key: cord-0911377-6pw1jd9c
authors: Martínez-Roque, Mateo Alejandro; Franco-Urquijo, Pablo Alberto; García-Velásquez, Víctor Miguel; Choukeife, Moujab; Mayer, Günther; Molina-Ramírez, Sergio Roberto; Figueroa-Miranda, Gabriela; Mayer, Dirk; Alvarez-Salas, Luis M.
title: DNA aptamer selection for SARS-CoV-2 spike glycoprotein detection
date: 2022-03-02
journal: Anal Biochem
DOI: 10.1016/j.ab.2022.114633
sha: 4726debf71d216e96e65b8d2cc5e1aadf9d08b42
doc_id: 911377
cord_uid: 6pw1jd9c

The rapid spread of SARS-CoV-2 infection throughout the world led to a global public health and economic crisis triggering an urgent need for the development of low-cost vaccines, therapies and high-throughput detection assays. In this work, we used a combination of Ideal-Filter Capillary Electrophoresis SELEX (IFCE-SELEX), Next Generation Sequencing (NGS) and binding assays to isolate and validate single-stranded DNA aptamers that can specifically recognize the SARS-CoV-2 Spike glycoprotein. Two selected non-competing DNA aptamers, C7 and C9 were successfully used as sensitive and specific biological recognition elements for the development of electrochemical and fluorescent aptasensors for the SARS-CoV-2 Spike glycoprotein with detection limits of 0.07 fM and 41.87 nM, respectively.

Over two years have passed since the initial outbreak of a new Coronavirus disease . The original report to the World Health Organization (WHO), anticipated that COVID-19 would present a challenge for the public health systems across the world due to the rapid spread of the disease [1] . To date, over 323 million confirmed COVID-19 cases have been reported worldwide leading to the death of more than 5.5 million people by the severe acute respiratory syndrome associated with COVID-19 [2, 3] . Although vaccines are already available in several countries, COVID-19 remains a major public health concern due to the uprising of SARS-CoV-2 variants and the lack of epidemiological surveillance and vaccination programs in impoverished countries [4] .

The etiological agent for COVID-19 is the new coronavirus SARS-CoV-2, a singlestranded positive sense RNA (+ssRNA) enveloped virus with a genome of approximately 30 Kb encoding four structural proteins: Spike (S), membrane (M), envelope (E) and nucleocapsid (N) [5] . The trimeric S protein is recognized as the main virulence factor [6, 7] . This is a type I transmembrane protein consisting of a large ectodomain, a single-pass transmembrane anchor and a short C-terminal intracellular tail [8] . The role of the S protein is crucial for viral adherence and entry to the host cell, where the receptor binding domain (RBD) within S protein mediates the interaction with the angiotensin-converting enzyme 2 (ACE2) attached to the cell membrane [9] .

In addition, the S protein appears highly immunogenic, making it a suitable candidate for vaccine development and theranostic applications [10] [11] [12] [13] .

Quantitative RT-PCR (RT-qPCR) or serological SARS-CoV-2 tests have become the standard COVID-19 diagnostic methods, however, they are costly, time-consuming J o u r n a l P r e -p r o o f and require specialized equipment and trained personnel [14] . In addition, serology and antigen tests require the production of purified proteins and specific antibodies, a long and expensive process that often leads to batch-to-batch variations [15] . Such problems related to antibodies may be one of the reasons why there is a difference in the detection performance (specificity and sensitivity) observed on rapid antigen tests when these parameters are determined in clinical conditions [16, 17] .

There are some new detection methods for SARS-CoV-2 infection based on technologies such as Field Effect Transistor, CRISPR-Cas12, Fluorine Doped Tin Oxide electrodes and functionalized gold nanoparticles or magnetic beads; however the equipment and the process to generate the materials needed for their implementation are difficult to obtain in most laboratories [18] [19] [20] [21] . As practical COVID-19 detection becomes necessary to save lives and return to a relative normality, there is a pressing need for efficient and affordable diagnosis tools.

