Abstract
Fluorescent protein (FP) maturation can limit the accuracy with which dynamic intracellular processes are captured and reduce the in vivo brightness of a given FP in fast-dividing cells. The knowledge of maturation timescales can therefore help users determine the appropriate FP for each application. However, in vivo maturation rates can greatly deviate from in vitro estimates that are mostly available. In this work, we present the first systematic study of in vivo maturation for 12 FPs in budding yeast. To overcome the technical limitations of translation inhibitors commonly used to study FP maturation, we implemented a new approach based on the optogenetic stimulations of FP expression in cells grown under constant nutrient conditions. Combining the rapid and orthogonal induction of FP transcription with a mathematical model of expression and maturation allowed us to accurately estimate maturation rates from microscopy data in a minimally invasive manner. Besides providing a useful resource for the budding yeast community, we present a new joint experimental and computational approach for characterizing FP maturation, which is applicable to a wide range of organisms.
Highlights
Fluorescent proteins (FPs) have become indispensable tools for the study of cellular dynamics in a wide range of applications, such as monitoring nutrient and stress responses, the quantification of gene expression noise, the measurement of protein turnover, and the characterization of synthetic inducible systems
To overcome the technical challenges associated with nutrient- and chemically induced gene expression systems, we used a single-component optogenetic gene expression system based on the bacterial light−oxygen−voltage (LOV) protein EL22227,28 to activate the expression of FPs in budding yeast
Because AQTrip is activated within a few seconds upon light induction, to the wild-type protein,[30] the induction of FP expression can be precisely timed, a feature that is important for precisely capturing the fluorescence dynamics via mathematical modeling
Summary
Fluorescent proteins (FPs) have become indispensable tools for the study of cellular dynamics in a wide range of applications, such as monitoring nutrient and stress responses, the quantification of gene expression noise, the measurement of protein turnover, and the characterization of synthetic inducible systems. They need to undergo a process of maturation, which collectively refers to the folding and post-translational modifications that result in the formation of a functional chromophore.[1,2] Maturation is largely autocatalytic (except for the strict requirement of molecular oxygen), but its kinetics is affected by environmental factors such as temperature.[3] Currently available FPs have in vivo maturation times that range from a few minutes to hours This fact needs to be taken into account when choosing an FP for a particular application, as the speed of FP maturation determines the range of timescales over which expression dynamics can be accurately captured.[4,5] slowmaturing FPs can generate artifacts in the dynamic measurements of signaling activity via fluorescence resonance energy transfer (FRET) biosensors.[6−8] Besides limiting the accuracy of dynamic measurements, maturation has a large effect on the in vivo brightness of a given FP.[9,10] This is because a fraction of immature FPs is always present in dividing cell populations where FPs are continuously produced and diluted by cell growth. For all these reasons, knowing the maturation rates of different available FPs is crucial for choosing the right protein for a particular application or for post-processing fluorescence time series to account for the effects of FP maturation
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