Figure 1. Target gene PCR amplification diagram

We constructed pET28a-phf6 and pET28a-tau using restriction digestion and ligation. Agarose gel electrophoresis was employed to separate and analyze the size of DNA fragments, thereby verifying the accuracy of gene amplification via PCR. This technique utilizes an electric field to facilitate the migration of DNA fragments, with smaller fragments exhibiting faster mobility. The size and purity of these fragments are assessed through staining and ultraviolet (UV) observation. By referencing a molecular weight marker positioned on the left, the approximate base pair (bp) lengths of the bands can be inferred. When compared to established reference values, the correct bands can be identified. For BD-Tau, the expected band length is 102 bp, which corresponds to the observed band in the Figure 1. For Tau, the anticipated band length is 105 bp; the first, second, and fourth bands align with this expectation, while the third band displays inconsistent intensities, likely due to uneven gel loading. Consequently, the third band is deemed incorrect as it does not match the expected value and is unsuitable for further experimentation. This analysis underscores the use of agarose gel electrophoresis in selecting the appropriate plasmids for subsequent recovery and insertion into enzyme-digested vectors through T4 ligase.

Figure 2. Growth of plasmid (BD-Tau & Tau) on LB agar plates

Following restriction digestion and ligation, which involves the precise insertion of plasmids into specific sites on the enzyme-digested vector to achieve effective integration of the target gene, the reconstructed plasmid was further cultured using the spread plate method. After we have transferred the reconstructed plasmid into the E coli DH5α , we have done a monoclonal colony verification. To verify successful plasmid uptake, we employed Kanamycin selection by culturing the transformed bacteria on LB agar plates supplemented with Kanamycin, and an antibiotic for which resistance was encoded in the plasmid. The Kanamycin should screen out all the E-coil that doesn’t has our plasmid. As we can see in the Figure 2, both E coli DH5α has successfully cultivated by the LB agar plate, which indicates our plasmid transfer is successful. Subsequently, the extracted plasmids were transformed into E. coli BL21, followed by monoclonal verification.

Figure 3. Single colony PCR validation graph

Single colonies from each of the LB agar plates were selected and subjected to amplification PCR. Multiple samples were collected from each plate to mitigate the impact of potential errors by ensuring redundancy. Subsequently, agarose gel electrophoresis was performed on all samples obtained from the four plates. This technique was employed to separate and analyze the DNA fragments by size, thereby verifying the accuracy of the genes amplified by PCR. By utilizing a molecular weight marker, the approximate base pair (bp) lengths of the DNA bands were estimated and compared to predetermined values to identify the correct bands. In Figure 3, the expected band length is 102 bp, and the colonies BD Tau-DH5α-3 and BD Tau-BL21-3 are suitable for further experimentation. In Figure 3, the expected band length is 105 bp, and the colonies Tau-DH5α-1 and Tau-BL21-4 are appropriate for subsequent experimentation. This analysis facilitates the identification of colonies with the correct DNA bands, which can then be cultured overnight for further sequencing.

Figure 4. Sanger sequencing map

In our project, we employed DNA sequencing for the identification and characterization of our DNA samples. We utilized this method to ascertain the complete nucleotide sequence of our reconstructed plasmids. This approach enabled us to verify both the accuracy and integrity of the reconstructed plasmid. Most peaks were sharp and well-defined, particularly in the central region of the sequence, suggesting minimal background noise and high signal clarity. Both reconstructed plasmids, BD Tau and Tau, exhibited sequencing results that fell within the anticipated parameters, indicating no significant deviations. The sequence alignment with the designed construct confirms the successful incorporation of the target gene into the plasmid. The high quality of the sequencing data allows us to confidently verify the efficacy of our reconstructed plasmids and demonstrates the absence of significant sequencing errors or contamination, as evidenced by the lack of ambiguous bases or unexpected peaks in the figure 4. This level of accuracy is essential for subsequent applications, ensuring the plasmids' suitability for further experimental use. The accuracy of the sequencing results is crucial for the reliability of follow-up studies, which is critical for ensuring the plasmid's applicability in subsequent experiments.

The harvested cells were lysed through sonication in a binding buffer composed of 20 mM Tris-HCl, 500 mM NaCl, and 20 mM imidazole at pH 7.9. The soluble fraction was subsequently subjected to immobilized affinity chromatography utilizing Ni-NTA resin. Stepwise elution with imidazole gradients ranging from 50 to 250 mM resulted in BD-tau with a purity exceeding 90%, as verified by SDS-PAGE on a 15% gel.

Figure 5. SDS-PAGE for the analysis of whole cell lysis and crude protein solution after centrifugation

SDS-PAGE was performed on plasmid-transformed E. coli BL21 to assess the initial protein expression levels. As depicted in Figure 5, both the crude protein extracted from the cell lysate and the protein obtained from the centrifuged supernatant revealed the presence of BD Tau (5.1 kDa) and Tau (5.2 kDa). The successfully expressed BD-tau and Tau proteins can be used for SELEX screening.

