Using fluorescence flow cytometry data for single-cell gene expression analysis in bacteria.

ABSTRACT: Fluorescence flow cytometry is increasingly being used to quantify single-cell expression distributions in bacteria in high-throughput. However, there has been no systematic investigation into the best practices for quantitative analysis of such data, what systematic biases exist, and what accuracy and sensitivity can be obtained. We investigate these issues by measuring the same E. coli strains carrying fluorescent reporters using both flow cytometry and microscopic setups and systematically comparing the resulting single-cell expression distributions. Using these results, we develop methods for rigorous quantitative inference of single-cell expression distributions from fluorescence flow cytometry data. First, we present a Bayesian mixture model to separate debris from viable cells using

SUBMITTER: Galbusera L 

PROVIDER: S-EPMC7549788 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature