Automated design of protein-binding riboswitches for sensing human biomarkers in a cell-free expression system

Abstract

The present invention relates to a protein-binding riboswitch comprising a pre-aptamer nucleotide sequence, an aptamer nucleotide sequence encoding an RNA structure capable of binding a target protein, a post-aptamer nucleotide sequence; and a protein-coding nucleotide sequence encoding a reporter, where binding of the target protein by the aptamer nucleotide sequence modulates expression of the reporter. Also disclosed are tests strips comprising such protein-binding riboswitches and methods of use thereof.

Description

AUTOMATED DESIGN OF PROTEIN-BINDING RIBOSWITCHES FOR SENSINGHUMAN BIOMARKERS IN A CELL-FREE EXPRESSION SYSTEM [0001| This application claims the benefit of U.S. Provisional Patent Application SerialNo. 63 / 614,023, filed December 22, 2023, which is hereby incorporated by reference in its entirety.

[0002] This invention was made with government support under Grant No. F A 9550-14- 1-0089 awarded by the United States Air Force / AFOSR, under Contract No. HR0011-17-C-0095 awarded by the Defense Advanced Research Projects Agency (DARPA) and under Hatch Act Project No, PEN04671 awarded by the United States Department of Agriculture. The government has certain rights in the invention.

[0003] This application contains a computer readable Sequence Listing which has been submitted in XM L file format with this application, the entire content of which is incorporated by reference herein in its entirety. The Sequence Listing XML fife submitted with this application is entitled “14841 1 .003202. xml”, was created on December 19, 2024, and is 81 ,239 bytes in size.FIELD

[0004] The present disclosure relates to protein-binding riboswitches as well as compositions and methods of use thereof.BACKGROUND

[0005] Synthetic biologists have created a wide variety of sensor systems to detect small molecules and nucleic acids (Tsao et al, “Autonomous Induction of Recombinant Proteins byMinimally Rewiring Nnative Quorum Sensing Regulon of E. coli,” Afetab. Eng. 12:291 -297 (2010); Branco et al,, “Highly Sensitive, Highly Specific Whole-Cell Bioreporters for the Defection of Chromate in Environmental Samples,” PLoS One 8:e54005 (2013); King et al., “Rapid, Sensitive Bioluminescent Reporter Technology for Naphthalene Exposure and Biodegradation,” Science 249: 778-781 (1990); Rogers et ah, “Synthetic Biosensors for PreciseGene Control and Real-Time Monitoring of Metabolites,” Nucleic Acids Res. 43: 7648-7660 (2015); Green et at, “Toehold Switches: De-Novo-Designed Regulators of Gene Expression,” Cell 159:925-939 (2014); Chappell et ah, “Computational Design of Small TranscriptionActivating RNAs for Versatile and Dynamic Gene Regulation,” Nat Commwn. 8: 1051 (2017); Davidson et al., “Development of a 2,4-Dinitrotoluene-Responsive Synthetic Riboswitch in E. coli cells,” ,4CS Chem. Biol. 8:234-241 (2013); Joe et al., “Pigment-Based Whole-Cell Biosensor System for Cadmium Detection using Genetically engineered Deinococcus Radiodurans,” Bioproeess Biosyst. Eng. 35:265-272 (2012); Kylilis et al., “Whole-Cell Biosensor with Tunable Limit of Detection Enables Low-Cost Agglutination Assays for Medical Diagnostic Applications,” ACS Sens. 4:370-378 (2019); Riangrungroj et al., “A Label-Free Optical Whole- Cell Escherichia coli Biosensor for the Detection of Pyrethroid Insecticide Exposure,” Sei. / ?tp, 9: 12466 (2019); Shaw et al., “Engineering a Model Cell for Rational Tuning of GPCR Signaling,” Cell 177:782-796 e727 (2019); Beltran et al., “Rapid Biosensor Development using Plant Hormone Receptors as Reprogrammable Scaffolds,” Nature Biotechnology. 40: 1855-1861 (2022); and Wu et al ., “Automated Design of Diverse Stand-Alone Riboswitches,”Synthetic Biology 8: 1838- 1846 (2019)). Several of these sensors have been developed for usage in cell-free expression systems, where there is no barrier between the expression machinery and exogenously added bulky macromolecules that would otherwise be unable to pass through a cellular membrane (Jung et al., “Cell-Free Biosensors for Rapid Detection of Water Contaminants,” Nat Biotechnol. 38(12): 1451-1459 (2020); Pardee et al., “Paper-Based Synthetic Gene Networks,” Cell 159(4): 940-954 (2014); and Voyvodic et al., “Plug-and-Play Metabolic Transducers Expand the Chemical Detection Space of Cell-Free Biosensors, ’Wat Commun. 10(1): 1697 (2019)). Cell-free sensors are particularly useful as low-cost, portable diagnostic and field assays as they genetically encode their own detection machinery and do not require a cold chain during storage and distribution (Jung et al., “Cell-Free Biosensors for Rapid Detection of Water Contaminants,” Nat. Biotechnol. 38( 12): 1451- I459 (2020); Pardee et al., “Paper-Based Synthetic Gene Networks,” Cell 159(4):940-954 (2014); Thavarajah et al., “Point-of-Use Detection of Environmental Fluoride via a Cell-Free Riboswitch-Based Biosensor,” ACS Synth, Biol. 9(1): 10- 18 (2020); Levine et al., “Escherichia coli-Based Cell-Free Protein Synthesis: Protocols for a Robust, Flexible, and Accessible Platform Technology,” J. Cis. Exp. 25:144 (2019); Pardee, K., “Perspective: Solidifying the Impac t of Cell-Free Synthetic Biology through Lyophilization,” Biochem. Eng. J. 15: 138:91-97 (2018); Silverman et al., “Deconstructing Cell- Free Extract Preparation for in Vitro Activation of Transcriptional Genetic Circuitry,” .4 CS Synth. Biol. 8(2):403~414 (2019); Chushak et al., “Characterization of Synthetic Riboswitch in Cell-Free Protein Expression Systems,” RNA Biology 18(11 ): 1727- 1738 (2021 ); Amalfitano et al., “A Glucose Meter Interface for Point-of-Care Gene Circuit-Based Diagnostics,” Nat.Cotnmun. I 2( 1 ):724 (2021)). However, even though protein detection is a cornerstone of both modern medical diagnostics and biological research (Leca-Bouvier and Blum, “Biosensors for Protein Detection: A Review,” Analytical Letters 38: 1491-1517 (2005)), there are only a few cell-free sensors that utilize gene regulation to detect proteins of interest (Iyer and Doktycz, ‘Thrombin-Mediated Transcriptional Regulation using DNA Aptamers in DNA-Based Cell-Free Protein Synthesis,” .ICS Synth. Biol. 3(6):340-346 (2014); Byun et al., “Cascading Amplification of Immunoassay Signal by Cell-Free Expression of Firefly Luciferase from Detection Antibody- Conjugated DN A in an Escherichia coli Extract,” A CS Sens. 4(1 ):93-99 (2019); and Katz et al., “Synthetic 5' UTRs Can Either Up- or Downregulate Expression upon RNA-Binding Protein Binding,” CW / SyxL 9(1 ):93~106 el 08 (2019)).

[0006] C Currently, measuring protein titers is widely carried out using immunoassays (e.g., ELISAs) or LC-MS analytics, which can offer high sensitivity and specificity across a diverse range of protein targets (Lequin, RM, “Enzyme Immunoassay (EIA) / Enzyme-Linked Immunosorbent Assay (ELISA),” Clin. Chem. 51( I 2):2415-2418 (2005) and Jannetto and Fitzgerald, '’Effective Use of Mass Spectrometry in the Clinical Laboratory,” Clin. Chem.62(1) :92-98 (2016)), More recently, another class of nucleic acid-based recognition elements, called aptamers, have been harnessed for protein detection and diagnostics (Cox and Ellington,” “Automated Selection of Anti-Protein Aptamers,” Bioorg. Med. Chem. 9( 10):2525-2531 (2001 ) and Dunn et al., “Analysis of Aptamer Discovery and Technology,” Aai. 7?ev. Chem. 1 -.0076 (2017)). Protein-binding aptamers are now available for specific binding to a wide variety of targets, including human proteins (Gold et al., “Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery,” PLoS One 5(12):e15004 (2010); Cox et al., “Automated Selection of Aptamers Against Protein Targets Translated in Vitro: From Gene to Aptamer,” M / ritefc Acids Res. 30(20):el()8 (2002); Chen et al., “Inhibition of Heregulin Signaling by an Aptamer that Preferentially Binds to the Oligomeric form of Human Epidermal Growth Factor Receptor-3,” AVJ5 100(16):9226~9231 (2003); and Wang et al., “Aptamer-Based Fluorescent Biosensors,” Cure. Med. Chem. 18(27):4175-4I 84 (2011)), HIV viral proteins (Kensch et al., “HIV-1 Reverse Transcriptase-Pseudoknot RNA Aptamer Interaction Has a Binding Affinity in the Low Picomolar Range Coupled with High Specificity,” Ji Biol Chem. 275(24): I 8271-18278 (2000) and Matsugami et al., “Structural Basis of the Highly Efficient Trapping of the HIV Tat Protein by an RNA Aptamer,” Structure 11 (5 ):533-545 (2003)), and bacterial toxins (Frohnmeyer et al., “Highly Affine and Selective Aptamers Against Cholera Toxin as Capture Elements in Magnetic Bead-Based Sandwich EL A A,” J. Biotechnol. 269:35-42 (2018)).However, these assays require expensive detection reagents (e.g,, purified antibodies or synthesized aptamers), expensive & bulky instruments, sample cold chain storage & distribution, and trained personnel. Instead, it is possible to utilize RNA-based aptamers to develop low-cost, genetically encoded riboswitch biosensors that carry out in situ protein detection within cell-free expression systems (TX-TL) (Garenne et al., “Cell-Free Gene Expression,” Nat. Rev. Methods Primers 1 : 1-18 (2021 )). Past efforts to engineer such riboswitch sensors have largely relied on trial-and-error experimentation, for example, constructing and characterizing large random libraries to identify riboswitch variants that work best.[0007| T he present invention is directed to overcoming these and other deficiencies in the art.SUMMARY[00081 A first aspect of the disclosure is directed to a protein-binding riboswitch comprising a pre-aplamer nucleotide sequence, an aptamer nucleotide sequence encoding an RNA structure capable of binding a target protein, a post-aptamer nucleotide sequence; and a protein-coding nucleotide sequence encoding a reporter, where binding of the target protein by the aptamer nucleotide sequence modulates expression of the reporter.

[0009] Another aspect of the disclosure is directed to a test strip comprising a sample collection zone configured to receive a biological sample, where the sample collection zone comprises: (i) a nucleic acid molecule encoding a protein -binding riboswitch according to the present disclosure and (ii) a cell-free transcription, translation system.

[0010] Another aspect of the present disclosure is directed to a method of detecting a target protein in a biological sample, where the method involves providing a test strip according to the present disclosure; placing a biological sample in the sample collection zone of the test strip, where said target protein, if present in the biological sample, will bind to the proteinbinding riboswitch to modulate the expression level of the reporter protein; detecting the reporter protein; and determining, based on said detecting, the presence or absence of the target protein in the biological sample.J9011 ] Another aspect of the present disclosure is directed to a method of detecting a target protein in a biological sample, where the method involves providing a test strip according to the present disclosure, where the test strip is operably linked to an electrode and a current comparator and where the current comparator is operably linked to a reference electrode thatsupplies a reference current; placing a biological sample in the sample collection zone of the test strip, where said target protein, if present in the biological sample, will bind to the proteinbinding riboswitch to modulate the expression level of the enzyme; passing a current through the counter electrode, sample, and working electrode; detecting the current produced by an electrochemical reaction between the enzyme and substrate; and quantifying, based on said detecting, the concentration of the target protein in the biological sample.10012] In the Examples of the present disclosure, biophysical modeling and computational design was applied to engineer protein-detecting riboswitches that directly regulate the expression of a desired output protein within the TX-TL cell-free expression system, by utilizing a Riboswitch Calculator algorithm to automatically convert RNA aptamers into designed riboswitch sequences (Borujeni et al., “Automated Physics-Based Design of Synthetic Riboswitches from Diverse RN A aptamers,” Nucleic Acids Res. 44(1): 1-13 ( 2016), which is hereby incorporated by reference in its entirety). Initially, riboswitches were engineered to detect the phage MS2 coat protein as a proof-of-principle, followed by engineering riboswitches to detect human monomeric C-reactive protein (mCRP) and interleukin-32 gamma (IL-32y) as examples of medically relevant biomarkers. The best riboswitch sensors regulated reporter expression levels by 13.8, 15.9, and 2,5-fokl when sensing the MS2, mCRP, and IL-32y proteins, respectively, at biomarker concentrations of 1.25 pM mCRP and 0.78 pM II,-32y. It was demonstrated that these riboswitches controlled gene expression levels via two distinct mechanisms: (i) protein-induced conformational changes to RNA structure, which modifies the ribosome’s ability to initiate translation; and (ii) protein-dependent steric repression, which blocks the ribosome from binding to the 5’ un translated region. The accuracy of the Riboswitch Calculator model predictions was critically tested and it was found that improving the specification of the protein-aptamer interaction led to higher model accuracy. Overall, this automated design approach can be applied to convert any protein-binding RNA aptamer into a protein-detecting, cell-free biosensor with potential applications as portable, low-cost diagnostics.10013] Cell -free genetically encoded biosensors have been developed to detect small molecules and nucleic acids, but they have yet to be reliably engineered to detect proteins. The results presented in the Examples of the present disclosure demonstrate the development of an automated platform to convert protein-binding RN A aptamers into riboswitch sensors that operate within low-cost cell- free assays. The platform was demonstrated by engineering 35 protein-sensing riboswitches for human monomeric C-reactive protein, human inter1eukin-32v,and phage MS2 coat protein. The riboswitch sensors regulate output expression levels by up to 16- fold with input protein concentrations within the human serum range. Two distinct mechanisms governing riboswitch-mediated regulation of translation rates were identified and computational analysis was leveraged to refine the protein-binding aptamer regions, improving design accuracy. Overall, the Examples presented herein expand the cell-free sensor toolbox and demonstrate how computational design is used to develop novel protein-sensing riboswitches with future applications as low-cost medical diagnostics.[0()14| The Examples of the present disclosure demonstrate the application of biophysical modeling and computational design to engineer riboswitch sensors to directly couple protein binding to gene regulation, thereby creating a sense-and-respond capability, without trial- and-error experimentation.BRIEF DESCRIPTION OF THE DRAWINGS

[0015] FIGS. 1 A-1C show the design of protein-sensing riboswitches and cell-free riboswitch characterization. FIG. 1A is a schematic showing a medel of translation-regulating riboswithces which takes as inputs the sequence, structure, and binding free energy of a proteinbinding RN A aptamer (5’-ACAUGAGGAUCACCCAUGU-3’ (SEQ ID NO:1)). The model designs candidate riboswitch sequences that maximize activation or repression of translation initiation in response to changing protein concentrations. FIG. IB is a schematic showing how a riboswitch sensor is tested in a cell -free expression system (TX-TL), adding either protein expression plasmid or purified protein. FIG. 1C demonstrates how riboswitch sensor function is characterized by measuring reporter protein expression levels in response to changing protein ligand concentrations, alongside the same measurements on a no-aptamer control. The riboswitch activation or repression ratio is determined by comparing reporter expression levels, including the no-aptamer control measurements to exclude non-specific interactions. Example cell-free assay measurements include a MS2-sensing riboswitch without added MS2 protein MS2”, light blue); a MS2-sensing riboswitch with added MS2 expression plasmid (“+MS2”, dark blue); the no-aptamer control without added MS2 protein (“-MS2”, light red); and the noaptamer control with added MS2 expression plasmid (“+MS2”, dark red). Lines are the mean mRFPl fluorescence levels at each timepoint. Shaded regions are the 95% confidence interval at each timepoint (N = 6 biological replicates).

[0016] FIGS. 2A-2E demonstrate the design and function of protein-sensing riboswitches. FIG. 2 A shows riboswitch sequence designs for detecting the MS2 (5 ’~ACAUGAGGAUCACCCAUGU-3' (SEQ ID NO: 1 ), mCRP (5’-GCCUGUAAGGUGGUCGGUGU GGCGAGUGUGUUAGGAGAGAOGGC-3’ (SEQ ID NO: 2), and 1L32V (5’~GGGUUCACUGCAGACU UGACGAAGCUUCCGGAGAG?AGGGUCA?AGUUGUGCGGGAGUGUGUUGUGGAAUGGAUCCACAU COACGAAUUC-3’ (SEQ ID NO: 3)) protein ligands. FIG. 2B is a graph showing mFRP.1 fluorescence of MS2 ON switches, induced with 8 nM MS2 CDS. FIG. 2C is a graph showing the characterization of MS2 OFF switches, induced with 16 nM MS2 CDS. FIG. 2D is a graph showing the characterization of mCRP OFF switches, induced with 1.25 mM of mCRP. FIG. 2E is a graph showing mRFPl fluorsecene mediated by IL32y OFF' switches, induced with 780 nM IL32y. Gray bars are the mean activation or repression ratios for designed riboswitches. Open circles are mean mRFP l fluorescence levels in the OFF state. Closed circles are mean mRFP l fluorescence levels in the ON state. Error bars are the 95% confidence intervals (N ~ 6 biological replicates for MS2 ON switches; N ~ 8 biological replicates for mCRP and IL32y OFF switches).

[0017] FIGS. 3A-3B show the sequence, structure, and interactions controlling riboswitch function. The model-predicted mRNA structures and ribosome-mRN A binding free energies for the MS2 ON switch (M2 riboswitch; FIG. 3 A) and the MS2 OFF switch (M7o riboswitch; FIG. 3B) across its four most relevant states. State 1 shows the initial mRNA structure and its Gibbs free energy of folding (OGiuiti»0 when the MS2 coat protein is not bound. State 2 shows the change in mRNA structure and the final Gibbs free energy (DGtwf) when the ribosome binds to the mRNA in State 1 . The free energy model for calculating DChtnat Includes hybridization between the mRNA and ribosomal RNA (DGrf!RNw-rRNA), base pairing between the tRNA and start codon (DGsmrt), and energetic penalties for non -optimal spacing (DGspadrig) and an inaccessible standby site (DGstandSy). State 3 shows how the mRNA structure changes when the MS2 coat protein binds to its cognate RNA aptamer with binding free energy DGiigmid, which results in a change in mRNA folding free energy (DGimtiat)- State 4 shows the change in mRNA structure and final Gibbs free energy (DG^O when the ribosome binds to the mRNA in State 3. The translation initiation rates arc predicted based on the difference in initial and final Gibbs free energies (DGt(<w;) according to Boltzmann’s relationship. FIG. 3 A shows MS2 ON switch nucleotide sequences identified according to their interactions, including the RNA aptamer domain (5’-ACA.UGAGGAUCACCCAUGU-3’; SEQ ID NO: 1 ; bold), which corresponds to nucleotides 20 to 38 of SEQ ID NO: 4 (S’- UCUAGACAAGUAAA GAG AC AC A i J GAG Cl A U C AC C G AUGUCUGAAGUAAGAUAAGGAGGGUGAGGAUGGCGAGCUCUGAAGACGUUAUCAAAGAGUUCAU GCGUUUCAAAGUUCGUAUGGAAGGUUCCGUUAA-3’); the last 9 nucleotides of the 16Sribosomal RNA (5’-ACCUCCUUA~3’, shown in bold text); the Shine-Dalgamo sequence (5’~ UAAGGAG-3’), which corresponds io nucleotides 50 to 56 of SEQ ID NO: 4; the start codon (5’-AUG-3’; shown in bold italic), which corresponds to nucleotides 64 to 66; and the standby site (5’-UCUAGACAAGUAAAG-3’ (SEQ ID NO: 5); in outlined text), corresponding to nucleotides 1 to 15 of SEQ ID NO: 4. The hatched bar is the ribosomal footprint for initiation (5’-UAAGGAGGGGGAGGAUGGCGAGCUCUGAA-3’. which corresponds to nucleotides 50 to 78 of SEQ ID NO: 4. FIG. 3B shows MS2 OFF switch nucleotide sequences identified according to their interactions, including the RNA aptamer domain (5’-ACAUGAGGAUCACCCAUGU-3’; SEQ ID NO: 1 ; bold), which corresponds to nucleotides 34 to 52 of SEQ ID NO: 7 (5’-UCUAGACAG CCCUCAUGUACGCUCCGAUGAGUAACAUGAGGAUCACCCAUGUGGGGCAUGAGGAUGGUAUCAU GGCGAGCUCUGAAGACGUUAUCAAAGAGUUCAUGCGUUUCAAAGUUCGUAUGGAAGGUUCCGUUAA-3’); the last 9 nucleotides of the 16S ribosomal RNA (5’-ACCUCCUUA-3’, shown in bold text); the Shine-Dalgamo sequence (5’~UGAGGAUGGU~3’);>which corresponds to nucleotides 59 to 68 of SEQ ID NO: 7; the start codon (5’~AUG~3’; shown in bold italic), which corresponds to nucleotides 72 to 74; and the standby site (5r-UCUAGACAGC“3’ (SEQ ID NO: 6); in outlined text), corresponding to nucleotides I to 15 of SEQ ID NO: 7. The hatched bar is the ribosomal footprint for initiation (5’-UAAGGAGGGUGAGGAUGGCGAGCUCUGAA~3\ which corresponds to nucleotides 1 to 10 of SEQ ID NO: 7. The hatched bar is the ribosomal footprint for initiation (5’-UGAGGAUGGUAUCAUGGCGAGCUCUGAA-3’, which corresponds to nucleotides 59 to 86 of SEQ ID NO: 7.10018| FIGS. 4A-4C show the dose-response of MS2, CRP, and IL32y riboswitches.The measured mRFPl fluorescence levels, normalized rnRFPl expression levels, and activation or repression ratios of the M2 (FIG. 4A), C5 ( FIG. 4B), and 12 (FIG. 4C) riboswitch sensors (open circles) in response to varied concentrations of the MS2 expression plasmid, purified human mCRP protein, and purified human lE32y protein, respectively (closed circles). The measured mRFPl fluorescence levels and normalized mRFP l expression levels of the noaptamer control (UTR-1.36) under the same conditions. Circles and bars are the mean and standard deviation of replicate cell-free assays (FIG. 4A, N ~ 8 biological replicates; FIG. 4B, N = 8 biological replicates; FIG. 4G, N = 6 biological replicates). (0019] FIGS. 5A-B demonstrate placement of mCRP aptamer in the standby site of the5TJTR represses gene expression. FIG. 5A is a schematic showing the sequence and structure of the mCRP-binding steric switches, showing the spacer length (A) separating the mCRP aptamerand a consensus Shine-Daigarno sequence. FIG. 5B is a graph comparing the repression ratios of the designed mCRP OFF switches (Col to Co5) and mCRP steric switches (+0, +5, -’-20). Gray bars are mean repression ratios. Open circles are mean mRFP 1 fluorescence levels in the OFF state. Filled circles are mean mRFPl fluorescence levels in the ON state. Error bars are the 95% confidence intervals (N ~ 8 biological replicates).

[0020] FIGS. 6A--6D demonstrate optimization of Riboswitch Calculator predictions for in vitro protein riboswitches. Model predictions were compared to measured riboswitch regulation (activation or repression) ratios, utilizing three different equations that take into account additional interactions for improved accuracy. Model predictions include the maximum predicted regulation ratio, Rmx(FIG. 6 A), the predicted regulation ratio when considering the protein concentration, Raw (FIG. 6B), and the predicted actual regulation ratio, Racial (FIG. 6C), when considering both the protein concentration and the thermodynamics of the mRNA -protein complex. Model predictions were recalculated while systematically varying the length of the aptamer subconstraint region, showing riboswitch Col as an example (FIG. 6D). The optimal aptamer subconstraints for the MS? (open circles), mCRP (closed circles), and IL32y (hatched circles) aptamers were identified and utilized to predict the actual regulation ratio, Racial, for all riboswitches (FIG. 6E). Overall accuracy is R2~ 0.64 with 56% of riboswitches predicted to within 2-fbld of their measured activation ratio. Circles and error bars are the mean and standard deviation of data with 6 to 8 biological replicates.

[0021] FIG. 7 is a graph showing mRFPl fluorescence endpoint vs. pFTVl-mRFPl plasmid concentration. Mean fluorescence levels (closed circles) are proportional to mRFPl- expressing plasmid concentration up to 32 nM. N = 2 biological replicates.

[0022] FIG. 8 is a graph showing mRFPl fluorescence levels vs. predicted binding free energies controlling translation initiation rates for all 35 riboswitches. The Riboswitch Calculator predicted the binding free energies ( AGt(^i) of the ribosome-mRNA interactions controlling translation initiation rates for riboswitches in the uninduced and protein-induced states. Open circles are mean uninduced mRFPl endpoint fluorescence levels, while filled circles are mean induced mRFPl fluorescence levels. Dotted lines show the best-fit log-linear line, log (mRFPl endpoint flu.) = log(K.) - pA( Jtotai, where the parameter K is a proportionality constant and p is the Boltzmann constant relating free energies to state probabilities. The black dotted line corresponds to uninduced riboswitch fluorescence levels (R2 :::0.48). The grey dotted line corresponds to induced riboswitch fluorescence levels (R2~ 0.10), The parameter p was previously determined to be 0.45+0.05 in in vivo systems across diverse bacterial species (Sailset. al., “Automated Design of Synthetic Ribosome Binding Sites to Control Protein Expression, Nat. Biolechnol. 27(10):946-950 (2009), which is hereby incorporated by reference in its entirety). In this cell-free, in vitro system, it was found that p is 0.23, indicating a reduction in the dynamic range of cell-free translation. R2= 0.48 for uninduced riboswitches. Error bars represent 95% confidence interval (N ~ 6 biological replicates for MS2 ON-riboswitches, N ~ 8 biological replicates for all other riboswitches).

[0023] FIGS. 9A--9D are heat maps showing the effect of varying the aptamer structural constraint region on mCRP and 1132? riboswitch predictions. The structural constraint of the aptamer region of riboswitches Col 2, C2, 12, and 15 were varied, and the effects on the predicted translation rate ratios (ARaejS!af) were calculated. For all, X represents the distance from the start of the full aptamer sequence to the beginning of the sub-constrained region, and Y represents the distance from the start of the full aptamer sequence to the end of the sub-constrained region.FIG. 9 A shows the effect of varying the size of the mCRP aptamer structural constraint in riboswitch Col2. FIG. 9B shows the effect of varying the size of the IL32? aptamer structural constraint in riboswitch 12. FIG. 9C shows the effect of varying the size of the mCRP aptamer structural constraint in riboswitch C2. FIG. 9D shows the effect of varying the size of the IL32y aptamer structural constraint in riboswitch 15.[(I024J FIGS. 10A-10E are tables providing riboswitch sequence (FIG. I0A), OFF-state prediction data (FIG. 10B), ON-state prediction data (FIG. 10C), Z\AGlt!RNA:iignnd data (FIG. 10D), predicated activation data (FIG. 10B), and predicted repression data (FIG. 1 OF). Sequences shown using DNA base symbols: adenine (A), cytosine (C), guanine (G), and thymine (T).When transcribed into RNA, thymine (T) bases are replaced with uracil ( U).DETAILED DESCRIPTION

[0025] Unless otherwise indicated, the definitions and embodiments described in this and other sections are intended to be applicable to all embodiments and aspects of the present application herein described for which they are suitable as would be understood by a person skilled in the art.

[0026] Singular forms “a”, “an”, and “the” include plural references unless the context clearly dictates otherwise. Thus, for example, a reference to “a method” includes one or more methods, and / or steps of the type described herein and / or which will become apparent to those persons skilled in the art upon reading this disclosure. In another example, reference to “a compound” includes both a single compound and a plurality of different compounds.

[0027] The term “about” or “approximately” includes being within a statistically meaningful range of a value. Such a range can be within an order of magnitude, preferably within 50%, more preferably within 20%, still more preferably within 10%, and even more preferably within 5% of a given value or range. The allowable variation encompassed by the term “about” or “approximately” depends on the particular system under study, and can be readily appreciated by one of ordinary skill in the art .

[0028] The term “and / or” as used herein means that the listed items are present, or used, individually or in combination. In effect, this term means that “at least one of’ or “one or more” of the listed items is used or present.

[0029] As will be understood by one skilled in the art, for any and all purposes, such as in tertns of providing a written description, all ranges disclosed herein also encompass any and all possible subranges and combinations of subranges thereof Any listed range can be easily recognized as sufficiently describing and enabling the same range being broken down into at least equal halves, thirds, quarters, fifths, tenths, and so on. As a non-limiting example, each range discussed herein can be readily broken down into a lower third, middle third and upper third, and so on. As will also be understood by one skilled in the art all language such as “up to,” “at least,” and the like include the number recited and refer io ranges which can be subsequently broken down into subranges as discussed above. Finally, as will be understood by one skilled in the art, a range includes each individual member.

[0030] In understanding the scope of the present application, the term “comprising” and its derivatives, as used herein, are intended to be open ended terms that specify the presence of the stated features, elements, components, groups, integers, and / or steps, but do not exclude the presence of other unstated features, elements, components, groups, integers and or steps. The foregoing also applies to words having similar meanings such as the terms, “including”, “involving”, “having”, and their derivatives. The term “consisting” and its derivatives, as used herein, are intended to be closed terms that specify the presence of the stated features, elements, components, groups, i ntegers, and. or steps, but exclude the presence of other unstated features, elements, components, groups, integers and / or steps. The term “consisting essentially of”, as used herein, is intended to specify the presence of the stated features, elements, components, groups, integers, and / or steps as well as those that do not materially affect the basic and novel characteristic(s) of features, elements, components, groups, integers, and / or steps. In embodiments or claims where the term comprising (or the like) is used as the transition phrase, such embodiments can also be envisioned with replacement of the term “comprising” with theterms “consisting of’ or “consisting essentially of.” The methods, kits, systems, and / or compositions of the present disclosure can comprise, consist essentially of, or consist of, the components di sc 1 osed.[0031 | In embodiments comprising an “additional” or “second” component, the second component as used herein is different from the other components or first component. A “third” component is different from the other, first, and second components, and further enumerated or “additional” components are similarly different.[0032| Preferences and options for a given aspect, feature, embodiment, or parameter of the disclosure should, unless the context indicates otherwise, be regarded as having been disclosed in combination with any and all preferences and options for all other aspects, features, embodiments, and parameters of the disclosure.

[0033] A first aspect of the disclosure is directed to a protein-binding riboswitch comprising a pre-aptamer nucleotide sequence, an aptamer nucleotide sequence encoding an RNA structure capable of binding a target protein, a post-aptamer nucleotide sequence; and a protein-coding nucleotide sequence encoding a reporter, where binding of the target protein by the aptamer nucleotide sequence modulates expression of the reporter.

[0034] As used herein, the term “aptamer” refers to a nucleic acid molecule that has a specific binding affinity for a ligand, e.g., a target protein.

[0035] The term “riboswitch” refers to an RNA -based sensor that uses an aptamer domain to bind a ligand (e.g., a target protein), changes shape, and alters the expression level of e.g., a gene of interest or a reporter.

[0036] In some embodiments, the pre-apiamer nucleotide sequence is upstream of the aptamer nucleotide sequence, the aptamer nucleotide sequence is 5 ’ to the post-aptamer nucleotide sequence, and the post-aptamer nucleotide sequence is 5’ to the protein-coding nucleotide sequence.

