Pure graphene-based biosensors for biomarker detection and related core particles, materials, compositions, methods and systems

Abstract

Provided herein are graphene biosensors and associated core particles, compositions, methods and systems, in which one or more pure graphene sheets are coated with a coating layer of an organic or inorganic material to provide a core graphene particle to which a detectable entity, including a detectable moiety and a peptide bond, is attached via the attachment of a peptide bond.

Description

[Technical field]

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS This application claims priority to U.S. Provisional Application No. 63 / 131,972, entitled "Pure Graphene-Based Biosensor for Biomarker Detection," filed on December 30, 2020, the contents of which are incorporated by reference in their entirety into this specification.

[0002] Government Subsidy Statement

[0002] This invention was made with Government support under Grant No. 2032751 awarded by the National Science Foundation. The Government has certain rights in this invention.

[0003] Technical Field

[0003] The present disclosure relates to the detection of biomarkers and related biosensors. In particular, the present disclosure relates to graphene biosensors for pure biomarker detection, as well as related core particles, material compositions, methods and systems. [Background technology]

[0004]

[0004] The detection of biomarkers is central to many areas of research, including medicine and basic biology research.

[0005] In particular, the detection of biomarkers is key to gaining an understanding of several biological events in various organisms, including the occurrence of various conditions ranging from cancer to viral infections, blood clotting and further events such as inflammation.

[0006] Despite the advances made in the field, robust and reproducible detection of biomarkers in samples at sub-nanomolar concentrations, particularly in relation to conditions, remains challenging. Summary of the Invention [Problem to be solved by the invention]

[0005]

[0007] The present disclosure relates to graphene-based biosensors (also referred to herein as graphene biosensors or biosensors) and related core particles, materials, compositions, methods and systems, in certain embodiments, that are capable of detecting picomolar or femtomolar concentrations of biomarkers with high reproducibility and signal-to-noise ratios, and that, in the context of the present disclosure, are extremely stable in a sample, as will be appreciated by one of skill in the art. [Means for solving the problem]

[0006]

[0008] In a first aspect, a graphene core particle is described. The graphene core particle comprises two or more pure graphene nanosheets coated with a coating layer comprising an organic and / or inorganic compound having a solubility in water of 1% by weight at 25° C. In the graphene core particle, the two or more pure graphene nanosheets and / or the organic and / or inorganic compound of the coating layer are configured to present functional groups that can bind to corresponding functional groups in aqueous solution.

[0009] In a second aspect, a biosensor configured to detect a target biomarker is described, comprising a graphene core particle of the present disclosure and a detectable moiety capable of emitting a fluorescent signal, the detectable moiety being attached to the core particle via a peptide bond that comprises a recognition sequence specific for the target biomarker. In the biosensor, the coating layer and the peptide bond are configured to set a quenching distance between the graphene nano-sheet and the detectable moiety, where the graphene nano-sheet quenches the fluorescent signal of the detectable moiety. In the biosensor, the peptide bond is further configured to set an emission distance between the graphene nano-sheet and the detectable moiety upon recognition of the recognition sequence by the target biomarker, wherein the graphene nano-sheet does not quench the fluorescent signal of the detectable moiety. Thus, in a biosensor, the target biomarker-specific peptide bond and the detectable moiety thus form a target-specific detectable component configured to emit a detectable fluorescent signal upon modification of the peptide bond by the target biomarker.

[0007]

[0010] In a third aspect, a multiplex biosensor is described that includes a core particle of the present disclosure and a plurality of target-specific detectable moieties attached to the graphene core particle, wherein each of the target-specific detectable moieties is formed from a detectable moiety capable of emitting a fluorescent signal, the detectable moiety being bound to a peptide bond that includes a recognition sequence specific for a target biomarker. In each target-specific detectable moiety, the peptide bond, in combination with the coating layer of the graphene core particle, is configured to provide a quenching distance between the detectable moiety and the graphene sheet core particle, such that the graphene nanosheet quenches the fluorescent signal of the detectable moiety. In the biosensor, the recognition sequence of each of the detectable moieties for the target biomarker is configured to specifically detect the target biomarker, and the multiple detectable moieties are selected to specifically detect multiple different target biomarkers. In the multiple target-specific detectable moieties of a biosensor, each detectable moiety has an excitation spectrum that has minimal overlap with the emission spectrum of another detectable moiety of the multiple target-specific detectable moieties.

[0008]

[0011] In a fourth aspect, compositions are described that include one or more graphene core particles and / or one or more biosensors as described herein in combination with a suitable adjuvant, such as a vehicle diluent, excipient, etc. In an embodiment, the composition is a pharmaceutical composition, and the adjuvant is a pharma- ceutically acceptable adjuvant. In an embodiment, the composition includes two or more graphene biosensors that display two or more detectable moieties specific for different target biomarkers, the excitation spectrum of each detectable moiety of the two or more detectable moieties has minimal overlap with the emission spectrum of another detectable moiety of the two or more detectable moieties.

[0009]

[0012] In a fifth aspect, a method and system for making the core particles described herein is described, the method comprising providing a pristine graphene nanosheet having a graphene surface, and coating the graphene surface with a layer of organic and / or inorganic molecules. The system for making core particles described herein includes a pure graphene nanosheet having a graphene surface and a reagent for chemically converting the graphene surface to provide a pure graphene nanosheet coated with a coating layer.

[0010]

[0013] In a sixth aspect, methods and systems for making a biosensor as described herein are described, the method comprising providing a core particle as described herein and attaching a detectable moiety to the graphene surface via a peptide bond. The system for making the biosensors described herein includes a pure graphene nanosheet that includes a graphene surface, a peptide bond, a detectable moiety, and a reagent for attaching the detectable moiety to the graphene surface via the peptide bond. In the system for making the biosensors described herein, the components are included in a configuration for simultaneous use or sequential use in the method for making the biosensors described herein.

[0011]

[0014] In a seventh aspect, a method and system for detecting the activity of a biomarker in a biological sample is described, the method comprising contacting the biological sample with any biosensor according to the present disclosure to generate a reaction solution and detecting a change in the reaction solution. The system includes a biosensor as described herein and reagents for simultaneous or sequential use in the methods of detecting the activity of a biomarker in a biological sample as described herein.

[0012]

[0015] In an eighth aspect, a method and system for multiplex detection of the activity of multiple biomarkers in a biological sample is described. The method includes contacting the biological sample with a multiplex biosensor according to the present disclosure configured to present detectable moieties specific to the multiple biomarkers to create a method reaction solution; and detecting a change in the reaction solution. Additionally or alternatively, the method may include contacting the biological sample with multiple biosensors, each presenting a peptide bond specific to one biomarker of the multiple biomarkers. A system for multiplexed detection of the activity of a plurality of biomarkers in a biological sample comprises a multiplexed biosensor as described herein, and / or a biosensor each presenting a peptide bond specific for one of the plurality of biomarkers, and optionally a plurality of reagents as described in any one of claims 40 to 42 for simultaneous use or sequential use in a method for multiplexed detection of the activity of biomarkers in a biological sample.

[0013]

[0016] In a ninth aspect, methods and systems for the detection of target biomarkers include heating of the sample and / or test solution prior to detection. In particular, it has been unexpectedly found that pre-treating serum and / or performing protease assays at a selected temperature improves signal to noise using a separate and additional mechanism.

[0014]

[0017] The biosensors and related graphene core particles, materials, compositions, methods and systems described herein, in some embodiments, provide graphene-based biosensors that are extremely stable in aqueous samples, maintaining at least 95% of the particles in suspension for several months with no more than -24% change in colloidal stability at OD650.

[0015]

[0018] The biosensors and associated core particles, materials, compositions, methods and systems described herein, in some embodiments, may enable highly reproducible detection of picomolar or femtomolar concentrations of biomarkers, in some embodiments with signal coefficients of variation of less than 10% between different manufacturing lots or batches.

[0016]

[0019] The biosensors and associated core particles, materials, compositions, methods and systems described herein, in certain embodiments, can detect picomolar or femtomolar concentrations of biomarkers in aqueous solution with a signal-to-noise ratio of 25 or greater across multiple sensors, as would be understood by one of skill in the art upon reading this disclosure.

[0017]

[0020] The biosensors and associated core particles, materials, compositions, methods and systems described herein may, in certain embodiments, detect multiple biomarkers in an aqueous sample with high multiplexing capabilities with up to 10 different detectable moieties in the UV / Vis spectrum, or up to 50 across the entire electromagnetic spectrum, presented on the same graphene particle or within the same solution, as will be understood by one of skill in the art upon consideration of this disclosure.

[0018]

[0021] The biosensors and associated core particles, materials, compositions, methods and systems described herein may, in certain embodiments, produce robust biosensors that can be dispersed in aqueous form, dried, and redispersed for up to 10 cycles of dispersion. Thus, the biosensors of the present disclosure may be included in compositions and systems in a dry form, as will be understood by those of skill in the art. Effect of the Invention

[0019]

[0022] The biosensors and associated core particles, materials, compositions, methods and systems described herein can be used in connection with a variety of applications in which reproducible detection of one or more biomarkers is desired, particularly when present at extremely low concentrations, such as picomolar or femtomolar concentrations. For example, the biosensors and associated core particles, materials, compositions, methods and systems described herein can be used in medical and diagnostic applications for visualization of the onset of disease pathology and biological events such as drug treatments and responses to treatments to facilitate the development of diagnostic and therapeutic cellular agents, as well as cell signaling, homeostasis, cell migration, responses to external stimuli such as temperature and pH, among other advantages identifiable by one of skill in the art.

[0020]

[0023] Further exemplary applications include the use of the biosensors and associated core particles, materials, compositions, methods and systems described herein in several fields including basic biology research, applied biology, bioengineering, pathogenesis, medical research, medical diagnostics, therapy, in drug research, and for developing diagnostic and therapeutic approaches and tools, as well as further fields identifiable by those of skill in the art upon reading this disclosure.

[0024] The details of one or more embodiments of the disclosure are set forth in the accompanying drawings and the description below. Other features, objects, and advantages will become apparent from the description and drawings, and from the claims.

[0025] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate one or more embodiments of the present disclosure and, together with the detailed description and the examples section, serve to explain the principles and implementations of the present disclosure. Exemplary embodiments of the present disclosure will become more fully understood from the detailed description and the accompanying drawings. [Brief description of the drawings]

[0021] [Figure 1]

[0026] [1] is a photo showing an SEM (scanning electron microscope) of exploded graphene. [Diagram 2]

[0027] FIG. 2A is a schematic diagram of an exemplary graphene-based biosensor for protease detection of the present disclosure.

[0028] FIG. 2B is a schematic diagram of an exemplary process for providing a biosensor according to the present disclosure: A: synthesis of carboxygraphene; B: chemical conjugation of polyethyleneimine via an amide bond; C: conjugation of a recognition sequence (oligopeptide) and a fluorescent dye such as tetracarboxy-phenyl-porphyrin (TCPP).

[0029] FIG. 2C is a schematic diagram showing a more ordered stack of nanosheets, including or consisting of thin monolayers or 2-3 layers of graphene entangled with each other at overlapping edges.

[0030] FIG. 2D is a schematic diagram of a high density of carboxylic acid groups added across the surface of a graphene nanosheet particulate. [Diagram 3]

[0031] FIG. 3A shows a reaction scheme of azirane cycloaddition to add controlled amounts of carboxylic acids to the surface of graphene.

[0032] FIG. 3B shows an exemplary structure of a single nanosheet of carboxygraphene (CG).

[0033] FIG. 3C is a side view of an exemplary carboxygraphene top layer structure showing a dense distribution of carboxylic acid groups across the surface.

[0034] FIG. 3D shows the differential thermal analysis (DTA) of the synthesized carboxygraphene 20 under N2. [Figure 4]

[0035] Figure 1 shows a titration curve (pH vs. volumetric 0.100 M HCl) starting with the addition of 20 mL of 0.100 M NaOH to 100 mg of cultured carboxygraphene. Round points: titration of carboxygraphene; square points: reference curve (no GO added). [Diagram 5]

[0036] FIG. 5A shows the structure of carboxygraphene-polyethylenimine, with only a single sheet shown for reference.

[0037] FIG. 5B is a chart reporting the results of differential thermal analysis (DTA) of an exemplary synthesized carboxygraphene-polyethylenimine (G-PEI) under N. [Figure 6]

[0038] FIG. 6A shows the structure of an exemplary carboxygraphene-polyethylenimine-based biosensor, with only a single sheet shown for reference.

[0039] FIG. 6B is a graph showing the UV / Vis spectra of carboxygraphene (top curve), carboxygraphene-PEI (bottom curve), and carboxygraphene-Biosensor (middle curve) for MMP-1 in water.

[0040] FIG. 6C shows four exemplary BODIPY dyes, specifically BODIPY FL, BODIPY TR, BODIPY 530550, and BODIPY 630650, that have no or minimal overlap between their excitation and absorption spectra. [Figure 7]

[0041] FIG. 1 is a schematic diagram of lysine and ornithine as possible spacers for biosensors. [Figure 8]

[0042] FIG. 1 is a schematic showing aromatic substituted nitrene reaction for chemical amination of graphene surfaces. [Figure 9]

[0043] We show a reaction scheme of the graphene-embedded carbocation with the secondary amine groups of PEI, resulting in chemical attachment of the PEI at the surface of the graphene. Note that primary amine groups can be reacted as well. [Figure 10]

[0044] 1 shows the Diels-Alder reaction between a maleimide derivative and graphene. [Figure 11]

[0045] FIG. 11 is a schematic diagram of the functional principle of the graphene-based biosensor of the present disclosure used for protease detection. [Figure 12]

[0046] FIG. 12 is a schematic illustration of the operating principle of an exemplary graphene-based biosensor configured to detect protease activity. [Figure 13]

[0047] FIG. 13A shows an estimate of the limit of detection (LOD) as indicated by logarithmic signal versus enzyme concentration for an exemplary biosensor of the present disclosure. In particular, FIG. 13A is a chart in which the left bar of each pair of bars shows the initial fluorescent signal detected after adding MMP1 to serum prior to incubation; the right bar of each pair of bars shows the fluorescent signal detected after 60 minutes of incubation at 37° C. AC (assay control) is biosensor solution mixed with buffer only, and blank is buffer only, which represent background signals, or fluorescent signals measured from buffer and biosensor only.

[0048] Figure 13B is a chart showing the fluorescence signal versus incubation time for different exemplary biosensor concentrations tested. Four different concentrations of graphene biosensor solutions were incubated with serum and measured over a 60 minute period. With incubation at 37°C, each concentration is represented by a symbol to show that the optimal signal quantified was for biosensor concentrations between 0.01 and 0.1 mg / mL. [Figure 14]

[0049] FIG. 1 is a table reporting eleven exemplary buffer formulations for pan-gNBS buffering. [Figure 15]

[0050] FIG. 15 is a chart reporting results showing the performance of cathepsin D (CTSD gNBS (panel A) and urokinase (uPA) gNBS (panel B) in the buffers of FIG. 17. CTSD and uPA gNBS were suspended at a final concentration of 30 μg / ml in buffers 1-11 of FIG. 17 as indicated. 5 μl of serum A, S or pooled normal serum (PNS) or buffer only (AC) was added to the working solution in triplicate. After incubation at 37° C. for 60 minutes, fluorescence at 421 nm / 650 nm was measured. [Figure 16]

[0051] 1 is a chart reporting results showing the effect of salt on zeta potential stability. uPAgNBS was assembled in working solutions of 5 mM MES buffer with the indicated pH, with (Panel B) or without (Panel A) 155 mM NaCl. Control solutions of uPAgNBS were prepared in deionized water. [Figure 17]

[0052] FIG. 1 is a chart of reported results of an experiment showing the performance of uPA gNBS (Panel A), matrix metalloproteinase 10 (MMP10) gNBS (Panel B), CTSD gNBS (Panel C), and cathepsin H (CTSH) gNBS (Panel D) in isotonic salt buffer. CTSD, uPA, MMP10, and CTSH gNBS were suspended at a final concentration of 30 μg / ml in 30 μg / ml buffers 1, 2, or 9. 5 μl of serum A, S, or pooled normal serum (PNS), or buffer only (AC), was added to the working solution in triplicate. After incubation at 37° C. for 60 minutes, fluorescence at 421 nm / 650 nm was measured. [Figure 18]

[0053] Graph showing the effect of NaCl concentration on background noise. uPAgNBS was incubated with 5 mM or 10 mM MES buffer containing 10 μM divalent cations or 154 mM NaCl or no salt. Signal obtained after 90 min at 37° C. (expressed as average RFU). [Figure 19]

[0054] Figure 19A shows TEM images of pure exploded graphene at different magnification scales, specifically 5 nm; 250,000; 10 nm; 120,000; 20 nm; 70,000; 200 nm: 10,000.

[0055] FIG. 19B is a TEM image of a graphene biosensor. gNBS was assembled with a peptide target for MMP15. Scanning electron micrographs were collected at 15,000x (left panel) and (middle panel) 300,000x (right panel). The overall size can be seen, revealing the layered structure of the graphene sheets. Bars indicate 200 nm or 5 nm. [Figure 20]

[0056] Photographs reporting the results of an experiment showing the effect of sonication on graphene starting material. The three tubes, from left to right, show samples of KSU Lot 1, HEB100, and HEB101. gNBS was assembled with the peptide target for NE using the original KSU protocol. The only difference was that HEB100 was probe sonicated for 10 min and HEB 101 was probe sonicated for 60 min prior to assembly of the gNBS sensor. After preparation of the gNBS working solution, particles of gNBS can be seen to precipitate from the KSU Lot 1 preparation. Small amounts can also be detected in HEB 100. No precipitation is observed in the HEB 101 preparation. [Figure 21]

[0057] 1 is a chart reporting the results of an experiment showing the effect of sonication of starting materials on polydispersity. The graph shows the polydispersity index (PDI) for each formulation when the working solution was first made and dispersed in a sonication water bath (0 min rest) and then 30 minutes later (30 min rest). A significant decrease in PDI was observed at each stage of production for particles made with sonicated graphene, reflecting greater uniformity of the particles produced at each stage of the process. [Figure 22]

[0058] Figure 22 is a chart reporting the absorbance at 270 nm for graphene with increasing sonication time. Solutions of graphene in DMF were probe sonicated for increasing times. Samples were taken at regular intervals, the absorbance was measured, and the associated measurements were plotted on the chart. [Figure 23]

[0059] 1 shows a table reporting thermogravimetric analysis (TGA) results for total mass loss of original KSU lot 120120 and CG preparations CG-1, CG-2, CG-3, and CG-4 after different drying protocols. [Figure 24]

[0060] FIG. 1 is a chart reporting the results of thermogravimetric analysis of a CG preparation characterized by 1.6±0.1×10-4 mol / g carboxylic acid functionality by titration. The graph shows the change in mass as the temperature increases from RT to 600° C. The graph shows the mass lost during the increase to 100° C. The mass change after 400° C. is minimal. [Diagram 25]

[0061] Figure 24 shows the results of thermogravimetric analysis of CG preparations CG1.1, CG1.2, CG1.3 and CG1.4 of Figure 23. Different preparations of CG were subjected to TG analysis. The graph shows the change in mass as the temperature increases from RT to 1000°C. The graph shows the mass lost during the increase to 100°C. The mass change after 400°C is minimal. [Figure 26]

[0062] 26 is a chart reporting experimental results showing the effect of solvent removal on gNBS performance. In particular, uPAgNBS was evaluated in triplicate at 2, 16 or 27 days after production using the standard protocol. Separate lots of uPAgNBS were produced including 30 minutes of ambient drying and overnight ambient drying at 37° C. These were evaluated 5 days after production. The chart shows the relative fluorescence index calculated by sample / assay control. In the experiment reported in FIG. 26, the uPA sensor used is based on carboxygraphene / polyethyleneimine. [Figure 27]

[0063] 1 is a chart reporting the effect of sonication of starting material on batch-to-batch variability of signal. Three lots of gNBS for neutrophil elastase (NE), HEB Lot NE100, HEB Lot NE 101, and HEB Lot NE 102, were manufactured and compared to the original KSU Lot 120120. gNBS was tested under normal conditions with serum from two different normal human donors. [Figure 28]

[0064] 1 shows a table reporting the formulations for biosensor manufactures HEB Lot NE100, HEB Lot NE 101, and HEB Lot NE 102 with increased dispersion effort. [Figure 29]

[0065] 1 is a chart reporting the results of an experiment aimed at evaluating the effect of water bath sonication on gNBS absorbance over time. gNBS HEB Lot NE100, HEB Lot NE 101 and HEB Lot NE 102 and KSU Lot 120120 were resuspended in working buffer and suspended for increasing times in a sonication water bath. At intervals, samples were withdrawn and absorbance at 425 nm and 265 nm was measured. Four different lots of gNBS for NE are shown. [Diagram 30]

[0066] Figure 30 Panel A and Figure 30 Panel B are charts reporting the results of pH titration of carboxygraphene. A solution of carboxygraphene prepared using the protocol described herein was prepared in 50 mL of 0.05 M NaOH. After incubation and removal of the CG, the resulting solution was treated with 20 mL of 0.05 M HCl and then neutralized with increasing amounts of 0.05 M NaOH and compared to neutralization of the aqueous solution. [Diagram 31]

[0067] Shown is a table reporting the results of elemental analysis of different lots of graphene carboxygraphene (CG) preparations and CG derivatized with polyethyleneimine (CGP) preparations. In particular, two different lots of graphene, six different preparations of CG as shown and one preparation of CGP were subjected to elemental analysis for C, H, O and, where results are quoted, N. All results were produced by Galbraith Laboratories except *data produced by KSU. Results are shown as percent composition. For comparison, CGP102 is a PEI derivatized product associated with CG1.0. [Diagram 32]

[0068] 1 is a chart reporting the results of an experiment on the preparation of gNBS without a carboxylation step. uPAgNBS was constructed by attaching PEI to a carboxygraphene scaffold (uPA) or directly to the graphene scaffold using EDC chemistry, or reacted with PEI without EDC by heating to 80° C. uPA-TCPP was then added to all three scaffolds, and the resulting gNBS was stimulated with pooled normal serum (pooled normal serum) or buffer (assay control) for 90 min at 45° C. before being measured on a VarioSkan Lux at 421 / 653 nm. [Diagram 33]

[0069] 1 is a chart reporting the results of rapid conjugation of PEI without prior carboxylation. uPAgNBS was prepared by activating 1.2k or 10k PEI with azidoacetic acid NHS ester and coupling it to graphene at 80° C. The activity of the resulting sensor was assessed by stimulation with buffer, 50 mg / mL BSA or pooled normal serum. [Diagram 34]

[0070] 1 shows a table reporting DLS and zeta potential results for the MMP1g-TEG3 amine biosensor. [Diagram 35]

[0071] Figure 1 is a chart reporting the results of the fluorescence intensity measured for the MMP1g-PEI biosensor (panel A) versus the MMP1g-TEG3amine biosensor (panel B). Fluorescence intensities were measured every 15 min after incubation at 37 °C, and these intensities continued to increase over time, following an approximately linear trend for both. Comparing both biosensors, G-TEG3amine gave a higher intensity after 60 min of incubation compared to G-PEI. [Diagram 36]

[0072] 1 is a chart reporting the results of fluorescence intensity after 60 minutes of incubation for G-PEI vs. G-TEG3amine and assay control. After 60 minutes of incubation (Panel A), the intensity for G-TEG3amine gave the highest intensity compared to G-PEI. This shows that for control serum S and P, the intensity of G-TEG3amine was almost 2-fold higher compared to G-PEI. (Panel B) Fluorescence intensity measured for mMP1g-PEI vs. assay control for G-TEG3amine biosensor. [Figure 37]

[0073] 1 is a chart reporting absorbance results across the visible spectrum for a solution of neutrophil elastase gNBS. [Figure 38]

[0074] FIG. 1 is a chart reporting the results of an experiment showing the quenching of several different dyes by graphene. gNBS were prepared by coupling NE-FAM (panel A), NE-TAMRA (panel B), or uPA-TCPP (panel C) to sonicated graphene using standard procedures. The dose response of each sensor in a 70 μL volume was stimulated in triplicate with buffer alone (AC) or 10 μl serum in a 384-well plate. Plates were incubated at 45° C. and fluorescence was read at 10 min intervals for 90 min. [Figure 39]

[0075] 1 is a chart reporting the results of an experiment showing quenching of rhodamine-B by graphene with rhodamine-BgNBS. MMP7 and MMP9 rhodamine B peptides were conjugated to CGP and incubated for 60 minutes in the presence of serum or buffer only (AC). [Diagram 40]

[0076] 1 is a chart reporting the results of an experiment with multiplexed gNBS. gNBS sensors were prepared by coupling Arg-FAM or NE-TAMRA as shown to sonicated graphene using standard procedures. 70 μl of working solution was prepared with each sensor alone (Singleplex) or both together (Multiplex) at a final concentration of 200 μg / ml. Triplicate wells were treated with 10 μl of buffer or 10 μl of serum and incubated at 45° C. for 90 min, with measurements taken at 10 min intervals. Each well was measured with 496 / 526 (FAM) and 555 / 586 (TAMRA) (D03-250). [Diagram 41]

[0077] Figure 1 is a chart reporting the results of nanosensor analysis on several different platforms. gNBS sensors were prepared by coupling NE-FAM to sonicated graphene using standard procedures. 125 μl of working solution was prepared with 200 μg / ml of sensor. Triplicate wells were treated with 5 μl of buffer (AC) or 5 μl of serum. Additional wells were also prepared in which 5 μl of serum was diluted into 125 μl of buffer (sample background). Each well was measured at 496 / 526 (FAM) at 30 min intervals on the Varioskan and 1 min intervals on the StepOnePlus. [Diagram 42]

[0078] The results of an experiment to detect proteases after heat treatment are shown (Panel A). MMP10gNBS and CTSHgNBS were stimulated in a 125 μl working solution of 5 mM MES, 10 μM cation and IS:155 with control serum and pooled normal control serum. An aliquot of each serum was incubated at 55° C. for 60 min and used to stimulate duplicate reactions. Both sets of reactions were incubated at 37° C. for 1 h and fluorescence was measured on a Varioskan Lux. (Panel B) MMP2gNBS and CTSHgNBS were stimulated in a 125 μl working solution of 5 mM MES, 10 μM cation and IS:155. They were stimulated with 5 μl of buffer (AC) or stimulated in triplicate with 5 μl of control serum C or pooled normal serum (PNS). Alternatively, serum was pretreated with EDTA to a final concentration of 5 mM for 10 min at 65° C. or with both. The resulting activities, reported in RFU, are shown for each sensor. [Diagram 43]

[0079] 1 is a chart reporting the results of an experiment involving heat pretreatment of serum. CTSHgNBS were stimulated in 125 μl of a working solution of 5 mM MES, 10 μM cation and IS:155. They were stimulated with 5 μl of buffer (AC) or in triplicate with 5 μl of PNS that had or had not been previously heat treated at 65° C. The activity of CTSHgNBS was monitored at 30 minute intervals for 6 hours at 37° C. incubation. This chart shows that healthy pretreatment results in linear activity. [Diagram 44]

[0080] 1 is a chart reporting the results of an experiment involving heat pretreatment of serum. 18 gNBS were prepared in 125 μl of a working solution of 5 mM MES, 10 μM cation and IS:155. They were stimulated with 5 μl of buffer (AC) or stimulated in triplicate with 5 μl of PNS that was or was not previously heat treated at 65° C. Activity of gNBS After incubation, the activity of gNBS was measured. Results are expressed as RFI, sample RFU divided by assay control (RFI=SM-(AC+SC)). The chart shows that heat pretreatment results in increased activity across the sensor panel. [Diagram 45]

[0081] 1 is a chart reporting the results of assays performed at different temperatures. 125 μL MMP12 and CTSDgNBS were stimulated in triplicate with 5 μL buffer (assay background graph) or with 5 μL PNS and assays were incubated at 37, 41 or 45° C. (open symbols) in a VarioSkan Lux. Alternatively, serum was heat treated at 65° C. for 12 min and then 5 μL was added in triplicate to 125 μL MMP12 or CTSDgNBS in standard MES buffer. Fluorescence was measured at 10 min intervals during incubation. Sample background measurements show results from wells incubated with 125 μL buffer without sensor but with 5 μL serum added. The chart shows that the high temperature of incubation mimics heat treatment of serum. [Diagram 46]

[0082] FIG. 1 is a chart reporting the detection of protein coronas of gBNS specific for 18 different target proteases shown on the chart. The average and minimum signal observed across 175 human samples was compared to a 20 mg / ml acetylated BSA solution. The graph shows the average and minimum fluorescence readout for the 175 samples across all 18 sensors. [Figure 47]

[0083] 1A-C are charts reporting the results of an experiment aimed at determining the precision of lyophilized gNBS reagents. A selection of gNBS were lyophilized in 384-well plates in one of three different excipient formulations: A, B, or C. Each formulation was compared to wet reagent prepared from the same batch but not lyophilized. (Panel A) Inter-assay precision: Three 384-well plates were tested over three separate days, 256 total serum samples and 4 NBS / plate. 64 serum samples per excipient on each plate were tested. %CV measured by averaging the quotient of the sample standard deviation of the mean and the mean of the mean for each excipient. (Panel B) Intra-assay precision: 64 serum samples and 4 NBS per excipient were tested. Precision was measured from the average %CV of each excipient within the 384-well plate run. [Figure 48]

[0084] A table is shown reporting the mean RFU for each NBS evaluated for 256 or 175 patients divided into lung cancer and non-lung cancer groups. Two studies are presented, called EU 351 and US SST-18, which examined 207 and 175 total patients, respectively. The numbers indicate the mean RFU generated by each gNBS for the indicated groups. Subjects in each group are divided into pathologically confirmed lung cancer cases or clinically confirmed negative lung cancer cases. All cases are untreated patients. [Figure 49]

[0085] A table of p-values ​​for two-tailed, heteroscedastic Student's t-test comparing RFU between lung cancer and non-lung cancer samples is shown. [Figure 50]

[0086] A plot of molecular weight (Da) versus particle diameter (Angstroms) is shown. Mn: number average polymer mass, Mw: mass average polymer mass, Mv: average polymer molecular weight (corresponding to Figure 1 in Loebach 1975. [2]). [Figure 51]

[0087] Figure 2 shows the acceptable ratio of peptide length (A) to polymer layer thickness (B) in graphene biosensors for protease activity detection. [Figure 52]

[0088] 1 shows an exemplary monolayer of a water-soluble organic molecule of oligoethylene glycol and the associated reaction scheme for the attachment to the surface of graphene 1. [Diagram 53]

[0089] Figure 2 shows the pH titration of carboxygraphene, where the difference in the volume of NaOH in the two titration curves for the same value of pH around 7.00 gives the concentration of ionized groups (carboxyl groups) per mass gain of carboxygraphene. [Figure 54]

[0090] 1 is a chart showing the results of an experiment demonstrating the detection of the target biomarker MMP-9 in three different control serum samples using core particles G-PEI and G-TEG3Amine presenting different cleavable peptide sequences labeled with two different dyes, specifically MMP-9 labeled with TCPP (GAGVPLS-LYSGAG) (SEQ ID NO: 132) and MMP-9 labeled with Rhodamin B (GCDDHAAG-LLGLDG) (SEQ ID NO: 133). Fluorescence intensity was measured over time as indicated in the three control samples (marked A, B and C on each chart). [Figure 55]

[0091] 54 is a chart showing an exemplary effect of dispersion and solvent removal on absorbance efficiency of gNBS. A working solution of gNBS was prepared in 5 mM MES pH 7.4 with 155 mM NaCl at a concentration of 25 μg / mL. Absorbance over 250 nm to 650 nm was measured for each lot reflecting two lots without sonication (lots 1 and 2) and two lots prepared with 1 hour of sonication (lots 3 and 4) and solvent removal (lot 4). Data is presented as spectra or absorbance efficiency at OD270. In particular, panel A of FIG. 54 shows the change in absorbance efficiency for the NE biosensor over 250 nm to 650 nm. Panel B of FIG. 54 shows the change in absorbance efficiency of the MMP15 biosensor over 250 nm to 650 nm. The table highlights the increase in absorbance efficiency at OD270 across the four lots of each biosensor. [Figure 56]

[0092] Figure 1 shows the effect of buffer formulation on signal-to-noise performance. Working solutions of gNBS were prepared in buffers as detailed in Figure 14. Signal-to-noise was calculated based on the ratio of fluorescence observed in the sample / assay control (RFI). Buffer 7, containing only MES, performed similarly to Buffer 1 (Hepes). Addition of 30 mM NaCl (Buffer 8) or 155 mM NaCl (Buffer 9) increases the RFI. [Figure 57]

[0093] 1 is a chart showing exemplary effects of buffer formulation and heat treatment on signal-to-noise performance. Working solutions of gNBS were prepared in HEPES or MES buffer supplemented with 10 μM divalent cations and 155 mM NaCl. Samples were heat treated at 65° C. for 12 min (MES baseline) or not heat treated (HEPES baseline) and incubated at 37° C. for 90 min. [Figure 58]

[0094] FIG. 1 is a chart showing exemplary colloidal stability of gNBS sensors. Working solutions of gNBS were prepared in 5 mM MES pH 7.4 with 155 mM NaCl at 25 μg / mL. Absorbance at 250 nm to 650 nm was measured for each lot upon vortexing the solution. Samples were left at room temperature for 1 hour. A second sample was measured after 60 minutes. Data represents the fold change in absorbance from time 0. The different samples reflect two gNBS lots without sonication (lots 1 and 2) and two lots prepared with 1 hour of sonication (lots 3 and 4) and solvent removal (lot 4). FeNB (300 μg / mL) is included for comparison. Lot 2 had large gNBS particles that did not remain in suspension at all, underestimating colloidal stability. [Figure 59]

[0095] 1 is a chart showing an exemplary evaluation of signal to noise across different manufacturing protocols for gNBS. CTSB was manufactured using the original iron scaffold (FeNB), using the graphene scaffold and the original KSU protocol (gNBS lot 1), using a replica of the KSU protocol with an extended drying procedure (gNBS lot 2), using a probe sonicated gNBS scaffold (gNBS lot 3), and using a probe sonicated gNBS scaffold that was fully dried due to solvent removal during manufacturing (gNBS lot 4). The graph shows the signal:noise measured by RFI (SM / AC) at time 0 (A), the signal:noise after 60 min incubation with pooled normal serum (B), and the signal:noise expressed as the ratio of RFI 60 / RFI 0 (C). Similar observations were made for CTSB, MMP12, and NE in separate experiments (D). [Figure 60]

[0096] 1 is a chart showing the results of detection of gNBS in a multiplex setup. Signals are expressed as a percentage of the signal obtained at 100%. [Figure 61]

[0097] FIG. 1 is a chart showing an exemplary evaluation of signal to noise across different fabrication protocols for Fe and graphene biosensors. Biosensors were fabricated using the original iron scaffold (FeNB), using the graphene scaffold and the original KSU protocol (gNBS lot 1), using a replica of the KSU protocol with an extended drying procedure (gNBS lot 2), using a probe sonicated gNBS scaffold (gNBS lot 3), and using a probe sonicated gNBS scaffold that was fully dried for solvent removal during fabrication (gNBS lot 4). The graph shows the signal:noise average at time 0 and after 60 min of incubation with two different normal human sera as measured by RFI (SM / AC). Four exemplary biosensors are shown. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0022]

[0098] The present disclosure relates to graphene-based biosensors and associated core particles, materials, compositions, methods and systems for assays for the non-invasive detection and quantification of various biological markers.

