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WO2025035209A1 - Système de biocapteur aptamère multimère sans étiquette pour la surveillance en temps réel d'analytes cibles dans une configuration monotope - Google Patents

Système de biocapteur aptamère multimère sans étiquette pour la surveillance en temps réel d'analytes cibles dans une configuration monotope Download PDF

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Publication number
WO2025035209A1
WO2025035209A1 PCT/CA2024/051053 CA2024051053W WO2025035209A1 WO 2025035209 A1 WO2025035209 A1 WO 2025035209A1 CA 2024051053 W CA2024051053 W CA 2024051053W WO 2025035209 A1 WO2025035209 A1 WO 2025035209A1
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Prior art keywords
target
biosensor system
aptamer
buffer
binding
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English (en)
Inventor
Leyla Soleymani
Yingfu Li
Payel SEN
Jimmy Gu
Zijie ZHANG
Bal Ram ADHIKARI
Jiuxing LI
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McMaster University
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McMaster University
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N27/00—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means
    • G01N27/26—Investigating or analysing materials by the use of electric, electrochemical, or magnetic means by investigating electrochemical variables; by using electrolysis or electrophoresis
    • G01N27/28—Electrolytic cell components
    • G01N27/30—Electrodes, e.g. test electrodes; Half-cells
    • G01N27/327—Biochemical electrodes, e.g. electrical or mechanical details for in vitro measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/5308—Immunoassay; Biospecific binding assay; Materials therefor for analytes not provided for elsewhere, e.g. nucleic acids, uric acid, worms, mites
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/543—Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals
    • G01N33/54353—Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals with ligand attached to the carrier via a chemical coupling agent
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
    • G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
    • G01N33/543—Immunoassay; Biospecific binding assay; Materials therefor with an insoluble carrier for immobilising immunochemicals
    • G01N33/54366—Apparatus specially adapted for solid-phase testing
    • G01N33/54373—Apparatus specially adapted for solid-phase testing involving physiochemical end-point determination, e.g. wave-guides, FETS, gratings
    • G01N33/5438—Electrodes

Definitions

  • the present disclosure relates to biosensor systems, and in particular, to electrochemical biosensor systems, methods, and kits for target analyte detection.
  • the present disclosure describes a label-free multimeric aptamer biosensor system for real-time monitoring of target analytes in a one-pot configuration.
  • the present inventors have employed a three-pronged approach that uses: 1) ultra-high affinity aptamers, 2) in-solution target extraction using multimeric aptamers, and 3) real-time signal monitoring, which has provided analytical sensitivity and precision that are necessary for combating signalloss and signal variability encountered in wash-free and single-pot electrochemical readout.
  • This three-pronged approach it was demonstrated that a range of viral targets and protein biomarkers can be detected using a wash-free and single-pot format in native biological matrices and clinical samples.
  • This approach is versatile and can be applied to a wide range of targets and their aptamers, providing a universal approach for aptamer-based target detection using electrochemical readout.
  • a biosensor for detecting a target analyte in a sample comprising: a) an electrochemical impedance spectroscopy (EIS) module comprising (i) a working electrode, operable at a single frequency for real-time monitoring of aptamer binding to target, aptamer-target dissociation, or aptamer or target degradation on the working electrode, (ii) a counter electrode, (iii) a reference electrode, and (iv) a circuit compatible with potentiostat; b) a multimeric aptamer comprising two or more units for specific target binding and formation of an aptamer-target complex in solution, wherein the target comprises two or more binding sites, wherein the multimeric aptamer has a K ⁇ about 300 pM; wherein the multimeric aptamer is configured to bind to the surface of the working electrode, and wherein the biosensor system is configured to operate in a wash-free and singlepot format.
  • EIS electrochemical impedance spectroscopy
  • the multimeric aptamer is biotinylated and the surface of the working electrode is coated with streptavidin.
  • the working electrode is a gold working electrode.
  • the counter electrode is a gold counter electrode.
  • the reference electrode is a silver reference electrode.
  • the biosensor system is configured to operate in a wash-free and single-pot format.
  • the solution comprises a readout buffer comprising phosphate buffer saline, KC1, and redox reporter.
  • the redox reporter comprises K3[Fe(CN) 6 ]/K4[Fe(CN) 6 ], [Fe(CN) 6 ] 3 7[Fe(CN) 6 ] 4 -, Q/H 2 Q, [Ru(NH3)6] 3+ /[Ru(NH 3 )6] 2+ ,
  • the solution comprises redox reporter at about 2 mM K 3 [ Fe(CN)e] and about 2 mM K4[Fe(CN)e].
  • the solution comprises a blocking buffer comprising biotin-BSA and BSA.
  • the solution comprises about 0.01 pM biotin-BSA and about 0.1% BSA.
  • the solution comprises a binding buffer comprising HEPES, NaCl, KC1, MgCh, and CaCh.
  • the solution comprises about 5 mM HEPES, pH about 7.4, about 15 mM NaCl, about 0.6 mM KC1, about 0.25 mM MgCh, and about 0.25 mM CaCh.
  • the sample is a clinical sample.
  • the sample is saliva.
  • the saliva is heat-treated saliva.
  • the target is a protein target, a viral target, or a bacterial target.
  • the viral target is SARS-CoV-2 or influenza.
  • the viral target is SARS-CoV-2.
  • the SARS-CoV-2 is SARS-CoV-2 B.1.1.529 omicron variant.
  • the protein target is SARS- CoV-2 B.1.1.529 omicron variant spike protein.
  • the aptamer is a SARS- CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 6, 7, or 11.
  • the biosensor system is configured to detect SARS-CoV-2 B.1.1.529 omicron variant with a limit-of-detection of about 138 copies/mL in the solution comprising the redox buffer, the blocking buffer, and the binding buffer. In some embodiments, the biosensor system is configured to detect SARS-CoV-2 with a limit-of-detection of about 584 copies/mL in heat- treated saliva diluted to about 25% (v/v) in the solution comprising the redox buffer, the blocking buffer, and the binding buffer.
  • the viral target is influenza.
  • the aptamer is an influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 1, 2, or 9.
  • the protein target is vascular endothelial growth factor (VEGF).
  • the aptamer is a VEGF specific aptamer having the nucleic acid sequence of SEQ ID NO: 4, 5, or 10.
  • the biosensor system provides at least 80% sensitivity and at least 99% specificity. In some embodiments, the biosensor system provides at least 93% sensitivity. In some embodiments, the biosensor system provides at least 98% sensitivity. In some embodiments, the biosensor system provides 100% specificity.
  • the single frequency is between about 1 and about 20 kHz. In some embodiments, the single frequency is between about 12.6 and about 80 Hz. In some embodiments, the single frequency is about 12.6 Hz. In some embodiments, the total impedance is measured at intervals of every 2 minutes.
  • kits for detecting a label-free target in a sample comprising the biosensor system described herein, further comprising at least one of a dropper, a collection tube, a container holding the redox readout buffer, a container holding the binding buffer, a container holding the block buffer, and instruction for use.
  • FIG. 1A shows real-time monitoring of target binding using aptamers and electrochemical readout through electrochemical impedance spectroscopy to determine the frequency for real-time electrochemical readout in an exemplary embodiment of the disclosure.
  • FIG. 1A shows impedance plots generated across a frequency range of 1-20 kHz, and AZ/Z signals obtained for both target (OPV at 10 4 copies/mL) and blank solutions using the monomeric aptamers MSA52 (left panel).
  • Target-to-blank ratio (T/B) analyzed across the frequency range of 1 -20 kHz, with particular focus on the frequency range of 12.6-80 Hz, which exhibited the best resolution for maximizing the T/B ratio (right panel).
