132, 2021 06 08.
Article in English | MEDLINE | ID: covidwho-1262519

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.


Subject(s)
COVID-19 , SARS-CoV-2 , Hospitals , Humans , Pandemics , Phylogeny , RNA, Ribosomal, 16S/genetics , RNA, Viral/genetics
14.
Infect Control Hosp Epidemiol ; : 1-4, 2021 Mar 12.
Article in English | MEDLINE | ID: covidwho-1253833

ABSTRACT

Transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) is possible among symptom-free individuals. Patients are avoiding medically necessary healthcare visits for fear of becoming infected in the healthcare setting. We screened 489 symptom-free healthcare workers for SARS-CoV-2 and found no positive results, strongly suggesting that the prevalence of SARS-CoV-2 was <1%.

15.
Cell Rep ; 35(6): 109091, 2021 05 11.
Article in English | MEDLINE | ID: covidwho-1213072

ABSTRACT

It is urgent and important to understand the relationship of the widespread severe acute respiratory syndrome coronavirus clade 2 (SARS-CoV-2) with host immune response and study the underlining molecular mechanism. N6-methylation of adenosine (m6A) in RNA regulates many physiological and disease processes. Here, we investigate m6A modification of the SARS-CoV-2 gene in regulating the host cell innate immune response. Our data show that the SARS-CoV-2 virus has m6A modifications that are enriched in the 3' end of the viral genome. We find that depletion of the host cell m6A methyltransferase METTL3 decreases m6A levels in SARS-CoV-2 and host genes, and m6A reduction in viral RNA increases RIG-I binding and subsequently enhances the downstream innate immune signaling pathway and inflammatory gene expression. METTL3 expression is reduced and inflammatory genes are induced in patients with severe coronavirus disease 2019 (COVID-19). These findings will aid in the understanding of COVID-19 pathogenesis and the design of future studies regulating innate immunity for COVID-19 treatment.


Subject(s)
COVID-19/genetics , Methyltransferases/metabolism , SARS-CoV-2/genetics , Adenosine/metabolism , COVID-19/metabolism , Cell Line , DEAD Box Protein 58/genetics , DEAD Box Protein 58/metabolism , Humans , Immunity, Innate/genetics , Methylation , Methyltransferases/genetics , RNA, Viral/genetics , Receptors, Immunologic/genetics , Receptors, Immunologic/metabolism , SARS-CoV-2/pathogenicity , Signal Transduction
16.
Cell ; 184(10): 2587-2594.e7, 2021 05 13.
Article in English | MEDLINE | ID: covidwho-1157175

ABSTRACT

The highly transmissible B.1.1.7 variant of SARS-CoV-2, first identified in the United Kingdom, has gained a foothold across the world. Using S gene target failure (SGTF) and SARS-CoV-2 genomic sequencing, we investigated the prevalence and dynamics of this variant in the United States (US), tracking it back to its early emergence. We found that, while the fraction of B.1.1.7 varied by state, the variant increased at a logistic rate with a roughly weekly doubling rate and an increased transmission of 40%-50%. We revealed several independent introductions of B.1.1.7 into the US as early as late November 2020, with community transmission spreading it to most states within months. We show that the US is on a similar trajectory as other countries where B.1.1.7 became dominant, requiring immediate and decisive action to minimize COVID-19 morbidity and mortality.


Subject(s)
COVID-19 , Models, Biological , SARS-CoV-2 , COVID-19/genetics , COVID-19/mortality , COVID-19/transmission , Female , Humans , Male , SARS-CoV-2/genetics , SARS-CoV-2/metabolism , SARS-CoV-2/pathogenicity , United States/epidemiology
17.
mSystems ; 6(2)2021 Mar 02.
Article in English | MEDLINE | ID: covidwho-1115101

ABSTRACT

Large-scale wastewater surveillance has the ability to greatly augment the tracking of infection dynamics especially in communities where the prevalence rates far exceed the testing capacity. However, current methods for viral detection in wastewater are severely lacking in terms of scaling up for high throughput. In the present study, we employed an automated magnetic-bead-based concentration approach for viral detection in sewage that can effectively be scaled up for processing 24 samples in a single 40-min run. The method compared favorably to conventionally used methods for viral wastewater concentrations with higher recovery efficiencies from input sample volumes as low as 10 ml and can enable the processing of over 100 wastewater samples in a day. The sensitivity of the high-throughput protocol was shown to detect 1 asymptomatic individual in a building of 415 residents. Using the high-throughput pipeline, samples from the influent stream of the primary wastewater treatment plant of San Diego County (serving 2.3 million residents) were processed for a period of 13 weeks. Wastewater estimates of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral genome copies in raw untreated wastewater correlated strongly with clinically reported cases by the county, and when used alongside past reported case numbers and temporal information in an autoregressive integrated moving average (ARIMA) model enabled prediction of new reported cases up to 3 weeks in advance. Taken together, the results show that the high-throughput surveillance could greatly ameliorate comprehensive community prevalence assessments by providing robust, rapid estimates.IMPORTANCE Wastewater monitoring has a lot of potential for revealing coronavirus disease 2019 (COVID-19) outbreaks before they happen because the virus is found in the wastewater before people have clinical symptoms. However, application of wastewater-based surveillance has been limited by long processing times specifically at the concentration step. Here we introduce a much faster method of processing the samples and show its robustness by demonstrating direct comparisons with existing methods and showing that we can predict cases in San Diego by a week with excellent accuracy, and 3 weeks with fair accuracy, using city sewage. The automated viral concentration method will greatly alleviate the major bottleneck in wastewater processing by reducing the turnaround time during epidemics.

