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Multicenter Study
. 2024 Jan 11;19(1):e0290062.
doi: 10.1371/journal.pone.0290062. eCollection 2024.

The salivary microbiota of patients with acute lower respiratory tract infection-A multicenter cohort study

Affiliations
Multicenter Study

The salivary microbiota of patients with acute lower respiratory tract infection-A multicenter cohort study

Matthew B Rogers et al. PLoS One. .

Erratum in

Abstract

The human microbiome contributes to health and disease, but the oral microbiota is understudied relative to the gut microbiota. The salivary microbiota is easily accessible, underexplored, and may provide insight into response to infections. We sought to determine the composition, association with clinical features, and heterogeneity of the salivary microbiota in patients with acute lower respiratory tract infection (LRTI). We conducted a multicenter prospective cohort study of 147 adults with acute LRTI presenting to the emergency department of seven hospitals in three states (Pennsylvania, Michigan, and Ohio) between May 2017 and November 2018. Salivary samples were collected in the emergency department, at days 2-5 if hospitalized, and at day 30, as well as fecal samples if patients were willing. We compared salivary microbiota profiles from patients to those of healthy adult volunteers by sequencing and analyzing bacterial 16-rRNA. Compared to healthy volunteers, the salivary microbiota of patients with LRTI was highly distinct and strongly enriched with intestinal anaerobes such as Bacteroidaceae, Ruminococcaceae, and Lachnospiraceae (e.g., mean 10% relative abundance of Bacteroides vs < 1% in healthy volunteers). Within the LRTI population, COPD exacerbation was associated with altered salivary microbiota composition compared to other LRTI conditions. The largest determinant of microbiota variation within the LRTI population was geography (city in which the hospital was located).

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Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1
Fig 1. Alpha diversity and beta diversity plots.
(A) Scatterplot of Alpha diversity values (Shannon metric) across groups. Mean values for each group are shown as a central red dot with non-parametric confidence limits indicated by red lines. (B) PCoA plot of weighted unifrac beta diversity distances between LRTI saliva samples, LRTI fecal samples and healthy saliva samples. Large circles indicate centroid of each group.
Fig 2
Fig 2. Taxonomic composition of saliva samples by cohort and body site.
A) Common bacterial families by relative abundance shared between saliva samples from the healthy cohort and the LRTI cohort. B) Differentially abundant families predicted by ANCOM that are enriched in the LRTI group versus the healthy group. C) Equivalent to (B) but with families that are enriched in the healthy group. Taxa with red labels are predicted to be enriched in the LRTI group by LOCOM, while those with blue font are predicted to be depleted by LOCOM.
Fig 3
Fig 3. PCoA plots of baseline saliva samples by clinical variables.
PcoA plot of samples from subjects experiencing a COPD exacerbation, red points indicate a positive diagnosis of COPD exacerbation. COPD exacerbation was the only clinical finding that was predicted to be significantly different by ADONIS multivariable analysis (p-value < 0.01).
Fig 4
Fig 4. Variations in taxonomic composition by clinical variable.
Differences in taxonomic family composition between patients that experienced an outcome of COPD exacerbation and those that did not. City of hospital site was used as a co-variate to correct for taxonomic families that varied between hospital sites. Differentially abundant families are represented as boxplot graphs, coloured by taxon, shown in the shared legend. The COPD exacerbation diagnosis is displayed on the x-axis, and relative abundances are plotted along the y-axis.
Fig 5
Fig 5. PCoA plot of Weighted Unifrac distances between all saliva samples.
Samples are coloured by city, each point indicates an individual sample, large points indicate the position the centroid of each hospital site group.

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