  • FIG. IB shows real-time monitoring of target binding (OPV at 10 4 copies/mL) in BR buffer to monomeric aptamer-modified electrodes without washing in an exemplary embodiment of the disclosure.
  • FIG. 1C shows real-time monitoring of target (OPV at 10 4 copies/mL) binding in BR buffer solution by monomeric aptamers, followed by target/ aptamer complex binding to streptavidin-modified electrode surfaces in an exemplary embodiment of the disclosure.
  • FIG. ID shows real-time of target (OPV at 10 4 copies/mL) binding in BR buffer solution by trimeric aptamers, followed by target/aptamer complex binding to streptavidin- modified electrode surfaces in an exemplary embodiment of the disclosure.
  • FIG. 2A shows the limit-of-detection of the RT-MAP Assay for detecting OPV spiked in buffer and saliva in an exemplary embodiment of the disclosure.
  • FIG. 2A shows realtime signals obtained for 0-10 5 copies/mL of OPV spiked in BBR buffer.
  • the insets demonstrate a schematic depicting the proposed binding mechanism and T/B refers to target- to-blank ratio.
  • FIG. 2B provides the plot of the peak impedance obtained for each OPV concentration from the corresponding real-time data (FIG. 2A), inferring a limit of detection of 138 copies/mL in buffer in an exemplary embodiment of the disclosure.
  • FIG. 2C shows the limit-of-detection of the RT-MAP Assay for detecting OPV spiked in buffer and saliva.
  • FIG. 2C shows real-time signals obtained for 0-10 5 copies/mL of OPV spiked in BBR Buffer mixed with 25% heat-treated saliva in an exemplary embodiment of the disclosure.
  • the insets demonstrate a schematic depicting the proposed binding mechanism and T/B refers to target-to-blank ratio.
  • FIG. 2D provides a plot of the peak impedance obtained for each OPV concentration from the corresponding real-time data (FIG. 2C), inferring a limit of detection of 584 copies/mL in 25% heat treated saliva in an exemplary embodiment of the disclosure.
  • FIG. 3A shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3A provides a schematic showing the steps followed by the user for clinical diagnosis.
  • FIG. 3B shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3B shows signals obtained at 2 min of real-time clinical testing for 18 known Negatives and 16 single Blind saliva samples.
  • FIG. 3C shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3C shows signals obtained at 10 min of real-time clinical testing for 18 known Negatives and 16 single Blind saliva samples.
  • FIG. 3D shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3D shows signals obtained at 18 min of real-time clinical testing for 18 known Negatives and 16 single Blind saliva samples.
  • FIG. 3E shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3E shows signals obtained at 26 min of real-time clinical testing for 18 known Negatives and 16 single Blind saliva samples.
  • FIG. 3F shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3F provides a box plot showing COVID-19 distribution for positive (infected) and negative (healthy) patient saliva samples corresponding to 2 min.
  • FIG. 3G shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3G provides a box plot showing COVID- 19 distribution for positive (infected) and negative (healthy) patient saliva samples corresponding to 10 min.
  • FIG. 3H shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3H provides a box plot showing COVID- 19 distribution for positive (infected) and negative (healthy) patient saliva samples corresponding to 18 min.
  • FIG. 31 shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 31 provides a box plot showing CO VID- 19 distribution for positive (infected) and negative (healthy) patient saliva samples corresponding to 26 min.
  • FIG. 3J shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3J provides an Operating Characteristic (ROC) curve obtained for 2 min.
  • ROC Operating Characteristic
  • FIG. 3K shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3K provides a Receiver Operating Characteristic (ROC) curve obtained for 10 min.
  • ROC Receiver Operating Characteristic
  • FIG. 3L shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3M shows assay validation for analyzing clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 3M provides a Receiver Operating Characteristic (ROC) curve obtained for 26 min.
  • FIG. 4A shows the limit of detection of the RT-MAP Assay for detecting Influenza A spiked in 25% heat treated saliva + BBR Buffer in an exemplary embodiment of the disclosure
  • FIG. 4A shows real-time signals obtained for 0-10 6 copies/mL of Influenza A.
  • FIG. 4B shows the limit of detection of the RT-MAP Assay for detecting Influenza A spiked in 25% heat treated saliva + BBR Buffer in an exemplary embodiment of the disclosure.
  • FIG. 4B shows the plot of the peak impedance obtained for each Influenza A concentration from the corresponding real-time data inferring a limit of detection of 408 copies/mL Influenza in 25% heat treated saliva and 0.96 pM VEGFiss in buffer.
  • FIG. 4C shows the limit-of-detection of the RT-MAP Assay for detecting VEGFiss spiked in BBR buffer in an exemplary embodiment of the disclosure.
  • FIG. 4C shows real-time signals obtained for 0-2500 pM of VEGFiss.
  • T/B refers to target-to-blank ratio.
  • FIG. 4D shows the limit-of-detection of the RT-MAP Assay for detecting VEGFiss spiked in BBR buffer in an exemplary embodiment of the disclosure.
  • FIG. 4D shows a plot of the peak impedance obtained for each VEGFiss concentration from the corresponding real-time data inferring a limit of detection of 408 copies/mL Influenza in 25% heat treated saliva and 0.96 pM VEGFiss in buffer.
  • FIG. 5A shows selecting the frequency for continuous monitoring in an exemplary embodiment of the disclosure.
  • FIG. 5A shows AZ/Z signals obtained for target and blank using solution binding strategy recorded at single frequency of 12.6 Hz showing a T/B of 2.1 for monomeric aptamer and 3.5 for trimeric aptamer.
  • FIG. 5B shows selecting the frequency for continuous monitoring in an exemplary embodiment of the disclosure.
  • FIG. 5B shows AZ/Z signals obtained for target and blank using solution binding strategy recorded at single frequency of 65 Hz showing a T/B of 2.2 for monomeric aptamer and 2.9 for trimeric aptamer.
  • FIG. 5C shows selecting the frequency for continuous monitoring in an exemplary embodiment of the disclosure.
  • FIG. 5C shows AZ/Z signals obtained for target and blank using solution binding strategy recorded at single frequency of 80 Hz showing a T/B of 2.1 for monomeric aptamer and 3.5 for trimeric aptamer.
  • FIG. 6A shows blocking buffer using concentration of trimeric aptamer at 0.5 pM and frequency of 12.6 Hz in an exemplary embodiment of the disclosure.
  • FIG. 6B shows blocking buffer using concentration of trimeric aptamer at 0.5 pM and frequency of 12.6 Hz in an exemplary embodiment of the disclosure.
  • FIG. 6B shows the concentration of BSA using the concentration of biotin-BSA at 0.01 pM.
  • a combination of 0.1% BSA and 0.01 pM biotin-BSA resulted in a T/B ratio of 5.
  • FIG. 6C shows blocking buffer using concentration of trimeric aptamer at 0.5 pM and frequency of 12.6 Hz in an exemplary embodiment of the disclosure.
  • FIG. 6C shows signals obtained using a one-pot system, where the concentrations of BSA (0.1%), biotin-BSA (0.01 pM), and trimeric aptamer (0.5 pM) were sequentially added. This setup allowed for accurate measurement of the signal specifically attributed to target binding.
  • FIG. 7A shows dilution and pre-treatment of saliva in an exemplary embodiment of the disclosure.
  • FIG. 7A provides a schematic illustrating the percentage dilution and treatment applied to saliva in each experimental setup.
  • FIG. 7B shows dilution and pre-treatment of saliva in an exemplary embodiment of the disclosure.
  • FIG. 7B shows target (T) and blank (B) signals recorded for 10%, 25% and 50% diluted saliva samples without heat treatment (top) compared with diluted saliva samples with heat treatment at 60 °C for 10 minutes (bottom).