Biosensors have been developed for the rapid, sensitive, and stable diagnostic methods that can use novel recognition elements such as nucleic acids aptamers [22, 23] . Nucleic acid aptamers are short, single-stranded DNA (ssDNA) or RNA molecules that are selected for binding to a specific target [24] . The high affinity and specificity of aptamers are comparable to those of antibodies, with the advantage of rapid and massive high-quality production by automated synthesizers [25] . Aptamers are obtained through a highly probabilistic process called Systematic Evolution of Ligands by Exponential Enrichment (SELEX) [26] . In SELEX, large single-stranded oligonucleotide combinatorial pools are challenged for binding to a desired target under a defined set of conditions [24, 25] . Aptamer selection is attained through iterative steps of target incubation with combinatorial pools, followed by the separation J o u r n a l P r e -p r o o f of unbound sequences (partitioning), and the PCR-mediated amplification and purification of the target-bound oligonucleotide species [27, 28] . Aptamers with high affinity can be recovered through several partitioning methods although efficiency is often affected by the nonspecific background binding that each SELEX variant may have [29] . SELEX based on capillary electrophoresis (CE-SELEX), where targetbound aptamers are separated in solution, eliminate the possible background against components of the partitioning method resulting in the fast selection of aptamers due to its higher partition efficiency [30] .

Aptamers are used in biosensors as biological recognition elements (BRE) for accurate and rapid detection of pathogens through fluorescence, chemiluminescence, electrochemistry and immunoluminescence techniques. These methods often require the chemical modification of the aptamer to produce visual or measurable signals upon interaction with the target molecule. Such modifications include labeling with fluorogenic, electrochemical or chromogenic moieties, addition of catalytic nucleic acids (aptasensors) or even allosteric aptamers (aptazymes) responsive to the target.

Recently, new biosensors for COVID-19, including devices targeting the RNA of SARS-CoV-2, and COVID-19 antibodies, as well as immunosensors targeting the S and N proteins have been reported [31] [32] [33] [34] [35] [36] [37] . Nonetheless, aptamer-based biosensors offer advantages compared to antibodies such as shorter generation time, lower manufacturing costs, negligible batch-to-batch variability, simple chemical modification, better thermal stability, long shelf-life and higher target selection potential [38] [39] [40] .

Aptamers against SARS-CoV-2 proteins have been previously isolated, some of them are able to block the interaction of S protein/RBD with ACE2 receptors and capable of J o u r n a l P r e -p r o o f 6 inhibiting infection in pseudovirus models demonstrating therapeutic potential [41] [42] [43] [44] .

Aptamer selection for the same virus using different viral targets and SELEX conditions is a common practice due to the rise of aptamer with different affinity, sequence, structure and binding capabilities [15] . In this regard, a variety of SELEX protocols have been used extensively, such as immobilization-free methods that expose the whole protein surface to the oligonucleotide pool thus making it more accessible to a variety of different aptatopes [45] . This is important when paired (noncompeting for the same target site) aptamer screening is sought as different combinations of aptamers can generate a response to a wider range of the analyte

Thus, newly selected aptamers may be necessary for a more versatile response range in novel biosensors. As different BRE are required for biosensor development, aptamers with different interaction properties could be useful, alone or in combination with previously published aptamers. In addition, different aptamers capable of interacting with various epitopes of the S protein may exhibit synergistic effects in the inhibition of the viral entry or the detection of target sequence or structural variants. Therefore, selection and characterization of novel SARS-CoV-2 S protein aptamers are necessary for the development of new theranostic and biotechnology applications.

In the present work, IFCE-SELEX (Ideal Filter Capillary Electrophoresis-SELEX) was used in combination with Next Generation Sequencing (NGS) for the selection and identification of single-stranded DNA (ssDNA) aptamers that specifically bind with high affinity to the SARS-CoV-2 S protein. Furthermore, as proof-of-concept applications, selected paired aptamers were implemented in a electrochemical aptasensor and a simple sandwich-type fluorescent aptasensor capable of detecting and quantifying S J o u r n a l P r e -p r o o f protein in diluted human saliva of multiple donors suggesting a novel tool for the rapid and opportune diagnosis of COVID-19.

The 

J o u r n a l P r e -p r o o f µL PCR reaction was combined with 500 µL of oil phase, vortexed for 20 minutes and cycled 50 times. The PCR water-in-oil emulsion was extracted with water-saturated dichloromethane and centrifuged at 17,200 x g for 5 min for aqueous phase recovery.

The ssDNA was separated from dsDNA through 10% native polyacrylamide gels followed by crush and soak elution. The ssDNA was quantified using a NanoDrop™ 2000 (Thermo Fisher) and visualized in denaturing 8% polyacrylamide/7M Urea gels after every purification.

