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Design

D E S I G N

Wet Lab

Figure 1: The overall design of our GPA system.

Aptamer

To accurately identify different types of disease biomarkers, we chose to use aptamers as our recognition probes. An aptamer is a sequence of DNA or RNA that can specifically recognize and bind to target molecules (proteins or other small molecules). By utilizing aptamers -protease crosslinking, we are able to detect the presence of specific disease biomarkers and generate downstream signals: when both aptamers bind to the target molecule, the two portions of the protease linked to each aptamer come into proximity, thereby restoring the protease’s activity and cleaving downstream proteins to generate an output.

Figure 2: Schematic illustration of aptamer binding to the target molecule and activating protease

For a specific disease biomarker, the well-established SELEX technology can be employed to screen for the corresponding aptamer sequences. In our dry lab, we also developed a model to predict aptamer sequences and conducted some validation.

Currently, several aptamer sequences have undergone extensive validation, along with a significant body of related research, including aptamer sequences corresponding to ATP and thrombin.

Therefore, we chose to base our disease monitoring platform on thrombin aptamers. Despite the ample literature support, we still need to validate the affinity of our obtained aptamer for thrombin. We employed two reliable methods: Electrophoretic Mobility Shift Assay (EMSA) and Surface Plasmon Resonance (SPR) to verify this.

EMSA

The aptamers were incubated with a concentration gradient of thrombin and subjected to non-denaturing polyacrylamide gel electrophoresis. The presence of gradually intensifying shift bands with increasing thrombin concentration would indicate an interaction between the aptamer and thrombin.

Figure 3: Principle of Electrophoretic Mobility Shift Assay (EMSA). In this assay, aptamers are incubated with thrombin or left unbound, followed by non-denaturing polyacrylamide gel electrophoresis to separate the components of the system. The appearance of free bands indicates aptamers that do not bind to thrombin, whereas shifted bands reveal aptamers that successfully bind to thrombin.

SPR

  1. Biotinylation of Aptamers: The aptamers are chemically modified with biotin for immobilization.
  2. Chip Preparation: A sensor chip coated with streptavidin is prepared, allowing for the specific binding of biotinylated aptamers.
  3. Aptamer Immobilization: The biotinylated aptamers are introduced to the sensor chip, where they bind to the streptavidin, forming a stable layer on the surface.
  4. Thrombin Injection: A series of thrombin concentrations are flowed over the chip, enabling interaction with the immobilized aptamers.
  5. Monitoring Interaction: The changes in the refractive index at the surface are measured in real-time, indicating binding events between the aptamer and thrombin.
  6. Data Analysis: The resulting sensorgrams are analyzed to determine the binding affinity and kinetics of the aptamer-thrombin interaction.

Figure 4: Schematic of the Surface Plasmon Resonance (SPR) Experiment. Biotinylated aptamers are immobilized on the SPR chip via streptavidin (SA) binding. Thrombin is then introduced to flow over the chip. When binding occurs, it causes a change in the resonance angle, indicating an interaction between the thrombin and the aptamers.

SPOC module

Circuit design

Based on literature, we designed a dimerization reaction with an amplification step. To lessen the burden of wet lab work, instead of directly testing the enzyme activity of the aptamer-protein complex, we retained the FRB and FKBP domain so that the function of SPOC module can be activated by adding rapamycin. Furthermore, to test whether the SPOC module works effectively, we design a special substrate with a PPV cut site linking two truncated protein originated from GFP and YFP.

The first step is for recognition. Once rapamycin is added, the FRB and FKBP domains will bind to two different sites on rapamycin simultaneously, bringing the two split proteases (nPPV and cPPV) together, resulting in the dimerization of the proteases. Therefore, the eventual output of this step is forming an active protease (PPV). The second step is for signal amplification. Once the first protease is activated, it cleaves the linker at the PPV-specific cut site, allowing another wild-type split protease to replace the mutant one. This results in the formation of another active protease (TEV), amplifying the signal.

To confirm whether each step produces the desired output, we use a specially designed substrate. Successful protease activation will result in substrate cleavage, which can be visualized by SDS-PAGE analysis, showing two distinct bands on the gel.

Wet lab experiment design

  1. Protein expression and extraction
  • For protein expression, IPTG induction is applied to induce bacteria to express proteins.
  • For protein extraction, ultrasonication is applied to disrupt cells. If the targeted protein is soluble, only centrifugation is needed to obtain the supernatant. If the targeted protein is in the inclusion bodies, additional dissolving step with special solutions is needed, accompanied by on-column refolding purification method in the next step.