[0023]

[0099] The term "graphene" as used herein refers to an allotrope of carbon consisting of a single layer of atoms arranged in a two-dimensional honeycomb lattice nanostructure. The name is derived from "graphite" and the suffix -ene, reflecting the fact that the graphitic allotrope of carbon contains a large number of double bonds. In particular, graphene, in the context of the present disclosure, refers to a single layer of at least 1000 carbon atoms of sp2 hybridization arranged hexagonally. Exchangeable graphene aggregates or graphene particles as used herein refer to at least two layers of graphene stacked on top of each other.

[0100] Thus, graphene in the sense of the present disclosure comprises at least 98% carbon atoms organized in a sheet. In a graphene sheet, each atom is connected to its three nearest neighbors by σ bonds and contributes one electron to a conduction band that extends over the entire sheet. [3] (see schematic diagram and properties discussed in Examples 1 and 2).

[0101] For graphene in the sense of the present disclosure, a typical apparent static contact angle θ* of a typical graphene surface is θ*=150±15°, which is borderline superhydrophobic (θ*≧150°). Based on this finding and the fact that graphene consists almost exclusively of carbon (at least 99±1%), it is well established that graphene is one of the most hydrophobic materials known. Its dispersibility in water is therefore <1×10 per milliliter. -8 mg.[4]

[0102] Graphene absorbs light in the UV, visible and near infrared ranges with an absorption coefficient exceeding that of graphite.[5] Graphene in the sense of this disclosure is therefore a material configured to absorb light of all visible wavelengths.[3] Stacked graphene is characterized by light absorption over the entire wavelength range from far UV to mid IR (100-1500 nm).[6] For exploded graphene (5-7 layers), the inventors have demonstrated an absorption coefficient α>5,000 mLmg at 660 nm. -1 m -1 We find that the absorption coefficient α at 660 nm ranges from 1,000 to 5,000, which is in excellent agreement with the literature [7]. In general, graphene from various sources has an absorption coefficient α at 660 nm ranging from 1,000 to 5,000.

[0024]

[0103] In graphene in the sense of this disclosure, direct excitation occurs in the deep / far UV, and surface plasmons of graphene in the visible range are of varying strength, and direct excitation and surface plasmons of graphene cannot effectively excite most detectable moieties (such as fluorescent dyes or particles) that can emit a fluorescent signal in the excited state. This indication applies to the entire visible range of the electromagnetic spectrum (400-730 nm), as will be understood by those skilled in the art. [6]

[0104] Graphene in the sense of the present disclosure includes pure graphene (graphene in its pristine, pure, unoxidized form), as well as oxidized or surface-modified forms of graphene, (surface-modified) graphene and further graphene forms identifiable by one of skill in the art.

[0105] Pure graphene can be identified by techniques identifiable by one of ordinary skill in the art, such as XRD (layer distance), TEM and SEM (morphology), RAMAN (layer distance and turbostratic characteristics, if present), and FTIR (lack of characteristic organic functional groups, except for carbon-carbon double bonds and aromatic overtones). In particular, FTIR and RAMAN spectra can be used to identify pure graphene over surface-only oxidized or chemically modified graphene, since the associated spectra change upon oxidation / chemical modification of the graphene surface, as understood by one of ordinary skill in the art. Pure graphene can be identified using XRD, TEM, SEM, RAMAN, FTIR, by considering the associated spectral changes, also identifiable by one of ordinary skill in the art, upon oxidation / chemical modification that destroys the layer structure of graphene. Additionally, in all cases, elemental analysis confirms that the graphene material is >98% carbon, as understood by one of ordinary skill in the art.

[0106] In the embodiments described herein, pure graphene in the sense of the present disclosure can be used as a component of the graphene core particles described herein, where two or more pure graphene sheets form graphene particles coated with a coating material configured for attachment of a detectable moiety specific for a target biomarker.

[0025]

[0107] The term "particle" or "particulate" as used herein refers to a portion of a substance with distinct physical or chemical properties, such as size, volume, density, or mass. Exemplary particles of various materials are described in U.S. Provisional Patent Application No. 63 / 132,058, filed December 30, 2020, entitled "Optical Nanobiosensors for Rapid Identification of Lung Conditions," and corresponding PCT application, docket number P2685-PCT, filed December 29, 2021, entitled "Nanosensors For Rapid Identification of Lung Conditions," the contents of which are incorporated herein by reference in their entirety.

[0026]

[0108] The size of a particle in the sense of the present invention is 1 to 5000 nanometers. In particular, the size of a particle in the sense of the present invention may be 1 to 250 nanometers, and 50 to 150 nm in nanoscopic / mesoscopic systems. Size as used herein is the maximum physical length of any two points of a particle. In a particle in the sense of the present disclosure, the size of a particle refers to the longest distance between any two points of the particle. For example, an irregularly shaped graphene particle has the longest size between any two carbons on the irregularly shaped graphene particle. In a spherical particle, the size of a particle is the diameter of the spherical particle.

[0027]

[0109] In the graphene particles of the present disclosure, the mass distribution of the graphene particles can be detected by measuring the time required for centrifugation and sedimentation, as well as further techniques that can be identified by those skilled in the art. The actual size of the graphene particles in air (or N2, Ar) and in a suitable hydrophobic solvent (e.g., chloroform) can be determined by dynamic light scattering (DLS). The surface charge of the particles can be determined by zeta potential measurement.

[0110] Graphene particulates may have layers arranged in an AB or Bernal stacking configuration, where half of the atoms are directly above and half of the atoms are above the hexagonal center of the underlying graphene sheet. Graphene particles may also have layers arranged in an AA configuration, where the layers are precisely aligned and each carbon atom in one layer is precisely positioned above another carbon atom in the adjacent layer of graphene. In turbostratic particles (AA and AB stacking), the individual layers can move relative to each other, as will be understood by those skilled in the art.

[0028]

[0111] The graphene core particles of the present disclosure comprise pure graphene sheets aggregated by van der Waals stacking in configurations comprising two or more graphene layers.

[0112] A "sheet" or "layer" in the sense of the present disclosure refers to a two-dimensional nanostructure with a scale thickness ranging from 1 to 150 nm. A single layer of carbon atoms with a hexagonal lattice of graphene material is 0.34 nm, as understood by those skilled in the art. Since a single layer of graphene absorbs 2.3% of incident light and allows about 97.7% to pass through, the inclusion of two or more sheets in the graphene core particles of the present disclosure can enhance the light absorption (blackness) resulting from the electron-electron interactions of the stacked graphene layers, especially when the stacked graphene layers are organized into few-layer graphene.

[0029]

[0113] As used herein, the term "few-layer graphene" refers to graphene having a number of graphene layers ranging from about 2 to about 100 graphene sheets, preferably 3 to 50 graphene sheets, and even more preferably 5 to 25 sheets. In few-layer graphene disclosed herein, the minimum number of layers is 2, the maximum number of stacked graphene layers is 100, and the interlayer distance in graphene is 0.348±0.003 nm, compared to 0.337 nm in graphite.[8] The maximum diameter of stacked graphene flakes has a lower limit of 10 nm and an upper limit of 5,000 nm.

[0030]

[0114] The number of nanosheets in a graphene particle in the sense of the present disclosure can be detected by transmission electron microscopy (TEM), X-ray diffraction (XRD), Raman spectroscopy, and further techniques that can be identified by the skilled artisan.

[0031]

[0115] In the graphene particles of the present disclosure, the size of the graphene nanosheets is typically in the range of about 20 to about 500 nm (e.g., a size of 200 nm or 150 nm as detected by transmission electron microscope (TEM) images), where the term "size" refers to the maximum point-to-point distance in the graphene core particle (e.g., the diameter in the case of a spherical particle, or the diagonal distance in a rectangular shape).

[0032]

[0116] In a preferred embodiment, the graphene particles of the present disclosure are few layer graphene particles having between 2 and 100 graphene sheets that enable light absorption properties that allow for efficient quenching of the fluorescent signal emitted by the detectable moieties of the present disclosure, as would be understood by one of skill in the art upon reading this disclosure.

[0033]

[0117] In a preferred embodiment of the present disclosure, the graphene particles are furthermore less than 900 nm in size, preferably less than 500 nm, more preferably less than 350 nm, and even more preferably between 50 nm and 250 nm, allowing for the formation of stable core particles of the present disclosure in combination with the coating material and detection of target biomarkers at picomolar or femtomolar concentrations.

[0034]

[0118] In particular, the pure graphene sheets that form the graphene particles described herein can be provided according to methods and techniques identifiable by one of ordinary skill in the art.

[0119] For example, pure graphene can be produced via the detonation of an acetylene / oxygen mixture in an explosion chamber. The graphene nanosheets so produced aggregate in the gas phase to form an aerogel, which can be harvested according to approaches identifiable by those skilled in the art to provide graphene, also identified as exploded graphene or exploded graphene.

[0035]

[0120] Pure graphene can also be obtained from graphite by oxidative exfoliation. According to a related method, graphite is oxidized under extremely harsh chemical conditions (e.g., Hummers method) and heat to obtain oxidized single-layer graphene (called graphene oxide). The graphene oxide is then reduced to few layers of pure graphene using hydrazine or other reducing agents, according to approaches identifiable by the skilled artisan.[9]

[0121] Pure graphene can also be obtained by performing a flash synthesis. Thus, organic materials can be transformed into few-layer graphene by applying a direct current to the obtained flash graphene according to approaches identifiable by the person skilled in the art. [10,11]

[0122] Pure graphene can also be obtained by CVD (chemical vapor deposition) to produce a graphene monolayer on a substrate (not suitable for sensitive optical biosensors) following approaches identifiable by those skilled in the art to provide CVD graphene.[9]

[0123] In certain embodiments of the graphene core particles described herein, the pure graphene starting material is preferably prepared using detonation-synthesized graphene or flash-synthesized graphene, which can be prepared by processes and approaches identifiable by one of skill in the art (e.g.,

[12] , [8],

[13] ,

[14] , which are incorporated herein by reference in their entireties).

[0036]

[0124] The preparation of exploded-sized graphene involves a process that involves the controlled explosion of carbon-containing material(s) as a solid, liquid, or gas with an oxidant or oxygen source (e.g., O2, NO, NO) at relatively high temperatures in a reaction vessel to produce pure graphene nanosheets and branched fractal aggregates of these nanosheets without the use of catalytic materials. Typically, a reaction vessel is loaded with the desired amount of reactants, and explosion of the materials is achieved using a spark. An aerosol is produced, which often undergoes gelation to form an aerosol gel containing graphene particles. (

[15] and

[16] ).

[0037]

[0125] In the scaled-up approach, the apparatus includes a reaction chamber, a vacuum source operably connected to the reaction chamber, and an ignition assembly. The reaction chamber is operably coupled to a carbon-containing material source and an oxidizer source. The vacuum source is operable to selectively evacuate at least a portion of the contents of the reaction chamber, particularly following generation of the particulate material. The ignition assembly is also operably connected to the reaction chamber and configured to initiate combustion of a quantity of carbon-containing material and a quantity of oxidizer delivered to the reaction chamber from each source. The ignition assembly includes a pair of electrodes operable to generate an ionized arc therebetween, each contained within a respective cassette that is removably received within the ignition assembly. Scaled-up apparatus and synthesis processes for the mass production of pure graphene are described in co-pending U.S. Patent Application No. 63 / 039,087, filed June 15, 2021, and corresponding PCT / US2021 / 037321, filed June 15, 2020, each of which is incorporated herein by reference.

[0038]

[0126] Exemplary carbon-containing materials for use in the reaction include carbon-rich precursors, gases, gas mixtures, powders, aerosols, and other injectable materials. The carbon-containing material may include a single material or compound, or a mixture of carbon-containing compounds. Examples include coal, petroleum coke, biochar, carbon black, biowaste (e.g., food or agricultural waste), biomass or organic waste (e.g., cellulosic materials, grasses, etc.). It will be understood that materials with higher carbon content are particularly preferred. The starting material may be any hydrocarbon compound, particularly saturated or unsaturated C1-C 12 It can contain hydrocarbon compounds, highly saturated C1-C 12 Hydrocarbons are particularly preferred. In certain embodiments, preferred hydrocarbon materials include acetylene, ethylene, toluene, butadiene, and / or isoprene. Temperature and / or pressure parameters can be adjusted depending on the material selected.

[0039]

[0127] In one or more embodiments, the combustion reaction occurs at a temperature of at least 3000K, at least 3500K, or at least 4000K. In certain embodiments, the combustion reaction occurs at a temperature between about 3000K and about 5000K, between about 3500K and about 4500K, or about 4000K. Combustion of the carbon-containing material and the oxidizer at these temperatures has been found to favor the formation of highly ordered graphene particulates as opposed to graphite soot. If necessary, an inert gaseous material such as helium, neon, argon, or nitrogen can be included in the reaction mixture charged to the reaction vessel to aid in temperature control during combustion. Also, in certain embodiments, especially those in which the combustion reaction is an explosion, the combustion of the reaction mixture proceeds extremely rapidly. The explosion typically involves a supersonic heat generation front that accelerates through the medium and ultimately drives a shock front that propagates directly in front of it. In certain embodiments, the duration of the combustion is from about 5 to about 100 ms, from about 10 to about 75 ms, or from about 20 to about 50 ms.

[0040]

[0128] The ratio of oxidant to carbon-containing material present in the reaction vessel prior to detonation may contribute to the properties of the graphene microparticles formed upon detonation of the reaction mixture. In certain embodiments, the molar ratio of oxidant to carbon-containing material is 1.5 or less, preferably 1.0 or less, and even more preferably 0.5 or less. In certain embodiments, the ratio of oxidant to carbon-containing material is about 0.1 to about 1.5, about 0.18 to about 1.2, about 0.18 to about 1.0, or about 0.18 to about 0.8, or about 0.18 to about 0.5. The present method allows for the bulk or mass synthesis of graphene of excellent purity. For the preferred purpose of making graphene nanosheet microparticles in the desired size range herein, the ratio of oxidant to carbon-containing material is preferably about 0.2 to about 0.5, with about 0.3, 0.35, or 0.4 being particularly preferred ratios. Preferred microparticles of pure graphene range in size from about 20 to about 500 nm, with a target size range of about 150 nm + / - 20 nm. Notably, in the biosensor of the present disclosure, it is not necessary that the resulting microparticles are monodisperse. Rather, polydisperse graphene microparticle mixtures can be easily used to prepare biosensors. Indeed, light scattering experiments show that graphene aggregates are characterized by a superaggregate fractal morphology with a fractal dimension of Df = 2.5 ± 0.1 at the micron scale composed of smaller aggregates with a fractal dimension of Df = 1.8 ± 0.1. This behavior has not been observed before for metal, metal oxide, metal / metal oxide, or semiconductor particles in (nano)biosensors.

[0041]

[0129] An alternative approach to synthesizing pure graphene includes flash graphene (PCT / US2019 / 047967, filed August 23, 2019, WIPO publication WO2020 / 051000, incorporated herein by reference) which uses flash Joule heating of various carbon-based materials or other carbon sources, such as coal, petroleum coke, biochar, carbon black, food waste, rubber tires, and mixed plastic waste, to convert the materials into graphene. The carbon source is lightly compressed in a reaction vessel between two electrodes, and a high voltage discharge from a capacitor bank brings the carbon source material in the reaction vessel to at least 3000 K in less than 100 Ms. This process converts the amorphous carbon in the carbon source into flash graphene. The yield in this method is highly dependent on the carbon content of the starting material. In some embodiments, the carbon source material may be mixed with carbon black or another similar conductive material to improve the electrical conductivity of the material. In some embodiments, the flash graphene has an average particle size of less than 20 nm. In some embodiments, flash graphene is produced in the form of larger but thin sheets with an average size of 0.5-1.2 μm. Such thin sheets may be suitable for alternative sensors in which single-layer graphene nanosheets are deposited on a solid surface instead of being used in particulate form.

[0130] The pure graphene resulting from these new synthetic processes can take a variety of morphologies, but is preferably in the form of branched fractal aggregates, nanosheets, crystalline flakes, nanoplatelets and platelet chains as single or multilayer graphene, and can generally be characterized macroscopically as a fluffy or fuzzy black powder or particulate material of high purity (≧98.5% carbon).

[0131] The microparticles may be observed as thin interlocking monolayers entangled with each other at overlapping edges, or as more ordered stacks of nanosheets comprising or consisting of 2-3 layers, potentially up to 25 layers, potentially up to 10 layers, for example 2-25 layers, even more preferably about 5 to about 10 layers (with overall sizes ranging from 20 nm to 500 nm).

[0132] Thus, references to "pure" graphene herein are used specifically to indicate high purity graphene produced by high temperature (e.g., ∼>3000K) conversion of a carbon source into graphene (e.g., rapid heating or combustion of amorphous carbon into exploded graphene, flash graphene, etc.) as compared to graphene made via organic synthesis, chemical vapor deposition, or exfoliation from graphite. In other words, pure graphene is preferably essentially free of graphite or graphite oxide. Pure graphene is therefore highly pure, meaning essentially free of foreign matter and impurities (less than 0.5% w / w, preferably less than 0.1% w / w) and has a carbon content of at least about 98.5%, preferably at least 99% (conversely, an oxygen content of less than 1%). A discussion of detection of exploded graphene using transmission electron microscopy (TEM) is provided in Example 21 and associated Figures 19A and 19B, which are exemplary TEM images of pure exploded graphene.

[0133] In certain embodiments, for biosensors based on pure graphene nanosheet particles and associated core particles, the material comprises exploded graphene (preferably 0.25, 0.30, or 0.35).

[0134] In some most preferred embodiments, the graphene nanosheet particulates comprise aggregates of graphene in a fractal morphology.

[0042]

[0135] The term "fractal" as used herein with reference to an object refers to an object that exhibits the property known as self-similarity, i.e., a geometric shape that can be reduced to smaller parts, with each smaller part being a reduced copy of the whole. Fractal dimension is a statistic that describes how a fractal appears to fill space.

[17]

[0136] Thus, typically, stacked few-layer graphene features with fractal morphology have a fractal dimension between Df=2.5±0.3 (upper limit) and Df=1.8±0.4 (lower limit), as understood by those skilled in the art. [8] (see also Example 1).

[0137] The fractal nature of graphene versus other nanomaterials used in biosensors can be confirmed by light scattering techniques such as SEM (scanning electron microscopy).

[18] and further techniques discernible by those skilled in the art such as light scattering.

[19] (see also Example 1).

[0138] In the graphene core particles described herein, two or more graphene nanosheets are coated with a coating layer of organic and / or inorganic material. Thus, to enable coating, the graphene nanosheets are functionalized or derivatized to present functional groups on the surface that can bind to corresponding functional groups presented on the organic and / or inorganic material to enable the formation of the coating layer.

[0139] The term "functional group" as used herein refers to a particular group of atoms within a molecular structure that participates in the characteristic chemical reactions of that structure. Exemplary functional groups include hydrocarbons, double or triple bond containing groups, halogen containing groups, oxygen containing groups, nitrogen containing groups, and phosphorus and sulfur containing groups, all of which can be identified by one of ordinary skill in the art.

[0140] The term "corresponding" when used in reference to an entity, such as a functional group, identifies two or more entities that are capable of reacting with one another under appropriate conditions. Typically, the reaction between a corresponding moiety and a particular functional group results in the bonding of the two entities.

[0043]

[0141] The terms "bond", "bonding", and "conjugation" as used herein refer to an attractive interaction between two elements that results in a stable association of elements that are in close proximity to one another. When each element is contained in a molecule, the result of the bond is typically the formation of a molecular complex. An attractive interaction in the sense of this disclosure includes both non-covalent and covalent bonds. A covalent bond refers to a form of chemical bond characterized by the sharing of electron pairs between atoms or between an atom and another covalent bond. For example, the attractive-repulsive stable forces formed between atoms when they share electrons are known as covalent bonds. Covalent bonds include many types of interactions including σ bonds, π bonds, metal-nonmetal bonds, agostic interactions, and three-center two-electron bonds. Non-covalent bonds as used herein refer to a type of chemical bond, such as protein-protein interactions, that does not involve the sharing of electron pairs, but rather a more diffuse variation of electromagnetic interactions. Non-covalent bonds include ionic bonds, hydrophobic interactions, electrostatic interactions, hydrogen bonds, and dipole-dipole bonds. Electrostatic interactions include associations between two oppositely charged entities.

[0044]

[0142] Exemplary pairing functional groups and corresponding coupling chemistries are shown in schemes (I)-(IX) below.

[0045] [ka]

[0046] [ka]

[0047] [ka] Further pairs of corresponding functional groups within the meaning of the present disclosure can be identified by one of skill in the art.

[0048]

[0143] In the embodiments described herein, the pure graphene nanosheet particulates obtained by the methods described herein can be functionalized with suitable functional groups as described herein to facilitate the preparation of derivative compounds suitable for use as core particles in biosensors. Graphene can be functionalized using chemical modification of organic groups by covalent functionalization. Another approach involves the Fenton oxidation process, which is described in detail in PCT / US2020 / 038055, filed June 17, 2020, which is incorporated herein by reference. In this process, the surface of stacked graphene is oxidized utilizing ferrous sulfate and hydrogen peroxide as oxidizing agents, resulting in >95% carboxylic acid functional groups on the surface. All other possible functional groups, such as hydroxides, aldehydes, ketones, or oxiranes, are present at <5%.

[0049]

[0144] The method generally involves reacting pure graphene microparticles with hydrogen peroxide in an aqueous reaction solution of low pH (<5.0) in the presence of an iron source. The reaction solution is stirred or agitated for a period of time to allow hydroperoxyl radicals generated in the reaction solution to react with the graphene microparticles to oxidize the outer surface of the pure graphene microparticles in solution and produce graphene / graphene oxide microparticles. The resulting graphene / graphene oxide microparticles contain a graphene core with a thin graphene oxide surface coating or shell that can be readily modified via a variety of reactions.

[0050]

[0145] In certain embodiments, preferred graphene derivatives with a high density of surface -COOH groups, referred to herein as "carboxygraphene", can be synthesized using pure graphene and surface functionalization based on nitrene cycloaddition resulting in a stable aziran anchor. In a specific process, pure graphene nanoparticles are dispersed at room temperature in a suitable organic polar solvent system such as anhydrous dimethylformamide (DMF), dimethylacetamide (DMA), dimethylsulfoxide (DMSO), acetone, acetonitrile, or chloroform. After dispersion is complete, a carboxylic acid with a primary or secondary halogen (e.g., chloroacetic acid, 3-iodopropionic acid, 4-bromobutyric acid, 4-bromovaleric acid, 5-bromovaleric acid, etc.) is added, followed by anhydrous hydrazoic acid, or its azide derivative, such as anhydrous sodium azide (NaN3), lithium azide, and / or potassium azide. The temperature of the reaction solution is then slowly increased (about 1°C / min) to about 80°C. Between 20°C and 40°C, a nucleophilic substitution reaction (SN) occurs, forming an organic azide and a solvent-soluble sodium halide. The organic azide releases dinitrogen (N2) to form a nitrene intermediate at temperatures above about 50°C. Nitrenes feature six electrons instead of eight in the nitrogen outer shell. This reactive intermediate undergoes cycloaddition with (S)-amines. PP forms double bonds at the surface of the graphene honeycomb lattice to form stable azirane anchors (three-membered CNC rings). The azirane cycloaddition offers the opportunity to add a tuned amount of carboxylic acid to the surface of graphene without compromising the optical and electrical properties of the graphene itself. In this case, a high density of carboxylic acid groups can be added throughout the surface of the graphene nanosheet particulates for further functionalization and / or interaction with water-soluble polymer coatings (see Examples 2-9).

[0051]

[0146] In certain embodiments, further functional modifications of graphene can be described to allow further reactions and formation of coating layers according to the present disclosure. In this context, although aliphatic bonds are used here for functionalization, aromatic reactions for chemical amination of graphene surfaces are also described in the literature (

[20] , incorporated herein by reference) (Example 10).

[0147] Furthermore, as will be understood by one of skill in the art upon reading this disclosure, instead of or in addition to the above-mentioned functionalizations, further modifications can be made to reduce the surface charge of graphene, making it suitable for binding cationic polymers.

[0052]

[0148] In the graphene core particles described herein, the graphene nanosheets are coated with a coating layer of organic and / or inorganic material.

[0149] The term "coating layer" as used herein refers to a sheet, amount, or thickness of a material that covers a surface or body. In particular, a coating layer in the sense of the present disclosure refers to a thickness of organic and / or inorganic material that covers the surface of a graphene particle. In the graphene core particles of the present disclosure, the coating layer has two main functions: a) to enable the dispersion of graphene in aqueous buffers, and b) to maintain the distance of the attached detectable disclosed moieties at less than 20 nm to facilitate effective quenching in their tethered state.

[0150] In particular, in the embodiments described herein, a coating layer of hydrophilic organic and / or inorganic compounds having a solubility in water of 1% by weight at 25° C. is applied.

[0053]

[0151] As used herein, the term "organic compound" refers to any chemical compound that contains carbon-hydrogen bonds and is capable of promoting and / or accepting hydrogen bonds from water. All or a portion of the hydrogen atoms in an organic compound may be replaced by other atoms.

[0152] The term "inorganic compound" as used herein refers to a chemical compound that lacks C-H bonds and is typically characterized by at least one element heavier than fluorine.

[0153] In particular, organic and / or inorganic compounds suitable for providing the biosensors described herein have a solubility in water of at least 10 grams / liter HO and can be covalently bonded to the graphene described herein or can be electrostatically stable bound to graphene in water, as will be understood by one of skill in the art.

[0154] In certain embodiments, organic and / or inorganic compounds suitable for providing the biosensors described herein are characterized by a consensus logP (or ClogP)<0.

[0155] The ClogP value in the sense of the present disclosure refers to the logarithm of its partition coefficient between n-octanol and water, log(Coctanol / Cwater), as known to those skilled in the art. High lipophilicity corresponds to high ClogP values. The organic molecules of the coatings of the present disclosure can be composed of a combination of moieties and / or substituents such that there is a specific ClogP value, as will be understood by those skilled in the art upon reading this disclosure.

[0156] Coating materials according to the present disclosure are expected to have a ClogP in the range of 1 to -2.5, preferably 0 to -2.

[0157] In some embodiments, the inorganic compounds include mesoporous silica, mesoporous silazane, aluminum oxide, tin oxide, titanium dioxide, zirconium dioxide, and oxides of lanthanides. Amine precursors (e.g., Si(NH-CH3)4; Si(O-CH2-CH3)3(CH2-CH2-CH2-NH2); M(O-CH2-CH3)4 (M=Si, Sn, Ti, Zn); or M(O-CH2-CH3)3 (M=Al or lanthanide(III) cations)) react with hydroxyl groups, carboxylic acids, or oxirane rings on the surface of graphene or chemically modified graphene to form stable O-metal bonds. This is followed by hydrolysis of alkoxy, alkoxy-amine, and amine bonds around the graphene-bound metal to yield semiconductor oxide and metal oxide layers surrounding the graphene.

[21]

[0158] In particular, in some embodiments, the inorganic compound can be mesoporous silica, which is a form of silica with pores of 2-50 nm in diameter. Mesoporous silica can be prepared, for example, using starting materials of tetraethyl orthosilicate (TEOS) or (3-mercaptopropyl)trimethoxysilane (often abbreviated as MPTMS). In an exemplary process, the silica precursor is stirred in a tetrahydrofuran / water mixture (THF / H2O: 99:1-95:5 wt%) at room temperature for 24 hours, followed by centrifugation at 5,000 RPM for 10 minutes, redispersed in H2O, and subsequently collected by centrifugation (5,000 RPM for 15 minutes). The thickness of the mesoporous silica layer around the (stacked) graphene is determined by the mass ratio of TEOS or MPTMS to graphene (0.001 / 1.0-0.1 / 1), as will be understood by those skilled in the art.

[0054]

[0159] In embodiments where the inorganic compound is mesoporous silica, functionalization of the silica surface featuring polar Si-OH groups (silanols) can be achieved, for example, by one of the following: - Silyl ether formation: Si-OH+XR → Si-O-R+HX (X=halogen), followed by organic chemistry. To do so, the organic radical R gas must contain a polar functional group. - A carboxylic acid ester group at the C-terminus of the peptide sequence or in its side chain is tethered to an amine group contained in the coating by a stable amide bond. - reacting the mesoporous silica layer (or metal oxide layer) around the graphene with SiCl4, SiHCl3, SiH2Cl2 or Si(CH3)2Cl2, followed by chemisorption of the N-terminus of a peptide to the Si-Cl group on the surface, which can also be achieved by reacting polar hydroxyl, thiol, or carboxylic acid groups. - Polar Si-Cl groups on the surface can react with NaN3 (sodium azide) to form silicon-azides, which undergo a click reaction.

[0055]

[0160] In some embodiments, the organic compound includes an aliphatic amine, an aromatic amine, an oligoethylene glycol, an aliphatic oligoamine, an ethylene oligoimine, an aliphatic carboxylic acid, an aromatic carboxylic acid, an aliphatic alcohol, an aliphatic sulfonic acid, an aromatic sulfonic acid, and combinations thereof.

[0056]

[0161] In some embodiments, the inorganic and / or organic compounds forming the coating layer include one or more polymers. As used herein, the term "polymer" refers to a substance or material consisting of very large molecules or macromolecules composed of many repeating subunits. Polymers can be organic or inorganic, synthetic and natural, and are usually made through the polymerization of many small molecules known as monomers. As will be appreciated by those skilled in the art, their resulting large molecular weight compared to small molecule compounds results in unique physical properties including toughness, high elasticity, viscoelasticity, and a tendency to form amorphous and semi-crystalline structures rather than crystals.

[22] )

[0162] In one or more embodiments, the coating organic polymer has the following formula (I):

[0057] [ka] (In the formula, M1 to Mm are polymerizable monomer moieties formed by the same or different polymerizable organic monomers, m is in the range of 1 to 10, and y1, y2 to ym are each independently 1 to 1,000.) It can be expressed as:

[0163] In particular, exemplary polymerizable organic monomers include aziridine propylene oxide, ethylene glycol, acrylic acid, methacrylic acid, 2-hydroxyethyl methacrylate, methacrylamide, N-iso-propylacrylamide, 2-hydroxypropyl methacrylate, N-vinylpyrrolidone, 2-vinylpyridine, 2-vinylpyridine N-oxide, 2-ethyl-2-oxazoline.

