151. Maturation models of fluorescent proteins are necessary for unbiased estimates of promoter activity
- Author
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Antrea, Pavlou, Eugenio, Cinquemani, Johannes, Geiselmann, Hidde, de Jong, Analyse, ingénierie et contrôle des micro-organismes (MICROCOSME), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Université Grenoble Alpes (UGA), Laboratoire Interdisciplinaire de Physique [Saint Martin d’Hères] (LIPhy ), Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), and ANR-20-CE45-0014,Ctrl-AB,Optimisation et controle de la productivité d'un écosystème algues-bactéries(2020)
- Subjects
[SDV.BBM.BP]Life Sciences [q-bio]/Biochemistry, Molecular Biology/Biophysics ,Luminescent Proteins ,Green Fluorescent Proteins ,Escherichia coli ,Biophysics ,Bayes Theorem ,Promoter Regions, Genetic ,[SDV.BIBS]Life Sciences [q-bio]/Quantitative Methods [q-bio.QM] - Abstract
Fluorescent proteins (FPs) are a powerful tool to quantitatively monitor gene expression. The dynamics of a promoter and its regulation can be inferred from fluorescence data. The interpretation of fluorescent data, however, is strongly dependent on the maturation of FPs since different proteins mature in distinct ways. We propose a novel approach for analyzing fluorescent reporter data by incorporating maturation dynamics in the reconstruction of promoter activities. Our approach consists of developing and calibrating mechanistic maturation models for distinct FPs. These models are then used alongside a Bayesian approach to estimate promoter activities from fluorescence data. We demonstrate by means of targeted experiments in Escherichia coli that our approach provides robust estimates and that accounting for maturation is, in many cases, essential for the interpretation of gene expression data.
- Published
- 2022