[0037] Embodiments of the protein-binding riboswitch according to the present disclosure are illustrated in FIG. 2 A. FIG. 2 A provides an illustration of an MS2-bindmg riboswitch comprising a pre-aptamer nucleotide sequence; an aptamer nucleotide sequence encoding an RNA structure capable of binding MS2 (i.e., an MS2 aptamer); a post-aptamer nucleotide sequence; and a protein -coding nucleotide sequence encoding a reporter ( / .<?., RFPI ).

[0038] Also illustrated in FIG, 2A is an mCRP-binding riboswitch comprising a pre- aptamer nucleotide sequence; an aptamer nucleotide sequence encoding an RNA structurecapable of binding mCRP (i.e., a mCRP aptamer); a post-aptamer nucleotide sequence; and a protein-coding nucleotide sequence encoding a reporter ( / .« ., RFP I ).

[0039] FIG. 2A also illustrates an IL32y-bmdmg riboswitch comprising a pre-aptamer nucleotide sequence; an aptamer nucleotide sequence encoding an RN A structure capable of binding IL32y (Ze., a IL32y aptamer); a post-aptamer nucleotide sequence; and a protein -coding nucleotide sequence encoding a reporter (i.e., RFP1).

[0040] The pre-aptamer nucleotide sequence and post-aptamer nucleotide sequence may comprise natural nucleotides and / or non-natural nucleotides. Exemplary non-natural and natural nucleotides are well known in the art.(0041] In some embodiments of the protein-bi ndi ng riboswitch, test strip, and methods of the present disclosure, the pre-aptamer nucleotide sequence and post-aptamer nucleotide sequence comprise natural nucleotides. Natural nucleotides include adenosine (A), guanosine (G), cytosine (C), and thymine (T) for DNA and adenosine (A) for RNA. ), guanosine (G), cytosine (C) and uridine ( U).

[0042] In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, the pre-aptamer nucleotide sequence and post-aptamer nucleotide sequence comprise non-natural nucleotides.

[0043] Non-natural nucleotides may include, e.g., a non-natural nucleobase ('.see, e.g., U.S. Patent No. 1 1 ,834.689, which is hereby incorporated by reference in its entirety). In some embodiments, the non-natural nucleotides includes non-natural nucleobases selected from the group consisting of 2-ammoadcnine-9-yl, 2 -aminoadenine, 2-F-adenine, 2-thiouracil, 2 -thiothymine, 2-thiocytosine, adenine, and 2-Propyl and alkyl derivatives of guanine, 2-amino- adenine, 2-amino-propyl- adenine, 2-aminopyridine, 2-pyridone, 2'-deoxyuridine, 2-amino-2’- deoxy Adenosine, 3-deazaguanine, 3 -deazaadenine , 4-tliio-uracil, 4-thio-thymine, uracil-5-yI, hypoxanthine-9-yl(I), 5-mcthyl-eytosine, 5 -hydroxymethyl cytosine, xanthine, hypoxanthine, 5- bromo, and 5~trifluoromethy1 uracil and cytosine; 5-halouracil, 5-halocytosine, 5-propynyl- uracil, 5-propynyl cytosine, 5-uracil, 5-substituted, 5-halo, 5-substituted pyrimidine, 5- hydroxycytosine, 5 -Bromocytosine, 5 -bromouracil, 5-chlorocytosine, chlorinated cytosine, cyclocytosine, cytosine arabinoside, 5-fluorocytosine, fluoropyrimidine, fluorouracil, 5,6- dihydro 6 of cytosine, 5 -iodocytosine, hydroxyurea, iodouracil, 5-nitrocytosine, 5-bromouracil, 5~chlorouracil, 5-fluorouracil, and 5-iodouracil, adenine, and guanine. -Alkyl derivatives, 6- azapyrimidine, 6-azo- uracil, 6-azo cytosine, azacytosine, 6-azo-thymine, 6-thio-guanine, 7- methylguanine, 7-methyladenine, 7-deaza Guanine, 7 -deazaguanosine, 7-deaza-adenine, 7~deaza-8-azaguanine, 8-azaguanine, 8-azaadenine, 8-halo, 8-amino, 8-thiol, 8- thioalkyl, and 8- hydroxyl substituted adenine and guanine; N4-ediylcytosine, N-2 substituted purine, N-6 substituted purine, 0-6 substituted purine, increasing the stability of duplex formation, universal nucleic acid, hydrophobic nucleic acid, promiscuous nucleic acid, size Expanded nucleic acids, fluorinated nucleic acids, tricyclic pyrimidines, phenothiazine cytidine ([5,4-b][1,4]benzoxazin- 2(3H)-one), phenothiazine cytidine (111 ~pyrimido[5,4-b][l,4]benzothiazin-2(3H)-one), G-clamp, phenoxazine cytidine (9-(2-aminocthoxy)-Il-pyrimido [5,4-b][l,4]benz.oxazine-2(3M)-one), carbazole cytidine (211-pyrimido[4,5-b]indol-2~one), pyridoindole cytidine Dean(I!-pyrido [3’,2':4,5]pyrrolo [2,3-d]pyrimidin-2-one), 5-fluorouracil, 5-bromouracil, 5 -chlorouracil , 5- iodouracil, hypoxanthine, xanthine, 4-acetylcytosine, 5-(carboxyhydroxyImethyl) uracil, 5- carboxymethylaminomethyl-2-thioiindine, 5-carboxymethylarninomethyluracil, Dihydrouracil, beta-D-galactosylcheosine, inosine, N6-isopentenyladenine, 1-methylguanine, 1 -methyl inosine, 2,2-dimethylguan.ine, 2-methyladenine, 2-methylguanine, 3 -Methy {cytosine, 5-methylcytosine, N6-adenine, 7 -methylguan ine, 5-methylam inomethyluracil, 5-methoxyami nometh yl-2 -thiouracil , beta-D-mannosylcheosine, 5 -me Toxycarboxymethyl uracil, 5 -methoxy uracil, 2-methylthio-N6- isopentenyiadenine, uracil -5 oxy acetic acid, wybutoxosine, pseudouracil, keosine, 2 -thiocytosine, 5-methyl -2-thiouracil, 2 -thiouracil, 4-ihiouracil, 5-methyluracil, uracil-5-oxacetic acid methyl ester, uracil-5-oxacetic acid, 5-inethyl-2-thiouraciL 3-(3 -amino-3-N-2-carboxypropyl) uracil, (acp3)w, and 2,6-dianimopurme, and purine or pyrimidine bases replaced by heterocycles, 10044] In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, the pre-aptamer nucleotide sequence and post-aptamer nucleotide sequence comprise one, two, three, four, five, six, seven, eight, nine, ten, eleven, twelve, thirteen, fourteen, fifteen, sixteen, seventeen, or more non- natural nucleotides.

[0045] As used herein, the term ‘'reporter” may refer to a “reporter protein” encoded by a nucleic acid sequence whose expression results in a detectable or reportable phenotype, either by itself or with the addition of a compound or substance.

[0046] Binding of the target protein may activate or inhibit expression of a reporter protein according to the present disclosure.

[0047] In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, binding of the target protein activates expression of a reporter, e.g. , a reporter protein. In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, the reporter is selected from the group consisting of a transcription factor, a fluorescent protein, an enzyme, and an antibody. Suitable exemplary reporter proteinsare well known in the art, such as fluorescein isothiocyanate (FITC)-labeled antibodies, rhodamine-labeled antibodies, Alexa Fluor-labeled antibodies, phycoerythrin (PE)-labeled antibodies, and allophycocyanin (APC)-labeled antibodies.[0048| Suitable reporter proteins include, without limitation fluorescent proteins such as red fluorescent protein ( RFP >, monomeric red fluorescent protein (mRPF 1 ), blue fluorescent protein (BFP), yellow fluorescent protein (BFP), green fluorescent protein (GFP). and derivatives thereof such as enhanced green fluorescent protein (EGFP), mGreenLantern, and superfolder GFP (sfGFP). Additional suitable reporter proteins include enzymes such as glucose oxidase, invertase, lactase, amylase (e.g., alpha-amylase, beta-amylase, gamma- amylase), trehalase, phosphatase (e.g,, alkaline phosphatase), and luciferase.

[0049] Suitable exemplary protein-coding nucleic acid sequences encoding a reporter for use in the protein-binding riboswitch, test strip, and / or methods of the present disclosure are provided in Table 1.Table i. Suitable Protein-Coding Amino Acid Sequences Encoding a Reporter for Use in the Protein-Binding Riboswitch, Test Strip, and / or Methods of the Present Disclosure[0050| One embodiment of a protein-binding riboswitch, where binding of the target protein activates expression of a reporter is illustrated in FIG. 3A. FIG. 3A illustrates an MS2- binding riboswitch (f e., an MS2 ON Switch) comprising a pre-aptanier nucleotide sequence; an aptamer nucleotide sequence encoding an RNA structure capable of binding MS2 coat protein (z.e, an MS2 aptamer); a post-aptamer nucleotide sequence; and a protein-coding nucleotide sequence encoding a reporter (i.e., monomeric red fluorescent protein (RFP1 )). As illustrated in FIG. 3 A. binding of a target protein (Le., an MS2 coat protein) to the MS2 ON Switch induces a conformation change in the riboswitch (State 3) which leads to activation of the translation rate of the post-aptamer sequence in the presence of a 30S ribosome.

[0051] In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, binding of the target protein inhibits expression of the reporter, [00521 One embodiment of a protein-binding riboswitch, where binding of the target protein inhibits expression of a reporter is illustrated in FIG, 3B. FIG. 3B illustrates an MS2- binding riboswitch (f.e., an MS2 OFF Switch) comprising a pre-aptamer nucleotide sequence; an aptamer nucleotide sequence encoding an RNA structure capable of binding MS2 coat protein (i.e., an MS2 aptamer); a post-aptamer nucleotide sequence; and a protein -coding nucleotide sequence encoding a reporter (i.e.. monomeric red fluorescent protein (RFP 1 )). As illustrated in FIG. 3B, binding of a target protein (te., an MS2 coat protein) to the MS2 OFF Switch induces a conformation change in the riboswitch (State 3) which leads to inhibition of the translation rate of the post-aptamer sequence in the presence of a 30S ribosome.

[0053] In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, the RNA structure comprises one or more of the group consisting of a hairpin, a stem, a loop, an internal loop, a multiloop, a junction, a pseudoknot, and or a bulge.

[0054] As used herein, the terms “hairpin”, “hairpin loop”, and “stem-loop” are used interchangeably and refer to a secondary structure in RNA where a single-stranded sequence folds back on itself to form a double-stranded stem with a loop at the end. The term “stem” refers to a double-stranded region of RNA formed by base pairing between complementary sequences within the same RNA molecule. The term “loop” refers to a single-stranded region of RNA that connects two stems. The term “internal loop” refers to a region within a doublestranded RNA where both strands have unpaired nucleotides, creating a loop within the stem. Internal loops can vary in size and are important for the flexibility and function of RNA. The terms “multiloop” and “multi-branched loop” are used interchangeably and refer to a complex RNA structure where three or more double-stranded regions (stems) converge.

[0055] As used herein, the terms “junction”, “branch point”, and multi-helix junction” are used interchangeably and refer to a point in an RN A molecule where three or more doublestranded regions (steins) come together.

[0056] As used herein, the term “pseudoknot” refers to a complex RNA structure where bases in a loop pair with complementary bases outside the loop, forming an additional stern.

[0057] As used herein, the term “bulge” refers to a region in a double-stranded RNA where one or more nucleotides are unpaired, causing a bulge in the otherwise regular helical structure.

[0058] In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, the target protein is a human protein, a viral protein, or a bacterial protein. As described in more detail infra, protein-binding aptamers are available for specific binding to a wide variety of targets, including human proteins (Gold et a!,, '‘Aptamer-Based Multiplexed Proteomic Technology for Biomarker Discovery,” PLoS One 5(12):e 15004 (2010); Cox et al., ‘'Automated Selection of Aptamers Against Protein Targets Translated in Vitro: From Gene to Aptamer,'’ Nucleic Acids Res. 30(20):el 08 (2002); Chen et al., “Inhibition of Heregulin Signaling by an Aptamer that Preferentially Binds to the Oligomeric form of Human Epidermal Growth Factor Receptor-3,” PAMS’ 100(16):9226-9231 (2003); and Wang ct a!., “Aptamer- Based Fluorescent Biosensors,” Curr. Med. Chem. 18(27):4175-4184 (2011), which are hereby incorporated by reference in their entirety), HIV viral proteins (Kensch et al., “HIV-1 Reverse Transcriptase-Pseudoknot RNA Aptamer Interaction Has a Binding Affinity in the Low Picomolar Range Coupled with High Specificity,” J. Biol. Chem. 275(24): 18271-18278 (2000) and Matsugami et al., “Structural Basis of the Highly Efficient Trapping of the HIV Tat Protein by an RNA Aptamer,” Structure 11(5):533-545 (2003), which are hereby incorporated by reference in their entirety), and bacterial toxins (Frohnmeyer et al., “Highly Affine and Selective Aptamers Against Cholera Toxin as Capture Elements in Magnetic Bead-Based Sandwich EL A A,” J. Biotechnol. 269:35-42 (2018), which are hereby incorporated by reference in their entirety).

[0059] In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, the target protein is a biomarker. As used herein, the term '‘biomarker” refers to a molecule that is associated either quantitatively or qualitatively with a biological change. Exemplary' biomarkers include polypeptides, proteins or fragments of a polypeptide or protein; and polynucleotides, such as a gene product, RNA or RNA fragment; and other body metabolites. In some embodiments, a “biomarker” means a compound that is differentially present (i.e., increased or decreased) in a biological sample from a subject or a group of subjects having a first phenotype (e.g., having a disease or condition) as compared to a biological sample from a subject or group of subjects having a second phenotype (e.g., not having the disease or condition or having a less severe version of the disease or condition).

[0060] In some embodiments of the protein-binding riboswitch, lest strip, and methods of the present disclosure, the target protein is a human protein,

[0061] Suitable exemplary target proteins include, without limitation, monomeric C- reactive protein, interleukin-32 receptor, hemoglobin, angiotensin-converting enzyme, anti-acetylcholine receptor antibody, adenosine deaminase, alpha-fetoprotein, pappalysin-1, aldolase A, alpha-1 -antitrypsin, serum amyloid A-l protein, interleukin-2 receptor subunit alpha, mucin- 1, lysozyme C, aspartate transaminase, osteocalcin, underearboxylated osteocalcin, N-terminal pro-B-type natriuretic peptide, gamma-glutamyltranspeptidase, antimitochondrial antibodies, anti neutrophil cytoplasmic antibodies, anti-streptolysin antibodies, anti-DNaase B antibodies, anti-cyclic citn.il! inated peptide, C-ierminal telopeptide, N-terminal propeptide of type 1 procollagen, N-terminal telopeptide, anticardiolipin antibody, anti-beta2 glycoprotein 1, mueilerian-inhibiting factor, proinsulin C -peptide, perineuclear antineutrophil cytoplasmic antibodies, anti -dengue virus antibody, vascu lar endothelial growth factor, macrophage colony- stimulating factor 1, amylase, lipoprotein lipase, antineutrophil cytoplasmic antibodies against proteinase 3, calprotectin, human epididymis protein 4, carbohydrate antigen 125, chromogranin- A, epstein-barr virus capsid antigen antibody, ceruloplasmin, anti-gliadin antibody IgA, p- selectin, sex hormone-binding globulin, des-gamma-carboxy prothrombin, hepatitis a virus cellular receptor 1, neutrophil gelatinase associated lipocalin, interleukin- 18, hepatocyte growth factor, cystatin-C, n-acetyl-beta-d-glucosaminidase, chemokine interferon inducible protein 10, fibronectin, nuclear ribonucleoprotein Hl antibodies, anti-ribosomal P antibodies, hemoglobin subunit beta, glucose-6-phosphate 1 -dehydrogenase, gastrin, acetylcholinesterase, amyloid beta42, vasopressin-neurophysin 2 -copeptin, apolipoprotein E, beta-2-microglobulin, bone specific alkaline phosphatase, brain natriuretic peptide, butyrylcholinesterase, ca 19-9 tumor marker, calcitonin, chymotrypsin, complement Cl, component C2, complement C3, complement C4, pancreatic elastase- 1 , ferritin, gammaglutamyl transferase (ggt), haptoglobin, hemoglobin, insulin, insulin-like growth factor 1 , interleukin-6, interferon gamma, lactate dehydrogenase, lactotransferrin, parathyroid hormone, adrenocorticotropic hormone, transglutaminase IgA antibody, renin, cardiac troponin T, cardiac troponin I, transthyretin, erythropoietin, thyroid stimulating hormone, thyroglobulin, prothrombin, tryptase, antithrombin, sex hormone binding globulin, apolipoprotein B-100, von willebrand factor, apolipoprotein A l, Clostridium difficile glutamate dehydrogenase, transferrin receptor (soluble), estrogen receptor, progesterone receptor, fibrinogen, factor V, transferrin, follicle stimulating hormone, hemoglobin S, her?, human chorionic gonadotropin, human growth hormone, kappa / lambda light chains, lactoferrin, leptin, luteinizing hormone, myoglobin, tan protein, tartrate resistant acid phosphatase, procalcitonin, prolactin, prostate specific antigen, protein C, protein S, albumin, and alanine transaminase.