Figure 5: Overview of protein purification work flow. The protein purification process begins with transformation (1), where the desired gene is introduced into a host cell. This is followed by selection (2) of successfully transformed cells on a selective medium. Next, protein production (3) is induced in the selected cells, which are then subjected to cell lysis (4) via ultrasonication to release the proteins. The lysate is then subjected to protein purification (5) using an AKTA system or gravity column. The purified proteins are analyzed (6) to assess the success of the purification process, and finally, an activity assay (7) is performed to evaluate the functionality of the purified proteins.

  • For further details, please refer to the Experiments page.
  1. Protein purification

We apply three purification methods, for the proteins being purified may be in the inclusion bodies. However, all of them use the mechanism of affinity chromatography. Details can be find in the Experiments page.

  • Method I On-column Refolding. This method combines purification and refolding by using a gradient dilution of urea solution during the protein’s binding to the nickel column, followed by an elution step.

Figure 6: Workflow for extracting and purifying target proteins from inclusion bodies. AU: after ultrasonication (total proteins). SU: supernatant after ultrasonication. PU: precipitate after ultrasonication. SW: supernatant after washing. PW: precipitate after washing. PD: precipitate after dissolution. FS: final supernatant.

  • Method II Addition of soluble tags. Common solubility tags such as MBP and FH8 are added to the N-terminal of the target proteins to improve solubility.

Figure 7: Effects of Soluble tags. When total proteins are extracted (AU) and centrifuged, the solubility of the proteins can be assessed. Soluble tags are expected to enhance the solubility of the target proteins.

  • Method III Cell-free protein expression system. We used the ALiCE® eukaryotic protein expression platform to express our proteins.

Figure 8: Working principle of the ALiCE® cell-free protein expression system.

  1. Enzyme activity test

We applied SDS-PAGE analysis to confirm the enzyme activity of the dimerized split proteases. For further details, please refer to the Experiments page.

Aptamer-Split Protease Crosslinking

To integrate the high affinity of aptamers with the cleavage capability of proteases, we are exploring two methods for crosslinking aptamers and split proteases: click chemistry and streptavidin-biotin interactions.

Click-chemistry-based crosslinking

Inspired by Prof. Liqin Zhang and Prof. Tao Liu, we have chosen to leverage the power of click chemistry. Specifically, we incorporated p-Azido phenylalanine (p-AzF) at a designated site on the split protease nPPVp/cPPVp. Concurrently, we modified the aptamer with dibenzoazacyclooctyne (DBCO). When incubated at room temperature, these two components can covalently bond to each other, creating a robust interaction between the aptamer and the split protease

Figure 9: Concept diagram of click chemistry-based crosslinking between an aptamer and split protease. The aptamer is modified with dibenzoazacyclooctyne (DBCO), while the split protease contains p-Azido phenylalanine (p-AzF). These components covalently bond when incubated at room temperature, creating a stable complex that recognize biomarkers.

Streptavidin-biotin-interactions-based crosslinking

Given the challenges of expressing proteins that incorporate non-canonical amino acids, we are also exploring natural bioaffinity systems that can be constructed using simpler fusion proteins. For this, we have selected streptavidin-biotin interactions. Streptavidin (SA) is a tetrameric protein derived from the bacterium Streptomyces Avidini, which exhibits extraordinary affinity for biotin. SA can be easily fused with the split protease, and biotinylated aptamers can be readily synthesized. This approach simplifies the crosslinking process while maintaining effective binding and functionality.

Figure 10: Concept diagram of crosslinking between an aptamer and split protease via streptavidin-biotin interactions. The split protease is fused with streptavidin (SA), while the aptamer is biotinylated, allowing for a strong and specific binding that enhances protease functionality.

Output module

In the output module, we developed two methods to convert the split-PPV cleavage event into a detectable signal. Both methods are based on the principle of colloidal gold test paper. The test of colloidal test paper is based on the principle of colloidal particles (typically metals like gold or silver) being immobilized on a test strip to detect specific analytes. A visible color change indicates the presence of the target analyte.

Realizing output with existing hCG colloidal gold test paper

Here’s the method of detecting PPV protease cleavage event.

  1. Designing the substrate: The PPV substrate is designed as a fusion protein (GST–PPV cleavage site–hCG) and immobilized on a GST affinity chromatography column.
  2. Cleavage event: When the sample flows through the column, if active split-PPV is present, it cleaves the substrate.
  3. Detection: The cleaved hCG is released and flows onto the hCG colloidal gold test paper, producing a positive result. If no active PPV is present, the test paper will show a negative result.