NSG was performed essentially as previously described [48] . A minimum of 500 ng dsDNA from each cycle was used with the TruSeq DNA PCR-Free LT kit (Illumina Inc., San Diego, CA). The different adapters were added to each partition round following the manufacturer instructions. The partitioned pools with ligated adapters were quantified using the NEBNext ® Library Quant Kit for Illumina ® and paired-end sequenced in a MiSeq System using a MiSeq Reagent Kit V2 (Illumina) flow cell. NGS data was analyzed with the Galaxy project platform and FASTaptamer software [49] .

To further increase the probability of selecting high affinity and specific aptamers, three additional oligodeoxynucleotide pools were included in the sequencing analysis.

These pools were obtained from nitrocellulose-bound sequences recovered from three interaction mixtures flowed through a Slot blot apparatus. The first mixture contained only 2R ssDNA (NC), the second (NC-100) and third (NC-25) contained 2R ssDNA and S protein at S protein concentrations of 100 nM and 25 nM, respectively. The ssDNA bound to the nitrocellulose membrane was eluted by incubating at 95°C in nuclease-free water for 10 minutes and then amplified by emPCR.

For Slot blot binding assays, the ssDNA pools and aptamers were radiolabeled using Thermo Scientific™ T4 polynucleotide kinase (PNK) (Thermo Fisher Scientific) and γ- %BF=Residual radioactivity on NC/total radioactivity on NC and NY)*100

The KD were calculated using the GraphPad Prism 8.4 software, curve-fitting to one site non-linear regression model:

Where B is the bound fraction, Bmax is the maximum binding, [M] is the protein concentration, and KD is the dissociation constant [50] .

The KD were also determined by single-cycle kinetic analysis using surface plasmon Data was fitted to a 1:1 binding stoichiometry model using the BIAcore T200 evaluation software 3.2 (Biacore) for KD determination.

Whole saliva was collected from consenting healthy volunteer subjects, three male and two female donors, between 08:00 a.m. and 14:00 p.m. to account for the influence of circadian rhythms and food debris. Subjects were asked to rinse their mouths with water and discard this before sample collection. Saliva was allowed to accumulate on the mouth floor. The accumulated saliva was then spit into a polypropylene test tube and this was repeated until enough saliva was collected.

During the collection process the sample tubes were kept on ice. Samples were cleared for 30 seconds in a microfuge. The pellet was discarded, and the supernatant diluted 10-fold in TNa7 buffer. Samples were kept on ice and used immediately.

The proof-of-principle FLAA test for SARS-CoV-2 S protein detection was set in 96well microplates as described with some modifications [51] . where is the constant of random error (which 3 is typically used), is the standard deviation of the blank, and is the slope of the calibration curve [19, 27, 76] .

The electrochemical detection of the S protein was made utilizing well-established flexible multi-electrode arrays (flex-MEAs) [52] . Protein interaction with aptamers changes drastically the mass-to-charge ratio of aptamers resulting in a less negative aptamer-S protein complex whose mobility is more affected by EOF rather than by its electrophoretic mobility. Therefore, a 45minute collection window was established for the partition step [53] . Because the low S protein concentration, the aptamer-complex peak was not detected; however, each electrophoresis condition was amplified by qPCR and aptamer recovery complex was confirmed by direct visualization on polyacrylamide gels.

To increase SELEX stringency, the resulting partitioned pool (1R) was used for two subsequent IFCE partition rounds (2R and 3R) with decreasing S protein concentrations (50 and 25 nM, respectively). This method was modified by performing extra selection rounds to increase strong binders, reduce the amount of non-binders and facilitate NGS enrichment analysis [54] . Binding assays showed that the M2 pool and 2R had differential binding affinities for S protein. The M2 pool showed low binding affinity for S protein at 200 nM concentration, while 2R showed a significantly increased binding affinity (Figure 2A) . These results suggest that the second IFCE partition round significantly increased the number of high affinity aptamers (HAA)

decreasing the amount of protein required for binding. Also, this higher binding affinity appeared specific for S protein as the BSA negative control showed no DNA retention ( Figure 2A) . Interestingly, a further selection cycle with decreased S protein concentration produced loss of binding affinity in the third IFCE partition. This approach is useful, however, as seen in some mathematical models, there is a limit in the protein concentration that can be used to improve SELEX. This can be explained because mostly all methods exhibit background binding that can compromise SELEX efficiency because represents a competitive presence [55] . In addition, this is consistent with previous CE-SELEX reports where binding enrichment occurred in early selection rounds and further partition rounds showed no improvement [56] or even the loss of affinity [57, 58] . It is unclear why the pool affinity decreases through several partition rounds but other plausible explanations include mutations in aptamer sequences, DNA contamination and even over-amplification of non-aptamer sequences due to Taq DNA polymerase bias, suggesting that decreasing concentrations to a lower limit could be detrimental for the SELEX process [55] [59] . Table 1) .

