Application of response surface Methodology coupled with Artificial Neural network and genetic algorithm to model and optimize symbiotic interactions between Chlorella vulgaris and Stutzerimonas stutzeri strain J3BG for chlorophyll accumulation.

Research on microalgae has surged due to its diverse biotechnological applications and capacity for accumulating bioactive compounds. Despite considerable advancements, microalgal cultivation remains costly, prompting efforts to reduce expenses while enhancing productivity. This study proposes a cost-effective approach through the coculture of microalgae and bacteria, exploiting mutualistic interactions. An engineered consortium of Chlorella vulgaris and Stutzerimonas stutzeri strain J3BG demonstrated biofilm-like arrangements, indicative of direct cell-to-cell interactions and metabolite exchange. Strain J3BG's enzymatic characterization revealed amylase, lipase, and protease production, sustaining mutual growth. Employing Response Surface Methodology (RSM), Artificial Neural Network (ANN), and Genetic Algorithm (GA) in a hybrid modeling approach resulted in a 2.1-fold increase in chlorophyll production. Optimized conditions included a NaNO3 concentration of 128.52 mg/l, a 1:2 (Algae:Bacteria) ratio, a 6-day cultivation period, and a pH of 5.4, yielding 10.92 ± 0.88 mg/l chlorophyll concentration.

Insights into Genomic Features and Potential Biotechnological Applications of Bacillus halotolerans Strain HGR5.

Algeria is one of the wealthiest countries in terms of hydrothermal sources, with more than two hundred hot springs. However, diverse and little-described microbial communities colonize these habitats, making them an intriguing research subject. This work reports the isolation of bacteria from two hot springs water samples in northeastern Algeria, evaluating their enzymatic activities and effect on plant pathogens. Out of the obtained 72 bacterial isolates and based on the 16S rRNA gene sequence analysis, the strain HGR5 belonging to Bacillus halotolerans had the most interesting activity profile. Interestingly, HGR5 was substantially active against Fusarium graminearum, Phytophthora infestans, and Alternaria alternata. Furthermore, this strain presented a high ability to degrade casein, Tween 80, starch, chitin, cellulose, and xylan. The genome sequence of HGR5 allowed taxonomic validation and screening of specific genetic traits, determining its antagonistic and enzymatic activities. Genome mining revealed that strain HGR5 encloses several secondary metabolite biosynthetic gene clusters (SM-BGCs) involved in metabolite production with antimicrobial properties. Thus, antimicrobial metabolites included bacillaene, fengycin, laterocidine, bacilysin, subtilosin, bacillibactin, surfactin, myxovirescin, dumulmycin, and elansolid A1. HGR5 strain genome was also mined for CAZymes associated with antifungal activity. Finally, the HGR5 strain exhibited the capacity to degrade polycaprolactone (PCL), a model substrate for polyester biodegradation. Overall, these results suggest that this strain may be a promising novel biocontrol agent with interesting plastic-degradation capability, opening the possibilities of its use in various biotechnological applications.