Proteomic snapshot of saliva samples predicts new pathways implicated in SARS-CoV-2 pathogenesis.

Functional analysis Pathogenesis Proteomics SARS-CoV-2 Saliva

Journal

Clinical proteomics
ISSN: 1542-6416
Titre abrégé: Clin Proteomics
Pays: England
ID NLM: 101184586

Informations de publication

Date de publication:
22 May 2024
Historique:
received: 13 10 2023
accepted: 15 04 2024
medline: 23 5 2024
pubmed: 23 5 2024
entrez: 22 5 2024
Statut: epublish

Résumé

Information on the microbiome's human pathways and active members that can affect SARS-CoV-2 susceptibility and pathogenesis in the salivary proteome is very scarce. Here, we studied a unique collection of samples harvested from April to June 2020 from unvaccinated patients. We compared 10 infected and hospitalized patients with severe (n = 5) and moderate (n = 5) coronavirus disease (COVID-19) with 10 uninfected individuals, including non-COVID-19 but susceptible individuals (n = 5) and non-COVID-19 and nonsusceptible healthcare workers with repeated high-risk exposures (n = 5). By performing high-throughput proteomic profiling in saliva samples, we detected 226 unique differentially expressed (DE) human proteins between groups (q-value ≤ 0.05) out of 3376 unambiguously identified proteins (false discovery rate ≤ 1%). Major differences were observed between the non-COVID-19 and nonsusceptible groups. Bioinformatics analysis of DE proteins revealed human proteomic signatures related to inflammatory responses, central cellular processes, and antiviral activity associated with the saliva of SARS-CoV-2-infected patients (p-value ≤ 0.0004). Discriminatory biomarker signatures from human saliva include cystatins, protective molecules present in the oral cavity, calprotectins, involved in cell cycle progression, and histones, related to nucleosome functions. The expression levels of two human proteins related to protein transport in the cytoplasm, DYNC1 (p-value, 0.0021) and MAPRE1 (p-value, 0.047), correlated with angiotensin-converting enzyme 2 (ACE2) plasma activity. Finally, the proteomes of microorganisms present in the saliva samples showed 4 main microbial functional features related to ribosome functioning that were overrepresented in the infected group. Our study explores potential candidates involved in pathways implicated in SARS-CoV-2 susceptibility, although further studies in larger cohorts will be necessary.

Sections du résumé

BACKGROUND BACKGROUND
Information on the microbiome's human pathways and active members that can affect SARS-CoV-2 susceptibility and pathogenesis in the salivary proteome is very scarce. Here, we studied a unique collection of samples harvested from April to June 2020 from unvaccinated patients.
METHODS METHODS
We compared 10 infected and hospitalized patients with severe (n = 5) and moderate (n = 5) coronavirus disease (COVID-19) with 10 uninfected individuals, including non-COVID-19 but susceptible individuals (n = 5) and non-COVID-19 and nonsusceptible healthcare workers with repeated high-risk exposures (n = 5).
RESULTS RESULTS
By performing high-throughput proteomic profiling in saliva samples, we detected 226 unique differentially expressed (DE) human proteins between groups (q-value ≤ 0.05) out of 3376 unambiguously identified proteins (false discovery rate ≤ 1%). Major differences were observed between the non-COVID-19 and nonsusceptible groups. Bioinformatics analysis of DE proteins revealed human proteomic signatures related to inflammatory responses, central cellular processes, and antiviral activity associated with the saliva of SARS-CoV-2-infected patients (p-value ≤ 0.0004). Discriminatory biomarker signatures from human saliva include cystatins, protective molecules present in the oral cavity, calprotectins, involved in cell cycle progression, and histones, related to nucleosome functions. The expression levels of two human proteins related to protein transport in the cytoplasm, DYNC1 (p-value, 0.0021) and MAPRE1 (p-value, 0.047), correlated with angiotensin-converting enzyme 2 (ACE2) plasma activity. Finally, the proteomes of microorganisms present in the saliva samples showed 4 main microbial functional features related to ribosome functioning that were overrepresented in the infected group.
CONCLUSION CONCLUSIONS
Our study explores potential candidates involved in pathways implicated in SARS-CoV-2 susceptibility, although further studies in larger cohorts will be necessary.

