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Employment Record in Research 【 display / non-display 】
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Tokyo University of Agriculture Faculty of Life Sciences Department of Molecular Microbiology Assistant Professor
2022.04
Professional Memberships 【 display / non-display 】
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日本微生物生態学会
2016
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日本生物工学会
2022
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日本農芸化学会
2022
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日本バイオインフォマティクス学会
2022
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日本ゲノム微生物学会
2022
Research seeds 【 display / non-display 】
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機械学習を用いた無細胞タンパク質合成系の開発
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メタゲノム解析を用いた河川・排水処理場の水質調査
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腸内微生物叢データからパーソナルデータを推測する機械学習モデルの開発
Papers 【 display / non-display 】
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Hydrocarbon Cycling in the Tokamachi Mud Volcano (Japan): Insights from Isotopologue and Metataxonomic Analyses Reviewed
Alexis Gilbert, Mayuko Nakagawa, Koudai Taguchi, Naizhong Zhang, Akifumi Nishida, Naohiro Yoshida
Microorganisms 10 ( 7 ) 1417 2022.07
Language：English Publishing type：Research paper (scientific journal)
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Shuuki Takizawa, Akifumi Nishida, Masayuki Yamamura
Ecosphere 13 ( 3 ) 2022.03
Language：English Publishing type：Research paper (scientific journal) Publisher：Wiley
DOI： 10.1002/ecs2.3981
Other Link： https://onlinelibrary.wiley.com/doi/full-xml/10.1002/ecs2.3981
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Determinism of microbial community assembly by drastic environmental change Reviewed
Akifumi Nishida*, Mayuko Nakagawa, Masayuki Yamamura
PLOS ONE 16 ( 12 ) e0260591 - e0260591 2021.12
Authorship：Lead author Language：English Publishing type：Research paper (scientific journal) Publisher：Public Library of Science (PLoS)
Microbial community assembly is shaped by deterministic and stochastic processes, but the relationship between these processes and the environment is not understood. Here we describe a rule for the determinism and stochasticity of microbial community assembly affected by the environment using in silico, in situ, and ex situ experiments. The in silico experiment with a simple mathematical model showed that the existence of essential symbiotic microorganisms caused stochastic microbial community assembly, unless the community was exposed to a non-adapted nutritional concentration. Then, a deterministic assembly occurred due to the low number of microorganisms adapted to the environment. In the in situ experiment in the middle of a river, the microbial community composition was relatively deterministic after the drastic environmental change caused by the treated wastewater contamination, as analyzed by 16S rRNA gene sequencing. Furthermore, by culturing microbial communities collected from the upstream natural area and downstream urban area of the river in test tubes with varying carbon source concentrations, the upstream community assembly became deterministic with high carbon concentrations while the downstream community assembly became deterministic with low carbon concentrations. These results suggest that large environmental changes, which are different from the original environment, result in a deterministic microbial community assembly.
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Satoshi WATANABE, Shoichiro KAMEOKA, Natsuko O. SHINOZAKI, Ryuichi KUBO, Akifumi NISHIDA, Minoru KURIYAMA, Aya K. TAKEDA
Bioscience of Microbiota, Food and Health 40 ( 2 ) 123 - 134 2021.04
Publishing type：Research paper (scientific journal) Publisher：BMFH Press
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Usefulness of Machine Learning-Based Gut Microbiome Analysis for Identifying Patients with Irritable Bowels Syndrome Reviewed
Hirokazu Fukui (co-1st), Akifumi Nishida (co-1st), Satoshi Matsuda, Fumitaka Kira, Satoshi Watanabe, Minoru Kuriyama, Kazuhiko Kawakami, Yoshiko Aikawa, Noritaka Oda, Kenichiro Arai, Atsushi Matsunaga, Masahiko Nonaka, Katsuhiko Nakai, Masao Matsumoto, Shinji Morishita, Aya K. Takeda, Hiroto Miwa
Journal of Clinical Medicine 9(8) ( 2403 ) 2020.07
Authorship：Lead author Language：English Publishing type：Research paper (scientific journal)
DOI： 10.3390/jcm9082403
Scientific Research Funds Acquisition Results 【 display / non-display 】
Other External Funds 【 display / non-display 】
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Cell-free protein snthesis system of non-model bacteria developed by transfer learning
2021.10 - 2023.03
JST ACT-X
Grant type：Competitive
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Mathematical modeling of microbiome ecosystems for elucidating environmental issues
2018.10 - 2019.09
Nippon Life Insurance Foundation Grant for Young Scientists
Nishida Akifumi
Grant type：Competitive
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多摩川の微生物生態系モデル構築による下水処理水の影響や季節変動の解析
2017.09 - 2019.03
とうきゅう環境財団 多摩川およびその流域の環境浄化に関する 基礎研究、応用研究、環境改善計画のための研究・活動助成
西田 暁史、山村雅幸, 西田暁史
Grant type：Competitive
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Elucidation of microbial interspecies and intraspecific interactions during micobial mat formation
2016.04 - 2017.02
The Japan Science Society the Sasakawa Scientific Research Grant
Nishida Akifumi
Grant type：Competitive
Basic stance of industry-university cooperation 【 display / non-display 】
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様々な環境の微生物を網羅的に解析し、モデルで表現することが可能です。ですので、微生物に由来するトラブルがあったときや介入操作したときの影響を明らかにすることができます。
また研究では機械学習や実験計画法を用いているため、効率的にデータを取りモデルを開発することが可能です。