Biobased short chain fatty acid production - Exploring microbial community dynamics and metabolic networks through kinetic and microbial modeling approaches.

In recent years, there has been growing interest in harnessing anaerobic digestion technology for resource recovery from waste streams. This approach has evolved beyond its traditional role in energy generation to encompass the production of valuable carboxylic acids, especially volatile fatty acids (VFAs) like acetic acid, propionic acid, and butyric acid. VFAs hold great potential for various industries and biobased applications due to their versatile properties. Despite increasing global demand, over 90% of VFAs are currently produced synthetically from petrochemicals. Realizing the potential of large-scale biobased VFA production from waste streams offers significant eco-friendly opportunities but comes with several key challenges. These include low VFA production yields, unstable acid compositions, complex and expensive purification methods, and post-processing needs. Among these, production yield and acid composition stand out as the most critical obstacles impacting economic viability and competitiveness. This paper seeks to offer a comprehensive view of combining complementary modeling approaches, including kinetic and microbial modeling, to understand the workings of microbial communities and metabolic pathways in VFA production, enhance production efficiency, and regulate acid profiles through the integration of omics and bioreactor data.

Steerable isobutyric and butyric acid production from CO2 and H2 by Clostridium luticellarii.

Clostridium luticellarii is a recently discovered acetogen that is uniquely capable of producing butyric and isobutyric acid from various substrates (e.g. methanol), but it is unclear which factors influence its (iso)butyric acid production from H2 and CO2 . We aimed to investigate the autotrophic metabolism of C. luticellarii by identifying the necessary growth conditions and examining the effects of pH and metabolite levels on product titers and selectivity. Results show that autotrophic growth of C. luticellarii requires the addition of complex nutrient sources and the absence of shaking conditions. Further experiments combined with thermodynamic calculations identified pH as a key parameter governing the direction of metabolic fluxes. At circumneutral pH (~6.5), acetic acid is the sole metabolic end product but C. luticellarii possesses the unique ability to co-oxidize organic acids such as valeric acid under high H2 partial pressures (>1 bar). Conversely, mildly acidic pH (≤5.5) stimulates the production of butyric and isobutyric acid while partly halting the oxidation of organic acids. Additionally, elevated acetic acid concentrations stimulated butyric and isobutyric acid production up to a combined selectivity of 53 ± 3%. Finally, our results suggest that isobutyric acid is produced by a reversible isomerization of butyric acid, but valeric and caproic acid are not isomerized. These combined insights can inform future efforts to optimize and scale-up the production of valuable chemicals from CO2 using C. luticellarii.

Thermophilic caproic acid production from grass juice by sugar-based chain elongation.

Medium chain carboxylic acids (MCCA) such as caproic acid have a plethora of applications, ranging from food additives to bioplastics. MCCA can be produced via microbial chain elongation using waste and side-streams as substrates, a process that can be more sustainable than conventional production routes. Most chain elongation studies have focused on mesophilic conditions, with only two recent studies hinting at the possibility of thermophilic chain elongation, but a systematic study of its mechanisms is lacking. Here, we investigated thermophilic chain elongation from grass juice, to understand the effect of key operational parameters (pH, temperature, substrate) on the process performance and to establish the key microbial genera and their role in the system. The genus Caproiciproducens was identified as responsible for thermophilic chain elongation, and caproic acid production was most favorable at pH 6.0 and 50 °C among the conditions tested, reaching an average concentration of 3.4 g/L. Batch experiments showed that the substrate for caproic acid production were glucose and xylose, while lactic acid led to the production of only butyric acid. Fed-batch experiments showed that substrate availability and the presence of caproic acid in the system play a major role in shaping the profile of thermophilic chain elongation. The increase of the total sugar concentration by glucose addition (without changing the organic load) during continuous operation led to a microbial community dominated (75 %) by Caproiciproducens and increased by 76 % the final average caproic acid concentration to 6.0 g/L (13 gCOD/L) which represented 32 % (g/g) of the total carboxylic acids. The highest concentration achieved was 7.2 g/L (day 197) which is the highest concentration reported under thermophilic conditions thus far. The results of this work pave the way to the potential development of thermophilic systems for upgrading various underexplored abundant and cheap sugar-rich side-streams to caproic acid.

Why do lactic acid bacteria thrive in chain elongation microbiomes?

