Experimental testing of a spatiotemporal metabolic model for carbon monoxide fermentation with Clostridium autoethanogenum

Acetic acid, growth rate, and mass transfer govern shifts in CO metabolism of Clostridium autoethanogenum

Syngas fermentation is a leading microbial process for the conversion of carbon monoxide, carbon dioxide, and hydrogen to valuable biochemicals. Clostridium autoethanogenum stands as a model organism for this process, showcasing its ability to convert syngas into ethanol industrially with simultaneous fixation of carbon and reduction of greenhouse gas emissions. A deep understanding on the metabolism of this microorganism and the influence of operational conditions on fermentation performance is key to advance the technology and enhancement of production yields. In this work, we studied the individual impact of acetic acid concentration, growth rate, and mass transfer rate on metabolic shifts, product titres, and rates in CO fermentation by C. autoethanogenum. Through continuous fermentations performed at a low mass transfer rate, we measured the production of formate in addition to acetate and ethanol. We hypothesise that low mass transfer results in low CO concentrations, leading to reduced activity of the Wood-Ljungdahl pathway and a bottleneck in formate conversion, thereby resulting in the accumulation of formate. The supplementation of the medium with exogenous acetate revealed that undissociated acetic acid concentration increases and governs ethanol yield and production rates, assumedly to counteract the inhibition by undissociated acetic acid. Since acetic acid concentration is determined by growth rate (via dilution rate), mass transfer rate, and working pH, these variables jointly determine ethanol production rates. These findings have significant implications for process optimisation as targeting an optimal undissociated acetic acid concentration can shift metabolism towards ethanol production. KEY POINTS: • Very low CO mass transfer rate leads to leaking of intermediate metabolite formate. • Undissociated acetic acid concentration governs ethanol yield on CO and productivity. • Impact of growth rate, mass transfer rate, and pH were considered jointly.

Overflow metabolism at the thermodynamic limit of life: How carboxydotrophic acetogens mitigate carbon monoxide toxicity

Carboxydotrophic metabolism is gaining interest due to its applications in gas fermentation technology, enabling the conversion of carbon monoxide to fuels and commodities. Acetogenic carboxydotrophs play a central role in current gas fermentation processes. In contrast to other energy-rich microbial substrates, CO is highly toxic, which makes it a challenging substrate to utilize. Instantaneous scavenging of CO upon entering the cell is required to mitigate its toxicity. Experiments conducted with Clostridium autoethanogenum at different biomass-specific growth rates show that elevated ethanol production occurs at increasing growth rates. The increased allocation of electrons towards ethanol at higher growth rates strongly suggests that C. autoethanogenum employs a form of overflow metabolism to cope with high dissolved CO concentrations. We argue that this overflow branch enables acetogens to efficiently use CO at highly variable substrate influxes by increasing the conversion rate almost instantaneously when required to remove toxic substrate and promote growth. In this perspective, we will address the case study of C. autoethanogenum grown solely on CO and syngas mixtures to assess how it employs acetate reduction to ethanol as a form of overflow metabolism.

Effects of Fishmeal Replacement by Clostridium Autoethanogenum Protein Meal on Cholesterol Bile Acid Metabolism, Antioxidant Capacity, Hepatic and Intestinal Health of Pearl Gentian Grouper (Epinephelus Fuscoguttatus ♀ × Epinephelus Lanceolatus ♂)

In this study, we present data from an eight-week growth trial with pearl gentian grouper fed either a reference diet (FM) with a fishmeal level of 50%, or test diet wherein 15% (CAP15), 30% (CAP30), 45% (CAP45), and 60% (CAP60) fishmeal was replaced by Clostridium autoethanogenum protein meal (CAP). Results showed that the weight gain and daily feed intake ratio of CAP60 were significantly lower than the FM group. In the serum, compared to the FM group, the content of malondialdehyde (MDA), the activities of alanine aminotransferase in CAP60 and CAP45 groups, and acid phosphatase in the CAP60 group were significantly higher, while the content of total cholesterol in CAP60 and CAP45 groups was significantly lower. In the liver, compared to the control group, the content of MDA in the CAP60 group was significantly higher. 3-hydroxy-3-methylglutaryl coenzyme A reductase in CAP30 to CAP60 groups and farnesoid X receptor in CAP60 were significantly upregulated. In distal intestines, the activities of trypsin and superoxide dismutase of CAP30 to CAP60 groups were significantly lower than the FM group. In conclusion, for pearl gentian grouper, CAP could replace up to 45% of the fishmeal in the feed, while a 60% replacement level will affect cholesterol bile acid metabolism and health.

