Method for analyzing biological samples

Abstract

Described herein are methods for analyzing a biological sample by liquid chromatography-tandem mass spectrometry or direct injection mass spectrometry.

Description

[0001] Cross-references

[0002] This application claims the benefit of U.S. Provisional Application No. 63 / 368,028, filed on July 8, 2022, U.S. Provisional Application No. 63 / 368,474, filed on July 14, 2022, and U.S. Provisional Application No. 63 / 386,483, filed on December 7, 2022, each of which is incorporated herein by reference in its entirety.

[0003] Sequence Listing

[0004] This application contains a sequence listing, which has been submitted electronically in XML format and is hereby incorporated by reference in its entirety. The XML copy was created on June 28, 2023, is named 53344-764_601_SL.xml, and is 4,529 bytes in size.

[0005] Incorporation by reference

[0006] All publications, patents, and patent applications mentioned in this specification are incorporated herein by reference to the same extent as if each individual publication, patent, or patent application was specifically and individually indicated to be incorporated by reference. If the publications and patents or patent applications incorporated by reference contradict the disclosure contained in this specification, this specification is intended to supersede and / or take precedence over any such contradictory material. Background Art

[0007] Nanoflow liquid chromatography-tandem mass spectrometry (nLC-MS / MS) has attracted attention in proteomics due to its high sensitivity and high throughput. LC systems can be coupled to MS systems to minimize ionization suppression, as ESI can be a major bottleneck for MS-based detection schemes. Comprehensive proteome coverage and throughput are inversely correlated, and scaling up proteomics (defined as the number of samples analyzed without compromising coverage) remains a challenge. Summary of the invention

[0008] Disclosed herein are methods that address the inherent problems of nLC-MS / MS in extended proteomics by removing the chromatographic domain and using surfaces (e.g., particles) to reduce sample complexity. In some embodiments, the methods disclosed herein can increase throughput by several orders of magnitude without compromising identification rates.

[0009] In some aspects, the present disclosure provides a method comprising: contacting a plurality of biomolecules with a surface to adsorb the plurality of biomolecules on the surface; and performing mass spectrometry on the plurality of biomolecules to generate a mass spectrum, wherein the mass spectrometry is (i) performed without chromatographic separation, or (ii) performed using chromatographic separation with a gradient length of up to 30 minutes.

[0010] In some embodiments, the gradient length is at most 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 minute.

[0011] In some embodiments, the chromatographic separation uses a chromatography column comprising a length of at most 30, 25, 20, 15, 10, 5, 4, 3, 2, 1, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, or 0.1 centimeters.

[0012] In some embodiments, performing mass spectrometry includes performing ion mobility separation.

[0013] In some embodiments, ion mobility separations are performed using traveling wave ion mobility separations.

[0014] In some embodiments, traveling wave ion mobility separation is performed along a distance greater than 5 m or greater than 10 m.

[0015] In some embodiments, traveling wave ion mobility separation is performed along a serpentine path.

[0016] In some embodiments, ion mobility separations are performed using high-field asymmetric waveform ion mobility spectrometry (FAIMS).

[0017] In some embodiments, performing mass spectrometry includes performing direct infusion mass spectrometry.

[0018] In some embodiments, direct infusion mass spectrometry is performed in less than about 10 minutes, less than about 5 minutes, less than about 3 minutes, or less than about 2 minutes.

[0019] In some embodiments, mass spectrometry is performed with an isolation width of about 0.4, 0.6, 0.8, 1, or 2 m / z.

[0020] In some embodiments, mass spectrometry is performed with a maximum injection time of about 500 ms, 1 s, 5 s, 30 s, 1 min, 2 min, 3 min, 4 min, 5 min, or 10 min.

[0021] In some embodiments, mass spectrometry is performed at a resolution of about 120, 240, or 500K.

[0022] In some embodiments, mass spectrometry is performed at a resolution of about 30 K to about 800 K. In some embodiments, contacting the plurality of biomolecules with the surface to adsorb the plurality of biomolecules on the surface comprises contacting a biological sample with the surface.

[0023] In some embodiments, the biological sample comprises blood, plasma, serum, urine, cerebrospinal fluid, synovial fluid, tears, saliva, whole blood, breast milk, nipple aspirate, ductal lavage, vaginal fluid, nasal fluid, ear fluid, gastric fluid, pancreatic fluid, trabecular fluid, lung lavage fluid, sweat, crevicular fluid, semen, prostatic fluid, sputum, feces, bronchial lavage fluid, fluid from a swab, bronchial aspirate, fluidized solids, fine needle aspiration sample, tissue homogenate, lymph fluid, cell culture sample, or any combination thereof.

[0024] In some embodiments, the biological sample comprises blood, serum, or plasma.

[0025] In some embodiments, the biological sample is a biological fluid.

[0026] In some embodiments, the biological sample comprises a cell lysate.

[0027] In some embodiments, the surface is a particle.

[0028] In some embodiments, contacting the plurality of biomolecules with the surface to adsorb the plurality of biomolecules on the surface comprises incubating the biomolecules with the surface for at least 15 minutes.

[0029] In some embodiments, the incubation is carried out at a temperature of about 5°C to about 40°C.

[0030] In some embodiments, mass spectrometry comprises tandem mass spectrometry.

[0031] In some embodiments, mass spectrometry comprises Fourier Transform mass spectrometry.

[0032] In some embodiments, mass spectrometry comprises time-of-flight mass spectrometry.

[0033] In some embodiments, mass spectrometry is performed to identify at least about 300 protein groups.

[0034] In some embodiments, performing mass spectrometry comprises data independent acquisition (DIA).

[0035] In some embodiments, the surface comprises a plurality of particles having a polydispersity index greater than 0.5, greater than 0.75, or greater than 1.0.

[0036] In some embodiments, the surface comprises a plurality of particles having a polydispersity index of less than 0.1.

[0037] In some embodiments, the plurality of biomolecules comprises a plurality of proteins.

[0038] In some embodiments, the surface selectively adsorbs extracellular vesicles.

[0039] In some embodiments, the surface is ammonium functionalized.

[0040] In some embodiments, the surface comprises polyethyleneimine.

[0041] In some embodiments, the surface comprises cross-linked polyethyleneimine.

[0042] In some embodiments, the surface comprises polyethylene oxide and aromatic groups.

[0043] In some aspects, the present disclosure provides a method comprising: contacting a plurality of biomolecules with a surface to adsorb the plurality of biomolecules on the surface; performing mass spectrometry on the plurality of biomolecules to generate a multiplexed mass spectrum; and deconvolving the multiplexed mass spectrum to generate a plurality of deconvoluted MS signals, wherein the deconvolution is based on the type of the surface.

[0044] In some embodiments, the deconvolution is based on genomic information associated with the plurality of biomolecules.

[0045] In some embodiments, the genomic information comprises a library of polyamino acids expressible by a plurality of organisms.

[0046] In some embodiments, the library comprises a plurality of mass spectrometry signals for a plurality of expressible polyamino acids.

[0047] In some embodiments, performing mass spectrometry includes scanning a plurality of biomolecules across a plurality of mass windows.

[0048] In some embodiments, scanning is performed at a frequency between 20 and 80 Hz.

[0049] In some embodiments, the plurality of mass windows are between 400 and 1600 Daltons.

[0050] In some embodiments, the plurality of mass windows comprises a window of about 2 Daltons.

[0051] In some embodiments, a multiplexed mass spectrometer comprises signals within a window.

[0052] In some embodiments, a plurality of mass spectrometric signals in the library are within the window.

