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Experimental validation of in silico estimated biomass yields of Pseudomonas putida KT2440
Author(s) -
Hintermayer Sarah Beate,
WeusterBotz Dirk
Publication year - 2017
Publication title -
biotechnology journal
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.144
H-Index - 84
eISSN - 1860-7314
pISSN - 1860-6768
DOI - 10.1002/biot.201600720
Subject(s) - pseudomonas putida , in silico , flux balance analysis , biomass (ecology) , glycerol , carbon fibers , biology , food science , chemistry , biochemistry , gene , materials science , ecology , composite number , composite material
Abstract Pseudomonas putida is rapidly becoming a microbial cell platform for biotechnological applications. In order to understand genotype‐phenotype relationships genome scale models represent helpful tools. However, the validation of in silico predictions of genome scale models is a task that is rarely performed. In this study the theoretical biomass yields of Pseudomonas putida KT2440 were estimated for 57 different carbon sources based on a genome scale stoichiometric model applying flux balance analysis. The batch growth of P. putida KT2440 with six individual carbon sources covering the range of maximal to minimal in silico biomass yields (acetate, glycerol, citrate, succinate, malate and methanol, respectively) was studied in a defined mineral medium in a fully controlled stirred‐tank bioreactor on a 3 L scale. The highest growth rate of P. putida KT2440 was measured with succinate as carbon source (0.51 h −1 ). Among the 57 carbon sources tested, glycerol resulted in the highest estimated biomass yield (0.61 molC Biomass molC −1 Glycerol ) which was experimentally confirmed. The comparison of experimental determined biomass yields with a modified version of the model iJP815 showed deviations of only up to 10%. The experimental data generated in this study can also be used in future studies to further improve the genome scale models of P. putida KT2440. Improved models will then help to gain deeper insights in genotype‐phenotype relationships.