The precise effects of HIV-1 on the gut microbiome are unclear. Initial cross-sectional studies provided contradictory associations between microbial richness and HIV serostatus and suggested shifts from Bacteroides to Prevotella predominance following HIV-1 infection, which have not been found in animal models or in studies matched for HIV-1 transmission groups. In two independent cohorts of HIV-1-infected subjects and HIV-1-negative controls in Barcelona (n = 156) and Stockholm (n = 84), men who have sex with men (MSM) predominantly belonged to the Prevotella-rich enterotype whereas most non-MSM subjects were enriched in Bacteroides, independently of HIV-1 status, and with only a limited contribution of diet effects. Moreover, MSM had a significantly richer and more diverse fecal microbiota than non-MSM individuals. After stratifying for sexual orientation, there was no solid evidence of an HIV-specific dysbiosis. However, HIV-1 infection remained consistently associated with reduced bacterial richness, the lowest bacterial richness being observed in subjects with a virological-immune discordant response to antiretroviral therapy. Our findings indicate that HIV gut microbiome studies must control for HIV risk factors and suggest interventions on gut bacterial richness as possible novel avenues to improve HIV-1-associated immune dysfunction.

High-throughput sequencing technologies have revolutionized microbiome research by allowing the relative quantification of microbiome composition and function in different environments. In this work we focus on the identification of microbial signatures, groups of microbial taxa that are predictive of a phenotype of interest. We do this by acknowledging the compositional nature of the microbiome and the fact that it carries relative information. Thus, instead of defining a microbial signature as a linear combination in real space corresponding to the abundances of a group of taxa, we consider microbial signatures given by the geometric means of data from two groups of taxa whose relative abundances, or balance, are associated with the response variable of interest. In this work we present selbal, a greedy stepwise algorithm for selection of balances or microbial signatures that preserves the principles of compositional data analysis. We illustrate the algorithm with 16S rRNA abundance data from a Crohn’s microbiome study and an HIV microbiome study. IMPORTANCE We propose a new algorithm for the identification of microbial signatures. These microbial signatures can be used for diagnosis, prognosis, or prediction of therapeutic response based on an individual’s specific microbiota.

Significance: COVID-19 is the most devastating pandemic in recent history. As with many emerging infectious diseases, it is of zoonotic origin, meaning that animals played a major role in the initial transmission events. Despite SARS-CoV-2 being highly adapted to jump from human to human, several animal species are naturally susceptible to SARS-CoV-2, including pets such as cats. In the present report, a cat from a family with several relatives affected by COVID-19 developed severe respiratory clinical signs, leading to humanitarian euthanasia. Due to the suspicion of a potential COVID-19 infection in the cat, different antemortem and postmortem tests were assayed. The clinical condition was finally attributed to a feline hypertrophic cardiomyopathy, but the animal was also infected by SARS-CoV-2.

It is still debated if pre-existing minority drug-resistant HIV-1 variants (MVs) affect the virological outcomes of first-line NNRTI-containing ART. This Europe-wide case–control study included ART-naive subjects infected with drug-susceptible HIV-1 as revealed by population sequencing, who achieved virological suppression on first-line ART including one NNRTI. Cases experienced virological failure and controls were subjects from the same cohort whose viraemia remained suppressed at a matched time since initiation of ART. Blinded, centralized 454 pyrosequencing with parallel bioinformatic analysis in two laboratories was used to identify MVs in the 1%–25% frequency range. ORs of virological failure according to MV detection were estimated by logistic regression. Two hundred and sixty samples (76 cases and 184 controls), mostly subtype B (73.5%), were used for the analysis. Identical MVs were detected in the two laboratories. 31.6% of cases and 16.8% of controls harboured pre-existing MVs. Detection of at least one MV versus no MVs was associated with an increased risk of virological failure (OR = 2.75, 95% CI = 1.35–5.60, P = 0.005); similar associations were observed for at least one MV versus no NRTI MVs (OR = 2.27, 95% CI = 0.76–6.77, P = 0.140) and at least one MV versus no NNRTI MVs (OR = 2.41, 95% CI = 1.12–5.18, P = 0.024). A dose–effect relationship between virological failure and mutational load was found. Pre-existing MVs more than double the risk of virological failure to first-line NNRTI-based ART.

In rhesus macaques, simian immunodeficiency virus infection is followed by expansion of enteric viruses but has a limited impact on the gut bacteriome. To understand the longitudinal effects of HIV-1 infection on the human gut microbiota, we prospectively followed 49 Mozambican subjects diagnosed with recent HIV-1 infection (RHI) and 54 HIV-1-negative controls for 9–18 months and compared them with 98 chronically HIV-1-infected subjects treated with antiretrovirals (n = 27) or not (n = 71). We show that RHI is followed by increased fecal adenovirus shedding, which persists during chronic HIV-1 infection and does not resolve with ART. Recent HIV-1 infection is also followed by transient non-HIV-specific changes in the gut bacterial richness and composition. Despite early resilience to change, an HIV-1-specific signature in the gut bacteriome—featuring depletion of Akkermansia, Anaerovibrio, Bifidobacterium, and Clostridium—previously associated with chronic inflammation, CD8+ T cell anergy, and metabolic disorders, can be eventually identified in chronically HIV-1-infected subjects. Recent HIV-1 infection is associated with increased fecal shedding of eukaryotic viruses, transient loss of bacterial taxonomic richness, and long-term reductions in microbial gene richness. An HIV-1-associated microbiome signature only becomes evident in chronically HIV-1-infected subjects.

Gut microbiota dysbiosis features progressive HIV infection and is a potential target for intervention. Herein, we explored the microbiome of 16 elite controllers (EC), 32 antiretroviral therapy naive progressors and 16 HIV negative controls. We found that the number of observed genera and richness indices in fecal microbiota were significantly higher in EC versus naive. Genera Succinivibrio, Sutterella, Rhizobium, Delftia, Anaerofilum and Oscillospira were more abundant in EC, whereas Blautia and Anaerostipes were depleted. Additionally, carbohydrate metabolism and secondary bile acid synthesis pathway related genes were less represented in EC. Conversely, fatty acid metabolism, PPAR-signalling and lipid biosynthesis proteins pathways were enriched in EC vs naive. The kynurenine pathway of tryptophan metabolism was altered during progressive HIV infection, and inversely associated with microbiota richness. In conclusion, EC have richer gut microbiota than untreated HIV patients, with unique bacterial signatures and a distinct metabolic profile which may contribute to control of HIV.