It was shown recently that individual cells of an isogenic Saccharomyces cerevisiae population show variability in acetic acid tolerance, and this variability affects the quantitative manifestation of the trait at the population level. In the current study, we investigated whether cell-to-cell variability in acetic acid tolerance could be explained by the observed differences in the cytosolic pHs of individual cells immediately before exposure to the acid. Results obtained with cells of the strain CEN.PK113-7D in synthetic medium containing 96 mM acetic acid (pH 4.5) showed a direct correlation between the initial cytosolic pH and the cytosolic pH drop after exposure to the acid. Moreover, only cells with a low initial cytosolic pH, which experienced a less severe drop in cytosolic pH, were able to proliferate. A similar correlation between initial cytosolic pH and cytosolic pH drop was also observed in the more acid-tolerant strain MUCL 11987-9. Interestingly, a fraction of cells in the MUCL 11987-9 population showed initial cytosolic pH values below the minimal cytosolic pH detected in cells of the strain CEN.PK113-7D; consequently, these cells experienced less severe drops in cytosolic pH. Although this might explain in part the difference between the two strains with regard to the number of cells that resumed proliferation, it was observed that all cells from strain MUCL 11987-9 were able to proliferate, independently of their initial cytosolic pH. Therefore, other factors must also be involved in the greater ability of MUCL 11987-9 cells to endure strong drops in cytosolic pH.

High acetic acid tolerance of Saccharomyces cerevisiae is a relevant phenotype in industrial biotechnology when using lignocellulosic hydrolysates as feedstock. A screening of 38 S. cerevisiae strains for tolerance to acetic acid revealed considerable differences, particularly with regard to the duration of the latency phase. To understand how this phenotype is quantitatively manifested, four strains exhibiting significant differences were studied in more detail. Our data show that the duration of the latency phase is primarily determined by the fraction of cells within the population that resume growth. Only this fraction contributed to the exponential growth observed after the latency phase, while all other cells persisted in a viable but non-proliferating state. A remarkable variation in the size of the fraction was observed among the tested strains differing by several orders of magnitude. In fact, only 11 out of 10⁷ cells of the industrial bioethanol production strain Ethanol Red resumed growth after exposure to 157 mM acetic acid at pH 4.5, while this fraction was 3.6 × 10⁶ (out of 10⁷ cells) in the highly acetic acid tolerant isolate ATCC 96581. These strain-specific differences are genetically determined and represent a valuable starting point to identify genetic targets for future strain improvement.

The increase in atmospheric CO₂ due to anthropogenic activities is generating climate change, which has resulted in a subsequent rise in global temperatures with severe environmental impacts. Biological mitigation has been considered as an alternative for environmental remediation and reduction of greenhouse gases in the atmosphere. In fact, the use of easily adapted photosynthetic organisms able to fix CO₂ with low-cost operation is revealing its high potential for industry. Among those organism, the algae Chlamydomonas reinhardtii have gain special attention as a model organism for studying CO₂ fixation, biomass accumulation and bioenergy production upon exposure to several environmental conditions. In the present study, we studied the Chlamydomonas response to different CO₂ levels by comparing metabolomics and transcriptomics data with the predicted results from our new-improved genomic-scale metabolic model. For this, we used in silico methods at steady dynamic state varying the levels of CO₂. Our main goal was to improve our capacity for predicting metabolic routes involved in biomass accumulation. The improved genomic-scale metabolic model presented in this study was shown to be phenotypically accurate, predictive, and a significant improvement over previously reported models. Our model consists of 3726 reactions and 2436 metabolites, and lacks any thermodynamically infeasible cycles. It was shown to be highly sensitive to environmental changes under both steady-state and dynamic conditions. As additional constraints, our dynamic model involved kinetic parameters associated with substrate consumption at different growth conditions (i.e., low CO₂-heterotrophic and high CO₂-mixotrophic). Our results suggest that cells growing at high CO₂ (i.e., photoautotrophic and mixotrophic conditions) have an increased capability for biomass production. In addition, we have observed that ATP production also seems to be an important limiting factor for growth under the conditions tested. Our experimental data (metabolomics and transcriptomics) and the results predicted by our model clearly suggest a differential behavior between low CO₂-heterotrophic and high CO₂-mixotrophic growth conditions. The data presented in the current study contributes to better dissect the biological response of C. reinhardtii, as a dynamic entity, to environmental and genetic changes. These findings are of great interest given the biotechnological potential of this microalga for CO₂ fixation, biomass accumulation, and bioenergy production.

