Rapid generation of high-performance aptamers with programmable binding affinities

Abstract

Aptamers as nucleic acid affinity reagents are gaining traction in analytical applications owing to their high stability, compact size, and amenability to chemical modifications. It is highly desired to generate aptamers with different binding affinities to meet the requirements of various applications. However, systematic evolution of ligands by exponential enrichment (SELEX), the gold standard for aptamer generation, is unable to quantitatively produce aptamers with desired binding affinities and requires multiple rounds of selection to eliminate false positive hits. Here we introduce Pro-SELEX, a new approach for rapid discovery of aptamers with precisely defined binding affinities that combines efficient particle display, high-performance microfluidic sorting and high-content bioinformatics. Using the Pro-SELEX workflow, we were able to investigate the binding performance of individual aptamer candidates under different selective pressure in a single round of selection. Using human myeloperoxidase (MPO) as a target, we demonstrated that aptamers with dissociation constants spanning a twenty-fold range of affinities can be identified within one round of Pro-SELEX. Our selection strategy will have a significant impact on the fields of biosensing and bioseparation by generating aptamers with tailored binding affinities.

Description

[0001] RAPID GENERATION OF HIGH-PERFORMANCE APTAMERS WITH PROGRAMMABLE BINDING AFFINITIES

[0002] FIELD OF THE DISCLOSURE

[0003] The present disclosure relates to a high-dimensional microfluidic approach for selection of aptamers with programmable binding affinities

[0004] BACKGROUND

[0005] Precise control over binding affinities between biomolecules is one of the critical means by which Nature allows thousands of types of biomolecules to operate in tandem with molecular-level control in heavily crowded environments. Moreover, molecules with well-defined binding affinities for a specific target - thus called affinity reagents - are essential for many applications, including biosensing, diagnostics, imaging, and therapeutics. For example, the binding affinity between a target analyte and its specific biorecognition element is the determinative factor that defines the dynamic range of a biosensor1 2.

[0006] High-affinity recognition molecules with low dissociation constants (K ) are sought for point-of-care applications to enable rapid binding events and low limits of detection. On the other hand, low-affinity reagents with fast association and dissociation rates have been used in real-time monitoring applications3-5, because they can resolve the dynamic changes in their target analyte level. The advancement of detection modalities with extremely high resolution and low background levels has also made it possible for low-affinity binding reagents to achieve high detection sensitivity2’67. Hence, to meet the diverse requirements of different sensing scenarios, it is highly desirable to be able to generate recognition molecules with desired binding affinities against a specific target.

[0007] Nucleic acid aptamers have garnered significant interest as versatile affinity reagents and as promising alternatives to antibodies over the past three decades8-10. In recent years, aptamers have demonstrated great potential in real-time monitoring and wearable sensing applications11-15. Compared to antibodies, aptamers offer several unique features, including high stability, compact size, cost-effective mass synthesis, minimal batch-to-batch variation, non-immunogenic properties, and amenability to site-specific chemical modification8’16’17.

[0008] Despite these attractive features, the use of aptamers in biosensing is relatively limited - one reason for this is a lack of high-quality aptamers for many biomolecular targets16. Conventional procedures for aptamer selection through SELEX are labor-intensive, time-consuming, and incapable of producing aptamers with programmable binding affinities. A typical SELEX experiment requires 10-15 rounds of selection to allow the target-binding sequences to dominate the nucleic acid pool16’18’19. This inefficiency is due to the inability of traditional SELEX to separate aptamer candidates with diverse binding affinities in each round, as well as the introduction of undesired biases - such as PCR bias and amplification of parasitic sequences, through repeated rounds of selection. These factors also make the binding affinities of the selected aptamers unpredictable, requiring a number of sequences to be tested to identify an aptamer with desired properties. Recent advancements in SELEX technologies with improved sequence partitioning efficiency, such as CE-SELEX20, Non-SELEX21, M-SELEX22, and particle display selection technology23, have provided novel solutions for the aptamer selection challenge. However, none of these methods are able to quantitatively generate aptamers with defined binding affinities.

[0009] SUMMARY

[0010] Herein the inventors describe a new approach, referred to as Pro- SELEX, for quantitative isolation of aptamers with programmable binding affinities. The present workflow comprises particle display, magnetic particle sorting, high-dimensional and parallelized selection, and high-content bioinformatics. Using this workflow, the inventors were able to profile the binding performance of individual aptamer candidates at different target concentrations in a single round of selection. As a proof of concept, the inventors selected aptamers specific to human myeloperoxidase (MPO), an emerging diagnostic and prognostic biomarker of coronary artery disease24 25. The inventors successfully isolated a number of anti-MPO aptamers with predefined binding affinities (Kd) and developed algorithms relating selection data to this important

[0011] Thus, the present disclosure provides a method of collecting aptamers based on binding affinity to a biomarker. The method comprising the steps of loading aptamers on surfaces of nonmagnetic particles (NM-particles) from a pool of a plurality of aptamers with different nucleic acid sequences, each NM- particle having respectively aptamers with the same nucleic acid sequences on its surface, followed by labelling magnetic particles (M-particles) with biomarkers. The method includes forming aptamer: biomolecule complexes by binding the aptamers to the biomolecules therefore forming NM-particle: M- particles complexes once the M-particles are labelled with the biomarkers. The complexes are then serially sorted according to aptamer-biomarker binding affinities using magnetic strength of the complexes wherein complexes with higher binding-affinity aptamers have a higher load of M-particles and wherein complexes with lower binding-affinity aptamers have a lower load of M- particles. Thereafter the method includes collecting the sorted complexes are collected followed by isolating and collecting aptamers of preselected binding affinities from the sorted complexes.

[0012] The method may comprise the step of selecting the desired binding affinities or range of binding affinities of the aptamers for each volume.

[0013] The method may further comprise the step of enriching the pool of a plurality of aptamers prior to loading the aptamers on the surfaces of the NM- particles. The step of enriching the pool of a plurality of aptamers may be performed with emulsion PCR.

[0014] The biomarker may be selected from the group of proteins, DNA, RNA, small molecules, viruses, and live cells (such as bacteria and mammalian cells).

[0015] The aptamers may be sequences of nucleotides of DNA, RNA or nonnatural nucleic acids or sequences of amino acids of proteins or peptides.

[0016] The step of serially sorting the complexes may comprise flowing the complexes through a plurality of sequentially placed defined volumes in fluid communication, each volume configured to sort the complexes based on the load of M-particles of the complexes.

[0017] The step of serially sorting the complexes may be followed by the step of isolating and collecting the complexes from each volume.

[0018] Each volume may have enclosed therein a structure having magnetic properties to collect the complexes having preselected magnetic load.

[0019] Each volume may be configured to have a different linear velocity for differential sorting of the complexes with different load of M-particles. A first volume may have the highest linear velocity and each successive volume has reduced linear velocities when compared to the linear velocity of the previous volume.

[0020] A linear velocity in a particular volume of the series of sequentially placed volumes is lower than the velocity of a previous adjacent volume and higher than the next adjacent volume, and the volumes may contain structures configured to define a flow velocity therein and wherein each volume of the series of sequentially placed volumes has a reduced linear velocity when compared to the linear velocity of the previous adjacent volume. The plurality of sequentially placed volumes may be grouped on a series of chips in fluid communication, each chip having a defined number of volumes in series.

[0021] There may be at least one more series of chips, the at least one or more series of chips being parallel with the first series of chips. Or, the chips may be configured in a parallel configuration. The chips in the series of chips may be configured in a serial configuration.

[0022] The plurality of chips may be 1 , 2, 3, 4, 5, 6, 7, 8, 9, or 10.

[0023] The M-particles may be first labelled with the biomarkers and the NM- particle:M-particles complexes are then formed by incubating the loaded NM- particles and the labelled M-particles

[0024] The aptamer biomolecule complexes may be first formed by incubating the loaded NM-particles with the biomolecules and then attaching the M- particles to the biomolecules therefore forming the NM-particle: M-particles complexes.

[0025] The step of isolating and collecting the aptamers may comprise using PCR amplification to amplify the nucleic acid sequences of the aptamers on the loaded NM-particles of the NM-particle: M-particles complexes.

[0026] A further understanding of the functional and advantageous aspects of the disclosure can be realized by reference to the following detailed description and drawings.