Figure 11: Concept diagram of realizing output with hCG colloidal gold test paper. Fusion protein (GST—PPVp site—hCG) is immobilized on a GST affinity column. Active PPVp in the sample cleaves the substrate, releasing hCG, which is detected by the hCG colloidal test paper, showing a positive result. No cleavage results in a negative test.

Making our own colloidal gold test paper

Compared to the first method, another more integrated way is to immobilize the substrate protein directly on the test paper. When the sample is added, the active PPV in the sample cleaves the immobilized substrate. The released fragment is carried to the test line, where it is recognized by a corresponding antibody, producing the detectable signal.

Dry Lab

AI

Accurate and timely detection of disease biomarkers is crucial for effective diagnosis and treatment across various medical conditions. Traditional methods, such as SELEX, used for screening Aptamers that bind to specific biomarkers, are often slow, costly, and lack the precision needed for diverse applications. To overcome these limitations, we introduce MAGA: Make Aptamer Generally Applied—a universal machine learning-based platform designed to predict Aptamer sequences that can target a wide range of disease biomarkers with high specificity and affinity.

Biophysics

The principle of SELEX: experimental and computational

In the past decade, aptamers with their high affinity and bio-compatibility have been heatedly discussed, while designing aptamer for specific target such as biomarker and cell has been proven rather complicated. In the past decades,  multiple studies which are dedicated to the development of biosensors functionalized with aptamers have been performed, and some of them have played a crucial role in therapeutic scenario. Initially, aptamers with specific binding affinity are mainly designed empirically and characterized by typical wet-lab experiments such as electrophoretical mobility shift assay (EMSA). Inspired with the perspective of oriented choices and evolution, the systematic evolution of ligands by exponential enrichment, or SELEX, is an in vitro Darwinian-evolutionary experimental method for the manual design of nucleic acid aptamers with high affinity and efficiency.

Figure 12: The conceptual procedure for the SELEX technique, which usually contains repetitive binding and PCR processes.

Generally, the construction of aptamers using SELEX technique usually includes selection (select UNA from aptamers pool), investigation (characterizing the binding affinity with target), separation (separating aptamers with high affinity from low affinity), and sequencing (reading out the sequence of the separating aptamers), which lasts for several rounds of processes and can sometimes be laborious. While the separating process is carried out by binding affinity data from experiments, additionally, to design aptamers in silico completely has been developed with the application of computational methods such as docking and molecular dynamics (MD). Performing molecular dynamic simulations, which is not a mandatory step, allows for an in silico evaluation of the stability of the aptamer/ligand complex and determination of the binding patterns with higher accuracy than would be possible during the docking step simply. Nevertheless, an obvious disadvantage of in silico aptamer design is that the current level of biochemical molecular modeling makes it difficult to construct complex system.

Figure 13: The conceptual procedure for molecular dynamics (MD) simulation, which normally prefabricates a natural “water box” and then mimics the dynamic properties of biochemical molecules (such as UNA and protein) under proper empirical force field.

Generation model steps into the SELEX technique

It has struck with us that the procedures of investigation and separation (usually tangled with a series of experiments) make the SELEX technique time-consuming, and actually we should do rounds of the whole process in order to diminish the aptamers pool and search out target aptamer. While the nucleotide only has four types, however, the space volume of the aptamers pool explodes up exponentially when we increase the length of our aptamer in order to gain more complex spatial structure and more specific binding affinity. SELEX may be combined with high-throughput sequencers to accelerate (a process that is usually called HT-SELEX, or HTS), but it needs to design our SELEX system carefully and introduce extra constrictions to our aptamers pool.

Therefore, that’s why we turn to the model. We hope to construct an ideal generation model, named Make Aptamer Generally Applied (MAGA), which uses the 3D structural information of the ligand as input and feeds back nucleic acid sequences with proper length and possible high binding affinity towards the ligand as output. As for the input information, we take advantage of the AphaFold2 to predict protein structures. Besides, MD simulation in silico plays a vital role in judging the model effect.