Figure 6. Flow symmetry concerning the product of various rounds of the SELEX process

Flow cytometry is a biological technique used for counting and sorting microscopic particles suspended in a fluid. In our experiments, we first incubate Ni-NTA magnetic beads with His-tagged BD-tau protein to allow complex formation. Subsequently, nucleic acid aptamers with high affinity can specifically bind to the BD-tau Ni-NTA magnetic beads. The test sample contains four distinct components: Ni-NTA magnetic beads, BD-tau-conjugated Ni-NTA magnetic beads, aptamer-bound BD-tau-Ni-NTA magnetic bead complexes, and free nucleic acid aptamers. Additionally, the nucleic acid aptamers are 5'-end labeled with a FAM fluorescent tag.

We employed flow cytometry to separate the four components in the experimental sample.The BD-tau-conjugated Ni-NTA magnetic beads and unconjugated Ni-NTA beads can be distinguished and sorted based on their physical properties, but they yield no RFU signal due to the absence of fluorescent labeling. Furthermore, free nucleic acid aptamers, being DNA molecules below the detection threshold of conventional flow cytometry, cannot be directly detected by this method. RFU signals are generated only when nucleic acid aptamers are complexed with BD-tau-Ni-NTA magnetic beads. The RFU value thereby serves as a quantitative indicator of the relative extent of aptamer-bead binding.

A 66-mer random DNA library (5'-GCCGGATCCGTCGAC-(N66)-GAAGCTTGGTACCGAGCTC-3') underwent 17 iterative rounds of selection against immobilized BD-tau (2 μg per round). The stringency of the selection process was progressively increased by reducing the incubation time from 60 to 20 minutes, introducing competitive elution with 10 mM free BD-tau in round 8, and decreasing the target concentration to 1 μg in the final rounds. Enriched pools were amplified using flanking primers containing Illumina adapter sequences, facilitating next-generation sequencing (MiSeq, 2×150 bp) after round 17.

This study presents our findings on flow symmetry concerning the product of various rounds of the SELEX process. RFU, or Relative Fluorescence Units, quantifies the intensity of the fluorescent signal emitted by the FAM attached to the F primer during PCR. As illustrated in the figure 6, RFU values progressively increased from round 1 to round 6, indicating a gradual enrichment of aptamers with binding affinity for BD-tau. Post round 6, we implemented reverse screening to eliminate non-specific binders, which resulted in a noticeable decline in RFU. By round 12, after additional rounds of stringent selection, there was a substantial decrease in RFU, suggesting that only a small pool of aptamers with the highest affinity remained.Finally, the selected nucleic acid aptamers were sequenced to determine their precise nucleotide sequences, thereby providing the essential molecular information for subsequent development steps.

From the 27 nucleic acid aptamers selected through the SELEX system, we employed molecular docking to predict the binding efficacy between BD-tau and the aptamers, ultimately screening three aptamers with the highest affinity.The binding score results from the molecular docking are presented in Table 1.

Table 1. Binding Affinity of Aptamer-1, Aptamer-2, and Aptamer-3 with BD-tau

The table 1 demonstrate that BD-tau exhibits binding affinity to Aptamer-1, Aptamer-2, and Aptamer-3, though no significant differences were observed among them. This indicates limitations in the molecular docking results, necessitating further experimental validation to determine the binding affinity of Aptamer-1, Aptamer-2, and Aptamer-3 for BD-tau.

To identify the nucleic acid aptamer with the highest binding affinity for BD-tau from Aptamer-1, Aptamer-2, and Aptamer-3, we employed Surface Plasmon Resonance (SPR) technology. Biotin exhibits high-affinity interaction with streptavidin. Therefore, we injected the biotinylated target protein BD-tau (ligand) into specific flow cells of the SPR sensor chip pre-coated with streptavidin (SA), enabling its specific and stable capture. When a high-affinity nucleic acid aptamer approaches, it will bind to BD-tau.

The binding event between the two molecules will lead to an increase in response units (RU). By fitting the sensorgram data with a 1:1 Langmuir binding model, the dissociation constant (Kd) value can be calculated. The Kd value serves as a quantitative measure of the binding affinity between BD-tau and the nucleic acid aptamer.

We serially diluted Aptamer-1, Aptamer-2, and Aptamer-3 to graded concentrations (e.g., 0 μM, 5 μM, 10 μM, 30 μM, 100 μM, 150 μM) and sequentially injected them at a constant flow rate over the sensor chip surface immobilized with the target protein to monitor the binding interactions.

