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. 2022 Dec 26;255:124221. doi: 10.1016/j.talanta.2022.124221

An ultrasensitive fluorescence aptasensor for SARS-CoV-2 antigen based on hyperbranched rolling circle amplification

Zecheng Wang 1, Chenchen Zhang 1, Si He 1, Danke Xu 1,∗
PMCID: PMC9792189  PMID: 36608425

Abstract

Sensitive and accurate diagnosis of SARS-CoV-2 infection at early stages can help to attenuate the effects of the COVID-19. Compared to RNA and antibodies detection, direct detection of viral antigens could reflect infectivity more appropriately. However, it is still a great challenge to construct a convenient, accurate and sensitive biosensor with a suitable molecular recognition element for SARS-CoV-2 antigens. Herein, we report a HRCA-based aptasensor for simple, ultrasensitive and quantitative detection of SARS-CoV-2 S1 protein and pseudovirus. The aptamer sequence used here is selected from several published aptamers by enzyme-linked oligonucleotide assay and molecular docking simulation. The sensor forms an antibody-target-aptamer sandwich complex on the surface of microplates and elicits HRCA for fluorescent detection. Without complicated operations or special instruments and reagents, the aptasensor can detect S1 protein with a LOD of 89.7 fg/mL in the linear range of 100 fg/mL to 1 μg/mL. And it can also detect SARS-CoV-2 spike pseudovirus in artificial saliva with a LOD of 51 TU/μL. Therefore, this simple and ultrasensitive aptasensor has the potential to detect SARS-CoV-2 infection at early stages. It may improve the timeliness and accuracy of SARS-CoV-2 diagnosis and demonstrate a strategy to conduct aptasensors for other targets.

Keywords: Aptasensor, SARS-CoV-2, S1-protein, Pseudovirus, HRCA

Graphical abstract

Image 1

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1. Introduction

By August 2022, the Coronavirus disease 2019 (COVID-19) pandemic, resulted by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has caused about 590 million confirmed cases and 6 million deaths globally (WHO, http://covid19.who.int/). The virus can affect a variety of organs, including the lungs, heart, and brain, and cause long-term health problems after cured [1,2]. Effective diagnosis of the virus can help to attenuate the effects of the COVID-19 [2]. Currently, three accepted SARS-CoV-2 detection methods are: 1) Detection of viral ribonucleic acid (RNA); 2) Detection of specific antibodies targeting viral antigens; 3) Detection of viral antigens, mostly nucleocapsid (N) protein and spike (S) protein [3]. Quantitative detection of viral RNA by reverse transcription polymerase chain reaction (RT-PCR) is the gold standard method for diagnosing SARS-CoV-2 infection. However, such method requires sample preparation, including RNA extraction, and calls for experienced operators [4]. For the detection of specific antibodies, it is limited by sensitivity and ‘delayed’ seroconversion. To detect effective antibody responses, it usually takes 1–2 weeks after initial symptoms, which is not suitable for diagnosis of the early-stage infection [3,5]. In comparison, direct detection of viral antigens could reflect infectivity more appropriately [6]. Currently, enzyme-linked immunosorbent assay (ELISA) and lateral flow immunoassays (LFIA) have been used to detect viral antigens [7,8]. These methods usually use artificial antibodies as probes to directly detect viruses in blood or saliva without pretreatment. However, moderate sensitivity (several pM) limits the practical application of these methods to early-stage infections [9]. Hence, there is an urgent need for convenient and sensitive detection of viral antigens.