[0027] BRIEF DESCRIPTION OF THE DRAWINGS

[0028] The disclosure will be more fully understood from the following detailed description thereof taken in connection with the accompanying drawings, which form part of this application, and in which:

[0029] FIGURE 1a shows the overall workflow of the Pro-SELEX for the quantitative isolation of aptamers with different binding affinities via a highdimensional microfluidic approach. FIGURE 1 b shows the isolation of aptamer particles with different levels of target binding using Pro-SELEX chips.

[0030] FIGURE 1c shows the separation rationale. Simulated linear flow velocity profile. Formation of capture pockets was observed in the valley of X- shaped microstructures.

[0031] FIGURE 1d is a plot of flow velocity (%) versus position (mm) which shows the magnitude of linear flow velocity.

[0032] FIGURE 1e are histograms of % magnetic load versus capture zones of Pro-SELEX chips which shows the determination of the median magnetic load of particles captured by Pro-SELEX at different flow rates (8 mL / hr, 16 mL / hr, and 32 mL / hr). Error bars represent the standard deviation of three replicates. W represents particles collected from outlet (waste).

[0033] Figure 2a shows representative SEM images of various printed ‘X’- shaped structures in Pro-SELEX chip in which Zone 1 to 4 showing different features designed to capture aptamers ranging from high binding affinities to low affinities. All designed features were printed without any major defects.

[0034] Figure 2b shows representative images showing the key components of Pro-SELEX microfluidic sorting, including a fabricated modular chip in the lefthand panel, arrayed magnets in the middle panel, and a sorting setup in the right hand panel. A red food dye was used to visualize the changes in height.

[0035] Figure 3 is a plot of normalized particle count versus fluorescence intensity (Cy5, APC channel) which shows representative flow cytometric profile of the particle populations recovered from each zone running at the flow rate of 8 mL / hr. To prepare particles with different magnetic contents, 107 of forward primer-coated particles were incubated with different concentrations of 5’ biotin- FP’, followed by labelling with anti-biotin MNP and Labeling Check Reagents- APC. The particles were then mixed and sorted using Pro-SELEX chip at flow rate of 8 mL / hr. The particles captured at each zone of the chip were collected and analyzed by flow cytometry.

[0036] Figure 4a shows the workflow of the validation experiments of the sorting performance of the Pro-SELEX chip using anti-thrombin aptamers with different binding affinities.

[0037] Figure 4b is a plot of normalized particle count versus fluorescence intensity (APC channel) which shows the evaluation of the binding performance of thrombin-03 coated aptamer particles at thrombin concentrations of 1 nM, 100 pM, 10 pM, 1 pM and 0 pM. The particles are labelled with MNPs and anti- MNPs labelling check reagent-APC and analyzed by flow cytometry.

[0038] Figure 4c and 4d are plots of % captured particles versus zones which shows the determination of the capture profile of particle-displayed thrombin-03 aptamer prepared using different thrombin concentrations at flow rates of 8 (Figure 4c) and 16 mL / hr (Figure 4d).

[0039] Figure 4e to 4g are plots of normalized particle count versus fluorescence intensity (APC channel) which show analysis of particle-displayed thrombin aptamer 03, TBA and a primer sequence after incubation with 1 pM (Figure 4e), 1 nM (Figure 4f) and 1 pM (Figure 4g) thrombin molecules. The particles are labelled with MNPs and anti-MNPs labelling check reagent-APC and analyzed by flow cytometry. Figure 4h to 4j are plots of % captured particles versus zones which show sorting of the particle-displayed thrombin aptamers 03, TBA and a primer sequence using Pro-SELEX chip at a flow rate of 8 mL / hr at 1 pM (Figure 4h), 1 nM (Figure 4i) and 1 pM (Figure 4j) thrombin molecules, Error bars represent the standard deviation of three replicates.

[0040] Figure 5a shows a representative gating strategy used for analysis of 03-aptamer particles and TBA-particles using flow cytometry.

[0041] Figure 5b is a plot of normalized particle count versus fluorescence intensity (Cy5, APC channel). To test the conjugation efficiency of the Thrombin-03 and Thrombin-TBA, the inventors incubated 1 pM Cy5-labeled FP complementary sequence (Cy5-FP’) with 1 pL of either 03-particles or TBA- particles in 100 pL of binding buffer at 60 °C for 10 minutes, then cooled down at RT for 10 minutes. The particles were washed twice with 100 pL binding buffer and analysed by flow cytometry. The results indicated that 03-particles and TBA particles retained comparable amount of their aptamers.

[0042] Figure 6 is a plot of % captured particles versus zones for 4 mL / hour, 8 mL / hour and 16 mL / hour which shows the determination of the capture profile of forward primer-coated particles at varying flow rates. 1 *107 of forward primer-coated particles were incubated with 20 pL of anti-biotin microbeads in 1 mL of selection buffer for 15 min at RT. The particles were then washed with the binding buffer twice and sorted by Pro-SELEX microfluidic devices at different flow rates. The particles captured by the chips were collected and analysed by flow cytometry. Less than 0.5% of particles were trapped in Pro- SELEX chips when using a flow rate of 8 mL / hr or 16 mL / hr. Error bars represent the standard deviation of three replicates

[0043] Figure 7 illustrates the nucleic acid sequences used in Pro-SELEX.

[0044] Figure 8 illustrates the evaluation of the binding specificity of DNA pools in the pre-enrichment rounds. 100 nM of Initial library and DNA recovered from round 1 , round 2 and round 3 of pre-enrichment were incubated with pure magnetic beads, magnetic beads conjugated with undesired targets (human serum proteins, thrombin, BNP and RANTES) or magnetic beads conjugated with MPO for 1 hr. The beads were washed five times with 500 pL of selection buffer. The DNA molecules were then eluted by adding 100 pL water and heating at 95°C for 15 minutes. The eluted DNA was quantified using qPCR, and the DNA recovery rate was then calculated. The results suggest that the specificity of the DNA pool has been improved after the three pre-enrichment rounds.

[0045] Figure 9a is a plot of normalized particle count versus fluorescence intensity (APC channel) which shows representative flow cytometric profile of uncoated polystyrene particles (left hand plot), and FP-coated particles hybridized with Cy5-FP’ (right hand plot).

[0046] Figure 9b is a plot of normalized particle count versus fluorescence intensity (APC channel) which shows representative flow cytometric profile of aptamer-displaying particles hybridized with Cy5-RP after emulsion PCR with two different concentrations of PCR GoTaq Hot Start Polymerase (Promega). The inventors used 50 pM of library molecules as template. The use of 0.5 U / pL of the polymerase demonstrated a significantly higher PCR efficiency. Figure 9c is a plot of normalized particle count versus fluorescence intensity (APC channel) which shows representative flow cytometric profiles of particles after emulsion PCR in the presence of different template concentrations and annealing with Cy5-RP. Since no more than one template molecule should be present per droplet, the total template DNA copy number should be kept below 30% and ideally at 20% based on the Poisson distribution. 2 pM of template was used to prepare the aptamer particle library.

[0047] Figure 9d is a plot of normalized particle count versus fluorescence intensity (APC channel) which shows representative flow cytometric profile of aptamer particles hybridized with Cy5-RP after particle PCR with different numbers of PCR cycles. The same amount (~1 X106) of DNA library molecules and FP-particles were used for particle PCR. SHOULD THIS BE (~1 xl 06)

[0048] Figure 9e is a plot of normalized particle count versus fluorescence intensity (APC channel) which shows representative flow cytometric profiles of particles hybridized with Cy5-RP after emulsion PCR with different numbers of PCR cycles. 2 pM of template was used for emulsion PCR.

[0049] Figure 9f is a plot of PCR threshold value versus number of templates shows a standard curve of qPCR with known numbers of DNA template. Threshold cycle values are plotted as a function of the template number.

[0050] Figure 9g are histograms of copy number of DNA template per particle versus Emulsion PCR cycles which shows qPCR was performed to quantify the template copy number for each aptamer particle prepared after different cycles of emulsion PCR. Although 60 PCR cycles produced the highest DNA copy number per particle, an increased background signal was also observed, as shown in Figure S6e. Therefore, we used 50 PCR cycles in the following experiments.

