Journal article
Robust estimation of bacterial cell count from optical density
Communications biology, Vol.3(1), pp.512-512
09/17/2020
DOI: 10.1038/s42003-020-01127-5
PMCID: PMC7499192
PMID: 32943734
Abstract
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.
Details
- Title: Subtitle
- Robust estimation of bacterial cell count from optical density
- Creators
- Jacob Beal - RTXNatalie G. Farny - Worcester Polytechnic InstituteTraci Haddock-Angelli - International Genetically Engineered Machine FoundationVinoo Selvarajah - International Genetically Engineered Machine FoundationGeoff S. Baldwin - Imperial College LondonRussell Buckley-Taylor - Imperial College LondonMarkus Gershater - SynthaceDaisuke Kiga - Waseda UniversityJohn Marken - California Institute of TechnologyVishal Sanchania - SynthaceAbigail Sison - International Genetically Engineered Machine FoundationChristopher T. Workman - Technical University of DenmarkIGEM Interlab Study Contributors
- Resource Type
- Journal article
- Publication Details
- Communications biology, Vol.3(1), pp.512-512
- Publisher
- Springer Nature
- DOI
- 10.1038/s42003-020-01127-5
- PMID
- 32943734
- PMCID
- PMC7499192
- ISSN
- 2399-3642
- eISSN
- 2399-3642
- Number of pages
- 29
- Grant note
- EP/R034915/1 / Engineering and Physical Sciences Research Council; UK Research & Innovation (UKRI); Engineering & Physical Sciences Research Council (EPSRC) 820699 / EU H2020; Horizon 2020 1522074 / NSF Expeditions in Computing Program Award as part of the Living Computing Project
- Language
- English
- Date published
- 09/17/2020
- Academic Unit
- Electrical and Computer Engineering
- Record Identifier
- 9984627291402771
Metrics
4 Record Views