Single-cell multi-parametric characterization of microbiota by flow cytometry

Abstract

It has become evident, that the microbes colonizing the human body have a great impact on health and disease. Investigations of microbiota currently primarily rely on culturomics, high-throughput sequencing and metaproteomics which have considerably advanced our knowledge regarding the role of the microbiota in our environment and for our health. While single-cell phenotyping of immune cells and other somatic cells by flow cytometry has become widely used, the detailed analysis of bacterial cells such as the human microbiota on the single-cell level, is lagging behind. Here, we outline a protocol for the single-cell characterization of bacterial cells from complex microbiota samples, such as stool, by multi-parametric flow cytometry. Our protocol describes the isotype-specific detection of host-antibody coating of intestinal bacteria ex vivo, which together with quantitative DNA staining and light scatter detection comprise an individual's microbiota fingerprint. Cryoconservation and appropriate staining controls ensure reliable, reproducible data generation and analysis. We have automated the analysis of the multi-dimensional data using a segmentation approach by self-organizing map (SOM) algorithm for downstream comparative analyses. Our protocol can be adapted to integrate further phenotypic markers and uses the power of analytical cytometry for the characterization of bacteria on the single-cell level.

Keywords: Antibody; Flow cytometry; Microbiota; Self-organizing map.