[0051] Figure 9h is a plot of normalized particle count versus fluorescence intensity (APC channel) which shows flow cytometric profile of aptamer particles prepared using Phos-RP as the reverse primer during particle PCR, hybridized with Cy5-RP after Lambda exonuclease treatment ( top second), NaOH treatments ( top first), or no treatment ( bottom first). Aptamer particles prepared using Cy5-RP as the reverse primer during particle PCR were used as the positive control bottom second) to calculate the yield of single-stranded products. Both Lambda exonuclease treatment and NaOH treatment have a -70% yield. But we noticed that the particles tend to aggregate after NaOH treatment. Therefore, Lambda exonuclease treatment was chosen in the following experiments.

[0052] Figure 9i is a plot of normalized particle count versus fluorescence intensity (APC channel) which shows forward primer (FP)-labeled particles were treated with lambda exonuclease at 37 °C for 2 hrs. We then stained both treated FP-particles and untreated FP-particles with Cy5-FP’ (a Cy5-labeled complementary strand of FP) and compared their signal by flow cytometry. The unchanged signal suggests that the lambda exonuclease does not digest the single-stranded DNA molecules on the particles.

[0053] Figure 10 is a table which shows the experimental conditions for Pro- SELEX.

[0054] Figure 11a shows the workflow of the selection experiments. Five MPO concentrations (100 nM, 10 nM, 1 nM, 100 pM, and 10 pM) were tested at flow rates of 16 and 32 mL / hr for the screening experiments. Particles were collected from individual capture zones (z1-z3) and analyzed by high- throughput sequencing and the AptZ tool for aptamer identification.

[0055] Figure 11b to 11c are bar charts of % of MPO aptamer particles captured versus capture zones of Pro-SELEX Chips which show aptamer particles collected from z1-z4 of Pro-SELEX chips at flow rates of 16 mL / hr (b) and 32 mL / hr (c).

[0056] Figure 11d is a pie chart which shows the distribution of calculated Z score over the pool of sequences presented in MPO selection and a plot of Z score versus index of sequences which shows the distribution of calculated Z score of the top 5x105sequences.

[0057] Figure 11e is a heatmap of fold of enrichment in all 30 conditions of sequences with different Z scores. The AptaZ algorithm comprehensively considers the fold of enrichment from different conditions to generate Z scores to quantitatively rank aptamers.

[0058] Figure 11f are plots of % of total binding versus MPO concentrations (pM) which shows that eight candidates with different Z scores were expressed on particles and incubated with Cy5-labeled MPO prior to analysis via flow cytometry. Each line represents a fitted Langmuir isotherm. Data are presented as mean values and error bars represent the standard deviation of three replicates.

[0059] Figure 11g is a plot of Log ( / <d, in pM) versus Logw(Z score) which shows the relationship between calculated Z score and validated Kd derived from the eight candidates was examined. The Z score correlates with the Kd value in a linear fashion according to curve fitting.

[0060] Figure 12 is a table which shows selected aptamer sequences.

[0061] Figure 13 are plots of normalized particle count versus fluorescence intensity (APC channel) which shows the evaluation of the binding performance of selected MPO aptamers (in table S3) using a beads-based fluorescent assay. Different concentrations of biotinylated MPO (10 pM to 200 nM) were incubated with a fixed amount of the APs (2x104 particles) in selection buffer for 1 hr at room temperature. The unbound MPO was washed away with selection buffer prior to incubation with Cy5-labeled streptavidin for 15 minutes to label the bound MPO. The particles were washed with binding buffer and the median fluorescence intensities were quantified via flow cytometry.

[0062] Figure 14a shows the strategy for validation. A Kd search band was generated based on the Kd-Z score curve fit. The Z score ranges of four desired Kd (1000 pM, 3000 pM, 9000 pM and 27,000 pM) were calculated. Several aptamer candidates within the Z score ranges can be tested and the difference between their actual Kd and the desired Kd can then be calculated to evaluate the accuracy of Z core-based aptamer identification.

[0063] Figure 14b are plots of d(pM) versus MPO aptamer candidates which shows evaluation of the accuracy of using Z scores to identify MPO aptamers with Kd values of 1000 pM, 3000 pM, 9000 pM and 27,000 pM. The red dots represent the aptamers with actual Kd <25% difference from the desired Kd. The data points of MPO-13 (Kd:9580 pM) and APO-27 (Kd:27700 pM) are outside their axis limits and not shown. Figure 14c are plots of % of total binding versus MPO concentrations

[0064] (pM) which shows the binding curve of the best-fit aptamer candidates. Polystyrene particles coated with aptamers, MPO-14, MPO-18, MPO-25, or MPO-34 were incubated with Cy-5 labelled MPO prior to analysis via flow cytometry. The red line represents the results of fitting a Langmuir binding isotherm to the MPO binding data. Data are presented as median values and the error bars represent the standard deviation of three replicates.

[0065] Figure 15 are plots of normalized particle count versus fluorescence intensity (APC channel) which shows the evaluation of the binding performance of the selected MPO aptamers (in table S4) using a beads-based fluorescent assay.

[0066] Figure 16 is a table which shows selected aptamer sequences for validation experiments.

[0067] Figure 17 shows the analysis of the secondary structure of the selected MPO aptamers. The secondary structure of MPO-14(a), MPO-18(b), MPO- 25(c) and MPO-34(d) were analyzed using M-fold.

[0068] Figure 18 are bar charts of fluorescence versus protein targets which shows the evaluation of the binding specificity of MPO aptamers. Aptamer particles displaying aptamer candidates were incubated with 50 nM MPO, BNP, insulin, peroxidase, human serum proteins, or thrombin for 1 hr and labelled with Cy5-streptavidin prior to analysis via flow cytometry. All the tested proteins are biotinylated. No protein was added in Control. Data are presented as median values, and the error bars represent the standard deviation of three replicates. The MPO aptamers demonstrated excellent binding specificity. Figure 19 are bar charts of the normalized % of binding versus MPO aptamer candidates which shows the evaluation of the binding performance of MPO aptamers in biological samples. Aptamer particles displaying seven aptamer candidates were incubated with 50 nM MPO in binding buffer, artificial interstitial fluid (ISF), sweat, urine, or serum for 1 hr and labelled with Cy5- streptavidin, prior to analysis via flow cytometry. The y-axis is the median fluorescence signal normalized to the binding buffer control. MPO aptamers demonstrated their target binding capability in multiple biofluids. To be noted, MPO-Apt27 produced a higher binding signal in ISF than in the binding buffer. All experiments were conducted in triplicates, and the median fluorescence intensity values were recorded. The error bars represent the standard deviation of three replicates.

[0069] Figures 20a to 20d shows the evaluation of the binding performance of MPO-16, in which:

[0070] Figure 20a shows the sequence and secondary structure of MPO-16. The secondary structure was generated using M-fold;

[0071] Figure 20b is a plot of fluorescence versus MPO concentrations(pM) which shows the assessment of binding affinity of MPO-16 and MPO16T, a truncated version of MPO-16;

[0072] Figure 20c are bar charts of fluorescence versus protein targets which shows the evaluation of the binding specificity of MPO aptamers; and

[0073] Figure 20d are bar charts of the normalized % of binding versus biological samples which shows the evaluation of the binding performance of MPO aptamers in biological samples in which the error bars represent the standard deviation of the three replicates.

[0074] Figure 21a is a diagram which shows conventional SELEX strategy.

[0075] Figure 21b is a diagram which shows Pro-SELEX strategy.

[0076] Figure 21c is a table which shows a comparison of Pro-SELEX with current aptamer selection technologies.

[0077] Figure 22 are tables which show the time required for SELEX and Pro- SELEX.

[0078] Figure 23 is a schematic representation of non-limiting chip configurations.

[0079] DETAILED DESCRIPTION

[0080] A high-dimensional microfluidic approach for selection of aptamers with programmable binding affinities is disclosed herein. Although embodiments of the present invention are disclosed herein, the disclosed embodiments are merely exemplary and it should be understood that the invention relates to many alternative forms, including different shapes and sizes. Furthermore, the Figures are not drawn to scale and some features may be exaggerated or minimized to show details of particular features while related elements may have been eliminated to prevent obscuring novel aspects. Therefore, specific structural and functional details disclosed herein are not to be interpreted as limiting but merely as a basis for the claims and as a representative basis for enabling someone skilled in the art to employ the present invention in a variety of manners.

[0081] As used herein, the terms “comprises”, “comprising”, “includes” and “including” are to be construed as being inclusive and open ended, and not exclusive. Specifically, when used in this specification including claims, the terms “comprises”, “comprising”, “includes” and “including” and variations thereof mean the specified features, steps or components are included. These terms are not to be interpreted to exclude the presence of other features, steps or components.

