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首页> 外文期刊>Applied Microbiology >Intra- and Interspecies Variability of Single-Cell Innate Fluorescence Signature of Microbial Cell
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Intra- and Interspecies Variability of Single-Cell Innate Fluorescence Signature of Microbial Cell

机译：种间和种间变异的微生物细胞的单细胞固有荧光签名。

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Here we analyzed the innate fluorescence signature of the single microbial cell, within both clonal and mixed populations of microorganisms. We found that even very similarly shaped cells differ noticeably in their autofluorescence features and that the innate fluorescence signatures change dynamically with growth phases. We demonstrated that machine learning models can be trained with a data set of single-cell innate fluorescence signatures to annotate cells according to their phenotypes and physiological status, for example, distinguishing a wild-type Aspergillus nidulans cell from its nitrogen metabolism mutant counterpart and log-phase cells from stationary-phase cells of Pseudomonas putida. We developed a minimally invasive method (confocal reflection microscopy-assisted single-cell innate fluorescence [CRIF] analysis) to optically extract and catalog the innate cellular fluorescence signatures of each of the individual live microbial cells in a three-dimensional space. This technique represents a step forward from traditional techniques which analyze the innate fluorescence signatures at the population level and necessitate a clonal culture. Since the fluorescence signature is an innate property of a cell, our technique allows the prediction of the types or physiological status of intact and tag-free single cells, within a cell population distributed in a three-dimensional space. Our study presents a blueprint for a streamlined cell analysis where one can directly assess the potential phenotype of each single cell in a heterogenous population by its autofluorescence signature under a microscope, without cell tagging.IMPORTANCE A cell’s innate fluorescence signature is an assemblage of fluorescence signals emitted by diverse biomolecules within a cell. It is known that the innate fluoresce signature reflects various cellular properties and physiological statuses; thus, they can serve as a rich source of information in cell characterization as well as cell identification. However, conventional techniques focus on the analysis of the innate fluorescence signatures at the population level but not at the single-cell level and thus necessitate a clonal culture. In the present study, we developed a technique to analyze the innate fluorescence signature of a single microbial cell. Using this novel method, we found that even very similarly shaped cells differ noticeably in their autofluorescence features, and the innate fluorescence signature changes dynamically with growth phases. We also demonstrated that the different cell types can be classified accurately within a mixed population under a microscope at the resolution of a single cell, depending solely on the innate fluorescence signature information. We suggest that single-cell autofluoresce signature analysis is a promising tool to directly assess the taxonomic or physiological heterogeneity within a microbial population, without cell tagging.
机译：在这里，我们分析了微生物的克隆种群和混合种群中单个微生物细胞的固有荧光特征。我们发现，即使形状非常相似的细胞，其自发荧光特征也存在明显差异，并且先天荧光标记会随生长期动态变化。我们证明了可以使用单细胞先天荧光信号的数据集训练机器学习模型，以根据它们的表型和生理状态注释细胞，例如，将野生型构巢曲霉细胞与其氮代谢突变体对应物和对数区分开来恶臭假单胞菌的固定相细胞中我们开发了一种微创方法（共焦反射显微镜辅助的单细胞先天荧光[CRIF]分析），以光学方式提取和分类三维空间中每个单独的活微生物细胞的先天细胞荧光特征。这项技术代表了从传统技术向前迈出的一步，传统技术分析了群体水平上的先天荧光特征并需要进行克隆培养。由于荧光标记是细胞的先天特性，因此我们的技术可以预测在三维空间中分布的细胞群中完整且无标签的单个细胞的类型或生理状态。我们的研究提出了一种简化细胞分析的蓝图，其中人们可以通过显微镜下的自身荧光特征直接评估异源群体中每个单个细胞的潜在表型，而无需细胞标记。细胞内各种生物分子发出的光。众所周知，先天的荧光特征反映了各种细胞特性和生理状态。因此，它们可以作为细胞表征和细胞鉴定的丰富信息来源。然而，常规技术集中于在群体水平而不是在单细胞水平上分析先天荧光特征，因此需要克隆培养。在本研究中，我们开发了一种技术来分析单个微生物细胞的固有荧光特征。使用这种新颖的方法，我们发现，即使形状非常相似的细胞，其自发荧光特征也明显不同，并且先天的荧光特征会随生长期动态变化。我们还证明，可以在显微镜下以单个细胞的分辨率将混合细胞中的不同细胞类型准确分类，这完全取决于先天荧光标记信息。我们建议单细胞自发荧光签名分析是一种有前途的工具，可以直接评估微生物种群内的分类学或生理学异质性，而无需细胞标记。

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