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      Lactobacillus crispatus thrives in pregnancy hormonal milieu in a Nigerian patient cohort

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          Abstract

          Steroid hormones are one of the presumed modulators of Lactobacillus abundance in the vaginal epithelium. We set out to characterize the vaginal microbiome (VMB) and also provide an in-depth understanding of the relative contribution of estradiol (E2) and progesterone (P1) in shaping the vaginal microbiome of Nigerian women (n = 38) who experienced both uncomplicated term delivery and preterm delivery using samples longitudinally collected during pregnancy (17–21, 27–31, 36–41 weeks gestation) and 6 weeks postpartum. Vaginal swabs and blood samples were aseptically collected. Vaginal swabs were used for microbiome assessment using 16S ribosomal RNA (rRNA) gene sequencing. Blood samples were used for hormonal measurement using a competitive-based enzyme-linked immunosorbent assay (ELISA). Across several maternal covariates, maternal age, pregnancy status and delivery mode were not significantly associated with the vaginal microbiota whereas maternal E2 level (p E2 = 0.006, Omnibus), and P1 level (p P1 = 0.001, Omnibus) were significantly associated with the vaginal microbiome. E2 and P1 concentrations increased throughout pregnancy commensurately with increasing proportions of L. crispatus (p E2 = 0.036, p P1 = 0.034, Linear Mixed Model). An increasing trend of α-diversity was also observed as pregnancy progressed (p observed ASV = 0.006, LMM). A compositional microbiome shift from Lactobacillus profile to non- Lactobacillus profile was observed in most postnatal women (p CST IV < 0.001, LMM). Analysis of our data shows a species-specific link between pregnancy steroid hormone concentration and L. crispatus abundance.

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          Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing

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            DADA2: High resolution sample inference from Illumina amplicon data

            We present DADA2, a software package that models and corrects Illumina-sequenced amplicon errors. DADA2 infers sample sequences exactly, without coarse-graining into OTUs, and resolves differences of as little as one nucleotide. In several mock communities DADA2 identified more real variants and output fewer spurious sequences than other methods. We applied DADA2 to vaginal samples from a cohort of pregnant women, revealing a diversity of previously undetected Lactobacillus crispatus variants.
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              QIIME allows analysis of high-throughput community sequencing data.

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                Author and article information

                Contributors
                nkechiodogwu27@gmail.com
                Chia.Nicholas@mayo.edu
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                13 September 2021
                13 September 2021
                2021
                : 11
                : 18152
                Affiliations
                [1 ]GRID grid.9582.6, ISNI 0000 0004 1794 5983, Pan African University Life and Earth Sciences Institute (PAULESI), University of Ibadan, ; Ibadan, Oyo State Nigeria
                [2 ]GRID grid.66875.3a, ISNI 0000 0004 0459 167X, Division of Surgical Research, Department of Surgery, , Mayo Clinic, ; Rochester, MN USA
                [3 ]GRID grid.66875.3a, ISNI 0000 0004 0459 167X, Microbiome Program, Center for Individualized Medicine, , Mayo Clinic, ; Rochester, MN USA
                [4 ]GRID grid.412438.8, ISNI 0000 0004 1764 5403, Department of Obstetrics and Gynecology, , University College Hospital, ; Ibadan, Nigeria
                [5 ]GRID grid.66875.3a, ISNI 0000 0004 0459 167X, Department of Health Science Research, , Mayo Clinic, ; Rochester, MN USA
                [6 ]GRID grid.9582.6, ISNI 0000 0004 1794 5983, Department of Pharmaceutical Microbiology, Faculty of Pharmacy, , University of Ibadan, ; Ibadan, Nigeria
                [7 ]GRID grid.66875.3a, ISNI 0000 0004 0459 167X, Department of Obstetrics and Gynecology, , Mayo Clinic, ; Rochester, MN USA
                [8 ]GRID grid.9582.6, ISNI 0000 0004 1794 5983, Department of Obstetrics and Gynecology, College of Medicine, , University of Ibadan, ; Ibadan, Nigeria
                [9 ]GRID grid.66875.3a, ISNI 0000 0004 0459 167X, Division of Clinical Microbiology, Department of Laboratory Medicine and Pathology, , Mayo Clinic, ; Rochester, MN USA
                Article
                96339
                10.1038/s41598-021-96339-y
                8437942
                34518588
                fd624bad-f3f1-4395-b796-212ac3475bf6
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 March 2021
                : 30 July 2021
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                © The Author(s) 2021

                Uncategorized
                microbiology,molecular biology,endocrinology,medical research
                Uncategorized
                microbiology, molecular biology, endocrinology, medical research

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