  • FIG. 8A shows pre-incubation time for clinical diagnosis in an exemplary embodiment of the disclosure.
  • FIG. 8A provides a schematic illustrating an experimental protocol and treatment applied to saliva.
  • FIG. 8B shows pre-incubation time for clinical diagnosis in an exemplary embodiment of the disclosure.
  • FIG. 8B shows change in AZ/Z signals recorded for 0 min, 5 min, 10 min pre-incubation using one individual COVID positive patient saliva sample.
  • FIG. 9A shows data processing pipeline for binary classification of clinical dataset in an exemplary embodiment of the disclosure.
  • FIG. 9B shows curve fitting with validated model for impedance kinetics data from select clinical samples in an exemplary embodiment of the disclosure.
  • FIG. 9C shows weights for first and second principal components (PCI and PC2) generated from dimensionality reduction of curve fitting features in an exemplary embodiment of the disclosure.
  • FIG. 9D shows binary classification of clinical samples through support vector machine analysis.
  • the clinical samples are visualized as a scatterplot with their first two principal components, overlaid with the decision map from support vector machine analysis.
  • the decision map shows the boundaries between positive and negative samples.
  • the inset table shows the confusion matrix of the support vector machine model on the test set of clinical samples.
  • FIG. 10A shows AZ/Z signals obtained for 19 COVID-negative saliva samples at 2 min to 30 min time points for establishing diagnostic threshold in an exemplary embodiment of the disclosure.
  • the dotted line for each denotes the diagnostic threshold at each time point.
  • FIG. 10B shows AZ/Z signals obtained for 19 COVID-negative saliva samples at 12 min to 20 min time points for establishing diagnostic threshold in an exemplary embodiment of the disclosure.
  • the dotted line for each denotes the diagnostic threshold at each time point.
  • FIG. 10C shows AZ/Z signals obtained for 19 COVID-negative saliva samples at 22 min to 30 min time points for establishing diagnostic threshold in an exemplary embodiment of the disclosure.
  • the dotted line for each denotes the diagnostic threshold at each time point.
  • FIG. 11A shows AZ/Z signals obtained for 19 single-blinded saliva samples at 2 min to 10 min time points in an exemplary embodiment of the disclosure.
  • the dotted line for each denotes the pre-established diagnostic threshold at each time point.
  • FIG. 11B shows AZ/Z signals obtained for 19 single-blinded saliva samples at 12 min to 20 min time points in an exemplary embodiment of the disclosure.
  • the dotted line for each denotes the pre-established diagnostic threshold at each time point.
  • FIG. 11C shows AZ/Z signals obtained for 19 single-blinded saliva samples at 22 min to 30 min time points in an exemplary embodiment of the disclosure.
  • the dotted line for each denotes the pre-established diagnostic threshold at each time point.
  • FIG. 12A shows receiver operating characteristic (ROC) curve obtained for 19 single-blinded saliva samples at 2 min to 10 min time points showing the sensitivity and specificity improvement with time in an exemplary embodiment of the disclosure.
  • ROC receiver operating characteristic
  • FIG. 12B shows receiver operating characteristic (ROC) curve obtained for 19 single-blinded saliva samples at 12 min to 20 min time points showing the sensitivity and specificity improvement with time in an exemplary embodiment of the disclosure.
  • ROC receiver operating characteristic
  • FIG. 12C shows receiver operating characteristic (ROC) curve obtained for 19 single-blinded saliva samples at 22 min to 30 min time points showing the sensitivity and specificity improvement with time in an exemplary embodiment of the disclosure.
  • ROC receiver operating characteristic
  • FIG. 13A shows the assessment of the binding affinity of monomeric (RHA06) and trimeric (TRHA06) for influenza HA proteins using dot blot assay in an exemplary embodiment of the disclosure.
  • FIG. 13A shows representative dot blot results.
  • FIG. 13B shows the assessment of the binding affinity of monomeric (RHA06) and trimeric (TRHA06) for influenza HA proteins using dot blot assay in an exemplary embodiment of the disclosure.
  • FIG. 13B shows binding curves used to derive the id values and affinity enhancement folds.
  • TRHA06 with control protein (BSA) and mutant trimeric aptamer with H3N2 were also included as controls.
  • BA bound aptamer
  • UA unbound aptamer.
  • FIG. 14A shows a cooperativity assessment of binding trimeric H3N2-HA protein by the three arms of trimeric aptamer (TRHA06) aptamer by adding antisense sequence (AS) of RHA06 (SEQ ID NO: 1) in an exemplary embodiment of the disclosure.
  • FIG. 14B shows binding curves in an exemplary embodiment of the disclosure.
  • FIG. 14B shows KA increases indicating reduced affinity.
  • the three arms of TRHA06 were determined bound with the trimeric HA protein.
  • FIG. 15 shows the concentration of Influenza A trimeric aptamer (TRHA06) in an exemplary embodiment of the disclosure.
  • FIG. 15 shows four Hl A concentrations tested: 250 nM, 500 nM and 1 pM.
  • Target-to-blank ratio (T/B) ratio obtained for 10 4 copies/mL H3N2 subtype of Influenza A shows that 500 nM of TRHA06 is the selected concentration.
  • FIG. 16A shows an assessment of the binding affinity of monomeric (Hl A) and trimeric (THIA) aptamers for VEGFies using dot blot assay in an exemplary embodiment of the disclosure.
  • FIG. 16A provides a dot blot of the results.
  • FIG. 16B shows an assessment of the binding affinity of monomeric (Hl A) and trimeric (THIA) aptamers for VEGFiss using dot blot assay in an exemplary embodiment of the disclosure.
  • FIG. 16B shows binding curves used to derive the id values. Affinity enhanced ⁇ 78-fold.
  • FIG. 17A shows a cooperativity assessment of binding VEGFiss by three arms of trimeric (THIA) aptamer using antisense sequence (AS) of H1A (SEQ ID NO: 4) in an exemplary embodiment of the disclosure.
  • FIG. 17B shows binding curves in an exemplary embodiment of the disclosure.
  • FIG. 17B shows KA increased indicating reduced affinity.
  • the three arms of THIA were determined bound with VEGF protein, though VEGF was determined a dimeric protein.
  • FIG. 18A shows the concentration of VEGFiss trimeric aptamer (THIA) at 25 nM in an exemplary embodiment of the disclosure.
  • THIA concentrations were tested 25 nM, 100 nM, 250 nM and 500 nM.
  • Target-to-blank ratio (T/B) ratio obtained for two concentrations (2.5 pM and 250 pM) of VEGFiss shows that 250 nM of Hl A is the selected concentration.
  • FIG. 18B shows the concentration of VEGFiss trimeric aptamer (THIA) at lOOnM in an exemplary embodiment of the disclosure.
  • THIA concentrations were tested 25 nM, 100 nM, 250 nM and 500 nM.
  • Target-to-blank ratio (T/B) ratio obtained for two concentrations (2.5 pM and 250 pM) of VEGFiss shows that 250 nM of Hl A is the selected concentration.
  • FIG. 18C shows the concentration of VEGFiss trimeric aptamer (THIA) at 250 nM in an exemplary embodiment of the disclosure.
  • THIA concentrations that were tested: 25 nM, 100 nM, 250 nM and (500 nM.
  • Target-to-blank ratio (T/B) ratio obtained for two concentrations (2.5 pM and 250 pM) of VEGFiss shows that 250 nM of Hl A is the selected concentration.
  • FIG. 18D shows the concentration of VEGFiss trimeric aptamer (THIA) at 500nM in an exemplary embodiment of the disclosure.
  • THIA concentrations were tested: 25 nM, 100 nM, 250 nM and 500 nM.
  • Target-to-blank ratio (T/B) ratio obtained for two concentrations (2.5 pM and 250 pM) of VEGFiss shows that 250 nM of Hl A is the selected concentration.
