Sastia Prama Putri1, Yasumune Nakayama2,3, Claire Shen4,5, Shingo Noguchi2,6, Katsuaki Nitta2, Takeshi Bamba2,7, Sammy Pontrelli5, James Liao5, Eiichiro Fukusaki2. 1. Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan. sastia_putri@bio.eng.osaka-u.ac.jp. 2. Department of Biotechnology, Graduate School of Engineering, Osaka University, 2-1 Yamadaoka, Suita, Osaka, 565-0871, Japan. 3. Department of Applied Microbial Technology, Sojo University, 4-22-1 Ikeda, Kumamoto, 860-0082, Japan. 4. Department of Chemical Engineering, National Tsing Hua University, Hsinchu, 300, Taiwan, Republic of China. 5. Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, 5531 Boelter Hall, 420 Westwood Plaza, Los Angeles, CA, 90095, USA. 6. Drug Metabolism & Pharmacokinetics Research Laboratories, R&D Division, Daiichi Sankyo Co., Ltd., Shinagawa R&D Center, 1-2-58, Hiromachi, Shinagawa-ku, Tokyo, 140-8710, Japan. 7. Research Center for Transomics Medicine, Medical Institute of Bioregulation, Kyushu University, 3-1-1 Maidashi, Higashi-ku, Fukuoka, Fukuoka, 812-8285, Japan.
Abstract
INTRODUCTION: Previously constructed Escherichia coli strains that produce 1-propanol use the native threonine pathway, or a heterologous citramalate pathway. However, based on the energy and cofactor requirements of each pathway, a combination of the two pathways produces synergistic effects that increase the theoretical maximum yield with a simultaneous unexplained increase in productivity. OBJECTIVE: Identification of key factors that contribute to synergistic effect leading to 1-propanol yield and productivity improvement in E. coli with native threonine pathway and heterologous citramalate pathway. METHOD: A combination of snapshot metabolomic profiling and dynamic metabolic turnover analysis were used to identify system-wide perturbations that contribute to the productivity improvement. RESULT AND CONCLUSION: In the presence of both pathways, increased glucose consumption and elevated levels of glycolytic intermediates are attributed to an elevated phosphoenolpyruvate (PEP)/pyruvate ratio that is known to increase the function of the native phosphotransferase. Turnover analysis of nitrogen containing byproducts reveals that ammonia assimilation, required for the threonine pathway, is streamlined when provided with an NAD(P)H surplus in the presence of the citramalate pathway. Our study illustrates the application of metabolomics in identification of factors that alter cellular physiology for improvement of 1-propanol bioproduction.
INTRODUCTION: Previously constructed Escherichia coli strains that produce 1-propanol use the native threonine pathway, or a heterologous citramalate pathway. However, based on the energy and cofactor requirements of each pathway, a combination of the two pathways produces synergistic effects that increase the theoretical maximum yield with a simultaneous unexplained increase in productivity. OBJECTIVE: Identification of key factors that contribute to synergistic effect leading to 1-propanol yield and productivity improvement in E. coli with native threonine pathway and heterologous citramalate pathway. METHOD: A combination of snapshot metabolomic profiling and dynamic metabolic turnover analysis were used to identify system-wide perturbations that contribute to the productivity improvement. RESULT AND CONCLUSION: In the presence of both pathways, increased glucose consumption and elevated levels of glycolytic intermediates are attributed to an elevated phosphoenolpyruvate (PEP)/pyruvate ratio that is known to increase the function of the native phosphotransferase. Turnover analysis of nitrogen containing byproducts reveals that ammonia assimilation, required for the threonine pathway, is streamlined when provided with an NAD(P)H surplus in the presence of the citramalate pathway. Our study illustrates the application of metabolomics in identification of factors that alter cellular physiology for improvement of 1-propanol bioproduction.
Authors: Toshiyuki Ohtake; Sammy Pontrelli; Walter A Laviña; James C Liao; Sastia P Putri; Eiichiro Fukusaki Journal: Metab Eng Date: 2017-04-08 Impact factor: 9.783
Authors: Shota Atsumi; Anthony F Cann; Michael R Connor; Claire R Shen; Kevin M Smith; Mark P Brynildsen; Katherine J Y Chou; Taizo Hanai; James C Liao Journal: Metab Eng Date: 2007-09-14 Impact factor: 9.783
Authors: Nicholas D Gold; Christopher M Gowen; Francois-Xavier Lussier; Sarat C Cautha; Radhakrishnan Mahadevan; Vincent J J Martin Journal: Microb Cell Fact Date: 2015-05-28 Impact factor: 5.328
Authors: Toshiyuki Ohtake; Naoki Kawase; Sammy Pontrelli; Katsuaki Nitta; Walter A Laviña; Claire R Shen; Sastia P Putri; James C Liao; Eiichiro Fukusaki Journal: Front Microbiol Date: 2022-04-14 Impact factor: 5.640