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Raman Spectroscopy-Based Measurements of Single-Cell Phenotypic Diversity in Microbial Populations
mSphere ( IF 3.7 ) Pub Date : 2020-10-28 , DOI: 10.1128/msphere.00806-20
Cristina García-Timermans 1 , Ruben Props 1 , Boris Zacchetti 2 , Myrsini Sakarika 1 , Frank Delvigne 2 , Nico Boon 3
Affiliation  

Microbial cells experience physiological changes due to environmental change, such as pH and temperature, the release of bactericidal agents, or nutrient limitation. This has been shown to affect community assembly and physiological processes (e.g., stress tolerance, virulence, or cellular metabolic activity). Metabolic stress is typically quantified by measuring community phenotypic properties such as biomass growth, reactive oxygen species, or cell permeability. However, bulk community measurements do not take into account single-cell phenotypic diversity, which is important for a better understanding and the subsequent management of microbial populations. Raman spectroscopy is a nondestructive alternative that provides detailed information on the biochemical makeup of each individual cell. Here, we introduce a method for describing single-cell phenotypic diversity using the Hill diversity framework of Raman spectra. Using the biomolecular profile of individual cells, we obtained a metric to compare cellular states and used it to study stress-induced changes. First, in two Escherichia coli populations either treated with ethanol or nontreated and then in two Saccharomyces cerevisiae subpopulations with either high or low expression of a stress reporter. In both cases, we were able to quantify single-cell phenotypic diversity and to discriminate metabolically stressed cells using a clustering algorithm. We also described how the lipid, protein, and nucleic acid compositions changed after the exposure to the stressor using information from the Raman spectra. Our results show that Raman spectroscopy delivers the necessary resolution to quantify phenotypic diversity within individual cells and that this information can be used to study stress-driven metabolic diversity in microbial populations.

中文翻译:

基于拉曼光谱的微生物种群单细胞表型多样性测量

微生物细胞会因环境变化而发生生理变化,例如 pH 值和温度、杀菌剂的释放或营养限制。这已被证明会影响群落组装和生理过程(例如,压力耐受性、毒力或细胞代谢活动)。代谢压力通常通过测量群落表型特性(例如生物量生长、活性氧或细胞渗透性)来量化。然而,大量群落测量并未考虑单细胞表型多样性,这对于更好地理解和随后管理微生物种群很重要。拉曼光谱是一种无损替代方法,可提供有关每个细胞的生化组成的详细信息。这里,我们介绍了一种使用拉曼光谱的希尔多样性框架来描述单细胞表型多样性的方法。使用单个细胞的生物分子概况,我们获得了一个指标来比较细胞状态,并用它来研究压力引起的变化。首先,在两个大肠杆菌群体要么用乙醇处理,要么未经处理,然后在两个酿酒酵母亚群中,压力报告基因的表达要么高要么低。在这两种情况下,我们都能够量化单细胞表型多样性并使用聚类算法区分代谢应激细胞。我们还使用来自拉曼光谱的信息描述了脂质、蛋白质和核酸成分在暴露于压力源后如何变化。我们的结果表明,拉曼光谱提供了量化单个细胞内表型多样性所需的分辨率,并且该信息可用于研究微生物种群中压力驱动的代谢多样性。
更新日期:2020-10-30
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