Design and evaluation of gas fermentation systems for CO2 reduction to C2 and C4 fatty acids: Non-genetic metabolic regulation with pressure, pH and reaction time

Addressing the carbon emissions through microbial mediated fermentation is an emerging interest. Custom designed and fabricated gas fermentation (GF) systems were evaluated to optimize the headspace pressure, pH (6.5, 7.5, and 8.5), fermentation time, and substrate concentration by employing enriched homoacetogenic chemolithoautotrophs in non-genetic approach. Headspace pressure showed marked influence on the metabolic conversion of inorganic carbon to acetic and butyric acids with 26% higher productivity than the control (atmospheric pressure). Maximum volatile fatty acid (VFA) yield of 3.7 g/L was observed at alkaline pH (8.5) under 2 bar pressure at carbon load of 10 g/L, 96 h). Acetic (3.0 g/L) and butyric (0.7 g/L) acids were the major products upon conversion of 85% of the inorganic substrate. A better in-situ buffering (β = 0.048) at pH 8.5 along with higher reductive current (RCC: -4.4 mA) depicted better performance of GF towards CO₂ reduction.

Determining global trends in syngas fermentation research through a bibliometric analysis

Syngas fermentation, in which microorganisms convert H₂, CO, and CO₂ to acids and alcohols, is a promising alternative for carbon cycling and valorization. The intellectual landscape of the topic was characterized through a bibliometric analysis using a search query (SQ) that included all relevant documents on syngas fermentation available through the Web of Science database up to December 31st, 2021. The SQ was validated with a preliminary analysis in bibliometrix and a review of titles and abstracts of all sources. Although syngas fermentation began in the early 1980s, it grew rapidly beginning in 2008, with 92.5% of total publications and 87.3% of total citations from 2008 to 2021. The field has been steadily moving from fundamentals towards applications, suggesting that the field is maturing scientifically. The greatest number of publications and citations are from the USA, and researchers in China, Germany, and Spain also are highly active. Although collaborations have increased in the past few years, author-cluster analysis shows specialized research domains with little collaboration between groups. Based on topic trends, the main challenges to be address are related to mass-transfer limitations, and researchers are starting to explore mixed cultures, genetic engineering, microbial chain elongation, and biorefineries.

Analytical tools for unravelling the metabolism of gas-fermenting Clostridia

Acetogens harness the Wood-Ljungdahl Pathway, a unique metabolic pathway for C1 capture close to the thermodynamic limit. Gas fermentation using acetogens is already used for CO-to-ethanol conversion at industrial-scale and has the potential to valorise a range of C1 and waste substrates to short-chain and medium-chain carboxylic acids and alcohols. Advances in analytical quantification and metabolic modelling have helped guide industrial gas fermentation designs. Further advances in the measurements of difficult to measure metabolites are required to improve kinetic modelling and understand the regulation of acetogen metabolism. This will help guide future synthetic biology designs needed to realise the full potential of gas fermentation in stimulating a circular bioeconomy.

Dynamic metabolic modelling predicts efficient acetogen-gut bacterium cocultures for CO-to-butyrate conversion

AIMS

While gas-fermenting acetogens have been engineered to secrete non-native metabolites such as butyrate, acetate remains the most thermodynamically favourable product. An alternative to metabolic engineering is to exploit native capabilities for CO-to-acetate conversion by coculturing an acetogen with a second bacterium that provides efficient acetate-butyrate conversion.

METHODS AND RESULTS

We used dynamic metabolic modelling to computationally evaluate the CO-to-butyrate conversion capabilities of candidate coculture systems by exploiting the diversity of human gut bacteria for anaerobic synthesis of butyrate from acetate and ethanol. A preliminary screening procedure based on flux balance analysis was developed to identify 48 gut bacteria which satisfied minimal growth rate and acetate-to-butyrate conversion requirements when cultured on minimal medium containing acetate and a simple sugar not consumed by the paired acetogen. A total of 170 acetogen/gut bacterium/sugar combinations were dynamically simulated for continuous growth using a 70/30 CO/CO₂ feed gas mixture and minimal medium computationally determined for each combination.

