Rapid biosensor development using plant hormone receptors as reprogrammable scaffolds

Rapid biosensor development using plant hormone receptors as reprogrammable scaffolds


We have previously shown that PYR1 can be repurposed to create an agrochemical receptor that functions in planta to modulate stress tolerance11; in that work, receptors were isolated from a library of variants created by single-site saturation mutagenesis. We reasoned that a structure-guided approach would facilitate the design of a larger collection of stable double mutants and ultimately enable the recognition of more ligands. There are 25 residues in PYR1’s ligand-binding pocket that make close contact to ABA and, therefore, 475 possible single mutants that can be combined to create 108,300 double mutants. We used our knowledge of the conserved receptor activation mechanism to remove six positions. To avoid combining unstable single mutants in the new library, we also used the Rosetta protein design software to predict the stability of the 361 single mutants at the remaining 19 positions. This analysis identified four positions that are particularly sensitive to mutation and were therefore restricted to a small number of amino acids in the final library; the remaining sites were allowed to mutate to any amino acid except cysteine or proline (Supporting File 1). Together, these steps condensed the library to a collection of 37,797 single and double nonsynonymous mutants (42,743 total mutants), which we constructed using site-directed mutagenesis. A total of 36,452 mutants were constructed using a pool of 301 single-mutant oligos in two sequential rounds of single-site nicking mutagenesis (NM)15; 6,291 of the mutants involved residues too close to one another (within eight residues) to be combined using single-mutant oligonucleotides and were instead constructed by NM using a pool of double-mutant oligonucleotides (Fig. 1b)12. The two libraries were combined to yield the double-site mutagenesis (DSM) pocket library for subsequent screening. The DSM library was deep sequenced and determined to possess >99.8% of the desired double mutants (Supporting File 1).

Fig. 1: Protein structure-guided design of high-affinity PYR1-based cannabinoid sensors.
figure 1

a, The 19 side chains of residues in PYR1’s binding pocket targeted for double-site mutagenesis (DSM) are shown along with ABA (yellow) and HAB1’s W385 ‘lock’ residue and water network (3QN1). b, Sensor evolution pipeline. The PYR1 library was constructed by NM12,15 in two subpools, one using single-mutant oligos and another using double-mutant oligo pools. The combined pools were screened for sensors using Y2H growth selections in the presence of a ligand of interest. c, Representative screen results. The DSM library was screened for mutants that respond to the synthetic cannabinoid JWH-015 yielding five hits that were subsequently optimized by two rounds of DNA shuffling to yield PYR1JWH-015, which harbors four mutations. The yeast two-hybrid (Y2H) staining data show different receptor responses to JWH-015 by β-galactosidase activity.

With the improved library in hand, we set out to test its efficiency in a number of screens for biosensors. We first focused on developing cannabinoid sensors, in part to develop diagnostic reagents for synthetic cannabinoid mimics sold in products like ‘Spice,’ which have caused many hospitalizations16 and deaths17,18. We screened for PYR1 mutants responsive to any one of a panel of 28 cannabinoids, screening for mutants responsive to 30 μM of each test chemical (Extended Data Fig. 1 shows chemical structures). Selections were accomplished in a Y2H strain in which expression of URA3 rescues uracil auxotrophy via PYR1 binding to HAB1. Before selection, mutations that produced ligand-independent URA3 activation were removed by a negative selection in the presence of 5-fluoroorotic acid. Our initial positive selections identified double mutants responsive to JWH-015 (Fig. 1c) and five other naphthoylindoles, as well as cannabicyclohexanol (CP 47,497), a different chemical scaffold and one of the active ingredients in ‘Spice’; this demonstrates that our library can yield sensors in a single screening step. Additional sensors were acquired by iteratively screening diversified cannabinoid-biased sublibraries that were created by shuffling hit receptors against both the parental DSM and previous single-site mutant (SSM) libraries. Ultimately, these efforts identified 12 PYR1-derived cannabinoid receptors that recognize 14 compounds, including sensors for CBDA, Δ9-THC and 4F-MDMB-BUTINACA (4F-MDMB), from a total of 28 cannabinoids screened (Fig. 2a,b and Extended Data Fig. 1). Overall, mutations in nine out of the 19 residue positions targeted in the parental library were obtained in the cannabinoid receptors (K59, V81, V83, L87, A89, Y120, F159, A160 and V164), along with two additional sites (H115 and M158) present in the SSM library used for DNA shuffling and affinity maturation. We note that in two cases, our selections converged on the identical sequences; receptors responsive to JWH-072 and JWH-015, closely related naphthoylindoles that differ by only a single methyl substituent, yielded nearly identical evolved sequences. Similarly, the sensors obtained for the closely related compounds 4F-MDMB and AB-PINACA contained identical mutations (Supporting File 2). In addition, wild-type PYR1 did not respond to any of the target ligands screened, nor did our evolved high-affinity sensors respond to ABA (Supplementary Fig. 1); collectively, these data show that PYR1’s ligand-binding pocket can be reprogrammed to recognize target molecules.

