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      Ewe Vaginal Microbiota: Associations With Pregnancy Outcome and Changes During Gestation

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          Abstract

          Reproductive performance is paramount to the success of livestock production enterprises focused on lamb meat production. Reproductive success is influenced by various factors, possibly including the reproductive tract microbial communities present at the time of copulation and throughout pregnancy. There are few publications that identify the vaginal microbial communities of livestock, and even fewer exist for sheep. To compare ewe vaginal microbial communities, vaginal swabs were taken from 67 Hampshire and Hampshire X Suffolk crossbred ewes from the Iowa State University sheep farm at a pre-breeding time point (S1) and after pregnancy testing (S2). Animals that were determined pregnant were sampled again within a few days of expected parturition (S3). DNA was extracted from these swabs, and 16S rRNA gene Illumina MiSeq amplicon sequencing was conducted to fingerprint the bacterial communities found within this system. Pre-breeding time point samples showed no differences in community structure between animals later found to be pregnant or non-pregnant, but significant changes were detected in species richness (Chao; P < 0.001) and species diversity (Shannon; P < 0.001) at the second sampling time point. A higher microbial diversity within the S2 time point samples may suggest a more stable environment driven by pregnancy, as this increased diversity is maintained in pregnant animals from the S2 to the S3 time point. Additionally, several bacterial phylotypes, such as Mannheimia, Oscillospiraceae-like OTUs and Alistipes, were more abundant at either the S1 or S2 time points in animals that established pregnancy, suggesting a beneficial effect on pregnancy outcome. This study identifies changes within the microbial communities of the ewe vagina before and during gestation and offers inferences on how these changes may impact pregnancy outcome. Information presented herein offers new knowledge about sheep vaginal microbial communities and serves as a starting point to help guide researchers to improve sheep reproductive performance in the future.

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          Most cited references46

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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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              Every base matters: assessing small subunit rRNA primers for marine microbiomes with mock communities, time series and global field samples.

              Microbial community analysis via high-throughput sequencing of amplified 16S rRNA genes is an essential microbiology tool. We found the popular primer pair 515F (515F-C) and 806R greatly underestimated (e.g. SAR11) or overestimated (e.g. Gammaproteobacteria) common marine taxa. We evaluated marine samples and mock communities (containing 11 or 27 marine 16S clones), showing alternative primers 515F-Y (5'-GTGYCAGCMGCCGCGGTAA) and 926R (5'-CCGYCAATTYMTTTRAGTTT) yield more accurate estimates of mock community abundances, produce longer amplicons that can differentiate taxa unresolvable with 515F-C/806R, and amplify eukaryotic 18S rRNA. Mock communities amplified with 515F-Y/926R yielded closer observed community composition versus expected (r(2)  = 0.95) compared with 515F-Y/806R (r(2)  ∼ 0.5). Unexpectedly, biases with 515F-Y/806R against SAR11 in field samples (∼4-10-fold) were stronger than in mock communities (∼2-fold). Correcting a mismatch to Thaumarchaea in the 515F-C increased their apparent abundance in field samples, but not as much as using 926R rather than 806R. With plankton samples rich in eukaryotic DNA (> 1 μm size fraction), 18S sequences averaged ∼17% of all sequences. A single mismatch can strongly bias amplification, but even perfectly matched primers can exhibit preferential amplification. We show that beyond in silico predictions, testing with mock communities and field samples is important in primer selection.
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                Author and article information

                Contributors
                Journal
                Front Microbiol
                Front Microbiol
                Front. Microbiol.
                Frontiers in Microbiology
                Frontiers Media S.A.
                1664-302X
                22 October 2021
                2021
                : 12
                : 745884
                Affiliations
                [1] 1Department of Veterinary Microbiology and Preventive Medicine, Iowa State University , Ames, IA, United States
                [2] 2Interdepartmental Microbiology Graduate Program, Iowa State University , Ames, IA, United States
                [3] 3Department of Animal and Food Sciences, Texas Tech University , Lubbock, TX, United States
                [4] 4Department of Animal Science, Iowa State University , Ames, IA, United States
                Author notes

                Edited by: Alfonso Benítez-Páez, Principe Felipe Research Center (CIPF), Spain

                Reviewed by: Malena Serrano, Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria (INIA), Spain; Laura Glendinning, University of Edinburgh, United Kingdom; Md. Abdullah Al Mamun, Bangladesh Agricultural University, Bangladesh

                *Correspondence: Stephan Schmitz-Esser, sse@ 123456iastate.edu

                This article was submitted to Microbial Symbioses, a section of the journal Frontiers in Microbiology

                Article
                10.3389/fmicb.2021.745884
                8570082
                34745049
                4eea6f1f-4ee4-43b0-bb61-92cd7c88235a
                Copyright © 2021 Koester, Petry, Youngs and Schmitz-Esser.

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 22 July 2021
                : 04 October 2021
                Page count
                Figures: 5, Tables: 1, Equations: 2, References: 47, Pages: 13, Words: 8848
                Categories
                Microbiology
                Original Research

                Microbiology & Virology
                ovine,sheep,fertility,reproduction,vaginal microbiome
                Microbiology & Virology
                ovine, sheep, fertility, reproduction, vaginal microbiome

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