Evolutionary engineering and molecular characterization of cobalt-resistant .

With its versatile metabolism including aerobic and anaerobic respiration, photosynthesis, photo-fermentation and nitrogen fixation, can adapt to diverse environmental and nutritional conditions, including the presence of various stressors such as heavy metals. Thus, it is an important microorganism to study the molecular mechanisms of bacterial stress response and resistance, and to be used as a microbial cell factory for biotechnological applications or bioremediation. In this study, a highly cobalt-resistant and genetically stable strain was obtained by evolutionary engineering, also known as adaptive laboratory evolution (ALE), a powerful strategy to improve and characterize genetically complex, desired microbial phenotypes, such as stress resistance.

From to Ethanol: Unlocking the Power of Evolutionary Engineering in Metabolic Engineering Applications.

Increased human population and the rapid decline of fossil fuels resulted in a global tendency to look for alternative fuel sources. Environmental concerns about fossil fuel combustion led to a sharp move towards renewable and environmentally friendly biofuels. Ethanol has been the primary fossil fuel alternative due to its low carbon emission rates, high octane content and comparatively facile microbial production processes.

Genomic, transcriptomic, and metabolic characterization of 2-Phenylethanol-resistant obtained by evolutionary engineering.

2-Phenylethanol is an aromatic compound commonly used in the food, cosmetic, and pharmaceutical industries. Due to increasing demand for natural products by consumers, the production of this flavor by microbial fermentation is gaining interest, as a sustainable alternative to chemical synthesis or expensive plant extraction, both processes relying on the use of fossil resources. However, the drawback of the fermentation process is the high toxicity of 2-phenylethanol to the producing microorganism.

Comprehensive genome-scale metabolic model of the human pathogen : A platform for understanding pathogen metabolism and identifying new drug targets.

The fungal priority pathogen causes cryptococcal meningoencephalitis in immunocompromised individuals and leads to hundreds of thousands of deaths per year. The undesirable side effects of existing treatments, the need for long application times to prevent the disease from recurring, the lack of resources for these treatment methods to spread over all continents necessitate the search for new treatment methods. Genome-scale models have been shown to be valuable in studying the metabolism of many organisms.