2021 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
|
|---|
| Research Institution | National Institute of Advanced Industrial Science and Technology |
|---|
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)
|
|---|
| Project Period (FY) |
2018-04-01 – 2023-03-31
|
| Keywords | Genomics / Metabolism / Evolution |
|---|
| Outline of Annual Research Achievements |
Through synthesis of machine-learning and phylogenetic analyses, plastics xenobiotics degrading genes in soil bacteria were identified and their evolutionary history/origin was predicted. Through comparison with bacteria living in engineering environments, their evolutionary trends were found to be nearly opposite - one depending on ancient inheritances and the other recent innovations. As a parallel project, combining phylogenetic, genomic, and thermodynamic analyses, a novel recently evolved metabolism in methanogenic archaea was discovered.
|
| 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.
|
| Strategy for Future Research Activity |
In the coming year, further analyses will be performed to identify novel genes evolved recently, presumably to degrade xenobiotic compounds. Through machine learning-facilitated data mining, we will search for operons of novel genes phylogenetically restricted to specific lineages and environmentally restricted to environments exposed to xenobiotic pollutants. The results will also be used to identify lineages that tend to make evolutionary breakthroughs in pollutant remediation.
|
Research Products
(1 results)