[0053] In some embodiments, the deconvolution is based on a library of a subset of a plurality of expressible polyamino acids, wherein the subset is configured to be preferentially adsorbed to a surface compared to expressible polyamino acids not in the subset.

[0054] In some embodiments, the abundance of the plurality of biomolecules is up to about 6 orders of magnitude lower than the most abundant biomolecule in the sample.

[0055] In some embodiments, the plurality of biomolecules are at least about 5 orders of magnitude and at most about 8 orders of magnitude less abundant than the most abundant biomolecule in the sample.

[0056] In some embodiments, the plurality of biomolecules are present in an abundance that is at least about 7 orders of magnitude less than the most abundant biomolecule in the sample.

[0057] In some embodiments, contacting the plurality of biomolecules with the surface to adsorb the plurality of biomolecules onto the surface comprises contacting a biological sample with the surface.

[0058] In some embodiments, the biological sample comprises blood, plasma, serum, urine, cerebrospinal fluid, synovial fluid, tears, saliva, whole blood, milk, nipple aspirate, ductal lavage, vaginal fluid, nasal fluid, ear fluid, gastric fluid, pancreatic fluid, trabecular fluid, lung lavage fluid, sweat, gingival crevicular fluid, semen, prostatic fluid, sputum, stool, bronchial lavage fluid, fluid from a swab, bronchial aspirate, fluidized solids, fine needle aspiration sample, tissue homogenate, lymph fluid, cell culture sample, or any combination thereof.

[0059] In some embodiments, the biological sample comprises blood, serum, or plasma.

[0060] In some embodiments, the biological sample comprises a cell lysate.

[0061] In some embodiments, the biological sample is a biological fluid.

[0062] In some embodiments, the surface is a particle.

[0063] In some embodiments, contacting the plurality of biomolecules with the surface to adsorb the plurality of biomolecules on the surface comprises incubating the biomolecules with the surface for at least 15 minutes.

[0064] In some embodiments, the incubation is carried out at a temperature of about 5°C to about 40°C.

[0065] In some embodiments, mass spectrometry comprises tandem mass spectrometry.

[0066] In some embodiments, mass spectrometry comprises Fourier transform mass spectrometry.

[0067] In some embodiments, mass spectrometry comprises time-of-flight mass spectrometry.

[0068] In some embodiments, mass spectrometry comprises data independent acquisition (DIA).

[0069] In some embodiments, mass spectrometry comprises targeted mass spectrometry.

[0070] In some embodiments, targeted mass spectrometry comprises multiple reaction monitoring (MRM).

[0071] In some embodiments, the surface selectively adsorbs extracellular vesicles.

[0072] In some embodiments, the surface is ammonium functionalized.

[0073] In some embodiments, the surface comprises polyethyleneimine.

[0074] In some embodiments, the surface comprises cross-linked polyethyleneimine.

[0075] In some embodiments, the surface comprises polyethylene oxide and aromatic groups.

[0076] Some embodiments disclosed herein include a method comprising incubating a biological sample with one or more surfaces to form a biomolecule corona on the one or more surfaces; performing mass spectrometry on the biomolecules from the biomolecule corona to generate a mass spectrum, wherein the mass spectrometry is (i) performed without chromatographic separation, or (ii) performed using chromatographic separation with a gradient length of up to 10 minutes.

[0077] In some embodiments, the gradient length is at most 9, 8, 7, 6, 5, 4, 3, 2, or 1 minute.

[0078] In some embodiments, the chromatographic separation uses a chromatography column comprising a length of at most 30, 25, 20, 15, 10, 5, 4, 3, 2, 1, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, or 0.1 centimeters.

[0079] In some embodiments, performing mass spectrometry includes performing ion mobility separation.

[0080] In some embodiments, the ion mobility separation is performed using high-field asymmetric waveform ion mobility spectrometry (FAIMS).

[0081] In some embodiments, ion mobility separations are performed using traveling wave ion mobility separations.

[0082] In some embodiments, traveling wave ion mobility separation is performed along a distance greater than 5 m or greater than 10 m.

[0083] In some embodiments, traveling wave ion mobility separation is performed along a serpentine path.

[0084] In some embodiments, performing mass spectrometry includes performing direct infusion mass spectrometry.

[0085] In some embodiments, performing mass spectrometry is performed without chromatographic separation.

[0086] In some embodiments, performing mass spectrometry comprises tandem mass spectrometry.

[0087] In some embodiments, performing mass spectrometry comprises data independent acquisition (DIA).

[0088] In some embodiments, performing mass spectrometry comprises targeted mass spectrometry.

[0089] In some embodiments, targeted mass spectrometry comprises multiple reaction monitoring (MRM).

[0090] In some embodiments, performing mass spectrometry comprises electrospray injection.

[0091] In some embodiments, the biomolecules from the biomolecule corona include proteins.

[0092] In some embodiments, performing mass spectrometry comprises detecting at least 50, 100, 200, 250, 300, 400, 500, or 1000 proteins in the biological sample.

[0093] In some embodiments, performing mass spectrometry comprises detecting at least 50, 100, 200, 250, 300, 400, 500, or 1000 proteomes in the biological sample.

[0094] In some embodiments, the method further comprises removing the biomolecule from the biomolecule corona prior to (b).

[0095] In some embodiments, removing the biomolecule from the biomolecule corona comprises digesting the biomolecule corona with an enzyme.

[0096] In some embodiments, the enzyme is a protease, such as trypsin.

[0097] In some embodiments, the method further comprises alkylating and reducing the biomolecule from the biomolecule corona prior to (b).

[0098] In some embodiments, the method further comprises alkylating, reducing, and digesting the biomolecule from the biomolecule corona prior to (b).

[0099] In some embodiments, the method further comprises applying one or more washing steps to the biomolecules from the biomolecule corona prior to (b).

[0100] In some embodiments, incubating comprises maintaining the biological sample at a temperature of 20°C to 50°C for at least 15 minutes.

[0101] In some embodiments, the biological sample comprises blood, plasma, serum, urine, cerebrospinal fluid, synovial fluid, tears, saliva, whole blood, milk, nipple aspirate, ductal lavage, vaginal fluid, nasal fluid, ear fluid, gastric fluid, pancreatic fluid, trabecular fluid, lung lavage fluid, sweat, gingival crevicular fluid, semen, prostatic fluid, sputum, stool, bronchial lavage fluid, fluid from a swab, bronchial aspirate, fluidized solids, fine needle aspiration sample, tissue homogenate, lymph fluid, cell culture sample, or any combination thereof.

[0102] In some embodiments, the biological sample comprises blood, serum, or plasma.

[0103] In some embodiments, the biological sample comprises a cell lysate.

[0104] In some embodiments, one or more surfaces include particles.

[0105] In some embodiments, the particles are porous particles.

[0106] In some embodiments, the particles are microparticles.

[0107] In some embodiments, the particles are nanoparticles.

[0108] In some embodiments, the particles comprise a paramagnetic material.

[0109] In some embodiments, the paramagnetic material is a superparamagnetic material.

[0110] In some embodiments, the paramagnetic material comprises iron oxide.

[0111] In some embodiments, a biological sample is incubated with a first surface and a second surface having different physicochemical properties such that a different protein corona is formed on each surface.

[0112] In some embodiments, the first surface and the second surface comprise different charge signatures.

[0113] In some embodiments, the first surface and the second surface comprise different zeta potential signatures.

[0114] In some embodiments, the first surface and the second surface comprise the same charge signature.

[0115] In some embodiments, the first surface and the second surface comprise the same zeta potential signature.

