Author(s):
Nobre, José Guilherme ; Delgadinho, Mariana ; Silva, Carina ; Mendes, Joana ; Mateus, Vanessa ; Ribeiro, Edna ; Costa, Diogo Alpuim ; Lopes, Miguel ; Pedroso, Ana Isabel ; Trigueiros, Frederico ; Rodrigues, Maria Inês ; de Sousa, Cristina Lino ; Brito, Miguel
Date: 2022
Persistent ID: http://hdl.handle.net/10362/146185
Origin: Repositório Institucional da UNL
Subject(s): COVID-19; dysbiosis; microbiome; microbiota; next generation sequencing; prognosis; risk stratification; Microbiology; Microbiology (medical); SDG 3 - Good Health and Well-being
Description
Funding Information: The authors acknowledge financial support from Instituto Politécnico de Lisboa that supported this project with the grant Microcovid. This project was also partially supported by FCT/MCTES (UIDB/05608/2020 and UIDP/05608/2020). Publisher Copyright: Copyright © 2022 Nobre, Delgadinho, Silva, Mendes, Mateus, Ribeiro, Costa, Lopes, Pedroso, Trigueiros, Rodrigues, de Sousa and Brito.
Background: Gut microbiota is intrinsically associated with the immune system and can promote or suppress infectious diseases, especially viral infections. This study aims to characterize and compare the microbiota profile of infected patients with SARS-CoV-2 (milder or severe symptoms), non-infected people, and recovered patients. This is a national, transversal, observational, multicenter, and case–control study that analyzed the microbiota of COVID-19 patients with mild or severe symptoms at home, at the hospital, or in the intensive care unit, patients already recovered, and healthy volunteers cohabiting with COVID-19 patients. DNA was isolated from stool samples and sequenced in a NGS platform. A demographic questionnaire was also applied. Statistical analysis was performed in SPSS. Results: Firmicutes/Bacteroidetes ratios were found to be significantly lower in infected patients (1.61 and 2.57) compared to healthy volunteers (3.23) and recovered patients (3.89). Furthermore, the microbiota composition differed significantly between healthy volunteers, mild and severe COVID-19 patients, and recovered patients. Furthermore, Escherichia coli, Actinomyces naeslundii, and Dorea longicatena were shown to be more frequent in severe cases. The most common COVID-19 symptoms were linked to certain microbiome groups. Conclusion: We can conclude that microbiota composition is significantly affected by SARS-CoV-2 infection and may be used to predict COVID-19 clinical evolution. Therefore, it will be possible to better allocate healthcare resources and better tackle future pandemics.
