The semen microbiome and its relationship with local immunology and viral load in HIV infection

Semen is a major vector for HIV transmission, but the semen HIV RNA viral load (VL) only correlates moderately with the blood VL. Viral shedding can be enhanced by genital infections and associated inflammation, but it can also occur in the absence of classical pathogens. Thus, we hypothesized that a dysregulated semen microbiome correlates with local HIV shedding. We analyzed semen samples from 49 men who have sex with men (MSM), including 22 HIV-uninfected and 27 HIV-infected men, at baseline and after starting antiretroviral therapy (ART) using 16S rRNA gene-based pyrosequencing and quantitative PCR. We studied the relationship of semen bacteria with HIV infection, semen cytokine levels, and semen VL by linear regression, non-metric multidimensional scaling, and goodness-of-fit test. Streptococcus, Corynebacterium, and Staphylococcus were common semen bacteria, irrespective of HIV status. While Ureaplasma was the more abundant Mollicutes in HIV-uninfected men, Mycoplasma dominated after HIV infection. HIV infection was associated with decreased semen microbiome diversity and richness, which were restored after six months of ART. In HIV-infected men, semen bacterial load correlated with seven pro-inflammatory semen cytokines, including IL-6 (p = 0.024), TNF-α (p = 0.009), and IL-1b (p = 0.002). IL-1b in particular was associated with semen VL (r2 = 0.18, p = 0.02). Semen bacterial load was also directly linked to the semen HIV VL (r2 = 0.15, p = 0.02). HIV infection reshapes the relationship between semen bacteria and pro-inflammatory cytokines, and both are linked to semen VL, which supports a role of the semen microbiome in HIV sexual transmission

The semen microbiome and its relationship with local immunology and viral load in HIV infection

Semen is a major vector for HIV transmission, but the semen HIV RNA viral load (VL) only correlates moderately with the blood VL. Viral shedding can be enhanced by genital infections and associated inflammation, but it can also occur in the absence of classical pathogens. Thus, we hypothesized that a dysregulated semen microbiome correlates with local HIV shedding. We analyzed semen samples from 49 men who have sex with men (MSM), including 22 HIV-uninfected and 27 HIV-infected men, at baseline and after starting antiretroviral therapy (ART) using 16S rRNA gene-based pyrosequencing and quantitative PCR. We studied the relationship of semen bacteria with HIV infection, semen cytokine levels, and semen VL by linear regression, non-metric multidimensional scaling, and goodness-of-fit test. Streptococcus, Corynebacterium, and Staphylococcus were common semen bacteria, irrespective of HIV status. While Ureaplasma was the more abundant Mollicutes in HIV-uninfected men, Mycoplasma dominated after HIV infection. HIV infection was associated with decreased semen microbiome diversity and richness, which were restored after six months of ART. In HIV-infected men, semen bacterial load correlated with seven pro-inflammatory semen cytokines, including IL-6 (p = 0.024), TNF-α (p = 0.009), and IL-1b (p = 0.002). IL-1b in particular was associated with semen VL (r(2)  = 0.18, p = 0.02). Semen bacterial load was also directly linked to the semen HIV VL (r(2) = 0.15, p = 0.02). HIV infection reshapes the relationship between semen bacteria and pro-inflammatory cytokines, and both are linked to semen VL, which supports a role of the semen microbiome in HIV sexual transmission

FungiQuant: A broad-coverage fungal quantitative real-time PCR assay

<p>Abstract</p> <p>Background</p> <p>Fungal load quantification is a critical component of fungal community analyses. Limitation of current approaches for quantifying the fungal component in the human microbiome suggests the need for new broad-coverage techniques.</p> <p>Methods</p> <p>We analyzed 2,085 18S rRNA gene sequences from the SILVA database for assay design. We generated and quantified plasmid standards using a qPCR-based approach. We evaluated assay coverage against 4,968 sequences and performed assay validation following the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines.</p> <p>Results</p> <p>We designed FungiQuant, a TaqMan^® qPCR assay targeting a 351 bp region in the fungal 18S rRNA gene. Our <it>in silico</it> analysis showed that FungiQuant is a perfect sequence match to 90.0% of the 2,617 fungal species analyzed. We showed that FungiQuant’s is 100% sensitive and its amplification efficiencies ranged from 76.3% to 114.5%, with <it>r</it>^<it>2</it>-values of >0.99 against the 69 fungal species tested. Additionally, FungiQuant inter- and intra-run coefficients of variance ranged from <10% and <20%, respectively. We further showed that FungiQuant has a limit of quantification 25 copies and a limit of detection at 5 copies. Lastly, by comparing results from human-only background DNA with low-level fungal DNA, we showed that amplification in two or three of a FungiQuant performed in triplicate is statistically significant for true positive fungal detection.</p> <p>Conclusions</p> <p>FungiQuant has comprehensive coverage against diverse fungi and is a robust quantification and detection tool for delineating between true fungal detection and non-target human DNA.</p

Prevalence and proportional abundances of the 40 most prevalent semen bacteria in uninfected men and HIV-infected men prior to initiation of antiretroviral therapy.

<p>Prevalence and proportional abundances of the 40 most prevalent semen bacteria in uninfected men and HIV-infected men prior to initiation of antiretroviral therapy.</p

Rank abundance and the five most abundant semen bacteria in uninfected versus HIV-infected men over the course of antiretroviral treatment.

<p>In this rank abundance plot, richness is the distance the plot extends along the x-axis, and evenness is low slope. Extreme dominance is a high y-intercept. HIV uninfected is both richer and more even than the ART- naïve, but by 6 months ART, the relationship converges onto the HIV uninfected. The five top-ranked semen bacteria from each group are listed, with its respective group-level proportional abundance in parenthesis.</p

Semen microbiome biodiversity in uninfected versus HIV-infected men over the course of antiretroviral treatment.

<p>In this set of two plots (<i>Panels A–B</i>), the solid circles represent HIV-uninfected men, whereas open circles represent HIV-infected men. Panel A depicts the higher richness (<i>i.e.</i>, greater number of unique bacterial types) of the semen microbiome in HIV-uninfected men, as well as the restoration of richness over the period of six months on ART. A similar trend was seen in semen microbiome diversity, as shown in Panel B.</p

Clinical parameters of the HIV-positive participants at baseline, prior to initiation of antiretroviral therapy.

<p>Clinical parameters of the HIV-positive participants at baseline, prior to initiation of antiretroviral therapy.</p

Meeting Report: Fungal ITS Workshop (October 2012)

Abstract This report summarizes a meeting held in Boulder, CO USA (19–20 October 2012) on fungal community analyses using ultra-high-throughput sequencing of the internal transcribed spacer (ITS) region of the nuclear ribosomal RNA (rRNA) genes. The meeting was organized as a two-day workshop, with the primary goal of supporting collaboration among researchers for improving fungal ITS sequence resources and developing recommendations for standard ITS primers for the research community