Effects of brewers’ spent grain protein hydrolysates on gas production, ruminal fermentation characteristics, microbial protein synthesis and microbial community in an artificial rumen fed a high grain diet

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Abstract

Background

Brewers’ spent grain (BSG) typically contains 20% – 29% crude protein (CP) with high concentrations of glutamine, proline and hydrophobic and non-polar amino acid, making it an ideal material for producing value-added products like bioactive peptides which have antioxidant properties. For this study, protein was extracted from BSG, hydrolyzed with 1% alcalase and flavourzyme, with the generated protein hydrolysates (AlcH and FlaH) showing antioxidant activities. This study evaluated the effects of AlcH and FlaH on gas production, ruminal fermentation characteristics, nutrient disappearance, microbial protein synthesis and microbial community using an artificial rumen system (RUSITEC) fed a high-grain diet.

Results

As compared to the control of grain only, supplementation of FlaH decreased ( P < 0.01) disappearances of dry matter (DM), organic matter (OM), CP and starch, without affecting fibre disappearances; while AlcH had no effect on nutrient disappearance. Neither AlcH nor FlaH affected gas production or VFA profiles, however they increased ( P < 0.01) NH ₃-N and decreased ( P < 0.01) H ₂ production. Supplementation of FlaH decreased ( P < 0.01) the percentage of CH ₄ in total gas and dissolved-CH ₄ (dCH ₄) in dissolved gas. Addition of monensin reduced ( P < 0.01) disappearance of nutrients, improved fermentation efficiency and reduced CH ₄ and H ₂ emissions. Total microbial nitrogen production was decreased ( P < 0.05) but the proportion of feed particle associated (FPA) bacteria was increased with FlaH and monensin supplementation. Numbers of OTUs and Shannon diversity indices of FPA microbial community were unaffected by AlcH and FlaH; whereas both indices were reduced ( P < 0.05) by monensin. Taxonomic analysis revealed no effect of AlcH and FlaH on the relative abundance (RA) of bacteria at phylum level, whereas monensin reduced ( P < 0.05) the RA of Firmicutes and Bacteroidetes and enhanced Proteobacteria. Supplementation of FlaH enhanced ( P < 0.05) the RA of genus Prevotella, reduced Selenomonas, Shuttleworthia, Bifidobacterium and Dialister as compared to control; monensin reduced ( P < 0.05) RA of genus Prevotella but enhaced Succinivibrio.

Conclusions

The supplementation of FlaH in high-grain diets may potentially protect CP and starch from ruminal degradation, without adversely affecting fibre degradation and VFA profiles. It also showed promising effects on reducing CH ₄ production by suppressing H ₂ production. Protein enzymatic hydrolysates from BSG using flavourzyme showed potential application to high value-added bio-products.

Supplementary Information

The online version contains supplementary material available at 10.1186/s40104-020-00531-5.

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

Michael Love, Wolfgang Huber, Simon Anders (2014)

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

Evan Bolyen, Jai Rideout, Matthew Dillon … (2019)

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

Paul McMurdie, Susan Holmes (2013)

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

Wenzhu Yang: wenzhu.yang@canada.ca

Journal

Journal ID (nlm-ta): J Anim Sci Biotechnol

Journal ID (iso-abbrev): J Anim Sci Biotechnol

Title: Journal of Animal Science and Biotechnology

Publisher: BioMed Central (London )

ISSN (Print): 1674-9782

ISSN (Electronic): 2049-1891

Publication date (Electronic): 4 January 2021

Publication date PMC-release: 4 January 2021

Publication date Collection: 2021

Volume: 12

Electronic Location Identifier: 1

Affiliations

[1 ]GRID grid.55614.33, ISNI 0000 0001 1302 4958, Agriculture and Agri-Food of Canada, , Lethbridge Research and Development Centre, ; Lethbridge, AB T1J 4B1 Canada

[2 ]GRID grid.458449.0, ISNI 0000 0004 1797 8937, Key Laboratory for Agro-Ecological Processes in Subtropical Region, , Institute of Subtropical Agriculture, Chinese Academy of Sciences, ; Changsha, 410125 Hunan China

[3 ]GRID grid.22072.35, ISNI 0000 0004 1936 7697, College of Veterinary Medicine, , University of Calgary, ; 2500 University Dr. NW, Calgary, AB T2N 1N4 Canada

[4 ]GRID grid.17089.37, Department of Agricultural, Food and Nutritional Science, , University of Alberta, ; Edmonton, T6G 2P5 Canada

[5 ]GRID grid.412707.7, ISNI 0000 0004 0621 7833, Department of Animal and Poultry Production, Faculty of Agriculture, , South Valley University, ; Qena, 83523 Egypt

Article

Publisher ID: 531

DOI: 10.1186/s40104-020-00531-5

PMC ID: 7780661

PubMed ID: 33397465

SO-VID: 420dd9c2-e0e3-41e0-9774-3f35ed568ca4

License:

Open AccessThis 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/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

History

Date received : 30 May 2020

Date accepted : 20 November 2020

Funding

Funded by: FundRef http://dx.doi.org/10.13039/501100000040, Agriculture and Agri-Food Canada;

Award ID: GF2#1542

Award Recipient : Wenzhu Yang

Custom metadata

ScienceOpen disciplines: Animal science & Zoology

Keywords: antioxidant peptide,brewers’ spent grain,fermentation,hydrogen production,methane production,protein hydrolysates,rusitec

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ScienceOpen disciplines: Animal science & Zoology

Keywords: antioxidant peptide, brewers’ spent grain, fermentation, hydrogen production, methane production, protein hydrolysates, rusitec

Effects of brewers’ spent grain protein hydrolysates on gas production, ruminal fermentation characteristics, microbial protein synthesis and microbial community in an artificial rumen fed a high grain diet

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Supplementary Information

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Porifera

Most cited references 74

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

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

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

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