2018 Fiscal Year Annual Research Report
Microbiome mining: machine learning for discovery of genetic dark matter, metabolic pathways, and ecological processes from metagenomes
| Project/Area Number |
18H03367
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| Research Institution | National Institute of Advanced Industrial Science and Technology |
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Principal Investigator |
延 優 国立研究開発法人産業技術総合研究所, 生命工学領域, 研究員 (40805644)
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| Project Period (FY) |
2018-04-01 – 2023-03-31
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| Keywords | Metagenomics / Machine Learning / Genomics / Metabolism |
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| Outline of Annual Research Achievements |
Using a gene-cassette-based approach, groups of genes that may interact together were identified using a machine-learning-based approach. Whether this concept held true for genomes for both cultured and uncultured organisms was evaluated. Metagenomic sequencing was performed for multiple samples to collect genomes for novel uncharacterized microbial lineages. Comparative genomics revealed gene clusters that were shared with and unique from cultured organisms. Further analysis is required to estimate the function of these genes. Specific analysis of genes conserved in a large uncultured archaeal clade revealed many genes including amino acid degradation and anaerobic metabolism at the common ancestor of an archaeal lineage deeply related to the origin of Eukaryotes.
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| Current Status of Research Progress |
Current Status of Research Progress
1: Research has progressed more than it was originally planned.
Reason
Research is proceeding as planned now.
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| Strategy for Future Research Activity |
In the coming year, the analysis will be expanded to genes involved in other high-profile metabolisms and catabolic pathways that may be unique to a specific domain (bacteria vs archaea). Targets include other genes for degrading non-aromatic xenobiotics and high-priority contaminants (detected frequently and persistent) with unknown genes and catabolic pathways that differentiate/distinguish bacteria and archaea. Bacteria and Archaea are distinct phylogenetic lineages, yet we understand very little about how they differ in physiology and way of life. Machine-learning-based approaches will be a novel approach to tackling this fundamental question in biology.
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Research Products
(4 results)
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[Journal Article] Isolation of an archaeon at the prokaryote?eukaryote interface2020
Author(s)
Imachi H, Nobu MK, Nakahara N, Morono Y, Ogawara M, Takaki Y, Takano Y, Uematsu K, Ikuta T, Ito M, Matsui Y, Miyazaki M, Murata K, Saito Y, Sakai S, et al.
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Journal Title
Nature
Volume: 577
Pages: 519～525
DOI
Peer Reviewed / Open Access
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