  • FIG. 19A shows the evaluating of analytical specificity in buffer and saliva samples in an exemplary embodiment of the disclosure.
  • FIG. 19A shows signals obtained for 10 4 copies/mL of OPV and non-binding respiratory viruses spiked in BBR buffer.
  • FIG. 19B shows the evaluating of analytical specificity in buffer and saliva samples in an exemplary embodiment of the disclosure.
  • FIG. 19B shows signals obtained for COVID assay in presence of specific (10 4 copies/mL OPV) target, non-binding target (10 4 copies/mL Influenza A) and a mixture of specific and non-binding target (10 4 copies/mL each of OPV + Influenza A) and Influenza assay in presence of specific (10 4 copies/mL Influenza A) target, non-binding target (10 4 copies/mL OPV) and a mixture of specific and non-binding target (10 4 copies/mL each of Influenza A + OPV) in BBR buffer.
  • the insets show simple schematics to explain the experimental protocol.
  • sample or "test sample” as used herein refers to any material in which the presence or amount of a target analyte is unknown and can be determined in an assay.
  • the sample can be from any source, for example, any biological (e.g. human or animal samples, including clinical samples), environmental (e.g. water, soil or air) or natural (e.g. plants) source, or from any manufactured or synthetic source (e.g. food or drinks).
  • the sample can be comprised or is suspected of comprising one or more analytes.
  • the sample can be a "biological sample” comprising cellular and non-cellular material, including, but not limited to, tissue samples, urine, blood, serum, other bodily fluids and/or secretions.
  • the sample can be in its undiluted form or diluted in an appropriate diluent, for example, a buffer or an aqueous solution known in the art.
  • the sample comprises blood, plasma, urine, saliva, sputum, oropharyngeal and/or nasopharyngeal secretions.
  • target refers to any agent, including, but not limited to, a small inorganic molecule, small organic molecule, metal ion, biomolecule, toxin, biopolymer (such as a nucleic acid, carbohydrate, lipid, peptide, protein), cell, tissue, microorganism and vims, for which one would like to sense or detect.
  • the analyte can be either isolated from a natural source or is synthetic.
  • the analyte can be a single compound or a class of compounds, such as a class of compounds that share structural or functional features.
  • the term analyte also includes combinations (e.g. mixtures) of compounds or agents such as, but not limited, to combinatorial libraries and samples from an organism or a natural environment.
  • nucleic acid refers to a polynucleotide or oligonucleotide, such as deoxyribonucleic acid (DNA), ribonucleic acid (RNA), modified nucleotides and/or nucleotide derivatives, and can be either double-stranded (ds) or singlestranded (ss).
  • strand as used herein is understood to refer to nucleic acid unless otherwise stated.
  • modified nucleotides can contain one or more modified bases (e.g. tritiated bases and unusual bases such as inosine), modified backbones (e.g. peptide nucleic acid, PNA) and/or other chemically, enzymatically, or metabolically modified forms.
  • coronavirus 2 refers to a coronavirus first identified in Wuhan, China in 2019 that causes coronavirus disease (COVID-19).
  • the virus previously had a provisional name, 2019 novel coronavirus (2019-nCoV), and has also been called the human coronavirus 2019 (HCoV-19 or hCoV-19).
  • the term includes any variant of the SARS-CoV-2 virus with a variant and/or mutated nucleic acid sequence from the original version identified in Wuhan. Variants includes, but are not limited to, Alpha (B. 1.1.7), Beta (B.1.351), Gamma (P. l), Delta (B. 1617.2), and Omicron (B. l. 1.529).
  • spike protein refers to a glycoprotein found on the surface of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the virus responsible for COVID- 19.
  • SARS-CoV-2 severe acute respiratory syndrome coronavirus 2
  • the spike protein plays a role in the virus's ability to bind to and enter host cells.
  • the S protein of SARS-CoV-2 consists of two functional subunits: SI and S2.
  • the SI subunit contains the receptor-binding domain (RBD) that recognizes and binds to the human angiotensin-converting enzyme 2 (ACE2) receptor. This binding facilitates the virus's attachment to the surface of host cells, primarily in the respiratory tract.
  • ACE2 subunit mediates fusion between the viral and host cell membranes, allowing the viral genome to enter the host cell and initiate infection.
  • the spike protein is a useful marker for detecting the presence of SARS-CoV-2.
  • influenza refers to a group of viruses that cause acute respiratory illness in humans and various other animals. Influenza viruses are classified into four types: A, B, C, and D. Type A and B viruses cause seasonal epidemics in humans, while type C causes mild respiratory illness, and type D primarily affects cattle. Influenza A viruses are further divided into subtypes based on the hemagglutinin (H) and neuraminidase (N) proteins on their surface, such as H1N1 and H3N2. These subtypes can further evolve into various strains, including those responsible for pandemics like the H1N1 pandemic in 2009. The term includes any variant of the influenza virus with a variant and/or mutated nucleic acid sequence from the original version identified. This includes, but is not limited to, various seasonal strains that may emerge and circulate each year.
  • H hemagglutinin
  • N neuraminidase
  • hemagglutinin refers to a glycoprotein found on the surface of the influenza virus. It plays a role in the virus's ability to infect a host. HA is responsible for binding the virus to cells with sialic acid on the membranes, such as cells in the human respiratory tract. This binding allows the virus to be internalized by the host cell, initiating infection.
  • HA subtypes There are 18 different HA subtypes in influenza A viruses, labeled Hl through Hl 8. These subtypes can combine with various neuraminidase (NA) subtypes to create different strains of the virus. The HA subtype contributes to the naming of the strain, such as H1N1 or H3N2. HA is a useful marker for detecting the presence of influenza virus.
  • vascular endothelial growth factor or "VEGF” or “VEGF-A” refers to a signal protein produced by cells that stimulates the formation of blood vessels, the protein. VEGF is part of the system that restores the oxygen supply to tissues when blood circulation is inadequate. It is a key driver of angiogenesis, which is the formation of new blood vessels from pre-existing vessels. VEGF-A has several isoforms (in human: VEGF121, VEGF 121b, VEGF145, VEGFiss, VEGFissb, VEGF189, and VEGF206), and its dysregulation has been associated with various pathological conditions, including cancer, where it may contribute to the growth of tumors by providing them with increased blood supply.
  • VEGF vascular endothelial growth factor
  • EIS electrochemical impedance spectroscopy
  • EIS electrochemical impedance spectroscopy
  • a small sinusoidal voltage or current is applied to the system, and the resultant current or voltage is measured.
  • impedance data can be represented as a Bode plot or a Nyquist plot, which gives insights into the mechanistic details of the electrochemical process.
  • EIS module refers to a tool or component designed to facilitate or conduct EIS measurements within an electrochemical system or a broader analytical device, such as a biosensor system.
  • the EIS module is a hardware or software component designed to carry out EIS measurements.
  • the EIS module can include a working electrode, a reference, a counter electrode, and a circuit compatible with potentiostat.
  • the EIS module can further incorporate a software component that can include algorithms and routines to control the hardware, collect and analyze the data, and visualize the results.
  • the software is also capable of fitting the measured impedance data to equivalent circuit models to extract meaningful parameters related to the electrochemical system.
  • the software can directly provide parameters which are relevant to accurate electrochemical interpretation.
  • the term “comprising” and its derivatives, as used herein, are intended to be open ended terms that specify the presence of the stated features, elements, components, groups, integers, and/or steps, but do not exclude the presence of other unstated features, elements, components, groups, integers and/or steps.
  • the foregoing also applies to words having similar meanings such as the terms, “including”, “having” and their derivatives.