[0058]

[0164] Thus, in one or more embodiments, one or more water-soluble organic polymers can then be added to the surface of the graphene derivative (e.g., carboxygraphene). Examples of suitable water-soluble polymers of formula (I) include polyethyleneimine, polycaprolactone, polyethylene glycol, polyvinyl alcohol, polyvinylpyrrolidone, (meth)acrylate and (meth)acrylamide polymers, polystyrene-carboxylic acid, polystyrene-amine, and natural biopolymers (e.g., dextran, pullulan, chitosan, alginate, cellulose, and hyaluronic acid), and mixtures or copolymers thereof.

[0165] In certain embodiments, the polymer comprises or consists of homopolymers such as polyethyleneimine, polycaprolactone, polyvinyl alcohol, polyglycolate, polyvinylpyrrolidone, (meth)acrylate and (meth)acrylamide polymers, polystyrene-carboxylic acid, polystyrene-amine, polystyrene-sulfonic acid, dextran, pullulan, chitosan, alginate, cellulose, and hyaluronic acid, as well as mixtures or copolymers thereof.

[0059]

[0166] In some embodiments, the polymer comprises or consists of a block copolymer. In these embodiments, when a block copolymer is used, the hydrophobic polymer (e.g., polystyrene, polyisobutylene, polyvinyl chloride, polyethylene, polypropylene, and more) is selected so that the block copolymer has a consensus logP<0, or a logP>1.0×10 per liter of HO. 3 They can be components of block copolymers, as long as they are characterized by a solubility in water of 100 g.

[23] Hydrophobic polymers are expected to be adsorbed onto the surface of pure graphene, while their hydrophilic components mediate water dispersibility. In some of these embodiments, the surface charge of graphene is positive (zeta potential = +60 mV). [1,8] This allows for the combination of hydrophobic and charge attraction when negatively charged polymers such as polystyrene sulfonate are used in block copolymers of polystyrene and additional organic copolymers identifiable by those skilled in the art.

[0167] In certain embodiments where a hydrophobic-hydrophilic block copolymer is used, the block copolymer is dissolved in a solvent that disperses graphene well (e.g., dimethylformamide (DMF)). With continued sonication, HO is added to the mixture to bond the hydrophobic end of the block copolymer to the graphene. This bond is strengthened due to the presence of negatively charged groups in the hydrophobic-hydrophilic block copolymer, as will be appreciated by those skilled in the art.

[0060]

[0168] In certain embodiments, preferred organic polymers include one or more of polyethyleneimine, polycaprolactone, polyethylene glycol, polyvinyl alcohol, polyvinylpyrrolidone, (meth)acrylate and (meth)acrylamide polymers, and polystyrene-carboxylic acid and polystyrene-amine. Other preferred coatings are chemically modified oligoethylene glycols, ethylene oligoimines, and starburst dendrimers.

[0169] In some embodiments, graphene particles can be coated with a monolayer of water-soluble organic molecules, such as oligoethylene glycol, which can be tethered to the surface of the graphene (see Example 32).

[0170] Note that all carbohydrates can be aminated at various positions.

[0061]

[0171] In some embodiments, the graphene particles can be coated with an inorganic water-soluble shell (e.g., a mesoporous silica nanolayer). Mesoporous silica, mesoporous aminosilica, and titanium dioxide are preferred.

[0172] In the graphene core particles of the present disclosure, one or more organic and / or inorganic compounds react with functional groups (e.g., carboxyl groups, see Examples 3-9) present on the surface of the graphene nanosheets to form a thin, dense layer of polymer (as opposed to a thick layer or halo) around the graphene aggregates (see Examples 30, 32, 35).

[24]

[0173] In an embodiment of the present disclosure, it has been surprisingly found that graphene core particles comprising two or more pure graphene nanosheets coated with a coating layer of organic and / or inorganic compounds having a solubility in water of 1% by weight at 25° C. are stable in aqueous solution and capable of attaching a detectable moiety specific for a target biomarker.

[0174] Surprisingly, it has been found that graphene particles with the above characteristics exhibit a stability in aqueous solution that may exceed 20 or even 30 days. Moreover, it has been found that possible settling of the graphene particles so coated, depending on the concentration as will be appreciated by the skilled person, can be countered by dispersing the particles, for example by sonication, so that a solution containing more than 95% of the particles can be obtained.

[0175] In particular, the biosensor as described is chemically stable and physically stable in the buffer suspension as defined by a decrease in optical absorbance of the detectable moiety in the buffer suspension of no more than 20%, preferably no more than 10%, and more preferably no more than 1% over a period of 30 days.

[0176] As used herein, the terms "stable" and "stability" refer to chemical stability as well as colloidal stability.

[0177] The term "chemical stability" as used herein refers to the preservation of the chemical identity of the biosensor. As one skilled in the art will appreciate, the biosensor described herein includes chemical bonds that connect each component of the biosensor together, including the graphene, the coating material, the peptide, and the detectable moiety. It should further be understood that each of the graphene, the coating material, the peptide, and the detectable moiety includes chemical bonds that connect the atoms to each other to form the graphene, the coating material, the peptide, and the detectable moiety. Preservation of the chemical identity of the biosensor means that none of the chemical bonds that make up the biosensor are broken and no new chemical bonds are formed. Such chemical integrity can be confirmed by measurements including, but not limited to, elemental analysis, UV-vis absorption spectroscopy, magnetic resonance spectroscopy, Raman spectroscopy, IR spectroscopy, and fluorescence spectroscopy.

[0178] The term "colloidal stability" as used herein refers to the preservation of the physical state of the colloidal suspension of the biosensor. Colloidal stability depends on several types of interactions, including van der Waals and electrostatic interactions (classical Derjaguin-Landau-Verwey-Overbeek (DLVO) theory), steric interactions (e.g., polymer adsorption), and hydrophobic effects. Electrophoretic light scattering (ELS) is a common technique used to evaluate the likelihood that a dispersion will remain stable. ELS allows the measurement of the zeta potential of the dispersion, which provides information about the electrostatic interactions and, by extrapolation, the tendency to aggregate. The zeta potential is considered to be a reliable indicator of dispersion stability, although several parameters such as steric effects, sedimentation, or hydrophobic effects also have a strong influence.

[0062]

[0179] In certain embodiments, the core graphene particles and related biosensors described herein are chemically and physically stable in buffer suspension as defined by a decrease in optical absorbance of the detectable moiety in the buffer suspension of no more than 20%, preferably no more than 10%, and more preferably no more than 1% over a period of 30 days.

[0180] Thus, in the embodiments described herein, stable graphene core particles of the present disclosure refer to graphene particles that, when placed in suspension in an aqueous solution, result in a solution in which at least 95% of the particles remain in suspension and have a change in colloidal stability of no more than -24% in OD650.

[0181] Notably, data are obtained in the subrange reflecting a change in colloidal stability of 26% or less. Sedimentation of 22% and 25% with an average of 24% reflects the worst performance of the four lots of nanobiosensors according to the present disclosure. In one representative embodiment, graphene stability at 60 minutes measured by OD650 showed a 9% and 10% decrease in absolute colloidal stability for the NE and MMP15 nanobiosensors (see lot 4 in Example 40). Thus, the graphene biosensors of the present disclosure according to preferred embodiments are expected to show less than a 10% decrease in colloidal stability in aqueous solutions.

[0182] In particular, in preferred embodiments described herein, the stable graphene core particles of the present disclosure have a molecular weight of at least 2.40±0.05×10 -5 mol / g, preferably up to 6.0±0.5×10 -4 It comprises one or more organic and / or inorganic compounds reacted to form a coating layer 1-20 nm thick with a packing density of mol / g.

[0183] Thus, in preferred stable graphene core particles of the present disclosure, the minimum geometric extent of the attached coating layer is 0.45 nm and can be up to 20 nm, with the coating layer covering at least 50%, preferably at least 85%, more preferably at least 90%. Most preferably, a monolayer of polymer is formed around the graphene, preferably completely encapsulating the graphene nanosheet therein. In the most preferred embodiment, the graphene particles have an average size of 10 nm to 5000 nm, preferably 150 to 500 nm, as determined using scanning electron microscopy and digital light scattering measurements.

[0063]

[0184] In such embodiments, the stability of the graphene core particles can be on the order of months and years, with examples of graphene particles and related biosensors being stable in aqueous solutions for greater than 12 months, as would be understood by one of ordinary skill in the art upon reading this disclosure.

[0064]

[0185] The determination of the surface coverage is carried out by comparing BET surfaces. The Brunauer-Emmett-Teller (BET) theory aims to explain the physical adsorption of gas molecules on solid surfaces and serves as the basis of an important analytical technique for the measurement of the specific surface area of ​​materials. It measures the adsorption of N2 on graphene at 77 K. The result of this measurement is the size of the accessible surface (here: 150 ± 40 m 2 / g). From titration experiments with polar head groups (acid or base) the average density of surface groups is determined. Dynamic light scattering is used to measure the size of the attached polymer as well as the size of the graphene + layer + polymer. Depending on the surface coating and the chemical nature of the polymer, the zeta potential of the surface changes continuously until complete surface coverage is achieved.

[0065]

[0186] In certain embodiments described herein, the graphene core particles of the present disclosure are combined with a detectable moiety to provide the graphene biosensors described herein. In particular, the graphene biosensors described herein include a detectable moiety attached to the graphene core particle via a peptide bond that includes a recognition sequence specific for a target biomarker.

[0066]

[0187] The term "biomarker" as used herein refers to a biological molecule found in a biological environment that is associated with a biological event. In particular, a biomarker may be associated with the occurrence of a physiological event (a biological event associated with the normal functioning of organisms and their parts) or an alteration of a physiological state, in particular the occurrence of an indication of a normal or abnormal process or condition.

[0188] As used herein, the term "condition", when used herein with respect to an organism, refers to a physical condition of the body of an organism (either as a whole or as one or more of its parts) that does not conform to a standard physical condition associated with the state of complete physical, mental and social health of the individual. Conditions described herein include, but are not limited to, disorders and diseases, where the term "disorder" refers to a condition of a living individual associated with an abnormality in the functioning of the body or any of its parts, and the term "disease" refers to a condition of a living individual that impairs the normal functioning of the body or any of its parts, and is typically manifested by characteristic signs and symptoms.

[0189] Thus, in the embodiments described herein, target biomarkers associated with an individual's condition can be selected for diagnostic purposes and / or to see how well the body responds to treatment of the condition.

[0190] The target biomarkers of the present disclosure are also molecules configured to interact with and modify the associated conformational structure of a peptide bond, hi certain embodiments, the target biomarkers are proteins configured for specific interaction with a peptide recognition sequence.

[0067]

[0191] The term "protein" as used herein refers to a polypeptide having secondary, tertiary, and possibly quaternary structure. The secondary, tertiary, and possibly quaternary structures of proteins can occur on a variety of length scales (tenths of Angstroms to nm) and time scales (ns to s), so that in various instances the secondary, tertiary, and possibly quaternary structures are dynamic and not completely rigid.

[0192] The term "polypeptide" as used herein refers to a polymer composed of two or more amino acid monomers and / or analogs thereof, where the moiety formed by the alpha carbon, amine group, and carboxyl group of the amino acid in the polymer forms the backbone of the polymer. The terms "amino acid", "amino acid monomer", or "amino acid residue" as used herein refer to any naturally occurring amino acid, any non-naturally occurring amino acid, and any artificial amino acid (including both D and L optical isomers of all amino acid subsets). In particular, amino acids refer to organic compounds composed of an amine (-NH2) and a carboxylic acid (-COOH) and a side chain specific to each amino acid connected to the alpha carbon. Different amino acids have different side chains and unique characteristics such as charge, polarity, aromaticity, reduction potential, hydrophobicity, and pKa. Amino acids can form polymers through peptide bonds by reaction between the amine group of a first amino acid and the carboxylic acid group of a second amino acid.

[0193] The term "polypeptide" includes amino acid polymers of any length, including full-length proteins, as well as analogs and fragments thereof. Polypeptides provide the primary structure of a protein, where the term "primary structure" of a protein refers to the sequence of amino acids in a polypeptide chain that are covalently linked to form a polypeptide polymer. A protein "sequence" indicates the order of amino acids that form the primary structure. The covalent bonds between amino acids in the primary structure can include peptide bonds or disulfide bonds. A polypeptide in the sense of the present disclosure is usually composed of a linear chain of amino acid residues covalently linked by peptide bonds. The two ends of a linear polypeptide chain, including the terminal residues and adjacent segments, are referred to as the carboxyl terminus (C-terminus) and the amino terminus (N-terminus) based on the nature of the free groups on each end.

[0068]

[0194] Depending on their size, peptides can be classified as oligopeptides (2-20 residues) and polypeptides (>20 residues). Proteins usually consist of polypeptide chains more than 50 residues long.

[25] The average length of a peptide can be estimated at 0.35-0.40 nm per amino acid, depending on the 2D structure of the peptide (alpha-helical or amorphous).

[25] It is noted that peptides forming beta-sheets are not suitable for the design of biosensors due to their extremely slow release kinetics upon enzymatic cleavage. Peptides of 50 amino acids have a length of 17.5-20 nm, depending on their 2D structure. It is also noted that non-natural amino acids can be used in these peptides to immobilize the peptides on the surface of graphene or graphene-bound organic or inorganic shells, or for the attachment of fluorophores (organic dyes or nanostructures).

[0069]

[0195] As used herein, the term "amino acid", "amino acid monomer", or "amino acid residue" refers to an organic compound composed of an amine functional group and a carboxylic acid functional group, together with a side chain specific to each amino acid. In particular, alpha (α)-amino acid refers to an organic compound composed of an amine (-NH2) and a carboxylic acid (-COOH), with a side chain specific to each amino acid attached to the alpha carbon. Different amino acids have different side chains and unique characteristics such as charge, polarity, aromaticity, reduction potential, hydrophobicity, and pKa. Amino acids can be covalently linked to form polymers via peptide bonds by reaction between the amine group of a first amino acid and the carboxylic acid group of a second amino acid. Amino acid in the sense of this disclosure refers to any of the 20 naturally occurring or unnatural amino acids, including both D and L optical isomers.

[0070]

[0196] In a preferred embodiment, the target biomarkers are proteins >50 amino acids in length, such as enzymes and chemokines / cytokines. Some of these enzymes have coenzymes and cofactors that consist of heterocycle-bound metalloproteinases (e.g., all matrix metalloproteinases). Some of these proteins are post-translationally modified and conjugated to sugars or lipids, as will be appreciated by those skilled in the art.

[0197] In further embodiments, the target biomarkers can include many inorganic and organic molecules that can change the conformation of a peptide bond or cleave a peptide bond. The term "conformation" as used herein in relation to a peptide or protein is defined as the protein structure (the three-dimensional arrangement of atoms in a polypeptide) and the spatial arrangement of its constituent atoms that determines the protein's overall shape of the molecule. The term "cleavage" as used herein in relation to compounds and peptides refers to the breaking of a chemical bond and / or a chemical reaction involving the breaking of a chemical bond. Cleavage of a peptide bond usually results in enzymatic hydrolysis of the peptide bond in the bond and the breakdown of the bond into smaller peptide moieties, as understood by those skilled in the art.

[0198] A method for identifying organic and / or inorganic biomarkers configured to interact with and alter the conformation of a peptide bond or cleave a peptide bond, comprising: - computationally modeling the tertiary structure of a peptide bond to provide a computationally modeled peptide bond. - computationally modeling the tertiary structure of the candidate organic or inorganic biomarker to provide a computationally modeled candidate organic or inorganic biomarker. - determining a target site of interaction between said computer-modeled peptide bond and a computer-modeled candidate organic or inorganic biomarker. - determining a change in said computer modeled peptide binding following interaction of candidate organic or inorganic biomarkers at the target site of said interaction. - if the determined alteration is a conformational change in the peptide bond or cleavage of the peptide bond, this is done by selecting the computer modeled peptide bond and an organic or inorganic target biomarker.

[0071]

[0199] Additionally or alternatively, a method for identifying organic and / or inorganic biomarkers configured to interact with peptide bonds, comprising: - contacting the candidate organic and / or inorganic biomarker with the peptide bond for a time and under conditions that allow an interaction between the candidate organic and / or inorganic compound and the peptide bond; and - detecting a change in conformation of the peptide bond and / or cleavage of the peptide bond, which is performed subsequent to the contacting to provide a detection result. - selecting an organic and / or inorganic biomarker if the detection result is a detected change in the conformation of a peptide bond or a detected cleavage of a peptide bond, thus providing an identified organic and / or inorganic biomarker.

[0072]

[0200] The biosensor of the present disclosure can then be configured to detect a target compound by attaching a peptide bond to a detectable moiety and a coating layer of a thickness selected such that the detectable moiety is at an extinction distance of 20 nm or less to the graphene particle after attachment. In particular, if the target compound has a detected change in conformation of the peptide bond that results in an increase in the length of the peptide bond, the coating layer is configured such that in the biosensor provided after attachment, the detectable moiety is at an emission distance after the increase in the length of the peptide bond, as will be understood by those skilled in the art upon reading this disclosure. The functionality of the biosensor so constructed can then be tested, as will be understood by those skilled in the art.

[0073]

[0201] For example, the identification of protein biomarkers and corresponding supramolecular recognition sequences was carried out according to the following procedure. 1) The primary structure of the target was searched from a databank (eg, UniProtKB or Protein Databank). 2) The tertiary structure of the target was determined and then refined using protein structure prediction software such as the GalaxyWEB protein structure prediction cluster developed by Dr. Seok at the Computational Biology Lab, Seoul National University (Korea). 3) The primary structures of monoclonal antibody (MAB) fragments against the targets were retrieved from data sources (e.g., Protein Data Bank, SciFinder, or information provided by antibody vendors). Tertiary structures were generated using Galaxy-WEB. 4) Using the Mobyle platform developed by the Institute Pasteur Biology IT Center, Paris, France, the docking procedure between the target and the antibody chain is simulated, which reveals the "true" epitope of the target. 5) A final "site finder" step is then performed on the Mobyle platform that docks the epitope of the target into the improved structure of an antibody (Ab) fragment. This structure reveals the peptide sequence of the Ab fragment that is actually involved in binding to the target in the example of a protein-protein interaction. F)

[0202] Additionally or alternatively to the exemplary method for identification of protein biomarkers and corresponding supramolecular recognition sequences, a final "site finder" procedure is then performed on the Mobyle platform in which the target protease epitopes are docked into the improved structure of the protease enzyme active site, which reveals the peptide sequence of the active site that is actually involved in binding to the target.

[0203] In addition to or alternatively to the exemplary method for the identification of protein biomarkers and corresponding supramolecular recognition sequences, cleavage sites and sequences for protease targeting can be identified from available sites such as MEROPS (peptidase database).

[0204] In an exemplary method for identifying a protein biomarker and the corresponding supramolecular recognition sequence, if the supramolecular recognition sequence is linear, it is synthesized and used as the recognition sequence of the nanosensor. The LOD of the obtained nanobiosensor is at least 10 -14 If not M, the in silico procedure was repeated using structural information from another mAb.

[0074]

[0205] In some exemplary embodiments, many organic molecules can also interact with proteins, such as enzymes, which can interact with peptides and change their conformation. In this regard, all enzyme inhibitors can change the conformation of the protein to which they bind. Exemplary enzyme inhibitors include the non-peptidic HIV-1 protease inhibitor tipranavir, diisopropylfluorophosphate (DFP), the anticancer drug methotrexate, and penicillin G as an inhibitor of Streptomyces transpeptidase.

[0075]

[0206] In some exemplary embodiments, the interaction between the target biomarker and the peptide bond may result in cleavage of the peptide bond. In particular, in certain embodiments, the target biomarker comprises a protease. Exemplary proteases include serine proteases, cysteine, threonine proteases, aspartic acid proteases, glutamic acid proteases, metalloproteases, and aspartic acid peptide lyases. In general, all 553 known proteases in the human genome (21 aspartic acid proteases, 143 cysteine ​​proteases, 186 metalloproteases, 176 serine proteases, and 27 threonine proteases), as well as their analogs in rodent models, can be detected using the biosensor of the present disclosure, as will be appreciated by those skilled in the art.

[26]

[0207] In certain embodiments, the target biomarkers include enzymes that perform post-translational modifications of peptides, which change their biophysical properties (dynamics, effective length, etc.). Examples are arginase (which converts arginine to ornithine) and the whole group of enzymes that attach or remove any chemical group to the peptide's size chain. Examples include enzymes capable of (de)phosphorylation (kinases, phosphatases), glycosylation enzymes (N-glycosylation, N-glycosylation, glycation, C-glycosylation, and phosphoglycation), ubiquitination, S-nitrosylation, methylation, N-acetylation, and lipidation (C-terminal glycosylphosphatidylinositol (GPI) anchor, N-terminal myristoylation, S-myristoylation, S-prenylation).

[0076]

[0208] In certain embodiments, the target biomarkers include proteins (e.g., cytokines / chemokines) that can bind to the tailored oligopeptides. The binding event changes the biophysical properties of the peptide (dynamics, effective length, etc.). Exemplary biomarkers that can be detected include all cytokines, chemokines, signal peptides (e.g., pro-inflammatory factors, anti-inflammatory factors, growth factors), and hormones are of interest as will be appreciated by those skilled in the art.

[0077]

[0209] In the embodiments described herein, the peptide bonds that are part of the detectable component of the graphene biosensor of the present disclosure are selected to specifically bind to a target biomarker of interest, as will be understood by one of skill in the art.

[0210] The terms "specific", "specifically" or "specificity" as used herein with respect to the binding of a first molecule to a second molecule refer to substantially less or no recognition, contact and formation of stable complexes between the first molecule and the second molecule, and between each of the first molecule and the second molecule and other molecules that may be present. Exemplary specific bindings are antibody-antigen interactions, cell receptor-ligand interactions, polynucleotide hybridization, enzyme-substrate interactions, and further interactions identifiable by one of skill in the art. The terms "specific", "specifically" or "specificity" as used herein with respect to computer-assisted tools such as software refer to tools that can identify a target sequence (such as one of the markers described herein) among a group of sequences in a database, for example, after alignment of the target sequence with a sequence in a database. Exemplary software configured to specifically detect a target sequence include Primer-3, PerlPrimer, and PrimerBlast. - Simultaneously measure multiple analytes in a single experiment.

[0078]

[0211] In some embodiments, the recognition sequence can be a supramolecular recognition sequence or a recognition sequence for a target protein, which means that the binding recognition is specific to the target protein (i.e., contains a selective binding site).It is therefore understood that the recognition sequence avoids non-specific binding motifs.The recognition sequences described herein are preferably cleavable for rapid diagnosis.

[0079]

[0212] In the graphene nanobiosensor embodiments of the present disclosure, the peptide bond can include any of a variety of recognition sequences or recognition sequences for the biomarker of interest, meaning that the binding sequence is specific for the target biomarker (i.e., contains a selective binding and / or cleavage site for the target biomarker). It is therefore understood that the linking sequence avoids non-specific binding motifs. The peptide bond is usually a short linear oligopeptide that places the detectable moiety within the appropriate vicinity of the graphene carrier particle for quenching. In certain embodiments, the length of the peptide bond can be less than 100 amino acid residues, preferably less than 75 amino acid residues, more preferably 50 amino acid residues or less. In the most preferred embodiments, the peptide bond length is shorter, less than 50 amino acid residues, more preferably less than 30 amino acid residues, and even more preferably 20 amino acid residues or less.

[0080]

[0213] For example, in the graphene biosensor of the present disclosure, the peptide bond can range from 4 to 50 amino acid residues, more preferably 4 to 30 amino acid residues, and even more preferably 10 to 20 amino acid residues. As used herein, reference to "specific interaction" or "specificity" in the context of recognition intended to distinguish recognition sequences from non-specific binding or reactions between molecules means that the set of specific target biomarkers with which an oligopeptide sequence may interact is limited, and in some cases even exclusive, such that binding to or enzymatic cleavage of any other molecule other than the target biomarker does not occur with any appreciable rate or frequency.

[0214] In particular, in the embodiments described herein, the specificity of the peptide bond for a target biomarker results in minimal interaction of the peptide bond with biomarkers other than the particular biomarker targeted by the peptide bond, as will be understood by one of skill in the art.

[0081]

[0215] Biosensors can be configured to target a wide variety of biomarkers depending on the recognition sequence selected. Examples include numerous enzymes, including proteases, kinases, arginases, cytokines / chemokines, dioxygenases (e.g., indoleamine 2,3-dioxygenase 1, and / or tryptophan 2,3-dioxygenase), esterases, etc., which can then be correlated with a particular health condition in the sample being tested. For example, such biomarkers can be indicative of cancer or pre-cancerous cellular activity, bacterial activity, inflammation, etc., and are known in the literature. In one or more embodiments, the recognition sequence comprises, consists essentially of, or consists of a "recognition sequence," which refers to an enzyme substrate (peptide sequence) that undergoes enzymatic cleavage in the presence of a target analyte (e.g., a protease, esterase, etc.). Such recognition sequences are described, for example, in U.S. Patent Nos. 8,969,027 and 9,216,154, and U.S. Publication No. 2017 / 0219548, each of which is incorporated herein by reference to the extent not inconsistent with this disclosure. Relevant recognition sequences are provided in the tables of this disclosure. The guiding paradigm is that for any protease, a recognition sequence can be designed in silico that is cleaved faster by its target protease than by any other protease.

[0082]

[0216] In one or more embodiments, the recognition sequence is an enzymatic post-translational modification, such as described in International Publication WO 2016 / 149637, filed March 18, 2016, which is incorporated by reference herein to the extent not inconsistent with the present disclosure. In this embodiment, arginine in GR7G is converted to ornithine GO7G, thus changing the kinetics and geometric extension of the peptide, which allows for fluorescent detection in an optical Fe / Fe3O4 nanobiosensor. Other post-translational enzymes have been detected by areindeolamine-2,3-dioxygenase and tryptophan 2,3-dioxygenase, as will be appreciated by those skilled in the art.

[0083]

[0217] In the presence of a target biomarker, such as a target enzyme, the enzyme modifies (without cleaving) the recognition sequence, more specifically, modifies both the primary structure (amino acid residues and metabolites) and the secondary structure of the recognition sequence. As used herein, such terms "modification" or "post-translational modification" refer to the conversion or transformation of amino acid residues (and especially side chains) in the substrate sequence into different forms and / or different residues. This in turn extends, "unfolds" or "unfolds" the secondary structure, and / or increases and / or decreases the mobility of the recognition sequence. In one or more embodiments, the recognition sequence is a supramolecular recognition sequence for detecting physical binding without chemical modification or enzymatic cleavage. In particular, the target protein linearly binds to the supramolecular recognition sequence such that the initial folded secondary structure, such as an alpha helix and / or beta sheet structure, is modified and linearly extends or unfolds. In each case, the interaction of the target analyte (e.g., protein, enzyme, etc.) with the recognition sequence causes a detectable change in the biosensor, indicative of the presence of the target analyte.

[0084]

[0218] In one or more embodiments, the recognition sequence comprises, consists essentially of, or consists of a recognition sequence for a biomarker of inflammation, infection, and / or bacterial activity, for example, as described in International Publication WO 2016 / 018798, filed July 27, 2015, which is incorporated by reference herein to the extent not inconsistent with this disclosure. In some of these embodiments, the target biomarker can be an enzyme indicative of inflammation, infection, and / or bacterial activity, such as MMP-8, MMP-9, MMP-11, MMP-14, and neutrophil elastase, as compared to MMP-1, MMP-2, MMP-3, MMP-7, MMP-12, and MMP-13. Other enzyme target biomarkers believed to be indicative, in part, of inflammation, infection, and / or bacterial activity were cathepsin-B, -D, -E, -K, and -L, and urokinase plasminogen activator, as would be understood by one of skill in the art.

[0085]

[0219] In general, enzymes such as proteases and / or esterases are exemplary biomarkers that indicate inflammation, infection, and / or bacterial activity. The recognition sequence is selected to be cleavable by a protease or esterase, either specifically (e.g., with a recognition sequence that is cleavable only by the target protease) or generally (e.g., with a sequence that is cleavable by any protease or esterase). When the bond is cleaved, the particles are released from each other, resulting in a spectral change that can be detected in the system.

[0220] The recognition sequence is usually provided as part of an oligopeptide bond between the detectable moiety and the pure graphene carrier particle. A suitable oligopeptide bond comprises (consists essentially of, or even consists of) the recognition sequence of the target biomarker, typically with a terminal carboxylic acid group (C-terminus) and a terminal amine group (N-terminus). The oligopeptide may also comprise a thiol group at the C-terminus and a carboxylic acid group at the N-terminus. In an embodiment, the oligopeptide linker comprises a hydrophilic region of at least 10 amino acids on the N-terminus side of the recognition sequence and a linking region on the C-terminus side of the recognition sequence, the C-terminal linking region comprising a thiol-reactive group at its terminus. In an embodiment, the C-terminus of the oligopeptide comprises a cysteine ​​residue, lysine, or aspartic acid. In an embodiment, the N-terminal hydrophilic region of the oligopeptide has an excess of positive or negative charges in a ratio of about 1:1. The N-terminal hydrophilic region may also comprise amino acid residues capable of forming hydrogen bonds with each other.

[0086]

[0221] In one embodiment, the C-terminal and N-terminal linking regions can consist of substantially any amino acid sequence that is not cleavable (e.g., is not a recognition sequence): (X)n-[recognition sequence]-(X)m, where X is any amino acid (that does not result in a cleavage sequence in the sequence) and each of n and m is less than 5.

[0222] In certain embodiments, the recognition sequence may include one or more spacer residues at the N- and / or C-terminus. For example, 1-10 amino acids (any amino acid, natural and unnatural, L- and D-, or combinations thereof) may be used as spacers at one or both ends to further extend the length of the oligopeptide chain depending on the detectable moiety selected. Examples include N-terminal sequences such as GAG and C-terminal sequences such as -AG.

[0223] Depending on the target biomarker, a desired recognition sequence can be selected and synthesized, it being understood that a variety of sequences are also available in the literature or can be determined through in silico binding studies.

[0087]

[0224] Exemplary recognition sequences are listed in the table below along with their associated biomarkers. In some cases, proposed breakpoints are indicated with "-". Variants of the listed sequences are also contemplated.

[0088] [Table 1]

[0089] [Table 2]

[0090] [Table 3]

[0091] [Table 4] a monocyte chemoattractant protein-1; b chemokine (CC motif) ligand 20 (CCL20) or liver activation-regulated chemokine (LARC) or macrophage inflammatory protein-3 (MIP3A); c granulocyte colony-stimulating factor; d Interleukin-1-receptor-like type 1; e macrophage inflammatory proteins; fosteoclast-stimulating factor-1; g Metalloproteinase inhibitor 1; h Thymic stromal lymphopoietin.

[0092]

[0225] In one or more embodiments, the nanosensor can be configured with a recognition sequence specific for cytokine detection. In these embodiments, the oligopeptide bond contains a linear supramolecular recognition sequence (i.e., a paratope) for the receptor / binding site of the cytokine of interest. In the presence of the cytokine, the extension of the tether during cytokine binding results in a signal change (e.g., increased fluorescence) from the bound detectable particle, which can be detected. The nanosensor can measure the cytokine concentration. Exemplary supramolecular recognition sequences are listed in Table 2 below.

[0093] [Table 5]

[0094] [Table 6]

[0095] [Table 7]

[0226] a monocyte chemoattractant protein-1; b chemokine (CC motif) ligand 20 (CCL20) or liver activation-regulated chemokine (LARC) or macrophage inflammatory protein-3 (MIP3A); c granulocyte colony-stimulating factor; d Interleukin-1-receptor-like type 1; e macrophage inflammatory proteins; f osteoclast-stimulating factor-1; g Metalloproteinase inhibitor 1; h thymic stromal lymphopoietin; i CD: cluster of differentiation; j ATP-dependent RNA helicase DDX3X (from human bronchial epithelial cells); kalkaline phosphatase, placental type phosphatase PPB1; l arginine tRNA ligase, cytoplasmic; m E3 ubiquitin-protein ligase UBR4 (peripheral airway epithelial cells); * Estimated limit of detection (LOD).

[0227] In some embodiments, the supramolecular recognition sequence can include one or more spacer residues at the N- and / or C-terminus. For example, 1-10 amino acids (any amino acid, natural and unnatural, L- and D-, or combinations thereof) can be used as spacers at one or both ends. Examples include N-terminal sequences such as GAG and C-terminal sequences such as -AG.

[0228] In some embodiments, any other linear peptide sequence of suitable length (e.g., at least 10 amino acid residues) can be used for the supramolecular recognition sequence, except for sequences characterized by consensus motifs. When synthesized on a peptide synthesizer, peptide sequences up to about 25 amino acid residues can be used, while sequences synthesized in organisms (e.g., E. coli) can be up to about 300 amino acid residues long. Any designed sequence should be checked for the presence of cleavage sequences using data banks such as MEROPS.

