Literature DB >> 32591382

Validating the Use of Bovine Buccal Sampling as a Proxy for the Rumen Microbiota by Using a Time Course and Random Forest Classification Approach.

Juliana Young1, Joseph H Skarlupka2, Madison S Cox2, Rafael Tassinari Resende3, Amelie Fischer4, Kenneth F Kalscheur1, Jennifer C McClure1, John B Cole5, Garret Suen2, Derek M Bickhart6.   

Abstract

Analysis of the cow microbiome, as well as host genetic influences on the establishment and colonization of the rumen microbiota, is critical for development of strategies to manipulate ruminal function toward more efficient and environmentally friendly milk production. To this end, the development and validation of noninvasive methods to sample the rumen microbiota at a large scale are required. In this study, we further optimized the analysis of buccal swab samples as a proxy for direct bacterial samples of the rumen of dairy cows. To identify an optimal time for sampling, we collected buccal swab and rumen samples at six different time points relative to animal feeding. We then evaluated several biases in these samples using a machine learning classifier (random forest) to select taxa that discriminate between buccal swab and rumen samples. Differences in the inverse Simpson's diversity, Shannon's evenness, and Bray-Curtis dissimilarities between methods were significantly less apparent when sampling was performed prior to morning feeding (P < 0.05), suggesting that this time point was optimal for representative sampling. In addition, the random forest classifier was able to accurately identify nonrumen taxa, including 10 oral and putative feed-associated taxa. Two highly prevalent (>60%) taxa in buccal and rumen samples had significant variance in relative abundances between sampling methods but could be qualitatively assessed via regular buccal swab sampling. This work not only provides new insights into the oral community of ruminants but also further validates and refines buccal swabbing as a method to assess the rumen bacterial in large herds.IMPORTANCE The gastrointestinal tracts of ruminants harbor a diverse microbial community that coevolved symbiotically with the host, influencing its nutrition, health, and performance. While the influence of environmental factors on rumen microbes is well documented, the process by which host genetics influences the establishment and colonization of the rumen microbiota still needs to be elucidated. This knowledge gap is due largely to our inability to easily sample the rumen microbiota. There are three common methods for rumen sampling but all of them present at least one disadvantage, including animal welfare, sample quality, labor, and scalability. The development and validation of noninvasive methods, such as buccal swabbing, for large-scale rumen sampling is needed to support studies that require large sample sizes to generate reliable results. The validation of buccal swabbing will also support the development of molecular tools for the early diagnosis of metabolic disorders associated with microbial changes in large herds.

Entities:  

Keywords:  bacteria; buccal swab; machine learning; oral community; random forest; rumen microbiota

Mesh:

Year:  2020        PMID: 32591382      PMCID: PMC7440797          DOI: 10.1128/AEM.00861-20

Source DB:  PubMed          Journal:  Appl Environ Microbiol        ISSN: 0099-2240            Impact factor:   4.792


  37 in total

1.  Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB.

Authors:  T Z DeSantis; P Hugenholtz; N Larsen; M Rojas; E L Brodie; K Keller; T Huber; D Dalevi; P Hu; G L Andersen
Journal:  Appl Environ Microbiol       Date:  2006-07       Impact factor: 4.792

2.  Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform.

Authors:  James J Kozich; Sarah L Westcott; Nielson T Baxter; Sarah K Highlander; Patrick D Schloss
Journal:  Appl Environ Microbiol       Date:  2013-06-21       Impact factor: 4.792

Review 3.  Invited review: Current perspectives on eating and rumination activity in dairy cows.

Authors:  K A Beauchemin
Journal:  J Dairy Sci       Date:  2018-04-05       Impact factor: 4.034

4.  Effect of feeding duration and rumen fill on behaviour in dairy cows.

Authors: 
Journal:  Appl Anim Behav Sci       Date:  2000-12-01       Impact factor: 2.448

5.  Comparison of techniques for measurement of rumen pH in lactating dairy cows.

Authors:  T Duffield; J C Plaizier; A Fairfield; R Bagg; G Vessie; P Dick; J Wilson; J Aramini; B McBride
Journal:  J Dairy Sci       Date:  2004-01       Impact factor: 4.034

6.  Rumen Bacterial Community Composition in Holstein and Jersey Cows Is Different under Same Dietary Condition and Is Not Affected by Sampling Method.

Authors:  Henry A Paz; Christopher L Anderson; Makala J Muller; Paul J Kononoff; Samodha C Fernando
Journal:  Front Microbiol       Date:  2016-08-03       Impact factor: 5.640

7.  Comparison of rumen bacteria distribution in original rumen digesta, rumen liquid and solid fractions in lactating Holstein cows.

Authors:  Shoukun Ji; Hongtao Zhang; Hui Yan; Arash Azarfar; Haitao Shi; Gibson Alugongo; Shengli Li; Zhijun Cao; Yajing Wang
Journal:  J Anim Sci Biotechnol       Date:  2017-02-01

8.  Host genetics influence the rumen microbiota and heritable rumen microbial features associate with feed efficiency in cattle.

Authors:  Fuyong Li; Changxi Li; Yanhong Chen; Junhong Liu; Chunyan Zhang; Barry Irving; Carolyn Fitzsimmons; Graham Plastow; Le Luo Guan
Journal:  Microbiome       Date:  2019-06-13       Impact factor: 14.650

9.  SMOTE for high-dimensional class-imbalanced data.

Authors:  Rok Blagus; Lara Lusa
Journal:  BMC Bioinformatics       Date:  2013-03-22       Impact factor: 3.169

10.  SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB.

Authors:  Elmar Pruesse; Christian Quast; Katrin Knittel; Bernhard M Fuchs; Wolfgang Ludwig; Jörg Peplies; Frank Oliver Glöckner
Journal:  Nucleic Acids Res       Date:  2007-10-18       Impact factor: 16.971

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  1 in total

1.  Application of MinION Amplicon Sequencing to Buccal Swab Samples for Improving Resolution and Throughput of Rumen Microbiota Analysis.

Authors:  Hiroto Miura; Masayuki Takeda; Megumi Yamaguchi; Yoshihisa Ohtani; Go Endo; Yasuhisa Masuda; Kaede Ito; Yoshio Nagura; Kunihiro Iwashita; Tomohiro Mitani; Yutaka Suzuki; Yasuo Kobayashi; Satoshi Koike
Journal:  Front Microbiol       Date:  2022-03-24       Impact factor: 5.640

  1 in total

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