Figure 7. Affinity assessed by using surface plasmon resonance

The initial graph illustrates the relationship between aptamer concentration and the energy required to dissociate the aptamer from its target protein. Five different concentrations of the aptamer were utilized for the SPR analysis. Subsequently, the second graph re-plotted the data from the Figure 7 with the x-axis representing aptamer concentration, and a logistic best-fit line was derived.

Table 2. Aptamer Sequences and Dissociation Constants

The Table 2 above illustrates the three optimal aptamers. The dissociation constant (Kd) represents the affinity for the target protein, with this value being determined through the Surface Plasmon Resonance (SPR) method. A lower Kd value indicates a higher affinity. The midpoint of this graph was identified as the dissociation constant (Kd) value. In our analysis of various aptamers using SPR, we observed that a lower Kd value corresponds to a higher energy requirement for dissociation, indicating greater affinity. Notably, the Aptamer-3 exhibited a Kd value of approximately 56.66, signifying maybe affinity for the BD-tau protein.Based on the Kd values, we selected Aptamer-3 from the three nucleic acid aptamers as having the highest affinity for BD-tau, and subsequently validated the specificity of Aptamer-3 for BD-tau using ELISA.

We further validated the binding affinity of aptamer Aptamer-3 using ELISA. To simulate conditions in AD and non-AD patients, artificial blood was spiked with varying concentrations of BD-tau and peripheral tau, thereby minimizing potential interference from other factors. Specifically, the biotinylated nucleic acid aptamer Aptamer-3 was immobilized on ELISA plates, followed by incubation with BD-tau protein and colorimetric detection. The measured absorbance quantitatively reflected the relative concentration of BD-tau protein.

Figure 8. Quantitative binding analysis of BD-Tau aptamer in simulated plasma environments

In the figure 8A, the initial graph illustrates a positive correlation between the increased concentration of our Aptamer-3 and the bound BD-tau levels. The figure 8B demonstrates the results of an ELISA assay conducted to detect Alzheimer's Disease (AD) within a simulated blood plasma environment. The data indicate that the ELISA assay consistently identified elevated BD-tau levels in the plasma of the AD group, whereas the control group exhibited significantly lower BD-tau levels. These findings suggest that the aptamer is capable of accurately detecting AD within a plasma environment.

Utilizing expression level data from these three proteins (Tau,BD-tauand BD-tau+Tau) by Elisa date, we developed a machine learning model to predict individual Alzheimer's Disease (AD) status. The results demonstrate the feasibility of this approach. The Support Vector Machine (SVM) model, in particular, demonstrated superior performance, while the Random Forest (RF) model requires further optimization. Additionally, we employed methods such as Out-of-Fold (OOF) prediction to thoroughly evaluate the model's accuracy and reliability. For detailed modeling procedures, click here: https://2025.igem.wiki/keystone/model

ROC Curve (Receiver Operating Characteristic Curve)

This chart for evaluating the performance of a binary classification model shows how the model's performance changes under different classification thresholds. The closer the curve is to the top-left corner, the better the model's performance.

The x-axis of the chart represents the False Positive Rate (FPR), also known as the fall-out rate, which indicates the proportion of all actually negative instances that are incorrectly predicted as positive. The y-axis represents the True Positive Rate (TPR), also known as recall or sensitivity, which indicates the proportion of all actually positive instances that are correctly predicted as positive.

The AUC (Area Under Curve) is a key metric for measuring a model's ability to distinguish between classes. Its value ranges from 0 to 1; a value closer to 1 indicates better model performance in distinguishing between the positive and negative classes.

7.1 Random Forest (RF) Model

Figure 9. The ROC curve of Random forest model

The figure 9 indicate that the RF model achieved a mean AUC of 0.789 with a standard deviation of 0.131 under 5-fold cross-validation, indicating that the model possesses reasonably good overall discriminative ability.

7.2 Support Vector Machine (SVM) Model

Figure 10. The ROC curve of SVM model

The figure 10 indicate that the SVM model achieved a mean AUC of 0.860 with a standard deviation of 0.119 under 5-fold cross-validation, demonstrating relatively strong overall discriminative ability.

7.3 Lasso Model

Figure 11. The ROC curve of Lasso model

The figure 12 indicate that the Lasso model achieved a mean AUC of 0.844 with a standard deviation of 0.104 under 5-fold cross-validation, demonstrating good and relatively consistent overall discriminative ability.

ROC Curve Cross Comparison

A comparative analysis of the three models reveals a performance hierarchy. The SVM model achieved the highest mean AUC (0.860), indicating superior overall discriminative ability. It was followed closely by the Lasso model (0.844), which also demonstrated the lowest standard deviation (0.104), signifying the most stable and reliable performance across cross-validation folds. While the Random Forest (RF) model possessed reasonably good discriminative ability (AUC 0.789), its higher standard deviation (0.131) points to greater performance variability, and its mean AUC was lower than the other two models. In conclusion, the SVM model is the recommended choice for predictive power, though the Lasso model presents a compelling alternative due to its consistency.