[0096]

[0229] In one embodiment, peptide-aptamers have also been developed to target CD9, CD63, and CD81, which are commonly accepted surface markers for exosomes. They can bind to exosomes, allowing them to be directly isolated from biological samples collected using nanosensors without prior (ultra)centrifugation. The combined use of CD9, CD63, and CD81 will ensure that virtually all exosomes originating from samples such as airway cells are captured. After treatment with lysis buffer, the cargo of the captured exosomes can be analyzed. The analysis of exosomes represents another existing aspect of the technology. Exosomes originating from small airway epithelial cells and bronchial airway epithelial cells differ significantly in their proteasomes in their outer membrane, including tetraspanin content (CD9, CD63, CD81).

[0230] In certain embodiments, the biosensors of the present disclosure exhibit the flexibility to adapt the underlying nanosensor structure by modifying the particles, oligopeptide bonds, etc. to fit available sensor technology, as well as by using different sensor technologies to detect additional targets. For example, nanosensors can be prepared to detect protease activity, where the graphene core particles of the present disclosure are used in conjunction with peptide bonds and moieties described in U.S. Pat. No. 8,969,027, as will be appreciated by those skilled in the art.

[0097]

[0231] In certain embodiments, enzyme recognition sequences that may be used in a nanosensor in combination with one or more of the above include those in Table 3 below, where the breakpoints are indicated with a "-".

[0098] [Table 8]

[0099] [Table 9]

[0100] [Table 10]

[0232] In certain embodiments, the recognition sequence for a peptide bond can include an N-terminal spacer (eg, GAG, GAA, GAP) and a C-terminal spacer (eg, GA, AG, or EG).

[0101]

[0233] In the graphene biosensors of the present disclosure, peptide bonds are used to attach detectable moieties or labels to the graphene core particles.

[0234] The terms "attach" or "attached" as used herein refer to connecting or uniting by a bond, link, force, or tie to hold two or more components together, and encompasses either direct or indirect attachment, for example, where a first molecule is directly bonded to a second molecule or material, or where one or more intermediate molecules are disposed between the first molecule and the second molecule or material.

[0235] The term "detect" or "detection" as used herein refers to the determination of the presence, existence or fact of a target in a limited portion of space, including but not limited to a sample, a reaction mixture, a molecular complex and a substrate. The term "detect" or "detection" as used herein may include the determination of the chemical and / or biological properties of a target, including but not limited to its ability to interact with and specifically bind to other compounds, its ability to activate another compound, and further properties identifiable by the skilled artisan upon reading this disclosure. Detection may be quantitative or qualitative. Detection is "qualitative" when it refers to, relates to, or involves the identification of the quality or type of a target or signal in terms of its relative abundance relative to another target or signal that is not quantified. Detection is "quantitative" when it refers to, relates to, or involves the measurement of the amount or quantity of a target or signal (also called quantification), including but not limited to any analysis designed to determine the amount or proportion of a target or signal. Quantitative detection within the meaning of this disclosure includes detection that is performed semi-quantitatively, above / below a certain amount of a target biomarker, as will be understood by the skilled artisan.

[0236] The term "detectable moiety" or "label" as used herein refers to a detectable molecule, including, but not limited to, a radioisotope, a fluorophore, a chemiluminescent dye, a chromophore, an enzyme, an enzyme substrate, an enzyme cofactor, an enzyme inhibitor, a dye, a metal ion, a particle, a metal sol, a ligand (such as biotin, avidin, streptavidin, or a hapten), etc. As a result, the term "label signal" as used herein refers to a signal emitted from a label that allows for detection of the label, including, but not limited to, radioactivity, fluorescence, chemiluminescence, production of a compound as a result of an enzymatic reaction, etc.

[0237] In the embodiments described herein, the detectable moiety is capable of emitting a fluorescent signal, the term fluorescent signal referring to a longer wavelength light signal emitted by a compound that can be electronically excited by a shorter wavelength light source.

[0238] Exemplary detectable labels, which are compounds that can be excited by a light source to emit a fluorescent signal, include detectable particles that produce a detectable signal (e.g., optical or spectroscopic), such as fluorescence or a color change that can be visually perceived or measured using an appropriate instrument. Chromophores / luminophores suitable for use in the assays of the present invention include any organic or inorganic dye, fluorophore, phosphor, light absorbing particle (e.g., Au, Ag, Pt, Pd), combinations thereof, or non-magnetic metallized complexes thereof. Preferably, the selected chromophore / luminophore is smaller than the graphene carrier particles, typically having a particle size (maximum edge-to-edge size, i.e., diameter) of less than about 20 nm.

[0102]

[0239] Suitable organic dyes are selected from the group consisting of coumarin, pyrene, cyanine, benzene, N-methylcarbazole, erythrosine B, N-acetyl-L-tryptophanamide, 2,5-diphenyloxazole, rubrene, and N-(3-sulfopropyl)acridinium. Specific examples of preferred coumarins include 7-aminocoumarin, 7-dialkylaminocoumarin, and coumarin 153. Examples of preferred benzenes include 1,4-bis(5-phenyloxazol-2-yl)benzene and 1,4-diphenylbenzene. Examples of preferred cyanines include oxacyanine, thiacyanine, indocyanine, merocyanine, and carbocyanine. Other exemplary cyanines include ECL Plus, ECF, C3-oxacyanine, C3-thiacyanine dye (EtOH), C3-thiacyanine dye (PrOH), C5-indocyanine, C5-oxacyanine, C5-thiacyanine, C7-indocyanine, C7-oxacyanine, CypHer5, Dye-33, cyanines (Cy7, Cy7.5, Cy5.0, Cy5.5, Cy3Cy5 ET, Cy3B, Cy3.0, Cy3.5, Cy2), CBQCA, NIR1, NIR2, NIR3, NIR4, NIR820, SNIR1, SNIR2, SNIR4, merocyanine 540, pinacyanol-iodide, 1,1-diethyl-4,4-carbocyanine iodide, Stains All, Dye-1041, or Dye-304, as well as all BODIPY dyes.

[0240] Cyanine dyes can be attached in various configurations using peptide bonds ideally shorter than the Förster radius of the cyanine dye (5-6 nm for Cy3.0 and Cy3.5, 6-7 nm for Cy5.0 and Cy5.5, and about 7 nm for Cy7 and Cy7.5). The maximum length of the tether consisting of 12 or fewer amino acid residues (up to 4 nm) in any spacer (up to about 2.84 nm) and cleavage sequence indicates that cathepsins are preferably linked to Cy5.x and Cy7.x dyes to allow optimal quenching of the tethered cyanine dye, although shorter cleavage sequences (uPA and MMP) are suitable for use with Cy3.x and Cy5.x dyes. For all cyanines, their emission maxima are red-shifted relative to the autofluorescence of human urine. Multiple cyanines can be attached to a single particle to create an oligoplex nanoplatform to measure the activity of up to four enzymes simultaneously. All four dyes can be excited simultaneously in the UVA or blue region of the electromagnetic spectrum, or each dye can be excited individually. All cyanine dyes have excitation maxima blue-shifted by 20-25 nm relative to their emission maxima (typical of fluorescent singlet states). Exemplary emission spectra: NS-Cy3.0 (λex=538, λem=560), NS-Cy5.5 (λex=639, λem=660), NS-Cy7.0 (λex=740, λem=760) and NS-Cy7.5 (λex=808, λem=830).

[0103]

[0241] Suitable inorganic dyes are selected from the group consisting of metallized and non-metallized porphyrins, phthalocyanines, chlorins (e.g., chlorophyll A and B), and metallized chromophores. Preferred porphyrins are selected from the group consisting of tetracarboxy-phenyl-porphyrin (TCPP) and Zn-TCPP. Preferred metallized chromophores are selected from the group consisting of ruthenium polypyridyl complexes, osmium polypyridyl complexes, rhodium polypyridyl complexes, 3-(1-methylbenzimidazol-2-yl)-7-(diethylamino)-coumarin complexes of iridium(III), and 3-(benzothiazol-2-yl)-7-(diethylamino)-coumarin complexes with iridium(III).

[0242] Suitable fluorophores and phosphophores are selected from the group consisting of phosphorescent dyes, fluoresceins, rhodamines (e.g., rhodamine B, rhodamine 6G), and anthracenes (e.g., 9-cyanoanthracene, 9,10-diphenylanthracene, 1-chloro-9,10-bis(phenyl-ethynyl)anthracene).

[0104]

[0243] The broad UV / Vis absorption spectrum of graphene and derivatives allows the attachment of multiple detectable labels, each with a (different) recognition sequence, to target more than one biomarker at a time. To function, there should be no or minimal overlap between the excitation and absorption spectra of the co-bound detectable labels, thus minimizing FRET between particles and / or interference of the respective signals. In principle, any combination of fluorescent dyes can be envisaged, but BODIPY dyes are particularly suitable, since they are characterized by a small Stokes shift (the distance between the maximum of the lowest excitation band and the maximum of the fluorescence band). An example of this strategy is the parallel use of BODIPY FL (505 λex / 513 λem), BODIPY 530550 (534 λex / 554 λem), BODIPY TR (589 λex / 617 λem), and BODIPY 630650 (646 λex / 660 λem), connected via their respective (different) sequences, to independently monitor the activity of four biomarkers on a single biosensor. Exemplary BODIPY dyes are described in Example 7.

[0244] Alternatively, cyanine dyes 2, 3, 5, and 7 are another possible combination. However, they have extremely large Förster radii and may interfere with each other even when diluted.

[0245] Fluorescent quantum dots and fluorescent particles can also be used. Quantum dots are semiconductors composed of atoms from the II-VI or III-V elements of the periodic table (e.g., CdSe, CdTe, InP). The optical properties of quantum dots can be manipulated by synthesizing (usually stabilizing) shells. Such quantum dots are known as core-shell quantum dots (e.g., CdSe / ZnS, InP / ZnS, InP / CdSe). Quantum dots of the same material but different sizes can emit light of different colors. Their brightness is due to the quantization of energy levels due to the confinement of electrons in all three spatial dimensions. In bulk semiconductors, electron-hole pairs are bound within the Bohr exciton radius, which is characteristic for each type of semiconductor. Quantum dots are smaller than the Bohr exciton radius, causing the appearance of discrete energy levels. The band gap ΔE between the valence and conduction bands of a semiconductor is a function of the size and shape of the nanocrystal. Although quantum dots are characterized by a slightly lower emission quantum yield than conventional organic fluorophores, they have a much larger absorption cross section and extremely low photobleaching rates. The molar extinction coefficient of quantum dots is about 10 5 ~10 6 M -1 cm -1 , which is 10 to 100 times larger than that of organic dyes.

[0105]

[0246] Core / shell quantum dots have a higher band gap shell around a lower band gap core, which emits light without being absorbed by the shell. The shell passivates the surface non-radiative emission from the core, improving the photoluminescence quantum yield and preventing spontaneous degradation. The shell of type I quantum dots (e.g., CdSe / ZnS) has a higher energy conduction band and a lower energy valence band than the core, resulting in both electrons and holes being confined to the core. The conduction and valence bands of the shell of type II quantum dots (e.g., CdTe / CdSe, CdSe / ZnTe) are both lower or both higher in energy than the conduction and valence bands of the core. Thus, the motion of electrons and holes is restricted to one dimension. Radiative recombination of excitons at the core-shell interface gives rise to type II emission. Type II quantum dots behave as indirect semiconductors near the band edges, and therefore have an absorption tail into the red and near infrared. Alloyed semiconductor quantum dots (CdSeTe) can also be used, but types I and II are most preferred. The variable alloy composition and internal structure allow for tuning of the optical properties without changing the size of the particle.

[0247] Particularly preferred quantum dots are selected from the group consisting of CdSe / ZnS core / shell quantum dots, CdTe / CdSe core / shell quantum dots, CdSe / ZnTe core / shell quantum dots, and alloyed semiconductor quantum dots (e.g., CdSeTe). More preferably, the quantum dots are less than about 10 nm in diameter, even more preferably about 2 nm to about 5.5 nm in diameter, and most preferably about 1.5 nm to about 4.5 nm in diameter. If emission of different colors is required to create multiple sensors (multiplex detection), this can be achieved by varying the size of the quantum dot core, which results in different emission wavelengths. The quantum dots may be stabilized or unstabilized, as described above for the particles. A preferred ligand for stabilizing the quantum dots is resorcinarene.

[0106]

[0248] In the graphene biosensor of the present disclosure, advantageously, the graphene core particle acts as a quencher for the signal of the detectable moiety, so that there is no need to separately add a co-linked quencher particle to the sensor (e.g., directly bind to the carrier particle). Thus, unlike other sensors, the particles (detectable moieties) attached to the graphene core particle interact with the graphene core particle carrier particle, but are usually selected and positioned (e.g., in close proximity to each other and to the carrier particle) so that they do not interact with each other, but only with the graphene core particle for the sensing function. (See, for example, the characteristics of the peptides attached to the graphene particles illustrated and exemplified in the Examples section).

[0249] Thus, in the embodiments described herein, the core particle and the biosensor each comprise a graphene core particle having at least one detectable moiety attached to a pure graphene nanosheet microparticle via a peptide bond. In this configuration, the detectable moiety is at a quenching distance to the graphene, and the detectable signal of the detectable moiety is quenched, weakened, or undetectable due to its proximity to the central graphene nanosheet microparticle. The peptide bond comprises a recognition sequence specific to the target biomarker, such that the target biomarker, if present in the test sample, interacts with the peptide bond (typically cleaving or modifying the conformation of the peptide bond), thereby bringing the detectable moiety to an emission distance where quenching of the graphene particle does not occur (e.g., by releasing the detectable moiety or by modifying the distance through an associated conformational change). Once released or brought to an emission distance via a conformational change, the detectable moiety is no longer quenched by the central graphene nanosheet microparticle, and its signal (or a change in its signal) can be detected, thereby indicating the presence and / or activity of the target biomarker in the sample.

[0107]

[0250] In most embodiments described herein, in the graphene biosensors of the present disclosure, the diameter of the attached polymer layer plus co-attached recognition sequence does not exceed 20 nm to allow for positioning the detectable moiety at a quenching distance relative to the graphene particle where the graphene quenches the signal of the detectable moiety (see polymer properties described and exemplified in the Examples section).

[0251] Thus, in an embodiment, the thickness of the coating material in the graphene core particles and / or biosensors of the present disclosure may be 18 nm or less, with a minimum of 2 nm for the binding peptide sequence characterized by targeting capability.

[0252] In certain embodiments, the thickness of the coating material in the graphene core particles and / or biosensors of the present disclosure is 8-17 nm, 2-18 nm, or 5-15 nm, depending on the size of the detectable moiety attached or capable of being attached to the coating material, as would be understood by one of skill in the art upon reading this disclosure.

[0253] In certain embodiments described herein, the acceptable ratio of peptide length (A) to polymer layer thickness (B) in a graphene biosensor for detecting protease activity can be detected by the procedure exemplified in Example 31.

[0254] In certain embodiments where the target biomarkers undergo post-translational modifications, the layer thickness is close to 20 nm prior to binding to their targets or post-translational modification, both events extending the peptide sequence to give rise to detectable moieties at emission distances where the graphene particles do not quench the detectable moiety, thus causing increased fluorescence from the tethered fluorophore.

[0108]

[0255] The biosensors of the present disclosure have surprisingly been found to have high stability as well as high reproducibility of associated signal detection, particularly in embodiments where the graphene layer comprises 2-100 sheets of pure graphene, more preferably fractal pure graphene, with at least 90%, preferably at least 99%, more preferably up to 100% of the graphene particles coated with a coating material. In these embodiments, the target biomarkers can be detected with high reproducibility, particularly with a coefficient of variation of the signal detected between different manufacturing lots or batches of less than 10%, where the signal is the amount of fluorescence above the background of each lot of sensors alone.

[0256] In the embodiments described herein, the reproducibility of a nanobiosensor is determined by its ability to reproduce measurement conditions of a defined biological sample, which can be expressed in terms of the coefficient of variation.

[0257] Thus, the high reproducibility of the biosensors of the present disclosure allows one skilled in the art to formulate core particles modified to be chemically stable in aqueous solution and coupled to various sensor moieties according to the present disclosure in independent assemblies to generate the same amount of signal from a single biological sample. To be of value for measuring biological processes, the amount of signal emitted by a defined biological sample must be reproducible.

[0258] In embodiments of the graphene biosensors described herein, where the graphene layers comprise between 2 and 100 sheets of pure graphene with at least 90% coated with a coating material, differences between different manufacturing lots or batches of the sensor are expected to display signals with a coefficient of variation of less than 10% for each build.

[0259] In particular, to detect reproducibility, the amount of sensor added to the reaction is preferably carried out using absorbance, not mass-dependent. In particular, the concentration of particles can be determined by absorbance measurement using a standard curve with R2>0.99. Under these conditions, the concentration of particles can be adjusted with CV%<4%.

[0260] In embodiments described herein where a suspension of particles containing particles with an average size of 10 nm to 5000 nm, preferably 150 to 500 nm, as determined using scanning electron microscopy and digital light scattering measurements, is at least 90% coated with a coating material, reproducibility can also be detected with respect to the stability of the aqueous suspension containing the sensor, where reproducibility is assessed by evaluating colloidal stability at OD650 or OD270. In embodiments where the size of the particles is 10 nm to 5000 nm, preferably 150 to 500 nm, within a set time, the average decrease in OD650 between measurements is 24% or less, and in preferred embodiments is typically 10% or less.

[0109]

[0261] In these embodiments, the configuration of the sensors allows for a formulation in which the sensors remain uniformly suspended in aqueous solution. This feature allows for uniform distribution of the particles and subsequent interaction with rare specific biomarkers present in biological samples that are present in concentrations as low as femtomolar. Stability is further supported by the modification of few-layer graphene with surface modifications that mask the non-polar nature of the graphene surface. These modifications introduce charges that allow the particles to remain in suspension in an aqueous environment. The introduction of polar modifications is required to support the preparation of the sensors in a buffer solution of at least 1 mg / ml. With a stable solution of at least 1 mg / ml, all sensors can be mixed at a functional concentration with samples of 5 to 500 μg / mL. Preferably, the sensor concentration is kept at 25, or 30, or 50, or 100, or 200, or 300 μg / mL. The optimal functional concentration can be determined for each sensor based on the specific components and relevant characteristics. The combined effect of introducing size and charge modifications is to produce a solution that maintains a stable suspension of particles such that the absorbance of the graphene nanobiosensor does not change over a period of 1 hour at room temperature. This solution stability is evaluated by assessing colloidal stability at OD650 or OD270 over a 60 minute interval at room temperature. The graphene sensor shows a change in OD650 of -20 to -26%. The absorbance of the graphene sensor at OD270 can show a change of -17% to -21%. Thus, the colloidal suspension of graphene sensor stays in suspension more efficiently than other particles known in the art, as will be appreciated by those skilled in the art.

[0262] In a preferred embodiment, the graphene particles have a size of 900 nm or less, preferably 350 nm or less, more preferably 250 nm or less, and are capable of detecting target biomarkers present at concentrations as low as femtomolar concentrations.

[0110]

[0263] The biosensor of the present disclosure has also surprisingly been found to have a high signal to noise ratio as well as high stability and reproducibility of signal detection, particularly in embodiments where the graphene layer comprises 2-100 sheets of pure graphene, more preferably fractal pure graphene, with at least 90%, preferably 100% of the surface of the graphene particle coated with the coating material, and interference with the fluorescence readout due to adsorption and quenching of previously cleaved detectable moieties (such as fluorescent dyes) on the surface of the uncoated graphene is minimized.

[0264] In particular, the biosensors characterized above provide a signal to noise performance (S:N) of at least 25 or greater in aqueous solution. In experiments performed with the exemplary biosensors characterized above, the relationship between the sensor and samples incubated with serum at time 0 for the biosensor found a relative fluorescence index (RFI) or sample RFU / assay control RFU average of 4.3+ / -1.9. Furthermore, biosensors maintained in aqueous solution for up to 90 minutes showed no significant change in background signal, and the integrated S:N increases from 25 to 46, 159, 312 on average across multiple sensors when different lots of biosensors are measured. Thus, the integrated S:N, which assesses both the signal to noise ratio at t=0 and t=60, demonstrates an increase in sensitivity to a defined stimulus between 3-fold and 13-fold as graphene biosensor size and solvent contamination are stabilized (see representative Example 44 and corresponding Figures 59 and 60). This S:N performance is sensor dependent, as will be understood by those skilled in the art.

[0265] In particular, in these experiments performed with the exemplary nanobiosensors described herein, a 25-fold improvement was measured averaged across four different sensors (see Example 17, FIG. 20; Lot 1 formulation, FIG. 59) ranging from 8 to 50, as would be understood by one of skill in the art. The same four sensors improved to an average S:N of 312 (see Example 40 and Example 43 Lot 4) with a range of S:N from 109 to 623 times. In comparison, the iron particle sensor had an average S:N of 20 (range 6 to 42) for the same four sensors measured simultaneously using the same buffer and sample (see Example 44).

[0111]

[0266] In some embodiments, the biosensor can have different lengths and configurations of sensors of the above configurations. For example, in some embodiments, the length of the peptide tether can be more than 50 amino acids. This is possible in all cases where, for example, back bending of the peptide chain is envisioned to bring the detectable moiety into emission distance.

[0267] In some embodiments, the peptide bond may be attached to the coating layer or graphene surface of the graphene core particle of the present disclosure and / or the detectable moiety indirectly through a moiety also referred to herein as a spacer or connector. For example, the exemplary peptide bond in Table 1 may include a spacer GAG before the N-terminus of each sequence, and a spacer AG is used at the C-terminus. Selection of an appropriate spacer in the graphene biosensor of the present disclosure may be made taking into consideration the target biomarker to be detected and the quenching and emission distances of the particular biosensor, as will be understood by those skilled in the art (see Example 9).

[0112]

[0268] In one embodiment, the peptide bond is an oligopeptide containing a 3 amino acid spacer GAG, a 4+4 amino acid recognition sequence, and a 2-3 amino acid spacer (G)AG, and is 5±0.5 nm in length. In one embodiment, the layer size is 2 nm (functionalized graphene) + 12 nm (coating material such as PEI) = 14 nm. A peptide bond with a 14 nm + 5 nm spacer = 19 nm < 20 nm.

[0113]

[0269] In an embodiment, the graphene-based biosensor is configured for a detection method based on surface plasmon resonance and FRET between the graphene carrier particle and the detectable moiety. FRET stands for energy transfer between two particles. Surface plasmon resonance is used to excite the particle. The donor particle, which is initially in an excited state, can transfer this energy to a nearby acceptor particle via non-radiative dipole-dipole coupling. Briefly, the detectable particle is bound by an oligopeptide in its initial state, and a first emission is observed upon excitation of the donor particle. When the target biomarker binds and / or cleaves its recognition sequence, a FRET change is observed, resulting in a change in the emission spectrum. Typically, when the distance between the two particles is changed by the biomarker (either by cleavage or extension of the peptide bond), light is emitted from the detectable particle, and a distinct blue shift in absorption and emission can be observed. This is due to the increased distance between both particles. In an embodiment, the signal intensity from the detectable particle increases as the distance between the two particles increases.

[0270] In the biosensors described herein, given the photophysical properties of graphene, plasmonic quenching dominates in contrast to other nanomaterials that are characterized by an overlay of plasmonic excitation and quenching, as will be appreciated by those skilled in the art.

[0271] Generally, the excitation of the biosensor is directed towards the particle (e.g., the donor particle) for which there is a higher energy state. The absorption spectrum of graphene (and carboxygraphene) changes very little between UV and near IR, so the biosensor can operate in a wide optical range. Excitation of the detectable particles can advantageously be performed at about 300 nm to about 1500 nm. Excitation is typically performed using an energy source of appropriate wavelength selected from the group consisting of tungsten lamps, LEDs, lasers, and / or bioluminescence (e.g., luciferase, Renilla, green fluorescent protein). Changes in the absorption and / or emission of the particles as the peptides bind, cleave, or chemically modify the oligopeptide bonds are observed over a period of about 1 minute to about 120 minutes, preferably about 1 minute to about 60 minutes, and in some cases about 1 minute to about 30 minutes, depending on the biomarker activity. In practice, the assay can first be calibrated for a particular biosensor using control samples with and without known concentrations of the target biomarker.

[0272] In particular, the pure graphene nanosheets are within a core particle as described herein and attachment is achieved by attaching a detectable moiety to a chemically modified surface of the core particle as described herein. In embodiments where the core particle comprises a layer of organic and / or inorganic molecules, the chemically modified surface is coated with a layer of organic and / or inorganic molecules and attachment is achieved via attachment of a peptide bond to the layer of organic and / or inorganic molecules.

[0273] In a most preferred embodiment, prior to deposition, the pure graphene nano-sheets are dispersed (eg, by sonication) and the deposition is carried out on the dispersed pure graphene nano-sheets.

[0274] In preferred embodiments, dispersion is performed with graphene particles, including fractal graphene. In these embodiments, dispersion may be desirable to reduce the representation of larger fractals in the population of graphene going into production. In certain embodiments detecting target biomarkers at femtomolar concentrations, the particle population size of the particles is typically 10-5000 nm, optimally 50-500 nm, to support a homogenous and stable aqueous solution of the particles. The use of sonication introduces energy into the system to break the electrostatic bonds and van der Waals forces that hold the fractals together. Once broken, the coating reaction (e.g., polymerization) captures the population as shown. Sonication represents one mechanism to introduce energy into the system, some of which is used to break the larger fractals. This continues to equilibrium depending on the power of sonication. A suitable population of particles is generated by introducing 2-40 KJ or 10-20 KJ or more preferably 12-15 KJ with a microtip probe sonicator in a 200 mL solution of few layer graphene in DMF. Alternatively, the size of the fractal population may be altered by dispersion using a high shear homogenizer. Alternatively, it is expected that energy may be supplied by microwaves to break up larger fractals or by extrusion under high pressure. These methods use mechanical methods to disperse larger fractals to reduce the overall population size. Alternatively, it is expected that size selection may be performed to select the population representing 50-500 nm using size selection techniques such as filtration or size fractionation or sedimentation under centrifugation. Examples included reference probe sonication (see Example 22 and associated Figures 27 and 29). The effective end point is determined by determining the size of the final population after processing for dispersion by any method such as TEM or light scattering. Using absorbance efficiency measured by OD270 / mg / ml, as dispersion is included, efficiencies of >1.0, as well as >2.0 and >3.0 have been observed. (See Example 40 and associated data in Table Figure 55 representing the efficiency of the preferred embodiment).

[0114]

[0275] The attachment of the coating material by binding of the groups FGg and FGcg is preferably carried out after dispersion of the functionalized graphene microparticles, resulting in core graphene microparticles presenting functional groups FGcp configured to bind to corresponding functional groups FGp presented in a peptide bond.

[0115]

[0276] In one embodiment, the following schemes are described for the synthesis of biosensors based on appropriate coupling chemistries as illustrated in Schemes (I)-(IX).

[0116] [ka] (wherein A is a reagent configured to functionalize graphene, CM is a coating material within the meaning of the present disclosure, P is a peptide bond within the meaning of the present disclosure, and DM is a detectable moiety).

[0277] As shown in Scheme X, graphene of formula (Xa) is reacted with a reagent FG1-A-FGg, where FG1 is a reactive functional group that reacts or can be reacted with graphene, FGg is a functional group that can be chemically bonded to a coating material, and A is a chemical moiety of a C2-C4 or C5-C12 substituted or unsubstituted linear or branched alkyl group, where 1-4 carbon atoms may be replaced with one or more heteroatoms selected from O, S, or NH. Exemplary FG1 include, but are not limited to, -N3 (azide), which decomposes to nitrenes under heating conditions, maleimides, which are dienophiles. Exemplary FGg include -COOH or NH2.

[0278] The functionalized graphene of formula (Xb) reacts with the functionalized coating material FGcg-CM-FGcp, where FGcg is a functional group that can react with FGg on the functionalized graphene. Thus, when FGg is -COOH, an exemplary FGcg can be NH2, which forms an amide bond with FGg.

[0279] The coated graphene of formula (Xc) comprises a functional group FGcp, where FGcp is a functional group that can react with FGpc on the functionalized peptide FGpc-P-FGpd. Similarly, exemplary FGcp includes -COOH or NH2. Thus, when FGcp is -COOH, exemplary corresponding Fpc can be NH2 to form an amide bond with FGcp.

[0280] The peptide-derivatized graphene of formula (Xd) comprises a functional group FGpd, where FGpd is a functional group that can react with FGdp on the functionalized detection moiety FGdp-DM. Similarly, exemplary FGdp includes -COOH or NH2. Thus, when FGdp is -COOH, an exemplary corresponding Fpd can be NH2 that forms an amide bond with FGdp.

[0281] It should be understood that any of the pairs of coupling functional groups described herein can be practiced with any other coupling functional group, as illustrated in Schemes (I) through (IX) described herein. Thus, if one functional group is an amine -NH2, the other functional group can be, in addition to a carboxylic acid, an NHS (Scheme V) or an oxirane (Scheme IX).

[0117]

[0282] In certain embodiments described herein, the assembly of the coating onto the preferably dispersed microparticles can be carried out by first attaching the coating layer to the surface of the graphene microparticles to provide coated microparticles presenting functional groups of the coating layer FGcp, such as amide, amine, ester, ether, thioester or thioester bonds, and by attaching peptide bonds to the functional groups FGcp via corresponding functional groups of the peptide linker FGp. In certain embodiments, the linker to the polymer is first, which is then attached to the graphene. The attachment can be direct or indirect, and can be via covalent or non-covalent bonds depending on the corresponding functional groups, as will be understood by those skilled in the art.

[0118]

[0283] In certain embodiments, the peptide bonds of the present disclosure can be attached via spacers configured to directly attach graphene, such as EPLQLKM

[27] (to target the edge of graphene) and HSSYWYAFNNKT

[27] (to adsorb onto flat graphene surfaces) to anchor any peptide sequence to pristine graphene.

[27] (to adsorb onto flat graphene surfaces) to anchor any peptide sequence to pristine graphene.

[0284] In certain embodiments, the peptide bond of the present disclosure can be attached to a terminal cysteine ​​that is oxidized to a thiyl radical attached to graphene.

[0285] In certain embodiments, the unnatural amino acid can be tethered to the N-terminus of the peptide sequence to effect linkage (all chemistries as described above).

[0119]

[0286] In some embodiments, the coating material can include oligoethylene groups less than 20 nm in diameter, starburst dendrimers less than 20 nm in diameter, and block copolymers. In some embodiments, when the coating material can include block copolymers, hydrophobic polymers are used, such as polystyrene, polyisobutylene, polyvinyl chloride, polyethylene, polypropylene, and additional polymers identifiable by those skilled in the art. When negatively charged polymers such as polystyrene sulfonic acid are used in block copolymers of polystyrene, a combination of hydrophobicity and charge attraction can be a component of the block copolymer. In these embodiments, the hydrophobic-hydrophilic block copolymer can be dissolved in a solvent that disperses graphene well (e.g., dimethylformamide (DMF)). With continued sonication, H2O is added to the mixture, binding the hydrophobic end of the block copolymer to the graphene. This supramolecular attachment occurs spontaneously in the dispersion due to the increasing hydrophobicity decrease with successive H2O addition. Therefore, it is expected that this attachment principle will work reliably as long as the sensor is used in an aqueous solvent.

[0287] In accordance with the properties of graphene biosensors in the sense of the present disclosure in aqueous solutions, it has also been found that graphene biosensors are surprisingly stable and capable of providing highly reproducible detection of target biomarkers in aqueous samples.

[0120]

[0001] The term "sample" as used herein refers to a limited amount of something that represents a larger amount of something, such as a fluid from a biological environment, a culture, a tissue, a sample of a commercially available recombinant protein, a synthetic compound or a portion thereof, etc.

[0002] As used herein, the term "sample" refers to a portion of a substance from an environment for use in testing, examination, or research. The environment can include an individual. When referred to as a noun, the term "individual" as used herein in the context of detection, diagnosis, and treatment refers to a single biological organism, including but not limited to animals, particularly higher animals, particularly vertebrates such as mammals, and particularly humans. In these instances, the sample can include portions of tissues, organs, or other biological material from an organism, such as the urethra, urine, cervix, vagina, rectum, oropharynges, conjunctiva, or any bodily fluid.

[0121]

[0288] In particular, a biological sample may contain one or more cells of any biological lineage as representative of the entire population of similar cells in the sampled individual. Exemplary biological samples include: venous and arterial blood, plasma, serum, dried blood spots, cerebrospinal fluid, lumbar puncture, nasal secretions, sinus washings, tears, corneal scrapings, saliva, sputum or expectoration, bronchoscopic secretions, transtracheal aspirate, endotracheal aspirate, bronchoalveolar lavage, vomit, endoscopic biopsy, colonic biopsy, bile, vaginal fluid and secretions, endometrial fluid and secretions, urethral fluid and secretions, mucosal secretions, synovial fluid, peritoneal fluid, peritoneal washings, tympanic aspirate, urine, clean catch midstream urine, catheterized urine, suprapubic aspirate, kidney stones, prostatic secretions, feces, mucus, pus, wound drainage, skin scrapings, skin sections and skin biopsies, hair, nail clippings, buccal tissue, bone marrow biopsy, solid organ biopsy, surgical specimen, solid organ tissue, cadaver, or tumor cells, and the like, as may be identified by one of skill in the art. Biological samples can be obtained using sterile or non-sterile techniques appropriate to the sample type, as distinguishable by those skilled in the art. Some biological samples can be obtained by contacting a swab with a surface of the human body and removing some material from the surface, examples include throat swabs, nasal swabs, nasopharyngeal swabs, oropharyngeal swabs, buccal or cheek swabs, urethral swabs, vaginal swabs, cervical swabs, genital swabs, anal swabs, rectal swabs, conjunctival swabs, skin swabs, and any wound swabs. Depending on the type of biological sample and the intended analysis, the biological sample can be used fresh for sample preparation and analysis or can be fixed using a fixative.