[0062] Suitable exemplary aptamers for use in the protein-binding riboswitch, test strip, and / or methods of the present disc losure are provided in Table 2.Table 2. Suitable Aptamers for Use in the Protein-Binding Riboswitch, Test Strip, and / orMethods of the Present Disclosure[0063| In some embodiments, the target protein is monomeric C-reactive protein (CRP) or interleukin-32 gamma proteins. As disclosed in more detail infra, CRP is found in human plasma and natively forms a homopentameric complex, but will irreversibly dissociate into its monomeric form during a pro-inflammatory response (e.g. , tissue damage, heart disease, cancer, or bacterial infection) (Sproston and Ashworth, '‘Role ofC-Reactive Protein at Sites of Inflammation and infection,” Front. / mnnmol 13:9:754 (2018) and Black et al., “C-reactive Protein,” / Sial Chem. 279(47):48487-48490 (2004), which are hereby incorporated by reference in their entirety). A mC-RP concentration of 10 mg / L (430 riM) is considered elevated and, depending on the disease severity, mCRP concentrations can readily exceed 100 mg / L (4.3 mM).

[0064] In some embodiments, the target protein is monomeric CRP. Suitable riboswitches comprising an apatamer nucleotide sequence encoding an RNA structure capable of binding CRP include the CRP riboswitches shown in 'fable 3 below.Table 3. Suitable Riboswitches Comprising an Aptamer Nucleotide Sequence Encoding an RN A Structure Capable of Binding CRP

[0065] In some embodiments, the protein-binding riboswitch comprises an apatamer nucleotide sequence encoding an RNA structure capable of binding CRP and has a sequence of 5 ’•••• UCCuAGACZVXAAGCAGUUACGCCUGUAAGGUGGUCGGUGUGGCGAGUGUGUUAGGAGAGAUU GCUCACGGGUCAAUA.AGGAGGGUGGGU-3’ (SEQ ID NO: 8).

[11066] An exemplary embodiments of a protein- binding riboswitches comprising an aptamer nucleotide sequence encoding an R.NA structure capable of binding monomeric C- reactive protein is illustrated in FIG. 2A.

[0067] IL-32 is a cytokine that regulates the NF-KB pathway and acts during early host defense against pathogen infections (Heinhuis et al., “Interleukin-32: A Predominantly Intracellular Proinflammatory Mediator that Controls Cell Activation and Cell Death,” Cytokine 60(2):321 -327 (2012); El-Far et al., “Proinflaniniatory Isoforms of IL-32 as Novel and Robust Biomarkers for Control Failure in HIV- Infected Slow Progressors,”Rep. 15:6:22902 (2016); and Gui et al., “Clinical Significance of Interleukin-32 Expression in Patients with Rheumatoid .Arthritis,” Asian Pac. J. Allergy Immunol. 31( 1 ):73-78 (2013), which are hereby incorporated by reference in their entirety). IL-32? is the longest and most pro- inflammatory iso form of IL-32. Elevated levels of IL-32? in human serum have been found to be associated with heart failure, COPD, and multiple myeloma (Xin et al., “Interleukin-32: Its Role in Asthma and Potential as a Therapeutic Agent,”Res. 19(1 ): 124 (2018), which is hereby incorporated by reference in its entirety) (up to around 61 pM or 1.6 ng / ml). In some embodiments, the target protein is interleukin-32 gamma. Suitable riboswitches comprising an apatamer nucleotide sequence encoding an RNA structure capable of binding IL-32 include the IL -32 riboswitches shown in Table 4 below.Table 4. Suitable Riboswitches Comprising an Aptamer Nucleotide Sequence Encoding an RNA Structure Capable of Binding IL-32?|0068] In some embodiments, the protein-binding riboswitch comprises an apatamer nucleotide sequence encoding an RNA structure capable of binding II,-32y and has a sequence of 5 UC U AGAU AGAAAGAU AAAC G GU AAGAGGGUUCACUGCAGACUUGACGAAGCUUCCGGAGAGA AGGGUCAAAGUUGUGCGGGAGUGUGUUGUGGAAUGGAUCCACAUCUACGAAUUC CGUGCAAGAGAUAAGGAGGGUG AAA-3* (SEQ ID NO: 24).

[0069] An exemplary embodiments of a protein-binding riboswitches comprising an ap tamer nucleotide sequence encoding an RNA structure capable of binding interleukin-32 gamma is illustrated in FIG. 2A.

[0070] In some embodiments of the protein -binding riboswitch, test strip, and methods of the present disclosure, the pre-aptamer nucleotide sequence is between 2-35 nucleotides in length. For example, tire pre-aptamer nucleotide sequence may be 2, 3, 4, 5, 6, 7, 8, 9, 10, I I , 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 , 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, or 35 nucleotides in length.

[0071] In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, the post-aptamer nucleotide sequence is between 9-35 nucleotides. Forexample, the post-aptamer nucleotide sequence may be 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31 , 32, 33, 34, or 35 nucleotides in length.

[0072] In some embodiments of the protein-binding riboswitch, test strip, and methods of the present disclosure, the post-aptamer nucleotide sequence comprising a Shine Dalgamo sequence. Suitable Shine Dalgamo sequence are well known in the art. In some embodiments, the Shine Dalgamo sequence is 5’-UAAGGAGGU-3* or a subsequence thereof.Test Strips[0073| Another aspect of the disclosure is directed to a test strip comprising a sample collection zone configured to receive a biological sample, where the sample collection zone comprises: (i) a nucleic acid molecule encoding a protein-binding riboswitch according to the present disclosure and (if) a cell -free transcription / translation system.

[0074] As used herein, the term “sample collection zone” refers to refers to an area on, e.g., a test strip where a sample (such as a biological sample) is applied or deposited. As described herein, the sample collection zone comprises a nucleic acid molecule encoding a protein-binding riboswitch according to the present disclosure and a cell-tree transcription / translation system.

[0075] Exemplary embodiments of nucleic acid molecules encoding protein-binding riboswitches according to the present disclosure (e.g., nucleic acid molecules encoding proteinbinding riboswitches comprising RNA structures capable of binding monomeric C-reactive protein or interleukin-32 gamma proteins are provided in Tables 3 and 4, respectively.

[0076] Suitable cell-free transcription, translation systems are well known in the art and include, without limitation, myTX-TL, PURE expression systems, and customized cell lysates with energy and amino acid solutions.

[0077] Suitable reporter proteins are described in more detail supra. In some embodiments, the reporter protein is a fluorescent protein. For example, the fluorescent protein may be a monomeric fluorescent protein. Suitable fluorescent proteins include, without limitation, monomeric red fluorescent protein (niRPFI), mGreenLanteni, and superfolder GFP (sfGFP).

[0078] In some embodiments, the reporter is an enzyme. Suitable enzymes are described in more detail supra. For example, the enzyme may be selected from the group consisting of glucose oxidase, invertase, lactase, alpha- amylase, beta-amylase, gamma-amylase, trehalase, and phosphatase.

[0079] In some embodiments, the sample collection zone further comprises (iii) a substrate.[0080| The substrate may be present at a known concentration, hi some embodiments, the substrate is present at a concentration of 1 picomolar to 1 millimolar.[0081 | In some embodiments, the enzyme is glucose oxidase and the substrates is glucose. In some embodiments, the enzyme is invertase and the substrates is sucrose. In some embodiments, the enzyme is lactase and the substrate is lactose. In some embodiments, the enzyme is alpha-amylase, beta-amylase, or gamma-amylase and the substrate is maltose. In some embodiments, the enzyme is trehalase and the substrate is trehalose. In some embodiments, the enzyme is phosphatase and the substrate is glucose 6-phosphate,

[0082] In some embodiments, the sample collection zone further comprises (iv) one or more enzymatic cofactors. The one or more enzymatic cofactors may be selected from the group consisting of NADU, FAD 112. NADPI I, and ATP.

[0083] In some embodiments, the biological sample is selected from the group consisting of blood, serum, saliva, sputum, plasma, cerebral spinal fluid, synovial fluid, urine, breast milk, and bile.

[0084] In some embodiments, the cell free-transcription / translation system comprises one or more reagents selected from the group consisting of ATP, GTP, DTP, CTP, Folinic Acid, tRNA, Nicotinamide Adenine Dinucleotide (NAD), Coenzyme A (CoA), Oxalic Acid, Putrescine, Spermidine, HEPES buffer, Mg(Glu)2, NII4(Glu), K(GIu), 20 natural amino acids, and Phosphoenolpyruvate (PEP).[0085| In some embodiments, the cell free-transcription- ''translation system comprises a cell -free lysate. In other embodiments, the cell free-transcription / trtmslation system includes a recombinant cell-free system.|0086] The sample collection zone may further comprise (v) one or more RNase inhibitors, (vi) one or more protease inhibitors, and / or (vi) one or more cosolutes.

[0087] Suitable cosolutes include, without limitation, polyethylene glycol (PEG) and / or Ficol.

[0088] In some embodiments, the sample collection zone comprises at least two electrodes.

[0089] As used herein, the term '‘electrode” may generally refer to an arbitrary element which is configured to or which is usable to electrically or electrochemically detect a target protein. The electrodes may be embodied such that an electrochemical reaction may take placeat one or more of the electrodes, such as one or more working electrodes. Thus, the electrodes may be embodied such that an oxidation reaction and / or reduction reaction may take place at one or more of the electrodes. The electrochemical detection reaction may be detected by comparing one or more electrode potentials, such as an electrostatic potential of a working e lectrode with an electrostatic potential of one or more further electrodes, such as a counter electrode or a reference electrode. Generally, the two or more electrodes may be used for one or more of an amperometric measurement and / or a voltammetric measurement.

[0090] hi some embodiments, the sample collection zone comprises a working electrode and a counter electrode.

[0091] As used herein, the term ‘'working electrode” refers to an electrode being adapted for or being usable for performing at least one electrochemical detection reaction for detecting the at least one target protein in a sample, e.g., a biological sample.[00921 As used herein, the term '‘counter electrode” refers to an electrode adapted for performing at least one electrochemical counter reaction and adapted for balancing a current flow required by the detection reaction at the working electrode.

[0093] Additionally or alternatively, the at least two electrodes may further comprise at least one reference electrode. The reference electrode may have a stable and well-known electrode potential. The electrode potential of the reference electrode may typically be highly stable. The counter electrode and the reference electrode may be one of a common electrode or two separate electrodes.Methods of Detecting a Target Protein in a Biological Sample|0094] Another aspect of the present disclosure is directed to a method of detecting a target protein in a biological sample, where the method involves providing a test strip according to the present disclosure; placing a biological sample in the sample collection zone of the test strip, where said target protein, if present in the biological sample, will bind to the proteinbinding riboswitch to modulate the expression level of the reporter protein; detecting the reporter protein; and determining, based on said detecting, the presence or absence of the target protein in the biological sample.[0O95| In some embodiments, expression of the reporter protein results in a measurable signal. The measurable signal may be selected from the group consisting of a fluorescent signal, a photometrically detectable signal, electrical current detectable signal, magnetic force detectablesignal, light diffraction detectable signal volatile organic chemical detectable signal, or colorimetric detectable signal.[0096| In some embodiments, determining, based on said detecting, the presence or absence of the target protein in the biological sample involves comparing the expression level of the reporter protein relative to one or more reference) s). The one or more referenee(s) may include a control comprising a known amount of the target protein (positive control) and / or a control comprising no target protein (negative control).[0097| hi some embodiments, the determining step may involve quantifying the concentration of the target protein in the biological sample.

[0098] The method may be carried out at temperatures from 4 to 50 degrees Celsius. In some embodiments, the method is carried out at room temperature.

[0099] Another aspect of the present disclosure is directed to a method of detecting a target protein in a biological sample, where the method involves providing a test strip according to the present disclosure, where the test strip is operably linked to an electrode and a current comparator and where the current comparator is operably linked to a reference electrode that supplies a reference current; placing a biological sample in the sample collection zone of the test strip, where said target protein, if present in the biological sample, will bind to the proteinbinding riboswitch to modulate the expression level of the enzyme; passing a current through the counter electrode, sample, and working electrode; detecting the current produced by an electrochemical reaction between the enzyme and substrate; and quantifying, based on said detecting, the concentration of the target protein in the biological sample.

[0100] In some embodiments, quantifying, based on said detecting, the concentration of the target protein in the biological sample involves comparing the current produced by the sample relative to one or more reference(s). The one or more reference(s) may include a control comprising a known amount of the target protein ( positive control) and / or a control comprising no target protein (negative control).[0101| The method may be carried out at temperatures from 4 to 50 degrees Celsius. In some embodiments, the method is carried out at room temperature.

[0102] Suitable electrodes are described supra. In some embodiments the test strip is operably linked to at least two electrodes. For example, the test strip may be operably linked to a working electrode and a counter electrode.

[0103] Suitable exemplary target proteins, biological samples, and reporter proteins are described in more detail infra.

[0104] In some embodiments of the methods according to the present disclosure, the biological sample is from a subject, e.g., a mammalian subject. Suitable mammalian subjects include, without limitation, humans, non-human primates, rodents, felines, and canines. In some embodiments, the biological sample is from a human subject.

[0105] In some embodiments of the methods according to the present disclosure, the biological sample is selected from the group consisting of blood, serum, saliva, sputum, plasma, cerebral spinal fluid, synovial fluid, urine, breast milk, and bile.

[0106] As described infra, the target protein may be a biomarker,

[0107] In some embodiments, the target protein is a human protein.

