An integrative framework for functional analysis of cattle rumen microbiomes

Jyotsna Talreja Wassan; Huiru Zheng; Fiona Browne; J M Bowen; Paul Walsh; R Roehe; RJ Dewhurst; Cintia Palu; Brian Kelly; Haiying Wang

doi:10.1109/BIBM.2018.8621104

An integrative framework for functional analysis of cattle rumen microbiomes

Jyotsna Talreja Wassan, Huiru Zheng, Fiona Browne, J M Bowen, Paul Walsh, R Roehe, RJ Dewhurst, Cintia Palu, Brian Kelly, Haiying Wang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Citations (Scopus)

Abstract

Metagenomics is the study of environmental microbial communities and has various applications and implications in biological research. This paper aims to study the role of microbial communities in cattle rumen and their relation to probiotic diet supplement usage as part of the EU H2020 MetaPIat project l1 MetaPlat, http://www.metaplat.eu. In this research, we proposed and evaluated a computational framework to classify 16S rRNA samples from Bos taurus (cattle) rumen microbiome into a diet phenotype. We performed analysis by benchmarking various phylogeny-driven methods based on integration of biological domain knowledge of relationships and non-phylogenetic methods based on the raw abundances. The integrative approach incorporating phylogenetic tree structure into machine learning (ML) modelling achieved a high predictive performance with Accuracy of 0.925 and Kappa of 0.900 for classifying cattle microbiomes into diets supplemented with oil, nitrate, a combination and controls.

Original language	English
Title of host publication	Proceedings of 2018 IEEE International Conference on Bioinformatics and Biomedicine
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	1854
Number of pages	1860
ISBN (Electronic)	978-1-5386-5488-0
DOIs	https://doi.org/10.1109/BIBM.2018.8621104
Publication status	Print publication - 12 Mar 2018

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Wassan, J. T., Zheng, H., Browne, F., Bowen, J. M., Walsh, P., Roehe, R., Dewhurst, RJ., Palu, C., Kelly, B., & Wang, H. (2018). An integrative framework for functional analysis of cattle rumen microbiomes. In Proceedings of 2018 IEEE International Conference on Bioinformatics and Biomedicine (pp. 1854). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2018.8621104

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title = "An integrative framework for functional analysis of cattle rumen microbiomes",

abstract = "Metagenomics is the study of environmental microbial communities and has various applications and implications in biological research. This paper aims to study the role of microbial communities in cattle rumen and their relation to probiotic diet supplement usage as part of the EU H2020 MetaPIat project l1 MetaPlat, http://www.metaplat.eu. In this research, we proposed and evaluated a computational framework to classify 16S rRNA samples from Bos taurus (cattle) rumen microbiome into a diet phenotype. We performed analysis by benchmarking various phylogeny-driven methods based on integration of biological domain knowledge of relationships and non-phylogenetic methods based on the raw abundances. The integrative approach incorporating phylogenetic tree structure into machine learning (ML) modelling achieved a high predictive performance with Accuracy of 0.925 and Kappa of 0.900 for classifying cattle microbiomes into diets supplemented with oil, nitrate, a combination and controls.",

author = "Wassan, {Jyotsna Talreja} and Huiru Zheng and Fiona Browne and Bowen, {J M} and Paul Walsh and R Roehe and RJ Dewhurst and Cintia Palu and Brian Kelly and Haiying Wang",

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Wassan, JT, Zheng, H, Browne, F, Bowen, JM, Walsh, P, Roehe, R , Dewhurst, RJ, Palu, C, Kelly, B & Wang, H 2018, An integrative framework for functional analysis of cattle rumen microbiomes. in Proceedings of 2018 IEEE International Conference on Bioinformatics and Biomedicine. Institute of Electrical and Electronics Engineers Inc., pp. 1854. https://doi.org/10.1109/BIBM.2018.8621104

An integrative framework for functional analysis of cattle rumen microbiomes. / Wassan, Jyotsna Talreja; Zheng, Huiru; Browne, Fiona et al.
Proceedings of 2018 IEEE International Conference on Bioinformatics and Biomedicine. Institute of Electrical and Electronics Engineers Inc., 2018. p. 1854.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Wassan, Jyotsna Talreja

AU - Zheng, Huiru

AU - Browne, Fiona

AU - Bowen, J M

AU - Walsh, Paul

AU - Roehe, R

AU - Dewhurst, RJ

AU - Palu, Cintia

AU - Kelly, Brian

AU - Wang, Haiying

PY - 2018/3/12

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N2 - Metagenomics is the study of environmental microbial communities and has various applications and implications in biological research. This paper aims to study the role of microbial communities in cattle rumen and their relation to probiotic diet supplement usage as part of the EU H2020 MetaPIat project l1 MetaPlat, http://www.metaplat.eu. In this research, we proposed and evaluated a computational framework to classify 16S rRNA samples from Bos taurus (cattle) rumen microbiome into a diet phenotype. We performed analysis by benchmarking various phylogeny-driven methods based on integration of biological domain knowledge of relationships and non-phylogenetic methods based on the raw abundances. The integrative approach incorporating phylogenetic tree structure into machine learning (ML) modelling achieved a high predictive performance with Accuracy of 0.925 and Kappa of 0.900 for classifying cattle microbiomes into diets supplemented with oil, nitrate, a combination and controls.

AB - Metagenomics is the study of environmental microbial communities and has various applications and implications in biological research. This paper aims to study the role of microbial communities in cattle rumen and their relation to probiotic diet supplement usage as part of the EU H2020 MetaPIat project l1 MetaPlat, http://www.metaplat.eu. In this research, we proposed and evaluated a computational framework to classify 16S rRNA samples from Bos taurus (cattle) rumen microbiome into a diet phenotype. We performed analysis by benchmarking various phylogeny-driven methods based on integration of biological domain knowledge of relationships and non-phylogenetic methods based on the raw abundances. The integrative approach incorporating phylogenetic tree structure into machine learning (ML) modelling achieved a high predictive performance with Accuracy of 0.925 and Kappa of 0.900 for classifying cattle microbiomes into diets supplemented with oil, nitrate, a combination and controls.

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M3 - Conference contribution

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BT - Proceedings of 2018 IEEE International Conference on Bioinformatics and Biomedicine

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An integrative framework for functional analysis of cattle rumen microbiomes

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