PLATERO: A calibration protocol for plate reader green fluorescence measurements.

fluorescence measurements measurement data standardization measurement system analysis plate reader units conversion model

Journal

Frontiers in bioengineering and biotechnology
ISSN: 2296-4185
Titre abrégé: Front Bioeng Biotechnol
Pays: Switzerland
ID NLM: 101632513

Informations de publication

Date de publication:
2023
Historique:
received: 21 11 2022
accepted: 09 01 2023
entrez: 6 2 2023
pubmed: 7 2 2023
medline: 7 2 2023
Statut: epublish

Résumé

One of the most common sources of information in Synthetic Biology is the data coming from plate reader fluorescence measurements. These experiments provide a measure of the light emitted by a certain fluorescent molecule, such as the Green Fluorescent Protein (GFP). However, these measurements are generally expressed in arbitrary units and are affected by the measurement device gain. This limits the range of measurements in a single experiment and hampers the comparison of results among experiments. In this work, we describe PLATERO, a calibration protocol to express fluorescence measures in concentration units of a reference fluorophore. The protocol removes the gain effect of the measurement device on the acquired data. In addition, the fluorescence intensity values are transformed into units of concentration using a Fluorescein calibration model. Both steps are expressed in a single mathematical expression that returns normalized, gain-independent, and comparable data, even if the acquisition was done at different device gain levels. Most important, the PLATERO embeds a Linearity and Bias Analysis that provides an assessment of the uncertainty of the model estimations, and a Reproducibility and Repeatability analysis that evaluates the sources of variability originating from the measurements and the equipment. All the functions used to build the model, exploit it with new data, and perform the uncertainty and variability assessment are available in an open access repository.

Identifiants

pubmed: 36741754
doi: 10.3389/fbioe.2023.1104445
pii: 1104445
pmc: PMC9895789
doi:

Types de publication

Journal Article

Langues

eng

Pagination

1104445

Informations de copyright

Copyright © 2023 González-Cebrián, Borràs-Ferrís, Boada, Vignoni, Ferrer and Picó.

Déclaration de conflit d'intérêts

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Auteurs

Alba González-Cebrián (A)

Multivariate Statistical Engineering Group, Department of Applied Statistics and O.R. and Quality, Universitat Politècnica de València, València, Spain.

Joan Borràs-Ferrís (J)

Multivariate Statistical Engineering Group, Department of Applied Statistics and O.R. and Quality, Universitat Politècnica de València, València, Spain.

Yadira Boada (Y)

Synthetic Biology and Biosystems Control Lab, Instituto de Automática e Informática Industrial, Universitat Politècnica de València, València, Spain.

Alejandro Vignoni (A)

Synthetic Biology and Biosystems Control Lab, Instituto de Automática e Informática Industrial, Universitat Politècnica de València, València, Spain.

Alberto Ferrer (A)

Multivariate Statistical Engineering Group, Department of Applied Statistics and O.R. and Quality, Universitat Politècnica de València, València, Spain.

Jesús Picó (J)

Synthetic Biology and Biosystems Control Lab, Instituto de Automática e Informática Industrial, Universitat Politècnica de València, València, Spain.

Classifications MeSH