Deep Mutational Scanning of an Oxygen-Independent Fluorescent Protein CreiLOV for Comprehensive Profiling of Mutational and Epistatic Effects

Oxygen-independent, flavin mononucleotide-based fluorescent
proteins
(FbFPs) are promising alternatives to green fluorescent protein in
anaerobic contexts. Deep mutational scanning performs systematic profiling
of protein sequence–function relationships but has not been
applied to FbFPs. Focusing on CreiLOV from Chlamydomonas reinhardtii, we created and analyzed two comprehensive mutant collections: (1)
single-residue, site-saturation mutagenesis libraries covering all
118 residues; and (2) a full combinatorial metagenesis library among
20 mutations at 15 residues, where mutation and residue selection
was based on single-site mutagenesis results. Notably, the second
type of library is indispensable to study higher-order epistasis but
underrepresented in the literature. Using optimized FACS-seq assays,
2,185 (>92.5%) out of 2,360 possible single-site mutants and 165,428
(>89.7%) out of 184,320 possible combinatorial mutants were reliably
assigned with fitness values. We constructed statistical and machine-learning
models to analyze the CreiLOV data set, enabling accurate fitness
prediction of higher-order mutants using lower-order mutagenesis data.
In addition, we successfully isolated CreiLOV variants with improved
fluorescence quantum yield and thermostability. This work provides
new empirical data and design rules to engineer combinatorial protein
variants.