[0082] As used herein, the terms “about” and “approximately”, when used in conjunction with ranges of dimensions, compositions of mixtures or other physical properties or characteristics, is meant to cover slight variations that may exist in the upper and lower limits of the ranges of dimensions so as to not exclude embodiments where on average most of the dimensions are satisfied but where statistically dimensions may exist outside this region. It is not the intention to exclude embodiments such as these from the present invention.

[0083] As used herein, the coordinating conjunction “and / or” is meant to be a selection between a logical disjunction and a logical conjunction of the adjacent words, phrases, or clauses. Specifically, the phrase “X and / or Y” is meant to be interpreted as “one or both of X and Y” wherein X and Y are any word, phrase, or clause.

[0084] As used herein, aptamers may be nucleotides sequences of singlestranded DNA, RNA or non-natural nucleic acids, i.e. synthetic nucleic acid analogues that have a different sugar backbone than the natural nucleic acids DNA and RNA. Aptamers may also be or amino acid sequences of proteins or peptides. Aptamers may selectively bind a specific target, or family of targets including proteins, peptides, carbohydrates, DNAs, RNAs, small molecules, toxins, viruses and live cells such as mammalian cells and bacteria. Aptamers may exhibit a range of affinities, with variable levels of off-target binding and are sometimes classified as chemical antibodies.

[0085] As used herein, the term “capture zone” or “zone” may be used interchangeably with “defined volume”.

[0086] Methods

[0087] Materials

[0088] Carboxyl polystyrene particles (7 pm, #PC06004) were purchased from Bangs Laboratories, Inc. DPBS (#14190250), streptavidin (Cy5, #SA1011 ), Dynal MyOne C1 streptavidin dynabeads (65001), biotinylated peroxidase (#432040), PureLink™ Quick Gel Extraction Kit (K210012), EZ-Link™ Micro NHS-PEG4-biotinylation Kit(#21955) and dNTP Mix(#R0192) were ordered from Thermo Fisher Scientific. Light mineral oil (#M5310), 2-butanol (#294810), N-(3-dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC, #161462), N-hydroxysuccinimide (NHS, #130672), Human serum (H4522-100ML) and imidazole hydrochloride (#13386) were purchased from Sigma Aldrich. Antibiotin microbeads ultrapure (#130-105-637) and Labeling Check Reagents-APC (#130-122-219) were purchased from Miltenyi Biotech. Recombinant Human myeloperoxidase protein (MPO, 3174-MP-250) was ordered from R&D Systems. Lambda exonuclease (#M0262S) was ordered from New England Biolabs (NEB). GoTaq G2 Hot Start Taq Polymerase (#M7405) was purchased from Promega. ABIL® EM 90 was obtained from Evonik. Recombinant Human B-Type Natriuretic Peptide (BNP) protein (#ab87200) and recombinant human RANTES protein (#ab269212) were ordered from Abeam. Simulated Interstitial Fluid (#BZ254) was purchased from Biochemazone. Sweat (#991-20-P) and urine (#991-03-P-FNF-1) were ordered from Lee Biosolutions. Biotinylated thrombin (#69723) was obtained from Fisher Scientific. Biotinylated thrombin (#69723) was obtained from Fisher Scientific. DT-20-M Gamma tubes were ordered from I KA Works. Water was purified with a Millipore Milli-Q Biocel water purification system.

[0089] All DNA oligonucleotides (see Figure 7) were obtained from Integrated DNA Technologies and purified by 10% denaturing (8 M urea) polyacrylamide gel electrophoresis (dPAGE), and their concentrations were determined by a NanoDrop spectrophotometer. The library was 90-nt long, consisting of a 50-nt variable region flanked by two 20-nt primer sites (5’- AGCAGCACAGAGGTCAGATG-N50-AAGTGTAGTGTCTCCGTGGC-3’). The Forward primer (FP) sequence was 5’-AGCAGCACAGAGGTCAGATG-3’ and the reverse primer (RP) was 5’-GCCACGGAGACACTACACTT-3’. The sequencing adaptors were 5’- ACACTCTTTCCCTACACGACGCTCTTCCGATCT-N N N N- AGCAGCACAGAGGTCAGATG-3’ for the FP adaptor and 5'- GTGACTGGAGTTCAGACGTGTGCTCTTCCGATCTGCCACGGAGACACTAC ACTT-3' for the RP adaptor.

[0090] Chip fabrication and operation

[0091] The microfluidic device was fabricated using the protocol combining 3D printing and soft lithography techniques. In brief, the master mold was manufactured by a stereolithographic 3D printer (Microfluidics Edition 3D Printer, Creative CADworks, Canada) using the “CCW master mold for PDMS” resin (Resinworks 3D, Canada) with a layer thickness of 50 pm. The actual chips were fabricated by casting polydimethylsiloxane (PDMS, Sylgard 184, Dow Chemical, US) on the printed molds, followed by 120-min incubation at 70 °C for curing. Cured PDMS replicas were peeled off, punched and plasma bonded to no.1 glass thickness coverslips (260462, Ted Pella, US) to finish the chip. Before use, the chips were conditioned by a binding buffer (DPBS with 2.5 mM MgCl2, 1 mM CaC , 0.01 % TWEEN-20) to remove air bubbles. During operation, each chip was attached to arrayed N52 NdFeB magnets (D14-N52, K&J Magnetics, US) and fluidically connected to a digital syringe pump (Fusion 100, Chemyx, US) under the withdrawn mode.

[0092] Finite Element Simulation

[0093] Numerical simulation of the flow velocity pattern within the microfluidic device was carried out by COMSOL Multiphysics (Version 5.6, COMSOL Inc., Sweden) using the 3D creeping flow module. The key parameters for simulation were set as below: boundary condition: pressure of 0 Pa with suppression of backflow, wall condition: no slip, and mesh size: physics-controlled, fine.

[0094] Scanning electron microscopy

[0095] Fabricated chips were coated with 15 nm Au using a desktop sputter coater (Denton Desk II, Leica, Germany). Coated chips were imaged under a field-emission scanning electron microscope (SU5000, Hitachi, Japan) using

[0096] 5kV accelerating voltage and high-vacuum mode. Preparation of biotin-labelled protein targets

[0097] MPO protein, as well as counter selection proteins, including human serum proteins, BNP and RANTES, were biotinylated using the EZ-Link Micro NHS-PEG4-Biotinylation Kit (Thermo Fisher Scientific). The free biotin was removed by Zeba Desalt Spin Column with 7K molecular weight cut off (10 mL, Thermo Fisher Scientific). We measured biotinylated protein concentration based on absorbance at 280 nm using a NanoDrop spectrophotometer. To be noted, the average molecular weight of human serum protein is estimated to be 150 kDa.

[0098] Pre-enrichment by SELEX

[0099] The DNA library (6 x 1014random DNA molecules) was diluted with 1 mL of binding buffer and heated at 90°C for 1 min, followed by annealing at room temperature for 10 min. Then, a mixture of magnetic beads (Dynabeads MyOne streptavidin C1 , Thermo Fisher Scientific) conjugated with human serum proteins, thrombin, BNP and RANTES were washed twice with binding buffer and incubated with the DNA library at room temperature (RT) for 2 hrs. The DNA in the supernatant was collected, mixed with MPO (R&D Systems)- conjugated magnetic beads, and incubated at RT for 1 hr. The beads were washed five times with 500 pL of binding buffer. The MPO-bound DNA molecules were then eluted by adding 100 pL water and heating at 95°C for 15 minutes. The eluted DNA was PCR amplified and used for the following round of enrichment and aptamer particle synthesis. Three rounds of pre-enrichment were performed to remove nonspecific DNA molecules that bind to undesired targets and enrich DNA molecules that bind to MPO.