The issue is to explore the specific molecular recognition element with sensitive signal amplification system. Aptamers, known as ‘chemical antibodies’, are short sequences of synthetic oligonucleotides with comparable affinity to antibodies [10]. Due to their small size, flexible structure, low cross reactivity and immunogenicity, aptamers are highly suited as the recognition elements in SARS-CoV-2 sensors [11]. Several antigen-specific aptamers have already been identified recently with different performances [12]. Furthermore, aptamers can flexibly connect to various nucleic acid amplification methods by terminal extension or strand competition [13]. This makes aptamers more easily construct ultrasensitive SARS-CoV-2 antigen biosensors with the help of signal amplification methods. A number of SARS-CoV-2 antigen aptasensors have been published, such as a surface enhanced Raman spectroscopy (SERS) aptasensor [14] based on strand displacement amplification (SDA); a fluorescent aptasensor [15] combined with PCR; a fluorescent sandwich aptasensor [16] contained recombinant polymerase amplification (RPA) and an electrochemical aptasensor [17] based on clustered regularly interspaced short palindromic repeats (CRISPR). However, the performance of aptamers, the efficiency of nucleic acid amplification methods, and the complexity of detection strategies greatly affect the sensitivity and application fields of such biosensors. Few such aptasensors can combine simplicity with ultra-high sensitivity. Therefore, it is still challenging to single out a suitable aptamer sequence and construct a simple, accurate and ultrasensitive aptasensor for SARS-CoV-2 antigens.

In this work, we developed a fluorescent aptasensor in 96-well plates for SARS-CoV-2 antigen S1 protein based on isothermal hyperbranched rolling cycle amplification (HRCA). The detection process of our aptasensor is similar to ELISA, which is simple and can be quickly mastered by inexperienced operators. At the same time, without the need of special instruments and reagents, the aptasensor exhibits ultra-high sensitivity. Its performance is better than most of the published SARS-CoV-2 aptasensors. In order to achieve expected requirements, we first selected the optimum sequence from several published aptamers. Enzyme-linked oligonucleotide assay (ELONA) was employed here to simulate the proposed detection process. And molecular docking simulation was applied to verify the sequence feasibility in theory. Subsequently, the proposed aptasensor was conducted. In the presence of the target, the sensor forms an antibody-target-aptamer sandwich complex on the surface of microplates and elicits HRCA via a primer located at the terminal of the aptamer. SYBR Green I was used to indicate the reaction in real-time fluorescence detection. The aptasensor exhibited excellent sensitivity and selectivity. It also can directly quantitate SARS-CoV-2 spike pseudovirus in artificial saliva. The results demonstrate that the developed aptasensor has the potential to ultra-sensitively, accurately, and conveniently detect SARS-CoV-2 viruses in patients’ saliva. It has a more simple detection process than clinical RT-PCR methods and has a lower limit of detection than commercial ELISA antigen kit. This indicates that our developed aptasensor can meet the current demand for rapid clinical detection of early-stage infections. At the same time, it has a degree of demonstration effect on selecting the sequence and constructing the aptasensor.

2. Materials and methods

2.1. Preparation of circular templates (CTs)

Before the ligation, 8 μM padlock and 10 μM CDNA were mixed in T4 DNA ligase reaction buffer and kept at 95 °C for 5 min. After returned to room temperature, 20 U/μL T4 DNA ligase was added and incubated at 16 °C overnight. Then exonuclease I (0.4 U/μL) and III (2 U/μL) were added to the solution at 37 °C for 4 h. The purification was carried out using the oligonucleotide cleanup protocol contained in a commercial PCR & DNA cleanup kit. The final concentration of CTs was measured by Nanodrop (Thermo Fisher Scientific Inc., Waltham, USA). The prepared CTs were stored at 4 °C for further use.

2.2. Fluorescent measurement based on HRCA

96-well plates (Thermo Fisher Scientific Inc., Waltham, USA) were pre-coated with 2 μg/mL antibodies in the coating buffer at 4 °C overnight. After one wash, blocking buffer was added at 37 °C for 2 h. After the wash step, 1 μg/mL S1 protein was added at 37 °C for 2 h with gentle shaking (350 rpm). After three washes, 500 nM DSA1N5C was added at 37 °C for 1 h, followed by 500 nM CTs for another 1 h. After five washes, HRCA reaction solution was added. The fluorescence was monitored every 10 min and continuously for 2 h at 30 °C. The emission spectra were collected from 510 to 650 nm with an excitation wavelength of 485 nm. The emission slit width was set at 5.0 nm. The fluorescence intensity at 525 nm was used for quantitative analysis.