Efficient waste management is necessary to transition towards a more sustainable society. An emerging trend is to use mixed culture biotechnology to produce chemicals from organic waste. Insights into the metabolic interactions between community members and their growth characterization are needed to mediate knowledge-driven bioprocess development and optimization. Here, a granular sludge bioprocess for the production of caproic acid through sugar-based chain elongation metabolism was established. Lactic acid and chain-elongating bacteria were identified as the two main functional guilds in the granular community. The growth features of the main community representatives (isolate Limosilactobacillus musocae G03 for lactic acid bacteria and type strain Caproiciproducens lactatifermentans for chain-elongating bacteria) were characterized. The measured growth rates of lactic acid bacteria (0.051 ± 0.005 h-1) were two times higher than those of chain-elongating bacteria (0.026 ± 0.004 h-1), while the biomass yields of lactic acid bacteria (0.120 ± 0.005 g biomass/g glucose) were two times lower than that of chain-elongating bacteria (0.239 ± 0.007 g biomass/g glucose). This points towards differential growth strategies, with lactic acid bacteria resembling that of a r-strategist and chain-elongating bacteria resembling that of a K-strategist. Furthermore, the half-saturation constant of glucose for L. mucosae was determined to be 0.35 ± 0.05 g/L of glucose. A linear trend of caproic acid inhibition on the growth of L. mucosae was observed, and the growth inhibitory caproic acid concentration was predicted to be 13.6 ± 0.5 g/L, which is the highest reported so far. The pre-adjustment of L. mucosae to 4 g/L of caproic acid did not improve the overall resistance to it, but did restore the growth rates at low caproic acid concentrations (1-4 g/L) to the baseline values (i.e., growth rate at 0 g/L of caproic acid). High resistance to caproic acid enables lactic acid bacteria to persist and thrive in the systems intended for caproic acid production. Here, insights into the growth of two main functional guilds of sugar-based chain elongation systems are provided which allows for a better understanding of their interactions and promotes future bioprocess design and optimization.

Fostering the valorization of organic wastes into carboxylates by a computer-aided design tool.

The carboxylate platform has the potential to constitute an outstanding opportunity for converting organic wastes into chemicals and other value-added products within a circular economy framework. However, its development is still hampered by technological and financial constraints due to difficulties at forecasting the carboxylates yields by different wastes. This work provides a framework that can be the key to foster circular economy and bridge the development risks, allowing early-stage evaluation of process performance. This framework, which is implemented as a computer-aided design tool, is comprised by: (i) a library of substrates including their characterization and appropriate kinetic parameter selection, (ii) an integral kinetic and stoichiometric model which solves both identified gaps regarding the disintegration mechanisms and the acidogenic stoichiometry variability in the anaerobic mono and cofermentation of complex organic wastes, and (iii) a set of indicators to interpret simulation results and assist the decision making; and presents a showcase of applications supported by two case studies. These case studies show that the optimal conditions to steer VFA spectrum towards odd-chain VFA in MCF of regrind pasta are neutral pH (6.5-7) and a relatively low HRT (3-4 days), while cofermentation of tuna canning wastewater and regrind pasta follows interactive mechanisms that cannot be captured by a "naïve approach", i.e. by adding up the individual contributions. Finally, it is discussed how value chain actors with different interests can benefit from the proposed tool: identifying technical, economic, and environmental bottlenecks, and proposing innovative solutions prior to costly lab research and piloting.

Microbial inefficient substrate use through the perspective of resource allocation models.

Microorganisms extract energy from substrates following strategies that may seem suboptimal at first glance. Beyond the so-called yield-rate trade-off, resource allocation models, which focus on assigning different functional roles to the limited number of enzymes that a cell can support, offer a framework to interpret the inefficient substrate use by microorganisms. We review here relevant examples of substrate conversions where a significant part of the available energy is not utilised and how resource allocation models offer a mechanistic interpretation thereof, notably for open mixed cultures. Future developments are identified, in particular, the challenge of considering metabolic flexibility towards uncertain environmental changes instead of strict fixed optimality objectives, with the final goal of increasing the prediction capabilities of resource allocation models. Finally, we highlight the relevance of resource allocation to understand and enable a promising biorefinery platform revolving around lactate, which would increase the flexibility of waste-to-chemical biorefinery schemes.

Resource allocation explains lactic acid production in mixed-culture anaerobic fermentations.

Lactate production in anaerobic carbohydrate fermentations with mixed cultures of microorganisms is generally observed only in very specific conditions: the reactor should be run discontinuously and peptides and B vitamins must be present in the culture medium as lactic acid bacteria (LAB) are typically auxotrophic for amino acids. State-of-the-art anaerobic fermentation models assume that microorganisms optimise the adenosine triphosphate (ATP) yield on substrate and therefore they do not predict the less ATP efficient lactate production, which limits their application for designing lactate production in mixed-culture fermentations. In this study, a metabolic model taking into account cellular resource allocation and limitation is proposed to predict and analyse under which conditions lactate production from glucose can be beneficial for microorganisms. The model uses a flux balances analysis approach incorporating additional constraints from the resource allocation theory and simulates glucose fermentation in a continuous reactor. This approach predicts lactate production is predicted at high dilution rates, provided that amino acids are in the culture medium. In minimal medium and lower dilution rates, mostly butyrate and no lactate is predicted. Auxotrophy for amino acids of LAB is identified to provide a competitive advantage in rich media because less resources need to be allocated for anabolic machinery and higher specific growth rates can be achieved. The Matlab™ codes required for performing the simulations presented in this study are available at https://doi.org/10.5281/zenodo.4031144.

