Detecting ribonucleic acid (RNA) using polymerase strand recycling (PSR)

Abstract

Disclosed are compositions, systems, kits, and methods for detecting an RNA molecule in a sample. The compositions, systems, kits, and methods can comprise and / or utilize one or more components selected from: an RNA polymerase; a dsDNA signal gate molecule; a fuel gate molecule; and / or any combination thereof.

Description

DETECTING RIBONUCLEIC ACID (RNA) USING POLYMERASE STRAND RECYCLING (PSR)CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] This application claims priority to U.S. Provisional Application No. 63 / 637,174, filed on April 22, 2024. The contents of which are herein incorporated by reference in their entirety.STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

[0002] This invention was made with government support under grant number N66001-23-2- 4041 awarded by the Defense Advanced Research Projects Agency, and grant number GM008449 awarded by the National Institutes of Health. The government has certain rights in the invention.REFERENCE TO AN ELECTRONIC SEQUENCE LISTING

[0003] The contents of the electronic sequence listing (70258102653. xml; Size: 66,608 bytes; and Date of Creation: April 22, 2025) is herein incorporated by reference in its entirety.FIELD

[0004] The technical field relates to sensors for detecting RNA molecules. In particular, the technical field relates to low-cost, programmable, and rapid sensors for detecting RNA molecules.BACKGROUND

[0005] Cell-free systems have enabled rapid, point-of-care detection of a wide range of important environmental and human health targets such as metals (arsenic, lead, copper, cadmium, zinc, mercury), ions and small molecules (fluoride, vitamin B12. benzoic acid derivatives), antibiotics (tetracycline, oxytetracycline, chlortetracycline), disinfectant bi- products (benzalkonium chloride), viruses (Zika, Ebola), agricultural toxins (atrazine), drugs (cocaine, gamma-hydroxybutyrate) and microbial quorum sensing molecules.SUMMARY

[0006] The present invention relates to compositions, systems, kits, and methods for detecting RNA molecules. The compositions, systems, kits, and methods utilize regulated in vitro transcription in order to detect an RNA molecule in a sample via toehold-mediated strand displacement circuits.

[0007] The disclosed compositions, systems, kits, and methods can comprise and / or utilize one or more components selected from: (a) an RNA polymerase; (b) a signal gate molecule; (c) a fuel gate molecule; and / or any combination thereof. The fuel gate molecule can include a waste strand and a RecycleD strand, where the waste strand and the RecycleD strand are at least partly complementary to one another and form a double-stranded polynucleotide. When in the presence of the target RNA molecule, the target RNA molecule binds the waste strand of the fuel gate molecule thereby displacing the RecycleD strand generating a free single-stranded polynucleotide that displaces a DNA strand of the signal gate molecule to produce a detectable signal and a new hybrid signal / fuel gate. The RNA polymerase transcribes the hybrid signal / fuel gate to release the RecycleD strand which can then displace an additional signal gate molecule, thus creating a positive feedback loop of signal amplification.

[0008] The disclosure provides compositions, systems, and / or kits for detecting a target RNA molecule comprising as components: (a) an RNA polymerase; (b) a double-stranded DNA (dsDNA) signal gate molecule; and (c) a fuel gate molecule comprising a waste strand and a RecycleD strand, wherein the waste strand and the RecycleD strand are at least partly complementary to one another and form a double-stranded polynucleotide; wherein, when in the presence of the target RNA molecule, the target RNA molecule binds the fuel gate molecule thereby displacing the RecycleD strand generating a free single-stranded polynucleotide that displaces a DNA strand of the signal gate molecule to produce a detectable signal and a new hybrid signal / fuel gate, and wherein the RNA polymerase transcribes the hybrid signal / fuel gate to release the RecycleD strand which can then displace an additional dsDNA signal gate molecule, thus creating a positive feedback loop of signal amplification.

[0009] In some aspects, the dsDNA signal gate molecule is labeled with one or more functional chemical groups. In such aspects, the one or more functional chemical groups comprise one or more of a fluorophore, a quencher, biotin, or methylene blue. In one example aspect, the dsDNA signal gate molecule is a fluorescently labeled double-stranded DNA molecule comprising a fluorophore-conjugated strand having a fluorophore conjugated at its 3 ’-end and a quencher stand having a quencher conjugated at its 5’ end that quenches the fluorophore in the fluorescently labeled double-stranded DNA molecule. In some aspects, when in the presence of the target RNA molecule, the target RNA molecule binds the fuel gate molecule thereby displacing the RecycleD strandgenerating a free single-stranded polynucleotide that displaces the quencher strand from the dsDNA signal gate to produce a detectable signal.[00101 Insome aspects, when the RecycleD strand displaces the quencher strand of the fluorescently labeled double-stranded DNA molecule, the fluorophore of the fluorophore-conjugated strand is dequenched generating the detectable signal and the RecycleD strand hybridizes to the fluorophore-conjugated strand to generate the hybrid signal / fuel gate comprising a 3’ toehold on the fluorophore-conjugated strand and the RNA polymerase transcribes the fluorophore-conjugated strand and displaces the RecycleD strand and generates a fluorescent DNA / RNA hybrid, and wherein the released RecycleD strand can displace an additional signal gate generating a positive feedback loop of signal amplification.

[0011] The disclosure further provides a method for detecting a target RNA molecule in a sample, the method comprising contacting the sample with any one of the compositions, systems, and / or kits disclosed herein.BRIEF DESCRIPTION OF THE FIGURES

[0012] FIG. 1 Amplifying outputs of programmable cell-free biosensor circuits with polymerase strand recycling. (Left) Programmable cell-free biosensor circuits are configured by genetically wiring multiple components together, including transcription factors for sensing, regulated DNA templates for outputs, RNA polymerases (RNAPs) to drive circuit function, and chemical ligands for detection. Biosensing circuits activate when a ligand binds to a protein transcription factor, causing it to un-bind from a DNA template and activate transcription of RNA output signals. (Middle) RNA output signals can then interact with programmable DNA gates via toehold-mediated strand displacement (TMSD). DNA gates can be configured to process biosensor signals by adding computational features such as logic processing and signal comparison. (Right) Outputs of the processor layer generate a detectable signal by strand displacing a quenched fluorophore signal gate. These output signals can be further amplified with polymerase strand recycling (PSR), a process by which RNAP transcribes the resulting bound fluorophore strand, thus releasing a strand that can invade a new signal gate to create a cycle of signal amplification.

[0013] FIGS. 2A-2B. A DNA-DNA duplex is required for T7 RNAP off-target transcription. (FIG. 2A) Invading RNA (RNA input) or DNA (DNA input) strands were designed to strand displace the DNA signal gate and form a new duplex with the fluorophore-strand, leaving a 4-nt 3’toehold. Transcription of the resulting 3’ toehold by T7 RNAP should result in signal amplification. (FIG. 2B) Fluorescent read outs of end-point reactions (1 hr) consisting of 2.5 pM of the signal gate, 2 ng T7 RNAP, and either 0.5 pM of RecycleD, RecycleR or no input. RecycleD is able to achieve significantly higher signal than RecycleR. Data shown are n = 3 experimentally independent replicates, each plotted as a point with raw fluorescence standardized to MEF (pM FITC). Bar heights represent the average over these replicates. A paired Student’s t-test was used to compare the fluorescent signals between RecycleR and RecycleD. The p-value range is indicated by asterisks (***p < 0.001, **p = 0.001-0.01, *p = 0.01-0.05). Exact p-value can be found in Source Data.

[0014] FIGS. 3A-3C: Interfacing PSR amplification with transcriptional signals via a “fuel gate”. (FIG. 3 A) The fuel gate concept. The fuel gate is designed to sequester RecycleD with a complementary strand, leaving 5’ toehold overhangs. Transcription of RecycleR can then lead to invasion of the fuel gate, releasing RecycleD for PSR. (FIG. 3B) Toehold length for PSR affects signal amplification. With a designed 4-nt 3’ toehold on the RecycleD:fluorophore duplex, greater fluorescence activation was observed after 1 hr from a circuit containing 1.5 pM of fuel gate, 2.5 pM of signal gate, 2 ng T7 RNAP and 0.5 nM - 50 nM of DNA transcription template encoding RecycleR, compared to the same circuit with a 0-nt 3’ toehold. In addition, the 4-nt toehold led to a plateau of signal at 0.5 nM transcription template compared to 10 nM for the 0-nt toehold. The DNA template concentrations at which the 4-nt signals are distinguishable from 0-nt signals were determined using paired Student’s t-tests. The p-value range is indicated by asterisks (***p < 0.001, **p = 0.001-0.01, *p = 0.01-0.05). Exact p-values can be found in Source Data. (FIG. 3C) Kinetic data for 0 nM and 0.5 nM DNA template concentrations with and without a 4nt toehold. Raw fluorescence data are standardized to MEF (pM FITC). Data shown in b are n = 3 experimentally independent replicates, each plotted as a point. Bar heights represent the average over these replicates. Data shown in c are n = 3 experimentally independent replicates. The lines and dotted lines represent the average of the replicates. Shading indicates the average of the replicates ± s.d.

[0015] FIGS. 4A-4C. Nucleic acid sensing with PSR. (FIG. 4A) PSR for detecting miRNAs. Fuel gates are designed to interact directly with miRNA targets, releasing RecycleD for PSR. (FIG. 4B) PSR miRNA sensing specificity. Different sequences for PSR fuel gates and signal gates were designed to sense miRNA3185, miRNA642a-5p, and miRNA134-3p. The PSR circuits containing 1.5 pM of fuel gate, 2.5 pM of signal gate, 2 ng T7 RNAP all detect 1 pM of their respective miRNA targets with significant specificity after 2 hrs. Significance values comparing fluorescence fromtargeted miRNA inputs and the indicated non-targeted inputs were determined using a paired Student’s t- test. The p-value range is indicated by asterisks (***p < 0.001, **p = 0.001-0.01, *p = 0.01-0.05). Exact p-values can be found in Source Data. (FIG. 4C) PSR miRNA sensing limit of detection. Dose response with miRNA3185 measured after 2 hrs shows limit of detection (LoD) of 100 nM. Dose response with miRNA642a-5p measured after 2 hrs shows LoD of 250 nM. Dose response with miRNA3185 measured after 2 hrs shows LoD of 5 nM. The LoDs were determined from the concentration value at which the signal was significantly greater than the no input condition using a paired Student’s t-test. The p-value range is indicated by asterisks (***p < 0.001, **p = 0.001-0.01, *p = 0.01-0.05). Exact p-values can be found in Source Data. Data shown in b are n = 3 experimentally independent replicates, each plotted as a point, with bar heights representing the average over these replicates. Data shown in c are n = 3 experimentally independent replicates, each plotted as a point with raw fluorescence standardized to MEF (pM FITC). Dotted curves in c represent Hill Equation fits (see Methods), with fit parameters in Source Data.

[0016] FIGS. 5A-5D. Interfacing transcriptional biosensors with PSR signal amplification. (FIG. 5A) RecycleR transcription can be allosterically regulated with a DNA template configured to bind a purified aTF (here TetR) via an operator sequence (here tetO) placed downstream of the T7 promoter and upstream of the RecycleR coding sequence. Activation of the aTF biosensor in the presence of a target ligand (here aTc) generates a signal which is amplified by the downstream PSR circuit. (FIG. 5B) Kinetic traces of the circuit containing 1.5 pM of fuel gate, 2.5 pM of signal gate, 2 ng T7 RNAP and 0 nM - 50 nM of RecycleR DNA transcription templates containing the tetO sequence, showing that even the lowest template concentration (0.5 nM) can reach nearly maximum fluorescence activation within 1 hr (FIG. 5C) Fluorescence levels after 1 hr for circuits containing 0.5 nM of DNA transcription template and a range of input TetR concentrations from 0 - 100 nM. A ratio of TetR dimer:DNA template of 25:1 (12.5 nM:0.5 nM, starred) was found to be the minimal amount of TetR needed to completely repress 0.5 nM of DNA template. (FIG. 5D) Kinetic traces of the complete biosensor-PSR circuit containing 1 nM of DNA transcription template and 25 nM of TetR dimer, with and without 1 pM of added tetracycline. The dashed line at 0.5 pM FITC represents the visible fluorescence threshold found previously

[0028] , Raw fluorescence data are standardized to MEF (pM FITC). Data shown in b and d are n = 3 experimentally independent replicates for each condition, with lines representing the average of these replicates. Shading indicates the average of thereplicates ± s.d. Data shown in c are n = 3 experimentally independent replicates, each plotted as a point, with bar heights representing the average over these replicates.[00171 FIGS. 6A-6D. Polymerase strand recycling circuits can sensitize cell-free biosensors. (FIG. 6A) The double equilibrium model predicts that decreasing aTF concentration at a constant aTF / DNA ratio improves sensitivity until aTF concentration approaches the aTF:DNA dissociation constant (14 pM), at which point leak becomes significant. (FIG. 6B) The double equilibrium model predicts that further sensitivity improvements can be achieved if aTF:DNA and aTF ligand dissociation constants are lowered from their literature values of 0.79 pM and 14 pM to 0.0079 pM and 0.14 pM, respectively. Compared with Figure 6a, significantly reduced levels of leak are observed at lower aTF concentrations. (FIG. 6C) Dose response with tetracycline measured at 1 hr for both PSR and TMSD-only schemes. A 4.6-fold decrease in EC50 was observed with PSR. (FIG. 6D) Application of PSR to zinc sensing with SmtB. Dose response with ZnSCf measured after Ihr for both PSR and TMSD-only schemes. A 3.6-fold decrease in EC50 was observed with PSR. Data shown in c and d are n = 3 experimentally independent replicates, each plotted as a point with raw fluorescence standardized to MEF (pM FITC). Dotted curves represent Hill Equation fits (see Methods), with fit parameters in Source Data.

[0018] FIG. 7. Micromolar Equivalent Fluorescein (MEF) standardization. Arbitrary units of fluorescence were standardized to pM equivalent fluorescein (pM FITC) using a NIST traceable standard (see Methods). In the representative example shown here, a dilution series of FITC standard was prepared in buffer (100 mM sodium borate, pH 9.5) and measured on a plate reader using the same settings for measuring 6-FAM signal (490 nm excitation, 525 nm emission). The resulting curve, calculated over the linear range of 0-3.125 pM, was then used to standardize fluorescence measured from PSR and TMSD reactions. The standard curve was generated at regular intervals for each plate reader and each measurement setting. Data shown are for n=3 experimentally independent replicates for each concentration. Error bars indicate standard deviation computed over n=3 replicates.

[0019] FIGS. 8A-8B. T7 RNAP can activate fluorescence signal from fuel gate and signal gate even in the absence of DNA template. (FIG. 8A) Both 1 nM DNA template and 0 nM DNA template activated fluorescent signal after 1 hr with 1.5 pM fuel gate and 2.5 pM signal gate. A dashed line indicates the fluorescence level of 2.5 pM of pure fluoprophore strand in 1VT buffer. Solid lines are averages over n = 3 experimentally independent replicates. Shading indicates theaverage of the replicates ± s.d. (FIG. 8B) Measured MEF (pM FITC) of 2.5 pM of fluorescent fluorophore strand in IVT buffer. Data shown are n = 3 experimentally independent replicates each plotted as a point with raw fluorescence standardized to MEF (pM FITC). Bar heights represent the average over these replicates.

[0020] FIG. 9. Design elements in a PSR circuit. Sequences for RecycleR, fuel gate, and signal gate. The fuel gate can be strand invaded by RecycleR. It consists of a 2’-O-methyl modified strand and a DNA strand, RecycleD. The DNA signal gate has a fluorophore strand and a quencher strand.

[0021] FIGS. 10A-10B. 2’-0-Me modification significantly reduces the amount of leak in PSR circuits. (FIG. 10A) Circuit scheme after including the fuel gate concept. (FIG. 10B) Fluorescence was characterized for different combinations of unmodified and 2’-O-Me modified fuel and signal gate in the presence of 1.5 pM fuel gate, 2.5 pM signal gate, 2 ng T7 RNAP, and the indicated amount of DNA template encoding RecycleR. Dotted lines represent 2’-0-Me modification. Data shown as points are for n = 3 experimentally independent replicates. Bar heights represent the average over these replicates.

[0022] FIG. 11. Design elements in PSR circuits to detect RNA inputs. Sequences for the miRNAs, and their respective fuel gates and signal gates. The fuel gates can be strand invaded by miRNAs. They consist of a 2’-O-methyl modified strand and an unmodified RecycleD DNA strand. The DNA signal gates have a fluorophore strand and a quencher strand.

[0023] FIGS. 12A-12B. Titrating DNA templates containing the tetO sequence to compare TMSD signal generation to signal generation with PSR. Time course trajectories of fluorescence from (FIG. 12A) TMSD circuits and (FIG. 12B) PSR circuits with various amounts of input DNA template added. TMSD circuits contained 2 ng of T7 RNAP, 2.5 pM DNA signal gate and various amounts of input DNA template. PSR circuits contained 2 ng of T7 RNAP, 1.5 pM fuel gate, 2.5 pM DNA signal gate and various amounts of input DNA template. Data shown are from n = 3 experimentally independent replicates each plotted as a line. Shading indicates the average of the replicates ± s.d. Data in b repeated from Figure 5b for comparison.

[0024] FIGS. 13A-13B. Titrating [TetR dimer] at a fixed [DNA] to identify the amount of TetR needed to fully repress transcription for TMSD and PSR biosensing circuits. (FIG. 13A) 5X [TetR dimer] to [DNA] ratio was shown to fully repress transcription in TMSD biosensing circuits (star), corresponding to 50 nM TetR dimer to 10 nM TMSD DNA template. (FIG. 13B) 25X [TetRdimer] to [DNA] ratio was shown to fully repress transcription in PSR biosensing circuits (star), which was 12.5 nM TetR dimer to 0.5 nM of PSR DNA template. Data in a and b shown are for n = 3 experimentally independent replicates shown as points. Bar heights represent the average over these replicates. Data in b repeated from Figure 5c for comparison.

[0025] FIGS. 14A-14B. Titrating DNA templates containing the smtO sequence to compare TMSD signal generation to signal generation with PSR. Time course trajectories of fluorescence from TMSD circuits (FIG. 14A) and PSR circuits (FIG. 14B). TMSD circuits contained 2 ng of T7 RNAP, 2.5 pM DNA signal gate and various amounts of input DNA template. PSR circuits contained 2 ng of T7 RNAP, 1.5 pM fuel gate, 2.5 pM DNA signal gate and various amounts of input DNA template. Data shown are from n = 3 experimentally independent replicates, with lines representing the average. Shading indicates the average of the replicates ± s.d.

[0026] FIGS. 15A-15B. Titrating [SmtB dimer] at a fixed [DNA] to identify the amount of SmtB to fully repress transcription for TMSD and PSR biosensing circuits. (FIG. 15 A) 25X [SmtB dimer] to [DNA] ratio was shown to fully repress transcription in TMSD biosensing circuits (star), corresponding to 625 nM SmtB dimer to 25 nM TMSD DNA template. (FIG. 15B) 250X [SmtB dimer] to [DNA] ratio was shown to fully repress transcription in PSR biosensing circuits (star), which was 250 nM SmtB dimer to 1 nM of PSR DNA template. Data in a and b shown are for n = 3 experimentally independent replicates shown as points. Bar heights represent the average over these replicates.

[0027] FIG. 16. Double equilibrium model of transcription factor binding to DNA and target compound. The double equilibrium model considers association / dissociation of ligand-aTF (top) and of aTF-operator site (bottom). Species are indicated with schematics. aTF refers to the functional aTF unit which could be a multimer for some mechanisms.