2.3. Gel electrophoresis

When applied to analyze the products of HRCA, 0.6% agarose gel electrophoresis in 1 × TAE was performed at 120 V in ice bath for 3 h. Then the gel was stained by nucleic acid stain for 30 min. When applied to analyze CTs, 2% agarose gel electrophoresis in 0.5 × TBE was performed at 120 V in room temperature for 30 min. All gel images were taken through GelSMART (DLAB Scientific Co., Ltd, Beijing, China).

2.4. The sensitivity and specificity of the assay

The sensitivity was evaluated by using 10-fold serial dilutions of the S1 protein. The specificity of the assay was measured by using undiluted artificial saliva, S1 protein (1 μg/mL) and 4 other protein sample (1 mg/mL, a thousand times that of S1 protein) including influenza hemagglutinin peptide fragment 1 (HA1), human serum albumin (HSA), bovine serum albumin (BSA) and His.

2.5. Detection SARS-CoV-2 spike pseudoviruses in artificial saliva

The pseudoviruses were serially diluted in artificial saliva by 2-fold before detection. This part of the experiment was carried out in a secondary biosafety laboratory, and all the reaction waste was treated carefully after being inactived at 120 °C for 20 min.

3. Results and discussion

3.1. Principle of the aptasensor

The working principle of the aptasensor are illustrated in Scheme 1 . The SARS-CoV-2 spike antibody is firstly immobilized on the bottom of 96-well plates via physical adsorption. In the presence of S1 protein, the target binds to antibodies through antibody antigen interactions. After adding the aptamer DSA1N5C, which specifically binds to the S1 protein, an antibody-S1-aptamer sandwich complex is formed. Meanwhile, one terminal of DSA1N5C, which is the complementary to CTs, doesn't take part in the interaction with S1 protein. This enables new added CTs to bind to DSA1N5C through base pairing. Thus, an antibody-S1-aptamer-CTs complex is formed. The HRCA reaction solution is then added to amplify CTs on DSA1N5C by Phi29 polymerase. Afterwards, P1 and P2 further amplify on the CTs amplified product. The HRCA products contain large quantities of double-stranded DNA fragments and can achieve 109-fold amplification under ideal conditions [18]. As a common double-stranded DNA fluorescent indicator [19], SYBR Green I is used here to generate a fluorescent signal and indicate the reaction. The intensity of fluorescence have a direct relationship with the concentration of S1 protein. In the absence of S1 protein, DSA1N5C cannot be retained in the microplates through the sandwich complex. And without the help of the complementary strand, CTs cannot participate in the subsequent amplification process. Then HRCA cannot generate. So only a low fluorescent background is detected. Based on this principle, an ultrasensitive fluorescent aptasensor targeting SARS-CoV-2 S1 protein can be realized.

Scheme 1.

Scheme 1

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Schematic illustration of the HRCA based aptasensor for SARS-CoV-2 S1 protein.

3.2. Selection of the optimum aptamer

The aptamer's capability can greatly affect the performance of the aptasensor. We collected several published aptamers targeting SARS-CoV-2 S1 protein (listed in Table S1). Among them, SSapt1 is screened via systematic evolution of ligands by exponential enrichment (SELEX) in sillicon, and DSA1N5 is assembled from MSA1T and MSA5T. The other 6 aptamers are screened by SELEX. All the affinities measured by SPR are in the nM level. We then used ELONA to simulate the proposed detection process and evaluate the performances of biotinylated aptamers. The main points are the ability to form antibody-S1-aptamer sandwich complex, and the specificity exhibited via this complex. As shown in Fig. S1, the S1 antibody was first immobilized on the surface of microplates and captured S1 protein. Then biotinylated aptamers bound to S1 protein and formed a sandwich complex. Next, peroxidase-conjugated streptavidin (SA-HRP) was combined with aptamers via the biotin–avidin system. And 3, 3′, 5, 5′-tetramethylbenzidine (TMB) was catalyzed to generate a colored solution. After 20 min, the reaction was terminated and the signal was measured using a microplate reader. Furthermore, since the performance of aptamers is easily affected by the environment [20], the dissolving buffers of each aptamer in this work were consistent with which in the original SELEX papers.

