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      The Effect of Antiretroviral Therapy Initiation on the Vaginal Microbiome in HIV-Infected Women

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          Abstract

          Background

          The impact of antiretroviral therapy (ART) initiation on the vaginal microbiome is unknown. This is of particular importance among women living in sub-Saharan Africa. Understanding this relationship could help elucidate if and how the host immune system interacts with the vaginal microbiome.

          Methods

          The vaginal microbiome of HIV-1/HSV-2-coinfected women (n = 92) in Uganda was evaluated from self-collected vaginal swabs 1 month pre-ART and at 4 and 6 months post–ART initiation. The vaginal microbiome was characterized by 16S rRNA gene-based sequencing and quantitative polymerase chain reaction. Vaginal community state types (CSTs) were identified using proportional abundance data. Changes in microbiome composition were assessed with permutational analyses of variance (PerMANOVA).

          Results

          Five vaginal CSTs were identified, which varied significantly by bacterial load (P < .01): CST-1 was characterized by Lactobacillus iners, CST-2 by Gardnerella, CST-3 by Gardnerella and Prevotella, CST-4 by Lactobacillus crispatus, and CST-5 was highly diverse. Vaginal microbiome composition also did not change significantly after ART initiation (P = .985). Immune reconstitution after ART initiation did not affect vaginal microbiome CST assignment (P = .722) or individual-level changes in bacterial load (log response ratio [interquartile range], –0.50 [–2.75 to 0.38] vs –0.29 [–2.03 to 1.42]; P = .40).

          Conclusions

          The vaginal microbiome of HIV-infected women was not affected by the initiation of ART or immune reconstitution in this observational study. Further research is needed to explore the long-term effects of ART treatment on the vaginal microbiome.

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          Most cited references44

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          Vaginal microbiome of reproductive-age women.

          The means by which vaginal microbiomes help prevent urogenital diseases in women and maintain health are poorly understood. To gain insight into this, the vaginal bacterial communities of 396 asymptomatic North American women who represented four ethnic groups (white, black, Hispanic, and Asian) were sampled and the species composition characterized by pyrosequencing of barcoded 16S rRNA genes. The communities clustered into five groups: four were dominated by Lactobacillus iners, L. crispatus, L. gasseri, or L. jensenii, whereas the fifth had lower proportions of lactic acid bacteria and higher proportions of strictly anaerobic organisms, indicating that a potential key ecological function, the production of lactic acid, seems to be conserved in all communities. The proportions of each community group varied among the four ethnic groups, and these differences were statistically significant [χ(2)(10) = 36.8, P < 0.0001]. Moreover, the vaginal pH of women in different ethnic groups also differed and was higher in Hispanic (pH 5.0 ± 0.59) and black (pH 4.7 ± 1.04) women as compared with Asian (pH 4.4 ± 0.59) and white (pH 4.2 ± 0.3) women. Phylotypes with correlated relative abundances were found in all communities, and these patterns were associated with either high or low Nugent scores, which are used as a factor for the diagnosis of bacterial vaginosis. The inherent differences within and between women in different ethnic groups strongly argues for a more refined definition of the kinds of bacterial communities normally found in healthy women and the need to appreciate differences between individuals so they can be taken into account in risk assessment and disease diagnosis.
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            Analysis of composition of microbiomes: a novel method for studying microbial composition

            Background Understanding the factors regulating our microbiota is important but requires appropriate statistical methodology. When comparing two or more populations most existing approaches either discount the underlying compositional structure in the microbiome data or use probability models such as the multinomial and Dirichlet-multinomial distributions, which may impose a correlation structure not suitable for microbiome data. Objective To develop a methodology that accounts for compositional constraints to reduce false discoveries in detecting differentially abundant taxa at an ecosystem level, while maintaining high statistical power. Methods We introduced a novel statistical framework called analysis of composition of microbiomes (ANCOM). ANCOM accounts for the underlying structure in the data and can be used for comparing the composition of microbiomes in two or more populations. ANCOM makes no distributional assumptions and can be implemented in a linear model framework to adjust for covariates as well as model longitudinal data. ANCOM also scales well to compare samples involving thousands of taxa. Results We compared the performance of ANCOM to the standard t-test and a recently published methodology called Zero Inflated Gaussian (ZIG) methodology (1) for drawing inferences on the mean taxa abundance in two or more populations. ANCOM controlled the false discovery rate (FDR) at the desired nominal level while also improving power, whereas the t-test and ZIG had inflated FDRs, in some instances as high as 68% for the t-test and 60% for ZIG. We illustrate the performance of ANCOM using two publicly available microbial datasets in the human gut, demonstrating its general applicability to testing hypotheses about compositional differences in microbial communities. Conclusion Accounting for compositionality using log-ratio analysis results in significantly improved inference in microbiota survey data.
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              The Ribosomal Database Project: improved alignments and new tools for rRNA analysis

              The Ribosomal Database Project (RDP) provides researchers with quality-controlled bacterial and archaeal small subunit rRNA alignments and analysis tools. An improved alignment strategy uses the Infernal secondary structure aware aligner to provide a more consistent higher quality alignment and faster processing of user sequences. Substantial new analysis features include a new Pyrosequencing Pipeline that provides tools to support analysis of ultra high-throughput rRNA sequencing data. This pipeline offers a collection of tools that automate the data processing and simplify the computationally intensive analysis of large sequencing libraries. In addition, a new Taxomatic visualization tool allows rapid visualization of taxonomic inconsistencies and suggests corrections, and a new class Assignment Generator provides instructors with a lesson plan and individualized teaching materials. Details about RDP data and analytical functions can be found at http://rdp.cme.msu.edu/.
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                Author and article information

                Journal
                Open Forum Infectious Diseases
                Oxford University Press (OUP)
                2328-8957
                September 2019
                September 01 2019
                September 2019
                September 01 2019
                July 12 2019
                : 6
                : 9
                Affiliations
                [1 ]Department of Environmental and Occupational Health, Milken Institute School of Public Health, George Washington University, Washington, DC
                [2 ]Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland
                [3 ]Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
                [4 ]Department of Ophthalmology, School of Medicine, Johns Hopkins University, Baltimore, Maryland
                [5 ]Rakai Health Sciences Program, Kalisizo, Uganda
                [6 ]Department of Microbiology and Immunology, Schulich School of Medicine and Dentistry, Western University, London, Ontario, Canada
                [7 ]Department of Medicine, University of Toronto, Toronto, Ontario, Canada
                [8 ]Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland
                [9 ]Division of Intramural Research, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, Maryland
                Article
                10.1093/ofid/ofz328
                6798248
                31660406
                1168c1df-cdd4-4721-a174-40eb45067d15
                © 2019
                History

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