[0108] Suitable target proteins include, without limitation, monomeric C-reactive protein. interleukin-32 receptor, hemoglobin, angiotensin-con verting enzyme, anti-acetylcholine receptor antibody, adenosine deaminase, alpha-fetoprotein, pappalysin-1, aldolase A, alpha- 1 -antitrypsin, serum amyloid A-l protein, interleukin-2 receptor subunit alpha, mucin- 1, lysozyme C, aspartate transaminase, osteocalcin, undercarboxy Sated osteocalcin, N-terminal pro-B-type natriuretic peptide, gamma-glutamyltranspeptidase, antimitochondrial antibodies, antineutrophii cytoplasmic antibodies, anti-streptolysin antibodies, anti-DNaase B antibodies, anti-cyclic citrulliuated peptide, C -terminal telopeptide, N-terminal propeptide of type I procollagen, N- terminal telopeptide, anticardiolipin antibody, anti-beta2 glycoproteinl, muellerian-inhibiting factor, proinsulin C-peptide, perineuclear antineutrophil cytoplasmic antibodies, anti-dengue virus antibody, vascular endothelial growth factor, macrophage colony-stimulating factor 1 , amylase, lipoprotein lipase, antineutrophil cytoplasmic antibodies against proteinase 3, calprotectin, human epididymis protein 4, carbohydrate antigen 125, chromogranin-A, epstein- barr virus capsid antigen antibody, ceruloplasmin, anti -gliadin antibody IgA, p-selectin, sex hormone-binding globulin, des-gamma-carboxy prothrombin, hepatitis a virus cellular receptor 1, neutrophil gelatinase associated lipocalin, interleukin- 18, hepatocyte growth factor, cystatin- C, n-a.eetyl-beta-d~glucosanmiidase, chemokine interferon inducible protein 10, fibronectin, nuclear ribonucleoprotein I I I antibodies, anti-ribosomal P antibodies, hemoglobin subunit beta, glucose-6-phosphate 1 -dehydrogenase, gastrin, acetylcholinesterase, amyloid beta42, vasopressin-neurophysin 2-copeptin, apolipoprotein E, beta-2-microglobulin, bone specific alkaline phosphatase, brain natriuretic peptide, butyrylcholinesterase, ca 19-9 tumor marker, calcitonin, chymotrypsin, complement Cl, component C2, complement C3, complement C4, pancreatic elastase- 1 , ferritin, gammaglutamyl transferase (ggt), haptoglobin, hemoglobin, insulin, insulin-like growth factor I , interleukin-6, interferon gamma, lactate dehydrogenase,lactotrans ferrin, parathyroid hormone, adrenocorticotropic hormone, transglutaminase IgA antibody, renin, cardiac troponin T, cardiac troponin I, transthyretin, erythropoietin, thyroid stimulating hormone, thyroglobulin, prothrombin, tryptase, antithrombin, sex hormone binding globulin, apolipoprotein B- 100, von willebrand factor, apolipoprotein Al, Clostridium difficile glutamate dehydrogenase, transferrin receptor (soluble), estrogen receptor, progesterone receptor, fibrinogen, factor V, transferrin, follicle stimulating hormone, hemoglobin S, her2, human chorionic gonadotropin, human growth hormone, kappa / lambda light chains, lactoferrin, leptin, luteinizing hormone, myoglobin, tau protein, tartrate resistant acid phosphatase, procalcitonin, prolactin, prostate specific antigen, protein C, protein S, albumin, and alanine transaminase.[0109) In some embodiments, the target protein is selected form the group consisting of monomeric C-reactive protein and interleukin -32 gamma receptor.EXAMPLES

[0110] The examples below are intended to exemplify the practice of embodiments of the disclosure but are by no means intended to limit the scope thereof.MethodsConstructio n o f Ribas witch and Prole in- Expres sing Plasm ids

[0111] To construct riboswitch and CDS plasmids for this study, the pFTV I vector backbone was used, which contains mRFPl modified to contain an N-terminal Sad restriction site (Borujeni et al., “Translation Rate is Controlled by Coupled Trade-Offs between Site Accessibility, Selective RNA Unfolding and Sliding at Upstream Standby Sites,” Nucleic Acids Res. 42:2646-2659 (2014), which is hereby incorporated by reference in Its entirety). The Riboswitch Calculator was used to design candidate riboswitch sequences, and the Operon Calculator was used to codon-optimize the MS2 coat protein CDS and design an optimal RBS sequence (Borujeni et al., “Automated Physics-Based Design of Synthetic Riboswitches from Diverse RNA Aptamers,” Nucleic Acids Res 44:1 -13 (2016) and Halper et al., “An Automated Pipeline for Engineering Maiiy-Enzyme Pathways: Computational Sequence Design, Pathway Expression-Flux Mapping, and Scalable Pathway Optimization,” Methods Mol. Biol. 1671 :39-61 (2018), which is hereby incorporated by reference in its entirety). gBlocks, containing primer binding sites and additional restriction sites, and PCR primers for both the riboswitches and MS2 coat protein CDS were designed and ordered (Integrated DNA Technologies). The gBlocks were PCR amplified using Phusion or Q5 DNA polymerase (New England Biolabs). For theriboswitches, the riboswitch amplicons and pFTVl vector backbone were digested with Xbal and Sacl-I IF (New England Biolabs), For the MS2 coat protein CDS, the CDS amplicon and pFTVl vector backbone were digested with Xbal and Notl-HF (New England Biolabs). For both the riboswitches and CDS, the digested inserts were ligated with digested backbone using T4 DNA ligase (New England Biolabs) and heat-shock transformed the ligation product into chemically competent DH10B. Sanger sequencing was performed to verily that the insert had been cloned correctly.

[0112] C ’andidate MS2 riboswitch sequences are shown in Table 5 below'.Table 5. Candidate MS2 Riboswitch SequencesCrude Ceti Lysate Preparation|0113| Crude cell lysate was prepared using the following protocol (Sun et al., “Protocols for Implementing an Escherichia coli Based TX-TL Cell-Free Expression System for Synthetic Biology,” J. Pis. Exp. 16(79):e50762 (2013). which is hereby incorporated by reference in its entirety). 20 L of Esctiericitia coli BL21 with the Rosetta2 plasmid encoding rare tRNAs was cultured in a Micros 30-fitcr fermentor (New Brunswick) in 2XYT4'P medium until the cells reached an ODf® of 1.5-2.0. The cell pellet was then collected in a T-l-P Laboratory continuous flow centrifuge (Sharpies), and resuspended in 1 mL S30A buffer per gram of cell pellet. The resuspended cells were run through a M l I0-EH-30 microfluidizer (Microfluidics Corp.) at 20,000 PSI twice to ensure complete lysis. The lysate was clarified by centrifugation at 12,000xg for 30 minutes at 4°C. The clarified lysate was then incubated for 80 minutes at 37°C while undergoing orbital shaking to perform the runoff reaction. After incubation, the lysate was centrifuged again for at 12,000xg for 30 minutes at 4CC. Following lysis, clarification, and the runoff reaction, the lysate was diafiltered with a Pellicon Biomax 10 kDa MWCO 0.005 m2ultrafiltration module. Six retentate volumes of buffer S30B were run against the lysate at 4°C. After diafiltration, the retentate was centrifuged for 30 minutes at 12.000xg at 4°C. The protein concentration of the retentate was quantified using a Bradford BSA Protein Assay Kit assay (Bio-Rad). The retentate was aliquoted and flash-frozen in liquid nitrogen, and stored at ~80°C. Cell-Free Expression Reactions|0114] Cell-free expression reactions were assembled on ice using the following protocol (Sun et al., "Protocols for Implementing an Escherichia coli Based TX-TL Cell-Tree ExpressionSystem for Synthetic Biology,” / FA. Exp. l6(79):e50762 (2013) and Shin and Noireaux, “Efficient Cell-Free Expression with the Endogenous E. Coli RNA Polymerase and Sigma Factor 70,” J Biol. Eng. 24:4:8 (2010), which are hereby incorporated by reference in their entirety). Amino acid and energy solutions were prepared separately, and combined with crude cell extract to reach the following final concentrations: 7,4 mg / niL protein ( l / 3"!total reaction volume), 1.5 ni.M each amino acid (except for leucine at 1.25 mM), 50 mM HEPES, 1.5 mM ATP and GTP, 0.9 mM CTP and UTP, 0.2 mg / ml tRNA. 0.26 mM CoA, 0.33 mM NAD, 0.75 mM cAMP, 0.068 mM folinic acid, 1 mM putrescine, and 30 mM PEP, 4 mM additional magnesium glutamate (8,67 mM total ), 80 mM additional potassium glutamate (100 mM total), and 2% w / v PEG-8000 were added to each reaction. Plasmid DNA was either miniprepped and ethanol precipitated, or midiprepped and isopropanol precipitated, and added to the reaction to a final concentration of 2 nM. Where protein was directly added to the reaction, mCRP (R&D Systems) or !L-32y (Biotechne) was added at the specified concentration. 5 mL reactions were incubated at 29"C for 16 hours in a 96- well polypropylene conical bottom plate sealed with a plate storage mat (Corning) in a TEC AN Spark microplate reader. mRFPl fluorescence was measured every' 10 minutes, using 584nm / 607nm ex / em with a 5 nm bandwidth.Endpoint mRFPl Data Analysis

[0115] I he endpoint was taken as the average of the last approximately 15 mRFPl fluorescence data points of each reaction, during which active mRFP 1 produetion had ceased. mRFPl fluorescence was measured using an excitation wavelength of 575 nm and an emission wavelength of 620 nm. The following corrections were applied: the background for each reaction was calculated as the average of the first 15 data points, approximately, of each reaction, prior to the onset of mature mRFPl accumulation. Since, even in the absence of plasm id DNA, a slight increase in the fluorescence between the beginning and end of each reaction was observed, each reaction was also corrected for the non-specific fluorescence increase by performing the same endpoint fluorescent calculation as above on a no-DNA reaction, and subtracting that non-specific fluorescence increase.Design of Protein-Delecting Riboswitch Sequences using the Ribaswitch Calculator

[0116] Sequence and binding affinity for each aptamer used was obtained from the literature. Aptamer secondary structures were determined using RNAfold (Vienna RN A v2.5), using the Turner 2004 nearest-neighbor parameter set, with no dangling end free energies (Gruber et al,, “The Vienna RNA websuite,” Nucleic Acids Res. 36(Web Server Issue): W70-74(2008), which is hereby incorporated by reference in its entirety). To design the riboswitches, the design mode of the Riboswitch Calculator model of translation initiation regulation (Python v2.7 and v3.7.7), which builds on the RBS Calculator v2.1 model to predict translation initiation states of each riboswitch in the uninduced and induced states, was used (Borujeni et al, “Automated Physics-Based Design of Synthetic Riboswitches from Diverse RNA Aptamers,” M / cZefe Acids 7es . 44(1): 1-13 (2016) and Reis and Salis, “An Automated Model Test System for Systematic Development and Improvement of Gene Expression Models,” ACS Synth Biol.9(11):3145-3156 (2020), which are hereby incorporated by reference in their entirety). From the output list of riboswitch sequences, sequences were sub-selected based on their predicted maximum regulation ratios, and on- and off-state expression levels. Structural schematics were partly made using Foma diagrams (Kerpedjiev et al,, “Foma (Force- Directed RNA): Simple and Effective Online RNA Secondary Structure Diagrams,” Bioinformatics 31 (20):3377-3379 (2015), which is hereby incorporated by reference in its entirety).Alternate Constraint Analysis

[0117] To perform the alternate constraint analysis on the selected riboswitches, every possible aptamer substring was iterated through and the predicted Racuat for each substring was re-calculated. Briefly, for subconstraints i (first subconstrained nucleotide position) and j (last subconstrained nucleotide position), the aptamer subconstraint was refolded from position i to j using RNAfold as described above. The sequence from the beginning of the full aptamer constraint to i was then appended to the existing pre-aptamer sequence to generate a new preaptamer sequence, and prepended the sequence from the end of the subconstraint to the end of the full aptamer sequence to the existing post-aptamer sequence to generate a new post-aptamer sequence. With the new’ pre-aptamer, post-aptamer, and aptamer sequences and structural constraint, the predicted RactuaIwas calculated at maximum induction using the Riboswitch Calculator.Statistical Analysis10118] For pairwise comparisons, two-tailed, two-sample t~ tests were used. For determining correlations, linear regression was used to calculate the Pearson squared correlation coefficient (R2) and a hypothesis test to calculate the test statistic and p-value for the regression slope. For all tests, the significance level was set to a = 0.(15.Example 1 - Riboswitch Design and Characterization Platform101191 Novel protein-binding riboswitch sequences were created using a biophysical model of translation-regulating riboswitches, called the Riboswitch Calculator, which combines statistical thermodynamics with computational optimization to design synthetic riboswitches according to inputted specifications (Borujeni et al„ “Automated Physics-Based Design of Synthetic Riboswitches from Diverse RNA aptamers,” Afac / eic zka’cfc Res. 44(1): 1-13 (2016), which is hereby incorporated by reference in its entirety). The design specifications include: (i) the sequence of an RN A aptamer that binds to the protein of interest; (ii) the secondary structure of the RNA aptamer when it is bound by the protein; (ii i) the protein ’s binding free energy (or binding affinity) to the RNA aptamer; and (iv) the coding sequence of the protein whose expression level is regulated by the riboswitch (FIG. 1 A). The Riboswitch Calculator then identifies synthetic pre- aptamer and post-aptamer sequences that maximize the riboswitch’s dynamic range, utilizing a genetic algorithm to carry out computational multi-objective sequence optimization. Exemplary MS2 pre-aptamer and MS2 post-aptamer sequences are shown in Table 5 preceding or following the MS2 aptamer sequence, respectively. Together, these pre- aptamer and post-aptamer sequences vary in length from 44 to 55 nucleotides, creating an overall searchable sequence space of 1026to 10J3sequences. When designing riboswitches that activate translation (ON switches), the activation ratio is Rmax::::TIRbowki / TIRuaboutwi, "where TIRswUW<i and TIRunbouna are the mRNA’s translation initiation rates in the protein-bound and unbound states, respectively. When designing riboswitches that repress the translation rate (OFF switches), the repression ratio is Rmsx ~ TIRmbowrf / TIRbotsnd. Multiple equally optimal riboswitch sequences are plausible. The Riboswitch Calculator identifies the Pareto-optimal set of synthetic riboswitch sequences that are all predicted to maximize Rnm with varying magnitudes of 1 IRbound and I IR«nj><>u«d-10120 J To do this, the Riboswitch Calculator uses a statistical thermodynamic model, called the RBS Calculator, to calculate the interaction energies between the ribosome and mRNA that control its translation initiation rate (Reis and Salts, “An Automated Model Test System for Systematic Development and Improvement of Gene Expression Models,” JCS 'Synth Bio / , 9(1 1 ):3145-3156 (2020) and Borujeni et al., “Translation Rate is Controlled by Coupled Trade- Offs between Site Accessibility, Selective RNA Unfolding and Sliding at Upstream Standby Sites,” Muc / eic Jdrfc Res. 42:2646-2659 (2014), which are hereby incorporated by reference in their entirety). The strengths of these interactions are determined by a 5 -term Gibbs free energy model, including (i) conformational distortions when ribosomes initially bind to upstreamstandby sites in the mRNA; (ii) hybridization between the last 9 nucleotides of the 16S rRNA and the mRNA at the Shine- Dalgarno sequence; (iii) the unfolding of inhibitory mRNA structures that overlap with the ribosome’s footprint, spanning the region from the 5’ end of the Shine-Da! garno sequence to 13 nucleotides past the start codon; (i v) base pairing between the start codon and the initiating tRNA^161; and (v) ribosomal stretching or compression due to non- optimal spacer sequences between the Shine- Dalgarno and start codon. The overall result is the binding free energy of the ribosome to the mRNA (DGtomi). By convention, a stronger interaction is denoted by a more negative binding tree energy. According to Boltzmann’s relationship, the mRNA's translation initiation rate is proportional to exp(-b DGtoui), where beta is a constant that relates free energies to state probabilities (Reis and Salis, “An Automated Model Test System for Systematic Development and Improvement of Gene Expression Models,” JCS SyntA Riol. 9(11):3145-3156 (2020), which is hereby incorporated by reference in its entirety).(01211 To predict riboswitch function, the Riboswitch Calculator carries out free energy calculations on the protein-bound and unbound states of the mRNA (DGtoEai.sound and DGioMunbwwd). hi the unbound state, the RNA aptamer is indistinguishable from other parts of the mRNA and is allowed to form any secondary structure as part of the overall tree energy minimization procedure, which utilizes the ViennaRNA suite of RNA folding algorithms (Gruber et al., “The Vienna RNA websuite,” Nucleic Acids Res. 36(Web Server Issue):W70-74 (2008), which is hereby incorporated by reference in its entirety). In the protein-bound state, the RNA aptamer is locked into its protein-bound structure, which can alter the accessibility of the standby site, the folding free energies of inhibitory mRNA structures, and the overall binding free energy of the ribosome to the mRNA. The switching free energy is also calculated to determine the thermodynamic stability of the protein-bound state, using the protein’s binding free energy to the RNA aptamer (DGifgana). The model predicts that the maximum fold-change in the mRNA’s translation rate is exp(-b [DGwiarbomi - DGtotarurtmjKi]) when the protein-bound state is stable and when an excess amount of protein is added. Riboswitch Calculator predictions were previously applied to engineer 62 synthetic riboswitches that detected a variety of small molecules (theophylline, tetramethylrosamineluoride, dopamine, thyroxine, 2,4-dinitrotoluene) and activated a protein reporter’s translation rate by up to 383-fold (Borujeni et al., “Automated Physics-Based Design of Synthetic Riboswitches from Diverse RNA aptamers,” Nucleic Adds Res. 44(1): 1-13 (2016), which is hereby incorporated by reference in its entirety). However, themodel has not yet been applied to convert protein-binding RNA aptamers into cell-free biosensors.|0122] Riboswitch function was characterized using the cell-free TX-TL expression system (Sun et al., ‘‘Protocols for Implementing an Escherichia coli Based TX-TL Cell-Free Expression System for Synthetic Biology,” J. PZs. Exp. 16(79):e50762 (2013 ), which is hereby incorporated by reference in its entirety), adding plasmid-encoded genetic circuits that utilize each riboswitch to regulate the expression of the mRFP I fluorescent protein reporter. Two different approaches were used to add varying concentrations of protein ligand to the cell-free expression system: (i) co-expression or (i i) co-addition. For co-expression, varying amounts of a second expression plasmid were added to the cell-free expression system to constitutively produce the protein-of-interest. For co-addition, the purified protein-of- interest was directed to the cell-free expression system. mRFPl fluorescence levels were measured every 10 minutes using spectrophotometry (TECAN Spark), followed by endpoint analysis to quantify the overall change in reporter expression levels (FIG. I B).