[0116] In some embodiments, the first surface, the second surface, or both comprise carboxylate groups, acrylate groups, methacrylate groups, acetal groups, hemiacetal groups, hemiketal groups, sulfonic acid groups, sulfinic acid groups, thiocarboxylic acid groups, phosphonic acid groups, phosphate groups, phosphodiester groups, boronic acid groups, borate ester groups, boric acid groups, borate ester groups, silica groups, silanol groups, polymers, or any combination thereof.

[0117] In some embodiments, the first surface and the second surface are incubated in separate aliquots of the biological sample.

[0118] In some embodiments, the biomolecule corona from the first surface and the biomolecule corona from the second surface are subjected to mass spectrometry separately.

[0119] In some embodiments, the first surface and the second surface are incubated in a single volume of the biological sample.

[0120] In some embodiments, the method further comprises washing the biomolecule corona with a washing composition prior to (b).

[0121] In some embodiments, the method further comprises determining the biological state of the subject using mass spectrometry.

[0122] In some embodiments, the biological sample is incubated with at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 surfaces having different physicochemical properties.

[0123] In some embodiments, the biological sample is incubated with 3 to 8 surfaces having different physicochemical properties.

[0124] In some embodiments, performing mass spectrometry comprises at least 2, 3, 4, 5, 6, 7, 8, 9, or 10 separate injections.

[0125] In some embodiments, performing mass spectrometry comprises 3-8 separate injections.

[0126] In some embodiments, each of the separate injections corresponds to a biomolecule corona obtained from a different surface.

[0127] In some embodiments, at least one of the surfaces selectively adsorbs extracellular vesicles.

[0128] In some embodiments, at least one of the surfaces is ammonium functionalized.

[0129] In some embodiments, at least one of the surfaces comprises polyethyleneimine.

[0130] In some embodiments, at least one of the surfaces comprises cross-linked polyethyleneimine.

[0131] In some embodiments, at least one of the surfaces comprises polyethylene oxide and aromatic groups.

[0132] Some embodiments disclosed herein include a method comprising incubating a biological sample with a first magnetic particle to form a first protein corona; incubating the biological sample with a second magnetic particle to form a second protein corona, wherein the first magnetic particle and the second magnetic particle have different physicochemical properties, and wherein the first magnetic particle and the second magnetic particle are incubated with separate volumes of the biological sample; and performing mass spectrometry on proteins from the first protein corona and the second protein corona using direct injection to generate a mass spectrum, wherein separate injections are performed for the first protein corona and the second protein corona.

[0133] In some embodiments, at least 500 different protein groups are detected.

[0134] In some embodiments, at least 1000 different protein groups are detected.

[0135] In some embodiments, the biological sample is blood, serum, or plasma.

[0136] In some embodiments, the first magnetic particles and the second magnetic particles have different zeta potential signatures.

[0137] In some embodiments, the outer surface of the first magnetic particle comprises amine functional groups and the outer surface of the second magnetic particle comprises carboxyl functional groups.

[0138] In some embodiments, the first magnetic particle comprises a polymeric outer surface and the second magnetic particle comprises a non-polymeric outer surface.

[0139] In some embodiments, at least 50 unique protein groups are detected from the first protein corona that are not detected from the second protein corona.

[0140] In some embodiments, at least 100 unique groups of proteins are detected from the first protein corona that are not detected from the second protein corona.

[0141] In some embodiments, the first magnetic particles and the second magnetic particles each have a polydispersity index of less than 0.25.

[0142] In some embodiments, the first magnetic particles and the second magnetic particles each have a polydispersity index of less than 0.1.

[0143] In some embodiments, the first magnetic particles and the second magnetic particles are nanoparticles.

[0144] In some embodiments, the first magnetic particles and the second magnetic particles have a diameter less than 500 nm.

[0145] In some embodiments, mass spectrometry is performed in less than 10 minutes. BRIEF DESCRIPTION OF THE DRAWINGS

[0146] This patent application contains at least one drawing drawn in color. Copies of this patent or patent application with color drawing(s) will be provided by the Office upon request and payment of the necessary fee.

[0147] Figure 1 is a diagram illustrating the steps in determining protein identity.

[0148] Figure 2 A linear system of equations showing the spectral demultiplexing algorithm.

[0149] Figure 3 Direct injection MS spectra (relative intensity vs. m / z) of four extracted protein groups ((1) KQTALVELVK (SEQ ID NO: 1); (2) YTCLPGYVR (SEQ ID NO: 2); (3) ESDTSYVSLK (SEQ ID NO: 3); and (4) DCHLAQVPSHTVVAR (SEQ ID NO: 4)) are shown.

[0150] Figure 4A Shown is the direct injection MS spectrum (relative intensity vs. m / z) of KQTALVELVK (SEQ ID NO: 1).

[0151] Figure 4B Shown is the direct injection MS spectrum (relative intensity vs. m / z) of YTCLPGYVR (SEQ ID NO: 2).

[0152] Figure 4C Shown is the direct injection MS spectrum (relative intensity vs. m / z) of ESDTSYVSLK (SEQ ID NO: 3).

[0153] Figure 4D Shown is the direct injection MS spectrum (relative intensity vs. m / z) of DCHLAQVPSHTVVAR (SEQ ID NO: 4).

[0154] Figure 5A Shown is a graph illustrating unique peptides discovered by the nanoparticles at 60k resolution.

[0155] Figure 5B Shown is a graph illustrating unique peptides discovered by the nanoparticles at 120k resolution.

[0156] Figure 6A flow chart showing proteome analysis using the "improved" protein inference module of AlphaPept.

[0157] Fig. 7A A waterfall plot of the MS-direct nanoparticle panel (Carr database) is shown. (Number of database entries: 5304; Number of input protein groups: 159; Number of isolated protein IDs: 159; and Number of matches to the database: 133).

[0158] Figure 7B A waterfall plot of the NEAT triplet is shown (Carr database). (Number of database entries: 5304; number of input protein groups: 130; number of isolated protein IDs: 130; and number of matches to the database: 108).

[0159] Figure 8 Bar graphs illustrating the number of proteomes for CsoDIAq, Matrix Demultiplexing-Neat, Matrix Demultiplexing-Panel, and 30 min-Neat-LCMS are shown.

[0160] Figure 9A-9C A waterfall plot for the 3-nanoparticle set is shown (Carr database).

[0161] Fig.10 The design of the experimental matrix in which sensitivity, resolution and flux are balanced is shown. The experimental conditions are shown in Table 3.

[0162] The novel features of the present disclosure are set forth with particularity in the appended claims.A better understanding of the features and advantages of the present disclosure will be obtained by reference to the following detailed description which sets forth illustrative embodiments. DETAILED DESCRIPTION

[0163] Overview

[0164] Liquid chromatography-mass spectrometry (LC-MS) is an important analytical technique in proteomics, in which proteins are digested and separated by high-efficiency chromatography and detected by a mass spectrometer. In particular, nanoflow liquid chromatography-tandem mass spectrometry (nLC-MS / MS) has attracted attention in proteomics due to its high sensitivity and high throughput. However, large-scale analysis of proteomics samples (such as plasma or tissue lysates) by nLC-MS / MS remains a challenge due to the complexity and dynamic range of proteomics samples.

[0165] Two major factors limiting the scale-up of nLC-MS / MS can include electrospray (ESI) dynamic range and instrument duty cycle. Despite continued improvements in instrument scan rates, ESI has been the rate limiting factor. Better peak capacity can directly contribute to identification rate. This means that reducing the dynamic concentration range of the MS detector for a mixture at a given analysis time point is likely to help improve identification rate, as ESI saturation occurs over five orders of magnitude of the dynamic range. However, gradient length is the main contributor to peak capacity, and therefore, analysts may be forced to make a trade-off between identification rate and throughput.

