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      Supplementation of xylo-oligosaccharides to suckling piglets promotes the growth of fiber-degrading gut bacterial populations during the lactation and nursery periods

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          Abstract

          Modulating early-life microbial colonization through xylo-oligosacharides (XOS) supplementation represents an opportunity to accelerate the establishment of fiber-degrading microbial populations and improve intestinal health. Ninety piglets from 15 litters were orally administered once a day from d7 to d27 of lactation with either 5 mL of water (CON) or 5 mL of a solution containing 30 to 60 mg of XOS (XOS). Supplementation ceased at weaning (d28) when all piglets were fed the same commercial pre-starter diet. Growth performance did not differ between treatments during the experimental period (d7 to d40). Piglet’s fecal microbiota (n = 30) shifted significantly from the end of lactation (d27) to nursery period (d40) exhibiting an increase in microbial alpha diversity. Animals supplemented with XOS showed higher richness and abundance of fiber-degrading bacteria and short-chain fatty acid (SCFA) production at d27 and d40. Additionally, the predicted abundance of the pyruvate to butanoate fermentation pathway was increased in the XOS group at d40. These results show that supplementation of XOS to lactating piglets promotes fiber-degrading bacterial populations in their hindgut. Moreover, differences observed in the nursery period suggest that XOS can influence the microbiota in the long-term.

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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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            Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2

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              Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy.

              The Ribosomal Database Project (RDP) Classifier, a naïve Bayesian classifier, can rapidly and accurately classify bacterial 16S rRNA sequences into the new higher-order taxonomy proposed in Bergey's Taxonomic Outline of the Prokaryotes (2nd ed., release 5.0, Springer-Verlag, New York, NY, 2004). It provides taxonomic assignments from domain to genus, with confidence estimates for each assignment. The majority of classifications (98%) were of high estimated confidence (> or = 95%) and high accuracy (98%). In addition to being tested with the corpus of 5,014 type strain sequences from Bergey's outline, the RDP Classifier was tested with a corpus of 23,095 rRNA sequences as assigned by the NCBI into their alternative higher-order taxonomy. The results from leave-one-out testing on both corpora show that the overall accuracies at all levels of confidence for near-full-length and 400-base segments were 89% or above down to the genus level, and the majority of the classification errors appear to be due to anomalies in the current taxonomies. For shorter rRNA segments, such as those that might be generated by pyrosequencing, the error rate varied greatly over the length of the 16S rRNA gene, with segments around the V2 and V4 variable regions giving the lowest error rates. The RDP Classifier is suitable both for the analysis of single rRNA sequences and for the analysis of libraries of thousands of sequences. Another related tool, RDP Library Compare, was developed to facilitate microbial-community comparison based on 16S rRNA gene sequence libraries. It combines the RDP Classifier with a statistical test to flag taxa differentially represented between samples. The RDP Classifier and RDP Library Compare are available online at http://rdp.cme.msu.edu/.
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                Author and article information

                Contributors
                David.Sola@uab.cat
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 July 2022
                8 July 2022
                2022
                : 12
                : 11594
                Affiliations
                [1 ]GRID grid.7080.f, ISNI 0000 0001 2296 0625, Animal Nutrition and Welfare Service (SNIBA), Department of Animal and Food Science, , Autonomous University of Barcelona, ; 08193 Bellaterra, Spain
                [2 ]GRID grid.8581.4, ISNI 0000 0001 1943 6646, Animal Breeding and Genetics Program, , Institute for Research and Technology in Food and Agriculture (IRTA), Torre Marimon, ; 08140 Caldes de Montbui, Spain
                [3 ]GRID grid.507482.c, AB Vista, ; Marlborough, SN8 4AN Wiltshire UK
                Article
                15963
                10.1038/s41598-022-15963-4
                9270449
                34992227
                8c043d73-c461-42f8-a25f-8ecf84f819dd
                © The Author(s) 2022

                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
                : 24 March 2022
                : 1 July 2022
                Funding
                Funded by: Ministerio de Ciencia, Innovación y Universidades
                Award ID: FPU18/00401
                Award ID: RYC2019-027244-I
                Award Recipient :
                Funded by: UAB-Banco de Santander
                Award ID: Talent Program
                Award Recipient :
                Funded by: Ministerio de Economía, Industria y Competitividad, Gobierno de España
                Award ID: AGL2016-75463-R
                Award Recipient :
                Categories
                Article
                Custom metadata
                © The Author(s) 2022

                Uncategorized
                molecular biology,microbiology,microbial genetics,dysbiosis,diarrhoea,animal physiology
                Uncategorized
                molecular biology, microbiology, microbial genetics, dysbiosis, diarrhoea, animal physiology

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