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Integration of parallel 13 C‐labeling experiments and in silico pathway analysis for enhanced production of ascomycin
Author(s) -
Qi Haishan,
Lv Mengmeng,
Song Kejing,
Wen Jianping
Publication year - 2017
Publication title -
biotechnology and bioengineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.136
H-Index - 189
eISSN - 1097-0290
pISSN - 0006-3592
DOI - 10.1002/bit.26223
Subject(s) - in silico , flux (metallurgy) , mutant , strain (injury) , flux balance analysis , metabolic engineering , metabolic flux analysis , biology , chemistry , computational biology , biochemistry , gene , metabolism , organic chemistry , anatomy
Herein, the hyper‐producing strain for ascomycin was engineered based on 13 C‐labeling experiments and elementary flux modes analysis (EFMA). First, the metabolism of non‐model organism Streptomyces hygroscopicus var . ascomyceticus SA68 was investigated and an updated network model was reconstructed using 13 C‐ metabolic flux analysis. Based on the precise model, EFMA was further employed to predict genetic targets for higher ascomycin production. Chorismatase (FkbO) and pyruvate carboxylase (Pyc) were predicted as the promising overexpression and deletion targets, respectively. The corresponding mutant TD‐FkbO and TD‐ΔPyc exhibited the consistency effects between model prediction and experimental results. Finally, the combined genetic manipulations were performed, achieving a high‐yield ascomycin engineering strain TD‐ΔPyc‐FkbO with production up to 610 mg/L, 84.8% improvement compared with the parent strain SA68. These results manifested that the integration of 13 C‐labeling experiments and in silico pathway analysis could serve as a promising concept to enhance ascomycin production, as well as other valuable products. Biotechnol. Bioeng. 2017;114: 1036–1044. © 2016 Wiley Periodicals, Inc.