The evaluation results are shown in Fig. 1 . The aptamers were tested under three concentrations of S1 protein (0.04, 0.2, 1 μg/mL). XN268s has a signal below 0.1 in all conditions. This indicates that this aptamer may compete with the antibody and fail to form a sandwich complex. The other 7 aptamers all have an OD450nm above 0.5, and their signals increase with the increasing concentrations of S1 protein. It means these 7 aptamers can all form the antibody-S1-aptamer complex. Moreover, DSA1N5 has the highest absorption intensity at every S1 protein concentrations and the highest signal rising trend with increasing S1 protein concentrations. And this is in accord with its best affinity (listed in Table S1). Therefore, DSA1N5 was selected for subsequent experiments.

Fig. 1.

Fig. 1

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(A) Performances of 8 biotinylated aptamers (500 nM) evaluated by ELONA under 0.04, 0.2, 1 μg/mL S1 protein. (B) The relationship between the absorbance and the logarithm of S1 protein concentrations (ranging from 64 pg/mL to 1 μg/mL) under 500 nM biotinylated DSA1N5. The absorbance reveals a linear correlation with the logarithm of the S1 protein concentration in the range 320 pg/mL to 1 μg/mL (linear line) with an LOD of 163 pg/mL. The error bars are the standard deviation of three repetitive measurements.

Furthermore, we evaluated the sensitivity of ELONA constructed by DSA1N5. As shown in Fig. 1B, signals were recorded under different concentrations of S1 protein. The absorption increases gradually with the increasing concentration. And a linear relationship appears between the absorption intensity and the logarithm of S1 protein concentration from 320 pg/mL to 1 μg/mL. The linear equation is OD450nm = 0.14 log CS1 + 1.25, (R2 = 0.9916). The LOD was 163 pg/mL (S/N = 3).

3.3. Sequence feasibility tested by molecular docking simulation

The proposed aptasensor requires an extended region at the terminal of DSA1N5 to bind with CTs. The effect of this region on the recognition process of DSA1N5 and S1 protein needs to be investigated. As shown in Fig. S2A, CDNA was extended at the 3’ terminal of DSA1N5. And it can hybridize with CTs. To further decrease the effect of CDNA, a spacer was added. The whole sequence was named DSA1N5C. No interactions between CDNA and the aptamer can be observed in the secondary structure.

Molecular docking simulations are usually used to investigate the interactions between aptamers and their targets [10]. However, in this work, we used the simulation to investigate the effect of CDNA region on the recognition between DSA1N5C and S1 protein. The three-dimensional (3D) ribbon model of DSA1N5C was generated through RNAcomposer [21,22], w3DNA [23], NAMD [24] and VMD [25]. And the 3D space model of S1 protein was obtained from PDB Bank [26,27] and VMD. HADDOCK [28,29] was employed for docking simulation between DSA1N5C and S1 protein. And the result with the best HADDOCK score was further analyzed. As shown in Fig. S2B, orange, green, red indicate DSA1N5, spacer and CDNA region in DSA1N5C, respectively. CDNA region is completely exposed to the outside and doesn't take part in the interaction towards S1 protein. And the spacer acts as expected, pushing the CDNA away from S1 protein. We then employed LigPlus [30] to further analyze the interaction of DSA1N5C–S1 complex. The CDNA region (ADE115 (B) – GUA135 (B)) forms neither hydrogen bonds nor hydrophobic interactions with S1 protein(Fig. S2C-H). Hence, the designed CDNA region can act as the complementary strand of CTs in the subsequent experiments. And DSA1N5C can meet the design requirements in theory.

