Modeling a co-culture of Clostridium autoethanogenum and Clostridium kluyveri to increase syngas conversion to medium-chain fatty-acids.

Research output: Working paper

Abstract

Microbial fermentation of synthesis gas (syngas) is becoming more attractive for sustainable production of commodity chemicals. To date, syngas fermentation focuses mainly on the use of Clostridium species for the production of small organic molecules such as ethanol and acetate. The co-cultivation of syngas-fermenting microorganisms with chain-elongating bacteria can expand the range of possible products, allowing, for instance, the production of medium-chain fatty acids (MCFA) and alcohols from syngas. To explore these possibilities, we report herein a genome-scale, constraint-based metabolic model to describe growth of a co-culture of Clostridium autoethanogenum and Clostridium kluyveri on syngas for the production of valuable compounds. Community flux balance analysis was used to gain insight into the metabolism of the two strains and their interactions, and to reveal potential strategies enabling production of butyrate and hexanoate. The model suggests that one strategy to optimize the production of medium-chain fatty-acids from syngas would be the addition of succinate. According to the prediction, addition of succinate would increase the pool of crotonyl-CoA and the ethanol/acetate uptake ratio in C. kluyveri, resulting in a flux of up to 60 of electrons into hexanoate. Another potential way to further optimize butyrate and hexanoate production would be an increase of C. autoethanogenum ethanol production. Blocking either acetaldehyde dehydrogenase or formate dehydrogenase (ferredoxin) activity or formate transport, in the C. autoethanogenum metabolic model could potentially lead to an up to 150 increase in ethanol production.
Original languageEnglish
PublisherBioRxiv
DOIs
Publication statusPublished - 16 Oct 2020

Keywords

  • Syngas fermentationMulti-species GEMClostridium autoethanogenum Clostridium kluyveriCommunity flux balance analysis

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