[0166] An existing method to reduce the intra-scan dynamic range in an LC-MS run is to increase the gradient length. Increasing the gradient length can increase peak capacity, which can allow co-eluting peaks to be resolved, and can alleviate ionization suppression in ESI, which in turn can reduce throughput.

[0167] Also disclosed herein is a method for detecting biomolecules in a sample. The method may include incubating the biological sample with one or more surfaces to form a biomolecule corona on the one or more surfaces; performing mass spectrometry on the biomolecules from the biomolecule corona to generate a mass spectrum, wherein the mass spectrometry is (i) performed without chromatographic separation, or (ii) performed using chromatographic separation with a gradient length of up to 10 minutes.

[0168] Also disclosed herein is a method comprising incubating a biological sample with a first magnetic particle to form a first protein corona; incubating the biological sample with a second magnetic particle to form a second protein corona, wherein the first magnetic particle and the second magnetic particle have different physicochemical properties, and wherein the first magnetic particle and the second magnetic particle are incubated with separate volumes of the biological sample; and performing mass spectrometry on proteins from the first protein corona and the second protein corona using direct injection to generate a mass spectrum, wherein separate injections are performed for the first protein corona and the second protein corona.

[0169] In some cases, the methods disclosed herein are advantageous because they can significantly reduce the amount of time required to perform mass spectrometry. Standard proteome mass spectrometry analysis may require a liquid chromatography gradient of one hour or more. The methods disclosed herein can be performed in less than 20 minutes or even less than 10 minutes while still detecting and / or quantifying a large number of biomolecules, such as at least 1000 proteins.

[0170] In some embodiments, disclosed herein is a method for reducing the dynamic range by using nanoparticles. A highly parallel protein quantification platform combining a nanoparticle (NP) protein corona with LC-MS can provide efficient proteome analysis because the enrichment is affinity-based rather than concentration-dependent. At equilibrium, binding kinetics can determine the protein corona. Thus, disclosed herein, in some embodiments, is a method for reducing the dynamic range of a large plasma sample (such as from about 10 to 20 μg / mL) by using a set of two, three, four, five or more different nanoparticles with different physicochemical properties on their surfaces. 9 to about 10 12 ) to five orders of magnitude.

[0171] In some embodiments, disclosed herein is a method for designing a set of multiple nanoparticles to exploit nanoparticle affinity, wherein the multiple nanoparticles are designed to enrich proteins at different concentration ranges, respectively. In some embodiments, the method for designing a set of multiple nanoparticles includes: establishing a training model for protein corona formation; adjusting particle chemistry to enrich proteins at different concentrations; injecting each peptide pool enriched nanoparticle for about 30 seconds, about 35 seconds, about 40 seconds, 45 seconds, about 50 seconds, or about 55 seconds of MS detection; using a reference genome to establish a predicted spectral library; and deconvoluting the multiplexed spectra using linear algebra.

[0172] In some embodiments, disclosed herein is a method for performing mass spectrometry. In some embodiments, the method includes classifying a sample with one or more nanoparticles. In some embodiments, the method includes performing ion migration separation on multiple biomolecules. For example, ion migration separation can include traveling wave ion migration or high field asymmetric waveform ion migration spectrum. In some embodiments, traveling wave ion migration includes a separation distance of at least 5m or 10m. In some embodiments, traveling wave ion migration includes a serpentine path. In some embodiments, the method includes performing direct injection mass spectrometry. In some embodiments, the method includes performing a demultiplexing algorithm. In some embodiments, quadrupole transmission can be performed with a mass range of 400-1200, scanning at 25 Hz with a 4 Dalton window at 3 CV, which provides about 24 seconds per injection.

[0173] In some embodiments, suitable nanoparticles include, but are not limited to, for example, organic nanoparticles, non-organic particles, inorganic nanoparticles, or combinations thereof. In some embodiments, nanoparticles are, for example, micelles, extracellular vesicles, liposomes, iron oxide, graphene, silicon dioxide, protein-based particles, polystyrene, silver and gold particles, quantum dots, palladium, platinum, titanium, and combinations thereof. In some embodiments, nanoparticles are polymer nanoparticles. In some embodiments, nanoparticles are metal oxides. In some embodiments, nanoparticles are metals. In some embodiments, nanoparticles are ceramics. In some embodiments, nanoparticles are liposomes. Those skilled in the art can select and prepare suitable nanoparticles. In some embodiments, suitable nanoparticles are less than 1000nm in at least one direction. In some embodiments, nanoparticles are less than about 100nm in at least one direction.

[0174] In some embodiments, nanoparticles are particles with a diameter of less than about 1000nm. In some embodiments, nanoparticles are particles with a diameter of less than about 900nm. In some embodiments, nanoparticles are particles with a diameter of less than about 800nm. In some embodiments, nanoparticles are particles with a diameter of less than about 700nm. In some embodiments, nanoparticles are particles with a diameter of less than about 600nm. In some embodiments, nanoparticles are particles with a diameter of less than about 500nm. In some embodiments, nanoparticles are particles with a diameter of less than about 400nm. In some embodiments, nanoparticles are particles with a diameter of less than about 300nm. In some embodiments, nanoparticles are particles with a diameter of less than about 200nm. In some embodiments, nanoparticles are particles with a diameter of less than about 100nm.

[0175] In some embodiments, the size of the nanoparticles ranges from about 1 nm to about 1,000 nm. In some embodiments, the size of the nanoparticles ranges from about 1 nm to about 10 nm, about 1 nm to about 50 nm, about 1 nm to about 100 nm, about 1 nm to about 200 nm, about 1 nm to about 300 nm, about 1 nm to about 500 nm, about 1 nm to about 600 nm, about 1 nm to about 700 nm, about 1 nm to about 800 nm, about 1 nm to about 900 nm, about 1 nm to about 1,000 nm, about 10 nm to about 50 nm, about 10 nm to about 100 nm, about 10 nm to about 200 nm, about 10 nm to about 300 nm, about 10 ...0 nm to about 600 nm, about 1 0nm to about 700nm, about 10nm to about 800nm, about 10nm to about 900nm, about 10nm to about 1,000nm, about 50nm to about 100nm, about 50nm to about 200nm, about 50nm to about 300nm, about 50nm to about 500nm, about 50nm to about 600nm, about 50nm to about 700nm, about 50nm to about 800nm, about 50nm to about 900nm, about 50nm to about 1,000nm, about 100nm to about 200nm, about 100nm to about 300nm, about 100nm to about 500nm, about 50nm to about 600nm, about 10 0nm to about 700nm, about 100nm to about 800nm, about 100nm to about 900nm, about 100nm to about 1,000nm, about 200nm to about 300nm, about 200nm to about 500nm, about 200nm to about 600nm, about 200nm to about 700nm, about 200nm to about 800nm, about 200nm to about 900nm, about 200nm to about 1,000nm, about 300nm to about 500nm, about 300nm to about 600nm, about 300nm to about 700nm, about 300nm to about 800nm, about 300nm to about 900nm, about 300nm to about 1,000nm, about 300nm to about 500nm, about 300nm to about 600nm, about 300nm to about 700nm, about 300nm to about 800nm, about 300nm to about 900nm, about 300nm to about In some embodiments, the present invention relates to a nanostructured carbon foam having a carbon foam and a nanostructured carbon foam. The nanostructured carbon foam has a carbon foam and a nanostructured carbon foam. In some embodiments, the nanostructured carbon foam has a carbon foam and a nanostructured carbon foam.In some embodiments, the size range of nanoparticles is about 1nm, about 10nm, about 50nm, about 100nm, about 200nm, about 300nm, about 500nm, about 600nm, about 700nm, about 800nm, about 900nm or about 1,000nm. In some embodiments, the size range of nanoparticles is at least about 1nm, about 10nm, about 50nm, about 100nm, about 200nm, about 300nm, about 500nm, about 600nm, about 700nm, about 800nm ​​or about 900nm. In some embodiments, the size range of nanoparticles is at most about 10nm, about 50nm, about 100nm, about 200nm, about 300nm, about 500nm, about 600nm, about 700nm, about 800nm, about 900nm or about 1,000nm.

