2020 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 | 環境ゲノム解析 / 遺伝子解析 / 微生物代謝 |
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| Outline of Annual Research Achievements |
Through synthesis of machine-learning and phylogenetic analyses, the origin of genes encoding proteins that degrade artificial contaminants (xenobiotics) have been identified. Notably, some evolutionary processes for modern metabolism can date back to the accumulation of oxygen on Earth more than two billion years ago. Specific lineages of life (Deltaproteobacteria and Firmicutes) have played a major role in evolving, retaining, and dispersing such genes. As a side project, evolutionary analyses was performed on Camponotus japonicus (carpenter ant) to identify gut microbiota differentiating castes within or between colonies.
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| Current Status of Research Progress |
Current Status of Research Progress
2: Research has progressed on the whole more than it was originally planned.
Reason
There have been major setbacks due to COVID-19, but progress is being made at a satisfactory pace.
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| Strategy for Future Research Activity |
In the coming year, further analyses will be performed to target 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. Preliminary analyses have shown differences in oxygen-independent energy metabolism between bacteria and archaea, suggesting ancient differences that may manifest today in unknown shapes that this project aims to identify.
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