A reduction in unique sequences was observed as the selection cycles progressed, confirming that the IFCE-SELEX process effectively decreased variability through the partition rounds with the lowest variability in the 3R pool despite the low binding affinity ( Figure 2, panel B) . This drop-in variability is also a common event in SELEX processes. Aptamer selection against ibuprofen performed a negative selection step (no target) reducing the number of sequences by 56% [60] . Also, in a SELEX against streptavidin variability decreased through ten selection rounds whereas affinity did not increase after round six [61] . Although the apparent low number of aptamers in 3R, this data was used to discriminate aptamer sequences that are present in both 2R and 3R pools. In addition, bioinformatics motif analysis using Multiple Expectation maximizations for Motif Elicitation Suite (MEME Suite) showed that top enriched sequences motifs are different in 2R and 3R. However, they were not considered for HAA selection due to a high E value (<0.05) in MEME motif analysis (Supplementary Figure S4 ) [62] .

To identify HAA, the enrichment-folds (reads per million between selection rounds) were calculated and ranked for every sequence through the partition rounds using the 

The arrangement in phylogenetic trees implies the acquisition of new characteristics with respect to their ancestors along the branches. Using Molecular Phylogenetic analysis by Maximum Likelihood method ten candidates were selected from different families in the selection cycle 2 (Table 1) and analyzed by binding analysis to find the best HAA (Figure 2 , panel D) [63, 64] . All sequences showing high enrichment or frequency in the NC data set were discarded. All ten candidate sequences exhibited no enrichment in the NC data set (Figure 2 , panel E), but some were present in the NC-100 and NC-25 data set.

NGS analysis revealed that the initial pool variability decreased through the SELEX procedure although there were not highly over-represented or predominant sequence motifs as previously described for other CE-SELEX experiments [56, [65] [66] [67] [68] [69] .

Nevertheless, the bioinformatic analysis allowed identification of enriched oligonucleotide sequences. It is also possible that data may be improved if the NGS output is increased by using higher capacity flow cells since other NGS aptamer analyses used a higher number of reads per cycle (>1 million reads) [50] .

Slot blot binding assays showed candidates C7 and C9 best binding affinities similar to that presented by the whole 2R pool. No significant differences were observed with the BSA negative binding control or without protein, suggesting specific interactions Figure S6) .

Biosensors can be classified as competitive and sandwich assays depending on the number of BRE that are used. Sandwich-type biosensors are preferred because of its dual recognition mechanism; in this type of biosensors, two different BRE are needed as two spatially distant regions are recognized within the target. This results in higher specificity and selectivity as one BRE is used for capture and the other for signal generation [70] .

For a FLAA setting, C7 was immobilized on the surface of treated multiwell plates as capture agent and fluorescein-labeled C9 was added as detection agent. Purified recombinant SARS-CoV-2 S protein was added to the C7-containing plates, blocked and incubated in the presence of 10% saliva prior to addition of FAM-labeled C9

( Figure 4A ). Other non-related proteins (mouse IgG, ACE2 and milk casein) were used as specificity controls (Figure 4, panel B) .

SARS-CoV-2 S protein exhibited the highest fluorescence intensity suggesting a positive recognition and that C7 and C9 bind to different sites within S protein as no signal will be recorded otherwise. Interestingly, when 5'-amino-C6-modified C9 aptamer was used as capture agent and FAM-labeled C7 aptamer as detection agent, no signal was detected when 250 nM of S protein was added in TNa7 buffer. This may be due to the higher KD of C9 (230 nM) compared to C7 (89 nM) suggesting that the capture agent must be the aptamer with the highest affinity for the target if a low limit of detection (LOD) is desired, although the KD may vary depending of the determination method as we observed by SPR analysis (Supplementary Figure S6) .