[0122]

[0289] In the methods and systems described herein, a sample can be divided into two or more portions and / or treated with a process to enrich target biomarkers and / or remove selected substances to enhance detection. Thus, the term sample as used herein includes samples that have been chemically treated or stored, preserved, or further analyzed.

[0290] The samples used in connection with the graphene core particles and related graphene biosensors, compositions, methods and systems are aqueous samples.

[0291] An "aqueous sample" in the sense of the present disclosure is a sample in which water is the solvent or main component. In particular, the aqueous solution usually contains a buffer component at a concentration capable of maintaining a defined pH in the presence of the sensor and sample during the experiment.

[0292] In the embodiments described herein, it has been found that graphene biosensors in the sense of the present disclosure, which have 2-100 pure graphene sheets, preferably fractal graphene, coated with at least 90% of a coating material, are surprisingly stable in aqueous samples and can provide detection characterized by high reproducibility and signal-to-noise ratio, especially when they have a size range of 10 nm to 5000 nm, preferably 150 to 500 nm.

[0123]

[0293] In particular, in certain embodiments, sensors of the present disclosure including these features exhibit absorbance to reproduce sensor concentrations (independent batches of biosensor solution with the same characteristics) with a coefficient of variation CV of less than 3%. Achieving this CV is obtained by having a solution with sensors that remain uniformly distributed in the determined reaction. Preparation of nanosensors prepared by the method, including dispersion (e.g., using sonication) and solvent removal, produced solutions of sensors that maintained colloidal stability with less than 15% sedimentation over a 60 minute interval. In particular, in embodiments where particles are provided by the method, including particle dispersion and solvent removal steps, 9% to 10% sedimentation was observed.

[0124]

[0294] In an embodiment, the reproducibility of the sensor of the present disclosure can also be detected through the reproducible estimation of both the assay control and the sample, since these two values ​​are divided to estimate S:N. The sensor of the present disclosure exhibits a batch-to-batch CV% of less than 20%. In this regard, the biosensor of the present disclosure, with the combination of the above features, can provide a batch-to-batch CV% of 3%-10%. Optimally, the batch-to-batch CV% will be <10%. This is assessed by preparing independent batches of the sensor and comparing the SN(SM / AC) under matched conditions to a standard stimulus. (See Example 22 and associated FIG. 27 and Example 44 and associated FIG. 59).

[0295] In an embodiment, the S:N of the graphene biosensors of the present disclosure can be determined by maintaining low and stable assay readings. For example, for biosensors evaluated on a VarioSkan Lux, ΔC is between 0.01 and 0.1. The signal is sensor and stimulus dependent. The sample signal for any given sensor using the same stimulus can be improved by 15-fold with dispersed, solvent cured sensors. Furthermore, incremental addition of dispersion (average increase in SN of 6.8-fold) as well as dispersion and solvent removal (average increase in SN of 15-fold) demonstrates that the combined use of core particles (see Example 44 and associated Figure 59), (1) dispersed using sonication or equivalent to an absorbance efficiency of >3.0 OD270 / mg / ml (see Example 40 and associated Figure 55), and (2) reducing the amount of solvent such that TGA measures less than 5% (wt%), and likely less than 2%, total mass loss, is related to this S:N performance (see Example 21 and associated Figure 25).

[0125]

[0296] In certain embodiments, reproducibility and signal to noise ratio can be increased by making appropriate buffer selection. Buffer selection can be made based on a selection from Good's list that reflects the most appropriate pH target for biomarker detection. The addition of monobasic salts increases S:N performance to an extent that depends on the concentration of salt added, as would be understood by one of skill in the art upon reading this disclosure. Monobasic salts reduce the assay control and increase the S:N ratio compared to the sample. The inclusion of monobasic salts reduces the assay control to an average of 0.01-0.1 RFU on the VarioSkan Lux. Overall, the impact of buffers across all sensors tested increases S:N by an average of 4-fold (ranging from 2.5-fold to 6.7-fold) (see Example 42 and associated Figure 57). Certain protease enzymes require buffer cofactors such as divalent cations. In a preferred embodiment for protease detection, the buffer contains 10 μM calcium, magnesium, and zinc divalent ions. The formulations tested focused on pH 7.2 as the physiologically relevant pH used across all sensors. However, the tumor environment and intracellular compartments often reflect a pH below 7.0. Thus, the pH does not need to be one condition, except when reaction chambers are shared, such as in multiplex reactions. Some enzymes require acidic conditions, and for any example, pH 7.0 and pH 6.0, as well as 6.4 and 6.8, are expected to support enzymes such as cathepsins or enzymes from inflammatory environments. Receptor-ligand interactions are preferably measured under physiological conditions, and therefore 155 mM and pH 7.2 are conditions that generally support many sensor formulations, as will be understood by those skilled in the art.

[0126]

[0297] In certain embodiments, the graphene biosensor of the present disclosure comprises multiple detectable components, each of which comprises a detectable moiety and a recognition sequence specific for a target biomarker.

[0298] In some of these embodiments, the recognition sequences of detectable moieties of the plurality of detectable moieties are configured to specifically recognize different target biomarkers.

[0299] Thus, in these embodiments, the graphene biosensors of the present disclosure are configured for multiplexed detection and to simultaneously measure multiple analytes in a single experiment.

[0300] In particular, the term "multiplexed" as used herein refers to embodiments in which two or more target biomarkers can be detected in the same reaction using the same mixture of reagents.

[0301] In the multiple target-specific detectable moieties of the nanobiosensor, the excitation spectrum of each detectable moiety has a minimized overlap with the emission spectrum of another detectable moiety of the multiple target-specific detectable moieties. Thus, in these embodiments, each detectable moiety is assigned to a specific biomarker with minimal or no overlap between the excitation and emission spectra of the detectable moieties of the multiple detectable moieties to minimize FRET effects between the detectable moieties that distort the readout.

[0302] In terms of the properties and characteristics of graphene sensors, in graphene sensors configured for multiplexed detection, the multiplexed detection capability of sensors with 2-100 graphene sheets and a coating layer that coats at least 90% of the graphene surface is greater than or equal to 5 peptide sequences + detectable moieties, and in some cases up to 10 in the UV / Vis spectrum and up to 50 in the entire electromagnetic spectrum.

[0127]

[0303] In certain embodiments of the graphene biosensors described herein, the detectable components, including peptides and detectable moieties (e.g., fluorophores), are present in a multiplexed biosensor at up to 1.0±0.25×10 -3 In one embodiment, where the fastest signal increase over the femtomolar to micromolar concentration range of a target biomarker (e.g., a protease) is desired, the concentration of the detectable moiety may be 1.6±0.2×10 per gram of graphene-nano biosensor, as would be understood by one of skill in the art upon reading this disclosure. -5 It may be molar.

[0304] Thus, in some of these embodiments, the biosensor comprises: <1> Considering the multiplexed biosensor, the nanobiosensor has a maximum sensitivity of 1.0 ± 0.25 × 10 per gram. -3 The concentration of molar detectable moieties (peptide sequence + detectable moiety) is divided by the number of peptide sequences + detectable moieties being used for multiplexing purposes. If unequal concentrations of each detectable moiety are used, as will be understood by one of skill in the art, the sum of all moiety concentrations for each peptide sequence + detectable moiety will be less than 1.0±0.25×10 per gram of nanobiosensor. -3 Must be equal to moles.

[0305] Furthermore, in some embodiments where the biosensor is a multiplexed biosensor, the preferred concentration of tethered peptide sequence plus detectable moiety is 1.6±0.2×10 per gram of nanobiosensor to obtain the fastest signal increase over the femtomolar to micromolar concentration range of the target biomarker (e.g., protease). -5 Considering it is molar, this concentration is divided by the number of detectable moieties being used for multiplexing purposes. If unequal concentrations are used, as will be understood by those of skill in the art upon reading this disclosure, the sum of all the moiety concentrations for each peptide sequence + fluorophore is 1.6±0.2×10 per gram of nanobiosensor. -5 Must be equal to moles.

[0306] Thus, in some preferred embodiments of the multiplexed nanobiosensors described herein, the total concentration of all peptides+fluorophores utilized is within the range of 1.0±0.25×10, as will be understood by those of skill in the art upon reading this disclosure. -3 Mole / gram ~ 1.0 ± 0.25 x 10 -7 moles / gram, preferably 1.0±0.25×10 -4 Mole / gram ~ 1.0 ± 0.25 x 10 -6 moles / gram, and even more preferably 1.0±0.25×10 -5 Mole / gram ~2.0±0.25×10 -5 It may be in the moles / gram range.

[0307] Similar multiplexing capabilities can be achieved by using compositions that include multiple biosensors of the present disclosure, each displaying a detectable moiety specific for a different target biomarker. In these embodiments, separately assembled sensors can be mixed together such that as part of the reaction, each sensor can still generate a signal greater than the background signal defined as the sensor alone. In this context, a biosensor specific for a target biomarker can be mixed with 1, or 2, or 3, or 4, or 5, or 6, or 7, or 10, or 20 different sensors and still generate a signal greater than background. At a 1:20 display, a multiplexed sensor is detectable at 5-7% of expected value. Thus, a multiplexed sensor can be detected with 1, or 10, or 4, or 2 of the 20 multiplexed sensors.

[0128]

[0308] In certain embodiments, multiplex detection of target biomarkers can be performed in conjunction with detection of a condition associated with multiple target biomarkers. For example, the disclosed sensors can be used for multiplex detection of MMP-9, CTS-K, MMP-2 and ARG for the presence and absence of lung cancer. In another example, the disclosed sensors can be used for multiplex detection of Arginase IL-13, Anti-inflammatory events and conditions, IL-6, GCSF, MIP-1, MCP-1 for detection and diagnosis of pro-inflammatory events and conditions in an individual.

[0129] Exemplary Process for Creating a Multiplex

[0309] In some embodiments, one or more graphene core particles, graphene biosensors described herein are included in a composition together with a suitable auxiliary. The term "auxiliary" as used herein refers to any of a variety of media that typically act as a solvent, carrier, binder or diluent for the graphene biosensors described herein that are included in the composition as an active ingredient. In particular, a composition that includes one or more oximes can be used in one of the methods or systems described herein.

[0310] In particular, in certain embodiments, for storage and / or use, the biosensor is typically dispersed in a pharma- ceutically acceptable solvent system, which may be any type of suitable diluent, excipient, vehicle, etc. As used herein, the term "pharma- ceutically acceptable" means not biologically or otherwise undesirable, in that it may be administered to a subject without undue toxicity, irritation, or allergic response, and does not cause unacceptable biological effects or interact in a deleterious manner with any of the other components of the composition in which it is included.

[0130]

[0311] In certain embodiments, the pharma- ceutically acceptable carrier can be selected to minimize any degradation of the biosensor components, as is well known to one of skill in the art, and to minimize any adverse side effects in the subject (for in vivo administration), as is well known to one of skill in the art. Exemplary carriers include non-aqueous solutions such as diethyl ether, DMF, DMSO, and the like. The biosensor is storage stable at room temperature conditions, even at elevated temperatures up to 100°C, without degradation, and can be stored and transported without special handling requirements (e.g., without refrigeration).

[0312] Pharmaceutically acceptable components include those that are acceptable for veterinary use as well as human pharmaceutical use, depending on the route of administration. For example, a composition suitable for administration by injection is usually a solution in a sterile isotonic aqueous buffer. Exemplary carriers include aqueous solutions such as normal (n.) saline (about 0.9% NaCl), phosphate buffered saline (PBS), sterile water / distilled autoclaved water (DAW), or other acceptable vehicles as understood by those skilled in the art.

[0131]

[0313] The graphene carrier particles are stable indefinitely based on the data of this disclosure. The peptide bonds are also stable for long periods of time (several years). It will be appreciated that the particular compound selected for the detectable moiety may reduce the storage stability of the overall biosensor, and that certain sensors can be stored under more careful conditions (e.g., under argon) to preserve the sensitive detectable moiety for longer periods, if desired.

[0132]

[0314] It will also be appreciated that biosensors can be manufactured in successive steps, where the graphene carrier particles can be stored until the time of use, and the peptide bond and detectable moiety are added at the time of use (e.g., just before shipment to the end user or by the end user). Similarly, the graphene carrier particles can be pre-conjugated with a selected peptide bond and stored without the detectable moiety attached, and the detectable moiety can be added at a later time closer to use. Notably, graphene carrier particles have a higher resistance to mislabeling, and a detectable moiety accidentally attached directly to the graphene particle itself (not via a bond) should not interfere with other correctly attached detectable moieties. That is, the signal of an incorrectly attached carrier particle is simply permanently quenched due to its proximity to the carrier particle. Thus, biosensors have a higher tolerance threshold during manufacturing, further contributing to their advantage.

[0133]

[0315] In the embodiments described herein, the composition may include components in appropriate concentrations in addition to the graphene core particles and / or biosensors of the present disclosure, as understood by those of skill in the art. In particular, a composition in the sense of the present disclosure may typically include a salt and a buffer (a substance capable of maintaining the pH of a solution in which it is dissolved) selected to maintain the pH of the solution in which it is dissolved at a controlled pH. In an exemplary preferred embodiment, the composition may include 5 mM MES with 10 μM divalent cations and 155 mM NaCl, as well as further combinations of salts and buffers identifiable by those of skill in the art upon reading this disclosure.

[0134]

[0316] In one or more embodiments, the biosensors can be pre-dispensed into microplate wells and stored / dispensed for use. Black chimney well microplates are particularly suitable for this purpose. Opaque microplate configurations are preferred for the assay to reduce ambient light interference and noise. Methods for non-invasive detection and quantification of various biological markers are also described herein. These methods utilize the biosensors described herein and can be performed at home or in the field as an integral part of point-of-care resources in medical facilities to evaluate biological markers indicative of various conditions and diseases. Such biological marker-based diagnostics can have numerous applications in precision medicine, particularly for airway diseases, for example, in distinguishing between lung cancer and other lung conditions.

[0135]

[0317] In a preferred embodiment, the composition can be in lyuphilized form. The auxiliary reagents supporting lyophilization can include trehalose, dextrose, sucrose, glycine, magnesium stearate, microcrystalline cellulose, starch (corn), silicone / titanium dioxide, stearic acid, sodium starch glycolate, gelatin, talc, sucrose, calcium stearate, povidone, pregelatinized starch, HPMC, OPA products, croscarmellose, hydroxypropyl cellulose, ethyl cellulose, calcium phosphate, or crospovidone.

[0136]

[0318] In an embodiment, the graphene biosensors described herein can be used in a method for detecting activity of a biomarker in an aqueous sample, the method comprising contacting a biological sample with any biosensor according to the present disclosure to form a reaction solution; and detecting a change in the reaction solution.

[0137]

[0319] In preferred embodiments, the aqueous sample is a biological sample from an individual. In these embodiments, the biological sample can be provided by collecting a sample from an individual and processing the sample for analysis. In these embodiments, processing the sample typically results in a processed aqueous sample configured for use in combination with a detection reagent. In particular, a biosensor in a reaction solution can be contacted with the processed biological sample for a sufficient time for the target biomarker (if present in the sample) to interact with the recognition sequence in the biosensor. Biological samples include, but are not limited to, blood, urine, saliva, tears, sputum, bronchoalveolar lavage fluid, nasal swabs, exhaled breath condensate, milk, feces, rectal fluid, vaginal fluid, and the like. In one aspect, the biological sample is collected from a subject and prepared for analysis. The sample can be collected and prepared manually, including, for example, manual pipetting or mixing / diluting the sample, manual protein spot cutting, manual biopsy collection, manual blood collection, and manual microwell loading. Alternatively, automated processes can be used, including, for example, the use of automated liquid handlers, automated protein spot cutters, automated biopsy collection, automated blood sampling, and automated microwell loading. It will be appreciated that the biological sample may contain a biomarker of interest, including various enzymes described herein, which can be used as biological markers indicative of the health status of the subject. A pharma- ceutically acceptable buffer can be added before, during, or after the sample is added to the reaction solution to adjust the pH to an optimal level depending on the biomarker of interest and the particular detectable moiety used. For example, a weakly alkaline buffer, such as HEPES, can be used to adjust the pH of the reaction mixture to within a desired range. Additionally, the pH can be adjusted to fine-tune the pH. For example, certain enzymes, such as MMPs and cathepsins, are more active under slightly acidic pH (lower limit of about 6.6) when taken from cancerous samples compared to non-cancerous samples. Thus, pH is a parameter that can be optimized within the scope of the present disclosure to further enhance the output of the assay. The reaction solution can also be spiked with a cofactor (e.g., Mg(II), Ca(II), or Zn(II)) to further enhance the enzyme activity for detection.

[0138]

[0320] When the target biomarker is present in the sample, the detectable moiety generates a detectable signal (e.g., optical or spectroscopic), such as fluorescence or color change, which can be visually perceived or measured with a suitable instrument. A plate reader can be used to detect the results of the assay. As described, when tethered, the central graphene particle quenches the emission of the detectable moiety. In the presence of a protease or other target biomarker, it cleaves the bond that separates the detectable moiety from the central particle, or modifies the bond that extends the detectable moiety outside of the quenching proximity. The detectable particle generates a detectable signal that varies depending on the proximity to the carrier particle, which can be detected and correlated with the activity of the target protein. For example, the maximum absorption of TCPP is near 420 nm, so an inexpensive 420 nm LED or any other type of laser diode can be used to excite a biosensor that uses TCPP as the detectable moiety. It will be understood that the biosensor is not limited to the TCPP-graphene FRET pair illustrated in the examples. Any FRET sensing pair can be used. If other FRET pairs are used, the excitation wavelengths and detection devices may be modified accordingly.

[0139]

[0321] In certain embodiments, FRET can occur across the entire electromagnetic spectrum.

[0322] In certain embodiments, photoacoustic detection (the photoacoustic responses of different fluorophores can be distinguished).

[0323] In some embodiments, the radioisotope can be released from the graphene core and then filtered out.

[0324] In one embodiment, the MRI probe may be emitted from graphene coated with ferromagnetic materials (iron oxide) or high spin dand f-block metal complexes.

[0325] In certain embodiments, the EPR probe can be emitted from graphene coated with ferromagnetic materials (iron oxide) or high spin Dan f-block metal complexes.

[0140]

[0326] Assays using biosensors can detect biomarkers down to sub-femtomole levels (<10-15 moles / liter), which is at least two orders of magnitude more sensitive than competing technologies such as immunoassays. Indeed, limits of detection (LODs) of 10-16 for proteases are possible, as demonstrated in examples using unoptimized biosensors. An inherent advantage of this technology is that different biomarkers (e.g., several proteases, cytokines, and kinases) can be measured in one liquid biopsy. That is, the technology allows for the simultaneous detection of different classes of biomarkers in a single platform. Thus, in multiplexed embodiments, it is preferable to use multiple different types of detectable moieties so that the assay can analyze multiple different types of target biomarkers in a single biological sample. Looking at multiple biomarkers allows for differentiation between related diseases (e.g., lung cancer vs. other diseases) and detection of disease at a very early stage. The latter is important for lung cancer detection, for example, because cancer survival is significantly increased when detected at stage 0 or 1 compared to stage 3 or 4.

[0141]

[0327] In particular, in the multiplexed biosensors described herein, the detectable moieties are selected so that the excitation and emission spectra of the co-linked detectable moieties (e.g., fluorophores) have minimal overlap. More specifically, the selection of detectable moieties in the multiplexed embodiments of the biosensors described herein is performed to minimize the occurrence of FRET between detectable moieties such as fluorophores. In this regard, the selection of variable moieties such as, for example, BODIPY dyes seems to be well suited, as they exhibit both narrow excitation and emission spectra, as will be understood by those skilled in the art.

[0328] In a preferred embodiment, the aqueous sample can be heat-treated prior to and / or while the sample is in contact with one or more of the graphene biosensors described herein.

[0142]

[0329] Additionally, in certain embodiments, the sample in the absence of a biosensor described herein may be heat treated at a temperature ranging from 40° C. to 75° C. for 0.5 to 3 hours. Preferably, the sample or serum may be heat treated at a temperature ranging from 50° C. to 60° C. for 0.5 to 2 hours. In certain embodiments, the sample or serum may be heat treated at a temperature of 55° C. for 1 hour.

[0143]

[0330] In certain embodiments of the method for detection of target biomarkers, the test solution is heated in the presence of a biosensor described herein prior to detection. The assay sample or serum in the presence of a biosensor described herein may be heat treated at a temperature ranging from 40° C. to 75° C. for 0.5 to 3 hours. Preferably, the assay sample or serum may be heat treated in the presence of the biosensor at a temperature ranging from 50° C. to 60° C. for 0.5 to 2 hours. In certain embodiments, the assay sample or serum may be heat treated in the presence of the biosensor at a temperature of 55° C. for 1 hour.

[0144]

[0331] In one embodiment, the heat treatment can be performed according to the protocol for heat treatment of samples exemplified in Example 21. Heat treatment can be applied to the sample before or during the assay, or both. The effect of heat treatment is to specifically increase the sample readings while leaving the assay controls unaffected. Thus, the SN increases due to the increased specific signal. Temperatures from room temperature to 75°C are effective. Preferably, the samples can be pretreated at 65°C for 5-12 minutes, or the assay is performed at 41°C or 45°C during incubation.

[0332] In some preferred embodiments, heating is performed on a solution containing a monobasic salt and / or incubation in a buffer solution maintaining a pH of 7.2. In some preferred embodiments, incubation is performed at 45° C.

[0333] Thus, in certain embodiments, the biosensor and / or associated combination can be configured to detect a target biomarker associated with a target condition in an individual, as will be understood by one of skill in the art.

[0145]

[0334] For example, in one or more embodiments, the nanosensor can be configured for rapid diagnosis of pulmonary conditions based on protease activity profiling of two or more proteases (e.g., in a panel). The recognition sequences undergo proteolytic cleavage by their respective proteases or the chemical makeup of the post-translational modification sequence changes. For example, arginase I+II converts arginine to ornithine without proteolytic cleavage of the oligopeptide. Thus, the methods described herein can also be adapted for use with other nanosensors, such as those described in WO 2016 / 149637 for the detection of enzymatic post-translational modifications, as will be appreciated by those skilled in the art. The nanobiosensors and methods can be used to detect target biomarkers and thereby diagnose a number of pulmonary conditions, including pulmonary diseases, cancer, and infectious diseases.

[0146]

[0335] In one embodiment, a nanobiosensor for chronic inflammatory lung diseases (asthma, COPD, fibrosis) targets the proteases reported in Table 4 with their corresponding recognition sequences for peptide binding.

[0147] [Table 11] *Except where noted, sequences further include an N-terminal GAG spacer and a C-terminal AG spacer.

[0148]

[0336] In an embodiment, a nanobiosensor for pulmonary hypertension (PAH) can be configured to target the proteases reported in Table 5 along with their corresponding recognition sequences for peptide binding.

[0149] [Table 12] *Except where noted, sequences further include an N-terminal GAG spacer and a C-terminal AG spacer.

[0150]

[0337] PAH can lead to secondary complications such as COPD (chronic obstructive pulmonary disease), asthma, and chronic bronchitis. The activity of three MMPs is enhanced in PAH, MMP-2, -9, and -14 (MT1-MMP-1). MMP-2 and MMP-9 can cleave basement membrane-bound collagen IV, which accelerates the remodeling of the pulmonary vasculature. MMP-14 is membrane-bound but can be detected in liquid biopsies (serum, BALF, and potentially EBC) in disease states.

[0151]

[0338] In an embodiment, a nanobiosensor can be designed for detection of influenza virus infection targeting the proteases reported in Table 6 along with the corresponding recognition sequences for peptide binding.

[0152] [Table 13] *Except where noted, sequences further include an N-terminal GAG spacer and a C-terminal AG spacer.

[0153]

[0339] In an embodiment, the biosensor of the present disclosure can be configured for detection of other proteases in the lungs, such as TMPRSS2 (epithesin) and trypsin-like peptidase (HAT), which promote influenza virus infection H1N1 (A / Memphis / 14 / 96), H2N9 (A / Mallard / Alberta / 205 / 98), and H3N2 (A / Texas / 6 / 96); in these conditions, when hemagglutinin (HA) is cleaved, the viral pathogen can stimulate protease expression in the "influenza cytokine protease cycle." Granzymes are also known to activate H1N1. Therefore, we included granzyme B in this panel. The advantage of the latter is that it can be detected in EBCs, as will be appreciated by those skilled in the art.

[0154]

[0340] In one embodiment, the nanobiosensor detects viral infection by targeting the activity of kallikrein in the lung. Kallikrein (KLK) is a family of proteases consisting of 15 closely related secreted serine proteases with either trypsin-like or chymotrypsin-like specificity. KLK-2, KLK-3, KLK-4, KLK-5, KLK-6, KLK-12, and KLK-15 are poorly expressed in the lungs of healthy individuals. This expression pattern changes in response to viral infection. In the case of influenza infection, the expression of KLK-1, KLK-2, and KLK-5 increases, while the expression of KLK-13 and KLK-14 decreases. KLK-13 increases in virtually all coronaviruses (SARS and MERS types). Infection. Exemplary kallikreins and the associated corresponding exemplary recognition sequences for peptide binding are reported in Table 7.

[0155] [Table 14] *Except where noted, sequences further include an N-terminal GAG spacer and a C-terminal AG spacer. ** includes an N-terminal GAG spacer and a C-terminal GA spacer. *** includes an N-terminal GAA spacer and a C-terminal AG spacer.

[0156]

[0341] In one embodiment, the biosensor can be configured for detection of target bacterial proteases in Streptococcus pneumoniae infection. Exemplary proteases that are target biomarkers for Streptococcus pneumococcus and the associated corresponding exemplary recognition sequences of peptide bonds are reported in Table 8.

[0157] [Table 15] ** includes an N-terminal GAG spacer and a C-terminal GA spacer.

[0342] S. pneumococcus is the most common bacterial infection in the lungs, and as will be appreciated by those skilled in the art, most, if not all, streptococci express S. pneumococcus IgA1 protease. This protease is therefore one of the most active proteases known and is only present in the case of streptococcal infections. It allows for a rapid test (<10 min) for bacterial lung infections.

[0158]

[0343] In one embodiment, the nanobiosensor for detecting Mycobacterium tuberculosis infection targets the following proteases: Exemplary proteases that are target biomarkers for (Mycobacterium tuberculosis) and the associated corresponding exemplary recognition sequences of peptide bonds are reported in Table 9.

[0159] [Table 16] ** includes an N-terminal GAG spacer and a C-terminal GA spacer.

[0344] Further secreted M. tuberculosis proteases that can be used as target biomarkers are MycP1 and Rv2869c (M. tuberculosis)-like peptidase (RIP-1), both of which are specific for MTb, as will be appreciated by those of skill in the art.

[0160]

[0345] In an embodiment, the nanobiosensor of the present disclosure can be configured for the detection of chronic obstructive pulmonary disease (COPD). Exemplary proteases that are target biomarkers for COPD and the associated corresponding exemplary recognition sequences for peptide bonds are reported in Table 10.

[0161] [Table 17] *Except where noted, sequences further include an N-terminal GAG spacer and a C-terminal AG spacer. **** includes an N-terminal GAP spacer and a C-terminal AG spacer. ***** includes an N-terminal GAA spacer and a C-terminal EG spacer.

[0162]

[0346] Further target biomarkers for COPD can be identified and selected based on the fact that endogenous serine protease inhibitors are involved in lung tissue protection against serine proteases in healthy human subjects. Genetic inhibitor deficiency is believed to be the most important reason for the development of COPD, followed by smoking. In the absence of effective inhibitors, uncontrolled protein degradation and subsequent lung damage are observed. The most important proteases for COPD detection are neutrophil elastase, neutrophil-derived MMP-8, macrophage-derived MMP-12, cathepsin G and proteinase 3. These proteases can damage ECM components such as collagen, laminin, fibrillin, and elastin. In particular, cleavage of pulmonary elastin leads to emphysema, which is a driving force in COPD pathophysiology. MMP-7 degrades the extracellular proteoglycan decorin, leading to the subsequent release of decorin-bound transforming growth factor-β (TGF-β). Thus, the simultaneous activation of all six proteases (NE, MMP-7, -8, -12, CTSG, and proteinase 3) allows the detection of COPD.

[0163]

[0347] In one embodiment, the nanobiosensor detects lung cancer using a panel of proteases and distinguishes between small cell lung cancer (SCLC) and non-small cell lung cancer (NSCLC) targets: Exemplary proteases that are target biomarkers for SCLC and NSCLC, and the associated corresponding exemplary recognition sequences for peptide bonds are reported in Table 11.

[0164] [Table 18] *Except where noted, sequences further include an N-terminal GAG spacer and a C-terminal AG spacer. ****** includes an N-terminal GAA spacer and a C-terminal AG spacer.

[0165]

[0348] In an embodiment, relevant data sets for the selection of proteases for the detection of SCLC and NSCLC versus non-cancerous health conditions and for the distinction between SCLC and NSCLC can be obtained from the NCBI geo database (see website www.ncbi.nlm.nih.gov / geo / as of the filing date of this disclosure). Data sets included in the analysis were obtained from human cancers, with data sets including both primary tumor samples and healthy human tissues. Exemplary calculated p-values ​​for SCLC and NSCLC are reported in Table 12 below.

[0166] [Table 19]

[0349] Based on these gene expression data, the selected panel of enzymes should be able to distinguish between SCLC and NSCLC.

[0350] The distinction between SCLC and NSCLC is important because of the different treatment approaches for each type of cancer. The main subtypes of NSCLC are adenocarcinoma, squamous cell carcinoma, and large cell carcinoma. These subtypes, which begin with different types of lung cells, are grouped together as NSCLC because their treatments and prognoses (outlooks) are often similar. A smaller subset of all lung cancers is SCLC. This subset is more sensitive to chemotherapy and radiation treatments, but their overall mortality rate is higher.

[0167]

[0351] Furthermore, similar to pancreatic cancer, the protease signature changes distinctly during the transition from non-cancerous to cancerous, allowing detection of NSCLC at stages 0 and 1 by liquid biopsy. Primarily, the same selection of proteases / arginase can distinguish SCLC from healthy tissue. Based on the differences in gene expression, MMP10 and cathepsin H can be selected as suitable proteases to distinguish SCLC from NSCLC.

[0352] Similar gene expression analysis, including using databases such as NCBIgEO, Entrezgene ID, Unigene ID and Gene Symbol, can be used to determine proteases that are overexpressed in other solid tumors, such as pancreatic cancer. This strategy can select enzyme candidates from the human genome that have a high probability of being proximal biomarkers for pancreatic cancer.

[0353] These target panel arrays and detection platforms can be any of the assays described herein, including solution-based assays, microfluidics assays, microwell assays, high-throughput assays, and the like, including those described in U.S. Pat. Nos. 8,969,027; 9,682,155; 9,731,034; and 9,216,154, which are incorporated by reference herein, and co-pending International Publication WO 2017 / 165800, filed March 24, 2017 (U.S. Patent Application Publication No. 2020 / 0300849).

[0168]

[0354] In a further preferred embodiment, inflammatory biological markers can be detected along with the detection of specific viral, bacterial, or fungal infections. For example, nanosensors can be prepared using peptide aptamers against capsid B (AISGSGGSTYYANSVLG (SEQ ID NO: 71), a recognition sequence for detecting Haemophilus influenzae B, or Haemophilus influenzae NT (TNLGILHSMVARAVGNNTQG (SEQ ID NO: 72)), or Moraxella catarrhalis (GIITYALSGGEIKILAG (SEQ ID NO: 73)). Similarly, nanosensors for viral infections can be prepared using protease recognition sequences (SAVL-LEAT (SEQ ID NO: 74) or SQNY-PIVQ (SEQ ID NO: 75)) for HIV detection.

[0169]

[0355] It will be appreciated that each of the aforementioned sensors above can be designed in alternative configurations in which the graphene core particle is linked via a modifiable recognition sequence, a protease recognition sequence, a post-translationally modifiable sequence nt bond that interacts with the target biomarker. In such embodiments, the detectable particle remains relatively stationary and attached to the carrier particle, but instead the quencher particle is cleaved or moved away from the detectable particle and the carrier particle, resulting in a change in the distance between the particles, as described above. As described above, an increase in the distance between the graphene core particle and the detectable particle (from cleavage or elongation of the quencher particle tether) results in a detectable change in the signal from the nanosensor.