[0028] FIGS. 17A-17C. RNA input sensing with PSR. (FIG. 17A) PSR circuit design for detecting microRNAs. Fuel gates are designed to sequester microRNAs and release RecycleD via toehold-mediated strand displacement. RecycleD is designed to strand invade the signal gate and form a new duplex with the fluorophore-strand, leaving a 4-nt 3’ toehold. T7 RNAP off-target transcription from the 3’ toehold results in RecycleD regeneration and signal amplification. (FIG. 17B) miR biomarkers that increase or decrease in response to physical stressors, cognitive stressors, or both. (FIG. 17C) PSR microRNA sensing performance. Different sequences for PSR fuel gates and signal gates were designed to detect purified model miR targets miR-320b, miR-29a-3p, miR-34-3p, miR-16-5p, miR-21-5p, and miR-20b-5p. The PSR circuits containing 1.5 pM of fuel gate, 2.5 pM of signal gate, 2 ng of T7 RNAP all detect 1 pM of their respective miR targets with significant specificity after 2 hrs. Significance values comparing fluorescence from targeted miR inputs and the indicated non-targeted inputs were determined using a two-tailed, paired Student’s t-test. Dose responses with miR-320b, miR-29a-3p, miR-34a-3p, miR-21-5p, miR-20b-5p measured after 2 hrs showed limit of detection (LoD) of 100 nM. Dose response with miR-16-5p measured after 2 hrs shows LoD of 5 nM. The LoDs were determined from the concentration value at which the signal was significantly greater (p < 0.05) than the no input condition using a two-tailed, heteroscedastic Student’s t-test. Data shown in bar graphs in 17C are n = 3 experimentally independent replicates, each plotted as a point with raw fluorescence standardized to MEF (pM FITC) and bar heights representing the average over these replicates. Data shown in dose response graphs in 17C are n = 3 experimentally independent replicates, each plotted as a point with raw fluorescence standardized to MEF (pM FITC). Curves in c represent Hill Equation fits (see Methods), with fit parameters in Source Data. The p-value range is indicated by asterisks (***p < 0.001, **p = 0.001-0.01, *p = 0.01- 0.05). Exact p-values can be found in Source Data.

[0029] FIGS. 18A-18C. PSR design process and troubleshooting approaches. (FIG. 18A) Design process for building PSR circuits. (Left) Select RNA inputs used to activate a PSR circuit can either come from transcription from ligand-regulated sensing mechanisms or directly as RNA molecules. (Middle) The PSR fuel gate is formed by two nucleic acid strands with an overlap of 20 - 22-bp, a 5-nt 5’ overhang on RecycleD and a 9 - 10-nt 5’ overhang on the sequester strand. The sequester strand is 2’-O-methyl modified and contains the complementary sequence for the RNA input. RecycleD is a DNA strand that gets released from RNA input strand invasion. (Right) The signal gate is formed by two nucleic acid strands with an overlap of 21 - 23 -bp and an 8-nt 5’ overhang on the fluorophore strand. The signal gate is designed to be strand invaded by RecycleD to form a new duplex with the fluorophore- strand containing a 4-nt 3’ toehold to enable T7 RNAP off- target transcription. (FIG 17B) Improving signal-to-noise ratio. The PSR circuit designed to detect miR-16-5p containing 1.5 pM of fuel gate, 2.5 pM of signal gate, 2 ng of T7 RNAP initially generated high fluorescent signal in the absence of its target miR after 2 hrs. By increasing the overlapping regions on the fuel and signal gates by 2-bp, the signal-to-noise ratio improved to -10- fold (see Supplementary Figure 4). Significance values comparing fluorescence from targeted miR inputs and the indicated non-targeted inputs were determined using a two-tailed, paired Student’s t-test. (FIG. 17C) Improving LoD for miR detection. The PSR circuit designed to detect miR-642a-5p initially showed an LoD of 250 nM after 2 hrs. By decreasing the overlapping regions on the fuel and signal gates by 2-bp, we demonstrated an LoD of 25 nM (see Supplementary Figure 5). The LoDs were determined from the concentration value at which the signal was significantly greater (p < 0.05) than the no input condition using a two- tailed, heteroscedastic Student’s t-test. The p-value range is indicated by asterisks (***p < 0.001,**p = 0.001-0.01, *p = 0.01-0.05). Exact p-values can be found in Source Data. Data shown in 17B are n = 3 experimentally independent replicates, each plotted as a point with raw fluorescence standardized to MEF (pM FITC) and bar heights representing the average over these replicates. Data shown in 17C are n = 3 experimentally independent replicates, each plotted as a point with raw fluorescence standardized to MEF (pM FITC). Curves in c represent Hill Equation fits (see Methods), with fit parameters in Source Data.

[0030] FIGS. 19A-19C. Design elements in PSR circuits for RNA detection. (FIG. 19A) Fuel gate design architecture for RNA detection. The fuel gate is designed with the sequester strand complementary to the target RNA. Invasion of the fuel gate by the target RNA releases RecycleD. 2’- O-methyl modifications of the sequester strand stabilizes the fuel gate and reduces leak. (FIG. 19B) Signal gate design architecture for RNA detection. The signal gate is designed to be invaded by RecycleD, releasing the quencher-modified strand and creating a RecycleD :Fluorophoremodified strand complex that fluoresces. (FIG. 19C) RecycleD :Fluorophore-modified strand complex. The complex has a 4-nt 3’ toehold on the fluoroph ore-modified strand to enable T7 RNAP off-target transcription of this strand, which releases RecycleD.

[0031] FIG. 20. T7 RNAP variants impact PSR circuit performance. The kinetic traces of the PSR circuit containing 0.2 pM of either wildtype T7 RNAP, M6 T7 RNAP (SEQ ID NO: 48) and Y639F T7 RNAP (SEQ ID NO: 49), 1.5 pM of fuel gate, and 2.5 pM of signal gate with (left) and without (right) 1 pM of added target miR, showing that different T7 RNAP variants could either improve or hinder PSR circuit performance. The data shown are n = 3 independent biological replicates for each condition, with the lines representing the average of the replicates. The shading indicates the average of the replicates ± standard deviation.

[0032] FIGS. 21A-21B. Increasing fuel gate base pairs improves signal-to-noise ratio. (FIG. 21A) miR-320b detection PSR circuit performance improvement. Extending RecycleD by 1-nt, thus introducing a 1-bp clamp on the fuel gate, improves the signal-to-noise ratio in detecting miR-320bcompared to off-target miRNA sequences from 6.1-6.4x to 10.7-1 lx. (FIG. 21B) miR-21 -5p detection PSR circuit performance improvement. Introducing a 1-bp clamp on fuel gate by extending the sequester strand improves the signal-to-noise ratio in detecting miR-21-5p compared to off-target miRNA sequences from 9.2-9.4x to 12.9-13.4x. Data shown in FIGS. 21A and 21B are n = 3 experimentally independent replicates from PSR reactions containing 1.5 pM of fuel gate, 2.5 pM of signal gate, and 2 ng of T7 RNAP, with fluorescence measured after 2 hrs. Each replicate is plotted as a point with raw fluorescence standardized to MEF (pM FITC) with bar heights representing the average over these replicates. Significance values comparing fluorescence from targeted miRNA inputs and the indicated non-targeted inputs were determined using a two-tailed, paired Student’s t- test. The p-value range is indicated by asterisks (***p < 0.001, **p = 0.001-0.01, *p = 0.01-0.05). Exact p-values can be found in Source Data.

[0033] FIG. 22. Increasing fuel and signal gate overlapping regions fixes broken-on PSR circuit for miR-16-5p detection. Introducing a 2-bp clamp on both the fuel and signal gates improves the signal-to-noise ratio from a nonfunctional, broken ON, PSR circuit (top), to a PSR circuit that shows 10.3-10.5x fold change in detecting miR-16-5p compared to off-target miRNA sequences (bottom). Data shown are n = 3 experimentally independent replicates from PSR reactions containing 1.5 pM of fuel gate, 2.5 pM of signal gate, and 2 ng of T7 RNAP, with fluorescence measured after 2 hrs. Each replicate is plotted as a point with raw fluorescence standardized to MEF (pM FITC) with bar heights representing the average over these replicates. Significance values comparing fluorescence from targeted miRNA inputs and the indicated nontargeted inputs were determined using a two-tailed, paired Student’s t-test. The p-value range is indicated by asterisks (***p < 0.001, **p = 0.001-0.01, *p = 0.01-0.05). Exact p-values can be found in Source Data.

[0034] FIG. 23. Decreasing overlapping regions on fuel and signal gates increases LoD for miR detection using PSR. Different designs of PSR circuits containing 1.5 pM of fuel gate, 2.5 pM of signal gate, and 2 ng of T7 RNAP were used to characterize dose responses to detecting miR- 642a-5p measured after 2 hrs. The LoD decreased successively from 250 nM (top) to 100 nM (middle) and 25 nM (bottom) by reducing the overlapping regions on fuel and signal gates by 1-2 -bp. The LoDs were determined from the concentration value at which the signal was significantly greater (p < 0.05) than the no input condition using a two-tailed, heteroscedastic Student’s t-test. The p-value range is indicated by asterisks (***p < 0.001, **p = 0.001-0.01, *p = 0.01-0.05). Exact p-values canbe found in Source Data. Data shown are n = 3 experimentally independent replicates, each plotted as a point with raw fluorescence standardized to MEF (pM FITC). Curves represent Hill Equation fits (see Methods), with fit parameters in Source Data.

[0035] FIGS. 24A-24B. aTF-based biosensing with PSR. (FIG. 24A) PSR circuit scheme for detecting small molecules. RecycleR transcription can be allosterically regulated with a DNA template configured to bind a purified aTF via an operator sequence placed downstream of the T7 promoter and upstream of the RecycleR coding sequence. Activation of the aTF biosensor in the presence of a target ligand generates a signal which is amplified by the downstream PSR circuit. (FIG. 24B) Design elements in an aTF-based PSR circuit. Sequences for RecycleR, fuel gate, and signal gate. The fuel gate can be strand invaded by RecycleR. It consists of a 2’-O-methyl modified strand and a DNA strand, RecycleD. The DNA signal gate has a fluorophore-labeled strand and a quencher-labeled strand. (Reproduced from Li, Y., Lucci, T., Villarruel Dujovne, M. et al. A cell-free biosensor signal amplification circuit with polymerase strand recycling. Nat Chem Biol (2025).

[0036] FIG. 25. Micromolar Equivalent Fluorescein (MEF) standardization. Arbitrary units of fluorescence were standardized to pM equivalent fluorescein (pM FITC) using a NIST traceable standard (see Methods). In the representative example shown here, a dilution series of FITC standard was prepared in buffer (100 mM sodium borate, pH 9.5) and measured on a plate reader using the same settings for measuring 6-FAM signal (490 nm excitation, 525 nm emission). The resulting curve, calculated over the linear range of 0-3.125 pM, was then used to standardize fluorescence measured from PSR reactions. The standard curve was generated at regular intervals for each plate reader and each measurement setting. Data shown are for n=3 experimentally independent replicates for each concentration. Error bars indicate standard deviation computed over n=3 replicates.DETAILED DESCRIPTION

[0037] The present invention is described herein using several definitions, as set forth below and throughout the application.

[0038] Unless otherwise specified or indicated by context, the terms "a", "an", and "the" mean "one or more." For example, "a component," "a composition," "a system," "a kit," "a method," "a protein," "a vector," "a domain," "a binding site," and "an RNA" should be interpreted to mean "one or more components," "one or more compositions," "one or more systems," "one or more kits,""one or more methods," "one or more proteins," "one or more vectors," "one or more domains," "one or more binding sites," and "one or more RNAs," respectively.[00391 As used herein, "about," "approximately," "substantially," and "significantly" will be understood by persons of ordinary skill in the art and will vary to some extent on the context in which they are used. If there are uses of these terms which are not clear to persons of ordinary skill in the art given the context in which they are used, "about" and "approximately" will mean plus or minus <10% of the particular term and "substantially" and "significantly" will mean plus or minus >10% of the particular term.

[0040] As used herein, the terms "include" and "including" have the same meaning as the terms "comprise" and "comprising" in that these latter terms are "open" transitional terms that do not limit claims only to the recited elements succeeding these transitional terms. The term "consisting of," while encompassed by the term "comprising," should be interpreted as a "closed" transitional term that limits claims only to the recited elements succeeding this transitional term. The term "consisting essentially of," while encompassed by the term "comprising," should be interpreted as a "partially closed" transitional term which permits additional elements succeeding this transitional term, but only if those additional elements do not materially affect the basic and novel characteristics of the claim.

[0041] As used herein, the terms "regulation" and "modulation" may be utilized interchangeably and may include "promotion" and "induction." For example, a transcription factor that regulates or modulates expression of a target gene may promote and / or induce expression of the target gene. In addition, the terms "regulation" and "modulation" may be utilized interchangeably and may include "inhibition" and "reduction." For example, a transcription factor that regulates or modulates expression of a target gene may inhibit and / or reduce expression of the target gene.

[0042] As used herein, the term "sample" may include "biological samples" and "non- biological samples." Biological samples may include samples obtained from a human or non-human subject. Biological samples may include but are not limited to, blood samples and blood product samples (e.g., serum or plasma), urine samples, saliva samples, fecal samples, perspiration samples, and tissue samples. Non-biological samples may include but are not limited to aqueous samples (e.g., watershed samples) and surface swab samples.Polynucleotides and Uses Thereof

[0043] The terms "polynucleotide," "polynucleotide sequence," "nucleic acid" and "nucleic acid sequence" refer to a nucleotide, oligonucleotide, polynucleotide (which terms may be used interchangeably), or any fragment thereof. These phrases also refer to DNA or RNA of genomic, natural, or synthetic origin (which may be single-stranded or double-stranded and may represent the sense or the antisense strand).

[0044] The terms "nucleic acid" and "oligonucleotide," as used herein, may refer to polydeoxyribonucleotides (containing 2-deoxy-D-ribose), polyribonucleotides (containing D-ribose), and to any other type of polynucleotide that is an N glycoside of a purine or pyrimidine base. There is no intended distinction in length between the terms "nucleic acid", "oligonucleotide" and "polynucleotide", and these terms will be used interchangeably. These terms refer only to the primary structure of the molecule. Thus, these terms include double- and single-stranded DNA, as well as double- and single-stranded RNA. For use in the present methods, an oligonucleotide also can comprise nucleotide analogs in which the base, sugar, or phosphate backbone is modified as well as non-purine or non-pyrimidine nucleotide analogs.

[0045] Oligonucleotides can be prepared by any suitable method, including direct chemical synthesis by a method such as the phosphotriester method of Narang et al., 1979, Meth. Enzymol. 68:90-99; the phosphodiester method of Brown et al., 1979, Meth. Enzymol. 68: 109-151; the diethylphosphoramidite method of Beaucage et al., 1981, Tetrahedron Letters 22:1859-1862; and the solid support method of U.S. Pat. No. 4,458,066, each incorporated herein by reference. A review of synthesis methods of conjugates of oligonucleotides and modified nucleotides is provided in Goodchild, 1990, Bioconjugate Chemistry 1(3): 165-187, incorporated herein by reference.

[0046] Regarding polynucleotide sequences, the terms "percent identity" and "% identity" refer to the percentage of residue matches between at least two polynucleotide sequences aligned using a standardized algorithm. Such an algorithm may insert, in a standardized and reproducible way, gaps in the sequences being compared in order to optimize alignment between two sequences, and therefore achieve a more meaningful comparison of the two sequences. Percent identity for a nucleic acid sequence may be determined as understood in the art. (See, e.g., U.S. Patent No. 7,396,664, which is incorporated herein by reference in its entirety). A suite of commonly used and freely available sequence comparison algorithms is provided by the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST), which is available from several sources, including the NCBI, Bethesda, Md., at its website. The BLAST software suiteincludes various sequence analysis programs including "blastn," that is used to align a known polynucleotide sequence with other polynucleotide sequences from a variety of databases. Also available is a tool called "BLAST 2 Sequences" that is used for direct pairwise comparison of two nucleotide sequences. "BLAST 2 Sequences" can be accessed and used interactively at the NCBI website. The "BLAST 2 Sequences" tool can be used for both blastn and blastp (discussed above).

[0047] Regarding polynucleotide sequences, percent identity may be measured over the length of an entire defined polynucleotide sequence, for example, as defined by a particular SEQ ID number, or may be measured over a shorter length, for example, over the length of a fragment taken from a larger, defined sequence, for instance, a fragment of at least 20, at least 30, at least 40, at least 50, at least 70, at least 100, or at least 200 contiguous nucleotides. Such lengths are exemplary only, and it is understood that any fragment length supported by the sequences shown herein, in the tables, figures, or Sequence Listing, may be used to describe a length over which percentage identity may be measured.

[0048] Regarding polynucleotide sequences, "variant," "mutant," or "derivative" may be defined as a nucleic acid sequence having at least 50% sequence identity to the particular nucleic acid sequence over a certain length of one of the nucleic acid sequences using blastn with the "BLAST 2 Sequences" tool available at the National Center for Biotechnology Information’s website. (See Tatiana A. Tatusova, Thomas L. Madden (1999), "Blast 2 sequences - a new tool for comparing protein and nucleotide sequences", FEMS Microbiol Lett. 174:247-250). Such a pair of nucleic acids may show, for example, at least 60%, at least 70%, at least 80%, at least 85%, at least 90%, at least 91%, at least 92%, at least 93%, at least 94%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% or greater sequence identity over a certain defined length.

[0049] Nucleic acid sequences that do not show a high degree of identity may nevertheless encode similar amino acid sequences due to the degeneracy of the genetic code where multiple codons may encode for a single amino acid. It is understood that changes in a nucleic acid sequence can be made using this degeneracy to produce multiple nucleic acid sequences that all encode substantially the same protein. For example, polynucleotide sequences as contemplated herein may encode a protein and may be codon-optimized for expression in a particular host. In the art, codon usage frequency tables have been prepared for a number of host organisms including humans, mouse, rat, pig, E. coli, plants, and other host cells.

[0050] A "recombinant nucleic acid" is a sequence that is not naturally occurring or has a sequence that is made by an artificial combination of two or more otherwise separated segments of sequence. This artificial combination is often accomplished by chemical synthesis or, more commonly, by the artificial manipulation of isolated segments of nucleic acids, e.g., by genetic engineering techniques known in the art. The term recombinant includes nucleic acids that have been altered solely by addition, substitution, or deletion of a portion of the nucleic acid. Frequently, a recombinant nucleic acid may include a nucleic acid sequence operably linked to a promoter sequence. Such a recombinant nucleic acid may be part of a vector that is used, for example, to transform a cell.

[0051] The nucleic acids disclosed herein may be "substantially isolated or purified." The term "substantially isolated or purified" refers to a nucleic acid that is removed from its natural environment, and is at least 60% free, preferably at least 75% free, and more preferably at least 90% free, even more preferably at least 95% free from other components with which it is naturally associated.

[0052] The term "amplification reaction" refers to any chemical reaction, including an enzymatic reaction, which results in increased copies of a template nucleic acid sequence or results in transcription of a template nucleic acid. Amplification reactions include reverse transcription, the polymerase chain reaction (PCR), including Real Time PCR (see U.S. Pat. Nos. 4,683,195 and 4,683,202; PCR Protocols: A Guide to Methods and Applications (Innis et al., eds, 1990)), and the ligase chain reaction (LCR) (see Barany et al., U.S. Pat. No. 5,494,810). Exemplary "amplification reactions conditions" or "amplification conditions" typically comprise either two or three step cycles. Two-step cycles have a high temperature denaturation step followed by a hybridization / elongation (or ligation) step. Three step cycles comprise a denaturation step followed by a hybridization step followed by a separate elongation step.