[0123] Prior work has demonstrated that gene expression in both the cellular and cell- free context is sensitive to added components or additional genetic load (Cai et al., “A Simplified and Robust Protocol for Immunoglobulin Expression in Escherichia coli Cell-Free Protein Synthesis Systems,” Biotec / inol. Frog. 31(3):823-831 (2015); Kai et al., “Artificial Environments for the Co-Translational Stabilization of Cell-Free Expressed Proteins.” FLoS One 8(2):e56637 (2013 ); Shin and Noireaux, “Efficient Cell-Free Expression with the Endogenous E. Coli RNA Polymerase and Sigma Factor 70,” J. Biol. Eng. 24:4:8 (2010); Siegal- Gaskins et al., “Gene Circuit Performance Characterization and Resource Usage in a Cell-Free "Breadboard'h”zlCSSy»r / j. Biol. 3(6):416-425 (2014); Takahashi et al., “Rapidly Characterizing the Fast Dynamics of RNA Genetic Circuitry with Cell-Free Transcription-Translation (TX-TL) Systems,” .4C5 Synth. Biol. 4(5):503-515 (2015); and Vezeau and Salis, “Tuning Cell-Free Composition Controls the Time Delay, Dynamics, and Productivity of TX-TL Expression,” ACS Synth. Biol. I0(10):2508-2519 (2021), which are hereby incorporated by reference in their entirety ). Two types of controls were carried out to eliminate such confounding factors. In the first set of no-mRFPl controls, red fluorescence levels were measured without any mRFPl expression to quantify the autofluorescence of the cell- free assay and protein ligands. During endpoint analysis, no-mRFPl autofluorescence was subtracted from all measurements. In the second set of no-aptamer controls, red fluorescence levels were measured from a genetic circuit that expresses mRFPl using a standard 5’ UTR without any protein-binding aptamer (UTR-136,Borujem et a!., “Translation Rate is Controlled by Coupled Trade-Offs between Site Accessibility, Selective RN A Unfolding and Sliding at Upstream Standby Sites,” Nucleic Acids Res. 42:2646-2659 (2014), which is hereby incorporated by reference in its entirety). According io the RBS Calculator v2. 1 model, UTR-136 binds to the ribosome with a moderately high translation initiation rate (36400 au or DGmi ~ -7.52 kcal / mol). The purpose of this no-aptamer control is to measure any non-specific changes in red fluorescence levels when co-expressing or co-adding a protein ligand at varying concentrations. If non-specific activation or repression is detected from the no-aptamer control, this confounding factor is removed by dividing the riboswitch’s measured activation or repression ratio by the no-aptamer control’s activation or repression ratio, respectively (FIG . 1 C). If these riboswitch sensors are to be used as sensors in a future device, it would be expected that the same controls would be performed on die device, in parallel, to carry out these same measurements and analysis.Example 2 - Design and Characterization of MS2, mCRP, and IL32y RiboswitchSensors(0124J For the first proof-of-principle example, riboswitches were engineered to detect the phage MS2 coat protein, utilizing an RNA aptamer that folds into a well-defined hairpin structure and binds to MS2 protein with very high affinity (IQ:::0.7 nM) (Valegard et al., “Crystal Structure of an RNA Bacteriophage Coat Protein-Operator Complex,” Nature 371(6498):623-626 (1994) and Lowary and Uhlenbeck, “An RN A Mutation that Increases the Affinity of an RNA -Protein Interaction,” Nucleic Acids Res. 15(24): 10483- 10493 (1987), which are hereby incorporated by reference in their entirety) (FIG. 2A). Two medically relevant protein biomarkers were then selected and riboswitches were engineered to detect changes in the levels of monomeric C-reactive protein (mCRP) and interleukin-32 gamma (IL-32y). CRP is found in human plasma and natively forms a homopentameric complex, but will irreversibly dissociate into its monomeric form during a pro-inflammatory response (c.g., tissue damage, heart disease, cancer, or bacterial infection) (Sproston and Ashworth, “Role of C-Reactive Protein at Sites of Inflammation and Infection,” Front. Immunol. 13:9:754 (2018) and Black et al, “C-reactive Protein,” J. Biol. Chem. 279(47):48487-48490 (2(304), which are hereby incorporated by reference in their entirety ). A mCRP concentration of I 0 mg- L (430 nM) is considered elevated and, depending on the disease severity, mCRP concentrations can readily exceed 100 mg / L (4,3 mM). To develop mCRP-scnsing riboswitches, a hairpin RNA aptamer that binds specifically to the monomeric form of CRP (mCRP) with high affinity (Kti::::187.7nM) and does not bind to pentameric CRP ( Wang et al,, “C-Reactive Protein (CRP) Aptamer Binds to Monomeric but not Pentameric form of CRP,” Anal. Biaanal. Chem. 401 (4): 1309- 1318 (201 1), which is hereby incorporated by reference in its entirety) was harnessed. IL-32 is a cytokine that regulates the NF-KB pathway and acts during early host defense against pathogen infections (Heinhuis et al., “Interleukin-32: A Predominantly Intracellular Proinflammatory Mediator that Controls Cell Activation and Cell Death.” Cytokine 60(2):321-327 (2012); El-Far et al., “Proinflammatory Isoforms of IL-32 as Novel and Robust Biomarkers for Control Failure in HIV-Infected Slow Progressors,” Sai. Rep. 15:6:22902 (2016); and Gui et al,, “Clinical Significance of Intcrleukin-32 Expression in Patients with Rheumatoid Arthritis,” Asian Pac. J. Allergy Immunol. 31 (I):73-78 (2013), which are hereby incorporated by reference in their entirety). IL-32? is the longest and most pro-inflammatory isoform of IL-32. Elevated levels of IL-32? in human serum have been found to be associated with heart, failure, COPD, and multiple myeloma (Xin et al., “Interleukin-32: Its Role in Asthma and Potential as a Therapeutic Agent,” Respir. AW 19( 1): 124 (2018), which is hereby incorporated by reference in its entirety) (up to around 61 pM or 1.6 ng / ml). To develop IL-32? sensing riboswitches, a highly structured RNA aptamer that binds specifically to the gamma isoform with a high affinity (IQ ~ 78 nM) (Kim ct al., “Generation of Antagonistic RNA Aptamers Specific to Proinflammatory Cytokine Interleukin-32,” AWZ. Korean Chem. Sac. 31(12):3561 -3566 (2010), which is hereby incorporated by reference in its entirety) was used. Altogether, 30 riboswitches were initially designed, constructed, and characterized to detect MS2, mCRP, and IL-32? protein, including ON switches that activated mRFPl expression and OFF switches that repressed mRFPl expression (FIG. 2A). Sequences, model calculations, experimental & control measurements, and statistical significance tests (two-tailed t-tests with unequal variances) are shown in FIGS. 10A-10F and Tables 6-8 below.Table 6. Aptamer Structure and Binding AffinityTable 7. Aptamer StructureTable 8. Aptamer Characterization101251 Five MS2-sensing riboswitches were first designed to activate mRFPl expression (ON switches) and carried out TX-TL assays using the co-expression approach to produce the MS2 protein. When adding 8 nM pFTV1 -MS2, the designed MS2-sensing ON switches all increased mRFPl fluorescence levels by significant amounts (between 10.8 to 27-fold). The same measurements were carried out using a no-aptamer control and it was found that coexpression of MS2 non-specifically increased mRFPl fluorescence levels increased by 1.9-fold (Tables 9 and 10 below). The no-aptamer control measurement was then used to remove the non-specific effect of MS2 on mRFPl expression. After removing the non-specific effect, it was found that all five MS2-sensing ON switches activated mRFPl expression by between 5.5 to 13.8-fold (FIG. 213). These results show that the Riboswitch Calculator was able to design MS2- sensing ON switches that significantly activated output protein expression with the highest activated ratios reported to date, compared to prior efforts (Katz et al., “Synthetic 5' UTRs Can Either Up- or Downregulate Expression upon RNA-Binding Protein Binding,” Cell Syst. 9(1):93- 106 el 08 (2019), which is hereby incorporated by reference in its entirety), though the dynamic ranges varied across the small number of designs tested.10126] Ten MS2-sensing riboswitches were then designed and tested to repress mRFPl expression (OFF switches), now adding 16 nM pF TV1-MS2 plasmid to the cell-free expression system as translation -repressing riboswitches are predicted to require higher proteinconcentrations to achieve a similar fold-change in output as compared to translation-activating riboswitches. Under the same conditions, the no-aptamer control increased mRFPl fluorescence levels by 2.3-fold. In this scenario, a non-iunctional OFF switch would also cause mRFPl fluorescence levels to increase by 2.3 -fold, due to this non-specific effect. Instead, it was found that adding 16 nM pFTVl-MS2 plasmid caused all of the 10 MS2-sensing OFF switches to produce reduced mRFPl fluorescence levels. After removing the non-specific effect, it was found that their repression ratios varied from 2.5 to 5.3-fold (FIG. 2C). These results show that the Riboswitch Calculator can design MS2~sensing OFF switches by simply flipping its objective function during sequence optimization, while utilizing the same biophysical calculations.101271 Ten mCRP-sensing riboswitches were next designed and characterized for their ability to repress mRFPl expression (OFF switches). Initially, 16 nM of a plasmid expressing mCRP was added (co-expression), but no significant change in mRFPl regulation was observed. Instead, when 1250 nM of purified mCRP was directly added (co-addition), it was found that the OFF switches decreased mRFPl fluorescence levels by up to 6,7-fold. As the purified mCRP was produced using HEK 293 cells, it is possible that chaperone-assisted protein folding or glycosylation is needed to produce a mCRP that binds to the RNA aptamer. Similar to the MS2 protein, it was found from no-aptamer controls that the addition of .1250 nM mCRP non- specifically activated mRFPl expression by about 2.3-fold (Tables 9 and 10). Once this nonspecific effect was removed, it was found that 90% of the mCRP-sensing OFF switches successfully repressed mRFPl expression with repression ratios from 2.8 -fold to 15.9-fold (FIG. 2D).[01281 Finally, five IL32y-sensing riboswitches were desgined and characterized for their ability to repress mRFPl expression (OFF switches). 780 nM of purified I L32y was directly added to the cell-free expression system (co-addition). Using no-aptamer controls, no significant non-specific effect on mRFPl expression levels was found (Tables 9 and 10), precluding the need to remove any non-specific effect. After characterizing the OFF switches, it was found that 4 out of the 5 riboswitches were able to significantly repress mRFPl fluorescence levels from 1.4 to 2.5-fold (FIG. 21:i). These results show that the Riboswitch Calculator was able to harness RNA aptamers that bind to human protein biomarkers to successfully design translationrepressing riboswitclies.Table 9Table 10Example 3 ~ Structural and Energetic Contributions to Riboswitch Function|0129] The mechanisms resposible for riboswitch function were investi gated to explain how protein binding to an aptamer domain can cause the riboswitch’s translation rate to be eitheractivated or repressed. As examples, an MS2-binding ON switch (M2 riboswiich) and an MS2- binding OFF switch (M7o riboswitch) were focused on, applying the Riboswitch Calculator model’s structural and thermodynamic calculations to visualize and quantify the process (Borujeni et aL, “Automated Physics-Based Design of Synthetic Riboswitches from Diverse RNA aptamers,” AucZefc Acids 7?es. 44( 1 ): I - 13 (2016), which is hereby incorporated by reference in its entirety). In FIG. 3A, the sequence, structure, and interactions of the M2 riboswitch in its free state (state 1 ) and in its ribosome-bound state (state 2) in the absence of the MS2 protein are shown. Before the ribosome has bound, the riboswitch mRNA is predicted to fold into a stable structure where the aptamer domain and Shine-Dalgarno (SD) sequence are both partly sequestered by base pairing. After the ribosome has bound to form a pre-initiation complex, there are significant structural re-arrangements, including unfolding an inhibitory structure within the N-terminal CDS region (Reis and Salts, “An Automated Model Test System for Systematic Development and Improvement of Gene Expression Models,” J CS Synth Biol. 9(11 ):3145-3156 (2020) and Borujeni et al., “Precise Quantification of Translation Inhibition by mRNA Structures that Overlap with the Ribosomal Footprint in N-Terniinal Coding Sequences,” Nucleic Acids Res. 45:5437-5448 (2017), which are hereby incorporated by reference in their entirety). While the structures provide visual cues, the ribosome’s ability to bind to the mRNA and initiate translation rate are actually controlled by the difference in Gibbs free energy between the initial and final states. In the absence of MS2, this difference is -3.7 kcal / mol.101301 The mRNA’s structure and ribosomal interactions are altered when the riboswitch is bound by MS2. When MS2 binds to its aptamer domain, the model predicts a substantial refolding of the 5’ UTR, almost completely exposing the SD sequence and creating a highly accessible standby site for ribosome binding (FIG. 3A, state 3). This structural re-arrangement requires an input of at least 5.2 kcal / mol energy to push the transition forward, which is provided by the -13.2 kcal / mol energy released when MS2 binds to its aptamer domain. The MS2-bound mRNA can now bind to the ribosome to form a more stable pre-initiation complex (FIG. 3 A, state 4) with a more negative binding free energy (-8.1 kcal / mol), leading to activation of translation rate. Like all models, the calculations provide a simplified version of reality that nonetheless enable riboswitch prediction and design. For example, the model considers only the four most predominant states of the riboswitch, though there exists an ensemble of states with varied mRN A structures and MS2 binding occupancies. Notably, MS2 binds to its aptamer while the mRN A is being transcribed, which can eliminate kinetic traps.[0l31| The mechanism of an OFF switch was next focused on, illustrating how MS? binding triggers refolding of the mRNA to make it more energetically unfavorable for the ribosome to bind. In the absence of MS2, the model predicts that the initial state of the M7o riboswitch folds into highly stable mRN A structures that sequester the aptamer domain and the SD sequence (FIG. 3B, state I). This mRNA structure does not favorably bind to the ribosome (2.8 kcal mol), particularly due to the short distance between the SD and start codon and the presence of mRNA structures that lower the accessibility of the standby site (FIG. 3B, state 2). However, once MS2 binds to the mRNA, the model predicts that the mRNA will bind even less favorably to the ribosome, due to a reconfiguring of both the initial and final mRNA states (FIG. 3B, states 3 and 4), The MS2~bound mRNA contains a highly stable structure that occludes the ribosome’s standby site (Borujeni et al., “Translation Rate is Controlled by Coupled Trade-Offs between Site Accessibility. Selective RNA Unfolding and Sliding at Upstream Standby Sites,” Nucleic Acids Res. 42:2646-2659 (2014), which is hereby incorporated by reference in its entirety) and adds a penalty of 3 kcal / mol to the ribosome’s total binding free energy (6.2 kcal. mol). Overall, using the model, a quantitative understanding of how MS? binds to the aptamer domain and causes large-scale re-arrangements in the riboswitch’s mRNA structure to control ribosome binding free energies and translation initiation rates can be achieved.Example 4 - Dose-response Characterization of Designed Riboswitch Sensors[0132| High-functioning riboswitches (M2, C5, and 12) were selected, and the effect of systematically increasing the MS2, mCRP, and IL32y concentrations on their output expression levels (dose response) was measured in comparison to the no-aptamer control (UTR-136). Measurements and statistical tests are shown in Tables 1 1-13 below. The cell-free expression system was reconfirmed to have sufficient capacity to express large amounts of mRFPl in proportion to the mRFPl expression plasmid across a wide range (0 to 32 nM plasmid added) (FIG. 7). The dose response of the M2 riboswitch was characterized by keeping the riboswitch plasmid concentration constant and systematically increasing the concentration of the MS2 expression plasmid from 0 to 16 nM. The M2 riboswitch activated mRFPl fluorescence levels with a dose-dependent sigmoidal behavior, increasing mRFPl expression levels by up to 26.6- fold (FIG. 4A). Under the same conditions, the mRFPl fluorescence levels from the no-aptamer control increased by up to 1.86-fold. When correcting for this non-specific effect, the M5 riboswitch activated mRFPl expression levels by 15.9-fold. Activation of mRFPl expression was detectable with statistical significance (p::::0.0008, two-tailed t-test) using only 0,5 nM ofexpression plasmid. These results confirm the expected sigmoidal dose response for a translation-activating riboswitch, consistent with previously engineered riboswitches (Borujeni et al., “Automated Physics-Based Design of Synthetic Riboswitches from Diverse RNA aptamers,” Nucleic Acids Res. 44(1 ): 1-13 (2016), which is hereby incorporated by reference in its entirety). [01331 The same dose response characterization was carried out on the C5 riboswitch, directly adding up to 2500 nM of purified mCRP to cell-free assays. The C5 riboswitch lowered mRFPl fluorescence levels by 1.74-fold at 1250 n.M mCRP and by 237-fold at 2500 nM mCRP (FIG. 4B). However, the no-aptamer control exhibited a non-linear dosage response such that mRFPl fluorescence levels were non-specifically increased by 2.37-fold at 1250 nM mCRP and non-specifically decreased by 11-fold at 2500 nM mCRP. Based on these measurements, mCRP non-specifically activates mRFPl expression at lower concentrations, but then interferes with cell-free expression at higher concentrations. After taking into account these non-specific effects, the C5 riboswitch was found to repress mRFPl expression by 4.1-fold at 1250 nM mCRP and by 21 .5 -fold at 2500 nM mCRP, though the interference with the cell-free assay at 2500 nM mCRP substantially increased the variability of the measurement. Repression was detectable with statistical signifance at 156 nM mCRP, which is the the lowest tested concentration above zero (p ~ 0.0005, two-tailed t-test), while half-maximal repression was achieved at 403 nM mCRP. These results show that the C5 riboswitch is sensitive enough to detect and quantify mCRP concentrations across the physiological range from normal levels (100 to 430 nM) to elevated levels (above 430 nM), though levels above 2500 n.M will inhibit cell- free expression.

