Coupling a Live Cell Directed Evolution Assay with Coevolutionary Landscapes to Engineer an Improved Fluorescent Rhodopsin Chloride Sensor

Abstract

Our understanding of chloride in biology has been accelerated through the application of fluorescent protein-based sensors in living cells. These sensors can be generated and diversified to have a range of properties using laboratory-guided evolution. Recently, we established that the fluorescent proton-pumping rhodopsin wtGR from Gloeobacter violaceus can be converted into a fluorescent sensor for chloride. To unlock this non-natural function, a single point mutation at the Schiff counterion position (D121V) was introduced into wtGR fused to cyan fluorescent protein (CFP) resulting in GR1-CFP. Here, we have integrated coevolutionary analysis with directed evolution to understand how the rhodopsin sequence space can be explored and engineered to improve this starting point. We first show how evolutionary couplings are predictive of functional sites in the rhodopsin family and how a fitness metric based on a sequence can be used to quantify the known proton-pumping activities of GR-CFP variants. Then, we couple this ability to predict potential functional outcomes with a screening and selection assay in live Escherichia coli to reduce the mutational search space of five residues along the proton-pumping pathway in GR1-CFP. This iterative selection process results in GR2-CFP with four additional mutations: E132K, A84K, T125C, and V245I. Finally, bulk and single fluorescence measurements in live E. coli reveal that GR2-CFP is a reversible, ratiometric fluorescent sensor for extracellular chloride with an improved dynamic range. We anticipate that our framework will be applicable to other systems, providing a more efficient methodology to engineer fluorescent protein-based sensors with desired properties.

Unlocking chloride sensing in the red at physiological pH with a fluorescent rhodopsin-based host

“…S1). 26,27,35 As hypothesized, the membrane-anchored Arch7-CFP fusion protein is fluorescent with a ratiometric output (Arch7: lex = 615 nm, lem = 710 nm; CFP: lex = 440 nm, lem = 475 nm), yet insensitive to chloride across a physiological pH range (Fig. 1, Fig.…”

“…25 As part of our efforts in this area, we have expanded beyond the GFP family and are actively investigating other classes of chromophore-containing proteins such as fluorescent microbial rhodopsins. [26][27][28][29][30][31] The rhodopsin family is a diverse group of transmembrane, photoactive proteins with a covalently bound Schiff base chromophore (SBC) formed from the condensation of a conserved lysine residue with retinal (Fig. 1).…”

“…1). 26,27 It is interesting to note glycine can be found at the SBC counterion position in uncharacterized members of the rhodopsin family, suggesting that this could be a signature to confer chloride recognition in Nature (Supplemental File 1). To our knowledge, the chloridesensitive module of ChloRED-1-CFP has the reddest single-photon excitation and emission reported to date.…”

Latent generative landscapes as maps of functional diversity in protein sequence space

“…These constraints impose statistical signatures in the collection of evolutionarily related sequences that allow features, such as structure, function, and interactions, to be reconstructed from homologous sequence alignments using methods such as direct coupling analysis (DCA), GREMLIN, and EVcouplings 3 – 6 . These methodologies offer excellent performance in identifying relevant amino acid interactions useful for structure inference 7 – 10 , complex formation 5 , 11 – 14 , molecular specificity 15 – 19 , the effects of protein mutations 20 – 22 , and protein design, including engineering of functional proteins with specific properties, such as repressors 23 , fluorescent proteins 24 , 25 , and enzymes 26 , and can be used to inform evolutionary models 27 , but they lack strong performance in classifying specific functions of a given protein. Recent focus has shifted towards using state-of-the-art machine learning approaches.…”

Discovery of a monomeric green fluorescent protein sensor for chloride by structure-guided bioinformatics

“…23,41–44 These efforts are part of our larger program aimed at decoding the sequence level determinants of biological anion recognition. 45–47…”