[0053] The term "hybridization," as used herein, refers to the formation of a duplex structure by two single-stranded nucleic acids due to complementary base pairing. Hybridization can occur between fully complementary nucleic acid strands or between "substantially complementary" nucleic acid strands that contain minor regions of mismatch. Conditions under which hybridization of fully complementary nucleic acid strands is strongly preferred are referred to as "stringent hybridization conditions" or "sequence-specific hybridization conditions". Stable duplexes of substantially complementary sequences can be achieved under less stringent hybridization conditions; the degreeof mismatch tolerated can be controlled by suitable adjustment of the hybridization conditions. Those skilled in the art of nucleic acid technology can determine duplex stability empirically considering a number of variables including, for example, the length and base pair composition of the oligonucleotides, ionic strength, and incidence of mismatched base pairs, following the guidance provided by the art (see, e.g., Sambrook et al., 1989, Molecular Cloning-A Laboratory Manual, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York; Wetmur, 1991, Critical Review in Biochem. and Mol. Biol. 26(3 / 4):227-259; and Owczarzy et al., 2008, Biochemistry, ^ . 5336-5353, which are incorporated herein by reference).

[0054] The term "primer," as used herein, refers to an oligonucleotide capable of acting as a point of initiation of DNA synthesis under suitable conditions. Such conditions include those in which synthesis of a primer extension product complementary to a nucleic acid strand is induced in the presence of four different nucleoside triphosphates and an agent for extension (for example, a DNA polymerase or reverse transcriptase) in an appropriate buffer and at a suitable temperature.

[0055] A primer is preferably a single-stranded DNA. The appropriate length of a primer depends on the intended use of the primer but typically ranges from about 6 to about 225 nucleotides, including intermediate ranges, such as from 15 to 35 nucleotides, from 18 to 75 nucleotides and from 25 to 150 nucleotides. Short primer molecules generally require cooler temperatures to form sufficiently stable hybrid complexes with the template. A primer need not reflect the exact sequence of the template nucleic acid, but must be sufficiently complementary to hybridize with the template. The design of suitable primers for the amplification of a given target sequence is well known in the art and described in the literature cited herein.

[0056] Primers can incorporate additional features which allow for the detection or immobilization of the primer but do not alter the basic property of the primer, that of acting as a point of initiation of DNA synthesis. For example, primers may contain an additional nucleic acid sequence at the 5' end which does not hybridize to the target nucleic acid, but which facilitates cloning or detection of the amplified product, or which enables transcription of RNA (for example, by inclusion of a promoter) or translation of protein (for example, by inclusion of a 5’-UTR, such as an Internal Ribosome Entry Site (IRES) or a 3’-UTR element, such as a poly(A)nsequence, where n is in the range from about 20 to about 200). The region of the primer that is sufficiently complementary to the template to hybridize is referred to herein as the hybridizing region.

[0057] As used herein, a primer is "specific," for a target sequence if, when used in an amplification reaction under sufficiently stringent conditions, the primer hybridizes primarily to the target nucleic acid. Typically, a primer is specific for a target sequence if the primer-target duplex stability is greater than the stability of a duplex formed between the primer and any other sequence found in the sample. One of skill in the art will recognize that various factors, such as salt conditions as well as base composition of the primer and the location of the mismatches, will affect the specificity of the primer, and that routine experimental confirmation of the primer specificity will be needed in many cases. Hybridization conditions can be chosen under which the primer can form stable duplexes only with a target sequence. Thus, the use of target-specific primers under suitably stringent amplification conditions enables the selective amplification of those target sequences that contain the target primer binding sites.

[0058] As used herein, a "polymerase" refers to an enzyme that catalyzes the polymerization of nucleotides. "DNA polymerase" catalyzes the polymerization of deoxyribonucleotides. Known DNA polymerases include, for example, Pyrococcus furiosus (Pfu) DNA polymerase, E. coll DNA polymerase I, T7 DNA polymerase and Thermits aquaticus (Taq) DNA polymerase, among others. The foregoing examples of DNA polymerases are also known as DNA-dependent DNA polymerases. RNA-dependent DNA polymerases also fall within the scope of DNA polymerases. Reverse transcriptase, which includes viral polymerases encoded by retroviruses, is an example of an RNA- dependent DNA polymerase. "RNA polymerase" catalyzes the polymerization of ribonucleotides. Known examples of RNA polymerase ("RNAP") include, for example, RNA polymerases of bacteriophages (e.g. T3 RNA polymerase, T7 RNA polymerase, SP6 RNA polymerase, Syn5 RNA polymerase), and E. coll RNA polymerase, among others. The foregoing examples of RNA polymerases are also known as DNA-dependent RNA polymerase. The polymerase activity of any of the above enzymes can be determined by means well known in the art.

[0059] Also contemplated for use in the disclosed compositions, systems, kits, and methods are engineered DNA or RNA polymerase. For example, an engineered polymerase may be a non- naturally occurring DNA or RNA polymerase whose amino acid sequence has been engineered to include one or more of an insertion, a deletion, or a substitution relative to the amino acid sequence of a naturally occurring or wild-type polymerase.

[0060] The term "promoter" refers to a c / .s-acting DNA sequence that directs RNA polymerase and other trans-acim transcription factors to initiate RNA transcription from the DNA template that includes the c / .s-acting DNA sequence.

[0061] As used herein, "an engineered transcription template" or "an engineered expression template" refers to a non-naturally occurring nucleic acid that serves as substrate for transcribing at least one RNA. As used herein, "expression template" and "transcription template" have the same meaning and are used interchangeably. Engineered include nucleic acids composed of DNA or RNA. Suitable sources of DNA for use in a nucleic acid for an expression template include genomic DNA, cDNA and RNA that can be converted into cDNA. Genomic DNA, cDNA and RNA can be from any biological source, such as a tissue sample, a biopsy, a swab, sputum, a blood sample, a fecal sample, a urine sample, a scraping, among others. The genomic DNA, cDNA and RNA can be from host cell or virus origins and from any species, including extant and extinct organisms.

[0062] Transformation" or "transfection" describes a process by which exogenous nucleic acid (c. ., DNA or RNA) is introduced into a recipient cell. Transformation or transfection may occur under natural or artificial conditions according to various methods well known in the art, and may rely on any known method for the insertion of foreign nucleic acid sequences into a prokaryotic or eukaryotic host cell. The method for transformation or transfection is selected based on the type of host cell being transformed and may include, but is not limited to, bacteriophage or viral infection or non-viral delivery. Methods of non-viral delivery of nucleic acids include lipofection, nucleofection, microinjection, electroporation, heat shock, particle bombardment, biolistics, virosomes, liposomes, immunoliposomes, polycation or lipidmucleic acid conjugates, naked DNA, artificial virions, and agent-enhanced uptake of DNA. Lipofection is described in e.g., U.S. Pat. Nos. 5,049,386, 4,946,787; and 4,897,355) and lipofection reagents are sold commercially (e.g., Transfectam.TM. and Lipofectin.TM.). Cationic and neutral lipids that are suitable for efficient receptor-recognition lipofection of polynucleotides include those of Feigner, WO 91 / 17424; WO 91 / 16024. Delivery can be to cells (e.g. in vitro or ex vivo administration) or target tissues (e.g. in vivo administration). The term "transformed cells" or "transfected cells" includes stably transformed or transfected cells in which the inserted DNA is capable of replication either as an autonomously replicating plasmid or as part of the host chromosome, as well as transiently transformed or transfected cells which express the inserted DNA or RNA for limited periods of time.

[0063] The polynucleotide sequences contemplated herein may be present in expression vectors. For example, the vectors may comprise a polynucleotide encoding an ORF of a protein operably linked to a promoter. "Operably linked" refers to the situation in which a first nucleic acid sequence is placed in a functional relationship with a second nucleic acid sequence. For instance, a promoter is operably linked to a coding sequence if the promoter affects the transcription or expression of the coding sequence. Operably linked DNA sequences may be in close proximity or contiguous and, where necessary to join two protein coding regions, in the same reading frame. Vectors contemplated herein may comprise a heterologous promoter operably linked to a polynucleotide that encodes a protein. A "heterologous promoter" refers to a promoter that is not the native or endogenous promoter for the protein or RNA that is being expressed.

[0064] As used herein, "expression" refers to the process by which a polynucleotide is transcribed from a DNA template (such as into mRNA or another RNA transcript) and / or the process by which a transcribed mRNA is subsequently translated into peptides, polypeptides, or proteins. Transcripts and encoded polypeptides may be collectively referred to as "gene product."

[0065] The term "vector" refers to some means by which nucleic acid (e.g., DNA) can be introduced into a host organism or host tissue. There are various types of vectors including plasmid vector, bacteriophage vectors, cosmid vectors, bacterial vectors, and viral vectors. As used herein, a "vector" may refer to a recombinant nucleic acid that has been engineered to express a heterologous polypeptide e.g., the fusion proteins disclosed herein). The recombinant nucleic acid typically includes cv.s-acting elements for expression of the heterologous polypeptide.

[0066] In the methods contemplated herein, a host cell may be transiently or non-transiently transfected (z.e., stably transfected) with one or more vectors described herein. A cell transfected with one or more vectors described herein may be used to establish a new cell line comprising one or more vector-derived sequences. In the methods contemplated herein, a cell may be transiently transfected with the components of a system as described herein (such as by transient transfection of one or more vectors), and modified through the activity of a complex, in order to establish a new cell line comprising cells containing the modification but lacking any other exogenous sequence.

[0067] As used herein, the term "fuel gate" refers to a system able to process input to release secondary fuels. A fuel gate may be a DNA and / or RNA system able to process input molecules to release secondary fuels. The fuel may be a molecular input (such as nucleic-acid strand, pH or small molecule) that serves to activate the system by initiating a strand-displacement reaction or other fuel-induced downstream processes. The fuel gate may be double stranded DNA (dsDNA) or an RNA:DNA hybrid, in various aspects. In certain aspects, the fuel gate may include DNA and RNA in one strand of the double-stranded fuel gate molecule. In one or more aspects, the RNA, if present, in the fuel gate molecule can be modified, e.g., methylated. In various aspects, the fuel gate can comprise dsDNA, an RNA-DNA hybrid, an RNA-RNA duplex, a chemically modified RNA duplex, a chemically modified dsDNA, and / or a chemically modified RNA-DNA duplex. As disclosed herein, the fuel gate may include a waste strand, a RecycleD strand, or both. In the same or alternative aspects, one of the strands (e.g., the waste strand) could be composed of both modified RNA and DNA and can form a duplex with either DNA, RNA or methylated RNA. The fuel gate may comprise a waste strand and a RecycleD strand. In some embodiments, the target RNA molecule displaces the RecycleD strand from the fuel gate molecule which then allows the RecycleD strand to bind to a reporter molecule, and the binding to the reporter molecule results in a detectable signal being generated from the reporter molecule. In some embodiments, the target RNA molecule displaces the RecycleD strand from the fuel gate molecule which then displaces one of the strands of the quenched, fluorescently labeled double-stranded nucleic acid reporter molecule which results in dequenching of the fluorophore to generate the detectable signal. In some embodiments, RNA transcribed by off-target transcription by T7 RNA polymerase (T7 RNAP; promoter independent T7 RNAP transcription) is used to recycle circuit inputs, creating a catalytic amplification effect by which one circuit input can activate multiple outputs to increase sensitivity, the molecules of which can be referred to as the fuel gate molecule. As used herein, “off-target transcription” refers to transcription of DNA by an RNAP which begins from a 3’ toehold region of a dsDNA molecule. As used herein, the term "signal gate" refers to a system able indicate that an analyte or target is present in a sample, as such, signal gates may be referred to as “reporter molecules”. Suitable reporter molecules may include dsDNA molecules which may be referred to as dsDNA signal gate molecules. A signal gate may be a nucleic acid system. A signal gate may be a DNA system. The signal may be a molecular signal (such as nucleic-acid strand, pH or small molecule). The signal gate may be double stranded DNA (dsDNA). In some embodiments, the dsDNA signal gate molecule can be labeled with one or more functional chemical groups. In such aspects, the one or more functional chemical groups comprise one or more of a fluorophore, a quencher, biotin, or methylene blue. In one example aspect, the signal gate may comprise a nucleic acid strand comprising a quencher strand and a fluorophore-conjugated strand. In some embodiments, the signal gate may comprise a dsDNAcomprising a quencher strand and a fluorophore-conjugated with a toehold region. In some embodiments, the signal gate may comprise a dsDNA comprising a quencher strand with a toehold region and a fluorophore-conjugated strand. In some embodiments, a target RNA molecule may displace a strand of the fuel gate molecule by hybridizing to a waste strand, and a RecycleD strand displaces a strand of the dsDNA signal gate whereby a signal is generated (for example, a fluorescent signal), thereby indicating that an analyte or target molecule is present. Signal gates may be referred to as “signal transducers” in the art and elsewhere.

[0068] In some embodiments, a hybrid signal / fuel gate may be produced when the fuel gate molecule (e.g., a molecule comprising a waste strand and a RecycleD strand) generates a free singlestranded polynucleotide(e.g., a RecycleD strand) which displaces a strand of the dsDNA signal gate molecule to produce a detectable signal and a new hybrid signal / fuel gate, and wherein RNA polymerase transcribes the hybrid signal / fuel gate to release the RecycleD strand of DNA which can then displace an additional dsDNA signal gate molecule, thus creating a positive feedback loop of signal amplification.Peptides, Polypeptides, and Proteins

[0069] As used herein, the terms "protein" or "polypeptide" or "peptide" may be used interchangeable to refer to a polymer of amino acids. Typically, a "polypeptide" or "protein" is defined as a longer polymer of amino acids, of a length typically of greater than 50, 60, 70, 80, 90, or 100 amino acids. A "peptide" is defined as a short polymer of amino acids, of a length typically of 50, 40, 30, 20 or less amino acids.

[0070] A "protein" as contemplated herein typically comprises a polymer of naturally or non- naturally occurring amino acids (e.g., alanine, arginine, asparagine, aspartic acid, cysteine, glutamine, glutamic acid, glycine, histidine, isoleucine, leucine, lysine, methionine, phenylalanine, proline, serine, threonine, tryptophan, tyrosine, and valine). The proteins contemplated herein may be further modified in vitro or in vivo to include non-amino acid moieties. These modifications may include but are not limited to acylation e.g., O-acylation (esters), N-acylation (amides), S-acylation (thioesters)), acetylation (e.g., the addition of an acetyl group, either at the N-terminus of the protein or at lysine residues), formylation lipoylation (e.g., attachment of a lipoate, a C8 functional group), myristoylation (e.g., attachment of myristate, a C14 saturated acid), palmitoylation (e.g., attachment of palmitate, a C16 saturated acid), alkylation (e.g., the addition of an alkyl group, such as an methyl at a lysine or arginine residue), isoprenylation or prenylation (e.g., the addition of an isoprenoidgroup such as farnesol or geranylgeraniol), amidation at C-terminus, glycosylation (e.g., the addition of a glycosyl group to either asparagine, hydroxylysine, serine, or threonine, resulting in a glycoprotein). Distinct from glycation, which is regarded as a nonenzymatic attachment of sugars, polysialylation (e.g., the addition of polysialic acid), glypiation (e.g., glycosylphosphatidylinositol (GPI) anchor formation), hydroxylation, iodination (e.g., of thyroid hormones), and phosphorylation e.g., the addition of a phosphate group, usually to serine, tyrosine, threonine or histidine).

[0071] The proteins disclosed herein may include "wild type" proteins and variants, mutants, and derivatives thereof. As used herein the term "wild type" is a term of the art understood by skilled persons and means the typical form of an organism, strain, gene or characteristic as it occurs in nature as distinguished from mutant or variant forms. As used herein, a "variant, "mutant," or "derivative" refers to a protein molecule having an amino acid sequence that differs from a reference protein or polypeptide molecule. A variant or mutant may have one or more insertions, deletions, or substitutions of an amino acid residue relative to a reference molecule. A variant or mutant may include a fragment of a reference molecule. For example, a mutant or variant molecule may have one or more insertions, deletions, or substitution of at least one amino acid residue relative to a reference polypeptide.

[0072] Regarding proteins, a "deletion" refers to a change in the amino acid sequence that results in the absence of one or more amino acid residues. A deletion may remove at least 1, 2, 3, 4, 5, 10, 20, 50, 100, 200, or more amino acids residues. A deletion may include an internal deletion and / or a terminal deletion (e.g., an N-terminal truncation, a C-terminal truncation or both of a reference polypeptide). A "variant," "mutant," or "derivative" of a reference polypeptide sequence may include a deletion relative to the reference polypeptide sequence.

[0073] Regarding proteins, "fragment" is a portion of an amino acid sequence which is identical in sequence to but shorter in length than a reference sequence. A fragment may comprise up to the entire length of the reference sequence, minus at least one amino acid residue. For example, a fragment may comprise from 5 to 1000 contiguous amino acid residues of a reference polypeptide, respectively. In some embodiments, a fragment may comprise at least 5, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, 100, 150, 250, or 500 contiguous amino acid residues of a reference polypeptide. Fragments may be preferentially selected from certain regions of a molecule. The term "at least a fragment" encompasses the full-length polypeptide. A fragment may include an N-terminal truncation, a C-terminal truncation, or both truncations relative to the full-length protein. A "variant,""mutant," or "derivative" of a reference polypeptide sequence may include a fragment of the reference polypeptide sequence.[00741 Regarding proteins, the words "insertion" and "addition" refer to changes in an amino acid sequence resulting in the addition of one or more amino acid residues. An insertion or addition may refer to 1, 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 150, 200, or more amino acid residues. A "variant," "mutant," or "derivative" of a reference polypeptide sequence may include an insertion or addition relative to the reference polypeptide sequence. A variant of a protein may have N-terminal insertions, C-terminal insertions, internal insertions, or any combination of N-terminal insertions, C-terminal insertions, and internal insertions.

[0075] Regarding proteins, the phrases "percent identity" and "% identity," refer to the percentage of residue matches between at least two amino acid sequences aligned using a standardized algorithm. Methods of amino acid sequence alignment are well-known. Some alignment methods take into account conservative amino acid substitutions. Such conservative substitutions, explained in more detail below, generally preserve the charge and hydrophobicity at the site of substitution, thus preserving the structure (and therefore function) of the polypeptide. Percent identity for amino acid sequences may be determined as understood in the art. (See, e.g., U.S. Patent No. 7,396,664, which is incorporated herein by reference in its entirety). A suite of commonly used and freely available sequence comparison algorithms is provided by the National Center for Biotechnology Information (NCBI) Basic Local Alignment Search Tool (BLAST), which is available from several sources, including the NCBI, Bethesda, Md., at its website. The BLAST software suite includes various sequence analysis programs including "blastp," that is used to align a known amino acid sequence with other amino acids sequences from a variety of databases.

[0076] Regarding proteins, percent identity may be measured over the length of an entire defined polypeptide sequence, for example, as defined by a particular SEQ ID number, or may be measured over a shorter length, for example, over the length of a fragment taken from a larger, defined polypeptide sequence, for instance, a fragment of at least 15, at least 20, at least 30, at least 40, at least 50, at least 70 or at least 150 contiguous residues. Such lengths are exemplary only, and it is understood that any fragment length supported by the sequences shown herein, in the tables, figures or Sequence Listing, may be used to describe a length over which percentage identity may be measured.

