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Individual cell heterogeneity as variability source in population dynamics of microbial inactivation

机译：个体细胞异质性作为微生物灭活种群动态的变异性来源

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摘要

A statistical modeling approach was applied for describing and evaluating the individual cell heterogeneity as variability source in microbial inactivation. The inactivation data (N_t vs time) of Salmonella enterica serotype Agona, with initial concentration N_0 = 10~9 CFU/ml in acidified tryptone soy broth (pH 3.5), were transformed to (No - N_t)/No vs time leading to the cumulative probability distribution of the individual cell inactivation times (t_i), which was further fitted to a variety of continuous distributions using @Risk software. The best-fitted t_i distribution (Gamma) was used to predict the inactivation of S. Agona populations of various N_0 using Monte Carlo simulation, with the number of iterations in each simulation being equal to N_0 and the number of simulations representing the variability of the population inactivation behavior. The Monte Carlo simulation results for a population with N_0 = 10,000 CFU/ ml showed that the variability in the predicted inactivation behavior is negligible for concentrations down to 100 cells. As the concentration decreases below 100 cells, however, the variability increases significantly. The results also indicated that the D-value used in deterministic first order kinetic models is valid only for large populations. For small populations, D-value shows a high variability, originating from individual cell heterogeneity, and, thus, can be better characterized by a probability distribution rather than a uniform value. Validation experiments with small populations confirmed the variability predicted by the statistical model. The use of the proposed approach to quantify the variability in the inactivation of mixed microbial populations, consisting of subpopulations with different probability distributions of t_i, was also demonstrated.
机译：统计建模方法用于描述和评估单个细胞异质性作为微生物灭活的变异性来源。在酸化胰蛋白so大豆肉汤（pH 3.5）中初始浓度为N_0 = 10〜9 CFU / ml的肠炎沙门氏菌血清型Agona的失活数据（N_t对时间）转化为（No-N_t）/ No对时间，从而导致单个细胞失活时间的累积概率分布（t_i），使用@Risk软件进一步拟合为各种连续分布。使用最合适的t_i分布（Gamma），使用蒙特卡洛模拟法预测各种N_0的S. Agona种群的失活，每个模拟中的迭代次数等于N_0，并且模拟次数表示变量的可变性。人口灭活行为。 N_0 = 10,000 CFU / ml的种群的蒙特卡洛模拟结果表明，对于低至100个细胞的浓度，预测的失活行为的变异性可以忽略不计。但是，当浓度降低到100个细胞以下时，变异性显着增加。结果还表明，确定性一阶动力学模型中使用的D值仅对大种群有效。对于较小的种群，D值显示出较高的可变性，其起源于单个细胞的异质性，因此可以通过概率分布而不是均匀值更好地表征。少数人群的验证实验证实了统计模型预测的可变性。还证明了使用所提出的方法来量化混合微生物种群灭活中的变异性，该变异性由具有不同概率分布t_i的亚种群组成。

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  • 来源
    《Food microbiology》 |2015年第febaptab期|216-221|共6页
  • 作者

    Zafiro Aspridou; Konstantinos P. Koutsoumanis;

  • 作者单位

    Laboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessahniki 54124, Greece;

    Laboratory of Food Microbiology and Hygiene, Department of Food Science and Technology, School of Agriculture, Forestry and Natural Environment, Aristotle University of Thessaloniki, Thessahniki 54124, Greece;

  • 收录信息 美国《科学引文索引》(SCI);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Salmonella enterica; Microbial inactivation; Variability; Individual cell;

    机译：肠沙门氏菌微生物灭活;变化性;个别细胞;

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