Maximization of growth and lipid production of a toxic isolate of Anabaena circinalis by optimization of various parameters with mathematical modeling and computational validation.

Toxic cyanobacterial blooms are recurrent for few decades throughout the globe, due to climate change, atmospheric warming and various anthropogenic activities with severe impacts of potential toxins on various ecosystems finally affecting the entire environment. These cyanobacteria are merely unexplored regarding their biochemical components except toxins. Variable influences and interactions of different factors including nitrogen, carbon, and availability of light are well known to crucially regulate cyanobacterial growth and metabolism. Thus, current research work is motivated for the evaluation and optimization of the effects of the aforementioned vital factors for improvement of biomass and lipid production of a freshwater, toxic strain of Anabaena circinalis. The modelling and optimization of factors such as nitrogen, light intensity and bicarbonate concentration (source of carbon) to maximize growth and lipid production were based on 20 design point experiments by Response Surface Methodology (RSM) and optimized values were further improved and validated by Particle Swarm Optimization (PSO) algorithm. The maximum optima were obtained 1.829 g L-1 and 39.64 % for biomass production and lipid content respectively from PSO optimization with two different sets of optimal values of factors. It shows 0.44 % and 2.77 % higher values of responses than that of RSM optimization. These asynchronous findings pioneered the enhanced lipid accumulation as well as the growth of a toxic cyanobacterium by optimizing interaction effects of culture conditions through various statistical and computational approaches.

A comparative assessment of growth, pigment and enhanced lipid production by two toxic freshwater cyanobacteria Anabaena circinalis FSS 124 and Cylindrospermopsis raciborskii FSS 127 under various combinations of nitrogen and phosphorous inputs.

Nitrogen and phosphorous are important nutritional regulators for the growth of cyanobacteria, thereby having a significant impact in bloom formation by toxic species. Usage of toxic cyanobacteria for increasing valuable metabolite production by nutrient manipulation is still unexplored. Hence, the current work is aimed to estimate and compare growth, pigment, and increased lipid production coupled with the identification of fatty acids between two toxic strains-Anabaena circinalis FSS 124 and Cylindrospermopsis raciborskii FSS 127 under various combinations of these two nutrients. Low level of nitrogen and phosphorous enhanced lipid content in both strains (˃ 20% and 30% respectively) and C. raciborskii, respectively. Lipid productivity in low phosphorous concentration (P0.5) was achieved significantly high in C. raciborskii. Similarly, a substantial amount of carotenoids was obtained at reduced nitrogen and phosphorous in C. raciborskii accompanied by lessened growth and Chl a concentration. Unlikely, enough biomass (˃ 2 g L-1) was produced at high nutrient levels in both species. Comparative statistical significance (p < 0.05) was found between two species regarding biomass production, chlorophyll concentration, lipid content, and productivity and between these factors in each species under both nutrient variations. FAME of Cylindrospermopsis is composed of saturated fatty acids (˃ 50%) and MUFA (˃ 25%) while Anabaena contains PUFA (˃ 21%) additionally. However, the study highlights C. raciborskii as potential lipid and carotenoid producer at nutrient stress and finds a novel way to utilize these cyanobacterial biomasses, which cause immense environmental hazards and life threats.

Computational optimization of in vitro parameters for di-(2-ethylhexyl) phthalate production from Anabaena circinalis.

Di-(2-ethylhexyl) phthalate (DEHP) is a ubiquitous environmental toxicant, and finds extensive commercial application as a plasticizer to reduce the rigidity of polyvinyl chloride. Besides numerous negative impacts on environment and public health, the compound exhibits acute bioactivity against microbes and has therapeutic value too. Considering this biochemical significance, searching of its new biogenic sources has become an active area of research. Here, DEHP is identified from the biomass of a toxic strain of Anabaena circinalis, which is quite unobvious, and simultaneously, the in vitro physical conditions are optimized by using a swarm-based multiparameter optimization technique. A purified fraction collected from column chromatography is subjected to gas chromatography (GC) to fetch the compound peak and then subsequent mass analysis for its identification. The mass spectrum describes the molecular weight along with the structure of DEHP with 99.9% experimental accuracy. An experimental observation table has been used to frame a fitness function using the curve fitting approach when temperature (T), light and dark period (LD), and duration of subculture cycle (DSC) are considered as the target parameters to be optimized. The optimum values obtained for T, LD, and DSC are 20°C, 14:10 hour light and dark ratio approximately, and 40 days, respectively. This experimental finding of A. circinalis FSS 124 as a novel source of DEHP and subsequent optimization using soft computing tools might be a benchmark for process optimization in biological research.