Castillo-Gómez Odette, Ramírez-Rivera Víctor M, Canto-Canché Blondy B, Valdez-Ojeda Ruby A
Unidad de Energía Renovable, Centro de Investigación Científica de Yucatán, Mérida, Mexico.
Unidad de Biotecnología, Centro de Investigación Científica de Yucatán, Mérida, Mexico.
Luminescence. 2019 Dec;34(8):859-869. doi: 10.1002/bio.3683. Epub 2019 Jul 25.
Increasing numbers of studies are using Aliivibrio fischeri (A. fischeri), a marine bioluminescent bacterium as a model, however the culture medium used for its growth are complex and expensive. The objectives of this study were: (1) to evaluate the effect of yeast extract, tryptone, and NaCl to select a simple and inexpensive culture medium suitable for A. fischeri growth and bioluminescence induction; and (2) to compare the performance of mathematical models to predict the growth of A. fischeri. A fractional factorial design was performed to evaluate the effect of yeast extract, tryptone, and sodium chloride on the luminescence of A. fischeri. The result showed that sodium chloride is the most important factor, congruent with its inducer role in bioluminescence. The best medium for bioluminescence induction was selected through an optimization plot, this medium is inexpensive, and generates the same luminescence as commercial formulations. The estimation of A. fischeri growth at OD measurement was statistically analyzed. All evaluated models fitted the data adequately (r > 0.96). The nonlinear models Gompertz, Richards and logistic provided a lower variation and a better fit of the growth estimation (r >0.99), showing that these mathematical models can be used for the accurate growth prediction of A. fischeri.
越来越多的研究使用费氏弧菌(Aliivibrio fischeri),一种海洋发光细菌作为模型,然而用于其生长的培养基复杂且昂贵。本研究的目的是:(1)评估酵母提取物、胰蛋白胨和氯化钠的作用,以选择一种适合费氏弧菌生长和生物发光诱导的简单且廉价的培养基;(2)比较数学模型预测费氏弧菌生长的性能。进行了析因设计以评估酵母提取物、胰蛋白胨和氯化钠对费氏弧菌发光的影响。结果表明氯化钠是最重要的因素,与其在生物发光中的诱导作用一致。通过优化图选择了用于生物发光诱导的最佳培养基,该培养基价格低廉,并且产生与商业配方相同的发光效果。对在OD测量时费氏弧菌的生长估计进行了统计分析。所有评估的模型都能充分拟合数据(r > 0.96)。非线性模型Gompertz、Richards和逻辑模型提供了更低的变异和更好的生长估计拟合度(r > 0.99),表明这些数学模型可用于准确预测费氏弧菌的生长。