3.4. Assay feasibility test

The difference between the positive signal and other signals was investigated. As shown in Fig. 2 A, without the protein targets, we obtained nearly no fluorescent signal by using original aptamer DSA1N5 as the probe. This indicates that the adsorption of CTs on the blocked antibody-microplate surface is negligible because DSA1N5 cannot bind to CTs. When it came to DSA1N5C which has a CDNA region, a low fluorescent signal was obtained. It means that the blocked antibody-microplate surface can well prevent the non-specific adsorption of DSA1N5C. Two negative assays were also performed including detecting S1 protein by N40C and detecting BSA by DSA1N5C. Both fluorescent intensity increased to about 5000 a.u. after 6 h reaction. Their signal rising trends could be identified. However, the signal of the positive assay in which S1 protein was detected by DSA1N5C, increased to about 27,500 a.u. in 6 h. It is much higher than that of the negative assays. This indicates that the antibody-S1-DSA1N5C-CTs complex is an important factor for realization of the proposed aptasensor. Meanwhile, as the positive reaction started, the fluorescence signal first increased quickly with the time increasing, then gradually reached a plateau after 2 h. Automatic termination of the reaction can be due to a decrease in dNTPs concentration or enzyme activity. Hence, 2 h is enough for the reaction to complete. The positive fluorescence signal at 2 h can also be distinguished from other signals (Fig. 2B) and used for analysis.

Fig. 2.

Fig. 2

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Feasibility of the aptasensor. (A) Real-time fluorescence under different samples and nucleic acid probes for 6 h (S1 protein + DSA1N5C (positive sample and probe); BSA + DSA1N5C (negative sample); S1 protein + N40C (negative probe); DSA1N5C (blank sample); DSA1N5 (blank sample with no HRCA reaction)). The final concentrations of S1 protein, BSA, nucleic acid probe are 1 μg/mL, 1 mg/mL and 500 nM, respectively. (B) The fluorescence emission spectra (λex = 485 nm) under various conditions described in (A) after 2 h reaction. The error bars are the standard deviation of three repetitive measurements.

We used agarose gel electrophoresis to investigate CTs. The lack of padlock, CDNA, or T4 DNA ligase cause no ligation products (Fig. 3 A lane 2–4). Before the purification, large amounts of CTs and padlock-CDNA polymers can be recognized with a little of unreacted CDNA (Fig. 3A lane 5). After the purification, most of remained products are CTs (Fig. 3A lane 6). After DSA1N5C is incubated with CTs, the bands of DSA1N5C rise to larger bps, indicating that DSA1N5C can form a stable complex with CTs (Fig. 3A lane 1 and 7). We also used agarose gel electrophoresis to investigate HRCA. The lack of Phi29 polymerase, dNTPs, or CTs cause no amplification products (Fig. 3B lane 1–3). The RCA and HRCA both have products mainly bigger than 10 k bp (Fig. 3B lane 4–5). However, the bands of HRCA have a brighter fluorescence than that of RCA. This indicates that HRCA is more efficient than RCA, which is consistent with the results of fluorescence assays above.

Fig. 3.

Fig. 3

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(A) Agarose gel electrophoresis image of CTs obtained after the ligation and purification reaction (1. DSA1N5C; 2. CDNA + T4 DNA ligase + Exonuclease I + Exonuclease III (no ligation); 3. T4 DNA ligase + padlock + Exonuclease I + Exonuclease III (no ligation); 4. CDNA + padlock + Exonuclease I + Exonuclease III (no ligation); 5. CDNA + T4 DNA ligase + padlock (no purification); 6. CDNA + T4 DNA ligase + padlock + Exonuclease I + Exonuclease III (ligation and purification); 7. CTs (product of 6) + DSA1N5C)). The final concentrations of DSA1N5C, padlock, CDNA, CTs are 5 μM，8 μM，10 μM，5 μM, respectively. (B) Agarose gel electrophoresis image of HRCA products obtained after 2 h reaction (1. DSA1N5C + CTs + dNTPs + P1 + P2 (no HRCA); 2. DSA1N5C + CTs + Phi29 polymerase + P1 + P2 (no HRCA); 3. DSA1N5C + Phi29 polymerase + dNTPs + P1 + P2 (no HRCA); 4. DSA1N5C + CTs + Phi29 polymerase + dNTPs (RCA); 5. DSA1N5C + CTs + Phi29 polymerase + dNTPs + P1 + P2 (HRCA)). The final concentrations of DSA1N5C, CTs are both 100 nM.