  • the term “consisting” and its derivatives, as used herein, are intended to be closed terms that specify the presence of the stated features, elements, components, groups, integers, and/or steps, but exclude the presence of other unstated features, elements, components, groups, integers and/or steps.
  • the second component as used herein is chemically different from the other components or first component.
  • a “third” component is different from the other, first, and second components, and further enumerated or “additional” components are similarly different.
  • the present disclosure is directed to the generation of a universal biosensor system designed to detect the presence of a target by monitoring the binding of the target to an electrode surface in real time.
  • the biosensor system enables the real-time measurement of these interactions, employing multimeric aptamers for solution-based capture, and forming target-aptamer complexes.
  • the biosensor system incorporates high affinity coupling chemistry, such as biotinstreptavidin chemistry, to attach the target-aptamer complexes to the electrode surface, allowing for continuous real-time monitoring.
  • the biosensor system incorporates machine learning approach for enhanced performance.
  • the biosensor system is versatile, suitable for a wide array of target analytes, and offers several advantages over state-of-the-art electrochemical assays.
  • the real-time analysis feature of the biosensor system allows for continuous measurement throughout the sample incubation period with an unlabeled target using electrochemical impedance. This not only captures changes induced by the target but also reveals information on binding kinetics, supporting the creation of more reliable and robust biosensor systems.
  • the use of multimeric aptamers, as opposed to their monomeric counterparts provides enhanced binding affinity in the biosensor system. This allows for the formation of target/aptamer aggregates, resulting in a more efficient and effective binding process.
  • simplified manufacturing is another key advantage of the biosensor system, as the production process is streamlined. The diagnostic chips only require, for instance, streptavidin modification and do not depend on additional capture probe modification on the chip, thereby reducing complexity and lowering costs.
  • a biosensor for detecting a target analyte in a sample comprising: a) an electrochemical impedance spectroscopy (EIS) module comprising (i) a working electrode, operable at a single frequency for real-time monitoring of aptamer binding to target, aptamer-target dissociation, or aptamer or target degradation on the working electrode, (ii) a counter electrode, (iii) a reference electrode, and (iv) a circuit compatible with potentiostat; b) a multimeric aptamer comprising two or more units for specific target binding and formation of an aptamer-target complex in solution, wherein the target comprises two or more binding sites, wherein the multimeric aptamer has a K ⁇ about 300 pM; wherein the multimeric aptamer is configured to bind to the surface of the working electrode, and wherein the biosensor system is configured to operate in a wash-free and singlepot format.
  • EIS electrochemical impedance spectroscopy
  • the multimeric aptamer is biotinylated and the surface of the working electrode is coated with streptavidin. In some embodiments, the multimeric aptamer is aminated and the surface of the working electrode is coated with NHS-ester or an epoxy group. In some embodiments, the multimeric aptamer is thiolated and the surface of the working electrode is coated with a metal, a thiol, or a disulphide. In some embodiments, the multimeric aptamer is alkynylated and the surface of the working electrode is coated with an azide. In some embodiments, the multimeric aptamer is azido-modified and the surface of the working electrode is coated with an alkyne.
  • the working electrode is a gold working electrode.
  • the counter electrode is a gold counter electrode.
  • the reference electrode is a silver reference electrode.
  • the target is a viral target and KA ⁇ about 100 pM. In some embodiments, the target is a viral target and KA ⁇ about 25 pM. In some embodiments, the target is SARS-CoV-2 and KA ⁇ about 23 pM. In some embodiments, the target is SARS-CoV-2 and KA ⁇ about 8 pM. In some embodiments, the target is SARS-CoV-2 and Kd ⁇ about 0.13 pM. In some embodiments, the target is influenza and VEGF and K ⁇ about 300 pM.
  • the target is influenza and VEGF and Kd ⁇ about 270 pM. In some embodiments, the target is influenza and VEGF and Kd ⁇ about 90 pM. In some embodiments, the target is influenza and Kd ⁇ about 100 pM. In some embodiments, the target is VEGF and id ⁇ about 300 pM. In some embodiments, the target is VEGF and Kd ⁇ about 270 pM. In some embodiments, the target is VEGF and Kd ⁇ about 90 pM.
  • the biosensor system described herein uses a solution comprising a readout buffer, a binding buffer, and a blocking buffer, which can be premixed or mixed prior to use.
  • the solution comprises a readout buffer comprising phosphate buffer saline, KC1, and redox reporter.
  • the redox reporter can be redox pair can be potassium ferricyanide and potassium ferrocyanide (K3[Fe(CN)6]/K4[Fe(CN)e]), ferricyanide ion and ferrocyanide ion ([Fe(CN)6] 3 7[Fe(CN)6] 4 '), quinone and hydroquinone (Q/H2Q), hexaammineruthenium(III) ion and hexaammineruthenium(II) ion ([Ru(NH3)6] 3+ /[Ru(NH3)e] 2+ ), oxidized methylene blue and reduced methylene blue (MB /MBH2).
  • the redox reporter comprises K3[Fe(CN) 6 ]/K4[Fe(CN) 6 ], [Fe(CN) 6 ] 3 7[Fe(CN) 6 ] 4 -, Q/H 2 Q, [Ru(NH3)6] 3+ /[Ru(NH 3 )6] 2+ , MB /MBH2. or MV 2+ /MV + redox reporter.
  • the solution comprises redox reporter at about 2 mM K3[Fe(CN)e] and about 2 mM K4[Fe(CN)e].
  • the solution comprises a blocking buffer comprising biotin-BSA and BSA. In some embodiments, the solution comprises about 0.01 pM biotin- BSA and about 0.1% BSA. In some embodiments, the solution comprises a binding buffer comprising HEPES, NaCl, KC1, MgCh, and CaCh. In some embodiments, the solution comprises about 5 mM HEPES, pH about 7.4, about 15 mM NaCl, about 0.6 mM KC1, about 0.25 mM MgCh, and about 0.25 mM CaCh.
  • the biosensor system described herein can be used for detecting a target in different types of samples.
  • the sample is a clinical sample.
  • the sample comprises blood, plasma, urine, saliva, sputum, oropharyngeal and/or nasopharyngeal secretions.
  • the sample comprises saliva.
  • the sample is saliva.
  • the sample is a heat-treated sample.
  • the saliva is heat-treated saliva.
  • the biosensor system described herein can be used for detecting different types of targets.
  • the target is a small inorganic molecule, a small organic molecule, a metal ion, a biomolecule, a toxin, a biopolymer, a cell, a tissue, a microorganism, or a virus.
  • the target is a component from a cell, a tissue, a microorganism, or a virus.
  • the biopolymer is a nucleic acid, a carbohydrate, a lipid, peptide, or a protein.
  • the target is a protein target, a viral target, or a bacterial target.
  • the target is a protein target. In some embodiments, the target is a viral target. In some embodiments, the target is a bacterial target. In some embodiments, the viral target is SARS-CoV-2, influenza, or HIV. In some embodiments, the viral target is SARS-CoV-2. In some embodiments, the SARS-CoV-2 is SARS-CoV-2 B.1.1.529 omicron variant. In some embodiments, the protein target is SARS- CoV-2 B.1.1.529 omicron variant spike protein.
  • the aptamer is a SARS- CoV-2 specific aptamer and it does not cross-react with human coronavirus 229E, human coronavirus OC43, influenza A, adenovirus, or other respiratory viruses.
  • the aptamer is a SARS-CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 6, 7, or 11.
  • the aptamer is a SARS-CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 6.
  • the aptamer is a SARS-CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 7.
  • the aptamer is a SARS-CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 11. In some embodiments, the aptamer is a monomeric SARS-CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 6. In some embodiments, the aptamer is a trimeric SARS-CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 6. In some embodiments, the aptamer is a trimeric SARS-CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 7.