[0100] Preparation of Forward Primer Particles

[0101] 1 mL of 7-pm carboxyl polystyrene particles (Bangs Laboratories) were washed once with 1 mL of 0.01 N NaOH and three times with 1 mL of nuclease- free water, then resuspended in a 500 pL reaction mixture containing 200 mM NaCI, 0.2 mM 5'-amino-modified FP (or amino-modified thrombin aptamers), 1 mM imidazole chloride, and 250 mM EDC (Sigma Aldrich). The free carboxyls on the particles were then converted into amino-reactive NHS-ester in the presence of 250 mM EDC and 100 mM NHS in 2-(N-morpholino) ethanesulfonic acid (MES) buffer (100 mM, PH 4.7) (Thermo Scientific) for 30 minutes at RT. The particles were then conjugated with 20 mM amino-PEG12 (Thermo Scientific) in MES buffer for one hour. The particles were washed three times with 1 mL of TE (10 mM Tris, pH 8.0, 0.1 mM EDTA), suspended in 1 mL of TE buffer, and stored at 4 °C.

[0102] Preparation of aptamer particles. Emulsion PCR: The oil phase (prepared fresh each time) was composed of 3% ABIL®EM90, and 0.05% Triton X-100 in mineral oil. The aqueous phase consisted of 1 x GoTaq PCR buffer (Promega), 25 mM MgCh, 3.5 mM of each dNTP (Therm Fisher Scientific), 3 pM 5’ phosphorylated reverse primer (Phos-RP), 0.5 U / pl of GoTaq Hot Start Polymerase (Promega), 2 pM template DNA, and 5x107FP-coated particles in a total volume of 1 mL. Water-in-oil emulsions were prepared by adding 1 mL of the aqueous phase to 7 mL of the oil phase in a DT-20 tube (I KA) locked into the Ultra-Turrax Device (IKA). This addition was performed dropwise over 30 seconds while the mixture was stirred at 650 rpm in the Ultra-Turrax. After adding the aqueous phase, we continued stirring the mixture for 5 min. The emulsions were distributed in 100 pl aliquots into ~80 wells of a 96-well PCR plate. We performed PCR under the following cycling conditions: 94 °C for 3 min, followed by 50 cycles of 94 °C for 15 sec, 58 °C for 30 sec and 72 °C for 75 sec. Emulsion PCR cleanup: After PCR, each PCR well was mixed with 50 pl of 2-butanol to break the emulsion. The broken emulsions were then transferred to a 50 mL tube. Next, 150 pl of 2-butanol was added to each PCR well to collect the leftover emulsions and transferred to the 50 mL collection tube. After vortexing for 30 sec, the particles were pelleted by centrifugation at 2,500 x g for 5 min. After carefully removing the oil phase, we resuspended the particles in 1 mL of emulsion breaking (EB) buffer (100 mM NaCI, 1 % Triton X- 100, 10 mM Tris-HCI, pH 7.5, and 1 mM EDTA) and transferred them to a new 1 .5 mL tube. After vortexing for 30 sec and centrifugation for 90 sec at 15,000 x g, we removed the supernatant. Particles were then washed three times with TE buffer by centrifugation followed by resuspension in 500 pl TE. Singlestranded APs generation: To generate single-stranded DNA, we first removed the supernatant by centrifugation. We then treated the particles with 100 U of Lambda exonuclease (NEB) in 500 pl of reaction buffer (67 mM glycine-KOH (pH 9.4), 2.5 mM MgCh, 0.01 % (v / v) Triton X-100.) at 37 °C for 1 hour, following by inactivation of the reaction by heating at 80°C for 15 min. The particles were then washed three times with 1 mL of TE buffer, suspended in 1 mL of TE buffer and stored at 4 °C.

[0103] Aptamer particle (AP) quality control. Forward primer conjugation:

[0104] The conjugation efficiency of the forward primers was evaluated by incubating 1 pM Cy5-labeled FP complementary sequence (Cy5-FP’) with 1 pL of FP particles in 100 pL of binding buffer at 60 °C for 10 minutes, then cooled down at RT for 10 minutes. The particles were washed twice with 100 pL binding buffer and analysed with a Cytoflex flow cytometer (Beckman Coulter Life Science).

[0105] Aptamer particle monoclonality

[0106] Based on the Poisson distribution, we predicted that most particles would be monoclonal when <35% of the particles contain PCR products. To confirm this, we annealed the aptamer particles with Cy5-labeled RP in binding buffer at 60°C for 10 minutes and cooled down at RT for 10 minutes. The particles were then washed twice with 100 pL binding buffer then analysed by flow cytometry.

[0107] Determining Aptamer Copy Number on Each AP

[0108] Quantitative PCR (qPCR) was performed with a CFX384 Real-Time

[0109] PCR detection system (Bio-Rad) to estimate the aptamer copy number for each AP. Calibration samples were prepared by adding 1 *10, 1 xio2, 1 xi o3, 1 xio4, 1 xio5, 1 xio6, 1 xio7, 1 xio8, 1 xio9, or 1 xio10templates into a 20 pL reaction containing 250 nM each of FP and RP, -8,000 FP-coated particles, 5 pL GoTaq PCR Master Mix (Promega) and 0.5x SYBR green (Life Technologies). Test samples were prepared identically, but with -8000 APs. From the threshold cycle, we quantified - 4.8 xio8sequences on 8000 APs. Since only -20% of APs displayed template sequences, the average copy number of sequences on each template-bearing AP was ~3x105.

[0110] Pro-SELEX Screening

[0111] During Pro-SELEX screening, we incubated 5*107aptamer particles with biotin-labelled MPO protein at different concentrations (see Figure 10 for detailed experimental conditions) in selection buffer (DPBS with 2.5 mM MgCh, 1 mM CaCh, 0.01 % TWEEN-20, 0.2% BSA). To ensure the MPO molecules are not depleted during selection, reaction volumes were increased when using lower concentrations of the target. After 1 hour of incubation, the beads were washed three times with selection buffer. We then magnetically labeled the bound MPO proteins by incubating the particles with 20 pL of anti-biotin microbeads (Miltenyi Biotech) in 1 mL of selection buffer for 15 min at RT. The particles were then washed with selection buffer twice and sorted by Pro- SELEX microfluidic devices. The aptamer particles captured at each capture zone (or defined volume) of Pro-SELEX microfluidic devices were collected and stored at 4 °C.

[0112] High-throughput Sequencing

[0113] For each collected aptamer pool and the unsorted DNA pool, two rounds of PCR were performed to add adaptor sequences and sequencing indexes. The amplified sequences were then purified using agarose gel electrophoresis and PureLink™ Quick Gel Extraction Kit, quantified using a NanoDrop spectrophotometer and sent to the McMaster Genomics Facility for sequencing on an Illumina MiSeq.

[0114] Bioinformatics Raw sequencing data was processed using Illumina’s Basespace online platform to sort tagged sequence pools and output sequence data in FASTQ format. Paired-end reads were merged using USEARCH (V10) and the primers were then trimmed using Cutadapt (V3.5). Sequences containing less than perfect complementarity were discarded to minimize sequencing errors in the dataset. FASTA format trimmed sequences were dereplicated and tagged with copy number using USEARCH. Read counts were then generated in the format of tab-delimited text files. The files were processed by the AptaZ script written in MATLAB (Version 2021a, MathWorks, US) to calculate the corresponding Z score for each sequence. Calculated Z scores were exported as CSV files for visualization and validation.

[0115] Affinity Measurement

[0116] After sequencing analysis, we performed particle PCR to synthesize APs displaying each unique aptamer candidate sequence. Each particle PCR reaction (100 pL) consisted of 1x GoTaq PCR Master Mix (Promega), 25 mM MgCh, 2 pM phos-RP, 10 nM aptamer template and 5*106FP-coated particles. PCR was carried out under the following cycling conditions: 94 °C for 3 min, followed by 30 cycles of 94 °C for 15 sec, 58 °C for 30 sec and 72 °C for 30 sec. To avoid particle aggregation and increase particle PCR efficiency, we vortexed the reaction every four cycles after the 94 °C denaturing step. We then removed the reverse strands using Lambda exonuclease as described above and incubated 1 pL of the APs with Cy5-RP and measured AP fluorescence intensity using flow cytometry to test particle PCR efficiency. For affinity measurement, different concentrations of biotinylated MPO (10 pM to 200 nM) were incubated with a fixed amount of the APs (~2X104particles) in selection buffer for 1 hr at room temperature. The unbound MPO was washed away with selection buffer, after which streptavidin-labeled Cy5 was introduced and incubated for 15 minutes to label the bound MPO. The particles were washed with selection buffer and median fluorescence intensities were quantified via flow cytometry.

