Evidence map›Paper›PMID 37310423›Full record

ArticlemSystems2023

Diversity, composition, and networking of saliva microbiota distinguish the severity of COVID-19 episodes as revealed by an analysis of 16S rRNA variable V1-V3 region sequences.

Violeta Larios Serrato, Beatriz Meza, Carolina Gonzalez-Torres, Javier Gaytan-Cervantes, Joaquín González Ibarra, Clara Esperanza Santacruz Tinoco, Yu-Mei Anguiano Hernández, Bernardo Martínez Miguel, Allison Cázarez Cortazar, Brenda Sarquiz Martínez and 9 more

Open access · goldAbstract read
In one paragraph

Article in mSystems, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 7 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

19 authors at 5 institutions in 1 country.

Violeta Larios SerratoDepartamento de Bioquímica, Escuela Nacional de Ciencias Biológicas, Instituto Politécnico Nacional , México, Mexico.
Beatriz MezaUniversidad Autónoma de Baja California Sur , La Paz, Baja California Sur, Mexico.
Carolina Gonzalez-TorresLaboratorio de Secuenciación, División de Desarrollo de la Investigación, IMSS , Torreón, Mexico.
Javier Gaytan-CervantesLaboratorio de Secuenciación, División de Desarrollo de la Investigación, IMSS , Torreón, Mexico.
Joaquín González IbarraDivisión de Desarrollo de la Investigación en Salud, Coordinación de Investigación en Salud, IMSS , Torreón, Mexico.
Clara Esperanza Santacruz TinocoDivisión de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS , Torreón, Mexico.
Yu-Mei Anguiano HernándezDivisión de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS , Torreón, Mexico.
Bernardo Martínez MiguelDivisión de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS , Torreón, Mexico.
Allison Cázarez CortazarDivisión de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS , Torreón, Mexico.
Brenda Sarquiz MartínezDivisión de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS , Torreón, Mexico.
Julio Elias Alvarado YaahDivisión de Laboratorios Especializados, Coordinación de Calidad de Insumos y Laboratorios Especializados, IMSS , Torreón, Mexico.
Antonina Reyna Mendoza PérezCoordinación de Vigilancia Epidemiológica, Dirección de Prestaciones Médicas, IMSS , Torreón, Mexico.
Juan José Palma HerreraHospital General de Zona No. 27, Ciudad de México Norte, IMSS , México, Mexico.
Leticia Margarita García SotoHospital General de Zona No. 27, Ciudad de México Norte, IMSS , México, Mexico.
Adriana Inés Chávez RojasCoordinadora de Información y Análisis Estratégicos, OOAD Cd de México , México, Mexico.
Guillermo Bravo MateosHospital General de Zona con Medicina Familiar No. 8 Cd de México, IMSS , México, Mexico.
Gabriel Samano MarquezHospital General de Zona con Medicina Familiar No. 8 Cd de México, IMSS , México, Mexico.
Concepción Grajales MuñizDepartamento de Vigilancia Epidemiológica, IMSS Bienestar , México, Mexico.
Javier TorresUnidad de Investigación Médica en Enfermedades Infecciosas, UMAE Pediatría, Centro Médico Nacional SXXI, IMSS , Torreón, Mexico.ORCID 0000-0003-3945-4221
Hospital General De Zona · MXInformation Group on Reproductive Choice · MXInstituto Politécnico Nacional · MXMexican Social Security Institute · MXUniversidad Autónoma de Baja California Sur · MX

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Studies on the role of the oral microbiome in SARS-CoV-2 infection and severity of the disease are limited. We aimed to characterize the bacterial communities present in the saliva of patients with varied COVID-19 severity to learn if there are differences in the characteristics of the microbiome among the clinical groups. We included 31 asymptomatic subjects with no previous COVID-19 infection or vaccination; 176 patients with mild respiratory symptoms, positive or negative for SARS-CoV-2 infection; 57 patients that required hospitalization because of severe COVID-19 with oxygen saturation below 92%, and 18 fatal cases of COVID-19. Saliva samples collected before any treatment were tested for SARS-CoV-2 by PCR. Oral microbiota in saliva was studied by amplification and sequencing of the V1-V3 variable regions of 16S gene using an Illumina MiSeq platform. We found significant changes in diversity, composition, and networking in saliva microbiota of patients with COVID-19, as well as patterns associated with severity of disease. The presence or abundance of several commensal species and opportunistic pathogens were associated with each clinical stage. Patterns of networking were also found associated with severity of disease: a highly regulated bacterial community (normonetting) was found in healthy people whereas poorly regulated populations (disnetting) were characteristic of severe cases. Characterization of microbiota in saliva may offer important clues in the pathogenesis of COVID-19 and may also identify potential markers for prognosis in the severity of the disease. IMPORTANCE SARS-CoV-2 infection is the most severe pandemic of humankind in the last hundred years. The outcome of the infection ranges from asymptomatic or mild to severe and even fatal cases, but reasons for this remain unknown. Microbes normally colonizing the respiratory tract form communities that may mitigate the transmission, symptoms, and severity of viral infections, but very little is known on the role of these microbial communities in the severity of COVID-19. We aimed to characterize the bacterial communities in saliva of patients with different severity of COVID-19 disease, from mild to fatal cases. Our results revealed clear differences in the composition and in the nature of interactions (networking) of the bacterial species present in the different clinical groups and show community-patterns associated with disease severity. Characterization of the microbial communities in saliva may offer important clues to learn ways COVID-19 patients may suffer from different disease severities.

Indexed as

COVID-19MicrobiotaBacteriaHumansRNA, Ribosomal, 16SSalivaSARS-CoV-2RNA, Ribosomal, 16SCOVID-19disease severitymicrobial networksmicrobiotaviral infections

Identifiers

PMID37310423
PMCPMC10470033
OpenAlexW4380421989

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.