  • the aptamer is a monomeric SARS-CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 11. In some embodiments, the aptamer is a trimeric SARS-CoV-2 specific aptamer having the nucleic acid sequence of SEQ ID NO: 11. In some embodiments, the biosensor system is configured to detect SARS-CoV-2 B.1.1.529 omicron variant with a limit-of-detection of about 138 copies/mL in the solution comprising the redox buffer, the blocking buffer, and the binding buffer.
  • the biosensor system is configured to detect SARS-CoV-2 with a limit-of-detection of about 584 copies/mL in heat-treated saliva diluted to about 25% (v/v) in the solution comprising the redox buffer, the blocking buffer, and the binding buffer.
  • the viral target is influenza.
  • the target is influenza hemagglutinin (HA).
  • the target is H3N2.
  • the aptamer is an influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 1, 2, or 9.
  • the aptamer is an influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 1.
  • the aptamer is an influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 2. In some embodiments, the aptamer is an influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 9. In some embodiments, the aptamer is a monomeric influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 1. In some embodiments, the aptamer is a trimeric influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 1. In some embodiments, the aptamer is a trimeric influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 2.
  • the aptamer is a monomeric influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 9. In some embodiments, the aptamer is a trimeric influenza specific aptamer having the nucleic acid sequence of SEQ ID NO: 9. In some embodiments, the biosensor system is configured to detect H3N2 with a limit-of-detection of about 408 copies/mL in heat-treated saliva diluted to about 25% (v/v) in the solution comprising the redox buffer, the blocking buffer, and the binding buffer.
  • the viral target is HIV.
  • the protein target is vascular endothelial growth factor (VEGF). In some embodiments, the VEGF is isoform VEGFies.
  • the aptamer is a VEGF specific aptamer having the nucleic acid sequence of SEQ ID NO: 4 or 5. In some embodiments, the aptamer is a VEGF specific aptamer having the nucleic acid sequence of SEQ ID NO: 4. In some embodiments, the aptamer is a VEGF specific aptamer having the nucleic acid sequence of SEQ ID NO: 5. In some embodiments, the aptamer is a VEGF specific aptamer having the nucleic acid sequence of SEQ ID NO: 10. In some embodiments, the aptamer is a monomeric VEGF specific aptamer having the nucleic acid sequence of SEQ ID NO: 4.
  • the trebler is 3,3'-((2-(oxidomethyl)-2-((3- oxidopropoxy)methyl)propane-l,3-diyl)bis(oxy))bis(propan-l-olate). In some embodiments, the trebler is Formula (I):
  • the biosensor system is configured to detect VEGFies with a limit-of-detection of about 0.96 pM VEGFiss in the solution comprising the redox buffer, the blocking buffer, and the binding buffer.
  • the biosensor system provides at least 80% sensitivity and at least 99% specificity.
  • the biosensor system provides at least 93% sensitivity.
  • the biosensor system provides at least 98% sensitivity.
  • the biosensor system provides 100% specificity.
  • the single frequency is between about 1 and about 20 kHz. In some embodiments, the single frequency is between about 12.6 and about 80 Hz. In some embodiments, the single frequency is about 10, 10.1, 10.2, 10.3, 10.4, 10.5, 10.6, 10.7,
  • the single frequency is about 12.6 Hz.
  • the total impedance is measured at intervals of every 2 minutes. In some embodiments, the total impedance is measured continuously.
  • kits for detecting a label-free target in a sample comprising the biosensor system described herein, further comprising at least one of a dropper, a collection tube, a container holding the redox readout buffer, a container holding the binding buffer, a container holding the block buffer, and instruction for use.
  • DNA oligonucleotides for aptamer synthesis were obtained from Integrated DNA Technologies (IDT). Before use, the oligonucleotides were purified using standard 10% denaturing polyacrylamide gel electrophoresis (dPAGE) with 8 M urea.
  • the trebler phosphoramidite Tris-2, 2, 2-[3-(4,4'-dimethoxytrityloxy)propyloxymethyl]ethyl-[(2- cyanoethyl)-(N,Ndiisopropyl)]-phosphoramidite, Cat. No. 10-1922-90
  • Synthetic DNA oligonucleotides used in this research are provided in the Table 1.
  • the B.1.1.529 omicron variant of the SARS-CoV-2 spike pseudotyped lentivirus (OMPV) was sourced from BPS Bioscience (catalog number: 78349-1).
  • OMPV SARS-CoV-2 spike pseudotyped lentivirus
  • nitrocellulose blotting membranes catalog No. 10600125
  • nylon hybridization transfer membranes NEF994001PK
  • Thermo Scientific (Ottawa, ON, Canada) provided T4 DNA ligase, T4 polynucleotide kinase (PNK), adenosine triphosphate (ATP), and deoxyribonucleoside 5 ’-triphosphates (dNTPs) for biotinylation of the aptamers.
  • PNK T4 polynucleotide kinase
  • ATP adenosine triphosphate
  • dNTPs deoxyribonucleoside 5 ’-triphosphates
  • All other chemicals and reagents including 4-(2-hydroxyethyl)-l- piperazineethanesulfonic acid (HEPES), sodium chloride, magnesium chloride, Tween-20, Bovine serum albumin, Biotinylated Bovine Serum albumin, K3[Fe(CN)e], and K4[Fe(CN)e], were purchased from Sigma-Aldrich (Oakville, Canada) and used without further purification. All electrochemical tests were conducted using screen printed gold electrodes with silver reference and gold auxiliary electrodes purchased from Palmsens. Autoclaved DI water was used for all experiments.
  • the SARS-Related Coronavirus 2 Pseudotyped Lentiviral Kit (BEI catalog number NR-52948) was obtained from BEI resources, National Institute of Allergy and Infectious Diseases, National Institutes of Health.
  • Table 1 Synthetic DNA oligonucleotides (aptamers) used in this work. All sequences are written in a 5' to 3' direction. Italics in SEQ ID NO: 2, 3, 5, 7, and 8 are linkers.
  • VEGF165 28 GCCCGTCTTCCAGACAAGAGTGCAGGGC 5 THIA VEGF165 125 GCCCGTCTTCCAGACAAGAGTGCAGGGC TTT
  • TMSA52 SARS-Cov-2 282 TTACGTCAAG GTGTCACTCC spike protein GTAGGGTTTG GCTCCGGGCC
  • the e-CoV sensor chip used screen printed electrodes with gold working and counter electrodes, as well as silver reference electrodes, obtained from Palmsens. 39 To prepare the chip, it was initially cleaned by washing it with isopropanol (IP A) and DI water. The working electrode was then electroactivated through 15 cyclic voltammetry scans in 0.5 M H2SO4. 40 The scans ranged from 0 V to 1.5 V, with a scan rate of 10 mV/s. Afterward, the chip was washed with water.
  • DSP reduction 50 pl of DSP-DMSO was added to 450 pl of tris(2- carboxyethyl)phosphine (TCEP) dissolved in DMSO and thoroughly mixed. The mixture was then incubated for at least 1 hour. Then, 3.5 pl of TCEP -reduced DSP was deposited onto the working electrode and incubated for 2 hours. The chip was subsequently washed with DMSO and then with water. Then, 5 pl of streptavidin, diluted to a concentration of 0.5 pM in IX PBS, was deposited onto the working electrode and left to incubate overnight (at least 6 hours) at 4°C. Finally, the chips were washed and stored in IX PBS. In this way, streptavidin modified electrodes were prepared and then treated using three different strategies to determine the most effective approach for assay development.
  • TCEP tris(2- carboxyethyl)phosphine
  • the first strategy involved the sequential deposition of aptamer and target on the streptavidin modified electrodes.