[0134] T he same cell-free assays were repeated using the 12 riboswitch, directly adding up to 780 nM of purified IL32y. The 12 riboswitch lowered mRFPl fluorescence levels by 2.6- fold at the highest IL32y concentration (FIG. 4C). In comparison, the no-aptamer control exhibited non-specific repression of only 1 .09-fold, which was statistically indistinguishable from the baseline (p -- 0. 18, two-tailed t-test). Using the 12 riboswitch, repression of mRFP l expression levels was detectable with statistical signiflance at a concentration of 195 nM IL32y with half-maximal repression taking place at about 548 nM IL32y (p = 0.015, two-tailed t-test). However, using the current I1..32y aptamer (Ku = 78 nM), the 12 riboswitch could not sense IL32y levels within the picomolar range, which would be needed to distinguish between normal and elevated levels in human serum.Table 11Table 12Table 13Inducer - recombinant hCRP (Enzo Scientific) (batch 1)Example 5 - Translation Repression by Steric Hindrance and Structural Switching[0135J The mechanisms responsible for protein- induced translational repression were investigated with the goal of distinguishing between two types of interactions. When a proteinbinds specifically io the aptamer region of the mRNA, translational repression could be exerted by steric hindrance alone; a stably bound protein could prevent the 30S ribosomal subunit from associating with the mRNA, for example, at upstream standby sites, or it could block the 30S ribosomal subunit’s 16S rRNA from hybridizing to the Shine-Dalgarno (SD) sequence to form a stable ternary complex. As a second mechanism, when a protein binds specifically to the aptamer region, it can induce changes in the mRNA structure, including the formation or removal of inhibitory mRNA structures that the ribosome must unfold prior to initiating translation. These mechanisms are layered on top of any non-specific interactions when adding protein to the cell-free system. Using a learn-by -design approach to distinguish these mechanisms, several niCRP-binding riboswitches that employ either the first mechanism alone (‘‘steric s witches”) or a combination of both mechanisms together (“OFF switches”) were designed and characterized alongside no-aptamer controls that measure the effects of nonspecific interactions. For these experiments, a second batch of purified mCRP was used that, through comparative testing on the same riboswitch (CIO), exhibited about 4.1 -fold less activity, though the cell-free composition remained the same (Tables 14-16).Table 14.*recombinant hCRP (Enzo Scientific) (batch 2)Table 15.^recombinant hCRP (Enzo Scientific) (batch 2)Table 16.^recombinant hCRP (Enzo Scientific) (batch 2)I0136J For the steric switch designs, the mCRP-binding aptamer was inserted upstream of a consensus SD sequence at varying distances (0 to 20 nt upstream of the 5’ end of the SD sequence). The pre-aptamer and post-aptamer were also designed so that the mRNA’s structure remained the same in both the free and mCRP-bound states, eliminating the second mechanism as a source of translation regulation (FIG . 5 A). The regulations of mRFPl expression levels by these riboswitches was then characterized, adding either 0 or 1250 nM mCRP. Placing the mCRP-binding aptamer directly upstream of the SD sequence lowered mRFPl fluorescence levels by 3.2-fold. After using no-aptamer controls to remove the effect of the non-specific interactions (1250 nM mCRP activated mRFPl fluorescence levels by 1 .65-fold), it was found that specific binding of mCRP repressed mRFPl expression by 5.3-fold, showing that steric hindrance alone is greatly contributing to protein- induced translational repression (FIG. 513). When the aptamer was placed farther upstream of the SD sequence (5 or 20 nt), mRFPl expression was repressed by smaller, but similar magnitudes, of 3.0 and 3.4-fold, respectively, again removing the non-specific interactions’ contributions. These results show that steric hindrance can repress translation even when the aptamer is farther from the SD sequence.|0137] In the second set of OFF switch designs, the Riboswitch Calculator algorithm was applied to design 5 additional mCRP-binding riboswitches (Col to Co5), while varying the distance between the aptamer region and the SD-like sequence from 4 to 13 nt. mRFPl expression levels were repressed by 3.2 to 13.6-fold (FIG. 5C), while taking into account the noaptamer controls. Two of the OFF switches (Col, Co2) had repression ratios far greater than the steric switches, showing that some of the designed riboswitches are utilizing both mechanisms to regulate translation rate. Overall, these results show that translation repression can take place by either steric inhibition alone or through a combination of both steric inhibition and protein- induced structural re-arrangements that block ribosome binding.Example 6 - Accuracy Analysis and Improvement by Modifying Aptamer Structural Constraints

[0138] The Riboswitch Calculator's model accuracy for protein-sensing riboswitches was critically analyzed. The analysis first considered the riboswitches ‘ OFF states where no protein ligand is added. The Riboswitch Calculator predicts how well the ribosome binds to the mRNA as quantified by a change in binding free energy (AGwtai), which is expected to be related io the mRNA’s translation initiation rate according to the log-linear Boltzmann relationship. Theriboswitches’ model-predicted AGtmai free energies to the natural logarithm of the end-point niRFPl expression levels, revealing statistically significant and quantitative agreement0.47, p=5.8xl(f<’, N = 34) (FIG. 8). However, the expected dynamic range in translation rates was compacted in TX-TL assays as compared to equivalent in viva assays. In other words, changing the ribosome’s binding free energy to a mRNA had a smaller than expected effect on its translation rate. Quantitatively, the apparent Boltzmann factor for these TX-TL assays was p -- 0.23 as compared to p ™ 0.45 in equivalent in vivo assays. This phenomenon has been previously observed in prior comparisons between cell-free and in vivo assays ( Vezeau and Salis, ‘Tuning Cell-Free Composition Controls the Time Delay, Dynamics, and Productivity of TX-TL Expression,” ACS Synth. Biol, 10( 10):2508-2519 (2021 ): Moore et al., '‘Rapid Acquisition and Model-Based Analysis of Cell-Free Transcription- Translation Reactions from Nonmodel Bacteria,” PNAS I 15(19):E4340-E4349 (2018); and Underwood et al., “Quantitative Polysome Analysis Identifies Limitations in Bacterial Cell-Free Protein Synthesis,” BiotechnoL Bioeng. 91(4):425-435 (2005), which are hereby incorporated by reference in their entirety).

[0139] The Riboswitch Calculator’s ability to predict the activation or repression of mRFPl expression levels was analyzed using three related calculations (Borujeni et ah, “Automated Physics-Based Design of Synthetic Riboswitches from Diverse RNA aptamers,” Nucleic Acids Res. 44(1); 1-13 (2016), which is hereby incorporated by reference in its entirety): R«iax, Rome, and Ractat. Rmsx is the maximum possible fold-change in translation rate when an excess amount of protein is added and 100% of the riboswitch is bound by protein, while RCOT!<; is the fold-change in translation rate when a specified concentration of protein is added. Racw is an extension of the Rcoae calculation that additionally takes into account the thermodynamic stability of the riboswitch’s protein-bound state; if the protein’s binding free energy is insufficient to stabilize that state, the riboswitch can spontaneously transition back to its free state. The Rmax and RCOBC calculations make simplifying assumptions whereas the Raceuaj calculation is the most complete version of the current model. In the first comparison, the Rsnax prediction had a measurable, but weaker, correlation with the measured activation or repression ratios (R2~ 0.38, p ~ 9.3xl0'9, N ~ 34, linear regression) with only 15% of riboswitch variants regulating expression levels to within 2-fold of the predicted ratios (FIG. 6A). However, when the proteins’ concentrations are considered using the RCot1cprediction, the model more accurately predicted the riboswitches’ activation or repression ratios (R2 ::::0.46, p::::1 x10" , N:::34, linear regression) with 38% of variants regulating expression to within 2-fold of the predicted ratio (FIG. 6B). Finally, using the RacUi&i prediction to account for differences in the proteins’ bindingfree energies to their respective RNA aptamers, the model accuracy increased even further (R2~ 0.48, p:::4.7x 1 O'6, N:::34, linear regression) with 44% of the riboswitch variants falling within the 2-fold tolerance (FIG. 6C).

[0140] A key input into the model calculations is the mRNA structure of the aptamer region when it is bound to the protein. When calculating the translation initiation rate of the riboswitch’s protein-bound state, this mRNA structure is “locked” into place, referred to as the aptamer structural constraint. In initial model predictions, the aptamer region was extracted from the studies that developed it and it was assumed that the entire region is important to protein binding. However, it is possible that only a portion of the aptamer binds to its protein. For example, only 13 nucleotides of the 19-nt long MS2 aptamer are fully resolved in a crystal structure of the aptamer in complex with a MS2 coat protein dimer ((Valegard et al,, '‘Crystal Structure of an RNA Bacteriophage Coat Protein -Operator Complex.” Nature 371(6498):623- 626 (1994), which is hereby incorporated by reference in its entirety ). Considering that the mCRP and IL32y aptamers have longer sequences (44-nt and 90-nt, respectively), it is likely that only a portion of these aptamers is truly “locked” into place when bound by protein.10141] The impact of changing the aptamer structural constraint on the moder s calculations and its predictive accuracy were investigated. The portion of the aptamer region that is “locked” in the protein-bound state was systematically varied, leaving a shorter contiguous region (FIG. 6D). For each of these shorter ap tamer subregions, its mRNA structure was recalculated and used as the aptamer’s structural constraint. Here, any flanking unpaired nucleotides were left as unconstrained positions (dots) in the structural constraint, allowing them to refold with adjacent mRN A regions in the riboswitch’s protein-bound state. The model Kactuai calculations were then repeated. Throughout, all other riboswitch sequences and model parameters remain the same. Overall, changing the aptamer structural constraint varied the model’s predicted Racial by up to 385-fold with a very rugged response surface, indicating that small changes to this input could have large effects on the model’s predictions (FIG. 6D, FIGS.9 A - 9D). The structural constraint for the mCRP and IL32y aptamers that achieved the highest overall model accuracy across all riboswitches was identified. Higher model accuracies were achieved by allowing more of the 5’ portion of the mCRP aptamer to freely Ibid and by only “locking” a single bulged haitpin structure of the IL32y aptamer. When inputting these aptamer structural constraints into the model), overall accuracy greatly improved (R2 :::0.64, p:::1.2xl.O"8, N ~ 34, linear regression) with 56% of the riboswitch variants achieving less than 2-fold prediction error (FIG. 6E). Altogether, this analysis shows that accurately predicting riboswitchfunction requires correctly inputting the concentration of the protein ligand, the binding free energy of the protein to its respective aptamer, and the actual aptamer structure that becomes “locked” when in its protein-bound state.Discussion of Examples 1 610142 J 35 protein-sensing ribos witches were engineered to operate within cell-free expression assays, demonstrating an automated model-predictive workflow for converting protein-binding RNA aptamers into high-performance sensors with potential medical diagnostic applications. As demonstrations of this approach, sensors were developed for two human biomarkers previously used as serum-accessible proxies tor cardiovascular disease, pro- inflammatory conditions, and pathogen infection -- monomeric C-reactive protein and interl eukin-32y protein. As RN A aptamers can be developed to bind many proteins of interest, this design platform provides a reliable and versatile route to developing larger toolboxes of protein diagnostic assays using a variety of low-cost input and output formats.(01431 I hese genetically encoded protein sensors were designed using a forward engineering approach, applying our Riboswitch Calculator algorithm to predict the riboswitches’ sequence-structure-fonetion relationship and computationally optimizing riboswitch sequences towards maximum translation activation or repression. The use of computational design enabled the reduction of the large riboswitch sequence space to just a few designs that have a high chance of success. This approach yielded protein-sensing riboswitches with high activation or repression ratios - 13.9-fold. 15.9, and 2.6-fold when detecting the MS2, mCRP, and IL-32y proteins, respectively - at protein concentrations within the relevant physiological range.Notably, the biophysical model equations and parameters were fixed and constant throughout this study, demonstrating that a quantitative & predictive knowledge of biophysics from one realm can be applied to solve challenges in another realm widiout requiring new training or validation datasets,(0'144] Key determ inants of protein-sensing riboswitch function were also investigated and two distinct mechanisms responsible for translation regulation were identified. MS2-binding riboswitches were engineered to act as either ON and OFF switches and their pre-aptamer and post-aptamer sequences were changed to show that protein -induced changes to mRNA structure can be harnessed for either translation activation or repression. However, when designing mCRP-sensing OFF switches, it was found that steric hindrance alone could explain how mCRP could bind, block the ribosome binding site, and repress translation rate. While it was possible toengineer mCRP OFF switches that combined both steric inhibition and protein-induced structural inhibition at the same time to repress translation rate, engineering mCRP ON switches was not successful after testing a small number of candidate designs. In practice, when developing a new protein-sensing riboswitch, it is worthwhile to design both ON and OFF switches to best determine how each protein interacts with the ribosome and whether stcric inhibition plays an overriding role.(0'145] With this automated platform, it is now feasible to design large toolboxes of riboswitch sensors able to detect small molecule and protein ligands across a range of medical applications. For example, rather than using a fluorescent protein reporter, protein-sensing riboswitches can regulate the expression of enzymes, such as glucose oxidase, enabling electrical current generation as a measurable output signal (Amalfitano et al., “A Glucose Meter Interface tor Point-of-Care Gene Circuit-Based Diagnostics / ’ AW. Commun. I2(l):724 (2021), which is hereby incorporated by reference in its entirety). Notably, cell-free systems have already been harnessed for such medical diagnostic applications. Though the addition of complex sample matrices (plasma, serum, urine, saliva) have been found to inhibit cell-free expression, due to the presence of RNases, it has been shown that co-expression of RNase inhibitors can mitigate this inhibition, unlocking their potential (Voyvodic et ah, “Evaluating and Mitigating Clinical Samples Matrix Effects on TX-TL Cell-Free Performance,” Scientific Reports 12:13785 (2022), which is hereby incorporated by reference in its entirety). A platform combining genetically encoded biosensors and cell-free expression could finally enable multiplexed protein detection in a compact, low-cost device that would provide longitudinal biomarker measurements in non- clinical setings for data-driven medicine.[01461 Although preferred embodiments have been depicted and described in detail herein, it will be apparent io those skilled in the relevant art that various modifications, additions, substitutions, and the like can be made without departing from the spirit of the invention and these are therefore considered to be within the scope of the invention as defi ned in the claims which follow.

