Raman spectroscopy-based measurements of single-cell phenotypic diversity in microbial communities

Abstract 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 other processes such as stress tolerance, virulence or cell physiology. Metabolic stress is one such physiological changes and is typically quantified by measuring community phenotypic properties such as biomass growth, reactive oxygen species or cell permeability. However, community measurements do not take into account single-cell phenotypic diversity, important for a better understanding and management of microbial populations. Raman spectroscopy is a non-destructive alternative that provides detailed information on the biochemical make-up 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 non-treated. 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 composition 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 communities. Importance Microbes that live in the same community respond differently to stress. This phenomemon is known as phenotypic diversity. Describing this plethora of expressions can help to better understand and manage microbial processes. However, most tools to study phenotypic diversity only average the behaviour of the community. In this work, we present a way to quantify the phenotypic diversity of single cells using Raman spectroscopy - a tool that can describe the molecular profile of microbes. We demonstrate how this tool can be used to quantify the phenotypic diversity that arises after the exposure of microbes to stress. We also show its potential as an ‘alarm’ system to detect when communities are changing into a ‘stressed’ type.