  • 5 pl of a selected concentration of aptamer diluted in IX binding buffer 50 mM HEPES, pH 7.4, 150 mM NaCl, 6 mM KC1, 2.5 mM MgCh, 2.5 mM CaCh
  • IX binding buffer 50 mM HEPES, pH 7.4, 150 mM NaCl, 6 mM KC1, 2.5 mM MgCh, 2.5 mM CaCh
  • the electrodes were washed and incubated with 5 pl of the target solution diluted in IX binding buffer or a blank binding buffer solution for 10-minute.
  • the electrodes were washed again by dipping them in IX binding buffer and taken for reading charge transfer resistance change using multi-frequency EIS. This strategy was carried out only in a control buffer (IX binding buffer).
  • the second strategy involved depositing a monolayer of aptamer on the streptavidin modified electrodes and then monitoring the kinetics of target binding to the deposited aptamers in real-time. Similar to the first strategy, 5 pl of a selected concentration of aptamer diluted in IX binding buffer was incubated on the streptavidin modified electrodes for 30 minutes. Subsequently, 50 pl of the target solution diluted in BR Buffer which contains IX binding buffer and IX readout buffer was dropped onto the aptamer modified electrodes. Single frequency electrochemical impedance spectroscopy (EIS) was then performed continuously for 30 minutes at a selected frequency of 12.6 Hz to monitor the signal change as the target binds to the aptamer and dissociates. This strategy was also carried out only in the control buffer (IX binding buffer).
  • EIS electrochemical impedance spectroscopy
  • the third strategy which was selected as the best-performing strategy for the study, involved mixing the aptamer and target in a "one-pot" fashion with BBR Buffer which contains IX binding buffer, blocking buffer and IX redox readout solution.
  • a 50 pl mixture was prepared, consisting of 25 pl of 2X redox readout buffer (comprising 2X phosphate buffer saline, 100 mM KC1, 4 mM ferrocyanide, and 4 mM ferricyanide), 2.5 pl of a 10 pM aptamer, 5 pl of a 1 OX target (diluted in binding buffer, specifically when working with spike samples), 2.5 pl of blocking buffer (0.2 pM biotin-BSA + 2% BSA) prepared in IX binding buffer, 2.5 pl of IX binding buffer without tween, and 12.5 pl of saliva (only for spiked clinical saliva samples).
  • 2X redox readout buffer comprising 2X phosphate buffer saline, 100 mM KC1, 4 mM ferrocyanide
  • the entire mixture was drop-deposited onto the streptavidin-modified chips, and single frequency EIS was performed continuously for 30 minutes at a selected frequency of 12.6 Hz to monitor the signal change as the aptamer and target formed multilayered stacked aggregates and bound to the streptavidin modified electrodes.
  • EIS electrochemical impedance spectroscopy
  • the Rct fold change was calculated as:
  • FIG. 9A To enhance the efficiency of the biosensor, disclosed herein, for evaluating unknown samples and determining their positive/negative attributes, a machine learning algorithm was integrated (FIG. 9A). The algorithm generated a model which incorporates viral and aptamer association and dissociation, molecular degradation, non-specific adsorption and time lag to signal generation.
  • the algorithm generated a segmented model based on its analysis of various parameters derived from the recorded graph of impedance kinetics data.
  • the kinetics data revealed two distinct patterns: one characterized by a relatively steady or gradual increase in signal, and another marked by an initial signal increase followed by a rapid decline.
  • the resulting segmented model combined an associationdissociation binding kinetic model with an extra initial transient lag phase.
  • the lag phase consisted of two components: the first simulated a decay function (Weibull decay) that appeared to commence from the outset. This component could represent either adsorbed Bovine serum albumin (BSA) or the time-sensitive protein streptavidin, both subject to degradation over time. The second component of the lag was attributed to non-specific adsorption resulting from salivary proteins.
  • BSA Bovine serum albumin
  • streptavidin time-sensitive protein streptavidin
  • association component was formulated as follows:
  • Z ass oc denotes the signal (impedance fold change) corresponding to ligand association
  • Z max represents the maximum attainable signal
  • kA and ko are the association and dissociation constants
  • ko is the dissociation constant
  • t is the time
  • Cii gan d is the resultant ligand concentration (aptamer and virus for target and aptamer only for blank) in micromolar (pM).
  • the aptamer concentration was kept constant at 0.5 pM which is the concentration used for assay.
  • the viral concentration was considerable as a variable to the model.
  • Zi ag represents the signal during the initial lag phase
  • k a d s is the adsorption rate constant
  • r is the lag residence time
  • ZNS is the non-specific signal contribution.
  • the dissociation component was considered after the time point at which the maximum signal was obtained following which signal decreased.
  • the dissociation component was incorporated into the model to generate the resultant signal as: [00130] Where, Z re suit is the resultant signal considering all functions, t max is the time corresponding to maximum signal Z max .
  • the model was applied to the calibration data 905 to validate the model at 910.
  • the calibration data 905 was obtained from spiked saliva samples.
  • training data 915 was used for model fitting and training at 920.
  • training data 915 included a randomly selected subset of clinical samples.
  • Fig. 9B illustrates an example of curve fitting with the validated model for impedance kinetics data derived from select clinical samples used as training data.
  • the training data 915 contained values for various parameters such as, for example, kA, ko, k a d s , T, tmax, Z max , area under the recorded curve (AUC) and R-squared (goodness of fit), where kA and ko are the association and dissociation constants, k a d s is the adsorption rate constant, r is the lag residence time, Z max represents the maximum attainable signal and t max is the time corresponding to maximum signal Zm aX .
  • the PCA of the training data resulted in two new variables: a first principal component (PCI) and a second principal component (PC2), where PCI represents the direction in the data where there is the most variance and PC2 represents the second most variance.
  • the first and second principal components were created as linear combinations of the original variables with specific weights assigned to the original variables.
  • Fig. 9C illustrates an example of weights for the first and second principal components (PCI and PC2) generated from PCA or dimensionality reduction of curve fitting features.
  • Fig. 9D illustrates an example of binary classification of clinical samples through support vector machine analysis.
  • the two principal components, PCI and PC2 are plotted on x- and y- axis, respectively.
  • the clinical samples are visualized as a scatterplot with their first two principal components, overlaid with the decision map from support vector machine analysis.
  • the decision map shows the boundaries between the positive and negative samples.
  • a confusion matrix 935 of the support vector machine model on the test set of clinical samples.
  • the binary classification of the clinical samples shown in Fig. 9D resulted in a 100% accuracy.
  • the charge transfer from the redox solution to the electrode is impeded, causing an increase in charge transfer resistance (0.71 kQ for blank and 1.79 k for target) and a decrease in the double layer capacitance (236 nF for blanks and 182 nF for target), resulting in a corresponding increase in the magnitude of electrochemical impedance (0.82 kQ for blank and 2.432 kQ for target) with increasing time (FIG. IB).
  • the blank signal showed a similar trend with a lower increase in impedance.
  • Trimeric aptamers have a higher binding affinity to multimeric targets 10 compared to monomeric aptamers.
  • the trimeric aptamer, TMSA52 has a 2 orders of magnitude improvement in binding affinity compared to its monomeric counterpart toward the trimeric spike protein of SARS- CoV-2 Omicron variant.
  • multimeric aptamers possessing multiple binding regions can extract, concentrate, and aggregate targets in solution for more effective delivery of targets to the surface 12,18 and improved surface blocking and signal transduction.
  • Electrodes were modified with streptavidin and introduced biotinylated trimeric aptamers (or monomeric as control, FIG. 1C), viral targets (10 4 copies/mL of OPV and nothing in case of blank), binding buffer, and a readout buffer in a single pot and performed real-time measurements using single frequency impedance monitoring (FIG. ID).
