Model development and experimental validation of capnophilic lactic fermentation and hydrogen synthesis by Thermotoga neapolitana

Biochemical hydrogen potential assay for predicting the patterns of the kinetics of semi-continuous dark fermentation

The performance and kinetics response of thermophilic semi-continuous dark fermentation (DF) of simulated complex carbohydrate-rich waste was investigated at various hydraulic retention times (HRT) (2, 2.5, and 3 d) and compared with data obtained from biochemical hydrogen potential assay (BHP). A culture of Thermoanaerobacterium thermosaccharolyticum was used as the inoculum and dominated both in BHP and semi-continuous reactor. Both the modified Gompertz and first-order models described the DF kinetics well (R² = 0.97-1.00). HRT of 2.5 d was found to be optimal in terms of maximum hydrogen production rate and hydrogen potential, which were 3.97 and 1.26 times higher, respectively, than in BHP. The hydrolysis constant was highest at HRT of 3 d and was closest to the value obtained in the BHP. Overall, BHP has been shown to be a useful tool for predicting H₂ potential and the hydrolysis constant, while the maximum H₂ production rate is greatly underestimated.

Machine learning in fermentative biohydrogen production: Advantages, challenges, and applications

Hydrogen can be produced in an environmentally friendly manner through biological processes using a variety of organic waste and biomass as feedstock. However, the complexity of biological processes limits their predictability and reliability, which hinders the scale-up and dissemination. This article reviews contemporary research and perspectives on the application of machine learning in biohydrogen production technology. Several machine learning algorithems have recently been implemented for modeling the nonlinear and complex relationships among operational and performance parameters in biohydrogen production as well as predicting the process performance and microbial population dynamics. Reinforced machine learning methods exhibited precise state prediction and retrieved the underlying kinetics effectively. Machine-learning based prediction was also improved by using microbial sequencing data as input parameters. Further research on machine learning could be instrumental in designing a process control tool to maintain reliable hydrogen production performance and identify connection between the process performance and the microbial population.

Strategies to control pH in the dark fermentation of sugarcane vinasse: Impacts on sulfate reduction, biohydrogen production and metabolite distribution

pH is notably known as the main variable defining distinct metabolic pathways during sugarcane vinasse dark fermentation. However, different alkalinizing (e.g. sodium bicarbonate; NaHCO₃) and/or neutralizing (e.g. sodium hydroxide; NaOH) approaches were never directly compared to understand the associated impacts on metabolite profiles. Three anaerobic structured-bed reactors (AnSTBR) were operated in parallel and subjected to equivalent operational parameters, except for the pH control: an acidogenic-sulfidogenic (R1; NaOH + NaHCO₃) designed to remove sulfur compounds (sulfate and sulfide), a hydrogenogenic (R2; NaOH) aimed to optimize biohydrogen (bioH₂) production, and a strictly fermentative system without pH adjustment (R3) to mainly evaluate lactic acid (HLa) production and other soluble metabolites. NaHCO₃ dosing triggered advantages not only for sulfate reduction (up to 56%), but also to enhance the stripping of sulfide to the gas phase (75-96% of the theoretical sulfide produced) by the high and constant biogas flow resulting from the CO₂ released during NaHCO₃ dissociation. Meanwhile, molasses-based vinasse presented higher potential for bioH₂ (up to 4545 mL-H₂ L^-1 d^-1) and HLa (up to 4800 mg L^-1) production by butyric-type and capnophilic lactic fermentation pathways. Finally, heterolactic fermentation was the main metabolic route established when no pH control was provided (R3), as indicated by the high production of both HLa (up to 4315 mg L^-1) and ethanol (1987 mg L^-1). Hence, one single substrate (from which one single source of inoculum was originated) offers a wide range of metabolic possibilities to be exploited, providing substantial versatility to the application of anaerobic digestion in sugarcane biorefineries.

