By utilizing laboratory-guided evolution, we have converted the fluorescent proton-pumping rhodopsin GR from Gloeobacter violaceus into GR1, a red-shifted, turn-on fluorescent sensor for chloride.
RNA–protein interactions permeate biology. Transcription, translation, and splicing all hinge on the recognition of structured RNA elements by RNA-binding proteins. Models of RNA–protein interactions are generally limited to short linear motifs and structures because of the vast sequence sampling required to access longer elements. Here, we develop an integrated approach that calculates global pairwise interaction scores from in vitro selection and high-throughput sequencing. We examine four RNA-binding proteins of phage, viral, and human origin. Our approach reveals regulatory motifs, discriminates between regulated and non-regulated RNAs within their native genomic context, and correctly predicts the consequence of mutational events on binding activity. We design binding elements that improve binding activity in cells and infer mutational pathways that reveal permissive versus disruptive evolutionary trajectories between regulated motifs. These coupling landscapes are broadly applicable for the discovery and characterization of protein–RNA recognition at single nucleotide resolution.
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.
Bemisia tabaci (Gennadius) is a species complex, and its two most damaging biotypes B and Q are globally distributed pests. Despite increasing biological and economic impacts, little is known about the evolutionary mechanisms that favor their competition with native populations. Here, we investigated the genetic mutations in the P450 gene of the invasive B, Q biotypes and the native Cv population. Four mutations associated with chemical resistance, Pro-Leu, Ala-Ser, Ser-Phe and Trp-Leu, were found in the cytochrome P450 CYP6C and CYP9F genes of the B and Q biotypes. Bioassay results also revealed that both the B and Q biotypes have about 12-47 times more resistance to acephate, betacypermethrin, methomyl, and 5-7 times more resistance to imidacloprid insecticide than Cv population. Our results provide a molecular approach for better understanding and monitoring the pesticide resistances of invasive and native B. tabaci populations in China.
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