Development and Characterization of Flavin-Binding Fluorescent Proteins, Part II: Advanced Characterization

Machine Learning-Assisted Engineering of Light, Oxygen, Voltage Photoreceptor Adduct Lifetime

Naturally occurring and engineered flavin-binding, blue-light-sensing, light, oxygen, voltage (LOV) photoreceptor domains have been used widely to design fluorescent reporters, optogenetic tools, and photosensitizers for the visualization and control of biological processes. In addition, natural LOV photoreceptors with engineered properties were recently employed for optimizing plant biomass production in the framework of a plant-based bioeconomy. Here, the understanding and fine-tuning of LOV photoreceptor (kinetic) properties is instrumental for application. In response to blue-light illumination, LOV domains undergo a cascade of photophysical and photochemical events that yield a transient covalent FMN-cysteine adduct, allowing for signaling. The rate-limiting step of the LOV photocycle is the dark-recovery process, which involves adduct scission and can take between seconds and days. Rational engineering of LOV domains with fine-tuned dark recovery has been challenging due to the lack of a mechanistic model, the long time scale of the process, which hampers atomistic simulations, and a gigantic protein sequence space covering known mutations (combinatorial challenge). To address these issues, we used machine learning (ML) trained on scarce literature data and iteratively generated and implemented experimental data to design LOV variants with faster and slower dark recovery. Over the three prediction-validation cycles, LOV domain variants were successfully predicted, whose adduct-state lifetimes spanned 7 orders of magnitude, yielding optimized tools for synthetic (opto)biology. In summary, our results demonstrate ML as a viable method to guide the design of proteins even with limited experimental data and when no mechanistic model of the underlying physical principles is available.

Fine spectral tuning of a flavin-binding fluorescent protein for multicolor imaging

Flavin-binding fluorescent proteins are promising genetically encoded tags for microscopy. However, spectral properties of their chromophores (riboflavin, flavin mononucleotide, and flavin adenine dinucleotide) are notoriously similar even between different protein families, which limits applications of flavoproteins in multicolor imaging. Here, we present a palette of 22 finely tuned fluorescent tags based on the thermostable LOV domain from Chloroflexus aggregans. We performed site saturation mutagenesis of three amino acid positions in the flavin-binding pocket, including the photoactive cysteine, to obtain variants with fluorescence emission maxima uniformly covering the wavelength range from 486 to 512 nm. We demonstrate three-color imaging based on spectral separation and two-color fluorescence lifetime imaging of bacteria, as well as two-color imaging of mammalian cells (HEK293T), using the proteins from the palette. These results highlight the possibility of fine spectral tuning of flavoproteins and pave the way for further applications of flavin-binding fluorescent proteins in fluorescence microscopy.