Claims

WHAT IS CLAIMED IS:

1. A protein-binding riboswitch comprising: a pre-aptamer nucleotide sequence; an aptamer nucleotide sequence encoding an R.NA structure capable ofbinding a target protein; a post-aptamer nucleotide sequence; and a protein -coding nucleotide sequence encoding a reporter, wherein binding of the target protein by the aptamer nucleotide sequence modulates expression of the reporter.The protein-binding riboswitch according to claim 1, wherein the pre-aptamer nucleotide sequence is upstream of the aptamer nucleotide sequence, the aptamer nucleotide sequence is 5’ to the post-aptamer nucleotide sequence, and the post-aptamer nucleotide sequence is 5' to the protein-coding nucleotide sequence.3, The protein-binding riboswitch according to claim 1 or claim 2, wherein the pre- aptamer nucleotide sequence and post-aptamer nucleotide sequence comprise non-naturai nucleotides.4, The protein-binding riboswitch according to any one of claims I to 3, wherein binding of the target protein activates expression of the reporter.5, The protein-binding riboswitch according to any one of claims 1 to 3, wherein binding of the target protein inhibits expression of the reporter.

6. The protein-binding riboswitch according to any one of claims 1 to 5, wherein theR.NA structure comprises one or more of the group consisting of a hairpin, a stem, a loop, an internal loop, a multiloop, a junction, a pseudoknot, and / or a bulge.

7. The protein-binding riboswitch according to any one of claims 1 to 6, wherein the target protein is a biomarker.

8. The protein-bi ndi ng riboswitch according to any one of claims 1 to 7, wherein the target protein is a human protein.

9. The protein-binding riboswitch according to claim 7 or claim 8, wherein the target protein is selected from the group consisting of monomeric C-reactive protein, interleukin-32receptor, hemoglobin, angiotensin-converting enzyme, anti-acetylcholine receptor antibody, adenosine deaminase, alpha-fetoprotein, pappalysln-1 , aldolase A, alpha- 1 -antitrypsin, serum amyloid A-l protein, interleukin-2 receptor subunit alpha, mucin- 1, lysozyme C, aspartate transaminase, osteocalcin, underearboxylated osteocalcin, N-terminal pro-B-type natriuretic peptide, gamma-glutamyltranspeptidase, antimitochondrial antibodies, anti neutrophil cytoplasmic antibodies, anti-streptolysin antibodies, anti-DNaase B antibodies, anti-cyclic citrullinated peptide, C-terminal telopeptide, N-terminal propeptide of type I procollagen, N- terminal telopeptide, anticardiolipin antibody, anti-beta2 glycoprotein 1 , muellerian-inhibiting factor, proinsulin C-peptidc, pcrineuclear anti neutrophil cytoplasmic antibodies, anti-dengue virus antibody, vascular endothelial growth factor, macrophage colony-stimulating factor 1, amylase, lipoprotein lipase, antineutrophil cytoplasmic antibodies against proteinase 3, calprotectin, human epididymis protein 4, carbohydrate antigen 125, chromogranin-A, epstein- barr virus capsid antigen antibody, ceruloplasmin, anti-giiadin antibody IgA, p-selectin, sex hormone-binding globulin, des-gamma-carboxy prothrombin, hepatitis a virus cellular receptor 1 , neutrophil gelatinase associated lipocalin, interleukin-18, hepatocyte growth factor, cystatin- C, n-acetyl-beta-d-glucosaminidase, chemokine interferon inducible protein 10, fibronectin, nuclear ribonucleoprotein H l antibodies, anti-ribosomal P antibodies, hemoglobin subunit beta, glucose-6-phosphate 1 -dehydrogenase, gastrin, acetylcholinesterase, amyloid beta42, vasqpressin-neurqphysin 2-copeptin, apolipoprotein E, beta-2 -microglobulin, bone specific alkaline phosphatase, brain natriuretic peptide, butyrylcholinesterase, ca 19-9 tumor marker, calcitonin, chymotrypsin, complement CI, component C2, complement C3, complement C4, pancreatic elastase-1, ferritin, gammaglutamyl transferase (ggt), haptoglobin, hemoglobin, insulin, insulin-like growth factor 1, interleukin-6, interferon gamma, lactate dehydrogenase, lactotransferrin, parathyroid hormone, adrenocorticotropic hormone, transglutaminase IgA antibody, renin, cardiac troponin T, eardiac troponin I, transthyretin, erythropoietin, thyroid stimulating hormone, thyroglobulin, prothrombin, tryptase, antithrombin, sex hormone binding globulin, apolipoprotein B- 100, von willebrand factor, apolipoprotein A l, Clostridium difficile glutamate dehydrogenase, transferrin receptor (soluble), estrogen receptor, progesterone receptor, fibrinogen, factor V, transferrin, follicle stimulating hormone, hemoglobin S, her2, human chorionic gonadotropin, human growth hormone, kappa / lambda light chains, lactoferrin, leptin, luteinizing hormone, myoglobin, tan protein, tartrate resistant acid phosphatase, procalcitonin, prolactin, prostate specific antigen, protein C, protein S, albumin, and alanine transaminase.

10. The protein-binding riboswitch according to claim 9, wherein the target protein is monomeric C-reactive protein or interleukin-32 y proteins.

11. The protein-binding riboswitch according to any one of claims 1 to 10, wherein the pre-aptamer nucleotide sequence is between 2-35 nucleotides in length.

12. The protein -binding riboswitch according to any one of claims 1 to 11, wherein the post-aptamer nucleotide sequence is between 9-35 nucleotides.

13. The protein-bi ndi ng riboswitch according to any one of claims 1 to 12, wherein the post-aptamer nucleotide sequence comprises a ribosome binding site.

14. 'fhe protein-binding riboswitch according to any one of claims 1 to 13, wherein the reporter is selected from the group consisting of a transcription factor, a fluorescent protein, an enzyme, and an antibody.

15. A test strip comprising: a sample collection zone configured to receive a biological sample, wherein said sample collection zone comprises:(i) a nucleic acid molecule encoding the protein- binding riboswitch according to any one of claims 1 to 14; and(ii) a cell-free transcriptiow'tfanslation system.

16. The test strip according to claim 15, wherein the reporter is a fluorescent protein.

17. The test strip according to claim 16, wherein the fluorescent protein is a monomeric fluorescent protein.

18. The test strip according to claim 17, wherein the fluorescent protein is selected from the group consisting of monomeric red fluorescent protein (mRPF 1), mGreenLantem, and superfolder GFP (sfGFP).

19. The test strip according to any one of claims 15 to 18, wherein the reporter is an enzyme.

20. The test strip according to claim 19, wherein the enzyme is selected from the group consisting of glucose oxidase, invertase, lactase, alpha-amylase, beta-amylase, gammaamylase, trehalase, and phosphatase.

21. The test strip according to claim 19 or claim 20, wherein the sample collection zone further comprises:( ii i ) a substrate.

22. The test strip according to claim 21 , wherein the substrate is present at a known concentration.

23. The test strip according to claim 21 or claim 22, wherein the enzyme is glucose oxidase and the substrates is glucose.

24. The test strip according to claim 21 or claim 22, wherein the enzyme is invertase and the substrates is sucrose.

25. The test strip according to claim 21 or claim 22, wherein the enzyme is lactase and the substrate is lactose.

26. The test strip according to claim 21 or claim 22, wherein the enzyme is alpha- amylase, beta-amylase, or gamma- amylase and the substrate is maltose.

27. The test strip according to claim 21 or claim 22, wherein the enzyme is trehalase and the substrate is trehalose.

28. The test strip according to claim 21 or claim 22, wherein the enzyme is phosphatase and the substrate is glucose 6-phosphate.

29. The test strip according to any one of claims 21 to 28, wherein the sample collection zone further comprises:(iv) one or more enzymatic cofactors.

30. The test strip according to claim 29, wherein the one or more enzymatic cofactors are selected from the group consisting of NADH, FADH2, NADPH, and ATP.

31. The test strip according to any one of claims 15 to 30, wherein the biological sample is selected from the group consisting of blood, serum, saliva, sputum, plasma, cerebral spinal fluid, synovial fluid, urine, breast milk, and bile.

32. The test strip according to any one of claims 15 to 31, wherein the cell free- transcription translation system comprises one or more reagents selected from the group consisting of ATP, GTP, UTP, CTP, Folinic Acid, tRNA, Nicotinamide Adenine Dinucleotide (NAD), Coenzyme A (CoA), Oxalic Acid, Putrescine, Spermidine, I H-I'I S buffer, Mg(Glu)2, NH4(Glu), K(Glu), 20 natural amino acids, and Phosphoenolpyruvate (PEP).

33. The test strip according to any one of claims 15 to 32, wherein the cell free- transcription / translation system comprises a cell-free lysate.

34. The test strip according to any one of claims 15 to 32, wherein the cell free- transcription. trans lation system comprises a recombinant cell-tree system.

35. The test strip according to any one of claims 15 to 34, wherein the sample collection zone further comprises: (v) one or more RNase inhibitors.

36. The test strip according to any one of claims 15 to 35, wherein the sample collection zone further comprises:(vi) one or more protease inhibitors.

37. The test strip according to any one of claims 15 to 36, wherein the sample collection zone further comprises:(vi) one or more cosolutes.

38. The test strip according to claim 37, wherein the cosolutes are polyethylene glycol (PEG) and / or Ficol.

39. The test strip according to any one of claims 15 to 38, wherein the sample collection zone comprises a working electrode and a counter electrode.

40. A method of detecting a target protein in a biological sample, wherein said method comprises:providing the test strip according to claim 39, wherein the test strip is operably linked to an electrode and a current comparator, wherein said current comparator is operably linked to a reference electrode that supplies a reference current; placing a biological sample in the sample collection zone of the test strip, wherein said target protein, if present in the biological sample, will bind to the protein-binding riboswitch to modulate the expression level of the enzyme; passing a current through the counter electrode, sample, and working electrode; detecting the current produced by an electrochemical reaction between the enzyme and substrate; and quantifying, based on said detecting, the concentration of the target protein in the biological sample.

41. The method according to claim 40, wherein the biological sample is selected from the group consisting of blood, serum, saliva, sputum, plasma, cerebral spinal fluid, synovial fluid, urine, breast milk, and bile.

42. The method according to claim 40 or claim 41, wherein the target protein is a biomarker.

43. The method according to any one of claims 40 to 42, wherein the target protein is a human protein.

44. The method according to any one of claims 40 io 43, wherein the target protein is selected from the group consisting of monomeric C-reactive protein, interleukin-32 receptor, hemoglobin, angiotensin-converting enzyme, anti-acetylcholine receptor antibody, adenosine deaminase, alpha- fetoprotein, pappalysin-1, aldolase A, alpha- 1 -antitrypsin, serum amyloid A- 1 protein, interleukin-2 receptor subunit alpha, mucin- 1, lysozyme C, aspartate transaminase, osteocalcin, undercarboxylated osteocalcin, N-terminal pro-B-type natriuretic peptide, gamma- glutamyltranspeptidase, antimitochondrial antibodies, antineutrophil cytoplasmic antibodies, anti-streptolysin antibodies, anti-DNaase B antibodies, anti-cyclic citrull mated peptide, C- tenninal telopeptide, N-terminal propeptide of type 1 procollagen, N-terminal telopeptide, anticardiolipin antibody, anti-beta2 glycoprotein 1, muelleri an -inhibiting factor, proinsulin C- peptide, perineuclear antineutrophil cytoplasmic antibodies, anti-dengue virus antibody, vascular endothelial growth factor, macrophage colony-stimulating factor 1 , amylase, lipoprotein lipase, antineutrophil cytoplasmic antibodies against proteinase 3, calprotectin, human epididymisprotein 4, carbohydrate antigen 125, chromogranin-A, epstein-barr virus capsid antigen antibody, ceruloplasmin, anti-gliadin antibody IgA, p-selectin, sex hormone-binding globulin, des-gamma- carboxy prothrombin, hepatitis a virus cellular receptor 1, neutrophil gelatinase associated lipocalin, interleukin- 18, hepatocyte growth factor, cystatin-C, n-acetyl-beia-d-glucosaminidase, chemokine interferon inducible protein 10, fibronectin, nuclear ribonucleoprotein Hl antibodies, anti-ribosomal P antibodies, hemoglobin subunit beta, glucose-6-phosphate 1 -dehydrogenase, gastrin, acetylcholinesterase, amyloid beta42, vasopressin-neurophysin 2-copeptin, apolipoprotein E, beta-2 -microglobulin, bone specific alkaline phosphatase, brain natriuretic peptide, butyrylcholinesterase, ca 1.9-9 tumor marker, calcitonin, chymotrypsin, complement Cl, component C2, complement C3, complement C4, pancreatic elastase- 1 , ferritin, gammaglutamy! transferase (ggt), haptoglobin, hemoglobin, insulin, insulin-like growth factor 1, interleukin-6, interferon gamma, lactate dehydrogenase, lactotransferrin, parathyroid hormone, adrenocorticotropic hormone, transglutaminase IgA antibody, renin, cardiac troponin T, cardiac troponin I, transthyretin, erythropoietin, thyroid stimulating hormone, thyroglobulin, prothrombin, tryptase, antithrombin, sex hormone binding globulin, apolipoprotein B-100, von willebrand factor, apolipoprotein A l, Clostridium difficile glutamate dehydrogenase, transferrin receptor (soluble), estrogen receptor, progesterone receptor, fibrinogen, factor V, transferrin, follicle stimulating hormone, hemoglobin S. her2, human chorionic gonadotropin, human growth hormone, kappadambda light chains, lactoferrin, leptin, luteinizing hormone, myoglobin, tau protein, tartrate resistant acid phosphatase, procalcitonin, prolactin, prostate specific antigen, protein C, protein S, albumin, and alanine transaminase.

45. The protein -binding riboswitch according to claim 44, wherein the target protein is selected form the group consisting of monomeric C-reactive protein, and interleukin-32 receptor.

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