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      Feeding an unsalable carrot total-mixed ration altered bacterial amino acid degradation in the rumen of lambs

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          Abstract

          The objective of this study was to determine the influence of a total-mixed ration including unsalable carrots at 45% DM on the rumen microbiome; and the plasma, rumen and liver metabolomes. Carrots discarded at processing were investigated as an energy-dense substitute for barley grain in a conventional feedlot diet, and improved feed conversion efficiency by 25%. Here, rumen fluid was collected from 34 Merino lambs at slaughter (n = 16 control; n = 18 carrot) after a feeding period of 11-weeks. The V4 region of the 16S rRNA gene was sequenced to profile archaeal and bacterial microbe communities. Further, a comprehensive, targeted profile of known metabolites was constructed for blood plasma, rumen fluid and biopsied liver metabolites using a gas chromatography mass spectrometry (GC–MS) metabolomics approach. An in vitro batch culture was used to characterise ruminal fermentation including gas and methane (CH 4) production. In vivo rumen microbial community structure of carrot fed lambs was dissimilar ( P < 0.01; PERMANOVA), and all measures of alpha diversity were greater ( P < 0.01), compared to those fed the control diet. Unclassified genera in Bacteroidales (15.9 ± 6.74% relative abundance; RA) were more abundant ( P < 0.01) in the rumen fluid of carrot-fed lambs, while unclassified taxa in the Succinivibrionaceae family (11.1 ± 3.85% RA) were greater ( P < 0.01) in the control. The carrot diet improved in vitro ruminal fermentation evidenced as an 8% increase ( P < 0.01) in DM digestibility and a 13.8% reduction ( P = 0.01) in CH 4 on a mg/ g DM basis, while the control diet increased ( P = 0.04) percentage of propionate within total VFA by 20%. Fourteen rumen fluid metabolites and 27 liver metabolites were influenced ( P ≤ 0.05) by diet, while no effect ( P ≥ 0.05) was observed in plasma metabolites. The carrot diet enriched (impact value = 0.13; P = 0.01) the tyrosine metabolism pathway (acetoacetic acid, dopamine and pyruvate), while the control diet enriched (impact value = 0.42; P ≤ 0.02) starch and sucrose metabolism (trehalose and glucose) in rumen fluid. This study demonstrated that feeding 45% DM unsalable carrots diversified bacterial communities in the rumen. These dietary changes influenced pathways of tyrosine degradation, such that previous improvements in feed conversion efficiency in lambs could be explained.

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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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            KEGG: kyoto encyclopedia of genes and genomes.

            M Kanehisa (2000)
            KEGG (Kyoto Encyclopedia of Genes and Genomes) is a knowledge base for systematic analysis of gene functions, linking genomic information with higher order functional information. The genomic information is stored in the GENES database, which is a collection of gene catalogs for all the completely sequenced genomes and some partial genomes with up-to-date annotation of gene functions. The higher order functional information is stored in the PATHWAY database, which contains graphical representations of cellular processes, such as metabolism, membrane transport, signal transduction and cell cycle. The PATHWAY database is supplemented by a set of ortholog group tables for the information about conserved subpathways (pathway motifs), which are often encoded by positionally coupled genes on the chromosome and which are especially useful in predicting gene functions. A third database in KEGG is LIGAND for the information about chemical compounds, enzyme molecules and enzymatic reactions. KEGG provides Java graphics tools for browsing genome maps, comparing two genome maps and manipulating expression maps, as well as computational tools for sequence comparison, graph comparison and path computation. The KEGG databases are daily updated and made freely available (http://www. genome.ad.jp/kegg/).
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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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                Author and article information

                Contributors
                s.meale@uq.edu.au
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                28 April 2023
                28 April 2023
                2023
                : 13
                : 6942
                Affiliations
                [1 ]GRID grid.1003.2, ISNI 0000 0000 9320 7537, School of Agriculture and Food Sciences, Faculty of Science, , The University of Queensland, ; Gatton, Australia
                [2 ]GRID grid.1003.2, ISNI 0000 0000 9320 7537, Australian Institute for Bioengineering and Nanotechnology, , The University of Queensland, ; St Lucia, Australia
                [3 ]GRID grid.1008.9, ISNI 0000 0001 2179 088X, Metabolomics Australia, Bio21 Institute, , The University of Melbourne, ; Parkville, Australia
                [4 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, School of Life and Environmental Sciences, Faculty of Science, , The University of Sydney, ; Camperdown, Australia
                Article
                34181
                10.1038/s41598-023-34181-0
                10147942
                37117259
                444f058c-77c2-4cb3-b935-b98c9c99f300
                © The Author(s) 2023

                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
                : 22 April 2022
                : 25 April 2023
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                © The Author(s) 2023

                Uncategorized
                applied microbiology,microbiome,metabolomics
                Uncategorized
                applied microbiology, microbiome, metabolomics

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