  • the target-to-blank ratio calculated from the ratio of the peak target current, and the peak blank current is 2.1, which, as expected, is higher than the value (1.98) obtained using surface-based monomeric aptamers.
  • the real-time target and blank signals demonstrated a similar trend, with blank increasing till 14-16 minutes and target reaching peak values monotonically till 22 minutes, with a target-to-blank ratio of only 3.5. This clearly highlights the importance of using trimeric aptamers for the RT-MAP Assay.
  • the enhanced target-to-blank ratio observed with the trimeric aptamer is likely caused by the increased binding affinity of trimeric versus monomeric aptamers, increased number of negatively charged nucleotides bound to each viral target, and the steric hindrance produced by virus/aptamer cluster formation as opposed to monolayer surface binding of individual targets. 19,20 [00140] Following the demonstration that real-time monitoring of target binding was possible using a wash-free and single pot aptamer assay, the experimentation aimed at determining the limit-of-detection of the assay both in buffer and saliva. To enable measurement in saliva, a blocking buffer was added and a selected concentration of the surface blocker (bovine serum albumin) used for reducing non-specific binding (FIG. 6A-6C).
  • the surface blocker bovine serum albumin
  • the Receiver Operating Characteristic (ROC) curve was employed to assess the sensitivity, specificity, and concordance values of the test compared to PCR at every 2 minutes interval (FIG. 12A-12C).
  • the sensitivity showed a substantial improvement, increasing from 78% at 10 minutes to 89% at 18 minutes. After 18 minutes, the sensitivity remained relatively constant, hovering around 89%. Meanwhile, the specificity showed a continuous improvement, starting from 10% at 2 minutes, reaching 33% at 18 minutes, and finally achieving 100% at 26 minutes.
  • the enhanced sensitivity and specificity over time can be attributed to the optimal binding of the aptamer, which is essential for discernible viral association. However, beyond 26 minutes, there was a slight deterioration in specificity, likely due to increased non-specific fouling of the sensor surface caused by saliva samples.
  • the testing aimed to implement the RT- MAp strategy for detecting the flu virus.
  • the concentration of the TRHA06 was selected at 500 nM (FIG. 15).
  • the assay was then used by using spiked H3N2 (which displayed the best affinity towards TRHA06) in 25% saliva mixed with BBR Buffer.
  • the obtained limit of detection in saliva was 408 copies/mL of H3N2 (FIG. 4A-4B).
  • the limitation of detection for Influenza A (H3N2) was similar in comparison to COVID (OPV), and the resolution of the signal was different with OPV having a better resolution of the signal with increasing target concentration. This difference can be attributed to the lower affinity of the TRHA06 (FIG. 13A-13B). 10 Interestingly, generation of the maximum signal took longer for the Influenza A assay (24 minutes to 30 minutes) compared to COVID (14 minutes to 26 minutes).
  • VEGFiss vascular endothelial growth factor
  • This enhanced affinity trend allowed the present inventors to use the trimeric aptamer for VEGF detection as well.
  • the aptamer concentration to 250 nM (as illustrated in FIG. 18A-18D), a limit of detection of 0.96 pM VEGFies in buffer solution was achieved (FIG. 4C-4D). This accomplishment allowed the present inventors to translate this assay into plasma or serum samples.
  • Point-of-care tests play a crucial role in disease monitoring by providing rapid diagnostic information at the point of patient care, enabling early intervention and treatment.
  • 34,35 They are particularly valuable for infectious diseases like influenza, HIV, and COVID- 19, aiding in disease prevention and management.
  • POCTs are used for rapid disease screening in various healthcare settings and facilitate immediate decision-making for patient care. 36,37 Additionally, they are employed for real-time monitoring of health parameters, allowing for timely adjustments to treatment and lifestyle.
  • Electrochemical biosensors including electrochemical impedance spectroscopy (EIS), offer sensitive, portable, and versatile options for real-time POCTs, providing dynamic information on biomolecular interactions and enabling continuous monitoring without the need for frequent sampling. 38 EIS multifrequency spectra can capture comprehensive electrical properties of the system across a range of frequencies, while single frequency EIS simplifies experimental setup and analysis for specific biomolecular interactions. 16
  • This disclosure showed a sensor for real-time monitoring of infections.
  • the sensor utilizes single frequency Electrochemical Impedance Spectroscopy (EIS) and aptamers to detect the viral targets and monitor the progress of the infection in real-time. Initially, monomeric aptamers were used, but trimeric aptamers were found to have higher binding affinity. A one-pot strategy was adopted, where the aptamers and viral targets were introduced together with the readout buffer. This approach improved the signal by forming large aptamervirus aggregates and demonstrated a sensor with superior sensitivity.
  • the sensor could detect as low as 138 copies/mL of the COVID viral target in buffer and 584 copies/mL in 25% diluted heat-treated saliva. The specificity of the assay was evaluated, and minimal cross-reactivity was observed in both buffer and saliva samples. Assessment of known and unknown clinical samples demonstrated an optimal clinical sensitivity of 93%.

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Abstract

La présente divulgation concerne un biocapteur permettant de détecter un analyte cible dans un échantillon comprenant : a) un module de spectroscopie d'impédance électrochimique (EIS) comprenant (i) une électrode de travail, utilisable à une seule fréquence pour la surveillance en temps réel d'un aptamère se liant à une cible, une dissociation aptamère-cible, ou une dégradation d'aptamère ou de cible sur l'électrode de travail, (ii) une contre-électrode, (iii) une électrode de référence et (iv) un circuit compatible avec le potentiostat ; b) un aptamère multimère comprenant au moins deux unités pour la liaison cible spécifique et la formation d'un complexe aptamère-cible en solution, la cible comprenant au moins deux sites de liaison, l'aptamère multimère ayant une K d < environ 300 pM ; l'aptamère multimère étant conçu pour se lier à la surface de l'électrode de travail, et le système de biocapteur étant conçu pour fonctionner dans un format sans lavage et monotope.
PCT/CA2024/051053 2023-08-11 2024-08-09 Système de biocapteur aptamère multimère sans étiquette pour la surveillance en temps réel d'analytes cibles dans une configuration monotope Pending WO2025035209A1 (fr)

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020012943A1 (en) * 1997-02-06 2002-01-31 Dana M. Fowlkes Electrochemical probes for detection of molecular interactions and drug discovery
CA2763842A1 (fr) * 2009-06-08 2010-12-16 The University Of Western Ontario Appareil et procede electrochimique pour l'identification de la presence d'une cible
CA3144887A1 (fr) * 2019-07-05 2021-01-14 Eir Diagnostics Aps Biocapteur pour le diagnostic en centre de soins et les mesures sur site
WO2022020202A1 (fr) * 2020-07-23 2022-01-27 Massachusetts Institute Of Technology Détecteurs d'analytes électrochimiques microfluidiques
WO2022261776A1 (fr) * 2021-06-16 2022-12-22 Mcmaster University Biocapteurs pour la détection de pathogènes et leurs utilisations

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20020012943A1 (en) * 1997-02-06 2002-01-31 Dana M. Fowlkes Electrochemical probes for detection of molecular interactions and drug discovery
CA2763842A1 (fr) * 2009-06-08 2010-12-16 The University Of Western Ontario Appareil et procede electrochimique pour l'identification de la presence d'une cible
CA3144887A1 (fr) * 2019-07-05 2021-01-14 Eir Diagnostics Aps Biocapteur pour le diagnostic en centre de soins et les mesures sur site
WO2022020202A1 (fr) * 2020-07-23 2022-01-27 Massachusetts Institute Of Technology Détecteurs d'analytes électrochimiques microfluidiques
WO2022261776A1 (fr) * 2021-06-16 2022-12-22 Mcmaster University Biocapteurs pour la détection de pathogènes et leurs utilisations

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