[0170]

[0356] In one or more embodiments, the sensor according to the present disclosure can be used to diagnose lower airway infection by detecting markers associated with infection of infected lower airway epithelial cells. These markers include CCL20, TSLP, and CCL3-L1. As described herein, exosome content can be used to determine whether the exosome originates from the upper or lower airways, further aiding in localizing where an infection or other condition may originate in the subject's body. The sensor can also be used for environmental risk assessment in patients with chronic lung disease. Exposure to air pollutants, ozone, particulates, acetaldehyde, acrolein, formaldehyde, cigarette smoke, and other compounds cause inflammation of the airways. Detection of markers such as cytokines, proteases, and / or kinases can be used to identify the stage at which lower airway inflammation is evident, allowing for personalized environmental assessment. The nanosensor can also be used to measure lower airway inflammation in real-time management of inflammation in asthma. Further details regarding understanding biological markers and protein expression patterns associated with severe asthma are described in U.S. Patent No. 8,053,199, which is incorporated herein by reference. Currently, anti-inflammatory drugs (corticosteroids, IL-13 antibodies, etc.) are administered and monitored based on symptoms and exacerbations. By testing for lower airway markers such as cytokines, proteases, and / or kinases, patients and caregivers can track inflammation in real time and adjust treatment accordingly. Similarly, nanosensors can be used to measure lower airway remodeling in severe asthma and chronic obstructive pulmonary disease (COPD). Remodeling refers to the process of fibrosis of the airways and is associated with progressive lung function decline in a subset of patients with severe asthma and COPD. There are currently no available treatments or diagnostics. New therapies targeting epigenetic remodeling are currently being developed. Our method allows for the development and approval of remodeling inhibitors for clinical use by detecting and measuring the presence of fibronectin, IL6, or vimentin as indicators of progressive airway remodeling.

[0171]

[0357] In an embodiment, the sensor of the present disclosure can be used in connection with the detection of opportunistic infections. Opportunistic infections are also important complications in patients undergoing treatment for cancer, patients who are immunosuppressed by treatment for rheumatoid arthritis or inflammatory bowel disease, or patients with HIV. Pneumocystis pneumonia (PCP) is the most common infection in HIV patients and can currently only be diagnosed by invasive bronchoscopy. Invasive aspergillosis is also an opportunistic lung infection that occurs in patients undergoing chemotherapy for leukemia. When fungi invade the airways in patients who are immunosuppressed from leukemia treatment, nanosensors can be used to indicate the presence of distinct host response proteins.

[0172]

[0358] In an embodiment, the sensor of the present disclosure can also be used to monitor transplant rejection or host-versus-graft disease in lung transplants. Lung transplant patients are treated with intensive immunosuppressive therapy, and their physicians walk a fine line between too much immunosuppression (suffering opportunistic infections) or too little immunosuppression (rejecting the organ). If transplant patients could monitor their immune profile on a real-time basis, this would make the management of the transplant much easier. It will also be appreciated that nanosensors can be used to monitor the response to lung cancer treatment. Mobile biosensing detects cancer signatures such as cytokines, proteases, and / or kinases (e.g., MMPs, EMT, etc.) in the airways or circulating in the blood. This includes free proteins and proteins contained within microparticles (exosomes).

[0173]

[0359] In certain embodiments, the sensors of the present disclosure can be used in conjunction with protein sample collection, processing, profiling, and detection. The embodiments described herein can also be utilized in conjunction with conventional PCR / RT-PCR, real-time quantitative PCR / RT-PCR, and isothermal PCR / RT-PCR methods to assess bacterial, viral, and fungal infections associated with increased or decreased protein level expression. Thus, the assays according to the present invention can be used as stand-alone techniques and / or in conjunction with conventional approaches, particularly in risk groups previously identified as at risk by genetic testing.

[0174]

[0360] In general, detection performed by the sensors of the present disclosure involves contacting a prepared sample with a nanosensor (and generally multiple nanosensors) to produce a reaction mixture. The nanosensor can then be probed or excited with an appropriate energy source. The wavelengths used depend on the particles used in the nanosensor. A change in the absorption and / or emission of the particle is then detected over a period of time as the target biomarker interacts with the nanosensor (e.g., binding and extension of the recognition sequence and / or a change in emission).

[0175]

[0361] The embodiments described herein also rely on nanosensors integrated with microfluidic and smart device platforms, which can then be read by simple yet robust fluorescent or optical readers. "Microfluidic" refers generally to volumes on the order of microliters (10 -6 ) to picoliters (10 -12) range. In one aspect, microfluidic technology is used to introduce rapid high-throughput sample collection, sample processing, sample profiling and target detection. In a further preferred embodiment, the microfluidic device interfaces with a mobile computing device, such as, but not limited to, a smartphone or smart tablet. Mobile computing devices, including tablets, smartphones, handheld computers, laptops, etc., that can transmit information to other computing devices. This integrated platform revolutionizes the current "traditional" protocols using multiple instruments with time-consuming manual sample handling. In a further preferred embodiment, a standalone battery-powered diagnostic platform with rapid analysis time and multiplexing capabilities achieves statistical significance of the measured quantities with minimal consumption of human body fluids (<5 μl / sampling) using a handheld smartphone-based system that can be used as a diagnostic tool by patients and medical professionals.

[0176]

[0362] In some embodiments, the assay performed using the biosensor of the present disclosure can utilize a combination of two or more of the various sensors described above. Importantly, the nanosensor utilized according to the present disclosure can be designed to include supramolecular recognition sequences, protease recognition sequences, and post-translationally modifiable sequences that cause specific interactions with biological markers. As used herein, the reference to "specific interaction" is intended to distinguish the interaction between the recognition sequences of the sensor from non-specific binding or reaction between molecules, and means that the set of specific target analytes with which the oligopeptide sequence can interact is limited, and in some cases even exclusive, such that neither binding nor enzymatic cleavage occurs at an appreciable rate with other molecules.

[0177]

[0363] The methods of the present disclosure can be carried out using corresponding systems that include various combinations of layered graphene, organic and / or inorganic molecules, detectable moieties, peptide bonds, detectable components, biosensors, reagents for carrying out the chemical reactions described herein, as well as additional components identifiable by one of skill in the art.

[0364] Exemplary optical detection techniques are described. However, it should be understood that other methods of analyzing the assay can be used. In general, the method involves exposing the reaction solution (e.g., in a microwell) to a suitable energy source. The wavelength used depends on the detectable label used in the biosensor. Both the location / presence and concentration / intensity of the signal from the detectable moiety can then be sensed or detected using a suitable sensing or detection instrument for both quantitative and qualitative evaluation of the detectable moiety.

[0178]

[0365] The system disclosed herein may be provided in the form of a kit of parts. In a kit of parts for carrying out any one of the methods described herein for making a biosensor, graphene particles may be included in the kit alone or in the presence of one or more buffers and reagents for carrying out chemical transformation of the graphene particles. In a kit for detecting biomarkers, one or more biosensors described herein may be included in the kit alone or in the presence of one or more buffers and reagents for carrying out detection of one or more biomarkers. Additional components identifiable by those skilled in the art may also be included.

[0366] In the components, the graphene particles, biosensors and reagents are included separately in the kit, or in some cases, in a composition together with a suitable vehicle, carrier or adjuvant. For example, one or more biosensors can be included in one or more compositions together with the reagents for detection in one or more suitable compositions. The additional components can include labels, reference standards, and additional components identifiable by one of skill in the art upon reading this disclosure.

[0179]

[0367] In the embodiments described herein, the components of the kit may be provided with appropriate instructions and other necessary reagents to carry out the methods disclosed herein. The kit typically contains the compositions in separate containers. Instructions are typically included in the kit, e.g., written or audio instructions on paper or tape, CD-ROM, electronic support such as flash drive, or instructions by indication of a Uniform Resource Locator (URL) containing a pdf copy of the instructions for carrying out the assay. The kit may also include other packaged reagents and materials (i.e., washing buffers, etc.), depending on the particular method to be used.

[0368] The identification of suitable adjuvants for the compositions, as well as further details regarding the manufacture and packaging of kits in general, can be identified by one of skill in the art upon reading this disclosure.

[0180] [Example]

[0369] The following examples illustrate methods according to the present disclosure, however, it should be understood that these examples are provided for illustrative purposes and that nothing therein should be construed as a limitation on the overall scope of the present disclosure. EXAMPLES

[0181] Photochemical properties of graphene and metals

[0370] Graphene contains at least 98% carbon and in aerated aqueous buffers exhibits minimal reaction with water or aqueous buffers as well as thiol functional groups (e.g., those presented on proteins and glutathione). These properties are opposite to those of metal / metal oxide materials.

[0371] The UV / V absorption of graphene in the ultraviolet (UV), visible, and near-infrared (IR) regions exceeds that of graphite.

[28] In particular, stacked graphene is characterized by light absorption across the entire wavelength range from far UV to mid-IR (100-1500 nm).[6]

[0372] Direct excitation occurs in the deep / far UV, but the surface plasmons of graphene in the visible range are too strong to effectively excite attached organic fluorescent dyes or nanoparticles.[6]

[0373] In contrast, many nanoparticles (especially Au, Ag, but also Fe in Fe / Fe3O4) exhibit strong plasmons in the visible range of the electromagnetic spectrum, which contribute to both fluorophore excitation and quenching.[29,30] In graphene, plasmonic excitation in the visible range of the spectrum can arise from energy transfer from nearby attached fluorescent organic dyes, and is expected from metallic nanostructures and quantum dots as well.

[31]

[0374] Due to the photophysical properties of graphene, it is not necessary to incorporate a FRET acceptor per fluorophore into the design, which allows for multitasking and avoids overcrowding at the surface of the nanobiosensor, which would significantly slow down the kinetics of the nanobiosensor.

[0375] Due to the photophysical properties of graphene, when graphene is used in a FRET pair, it is not necessary to incorporate a FRET acceptor into the design to complement the FRET donor (such as a fluorophore). These properties of graphene allow the user to minimize overcrowding at the surface of the nanobiosensor, which, as will be appreciated by those skilled in the art, can significantly slow down the kinetics of the nanobiosensor.

[0376] In addition to the above, some forms of graphene, such as exploded graphene and some fractions from flash graphene, have a hyper-aggregated fractal morphology that can be confirmed by light scattering techniques such as SEM (scanning electron microscopy) and light scattering.[18,19]

[0377] An exemplary SEM (scanning electron microscope) image of a fractal graphene containing seven layers is reported in Figure 1. [8]

[0378] As can be seen from the illustration in Figure 1, the graphene stacks are characterized by a fractal dimension between Df = 2.5 ± 0.3 (upper limit) and Df = 1.8 ± 0.4 (lower limit). In general, depending on the size and surface modification of the exploded graphene, any fractal dimension between Df = 2.9 ± 0.09 and Df = 2.1 ± 0.09 can be achieved.

[0379] The fractal shape of exploded graphene enhances light absorption because light is "trapped" within the structure. In a flat graphene sheet, light passes through the graphene only once, but light reflection and diffraction from within the fractal morphology causes multiple absorption events, as will be understood by those skilled in the art. EXAMPLES

[0182] Overview of biosensors and manufacturing methods

[0380] A schematic diagram of the main components of the biosensor described herein is provided in FIG. 2A in relation to an exemplary embodiment in which the graphene is provided by exploded graphene and the coating of the core particle is provided by a polymer coating.

[0381] In an exemplary configuration shown generally in Figure 2A, nanosheets of exploded graphene aggregates are used to provide a graphene component of a core particle coated with a monolayer of a polymer coating. A detection component formed by a peptide bond comprising a recognition sequence and a detectable moiety is further attached to the core particle via a bond to the polymer coating.

[0183]

[0382] A biosensor having the structure shown in FIG. 2A can be provided using an exemplary process shown in FIG. 2B. In the schematic diagram of FIG. 2B, a graphene surface is functionalized, for example, with multiple carboxylic acid groups and / or coated with a thin polymer monolayer. In the exemplary diagram of FIG. 2B, multiple detectable moieties can be attached to the same carrier particle via respective oligopeptide bonds. For example, as shown in FIG. 2B, two or more different detectable moieties can be attached to the same carrier particle via respective oligopeptide bonds with specificity for respective target biomarkers.

[0184]

[0383] In particular, the schematic diagram in Figure 1. 2B shows the design of the novel biosensor: A: synthesis of carboxygraphene; B: chemical conjugation of polyethyleneimine via an amide bond; C: conjugation of the recognition sequence (oligopeptide) and the fluorescent dye (TCPP). TCPP is attached to the N-terminus of the oligopeptide while on the resin. After cleavage from the resin and HPLC purification (if necessary), the recognition sequence + TCPP is attached to the polyethyleneimine by its C-terminus. For kinetic reasons, the recognition sequence + TCPP is attached via the C-terminus of the oligopeptide. In the presence of the correct protease, the recognition sequence is proteolytically cleaved and the fluorescent dye TCPP+ covalently attached to the recognition sequence half is released (photoswitch effect).

[0384] A further schematic diagram of a more ordered stack of nanosheets, including or consisting of thin monolayers or 2-3 layers of graphene entangled with each other at their overlapping edges, is reported in FIG. 2C.

[0385] A schematic diagram of the high density of carboxylic acid groups added across the surface of the graphene nanosheet particulate is reported in Figure 2D.

[0386] Further details regarding the process for carboxylation of graphene and attachment of detectable moieties via the PEI polymer coating are reported in Examples 3 to 9. EXAMPLES

[0185] Carboxygraphene synthesis – general method

[0387] To synthesize the graphene derivative referred to herein as "carboxygraphene," degassed graphene (0.2-0.5) nanoparticles (nanosheet particles) are dispersed in anhydrous dimethylformamide (DMF) at room temperature.

[0388] After dispersion is complete, a carboxylic acid bearing a primary or secondary halogen is added, followed by anhydrous sodium azide (NaN3). The temperature is then slowly increased (1°C / min) to 80°C. At 20°C-40°C, a nucleophilic substitution reaction (SN) occurs, in which an organic azide and a DMF soluble sodium halide are formed. The organic azide releases dinitrogen (N2) and forms a nitrene intermediate at temperatures >50°C. Nitrenes feature six electrons instead of eight in the nitrogen outer shell. This reactive intermediate undergoes cycloaddition with (S)-amines. II-II double bonds form on the surface of graphene to form stable aziran anchors.

[0389] Aziran cycloaddition offers the opportunity to add controlled amounts of carboxylic acids to the surface of graphene without compromising its optical and electronic properties.

[0390] Exemplary reaction schemes and protocols are outlined in Example 4. EXAMPLES

[0186] Graphene derivatization (Carboxygraphene (CG))

[0391] An exemplary reaction scheme for the synthesis of carboxygraphene from exploded graphene in a one-pot reaction is shown in FIG. 3A.

[0392] The protocol begins with detonation-synthesized graphene (0.40) nanosheet microparticles with an elemental composition of 98.9% C, 0.08% H, and 1.02% O. The material is then reacted with bromovaleric acid and sodium azide to obtain carboxygraphene (CG) as follows:

[0393] 1.0 g of graphene nanosheet (GN) microparticles were suspended in 20 mL of DMF at 20 °C in a 250 mL three-neck round bottom flask. Then, at 40 °C, 0.50 g of 5-bromovaleric acid (0.0028 mol) as well as 0.18 g of NaN3 crystals were added to the GN suspension. After NaN3 was dissolved, the suspension was slowly heated (~1 °C / min) to 80 °C and stirred for 1 h. Evolution of N2 was observed. Finally, after 1 h, the suspension was cooled to room temperature and the derivatized GN was collected by centrifugation (7,000 RPM for 5 min) and washed 5 times with DMF and then 3 times with anhydrous diethyl ether. The obtained CG was dried at 50 °C for 1 h and then stored under argon for characterization. Yield: 82% (by mass assuming total reaction). The elemental analysis of carboxygraphene is 94.22% C, 1.79% H, 1.17% N, and 2.82% O. The incorporation of N indicates that the addition reaction was successful.

[0394] A schematic structure of carboxygraphene, in which only a single graphene nanosheet is shown, is reported in Figure 3B, and a side view of the carboxygraphene top layer showing a dense distribution of carboxylic acid groups across the surface is reported in Figure 3C.

[0395] As shown in Figure 3D, differential thermal analysis (DTA) indicates a mass loss of 4.5 ± 0.5 wt % when heated above 100 °C. At temperatures above 100 °C, the material is essentially stable, as expected for graphene. The initial mass loss results from partial loss of valeric acid units attached to the outer shell of carboxygraphene. EXAMPLES

[0187] Carboxygraphene (CG) titration

[0396] 100 mg of carboxygraphene (CG) was suspended in 20 mL of 0.100 M NaOH. The suspension was stirred at 300 K for 5 min, after which a 0.100 M HCl solution was added stepwise. At each step, after ensuring that equilibrium had been reached (1–5 min), the pH of the solution was recorded using a pH meter before adding the next amount of HCl. The same procedure was used with the same volume of NaOH, but without the addition of carboxygraphene.

[0397] As shown in Figure 4, the difference in the volume of HCl in the two titration curves for the same value of pH around 7.00 gives the concentration of ionized groups (carboxyl groups) per mass gain of carboxygraphene. -4 mol / g of acidic groups (-COOH) (i.e., a surface density of 4-COOH groups per nm2). For comparison, this is 1.7 x 10 -4 mol / g (i.e., surface density of 1-COOH group per nm2) is 4 times higher than that of our Fenton graphene oxide. This density of -COOH groups on the carboxygraphene surface corresponds to an average spacing of 0.27 nm2 per -COOH group in the synthesized carboxygraphene. This corresponds to an extremely high labeling density by surface -COOH groups and contributes to the much higher water dispersibility of these carboxygraphene nanosheet microparticles.

[0398] It will be appreciated that the synthesis of carboxygraphene is further simplified compared to Fenton graphene oxide, with faster reaction times. The process also does not involve the addition of iron salts, which somewhat interfere with the photophysical properties of the bound fluorophores in the biosensors described herein. EXAMPLES

[0188] Carboxygraphene-polyethylenimine (G-PEI)

[0399] An exemplary synthetic procedure for tethering polyethyleneimine to carboxygraphene to produce polyethyleneimine-derivatized carboxygraphene is described below.

[0400] 100 mg of carboxygraphene synthesized above was suspended in 20 mL anhydrous DMF in a 50 mL round bottom flask at room temperature. Then, 50 mg of polyethyleneimine, branched, molecular weight 10,000 (PEI), 25 mg of 1-ethyl-3-(3-dimethylaminopropyl) carbodiimide (EDC), and 25 mg of 4-dimethylaminopyridine (DMAP) were added to the carboxygraphene solution. The reaction was stirred overnight at room temperature. The carboxygraphene-polyethyleneimine (G-PEI) was then collected by centrifugation (7000 RPM for 5 min) and washed twice with DMF and three times with diethyl ether. The material was collected by centrifugation after each wash. Yield: 65% (by mass assuming total reaction).

[0401] A schematic diagram of the resulting carboxygraphene-polyethylenimine structure is shown in Figure 5A, with only one sheet shown for reference. Elemental analysis of the resulting carboxygraphene-PEI: 82.58% C, 4.65% H, 10.65% N, and 2.12% O. The significant increase in N content indicates that the addition reaction of PEI was successful. Based on the N content, we estimate that the resulting carboxygraphene-PEI contains 27±2% PEI.

[0402] Differential thermal analysis (DTA), shown in Figure 5B, indicates a mass loss of 4.5 ± 0.5 wt % beginning at 150 °C and extending over the entire temperature range. This behavior is clearly distinct from carboxygraphene and is consistent with the stabilization of the graphene nanosheets by polyethyleneimine attachment. EXAMPLES

[0189] Synthesis of PEI-coated exploded graphene-based biosensors

[0403] The sensing components formed by tetra(4-carboxyphenyl)porphyrin (TCPP) and the peptide cleavage sequence of MMP-1 (GAGVPMS-MRGGAG) were attached to a PEI-coated graphene-based biosensor according to the following protocol.

[0404] 50 mg of the carboxygraphene-PEI synthesized above was suspended in approximately 8.1 mL of DMF in a small glass vial. 5 mg of DMAP and 5 mg of EDC were then added to the vial along with approximately 3.5 mg of TCPP pre-conjugated with a peptide cleavage sequence for MMP-1 (GAGVPMS MRGGAG). The sample was sonicated for 5 minutes to ensure that everything was suspended in the DMF. The reaction was then stirred overnight at room temperature.

[0405] The biosensor was collected by centrifugation (7000 RPM for 5 min), washed with DMF, and washed three times with diethyl ether. Figure 6A shows the structure of the carboxygraphene-polyethylenimine based biosensor, where only a single sheet is shown for reference.

[0406] The synthesized materials were analyzed by spectroscopy. As shown in Figure 6B, the UV / Vis spectra of carboxygraphene, carboxygraphene-PEI, and carboxygraphene-biosensor for MMP-1 in water were analyzed. The Soret band of the TCPP detectable label is clearly identifiable at about 420 nm. TCPP is tethered to the polyethyleneimine layer via a peptide containing the recognition sequence of MMP-1. The 135,000 M -1 cm -1 Based on the estimated absorption coefficient of , the TCPP concentration is 1.63 × 10 per gram of carboxygraphene. -5 It is a mole.

[0407] Further exemplary detectable moieties that can be added in the process outlined above are reported in FIG. 6C, which shows BODIPY dyes with no or minimal overlap between their excitation and absorption spectra, including BODIPY FL, BODIPY TR, BODIPY 530550, and BODIPY 630650. EXAMPLES

[0190] Further functionalization of the graphene surface

[0408] In the previous examples, graphene surface functionalization was performed to tether carboxylic acid groups to the surface of graphene, and then polyethyleneimine (or primarily other polymers) was attached to the carboxylic acid functional groups via stable amide bonds.

[0409] Further functional groups can be presented on the surface of graphene, for example through modification of carboxyl groups. Those skilled in the art can use the entire toolbox of organic chemistry to perform such functionalization.

[32] This is applicable for anchoring polymers or monomers to the surface of graphene. See, for example, the following exemplary reactions: -Conversion of carboxylic acids to alcohols and formation of stable ethers -Conversion of carboxylic acids to esters -Conversion of the carboxylic acid to an aldehyde and then to a double bond (Wittig type reaction). -Converting a carboxylic acid into a carbon center with an available leaving group, followed by a nuclear displacement reaction It is.

[0410] As will be appreciated by those skilled in the art, further reactions can be used on the graphene, with or without prior functionalization, to present functional groups configured to bond to corresponding functional groups on organic or inorganic compounds or directly on peptide bonds. These reactions include: Click reactions [33,34], especially the Diels-Alder reaction [35,36], can be carried out directly with the graphene surface or to connect peptide sequences to tethers that are already attached to the surface. Addition of radicals (e.g., carbon-, nitrogen-, oxygen-, and sulfur-centered) to the surface of graphene [37, 38] Addition of electrophiles (e.g., carbon, nitrogen, oxygen, and sulfur-based) to the surface of graphene

[38]

[0411] In embodiments where functionalization is performed to provide carboxygraphene according to titration experiments of carboxygraphene and molecular modeling, the highest possible packing density of linear molecules attached to the surface of graphene is 6.0±0.5×10-4 The lower limit at which water dispersibility can still be observed is 2.40±0.05×10 -5 It is in mol / g.

[0412] As will be appreciated by those skilled in the art, additional maximum and minimum packing densities can be specified for different functionalizations. When synthesizing asymmetric nanobiosensors featuring a surface area of ​​unsubstituted (pure) graphene, this area is not greater than 10 relative percent in order to minimize interference with the fluorescence readout of the particles due to adsorption and quenching of fluorescent dyes previously cleaved at the surface of the graphene. EXAMPLES

[0191] Direct and indirect attachment of peptides to carboxylated graphene

[0413] In an alternative attachment process for the detection moiety, instead of utilizing polyethyleneimine or other water soluble polymers, a peptide sequence linked to a fluorescent dye can also be directly linked to the carboxyl group of carboxygraphene.

[0414] In some cases, in addition to or instead of direct attachment to the graphene surface, peptide bonds can be indirectly attached via a spacer or connercor presenting an amine group for binding to the carboxylate. To that end, lysine, ornithine, or any unnatural amino acid featuring a spacer and an accessible extra primary amine can be utilized to facilitate attachment, as shown by the schematic diagram in FIG.

[0415] Spacers can be used by one skilled in the art in combination with the desired peptide bond while controlling the particle size to obtain the desired distance between the particle and the detectable moiety.

[0416] A special class of "connectors" between the central graphene-based nanostructure and the detectable components of the biosensors described herein (e.g., fluorophore-linked recognition sequences) are supramolecular systems. Numerous supramolecular host-guest systems have been published in the literature.

[39]

[40] The following host-guest systems are noteworthy: a) Biotin / Streptavidin

[41] b) Cyclodextrin and various hosts

[42] c) Stodart-cyclophane and a hydrophilic host

[43] d) Cucurbituril and tailored host

[44] e) (structurally modified) DNA assemblies

[45] f) Nucleic acid / peptide hybrids

[46] g) Supramolecular binding of designer peptides

[47] EXAMPLES

[0192] Chemical amination of graphene surfaces and attachment of peptide bonds

[0417] An exemplary further chemical amination of graphene surfaces, such as the reaction of aromatic substituted nitrenes for chemical amination of graphene surfaces, is as follows.

[20] It is shown diagrammatically in FIG.

[0418] According to the exemplary protocol, 1.0 g of graphene nanosheet (GN) microparticles were suspended in 20 mL of DMF at 20 °C in a 250 mL three-neck round-bottom flask. Then, at 40 °C, 0.50 g of 1-amino-4-bromo-butane (0.0033 mol) as well as 0.20 g of NaN3 crystals were added to the GN suspension. After NaN3 was dissolved, the suspension was slowly heated to 80 °C (approximately 1 °C / min) and stirred for 1 h. Evolution of N2 was observed. Finally, after 1 h, the suspension was cooled to room temperature and the derivatized GN was collected by centrifugation (7,000 RPM for 5 min) and washed 5 times with DMF and then 3 times with anhydrous diethyl ether. The obtained graphene amine (GA) was dried at 50 °C for 1 h and then stored under argon for characterization. Yield: 80% (by mass assuming total reaction). The elemental analysis of carboxygraphene is 95.48% C, 1.86% H, 2.38% N, and 0.28% O. The incorporation of N indicates that the addition reaction was successful.

[0419] To add the detectable component TCPP-GAG RPFS-MIMG AEG, 1.00 g of GA was dispersed in 30 mL of DMF in a flask equipped with a stir bar. 0.54 g of EDC and 0.53 g of DMAP were added and stirred at room temperature until dissolved. 0.20 g of TCPP-GAG RPFS-MIMG AEG was added and the reaction was stirred for 21 hours. The CGP particles were washed four times with DMF using centrifugation as above and three times with ethyl ether. The GA recognition sequence of the MMP 3-TCPP labeled particles was dried by flushing with argon and keeping loosely covered at room temperature for 48 hours. This reaction can be carried out with any peptide designed and constructed as a peptide bond (recognition sequence, post-translational modification and supramolecular bond) within the meaning of this disclosure. EXAMPLES

[0193] Reaction of graphene-embedded carbocations with secondary amine groups of PEI

[0420] Further binding reactions of PEI can be carried out via binding of secondary amine groups with carbocations in the exploded graphene.

[0421] In exploded graphene 0.3, a large number of "holes" (carbocations) are embedded within the structure, thus giving rise to a zeta potential of +60 mV. [8] The holes near the surface can react with polyethyleneimine as shown above. It is noteworthy that nucleophilic addition reactions can occur between exploded graphene and virtually all (polymers, monomers, and small molecules) alcohols, thiols, amines, phosphines, and potentially carboxylic acids.

[0422] In conventional few-layer graphene, hydroxyl and oxirane functional groups can react with PEI. The hydroxyl groups form carbocations after elimination, which then react according to the scheme in Figure 9. The oxirane (oxygen-containing three-membered ring) reacts with amines under nucleophilic addition. These reactions covalently bond PEI to the graphene layers. Another possibility for direct attachment of PEI to graphene exists when defects (carbocations) exist in graphene. This allows for direct nucleophilic attachment of PEI to the graphene surface. EXAMPLES

[0194] Electrostatic attraction at the surface of graphene

[0423] Taking advantage of the strong positive charge of exploded graphene, anionic polymers featuring sulfonic acids, aminosulfonic acids, and organosulfates can be adsorbed onto the surface of graphene. The driving force is electrostatic attraction. It should be noted that when block copolymers are used, hydrophobic polymers (e.g., polystyrene, polyisobutylene, polyvinyl chloride, polyethylene, polypropylene, etc.) can be components of the block copolymer. They are adsorbed on the surface of pure graphene, while their hydrophilic components mediate water dispersibility. It should be noted that the surface charge of exploded-graphene is positive (zeta potential = +60 mV). [8] This allows for the combination of hydrophobic and charge attraction when negatively charged polymers such as polystyrene sulfonate are used in block copolymers such as polystyrene. EXAMPLES

[0195] Graphene "Click Chemistry"

[0424] Further reactions allowing attachment of molecules onto the surface of the graphene nanosheets of the core particles described herein can be carried out by click chemistry.

[0425] "Click chemistry" can be carried out on the surface of exploded (and few-layer) graphene. A typical reaction is the Diels-Alder reaction, since it does not require a copper catalyst. Figure 10 shows a scheme of the Diels-Alder reaction between maleimide derivatives and graphene. However, any click reaction can be carried out, mainly involving the addition of thiols on the surface, as described for example in Li et al. 2016.

[48] , Namvari et al., 2014.

[49] and Farivar et al., 2021.

[50] -Addition of electrophiles (e.g., carbon, nitrogen, oxygen, and sulfur-centered) to the surface of graphene [37,38] -Addition of radicals (e.g., carbon, nitrogen, oxygen, and sulfur-centered) to the surface of graphene

[38] and other methods identifiable by the skilled person (see also Example 8). EXAMPLES

[0196] Use of biosensors and related functional principles

[0426] The functional principle of the biosensor described herein for related uses is shown diagrammatically in FIG.

[0427] The schematic in Figure 11 shows that upon interaction with a biological sample containing a target biomarker, the peptide bond is altered (e.g., cleaved or elongated), resulting in a characteristic change in the detectable signal of the detectable moiety used in the sensor, such as a change in the fluorescence spectrum. The observable change in fluorescence (increase, decrease, shift, etc., depending on the detectable moiety) is a function of the presence and / or activity of the biomarker.

[0428] In an exemplary embodiment shown diagrammatically in FIG. 11, upon proteolytic cleavage of the recognition sequence (oligopeptide), the bound fluorophore is released and escapes quenching by the graphene core of the biosensor. An increase in fluorescence and intensity that is a function of protease activity is observed. Instead of particle-based biosensors, biosensors can be constructed using similar components, except that the graphene is first immobilized on a solid support (e.g., a planar substrate) onto which other elements, e.g., peptide bonds, and then detectable moieties, are attached to create a planar sensor, e.g., a lateral flow type sensor or a fixed microwell sensor. As will be understood by those of skill in the art upon reading this disclosure, the sensor otherwise operates in the same way, a sample is added to the solid support, and binding or cleavage by the target biomarker in the sample results in a detectable change in the assay on the solid support. EXAMPLES

[0197] Multiplexed biosensors

[0429] While classical biosensor designs allow the use of only one protease-cleavable fluorescent dye or quantum dot per particle, the broad UV / Vis absorption spectrum of graphene and derivatives allows the attachment of several biosensors against different proteases.

[0430] Figure 12 shows an example of an exploded-graphene based biosensor for matrix metalloproteinase-1. The working principle of the graphene based biosensor for protease activity is presented herein.

[0431] As shown in Figure 12, the protease (if present in the test sample) cleaves its consensus (cleavage) sequence and releases the fluorophore. The latter avoids quenching of the graphene, resulting in a measurable increase in fluorescence ("fluorophore-on"). A prototype biosensor for MMP1 was tested in samples with increasing concentrations of the enzyme.

[0432] As shown in Figures 13A and 13B, it can be seen that the intensity of the detected signal is proportional to the concentration of the enzyme. Even under a non-optimal experimental design, the limit of detection (LOD) estimated for this prototype biosensor still indicates that femtomoles of protease activity can be detected. When TCPP is bound, it shows virtually no fluorescence due to strong carboxygraphene quenching. It is then released for 60 minutes. Its fluorescence is detectable. EXAMPLES

[0198] Buffers and standard reactions

[0433] Protease enzymes are protein digestive enzymes that act under physiological conditions. The matrix metalloproteinase family contains complexed divalent cations, whereas cathepsin proteases are primarily activated in the acidic lysosomal environment. The operation of the Fe-NBS protocol was initially designed and prepared in 25 μM HEPES buffer containing 10 μM divalent cations.

[0434] The system was modified to achieve a stronger signal through improved pH control and by including isotonic conditions to support protease activity while also supporting the requirement for divalent cations. We also sought to demonstrate that it was possible to construct buffers compatible with multiple different gNBS sensors at once to enable future multiplexing.