[0117] Results

[0118] The overall Pro-SELEX approach is summarized in Figure 1a and Figure 1 b. Aptamer libraries displayed on particles are incubated with the binding target, where they are expected to bind to differing numbers of analyte molecules based on affinity. Magnetic nanoparticles are used to label the aptamer particles according to number of analyte molecules bound, and the aptamer particles are then sorted into different compartments of a microfluidic chip based on magnetic content. Pools of aptamers are then generated based on the material collected in each compartment and sequenced. Comparative bioinformatics are then used to analyze the representation of individual aptamers and confirm the validity of sequences as true positive hits as well as infer relative affinity ranges.

[0119] Development of Pro-SELEX selection platform.

[0120] To measure the relative affinity of each aptamer sequence in a nucleic acid library, particle display techniques23can be used to transform individual aptamer candidates from a solution-based aptamer library into monoclonal aptamer particles (APs) via emulsion PCR, where each particle presents many copies of a single nucleic acid sequence on its surface (see Figure 1a). The AP libraries can then be incubated with a specific target over a range of concentrations. Based on the Langmuir isotherm, the target binding level of an AP is dependent on the target concentration and the binding affinity of the aptamer coated on its surface, where half of the aptamer molecules will be bound to the target when the target concentration is equal to the K of the aptamer. APs with different binding levels can then be separated and collected using a high-resolution microfluidic sorting approach followed by sequencing analysis to identify aptamers with different binding affinities based on their binding performance at different target concentrations.

[0121] To accurately partition APs with different levels of target binding, we developed a magnetic labelling and microfluidic sorting approach (see Figure 1 b). Polystyrene particles (7 pm in diameter) were used to prepare APs. After incubation of APs with a biotinylated target of interest, the particles were labelled with anti-biotin magnetic nanoparticles (MNPs, 50 nm in diameter) to convert the target binding into a magnetic content. The labelled mixture was then sorted and isolated using a microfluidic device (Pro-SELEX chip).

[0122] This device features four capture zones (or defined volumes) with differing linear velocities to allow differential sorting of APs with varying levels of magnetic content. Owing to the low magnetic susceptibility of MNPs, each capture zone contains microfabricated structures to create localized regions of low flow velocity and enhanced capture dynamics (see Figure 2a and Figure 2b). The first zone exhibits the highest linear velocity and thus retains APs with high magnetic content, as the retaining magnetic force overcomes the drag force exerted by the high flow velocity. The ensuing three zones exhibit gradually reduced linear velocities (see Figure 1c for simulation information and Figure 1d). This design allows APs to be separated and captured in different zones according to their target binding levels. We demonstrated that the Pro-SELEX chip is able to sort the particles based on their magnetic content (see Figure 1e and Figure 3).

[0123] It is worth noting that the stringency and resolution of magnetic separation of the Pro-SELEX chip are programable by adjusting the chip flow rate (see Figure 1 e). Similar device design has been used to perform profiling of cellular proteins and nucleic acids as well as rare cell capture, demonstrating superior throughput and recovery rate compared to fluorescence-activated cell sorting (FACS) and magnetic-activated cell sorting (MACS)26-29. This is the first report that demonstrates the utility of a device iteration for aptamer selection.

[0124] Validation of the sorting performance of Pro-SELEX chip.

[0125] In the first suite of experiments, we used thrombin aptamers as a test case to validate the approach (see Figure 4a). We first tested whether the Pro- SELEX chip could sort APs with different levels of target binding. Thrombin-03 aptamer23-coated particles (03-particles) with varying target binding levels were prepared by incubating the particles with a range of thrombin concentrations, from 1 pM to 1 nM, followed by labelling with MNPs (see Figure 4b). These 03- particles were then sorted using Pro-SELEX chips at flow rates of 8 mL / hr and 16 mL / hr and distinctive sorting profiles were generated (see Figure 4c and Figure 4d). The particles with high magnetic content (1 nM and 100 pM) were primarily captured in zone 1 of the chip at a flow rate of 8 mL / hr and partially shifted to zone 2 upon increasing the flow rate to 16 mL / hr, whereas particles with lower magnetic content were mainly collected in later zones and almost all of the non-target bound particles were detected in the waste. This indicates that the Pro-SELEX chip is able to sort and capture APs based on their target binding levels, employing several flow rates to stratify the sorting profile.

[0126] Next, we explored whether the Pro-SELEX approach could separate APs with different binding affinities. Two types of APs were prepared carrying comparable copy numbers of either Thrombin-03 ( d 7.04 pM) or Thrombin- TBA ( d 2.6 nM)2330(see Figure 5). Both APs together with primer-coated particles were tested with three thrombin concentrations and analysed using flow cytometry (see Figures 4e, Figure 4f and Figure 4g) and the Pro-SELEX chip (see Figures 4h, Figure 4i and Figure 4j). When using a thrombin concentration of 1 pM which is significantly higher than the K of both aptamers, both APs became saturated by the target and were captured in zone 1 of the chip. When the target concentration dropped to 1 nM, a significant separation was observed such that the high-affinity 03-particles remained in zone 1 and the low-affinity TBA-particles were binned in zones 2 and 3.

[0127] When the target concentration further decreased to 1 pM, most TBA- particles were collected in the waste whereas a significant fraction of the 03- particles were still captured in the chip. Notably, less than 0.5% of the primer- coated particles were captured by the chip at a flow rate of 8 mL / hr regardless of the thrombin concentrations, showcasing the high capture specificity of the Pro-SELEX chip. We further investigated the effect of flow rate on the nonspecific capture of aptamers to ensure that nonbinders can efficiently be removed during the selection process (see Figure 6). Together, these results demonstrated that the Pro-SELEX chip is capable of separating APs with distinctive binding affinities, where target concentrations play a prominent role in determining the separation efficiency.

[0128] Selection of MPO aptamers using Pro-SELEX.

[0129] We next explored whether we could use the Pro-SELEX platform to efficiently generate aptamers. We selected MPO as the model target for testing the capability of Pro-SELEX for aptamer selection. An initial random DNA library containing ~1014random DNA molecules was first subjected to a preenrichment step consisting of 3 rounds of both counter selections against undesired targets and conventional SELEX towards MPO immobilized beads to remove nonspecific binders and reduce the sequence space of the library (see Figure 7 and Figure 8).

[0130] The enriched library was then used as a template to prepare AP libraries through emulsion PCR (see Figure 9a to 9i). The AP libraries were tested at five MPO concentrations (10 pM, 100 pM, 1 nM, 10 nM, and 100 nM), in an attempt to isolate aptamers with K within this range. It was critical to ensure that the MPO molecules were available in excess and not depleted during the target incubation (see Figure 10), especially when testing low target concentrations, to confirm that the binding between APs and MPO follows the Langmuir isotherm.

[0131] AP libraries were then sorted by Pro-SELEX chips at two flow rates, 16 mL / hr and 32 mL / hr (see Figure 11a). It required less than 20 minutes for the Pro-SELEX chip to sort 5*107APs, which is faster than the FACS-based sorting method23. Particles captured by each zone within the ten chips were then collected (see Figure 11 b and Figure 11c). As expected, we clearly observed that the fractions of APs captured by Pro-SELEX chips decreased upon lowering the target concentration and the sorting profiles of the APs libraries were shifted when using a faster flow rate, highlighting the high resolution of our approach. The particles collected from zones 1-3 of each chip together with the unsorted aptamer population, for a total of 31 DNA pools, were subjected to high-throughput sequencing (HTS). We also created a scoring tool, AptaZ, which was employed to comprehensively analyse the fold of enrichment of each aptamer candidate from 30 DNA pools and generate a Z score (see details below in development of the algorithm and Figure 11 d).

[0132] Development of AptaZ algorithm.

[0133] A Z-score is a numerical measurement that describes a value’s relationship to the mean of a group of values. Its value is a quantitative reflection of the deviation from the average. If a Z-score is 0, it indicates the score of that specific data point is identical to the average score. Z score may be positive or negative, with a positive value indicating the score is above the average and a negative score indicating it is below the average. Higher Z score means the specific data point is significantly enriched or depleted in the dataset.