3.5. Optimization of assay conditions

In addition to the reaction time mentioned above, other factors that affect the aptasensor performance were optimized. Phi29 polymerase plays an important role in strand extension and displacement. As shown in Fig. 4 A, the fluorescence intensity increases with increasing dosage of Phi29 polymerase from 0 U to 6 U. After 6 U, the signal enters a plateau. This indicates that 6 U Phi29 polymerase is sufficient for the designed reaction. Fig. 4B shows the effect of dNTP concentration on the signal. The fluorescence signal first increases with increasing dNTP concentration and then decreases when the dNTP concentration is greater than 0.6 mM. This may be due to extra dNTPs inhibiting the polymerase activity [31]. Therefore, 0.6 mM of dNTP was used in the subsequent experiments. The concentration of SYBR Green I is also an important factor. As shown in Fig. 4C, with the increase of the final concentration of SYBR Green I, the fluorescence signal first increases and then decreases after 0.8 × . This is probably caused by too much dimethyl sulphoxide, the solvent of SYBR Green I, in the HRCA reaction solution [32]. Therefore, 0.8 × was chosen as the optimal final concentration of SYBR Green I.

Fig. 4.

Fig. 4

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Optimization of the reaction conditions with 1 μg/mL S1 protein. Effect of the dosage of Phi29 DNA polymerase (A), the concentration of dNTP (B) and the final concentration of SYBR Green I (C) on the fluorescence intensity after 2 h reaction. The error bars are the standard deviation of three repetitive measurements. (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

3.6. Sensitivity and selectivity of the aptasensor

To evaluate the sensitivity of the aptasensor, the sensor detected a series of 10-fold diluted S1 protein solutions under optimized conditions. As shown in Fig. 5 A, the fluorescence signal increases with the increasing concentration of S1 protein from 100 fg/mL to 1 μg/mL. When the concentration is below 100 fg/mL, the signal is almost unchanged. So 100 fg/mL of S1 protein is close to the detection limit. Fig. 5B shows the linear relationship between the fluorescence intensity and the logarithm of S1 concentrations in the range of 100 fg/mL to 1 μg/mL. The linear equation is F = 3257 log CS1 + 44,692, (R2 = 0.9885). The LOD was 89.7 fg/mL (1.17 fM as taking 76.5 kDa for S1 protein, S/N = 3). The corresponding LOD for virus titer was approximately 8000 TU/mL. Compared with the ELONA result above, the LOD is reduced by about three orders of magnitude. And compared with the commercial detection kit, such as KIT40591 from Sino Biological Inc. (Beijing, China), the LOD of our method is 122 times lower. This indicates the ultra-high sensitivity of the proposed aptasensor.

Fig. 5.

Fig. 5

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The sensitivity and selectivity of the aptasensor after 2 h reaction. (A) The fluorescence emission spectra (λex = 485 nm) at different S1 protein concentrations. (B) The relationship between the fluorescence intensity and the S1 protein concentrations. The inset shows the linear calibration curve between the fluorescence intensity and the logarithm of S1 protein concentrations in the range of 100 fg/mL to 1 μg/mL (linear line) with a LOD value of 89.7 fg/mL. (C) The selectivity of the aptasensor to S1 protein (1 μg/mL) with control proteins (1 mg/mL) including HA1, His, HSA, BSA, and artificial saliva. (D) The relationship between the fluorescence intensity and the SARS-CoV-2 spike protein pseudovirus titers. The fluorescence intensity reveals a linear correlation with the logarithm of the pseudovirus titers in the range of 6.25 × 104 TU/mL to 1 × 106 TU/mL (linear line) with an LOD value of 5.1 × 104 TU/mL. The error bars are the standard deviation of three repetitive measurements.