[0077] Regarding proteins, the amino acid sequences of variants, mutants, or derivatives as contemplated herein may include conservative amino acid substitutions relative to a reference amino acid sequence. For example, a variant, mutant, or derivative protein may include conservative amino acid substitutions relative to a reference molecule. "Conservative amino acid substitutions" are those substitutions that are a substitution of an amino acid for a different amino acid where the substitution is predicted to interfere least with the properties of the reference polypeptide. In other words, conservative amino acid substitutions substantially conserve the structure and the function of the reference polypeptide. The following table provides a list of exemplary conservative amino acid substitutions which are contemplated herein:OriginalResidue Conservative SubstitutionAla Gly, Ser Arg His, Lys Asn Asp, Gin, His Asp Asn, Glu Cys Ala, Ser Gin Asn, Glu, His Glu Asp, Gin, His Gly Ala His Asn, Arg, Gin, Glu He Leu, Vai Leu He, Vai Lys Arg, Gin, Glu Met Leu, He Phe His, Met, Leu, Trp, Tyr Ser Cys, Thr Thr Ser, Vai Trp Phe, Tyr Tyr His, Phe, TrpVai He, Leu, Thr

[0078] Conservative amino acid substitutions generally maintain (a) the structure of the polypeptide backbone in the area of the substitution, for example, as a beta sheet or alpha helical conformation, (b) the charge or hydrophobicity of the molecule at the site of the substitution, and / or (c) the bulk of the side chain. Non-conservative amino acids typically disrupt (a) the structure of the polypeptide backbone in the area of the substitution, for example, as a beta sheet or alpha helicalconformation, (b) the charge or hydrophobicity of the molecule at the site of the substitution, and / or (c) the bulk of the side chain.[00791 The disclosed proteins, mutants, variants, or described herein may have one or more functional or biological activities exhibited by a reference polypeptide (e.g., one or more functional or biological activities exhibited by wild-type protein).

[0080] In some embodiments of the disclosed compositions, systems, kits, and methods, the components may be substantially isolated or purified. The term "substantially isolated or purified" refers to components that are removed from their natural environment, and are at least 60% free, preferably at least 75% free, and more preferably at least 90% free, even more preferably at least 95% free from other components with which they are naturally associated.Detection of RNA Molecules Using Regulated In Vitro Transcription with DNA Strand Displacement Circuits

[0081] Disclosed herein are compositions, systems, kits, and methods that relate to the detection of target RNA molecules using regulated in vitro transcription. The disclosed compositions, systems, kits, and methods include and utilize components as described herein including components for forming DNA strand displacement circuits.

[0082] In various aspects, the target RNA molecules can be any type of RNA molecule, including but not limited to micro RNAs (miRNAs), and viruses or parts thereof.

[0083] The disclosed compositions, systems, kits, and methods can comprise and / or utilize one or more components selected from: (a) an RNA polymerase; (b) a signal gate molecule; (c) a fuel gate molecule; and / or any combination thereof. The fuel gate molecule can include a waste strand and a RecycleD strand, where the waste strand and the RecycleD strand are at least partly complementary to one another and form an a double-stranded polynucleotide. When in the presence of the target RNA molecule, the target RNA molecule binds the fuel gate molecule thereby displacing the RecycleD strand generating a free single-stranded polynucleotide molecule that displaces a DNA strand of the signal gate molecule to produce a detectable signal and a new hybrid signal / fuel gate. The RNA polymerase transcribes the hybrid signal / fuel gate to release the RecycleD strand which can then displace an additional dsDNA signal gate molecule, thus creating a positive feedback loop of signal amplification.

[0084] The disclosure provides compositions, systems, and / or kits for detecting a target RNA molecule comprising as components: (a) an RNA polymerase; (b) a double-stranded DNA (dsDNA)signal gate molecule; and (c) a fuel gate molecule comprising a waste strand and a RecycleD strand, wherein the waste strand and the RecycleD strand are at least partly complementary to one another and form a double-stranded polynucleotide; wherein, when in the presence of the target RNA molecule, the target RNA molecule binds the fuel gate molecule thereby displacing the RecycleD strand generating a free single-stranded polynucleotide that displaces a DNA strand of the signal gate molecule to produce a detectable signal and a new hybrid signal / fuel gate, and wherein the RNA polymerase transcribes the hybrid signal / fuel gate to release the RecycleD strand which can then displace an additional dsDNA signal gate molecule, thus creating a positive feedback loop of signal amplification.

[0085] In some aspects, the dsDNA signal gate molecule is labeled with one or more functional chemical groups. In such aspects, the one or more functional chemical groups comprise one or more of a fluorophore, a quencher, biotin, or methylene blue. In one example aspect, the dsDNA signal gate molecule is a fluorescently labeled double-stranded DNA molecule comprising a fluorophore-conjugated strand having a fluorophore conjugated at its 3 ’-end and a quencher stand having a quencher conjugated at its 5’ end that quenches the fluorophore in the fluorescently labeled double-stranded DNA molecule. In some aspects, when in the presence of the of the target RNA molecule, the target RNA molecule binds the fuel gate molecule thereby displacing the RecycleD strand generating a free single-stranded polynucleotide that displaces the quencher strand from the dsDNA signal gate to produce a detectable signal. Depending upon the type of functional chemical groups associated with the dsDNA signal gate molecule, the detectable signal can be detected using one or more of fluorescence detection, e.g., in the case of a fluorophore label, lateral flow assay, e.g., in the case of a biotin label, or electrochemical detection, e.g., in the case of a methylene blue label.

[0086] In some aspects, when the RecycleD strand displaces the quencher strand of the fluorescently labeled double-stranded DNA molecule, the fluorophore of the fluorophore-conjugated strand is dequenched generating the detectable signal and the RecycleD strand hybridizes to the fluorophore-conjugated strand to generate the hybrid signal / fuel gate comprising a 3’ toehold on the fluorophore-conjugated strand and the RNA polymerase transcribes the fluorophore-conjugated strand and displaces the RecycleD strand and generates a fluorescent DNA / RNA hybrid, and wherein the released RecycleD strand can displace an additional signal gate generating a positive feedback loop of signal amplification.

[0087] Suitable RNA polymerases for inclusion or use in the disclosed compositions, systems, kits, and methods may include, but are not limited to, RNA polymerases derived from bacteriophages. Suitable RNA polymerases may include but are not limited to T7 RNA polymerase, T3 RNA polymerase, SP6 RNA polymerase, and Syn5 RNA polymerase. Suitable RNA polymerases may include engineered RNA polymerases as contemplated herein. In some embodiments, the RNA polymerase is T7 RNA polymerase.

[0088] In some aspects of the disclosed compositions, systems, kits, and methods, RNA transcribed by off-target transcription by T7 RNA polymerase (T7 RNAP; (promoter independent T7 RNAP transcription) is used to recycle circuit inputs, creating a catalytic amplification effect by which one circuit input can activate multiple outputs to increase sensitivity, the molecules of which can be referred to as the fuel gate molecule. In some embodiments, the fuel gate molecule (e.g., a hyrbid molecule comprising a waste strand and a RecycleD strand) generates a free single-stranded polynucleotide (e.g., a RecycleD strand) which displaces a strand of the dsDNA signal gate molecule to produce a detectable signal and a new hybrid signal / fuel gate, and wherein RNA polymerase transcribes the hybrid signal / fuel gate to release the RecycleD strand of DNA which can then displace an additional dsDNA signal gate molecule, thus creating a positive feedback loop of signal amplification.

[0089] In some aspects, suitable reporter molecules may include but are not limited to fluorescently labeled double-stranded DNA molecules e.g., which function as an output gate) comprising a top strand having a fluorophore conjugated at its 3’-end and a bottom strand having a quencher conjugated at its 5’ end that quenches the fluorophore in the fluorescently labeled doublestranded DNA molecule and a toehold region. In these embodiments, the RecycleD strand comprises a sequence that is complementary to the full length of the fluorophore-conjugated strand and the RecycleD displaces the quencher strand which results in dequenching of the fluorophore to generate the detectable signal. Typically, these reporter molecules are configured such that, the fluorophore- conjugated strand is longer than the quencher strand (e.g., by about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 nucleotides or more). In this configuration, displacement of the quencher strand by the RecycleD strand is thermodynamically favored because the RecycleD strand comprises a sequence that permits additional base-pairing between the RecycleD strand and the fluorophore-conjugated strand that is not presented between the fluorophore-conjugated strand and the quencher strand. The compositions, systems, kits, and methods may also suitably comprise or utilize a fluorescentlylabeled double-stranded DNA molecule comprising a top strand having a quencher conjugated at its 3 ’-end and a bottom strand comprising a fluorophore conjugated at its 5 ’-end. In these embodiments, the RecycleD strand is configured to bind the quencher strand, thereby displacing the fluorophore- conjugated strand and producing the detectable signal.

[0090] In some embodiments, the fuel gate molecule is a dsDNA molecule or an RNA:DNA hybrid molecule in various aspects. In certain aspects, the fuel gate may include DNA and RNA in one strand of the double-stranded fuel gate molecule. In one or more aspects, the RNA, if present, in the fuel gate molecule can be modified, e.g., methylated. In various aspects, the fuel gate can comprise dsDNA, an RNA-DNA hybrid, an RNA-RNA duplex, a chemically modified RNA duplex, and / or a chemically modified RNA-DNA duplex. In the same or alternative aspects, one of the strands (e.g., a waste strand) could also be composed of both modified RNA and DNA and can form a duplex with either DNA, RNA or methylated RNA. In one aspect, the fuel gate can comprise a fully methylated RNA strand and a DNA strand. In one or more aspects, the fuel gate molecule comprises a waste strand and a RecycleD strand. In some embodiments, the target RNA molecule is complementary to the waste strand and displaces the RecycleD strand. In such embodiments, the RecycleD strand is complementary to the fluorophore-conjugated strand of the dsDNA signal gate molecule and displaces the quencher strand comprising the quencher. Therefore, binding of the target RNA molecule to the waste strand must be thermodynamically favored compared to binding of the RecycleD strand to the waste strand. Likewise, the binding of the RecycleD strand to the fluorophore-conjugated strand of the dsDNA signal gate must be thermodynamically favored compared to the binding of the fluorophore-conjugated strand to the quencher strand, in an example aspect. Furthermore, in some embodiments, the full length of the RecycleD strand hybridizes to the fluorophore-conjugated strand, but leaves one or more nucleotides unhybridized, i.e., a toehold, at the 3’ end of the top strand. In some embodiments, the toehold is about 4 to about 8 nucleotides in length. In some embodiments, the toehold is about 4 nucleotides in length. In some embodiments, the waste strand, the quencher strand, or both comprise methylated nucleotides to prevent leakage of transcription. In some embodiments, the fuel gate molecule can comprise a 5’ waste strand toehold, a fuel gate dual-stranded region formed by hybridization of complementary nucleotides on the waste strand and RecycleD strand, and a 5’ RecycleD strand toehold. In various aspects, the 5’ waste strand toehold may be about 1-20 nucleotides in length, about 5-15 nucleotides in length, about 7-12 nucleotides in length, or about 9-10 nucleotides in length. In various aspects, the fuel gate dual-stranded region may be about 1-40 base pairs in length, about 10-30 base pairs in length, about 15-25 base pairs in length, about 18-22 base pairs in length, or about 20-22 base pairs in length. In various aspects, the 5’ RecycleD strand toehold may be about 1-10 nucleotides in length, about 2-8 nucleotides in length, about 4-6 nucleotides in length, or about 5 nucleotides in length. In one exemplary aspect, the 5’ waste strand toehold is about 9-10 nucleotides in length, the fuel gate dualstranded region is about 20-22 base pairs in length, and the 5’ RecycleD strand toehold is about 5 nucleotides in length. In some embodiments, the dsDNA signal gate can comprise a 5’ fluorophore strand toehold and a signal gate dual-stranded region formed by hybridization of complementary nucleotides on the fluorophore-conjugated strand to the quencher strand. In various aspects, the 5’ fluorophore strand toehold may be about 1-15 nucleotides in length, about 4-12 nucleotides in length, about 6-10 nucleotides in length, about 7-9 nucleotides in length, or about 8 nucleotides in length. In various aspects, the signal gate dual-stranded region dual-stranded region may be about 1-40 base pairs in length, about 10-30 base pairs in length, about 15-25 base pairs in length, about 18-24 base pairs in length, about 19-22 base pairs in length, or about 21-23 base pairs in length. In an exemplary aspect, the 5’ fluorophore strand toehold is about 8 nucleotides in length and the signal gate dualstranded region is about 21-23 base pairs in length.

[0091] In various aspects, each strand of the fuel gate molecule can be about 15-40 nucleotides in length, about 20-35 nucleotides in length, about 25-35 nucleotides in length, about 25- 32 nucleotides in length, or about 25-27 nucleotides in length. In various aspects, each strand of the signal gate molecule can be about 15-40 nucleotides in length, about 20-35 nucleotides in length, about 21-31 nucleotides in length, about 21-29 nucleotides in length, or about 21-23 nucleotides in length. In one aspect, the RecycleD strand of the fuel gate molecule is about 25-27 nucleotides in length, and the waste strand of the fuel gate molecule is about 29-32 nucleotides in length. In the same or alternative aspects, the fluorophore-conjugated strand is about 29-31 nucleotides in length, and the quencher strand is about 21-23 nucleotides in length. In one aspect, each strand of the signal gate molecule is about 15-30 nucleotides in length, about 19-27 nucleotides in length, about 15-25 nucleotides in length, or about 18-22 nucleotides in length. In the same or alternative aspects, each strand of the fuel gate molecule is about 15-25 nucleotides in length, or about 18-22 nucleotides in length.

[0092] In some embodiments, the waste strand comprises the sequence set forth in any one of SEQ ID NOs: 2, 7, 12, 17, 22, 28, 33, 40, or 50-56, or comprises a sequence having at least 70%, atleast 75%, at least 80%, at least 85%, at least 88%, at least 90%, at least 92%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% sequence identity to any one of one of SEQ ID NOs: 2, 7, 12, 17, 22, 28, 33, 40, or 50-56. In some embodiments, the RecycleD strand comprises the sequence set forth in any one of SEQ ID NOs: 3, 8, 13, 18, 23, 26, 29, 34, 37, 41, or 44, or comprises a sequence having at least 70%, at least 75%, at least 80%, at least 85%, at least 88%, at least 90%, at least 92%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% sequence identity to any one of one of SEQ ID NOs: 3, 8, 13, 18, 23, 26, 29, 34, 37, 41, or 44. In some embodiments, the fluorophore-conjugated strand of the dsDNA signal gate comprises the sequence set forth in any one of SEQ ID NOs: 4, 9, 14, 19, 24, 30, 35, 38, 42, or 45, or comprises a sequence having at least 70%, at least 75%, at least 80%, at least 85%, at least 88%, at least 90%, at least 92%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% sequence identity to any one of one of SEQ ID NOs: 4, 9, 14, 19, 24, 30, 35, 38, 42, or 45. In some embodiments, the quencher strand of the dsDNA signal gate comprises the sequence set forth in any one of SEQ ID NOs: 5, 10, 15, 20, 25, 31, 36, 39, 43, or 46, or comprises a sequence having at least 70%, at least 75%, at least 80%, at least 85%, at least 88%, at least 90%, at least 92%, at least 95%, at least 96%, at least 97%, at least 98%, or at least 99% sequence identity to any one of one of SEQ ID NOs: 5, 10, 15, 20, 25, 31, 36, 39, 43, or 46.

[0093] The compositions, systems, kits, and methods disclosed herein further may include or utilize additional components, such as additional components for performing RNA transcription. Additional components may include but are not limited to one or more of ribonucleoside triphosphates, an aqueous butter system that includes a reducing agent such dithiothreitol (DTT), divalent cations such as Mg++, spermidine, an inorganic pyrophosphatase, an RNase inhibitor, crowding agents, and monovalent salts (e.g.tNaCl and K-glutamate).

[0094] The components of the disclosed compositions, systems, kits, and methods may be mixed. For example, the components of the disclosed compositions, systems, kits, and methods may be mixed as an aqueous solution and / or may be dried or lyophilized to prepare a dried mixture which may be reconstituted (e.g., to perform the methods disclosed herein).

[0095] The disclosed compositions, systems, and kits, and the components thereof may be utilized in methods for detecting an analyte or target molecule in a sample (e.g., by performing an RNA transcription reaction). The methods may include contacting one or more components of the disclosed compositions, systems, and kits with the sample and detecting a detectable signal, thereby detecting the analyte or target molecule in the sample.EXEMPLARY EMBODIMENTS

[0096] Embodiment 1. A composition, system, or kit for detecting a target RNA molecule comprising as components:(a) an RNA polymerase;(b) a double-stranded DNA (dsDNA) signal gate molecule; and(c) a fuel gate molecule comprising a waste strand and a RecycleD strand, wherein the waste strand and the RecycleD strand are at least partly complementary to one another and form a double-stranded polynucleotide;

[0097] wherein, when in the presence of the target RNA molecule, the target RNA molecule binds the fuel gate molecule thereby displacing the RecycleD strand generating a free single-stranded polynucleotide that displaces a DNA strand of the signal gate molecule to produce a detectable signal and a new hybrid signal / fuel gate, and wherein the RNA polymerase transcribes the hybrid signal / fuel gate to release the RecycleD strand which can then displace an additional dsDNA signal gate molecule, thus creating a positive feedback loop of signal amplification.

[0098] Embodiment 2. The composition, system, or kit of embodiment 1, wherein the waste strand is at least partly complementary to the target RNA molecule.

[0099] Embodiment 3. The composition, system, or kit of embodiment 2, wherein the dsDNA signal gate molecule is labeled with one or more functional chemical groups.

[0100] Embodiment 4. The composition, system, or kit of embodiment 3, wherein the one or more functional chemical groups comprise a fluorophore, a quencher, biotin, or methylene blue.

[0101] Embodiment 5. The composition, system, or kit of embodiment 4, wherein the dsDNA signal gate molecule is a fluorescently labeled double-stranded DNA molecule comprising a fluorophore-conjugated strand having a fluorophore conjugated at its 3 ’-end and a quencher stand having a quencher conjugated at its 5’ end that quenches the fluorophore in the fluorescently labeled double-stranded DNA molecule.

[0102] Embodiment 6. The composition, system, or kit, of embodiment 5, wherein, when in the presence of the target RNA molecule, the target RNA molecule binds the fuel gate molecule thereby displacing the RecycleD strand generating a free single- stranded polynucleotide molecule that displaces the quencher strand from the dsDNA signal gate to produce a detectable signal.

[0103] Embodiment 7. The composition, system, or kit of embodiment 6, wherein, when the RecycleD strand displaces the quencher strand of the fluorescently labeled double-stranded DNAmolecule, the fluorophore of the fluorophore-conjugated strand is dequenched generating the detectable signal and the RecycleD strand hybridizes to the fluorophore-conjugated strand to generate the hybrid signal / fuel gate comprising a 3’ toehold on the fluorophore-conjugated strand and the RNA polymerase transcribes the fluorophore-conjugated strand and displaces the RecycleD strand and generates a fluorescent DNA / RNA hybrid, and wherein the released RecycleD strand can displace an additional signal gate generating a positive feedback loop of signal amplification.

[0104] Embodiment 8. The composition, system, or kit of embodiment 7, wherein the fluorophore-conjugated strand is longer than the quencher strand.

[0105] Embodiment 9. The composition, system, or kit of embodiment 8, wherein the fluorophore-conjugated strand is longer than the quencher strand by about 2 nucleotides to about 12 nucleotides, or about 2 to about 10 nucleotides.

[0106] Embodiment 10. The composition, system, or kit of any one of embodiments 5-9, wherein an RNA produced via transcription of the fluorophore-conjugated strand comprises a sequence that is complementary to the full length of the fluorophore-conjugated strand.

[0107] Embodiment 11. The composition, system, or kit of embodiment or any one of embodiments 5-10, wherein the fluorophore comprises fluorescein and / or 6-Carboxyfluorescein (6- FAM).

