The carboxylate platform offers a sustainable bioconversion strategy for biorefineries, utilizing anaerobic mixed cultures to produce carboxylate mixtures, including medium-chain fatty acids (MCFAs), as valuable intermediates. The effects of carbon sources (glucose, glycerol, casein) and exogenous supplied electron donors (ethanol, methanol, propanol, pyruvate) on MCFA production via chain elongation were investigated to elucidate the role of external electron donors and assess the feasibility of self-sufficient MCFA production in their absence. For this purpose, all experimental sets included corresponding control conditions without external electron donor addition. Batch experiments were conducted without active pH control, allowing pH to evolve dynamically in response to substrate type and metabolic activity. Results showed that the carbon source significantly affected carboxylic acid production and composition. Glucose primarily yielded propionate, independent of the electron donor. Casein resulted in the lowest carboxylic acid and gas production but uniquely produced the highest MCFA. Acidic pH conditions (5.0–5.5), which developed primarily in glucose- and glycerol-fed systems, favoured short-chain fatty acid production, whereas near-neutral pH conditions (6.0–6.7), observed in casein-fed systems, enhanced MCFA formation. Electron donors significantly influenced the degradation rate of glycerol. Methane production was observed in glucose and glycerol sets but was absent in casein sets. Microbial community analysis revealed methanogen dominance across most sets, irrespective of substrate. These findings highlight the complex interactions between pH, electron donor/acceptor availability, and microbial community dynamics in anaerobic digestion. Future multi-omics and flux analyses are needed to elucidate the metabolic pathways governing chain elongation and anaerobic digestion.

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.

Natural microbial communities are composed of a large diversity of interacting microorganisms, each with a specific role in the functional properties of the ecosystem. The objectives in microbial ecology research are related to identifying, understanding and exploring the role of these different microorganisms. Because of the rapidly increasing power of DNA sequencing and the rapid increase of genomic data, main attention of microbial ecology research shifted from cultivation-oriented studies towards metagenomic studies. Despite these efforts, the direct link between the molecular properties and the measurable changes in the functional performance of the ecosystem is often poorly documented. A quantitative understanding of functional properties in relation to the molecular changes requires effective integration, standardization, and parallelization of experiments. High-resolution functional characterization is a prerequisite for interpretation of changes in metagenomic properties, and will improve our understanding of microbial communities and facilitate their exploration for health and circular economy related objectives.