Fig. 2: Sequence and structural basis of ligand recognition by evolved PYR1 sensors.
figure 2

a, Sequence diversity of cannabinoid receptor ligand-binding pocket residues (mutant residues are shown in bold type). The minimal ligand concentrations required for Y2H signal generation are indicated at right (Supplementary Fig. 2 shows full data, including mutations outside the pocket). The heatmap shows the ligands screened clustered by their pairwise Tanimoto distance scores calculated using ChemMine33; blue indicates high similarity, and orange has lower similarity. b, Representative optimized sensor Y2H β-galactosidase responses to the ligands indicated; PYR1CBDA was evolved for recognition of CBDA, PYR1CP for CP 47,497, PYR14F for 4F-MDMB and PYR1WIN for WIN 55,212-2. ce, Structural basis for cannabinoid recognition. c, WIN is colored yellow, and key ligand-contacting residues are indicated with dashes. The Trp-lock water network that stabilizes binding is shown at top. d, Relief of steric clash by the evolved receptor. e, Structural poses of WIN in PYL2-bound (top) and CB2-bound (bottom, 6PT0) structures.

Most synthetic cannabinoids share a central indole or indazole scaffold. We anticipated that our evolved cannabinoid receptors might show cross-reactivity. To explore this, we tested several high-affinity sensors for cross-reactivity to cognate ligands (Supplementary Figs. 1 and 2). Although these tests indicate some cross-reactivity, particularly for PYR14F and to a lesser degree PYR1JHW-072, in all cases, on-target sensitivity was at least tenfold higher than the off-target sensitivity. Thus, PYR1-derived sensors can provide sensitive and selective ligand detection, although this will vary by receptor and chemical.

To understand the underlying molecular basis for cannabinoid recognition by our evolved receptors, we sought to obtain the structure of a receptor–cannabinoid–HAB1 complex and targeted two high-affinity sensors, PYR14F and PYR1WIN. In our experience, PYL2 (a close relative of PYR1) forms crystals more readily than PYR1. PYL2 shares 88% pairwise sequence identity with PYR1 for the 25 ABA-proximal positions, and structures of the two proteins are globally alignable to 0.55 Å root mean squared deviation. We, therefore transposed mutations conferring ligand-selective responsiveness to PYL2, creating PYL24F and PYL2WIN, which both retain nanomolar ligand responsiveness (Supplementary Fig. 2). In addition, we created a stabilized, catalytically inactive derivative of HAB1 less prone to oxidative inactivation by employing computational redesign, yielding ΔN-HAB1T+ (derived from a HAB1 truncation that contains its PYR1-binding catalytic domain). This variant harbors 15 mutations, displays a ~7 °C increase in apparent Tm, and retains high-affinity ligand-dependent binding to PYR1, as measured by a yeast surface display assay that uses PYR1M (H60P, N90S), a monomeric double mutant optimized for yeast surface display19 (Supplementary Fig. 3 and Supporting File 1). Using these engineered proteins in matrix screens, we obtained diffraction quality crystals for a ternary PYL2WIN/WIN 55,212-2/ΔN-HAB1T+ complex, whose structure was solved by molecular replacement (1.9 Å resolution; Supplementary Table 1). Diffraction quality PYL24F crystals were not obtained. Several rounds of structural refinement were carried out before modeling WIN 55,212-2 into the ligand-binding pocket’s unbiased electron density (Supplementary Fig. 4). A real-space correlation coefficient of 0.967 calculated between the unbiased electron density and (+)-WIN 55,212-2 indicates agreement between the model and observed electron density. We note that the evolved receptor recognizes the biologically active (+)-WIN 55,212-2 stereoisomer, although selections were conducted using a racemate (Supplementary Fig. 2).