[0134] Z score has multiple realization and modifications at this moment, for example, some algorithms use median instead of mean as the average. In addition, many algorithms have different ways of measuring the ‘deviation’ from the average, for example, standard deviation (SD), median of absolution deviation (MAD) or fold change (FC). In the realization of AptaZ, we considered the median of the whole dataset as the measure of average and fold change (FC) as the measure of deviation. The concept of AptaZ is adapted from the DrugZ algorithm used to identify genetic perturbations using the degree of enrichment of specific barcode. During the operation of Pro-SELEX, we obtained the degree of enrichment of specific sequences under different selection pressures from the parallelized microfluidic sorting. The AptaZ algorithm weighted each selection condition and quantitatively measured how far a specific sequence deviated from the bulk average. It provides a comprehensive measure regarding how a specific sequence gets enriched under all selection conditions, which is tightly linked to their binding affinity against the target molecule.

[0135] Procedures

[0136] The AptaZ algorithm consists of three steps as discussed below:

[0137] 1. Calculate the fold change of each DNA sequence under a specific condition

[0138] (e.g., Zone 1 , flowrate 16 mL / hr, protein concentration 100 pM).

[0139] Where:

[0140] • FC = fold change

[0141] • i = sequence index

[0142] • j = condition index

[0143] • S = sorted sample

[0144] • C = control (unsorted) sample pseudocount = default value is set to 5 • norm() = normalizing the total read count of the sample into 1 million reads

[0145] 2. Calculate the Z score of each sequence under a specific condition

[0146] Given the nature of aptamer selection, we assume that the majority of the sequences shall not give any specific binding, which is equivalent to a zero contribution to Z score. With this in mind, each Fc was normalized by the median value of Fc.

[0147] Where:

[0148] • Z = Z score

[0149] • i = sequence index

[0150] • j = condition index

[0151] • S = sorted sample

[0152] • FCAJ = a vector consisting of all FC values calculated from the index under condition j

[0153] • median() = taking the median of the input vector

[0154] 3. Calculate the sumZ score of each sequence from all conditions

[0155] To comprehensively consider all selection conditions, we calculate the sumZ score from the Z score in a weighted fashion Where:

[0156] • sumZ = sumZ score

[0157] • N = Total number of conditions

[0158] • WZ = zonal weight o Considering that the fluidic velocity in the next zone is 1 / 3 of the previous zone, we assigned a weight 9, 3, 1 to zone number 1 , 2, 3, respectively.

[0159] • WF = flowrate-defined weight o Considering that the fluidic velocity in a zone is proportional to the flow rate, we assigned a weight of 2, 1 to the flow rate of 32, 16 mL / hr, respectively.

[0160] • WC = concentration-defined weight o We assume the difficulties of binding is a logarithmic function of protein concentration. With this in mind, we assigned a weight of 5, 4, 3, 2, 1 to the concentration of 10, 100, 1000, 10000, 100000 pM.

[0161] Sample calculations

[0162] Case 1 :

[0163] MPO-01

[0164] Sequence:

[0165] CACTCGTGAAGATCTTTAATAGATAGAATAATCGAGGTTGATTCGATGTA sumZ score = 1267.38

[0166] Case 2:

[0167] MPO-25

[0168] Sequence: GATCGCAGCATCAAATAAGAACATTGTGAATTATGTAATCTGGCTATGTG sumZ score = 10.82

[0169] Aptamer candidates that can survive multiple target concentrations, especially low concentrations at two flow rates and be repeatedly captured by the chips would generate high Z scores (see Figure 11e). Eight MPO aptamer candidates, MPO-01 to MPO-08, with diverse Z scores were randomly chosen for characterization (see Figure 12). All eight aptamers demonstrated an affinity for MPO with Kd values ranging from 227 pM to 27.8 nM (see Figure 3f, Figure 11f and Figure 13). A linear relationship was observed between the K values of the 8 candidates and their calculated Z scores based on curve fitting (see Figure 11g), indicating the potential of using Z scores to search for the aptamer candidates with desired binding affinities.

[0170] Quantitative selection of MPO-aptamers with desired binding affinities.

[0171] We next explored whether the Z score could be used to quantitatively screen aptamers with desired binding affinities. A search band was generated based on the correlation between the Z score and the Kd values of the validated MPO aptamers (see Figure 14a). We set the desired Kd values as 1000 pM, 3000 pM, 9000 pM, and 27,000 pM and calculated their theoretical Z score ranges based on the search band. Aptamer candidates within this range were then chosen and examined for their binding affinities, and the differences between their experimental Kd and the desired Kd were calculated. We defined a difference smaller than 25% as a “great fit”.

[0172] By evaluating the binding affinity of multiple MPO aptamer candidates in different Z score ranges (see Figure 15 and Figure 16), we found that the success rate in identifying a “great fit” was between 20%-50%, suggesting that by testing no more than five aptamer candidates within the Z score range, we can identify one aptamer with the desired binding affinity (see Figure 14b).

[0173] The “best fits” for the requested affinities are MPO-14 with Kd of 897 pM, MPO-18 with d of 3192 pM, MPO-25 with Kd of 8778 pM, and MPO-34 with Kd of 24910 pM (see Figure 4c, their secondary structures are provided in Figure 17). The Ka values of the tested aptamers spanning more than 100-fold. The selected aptamers also demonstrated excellent specificities for MPO (see Figure 18) as well as the potential to be used to analyse biological samples (see Figure 19). MPO-16 revealed the highest binding affinity ( d =166 pM) and its sequence, secondary structure, binding specificity and binding performance in biological samples have been highlighted in Figure 20. It should be noted that the normal MPO level from a healthy middle-aged population has been reported to be <640 pM, with higher MPO levels being associated with increased risk of cardiovascular diseases31. We believe that the anti-MPO aptamers with different binding affinities reported here will become valuable tools in future MPO monitoring applications.

[0174] Discussion

[0175] Here we report an aptamer generation method, Pro-SELEX, which enables efficient and quantitative generation of aptamers with desired binding affinities. Unlike conventional SELEX methods that rely on iterative rounds of selection to screen for aptamer candidates (see Figure 21a), the present approach disclosed herein monitors the binding performance of individual aptamer candidates at different target concentrations in a single round of selection (see Figure 21b), taking advantage of the high level of parallelization enabled by high-dimensional microfluidics. Current iterations of SELEX, such as CE-SELEX and Particle display, despite their significantly improved efficiency in generating aptamers, still select for aptamers with the highest affinities (see Figure 5c and see Figure 21c). Unfortunately, high-affinity aptamers might not be suitable for all applications. For instance, affinity receptors with suitable Kd should be selected based on the target concentration range to achieve quantitative biomolecular recognition, as the dynamic range of single-site binding typically spans 81 -fold changes in target concentrations which is dependent on the K of receptors2. If the Kd of a receptor is significantly lower than the relevant concentration range, the resulting saturated signal will not change over the detection range2. A strategy to manipulate the dynamic range of sensing is to combine receptors with different target affinities1 32. This naturally raises the demand to generate aptamers with different Kd. In addition, lower-affinity receptors with fast binding kinetics (high on-rate and off-rate) are ideal for continuous monitoring as they allow for rapid equilibration with the surrounding target4 33.

[0176] The development of sophisticated detection modalities in recent years with considerably lower levels of background and digital outputs makes it possible to quantify molecules in log dynamic ranges at concentrations much lower than d34-36. By exploiting these types of sensing mechanisms, low-affinity receptors can also achieve high detection sensitivity. Collectively, it will be advantageous to have the capability of generating receptors with customizable binding affinities to meet the requirements of diverse applications. The Pro- SELEX platform was developed to fulfill this need.

[0177] The Pro-SELEX approach is also highly programable and can be easily customized to suit various other applications. For example, the particle size used in this platform is large enough (7 pm in diameter) to capture a wide range of targets, from small molecules to viruses or bacteria. Given the high efficiency of Pro-SELEX and the broad applications of aptamers during the SAES-Cov-2 pandemic37-39, our platform can be applied for rapid generation of anti-virus aptamers during the early stage of a pandemic. The time required for Pro- SELEX and SELEX has been summarized in Figure 22. In addition, recent advances in incorporating non-natural nucleotides with diverse structures and functional groups into aptamers would enable aptamers with enhanced binding performance and expanded target range40-43. We believe our approach can be adapted to accommodate these unnatural nucleotides to efficiently produce modified aptamers.

[0178] According to an embodiment, the chips may be assembled under various configurations that may allow effective collection of the NM-particle:M-particles complexes and / or isolation and collection of aptamers of preselected binding affinities from the sorted complexes. Figure 23 shows non-limiting configurations of the chips for the present invention. The chips may be assembled in series, in parallel or combination of thereof. According to an embodiment, x may be 0 or greater than 0 and n, m...z may be 0 or greater than 0.

