Control of redox potential in a novel continuous bioelectrochemical system led to remarkable metabolic and energetic responses of Clostridium pasteurianum grown on glycerol

Artificial neural networks in the modeling of the catalytic activity of a biosensor composed of conjugated polymers and urease

Thin films of conjugated polymer and enzyme can be used to unravel the interaction between components in a biosensor. Using artificial neural networks (ANNs) improves data interpretability and helps construct models with great capacity for classifying and processing information. The present work used kinetic data from the catalytic activity of urease immobilized in different conjugated polymers to create ANN models using time, substrate concentration, and absorbance as input variables since the models had absorbance in a posterior instant as output value to explore the predictivity of the ANNs. The performance of the models was evaluated by Pearson's correlation coefficient (ρ) and mean squared error (MSE) values. After the learning process, a series of new experiments were performed to verify the generality of the models. As the main results, the best ANN model presented 0.9980 and 3.0736 × 10-5 for ρ and MSE, respectively. For the simulation step, intermediary values of substrate concentration were used. The mean absolute percentage error (MAPE) values were 3.34, 3.07, and 3.78 for 12 mM, 22 mM, and 32 mM concentrations, respectively. Overall, with the simulations, it was possible to ascertain the interpolatory capacity of the model, which has a learning mechanism based on absorbance and time as variables. Thus, the potential of ANNs would be in their use in pre-evaluations, helping to determine the substrate concentration at which there is higher catalytic activity or in determining the linear range of the sensor.

Lactate based caproate production with Clostridium drakei and process control of Acetobacterium woodii via lactate dependent in situ electrolysis

Syngas fermentation processes with acetogens represent a promising process for the reduction of CO₂ emissions alongside bulk chemical production. However, to fully realize this potential the thermodynamic limits of acetogens need to be considered when designing a fermentation process. An adjustable supply of H₂ as electron donor plays a key role in autotrophic product formation. In this study an anaerobic laboratory scale continuously stirred tank reactor was equipped with an All-in-One electrode allowing for in-situ H₂ generation via electrolysis. Furthermore, this system was coupled to online lactate measurements to control the co-culture of a recombinant lactate-producing Acetobacterium woodii strain and a lactate-consuming Clostridium drakei strain to produce caproate. When C. drakei was grown in batch cultivations with lactate as substrate, 1.6 g·L^-1 caproate were produced. Furthermore, lactate production of the A. woodii mutant strain could manually be stopped and reinitiated by controlling the electrolysis. Applying this automated process control, lactate production of the A. woodii mutant strain could be halted to achieve a steady lactate concentration. In a co-culture experiment with the A. woodii mutant strain and the C. drakei strain, the automated process control was able to dynamically react to changing lactate concentrations and adjust H₂ formation respectively. This study confirms the potential of C. drakei as medium chain fatty acid producer in a lactate-mediated, autotrophic co-cultivation with an engineered A. woodii strain. Moreover, the monitoring and control strategy presented in this study reinforces the case for autotrophically produced lactate as a transfer metabolite in defined co-cultivations for value-added chemical production.

Enhanced continuous biohydrogen production using dynamic membrane with conductive biofilm supporter

The present study investigated the effect of a conductive biofilm supporter on continuous production of biohydrogen in a dynamic membrane bioreactor (DMBR). Two lab-scale DMBRs were operated: one with a nonconductive polyester mesh (DMBR I) and the other with a conductive stainless-steel mesh (DMBR II). The highest average hydrogen productivity and the yield were 16.8% greater in DMBR II than in DMBR I, with values of 51.64 ± 0.66 L/L-d and 2.01 ± 0.03 mol H₂/mol hexose_consumed, respectively. The improved hydrogen production was concurrent with a higher NADH/NAD⁺ ratio and a lower ORP (Oxidation-reduction potential). Metabolic flux analysis implied that the conductive supporter promoted H₂-producing acetogenesis and repressed competitive NADH-consuming pathways, such as homoacetogenesis and lactate production. Microbial community analysis revealed that electroactive Clostridium sp. were the dominant H₂ producers in DMBR II. Conclusively, conductive meshes may be useful as biofilm supporters of dynamic membranes during H₂ production for selectively enhancing H₂-producing pathways.

Electrochemically mediated bioconversion and integrated purification greatly enhanced co-production of 1,3-propanediol and organic acids from glycerol in an industrial bioprocess

In this study, we show how electrochemically mediated bioconversion can greatly increase the co-production of 1,3-propanediol and organic acids from glycerol in an industrial bioprocess using a Clostridum pasteurianum mutant. Remarkably, an enhanced butyrate formation was observed due to a weakened butanol pathway of the mutant. This allowed the strain to have a higher ATP generation for an enhanced growth, higher glycerol consumption and PDO production. The PDO titer reached as high as 120.67 g/L at a cathodic current of -400 mA, which is 33% higher than that without electricity, with a concurrent increase of butyric acid by 80%. To fully recover the increased PDO and organic acids, a novel downstream process combining thin film evaporation of PDO and esterification of organic acids with ethanol was developed. This enables the efficient co-production of PDO, ethyl acetate and ethyl butyrate with a high overall carbon use of 87%.