[0108] Embodiment 12. The composition, system, or kit of any one of embodiments 1-11, wherein the waste strand or the quencher strand comprises one or more non-natural modifications that prevent the strand from being utilized as a template for transcription (e.g., 2'-O-methylation).

[0109] Embodiment 13. The composition, system, or kit of any one of embodiments 1-12, wherein each strand of the signal gate molecule is about 15 to about 25 nucleotides in length, or about 18 to about 22 nucleotides in length.

[0110] Embodiment 14. The composition, system, or kit of any one of embodiments 1-13, wherein each strand of the fuel gate molecule is about 15 to about 25 nucleotides in length, or about 18 to about 22 nucleotides in length.

[0111] Embodiment 15. The composition, system, or kit of any one of embodiments 1-14, wherein the target RNA molecule is a miRNA or a virus.

[0112] Embodiment 16. The composition, system, or kit of any one of embodiments 1-15, wherein the RNA polymerase is selected from T7 RNA polymerase, T3 RNA polymerase, SP6 RNA polymerase, and Syn5 RNA polymerase or the RNA polymerase is an engineered polymerase.

[0113] Embodiment 17. The composition, system, or kit of any one of embodiments 1-16, further comprising one or more components for preparing a reaction mixture for RNA transcription.

[0114] Embodiment 18. The composition, system, or kit of any one of embodiments 1-17, wherein the double-stranded polynucleotide of the fuel gate molecule comprises a dsDNA molecule, an RNA-DNA hybrid, or an RNA-RNA duplex.

[0115] Embodiment 19. The composition, system, or kit of any one of embodiments 1-17, wherein at least one of the strands of the double-stranded polynucleotide of the fuel gate molecule comprises at least two of RNA, modified RNA, and DNA.

[0116] Embodiment 20. The composition, system, or kit of any one of embodiments 1-19, wherein the RecycleD strand is a DNA molecule.

[0117] Embodiment 21. The composition, system, or kit of any one of embodiments 1-20, wherein the waste strand comprises at least two of RNA, modified RNA, and DNA.

[0118] Embodiment 22. The composition, system, or kit of embodiment 21, wherein the modified RNA comprises methylated RNA.

[0119] Embodiment 23. A method for detecting an RNA molecule in a sample, the method comprising contacting the sample with the composition, system, or kit of any one of embodiments 1- 22.

[0120] Embodiment 24. The method of embodiment 23, further comprising detecting a signal.

[0121] Embodiment 25. The method of embodiment 23 or 24, wherein the RNA molecule can be detected in the sample at a concentration of at least about 0.1 nanomolar (nm), at least about 0.5 nm, or at least about 1 nm.

[0122] Embodiment 26. The composition, system, kit, or method of any one of embodiments 1-25, wherein the fuel gate molecule comprises a 5’ waste strand toehold, a fuel gate dual-stranded region, and a 5’ RecycleD strand toehold.

[0123] Embodiment 27. The composition, system, kit, or method of embodiment 26, wherein (i) the 5’ waste strand toehold is about 9-10 nucleotides in length, (2) the fuel gate dual-stranded region is about 20-22 base pairs in length, and / or (3) the 5’ RecycleD strand toehold is about 5 nucleotides in length.

[0124] Embodiment 28. The composition, system, kit, or method of any one of embodiments 1-25, wherein the dsDNA signal gate molecule comprises a 5’ fluorophore strand toehold and a signal gate dual-stranded region.

[0125] Embodiment 29. The composition, system, kit, or method of embodiment 28, wherein the 5’ fluorophore strand toehold is about 8 nucleotides in length and the signal gate dual-stranded region is about 21-23 base pairs in length.EXAMPLES

[0126] The following examples are illustrative and should not be interpreted to limit the scope of the claimed subject matter.Example 1 - Programming Cell-Free Biosensors with DNA Strand Displacement Circuits

[0127] Cell-free systems are powerful synthetic biology technologies because of their ability to recapitulate sensing and gene expression without the complications of living cells. Cell-free systems can perform even more advanced functions when genetic circuits are incorporated as information processing components (see, e.g., PCT / US2019 / 060790, PCT / US2022 / 018133, 18 / 311,030). Here we expand cell-free biosensing by engineering a highly specific isothermal signal amplification circuit called polymerase strand recycling (PSR) that leverages T7 RNA polymerase off-target transcription to recycle nucleic acid inputs within DNA strand displacement circuits. We develop design rules for PSR circuit components and use these rules to construct modular biosensors that can directly sense different RNA targets with limits of detection in the nM range and high specificity. We then use PSR for signal amplification within allosteric transcription factor-based biosensors for small molecule detection. We use a double equilibrium model of transcription factorDNA and transcription factorligand binding interactions to predict biosensor sensitivity enhancement by PSR, and then demonstrate this approach experimentally by achieving 3.6-4.6-fold decreases in biosensor EC50 to sub micromolar ranges. We believe this work expands the current capabilities of cell-free circuits by incorporating PSR, which we anticipate will have a wide range of uses within biotechnology.

[0128] Cell-free systems have enabled rapid, point-of-care detection of a wide range of important environmental and human health targets such as metals [1-3] (arsenic, lead, copper, cadmium, zinc, mercury), ions and small molecules [4-6] (fluoride, vitamin B1;benzoic acidderivatives), antibiotics [2] (tetracycline, oxytetracycline, chlortetracycline), disinfectant bi- products [2] (benzalkonium chloride), viruses [7] (Zika, Ebola), agricultural toxins [8] (atrazine), drugs [9, 10] (cocaine, gamma-hydroxybutyrate) and microbial quorum sensing molecules

[0011] , Furthermore, cell- free biosensing reactions can be assembled, freeze-dried, and simply rehydrated with samples for usage [12-15], and can be incorporated into device formats that can be used by non-experts

[0016] , As such, these systems are safe, easy-to-use, and field- deployable, showing great promise to address societal needs in environmental monitoring and human health [2, 5, 7, 9],

[0129] While promising, it is still a challenge to engineer cell-free biosensors to be able to detect chemicals at low enough concentrations to meet practical or regulatory use requirements, with recent reports of allosteric transcription factor (aTF)-based cell-free biosensors demonstrating limits of detection in the pM to mM range [2, 17, 18], while many toxic chemicals are regulated at the nM level [2, 17-19], To date, many strategies have been pursued for improving cell-free biosensor sensitivity such as enzymatic amplification or interfacing biosensors with physical devices such as electrochemical devices or lateral flow assays

[0020] , Electrochemical biosensing has the potential to increase sensitivity [21-23], but assay development is complex and expensive and often requires further miniaturization

[0020] , Lateral flow assays can improve limit of detection by decreasing the sample flow rate and increasing the duration of affinity reactions [24-26], but can be prone to interference by other analytes

[0020] , Enzymatic amplification systems such as isothermal nucleic acid amplification combined with CRISPR-Cas detection have been adapted for rapid sensing of nucleic acids and have reached the aM range for sensitivity

[0027] , However, these systems require extensive sample preparation steps

[0027] , and are not immediately applicable to the detection of small molecule compounds.

[0130] Here we sought to develop a simpler approach to improving cell-free biosensor sensitivity that leverages our ability to program nucleic acid circuits. Cell-free biosensors typically consist of an aTF that is designed to bind to a DNA reporter template: binding of the aTF to the DNA blocks expression of the reporter molecule, while the presence of a target ligand that binds to the aTF removes this block and allows reporter expression [2], Previously, we showed that biosensors could be made more sensitive by simply reducing the amount of aTF in these reactions [2], However, this strategy resulted in a significant increase in background signal (i.e., signal in the absence of ligand) due to insufficient repression of the DNA reporter template [2], We reasoned that this could be overcome by introducing a signal amplification layer to the system that would allow lower amountsof DNA template to be used, resulting in lower background in the absence of ligand and strong signals when small amounts of ligand are present.[001311 Our recent development of a cell-free small molecule sensing platform called RNA

[0132] Output Sensors Activated by Ligand INDuction (ROSALIND) [2] that utilizes toehold mediated strand displacement (TMSD) circuits

[0028] creates the possibility for such a signal amplification layer by leveraging the natural ability of T7 RNA polymerase to transcribe from 3’ toeholds exposed on DNA duplexes [28, 29], Specifically, we developed a new concept in nucleic acid circuitry, called polymerase strand recycling (PSR), that uses T7 RNAP off-target transcription from 3’ toeholds to recycle TMSD circuit inputs during the course of a biosensing reaction.

[0133] ROSALIND interfaced with PSR consists of three core layers: a sensing layer, a processing layer, and signal amplification layer (Figure 1). The sensing layer generates an RNA strand as a result of target ligand sensing. The processing layer takes the sensing layer RNA strand, utilizes TMSD circuits to add computational features if desired

[0028] , and generates an output DNA strand. The signal amplification layer consists of a quenched fluorophore DNA TMSD gate that can be strand displaced by the output of the processing layer. This is designed to result in a 3’ overhanging toehold which can be transcribed by T7 RNAP off-target transcription, resulting in the release of the original DNA strand, thus recycling it for further rounds of signal generation to enable signal amplification.

[0134] Here, we develop PSR by exploring the design principles of this architecture and applying it to sensitize circuits for the detection of both nucleic acid and small molecule ligands. We start by investigating the PSR phenomenon using RNA and DNA inputs, and show that T7 RNAP- mediated strand recycling only occurs when DNA TMSD gates are used. We next show that PSR can be used to amplify the signals from transcriptional circuits by designing an intermediate fuel gate as part of the processing layer to convert an input RNA into a recyclable DNA molecule that can be regenerated through PSR. We show this circuit design can be directly applied to the detection of RNA inputs, and demonstrate a limit of detection (LoD) of 5 - 250 nM for model miRNA targets. Interfacing PSR with ROSALIND by incorporating aTF operator sequences in the transcriptional templates allows PSR circuits to amplify signals from biosensing circuits that detect small molecules. We show that the incorporation of PSR allows a reduction in both the aTF and DNA template concentration required to enact sensing function, while still producing a signal compatible with onsite readout. Using a double equilibrium model of aTF DNA and aTFdigand binding interactions, wepredict that lowering aTF concentration can potentially improve sensitivity characterized by EC50 by up to three orders of magnitude if DNA template concentration is also sufficiently lowered to ensure adequate repression. We experimentally demonstrate how PSR enables this approach by applying it to the tetracycline sensing system using the TetR aTF to achieve an EC50 of 0.07 pM, representing a 3.6-fold reduction in EC50 from TMSD sensor circuits that do not use PSR. We also apply this approach to the zinc sensing system using the SmtB aTF to achieve an EC50 of 0.46 pM, representing a 4.6-fold reduction in EC50 from TMSD sensor circuits that do not use PSR. Importantly, these results represent a respective 14.7- and 15.1-fold reduction in EC50 over previously reported values for tetracycline and zinc detection

[0028] , Overall, this work shows that PSR is a generalizable method that can amplify cell-free biosensor signals and be used to improve the sensitivity of detection of a range of target ligands.

[0135] Results

[0136] Establishing Polymerase Strand Recycling with T7 RNA Polymerase.

[0137] We first sought to test the principle of PSR by designing an amplification system using T7 RNAP. As T7 RNAP is well characterized to transcribe DNA duplexes that contain 3’ toeholds without its natural promoter sequence [28-30], it should be possible to generate a signal amplification system within TMSD circuits by leaving 3’ toeholds on the product duplexes of strand displacement reactions (Figure 1).

[0138] TMSD signal generation systems typically consist of two components: an output nucleic acid strand produced directly from the sensing layer, and a fluorophore-strand: quencherstrand DNA signal gate (Figure 1). Strand displacement of the signal gate by the output strand results in a fluorophore-strand: output duplex that can generate fluorescent signal. To test the concept of PSR, we designed two ‘recycle’ strands to strand displace a DNA signal gate from previous work

[0031] and leave a four-nucleotide (nt) toehold on the 3’-end of the fluorophore strand. Both RNA (RNA input) and DNA (DNA input) versions of the recycle strands were designed to investigate potential differences in the ability of T7 RNAP to transcribe RNA-DNA and DNA- DNA duplexes from 3’ overhangs (Figure 2a).

[0139] DNA and RNA inputs were purified and added to IVT reactions containing 2.5 pM of the DNA signal gate, 2 ng T7 RNAP, and 0.5 pM of either DNA input, RNA input, or no input (Figure 2b). In the presence of RNA input, we observed low fluorescence activation (Figure 2b), while with DNA input, the fluorescence activation reached a level that was close to that of 2.5 pM ofisolated fluorophore-strand (Figure 2b, Supplementary Figure 2b). This suggests that RNA input can strand displace the signal gate, but T7 RNAP cannot recycle it efficiently from the resulting DNA- RNA hybrid fluorophore-strand:RNA-input complex. In contrast, the high signal observed from using DNA input suggests that T7 RNAP can transcribe the DNA-DNA fluorophore- strand :DNA- input complex. Overall, these results show that PSR is possible, though only with DNA-DNA duplexes, which informs the implementation of PSR within biosensing circuits.

[0140] Adding a “ fuel gate” to enable signal amplification through polymerase strand recycling.

[0141] The above results showed that PSR only works using a DNA strand as the recyclable output signal. However, transcriptional biosensors only produce RNA outputs, necessitating an interface that can convert an RNA signal into a DNA strand. To create this interface, we designed a “fuel gate”

[0032] that consisted of a DNA duplex comprised of a DNA strand, RecycleD and a complementary strand, designed to exchange a generated RNA strand, RecycleR, with RecycleD via toehold-mediated strand displacement (Figure 3a, Supplementary Figure 3). In this way, transcription of the RecycleR sequence can in principle invade and strand displace the fuel gate, releasing RecycleD for participation in downstream PSR amplification.

[0142] To test this concept, we designed DNA templates encoding the T7 RNAP promoter followed by two initiating guanines and the RecycleR sequence (Supplementary Data). Reactions were then assembled containing 2 ng T7 RNAP, 1.5 pM of the fuel gate, 2.5 pM of the signal gate and either 0 nM or 1 nM of the DNA template (Supplementary Figure 2). Interestingly, we observed that T7 RNAP could activate fluorescence signal even without the presence of DNA template (Supplementary Figure 2). We also observed that the signal activation did not reach the full level of the fluorescence observed only with 2.5 pM of the fluorophore strand alone, which we attribute to TMSD being unable to fully release 2.5 pM of the fluorophore strand from the quencher strand, as well as freed quencher strands still sequestering some fluorescent signal.

[0143] We hypothesized that the signal observed even without DNA transcription template was caused by the fuel gate duplex being too weak, allowing a small amount of dissociated RecycleD strand to displaced DNA signal gates and initiate PSR. To mitigate this effect, we incorporated 2’-O- methyl modifications on both fuel and signal gates, which are known to stabilize nucleic acid duplexes

[0033] (Supplementary Figure 4). Testing different combinations of modified fuel and signalgates showed that incorporating 2’-O-methyl modified fuel gates significantly reduced the background signal in the absence of DNA template (Supplementary Figure 4).[001441 Having demonstrated a functioning system, we next investigated how the system’s response varied with DNA template concentration, as well as the importance of the 4nt toehold of the signal gate. Reactions were set up as before, but containing a variable amount of DNA template in the range of 0.5-50 nM, and using versions of RecycleD designed to leave either 4- nt or 0-nt 3’ toeholds on the fluorophore-strand:RecycleD complex (Figure 3b). As expected, we observed significantly higher fluorescent signal with the 4-nt toehold than the 0-nt toehold (Figure 3b). In addition, for the 4-nt toehold case, we observed full signal generation with as little as 0.5 nM DNA template (Figure 3b), which is markedly lower than the 10-25 nM used in previous versions of the ROSALIND system [2, 28], An examination of reaction kinetics showed that this signal amplification can be achieved in ~35 minutes (Figure 3c), similar to the signal generation times in previous versions of ROSALIND

[0028] ,

[0145] Overall, these results demonstrate that PSR can process RNA inputs and serve as an amplification system for transcriptional circuits through the inclusion of a fuel gate, and that doing so allows a significant reduction in DNA template while preserving reaction kinetics with similar fluorescent output.

[0146] PSR circuits can be used to directly sense RNA targets.

[0147] After demonstrating that PSR can generate a fluorescent signal from RNA molecules transcribed from DNA templates, we next sought to explore the detection of RNA targets that are directly input into the system. Specifically, we modified the sequences of the fuel and signal gates to match portions of desired target RNAs where the target RNAs can release RecycleD for downstream PSR amplification (Supplementary Figure 5). The fuel gate contains a 2’-O- methyl modified strand that is complementary to the RNA target, plus several additional nucleotides to form a ~20-bp overlap with the unmodified RecycleD strand. The signal gate includes a fluorophore- strand that contains complementary sequence to RecycleD but leaves a 4-nt 3’ toehold when displaced to allow PSR, and a quencher- strand that is complementary to the fluorophore-strand but leaves an 8nt 5’ toehold on the fluorophore-strand to allow efficient invasion by RecycleD (Figure 4a). In this way, inputting the desired RNA signal should strand invade the fuel gate and release RecycleD to generate and amplify a fluorescent signal.

[0148] As a model target, we chose microRNAs (miRNAs), short non-coding RNAs that play an important role in gene regulation and have been widely reported as potential biomarkers for human diseases [34, 35], thus making them valuable targets for biosensors [36-38], Specifically, we chose three distinct miRNAs (miR-3185, miR-642a-5p, and miR-134-3p) that are biomarkers for fatigue and mood disturbances as inputs for PSR

[0039] ,

[0149] As a proof-of-concept, miRNA targets were synthesized and purified, and specificity of the platform was tested by adding 1 pM of input to each of three PSR circuits configured to sense only a single miRNA. Fluorescence characterization demonstrated that all three PSR systems were able to generate significantly higher fluorescent signal with their respective miRNA compared to the other two miRNAs (Figure 4b).

[0150] We next assessed sensitivity of the system by performing a titration with miRNAs and found the LoD, defined as the concentration value at which the signal was significantly greater than the no input condition, to be within the 5 - 250 nM range for PSR to detect nucleic acid targets (Figure 4c). Specifically, the miR-3185 target was detected with a LoD of 100 nM, the miR-642a-5p with a LoD of 250 nM, and the miR-134-3p with a LoD of 5 nM. Differences may be attributed to the number of base pairs in the fuel gate design (Supplementary Figure 5).

[0151] Overall, these results demonstrate that PSR circuits can be used to directly sense RNA inputs with high specificity and LoDs between 5 - 250 nM.

[0152] Interfacing transcriptional biosensors with PSR signal amplification.

[0153] We next sought to interface the PSR platform with transcriptional regulation by allosteric transcription factors (aTFs). With appropriately configured reporter templates, aTFs can bind to their cognate operator sequences and repress downstream transcription by T7 RNAP in the absence of its cognate ligand. However, in the presence of an aTF’s cognate ligand, the aTF unbinds from its operator sequence, allowing downstream transcription. We previously showed that this setup can be used as a cell-free biosensing platform by swapping in different aTF / operator pairs to detect different chemical contaminants in water

[0028] , In addition, we showed that this platform can be coupled to strand displacement circuitry by configuring the transcribed output RNA molecules to be complementary to downstream DNA gates, creating an opportunity to interface aTF biosensors with PSR circuitry.

[0154] To explore whether PSR signal amplification can be regulated with an aTF, we chose to focus on the TetR repressor by inserting the tetO operator sequence in between the T7 RNAPpromoter and RecycleR, using a 2-bp spacer between the two sequences that was found in previous work to be optimal for TMSD signal generation

[0028] (Figure 5a). We first tested whether the addition of tetO impacted PSR signal generation without TetR. Titrating a range of input DNA template concentrations revealed full signal generation with as little as 0.5 nM DNA template (Figure 5b), representing a 20X reduction compared to the 10 nM DNA template needed to generate signal from an equivalent TMSD reaction without PSR circuitry (Supplementary Figure 6).

