Delvigne Frank, Baert Jonathan, Sassi Hosni, Fickers Patrick, Grünberger Alexander, Dusny Christian
University of Liège, TERRA research center, Gembloux Agro-Bio Tech, Microbial Processes and Interactions (MiPI lab), Gembloux, Belgium.
Forschungszentrum Jülich GmbH, IBG-1: Biotechnology, Jülich, Germany.
Biotechnol J. 2017 Jul;12(7). doi: 10.1002/biot.201600549. Epub 2017 May 24.
Phenotypic plasticity of microbial cells has attracted much attention and several research efforts have been dedicated to the description of methods aiming at characterizing phenotypic heterogeneity and its impact on microbial populations. However, different approaches have also been suggested in order to take benefit from noise in a bioprocess perspective, e.g. by increasing the robustness or productivity of a microbial population. This review is dedicated to outline these controlling methods. A common issue, that has still to be addressed, is the experimental identification and the mathematical expression of noise. Indeed, the effective interfacing of microbial physiology with external parameters that can be used for controlling physiology depends on the acquisition of reliable signals. Latest technologies, like single cell microfluidics and advanced flow cytometric approaches, enable linking physiology, noise, heterogeneity in productive microbes with environmental cues and hence allow correctly mapping and predicting biological behavior via mathematical representations. However, like in the field of electronics, signals are perpetually subjected to noise. If appropriately interpreted, this noise can give an additional insight into the behavior of the individual cells within a microbial population of interest. This review focuses on recent progress made at describing, treating and exploiting biological noise in the context of microbial populations used in various bioprocess applications.
微生物细胞的表型可塑性已引起广泛关注,并且已有多项研究致力于描述旨在表征表型异质性及其对微生物群体影响的方法。然而,为了从生物过程的角度利用噪声,例如通过提高微生物群体的稳健性或生产力,也有人提出了不同的方法。本综述致力于概述这些控制方法。一个仍有待解决的常见问题是噪声的实验识别和数学表达。事实上,微生物生理学与可用于控制生理学的外部参数的有效对接取决于可靠信号的获取。最新技术,如单细胞微流体技术和先进的流式细胞术方法,能够将生产性微生物的生理学、噪声、异质性与环境线索联系起来,从而通过数学表示正确地描绘和预测生物行为。然而,就像在电子领域一样,信号总是会受到噪声的干扰。如果能得到恰当的解读,这种噪声可以为感兴趣的微生物群体中单个细胞的行为提供额外的见解。本综述重点关注在各种生物过程应用中使用的微生物群体背景下,在描述、处理和利用生物噪声方面取得的最新进展。