Since the primers already contained NheI and HindIII restriction sites, which correspond to the sites within the vector pET28a. A 1% agarose gel electrophoresis can separate negatively charged nucleic acid fragments of different sizes in the PCR product under an electric field. As shown in the figure, the target band has a size of 3753 bp, and a bright and wide band can be clearly identified, indicating that we successfully amplified and separated the target fragment(Figure 12). The weaker bands surrounding the target band may be due to nonspecific primer binding and abnormal amplification.

Figure 12. PCR amplification of Cas12a.

The ligated plasmid was subsequently amplified in cells through chemical transformation and antibiotic selection. After mixing, heat-shock, ice bath, and recovery, the cells were centrifuged, most of the medium was discarded, and the pellet was resuspended before plating onto LB agar plates containing kanamycin. The plates were incubated statically at 37 °C for 12 hours, and the results are shown in the figure 13.

Figure 13. Chemical transformation results of pET28a-LbCas12a

Next, PCR verification was performed on the colonies on the plate to ensure that the plasmids containing the target band had successfully entered the cells and replicated. A certain number of single colonies were selected and dissolved in 10 μl of sterile ddH₂O, and 1 μl of the solution was used for PCR verification. The results are shown in the figure 14.

Figure 14. Colony PCR results.

As shown in the figure 15, the target band size is 3753 bp, and a bright band can be clearly observed, indicating that the desired gene fragment has been successfully transformed into the cells. However, to ensure that no potential mutations occurred, this clone was sent to a gene service company for plasmid extraction and Sanger sequencing to verify the sequence accuracy. The results are shown in the figure below.

Figure 15. Sequencing validation.

In the figure 15, the target sequence can be clearly detected in its entirety. Within the high-confidence regions (noting that Sanger sequencing may show lower confidence at the ends, and a single reaction can only cover approximately 1000 bp, which is why multiple sequences are joined end-to-end in the figure18), the sequencing quality is good, with well-resolved peaks. No mutations are observed in the target fragment, indicating that the fragment has been successfully integrated into the plasmid backbone and that the recombinant plasmid has been successfully constructed.

In vitro synthesis of crRNA is typically based on the recognition sequence of T7 RNA polymerase (T7 promoter). By synthesizing one oligonucleotide containing the T7 promoter sequence and annealing it with another oligonucleotide complementary to the target sequence, a double-stranded DNA transcription template is obtained, which serves as a template for crRNA synthesis by T7 polymerase. The template DNA was generated by annealing oligo DNA, and the PCR product was purified by agarose gel electrophoresis. The results are shown in the figure 16.

Figure 16. Oligo DNA validation

As shown in the figure 16, a clear target band appears at 59 bp, while the faint band at the bottom is due to primer dimers formed by complementary primers. After obtaining the crRNA transcription template DNA, crRNA was synthesized using the HiScribe T7 Quick High-Yield RNA Synthesis Kit. The resulting RNA was quantified, with a concentration of 60 ng/μl.

In the T7 expression system (pET28a), the target gene is placed under the control of a T7 promoter, and the host (BL21(DE3)) contains T7 RNA polymerase (or a T7 RNAP that can be induced by IPTG). Upon addition of the inducer (IPTG), expression of T7 RNAP is induced, which in turn drives high-level expression of the target protein in the cells. The resulting plasmid was introduced into E. coli BL21(DE3) via chemical transformation, and the colony plates are shown in the figure 17.

Figure 17. Verification of BL21(DE3) chemical transformation results

Single colonies from the figure above were expanded in 600 ml of culture and induced with IPTG for overnight expression at 16°C. The cells were collected, washed, lysed, and centrifuged for subsequent purification. Ni²⁺ and other metal ions exhibit high specificity and chelating ability toward His-tagged fusion proteins, allowing the fusion proteins to be captured on a designated chromatographic medium while untagged proteins are washed away. Using this principle, the protein was purified, and the purified fractions were analyzed by SDS-PAGE. The results are shown in the figure.

Figure 18. SDS-PAGE of Cas12a

The figure clearly displays the bands corresponding to the crude protein, wash fractions, and purified protein. Lanes E1–E5 represent the purified protein, showing a strong band at the target position (approximately 120 kDa) with very high concentration and minimal contaminating proteins, indicating high efficiency of protein expression and purification. This observation is further supported by the bands in the crude protein sample. In contrast, the wash fractions contain mostly contaminating proteins and only trace amounts of the target protein.

4.1 Screening ComDNA for the highest signal-to-noise ratio

We constructed the biosensor using Aptamer-3. And we were constructed using five different sources of ComDNA and incubated with BD-Tau at the same concentration. Following the experimental procedure, the released protein–aptamer-3–dsDNA complexes were collected, and the dsDNA content was quantified by qPCR. The sample with the highest dsDNA content was identified, thereby confirming the ComDNA with the highest signal-to-noise ratio. The results are shown in the figure 19.

