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      Vaginal microbiota differences associated with pelvic organ prolapse risk during late gestation in commercial sows

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          Abstract

          During the last decade, sow mortality due to pelvic organ prolapse (POP) has increased. To better understand the biology associated with POP, sows were phenotypically assessed and assigned a perineal score (PS) based on presumed POP risk and categorized as PS1 (low), PS2 (moderate), or PS3 (high). The study objective was to identify changes in sow vaginal microbiota that may be associated with POP. The hypothesis is that vaginal microbiota differs between sows with variable risk for POP, and changes in microbiota during late gestation exist between sows with differing risk. Of the 2864 sows scored during gestation week 15, 1.0, 2.7, and 23.4% of PS1, PS2, and PS3 sows, respectively, subsequently experienced POP. Vaginal swabs subjected to 16S rRNA gene sequencing revealed differences in community composition (Bray–Curtis; P < 0.05) and individual operational taxonomic unit (OTU) comparisons between vaginal microbiota of PS1 and PS3 sows at gestation week 15. Further, differences ( P < 0.05) in community composition and OTUs ( Q < 0.05) were observed in PS3 sows that either did or did not subsequently experience POP. Differences in community structure (alpha diversity measurements; P < 0.05), composition ( P < 0.05), and OTUs ( Q < 0.05) were observed in gestation week 12 sows scored PS1 compared to week 15 sows scored PS1 or PS3, suggesting that sow vaginal microbiota shifts during late gestation differently as POP risk changes. Collectively, these data demonstrate that sows with greater POP risk have unique vaginal microflora, for which a better understanding could aid in the development of mitigation strategies.

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          Most cited references59

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          phyloseq: An R Package for Reproducible Interactive Analysis and Graphics of Microbiome Census Data

          Background The analysis of microbial communities through DNA sequencing brings many challenges: the integration of different types of data with methods from ecology, genetics, phylogenetics, multivariate statistics, visualization and testing. With the increased breadth of experimental designs now being pursued, project-specific statistical analyses are often needed, and these analyses are often difficult (or impossible) for peer researchers to independently reproduce. The vast majority of the requisite tools for performing these analyses reproducibly are already implemented in R and its extensions (packages), but with limited support for high throughput microbiome census data. Results Here we describe a software project, phyloseq, dedicated to the object-oriented representation and analysis of microbiome census data in R. It supports importing data from a variety of common formats, as well as many analysis techniques. These include calibration, filtering, subsetting, agglomeration, multi-table comparisons, diversity analysis, parallelized Fast UniFrac, ordination methods, and production of publication-quality graphics; all in a manner that is easy to document, share, and modify. We show how to apply functions from other R packages to phyloseq-represented data, illustrating the availability of a large number of open source analysis techniques. We discuss the use of phyloseq with tools for reproducible research, a practice common in other fields but still rare in the analysis of highly parallel microbiome census data. We have made available all of the materials necessary to completely reproduce the analysis and figures included in this article, an example of best practices for reproducible research. Conclusions The phyloseq project for R is a new open-source software package, freely available on the web from both GitHub and Bioconductor.
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            Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform.

            Rapid advances in sequencing technology have changed the experimental landscape of microbial ecology. In the last 10 years, the field has moved from sequencing hundreds of 16S rRNA gene fragments per study using clone libraries to the sequencing of millions of fragments per study using next-generation sequencing technologies from 454 and Illumina. As these technologies advance, it is critical to assess the strengths, weaknesses, and overall suitability of these platforms for the interrogation of microbial communities. Here, we present an improved method for sequencing variable regions within the 16S rRNA gene using Illumina's MiSeq platform, which is currently capable of producing paired 250-nucleotide reads. We evaluated three overlapping regions of the 16S rRNA gene that vary in length (i.e., V34, V4, and V45) by resequencing a mock community and natural samples from human feces, mouse feces, and soil. By titrating the concentration of 16S rRNA gene amplicons applied to the flow cell and using a quality score-based approach to correct discrepancies between reads used to construct contigs, we were able to reduce error rates by as much as two orders of magnitude. Finally, we reprocessed samples from a previous study to demonstrate that large numbers of samples could be multiplexed and sequenced in parallel with shotgun metagenomes. These analyses demonstrate that our approach can provide data that are at least as good as that generated by the 454 platform while providing considerably higher sequencing coverage for a fraction of the cost.
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              An Ordination of the Upland Forest Communities of Southern Wisconsin

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                Author and article information

                Contributors
                Journal
                Biol Reprod
                Biol Reprod
                biolreprod
                Biology of Reproduction
                Oxford University Press
                0006-3363
                1529-7268
                December 2021
                20 September 2021
                20 September 2021
                : 105
                : 6
                : 1545-1561
                Affiliations
                Department of Animal Science , Iowa State University , Ames, IA, USA
                Department of Veterinary Microbiology and Preventive Medicine , Iowa State University , Ames, IA, USA
                Interdepartmental Microbiology Graduate Program , Iowa State University , Ames, IA, USA
                Department of Animal Science , Iowa State University , Ames, IA, USA
                Iowa Pork Industry Center , Ames, IA, USA
                Pillen Family Farms , Columbus, NE, USA
                Department of Animal Science , Iowa State University , Ames, IA, USA
                Department of Animal Science , Iowa State University , Ames, IA, USA
                Interdepartmental Microbiology Graduate Program , Iowa State University , Ames, IA, USA
                Department of Animal Science , Iowa State University , Ames, IA, USA
                Iowa Pork Industry Center , Ames, IA, USA
                Author notes
                Correspondence: Department of Animal Science, Iowa State University, Ames, IA 50011, USA. Tel: +1(515)2948647; Fax: +15152944471; E-mail: jwross@ 123456iastate.edu
                Article
                ioab178
                10.1093/biolre/ioab178
                8689292
                34542158
                b873fa1f-2090-4694-8145-5bf2582ea5cd
                © The Author(s) 2021. Published by Oxford University Press on behalf of Society for the Study of Reproduction.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( https://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com

                History
                : 6 July 2021
                : 13 August 2021
                : 14 September 2021
                : 06 November 2021
                Page count
                Pages: 17
                Funding
                Funded by: National Pork Board and Foundation for Food and Agriculture Research;
                Award ID: #18-147
                Categories
                Research Article
                AcademicSubjects/MED00773
                AcademicSubjects/SCI01070

                pelvic organ prolapse,vaginal microbiota,reproduction,pig sow

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