Comparative analysis of three studies measuring fluorescence from engineered bacterial genetic constructs

Reproducibility is a key challenge of synthetic biology, but the foundation of reproducibility is only as solid as the reference materials it is built upon. Here we focus on the reproducibility of fluorescence measurements from bacteria transformed with engineered genetic constructs. This comparative analysis comprises three large interlaboratory studies using flow cytometry and plate readers, identical genetic constructs, and compatible unit calibration protocols. Across all three studies, we find similarly high precision in the calibrants used for plate readers. We also find that fluorescence measurements agree closely across the flow cytometry results and two years of plate reader results, with an average standard deviation of 1.52-fold, while the third year of plate reader results are consistently shifted by more than an order of magnitude, with an average shift of 28.9-fold. Analyzing possible sources of error indicates this shift is due to incorrect preparation of the fluorescein calibrant. These findings suggest that measuring fluorescence from engineered constructs is highly reproducible, but also that there is a critical need for access to quality controlled fluorescent calibrants for plate readers

Robust estimation of bacterial cell count from optical density

Optical density (OD) is widely used to estimate the density of cells in liquid culture, but cannot be compared between instruments without a standardized calibration protocol and is challenging to relate to actual cell count. We address this with an interlaboratory study comparing three simple, low-cost, and highly accessible OD calibration protocols across 244 laboratories, applied to eight strains of constitutive GFP-expressing E. coli. Based on our results, we recommend calibrating OD to estimated cell count using serial dilution of silica microspheres, which produces highly precise calibration (95.5% of residuals <1.2-fold), is easily assessed for quality control, also assesses instrument effective linear range, and can be combined with fluorescence calibration to obtain units of Molecules of Equivalent Fluorescein (MEFL) per cell, allowing direct comparison and data fusion with flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data

Calibration Protocol - Plate Reader Abs600 (OD) Calibration with Microsphere Particles v3

You will prepare a dilution series of monodisperse silica microspheres and measure the Abs600 in your plate reader. The size and optical characteristics of these microspheres are similar to cells, and there is a known amount of particles per volume. This measurement will allow you to construct a standard curve of particle concentration which can be used to convert 600 nm absorbance measurements into an estimated equivalent number of cells. </p

Calibration Protocol - Plate Reader Abs600 (OD) Calibration with Microsphere Particles v4

You will prepare a dilution series of monodisperse silica microspheres and measure the Abs600 in your plate reader. The size and optical characteristics of these microspheres are similar to cells, and there is a known amount of particles per volume. This measurement will allow you to construct a standard curve of particle concentration which can be used to convert 600 nm absorbance measurements into an estimated equivalent number of cells. </p

Calibration Protocol - Particle Standard Curve with Microspheres v1

You will prepare a dilution series of monodisperse silica microspheres and measure the Abs600 in your plate reader. The size and optical characteristics of these microspheres are similar to cells, and there is a known amount of particles per volume. This measurement will allow you to construct a standard curve of particle concentration which can be used to convert 600 nm absorbance measurements into an estimated equivalent number of cells. </p

Calibration Protocol - Plate Reader Abs600 (OD) Calibration with Microsphere Particles v2

You will prepare a dilution series of monodisperse silica microspheres and measure the Abs600 in your plate reader. The size and optical characteristics of these microspheres are similar to cells, and there is a known amount of particles per volume. This measurement will allow you to construct a standard curve of particle concentration which can be used to convert 600 nm absorbance measurements into an estimated equivalent number of cells. </p

Robust Estimation of Bacterial Cell Count from Optical Density

AbstractOptical density (OD) is a fast, cheap, and high-throughput measurement widely used to estimate the density of cells in liquid culture. These measurements, however, cannot be compared between instruments without a standardized calibration protocol and are challenging to relate to actual cell count. We address these shortcomings with an interlaboratory study comparing three OD calibration protocols, as applied to eight strains of E. coli engineered to constitutively express varying levels of GFP. These three protocols—comparison with colloidal silica (LUDOX), serial dilution of silica microspheres, and a reference colony-forming unit (CFU) assay—are all simple, low-cost, and highly accessible. Based on the results produced by the 244 teams completing this interlaboratory study, we recommend calibrating OD using serial dilution of silica microspheres, which readily produces highly precise calibration (95.5% of teams having residuals less than 1.2-fold), is easily assessed for quality control, and as a side effect also assesses the effective linear range of an instrument. Moreover, estimates of cell count from silica microspheres can be combined with fluorescence calibration against fluorescein to obtain units of Molecules of Equivalent Fluorescein (MEFL), allowing direct comparison and data fusion with equivalently calibrated flow cytometry measurements: in our study, fluorescence per cell measurements showed only a 1.07-fold mean difference between plate reader and flow cytometry data.</jats:p

Author Correction: Robust estimation of bacterial cell count from optical density.

An amendment to this paper has been published and can be accessed via a link at the top of the paper