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Approximately 40% of global HIV-1 transmission occurs in the female genital tract (FGT) through heterosexual transmission. Epithelial cells lining the FGT provide the first barrier to HIV-1 entry. Previous studies have suggested that certain hormonal contraceptives or a dysbiosis of the vaginal microbiota can enhance HIV-1 acquisition in the FGT. We examined the effects of lactobacilli and female sex hormones on the barrier functions and innate immune responses of primary endometrial genital epithelial cells (GECs). Two probiotic strains, Lactobacillus reuteri RC-14 and L. rhamnosus GR-1, were tested, as were sex hormones estrogen (E2), progesterone (P4), and the hormonal contraceptive medroxyprogesterone acetate (MPA). Our results demonstrate that probiotic lactobacilli enhance barrier function without affecting cytokines. Treatment of GECs with MPA resulted in reduced barrier function. In contrast, E2 treatment enhanced barrier function and reduced production of proinflammatory cytokines. Comparison of hormones plus lactobacilli as a pre-treatment prior to HIV exposure revealed a dominant effect of lactobacilli in preventing loss of barrier function by GECs. In summary, the combination of E2 and lactobacilli had the best protective effect against HIV-1 seen by enhancement of barrier function and reduction in proinflammatory cytokines. These studies provide insights into how probiotic lactobacilli in the female genital microenvironment can alter HIV-1-mediated barrier disruption and how the combination of E2 and lactobacilli may decrease susceptibility to primary HIV infection.
Pubmed ID: 31546582
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THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 5,2022.Tool that predicts interactions between transcription factors and their regulated genes from binding motifs. Understanding vertebrate development requires unraveling the cis-regulatory architecture of gene regulation. PRISM provides accurate genome-wide computational predictions of transcription factor binding sites for the human and mouse genomes, and integrates the predictions with GREAT to provide functional biological context. Together, accurate computational binding site prediction and GREAT produce for each transcription factor: 1. putative binding sites, 2. putative target genes, 3. putative biological roles of the transcription factor, and 4. putative cis-regulatory elements through which the factor regulates each target in each functional role.
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