Robust Estimation of Bacterial Cell Count from Optical Density

Beal, J.; Farny, N. G.; Haddock-Angelli, T.; Selvarajah, V.; Baldwin, G. S.; Buckley-Taylor, R.; Gershater, M.; Kiga, D.; Marken, J. P.; Sanchania, V.; Sison, A.; Workman, C.; iGEM Interlab Study Contributors,

doi:10.1101/803239

bioRxiv · 10.1101/803239

Robust Estimation of Bacterial Cell Count from Optical Density

Beal, J.·Farny, N. G.·Haddock-Angelli, T.·Selvarajah, V.·Baldwin, G. S.·Buckley-Taylor, R.·Gershater, M.·Kiga, D.·Marken, J. P.·Sanchania, V.·Sison, A.·Workman, C.·iGEM Interlab Study Contributors,

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Abstract

Optical 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.

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Beal, J., Farny, N. G., Haddock-Angelli, T., Selvarajah, V., Baldwin, G. S., Buckley-Taylor, R., Gershater, M., Kiga, D., Marken, J. P., Sanchania, V., Sison, A., Workman, C., iGEM Interlab Study Contributors,. 2019-10-13. Robust Estimation of Bacterial Cell Count from Optical Density. https://doi.org/10.1101/803239

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