A compositional look at the human gastrointestinal microbiome and immune activation parameters in HIV infected subjects

Abstract

HIV progression is characterized by immune activation and microbial translocation. One factor that may be contributing to HIV progression could be a dysbiotic microbiome. We therefore hypothesized that the GI mucosal microbiome is altered in HIV patients and this alteration correlates with immune activation in HIV. 121 specimens were collected from 21 HIV positive and 22 control human subjects during colonoscopy. The composition of the lower gastrointestinal tract mucosal and luminal bacterial microbiome was characterized using 16S rDNA pyrosequencing and was correlated to clinical parameters as well as immune activation and circulating bacterial products in HIV patients on ART. The composition of the HIV microbiome was significantly different than that of controls; it was less diverse in the right colon and terminal ileum, and was characterized by loss of bacterial taxa that are typically considered commensals. In HIV samples, there was a gain of some pathogenic bacterial taxa. This is the first report characterizing the terminal ileal and colonic mucosal microbiome in HIV patients with next generation sequencing. Limitations include use of HIV-infected subjects on HAART therapy.

Conflict of interest statement

The authors have declared that no competing interests exist.

Figures

Figure 1. Diversity indices in HIV samples versus control samples.

HIV samples have decreased diversity compared to controls. HIV samples are in red; Control samples are in blue. Panels : (a) OTU richness, (b) Chao1 index, (c) Phylogenetic Diversity (PD) Whole Tree metric.

Figure 2. Sample diversity assessed by diversity indices in HIV cases versus controls by sample site.

HIV cases have decreased diversity compared to controls. HIV samples are in red; Control samples are in blue. Diversity indices shown are OTU richness (panels (a–d)), Chao1 index (panels (e–h)), and Phylogenetic Diversity (PD) Whole Tree metric (panels (i–l)). Samples from ileum are shown in panels (a),(e),(i); samples from right colon are shown in panels (b),(f),(j) ; samples from left colon are shown in panels (c),(g),(k); and fecal samples are shown in panels (d),(h),(l).

Figure 3. Beta diversity measures in HIV versus controls.

HIV samples appear separated from control samples in beta diversity analyses. HIV samples are in red; Control samples are in blue. Panel (a) shows nonmetric multidimensional scaling (NMDS) of all the samples using the Bray-Curtis similarity at the OTU level. Panel (b) shows principal coordinates analysis of all of the samples using the Unifrac metric at the OTU level. Panels (c–f) show principal coordinates analysis using the Unifrac metric, by sample site. Panels: (c) For samples from ileum; (d) For samples from right colon; (e) For samples from left colon; (f) For fecal samples.

Figure 4. UPGMA dendogram based on Bray-Curtis similarity.

Branches related to HIV samples are colored in red. Branches related to control samples are colored in blue. There is significant clustering within the dendogram.

Figure 5. Stacked histogram of bacterial composition in all samples by disease and site, to the family level of taxonomic resolution.

Each column represents bacterial composition in one single sample (n = 121 for all samples; n = 65 for controls; n = 56 for HIV). Y- axis denotes abundance of bacterial taxa as a percentage within the sample, with each column totaling 100%. X-axis shows samples from healthy subjects to the left of the graph, and samples from HIV subjects to the right of the graph. TI = samples from terminal ileum; RC = samples from right colon; LC = samples from left colon; F = fecal samples. While all identified families are shown on the graph, sample coloring is grouped by phylogeny. Among the colors used, Bacteroidales are shown in brown tones, Bacilli are shown in orange tones, Clostridia are shown in red tones, Alphaproteobacteria are shown in green tones, Betaproteobacteria are shown in yellow tones, Gammaproteobacteria are shown in blue tones. Major differences between control and HIV samples are visually apparent based on difference in coloring of the samples.

Figure 6. Indicator values for bacterial taxa, which are indicative of control or HIV samples.

Indicator species analysis was performed after rarification and log transformation. Analysis was blocked by site. Genera and those unclassified bacterial members of families that not able to be classified down to a particular genus, that also have indicator values >15 and p

Figure 7. Scatterplots of bacterial taxa indicative of HIV samples.

Y-axis shows percent abundance in rarified sequences for each sample. Control samples are shown as black dots and HIV samples are shown as upward black triangles. Horizontal lines denote mean value in each group. P-values shown are results from indicator species analysis. Genera and those unclassified bacterial members of families that not able to be classified down to a particular genus, that also have indicator values >15 and p

Figure 8. Scatterplots of bacterial taxa indicative of control samples.

Y-axis shows percent abundance in rarified sequences for each sample. Control samples are shown as black dots and HIV samples are shown as upward black triangles. Horizontal lines denote mean value in each group. P-values shown are results from indicator species analysis. Genera and those unclassified bacterial members of families that not able to be classified down to a particular genus, that also have indicator values >15 and p

Figure 9. Canonical correspondence analysis of genera with measured cytokines.

HIV samples are shown in red vs. control samples are shown in blue. (a)The eigenvalues for axis 1 and axis 2 are 0.107 and 0.087, respectively. The axes 1 and 2 explain 2.8% and 2.2% of the total variance, respectively. The first canonical axis is statistically significant with p = 0.003 using a randomization test where p = proportion of randomized runs with eigenvalue greater than or equal to the observed eigenvalue with 998 randomizations. The vectors in the mid portion of the graph represent cytokines or microbial translocation products. LTA increases going toward the HIV group, and IL-6 increases going toward the control group. The effect of TNF and sCD14 are minimal along the first axis of separation between the cases. (b) Canonical correspondence analysis of genera with IL-6 effect overlay. The size of the case dots correspond to the impact of IL-6 on the analysis. The regression plot for each axis coordinates and IL-6 is given below the axis for axis 1 and to the left of the axis for axis 2. (c) Canonical correspondence analysis of genera with LTA effect overlay. The size of the case dots correspond to the impact of LTA on the analysis. The regression plot for each axis coordinates and LTA is given below the axis for axis 1 and to the left of the axis for axis 2.