[0155] We next determined the amount of TetR dimer required to fully repress the PSR and TMSD-only systems. For purposes of comparing regulated PSR vs. TMSD reactions, we chose to use 0.5 nM of PSR DNA template and 10 nM of TMSD DNA template which generated full reaction signals (Supplementary Fig 6). Titrating in a range of TetR concentrations showed that 0.5 nM of PSR DNA template can be fully repressed by 12.5 nM TetR dimer (25X) (Figure 5c), while 50 nM of TetR dimer (5X) was required to repress the TMSD circuit (Supplementary Figure 7).

[0156] Finally, we tested whether the PSR signal amplification circuitry could be derepressed by introducing the cognate ligand, tetracycline, to the TetR-regulated PSR system. Kinetic reaction traces demonstrate that the addition of tetracycline can induce transcription of RecycleR and activate fluorescent signal in a PSR reaction in a similar amount of time (~30 min) as previously observed in regulated TMSD reactions (Figure 5d)

[0028] ,

[0157] Overall, these results demonstrate that PSR can be coupled with aTF regulation to yield a functional biosensor signal amplification system. Intriguingly, the use of PSR also allows the reduction of the amount of DNA template and aTF needed to activate full fluorescent signal in the presence of ligand.

[0158] A simple equilibrium model of aTF:Ligand and aTF:DNA interactions predicts improvements in biosensor sensitivity.

[0159] The previous results demonstrate that PSR amplified biosensor circuits reduce the concentrations of aTF and DNA template required to enact sensing function. Previous work showed that reducing the concentration of aTF in the system can sensitize cell-free biosensors, though this strategy had the undesirable effect of increasing background signal in the absence of ligand because DNA template concentration was not sufficiently reduced, resulting in insufficient repression [2], Because PSR reduces both the required DNA template concentration and aTF concentration to enact sensing function, we hypothesized that PSR signal amplification circuitry could achieve the effect ofincreased sensitivity as observed in previous work without suffering from increased background signal in the absence of ligand.[001601 To investigate this hypothesis, we constructed a simple double-equilibrium model describing the behavior of aTFdigand and aTF:DNA binding interactions (see Supplementary Note). The model assumes that the timescale of transcription is much longer than the timescales of aTF ligand and aTF:DNA binding, which exist at equilibrium. The model takes as input DNA template concentration, aTF concentration, aTFdigand dissociation constant, aTF:DNA dissociation constant, and a range of ligand concentrations. The model then solves for the fraction of DNA template without aTF bound, which we assume directly relates to the level of transcription output.

[0161] To study the tetracycline-TetR system, we used literature values for the TetR:tetracy cline and TetR:DNA dissociation constants. We used the model to generate dose response curves for a range of TetR and DNA template concentrations. The model predicts that decreasing TetR concentration at constant TetR / DNA ratio can improve sensitivity characterized by EC50, the amount of ligand required to produce half-maximal induction, by approximately three orders of magnitude (Figure 6a). However, when TetR concentration approaches the TetR-DNA dissociation constant (-0.014 nM), predicted leak begins to increase where a non- negligible fraction of DNA template remains free from TetR repression in the absence of appreciable ligand (Figure 6a). The TetR:DNA dissociation constant thus limits the extent to which lowering TetR concentration can be used to reduce EC50 without resulting in increased background signal. Accordingly, the model predicts that lowering the TetR:DNA dissociation constant can allow further reductions in EC50 without increasing background signal, as long as TetR will still preferentially bind ligand over DNA, or in other words, as long as the TetR:tetracycline dissociation constant is sufficiently lower than the TetR:DNA dissociation constant (Figure 6b). Overall, these results suggest that the ability of PSR- amplified reactions to reduce aTF concentration should lead to improvements in biosensor sensitivity.

[0162] PSR signal amplification can be used to increase biosensor sensitivity.

[0163] Given that the model predicted enhanced sensitivity characterized by EC50, we next tested PSR with the tetracycline-sensing circuit. Using the previously optimized aTF and DNA template concentrations (Supplementary Figures 6, 7), we observed that the EC50 of the dose response with tetracycline was decreased by 4.6-fold with PSR (0.07 pM) compared to a TMSD- only system (0.32 pM), which is a 2.4-fold greater decrease than the 1.9-fold decrease predicted by the double equilibrium model (Figure 6c). Compared to the previously characterized EC50 fortetracycline sensing with TMSD circuits (1.03 pM)

[0028] , we demonstrated a 14.7-fold reduction in EC50 due to the fact that the previously published work used a higher amount of DNA template and TetR than the TMSD-only controls in this study.

[0164] To test the generality of the system, we next applied it to zinc-sensing with the SmtB transcription factor. SmtB is the canonical zinc-sensing aTF from the ArsR / SmtB family of regulators that responds to metal ions

[0040] , Similar to TetR, SmtB is also an aTF that binds to its cognate operator sequence as a dimer, smtO, and can be de-repressed by zinc as well as Co(II) and Cd(II)

[0041] , Using a similar approach as for TetR, we first determined the DNA template concentration to use for PSR and TMSD-only systems and chose 1 nM of PSR DNA template and 25 nM of TMSD DNA template to use with circuits configured with smtO (Supplementary Figure 8). We next optimized [SmtB dimer]: [DNA] ratios to find the minimum amount of SmtB dimer needed to repress each system which was 0.25 pM (250X) for PSR and 0.625 pM (25X) for TMSD (Supplementary Figure 9). With the optimized component concentrations, we then performed a titration with ZnSO4and found that the EC50 of the zinc- sensing biosensor could also be reduced with PSR (0.46 pM) by 3.6-fold compared to TMSD (1.66 pM) (Figure 6d), representing a 15.1-fold EC50 reduction in EC50 compared to previously published work (6.95 pM) which used a higher amount of DNA template and SmtB than the TMSD-only controls in this study

[0028] ,

[0165] Overall, these results showed that PSR signal amplification can be generalized and applied to biosensors based on both the TetR and SmtB / ArsR families of transcription factors, and that sensitivity enhancements can be achieved through PSR as hypothesized.

[0166] Discussion

[0167] In this study, we present the development of polymerase strand recycling - a new concept in nucleic acid circuitry and DNA nanotechnology that uses T7 RNAP off-target transcription to create autocatalytic cycles of signal amplification of TMSD circuits. By using transcription to regenerate TMSD circuit inputs, the PSR process acts conceptually similarly to ‘fuel’ strands that regenerate inputs in other TMSD autocatalytic schemes

[0032] , However, by designing PSR to function in the context of in vitro transcription reactions, we show that PSR can be used as a signal amplification module for cell-free biosensing circuits that can sense RNA targets and small molecules, thus expanding the function of autocatalytic TMSD signal amplification. In this way, PSR is another type of information processing circuit system that can improve overall biosensor performance without having to perform protein engineering of the components

[0028] ,

[0168] The concept of PSR is inspired by previous work in DNA nanotechnology that developed nucleic acid signal amplification circuits such as catalytic hairpin assembly (CHA) [42, 43] and hybridization chain reaction (HCR)

[0044] which use TMSD to recycle a nucleic acid strand to enable an autocatalytic cycle of amplification. However, these existing circuits are not compatible with transcriptional biosensors due to exposed 3’ toeholds that cause T7 RNA Polymerase (RNAP) off-target transcription [28, 29], PSR thus represents an advance of the fuel concept in two ways: (1) it allows fuel-driven signal amplification to be compatible with transcriptional circuitry, and (2) instead of using a nucleic acid fuel, it uses the RNA polymerase enzyme. The latter concept is important, as in PSR the fuel-driven reactions are not limited by the amount of specific fuel strand supplied in the reactions, but rather could continue as long as T7 transcription was supported by the reaction. We therefore anticipate creative uses of the PSR concept in a range of DNA nanotechnology circuits and applications.

[0169] An intriguing feature of signal amplification is that it can potentially be used to enhance biosensor sensitivity. Specifically, a double equilibrium model of aTF:DNA and aTFdigand binding interactions predicts that decreasing aTF and DNA template concentration can improve biosensor sensitivity characterized by EC50 (Figure 6a). Signal amplification enables this prediction to be realized in practice because it lowers the concentrations of aTF and DNA template required to enact sensing function without increasing sensor leak. Theoretically, we can lower the aTF concentration required to sufficiently repress transcription down to near its KD, where KDis the aTF:DNA dissociation constant. For the TetR system, this dissociation constant is approximately 0.014 nM, though this limit may be unattainable in practice if stochastic effects begin to dominate at low concentrations. In our present study, we show that in the case of tetracycline sensing with the TetR aTF, PSR can provide a 4.6-fold reduction in EC50 and in the case of zinc sensing with the SmtB aTF, PSR can provide a 3.6-fold reduction in EC50 compared to TMSD biosensing circuits without signal amplification (Figure 6c-d). These results overall support the model, but do not exactly match model predictions. This could be caused by several factors, including the potential for PSR to generate and amplify fluorescent signal from low amounts of unbound DNA template which causes a non-linear relationship between the amount of unbound DNA template and observed fluorescence output, potential problems with aTF quality causing a fraction of the aTF population to be non-functional, and discrepancies between the dissociation constants used in the model and those apparent in the actual system. With further improvements in aTF purification strategies that cangenerate high quality proteins, and further engineering of the system, it may be possible to get closer to the theoretical limit, which could greatly improve the performance of cell-free biosensors and allow them to meet various regulatory and recommended detection thresholds for a range of important contaminants

[0045] ,

[0170] T7 RNAP off-target transcription from 3’ toeholds is typically presented as a design limitation in DNA nanotechnology circuits [28, 29], Here we were able to turn this ‘bug’ into a ‘feature’ by developing design rules to control and leverage this behavior to act as a fuel that recycles input nucleic acid strands. One challenge we encountered was the inhibiting effects of DNA-RNA duplexes on T7 RNAP off-target transcription (Figure 2). Based on previous reports showing that DNA-RNA duplexes appear to adopt an overall A-form while DNA-DNA duplexes adopt B-form helices, we speculate that the DNA-RNA duplex conflicts with the polymerase structure and inhibits 3’ toehold off-target transcription

[0046] , We were ultimately able to address this challenge by implementing an intermediate fuel gate design that in effect takes an input RNA and converts it to a DNA strand that can then participate in strand recycling (Figure 3).

[0171] For the most part, the design of PSR circuits follows simple rules of designing a fuel gate with an overlap of 18- to 22-bp between RecycleD and a 2’-O-methyl modified strand to sequester the RNA input, and designing a signal gate that can be strand invaded by RecycleD to form a new duplex with a 3’-toehold for T7 RNAP off-target transcription (Supplementary Figures 3, 5). Using these rules, we were able to design a modular system that works with transcription, and that can sense different compounds with aTFs by changing the aTF operator site in the transcription template (Figure 6). Applying these concepts to direct detection of RNAs was also possible by designing the sequence of the fuel gate to be strand invaded by an RNA input sequence while maintaining a ~20-bp overlap between RecycleD and the 2’-O-methyl modified strand. This worked well in the context of detecting miRNA sequences, where we were able to design systems that can detect in vitro synthesized versions of miR-3185, miR-134-3p and miR-642a-5p with high degrees of specificity and LoDs on the order of 5 - 250 nM.

[0172] One limitation of the PSR system is the cost of the chemically modified gate components. We found that introduction of 2’-O-methyl to the waste strand to form the duplex with RecycleD in the fuel gate reduced leak in the absence of input and improved the biosensor dynamic range. While each set of gate designs with these modifications currently cost -100 USD, we found we could still perform hundreds of reactions with each batch of oligos. Fortunately, the PSR systemis highly modular, allowing us to use the same set of fuel gate and signal gate for different sensing targets to justify the cost of oligos.[001731 We believe the PSR circuit can be interfaced with other molecular computation circuits to expand capabilities of cell-free systems. For example, PSR could serve as an amplified output for logic gates [3, 28, 47], genelets [48, 49], co-transcriptionally activated RNA gates [50, 51], or other signal processing circuits to control complex computations in cell-free systems

[0052] , We also envision using PSR to amplify RNA transcriptional signals from other polymerases that are less efficient than T7 RNAP, such as E. coll RNAP, to enable robust signal generation.

[0174] Overall, we believe PSR will serve as an important component in an expanding toolbox of cell-free nucleic acid circuitry that can be used to enhance biosensing reaction performance. In this way they enhance the many strong features of cell-free biosensors including their accessibility, relatively low cost, modularity and ability to operate in field conditions [2, 5, 16, 28], In addition, we anticipate other creative applications of the PSR concept in a range of biotechnologies, including TMSD circuits, where signal amplification and genetic circuits are important for function.

[0175] Materials and Methods

[0176] Strains and growth medium.

[0177] Escherichia coli strain K12 (NEB Turbo Competent E. coli, New England Biolabs, catalog no. C2984) was used for routine cloning. E. coli strain Rosetta 2(DE3)pLysS (Novagen, catalog no. 71401) was used for recombinant protein expression. Luria broth supplemented with the appropriate antibiotic(s) (lOO pg mE1carbenicillin, lOO pg mE1kanamycin and / or Sd pg mE1chloramphenicol) was used as the growth media.

[0178] DNA gate preparation.

[0179] DNA fuel gates and signal gates used in this study were synthesized by Integrated DNA technologies as HPLC purified and chemically modified oligos (Supplementary Data). Gates were generated by denaturing complementary strands at 95° C for 5 min and slow cooling (- 0.1 °C s ') to room temperature in annealing buffer (50 mM Tris-HCl, pH 8.0, 10 mM MgCl2). DNA fuel gates and signal gates were stored at 4°C until use.

[0180] Plasmids and genetic parts assembly.

[0181] DNA oligonucleotides for cloning and sequencing were synthesized by Integrated DNA Technologies. Genes encoding aTFs were synthesized either as gBlocks (Integrated DNATechnologies) or gene fragments (Twist Bioscience). Protein expression plasmids were cloned using Gibson Assembly (NEB Gibson Assembly Master Mix, New England Biolabs, catalog no. E2611) into a pET-28c plasmid backbone and were designed to overexpress recombinant proteins as C- terminus His-tagged fusions. A construct for expressing SmtB additionally incorporated a recognition sequence for cleavage and removal of the His-tag using TEV protease. Gibson assembled constructs were transformed into NEB Turbo cells, and isolated colonies were purified for plasmid DNA (QIAprep Spin Miniprep Kit, Qiagen, catalog no. 27106). Plasmid sequences were verified with Sanger DNA sequencing (Quintara Biosciences) using the primers listed in Supplementary Data.

[0182] All transcription templates were generated using PCR amplification (Phusion High- Fidelity PCR Kit, New England Biolabs, catalog no. E0553) of an oligo that includes a T7 RNAP promoter, an optional aTF operator site, and the InvadeR or RecycleR coding sequence. All oligos and primer sets used in this study are listed in Supplementary Data. Here, we define the T7 RNAP promoter as a minimal 17-bp sequence (TAATACGACTCACTATA; SEQ ID NO: 47) excluding the first G that is transcribed. The PCR-amplified templates were purified (QIAquick PCR purification kit, Qiagen, catalog no. 28106) and verified for the presence of a single DNA band of expected size on a 2% Tris-Acetate-EDTA-agarose gel. Concentrations of all DNA templates were determined using the Qubit dsDNA BR Assay Kit (Invitrogen, catalog no. Q32853)

[0183] All plasmids and DNA templates were stored at 4 °C until use. A spreadsheet listing the sequences and the Addgene accession numbers of all plasmids and oligos used or generated in this study are listed in Supplementary Data

[0184] RNA expression and purification.

[0185] RecycleR used for Figure 2 was first expressed by an overnight IVT at 37 °C from a transcription template encoding a c / s-cleaving hepatitis D ribozyme on the 3 '-end of the RecycleR sequence with the following components: IVT buffer (40 mM Tris-HCl pH 8, 8 mM MgCl2, 10 mM dithiothreitol, 20 mM NaCl and 2. mM spermidine), 11.4 mM NTPs pH 7.5, 0.3 units (U) of thermostable inorganic pyrophosphatase (New England Biolabs, catalog no. M0296S), lOO nM transcription template, 50 ng of T7 RNAP and MilliQ ultrapure H?O to a total volume of 500 pl The overnight IVT reactions were then ethanol-precipitated and purified by resolving them on a 20% urea-PAGE-TBE gel, isolating the band of expected size (26-29 nucleotides) and eluting at 4 °C overnight in MilliQ ultrapure H;O. The eluted InvadeR and RecycleR variants were ethanol- precipitated, resuspended in MilliQ ultrapure H2O, quantified using the Qubit RNA BR Assay Kit(Invitrogen, catalog no. QI 021 1) and stored at -20 °C until use. The hepatitis D ribozyme sequence used can be found in Supplementary Data. miRNA used for miRNA sensing experiments were synthesized and PAGE purified by Integrated DNA Technologies.

[0186] aTF expression and purification.

[0187] aTFs were expressed and purified as previously described [2], Briefly, sequence- verified pET- 28c plasmids were transformed into the Rosetta 2(DE3)pLysS E. colt strain. Cell cultures (1- 2 L) were grown in Luria broth at 37 °C, induced with 0.5 raM of isopropyl-p-D- thiogalactoside at an optical density (600 nm) of ~0.5 and grown for a further 4 h at. 37 °C. Cultures were then pelleted by centrifugation and were either stored at -80 °C or resuspended in lysis buffer (10 mM Tris-HCl pH 8, 500 mM NaCl, 1 mM Tris(2-carboxyethyl)phosphine (TCEP) and protease inhibitor (Complete EDTA-free Protease Inhibitor Cocktail, Roche)) for purification. Resuspended cells were then lysed on ice through ultrasonication, and insoluble materials were removed by centrifugation. Clarified supernatant containing TetR was then purified using His-tag affinity chromatography with a Ni-NTA column (HisTrap FF 5 ml column, GE Healthcare Life Sciences) followed by size-exclusion chromatography (Superdex HiLoad 26 / 600 200 pg column, GE Healthcare Life Sciences) using an AKTAxpress fast protein liquid chromatography system. For SmtB expression and purification cultures and induction were performed in the same fashion as TetR, pellets were resuspended with a previously degassed lysis buffer (25mM MES, 750mM NaCl ImM EDTA, pH 6, 2mM TCEP, O.lmM PMSF) and then lysed via ultrasonication. Lysates were then centrifuged, and the supernatant treated with 0.015 %V / V of Poly (ethyleneimine) solution. The suspension was again centrifuged, and the supernatant taken to 70% ammonium sulfate. The suspension was centrifuged, and the pellet resuspended in lysis buffer with 75mM NaCl, for subsequent dialysis with the same buffer in a 10kDa dialysis bag. The dialysis product was centrifuged, and the supernatant loaded into a SP cation exchange column to be eluted with a gradient of high salt lysis buffer. The fractions containing protein were pooled and treated for 16 hours with TEV protease, then loaded into a Superdex 75 size exclusion column equilibrated with S75 buffer (25mM Tris, 200mM NaCl, pH 8, degassed, 2mM TCEP). Fractions corresponding with the protein’s weight were pooled and concentrated. Protein concentrations were measured via the Qubit Protein Assay Kit, and protein purity and size were verified via SDS-PAGE gel. Purified proteins were stored at -20 °C. The eluted fractions from the fast, protein liquid chromatography for TetR were concentrated and buffer exchanged (25 mM Tris-HCl, 100 mM NaCl, 1 mM TCEP, 50% glycerolv / v) using centrifugal filtration (Aniicon Ultra-0.5, Millipore Sigma). Protein concentrations were determined using the Qubit Protein Assay Kit (Invitrogen, catalog no. Q33212). The purity and size of the proteins were validated on an SDS PAGE gel (Mini-PROTEAN TGX and Mini -TETRA cell, Bio-Rad). Purified proteins were stored at -20 °C.

