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细菌单细胞参数的分布及其从浊度检测时间的估计。

Distribution of bacterial single cell parameters and their estimation from turbidity detection times.

机构信息

Hungarian University of Agriculture and Life Sciences, Department of Food Microbiology, Hygiene and Safety, Budapest, Hungary.

Eötvös Loránd University, Department of Microbiology, Budapest, Hungary.

出版信息

Food Microbiol. 2022 Jun;104:103972. doi: 10.1016/j.fm.2021.103972. Epub 2021 Dec 20.

Abstract

The stochastic growth of homogeneous bacterial populations in the wells of a microtiter plate was studied as a function of the random initial cell number and their random individual lag times. These significantly affected the population growth in the well, while the maximum specific growth rate of the population was constant (or its variance was negligible) for each well. We showed the advantages of the mathematical assumption that a transformation of the single cell lag time, called the single cell physiological state (or, more accurately, that of the sub-population generated by the single cell) follow the Beta distribution. Simulations demonstrated what patterns would such assumption generate for the distribution of the detection times observed in the wells. An estimation procedure was developed, based on the beta-assumption, that resulted in an explicit expression for the expected value of the single cell physiological state as a function of measured "time to detection" values using turbidity experiments. The method was illustrated using laboratory data with Escherichia coli, Salmonella enterica subsp. enterica strains. The results gave a basis to quantify the difference between the studied organisms in terms of their single-cell kinetics.

摘要

研究了微滴定板孔中同质细菌群体的随机生长情况,作为随机初始细胞数和其随机个体滞后时间的函数。这些因素显著影响了孔内的种群增长,而种群的最大比生长速率在每个孔中保持不变(或其方差可忽略不计)。我们展示了一个数学假设的优势,即单细胞滞后时间的转换,称为单细胞生理状态(或者更准确地说,是由单细胞产生的亚群的生理状态)遵循 Beta 分布。模拟表明,这种假设会为在孔中观察到的检测时间分布生成什么样的模式。基于 Beta 假设,开发了一种估计程序,该程序给出了在使用浊度实验测量的“检测到的时间”值的基础上,作为单细胞生理状态的函数的预期值的显式表达式。该方法使用大肠杆菌和肠炎沙门氏菌亚种的实验室数据进行了说明。结果为定量研究不同生物体的单细胞动力学差异提供了基础。

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