A central feature of ABA recognition by native sensors is the formation of a closed-receptor conformer that is stabilized by a hydrogen-bond network between a structurally conserved water, ABA’s ring ketone, main-chain amides in the gate and latch loops and HAB1’s W385 Trp-‘lock’ residue20,21,22. In our PYL2WIN structure, WIN 55,212-2’s naphthoylindole ketone functions analogously to ABA’s ketone and is coordinated through water-mediated hydrogen bonds to backbone P92 in the gate, R120 in the latch and HAB1’s W385 lock residue (Fig. 2c).

Analysis of the PLY2-WIN structure also revealed that ligand binding is stabilized by an extensive network of hydrophobic contacts and a water-mediated contact to WIN’s morpholine oxygen (Supplementary Fig. 4). In comparison to PYR1, PYR1WIN harbors three mutations (K59Q, F159A and A160I), and our structure illuminates their roles in allowing favorable binding. The most conspicuous effect is a relief of steric clash that would occur between F159 and WIN’s naphthalene ring in a wild-type receptor (Fig. 2d). The neighboring A160I mutation is positioned to enhance receptor-ligand surface complementarity by enabling the naphthoylindole to better pack in this position relative to the wild-type receptor. The K59Q mutation appears to reduce the electrostatic penalty of burying WIN’s positively charged morpholine ring but also organizes a water-mediated hydrogen-bond network at the base of the pocket (Fig. 2d and Supplementary Fig. 4). Thus, WIN’s binding to PYL2WIN involves a combination of polar and hydrophobic contacts, which contrasts with its binding mode in the human cannabinoid receptor CB2, where binding involves exclusively hydrophobic contacts and a more extended ligand conformer23 (Fig. 2e). In addition, the structure illustrates the success of our HAB1 redesign, showing that ΔN-HAB1T+’s main chain is nearly superimposable with that of wild-type (0.85 Å root mean squared deviation) and that the key rotamers for residues involved in receptor interactions are maintained (Supplementary Fig. 3). Collectively, these data provide a mechanistic basis for the sensitive and selective cannabinoid recognition by our evolved receptor, illuminate the mutability of PYR1’s ligand-binding pocket and validate our computational HAB1 redesign.