Characterization of biochemical system with molecular dynamics and mathematical modeling

Not only can MD manipulation enable the model to judging the performance of the generating aptamers, but also it can be exploited to characterize our SPOC system. Choosing GROMACS to implement the MD manipulation, our team first constructs the split enzyme systems of nTEV, cTEV, nPPV, and cPPV separately under the OPLS-AA/L all-atom force field, and then mimics these systems at 300K, 1 bar, ion-neutral environment over a period of 10 ns. Major MD calculations occur under the NVT ensemble, while equilibrium under the NPT ensemble is used for 200 ps prior to the MD simulation. According to the calculation results, the optimal Phe (acting as the site for introducing unnatural amino acid to carry out the “click reaction”) is chosen for each split enzyme, which is situated on a relative flexible peptide and away from the functional core of the enzyme. In order to validate our choices, a system of paired enzyme (such as the nTEV and cTEV) is constructed under the CHARMM36 all-atom force field and programmed at 300K, 1 bar, ion-neutral environment over a period of 10 ns, which proves that the two chosen Phe sites exert little influence on the enzyme function. Besides, some important physical parameters such as the diffusion constant of the enzymes can be predicted by our MD manipulation as well.

Figure 14: Conceptual imitation of our idea about finding out proper Phe sites on split enzymes to perform “click reaction” mentioned above.

Moreover, ordinary differential equations (ODEs) are established to characterize the censoring step and the amplifying step based on a few assumptions. Besides, a two-dimensional Fokker-Plank equation is used to characterize our diffusion system. For further explanation, please click to our dry lab part.

R E F E R E N C E

Wet Lab

1. Aptamer-Recognition Module:

  1. Buglak, A. A., Samokhvalov, A. V., Zherdev, A. V., & Dzantiev, B. B. (2020). Methods and Applications of In Silico Aptamer Design and Modeling. International journal of molecular sciences, 21(22), 8420. https://doi.org/10.3390/ijms21228420
  2. Manochehry, S., McConnell, E. M., & Li, Y. (2019). Unraveling Determinants of Affinity Enhancement in Dimeric Aptamers for a Dimeric Protein. Scientific reports, 9(1), 17824. https://doi.org/10.1038/s41598-019-54005-4
  3. Ayass, M. A., Griko, N., Pashkov, V., Tripathi, T., Zhang, J., Ramankutty Nair, R., Okyay, T., Zhu, K., & Abi-Mosleh, L. (2023). New High-Affinity Thrombin Aptamers for Advancing Coagulation Therapy: Balancing Thrombin Inhibition for Clot Prevention and Effective Bleeding Management with Antidote. Cells, 12(18), 2230. https://doi.org/10.3390/cells12182230
  4. Njock, M. S., Guiot, J., Henket, M. A., Nivelles, O., Thiry, M., Dequiedt, F., Corhay, J. L., Louis, R. E., & Struman, I. (2019). Sputum exosomes: promising biomarkers for idiopathic pulmonary fibrosis. Thorax, 74(3), 309–312. https://doi.org/10.1136/thoraxjnl-2018-211897
  5. Zhang, M., Yu, Q., Tang, W., Wu, Y., Lv, J., Sun, L., Shi, G., Wu, M., Qu, J., Di, C., & Xia, Z. (2021). Epithelial exosomal contactin-1 promotes monocyte-derived dendritic cell-dominant T-cell responses in asthma. The Journal of allergy and clinical immunology, 148(6), 1545–1558. https://doi.org/10.1016/j.jaci.2021.04.025
  6. Arsić, A., Hagemann, C., Stajković, N., Schubert, T., & Nikić-Spiegel, I. (2022). Minimal genetically encoded tags for fluorescent protein labeling in living neurons. Nature communications, 13(1), 314. https://doi.org/10.1038/s41467-022-27956-y
  7. Chin, J. W., Santoro, S. W., Martin, A. B., King, D. S., Wang, L., & Schultz, P. G. (2002). Addition of p-azido-L-phenylalanine to the genetic code of Escherichia coli. Journal of the American Chemical Society, 124(31), 9026–9027. https://doi.org/10.1021/ja027007w
  8. López, C. J., Fleissner, M. R., Brooks, E. K., & Hubbell, W. L. (2014). Stationary-phase EPR for exploring protein structure, conformation, and dynamics in spin-labeled proteins. Biochemistry, 53(45), 7067–7075. https://doi.org/10.1021/bi5011128
  9. Tsai, Y., Elsässer, S. J. (2023). Genetically Incorporated Non-Canonical Amino Acids (1 ed). Humana Press. https://doi.org/10.1007/978-1-0716-3251-2 DOI: 10.1007/978-1-0716-3251-2
  10. Martin, R. W., Des Soye, B. J., Kwon, Y. C., Kay, J., Davis, R. G., Thomas, P. M., Majewska, N. I., Chen, C. X., Marcum, R. D., Weiss, M. G., Stoddart, A. E., Amiram, M., Ranji Charna, A. K., Patel, J. R., Isaacs, F. J., Kelleher, N. L., Hong, S. H., & Jewett, M. C. (2018). Cell-free protein synthesis from genomically recoded bacteria enables multisite incorporation of noncanonical amino acids. Nature communications, 9(1), 1203. https://doi.org/10.1038/s41467-018-03469-5
  11. Wang, Z. A., Kurra, Y., Wang, X., Zeng, Y., Lee, Y. J., Sharma, V., Lin, H., Dai, S. Y., & Liu, W. R. (2017). A Versatile Approach for Site-Specific Lysine Acylation in Proteins. Angewandte Chemie (International ed. in English), 56(6), 1643–1647. https://doi.org/10.1002/anie.201611415
  12. Kumar Kulabhusan, P., Hussain, B., & Yüce, M. (2020). Current Perspectives on Aptamers as Diagnostic Tools and Therapeutic Agents. Pharmaceutics, 12(7), 646. https://doi.org/10.3390/pharmaceutics12070646
  13. Thevendran, R., & Citartan, M. (2022). Assays to Estimate the Binding Affinity of Aptamers. Talanta, 238(Pt 1), 122971. https://doi.org/10.1016/j.talanta.2021.122971
  14. Chen, A., Yan, M., Yang, S. (2016). Split aptamers and their applications in sandwich aptasensors. TrAC Trends in Analytical Chemistry, 80(2016), 581-593. https://doi.org/10.1016/j.trac.2016.04.006
  15. Troisi, R., Balasco, N., Autiero, I., Vitagliano, L., & Sica, F. (2021). Exosite Binding in Thrombin: A Global Structural/Dynamic Overview of Complexes with Aptamers and Other Ligands. International journal of molecular sciences, 22(19), 10803. https://doi.org/10.3390/ijms221910803

