This study aimed to examine the impact of crude glycerol as the main carbon source on the growth, cell morphology, and production of high-value-added metabolites of two microalgal species, namely Chlorella vulgaris and Scenedesmus quadricauda, under heterotrophic and mixotrophic conditions, using monochromatic illumination from light-emitting diodes (LEDs) emitting blue, red, yellow, and white (control) light. The findings indicated that both microalgae strains exhibited higher biomass yield on the mixotrophic growth system when compared to the heterotrophic one, while S. quadricauda generally performed better than C. vulgaris. In mixotrophic mode, the use of different monochromatic illumination affected biomass production differently on both strains. In S. quadricauda, growth rate was higher under red light (μ_max = 0.89 d⁻¹), while the highest biomass concentration and yield per gram of consumed glycerol were achieved under yellow light, reaching 1.86 g/L and Y_x/s = 0.18, respectively. On the other hand, C. vulgaris demonstrated a higher growth rate on blue light (μ_max = 0.45 d⁻¹) and a higher biomass production on white (control) lighting (1.34 g/L). Regarding the production of metabolites, higher yields were achieved during mixotrophic mode in both strains. In C. vulgaris, the highest lipid (26.5% of dry cell weight), protein (63%), and carbohydrate (20.3%) contents were obtained under blue, red, and yellow light, respectively, thus indicating that different light wavelengths probably activate different metabolic pathways. Similar results were obtained for S. quadricauda with red light leading to higher lipid content, while white lighting caused higher production of proteins and carbohydrates. Overall, the study demonstrated the potential of utilizing crude glycerol as a carbon source for the growth and metabolite production of microalgae and, furthermore, revealed that the strains’ behavior varied depending on lighting conditions.

As crude glycerol comprises a potential substrate for microalga fermentation and value added products’ biosynthesis, Auxenochlorella protothecoides was grown on it under heterotrophic and mixotrophic conditions and its growth kinetics were evaluated in a continuous system under steady state conditions. Increasing initial glycerol concentration (from 30 to 50 g/L) in the heterotrophic culture led to reduced biomass yield (Y_x/S) and productivity (P_x), but favored lipid accumulation. Under heterotrophic conditions, the microalga was found to grow better (biomass up to 7.888 g/L) and faster (higher growth rates), the system functioned more effectively (higher P_x) and crude glycerol was exploited more efficiently. Heterotrophy also favored proteins synthesis (up to 53%), lipids (up to 9.8%), and carbohydrates (up to 44.6%) accumulation. However, different trophic modes had no significant impact on the consistency of proteins and lipids. Oleic acid was the most abundant fatty acid detected (55–61.2% of the total lipids). The algal biomass contained many essential and non-essential amino acids, especially arginine, glutamic acid, lysine, aspartic acid, leucine, and alanine. In all the experimental trials, the protein contents in the microalgal biomass increased with the increasing dilution rate (D), with a concomitant decrease in the lipids and carbohydrates fractions.

This study examined the effects of monochromatic illumination (blue, red, green and yellow) employing light-emitting diodes (LEDs), trophic conditions (photoautotrophic and mixotrophic), and nitrogen availability (high and low peptone concentration) on the growth and biochemical composition of Auxenochlorella protothecoides. The results revealed that mixotrophic conditions did not favor A. protothecoides, giving lower growth rates compared to heterotrophy (dark conditions). However, mixotrophy gave significantly higher growth rates compared to photoautotrophy. The best light wavelengths for mixotrophic cultivation were that of white and red. In all cases investigated in this study, high peptone concentration (4 g/L) resulted in decreased growth rates. Regarding the biochemical composition of A. protothecoides, the strongest effect, irrespective of trophic conditions, was caused by nitrogen availability (peptone concentration). Specifically, at nitrogen replete conditions (4 g/L peptone), biomass was rich in proteins (32–67%), whereas under deplete conditions (0.5 g/L peptone), A. protothecoides accumulated mainly carbohydrates (up to 56%). Mixotrophic conditions generally favored higher carbohydrate content, whereas photoautotrophic conditions favored higher protein content. The different illumination spectra did not have any clear effect on the biochemical composition (metabolites content), except that, in all trophic conditions, the use of the green spectrum resulted in higher chlorophyll b content. Chlorophyll a fluorescence studies revealed that the trophic conditions and the high peptone concentrations impacted the photosystem II (PSII) performance, and also affected plastoquinone re-oxidation kinetics and the heterogeneity of the PSII reaction centers.

The cheese microbiome is a complex ecosystem strongly influenced by both technological practices and the processing environment. Moving beyond traditional cultured-based methods, the integration of shotgun metagenomics into cheese microbiology has enabled in-depth resolution of microbial communities at the species and strain levels. The aim of the present study was to review recent applications of shotgun metagenomics in cheese research, underscoring its role in tracking microbial dynamics during production and in discovering genes of technological importance. In addition, the review highlights how shotgun metagenomics enables the identification of key metabolic pathways, including amino acid catabolism, lipid metabolism, and citrate degradation, among others, which are central to flavor formation and ripening. Results of the discussed literature demonstrate how microbial composition, functional traits, and overall quality of cheese are determined by factors such as raw materials, the cheesemaking environment, and artisanal practices. Moreover, it highlights the analytical potentials of shotgun metagenomics, including metagenome-assembled genomes (MAGs) reconstruction, characterization of various genes contributing to flavor-related biosynthetic pathways, bacteriocin production, antimicrobial resistance, and virulence, as well as the identification of phages and CRISPR-Cas systems. These insights obtained are crucial for ensuring product’s authenticity, enabling traceability, and improving the assessment of safety and quality. Despite shotgun metagenomics’ advantages, there are still analytical restrictions concerning data handling and interpretation, which need to be addressed by importing standardization steps and moving towards integrating multi-omics approaches. Such strategies will lead to more accurate and reproducible results across studies and improved resolution of active ecosystems. Ultimately, shotgun metagenomics has shifted the field from descriptive surveys to a more detailed understanding of the underlying mechanisms shaping the overall quality and safety of cheese, thus bringing innovation in modern dairy microbiology.