[0176] In some embodiments, a plurality of nanoparticles include at least about two nanoparticles. In some embodiments, a plurality of nanoparticles include at least about three nanoparticles. In some embodiments, a plurality of nanoparticles include at least about four nanoparticles. In some embodiments, a plurality of nanoparticles include at least about five nanoparticles. In some embodiments, a plurality of nanoparticles include at least about six nanoparticles. In some embodiments, a plurality of nanoparticles include at least about seven nanoparticles. In some embodiments, a plurality of nanoparticles include at least about eight nanoparticles. In some embodiments, a plurality of nanoparticles include at least about nine nanoparticles. In some embodiments, a plurality of nanoparticles include at least about ten nanoparticles.

[0177] In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by increasing throughput by several orders of magnitude without compromising identification rate. In some embodiments, the increase in throughput can be achieved by removing the chromatographic domain and using nanoparticles to reduce sample complexity, thereby maintaining the dynamic range of sample analysis per unit time at about five orders of magnitude (the linear response range of ESI without ionization suppression).

[0178]

[0013] Disclosed herein, in some embodiments, is a method for large-scale analysis of proteomes, wherein increased instrument resolution can improve identification rates in a multiplexed environment.

[0179] In some embodiments, disclosed herein is a method for large-scale analysis of a proteome, wherein nanoparticle fractionation can increase the identification rate to at least about two times that of a pure sample.

[0180] In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct injection of MS / MS or nLC-MS / MS, at least about 300,000 samples per instrument per year. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct injection of MS / MS or nLC-MS / MS, at least about 250,000 samples per instrument per year. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct injection of MS / MS or nLC-MS / MS, at least about 200,000 samples per instrument per year. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct injection of MS / MS or nLC-MS / MS, at least about 150,000 samples per instrument per year. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct injection of MS / MS or nLC-MS / MS, at least about 100,000 samples per instrument per year. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct injection MS / MS or nLC-MS / MS, at least about 50,000 samples per instrument per year. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct injection MS / MS or nLC-MS / MS, at least about 10,000 samples per instrument per year. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct injection MS / MS or nLC-MS / MS, at least about 5,000 samples per instrument per year. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct injection MS / MS or nLC-MS / MS, at least about 1,000 samples per instrument per year.

[0181] In some embodiments, disclosed herein is a method comprising contacting a plurality of biomolecules with a surface to adsorb a plurality of biomolecules on a surface. In some embodiments, disclosed herein is a method comprising contacting a plurality of biomolecules with a plurality of surfaces to adsorb a plurality of biomolecules on a plurality of surfaces. In some embodiments, the method comprises performing mass spectrometry on a plurality of biomolecules to generate a mass spectrum. In some embodiments, mass spectrometry is performed without chromatographic separation. In some embodiments, mass spectrometry is performed with direct injection. In some embodiments, mass spectrometry is performed using chromatographic separation with a fast gradient length. In some embodiments, the gradient length is at least 30, 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 minutes. In some embodiments, the gradient length is at most 30, 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 minutes. In some embodiments, the gradient length is at least 30, 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 minutes for each surface. In some embodiments, the gradient length is at most 30, 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, or 1 minute per surface.

[0182] In some embodiments, disclosed herein is a method for analyzing a proteome on a large scale at a sampling rate of about 100% by direct injection of MS / MS or nLC-MS / MS. In some embodiments, disclosed herein is a method for analyzing a proteome on a large scale at a sampling rate of about 95% by direct injection of MS / MS or nLC-MS / MS. In some embodiments, disclosed herein is a method for analyzing a proteome on a large scale at a sampling rate of about 90% by direct injection of MS / MS or nLC-MS / MS. In some embodiments, disclosed herein is a method for analyzing a proteome on a large scale at a sampling rate of about 85% by direct injection of MS / MS or nLC-MS / MS. In some embodiments, disclosed herein is a method for analyzing a proteome on a large scale at a sampling rate of about 80% by direct injection of MS / MS or nLC-MS / MS. In some embodiments, disclosed herein is a method for analyzing a proteome on a large scale at a sampling rate of about 75% by direct injection of MS / MS or nLC-MS / MS. In some embodiments, disclosed herein is a method for analyzing a proteome on a large scale at a sampling rate of about 70% by direct injection of MS / MS or nLC-MS / MS. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct infusion MS / MS or nLC-MS / MS at a sampling rate of about 65%. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by direct infusion MS / MS or nLC-MS / MS at a sampling rate of about 60%. In some embodiments, the sampling rate refers to the ratio at which no detectable peptides are missed.

[0183] In some embodiments, disclosed herein is a method for large-scale analysis of proteomes in the absence of chromatographic separation and by using an MS detector at a scan rate of about 40 Hz. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes in the absence of chromatographic separation. In some embodiments, disclosed herein is a method for large-scale analysis of proteomes by using an MS detector at a scan rate of about 50 Hz. In some embodiments, the scan rate of the MS detector is about 45 Hz. In some embodiments, the scan rate of the MS detector is about 40 Hz. In some embodiments, the scan rate of the MS detector is about 35 Hz. In some embodiments, the scan rate of the MS detector is about 30 Hz.

[0184] In some embodiments, the scan rate of the MS detector ranges from about 20 Hz to about 60 Hz. In some embodiments, the scan rate of the MS detector ranges from about 20 Hz to about 25 Hz, about 20 Hz to about 30 Hz, about 20 Hz to about 35 Hz, about 20 Hz to about 40 Hz, about 20 Hz to about 45 Hz, about 20 Hz to about 50 Hz, about 20 Hz to about 55 Hz, about 20 Hz to about 60 Hz, about 25 Hz to about 30 Hz, about 25 Hz to about 35 Hz, about 25 Hz to about 40 Hz, about 25 Hz to about 45 Hz, about 25 Hz to about 50 Hz, about 25 Hz to about 55 Hz, about 25 Hz to about 60 Hz, about 30 Hz to about 35 Hz, about 30 Hz to about 40 Hz, about In some embodiments, the scan rate range of the MS detector is about 20 Hz, about 25 Hz, about 30 Hz, about 35 Hz, about 40 Hz, about 45 Hz, about 50 Hz, about 35 Hz to about 55 Hz, about 35 Hz to about 60 Hz, about 40 Hz to about 45 Hz, about 40 Hz to about 50 Hz, about 40 Hz to about 55 Hz, about 40 Hz to about 60 Hz, about 45 Hz to about 50 Hz, about 45 Hz to about 55 Hz, about 45 Hz to about 60 Hz, about 50 Hz to about 55 Hz, about 50 Hz to about 60 Hz, or about 55 Hz to about 60 Hz. In some embodiments, the scan rate range of the MS detector is about 20 Hz, about 25 Hz, about 30 Hz, about 35 Hz, about 40 Hz, about 45 Hz, about 50 Hz, about 55 Hz, or about 60 Hz. In some embodiments, the scan rate range of the MS detector is at least about 20 Hz, about 25 Hz, about 30 Hz, about 35 Hz, about 40 Hz, about 45 Hz, about 50 Hz, or about 55 Hz. In some embodiments, the scan rate range of the MS detector is at most about 25 Hz, about 30 Hz, about 35 Hz, about 40 Hz, about 45 Hz, about 50 Hz, about 55 Hz, or about 60 Hz.