In principle, the PYR1-HAB1 CID mechanism enables rapid construction of multiple sense-response outputs, as has been demonstrated with other designed CID sensors1. To explore the portability of the designed PYR1-HAB1 system, we selected two high-affinity receptors for evaluation of in vitro HAB1 inhibition, yeast transcriptional activation circuits and in vivo protein-fragment complementation with split luciferase. PYR1WIN and PYR14F displayed nanomolar half-maximum effective concentration (EC50) values using an inhibition assay that detects receptor activation by changes in HAB1 phosphatase activity using a fluorogenic substrate (EC50 PYR1WIN: 72 nM; PYR14F: 102 nM; Fig. 3 and Supplementary Fig. 5). Fusion of the transcriptional activator VP64 to ΔN-HAB1 and a zinc-finger DNA-binding domain to PYR1WIN enabled inducible GFP expression from a synthetic cassette integrated into the genome of Saccharomyces cerevisiae with an EC50 of 28 nM. The same transcriptional circuit built with PYR14F responded to 4F-MDMB with an EC50 of 23 nM. Similar success was achieved with the NanoLuc split luciferase systems24; NLucN-PYR1WIN/NLucC-ΔN-HAB1 responded with an EC50 of 56 nM, and NLucN-PYR14F/NLucC-ΔN-HAB1 responded with an EC50 of 25 nM. Taken together, these results show that the PYR1/ΔN-HAB1 CID mechanism enables portability to both in vitro and in vivo formats and can be deployed in multiple outputs. Moreover, the luminescence and fluorescence reporting modes may be advantageous for ligand detection using low-cost instrumentation and/or in remote settings using engineered living cells.

Fig. 3: PYR1-based sensors are portable to diverse CID-based output systems demonstrated with PYR1WIN.
figure 3

a, Phosphatase inhibition. Ligand-dependent inhibition of ΔN-HAB1 phosphatase activity by recombinant receptors using a fluorogenic substrate. Inhibition expressed relative to mock controls (n = 3). b, Gene activation. Ligand-induced gene activation in S. cerevisiae using an engineered Z4-PYR1/VP64-ΔN-HAB1 genetic circuit. Whole-cell fluorescence generated from an integrated Z44-CYC1core-GFP-CYC1t reporter is shown (12 h after ligand addition; n = 3). c, Split luciferase complementation. Addition of ligand results in luminescence from NLucN-PYR1/NLucC-ΔN-HAB1 (n = 3). d, PYR1 ELISA-like immunoassays. Immobilized receptors recruit biotinylated ΔN-HAB1T+ in response to ligand, and colorimetric signal is generated by a secondary streptavidin-HRP conjugate. Assays conducted in fivefold dilutions of saliva, urine, serum and blank saline are shown, with the lower limit of detection (LOD; Methods) of each assay shown (n = 3). Data points represent the mean, and the 95% confidence interval is shown on fits in ad as gray shading and stated in square brackets along with the EC50 values. e, Receptor cross-reactivity evaluation in PYR1 ELISAs. The cannabinoids shown were assayed for signal generation at 2 µM. + CNTRL, PYR1M tested with 2 µM ABA (n = 3); RLU, relative luminescence unit. Protein parts: DBD, DNA binding domain; AD, activation domain; MBP, maltose binding protein; SA, streptavidin. Chemicals: THC, tetrahydrocannabinol; WIN, (+)-WIN 55,212-2.

Source data

Synthetic cannabinoids are frequently modified to evade detection by routine drug testing. For example, 4F-MDMB is a relatively new indazole that first appeared in 2018 and rapidly became one of the most prevalent synthetic cannabinoids used in the United States25,26,27. Although mass spectrometry methods can sensitively detect this and most synthetic cannabinoids, lower-cost and easier-to-use immunoassays (e.g., ELISAs) dominate routine drug testing. Given this, we sought to convert our CID system into an ELISA-like system for microplate format measurements. To do so, we developed a hybrid sandwich-assay in which the PYR1 sensor is surface immobilized and then coincubated with biotinylated ΔN-HAB1T+ and the ligand of interest. Detection of ternary complexes can then be quantified using streptavidin-linked horseradish peroxidase (HRP), as is commonly done with ELISAs. We developed an ABA-detection system using PYR1M (LOD 2 nM, 0.7 ng ml−1) and then adopted this optimized format for PYR14F-M and PYR1WIN-M (Supplementary Fig. 5 and Supporting File 1). To evaluate the assay’s performance in forensically relevant samples, we tested it with spiked urine, blood and saliva samples and observed reliable detection of picomolar concentrations (LOD: 515 pM in urine, 1,105 pM in blood serum and 305 pM in saliva; Fig. 3d), which compares favorably with existing immunoassay kits that typically report low-nanomolar LODs28. In addition, minimal cross-reactivity between the PYR1WIN-M and PYR14F-M sensors and a panel of 14 cannabinoids was observed using this detection format (Fig. 3e and Supplementary Fig. 5). Combined with our other results, these data further demonstrate that PYR1’s native CID mechanism can be harnessed to develop multiple sense-response outputs and demonstrate that our optimized ELISA-like test enables selective and sensitive detection of target ligands using evolved PYR1-based sensors.