CONCLUSIONS

While coculture systems involving the acetogens Eubacterium limosum or Blautia producta yielded low butyrate productivities and CO-to-ethanol conversion had minimal impact on system performance, dynamic simulations predicted a large number of promising coculture designs with Clostridium ljungdahlii or C. autoethanogenum as the CO-to-acetate converter. Pairings with the gut bacterium Clostridium hylemonae or Roseburia hominis were particularly promising due to their ability to generate high butyrate productivities over a range of dilution rates with a variety of sugars. The higher specific acetate secretion rate of C. ljungdahlii proved more beneficial than the elevated growth rate of C. autoethanogenum for coculture butyrate productivity.

SIGNIFICANCE AND IMPACT OF THE STUDY

Our study demonstrated that metabolic modelling could provide useful insights into coculture design that can guide future experimental studies. More specifically, our predictions generated several favourable designs, which could serve as the first coculture systems realized experimentally.

The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes

For over 10 years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical 'Rosetta Stone' to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org/biochem and KBase.

The ModelSEED Biochemistry Database for the integration of metabolic annotations and the reconstruction, comparison and analysis of metabolic models for plants, fungi and microbes

For over ten years, ModelSEED has been a primary resource for the construction of draft genome-scale metabolic models based on annotated microbial or plant genomes. Now being released, the biochemistry database serves as the foundation of biochemical data underlying ModelSEED and KBase. The biochemistry database embodies several properties that, taken together, distinguish it from other published biochemistry resources by: (i) including compartmentalization, transport reactions, charged molecules and proton balancing on reactions;; (ii) being extensible by the user community, with all data stored in GitHub; and (iii) design as a biochemical “Rosetta Stone” to facilitate comparison and integration of annotations from many different tools and databases. The database was constructed by combining chemical data from many resources, applying standard transformations, identifying redundancies, and computing thermodynamic properties. The ModelSEED biochemistry is continually tested using flux balance analysis to ensure the biochemical network is modeling-ready and capable of simulating diverse phenotypes. Ontologies can be designed to aid in comparing and reconciling metabolic reconstructions that differ in how they represent various metabolic pathways. ModelSEED now includes 33,978 compounds and 36,645 reactions, available as a set of extensible files on GitHub, and available to search at https://modelseed.org and KBase.

Synergistically applying 1-D modeling and CFD for designing industrial scale bubble column syngas bioreactors

The reduction of greenhouse gas emissions and future perspectives of circular economy ask for new solutions to produce commodities and fine chemicals. Large-scale bubble columns operated by gaseous substrates such as CO, CO2, and H2 to feed acetogens for product formations could be promising approaches. Valid in silico predictions of large-scale performance are needed to dimension bioreactors properly taking into account biological constraints, too. This contribution deals with the trade-off between sophisticated spatiotemporally resolved large-scale simulations using computationally intensive Euler-Euler and Euler-Lagrange approaches and coarse-grained 1-D models enabling fast performance evaluations. It is shown that proper consideration of gas hold-up is key to predict biological performance. Intrinsic bias of 1-D models can be compensated by reconsideration of Sauter diameters derived from uniquely performed Euler-Lagrange computational fluid dynamics.

Metabolic modeling of bacterial co-culture systems predicts enhanced carbon monoxide-to-butyrate conversion compared to monoculture systems

We used metabolic modeling to computationally investigate the potential of bacterial coculture system designs for CO conversion to the platform chemical butyrate. By taking advantage of the native capabilities of wild-type strains, we developed two anaerobic coculture designs by combining Clostridium autoethanogenum for CO-to-acetate conversion with bacterial strains that offer high acetate-to-butyrate conversion capabilities: the environmental bacterium the human gut bacteriumEubacterium rectale. When grown in continuous stirred tank reactor on a 70/0/30 CO/H₂/N₂ gas mixture, the C. autoethanogenum-C Kluyveri co-culture was predicted to offer no mprovement in butyrate volumetric productivity compared to an engineered C. autoethanogenum monoculture despite utilizing vinyl acetate as a secondary carbon source for C. kluyveri growth enhancement. A coculture consisting of C. autoethanogenum and C. kluyveri engineered in silico to eliminate hexanoate synthesis was predicted to enhance both butyrate productivity and titer. The C. autoethanogenum-E. rectale coculture offered similar improvements in butyrate productivity without the need for metabolic engineering when glucose was provided as a secondary carbon source to enhance E. rectale growth. A bubble column model developed to assess the potential for large-scale butyrate production of the C. autoethanogenum-E. rectale design predicted that a 40/30/30 CO/H₂/N₂ gas mixture and a 5 m column length would be preferred to enhance C. autoethanogenum growth and counteract CO inhibitory effects on E. rectale.