[0185]

[0013] Disclosed herein, in some embodiments, is a method of analyzing a proteome by using a spectral demultiplexing algorithm.

[0186] In some embodiments, machine learning algorithms can be deployed to determine common features of proteins over different concentration ranges. In some embodiments, for example, each of the three nanoparticles only needs to resolve three orders of magnitude of dynamic range, which will be within the linear response range of ESI without ionization suppression. In some embodiments, if a robust "concentration-dependent" nanoparticle is designed, it may only take 1 minute of MS time to inject each sample. The reasons are as follows: (1) The quadrupole transmission mass range is 400-1600, and with a 2 Dalton window, it can take less than 1 minute ((1200 / 2) / 40x 3) = 45 seconds per injection (or 2 min per sample) at 40 Hz scanning and 3 independent collision energies; (2) Even a 2 Dalton window can contain multiplexed spectra, and they can be demultiplexed by using linear algebra techniques (such as matrix-based multivariate regression, convex optimization, or LU decomposition). Therefore, in some embodiments, about 80% of the capacity per instrument can give more than 200,000 samples per instrument per year at the theoretical upper limit. In some embodiments, a tool such as Prosit can be used to predict the spectral library.

[0187] In some embodiments, disclosed herein is a method for identifying a protein, comprising: (1) performing deep learning for enriching a dynamic range of three or more levels; (2) performing three or more intensity quartile injections of enriched nanoparticles (e.g., a quadrupole transmission mass range of 400-1600, with a 2 Dalton window, at a 40 Hz scan rate and at 3 independent collision energies, will take less than 1 min (1200 / 2) / 403) = 45 seconds per injection = approximately 2 minutes per sample); (3) establishing a library matrix binned at 2 Da windows; and (4) applying LU decomposition / window for demultiplexing; (5) reporting protein identification results ( Figure 1 ).

[0188] In some embodiments, demultiplexing can be achieved by solving a linear system of equations, where a matrix ( Figure 1 ). For example, if the precursor bins 400-402 contain 1000 different theoretical spectra, the matrix may have 1000 columns and N rows (depending on the desired m / z resolution). The matrix form of least squares can solve systems where an exact solution is not available. In some embodiments, LU decomposition or convex optimization using non-negative constraints may also be used. In some embodiments, Figure 2 In the example, the experimental spectra are multiplexed in a 1:1 ratio (black / blue). Solving this example yields two coefficients where 2 / 3 of the spectra in the library are detected.

[0189] In some embodiments, the number of proteins identified can be determined using Alphapept's "improved" protein inference module, such as Figure 6 shown.

[0190] Some embodiments disclosed herein are systems and methods for performing a method comprising treating a biological sample using protein corona formation and analyzing proteins in the protein corona using direct injection mass spectrometry that does not include chromatographic separation. Methods and systems for performing protein corona formation that can be used in the method are disclosed in U.S. Patent Application No. 17 / 216,520 and U.S. Patent Application No. 17 / 216,523, both of which are incorporated herein by reference in their entirety. In some embodiments, protein corona formation occurs on a plurality of different surfaces (e.g., particles, such as nanoparticles) having different physicochemical properties, thereby generating different protein coronas, and the different protein coronas are analyzed separately using direct injection mass spectrometry. In some embodiments, direct injection mass spectrometry is performed using electrospray injection followed by ion mobility fractionation. In some embodiments, the electrospray injection of each analyzed protein corona is performed for less than 5 minutes or less than 3 minutes. In some embodiments, the mass spectrometry is tandem mass spectrometry. In some embodiments, the method further comprises analyzing data from the direct injection mass spectrometry to identify proteins in the protein corona. In some embodiments, the analysis includes demultiplexing the data using linear algebra techniques such as matrix-based multivariate regression, convex optimization, or LU decomposition. In some embodiments, the demultiplexing is performed using a machine learning algorithm.

[0191] The method for incubating the composition is not particularly limited and can be any conditions sufficient to form a protein corona on one or more surfaces. Methods for forming a protein corona are disclosed in U.S. Patent No. 11,428,688, which is hereby incorporated by reference in its entirety. In some embodiments, the composition is incubated with the surface at a temperature of at least about 5, 10, 15, 20, 25, 30, 37, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, or 95°C. In some embodiments, the composition is incubated with the surface at a temperature of up to about 5, 10, 15, 20, 25, 30, 37, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90, or 95°C. In some embodiments, the composition is incubated with the surface at a temperature of about 5°C to 95°C, 10°C to 90°C, 15°C to 85°C, 20°C to 80°C, 25°C to 75°C, 30°C to 70°C, 35°C to 65°C, 40°C to 60°C, 45°C to 55°C, 50°C to 95°C, or about 37°C. In some embodiments, the composition is incubated with the surface for at least about 5 minutes, 10 minutes, 15 minutes, 20 minutes, 25 minutes, 30 minutes, 35 minutes, 40 minutes, 45 minutes, 50 minutes, 55 minutes, or 1 hour. In some embodiments, the composition is incubated with the surface for at most 5 minutes, 10 minutes, 15 minutes, 20 minutes, 25 minutes, 30 minutes, 35 minutes, 40 minutes, 45 minutes, 50 minutes, 55 minutes, or 1 hour. In some embodiments, the composition is incubated with the surface for at least about 5 minutes to 1 hour, 10 minutes to 55 minutes, 15 minutes to 50 minutes, 20 minutes to 45 minutes, 25 minutes to 40 minutes, or 30 minutes to 35 minutes. In some embodiments, the composition is incubated at a temperature of at least 20° C. for at least 15 minutes.

[0192] Biological samples

[0193] In some cases, the biological sample can contain cells or be acellular. In some cases, the biological sample can include a biological fluid, such as blood, serum, plasma, urine, or cerebrospinal fluid (CSF). In some cases, the biological fluid can be a fluidized solid, such as a tissue homogenate, or a fluid extracted from the biological sample. The biological sample can be, for example, a tissue sample or a fine needle aspiration (FNA) sample. The biological sample can be a cell culture sample. For example, the biological fluid can be a fluidized cell culture extract. In some cases, the biological sample can be obtained from an object. In some cases, the object can be human or non-human. In some cases, the object can be a plant, a fungus, or an archaea. In some cases, the biological sample can include multiple proteins or proteome data, which can be analyzed after the protein is adsorbed or bound to one or more surfaces of various sensor element (e.g., particle) types in the set and then digested The protein corona is analyzed.

[0194] In some cases, the biological sample may include plasma, serum, urine, cerebrospinal fluid, synovial fluid, tears, saliva, whole blood, milk, nipple aspirate, ductal lavage, vaginal fluid, nasal fluid, ear fluid, gastric juice, pancreatic juice, trabecular fluid, lung lavage, sweat, gingival sulcus fluid, semen, prostatic fluid, sputum, feces, bronchial lavage, liquid from swab, bronchial aspirate, fluidized solid, fine needle aspiration sample, tissue homogenate, lymph fluid, cell culture sample, or any combination thereof. In some cases, the biological sample may include multiple biological samples (e.g., pooled plasma from multiple subjects, or multiple tissue samples from a single subject). In some cases, the biological sample may include a single type of biological fluid or biological material from a single source.

