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Comparative Study
. 2021 Jun 7;16(6):e0252263.
doi: 10.1371/journal.pone.0252263. eCollection 2021.

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

Jacob Beal  1 , Geoff S Baldwin  2 , Natalie G Farny  3 , Markus Gershater  4 , Traci Haddock-Angelli  5 , Russell Buckley-Taylor  2 , Ari Dwijayanti  2 , Daisuke Kiga  6 , Meagan Lizarazo  5 , John Marken  7 , Kim de Mora  5 , Randy Rettberg  5 , Vishal Sanchania  4 , Vinoo Selvarajah  5 , Abigail Sison  5 , Marko Storch  8 , Christopher T Workman  9 ; iGEM Interlab Study Contributors
Affiliations
Comparative Study

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

Jacob Beal et al. PLoS One. .

Abstract

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.

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Conflict of interest statement

The authors of this manuscript have read the journal’s policy and have the following competing interests: The authors received no specific commercial funding for this work. The following authors are employed by for-profit companies: Jacob Beal is employed by Raytheon BBN Technologies; Markus Gershater and Vishal Sanchania are employed by Synthace, and their work on this paper was thus indirectly supported by their salaries. This does not alter the authors’ adherence to PLOS ONE policies on sharing data and materials.

Figures

Fig 1
Fig 1. Constitutive fluorescence genetic constructs measured in all three of the 2016, 2017, and 2018 iGEM Interlab Studies, diagrammed using standard SBOL visual symbols [13].
Fig 2
Fig 2. Distribution of the coefficient of variation.
Distribution for valid replicate sets in LUDOX and water calibrants for OD (a) and fluorescein calibrant for fluorescence (b). All distributions show an overall high degree of precision and similarity, except for the small fraction of outliers in the LUDOX and water calibrants.
Fig 3
Fig 3. Distribution of residuals for fluorescein calibrants.
Model fit residual distribution for every set of fluorescein replicates included in calibration computations for the 2016, 2017, and 2018 studies. Distributions for all three studies are similar, all indicating a high degree of precision.
Fig 4
Fig 4. Comparison of measured fluorescence of test genetic constructs.
Comparison of plate reader data in MEFL/OD units (a), and both plate reader and flow cytometry data in MEFL/cell units (b). Bars show geometric mean and standard deviation; dots show values from individual teams. Team count per condition is provided in S7 File Teams Per Condition.
Fig 5
Fig 5. Potential sources of error in studies.
Workflow block diagram of the different stages of each study, highlighting likely dependence or independence of potential errors in execution.
See this image and copyright information in PMC

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