Figure 19. qPCR verification of the ComDNA with the highest signal-to-noise ratio

As shown in figure 19, only ComDNA3 exhibited a relatively high signal-to-noise ratio, while the other samples showed no significant signal in the test.

4.2 Fluorescence intensity detection of BD-Tau protein at different concentrations

An aptamer-3-based biosensor was constructed using ComDNA3, and we further incorporated the Cas12a cleavage module, enabling the sensor to convert aptamer recognition events into amplified fluorescent signals, thereby establishing a complete detection model. To evaluate its feasibility in practical applications, we designed a concentration gradient experiment based on the physiological concentration range of BD-Tau protein in Alzheimer’s disease patients. Samples at different concentrations were then added to the sensing system, and the changes in fluorescence signals were monitored in real time using a microplate reader.

Figure 20. Fluorescence intensity detection of BD-Tau protein at different concentrations

The differences in signal between concentrations were not pronounced, and the sensitivity remains limited. This observation suggests that there is still room for improvement in the detection performance of the current system, potentially due to insufficient aptamer binding affinity or low efficiency of complex release.

To validate the feasibility of the biosensor, we selected a Tau protein aptamer sequence (target: 2N4R-Tau) that was previously characterized. To verify whether aptamer binding affects the spatial conformation of dsDNA and thereby influences subsequent signal transduction efficiency, we designed a comparative experiment. In brief, one system contained only the naked dsDNA fragment as a control, to test the activation capacity of Cas12a in the absence of aptamer interference. The other system represented the complete sensor setup, including the aptamer–dsDNA complex and T-Tau protein, to evaluate whether signal transduction remains effective when the aptamer participates and binds to the target protein. The results, quantified by fluorescence microplate reader, are shown figure 21.

Figure 21. Validation of whether aptamer binding affects dsDNA-mediated Cas12a activation (T-Tau)

The figure 21 showed that when 30 μM tau protein was added to the system, the sensor’s response reached, or even slightly exceeded, the signal level observed with naked dsDNA alone. This indicates that the binding of the aptamer to tau protein did not negatively affect the conformation of dsDNA or its ability to activate Cas12a.

2.1 Screening for ComDNA with Optimal Signal-to-Noise Ratio

To further evaluate the binding efficacy of ComDNA to the Tau aptamer-dsDNA complex and ensure efficient dissociation of ComDNA upon Tau protein. We designed five ComDNA variants (ComDNA1–ComDNA5) for systematic testing. Following incubation with an excess of Tau protein, the released Tau aptamer-dsDNA complex was quantified using quantitative PCR (qPCR). A control group, in which the Tau protein was replaced with an equivalent volume of water, was included to calculate the signal-to-noise ratio. This allowed for the screening of the ComDNA sequence with the highest signal-to-noise ratio.

Figure 22. Signal-to-noise ratio of ComDNA verified with T-Tau (Normalization Gene:actin )

The figure 22 clearly indicate that under the positive control condition with T-Tau, the sensor generated a significant fluorescent response, confirming the overall feasibility of the system. Additionally, in the comparative experiments among different ComDNAs, ComDNA3 outperformed the other sequences, exhibiting a higher signal-to-noise ratio and a more stable response.We have selected ComDNA3 as the linker to construct the biosensor.

2.2 Determination of Tau Aptamer-dsDNA Complex Concentration

Following the screening of the aptamer switch ComDNA3, it is necessary to determine the optimal concentration of the Tau aptamer-dsDNA complex. Different concentrations of the Tau aptamer-dsDNA complex were used to construct the "magnetic bead-biotinylated ComDNA-Tau aptamer-dsDNA" complex. The signal-to-noise ratios at different Tau aptamer-dsDNA concentrations were evaluated to identify the optimal concentration.

Figure 23. Determination of the concentration of the T-Tau aptamer–dsDNA complex

Figure 23 shows that the signal intensity increases with rising nucleic acid aptamer concentration, reaching a plateau between 10 μM and 20 μM. The system demonstrated maximum response at 10 μM. and 20μM .Therefore, 10 μM is likely the optimal concentration for the aptamer–dsDNA complex.

2.3 Determination of Incubation Time for T-tau with the Biosensor

To determine the optimal incubation time between the target protein and the sensor for practical applications, we designed and conducted a corresponding experiment. Under the same protein concentration, samples were incubated for different durations, and the fluorescence signals at each time point were collected and measured to compare the trend of signal intensity over time.

Figure 24. Determination of the incubation time between T-Tau and the aptamer–dsDNA complex

The figure 24 showed that the fluorescence intensity reached its maximum after 40 minutes of incubation, and further extension of the reaction time did not result in any significant increase in signal. This indicates that at 40 minutes, the binding between the target protein and the sensor had essentially reached saturation, and the system had completed effective signal transduction. Therefore, 40 minutes was determined to be the optimal incubation time for this sensor in practical applications.

