Valorization of Low-Cost Substrates for the Production of Odd Chain Fatty Acids by the Oleaginous Yeast Yarrowia lipolytica

Impact of glucose and propionic acid on even and odd chain fatty acid profiles of oleaginous yeasts

BACKGROUND

Odd chain fatty acids (OCFAs) are gaining attention for their valuable medical and nutritional applications. Microbial fermentation offers a sustainable and environmentally friendly alternative for OCFA production compared to traditional extraction or chemical synthesis methods. To achieve an economically feasible OCFA production process, it is essential to identify and develop microbial cell factories capable of producing OCFAs with high titers and yields.

RESULTS

We selected 19 yeast species, including both oleaginous yeasts and representatives from the Ascomycota and Basidiomycota phyla, based on their known or potential ability to produce OCFAs. These species were screened under various growth conditions to evaluate their OCFA production potential. In glucose-based, nitrogen-limited media, the strains produced fatty acids to varying extents, with OCFAs comprising 0.5-5% of the total fatty acids. When using the OCFAs precursor propionic acid as the sole carbon source, only eight strains exhibited growth, with tolerance to propionic acid concentrations between 5 and 29 g/L. The strains also displayed varying efficiencies in converting propionic acid into fatty acids, yielding between 0.16 and 1.22 g/L of fatty acids, with OCFAs constituting 37-89% of total fatty acids. Among the top performing strains, Cutaneotrichosporon oleaginosus produced the highest OCFA titers and yields (0.94 g/L, 0.07 g/g), Yarrowia lipolytica demonstrated superior growth rates even at elevated propionic acid concentrations, and Rhodotorula toruloides achieved the highest proportion of OCFAs relative to total fatty acids (89%).

CONCLUSIONS

Our findings highlight the diverse capacities of the selected yeast species for OCFA production, identifying several promising strains for further optimization as microbial cell factories in sustainable OCFA production processes.

Integrated Biorefinery for a Next-Generation Methanization Process Focusing on Volatile Fatty Acid Valorization: A Critical Review

This review addresses the critical issue of a rapidly increasing worldwide waste stream and the need for sustainable management. The paper proposes an integrated transformation toward a next-generation methanization process, which leads not only to treating waste but also to converting it into higher value compounds and greener energy. Although the current and commonly used anaerobic digestion process is useful for biogas production, it presents limitations of resource exploitation and some negative environmental impacts. Focusing on the acidogenic stage in waste stream processing, the paper discusses the recent strategies to enhance the recovery of volatile fatty acids (VFAs). These acids serve as precursors for synthesizing a variety of biochemicals and biofuels, offering higher value products than solely energy recovery and soil fertilizers. Additionally, the importance of recycling the fermentation residues back into the biorefinery process is highlighted. This recycling not only generates additional VFAs but also contributes to generating clean energy, thereby enhancing the overall sustainability and efficiency of the waste management system. Moreover, the review discusses the necessity to integrate life cycle assessment (LCA) and techno-economic analysis (TEA) to evaluate the environmental impacts, sustainability, and processing costs of the proposed biorefinery.

Unveiling the anticancer potentiality of single cell oils produced by marine oleaginous Paradendryphiella sp. under optimized economic growth conditions

Bioprospecting about new marine oleaginous fungi that produce advantageous bioproducts in a green sustainable process is the key of blue bioeconomy. Herein, the marine Paradendryphiella sp. was utilized for single cell oils (SCOs) production economically, via central composite design, the lipid content enhanced 2.2-fold by 5.5 g/L lipid yeild on seawater-based media supplemented with molasses concentration 50 g/L, yeast extract, 2.25 g/L at initial pH value (5.3) and 8 days of static incubation. Subsequently, the fatty acid methyl esters profiles of SCOs produced on optimized media under different abiotic conditions were determined; signifying qualitative and quantitative variations. Interestingly, the psychrophilic-prolonged incubation increased the unsaturation level of fatty acids to 59.34%, while ω-6 and ω-3 contents representing 23.53% and 0.67% respectively. Remarkably, it exhibited the highest EC100 dose by 677.03 µg/mL on normal human lung fibroblast Wi-38 cells. Meanwhile, it showed the highest inhibiting proliferation potential on cancer cell lines of A549, MDA-MB 231 and HepG-2 cells by 372.37, 417.48 and 365.00 µg/mL, respectively. Besides, it elevated the oxidative stress, the expression of key apoptotic genes and suppressed the expression of key oncogenes (NF-κB, BCL2 and cyclin D); implying its promising efficacy in cancer treatment as adjuvant drug. This study denoted the lipogenesis capacity of Paradendryphiella sp. under acidic/alkaline and psychrophilic/mesophilic conditions. Hereby attaining efficient and economic process under seasonal variation with different Egyptian marine sources to fill the gap of freshwater crisis and simultaneously preserve energy.

Purification of Natural Pigments Violacein and Deoxyviolacein Produced by Fermentation Using Yarrowia lipolytica

Violacein and deoxyviolacein are bis-indole pigments synthesized by a number of microorganisms. The present study describes the biosynthesis of a mixture of violacein and deoxyviolacein using a genetically modified Y. lipolytica strain as a production chassis, the subsequent extraction of the intracellular pigments, and ultimately their purification using column chromatography. The results show that the optimal separation between the pigments occurs using an ethyl acetate/cyclohexane mixture with different ratios, first 65:35 until both pigments were clearly visible and distinguishable, then 40:60 to create a noticeable separation between them and recover the deoxyviolacein, and finally 80:20, which allows the recovery of the violacein. The purified pigments were then analyzed by thin-layer chromatography and nuclear magnetic resonance.

Machine Learning Models Using Data Mining for Biomass Production from Yarrowia lipolytica Fermentation

In this paper, a database of biomass production from Yarrowia lipolytica fermentation is prepared and constructed using machine learning and data mining approaches. The database is curated from 15 publications and consists of 301 rows of data with 25 predictors and 1 label. The predictors include inoculum size, temperature, pH, and time, while the label is the corresponding biomass production. The database is then divided into training, validation, and test datasets and analyzed as a supervised machine learning task for regression. Twenty-six regression models are employed and compared for their performance in predicting biomass production. The best-performing model is the Matern 5/2 Gaussian process regression model, which has the lowest root-mean-squared error of 0.75 g/L, the highest R squared of 0.90, and the lowest mean absolute error of 0.52 g/L. The t-test is used to identify the most important predictors, and 14 predictors are sufficient for creating an accurate model. These 14 predictors are fermentation time, peptone, temperature, total Kjeldahl nitrogen, shaking rate, total nitrogen, inoculum size, yeast extract, crude glycerol, glucose, oil and grease, media pH, ammonium sulfate, and olive oil. This research demonstrates the application of machine learning and data mining to estimate biomass production and gives insight into which parameters are essential for Yarrowia lipolytica fermentation.