Protein composition determines the preferential consumption of amino acids during anaerobic mixed-culture fermentation.

The valorisation of protein-rich residual streams by anaerobic mixed-culture fermentation (MCF) has been barely studied in contrast to carbohydrate-rich wastes. The aim of this work was, therefore, to investigate how protein composition, i.e. the amino acid (AA) profile, affects the individual consumption of amino acids and, consequently, the outcome of the process. Mixed-culture fermentations were performed with two model proteins (casein and gelatin) using continuous and batch reactors at neutral pH values and 25 °C. The acidification was incomplete for both proteins, with casein achieving a higher value than gelatin. Albeit dominated by acetic acid, product spectra were different as well, with n-butyric acid as the second major product for casein and propionic acid for gelatin. The preferential consumption of amino acids was demonstrated, which interestingly depends on protein composition. The previously accepted stoichiometry accurately describes iso and n-butyric acid production, but it fails for propionic, iso and n-valeric acid generation. Overall, this study offers a better understanding of protein fermentation mechanisms, which will help to improve degradation models and to design fermentation processes, based on optimal substrate selection.

Selecting for lactic acid producing and utilising bacteria in anaerobic enrichment cultures.

Lactic acid-producing bacteria are important in many fermentations, such as the production of biobased plastics. Insight in the competitive advantage of lactic acid bacteria over other fermentative bacteria in a mixed culture enables ecology-based process design and can aid the development of sustainable and energy-efficient bioprocesses. Here we demonstrate the enrichment of lactic acid bacteria in a controlled sequencing batch bioreactor environment using a glucose-based medium supplemented with peptides and B vitamins. A mineral medium enrichment operated in parallel was dominated by Ethanoligenens species and fermented glucose to acetate, butyrate and hydrogen. The complex medium enrichment was populated by Lactococcus, Lactobacillus and Megasphaera species and showed a product spectrum of acetate, ethanol, propionate, butyrate and valerate. An intermediate peak of lactate was observed, showing the simultaneous production and consumption of lactate, which is of concern for lactic acid production purposes. This study underlines that the competitive advantage for lactic acid-producing bacteria primarily lies in their ability to attain a high biomass specific uptake rate of glucose, which was two times higher for the complex medium enrichment when compared to the mineral medium enrichment. The competitive advantage of lactic acid production in rich media can be explained using a resource allocation theory for microbial growth processes.

Metabolic modeling for predicting VFA production from protein-rich substrates by mixed-culture fermentation.

Proteinaceous organic wastes are suitable substrates to produce high added-value products in anaerobic mixed-culture fermentations. In these processes, the stoichiometry of the biotransformation depends highly on operational conditions such as pH or feeding characteristics and there are still no tools that allow the process to be directed toward those products of interest. Indeed, the lack of product selectivity strongly limits the potential industrial development of these bioprocesses. In this work, we developed a mathematical metabolic model for the production of volatile fatty acids from protein-rich wastes. In particular, the effect of pH on the product yields is analyzed and, for the first time, the observed changes are mechanistically explained. The model reproduces experimental results at both neutral and acidic pH and it is also capable of predicting the tendencies in product yields observed with a pH drop. It also offers mechanistic insights into the interaction among the different amino acids (AAs) of a particular protein and how an AA might yield different products depending on the relative abundance of other AAs. Particular emphasis is placed on the utility of this mathematical model as a process design tool and different examples are given on how to use the model for this purpose.

A metabolic model for targeted volatile fatty acids production by cofermentation of carbohydrates and proteins.

Anaerobic mixed-culture fermentations are interesting processes to valorise organic wastes by converting them to volatile fatty acids. One of the main issues is that certain operational conditions (e.g. pH or different substrate concentrations) can vary significantly the product spectrum. So far, there are no tools that take into the account the characteristic features of cofermentation processes, which hinders the possibility of designing processes that use real wastes as substrates. In this work a mathematical model was developed for the production of volatile fatty acids from organic wastes with a high concentration of carbohydrates and proteins. The model reproduces satisfactorily experimental results and is also able of giving mechanistic insight into the interactions between carbohydrates and proteins that explain the observed changes in the product spectrum. We envision this model as the core of an early-stage design tool for anaerobic cofermentation processes, as shown in this work with different examples.