3.1 Protocol for Standard Curve Preparation

Following the optimization of the above conditions—with ComDNA3 selected as the linker, the Tau aptamer–dsDNA complex concentration set at 10 μM, and the incubation time determined as 40 minutes—we proceeded with the detection of Tau protein.

Based on the designed sensor structure, sensor units were constructed using T-Tau and its corresponding Tau-aptamer. Gradient concentrations of T-Tau were added to generate a standard curve. The results are shown in the figure 25.

Figure 25. Standard curve of T-Tau

As shown in the figure 25, the fluorescence intensity exhibited a clear linear relationship with the target protein concentration. This result indicates that the release of the aptamer–dsDNA and the subsequent activation of Cas12a trans-cleavage are quantitatively dependent on the amount of protein present in the system. The observed linearity not only demonstrates the sensitivity of the sensing module but also validates its reliability for quantitative detection. Such linear correlation strongly supports that the system can be calibrated using a standard curve, thereby enabling accurate concentration measurements in practical applications. These findings not only confirm the applicability of the sensor but also highlight its potential for further optimization in real biological samples.

3.2 Biosensor Specificity Evaluation

Next, we evaluated the recognition specificity of this module, including T-Tau, bovine serum albumin (BSA), human serum albumin (HSA), IgE, and IgG. The results are shown figure 26.

Figure 26. Protein specificity detection of T-Tau

The results showed that this module exhibited a significant response to T-Tau, while no detectable response was observed for common interfering proteins in blood. This finding highlights the excellent specificity of the system, indicating that the sensor can effectively distinguish the target protein from background proteins

This is our flow symmetry result on the product of different round of SELEX process. RFU means the intensity of fluorescent signal that released by RAM we placed on F primer in PCR. As depicted in the Figure 27, the RFU increased progressively from round 1 to round 6, reflecting a gradual enrichment of aptamers with binding affinity for BD-tau. After round 6, we initiated reverse screening to eliminate non-specific binders, resulting in a noticeable decline in RFU. By round 12, following additional rounds of stringent selection, the RFU decreased substantially, indicating that only a small pool of aptamers with the highest affinity remained.

Figure 27.Flow symmetry concerning the product of various rounds of the SELEX process

We employed 27 DNA sequences obtained from the SELEX system to predict their interactions with Tau and BD-Tau proteins through molecular docking, aiming to screen nucleic acid aptamers with higher binding affinity. The PDB files of Tau and BD-Tau proteins were acquired from AlphaFold. Both files were submitted to the HADDOCK 2.4 platform (https://rascar.science.uu.nl/haddock2.4), which facilitates complex molecular docking and interaction analysis for researchers. For detailed modeling procedures, click here: https://2025.igem.wiki/keystone/model

Table 2. Nucleic Acid Aptamer Sequences and Z-Scores

Based on the molecular docking results of all 27 DNA sequences listed in Table 2, the binding strength between the DNA sequences and the target proteins was evaluated using Z-scores. A lower Z-score indicates a higher binding potential. We specifically prioritized nucleic acid aptamers exhibiting strong binding affinity to BD-Tau while showing weak affinity to Tau protein. This screening process identified three DNA sequences—Aptame-08, Aptame-14 and Aptame-16—with promising docking results.

Figure 28. Affinity assessed by using surface plasmon resonance

Figure 29. Affinity assessed by using surface plasmon resonance

Figure 30. Affinity assessed by using surface plasmon resonance

To identify the nucleic acid aptamer with the highest binding affinity for BD-tau from Aptamer-08, Aptamer-14, and Aptamer-16, we employed Surface Plasmon Resonance (SPR) technology. After we have our aptamer, we tested its affinity by SPR. the first graph shows how the concentration of aptamer affect the amount of energy needed to separate our aptamer and its target protein. It selected 5 different concentration of aptamer to do the SPR. The second graph then graphed out the first graph with x-axis changed to the concentration of aptamer and derived a logistic best fit line. Then, we get the mid point of the graph, thats our Kd value. As we tested other aptamers using the SPR, the lower the Kd value is, the higher energy will be needed to seperate aptamer and target protein, which means higher affinity.

As shown in the figure 28, 29 and30, the Kd values for Aptamer-08, Aptamer-14, and Aptamer-16 are 11.32, 6.38, and 21.38, respectively. Among them, Aptamer-14 demonstrates the lowest Kd value compared to Aptamer-08 and Aptamer-16, indicating it possesses the highest binding affinity for BD-tau. Based on the Kd values, we selected Aptamer-14 as the nucleic acid aptamer with the strongest affinity for BD-tau from the three candidates, and subsequently validated its specificity for BD-tau using ELISA.

