Metagenomic analysis reveals differences in the co-occurrence and abundance of viral species in SARS-CoV-2 patients with different severity of disease.
COVID-19
Disease severity
Metagenomic sequencing
Respiratory viruses
SARS-CoV-2
Journal
BMC infectious diseases
ISSN: 1471-2334
Titre abrégé: BMC Infect Dis
Pays: England
ID NLM: 100968551
Informations de publication
Date de publication:
19 Oct 2022
19 Oct 2022
Historique:
received:
06
05
2022
accepted:
06
10
2022
entrez:
19
10
2022
pubmed:
20
10
2022
medline:
22
10
2022
Statut:
epublish
Résumé
SARS-CoV-2 infections have a wide spectrum of clinical manifestations whose causes are not completely understood. Some human conditions predispose to severe outcome, like old age or the presence of comorbidities, but many other facets, including coinfections with other viruses, remain poorly characterized. In this study, the eukaryotic fraction of the respiratory virome of 120 COVID-19 patients was characterized through whole metagenomic sequencing. Genetic material from respiratory viruses was detected in 25% of all samples, whereas human viruses other than SARS-CoV-2 were found in 80% of them. Samples from hospitalized and deceased patients presented a higher prevalence of different viruses when compared to ambulatory individuals. Small circular DNA viruses from the Anneloviridae (Torque teno midi virus 8, TTV-like mini virus 19 and 26) and Cycloviridae families (Human associated cyclovirus 10), Human betaherpesvirus 6, were found to be significantly more abundant in samples from deceased and hospitalized patients compared to samples from ambulatory individuals. Similarly, Rotavirus A, Measles morbillivirus and Alphapapilomavirus 10 were significantly more prevalent in deceased patients compared to hospitalized and ambulatory individuals. Results show the suitability of using metagenomics to characterize a broader peripheric virological landscape of the eukaryotic virome in SARS-CoV-2 infected patients with distinct disease outcomes. Identified prevalent viruses in hospitalized and deceased patients may prove important for the targeted exploration of coinfections that may impact prognosis.
Sections du résumé
BACKGROUND
BACKGROUND
SARS-CoV-2 infections have a wide spectrum of clinical manifestations whose causes are not completely understood. Some human conditions predispose to severe outcome, like old age or the presence of comorbidities, but many other facets, including coinfections with other viruses, remain poorly characterized.
METHODS
METHODS
In this study, the eukaryotic fraction of the respiratory virome of 120 COVID-19 patients was characterized through whole metagenomic sequencing.
RESULTS
RESULTS
Genetic material from respiratory viruses was detected in 25% of all samples, whereas human viruses other than SARS-CoV-2 were found in 80% of them. Samples from hospitalized and deceased patients presented a higher prevalence of different viruses when compared to ambulatory individuals. Small circular DNA viruses from the Anneloviridae (Torque teno midi virus 8, TTV-like mini virus 19 and 26) and Cycloviridae families (Human associated cyclovirus 10), Human betaherpesvirus 6, were found to be significantly more abundant in samples from deceased and hospitalized patients compared to samples from ambulatory individuals. Similarly, Rotavirus A, Measles morbillivirus and Alphapapilomavirus 10 were significantly more prevalent in deceased patients compared to hospitalized and ambulatory individuals.
CONCLUSIONS
CONCLUSIONS
Results show the suitability of using metagenomics to characterize a broader peripheric virological landscape of the eukaryotic virome in SARS-CoV-2 infected patients with distinct disease outcomes. Identified prevalent viruses in hospitalized and deceased patients may prove important for the targeted exploration of coinfections that may impact prognosis.
Identifiants
pubmed: 36261802
doi: 10.1186/s12879-022-07783-8
pii: 10.1186/s12879-022-07783-8
pmc: PMC9580447
doi:
Substances chimiques
DNA, Circular
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
792Informations de copyright
© 2022. The Author(s).
