Elsevier

Metabolic Engineering

Volume 41, May 2017, Pages 135-143
Metabolic Engineering

Metabolomics-driven approach to solving a CoA imbalance for improved 1-butanol production in Escherichia coli

https://doi.org/10.1016/j.ymben.2017.04.003Get rights and content

Highlights

  • Improvement of 1-butanol production in E. coli was done by resolving CoA imbalance.

  • Fine-tuning AdhE2 expression with cysteine addition achieved 18.3 g/L 1-butanol titer.

  • Metabolomics-driven approach can be used to optimize the 1-butanol producing E. coli.

Abstract

High titer 1-butanol production in Escherichia coli has previously been achieved by overexpression of a modified clostridial 1-butanol production pathway and subsequent deletion of native fermentation pathways. This strategy couples growth with production as 1-butanol pathway offers the only available terminal electron acceptors required for growth in anaerobic conditions. With further inclusion of other well-established metabolic engineering principles, a titer of 15 g/L has been obtained. In achieving this titer, many currently existing strategies have been exhausted, and 1-butanol toxicity level has been surpassed. Therefore, continued engineering of the host strain for increased production requires implementation of alternative strategies that seek to identify non-obvious targets for improvement. In this study, a metabolomics-driven approach was used to reveal a CoA imbalance resulting from a pta deletion that caused undesirable accumulation of pyruvate, butanoate, and other CoA-derived compounds. Using metabolomics, the reduction of butanoyl-CoA to butanal catalyzed by alcohol dehydrogenase AdhE2 was determined as a rate-limiting step. Fine-tuning of this activity and subsequent release of free CoA restored the CoA balance that resulted in a titer of 18.3 g/L upon improvement of total free CoA levels using cysteine supplementation. By enhancing AdhE2 activity, carbon flux was directed towards 1-butanol production and undesirable accumulation of pyruvate and butanoate was diminished. This study represents the initial report describing the improvement of 1-butanol production in E. coli by resolving CoA imbalance, which was based on metabolome analysis and rational metabolic engineering strategies.

Introduction

As an important bulk chemical and potential biofuel, 1-butanol biosynthesis from microorganisms has attracted much attention. The clostridial CoA-dependent 1-butanol pathway has been successfully transferred to well-characterized and genetically tractable organisms such as Escherichia coli for further engineering and improvement of 1-butanol production (Atsumi et al., 2008, Bond-watts et al., 2011, Inui et al., 2008, Lan and Liao, 2012, Lim et al., 2013, Shen et al., 2011). Previously, 15 g/L of 1-butanol was produced within engineered E.coli by deletion of fermentative pathways, thereby requiring the use of the 1-butanol pathway as the sole NADH sink under anaerobic conditions (Shen et al., 2011). While this strategy yielded 1-butanol that is regarded as one of the highest biofuel production to date, (Baez et al., 2011, Friedlander et al., 2016, Inokuma et al., 2010, Pais et al., 2013, Wernick et al., 2016, York and Ingram, 1996) improved titers are desired. In addition to the deletion of NADH consuming pathways, many other metabolic engineering strategies have been applied in order to achieve such high titers. Furthermore, current titers extend beyond toxicity levels. Therefore, more innovative strategies need to be employed in order to further identify non-obvious targets that may be improved to increase 1-butanol production.

Metabolomics stands as a tool with great potential for strain engineering to obtain a desired phenotype. Metabolomics, the comprehensive analysis of a wide range of metabolites, has the ability to provide a dynamic and holistic understanding of how the implementation of a metabolic pathway affects the cellular metabolism in a broader sense. Metabolomics therefore may be used to complement current metabolic engineering strategies for optimizing biological production of chemicals within microorganisms (Oldiges et al., 2007, Putri et al., 2013). Through the detection of relevant metabolic perturbations, metabolomics can identify specific targets for strain improvement that may include detection of pathway bottlenecks, metabolite or product toxicity, imbalanced cofactor supply, or draining of metabolites by alternative pathways (Gold et al., 2015, Hasunuma et al., 2011, Korneli et al., 2012, Noguchi et al., 2016, Ohta et al., 2015, Teoh et al., 2015, Xu et al., 2016). Furthermore, metabolomics provides a comprehensive analysis of the metabolome that allows a deeper understanding of cellular metabolism and how gene modifications can be used for metabolic engineering. Therefore, a metabolomics-driven approach can be a powerful tool in generating strategies to enhance desired phenotypes.

A previously engineered 1-butanol producing E. coli strain with deleted phosphate acetyltransferase (pta), JCL299F, resulted in the highest improvement of 1-butanol titer by blocking acetate by-product formation and increasing flux through the 1-butanol pathway (Shen et al., 2011). While exhibiting high production titers, this strain has presented a number of metabolic perturbations that remain as targets for further engineering. In this study, we demonstrate the utility of a metabolomics-driven approach to optimize further the engineered 1-butanol producing E. coli strain, JCL299F, by revealing unexpected metabolic changes and identifying rate-limiting reactions within the strain. Consequently, these insights served as the basis for succeeding metabolic engineering strategies. Ultimately, successful engineering of the 1-butanol pathway to overcome this imbalance improved the production and resulted in a titer of 18.3 g/L.

Section snippets

Bacterial strains and plasmids

Escherichia coli strains and plasmids used in this study are summarized in Table 1. Primers were purchased through Integrated DNA Technologies (Coralville, IA, USA). All PCR reactions were performed with KOD Hot-Start DNA polymerase or KOD Xtreme Hot-Start Polymerase (Millipore, MA, USA). Gel purification, DpnI digestion, and PCR Clean (Zymo Research, CA, USA) were used to isolate and purify the correct amplicons. Assembly of fragments was performed using T4 DNA polymerase (New England Biolabs,

Metabolome analysis reveals a CoA imbalance

Previously, Shen et al. (2011) successfully engineered E. coli to produce 1-butanol with a titer of 15 g/L through deletion of NADH consuming pathways. This effectively created an NADH driving force that greatly enhanced production of 1-butanol in anaerobic conditions. Thus, the engineered E. coli strain (ΔldhA, ΔadhE, ΔfrdBC, Δpta) expressing the modified heterologous clostridial 1-butanol pathway (fdh, atoB, hbd, crt, ter and adhE2) hereinafter called JCL299F was used in this study as a

Discussion

In the previous work, anaerobic production of 1-butanol was enabled by establishing an NADH driving force, which relied on the production of 1-butanol as the sole electron sink for fermentation. Key to the high titer 1-butanol production of JCL299F was a pta deletion, which blocked degradation of acetyl-CoA into acetate. Simultaneously, metabolome analysis found that it caused a pathway imbalance by preventing release of CoA and identified the rate-limiting AdhE2 reaction (reduction of

Conclusions

Metabolomics, the comprehensive profiling of metabolites in the biological sample, allows the detection of complex biological changes using chemometrics. Metabolomics has been proven to strongly complement other “omics” and has essential applications in various fields such as functional genomics, medical science and food science. In metabolic engineering, metabolomics can be employed to search for rate-limiting steps and detect metabolic changes in samples such as metabolite toxicity and

Acknowledgements

This research was fully supported by Japan Science and Technology (JST), Strategic International Collaborative Research Program, SICORP for JP-US Metabolomics and National Science Foundation (NSF) MCB-1139318.

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