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细菌随机游动和趋化性系数的测量:二、基于单细胞的数学模型的应用。

Measurement of bacterial random motility and chemotaxis coefficients: II. Application of single-cell-based mathematical model.

机构信息

Department of Chemical Engineering, University of Pennsylvania, Philadelphia, Pennsylvania 19104, USA.

出版信息

Biotechnol Bioeng. 1991 Mar 25;37(7):661-72. doi: 10.1002/bit.260370708.

Abstract

A quantitative description of bacterial chemotaxis is necessary for making predictions about the migratory behavior of bacterial populations in applications such as biofilm development, release of genetically engineered bacteria into the environment, and in situ bioremediation technologies. The bacterial chemotactic response is characterized by a mathematical model which relates individual cell properties such as swimming speed and tumbling frequency to population parameters, specifically the random motility coefficient and the chemotactic sensitivity coefficient. Our model includes a nonlinear dependence of the chemotactic velocity on the attractant gradient as well as a dependence of the random motility coefficient on the temporal and spatial attractant gradients, both of which previous analyses have neglected. As we will show, these aspects are critical for interpreting the results from experiments like those performed in the stopped-flow diffusion chamber (SFDC) because the initial temporal and spatial gradients are very steep. Our analysis demonstrates that values for the random motility coefficient and chemotactic sensitivity coefficient can be obtained from experimental plots of net cell redistribution from initial conditions versus the square root of time. Values for these parameters are determined from experimental measurements of bacterial population distributions in the SFDC as described in the companion article. Using parameter values determined from independent experiments, mu = 1.1 +/- 0.4 +/- 10(-5) cm(2)/s and chi(0) = 8 +/- 3 +/- 10(-5) cm(2)/s, excellent agreement is found between theoretically predicted bacterial density profiles and actual experimental profiles for Escherichia coli K12 responding to fucose over two orders of magnitude in initial attractant concentration. Thus, our model captures the concentration dependence of this behavioral response satisfactorily in terms of cell population parameters which are derived from individual cell properties and will therefore be useful for making predictions about the migratory behavior of bacterial populations in the environment.

摘要

定量描述细菌的趋化性对于预测细菌群体在生物膜发展、遗传工程菌释放到环境中和原位生物修复技术等应用中的迁移行为是必要的。细菌的趋化反应特征是一个数学模型,该模型将个体细胞特性(如游泳速度和翻转频率)与种群参数(即随机运动系数和趋化敏感性系数)联系起来。我们的模型包括趋化速度对引诱剂梯度的非线性依赖性,以及随机运动系数对时间和空间引诱剂梯度的依赖性,这两个方面之前的分析都忽略了。正如我们将展示的,这些方面对于解释像在停止流动扩散室 (SFDC) 中进行的实验结果至关重要,因为初始的时间和空间梯度非常陡峭。我们的分析表明,可以从实验中获得关于净细胞再分配的初始条件与时间平方根的实验图来获取随机运动系数和趋化敏感性系数的值。这些参数的值是通过在 SFDC 中对细菌群体分布的实验测量确定的,如伴侣文章中所述。使用从独立实验确定的参数值,mu = 1.1 +/- 0.4 +/- 10(-5) cm(2)/s 和 chi(0) = 8 +/- 3 +/- 10(-5) cm(2)/s,对于响应于果糖的大肠杆菌 K12,在初始引诱剂浓度的两个数量级范围内,理论预测的细菌密度分布与实际实验分布之间存在极好的一致性。因此,我们的模型在个体细胞特性推导的细胞群体参数方面很好地捕捉了这种行为反应的浓度依赖性,因此对于预测环境中细菌群体的迁移行为将是有用的。

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