Profiling of Oral Microbiota and Cytokines in COVID-19 Patients

Valerio Iebba, Nunzia Zanotta, Giuseppina Campisciano, Verena Zerbato, Stefano Di Bella, Carolina Cason, Roberto Luzzati, Marco Confalonieri, Anna Teresa Palamara, Manola Comar

Research output: Contribution to journalArticlepeer-review

Abstract

The presence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been recently demonstrated in the sputum or saliva, suggesting how the shedding of viral RNA outlasts the end of symptoms. Recent data from transcriptome analysis show that the oral cavity mucosa harbors high levels of angiotensin-converting enzyme 2 (ACE2) and transmembrane protease, serine 2 (TMPRSS2), highlighting its role as a double-edged sword for SARS-CoV-2 body entrance or interpersonal transmission. Here, we studied the oral microbiota structure and inflammatory profile of 26 naive severe coronavirus disease 2019 (COVID-19) patients and 15 controls by 16S rRNA V2 automated targeted sequencing and magnetic bead-based multiplex immunoassays, respectively. A significant diminution in species richness was observed in COVID-19 patients, along with a marked difference in beta-diversity. Species such as Prevotella salivae and Veillonella infantium were distinctive for COVID-19 patients, while Neisseria perflava and Rothia mucilaginosa were predominant in controls. Interestingly, these two groups of oral species oppositely clustered within the bacterial network, defining two distinct Species Interacting Groups (SIGs). COVID-19-related pro-inflammatory cytokines were found in both oral and serum samples, along with a specific bacterial consortium able to counteract them. We introduced a new parameter, named CytoCOV, able to predict COVID-19 susceptibility for an unknown subject at 71% of power with an Area Under Curve (AUC) equal to 0.995. This pilot study evidenced a distinctive oral microbiota composition in COVID-19 subjects, with a definite structural network in relation to secreted cytokines. Our results would be usable in clinics against COVID-19, using bacterial consortia as biomarkers or to reduce local inflammation.

Original languageEnglish
Article number671813
JournalFrontiers in Microbiology
Volume12
DOIs
Publication statusPublished - Jul 30 2021
Externally publishedYes

Keywords

  • COVID-19
  • cytokines
  • machine learning
  • metagenomics
  • microbiota (D064307)
  • network analysis
  • oral microbiota

ASJC Scopus subject areas

  • Microbiology
  • Microbiology (medical)

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