Identifiants

pubmed: 38778280
doi: 10.1186/s12014-024-09482-9
pii: 10.1186/s12014-024-09482-9
doi:

Types de publication

Journal Article

Langues

eng

Pagination

37

Subventions

Organisme : Consejo Superior de Investigaciones Científicas
ID : PIE 202020E108 and SEV 2017-0712
Organisme : Ministerio de Ciencia e Innovación, Agencia Estatal de Investigación (AEI)
ID : PID2020-112758RB-I00 and PDC2021-121534-I00
Organisme : Instituto de Salud Carlos III
ID : AC17/00019, PI18/00154, COV20/00349, ICI20/00058, PI21/00141
Organisme : Merck Sharp and Dohme
ID : MISP# IIS 60257
Organisme : Spanish Society of Infectious Diseases and Clinical Microbiology (SEIMC)
ID : Mobility grant
Organisme : Fundación Agencia Española contra el Cáncer
ID : AC17/00022

Informations de copyright

© 2024. The Author(s).

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Auteurs

Elena Moreno (E)

Department of Infectious Diseases, Facultad de Medicina, Hospital Universitario Ramón y Cajal, IRYCIS, Carretera de Colmenar Viejo, Km 9.100, 28034, Madrid, Spain. emolmo@salud.madrid.org.
CIBERINFEC, Instituto de Salud Carlos III, 28029, Madrid, Spain. emolmo@salud.madrid.org.

Sergio Ciordia (S)

Functional Proteomics Laboratory, Centro Nacional de Biotecnología (CNB), CSIC, 28049, Madrid, Spain.

Santos Milhano Fátima (SM)

Functional Proteomics Laboratory, Centro Nacional de Biotecnología (CNB), CSIC, 28049, Madrid, Spain.

Daniel Jiménez (D)

Department of Infectious Diseases, Facultad de Medicina, Hospital Universitario Ramón y Cajal, IRYCIS, Carretera de Colmenar Viejo, Km 9.100, 28034, Madrid, Spain.

Javier Martínez-Sanz (J)

Department of Infectious Diseases, Facultad de Medicina, Hospital Universitario Ramón y Cajal, IRYCIS, Carretera de Colmenar Viejo, Km 9.100, 28034, Madrid, Spain.
CIBERINFEC, Instituto de Salud Carlos III, 28029, Madrid, Spain.

Pilar Vizcarra (P)

Department of Infectious Diseases, Facultad de Medicina, Hospital Universitario Ramón y Cajal, IRYCIS, Carretera de Colmenar Viejo, Km 9.100, 28034, Madrid, Spain.
CIBERINFEC, Instituto de Salud Carlos III, 28029, Madrid, Spain.

Raquel Ron (R)

Department of Infectious Diseases, Facultad de Medicina, Hospital Universitario Ramón y Cajal, IRYCIS, Carretera de Colmenar Viejo, Km 9.100, 28034, Madrid, Spain.
CIBERINFEC, Instituto de Salud Carlos III, 28029, Madrid, Spain.

Matilde Sánchez-Conde (M)

Department of Infectious Diseases, Facultad de Medicina, Hospital Universitario Ramón y Cajal, IRYCIS, Carretera de Colmenar Viejo, Km 9.100, 28034, Madrid, Spain.
CIBERINFEC, Instituto de Salud Carlos III, 28029, Madrid, Spain.

Rafael Bargiela (R)

Centre for Environmental Biotechnology, School of Natural Sciences, Bangor University, Bangor, LL57 2UW, UK.

Sergio Sanchez-Carrillo (S)

Instituto de Catalisis y Petroleoquimica (ICP), CSIC, 28049, Madrid, Spain.
Centro de Biologia Molecular Severo Ochoa (CBM), CSIC-UAM, 28049, Madrid, Spain.

Santiago Moreno (S)

Department of Infectious Diseases, Facultad de Medicina, Hospital Universitario Ramón y Cajal, IRYCIS, Carretera de Colmenar Viejo, Km 9.100, 28034, Madrid, Spain.
CIBERINFEC, Instituto de Salud Carlos III, 28029, Madrid, Spain.
Facultad de Medicina, Universidad de Alcalá de Henares, 28801, Alcalá de Henares, Madrid, Spain.

Fernando Corrales (F)

Functional Proteomics Laboratory, Centro Nacional de Biotecnología (CNB), CSIC, 28049, Madrid, Spain.

Manuel Ferrer (M)

Instituto de Catalisis y Petroleoquimica (ICP), CSIC, 28049, Madrid, Spain.

Sergio Serrano-Villar (S)

Department of Infectious Diseases, Facultad de Medicina, Hospital Universitario Ramón y Cajal, IRYCIS, Carretera de Colmenar Viejo, Km 9.100, 28034, Madrid, Spain.
CIBERINFEC, Instituto de Salud Carlos III, 28029, Madrid, Spain.

Classifications MeSH