[0435] For this purpose, a series of buffers was designed, all containing MgCl2, CaCl2 and ZnCl2 at 10 μM final concentration. HEPES buffers as well as MES, TRIS and phosphate buffered saline were evaluated (Table in FIG. 14).

[0436] Solutions of uPAgNBS and CTSDgNBS were prepared at a 10x working concentration of 300 μg / ml in water. They were sonicated for 10 minutes in a sonication water bath. gNBS was diluted 1:10 in each of the different buffer formulations reported in FIG.

[0437] 125 μl of gNBS solution was dispensed in duplicate into a black 96-well plate. 5 μl of serum was added and the plate was incubated for 60 min at 37° C. The emitted fluorescence was read on a VarioSkan Lux plate reader at 421 nm excitation and 650 nm emission. The assay included an assay control where 5 μl of the appropriate buffer was added instead of serum. gNBS was incubated with two different normal healthy donor serum samples or pooled normal serum (PNS). Buffer 1 was the original formulation. Protease activity was observed in all buffer conditions. The results are reported in FIG. 15 Panel A (CTDSgNBS) and FIG. 15 Panel B (uPAgNBSS).

[0438] A much more stable pH was observed for the PBS and MES buffer formulations, where the pH remained stable for several days. Only DMSO significantly increased the RFU observed under stimulation conditions. Notably, however, the buffers containing NaCl significantly reduced both the background and serum signal. Reducing the AC helps to increase the signal-to-noise performance of gNBS. Buffers 2, 3, 6, 8, and 9, all containing NaCl, showed a significant decrease in AC performance compared to the original buffer.

[0439] Buffer 9 was selected as the buffer with the best signal-to-noise performance. This performance supported the conclusion that the influence of physiological ion concentrations stabilizes the zeta potential and allows for the native conformation of the peptide-TCPP construct. Thus, zeta potential stabilization, which contributes to the stability of the particle solution, also supports optimal enzyme conditions. The effect of NaCl on zeta potential can be observed in FIG. 16. To confirm these observations, the experiment was repeated with additional gNBS using buffers 1, 2, and 9. Evaluation of gNBS for uPA, CTSD, MMP10, and CTSH all showed a reduction in AC signal and the highest signal-to-noise for buffers containing isotonic salt concentrations, with buffer 9 being superior to buffer 2 (FIG. 17).

[0440] These experiments demonstrated the features of the biosensor of the present disclosure as well as the role of ions for the efficient functioning of gNBS used to detect protease activity.

[0441] In particular, the functionality of the sensors of the present disclosure depends on their ability to be repeatedly constructed to the same specifications, allowing for the measurement of activated proteases or other suitable biomarkers in normal serum samples, such that different batches and lots of sensors can be manufactured to produce the same signal.

[0442] Additionally, buffers and preparation conditions can be selected to generate optimal signal-to-noise ratios. In this experiment, it is observed that the inclusion of monobasic salt ions contributes to a significant reduction in noise as reflected by the reduction in the buffer-only signal (see AC values ​​in Figures 15 and 17).

[0443] The influence of monobasic salt ions has also been observed to stabilize the zeta potential of particles over a pH range of pH 5.0 to pH 8.0. This range reflects the natural working environment for certain protease family members that are normally expressed in lysosomes or other acidic environments. Protease activity can occur over a range of pH conditions that reflect the natural biological environment of pH 2.0 to pH 10.0. Depending on the pH requirements, the MES buffer may be replaced with a buffer whose pKa is more suited to the pH target, such as PIPES, MOPS, HEPES, TRIS, phosphate buffers, Bikini, CHES, or other buffers commonly found on Good's list.

[0444] The above observations supported the conclusion that the inclusion of salt reduces the AC activity of the sensor. The effective salt concentration can be observed as a ratio of less than 1.0 compared to the same sensor in the same buffer but without any monobasic salt ions present (shown in Figure 18). Monobasic salt ions from 15.5 mM to 155 mM reduce the ratio of AC of salt / no salt conditions. Hypertonic salt conditions may similarly increase the signal-to-noise performance by reducing AC. Salt concentrations in physiological conditions reflecting a high salinity environment can be as large as 600 mM or as high as 1 M. EXAMPLES

[0199] Preparation and performance of biosensors prepared using an ultrasonication process

[0445] In a detonation reaction using a gas-phase detonation of a hydrocarbon-based material in the presence of a defined ratio of oxygen, few-layer graphene can be produced. The graphene obtained consists of branched fractal aggregates with an average size of 50-500 nm when detonated with a molar oxygen ratio of 0.3.

[0446] Electron microscopy of the resulting particles reveals graphene aggregates variously composed of chains, sheets, aggregates and individual platelets, as shown by the exemplary photograph in FIG. 19A.

[0447] A spectrum of sizes and shapes is evident from the transmission electron microscopy analysis performed on gNBS (Figure 19B). The particles imaged in Figure 19B were prepared as described in the KSU disclosure of December 30, 2020 (Lot 120120). They show irregularly shaped particles of many different sizes, with the number of layers at higher magnification reflecting the expected 5-25 layer graphene.

[0448] As fractals, there is no defined size or shape for the individual particles: they are composed of aggregates that form in the explosion process and are therefore random in size and shape within the spectrum.

[0449] An exemplary SEM (scanning electron microscope) of exploded graphene is shown in Figure 1. [8] To prepare a solution of gNBS for the assay, gNBS is collected and resuspended in a buffer to a defined mass concentration. This solution is then dispersed in a sonication water bath. The time in the water bath is not defined in the original disclosure and may result in different levels of particle disruption. The effect of this variation is seen in Figure 20. When a working solution of gNBS is produced, the KSU Lot 120120 preparation results in some particles that precipitate out of solution. This is because there is no efficient dispersion of graphene during the initial fabrication process, resulting in an unstable final product. In contrast, when graphene is prepared by probe sonication during the fabrication and prior to construction of gNBS, the particles remain more polydisperse.

[0450] To further evaluate the effect of sonication on the distribution of the resulting gNBS population, the dispersion properties of the particles were analyzed with a Malvern Instruments ZetaSizer running v7.02 analysis software. Exploded graphene was either directly dissolved in DMF (without sonication) or actively dispersed by sonication in DMF for 1 h using a Fisherbrand FB705 Sonic Dismemberator.

[0200]

[0451] The resulting graphene solution was assembled into gNBS using standard protocols by first reacting it with bromovaleric acid and sodium azide to obtain carboxygraphene (CG) (Figure 21: Panel A). This was further modified by tethering Polyethyleiminine to the carboxygraphene using EDC and DMAP to obtain Polyethyleinimine-derivatized carboxygraphene (Figure 21, Panel B). Finally, peptide-TCPP was added using EDC chemistry with DMAP catalysis to obtain the sensor; in this case, a peptide recognized by the protease neutrophil elastase (NE). Solutions of each intermediate, CG, and CG derivatized with polyethyleneimine (CGP) were prepared and treated in a sonication water bath for 10 min to disperse the solution for efficient mixing and redistribution of the particles, ensuring effective surface modification and water solubility. PDI measurements were performed immediately after sonication and then again after standing for 30 min.

[0452] The results of polydispersity index (PDI) measurements are shown in FIG. 21. PDI is a measure of the uniformity of particles in solution. The data show that there is greater uniformity in particle size (lower PDI number) after sonicating the starting graphene material for 1 hour prior to assembly of gNBS. This uniformity was evident for the CG and CGP intermediates, as well as the NEgNBS final product.

[0453] In addition to this, a solution of 1.0 g of graphene 0.3 (0-C ratio) was dissolved in 20 mL of DMF without further processing. The absorbance at 270 nm was measured on a NanoDrop 1000C spectrophotometer. The solution was then dispersed using a probe sonicator with 20 sec on and 10 sec off pulses at 35 intensity levels for up to 60 minutes. Samples were collected at intervals and the ABS270nm was measured for up to 1 hour. As the probe sonication continued, the graphene slurry thickened to the point that it had to be diluted to take an ABS270nm reading and the reading was corrected for dilution. Figure 22 shows the increase in absorbance with increasing sonication time. The absorbance increases as more energy is applied as the graphene fractals are broken down into smaller particles.

[0454] As the number of particles increases from the energy applied during sonication, the overall particle size decreases, resulting in Mie or Rayleigh scattering of light, observed as a decrease in transmittance on the UV-vis spectrum.

[51] Thus, as the graphene is sonicated, the input mass is reduced into the manufacturing process, but the same or a greater number of attached peptide-TCPP particles can be maintained due to the overall increase in particle surface area.

[0201]

[0455] Proteases are extremely sensitive to environmental changes such as pH and chemicals in the buffer. It was confirmed that chemicals used during cleaning and manufacturing of the biosensor were not left on the sensor and did not contribute to the batch-to-batch variation we observed. Thermogravimetric analysis (TGA) was performed on four preparations of CG. A TGA Instrument TGA5500 was used to ramp the temperature from room temperature (20°C) to 1000°C at 20°C / min in a nitrogen environment.

[0456] In manufactured nanosensor lots where an effort was made to thoroughly dry the particles, an overall decrease in the percentage mass loss was observed (Table in FIG. 23).

[0457] Specifically, TGA of the original KSU lot (120110) showed that the majority of the mass was lost in the temperature interval up to 100° C., consistent with the boiling points of the solvents used in the preparation, indicating residual solvent contamination. As the protocol was modified to include temperature and drying efforts with desiccants, the percentage of mass loss decreased (FIGS. 24 and 25).

[0458] It was observed that sensors from which the solvent was not removed must undergo a curing period before becoming fully functional. For the first lot of nanosensors made by KSU, this period was determined to be two weeks, where the signal / noise ratio was insufficient to generate a significant signal, primarily due to elevated AC. In contrast, nanosensors prepared with efforts to remove residual solvent, including an overnight dry incubation at 37°C after fabrication, generated a strong signal within five days of fabrication (Figure 26). Drying of the final sensor product is believed to be important to remove residual solvent and reveal optimal activity.

[0459] Residual solvent impacts the performance of gNBS by inhibiting optimal activation of the sensor, which is manifested as a decrease in signal-to-noise performance. Therefore, removal of the fabrication solvent is characterized using TGA. TGA provides a measurement of the amount of solvent released as a percentage of the total mass. Specifically, the solvent is removed at 20°C to 200°C or 20°C to 400°C. As a contribution to the total mass of the sensor, the preparation of gNBS should result in a thermal transfer mass contribution of less than 30%. Optimally, the mass loss measured by TGA should be less than 10% or less than 5%. Optimally, the mass loss measured by TGA should be less than 1%. EXAMPLES

[0202] Batch-to-batch variation and the effect of sonication

[0460] The manufacturing protocol defined by the original disclosure was a three-step process.

[0461] The first graphene was modified to produce carboxygraphene (CG). This was achieved by dispersing 2.0 g of detonation synthesised graphene 0.3 (0-C ratio) in 40 mL of DMF in a 250 mL Erlenmeyer flask suspended in a silicone oil bath at room temperature with a magnetic stir bar. After dispersion, the absorbance of the solution was measured with a NanoDrop 2000C spectrophotometer. The temperature of the reaction was increased to 40 °C and 1.0 g of 5-bromovaleric acid was added to the graphene suspension, followed by the slow addition of 0.36 g of sodium azide crystals. Once all the reagents were dissolved, the temperature was slowly increased to 80 °C and incubated at 80 °C for 1 h, then allowed to cool to room temperature. The suspension was washed by centrifugation at 10,000 × g for 5 min, five times with DMF and three times with ethyl ether, before drying.

[0462] Second, for the preparation of the polyethyleneimine-derivatized carboxygraphene (CGP) intermediate, 1 g of CG was dispersed in 30 mL of DMF in a flask equipped with a stir bar. 0.54 g of EDC and 0.53 g of DMAP were added and stirred at room temperature until dissolved. 1.2 g of polyethyleneimine was added and the reaction was stirred for 21 hours. The CGP particles were washed four times with DMF using centrifugation as above and three times with ethyl ether. The CGP particles were dried by flushing with argon and keeping loosely covered at room temperature for 48 hours.

[0463] The last step is the conjugation of sensor peptide-TCPP. 103 mg of CGP was dispersed in 16 mL of DMF using a sonication water bath for 1 min. 10.5 mg of EDC and 11 mg of DMAP were added to the CGP with stirring at room temperature. 7 mg of TCPP-labeled peptide was added and the reaction was stirred at room temperature for 20 h. The resulting gNBS was washed three times with DMF and three times with ethyl ether, then flushed with argon. The final gNBS product was stored at -20 °C. This protocol reflects the original KSU protocol.

[0464] It was observed that preparations of gNBS made with graphene using the first protocol showed large variations in performance between lots, even for batches prepared on the same day (Figure 27 compares lots 120120 and NE100 with NE101 and NE102). It was considered possible that dispersion of the sensor using a sonication water bath in the preparation of the working solution may generate different population sizes and particle numbers with each sonication. Thus, unless particle size is optimized prior to production, repeated sonication of the gNBS working solution will regularly change the outcome of the analysis.

[0465] To determine the effect of sonication on the starting material, the preparation was modified as outlined in the table in Figure 28. The starting graphene material was either used without sonication as described in the original protocol and dispersed in DMF using only a stir bar, or the starting material was dispersed using a probe sonicator for 10 or 20 minutes (table in Figure 28). After dispersion, the graphene input was reduced due to increased particle number and surface area, but the amount of peptide TCPP input to the conjugation reaction remained the same. One lot of NEgNBS was prepared using the KSU protocol and two lots were prepared using 10 and 20 minutes of probe sonication of the starting graphene.

[0203]

[0466] All three were compared to lots produced at KSU (Figure 26). KSU lot 120120 and HEB lot NE100 were produced using the same protocol and dispersion procedure. HEB lots NE101 and NE102 were modified by including probe sonication. gNBS was evaluated under standard conditions with normal human serum compared to an assay control (AC) containing sensors and buffer but no serum. For lot 120120 and HEB lot NE100, a mean difference of 244% was observed between batches 1 and 2. In contrast, the probe sonicated lots (NE101 and NE102) showed a mean difference of 132% between batches (Figure 27). It was concluded that dispersion by sonication prior to production resulted in more consistent particle size in the graphene starting material, smaller and more acceptable PDI (<0.5) (Figure 21), and more reproducible activity in the final gNBS sensors.

[0467] To confirm the effect on particle size in the final preparation, we evaluated the effect of sonication in a water bath on the finished particles. A significant ABS increase was observed for NE-gNBS, which did not undergo sonication during production, with an average increase in ABS of 259% at the ABS wavelengths for graphene (265 nm) and TCPP (425 nm).

[0468] In contrast, the change in ABS over time for lots prepared with sonication showed an average of 121% change in ABS over time at the same wavelengths (Figure 29). Our conclusion was that particle preparations that included probe sonication produced more homogenous suspensions that were not affected by the water bath sonication used to prepare the working solutions. EXAMPLES

[0204] Biosensor preparation and performance

[0469] A preferred protocol for particle assembly involves tailoring the particle size distribution using sonication or physical disruption. Graphene is derivatized by attaching carboxyl moieties to the surface using azirane anchors. The surface is then modified by adding a polymer such as polyethyleneimine (PEI) followed by attachment of a peptide-dye conjugate.

[0470] Using a series of experiments reported in this Example, it was sought to discover these and the boundaries of the components by substituting other components to evaluate modifications that could be considered for alternative manufacturing protocols.

[0471] In particular, the experiment was repeated to determine the amount of carboxy labeling that occurs during the first step of the synthesis. Solutions of 0.5 M NaOH and HCl were prepared using high purity HPLC grade water. The 0.5 M NaOH solution was degassed with argon for 2 hours before dispersing the CG. After degassing, 250 mg of CG was dispersed in 50 mL of 0.05 M NaOH. The sample was sonicated in a water bath for 10 minutes and then stirred at room temperature for 24 hours. After 24 hours, the CG suspension was filtered to remove CH2 and the solution (CG filtered 0.05 M NaOH, 0.05 M NaOH and 0.05 M HCl) was degassed overnight. Then, 20 mL of 0.05 M HCl was added to a 10 mL aliquot of the CG treated and filtered NaOH solution. After each addition of NaOH, once the pH had stabilized, the pH was recorded before the next addition. For the blank, a 10 mL solution of 0.05 M NaOH was prepared in the same manner by addition of 0.05 M HCl and back titration with 0.05 M NaOH. Degassing was maintained during the titration. Using this protocol, the CG preparation required more NaOH for neutralization than the blank, suggesting the presence of acidic functional groups. Replicate experiments yielded a 1.765 x 10 -4 and 1.8 x 10 -4 The concentration of acidic groups in mol / g was calculated, which was lower than the original estimate, but supported the addition of acidic groups to graphene (Figure 30, panels A and B).

[0472] In support of this observation, elemental analysis of unmodified graphene and carboxygraphene showed undetectable levels of oxygen and hydrogen in the starting graphene material (table in Figure 31). After carboxylation, detectable levels of H and O of 0.5% to 3.5% were observed. Since a reduced oxygen content was observed compared to the original KSU protocol (KSU and CG1.0), we conclude that part of the oxygen content is derived from the solvent. In support of this, preparations CG1.2, CG1.3, and CG1.4 (see table in Figure 28), prepared using sonication and including a drying protocol, showed lower resulting percentages of H and O detected. For comparison, derivatives (CGP) with PEI (CGP102) resulted in significantly higher contributions of H, O, and N. CGP102 was assembled using CG1.0 (table in Figure 31).

[0473] On this basis, it was concluded that the original pH titration overestimated the number of carboxylic acid groups added to the graphene, which was more accurately estimated using argon degassing and back titration. This was supported by elemental analysis, which showed lower estimates of oxygen content in CG preparations in which efforts were made to eliminate residual solvent than in products produced with the original protocol. Despite the differences in elemental analysis, all of the protocols described were still capable of annotating graphene with H and O and producing functional biosensors.

[0205]

[0474] To determine the process for biosensor assembly, the addition of PEI to graphene was tested in the absence of a previous carboxylation step. In the first example, control uPAgNBS was assembled using the standard protocol with carboxylation of graphene followed by PEI polymerization. In the second example, 0.3 graphene was used instead of CG (no uPA-GC) with the same loading of 500 mg / g PEI, using 243 mg / g EDC and 247 mg / g DMAP, as outlined for CGP104 in the table of FIG. 28.

[0475] The reaction was incubated at room temperature for 90 minutes with stirring. In a third example, 0.3 graphene was dispersed in DMF with the addition of 550 mg / g PEI, but without the addition of EDC or DMAP catalyst. Instead, the reaction was heated to 80° C. for 1 hour (uPA-80° C.). Once the addition of PEI was complete, all three preparations were washed at least five times with 200 proof ethanol and resuspended in DMF. All three preparations were then conjugated to the peptide TCPP using the uPA-TCPP sequence. All three constructs were treated with 105 mg / g EDC, 111 mg / g DMAP, and 65 mg / g uPA-TCPP with stirring at room temperature for 90 minutes. The resulting particles were washed with ethanol and dried overnight in a 37° C. oven. The sensors were tested by preparing a 200 μg / ml solution in 10 mM MES, 10 μM CaCl2, MgCl2, ZnCl2, and IS:155. 70 μl of each working solution was incubated with 10 μl of pooled normal serum at 45° C. for 90 min.

[0476] Fluorescence was measured on a VarioSkan Lux plate reader at 425 nm excitation and 653 nm emission. All three preparations yielded assay control values ​​below 0.05 and had RFUs from pooled normal serum between 19 and 31 (Figure 32). All three sensors were insensitive to adjustment of the response to 10 mM KOH, a treatment that revealed non-covalently bound TCPP (data not shown).

[0477] It was therefore concluded that since elemental analysis of graphene has a detection limit of 0.5% oxygen, the amount of oxygen increases to detectable levels with the generation of CG, making it a target for the addition of PEI. However, when considering functional sensors generated by thermal-based condensation at 80°C or by the direct addition of catalyzed PEI to graphene, evidence is provided that 0.3 graphene has some capacity to bind the small number of PEI molecules required to assemble the sensor, suggesting the presence of oxygen in the exploded graphene.

[0206]

[0478] Additional methods of coupling PEI to graphene that may require fewer steps or be more efficient were also evaluated. Alternatives to the bromovaleric acid linker, such as modified tetraethylene glycol (TEG), azidoacetic acid NHS ester, or azidoacetic acid, were identified. These molecules provide an azidogroup and a carboxylate or amine group instead of bromovaleric acid + azide.

[0479] An experiment was performed in which 125 mg of graphene was probe sonicated in 22.5 mL of DMF and heated to 60°C. PEI was prepared by adding 60 mg of 10k MW PEI to 3 mL of DMF, followed by 270 mg of azidoacetic acid NHS ester. The mixture was heated to 60°C and incubated for 30 minutes. The activated PEI solution was then added to the graphene and the temperature was increased from 60°C to 80°C over 10 minutes. The reaction was allowed to continue for 1 hour and purified using ethanol washing and drying. A second preparation was made similarly, except that 10k MW PEI was used instead of 1.2k MW PEI. Both constructs were then treated with 105 mg / g EDC, 111 mg / g DMAP and 65 mg / g uPA-TCPP at room temperature for 90 minutes with stirring. The resulting particles were washed with ethanol and dried overnight in an oven at 37°C. The sensors were tested by preparing a 200 μg / ml solution in 10 mM MES, 10 μM CaCl2, MgCl2, ZnCl2, and IS: 155. 70 μl of each working solution was incubated with 10 μl of buffer, 50 mg / mL acetylated BSA, or pooled normal serum in black 384-well plates at 45° C. for 90 minutes.

[0480] Fluorescence was measured on a VarioSkan Lux plate reader at 425 nm excitation and 653 nm emission (Figure 33). Similar activation of uPA sensors made with either PEI preparation was observed. This observation indicates that it is possible to manipulate the distance of peptides and related dyes from the graphene backbone by choosing polymers of different molecular weights, thus decreasing the distance between the graphene quencher and the fluorophore. This will likely become necessary as we change to more efficient fluorescent dyes with shorter Förster radii or more efficient fluorophores. This experiment also confirms the ability to use anchors other than bromovaleric acid.

[0207]

[0481] Currently, the assembly of graphene-based biosensors consists of a series of surface modification reactions carried out using the following: modifications of graphene vs. carboxygraphene vs. carboxygraphene-PEI vs. graphene-biosensor. To reduce this complex synthesis procedure, a single surface modification of graphene was investigated prior to the assembly of the biosensor described below.

[0482] A small scale reaction was initiated by dispersing 1 g of 0.3 exploded graphene in 50 mL of distilled and degassed N,N-dimethylformamide (DMF) (Fisher Scientific Cat#: D119-20) in a round bottom flask at room temperature. The dispersion was then heated to 40°C and 556 μL (0.0028 mol) of azido-TEG3-amine (BroadPharm Cat#: BP-20580) was slowly added. The temperature was then increased to 80°C and the reaction solution was stirred for 1 hour. After 1 hour, the reaction was cooled to room temperature and a sample was collected by centrifugation (speed of 8000 RPM for 5 minutes). Finally, the G-TEG3 amine product was washed five times with DMF and three times with anhydrous diethyl ether. The resulting G-TEG3 amine was further dried with argon and stored at -20°C.

[0208]

[0483] Next, the MMP1 biosensor was assembled using G-TEG3amine, which was assembled following the same optimized conditions established for the G-PEI biosensor. For this, two solutions were prepared: 1) 3.75 mg of TCPP-MMP1 peptide, 5 mg of EDC, and 5 mg of DMAP were dissolved in 2 mL of distilled and degassed DMF, and 2) 50 mg of G-TEG3amine was dispersed in 2 mL of distilled and degassed DMF. Both solutions were sonicated in a sonication water bath (3 min) and vortexed until completely dissolved. Solutions 1) and 2) were then mixed, and the solution was further sonicated (3 min) to ensure that everything remained suspended in the DMF. The solution was then stirred overnight at room temperature. After 24 h, the biosensor was collected by centrifugation (8000 RPM for 8 min) and washed 3 times with DMF and 3 times with diethyl ether. Finally, the biosensor was dried with argon, stored, and stored at -20 °C.

[0484] Once the biosensor was assembled, dynamic light scattering (DLS) and zeta potential measurements were performed using a NanoBrook 90 Plus PALS. For this, a 0.03 mg / mL solution of MMP1 was prepared using high purity water (HPLC water, Fisher Cat#:W7-4). The average size (DLS), polydispersity index, and zeta potential surface charge are shown (table in FIG. 34). The results demonstrated that the biosensor had a slight positive charge of 4.36 mV, an average diameter size of 713.30 nm, and a PDI of 0.147.

[0209]

[0485] The following experiment was a side-by-side comparison of both biosensors, G-PEImMP1 vs. G-TEG3amineMMP1. For this experiment, a 0.03 mg / mL solution of each MMP1 biosensor was prepared using HEPES buffer (25 μmol / L HEPES buffer, pH 7.20, enriched with 10 μmol / L Ca2+, Mg2+, Zn2+). After preparing the biosensor solutions, the pH increased to 7.40 for G-TEG3amine and 7.52 for G-PEI, so the pH was then adjusted to 7.20 for both solutions using 0.1 M HCl solution.

[0486] Three solutions were prepared (as described below) and plated in duplicate in a 96-well plate (Greiner Bio-one, Microplate 96-well, PS, F-bottom, Black non-binding; Cat: 655900). - Solution 1: Sample control (125 μL HEPES buffer + 5 μL of collected control serum - S, P, or pooled) - Solution 2: Assay control (125 μL biosensor solution in HEPES buffer + 5 μL HEPES buffer) - Solution 3: Assay (125 μL biosensor solution in HEPES buffer + 5 μL of collected control serum - S, P, or pool).

[0487] After plating the solutions, the 96-well plate was incubated at 37° C. for 1 hour and the fluorescence intensity was measured every 15 minutes during the 1 hour incubation using a BioTek Synergy H1 plate reader (exc=425±10 nm, em: 650±20 nm). FIG. 35 shows the fluorescence intensity measured every 15 minutes for the MMP1g-PEI and MMP1g-TEG3amine biosensors for each control serum (S, P, and pool). The highest intensity measured after 1 hour incubation for the G-TEG3amine was higher for all three control sera tested compared to the G-PEI biosensor.

[0488] Also, the intensity increased over time following an approximately linear trend for both biosensors tested with all three control serum samples. Figure 36 panel (A) shows the intensity measured after 1 hour of incubation with both biosensors tested with each control serum. Here, it can be noted comparing G-PEIg-PEI vs. G-TEG3amine, which was almost 2-fold higher for G-TEG3amine than for control serum S and P compared to G-PEI. It should also be mentioned that the intensity for the assay control was lower for G-TEG3amine compared to G-PEI, which is summarized in Figure 36 panel (B). Overall, the G-TEG3amine-based biosensor results in improved signal / noise measurements with lower assay control and greater specific signal for serum.

[0210]

[0489] In view of the above experiments, it was concluded that since detonation-synthesized graphene is hydrophobic and does not disperse substantially in water or aqueous buffers (and many surfactants interfere with the fluorescence quantum yield of organic dyes), the addition of a hydrophilic coating should be performed to obtain the desired stability.

[0490] This can be achieved by attaching carboxylic acid groups to the surface of the graphene stacks via nitrene addition.

[52] Alternatively, amine-terminated oligoethylene glycols can be attached to the surface of exploded graphene via nitrene addition.

[0491] Polyethylenimine is attached to this carboxylic acid. Alternatively, amine groups can be attached to the surface of the exploded graphene and then attached to a polymer that exhibits carboxyl groups.

[0492] Alternatively, one can attach a precursor for graphene attachment with azide groups to a polymer and then anchor the polymer to the graphene surface.

[0493] The applied organic coating (polymers, oligoethylene glycols) has the following functions:

[0494] Without a hydrophilic coating, graphene nanobioensors are not dispersible in aqueous buffers. The achievable concentration of the biosensors strongly depends on the chemical nature of the coating and the mass ratio of coating to graphene.

[0495] The coating is responsible for the stability of the biosensor when dispersed in an aqueous buffer, and the graphene core of the biosensor is extremely stable.

[0211]

[0496] The size and structure of PEI are responsible for the increase in fluorescence observed upon proteolytic cleavage of the recognition sequence. In general, Förster resonance energy transfer (FRET) occurs between graphene (acceptor) and the bound organic fluorophore. The effectiveness of FRET is distance dependent. Thus, the structure of PEI (branched vs. linear) is important. However, graphene (especially graphene stacks) efficiently absorbs light from the UV to the near-infrared range. Theoretical studies by Bi'an et al. (2016) suggest that the quenching sphere around a graphene monolayer extends to about 20 nm.

[53] Within this "Förster Volume", strong quenching occurs, which reduces TCPP fluorescence extremely strongly. Upon escaping from the Förster Volume, TCPP starts to emit light. EXAMPLES

[0212] Multi-graphene biosensor

[0497] We considered the possibility of operating multiple different sensors in the same reaction well. Graphene has a broad spectrum of light absorption (Figure 37). Therefore, multiple different peptide-dye sequences can be assembled on a single graphene particle, or multiple sensors, each labeled with a different single peptide-dye, can be mixed together.

[0498] The latter system, mixing two independently labeled particles, was used to evaluate the multiplexing capabilities of the biosensor of the present disclosure. Peptides of neutrophil elastase (NE) and arginase (ARG) were variously labeled with FAM or TAMRA. Peptide-FAM or peptide-TAMRA were directly substituted into the manufacturing process of peptide-TCPP, with the only modification being the conjugation at half density due to the increased fluorescence efficiency of these dyes. Thus, peptides were added at 35 mg / g CGP (see table in Figure 28). gNBS working solutions were prepared by assembling NE-FAM, NE-TAMRA, or uPA-TCPPgNBS in an assay buffer consisting of 10 mM MES, 10 μM CaCl2, MgCl2, ZnCl2, IS:155. 125 μl of working solution containing increasing amounts of each gNBS was dispensed into a black 96-well plate and stimulated with buffer for assay control (AC) in single wells or 5 μl of pooled normal serum in triplicate. Plates were incubated at 45° C. in a Varioskan Lux (FIG. 38 and FIG. 39). Fluorescence was monitored for each reaction over 90 minutes using Ex496 / Em526 and Ex555 / Em586 for FAM. Alternatively, MMP7 and MMP9 peptides were conjugated to Rhodamine-B and CGP at 70 mg / g using the KSU production protocol described above. A gNBS working solution was prepared at a final concentration of 30 μg / mL gNBS in 10 mM MES, 10 μM CaCl2, MgCl2, ZnCl2, IS:155, and 125 μL reactions were set up in triplicate in black 96-well plates and incubated with 5 μL of serum or buffer only (AC) for 60 min at 37° C. Fluorescence was measured with Ex535 / Em570 on a BioTek Synergy H1 FL800 plate reader (FIG. 39).

[0499] These observations support the model that graphene can act as an effective quencher for multiple different dyes. Having demonstrated that multiple different sensors can be constructed with different dyes and that these dyes can be successfully quenched by the graphene backbone in separate reactions, we sought to demonstrate that multiple dyes can be observed in the same reaction.

[0213]

[0500] Arg-FAM and NE-TAMRAgNBS were prepared again to halve the input peptide dye contribution to gNBS production 35 mg / g CGP as described above. gNBS working solutions were prepared by assembling 400 μg / ml of Arg-FAM or NE-TAMRAgNBS in assay buffer composed of 10 mM MES, 10 μM CaCl2, MgCl2, ZnCl2, IS:155. 80 μl reactions were set up in a 384w black plate with 35 μl of a single sensor and 35 μl of buffer, or 35 μl of each sensor mixed for a final concentration of 200 μg / ml of either sensor. 10 μl of pooled normal serum or buffer was added to each sensor solution.

[0501] All sensors were stimulated in triplicate and incubated for 90 minutes at 45° C. with measurements taken at 10 minute intervals. Each well was measured at 496 / 526 nm (FAM) and 555 / 586 nm (TAMRA) (FIG. 40).

[0502] Note that both individual and multiplexed sensors could be detected, with no signal detected from one sensor in the other channel, but there was some evidence of quenching when both sensors were present (compare singleplex fluorescence to multiplexed fluorescence in either channel). It was also noted that Arg-FAM showed elevated background in singleplex and multiplex reactions. This was interpreted as an indication that the amount of peptide conjugated when a highly efficient dye is used may exceed the quenching capacity of the graphene backbone.

[0503] This noise can be mitigated by titrating the level of labeling. Alternatively, a shorter linking chemistry between the FAM dye and graphene would bring the FAM closer to the FRET partner and improve quenching. In this context, we considered replacing the 10k MW PEI with a 1.2K MW PEI as a viable solution, as described in Figure 32.

[0504] It was believed that using a combination of direct conjugation, such as with azidoacetic acid NHS ester or equivalent, to conjugate the dye-labeled peptide to the graphene scaffold would effectively quench the graphene scaffold-bound dyes.

[0505] This modification of the chemistry is expected to be effective as exemplified above, so long as the peptide-dye conjugate is kept within 20 nm of the graphene.