One of the main challenges in the food industry is to design strategies for the successful incorporation of natural sources of bioactive compounds. Recently, yogurts and other fermented dairy beverages have been proposed as ideal carriers of such bioactive compounds such as fatty acids and antioxidants that could improve consumers' health. However, the incorporation of new ingredients causes functional and structural modifications that may affect the consumers' preferences. In this work, a dairy beverage model supplemented with oleic acid has been designed by partial substitution of milk by Candida utilis single-cell protein extract. The changes in the structural properties of this new beverage were evaluated by following the fermentation process, pH, aggregate size, microstructure, and changes in rheological properties. Furthermore, molecular dynamics simulations were carried out to analyze the interaction between its main components. Our data revealed that samples with a percentage of milk substitution of 30% showed a higher viscosity as compared with the other percentages and less viscosity than the control (no substitution). These samples were then selected for fortification by incorporating oleic acid microcapsules. A concentration of 1.5 g/100 g was shown to be the optimal quantity of microcapsules for oleic acid supplementation. Molecular dynamic simulations revealed glutathione as an important component of the micro-gel structure. The present study forms the basis for novel studies where Candida utilis single-cell protein and microencapsulated essential oils could be used to design innovative bioproducts.

The development of new technologies for environmental reparation has allowed the application of inexpensive alternatives such as bioremediation, which has a high potential to treat ecosystems polluted with hydrocarbons. Microalgae-bacteria consortia have been identified as an efficient alternative for the detoxification of organic and inorganic contaminants and the removal of toxic compounds. This work investigates the phenol degradation potential of several alga-microbial consortia, which involved the algae Chlamydomonas reinhardtii and an osmotolerant phenol-resistant bacterial strain isolated from the bay of Cartagena, Colombia. A total of three bacterial strains were tested (i.e. Stenotrophomonas maltophilia, Microbacterium paraoxydans and Paenibacillus lactis) individually and in consortium with C. reinhardtii. Our data indicate a significant increase in the growth rate and a reduction in the lag phase of microorganisms in the consortium as compared to microorganisms growing in isolation. Interestingly, the inoculum ratio 2:1 (bacteria-microalgae) was shown to be the most robust taking into account that both microorganisms improved their growth. Afterward, the phenol degradation capacity of pure cultures and consortia in the presence of different phenol concentrations was evaluated. Our results reveal that such consortia perform better at low phenol concentrations; more specifically, the consortium Microbacterium paraoxydans-Chlamydomonas reinhardtii was the most effective: it reached a 49.89% phenol removal.

Over the past decades, Colombia has suffered complex social problems related to illicit crops, including forced displacement, violence, and environmental damage, among other consequences for vulnerable populations. Considerable effort has been made in the regulation of illicit crops, predominantly Cannabis sativa, leading to advances such as the legalization of medical cannabis and its derivatives, the improvement of crops, and leaving an open window to the development of scientific knowledge to explore alternative uses. It is estimated that C. sativa can produce approximately 750 specialized secondary metabolites. Some of the most relevant due to their anticancer properties, besides cannabinoids, are monoterpenes, sesquiterpenoids, triterpenoids, essential oils, flavonoids, and phenolic compounds. However, despite the increase in scientific research on the subject, it is necessary to study the primary and secondary metabolism of the plant and to identify key pathways that explore its great metabolic potential. For this purpose, a genome-scale metabolic reconstruction of C. sativa is described and contextualized using LC-QTOF-MS metabolic data obtained from the leaf extract from plants grown in the region of Pesca-Boyaca, Colombia under greenhouse conditions at the Clever Leaves facility. A compartmentalized model with 2101 reactions and 1314 metabolites highlights pathways associated with fatty acid biosynthesis, steroids, and amino acids, along with the metabolism of purine, pyrimidine, glucose, starch, and sucrose. Key metabolites were identified through metabolomic data, such as neurine, cannabisativine, cannflavin A, palmitoleic acid, cannabinoids, geranylhydroquinone, and steroids. They were analyzed and integrated into the reconstruction, and their potential applications are discussed. Cytotoxicity assays revealed high anticancer activity against gastric adenocarcinoma (AGS), melanoma cells (A375), and lung carcinoma cells (A549), combined with negligible impact against healthy human skin cells.