Discriminating bacterial phenotypes at the population and single-cell level: a comparison of flow cytometry and Raman spectroscopy fingerprinting

Abstract Background Investigating phenotypic heterogeneity can help to better understand and manage microbial communities. However, characterizing phenotypic heterogeneity remains a challenge, as there is no standardized analysis framework. Several optical tools are available, such as flow cytometry and Raman spectroscopy, which describe properties of the individual cell. Results In this work, we compare Raman spectroscopy and flow cytometry to study phenotypic heterogeneity in bacterial populations. The growth stages of three replicate E. coli populations were characterized using both technologies. Our findings show that flow cytometry detects and quantifies shifts in phenotypic heterogeneity at the population level due to its high-throughput nature. Raman spectroscopy, on the other hand, offers a much higher resolution at the single-cell level (i.e. more biochemical information is recorded). Therefore, it is capable of identifying distinct phenotypic populations in an automated way when coupled with analyses tailored towards single-cell data. In addition, it provides information about biomolecules that are present, which can be linked to cell functionality. Conclusions We propose a workflow to distinguish between bacterial phenotypic populations using Raman spectroscopy and validated this approach with an external dataset. We recommend to apply flow cytometry to quantify phenotypic heterogeneity at the population level, and Raman spectroscopy to perform a more in-depth analysis of heterogeneity at the single-cell level.