We further validated the binding affinity of Aptamer-14 using ELISA. To simulate conditions in AD and non-AD patients, artificial blood was spiked with varying concentrations of BD-tau and peripheral tau, thereby minimizing potential interference from other factors. Specifically, the biotinylated nucleic acid aptamer Aptamer-14 was immobilized on ELISA plates, followed by incubation with BD-tau protein and colorimetric detection. The measured absorbance quantitatively reflected the relative concentration of BD-tau protein.

Figure 31. Quantitative binding analysis of BD-Tau aptamer in simulated plasma environments

In the above figure 31, the first graph shows how the increase concentration of our aptamer has a positive correlatipn with the binded BD-tau level. we can see for the AD group plasma we classified Elisa all tested out a high BD-tau level, and control group has a significantly lower BD-tau level tested out. which shows aptamer can still accurately detect AD in Plasma envrionment. the nucleic acid aptamers obtained from the second round of SELEX screening demonstrated significantly enhanced binding affinity compared to those from the initial screening, validating the effectiveness of our SELEX platform. This confirms that the SELEX technology can be widely applied to screen nucleic acid aptamers for other target proteins. Furthermore, the results indicate that Aptamer-14 exhibits high-affinity interaction with BD-tau, making it suitable for constructing a biosensor to detect BD-tau.

We formed a complex using Aptamer-14 and dsDNA to further validate whether the structure of the nucleic acid aptamer affects Cas12a cleavage efficiency. Using 10 μM dsDNA as a positive control, Figure 32 demonstrates that the relative fluorescence intensity increases with rising dsDNA concentration. The signal observed at 10 μM dsDNA was higher than that of the control group, demonstrating that the incorporation of the aptamer does not compromise Cas12a-mediated cleavage efficiency.

Figure 32. Validation of whether aptamer binding affects dsDNA-mediated Cas12a activation (BD-Tau)

2.1 Screening for ComDNA with Optimal Signal-to-Noise Ratio

Melt Curve

This panel shows the raw melt curves for the different BD-Tau aptamer–ComDNA duplexes. On the x-axis is temperature (°C) and on the y-axis is fluorescence (RFU). As the temperature increases, the double-stranded regions of each dsDNA gradually denature into single strands, causing the dye that intercalates into double-stranded DNA to be released and the fluorescence to decrease. The downward slopes and inflection points indicate the melting transition of each duplex. Curves with a sharper, more defined drop represent more uniform and stable duplexes, while broader transitions suggest heterogeneous structures or weaker binding.

Melt Peak

This plot displays the derivative of the melt curve (–dRFU/dT vs. temperature), which highlights the temperature at which the most rapid loss of fluorescence occurs—effectively the melting temperature (Tm) peak. Each distinct peak corresponds to a specific duplex population. A higher, sharper peak at a specific temperature indicates a stronger and more uniform duplex, while multiple or broad peaks indicate heterogeneity. Comparing the Tm values across ComDNA candidates lets you identify which constructs form the most stable and predictable complexes with the aptamer.

Amplification Curves

This panel shows real-time amplification curves (RFU vs. cycle number) for reactions containing the T-Tau aptamer–ComDNA complexes. Each curve represents fluorescence accumulation as the reaction progresses. Early, steep rises indicate rapid signal generation and efficient Cas12a activation, while late or shallow curves reflect slower or weaker responses. By comparing the amplification profiles of different ComDNA candidates, you can gauge both sensitivity and kinetics—ideally you want a construct that shows an early threshold cycle and high end-point fluorescence.

Figure 33. Signal-to-noise ratio of ComDNA verified with BD-Tau (Normalization Gene:actin )

The figure 33 clearly indicate that under the positive control condition with BD-Tau, the sensor generated a significant fluorescent response, confirming the overall feasibility of the system.The relative fluorescence value of ComDNA3 was significantly higher than that of other groups, indicating that ComDNA3 achieves the highest signal-to-noise ratio. These experimental results are consistent with the findings presented in Cycle 3, confirming the selection of ComDNA3 for biosensor fabrication.

2.2 Determination of BD-tau Aptamer 14-dsDNA Complex Concentration

Figure 34. Signal-to-noise ratio of ComDNA verified with BD-Tau (Normalization Gene:actin )

Figure 34 shows that the signal intensity increases with rising nucleic acid aptamer concentration. The system demonstrated maximum response at 10 μM .

2.3 Determination of Incubation Time for BD-tau with the Biosensor

Figure 35. Signal-to-noise ratio of ComDNA verified with BD-Tau (Normalization Gene:actin )

The figure 35 showed that the fluorescence intensity reached its maximum after 40 minutes of incubation, and further extension of the reaction time did not result in any significant increase in signal. This indicates that at 40 minutes, the binding between the target protein and the sensor had essentially reached saturation, and the system had completed effective signal transduction. Therefore, 40 minutes was determined to be the optimal incubation time for this sensor in practical applications.