Références
Bioinformatics. 2012 Dec 1;28(23):3150-2
pubmed: 23060610
Cell Host Microbe. 2021 Mar 10;29(3):463-476.e6
pubmed: 33592168
Sci China Life Sci. 2020 Apr;63(4):606-609
pubmed: 32170625
Nucleic Acids Res. 2013 Jan;41(Database issue):D590-6
pubmed: 23193283
Clin Chem. 2020 Jul 1;66(7):966-972
pubmed: 32379863
Obesity (Silver Spring). 2020 Jul;28(7):1195-1199
pubmed: 32271993
J Virol. 2022 Mar 9;96(5):e0179121
pubmed: 34936487
Virus Res. 2020 Aug;285:198005
pubmed: 32408156
Clin Obes. 2020 Dec;10(6):e12403
pubmed: 32857454
AIDS. 2001 Mar 30;15(5):563-70
pubmed: 11316992
Int J Infect Dis. 2017 Sep;62:32-38
pubmed: 28673837
Microbiol Spectr. 2021 Oct 31;9(2):e0083121
pubmed: 34668725
J Clin Virol Plus. 2021 Sep;1(3):100036
pubmed: 35262019
mBio. 2020 Nov 20;11(6):
pubmed: 33219095
Genome Biol. 2009;10(3):R25
pubmed: 19261174
Sci Rep. 2021 Feb 16;11(1):3934
pubmed: 33594223
Nucleic Acids Res. 2012 May;40(10):4288-97
pubmed: 22287627
J Virol. 2022 Mar 23;96(6):e0187321
pubmed: 35107382
Infect Control Hosp Epidemiol. 2020 Oct;41(10):1228-1229
pubmed: 32616098
Nutr Rev. 2017 Jan;75(suppl 1):4-12
pubmed: 28049745
Appl Environ Microbiol. 2018 May 17;84(11):
pubmed: 29625974
J Clin Microbiol. 2020 Dec 17;59(1):
pubmed: 33067271
JAMA. 2020 May 26;323(20):2052-2059
pubmed: 32320003
Clin Microbiol Infect. 2016 Jul;22(7):589-93
pubmed: 27093875
J Allergy Clin Immunol. 2020 Jul;146(1):110-118
pubmed: 32294485
J Med Virol. 2022 May;94(5):1920-1925
pubmed: 34951498
J Virol. 2020 Aug 31;94(18):
pubmed: 32641486
Cell. 2020 Aug 20;182(4):812-827.e19
pubmed: 32697968
JAMA. 2004 Jun 2;291(21):2544-5
pubmed: 15173143
Curr Opin Virol. 2020 Apr;41:31-37
pubmed: 32339942
Bioinformatics. 2018 Sep 1;34(17):i884-i890
pubmed: 30423086
EClinicalMedicine. 2020 Oct;27:100518
pubmed: 32864588
Int J Infect Dis. 2021 Jan;102:79-84
pubmed: 33017694
J Med Virol. 2021 Jul;93(7):4392-4398
pubmed: 33829531
Biomed Res Int. 2018 Nov 19;2018:6362716
pubmed: 30581863
JAMA. 2020 May 26;323(20):2085-2086
pubmed: 32293646
Bioinformatics. 2012 Jun 1;28(11):1420-8
pubmed: 22495754
Microbiol Spectr. 2022 Feb 23;10(1):e0124921
pubmed: 35019701
Emerg Infect Dis. 2022 Jan;28(1):9-19
pubmed: 34932449
Front Genet. 2021 Apr 20;12:627128
pubmed: 33959147
J Comput Biol. 2012 May;19(5):455-77
pubmed: 22506599
BMC Res Notes. 2015 Jun 25;8:261
pubmed: 26108920
Hum Genomics. 2020 Oct 22;14(1):40
pubmed: 33092637
PLoS One. 2018 Aug 2;13(8):e0201156
pubmed: 30071000
Lancet. 2022 Apr 16;399(10334):1463-1464
pubmed: 35344735
J Med Virol. 2007 Jan;79(1):1-7
pubmed: 17133553
J Med Virol. 2021 Feb;93(2):1008-1012
pubmed: 32720703
J Med Virol. 2020 Oct;92(10):1699-1700
pubmed: 32352574
Sci Rep. 2021 Oct 29;11(1):21297
pubmed: 34716394
Genome Res. 2007 Mar;17(3):377-86
pubmed: 17255551
J Med Virol. 2022 May;94(5):2275-2283
pubmed: 34989406
Infect Drug Resist. 2020 Aug 26;13:3045-3053
pubmed: 32922049
Genome Biol. 2019 Jan 8;20(1):8
pubmed: 30621750
BMC Bioinformatics. 2009 Dec 15;10:421
pubmed: 20003500
J Infect. 2021 Jan;82(1):e44-e48
pubmed: 33307139