Model-driven approach for the production of butyrate from CO2/H2 by a novel co-culture of C. autoethanogenum and C. beijerinckii

Abstract

One-carbon (C1) compounds are promising feedstocks for the sustainable production of commodity chemicals. CO2 is a particularly advantageous C1-feedstock since it is an unwanted industrial off-gas that can be converted into valuable products while reducing its atmospheric levels. Acetogens are microorganisms that can grow on CO2/H2 gas mixtures and syngas converting these substrates into ethanol and acetate. Co-cultivation of acetogens with other microbial species that can further process such products, can expand the variety of products to, for example, medium chain fatty acids (MCFA) and longer chain alcohols. Solventogens are microorganisms known to produce MCFA and alcohols via the acetone-butanol-ethanol (ABE) fermentation in which acetate is a key metabolite. Thus, co-cultivation of an acetogen and a solventogen in a consortium provides a potential platform to produce valuable chemicals from CO2. In this study, metabolic modeling was implemented to design a new co-culture of an acetogen and a solventogen to produce butyrate from CO2/H2 mixtures. The model-driven approach suggested the ability of the studied solventogenic species to grow on lactate/glycerol with acetate as co-substrate. This ability was confirmed experimentally by cultivation of Clostridium beijerinckii on these substrates in batch serum bottles and subsequently in pH-controlled bioreactors. Community modeling also suggested that a novel microbial consortium consisting of the acetogen Clostridium autoethanogenum, and the solventogen C. beijerinckii would be feasible and stable. On the basis of this prediction, a co-culture was experimentally established. C. autoethanogenum grew on CO2/H2 producing acetate and traces of ethanol. Acetate was in turn, consumed by C. beijerinckii together with lactate, producing butyrate. These results show that community modeling of metabolism is a valuable tool to guide the design of microbial consortia for the tailored production of chemicals from renewable resources.

A structured evaluation of genome-scale constraint-based modeling tools for microbial consortia

“…The applicability of these tools to non-model organisms is critical for designing and optimizing synthetic communities. In the past decades, many synthetic communities have been established that do not depend on model organisms and have shown a high potential for producing commodity chemicals [4,[88][89][90][91]. On the other hand, GEMs require accurate genome annotation and curation to properly account for interactions mediated through pathways, but there is still difficulty identifying these components in microbial genomes.…”

“…Because metabolic traits are also a central determinant of ecological interactions in microbes (e.g. competition for resources or metabolite sharing), CBM also holds great promise as a predictive and an engineering tool in synthetic ecology [ 4 ]. In a nutshell, CBM use genome-scale metabolic models (GEMs), a mathematical representation of the metabolic network encoded in an organism’s genome, to simulate metabolic fluxes in a given environment [ 28 ].…”

“…Recent years have seen a soar in the use of multi-species microbial consortia beyond their traditional application in the production of food and beverages [1,2]. For example, microbial consortia are increasingly applied in the production of commodity chemicals [3,4], pharmaceuticals [5], or biofuels [6][7][8]; the valorization of waste and emissions [9][10][11], the improvement of sustainable agriculture systems [12][13][14], and applications in health [15] or bioremediation [16][17][18]. Besides the obvious advantage over established industrial processes in terms of sustainability, multi-species consortia offer a number of advantages compared to monocultures.…”

A structured evaluation of genome-scale constraint-based modeling tools for microbial consortia

“…Because metabolic traits are also a central determinant of ecological interactions in microbes (e.g. competition for resources or metabolite sharing), CBM also holds great promise as a predictive and an engineering tool in synthetic ecology [28]. In a nutshell, CBMs use genome-scale metabolic models (GEMs), a mathematical representation of the metabolic network encoded in an organism's genome, to simulate metabolic fluxes in a given environment [29].…”

Synthetic microbial communities for syngas-driven odd-chain elongation

“…The tri-culture model was generated by combining the single species models of each strain: iAWJM_ SB617 (this work), iANEO_607 (Benito-Vaquerizo et al, 2022b) and iCKL708 (Zou et al, 2018), for A. wieringae JM, A. neopropionicum and C. kluyveri, respectively. The methodology followed was the same as reported in our previous studies Benito-Vaquerizo et al, 2022a) and is summarised in Suppl. material § 5.6.1.…”