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模拟大肠杆菌为适应温度突然上升而需完成的工作。

Modelling the work to be done by Escherichia coli to adapt to sudden temperature upshifts.

作者信息

Swinnen I A M, Bernaerts K, Van Impe J F

机构信息

BioTeC - Bioprocess Technology and Control, Katholieke Universiteit Leuven, Belgium.

出版信息

Lett Appl Microbiol. 2006 May;42(5):507-13. doi: 10.1111/j.1472-765X.2006.01896.x.

Abstract

AIMS

This paper studies and models the effect of the amplitude of a sudden temperature upshift DeltaT on the adaptation period of Escherichia coli, in terms of the work to be done by the cells during the subsequent lag phase (i.e., the product of growth rate mumax and lag phase duration lambda).

METHODS AND RESULTS

Experimental data are obtained from bioreactor experiments with E. coli K12 MG1655. At a predetermined time instant during the exponential growth phase, a sudden temperature upshift is applied (no other environmental changes take place). The length of the (possibly) induced lag phase and the specific growth rate after the shift are quantified with the growth model of Baranyi and Roberts (Int J Food Microbiol 23, 1994, 277). Different models to describe the evolution of the product lambda x mumax as a function of the amplitude of the temperature shift are statistically compared.

CONCLUSIONS

The evolution of lambda x mumax is influenced by the amplitude of the temperature shift DeltaT and by the normal physiological temperature range. As some cut-off is observed, the linear model with translation is preferred to describe this evolution.

SIGNIFICANCE AND IMPACT OF THE STUDY

This work contributes to the characterization of microbial lag phenomena, in this case for E. coli K12 MG1655, in view of accurate predictive model building.

摘要

目的

本文从细胞在随后的延迟期内需要完成的功(即生长速率μmₐₓ与延迟期持续时间λ的乘积)方面,研究并建立突然温度上升幅度ΔT对大肠杆菌适应期的影响模型。

方法与结果

实验数据来自对大肠杆菌K12 MG1655的生物反应器实验。在指数生长期的预定时刻,施加突然的温度上升(无其他环境变化)。用Baranyi和Roberts的生长模型(《国际食品微生物学杂志》23,1994,277)对(可能)诱导的延迟期长度和温度变化后的比生长速率进行量化。对描述乘积λ×μmₐₓ随温度变化幅度的函数演化的不同模型进行统计比较。

结论

λ×μmₐₓ的演化受温度变化幅度ΔT和正常生理温度范围的影响。由于观察到一些截止情况,具有平移的线性模型更适合描述这种演化。

研究的意义和影响

鉴于准确预测模型的建立,这项工作有助于对微生物延迟现象进行表征,在这种情况下是针对大肠杆菌K12 MG1655。

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