Enhancing CO2-Valorization Using Clostridium autoethanogenum for Sustainable Fuel and Chemicals Production

Abstract

Acetogenic bacteria can convert waste gases into fuels and chemicals. Design of bioprocesses for waste carbon valorization requires quantification of steady-state carbon flows. Here, steady-state quantification of autotrophic chemostats containing Clostridium autoethanogenum grown on CO₂ and H₂ revealed that captured carbon (460 ± 80 mmol/gDCW/day) had a significant distribution to ethanol (54 ± 3 C-mol% with a 2.4 ± 0.3 g/L titer). We were impressed with this initial result, but also observed limitations to biomass concentration and growth rate. Metabolic modeling predicted culture performance and indicated significant metabolic adjustments when compared to fermentation with CO as the carbon source. Moreover, modeling highlighted flux to pyruvate, and subsequently reduced ferredoxin, as a target for improving CO₂ and H₂ fermentation. Supplementation with a small amount of CO enabled co-utilization with CO₂, and enhanced CO₂ fermentation performance significantly, while maintaining an industrially relevant product profile. Additionally, the highest specific flux through the Wood-Ljungdahl pathway was observed during co-utilization of CO₂ and CO. Furthermore, the addition of CO led to superior CO₂-valorizing characteristics (9.7 ± 0.4 g/L ethanol with a 66 ± 2 C-mol% distribution, and 540 ± 20 mmol CO₂/gDCW/day). Similar industrial processes are commercial or currently being scaled up, indicating CO-supplemented CO₂ and H₂ fermentation has high potential for sustainable fuel and chemical production. This work also provides a reference dataset to advance our understanding of CO₂ gas fermentation, which can contribute to mitigating climate change.

Keywords: Clostridium autoethanogenum; carbon dioxide; carbon recycling; fuel and chemical platforms; gas fermentation; valorization.

Figure 1

Important fermentation characteristics of Clostridium autoethanogenum in autotrophic chemostats. Results from Valgepea et al. (2018) are also displayed (B–D), the conditions of all fermentations are summarized in Table 1. Growth curves of novel fermentations with standard deviation at steady-state (A). Specific rates of uptake (B) and production (C) for important metabolites. Product carbon balances (D). Values represent the average ± standard deviation between biological replicates. Number of biological replicates, and detailed gas composition for each fermentation are available in Table 1. Patterned bars indicate a D of 1 day⁻¹, full bars indicate a D of 0.5 day⁻¹ (B–D). q, specific rate; DCW, dry cell weight.

Figure 2

Intracellular metabolic fluxes in Clostridium autoethanogenum growing on various gas mixes, estimated using the metabolic model iCLAU786 and flux balance analysis. Bar charts show specific flux rates (mmol/gDCW/h) from Tables S10, S11 and represent the average ± standard deviation between biological Replicates from SIM: 1–4 (CO), 9–10 (Syngas), 13–15 (CO/H₂), 20–21 (CO/CO₂/${\text{H}}_{2^1}$), 22–24 (CO₂/H₂), and 25–26 (CO/CO₂/${\text{H}}_{2^{0.5}}$). Results for CO, syngas, and CO/H₂ are low biomass condition data from Valgepea et al. (2018), the conditions of these fermentations are summarized in Table 1. Number of biological replicates, and detailed gas composition for each fermentation are available in Table 1. Arrows show the direction of calculated fluxes; red arrows denote uptake or secretion, dashed arrows denote a series of reactions. Brackets denote metabolites bound by an enzyme. Refer to Figures S1, S2 for enzyme involvement, metabolite abbreviations, and complete flux balance analysis datasets.