[53]

[54] Thus, the signal-to-noise performance is modified by altering the distance between the dye conjugate and the graphene backbone by optimizing the polymerization or conjugation chemistry to optimize efficient quenching of the dye depending on the quantum efficiency of the selected dye. This conjugation selection must also contribute sufficient charged groups, such as carboxylic acid, amino, or alcohol side chains, to allow secondary conjugation of the peptide-dye complex and support solubilization of the graphene particle.

[0214]

[0506] Finally, NE-FAMgNBS reactions were set up in duplicate, with one assay performed in a 96w black plate and analyzed on the Varioskan Lux platform, and the other assay using NE-FAMgNBS in a 96-well PCR plate and analyzed on the StepOnePlus PCR platform (Figure 31). The absence of background signal and a linear relationship between incubation time and fluorescence was evident on both platforms, raising the possibility that these types of gNBS assays could be performed on laboratory equipment that is even more widely distributed than fluorometers, such as quantitative PCR platforms. EXAMPLES

[0215] Heat treatment of serum

[0507] Experiments were designed to demonstrate the specificity of these reactions by heat inactivating the protease enzymes. For this purpose, samples of two different control sera were heat treated at 55°C for 1 h. Heat-treated and non-treated sera were incubated with MMP10 and CTSHgNBS using standard conditions. A slight increase in RFU was unexpectedly observed for both sera and both sensors. (Figure 42 Panel A). The experiment was repeated with the two control sera treated at 65°C for 10 min (longer intervals caused precipitation of the serum). In addition, we treated the serum with EDTA such that the final EDTA concentration in the sensor reaction was 5 mM. We also investigated how generalizable this observation was by using MMP2 instead of MMP10gNBS (Figure 42 Panel B). Treatment of the serum with EDTA slightly reduced the activity, consistent with other reports.

[55] In contrast, heat treatment of the serum at 65°C significantly increased the activity in both sera and both sensors. Addition of EDTA moderately reduced the elevated activity, as it did for untreated serum, and this effect was more pronounced for the MMP2 sensor. Surprisingly, therefore, treatment of serum at elevated temperature reveals additional protease activity that can increase the gNBS signal. To determine whether this change is the result of additional activation events occurring as the zymogens are activated, we stimulated CTSH gNBS with pooled normal serum or replicate samples heat-treated at 65°C for 10 min. Responses were measured over 240 min at 30 min intervals after the first hour. Both untreated and heat-treated serum activities were maintained as linear responses over the duration (Figure 43). If additional zymogens were activated, an increase in kinetics would be expected over time. However, no evidence of change in kinetics was seen.

[0508] In support of this conclusion, the effect of heat treatment on pooled normal serum sensor activity was evaluated in 18 protease biosensors (Figure 44). All sensors with signals significantly above the assay controls (RFI>0.05) showed an average 3.2-fold increase in activity with 65°C heat-treated serum.

[0509] Finally, MMP12 and CTSDgNBS were prepared in 125 μl of a working solution of 5 mM MES, 10 μM cation and IS:155. They were stimulated in triplicate with 5 μl of buffer (assay background) or with 5 μl of PNS. Replicate plates were assembled and each replicate was incubated at 37°C, 41°C or 45°C in a VarioSkan Lux. Fluorescence was measured at 10 min intervals during incubation. Sample background measurements showed results from wells incubated with 125 μL of buffer (without sensor) to which 5 μL of serum had been added. In this experimental group, serum was not heat treated before measurements. Instead, reactions were performed at increasing temperatures.

[0510] Each temperature increment revealed additional activity, so that for both MMP12 and CTSDgNBS, incubation at 41°C produced more fluorescence than at 37°C, and incubation at 45°C produced more fluorescence than at 41°C (Figure 45). For MMP12 and CTSD, increasing the assay temperature to 41°C in serum that was not previously heat-treated nearly doubled the RFU (1.7-fold and 1.9-fold, respectively). Increasing the assay temperature to 45°C tripled the RFU (3.1x). Under these conditions, there was no increase in the sensor background signal or sample background. For comparison, we also pretreated serum at 65°C for 5 min and compared the effect on signal-to-noise when both pretreatment at 65°C and increased assay temperature were applied (compare open and closed symbols in Figure 45).

[0511] Pretreating serum at 65° C. increases the signal 2.3-fold relative to heat-treated serum, which is also 2.3-fold and 2.0-fold higher for assays subsequently performed at 41° C. and 45° C., respectively. Thus, pretreating serum and performing protease assays at elevated temperatures improves signal-to-noise through a separate and additional mechanism.

[0512] Regarding the thermal stability of the protease enzyme, active MMP2 enzyme has been reported to have two irreversible unfolding temperatures, 70°C and 78°C, substantially higher than the temperatures used herein (A).

[56] It was considered possible that a family of inhibitors designed to modulate protease activity might exhibit higher temperature sensitivity, and operating these reactions at higher temperatures would reduce the effect of those inhibitors. It was concluded that the effect of increased temperature alters multiple aspects of the assay that together contribute to a significant improvement in the signal:noise ratio.

[0216]

[0513] The stability of the protease enzyme and the relative instability of the inhibitor protein with increasing temperature are expected to change the ratio of activity to inhibited enzyme. High temperature leads to increased enzyme kinetics at higher temperatures providing improved detection of protease activity. Furthermore, increasing the temperature is expected to modify the protein corona observed around the particles and described herein (Figure 46).

[0514] A temperature-dependent slope was expected that balances the temperature denaturing other proteins in the serum before precipitation occurs and the improvement on protease activity. Incubating the serum before or during the assay is both effective in increasing the signal-to-noise ratio. Temperatures of 41°C, or 45°C, or 50°C, or 55°C, or 60°C, or 65°C, or 70°C, or 75°C, or intervals between these targets, are believed to be effective for the desired effect. EXAMPLES

[0217] Negative control

[0515] There is ample literature describing the corona that forms when proteins aggregate around particles.

[57] It was desired to test whether a solution of protein lacking any activity could be shown to generate and contribute to the background signal. Recall that the majority of these sensors require protease-specific cleavage.

[0516] Arginase is an exception as an enzyme that post-translationally modifies targets. In the gNBS system, arginase converts arginine to ornithine and urea. This modification changes the structure and causes the peptide to position the terminal TCPP dye outside the Förster radius of graphene. Therefore, the contribution of the general protein corona to background performance is important to understand. To understand the signal-to-noise with proteins as negative controls, 175 human serum samples were evaluated with 18 gNBS. Each gNBS was assembled in MES assay buffer (10 mM MES, 10 μM Cations, 155 mM NaCl, pH 7.2). 125 μL of each gNBS working solution was added to triplicate wells. 5 μL of serum was added to duplicate wells and 5 μL of buffer was added to the third well.

[0517] Sample-only controls were also included, with 5 μL of serum added to 125 μL of sensor-free buffer. In addition, each set of sensors was also stimulated with 5 μL of a solution of 20 mg / mL acetylated BSA. After loosely covering the plate and incubating at 45° C. for 90 minutes, the fluorescence was measured for 500 ms at Ex / Em 425 / 653 nm in a Varioskan Lux plate reader ( FIG. 24 ). With one exception (ArggNBS), the mean fluorescence obtained by all gNBS was significantly greater than the BSA response. Only one sensor had a serum sample with a signal below the BSA control. The BSA control was significantly greater than the assay control used to measure the amount of fluorescence exhibited by the sensor in buffer alone. We interpret this negative control as a much more valuable reflection of the nonspecific performance of the gNBS. The effect of temperature on the activity of ArggNBS may demonstrate that the optimum temperature for this sensor is below 45° C. EXAMPLES

[0218] Freeze drying

[0518] Maintaining repeatable and reproducible performance is central to maintaining an effective signal-to-noise ratio. Preparations of uPA, CTSE, CTSK, and NEgNBS in MES working buffer were provided and lyophilized plates were prepared with three different excipient formulations. Plates were tested on different days with the same lot of normal serum and compared to wet chemistry batches spiked into the same plates.

[0519] Improved inter- and intra-assay precision was observed when compared to wet reagents, as measured by a reduction in the coefficient of variation in both settings (Figure 47). Maintaining higher precision therefore allows the measurement of protease activity to generate a more repeatable signal across different measurements. This precision is necessary to maintain constant signal-to-noise performance in the assay settings. With consistent, repeatable and reproducible measurements of protease activity, relationships between protease activities across a panel of protease targets can be constructed to distinguish sera from normal patients from patients with a spectrum of different inflammatory conditions. EXAMPLES

[0219] Clinical performance of graphene biosensors

[0520] The performance of gNBS was evaluated in clinical samples. In the first cohort, 256 subjects were recruited from European centers and classified as having lung cancer (n=89) or non-lung cancer (n=167). Serum samples were heat treated at 65 °C for 12 min in a thermal cycler and cooled to 15 °C. Final ABS values ​​of 0.1–0.15 depending on the sensor were determined using MES assay buffer (5 mM MES, 10 μM cations, pH 7.20, 154 mM NaCl). 425 A working solution was made with each gNBS adjusted to 100 nm. The preparation was sonicated in a water bath for 10 minutes and 125 μL was dispensed into replicate wells. 5 μl of heat-treated serum was added to duplicate wells and to a single serum only control. A sensor-only assay control was included on each plate.

[0521] Plates were covered with loose foil and placed in a 37° C. incubator for 90 minutes. Fluorescence was read on a VarioSkan Lux and read at Ex / Em 425 / 653 nm. The mean fluorescence observed for LC and non-LC subjects was reported (table in FIG. 48). A general decrease in protease activity was noted in lung cancer patients versus non-lung cancer patients. Patient stage and disease subtype did not influence this observation. Similarly, non-LC subjects included 9 patients with breast cancer, colorectal cancer, and hematological malignancies that did not confound the non-LC analysis, but these subjects were not included in this analysis. A second cohort of 175 subjects was recruited as part of the “US SST-18” cohort.

[0522] In this experiment, all non-LC controls were age-matched donors with ≥20 pack-year smoking habits and were case-controls for the LC cohort. In the LC cohort, the majority of LC samples were from untreated stage I subjects. In this experiment, we tested a second lot of sensors, a different Varioskan Lux fluorometer, and samples originating from the US instead of the EU. gNBS were collected and the solution was diluted to a final ABS concentration of 0.1–0.15 depending on the sensor in MES assay buffer (10 mM MES, 10 μM cations, pH 7.20, 155 mM NaCl). 425 The assay buffer was adjusted to nm. 125 μl of assay buffer or assay buffer containing each gNBS was loaded into a 96w black plate.

[0523] Plates were covered with loose foil and incubated at 45°C for 90 minutes. Fluorescence was read on a VarioSkan Lux using a one-time endpoint at Ex / Em 425 / 653 nm (500 ms). A similar significant reduction in overall protease activity in the LC samples was observed (Table in Figure 48). A two-tailed Student's heteroscedastic t-test comparing the RFU of lung cancer to the various non-lung cancer cohorts was calculated. This calculation gave p-values ​​of 2.6e-6 to 2.6e-27 across both cohorts and all sensors. The impact of this observation is the possibility that these sensors could be configured in many different configurations to achieve diagnostic potential with extremely strong capabilities to detect the presence of disease.

[0524] FIG. 49 shows a table of p-values ​​for the two-tailed, heteroscedastic Student's t-test comparing the RFU of lung cancer and non-lung cancer samples. EXAMPLES

[0220] Exemplary methods and systems for making biosensors

[0525] Exemplary methods for assembling particles include the following (a) to (e): 1) Add a small amount of layered graphene to dimethylformamide (DMF) to disperse the graphene clumps and obtain a solution. 2) Sonicate the solution for up to 1 h using a probe sonicator using 10-15 KJ per g of graphene for 1 h. 3) To obtain carboxylated graphene (CG), the graphene surface is functionalized to yield a carboxylated surface by using the nucleophilic substitution reaction with sodium azide and bromovaleric acid as described herein. 4) The CG is washed with DMF or ethanol to remove reactants. 5) For core particles assembled with PEI, resuspend the CG in DMF to obtain a CG / DMF solution. 6) Distribute CG / DMF using sonication. 7) For the exemplary polyethyleneimine (PEI), conjugate PEI using 1-ethyl-3-(-3-dimethylaminopropyl)carbodiimide hydrochloride (EDC) and 4-dimethylaminopyridine (DMAP) in a specified ratio for 1-2 hours at RT. 8) The product is thoroughly washed with ethanol to obtain core particles. 9) drying the core particles at ambient temperature for 30 minutes. and further drying the core particles at 37° C. for 24-48 hours. may include.

[0526] Supported systems are a) layered graphene; b) Reagents for graphene modification, polymer attachment, and subsequent sensing; c) Equipment for sonication, probe sonication, physical dispersion using high shear mixers, dispersion (e.g. microwave); d) a tool for measuring absorbance to standardize the concentration of graphene used in the assembly (e.g., a Nanodrop spectrophotometer); and / or e) Devices for sensor manufacturing for drying the sensors (eg ovens, possibly complemented by vacuum or drying chambers). EXAMPLES

[0221] Exemplary Systems for Detecting Biomarkers Using Biosensors of the Present Disclosure

[0527] Methods for detecting one or more target biomarkers according to the present disclosure can be carried out using a system that includes the following components. 1) Nanosensors. This can be a single sensor or multiple sensors. The sensors can be provided as solutions and adjusted to working concentrations with the absorbance defined for each sensor working solution. Alternatively, the sensors can be provided pre-lyophilized in opaque 96 or 384 well plates. 2) Buffer: Sensor activity is supported by an optimal buffer. This buffer can be provided as a solution or as a lyophilized cake in a multi-well plate. The buffer contains ingredients to stabilize the solution at a defined pH. In the current configuration, this pH is 7.2. The optimal pH can vary depending on the sensor present and the optimal pH needed to support enzyme health and activity. Preferably, the buffer also contains monobasic ions. Monobasic solutions support enzyme health and provide ionic buffering to particles to support dispersion. Peptide conformation is also affected by monobasic salt concentration. Generally, the buffer contains ions necessary for enzyme activity. In the example of protease enzymes, MMPs are enzymes that require divalent cations, so the buffer is supplemented with a selection of divalent cations.

[0528] Further ingredients may include, for example: 3) Standard curves were constructed from dyes included at a range of concentrations. These standard curves are used to convert relative fluorescence units (depending on the fluorometer used) to dye concentrations. Standard curves can contain multiple different dyes for multiplexed reactions. Thus, standard curves allow the kit to be used on many different platforms. Alternatively, relative fluorescence may be used.

[0529] Additionally or alternatively, the system may include: 4) Controls to demonstrate the presence of a functional sensor. These controls can include serum samples with known and demonstrated activity. They can be purified enzymes with known activity. They can be chemistries designed to hydrolyze peptides and release dyes non-enzymatically.

[0530] The system may include: 5) An incubator capable of maintaining the multi-well plate at a constant temperature for the duration of the experiment. For some fluorometers, this incubation capability is included. The plate needs to be maintained at 25°C or 37°C or 41°C or 45°C or 50°C or 55°C or 60°C or 65°C for the duration of the experiment or up to 5 minutes. 6) A fluorometer to determine the amount of fluorescence released during the reaction. This fluorescence is typically measured as an endpoint, but may also be measured kinetically such that the rate of change is measured at 1 minute or 5 minutes or 15 minutes or 30 minutes or 60 minutes intervals. 7) Defined, Application-Specific Algorithms. The integration of sensor activity to describe a diagnostic condition requires an algorithm that interprets the defined activity and assigns a classification to the sample. This algorithm is application and sensor specific.

[0531] In particular, components 1-4 and 7) may be included in a kit of parts, as would be understood by one of skill in the art.

[0532] For multiplex detection, further considerations are: dye selection, the combination of sensors with multiple dyes is calibrated to ensure there is no FRET between the dyes. In addition, depending on whether the sensors are attached to a single particle or to separate particles and mixed, the final concentration of particles must be optimized so that there are enough particles to interact with the reactants and drive the reaction, but not so many graphene particles that quench the emitted signal. Furthermore, for mixed sensors, there should be a buffer that compromises the optimal activity of both enzyme targets. Therefore, providing a buffer with a stable pH and defined salt concentration as well as a spectrophotometrically defined sensor concentration reproduces the environment and supports batch-to-batch stability (see Figure 27). EXAMPLES

[0222] Biosensor stability in test solutions, reproducibility, signal-to-noise ratio, and multiplexing capabilities

[0533] During the fabrication of the gNBS sensor, very little layered graphene is covalently bonded to the sensor reagent. The covalently assembled graphene particles do not break down in aqueous solution. As a result, the particles are observed not to cause pH drift in aqueous solution, and as described herein, they are dispersible in aqueous solution.

[0534] The second aspect of the structural advantage of graphene-based sensors is reflected in the signal-to-noise performance of each family of nanosensors in aqueous solution in the presence of serum. At time 0, no significant release of fluorescent signal is expected, since at t=0 the enzyme has not had time to cleave and release fluorescence. Furthermore, upon addition of serum, the increase in signal depends on both the sensitivity of the system and on the consistently low noise to be able to make the signal. For both FeNB and gNBS, we evaluated the relationship between the sensor and the sample incubated with serum at t=0 and found two differences.

[0535] The assay control, a sensor in the presence of buffer only, shows a slight increase in signal over 60 minutes, depending on the sensor for FeNB. This increase is on the order of two-fold. In contrast, gNBS kept in aqueous solution for up to 90 minutes shows no significant change in background signal. However, the S:N performance of gNBS that was not prepared by sonication and had not had the solvent removed also produces a lower signal over time, while the S:N is reduced at t=0. Thus, the performance of the gNBS sensor depends on better S:N at t=0 and improved S:N detection upon incubation with stimuli.

[0223]

[0536] More importantly, when the signal:noise for graphene NBS at t=0 is calculated, as measured by dividing the sample fluorescence by the assay control fluorescence, low signal to noise is observed. The gNBS sensor shows a smaller difference between the assay control and sample at t=0. The S:N at t=0 is 4.1+ / -1.6 (1S.D) for several different graphene sensors (in these examples, CTSB, uPA, CTSK, CTSD, CTSE, MMP12, MMP13, MMP15, NE, MMP3, MMP9) in the lot that were not manufactured using probe sonication or large scale drying.

[0537] In contrast, when sonication and drying are included, the S:N at t=0 increases to 6.9-7.6, not significantly different from FeNB. However, after 60 minutes of stimulation with serum, for the exemplary FeNB sensor CTSB, the S:N at t=60 was 2.0. For CTSB made with CGKSU lot 120120, the SN at t=60 was 9.8. For HEB CTSB100, the SN was 12.0, for HEB CTSB101, SN=18.5, and for CTSB102, SN=27. Thus, with solvent removal and sonication included in the preparation, the amount of enzyme activity evident in a single sample of serum increases from 2.0 to 27 in this example.

[0538] The S:N performance differences are evident in both the t=0 performance and the relative signal generated over time for a given sample. Thus, S:N is not dependent on the differential performance of any individual sensor. Rather, it can be generalized to the backbone and not to a specific enzyme activity. FeNB versus gNBS was compared in a single experiment using different lots of gNBS reflecting the inclusion of solvent removal and sonication. The S:N performance of gNBS increases with each iteration of the manufacturing protocol reflecting solvent removal and sonication.

[0224]

[0539] In defining the test solution, the optimal formulation will balance the best S:N performance, a measure of sensor stability, with the best kinetic increase in activity over time, reflecting the provision of a healthy environment for enzyme activity.

[0540] This. balance was observed. It is optimized in a pH environment of 7.2 with MES. The inclusion of monobasic salt maintained a physiological environment for enzyme activity when included at 155 mM. However, monobasic salt concentrations ranging from 0 mM to 1 M also affect the S:N of the sensor. As demonstrated by the results reported in Figure 14, increasing monobasic salt concentration reduces the assay control signal at 60 minutes. Thus, the "noise" due to particles alone becomes lower as the salt concentration increases. 155 mM was used as a concentration that reduces particle noise and supports enzyme activity in physiological conditions. EXAMPLES

[0225] Stability, reproducibility, signal-to-noise ratio, and multiplexing capabilities of biosensors in test solutions in embodiments with a heating step

[0541] The effect of heat treatment has been observed when serum was applied prior to incubation or when the assay was performed at a temperature higher than 37°C. For a typical sensor, in this example MMP10, heat treatment prior to the assay with incubation at 65°C for 5 minutes, SM / ΔCS:N is 1.2 without heat treatment and 1.3 with heat treatment. Thus, the low signal-to-noise ratio is not increased by heat treatment. After incubation in the presence of serum, the signal of the untreated serum increased to 14.1 SM / AC after 90 minutes. In contrast, the heat-treated sample SM / AC increased to 26.8, a 190% increase in signal intensity. Thus, the effect of heat treatment is not evident for the t=0 signal, rather, both heat treatment (Figure 44) and increased assay temperature (Figure 45) provide more enzyme activity, which results in a larger signal over the measured kinetic interval. Enzyme activity increases on average 3.2-fold when pretreated at elevated temperature (65°C). Similarly, the signal increased on average 3.1-fold when the assay was incubated at 45 °C and 1.7-1.9-fold when incubated at 41 °C. Such changes were observed for all sensors, and the measured increase in activity was temperature dependent. Thus, 41 °C showed higher activity than 37 °C. 45 °C showed higher activity than 41 °C.

[0542] The temperature was established and maintained in a temperature-controlled oven or fluorometer. High temperature results in increased enzyme kinetics at higher temperatures providing improved detection of protease activity. Furthermore, increased temperature is expected to modify the protein corona observed around the particles and described herein (Figure 46).

[0543] A temperature-dependent gradient is expected that balances the improvement on protease activity with temperature, which denatures other proteins in the serum before they can cause precipitation. Incubating serum before or during the assay is both effective in increasi...

Claims

1. at least two pure graphene nanosheets having a pure graphene nanosheet surface are stacked together to form a pure graphene assembly; A coating layer covering at least 50% of the surface of the pure graphene nanosheets. A graphene core particle comprising: the coating layer comprises an organic and / or inorganic compound having a solubility in water of at least 10 grams per liter of H2O at 25°C, the organic and / or inorganic compounds are attached to the pure graphene nanosheets to form the coating layer; The at least two pure graphene nano-sheets have a carbon content of at least 99% and an oxygen content of less than 1%, and the pure graphene is pure so as to be free of foreign matter and impurities; Graphene core particles, wherein the pure graphene nano-sheets and / or the organic and / or inorganic compounds of the coating layer are configured to present functional groups capable of binding to corresponding functional groups in aqueous solution.

2. Graphene core particles according to claim 1, having an average size of 10 nm to 5000 nm and at least 85% of the surface coated with the coating material.

3. 2. The graphene core particle of claim 1, comprising 2 to 100 of the stacked pure graphene nanosheets and having an average size of 900 nm or less, 350 nm or less, or 250 nm or less.

4. 2. The graphene core particle according to claim 1, comprising 2 to 100 of said stacked pure graphene nanosheets, and having at least 90% of its surface coated with a coating material.

5. 5. The graphene core particle according to claim 1, comprising 5 to 25 of the stacked pure graphene nanosheets.

6. The graphene core particle according to any one of claims 1 to 5, comprising 5 to 7 of the stacked pure graphene nanosheets.

7. 7. The graphene core particle according to claim 1, wherein the stacked pure graphene nanosheets form particles with an average size of 150 nm.

8. Graphene core particles according to any one of claims 1 to 7, wherein the coating material comprises an organic polymer.

9. Graphene core particles according to claim 8, wherein the organic polymer comprises one or more of polyethyleneimine, polycaprolactone, polyethylene glycol, polyvinyl alcohol, polyvinylpyrrolidone, (meth)acrylate and (meth)acrylamide polymers, polystyrene-carboxylic acid and polystyrene-amine.

10. Graphene core particle according to any one of claims 1 to 8, wherein a coating material covers at least 99% of the surface of the stacked pure graphene nanosheets.

11. Graphene core particle according to any one of claims 1 to 10, wherein the thickness of the coating material is not more than 18 nm, and can be as low as 2 nm for attached peptide sequences characterized by targeting ability.

12. Graphene core particles according to any one of claims 1 to 11, wherein the thickness of the coating material is from 8 to 17 nm, from 2 to 18 nm, or from 5 to 15 nm.

13. 1. A graphene biosensor configured to detect a target biomarker, comprising: A method for detecting a target biomarker comprising the steps of: detecting a target biomarker comprising: detecting a target biomarker by detecting a target biomarker; detecting a target biomarker by detecting a target biomarker; the coating layer and the peptide bond are configured to set up a quenching distance between the graphene nano-sheet and the detectable moiety such that the graphene nano-sheet quenches the fluorescent signal of the detectable moiety; the peptide bond is further configured to set up an emission distance between the graphene nano-sheet and the detectable moiety upon recognition of the recognition sequence by the target biomarker, wherein the graphene nano-sheet does not quench the fluorescent signal of the detectable moiety; A graphene biosensor, wherein the peptide bond specific for the target biomarker and the detectable moiety form a target-specific detectable moiety configured to emit a detectable fluorescent signal upon modification of the peptide bond by the target biomarker.

14. 14. The graphene biosensor of claim 13, wherein the recognition sequence is specific for a biomarker selected from the group consisting of proteases, kinases, arginases, cytokines / chemokines, dioxygenases, esterases, and combinations thereof.

15. 15. The graphene biosensor of claim 14, wherein the protease is selected from the group consisting of serine, aspartyl, cysteine, metalloproteases, caspases, urokinase, cathepsins, and combinations thereof.

16. 16. The graphene biosensor of any one of claims 13 to 15, wherein the target biomarker is indicative of a condition selected from the group consisting of cancerous or precancerous cell activity, bacterial activity, infection, inflammation, and combinations thereof.

17. 17. The graphene biosensor of any one of claims 13 to 16, wherein the detectable moiety is a chromophore / luminophore selected from the group consisting of organic dyes, inorganic dyes, fluorophores, phosphophores, light absorbing particles, quantum dots, and combinations thereof, and metallated complexes thereof.

18. 18. The graphene biosensor of claim 17, wherein the chromophore / luminophore is an organic dye selected from the group consisting of coumarin, pyrene, cyanine, BODIPY dyes, benzene, N-methylcarbazole, erythrosine B, N-acetyl-L-tryptophanamide, 2,5-diphenyloxazole, rubrene, and N-(3-sulfopropyl)acridinium.

19. 18. The graphene biosensor of claim 17, wherein the chromophore / luminophore is an inorganic dye selected from the group consisting of porphyrins, phthalocyanines, chlorines, and metallated chromophores.

20. The graphene biosensor of claim 19, wherein the porphyrin is tetracarboxy-phenyl-porphyrin (TCPP) or Zn-TCPP.

21. 18. The graphene biosensor of claim 17, wherein the chromophore / luminophore is a fluorophore or phosphorus selected from the group consisting of phosphorescent dyes, fluoresceins, rhodamines, and anthracenes.

22. 18. The graphene biosensor of claim 17, wherein the quantum dots are selected from the group consisting of CdSe / ZnS core / shell quantum dots, CdTe / CdSe core / shell quantum dots, CdSe / ZnTe core / shell quantum dots, and alloyed semiconductor quantum dots.

23. The graphene biosensor of any one of claims 13 to 22, wherein the coating layer is selected from the group consisting of polyethyleneimine, polycaprolactone, polyvinyl alcohol, polyvinylpyrrolidone, (meth)acrylate and (meth)acrylamide polymers, polystyrene-carboxylic acid, polystyrene-amine, dextran, pullulan, chitosan, alginate, cellulose, and hyaluronic acid, and mixtures or copolymers thereof.

24. The graphene biosensor of any one of claims 13 to 23, wherein the size of the graphene core particle is 50 nm to 500 nm.

25. 24. The graphene biosensor of any one of claims 13 to 23, comprising a plurality of detectable moieties attached to the graphene core particle via respective said peptide bonds.

26. 26. The graphene biosensor of any one of claims 13 to 25, comprising at least two different detectable moieties attached to the graphene core particle via the peptide bonds, each having a recognition sequence specific for a different target biomarker.

27. A multi-graphene biosensor comprising a graphene core particle according to any one of claims 1 to 12 and a plurality of target-specific detectable moieties attached to said graphene core particle, wherein: Each of the target-specific detectable moieties is formed from a detectable moiety capable of emitting a fluorescent signal, the detectable moiety being bound to a peptide bond that contains a recognition sequence specific for a target biomarker; In each of the target-specific detectable moieties, the peptide bond is configured in combination with the coating layer of the graphene core particle to provide a quenching distance between the detectable moiety and the graphene core particle, and the graphene nanosheets quench the fluorescent signal of the detectable moiety. A multi-graphene biosensor, wherein the recognition sequence of the detectable moiety for the target biomarker is configured to specifically detect the target biomarker, and the plurality of detectable moieties are selected to specifically detect a plurality of different target biomarkers.

28. 28. The multi-graphene biosensor of claim 27, comprising up to 10 target-specific detectable moieties, each of which exhibits a detectable moiety that is detectable across the entire range of the UV / Vis / NIR spectrum.

29. 1.6±0.2×10 per gram of biosensor －５ 29. The multi-graphene biosensor of claim 27 or 28, comprising target-specific detectable moiety oligopeptides at molar density.

30. A composition comprising one or more graphene core particles according to any one of claims 1 to 12 and / or one or more graphene biosensors according to any one of claims 13 to 29 in combination with suitable auxiliary agents.

31. 31. The composition of claim 30, which is a pharmaceutical composition, and the adjuvant is a pharma- ceutically acceptable adjuvant.

32. Contacting a biological sample with the graphene biosensor according to any one of claims 13 to 29 to produce a reaction solution; and detecting a change in the reaction solution; 23. A method for detecting activity of a biomarker in a biological sample, comprising:

33. moreover, exposing the reaction solution to an excitation light source; and detecting a change in the absorption or emission spectrum of said detectable moiety as a function of the activity of said biomarker in said biological sample.

33. The method of claim 32, comprising:

34. 34. The method of claim 32 or 33, wherein the change comprises a blue shift in the absorption or emission maximum of the detectable moiety after contacting relative to the absorption or emission spectrum before said contacting.

35. A method according to any one of claims 32 to 34, wherein the change comprises the appearance of a new visible colour or emission band relative to the absorption or emission spectrum of said detectable moiety prior to said contacting.

36. The method of any one of claims 32 to 35, wherein the contacting comprises incubating the biological sample with a biosensor for a period of less than 90 minutes, or less than 60 minutes.

37. 37. The method of any one of claims 32 to 36, wherein the contacting comprises providing a microplate comprising a plurality of microwells, one or more of which have a plurality of biosensors distributed therein, and adding the biological sample to the microwells to create a respective one of the reaction solutions in each of the microwells.

38. The method according to any one of claims 32 to 37, wherein the biological sample and / or the reaction solution are heated prior to detection.

39. A system for detecting the activity of a biomarker in a biological sample, comprising a biosensor according to any one of claims 13 to 29 and a reagent for simultaneous or sequential use in a method for detecting the activity of a biomarker in a biological sample according to any one of claims 32 to 38.

40. A method for multiplex detection of the activity of multiple biomarkers in a biological sample, comprising: Contacting a biological sample with the multi-graphene biosensor according to any one of claims 27 to 29, configured to present detectable moieties specific to a plurality of biomarkers, to produce a reaction solution; and detecting a change in the reaction solution; and / or Contacting the biological sample with a plurality of graphene biosensors according to any one of claims 13 to 26, each of which displays a peptide bond specific for one of the plurality of biomarkers; A method comprising:

41. 41. The method of claim 40, wherein the biological sample and / or the reaction solution are heated prior to detection.

42. 42. The method of claim 40 or 41, wherein the biological sample comprises a plurality of biological samples and the contacting is performed on the plurality of biological samples in parallel.

43. A system for multiplexed detection of the activity of multiple biomarkers in a biological sample comprising a multiple graphene biosensor according to any one of claims 27 to 29 and / or a method for multiplexed detection of the activity of multiple biomarkers in a biological sample according to any one of claims 40 to 42, each biosensor presenting a peptide bond specific for one of the multiple biomarkers, and optionally a plurality of reagents for simultaneous or sequential use.

44. A method for producing a graphene core particle according to any one of claims 1 to 12, comprising the steps of: Providing at least two pure graphene nanosheets having a pure graphene nanosheet surface stacked together to form a pure graphene assembly; and coating the surface of the graphene nanosheets with a coating layer of organic molecules and / or inorganic molecules.

45. A method for making a biosensor according to any one of claims 13 to 26, comprising providing a graphene core particle according to any one of claims 1 to 12 and attaching a detectable moiety to the graphene nanosheet surface via a peptide bond.

46. The method of claim 45, wherein prior to the attaching, the graphene core particles according to any one of claims 1 to 12 are dispersed, and the attaching is carried out by contacting the dispersed graphene core particles with the detectable moiety comprising the detectable moiety attached to the peptide bond.

47. A system for producing a biosensor according to any one of claims 13 to 25, comprising a graphene core particle according to any one of claims 1 to 12, a peptide bond, a detectable moiety, and a reagent for attaching the detectable moiety to a surface of the graphene core particle via the peptide bond.

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