Machine learning modeling and analysis of biohydrogen production from wastewater by dark fermentation process

Dark fermentation process for simultaneous wastewater treatment and H₂ production is gaining attention. This study aimed to use machine learning (ML) procedures to model and analyze H₂ production from wastewater during dark fermentation. Different ML procedures were assessed based on the mean squared error (MSE) and determination coefficient (R²) to select the most robust models for modeling the process. The research showed that gradient boosting machine (GBM), support vector machine (SVM), random forest (RF) and AdaBoost were the most appropriate models, which were optimized by grid search and deeply analyzed by permutation variable importance (PVI) to identify the relative importance of process variables. All four models demonstrated promising performances in predicting H₂ production with high R² values (0.893, 0.885, 0.902 and 0.889) and small MSE values (0.015, 0.015, 0.016 and 0.015). Moreover, RF-PVI demonstrated that acetate, butyrate, acetate/butyrate, ethanol, Fe and Ni were of high importance in decreasing order.

Improvement of CO2 and Acetate Coupling into Lactic Acid by Genetic Manipulation of the Hyperthermophilic Bacterium Thermotoga neapolitana

Capnophilic lactic fermentation (CLF) represents an attractive biotechnological process for biohydrogen production and synthesis of L-lactic acid from acetate and CO₂. The present study focuses on a genetic manipulation approach of the Thermotoga neapolitana DSM33003 strain to enhance lactic acid synthesis by the heterologous expression of a thermostable acetyl-CoA synthetase that catalyses the irreversible acetate assimilation. Because of the scarcity of available genetic tools, each transformation step was optimized for T. neapolitana DSM33003 to cope with the specific needs of the host strain. Batch fermentations with and without an external source of acetate revealed a strongly increased lactate production (up to 2.5 g/L) for the recombinant strain compared to wild type. In the engineered bacterium, the assimilation of CO₂ into lactic acid was increased 1.7 times but the hydrogen yield was impaired in comparison to the wild type strain. Analysis of fermentation yields revealed an impaired metabolism of hydrogen in the recombinant strain that should be addressed in future studies. These results offer an important prospective for the development of a sustainable approach that combines carbon capture, energy production from renewable source, and the synthesis of high value-added products, which will be addressed in future studies.

Kinetic modeling of hydrogen and L-lactic acid production by Thermotoga neapolitana via capnophilic lactic fermentation of starch

This study investigated the feasibility of hydrogen (H₂) and L-lactic acid production from starch under capnophilic lactic fermentation (CLF) conditions by using Thermotoga neapolitana. Batch experiments were performed in 120 mL serum bottles and a 3 L pH-controlled continuous stirred-tank reactors (CSTR) system with potato and wheat starch as the substrates. A H₂ yield of 3.34 (±0.17) and 2.79 (±0.17) mol H₂/mol of glucose eq. was achieved with, respectively, potato and wheat starch. In the presence of CO₂, L-lactic acid production by the acetyl-CoA carboxylation was significantly higher for the potato starch (0.88 ± 0.39 mol lactic acid/mol glucose eq.) than wheat starch (0.33 ± 0.11 mol lactic acid/mol glucose eq.). A kinetic model was applied to simulate and predict the T. neapolitana metabolic profile and bioreactor performance under CLF conditions. The CLF-based starch fermentation suggests a new direction to biotransform agri-food waste into biofuels and valuable biochemicals.

Effect of Cultivation Parameters on Fermentation and Hydrogen Production in the Phylum Thermotogae

The phylum Thermotogae is composed of a single class (Thermotogae), 4 orders (Thermotogales, Kosmotogales, Petrotogales, Mesoaciditogales), 5 families (Thermatogaceae, Fervidobacteriaceae, Kosmotogaceae, Petrotogaceae, Mesoaciditogaceae), and 13 genera. They have been isolated from extremely hot environments whose characteristics are reflected in the metabolic and phenotypic properties of the Thermotogae species. The metabolic versatility of Thermotogae members leads to a pool of high value-added products with application potentials in many industry fields. The low risk of contamination associated with their extreme culture conditions has made most species of the phylum attractive candidates in biotechnological processes. Almost all members of the phylum, especially those in the order Thermotogales, can produce bio-hydrogen from a variety of simple and complex sugars with yields close to the theoretical Thauer limit of 4 mol H₂/mol consumed glucose. Acetate, lactate, and L-alanine are the major organic end products. Thermotagae fermentation processes are influenced by various factors, such as hydrogen partial pressure, agitation, gas sparging, culture/headspace ratio, inoculum, pH, temperature, nitrogen sources, sulfur sources, inorganic compounds, metal ions, etc. Optimization of these parameters will help to fully unleash the biotechnological potentials of Thermotogae and promote their applications in industry. This article gives an overview of how these operational parameters could impact Thermotogae fermentation in terms of sugar consumption, hydrogen yields, and organic acids production.