[0195] In some cases, biological sample can be diluted or pre-treated. In some cases, biological sample can be exhausted before or after contacting with surface disclosed herein (for example, biological sample comprises serum). In some cases, biological sample can be physically (for example, homogenized or ultrasonicated) or chemically treated before or after contacting with surface disclosed herein. In some cases, biological sample can be diluted before or after contacting with surface disclosed herein. In some cases, dilution medium can include buffer or salt, or be purified water (for example, distilled water). In some cases, biological sample can be provided in multiple partitions, wherein each partition can experience different degrees of dilution. In some cases, biological sample can comprise experience at least about 1.1 times, 1.2 times, 1.3 times, 1.4 times, 1.5 times, 2 times, 3 times, 4 times, 5 times, 6 times, 8 times, 10 times, 12 times, 15 times, 20 times, 30 times, 40 times, 50 times, 75 times, 100 times, 200 times, 500 times or 1000 times dilution. In some cases, the biological sample can include an experience of up to about 1.1 times, 1.2 times, 1.3 times, 1.4 times, 1.5 times, 2 times, 3 times, 4 times, 5 times, 6 times, 8 times, 10 times, 12 times, 15 times, 20 times, 30 times, 40 times, 50 times, 75 times, 100 times, 200 times, 500 times or 1000 times dilution. In some cases, the biological sample can include an experience of about 1.1 times to 1000 times, 1.2 times to 500 times, 1.3 times to 200 times, 1.4 times to 100 times, 1.5 times to 75 times, 2 times to 50 times, 3 times to 40 times, 4 times to 30 times, 5 times to 20 times, 6 times to 15 times, 8 times to 12 times or 10 times to 1000 times dilution. In some cases, the biological sample can be diluted with a buffer that modifies the pH of the biological sample. In some cases, the pH can be modified to at least about 2, 3, 4, 5, 6, 7, 8, 9, 10. In some cases, the pH can be modified to at most about 2, 3, 4, 5, 6, 7, 8, 9, 10. In some cases, the pH can be modified to about 2 to 10, 3 to 9, 4 to 8, 5 to 7, 6 to 10. In some cases, the pH can be modified to 9-10. In some cases, the pH can be modified by diluting with pH 9.5 Tris buffer. In some cases, the biological sample can be divided into several parts, and each part can be adjusted to a different pH before being processed using the methods disclosed herein.

[0196] In some cases, a biological sample can include a plurality of biomolecules. In some cases, a plurality of biomolecules can include polyamino acids. In some cases, polyamino acids include peptides, proteins, or combinations thereof. In some cases, a plurality of biomolecules can include nucleic acids, carbohydrates, polyamino acids, or any combination thereof. A biological sample can include members of any class of biomolecules, where "class" can refer to any named class that defines a group of biomolecules (e.g., proteins, nucleic acids, carbohydrates) that have common characteristics.

[0197] Proteomic analysis

[0198] As used herein, "proteomic analysis", "protein analysis", etc. may refer to any system or method for analyzing proteins (including glycoproteins) in a sample, including the systems and methods disclosed herein in a sample. The systems and methods disclosed herein are used for assays using one or more surfaces. In some cases, the surface may include the surface of a high surface area material, such as a nanoparticle, a particle, a microparticle, or a porous material. As used herein, "surface" may refer to a surface for assaying polyamino acids. When the composition, physical properties, or use thereof of the particles are described herein, it is understood that, in some cases, the surface of the particles may include the same composition, the same physical properties, or the same use thereof. Similarly, when the surface composition, physical properties, or use thereof are described herein, it is understood that the particles may include a surface to include the same composition, the same physical properties, or the same use thereof.

[0199] The materials of the particles and surfaces can include metals, polymers, magnetic materials and lipids. In some cases, the magnetic particles can be iron oxide particles. Examples of metal materials include any one or any combination of the following: gold, silver, copper, nickel, cobalt, palladium, platinum, iridium, osmium, rhodium, ruthenium, rhenium, vanadium, chromium, manganese, niobium, molybdenum, tungsten, tantalum, iron, cadmium or any alloy thereof. In some cases, the particles disclosed herein can be magnetic particles, such as superparamagnetic iron oxide nanoparticles (SPION). In some cases, the magnetic particles can be ferromagnetic particles, ferrimagnetic particles, paramagnetic particles, superparamagnetic particles or any combination thereof (for example, particles can include ferromagnetic materials and ferrimagnetic materials). In some cases, the surface can be configured to selectively adsorb extracellular vesicles from biological samples. For example, the surface can be ammonium-functionalized magnetic particles, which can adsorb extracellular vesicles at least in part due to electrostatic interactions. In some cases, the surface can include polyethyleneimine functionalized with ammonium. As another example, the surface can include hydrophobic groups (eg, aromatic groups) and hydrophilic groups (eg, polyethylene oxide groups) distributed on the surface such that extracellular vesicles are selectively adsorbed.

[0200] The present disclosure describes a set of particles or surfaces. In some cases, the set can contain more than one different surface type. The sets described herein can vary in the number of surface types in a single set and the diversity of surface types. For example, the surface in the set can vary according to size, polydispersity, shape and morphology, surface charge, surface chemistry and functionalization, and substrate material. In some cases, the set can be incubated with a sample of a polyamino acid, polyamino acid concentration, nucleic acid, nucleic acid concentration, or any combination thereof to be analyzed. In some cases, the polyamino acid in the sample is adsorbed onto different surfaces to form one or more biomolecule adsorption layers. The identity of the biomolecules in the one or more adsorption layers and their concentrations can depend on the physical properties of the different surfaces and the physical properties of the biomolecules. Therefore, each surface type in the set can have different adsorbed biomolecules due to the adsorption of different biomolecule sets, different concentrations of specific biomolecules, or combinations thereof. Each surface type in the set can have mutually exclusive adsorbed biomolecules, or can have overlapping adsorbed biomolecules.

[0201] In some cases, the panels disclosed herein can be used to identify the number of different biomolecules disclosed herein within a wide dynamic range of a given biological sample. For example, the panel can enrich a subset of biomolecules in a sample that can be identified within a wide dynamic range of biomolecules present in a sample (e.g., a plasma sample). In some cases, the enrichment can be selective—for example, biomolecules in a subset can be enriched, but biomolecules outside the subset may not be enriched and / or depleted. In some cases, the subset can contain proteins with different post-translational modifications. For example, a first particle type in a particle panel can enrich for a protein or protein group with a first post-translational modification, a second particle type in a particle panel can enrich for the same protein or the same protein group with a second post-translational modification, and a third particle type in a particle panel can enrich for the same protein or the same protein group lacking a post-translational modification. In some cases, a panel comprising any number of different particle types disclosed herein enriches and identifies a single protein or protein group by binding to different domains, sequences, or epitopes of the protein or protein group. For example, a first particle type in a particle assembly can enrich a protein or a group of proteins by binding to a first domain of the protein or group of proteins, and a second particle type in a particle assembly can enrich the same protein or the same group of proteins by binding to a second domain of the protein or group of proteins. In some cases, an assembly comprising any number of different particle types disclosed herein can enrich and identify biomolecules over a dynamic range of at least about 5, 6, 7, 8, 9, 10, 15, or 20 orders of magnitude. In some cases, an assembly comprising any number of different particle types disclosed herein can enrich and identify biomolecules over a dynamic range of up to about 5, 6, 7, 8, 9, 10, 15, or 20 orders of magnitude. In some cases, an assembly comprising any number of different particle types disclosed herein can enrich and identify biomolecules over a dynamic range of about 5 to 20, 6 to 15, 7 to 10, or 8 to 9 orders of magnitude.

