Rapid detection and online analysis of microbial changes through flow cytometry

Short-read 16 S rRNA gene sequencing is the dominating technology to profile microbial communities in different habitats. Its uncontested taxonomic resolution paved the way for major contributions to the field. Sample measurement and analysis, that is, sequencing, is rather slow-in order of days. Alternatively, flow cytometry can be used to profile the microbiota of various sources within a few minutes per sample. To keep up with high measurement speed, we developed the open source-analyzing tool FlowSoFine. To validate the ability to distinguish microbial profiles, we examined human skin samples of three body sites (N = 3 × 54) with flow cytometry and 16 S rRNA gene amplicon sequencing. Confirmed by sequencing of the very same samples, body site was found to be significantly different by flow cytometry. For a proof-of-principle multidimensional approach, using stool samples of patients (N = 40) with/without inflammatory bowel diseases, we could discriminate the health status by their bacterial patterns. In conclusion, FlowSoFine enables the generation and comparison of cytometric fingerprints of microbial communities from different sources. The implemented interface supports the user through all analytical steps to work out the biological relevant signals from raw measurements to publication ready figures. Furthermore, we present flow cytometry as a valid method for skin microbiota analysis.