Metagenomic Next-Generation Sequencing of Nasopharyngeal Specimens Collected from Confirmed and Suspect COVID-19 Patients

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Reviewed Marked as Reviewed by Atrayees on 2023-7-26
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI
Authors
Mostafa HH, Fissel JA, Fanelli B, Bergman Y, Gniazdowski V, Dadlani M, Carroll KC, Colwell RR, Simner PJ
Journal
mBio
Year
2020
Keywords:
COVID-19, SARS-CoV-2, metagenomic next-generation sequencing, metagenomics, nasopharyngeal
Metagenomic next-generation sequencing (mNGS) offers an agnostic approach for emerging pathogen detection directly from clinical specimens. In contrast to targeted methods, mNGS also provides valuable information on the composition of the microbiome and might uncover coinfections that may associate with disease progression and impact prognosis. To evaluate the use of mNGS for detecting severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and/or other infecting pathogens, we applied direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing. Nasopharyngeal (NP) swab specimens from 50 patients under investigation for CoV disease 2019 (COVID-19) were sequenced, and the data were analyzed by the CosmosID bioinformatics platform. Further, we characterized coinfections and the microbiome associated with a four-point severity index. SARS-CoV-2 was identified in 77.5% (31/40) of samples positive by RT-PCR, correlating with lower cycle threshold (Ct) values and fewer days from symptom onset. At the time of sampling, possible bacterial or viral coinfections were detected in 12.5% of SARS-CoV-2-positive specimens. A decrease in microbial diversity was observed among COVID-19-confirmed patients (Shannon diversity index, P = 0.0082; Chao richness estimate, P = 0.0097; Simpson diversity index, P = 0.018), and differences in microbial communities were linked to disease severity (P = 0.022). Furthermore, statistically significant shifts in the microbiome were identified among SARS-CoV-2-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae (P = 0.028) and a reduction in the abundance of Corynebacterium accolens (P = 0.025) were observed. Our study corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages rather than the severity of COVID-19. Further, we demonstrate that SARS-CoV-2 causes a significant change in the respiratory microbiome. This work illustrates the utility of mNGS for the detection of SARS-CoV-2, for diagnosing coinfections without viral target enrichment or amplification, and for the analysis of the respiratory microbiome.IMPORTANCE SARS-CoV-2 has presented a rapidly accelerating global public health crisis. The ability to detect and analyze viral RNA from minimally invasive patient specimens is critical to the public health response. Metagenomic next-generation sequencing (mNGS) offers an opportunity to detect SARS-CoV-2 from nasopharyngeal (NP) swabs. This approach also provides information on the composition of the respiratory microbiome and its relationship to coinfections or the presence of other organisms that may impact SARS-CoV-2 disease progression and prognosis. Here, using direct Oxford Nanopore long-read third-generation metatranscriptomic and metagenomic sequencing of NP swab specimens from 50 patients under investigation for COVID-19, we detected SARS-CoV-2 sequences by applying the CosmosID bioinformatics platform. Further, we characterized coinfections and detected a decrease in the diversity of the microbiomes in these patients. Statistically significant shifts in the microbiome were identified among COVID-19-positive and -negative patients, in the latter of whom a higher abundance of Propionibacteriaceae and a reduction in the abundance of Corynebacterium accolens were observed. Our study also corroborates the growing evidence that increased SARS-CoV-2 RNA detection from NP swabs is associated with the early stages of disease rather than with severity of disease. This work illustrates the utility of mNGS for the detection and analysis of SARS-CoV-2 from NP swabs without viral target enrichment or amplification and for the analysis of the respiratory microbiome.

Experiment 1


Reviewed Marked as Reviewed by Atrayees on 2023-7-26

Curated date: 2021/06/05

Curator: Claregrieve1

Revision editor(s): Claregrieve1, WikiWorks, Atrayees

Subjects

Location of subjects
United States of America
Host species Species from which microbiome was sampled. Contact us to have more species added.
Homo sapiens
Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
Nasopharynx Nasenrachenraum,Epipharynx,Nasal part of pharynx,Pars nasalis pharyngis,Rhinopharynx,Nasopharynx,nasopharynx
Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
COVID-19 2019 novel coronavirus,2019 novel coronavirus infection,2019-nCoV,2019-nCoV infection,beta-CoV,beta-CoVs,betacoronavirus,coronavirus disease 2019,SARS-coronavirus 2,SARS-CoV-2,severe acute respiratory syndrome coronavirus 2,severe acute respiratory syndrome coronavirus 2 infectious disease,β-coronavirus,β-CoV,β-CoVs,COVID-19,cOVID-19
Group 0 name Corresponds to the control (unexposed) group for case-control studies
COVID-19 negative controls
Group 1 name Corresponds to the case (exposed) group for case-control studies
COVID-19 cases
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
Positive for SaRS-CoV-2 by diagnostic RT-PCR
Group 0 sample size Number of subjects in the control (unexposed) group
10
Group 1 sample size Number of subjects in the case (exposed) group
40

Lab analysis

Sequencing type
WMS
16S variable region One or more hypervariable region(s) of the bacterial 16S gene
Not specified
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Nanopore

Statistical Analysis

Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
relative abundances
Statistical test
Mann-Whitney (Wilcoxon)
Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
0.05
MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
No

Alpha Diversity

Shannon Estimator of species richness and species evenness: more weight on species richness
decreased
Chao1 Abundance-based estimator of species richness
decreased
Simpson Estimator of species richness and species evenness: more weight on species evenness
decreased

Signature 1

Reviewed Marked as Reviewed by Atrayees on 2023-7-26

Curated date: 2021/06/05

Curator: Claregrieve1

Revision editor(s): Claregrieve1, Aiyshaaaa, Atrayees

Source: Figure 3

Description: Relative abundance of bacteria at species level in COVID-19-positive and COVID-19-negative samples

Abundance in Group 1: decreased abundance in COVID-19 cases

NCBI Quality ControlLinks
Corynebacterium accolens

Revision editor(s): Claregrieve1, Aiyshaaaa, Atrayees

Signature 2

Reviewed Marked as Reviewed by Atrayees on 2023-7-26

Curated date: 2021/06/05

Curator: Claregrieve1

Revision editor(s): Claregrieve1, Aiyshaaaa, Atrayees

Source: Figure 3

Description: Relative abundance of bacteria at species level in COVID-19-positive and COVID-19-negative samples

Abundance in Group 1: increased abundance in COVID-19 cases

NCBI Quality ControlLinks
Propionibacteriaceae

Revision editor(s): Claregrieve1, Aiyshaaaa, Atrayees