文章基本信息

标题：Modelling Bioprocesses Using Component Profiles in Natural Media, Named “Substratome”, Obtained by Performing Comprehensive Non-Targeted Analysis
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作者：Masaaki Konishi ; Kazuki Watanabe ; Seiga Tachibana 等
期刊名称：MATEC Web of Conferences
电子版ISSN：2261-236X
出版年度：2021
卷号：333
页码：1-4
DOI：10.1051/matecconf/202133307010
语种：English
出版社：EDP Sciences
摘要：Natural media are often used for various commercial bioprocesses by manufacturers to cut raw material cost. However, the components of the raw materials varies between lot-to-lots and brand-to-brands. The varieties of raw materials influence to the cell growths and materials productivities, and results in unstable production across batches in manufacturing processes. To ensure the quality of raw materials among batches, it is necessary to perform a laboratory screening to purchasing the optimal one, and ensure a desirable performance in industrial process. To solve the serious problems in bioprocesses, it is developing that a modelling methodology using composition of raw materials, named us “substratome”, obtained by non-targeted metabolomicslike methods can estimate the cell growth and bio-productions. Here, we will present that two model studies: [1]Escherichia coligrowths have been estimated from hydrophilic components in yeast extract obtained by gas chromatography-mass spectrometry (GC-MS), and [2] bioethanol production have been estimated by the volatile components in corncob and corn stover hydrolysates obtained by GC-MS; by partial least square regression (PLS-R). Additionally, we will present preliminary results to solve the same issues by using artificial intelligence.