The performance of the proposed aptasensor was compared with that of other aptasensors targeting SARS-CoV-2 reported in the literature, including aptasensors targeting the N protein. As listed in Table S3, our aptasensor has a greater improvement in the detection limit with a wider linear range. HRCA efficiently amplifies the detection signal and further reduces the detection limit of the sensor.

The selectivity of the aptasensor was also evaluated. We tested HA1 which is responsible for the initiating infection of influenza, an illness with symptoms similar to COVID-19. We also tested His (a tags on S1 protein), HSA (preparing for serum samples), BSA (a commonly used blocking reagent) and artificial saliva (preparing for saliva samples). All the control proteins are at a thousand-fold concentration of S1 protein. As shown in Fig. 5C, HA1, His and artificial saliva all show no obvious fluorescence signals. BSA shows a low fluorescence signal, and HSA exhibits about half of the fluorescence intensity of S1 protein. Considering the differences in concentrations, the proposed aptasensor has good selectivity to the S1 protein. But the results also indicate that the proposed aptasensor is not recommended to detect S1 protein in serum samples, which may lead to false positives.

3.7. Detection of pseudovirus in artificial saliva

Detecting SARS-CoV-2 in saliva is an effective diagnostic method [33]. In the above we have demonstrated that artificial saliva hardly affects the detection performance of the aptasensor. Therefore, the practical application of the aptasensor can be simulated by detecting the SARS-CoV-2 spike pseudovirus in artificial saliva. Pseudoviruses were first spiked in artificial saliva. Then the aptasensor directly detected the pseudovirus samples at different titers under optimized conditions. Fig. 5d shows the linear relationship between the fluorescence intensity and the logarithm of pseudovirus titers in the range of 6.25 × 104–1 × 106 TU/mL. The linear equation is F = 11,939 log Cpseudovirus - 53,237, (R2 = 0.9803). The LOD was 5.1 × 104 TU/mL (51 TU/μL, S/N = 3). The corresponding LOD for antigens was about 7.5 fM. Compared with the average virus load of 3000 copies/μL (0.45 pM of antigens) in patients [34], our assay may be suitable for the realistic COVID-19 diagnosis. At the same time, when virus titer of the detecting solution is estimated to be over 51 TU/μL, the detection time could be further optimized according to Fig. S3F.

4. Conclusions

In conclusion, we have described a fluorescence aptasensor for simple, ultrasensitive and quantitative detection of SARS-CoV-2 S1 protein and pseudovirus. The aptamer sequence used here was picked out by ELONA and molecular docking simulation for purpose. The proposed aptasensor benefits from the high performance of the selected aptamer, the high amplification efficiency of isothermal HRCA, and the high specificity brought by the sandwich structure of antibody-S1-aptamer. Using this HRCA-based aptasensor, we achieved a LOD of 89.7 fg/mL for S1 protein in the linear range of 100 fg/mL to 1 μg/mL. This detection limit is about 1000-fold lower than that of ELONA. And we detected SARS-CoV-2 spike pseudovirus in artificial saliva with a LOD of 51 TU/μL. The detection process is similar to ELISA, which is simple and has no need of complicated operations or special instruments and reagents. The HRCA-based aptasensor has the potential to detect SARS-CoV-2 infection at early stages. It may improve the timeliness and accuracy of SARS-CoV-2 diagnosis, and demonstrate a strategy to conduct aptasensors for other targets.

Credit author statement

Zecheng Wang: Conceptualization, Methodology, Investigation, Formal analysis, Writing. Chenchen Zhang: Methodology. Si He: Methodology. Danke Xu: Conceptualization, Resources, Supervision, Funding acquisition.

Ackowledgments

This work was financially supported by the National Natural Science Foundation of China (Grant No. 21974066).

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Handling editor: J. Wang

Footnotes

Appendix A

Supplementary data related to this article can be found at https://doi.org/10.1016/j.talanta.2022.124221.

Appendix A. Supplementary data

The following is the supplementary data related to this article:

Multimedia component 1
mmc1.docx (2MB, docx)

Data availability

Data will be made available on request.

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