[0188] PSR Reactions.

[0189] PSR reactions and miRNA-sensing PSR reactions were set up by adding the following components listed at their final concentration: IVT buffer (40 mM Tris-HCl pH 8, 8 mM MgCL, 10 mM dithiothreitol, 20 mM NaCl and 2 mM spermidine), 11.4 mM NTPs pH 7.5, 0.3 U of thermostable inorganic pyrophosphatase (New England Biolabs, catalog no. M0296S), transcription template, DNA gate(s) and MilliQ ultrapure H2O to a total volume of 20 pL. Regulated PSR reactions additionally included a purified aTF at the indicated concentration and were incubated at 37 °C for ~10 min.

[0190] Immediately before plate reader measurements, 2 ng of T7 RNAP and, optionally, a ligand or purified miRNA at the indicated concentration were added to the reaction. Reactions were then characterized on a plate reader as described in ‘Plate reader quantification and micromolar equivalent fluorescein standardization’.

[0191] Plate reader quantification and micromolar equivalent fluorescein standardization.

[0192] A National Institute of Standards and Technology traceable standard (Invitrogen, catalog no. F36915) was used to convert arbitrary fluorescence measurements to micromolar equivalent fluorescein (MEF). Serial dilutions from a 50 pM stock were prepared in 100 mM sodium borate buffer at pH 9.5, including a 100 mM sodium borate buffer blank (total of 12 samples). For each concentration, three replicates of samples were created in batches of three, and fluorescence values were read at an excitation wavelength of 490 nm and emission wavelength of 525 nm for 6- FAM (fluorescein)-activated fluorescence (Synergy Hl, BioTek Gen5 v.2.04). Fluorescence values for a fluorescein concentration in which a single replicate saturated the plate reader were excluded from the analysis. The remaining replicates (three per sample) were then averaged at each fluorescein concentration, and the average fluorescence value of the blank was subtracted from all values. Linear regression was then performed for concentrations within the linear range of fluorescence (0- 3.125 pM fluorescein) between the measured fluorescence values in arbitrary units and the concentration of fluorescein to identify the conversion factor. For each plate reader, excitation,emission and gain setting, we found a linear conversion factor (setting the y intercept to 0) that was used to correlate arbitrary fluorescence values to MEF (Supplementary Figure 1).[001931 For reaction characterization, 19 pL of reactions were loaded onto a 384-well optically clear, flat- bottom plate using a multichannel pipette, covered with a plate seal and measured on a plate reader (Synergy Hl, BioTek Gen5 v.2.04). Kinetic analysis of 6-FAM (fluorescein)-activated fluorescence was performed by reading the plate at 1-min intervals with excitation and emission wavelengths of 490 and 525 nm, respectively, for 1 hr (ligand-sensing reactions) or 2 hrs (miRNA- sensing reactions) at 37 °C. Arbitrary fluorescence values were then converted to MEF by dividing by the appropriate calibration conversion factor.

[0194] Hill equation fits.

[0195] Where indicated, data were fit to the Hill equation with the following functional form:

[0196] Where [ligand] denotes ligand concentration, c represents the response with no ligand, a represents the maximum response, and n describes the cooperativity. Fitting was performed on individual replicate datasets using DataGraph 5.2 by starting with a = 1.5, EC5o = 1, c = 1, n = 1, then optimized for exact parameters with DataGraph 5.2. Curves were generated from fitting the average of the replicates for plotting. For TetR and SmtB dose response curves, EC5o values were obtained from the fits of the average of the replicates.

[0197] Statistics and reproducibility

[0198] The number of replicates and types of replicates performed are described in the legend of each figure. Individual data points are shown, and where relevant, the average ± s.d. is shown; this information is provided in each figure legend. The type of statistical analysis performed in Figures 2b, 3b, 4b, and 4c is described in the legend to each figure. Exact p-values along with degrees from the statistical analysis can be found in Source Data.

[0199] Data availability

[0200] All data presented in this paper are available as Source Data and as Supplementary Data. Both plasmids used in this paper are available in Addgene with the identifiers 140371 and 140395. Source Data are provided with this paper.

[0201] Supplementary Note. A double equilibrium model predicts enhancement of biosensor sensitivity when less aTF is included.

[0202] To predict expected transcription levels for different DNA / aTF / ligand concentrations, we developed a simple double equilibrium model describing the behavior of aTFdigand and aTF:DNA binding interactions. The model takes as input DNA template concentration, aTF concentration, ligand concentration, DNA / aTF dissociation constant, and ligand / aTF dissociation constant, and solves for the fraction of DNA template without aTF bound, which relates to expected transcription level. The model contains five equations (species balances and dissociation equilibria) and five unknowns (species concentrations). Using substitution, the five equations can be reduced to a single nonlinear equation containing a single unknown, which can be solved numerically. The remaining unknowns can then be solved for via back substitution.

[0203] Table 1 : Model Notation (see also Figure 16)

[0206] The species conservation equations for DNA, ligand, and aTF are as follows:

[0207] Solving the double equilibrium:

[0208] We assume that the aTF can bind to either the DNA template or the ligand, but not both simultaneously. For a given experimental condition (specified by the input concentration of each molecular species), we assume that the fraction of DNA unbound by aTF is proportional to the transcription output signal generated. Therefore, the goal of the double equilibrium analysis is to solve for [DNA] / [DNA]T as a function of [aTF]? and [L]T.

[0209] From (2) and (3):[00210J Rearranging gives:

[0211] [DNA] / [DNA]T can then be written as a function of [aTF]:

[0212] An expression for [aTF] is then needed to compute [DNA] / [DNA]T From (5):[aTF] = [aTF]T- [L • aTF] - [DNA ■ aTF]

[0213] Expressions for [L • aTF] and [DNA • aTF] are then required. From (4):[L • aTF] = [L]T- [L]

[0214] Using (1) to find an expression for [L], the above can be re-written as:

[0215] Combining terms in the above expression gives:

[0216] Similarly, using (3) and (2) gives:

[0217] Therefore,

[0218] Using (7) and (8) in the expression for [aTF] gives:

[0219] This non-linear equation can be numerically solved for the single unknown [aTF], which can then be used in equation (6) to find f. The remaining unknowns can then be found from equations (1) through (5).

[0220] For studying the tetracycline-TetR system, we assume in this model that:TetR exists only as a dimer. Two tetracycline molecules bind to one TetR dimer. TetR dimer bound to tetracycline cannot bind DNA. One tetO site per DNA. The fraction of DNA unbound by TetR is proportional to the transcription output signal generated.

[0221] Table 2: Parameters used for monitoring the testracycline-tetR system

[0222] It is important to note that TetR is a homodimer, and that each homodimer has the capacity to repress one DNA template and has the capacity to bind two tetracycline molecules. Therefore, all expressions stated here relating to aTF concentration including [aTF]?, [aTF], and [L ■ aTF] consider the TetR homodimer. When solving the generalized double equilibrium model stated in equations 1-8, the two-to-one ratio of tetracycline to TetR homodimer needs to be accounted for. To account for this, we use an “effective” total ligand concentration in the associated Jupyter Notebook calculations, which is equal to the total concentration of tetracycline added divided by two. When translating the model to other ligand-aTF systems, it is important to adjust the Jupyter Notebook calculations accordingly.

[0223] We then use this formalism to calculate fraction of unoccupied DNA template as a function of total DNA, TetR and aTc concentrations. A Jupyter Notebook solving this system of equations can be found in Supplementary _Data_2.ipynb

[0224] References for Example 1

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[0253] 30. Krupp, G., Unusual promoter-independent tianscription reactions with bacteriophage RNA polymerases. Nucleic Acids Res, 1989. 17(8): p. 3023-36.

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[0265] 42. Karunanayake Mudiyanselage, A.P.K.K., et al., Genetically Encoded CatalyticHairpin Assembly for Sensitive RNA Imaging in Live Cells. Journal of the American Chemical Society, 2018. 140(28): p. 8739-8745.

[0266] 43. Luo, Z., et al., Catalytic hairpin assembly as cascade nucleic acid circuits for fluorescent biosensor: Design, evolution and application. TrAC Trends in Analytical Chemistry, 2022. 151: p. 116582.29

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[0268] 45. USEPA. National Primary Drinking Water Regulations, [cited 2024 02 / 13 / 2024];Available from: https: / / www.epa.gov / ground-water-and-drinking-water / national-primary- drinkingwater-regulations#one.

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[0270] 47. Nielsen, A.A., et al., Genetic circuit design automation. Science, 2016. 352(6281): p. aac7341.

[0271] 48. Schaffter, S.W. and R. Schulman, Building in vitro transcriptional regulatory networks by successively integrating multiple functional circuit modules. Nature Chemistry, 2019. 11(9): p. 829-838.

[0272] 49. Schaffter, S.W., et al., Standardized excitable elements for scalable engineering of far from-equilibrium chemical networks. Nature Chemistry, 2022. 14(11): p. 1224-1232.

[0273] 50. Schaffter, S.W. and E.A. Strychalski, Cotranscriptionally encoded RNA strand displacement circuits. Science Advances, 2022. 8(12): p. eabl4354.

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[0275] 52. Jeong, D., et al., Cell-Free Synthetic Biology Platform for Engineering SyntheticBiological Circuits and Systems. Methods Protoc, 2019. 2(2).

[0276] References associated with Table 2

[0277] 1. Kamionka, A., et al., Two mutations in the tetracycline repressor change the inducer anhydrotetracycline to a corepressor. Nucleic Acids Res, 2004. 32(2): p. 842-7.

[0278] 2. Kedracka-Krok, S. and Z. Wasylewski, Kinetics and equilibrium studies of Tet repressor- operator interaction. J Protein Chem, 1999. 18(1): p. 117-25.Example 2 - Design Principles for Polymerase Strand Recycling Circuits

[0279] Cell-free biosensing is a rapidly developing technology platform because of its ability to detect a wide range of nucleic acid, protein and chemical targets at the point-of-need without expensive conventional laboratory equipment [1-6], A key component of cell-free biosensing reactions are programmable molecular circuits that improve biosensor speed, sensitivity andspecificity by performing molecular computations such as logic evaluation and signal amplification [7, 8], Recently there has been an interest in performing these computations with DNA nanotechnology approaches based on programmable nucleic acid interactions [9, 10], Such DNA computations utilize toehold-mediated strand displacement (TMSD) reactions, a process by which single-stranded DNA molecules can bind to, invade, and displace double stranded DNA ‘gates’ [7], releasing new strands that can participate in downstream interactions. In previous work, we interfaced toehold-mediated strand displacement (TMSD) circuits with allosteric transcription factors-based small molecule biosensors, creating new approaches to multi-input logic evaluation and signal thresholding, and expanding the functionality of cell-free biosensors for example by having them operate with analog-to-digital signal conversion [7], However, attempts at utilizing TMSD- based catalytic amplification circuits such as catalytic hairpin assembly (CHA)

[0011] , failed due to off- target transcription of DNA gates by T7 RNA polymerase (T7 RNAP) [8, 12, 13],

[0280] We recently addressed this limitation through a novel circuit architecture that leverages T7 RNAP off-target transcription to recycle nucleic acid inputs within DNA TMSD circuits called polymerase strand recycling (PSR) [8], PSR is compatible with T7 RNAP in vitro transcription and can detect RNA targets directly as well as enhancing the limit of detection for allosteric transcription factor-based biosensors to detect small molecules [8], PSR circuit designs are comprised of three main components: RNA input, fuel gate and signal gate (FIGS. 17A, 19A-19C). Both the fuel gate and signal gate are designed to be double stranded, but leave 5’ and 3’ unpaired overhangs called ‘toeholds’ that facilitate initial binding and strand invasion of the duplex (FIGS 19A-19C)

[0014] , In a PSR reaction, the circuit is activated by RNA inputs, which can be the input signal directly, or can be generated by upstream transcriptional biosensing mechanisms. RNA inputs are converted to DNA strands via strand invading a nucleic acid duplex called a “fuel gate”, which releases a DNA strand called RecycleD. The released RecycleD strand can in turn can invade a “signal gate”, consisting of a DNA duplex containing fluorophore-labeled strand and a quencher-labeled strand, releasing the quencher and generating fluorescent signal. The system is designed such that the resulting RecycleD:fluorophore-strand complex contains a 3’ toehold, which can be transcribed by T7 RNAP, releasing RecycleD for further rounds of signal generation and recycling (FIGS. 17A, 19A- 19C).

[0281] In previous work, we demonstrated PSR circuits can directly detect three distinct microRNAs (miRs) with high specificity and limits of detection (LoDs) within 5 - 100 nM range [8],In this study, we further explored the design principles for PSR circuits by developing seven distinct PSR circuit architectures to detect additional miR inputs. We analyzed the successful and unsuccessful PSR circuit designs across different RNA sequence inputs and developed design principles for optimizing specificity and sensitivity. We also provide evidence that PSR circuit function can be improved through engineering the T7 RNAP enzyme. Overall we demonstrate a general strategy for engineering PSR circuits that could have a range of applications in cell-free biosensing and DNA / RNA nanotechnology and synthetic biology more broadly.

[0282] Results

[0283] To demonstrate the generalizability of PSR circuits for detecting different RNA input sequences, we chose miRs as model targets. miRs are a class of small, noncoding RNAs that are key regulators of gene expression in eukaryotes, and are important biomarkers of cell-type and health status [15, 16], Most miRs are approximately 22-nucleotide (nt) long but exhibit a wide range of melting temperatures (Tms) due to sequence variation, making them challenging targets for generalizable sensing platforms

[0017] , Here, we chose six distinct miRs (miR-21-5p, miR-20b-5p, miR-16-5p, miR320b, miR-29a-3p, and miR-34a-5p) that are either upregulated or downregulated from physical stressors, cognitive stressors, or both [18-24] as model inputs for PSR circuits (FIG. 17B). These miRs have Tms ranging from 57°C - 70°C and are between 21- 23-nt in length.

[0284] To explore the ability of PSR circuits to detect this range of model input, we first designed modified fuel gate, RecycleD, and signal gate sequences to match the desired miR sequences (FIG. 17A). We first assessed the specificity of the PSR circuit designs by adding 1 pM of synthesized and purified miR to its respective PSR circuit, as well as two other PSR circuit designs that are intended to detect non-target miRs. Fluorescence characterization demonstrated that all seven PSR designs could only be activated by their target miR targets, each generating fluorescent signals that are at least 9.5-fold higher compared to non-target miRs (FIG. 17C).

[0285] We then assessed the sensitivity of PSR designs by performing a titration with miRs to determine the limits of detection (LoDs), defined as the concentration value at which the signal was significantly greater (p < 0.05) than the no input condition. We determined the LoDs to be within the 5 - 100 nM range for PSR to detect RNA targets. Specifically, miR-320b, miR-29a-3p, miR-34a-3p, miR-21-5p, miR-20b-5p targets showed LoDs of 100 nM, and miR-16-5p target showed LoD of 5 nM (FIG. 17C).

[0286] PSR relies on the function of T7 RNAP to perform the strand recycling reaction (FIG. 17A). We therefore reasoned that PSR circuit performance could be improved by varying the T7 RNAP itself. We compared wildtype T7 RNAP performance with two variants, M6 (SEQ ID NO: 48) and Y639F (SEQ ID NO: 49), to detect miR-29a-3p and found the M6 variant improves fluorescent signal while the Y639F variant hinders fluorescent signal generation compared to wildtype (FIG. 20). Overall, these results demonstrated that PSR circuits can be generalized to detect RNA inputs of various sequences and a wide range of Tms.

[0287] Establishing design principles and troubleshooting approaches for engineering PSR circuits

[0288] Next, we developed design principles that could be applied to achieve the expected performance from PSR circuits (FIG. 18A), along with troubleshooting approaches that could be used to improve the signal-to-noise ratio or the LoD if the initial circuit design fails to meet performance metrics (FIGS. 18B-18C).

[0289] We developed design principles for fuel and signal gates that could serve as a starting point to design PSR circuits for new RNA input sequences that are miRs or a ~22-nt region of a longer RNA target. These exemplary and non-limiting design principles include several features: (1) The fuel gate is comprised of two nucleic acid strands, sequester / waste and RecycleD with an overlapping / complementary region of 20 - 22-basepair (bp). (2) The sequester / waste strand is 2’-O-methyl modified and contains the complementary sequence for the RNA input, including a 5’ toehold that is 9 - 10-nt in length, as well as a region partially complementary to RecycleD (FIG. 19A). (3) The signal gate is comprised of a DNA strand with a 3’ fluorophore modification and another DNA strand with a 5’ quencher modification. The gate has a 21 - 23 -bp overlapping / complementary region as well as an 8-nt 5’ toehold on the fluorophore- strand (FIG. 19B). (4) The RecycleD:fluorophore-strand complex contains a 4-nt 3’ toehold on the fluorophorestrand (FIG. 19 A). Since the rate of T7 RNAP off-target transcription activity has been found to be dependent on the 3’ toehold sequence

[0012] , we reused the same 4-nt 3’ sequence for all existing PSR circuit designs.

[0290] If the initial PSR design did not produce the expected performance, we found that the results could likely be improved with design adjustments to the fuel and signal gates. In several cases we found that initial PSR designs showed high fluorescent leak or LoDs above the expected range of 5 - 100 nM. In these cases, we were able to improve the PSR circuit performance to be inthe expected range through adjusting the fuel and signal gate designs (FIGS. 21 A-23). For example, the initial circuit design for miR-16-5p produced high fluorescent signals in the absence of the miR target (FIG. 18B). By extending RecycleD on the 3’ end by 2-nt, thus increasing the fuel gate overlapping region by 2-bp and sub sequentially increasing the signal gate duplex by 2-bp (FIGS. 21A-21B), the signal-to-noise ratio improved to ~10-fold (FIG. 18B) In a previously published PSR circuit to detect miR-642a-5p, we initially demonstrated an LoD of 250 nM, which is above the expected range of 5 - 100 nM (FIG. 18C). We were able to decrease the LoD to 100 nM by decreasing the overlapping regions on the fuel and signal gate by 1-bp and subsequently to 25 nM by decreasing the overlapping regions on fuel and signal gate by an additional 1-bp (FIGS. 18C, 23). Overall these results demonstrate a general approach for designing and optimizing PSR circuits for RNA detection.

[0291] Discussion

[0292] In this study, we expanded the toolbox for building PSR circuits to detect a diverse set of input RNA sequences with greater than 10-fold signal-to-noise ratio and LoD within the range of 5 - 100 nM. We also developed design principles to achieve the expected circuit performance with new target RNA inputs. Even if an initial design fails, the signal-to-noise ratio and LoD can be optimized with adjustments to fuel and signal gates design. In some cases, only the RecycleD or sequester sequence needs to be adjusted to reduce fluorescent signal leak, which is more economic compared to redesigning the entire set of PSR circuit elements (including fluorophore- strand and quencher-strand) (FIGS. 21A-21B). If cost-saving is a priority, only extending RecycleD by 1-nt could be a potential initial troubleshooting step.