Given the success of the PYR1 scaffold as a platform for cannabinoid sensing, we sought to explore the possibility of rapidly generating sensors for a second class of compounds. To do so, we screened single and multisite mutational libraries against various different organophosphates, an important class of toxic, nonselective acetylcholinesterase inhibitors that were among the first insecticides broadly used in the 20th century. Due to their effects on nontarget organisms, most organophosphates have been banned in the United States, and they present an ongoing environmental monitoring challenge. We screened PYR1 libraries against a panel of 10 organophosphates (diazinon, pirimiphos, dimethoate, chlorfenvinphos, parathion, disulfoton, azinphos, bromophos, malathion and monocrotophos), none of which activated wild-type PYR1 (Supplementary Fig. 1; see Supporting File 1 for library details). These screens yielded receptors for diazinon, pirimiphos, dimethoate and chlorfenvinphos at concentrations between 5 and 100 μM (Supporting File 3). In addition, we screened the new DSM library against the same set of 10 compounds and obtained receptors for seven of these (Supplementary Fig. 6). To improve receptor affinity, we used recombination-based mutagenesis for four organophosphate receptors (diazinon, pirimiphos, chlorfenvinphos and dimethoate) by shuffling hits against parent libraries. This approach was repeated four times, reducing the ligand concentration at each step to ultimately yield improved sensors for these two compounds (Fig. 4a,b). The diazinon-responsive variant PYR1DIAZI is a heptuple mutant (E8G, V81Y, L87M, F108Y, M158V, F159G and A160V), and the pirimiphos-responsive variant PYR1PIRI is an octuple mutant (K59R, S92M, N119S, S122Q, E130G, F159T, A160T and V174A). These optimized sensors were also immediately portable to the split luciferase system with low-nanomolar sensitivity (Fig. 4c). Together, these data demonstrate that the PYR1 ligand-binding pocket can mutate to accommodate organophosphate ligands and provide a general system for developing organophosphate sensors.

Fig. 4: Facile development of potent, selective and portable organophosphate sensors.
figure 4

a, Summary of biosensor screening results for a panel of ten organophosphates. The compounds screened are clustered by similarity (blue indicates more similar) using a distance matrix of pairwise Tanimoto similarity scores, calculated in ChemMine 19. The molecules that yielded hits are shown in bold type; the minimal ligand concentrations required for Y2H signal generation for optimized receptors (Methods) are indicated (Supplementary Fig. 12 shows additional details). b, The optimized PYR1DIAZI and PYR1PIRI are high-affinity sensors. Optimized receptors were tested for responses to nanomolar concentrations of diazinon and pirimiphos-methyl, respectively, as evidenced by Y2H assays and receptor-mediated inhibition of HAB1 phosphatase activity in vitro. PYR1DIAZI (EC50 = 36 nM [32,40]); PYR1PIRI (EC50 = 58 nM [50,67]). Wild-type PYR1 was used as a control (gray lines). c, PYR1-derived receptors are portable. PYR1DIAZI and PYR1PIRI were tested in a protein-fragment complementation system based on split luciferase reconstitution with NLucN-PYR1/NLucC-HAB1 fusions in yeast (PYR1DIAZI, EC50 = 24 nM [12,50]; PYR1PIRI, EC50 = 19 nM [undef, 29]). d,e, PYR1DIAZI and PYR1PIRI are selective for their evolved target ligands. d, Y2H (top) and in vitro phosphatase inhibition assays (bottom) were used to profile receptor responses; the receptors no longer bind the native ligand ABA. Pirimiphos-methyl and diazinon were tested 20 nM, ABA, tested at 5,000 nM in Y2H assays. e, Characterization of receptor selectivity using a Z4-PYR1/VP64-ΔN-HAB1 gene activation circuit in the presence of the activating ligands shown (Supporting File 1 shows quantitative analyses of EC50 values). In all cases, the symbol represents the mean, and the error bars show 1 s.d. and may be smaller than the symbol. All data points represent the mean of triplicate data (n = 3), and error bars represent the standard deviation.

