Protocol to detect dilution cycles in chemostat experiments and estimate growth rate slopes with linear modeling with R software chemostat_regression
Samuel I. Koehler, Jennifer T. Pentz, Earl A. Middlebrook, Blake T. Hovde, Erik R. Hanschen · STAR Protocols · 2025
Chemostat growth chambers measure optical density over time and require manual calculation of growth rates. Here, we present chemostat_regression , R software that enables users to automatically identify chemostat cycles and estimate growth rate using a linear regression approach. We describe steps for creating requisite software environment(s), formatting input data, executing the software via command line/RStudio/R-Shiny, interpreting results, assessing the validity of results, and modifying input parameters. • Detailed walkthrough for analyzing chemostat data to estimate growth rate • Steps to download the R software chemostat_regression and its dependencies • Descriptions of chemostat dilution cycles and their automated detection • Example experiment provided for generating applicable chemostat data Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. Chemostat growth chambers measure optical density over time and require manual calculation of growth rates. Here, we present chemostat_regression , R software that enables users to automatically identify chemostat cycles and estimate growth rate using a linear regression approach. We describe steps for creating requisite software environment(s), formatting input data, executing the software via command line/RStudio/R-Shiny, interpreting results, assessing the validity of results, and modifying input parameters.