Progressive HIV infection is characterized by dysregulation of the intestinal immune barrier, translocation of immunostimulatory microbial products, and chronic systemic inflammation that is thought to drive progression of disease to AIDS. Elements of this pathologic process persist despite viral suppression during highly active antiretroviral therapy (HAART) and drivers of these phenomena remain poorly understood. Disrupted intestinal immunity can precipitate dysbiosis that induces chronic inflammation in the mucosa and periphery of mice. However, putative microbial drivers of HIV-associated immunopathology versus recovery have not been identified in humans. Using high-resolution bacterial community profiling, we identified a dysbiotic mucosal-adherent community enriched in Proteobacteria and depleted of Bacteroidia members that was associated with markers of mucosal immune disruption, T cell activation, and chronic inflammation in HIV-infected subjects. Furthermore, this dysbiosis was evident among HIV-infected subjects undergoing HAART, and the extent of dysbiosis correlated with activity of the kynurenine pathway of tryptophan metabolism and plasma concentrations of the inflammatory cytokine interleukin-6 (IL-6), two established markers of disease progression. Gut-resident bacteria with capacity to metabolize tryptophan through the kynurenine pathway were found to be enriched in HIV-infected subjects, strongly correlated with kynurenine levels in HIV-infected subjects, and capable of kynurenine production in vitro. These observations demonstrate a link between mucosal-adherent colonic bacteria and immunopathogenesis during progressive HIV infection, which is apparent even in the setting of viral suppression during HAART. This link suggests that gut-resident microbial populations may influence intestinal homeostasis during HIV disease.

Functional analysis of a clinical microbiome facilitates the elucidation of mechanisms by which microbiome perturbation can cause a phenotypic change in the patient. The direct approach for the analysis of the functional capacity of the microbiome is via shotgun metagenomics. An inexpensive method to estimate the functional capacity of a microbial community is through collecting 16S rRNA gene profiles then indirectly inferring the abundance of functional genes. This inference approach has been implemented in the PICRUSt and Tax4Fun software tools. However, those tools have important limitations since they rely on outdated functional databases and uncertain phylogenetic trees and require very specific data pre-processing protocols. Here we introduce Piphillin, a straightforward algorithm independent of any proposed phylogenetic tree, leveraging contemporary functional databases and not obliged to any singular data pre-processing protocol. When all three inference tools were evaluated against actual shotgun metagenomics, Piphillin was superior in predicting gene composition in human clinical samples compared to both PICRUSt and Tax4Fun (p<0.01 and p<0.001, respectively) and Piphillin’s ability to predict disease associations with specific gene orthologs exhibited a 15% increase in balanced accuracy compared to PICRUSt. From laboratory animal samples, no performance advantage was observed for any one of the tools over the others and for environmental samples all produced unsatisfactory predictions. Our results demonstrate that functional inference using the direct method implemented in Piphillin is preferable for clinical biospecimens. Piphillin is publicly available for academic use at http://secondgenome.com/Piphillin.

Studies of inflammatory bowel disease (IBD) have been inconclusive in relating microbiota with distribution of inflammation. We report microbiota, host transcriptomics, epigenomics and genetics from matched inflamed and non-inflamed colonic mucosa [50 Crohn's disease (CD); 80 ulcerative colitis (UC); 31 controls]. Changes in community-wide and within-patient microbiota are linked with inflammation, but we find no evidence for a distinct microbial diagnostic signature, probably due to heterogeneous host-microbe interactions, and show only marginal microbiota associations with habitual diet. Epithelial DNA methylation improves disease classification and is associated with both inflammation and microbiota composition. Microbiota sub-groups are driven by dominant Enterbacteriaceae and Bacteroides species, representative strains of which are pro-inflammatory in vitro, are also associated with immune-related epigenetic markers. In conclusion, inflamed and non-inflamed colonic segments in both CD and UC differ in microbiota composition and epigenetic profiles.

Understanding the relationship between gene diversity and function for important environmental processes are major ecological research goals. We applied gene-targeted-metagenomics and pyrosequencing to aromatic dioxygenase genes to obtain greater sequence depth than possible by other methods. A PCR primer set designed to target a 524 bp region that confers substrate specificity of biphenyl dioxygenases yielded 2000 and 604 sequences from 5′ and 3′ ends of the PCR products, respectively, that passed our validity criteria. Sequence alignment showed three known conserved residues as well as another seven conserved residues not previously reported. Ninety-five and 41% of the valid sequences were assigned to 22 and 3 novel clusters in that they did not include any previously reported sequences at 0.6 distance by Complete Linkage Clustering for the sequenced regions. The greater diversity revealed by this gene-targeted approach provides deeper insights into genes potentially important in environmental processes to better understand their ecology, functional differences and evolutionary origins. We also provide criteria for primer design for this approach as well as guidance for data processing of diverse functional genes since gene databases for most genes of environmental relevance are limited.

cDespite the increased frequency of recurrent pneumonia in HIV-infected patients and recent studies linking the airway bacterial community (microbiota) to acute and chronic respiratory infection, little is known of the oral and airway microbiota that exist in these individuals and their propensity to harbor pathogens despite antimicrobial treatment for acute pneumonia. This pilot study compared paired samples of the oral and airway microbiota from 15 hospitalized HIV-infected patients receiving antimicrobial treatment for acute pneumonia. Total DNA was extracted, bacterial burden was assessed by quantitative PCR, and amplified 16S rRNA was profiled for microbiome composition using a phylogenetic microarray (16S rRNA PhyloChip). Though the bacterial burden of the airway was significantly lower than that of the oral cavity, microbiota in both niches were comparably diverse. However, oral and airway microbiota exhibited niche specificity. Oral microbiota were characterized by significantly increased relative abundance of multiple species associated with the mouth, including members of the Bacteroides, Firmicutes, and TM7 phyla, while airway microbiota were primarily characterized by a relative expansion of the Proteobacteria. Twenty-two taxa were detected in both niches, including Streptococcus bovis and Chryseobacterium species, pathogens associated with HIV-infected populations. In addition, we compared the airway microbiota of five of these patients to those of five non-HIV-infected pneumonia patients from a previous study. Compared to the control population, HIV-infected patients exhibited relative increased abundance of a large number of phylogenetically distinct taxa, which included several known or suspected pathogenic organisms, suggesting that recurrent pneumonia in HIV-infected populations may be related to the presence of these species.

Background: Shotgun metagenomic sequencing reveals the potential in microbial communities. However, lowercost 16S ribosomal RNA (rRNA) gene sequencing provides taxonomic, not functional, observations. To remedy this, we previously introduced Piphillin, a software package that predicts functional metagenomic content based on the frequency of detected 16S rRNA gene sequences corresponding to genomes in regularly updated, functionally annotated genome databases. Piphillin (and similar tools) have previously been evaluated on 16S rRNA data processed by the clustering of sequences into operational taxonomic units (OTUs). New techniques such as amplicon sequence variant error correction are in increased use, but it is unknown if these techniques perform better in metagenomic content prediction pipelines, or if they should be treated the same as OTU data in respect to optimal pipeline parameters. Results: To evaluate the effect of 16S rRNA sequence analysis method (clustering sequences into OTUs vs amplicon sequence variant error correction into amplicon sequence variants (ASVs)) on the ability of Piphillin to predict functional metagenomic content, we evaluated Piphillin-predicted functional content from 16S rRNA sequence data processed through OTU clustering and error correction into ASVs compared to corresponding shotgun metagenomic data. We show a strong correlation between metagenomic data and Piphillin-predicted functional content resulting from both 16S rRNA sequence analysis methods. Differential abundance testing with Piphillinpredicted functional content exhibited a low false positive rate (< 0.05) while capturing a large fraction of the differentially abundant features resulting from corresponding metagenomic data. However, Piphillin prediction performance was optimal at different cutoff parameters depending on 16S rRNA sequence analysis method. Using data analyzed with amplicon sequence variant error correction, Piphillin outperformed comparable tools, for instance exhibiting 19% greater balanced accuracy and 54% greater precision compared to PICRUSt2. Conclusions: Our results demonstrate that raw Illumina sequences should be processed for subsequent Piphillin analysis using amplicon sequence variant error correction (with DADA2 or similar methods) and run using a 99% ID cutoff for Piphillin, while sequences generated on platforms other than Illumina should be processed via OTU clustering (e.g., UPARSE) and run using a 96% ID cutoff for Piphillin. Piphillin is publicly available for academic users (Piphillin server. http://piphillin.secondgenome.com/.

Sub-Saharan Africa represents 69% of the total number of individuals living with HIV infection worldwide and 72% of AIDS deaths globally. Pulmonary infection is a common and frequently fatal complication, though little is known regarding the lower airway microbiome composition of this population. Our objectives were to characterize the lower airway microbiome of Ugandan HIV-infected patients with pneumonia, to determine relationships with demographic, clinical, immunological, and microbiological variables and to compare the composition and predicted metagenome of these communities to a comparable cohort of patients in the US (San Francisco). Bronchoalveolar lavage samples from a cohort of 60 Ugandan HIV-infected patients with acute pneumonia were collected. Amplified 16S ribosomal RNA was profiled and aforementioned relationships examined. Ugandan airway microbiome composition and predicted metagenomic function were compared to US HIV-infected pneumonia patients. Among the most common bacterial pulmonary pathogens, Pseudomonas aeruginosa was most prevalent in the Ugandan cohort. Patients with a richer and more diverse airway microbiome exhibited lower bacterial burden, enrichment of members of the Lachnospiraceae and sulfur-reducing bacteria and reduced expression of TNF-alpha and matrix metalloproteinase-9. Compared to San Franciscan patients, Ugandan airway microbiome was significantly richer, and compositionally distinct with predicted metagenomes that encoded a multitude of distinct pathogenic pathways e.g secretion systems. Ugandan pneumonia-associated airway microbiome is compositionally and functionally distinct from those detected in comparable patients in developed countries, a feature which may contribute to adverse outcomes in this population.

These data provide evidence that compositionally and structurally distinct lower airway microbiomes are associated with discrete local host immune responses, peripheral metabolic reprogramming, and different rates of mortality.