2. SPOC Logic Amplification Module:

  1. Fink, T., & Jerala, R. (2022). Designed protease-based signaling networks. Current opinion in chemical biology, 68, 102146. https://doi.org/10.1016/j.cbpa.2022.102146
  2. Fink, T., Lonzarić, J., Praznik, A., Plaper, T., Merljak, E., Leben, K., Jerala, N., Lebar, T., Strmšek, Ž., Lapenta, F., Benčina, M., & Jerala, R. (2019). Design of fast proteolysis-based signaling and logic circuits in mammalian cells. Nature chemical biology, 15(2), 115–122. https://doi.org/10.1038/s41589-018-0181-6
  3. Parida, P. P., Saraswathi, D., Mopidevi, S. M. V., & Raran-Kurussi, S. (2023). Advancing large-scale production of TEV protease through an innovative NT* tag-based fusion construct. Current research in structural biology, 6, 100106. https://doi.org/10.1016/j.crstbi.2023.100106
  4. Han, X., Yang, J., Zeng, F., Weng, J., Zhang, Y., Peng, Q., Shen, L., Ding, S., Liu, K., & Gao, Y. (2020). Programmable Synthetic Protein Circuits for the Identification and Suppression of Hepatocellular Carcinoma. Molecular therapy oncolytics, 17, 70–82. https://doi.org/10.1016/j.omto.2020.03.008
  5. Blommel, P. G., & Fox, B. G. (2007). A combined approach to improving large-scale production of tobacco etch virus protease. Protein expression and purification, 55(1), 53–68. https://doi.org/10.1016/j.pep.2007.04.013
  6. Nam, H., Hwang, B. J., Choi, D. Y., Shin, S., & Choi, M. (2020). Tobacco etch virus (TEV) protease with multiple mutations to improve solubility and reduce self-cleavage exhibits enhanced enzymatic activity. FEBS open bio, 10(4), 619–626. https://doi.org/10.1002/2211-5463.12828

3. Output Signal Module:

  1. Chen, M., Luo, R., Li, S., Li, H., Qin, Y., Zhou, D., Liu, H., Gong, X., & Chang, J. (2020). Paper-Based Strip for Ultrasensitive Detection of OSCC-Associated Salivary MicroRNA via CRISPR/Cas12a Coupling with IS-Primer Amplification Reaction. Analytical chemistry, 92(19), 13336–13342. https://doi.org/10.1021/acs.analchem.0c02642
  2. Zhu, K., Zhou, X., Yan, Y., Mo, H., Xie, Y., Cheng, B., & Fan, J. (2017). Cleavage of fusion proteins on the affinity resins using the TEV protease variant. Protein expression and purification, 131, 27–33. https://doi.org/10.1016/j.pep.2016.02.003