Dysbiosis in the oral bacterial and fungal microbiome of HIV-infected subjects is associated with clinical and immunologic variables of HIV infection

Abstract

Background: The effect of smoking on microbial dysbiosis and the potential consequence of such shift on markers of HIV disease is unknown. Here we assessed the relationship of microbial dysbiosis with smoking and markers of HIV disease.

Methods: Oral wash was collected from: (1) HIV-infected smokers (HIV-SM, n = 48), (2) HIV-infected non-smokers (HIV-NS, n = 24), or (3) HIV-uninfected smokers (UI-SM, n = 24). Microbial DNA was extracted and their bacterial and fungal microbiota (bacteriome and mycobiome, respectively) were characterized using Ion-Torrent sequencing platform. Sequencing data were compared using clustering, diversity, abundance and inter-kingdom correlations analyses.

Results: Bacteriome was more widely dispersed than mycobiome, there was no noticeable difference in clustering between groups. Richness of oral bacteriome in HIV-SM was significantly lower than that of UI-SM (P ≤ .03). Diversity of HIV-NS was significantly lower than that of HIV-SM or UI-SM at phylum level (P ≤ .02). Abundance of Phylum Firmicutes was significantly decreased in HIV-NS compared to HIV-SM and UI-SM (P = .007 and .027, respectively), while abundance of Proteobacteria was significantly increased in HIV-NS compared to HIV-SM and UI-SM (P = .0005 and .011, respectively). Fungal phyla did not differ significantly between the three cohorts. Cumulative smoking was positively correlated with Facklamia but negatively with Enhydrobacter, and current alcohol use was negatively correlated with Geniculata. Bacteria Facklamia exhibited weakly positive correlation with longer PI duration (r = 0.094, P = 0.012), and a negative correlation with nadir CD4 count (r = -0.345; P = 0.004), while Granulicatella was negatively correlated with nadir CD4 count (r = -0.329; P = 0.007). Fungus Stemphylium correlated negatively with nadir CD4 (r = -0.323; P = 0.008).

Conclusions: Dysbiosis of the oral microbiota is associated with clinical and immunologic variables in HIV-infected patients.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Fig 1

Principal coordinates analysis (PCoA) of (A-F) bacteriome and (G-L) mycobiome data at different taxa in the three groups. Confidence ellipses are shown for each group, at 0.95% confidence.

Fig 2

Boxplots showing richness estimates (observed, chao1 and ACE) of (A) bacteriome and (B) mycobiome at phylum, genus, and species levels.

Fig 3

Venn diagrams showing frequency distribution of (A-C) core bacterial and (D-F) core fungal taxa (detected at abundance > 1%) in the three study groups. Frequency distribution in the core microbiota are shown for (A,D) Phylum, (B,E) Genus and (C,F) Species levels. HIV-SM: HIV-infected smokers, HIV-nSM: HIV-infected non-smokers, nHIV-SM: uninfected smokers.

Fig 4

Stacked bar charts showing distribution of (A-C) bacterial and (D-F) fungal phyla across the tested samples in the three groups. Phyla present at an abundance of at least 1% relative to the total abundance in each sample were included in the analyses.

Fig 5. Abundance profile of bacterial and fungal phyla in study groups.

(A) Boxplots showing relative abundance of bacterial and fungal phyla, (B) abundance ratio of Fusobacteria:Proteobacteria (ratio F:P) and Bacteriodetes:Proteobacteria (ratio B:P).

Fig 6

Intra-kingdom correlations within the bacteriome and mycobiome for (A,D) HIV-infected non-smokers, (B,E) HIV-infected smokers, and (C,F) uninfected smokers. Spearman’s correlation for each comparison was determined for the three groups. Blue circles indicate positive correlations; red circles indicate negative correlation; diameter of circles represent the absolute value of correlation for each pair of the microbe-microbe matrix.

Fig 7

Inter-kingdom correlations between the bacteriome and mycobiome for (A) HIV-infected non-smokers, (B) HIV-infected smokers, and (C) uninfected smokers. Spearman’s correlation for each comparison was determined for the three groups. Blue tiles indicate positive correlation; red tiles indicate negative correlations; tile sizes represent the absolute value of correlation for each pair of the microbe-microbe matrix.