Another explanation may be that the chemical modification itself impaired C9 binding, since such an effect has been observed with other chemical modifications causing the J o u r n a l P r e -p r o o f partial or total loss of aptamer binding [71, 72] . Also, it has been reported that the negative phosphate backbone of an aptamer can interact with the immobilization surface electrostatically, resulting in denaturation of the aptamer structure. This last may impact more C9 structure (ΔG= -7.4 kcal/mol) since it is less stable than C7 structure (ΔG= -8.9 kcal/mol) [73] .

In addition, FLAA was tested against other surface virus proteins, such as human RSV glycoprotein G and HCoV-NL63 S protein, using milk casein and egg lysozyme as negative controls (Figure 4 , panel C To further characterize FLAA detection parameters, a calibration curve was generated BREs is wider and may be used with higher protein concentrations.

To determine FLAA detection performance in biofluids, spike-and-recovery assays were performed using diluted human saliva as matrix. As biological matrices may contain components that affect the response to the analyte more than the standard diluent (TNa), a spike-and-recovery assay is appropriate to assess the difference response between the standard diluent and the biological matrix [77] . A specific amount of purified S protein (spike) in 10-fold diluted human saliva (from multiple or single donors) was added to the microplate wells in TNa buffer and the fluorescence response (recovery) read after incubation in comparison with the response without saliva. BSA was used as negative control (Figure 4, panel D) . It was established that the FLAA assay determines S protein concentration with an average recovery well within the 80-110% acceptable range (Table 2 ) [73] . These results also showed that other components found in saliva had low detrimental effect in the capacity of C7 and C9 aptamers to detect and quantify S protein, indicating that the FLAA may be suitable for COVID-19 detection in diluted saliva samples.

As a second proof-of-principle test, the C7 aptamer was implanted in an electrochemical aptasensor configuration. A 5'-end thiol-terminal group was added to the C7 aptamer for its immobilization on a gold electrode through a sulfur-gold bond ( Figure 5A ). Furthermore, thiol terminated PEG molecules were used as anti-fouling backfill to suppress unspecific binding [78] . The binding of the target to the receptor layer induced conformational changes within the aptamer film. These modulations of the receptor layer caused alterations of the ferri/ferrocyanide charge transfer characteristics which were registered by differential pulse voltammetry (DPV). Firstly, J o u r n a l P r e -p r o o f the starting DPV current signal of the sensor electrodes was measured without analyte exposure. Subsequently, the sensor responses were recorded after 30-minute incubation for different S protein concentrations covering a range from 1 fg/mL to 100 ng/mL. An increase of the peak current signal was observed as the concentration of the protein rose. The current increase can be understood as a result of a reduced charge transfer resistance due to conformational rearrangements within the receptor layer (Fig. 5A) . The sensitivity of the sensor was calculated to 6.29±0.98 /decade while the LOD was calculated to 8.85 fg/mL (0.07 fM). Correspondingly, a dynamic detection was feasible in the range from 8.85 fg/mL to 100 pg/mL. Hereby, the calculated KD for 5'-thio-C7 was 141 fg/mL (1.04 fM) ( Figure 5B) .

A high selectivity of the C7 aptamer was obtained for S protein of the SARS-CoV-2 virus over proteins from other viruses such as the Glycoprotein G of the RSV, the Hemagglutinin protein of the influenza (H1N1) virus, or the S protein of the MERS-CoV virus even at high concentrations ( Figure 5B ).

In the present work, C7 and C9 aptamers specific for the SARS-CoV-2 S protein were selected by combining IFCE partition with an optimized SELEX protocol. The high partition efficiency coupled with the use of emPCR for efficient aptamer amplification allowed the enrichment of HHA in only two selection cycles. Aptamer sequence identification was facilitated by using Slot-blot assays with the generated pools and the use of NGS data combined with phylogenetic analysis. This combination of methods can be easily applied to different targets for rapid HAA discovery. J o u r n a l P r e -p r o o f Step 1: 5'-amino-C6-modified C7 aptamer was immobilized on the surface of maleic anhydride-activated multiwell plates as capture agent.

Step 2: The purified recombinant SARS-CoV-2 S or negative binding control protein were added to the C7containing plates.

Step 3: Fluorescein-labeled C9 was added as detection agent.

Step J o u r n a l P r e -p r o o f 

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This project was funded by CONACyT grants 311385 and 300073 and SRE-AMEXCID grant 2020-6. We thank to Ian Gering and María Fernanda Pérez y Pérez for excellent technical assistance during SPR and binding experiments, respectively.