[0179] According to an embodiment, the skilled person understands that the present invention may be used with peptide-based aptamers. By using his / her common general knowledge, the skilled person will adapt the method to peptide-based aptamers. As a non-limiting example, the step of “isolating and collecting aptamers of preselected binding affinities from the sorted complexes” may comprise collecting the complexes, determining the amino acid sequences of the peptide-based aptamers from the collected complexes and synthesizing peptides corresponding to the sequenced aptamers using a peptide synthesizer or other suitable techniques. In an embodiment the present disclosure provides a method of collecting aptamers based on binding affinity to a biomarker, the method comprising the steps of: loading aptamers on surfaces of nonmagnetic particles (NM-particles) from a pool of a plurality of aptamers with different nucleic acid sequences, each NM-particles having respectively aptamers with the same nucleic acid sequences on the surface of the NM-particles; labelling magnetic particles (M-particles) with biomarkers; forming aptamerbiomarker complexes by binding the aptamers to the biomarkers therefore forming NM-particle:M-particles complexes once the M- particles are labelled with the biomarkers; serially sorting the complexes according to aptamer-biomarker binding affinities using magnetic strength of the complexes wherein complexes with higher binding-affinity aptamers have a higher load of M-particles and wherein complexes with lower binding-affinity aptamers have a lower load of M- particles; collecting the sorted complexes; and isolating and collecting aptamers of preselected binding affinities from the sorted complexes.

[0180] In an embodiment the method further comprises the step of enriching the pool of a plurality of aptamers prior loading the aptamers on the surfaces of the

[0181] NM-particles. In an embodiment the step of enriching the pool of a plurality of aptamers is performed with emulsion PCR.

[0182] In an embodiment the biomarker is selected from the group of proteins, DNA, RNA, small molecules, viruses, and live cells (such as bacteria and mammalian cells).

[0183] In an embodiment the aptamers are sequences of nucleotides of DNA, RNA or non-natural nucleic acids or sequences of amino acids of proteins or peptides.

[0184] In an embodiment the step of serially sorting the complexes comprises flowing the complexes through a plurality of sequentially placed defined volumes in fluid communication, each volume configured to sort the complexes based on the load of M-particles of the complexes.

[0185] In an embodiment the step of serially sorting the complexes is followed by the step of isolating and collecting the complexes from each volume.

[0186] In an embodiment each volume has enclosed therein a structure having magnetic properties to collect the complexes having preselected magnetic load.

[0187] In an embodiment each volume is configured to have a different linear velocity for differential sorting of the complexes with different load of M- particles.

[0188] In an embodiment the first volume has the highest linear velocity and each successive volume has reduced linear velocities when compared to the linear velocity of the previous volume. In an embodiment a linear velocity in a particular volume of the series of sequentially placed volumes is lower than the velocity of a previous adjacent volume and higher than the next adjacent volume.

[0189] In an embodiment the volumes contain structures configured to define a flow velocity therein and wherein each volume of the series of sequentially placed volumes has a reduced linear velocity when compared to the linear velocity of the previous adjacent volume.

[0190] In an embodiment the plurality of sequentially placed volumes is grouped on a series of chips in fluid communication, each chip having a defined number of volumes in series.

[0191] In an embodiment the method further comprises at least one or more series of chips, the at least one more series of chips being parallel with the first series of chips.

[0192] In an embodiment the series of chips are configured in a parallel configuration.

[0193] In an embodiment the series of chips are configured in a serial configuration.

[0194] In an embodiment the plurality of chips is 1 , 2, 3, 4, 5, 6, 7, 8, 9, or 10.

[0195] In an embodiment the method further comprises the steps of selecting the desired binding affinities or range of binding affinities of the aptamers for each volume. In an embodiment the M-particles are first labelled with the biomarkers and the NM-particle: M-particles complexes are then formed by incubating the loaded NM-particles and the labelled M-particles

[0196] In an embodiment the aptamerbiomolecule complexes are first formed by incubating the loaded NM-particles with the biomolecules and then attaching the M-particles to the biomolecules therefore forming the NM-particle: M- particles complexes.

[0197] In an embodiment the step of isolating and collecting the aptamers comprises using PCR amplification to amplify the nucleic acid sequences of the aptamers on the loaded NM-particles of the NM-particle: M-particles complexes.

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Claims

Claims1 . A method of collecting aptamers based on binding affinity to a biomarker, the method comprising the steps of: loading aptamers on surfaces of nonmagnetic particles (NM-particles) from a pool of a plurality of aptamers with different nucleic acid sequences, each NM- particles having respectively aptamers with the same nucleic acid sequences on the surface of the NM-particles; labelling magnetic particles (M-particles) with biomarkers; forming aptamer: biomarker complexes by binding the aptamers to the biomarkers therefore forming NM-particle:M-particles complexes once the M- particles are labelled with the biomarkers; serially sorting the complexes according to aptamer-biomarker binding affinities using magnetic strength of the complexes wherein complexes with higher binding-affinity aptamers have a higher load of M-particles and wherein complexes with lower binding-affinity aptamers have a lower load of M-particles; collecting the sorted complexes; and isolating and collecting aptamers of preselected binding affinities from the sorted complexes.

2. The method according to claim 1 further comprising the step of enriching the pool of a plurality of aptamers prior loading the aptamers on the surfaces of the NM-particles.

3. The method according to claim 1 or 2, wherein the biomarker is selected from the group of proteins, DNA, RNA, small molecules, viruses, and live cells (such as bacteria and mammalian cells).

4. The method according to claim 1 , 2 or 3, wherein the aptamers are sequences of nucleotides of DNA, RNA or non-natural nucleic acids or sequences of amino acids of proteins or peptides.

5. The method according to any one of claims 1 to 4, wherein the step of serially sorting the complexes comprises flowing the complexes through a plurality of sequentially placed defined volumes in fluid communication, each volume configured to sort the complexes based on the load of M-particles of the complexes.

6. The method according to claim 5 wherein the step of serially sorting the complexes is followed by the step of isolating and collecting the complexes from each volume.

7. The method according to claim 5, wherein each volume has enclosed therein a structure having magnetic properties to collect the complexes having preselected magnetic load.

8. The method according to any one of claims 5 to 7, wherein each volume is configured to have a different linear velocity for differential sorting of the complexes with different load of M-particles.

9. The method according to claim 8, wherein the first volume has the highest linear velocity and each successive volume has reduced linear velocities when compared to the linear velocity of the previous volume.

10. The method of claim 5 wherein a linear velocity in a particular volume of the series of sequentially placed volumes is lower than the velocity of a previous adjacent volume and higher than the next adjacent volume.11 . The method according to claim 10, wherein the volumes contain structures configured to define a flow velocity therein and wherein each volume of the series of sequentially placed volumes has a reduced linear velocity when compared to the linear velocity of the previous adjacent volume.

12. The method according to claim 10 or 11 wherein the plurality of sequentially placed volumes is grouped on a series of chips in fluid communication, each chip having a defined number of volumes in series.

13. The method according to claim 12 further comprising at least one or more series of chips, the at least one more series of chips being parallel with the first series of chips.

14. The method according to claim 12 wherein the chips in the series of chips are configured in a parallel configuration.

15. The method according to claim 12 wherein the chips in the series of chips are configured in a serial configuration.

16. The method according to claim 12, 13, 14 or 15 wherein the plurality of chips is 1 , 2, 3, 4, 5, 6, 7, 8, 9, or 10.

17. The method of claim 1 further comprising the steps of selecting the desired binding affinities or range of binding affinities of the aptamers for each volume.

18. The method of claim 2 wherein the step of enriching the pool of a plurality of aptamers is performed with emulsion PCR.

19. The method according to any one of claims 1 to 18 wherein the M-particles are first labelled with the biomarkers and the NM-particle: M-particles complexes are then formed by incubating the loaded NM-particles and the labelled M-particles20. The method according to any one of claims 1 to 18 wherein the aptamer biomolecule complexes are first formed by incubating the loaded NM- particles with the biomolecules and then attaching the M-particles to the biomolecules therefore forming the NM-particle: M-particles complexes.21 . The method according to any one of claims 1 to 20 wherein the step of isolating and collecting the aptamers comprises using PCR amplification to amplify the nucleic acid sequences of the aptamers on the loaded NM-particles of the NM- particle: M-particles complexes.

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