延长雨红球菌绿色阶段作为高效虾青素生产的关键前体:田口设计优化

IF 3.7 3区 生物学 Q2 BIOTECHNOLOGY & APPLIED MICROBIOLOGY
Christina Samara, Alexandros Biziouras, Georgia Papapanagiotou, Christos Chatzidoukas
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引用次数: 0

摘要

在多种胁迫条件下,雨红球藻的天然抗氧化剂虾青素积累量可达其干重的5% %。提高这一比例仍然具有挑战性;因此,有效生产虾青素的关键在于在诱导胡萝卜形成之前形成一个充满活力、高密度和同步的绿色细胞群体。尽管其重要性,营养生长阶段的优化往往被低估。本研究采用L9-Taguchi试验设计,系统研究了温度、碳酸氢钠、氮、磷4个关键栽培因子对雨毛藻营养生长的组合影响。温度是影响生物量产量的最主要因素,随着温度的增加,温度对生物量产量的影响呈负相关。氮和磷的限制加上碳酸氢钠的补充导致过早地转移到非增殖的红色阶段。总体而言,确定的营养阶段维持和生物量最大化的最佳条件为:22°C, 250 mg L−1碳酸氢钠,150 mg L−1氮和40 mg L−1磷。这些条件导致15天后产生1.53 g L−1的绿色干生物量,优于0.3 g L−1的次优绿期条件。田口导出的预测经过实验验证,为密集而强健的绿色细胞群的形成铺平了道路,这些细胞群将随之转移到红色阶段。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Extending the green stage of Haematococcus pluvialis as a crucial precursor for efficient astaxanthin production: Optimization via Taguchi design
The microalga Haematococcus pluvialis can accumulate the natural antioxidant astaxanthin up to 5 % of its dry weight under multi-stress conditions. Increasing this percentage remains challenging; therefore, the key to efficient astaxanthin production lies significantly on the formation of a vigorous, high-density, and synchronized green-cell population prior to the induction of carotogenesis. Despite its importance, optimization of the vegetative growth phase is often underestimated. This study employs an L9-Taguchi design of experiments to systematically investigate the combinatorial effects of four key cultivation factors - temperature, sodium bicarbonate, nitrogen, and phosphorus - on the vegetative growth of H. pluvialis. Temperature emerges as the most influential factor for biomass production, showing an adverse effect with its increment. Nitrogen and phosphorus limitation combined with sodium bicarbonate supplementation induces a premature shift to the non-proliferative red stage. Overall, the optimal conditions identified for vegetative stage maintenance and biomass maximization are: 22 °C, 250 mg L−1 sodium bicarbonate, 150 mg L−1 nitrogen and 40 mg L−1 phosphorus. These conditions result in the production of 1.53 g L−1 green dry biomass after 15 days of cultivation, outperforming by 0.3 g L−1 suboptimal green phase conditions. Post-verification of the Taguchi-derived predictions is experimentally demonstrated paving the way for the formulation of dense and robust green-cell populations that will be concomitantly transferred to the red stage.
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来源期刊
Biochemical Engineering Journal
Biochemical Engineering Journal 工程技术-工程:化工
CiteScore
7.10
自引率
5.10%
发文量
380
审稿时长
34 days
期刊介绍: The Biochemical Engineering Journal aims to promote progress in the crucial chemical engineering aspects of the development of biological processes associated with everything from raw materials preparation to product recovery relevant to industries as diverse as medical/healthcare, industrial biotechnology, and environmental biotechnology. The Journal welcomes full length original research papers, short communications, and review papers* in the following research fields: Biocatalysis (enzyme or microbial) and biotransformations, including immobilized biocatalyst preparation and kinetics Biosensors and Biodevices including biofabrication and novel fuel cell development Bioseparations including scale-up and protein refolding/renaturation Environmental Bioengineering including bioconversion, bioremediation, and microbial fuel cells Bioreactor Systems including characterization, optimization and scale-up Bioresources and Biorefinery Engineering including biomass conversion, biofuels, bioenergy, and optimization Industrial Biotechnology including specialty chemicals, platform chemicals and neutraceuticals Biomaterials and Tissue Engineering including bioartificial organs, cell encapsulation, and controlled release Cell Culture Engineering (plant, animal or insect cells) including viral vectors, monoclonal antibodies, recombinant proteins, vaccines, and secondary metabolites Cell Therapies and Stem Cells including pluripotent, mesenchymal and hematopoietic stem cells; immunotherapies; tissue-specific differentiation; and cryopreservation Metabolic Engineering, Systems and Synthetic Biology including OMICS, bioinformatics, in silico biology, and metabolic flux analysis Protein Engineering including enzyme engineering and directed evolution.
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