18.
Microbiome ; 9(1): 2, 2021 01 04.
Article in English | MEDLINE | ID: covidwho-1067276

ABSTRACT

The inaugural "Microbiome for Mars" virtual workshop took place on July 13, 2020. This event assembled leaders in microbiome research and development to discuss their work and how it may relate to long-duration human space travel. The conference focused on surveying current microbiome research, future endeavors, and how this growing field could broadly impact human health and space exploration. This report summarizes each speaker's presentation in the order presented at the workshop.


Subject(s)
Astronauts , Delivery of Health Care/trends , Mars , Microbiota/physiology , Space Flight , Animals , Gastrointestinal Microbiome/genetics , Gastrointestinal Microbiome/physiology , Humans , Microbiota/genetics
19.
Biotechniques ; 70(3): 149-159, 2021 03.
Article in English | MEDLINE | ID: covidwho-1054921

ABSTRACT

One goal of microbial ecology researchers is to capture the maximum amount of information from all organisms in a sample. The recent COVID-19 pandemic, caused by the RNA virus SARS-CoV-2, has highlighted a gap in traditional DNA-based protocols, including the high-throughput methods the authors previously established as field standards. To enable simultaneous SARS-CoV-2 and microbial community profiling, the authors compared the relative performance of two total nucleic acid extraction protocols with the authors' previously benchmarked protocol. The authors included a diverse panel of environmental and host-associated sample types, including body sites commonly swabbed for COVID-19 testing. Here the authors present results comparing the cost, processing time, DNA and RNA yield, microbial community composition, limit of detection and well-to-well contamination between these protocols.


Subject(s)
DNA, Viral/isolation & purification , High-Throughput Nucleotide Sequencing/methods , Microbiota/genetics , RNA, Ribosomal, 16S/isolation & purification , SARS-CoV-2/genetics , Animals , Biodiversity , Cats , Chemical Fractionation/methods , Feces/microbiology , Feces/virology , Female , Humans , Limit of Detection , Male , Metagenomics/methods , Mice , Saliva/microbiology , Saliva/virology , Skin/microbiology , Skin/virology
20.
Microbiome ; 9(1): 25, 2021 01 22.
Article in English | MEDLINE | ID: covidwho-1043251

ABSTRACT

BACKGROUND: Determining the role of fomites in the transmission of SARS-CoV-2 is essential in the hospital setting and will likely be important outside of medical facilities as governments around the world make plans to ease COVID-19 public health restrictions and attempt to safely reopen economies. Expanding COVID-19 testing to include environmental surfaces would ideally be performed with inexpensive swabs that could be transported safely without concern of being a source of new infections. However, CDC-approved clinical-grade sampling supplies and techniques using a synthetic swab are expensive, potentially expose laboratory workers to viable virus and prohibit analysis of the microbiome due to the presence of antibiotics in viral transport media (VTM). To this end, we performed a series of experiments comparing the diagnostic yield using five consumer-grade swabs (including plastic and wood shafts and various head materials including cotton, synthetic, and foam) and one clinical-grade swab for inhibition to RNA. For three of these swabs, we evaluated performance to detect SARS-CoV-2 in twenty intensive care unit (ICU) hospital rooms of patients including COVID-19+ patients. All swabs were placed in 95% ethanol and further evaluated in terms of RNase activity. SARS-CoV-2 was measured both directly from the swab and from the swab eluent. RESULTS: Compared to samples collected in VTM, 95% ethanol demonstrated significant inhibition properties against RNases. When extracting directly from the swab head as opposed to the eluent, RNA recovery was approximately 2-4× higher from all six swab types tested as compared to the clinical standard of testing the eluent from a CDC-approved synthetic (SYN) swab. The limit of detection (LoD) of SARS-CoV-2 from floor samples collected using the consumer-grade plastic (CGp) or research-grade plastic The Microsetta Initiative (TMI) swabs was similar or better than the SYN swab, further suggesting that swab type does not impact RNA recovery as measured by the abundance of SARS-CoV-2. The LoD for TMI was between 0 and 362.5 viral particles, while SYN and CGp were both between 725 and 1450 particles. Lastly microbiome analyses (16S rRNA gene sequencing) of paired samples (nasal and floor from same patient room) collected using different swab types in triplicate indicated that microbial communities were not impacted by swab type, but instead driven by the patient and sample type. CONCLUSIONS: Compared to using a clinical-grade synthetic swab, detection of SARS-CoV-2 from environmental samples collected from ICU rooms of patients with COVID was similar using consumer-grade swabs, stored in 95% ethanol. The yield was best from the swab head rather than the eluent and the low level of RNase activity and lack of antibiotics in these samples makes it possible to perform concomitant microbiome analyses. Video abstract.


Subject(s)
COVID-19 Nucleic Acid Testing/instrumentation , COVID-19 Nucleic Acid Testing/methods , Microbiota , RNA, Viral/analysis , SARS-CoV-2/isolation & purification , Specimen Handling/methods , Biological Transport , Ethanol/chemistry , Feasibility Studies , Humans , Intensive Care Units , Limit of Detection , RNA, Ribosomal, 16S/genetics , RNA, Viral/genetics , Ribonucleases/metabolism
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