Source data

To address the selectivity profiles of the evolved organophosphate receptors, we characterized their cross-reactivity to target ligands, given the close structural similarity of diazinon and pirimiphos. Both HAB1 inhibition and Y2H assays showed that the evolved receptors are highly selective to their on-target ligands (Fig. 4d). PYR1PIRI was activated by low-nanomolar concentrations of pirimiphos but required high-nanomolar to low-micromolar diazinon concentrations for activation above background levels. Similar results were observed with the PYR1DIAZI receptor, and neither receptor was activated by ABA. In a strict test of specificity, we used our yeast transcription circuit to characterize the off-target responses of these engineered receptors to a panel of six chemically similar organophosphates. The PYR1DIAZI EC50 to diazinon was greater than tenfold lower than all other molecules profiled (Fig. 4e). For example, PYR1DIAZI responded with an EC50 of 1.1 μM to azinphos but with an EC50 of 43 nM to diazinon. Other off-target ligands responded with higher EC50 values and with lower activation levels (Supporting File 1). Similarly, the PYR1DIAZI receptor showed good discrimination between its on-target ligand diazinon and other organophosphates when tested at 20 μM in the ELISA-format mode (Supplementary Fig. 7). Lastly, we examined how receptor selectivity changed over the evolutionary trajectory of the PYR1DIAZI sensor. Off-target ligand responses remained weak throughout the evolutionary process and decreased as affinity increased (Supplementary Fig. 7). Collectively, these data show that improvements in affinity were not obtained at the cost of increased promiscuity and that high-affinity and high-selectivity can be evolved using the PYR1 scaffold.

Using our designed PYR1-HAB1 system, we isolated sensors for 21 of the 38 compounds screened, which included a diverse set of ligands that fall into distinct chemotypes (Extended Data Fig. 2). Although structurally diverse, many of the ligands screened contain a carbonyl functional group that, as observed with WIN 55,212-2, can engage the Trp-lock to stabilize activated receptors (Fig. 2 and Extended Data Fig. 3). Prior work has shown that other H-bond acceptors (e.g., nitriles and others) can function in place of a carbonyl to activate both wild-type and engineered PYR1 receptors11,29,30,31 (Extended Data Fig. 3). In addition, our evolved PYR1CP sensor recognizes a ligand lacking a C=O (Fig. 2). Thus, the chemical scope of ligands compatible with our system should be quite broad. However, even if there is a bias towards carbonyl-containing ligands, approximately one-third of natural products and drugs contain a carbonyl32 and provide a large set of ligands. When coupled to the high hit rates obtained with our DSM library, it should be possible to evolve molecular switches controlled by a large number of drugs, natural products or metabolites. Although many technologies for chemically regulated dimerization have been developed, our system is unique, because it empowers the design systems controlled by user-specified ligands, which is particularly useful when specific properties (such as low cost or low toxicity) are required in downstream applications. Thus, the PYR1/HAB1 system provides an easily reprogrammable chemical-induced dimerization module that will enable new applications in biotechnology, synthetic biology and medicine.

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