Dynamic modeling of syngas fermentation in a continuous stirred-tank reactor: Multi-response parameter estimation and process optimization

Syngas fermentation is one of the bets for the future sustainable biobased economies due to its potential as an intermediate step in the conversion of waste carbon to ethanol fuel and other chemicals. Integrated with gasification and suitable downstream processing, it may constitute an efficient and competitive route for the valorization of various waste materials, especially if systems engineering principles are employed targeting process optimization. In this study, a dynamic multi‐response model is presented for syngas fermentation with acetogenic bacteria in a continuous stirred‐tank reactor, accounting for gas–liquid mass transfer, substrate (CO, H₂) uptake, biomass growth and death, acetic acid reassimilation, and product selectivity. The unknown parameters were estimated from literature data using the maximum likelihood principle with a multi‐response nonlinear modeling framework and metaheuristic optimization, and model adequacy was verified with statistical analysis via generation of confidence intervals as well as parameter significance tests. The model was then used to study the effects of process conditions (gas composition, dilution rate, gas flow rates, and cell recycle) as well as the sensitivity of kinetic parameters, and multiobjective genetic algorithm was used to maximize ethanol productivity and CO conversion. It was observed that these two objectives were clearly conflicting when CO‐rich gas was used, but increasing the content of H₂ favored higher productivities while maintaining 100% CO conversion. The maximum productivity predicted with full conversion was 2 g·L⁻¹·hr⁻¹ with a feed gas composition of 54% CO and 46% H₂ and a dilution rate of 0.06 hr⁻¹ with roughly 90% of cell recycle.

Incorporating hydrodynamics into spatiotemporal metabolic models of bubble column gas fermentation

Gas fermentation has emerged as a technologically and economically attractive option for producing renewable fuels and chemicals from carbon monoxide (CO) rich waste streams. LanzaTech has developed a proprietary strain of the gas fermentating acetogen Clostridium autoethanogenum as a microbial platform for synthesizing ethanol, 2,3-butanediol, and other chemicals. Bubble column reactor technology is being developed for the large-scale production, motivating the investigation of multiphase reactor hydrodynamics. In this study, we combined hydrodynamics with a genome-scale reconstruction of C. autoethanogenum metabolism and multiphase convection-dispersion equations to compare the performance of bubble column reactors with and without liquid recycle. For both reactor configurations, hydrodynamics was predicted to diminish bubble column performance with respect to CO conversion, biomass production, and ethanol production when compared with bubble column models in which the gas phase was modeled as ideal plug flow plus axial dispersion. Liquid recycle was predicted to be advantageous by increasing CO conversion, biomass production, and ethanol and 2,3-butanediol production compared with the non-recycle reactor configuration. Parametric studies performed for the liquid recycle configuration with two-phase hydrodynamics showed that increased CO feed flow rates (more gas supply), smaller CO gas bubbles (more gas-liquid mass transfer), and shorter column heights (more gas per volume of liquid per time) favored ethanol production over acetate production. Our computational results demonstrate the power of combining cellular metabolic models and two-phase hydrodynamics for simulating and optimizing gas fermentation reactors.

Bubble coalescence suppression driven carbon monoxide (CO)-water mass transfer increase by electrolyte addition in a hollow fiber membrane bioreactor (HFMBR) for microbial CO conversion to ethanol

This study investigated the effects of electrolytes (CaCl₂, K₂HPO₄, MgSO₄, NaCl, and NH₄Cl) on CO mass transfer and ethanol production in a HFMBR. The hollow fiber membranes (HFM) were found to generate tiny gas bubbles; the bubble coalescence was significantly suppressed in electrolyte solution. The volumetric gas-liquid mass transfer coefficients (k_La) increased up to 414% compared to the control. Saturated CO (C^∗) decreased as electrolyte concentrations increased. Overall, the maximum mass transfer rate (R_max) in electrolyte solution ranged from 106% to 339% of the value obtained in water. The electrolyte toxicity on cell growth was tested using Clostridium autoethanogenum. Most electrolytes, except for MgSO₄, inhibited cell growth. The HFMBR operation using a medium containing 1% MgSO₄ achieved 119% ethanol production compared to that without electrolytes. Finally, a kinetic simulation using the parameters got from the 1% MgSO₄ medium predicted a higher ethanol production compared to the control.