mCranberry: A rationally engineered monomeric red fluorescent protein with 85% quantum yield
Year: 2026
Type: preprint
Abstract: Fluorescent proteins (FPs) are the workhorse of modern-day cellular imaging and biosensing. However, rationally predicting and engineering the photophysical properties of FPs remain challenging, as these are governed by complex three-dimensional microenvironments and post-translational modifications. Here, we present a novel surface-mutation-guided engineering strategy combined with iterative rounds of rational mutagenesis to improve key photophysical properties of red fluorescent proteins (RFPs). This approach generated two bright, monomeric RFP variants from the mFruits lineage, mCranberry and mCranberry2, with quantum yields of 85% and 80%, respectively. Strategic incorporation of charged amino acid residues on the protein surface enhanced fluorescence quantum yield without compromising photostability. Comprehensive photophysical characterization and live-cell microscopy demonstrate enhanced performance of these variants and establish their utility as robust probes for fluorescence imaging. However, the exact mechanism of such improvements is subject to further investigation. Collectively, this work introduces a strategy for optimizing fluorescence properties and provides a framework that may be broadly applicable to other pigment-protein systems such as genetically encoded metal-ion indicators and photosynthetic light-harvesting complexes.
Language: English
Subfield: Biophysics
Domain: Life Sciences
Open Access status: green
Funders: U.S. Department of Energy, Ohio State University, National Sun Yat-sen University, National Institutes of Health, National Institute of Standards and Technology, Office of Science, University of Colorado Boulder, National Institute of General Medical Sciences, SLAC National Accelerator Laboratory
Awards: G1229526393, G2371548206, G262532246, G303061748, G4235786860, G4845168670, G495301720, G498139845, G5570207115, G7863156295, G8207748872, G8382000481, G8925327636, Biophysical studies of macromolecules and molecular assemblies, A Synchrotron Radiation Structural Biology Resource, Computational rational design of carbohydrate and nucleic acid drug scaffolds with multiscale dynamics and AI
OpenAlex ID: W7221158315