Kinetic models of biological hydrogen production by Enterobacter aerogenes

Dark fermentative hydrogen production from glucose by Enterobacter aerogenes was studied. The kinetic models of modified Gompertz and Logistic were employed to investigate the progress of hydrogen production. The predicted maximum hydrogen production (H_max) by modified Gompertz and Logistic was 11.92 and 11.28 mL, respectively. The kinetic models of modified Gompertz, Logistic, and Richards were used to study biomass growth in batch experiments. The maximum biomass growth (X_max) by models of modified Gompertz, Logistic, and Richards was 4.90, 4.85, and 4.95 (g L^-1), respectively. The modified Gompertz was applied to simulate the consumption of glucose where the maximum degraded glucose (S_max) was obtained 19.77 g L^-1. The correlation coefficients of all the models were over 0.97, which illustrate that the models fit the data very well. However, the modified Gompertz model presents higher R² and lower RSS and is more appropriate than the other models.

CO2-Induced Transcriptional Reorganization: Molecular Basis of Capnophillic Lactic Fermentation in Thermotoga neapolitana

Capnophilic lactic fermentation (CLF) is a novel anaplerotic pathway able to convert sugars to lactic acid (LA) and hydrogen using CO₂ as carbon enhancer in the hyperthermophilic bacterium Thermotoga neapolitana. In order to give further insights into CLF metabolic networks, we investigated the transcriptional modification induced by CO₂ using a RNA-seq approach. Transcriptomic analysis revealed 1601 differentially expressed genes (DEGs) in an enriched CO₂ atmosphere over a total of 1938 genes of the T. neapolitana genome. Transcription of PFOR and LDH genes belonging to the CLF pathway was up-regulated by CO₂ together with 6-phosphogluconolactonase (6PGL) and 6-phosphogluconate dehydratase (EDD) of the Entner–Doudoroff (ED) pathway. The transcriptomic study also revealed up-regulation of genes coding for the flavin-based enzymes NADH-dependent reduced ferredoxin:NADP oxidoreductase (NFN) and NAD-ferredoxin oxidoreductase (RNF) that control supply of reduced ferredoxin and NADH and allow energy conservation-based sodium translocation through the cell membrane. These results support the hypothesis that CO₂ induces rearrangement of the central carbon metabolism together with activation of mechanisms that increase availability of the reducing equivalents that are necessary to sustain CLF. In this view, this study reports a first rationale of the molecular basis of CLF in T. neapolitana and provides a list of target genes for the biotechnological implementation of this process.

Capnophilic Lactic Fermentation from Thermotoga neapolitana: A Resourceful Pathway to Obtain Almost Enantiopure L-lactic Acid

The industrial production of lactic acid (LA) is mainly based on bacterial fermentation. This process can result in enantiopure or racemic mixture according to the producing organism. Between the enantiomers, L-lactic acid shows superior market value. Recently, we reported a novel anaplerotic pathway called capnophilic lactic fermentation (CLF) that produces a high concentration of LA by fermentation of sugar in the anaerobic thermophilic bacterium Thermotoga neapolitana. The aim of this work was the identification of the enantiomeric characterization of the LA produced by T. neapolitana and identification of the lactate dehydrogenase in T. neapolitana (TnLDH) and related bacteria of the order Thermotogales. Chemical derivatization and GC/MS analysis were applied to define the stereochemistry of LA from T. neapolitana. A bioinformatics study on TnLDH was carried out for the characterization of the enzyme. Chemical analysis showed a 95.2% enantiomeric excess of L-LA produced by T. neapolitana. A phylogenetic approach clearly clustered the TnLDH together with the L-LDH from lactic acid bacteria. We report for the first time that T. neapolitana is able to produce almost enantiopure L-lactic acid. The result was confirmed by bioinformatics analysis on TnLDH, which is a member of the L-LDH sub-family.