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      Next-Generation Sequencing as a Tool to Detect Vaginal Microbiota Disturbances during Pregnancy

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          Abstract

          The physiological microbiota of the vagina is responsible for providing a protective barrier, but Some factors can disturb the balance in its composition. At that time, the amounts of the genus Lactobacillus decrease, which may lead to the development of infection and severe complications during pregnancy. The aim of the study was the analysis of the bacterial composition of the vagina in 32 Caucasian women at each trimester of pregnancy using the next-generation sequencing method and primers targeting V3-V4 regions. In the studied group, the dominant species were Lactobacillus iners, Lactobacillus gasseri, and Lactobacillus plantarum. Statistically significant differences in the quantitative composition between trimesters were observed in relation to Lactobacillus jensenii, Streptococcus agalactiae, Lactobacillus iners, Gardnerella spp. Out of the 32 patients, 20 demonstrated fluctuations within the genus Lactobacillus, and 9 of them, at different stages of pregnancy, exhibited the presence of potentially pathogenic microbiota, among others: Streptococcus agalactiae, Gardnerella spp., Atopobium vaginae, and Enterococcus faecalis. The composition of the vaginal microbiota during pregnancy was subject to partial changes over trimesters. Although in one-third of the studied patients, both the qualitative and quantitative composition of microbiota was relatively constant, in the remaining patients, physiological and potentially pathogenic fluctuations were distinguished.

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

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            Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2

            In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental conditions. Small replicate numbers, discreteness, large dynamic range and the presence of outliers require a suitable statistical approach. We present DESeq2, a method for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates. This enables a more quantitative analysis focused on the strength rather than the mere presence of differential expression. The DESeq2 package is available at http://www.bioconductor.org/packages/release/bioc/html/DESeq2.html. Electronic supplementary material The online version of this article (doi:10.1186/s13059-014-0550-8) contains supplementary material, which is available to authorized users.
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              The SILVA ribosomal RNA gene database project: improved data processing and web-based tools

              SILVA (from Latin silva, forest, http://www.arb-silva.de) is a comprehensive web resource for up to date, quality-controlled databases of aligned ribosomal RNA (rRNA) gene sequences from the Bacteria, Archaea and Eukaryota domains and supplementary online services. The referred database release 111 (July 2012) contains 3 194 778 small subunit and 288 717 large subunit rRNA gene sequences. Since the initial description of the project, substantial new features have been introduced, including advanced quality control procedures, an improved rRNA gene aligner, online tools for probe and primer evaluation and optimized browsing, searching and downloading on the website. Furthermore, the extensively curated SILVA taxonomy and the new non-redundant SILVA datasets provide an ideal reference for high-throughput classification of data from next-generation sequencing approaches.
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                Author and article information

                Journal
                Microorganisms
                Microorganisms
                microorganisms
                Microorganisms
                MDPI
                2076-2607
                18 November 2020
                November 2020
                : 8
                : 11
                : 1813
                Affiliations
                [1 ]Department of Molecular Medical Microbiology, Chair of Microbiology, Faculty of Medicine, Jagiellonian University Medical College, 31-121 Krakow, Poland; agnieszka.sroka@ 123456uj.edu.pl (A.S.-O.); tomasz.gosiewski@ 123456uj.edu.pl (T.G.)
                [2 ]Clinical Department of Gynecological Endocrinology and Gynecology, Jagiellonian University Medical College, Kopernika 23, 31-501 Krakow, Poland; mopabian@ 123456cyfronet.pl
                [3 ]Center for Experimental and Innovative Medicine, University of Agriculture in Krakow, Rędzina 1c, 30-248 Kraków, Poland; artur.gurgul@ 123456urk.edu.pl
                [4 ]Center for Medical Genomics OMICRON, Jagiellonian University Medical College, Kopernika 7c, 31-034 Krakow, Poland; przemyslaw.kapusta@ 123456uj.edu.pl (P.K.); agnieszka.ludwig@ 123456uj.edu.pl (A.H.L.-S.); pawel.wolkow@ 123456uj.edu.pl (P.P.W.)
                Author notes
                [* ]Correspondence: m.brzychczy-wloch@ 123456uj.edu.pl ; Tel.: +48-1263-325-67
                Author information
                https://orcid.org/0000-0003-4725-5943
                https://orcid.org/0000-0001-5979-144X
                https://orcid.org/0000-0003-4467-1175
                https://orcid.org/0000-0002-0548-4767
                https://orcid.org/0000-0002-9322-5545
                Article
                microorganisms-08-01813
                10.3390/microorganisms8111813
                7698737
                33217908
                35144109-425f-49a1-89e3-d3b4a8497e7b
                © 2020 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 28 October 2020
                : 16 November 2020
                Categories
                Article

                pregnant women,vaginal microbiota,next-generation sequencing,lactobacillus spp.,streptococcus agalactiae,gbs,gardnerella spp.

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