[0293] In previous work, we showed that the major strength of PSR circuit is their ability to interface with transcriptional biosensors to optimize the sensitivity of detection of the large number of allosteric transcription factors (aTFs) used for chemical biosensing applications . aTF -based PSR circuit design is similar to the design principles described above but requires designing a DNA template comprised of the T7 RNAP promoter, a 2-bp spacer, an aTF-operator site, and a target RNA input sequence (RecycleR). To adapt PSR circuit for a new aTF, the corresponding aTF- operator site needs to be inserted between the 2-bp spacer and the RecycleR sequence (FIGS. 24 A- 24B). Unless there are downstream sequence constraints, the sequences for RecycleR, fuel and signal gate can be directly adapted from previously published designs. It is interesting to note that the aTF-based PSR circuit fuel and signal gate overlapping regions do not follow the same designrules as purified target RNA detection (FIGS. 24A-24B). We hypothesize that the overlapping regions could be shorter in aTF-based PSR circuits without significant fluorescent signal leak because there is a T7 RNAP promoter site, which slows down T7 RNAP off-target transcription activities

[0013] ,

[0294] Because PSR has a unique configuration for signal amplification, and relies on a T7 RNA polymerase mechanism, promoter-less initiation of transcription

[0025] [7] that is poorly understood, we hypothesized that variants of T7 RNAP might improve circuit performance. To that end, we and others had previously developed a number of T7 RNAP variants with higher thermostabilities and wider substrate specificities

[0026]

[0027] , When tested in the context of the PSR circuitry, we observed different T7 variants could either enhance or hinder PSR reactions, suggesting PSR performance could be further tuned and PSR could have additional applications due to the qualities of the variants (FIG. 20).

[0295] Other nucleic acid-based miR detection methods, such as catalytic hairpin assembly, have demonstrated high sensitivity in the fM ranges. However, PSR stands out as a detection platform due to its simplicity and programmability. Furthermore, the ability to integrate PSR into transcriptional circuits expands its potential for application in advanced circuit designs.

[0296] Overall, we believe that the PSR circuits can serve as a platform technology that can be adapted to detect RNA inputs through PSR gate design, and chemical targets through interfacing with aTF biosensors [8], We anticipate this toolbox for PSR circuit design will serve important roles in cell-free technologies including in biosensing and further expanding molecular computation in cell -free systems.

[0297] Materials and Methods

[0298] DNA gate preparation

[0299] DNA fuel gates and signal gates used in this study were synthesized by Integrated DNA technologies as HPLC or PAGE purified and chemically modified oligos (Supplementary Data). Gates were generated by denaturing complementary strands at 95° C for 5 min and slow cooling (-0.1 °C s ') to room temperature in annealing buffer (50 mM Tris-HCl, pH 8.0, 10 mM MgC12). Fuel gates are annealed with 20% excess sequester strands and signal gates are annealed 20% excess quencher-strands. DNA fuel gates and signal gates were stored at 4°C until use. See Li Supplementary Data l.xlsx for a list of oligo sequences used in this study.

[0300] RNA preparation

[0301] Purified miRs, representing processed microRNA sequences, were synthesized and HPLC purified by Integrated DNA Technologies and rehydrated with nuclease-free water. miR aliquots were stored at -80°C until use. See Li Supplementary Data l.xlsx for a list of miR sequences used in this study.

[0302] PSR Reactions

[0303] PSR reactions were set up by adding the following components listed at their final concentration: IVT buffer (40 mM Tris-HCl pH 8, 8 mM MgC12, 10 mM dithiothreitol, 20 mMNaCl and 2 mM spermidine), 11.4 mM NTPs pH 7.5, 1.5 pM fuel gate, 2.5 pM signal gate, and MilliQ ultrapure H2O to a total volume of 20 pL. Immediately before plate reader measurements,2 ng of wildtype T7 RNAP and, optionally, purified miRs at the indicated concentration were added to the reaction. T7 RNAP variants were added at a final concentration of 0.2 pM. Reactions were then characterized on a plate reader as described in ‘Plate reader quantification and micromolar equivalent fluorescein standardization’.

[0304] Hill equation fits

[0305] Where indicated, data were fit to the Hill equation with the following functional form:

[0306] Where [ligand] denotes ligand concentration, c represents the response with no ligand, a represents the maximum response, and n describes the cooperativity. Fitting was performed on individual replicate datasets using DataGraph 5.2 by starting with a = 1.5, EC50 = 1, c = 1, n = l,then optimized for exact parameters with DataGraph 5.2. Curves were generated from fitting the average of the replicates for plotting.

[0307] T7 RNAP variants preparation

[0308] Plasmids containing T7 RNAP gene variants with an N-terminal his-tag were transformed into NEB BL21. Colonies were inoculated for overnight culture. Overnight cultures were subcultured the next day 1 : 100 in superior broth at 37°C. Expression was induced with IPTG at OD .6 and cultured overnight at 18°C. Cells were pelleted through centrifugation at 4,000 g for 10 minutes, resuspended in 30 mL of resuspension buffer (50 mM phosphate buffer [pH 7.5], 300mM NaCl, 20 mM imidazole, 0.1% Igepal CO-630, 5 mM MgSO4), and lysed through sonication. The lysate was centrifuged at 35,000 g for 30 minutes. A gravity column was assembled with 1 mL of Ni-NTA resin and equilibrated with 10 mL equilibration buffer (50 mM phosphate buffer [pH 7.5], 300 mM NaCl, 20 mM imidazole). The supernatant was applied to a gravity column containing Ni-NTA resin, washed with 20 mL equilibration buffer, then washed with 5 mL wash buffer (50 mM phosphate buffer [pH 7.5], 300 mM NaCl, 50 mM imidazole), and eluted with 3 mL elution buffer (50 mM phosphate buffer [pH 7.5], 300 mM NaCl, 250 mM imidazole). The eluate was dialyzed twice in 2 L Ni-NTA buffer (40 mM Tris-HCl [pH 7.5], 100 mM NaCl, 1 mM DTT, 0.1% Igepal CO-630), once for 4 hours, then overnight. A final dialysis was performed with 1 L buffer (50% Glycerol, 50 mM Tris-HCl [pH 8.0], 50 mM KC1, 0.1% Tween-20, 0.1% Igepal CO-630). The enzyme concentration was measured using the Bradford assay and diluted using the final dialysis buffer. Protein samples were stored at -20°C until use.

[0309] Plate reader quantification and micromolar equivalent fluorescein standardization

[0310] A National Institute of Standards and Technology traceable standard (Invitrogen, catalog no. F36915) was used to convert arbitrary fluorescence measurements to micromolar equivalent fluorescein (MEF). Serial dilutions from a 50 pM stock were prepared in 100 mM sodium borate buffer at pH 9.5, including a 100 mM sodium borate buffer blank (total of 12 samples). For each concentration, three replicates of samples were created in batches of three, and fluorescence values were read at an excitation wavelength of 490 nm and emission wavelength of 525 nm for 6- FAM (fluorescein)-activated fluorescence (Synergy Hl, BioTek Gen5 v.2.04). Fluorescence values for a fluorescein concentration in which a single replicate saturated the plate reader were excluded from the analysis. The remaining replicates (three per sample) were then averaged at each fluorescein concentration, and the average fluorescence value of the blank was subtracted from all values. Linear regression was then performed for concentrations within the linear range of fluorescence (0- 3.125 pM fluorescein) between the measured fluorescence values in arbitrary units and the concentration of fluorescein to identify the conversion factor. For each plate reader, excitation, emission and gain setting, we found a linear conversion factor (setting the y intercept to 0) that was used to correlate arbitrary fluorescence values to MEF (FIG. 25).

[0311] For reaction characterization, 19 pL of reactions were loaded onto a 384-well optically clear, flat- bottom plate using a multichannel pipette, covered with a plate seal and measured on a plate reader (Synergy Hl, BioTek Gen5 v.2.04). Kinetic analysis of 6-FAM (fluorescein)-activatedfluorescence was performed by reading the plate at 1-min intervals with excitation and emission wavelengths of 490 and 525 nm for 2 hrs at 37 °C. Arbitrary fluorescence values were then converted to MEF by dividing by the appropriate calibration conversion factor.

[0312] Statistics and reproducibility

[0313] The number of replicates and types of replicates performed are described in the legend of each figure. Individual data points are shown, and where relevant, the average ± s.d. is shown; this information is provided in each figure legend. The type of statistical analysis performed in FIGS. 17A-17C, 18A-18D, 20, 21A-21B, 22is described in the legend to each figure. Exact p-values along with degrees from the statistical analysis can be found in Source Data.

[0314] References for Example 2

[0315] 1. Wen, K.Y., et al., A Cell-Free Biosensor for Detecting Quorum Sensing Molecules in P. aeruginosa-infected Respiratory Samples. ACS Synth Biol, 2017. 6(12): p. 2293- 2301.

[0316] 2. Thavarajah, W ., et al., Point-of-Use Detection of Environmental Fluoride via aCell- Free Riboswitch-Based Biosensor. ACS Synth Biol, 2020. 9(1): p. 10-18.

[0317] 3 Silverman, A.D., et al., Design and Optimization of a Cell-Free Atrazine Biosensor.ACS Synth Biol, 2020. 9(3): p. 671-677.

[0318] 4. Pardee, K., et al., Rapid, Low-Cost Detection of Zika Virus Using ProgrammableBiomolecular Components. Cell, 2016. 165(5): p. 1255-1266.

[0319] 5. McSweeney, M.A., et al., A modular cell-free protein biosensor platform using splitT7 RNA polymerase. bioRxiv, 2024.

[0320] 6. Jung, J.K., et al ., Cell-free biosensors for rapid detection of water contaminants. NatBiotechnol, 2020. 38(12): p. 1451-1459.

[0321] 7. Jung, J.K., et al., Programming cell-free biosensors with DNA strand displacement circuits. Nat Chem Biol, 2022. 18(4): p. 385-393.

[0322] 8. Li, Y., et al., A cell-free biosensor signal amplification circuit with polymerase strand recycling. Nature Chemical Biology, 2025.

[0323] 9. Schaffter, S.W. and R. Schulman, Building in vitro transcriptional regulatory networks by successively integrating multiple functional circuit modules. Nature Chemistry, 2019. 11(9): p. 829-838.

[0324] 10. Schaffter, S.W., et al., Standardized excitable elements for scalable engineering of far-from-equilibrium chemical networks. Nature Chemistry, 2022. 14(11): p. 1224- 1232.

[0325] 11 Li, B., A.D. Ellington, and X. Chen, Rational, modular adaptation of enzyme-freeDNA circuits to multiple detection methods. Nucleic Acids Res, 2011. 39(16): p. el 10.

[0326] 12. Schaffter, S.W., et al., Strategies to Reduce Promoter-Independent Transcription of DNA Nanostructures and Strand Displacement Complexes. ACS Synthetic Biology, 2024.

[0327] 13. Schaffter, S.W., et al., T7 RNA polymerase non-specifically transcribes and induces disassembly of DNA nanostructures. Nucleic Acids Res, 2018. 46(10): p. 5332-5343.

[0328] 14. Hong, F. and P. Sulc, An emergent understanding of strand displacement in RNA biology. J Struct Biol, 2019. 207(3): p. 241-249.

[0329] 15. Ardekani, A.M. and M.M. Naeini, The Role of MicroRNAs in Human Diseases.Avicenna J Med Biotechnol, 2010. 2(4): p. 161-79.

[0330] 16. O'Brien, J., et al., Overview of MicroRNA Biogenesis, Mechanisms of Actions, and Circulation. Front Endocrinol (Lausanne), 2018. 9: p. 402.

[0331] 17. Jet, T., et al., Advances in multiplexed techniques for the detection and quantification of microRNAs. Chemical Society Reviews, 2021. 50(6): p. 4141-4161.

[0332] 18. Wiegand, C., et al., Stress-associated changes in salivary microRNAs can be detected in response to the Trier Social Stress Test: An exploratory study. Sci Rep, 2018. 8(1): p. 7112.

[0333] 19. Cohn, W., et al., Integrated Multiomics Analysis of Salivary Exosomes to IdentifyBiomarkers Associated with Changes in Mood States and Fatigue. Int J Mol Sci, 2022. 23(9).

[0334] 20. Hicks, S.D., et al., Refinement of saliva microRNA biomarkers for sports-related concussion. J Sport Health Sci, 2023. 12(3): p. 369-378.

[0335] 21. de Gonzalo-Calvo, D., et al., Circulating microRNAs as emerging cardiac biomarkers responsive to acute exercise. Int J Cardiol, 2018. 264: p. 130-136.

[0336] 22. Fernandez- Sanjurjo, M., et al., Exercise dose aUects the circulating microRNA profile in response to acute endurance exercise in male amateur runners. Scand J Med Sci Sports, 2020. 30(10): p. 1896-1907.

[0337] 23. Backes, C., et al., Blood born miRNAs signatures that can serve as disease specific biomarkers are not significantly aUected by overall fitness and exercise. PLoS One, 2014. 9(7): p. el02183.

[0338] 24. Baggish, A.L., et al., Dynamic regulation of circulating microRNA during acute exhaustive exercise and sustained aerobic exercise training. J Physiol, 2011. 589(Pt 16): p. 3983-94.

[0339] 25. Krupp, G., Unusual promoter-independent transcription reactions with bacteriophage RNA polymerases. Nucleic Acids Res, 1989. 17(8): p. 3023-36.

[0340] 26. Meyer, A.J., et al., Transcription yield of fully 2'-modified RNA can be increased by the addition of thermostabilizing mutations to T7 RNA polymerase mutants. Nucleic Acids Res, 2015. 43(15): p. 7480-8.

[0341] 27. Kimoto, M., et al., Genetic alphabet expansion transcription generating functionalRNA molecules containing a five-letter alphabet including modified unnatural and natural base nucleotides by thermostable T7 RNA polymerase variants. Chem Commun (Camb), 2017. 53(91): p. 12309-12312.

[0342] In the foregoing description, it will be readily apparent to one skilled in the art that varying substitutions and modifications may be made to the invention disclosed herein without departing from the scope and spirit of the invention. The invention illustratively described herein suitably may be practiced in the absence of any element or elements, limitation or limitations which is not specifically disclosed herein. The terms and expressions which have been employed are used as terms of description and not of limitation, and there is no intention that in the use of such terms and expressions of excluding any equivalents of the features shown and described or portions thereof, but it is recognized that various modifications are possible within the scope of the invention. Thus, it should be understood that although the present invention has been illustrated by specific embodiments and optional features, modification and / or variation of the concepts herein disclosed may be resorted to by those skilled in the art, and that such modifications and variations are considered to be within the scope of this invention.

[0343] Citations to a number of patent and non-patent references may be made herein. The cited references are incorporated by reference herein in their entireties. In the event that there is an inconsistency between a definition of a term in the specification as compared to a definition of the term in a cited reference, the term should be interpreted based on the definition in the specification.

Claims

CLAIMSWe claim:

1. A composition, system, or kit for detecting a target RNA molecule comprising as components:(a) an RNA polymerase;(b) a double-stranded DNA (dsDNA) signal gate molecule; and(c) a fuel gate molecule comprising a waste strand and a RecycleD strand, wherein the waste strand and the RecycleD strand are at least partly complementary to one another and form a double-stranded polynucleotide; wherein, when in the presence of the target RNA molecule, the target RNA molecule binds the fuel gate molecule thereby displacing the RecycleD strand generating a free single-stranded polynucleotide that displaces a DNA strand of the signal gate molecule to produce a detectable signal and a new hybrid signal / fuel gate, and wherein the RNA polymerase transcribes the hybrid signal / fuel gate to release the RecycleD strand which can then displace an additional dsDNA signal gate molecule, thus creating a positive feedback loop of signal amplification.

2. The composition, system, or kit of claim 1, wherein the waste strand is at least partly complementary to the target RNA molecule.

3. The composition, system, or kit of claim 2, wherein the dsDNA signal gate molecule is labeled with one or more functional chemical groups.

4. The composition, system, or kit of claim 3, wherein the one or more functional chemical groups comprise a fluorophore, a quencher, biotin, or methylene blue.

5. The composition, system, or kit of claim 4, wherein the dsDNA signal gate molecule is a fluorescently labeled double-stranded DNA molecule comprising a fluorophore-conjugated strand having a fluorophore conjugated at its 3 ’-end and a quencher stand having a quencher conjugated at its 5’ end that quenches the fluorophore in the fluorescently labeled doublestranded DNA molecule.

6. The composition, system, or kit, of claim 5, wherein, when in the presence of the target RNA molecule, the target RNA molecule binds the fuel gate molecule thereby displacing the RecycleD strand generating a free single-stranded polynucleotide molecule that displaces the quencher strand from the dsDNA signal gate to produce a detectable signal.

7. The composition, system, or kit of claim 6, wherein, when the RecycleD strand displaces the quencher strand of the fluorescently labeled double-stranded DNA molecule, the fluorophore of the fluorophore-conjugated strand is dequenched generating the detectable signal and the RecycleD strand hybridizes to the fluorophore-conjugated strand to generate the hybrid signal / fuel gate comprising a 3’ toehold on the fluorophore-conjugated strand and the RNA polymerase transcribes the fluorophore-conjugated strand and displaces the RecycleD strand and generates a fluorescent DNA / RNA hybrid, and wherein the released RecycleD strand can displace an additional signal gate generating a positive feedback loop of signal amplification.

8. The composition, system, or kit of claim 7, wherein the fluorophore-conjugated strand is longer than the quencher strand.

9. The composition, system, or kit of claim 8, wherein the fluorophore-conjugated strand is longer than the quencher strand by about 2 nucleotides to about 12 nucleotides, or about 2 to about 10 nucleotides.

10. The composition, system, or kit of any one of claims 5-9, wherein an RNA produced via transcription of the fluorophore-conjugated strand comprises a sequence that is complementary to the full length of the fluorophore-conjugated strand.

11. The composition, system, or kit of claim or any one of claims 5-10, wherein the fluorophore comprises fluorescein and / or 6-Carboxyfluorescein (6-FAM).

12. The composition, system, or kit of any one of claims 1-11, wherein the waste strand or the quencher strand comprises one or more non-natural modifications that prevent the strand from being utilized as a template for transcription (e. ., 2'-O-m ethylation).

13. The composition, system, or kit of any one of claims 1-12, wherein the signal gate molecule comprises a dual-stranded region that is about 15 to about 25 nucleotides in length, or about 18 to about 22 nucleotides in length.

14. The composition, system, or kit of any one of claims 1-13, wherein the fuel gate molecule comprises a dual-stranded region that is about 15 to about 25 nucleotides in length, or about 18 to about 22 nucleotides in length.

15. The composition, system, or kit of any one of claims 1-14, wherein the target RNA molecule is a miRNA or a virus.

16. The composition, system, or kit of any one of claims 1-15, wherein the RNA polymerase is selected from T7 RNA polymerase, T3 RNA polymerase, SP6 RNA polymerase, and Syn5 RNA polymerase or the RNA polymerase is an engineered polymerase.

17. The composition, system, or kit of any one of claims 1-16, further comprising one or more components for preparing a reaction mixture for RNA transcription.

18. The composition, system, or kit of any one of claims 1-17, wherein the double-stranded polynucleotide of the fuel gate molecule comprises a dsDNA molecule, an RNA-DNA hybrid, or an RNA-RNA duplex.

19. The composition, system, or kit of any one of claims 1-17, wherein at least one of the strands of the double-stranded polynucleotide of the fuel gate molecule comprises at least two of RNA, modified RNA, and DNA.

20. The composition, system, or kit of any one of claims 1-19, wherein the RecycleD strand is a DNA molecule.

21. The composition, system, or kit of any one of claims 1-20, wherein the waste strand comprises at least two of RNA, modified RNA, and DNA.

22. The composition, system, or kit of claim 21, wherein the modified RNA comprises methylated RNA.

23. A method for detecting an RNA molecule in a sample, the method comprising contacting the sample with the composition, system, or kit of any one of claims 1-22.

24. The method of claim 23, further comprising detecting a signal.

25. The method of claim 23 or 24, wherein the RNA molecule can be detected in the sample at a concentration of at least about 0.1 nanomolar (nm), at least about 0.5 nm, or at least about 1 nm.

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