3.1 Standard Curve

Based on the optimized conditions described above, the biosensor has constructed using Aptamer-14. This linearity means that within this concentration range the assay behaves quantitatively: every increase in protein concentration produces a proportional increase in fluorescence. The slope of the line represents assay sensitivity; the steeper the slope, the greater the response per unit of protein. The intercept near zero indicates very low background, suggesting minimal non-specific activation of Cas12a. With this curve, unknown samples can be interpolated accurately by matching their fluorescence to the line. Replicates plotted at each concentration also demonstrate reproducibility, with small variation between points. Together, these data confirm that the BD-Tau aptamer 14–dsDNA–Cas12a system can be used not just for detection but for quantitative measurement of BD-Tau protein over a defined range.

Figue 36.The Standard Curve of BD-tau

3.2 Biosensor Specificity Evaluation

Figure 37. Specificity Testing of BD-tau Protein

This figure compares relative fluorescence signals generated by the system when exposed to BD-Tau and several unrelated proteins (bovine serum albumin, human serum albumin, immunoglobulin E, immunoglobulin G). Only the bar corresponding to BD-Tau shows a strong signal; all other proteins produce minimal responses near baseline. This demonstrates that the aptamer–dsDNA complex specifically recognizes BD-Tau and does not significantly bind or activate Cas12a in the presence of abundant off-target proteins. The low background from serum albumins and immunoglobulins indicates the assay is likely to remain specific even in complex biological samples such as blood or cerebrospinal fluid. The error bars are small, indicating good reproducibility of these specificity measurements. These results validate the selectivity of the BD-Tau detection system and support its potential application as a reliable biomarker assay.

We attached platinum nanoparticles (PtNPs) to the 3' end of the nucleic acid aptamer, while conjugating the aptamer to complementary DNA (ComDNA). The other end of ComDNA was immobilized to streptavidin-coated magnetic beads via biotin linkage (Li et al., 2016; Song et al., 2011). In the presence of BD-tau, the activated CRISPR-Cas12a system cleaves the substrate, and the resulting supernatant is transferred to a hydrogen peroxide (H₂O₂) chamber. The PtNPs catalyze the decomposition of H₂O₂ into water and oxygen, and the released oxygen propels the red-dyed silicone oil to move forward. The distance of movement correlates with BD-tau concentration—higher levels result in greater displacement of the indicator (Figure 38).

Chip Architecture Design:

Sample Injection Zone: For loading serum/plasma samples to be tested

Reaction Microchamber: Pre-loaded with H₂O₂ solution as catalytic reaction substrate

Signal Detection Zone: Filled with red-dyed silicone oil as visual flow indicator

This innovation provides crucial technical support for developing a new generation of portable rapid AD diagnostic devices, effectively addressing the limitations of traditional laboratory methods such as complex procedures, long processing times, and dependence on large-scale instruments.

Figure 38.Microfluidic Sensor Principle

We also developed a lab prototype for our TauTrack microfluidics diagnostic platform and tested the its functionality accordingly. Please note that due to issues of time and material (especially the difficulty and time-consuming nature of producing integrated platinum nanoprobes, we chose an alternative using aptamer–comDNA–PtNP. By doing so we can design and experiment with all core functions of the TauTrack “samplein, resultout” microfluidics platform comprised “onchip no human interference” without changing the chip device process.

How to Reconstitute？

A BD‐Tau aptamer is used to bind the PtNP.

The Aptamer contains a short "dock" sequence that will hybridize with a complementary DNA (comDNA).

Streptavidin‐coated magnetic beads are used to capture the biotinylated comDNA. PtNPs are initially fixed to the beads through the aptamer‐comDNA duplex as a complete sensor.

How It Fits the Workflow on‐chip in Three Stages

Stage 1: Target identification and release

BD‐Tau in the sample will bind the aptamer to destabilize the duplex (assisted by a designed toehold) and displace the comDNA.

Results: The PtNP‐aptamer is released into solution and the comDNA remains on the bead. The level of released PtNPs increases as the BD‐Tau concentration rises.

Stage 2: Magnetic separation

A magnet placed externally immobilizes the beads (together with any PtNPs which are still tethered).

Only the supernatant containing truly released PtNPs can pass through to the next chamber.

Stage 3: Catalytic amplification and readout

The released PtNPs cause decomposition of H2O2 to generate oxygen in a closed chamber.

The pressure which is produced pushes a colored ink slug; the distance it moves reflects the level of BD‐Tau.

Representative Results Showcase:

We have preliminarily validated the feasibility of using microfluidic technology for AD detection with Aptamer-14. The figure shows that Line 4 and Line 5 exhibit slightly higher signals than Line 1, Line 2, and Line 3, demonstrating the operational functionality of our microfluidic chip. However, further optimization is required in practical operation.

Figure 39.Microfluidic Sensor result.