[0202] A panel may have more than one surface type. Increasing the number of surface types in a panel can be a way to increase the number of proteins that can be identified in a given sample.

[0203] The particle or surface may include a polymer. The polymer may constitute a core material (e.g., the core of the particle may include a particle), a layer (e.g., the particle may include a polymer layer between its core and its shell), a shell material (e.g., the surface of the particle may be coated with a polymer) or any combination thereof. Examples of polymers include any one or any combination of polyethylene, polycarbonate, polyanhydride, polyhydroxy acid, polypropylfumarate, polycaprolactone, polyamide, polyacetal, polyether, polyester, poly(orthoester), polycyanoacrylate, polyvinyl alcohol, polyurethane, polyphosphazene, polyacrylate, polymethacrylate, polycyanoacrylate, polyurea, polystyrene or polyamine, polyalkylene glycol (e.g., polyethylene glycol (PEG)), polyester (e.g., poly(lactide-co-glycolide) (PLGA), polylactic acid or polycaprolactone) or a copolymer of two or more polymers (such as a copolymer of polyalkylene glycol (e.g., PEG) and polyester (e.g., PLGA)). The polymer may include crosslinking. The various polymers in the particle may be phase separated, or may include a degree of phase separation.

[0204] Examples of lipids that can be used to form particles or surfaces of the present disclosure include cationic, anionic, and neutrally charged lipids. For example, the particles and / or surfaces can be made of any one or any combination of the following: dioleoylphosphatidylglycerol (DOPG), diacylphosphatidylcholine, diacylphosphatidylethanolamine, ceramide, sphingomyelin, cephalin, cholesterol, cerebrosides and diacylglycerol, dioleoylphosphatidylcholine (DOPC), dimyristoylphosphatidylcholine (DMPC) and dioleoylphosphatidylserine (DOPS), phosphatidylglycerol, cardiolipin, diacylphosphatidylserine, diacylphosphatidic acid, N-dodecylphosphatidylethanolamine, N-succinylphosphatidylethanolamine, N-glutarylphosphatidylethanolamine, lysylphosphatidylglycerol, palmitoyloleoylphosphatidylglycerol (POPG), lecithin, lysolecithin, phosphatidylethanolamine, lysophatidylethanolamine, dioleoylphosphatidylethanolamine (DOPE), dipalmitoylphosphatidylethanolamine (DPPE), dimyristoylphosphoethanolamine (DMPE), distearoyl-phosphatidyl-ethanolamine (DSPE), palmitoyloleoyl-phosphatidylethanolamine (POPE), palmitoyloleoylphosphatidylcholine (POPC), egg phosphatidylcholine (EPC), distearoylphosphatidylcholine (DSPC), dioleoylphosphatidylcholine (DOPC), dipalmitoylphosphatidylcholine (DPPC), dioleoylphosphatidylglycerol (DOPG), dipalmitoylphosphatidylglycerol (DPPG), palmitoyloleoylphosphatidylglycerol (POPG), 16-O-monomethyl PE, 16-O-dimethyl PE, 18-1-trans PE, palmitoyloleoyl-phosphatidylethanolamine (POPE), 1-stearoyl-2-oleoyl-phosphatidylethanolamine (SOPE), phosphatidylserine, phosphatidylinositol, sphingomyelin, cephalin, cardiolipin, phosphatidic acid, cerebroside, dicetyl phosphate, cholesterol, and any combination thereof.

[0205] Particle sets can include combinations of particles with silica and polymer surfaces. For example, particle sets can include particles coated with an outer layer of silica and particles coated with an outer layer of poly(dimethylaminopropylmethacrylamide) (PDMAPMA). Particle sets consistent with the present disclosure can also include two or more particles selected from the following: silica-coated particles, N-(3-trimethoxysilylpropyl)diethylenetriamine-coated particles, PDMAPMA-coated particles, carboxyl-functionalized polyacrylic acid-coated particles, amino-surface-functionalized particles, polystyrene carboxyl-functionalized particles, and dextran-coated particles. Particle sets consistent with the present disclosure may also include two or more particles selected from the group consisting of surfactant-free carboxylate functionalized particles, carboxyl functionalized polystyrene particles, silica coated particles, silica particles, dextran coated particles, oleic acid coated particles, boronated nanopowder coated particles, PDMAPMA coated particles, poly(glycidyl methacrylate-benzylamine) coated particles, and poly(N-[3-(dimethylamino)propyl]methacrylamide-co-[2-(methacryloyloxy)ethyl]dimethyl-(3-sulfopropyl)ammonium hydroxide (P(DMAPMA-co-SBMA)) coated particles. Particles. Particle sets consistent with the present disclosure may include silica-coated particles, N-(3-trimethoxysilylpropyl)diethylenetriamine-coated particles, poly(N-(3-(dimethylamino)propyl)methacrylamide)(PDMAPMA)-coated particles, phosphate-sugar functionalized polystyrene particles, amine-functionalized polystyrene particles, polystyrene carboxyl-functionalized particles, ubiquitin-functionalized polystyrene particles, dextran-coated particles, or any combination thereof. In some cases, the particle set may include silica-coated particles, amine-functionalized particles, amine-functionalized polymer-coated particles, and carboxylate-functionalized particles.

[0206] Particle sets consistent with the present disclosure can include silica functionalized particles, amine functionalized particles, silicon alkoxide functionalized particles, carboxylate functionalized particles and benzyl or phenyl functionalized particles. Particle sets consistent with the present disclosure can include silica functionalized particles, amine functionalized particles, silicon alkoxide functionalized particles, polystyrene functionalized particles and sugar functionalized particles. Particle sets consistent with the present disclosure can include silica functionalized particles, N-(3-trimethoxysilylpropyl)diethylenetriamine functionalized particles, PDMAPMA functionalized particles, dextran functionalized particles and polystyrene carboxyl functionalized particles. Particle sets consistent with the present disclosure can include 5 kinds of particles, including silica functionalized particles, amine functionalized particles, silicon alkoxide functionalized particles.

[0207] Different surfaces or different particles of the present disclosure may differ in one or more physicochemical properties. One or more physicochemical properties are selected from: composition, size, surface charge, hydrophobicity, hydrophilicity, roughness, density surface functionalization, surface morphology, surface curvature, porosity, core material, shell material, shape and any combination thereof. Surface functionalization may include macromolecular functionalization, small molecule functionalization or any combination thereof. Small molecule functionalization may include aminopropyl functionalization, amine functionalization, boric acid functionalization, carboxylic acid functionalization, alkyl functionalization, N-succinimide ester functionalization, monosaccharide functionalization, phosphate sugar functionalization, sulfated sugar functionalization, ethylene glycol functionalization, streptavidin functionalization, methyl ether functionalization, trimethoxysilyl propyl functionalization, silica functionalization, triethoxypropylaminosilane functionalization, thiol functionalization, PCP functionalization, citrate functionalization, lipoic acid functionalization, ethyleneimine functionalization. The particle kit may comprise a plurality of particles having a plurality of small molecule functionalizations selected from the group consisting of silica functionalization, trimethoxysilylpropyl functionalization, dimethylaminopropyl functionalization, phosphate sugar functionalization, amine functionalization, and carboxyl functionalization.

[0208] Small molecule functionalization can include polar functional groups. Non-limiting examples of polar functional groups include carboxyl, hydroxyl, thiol, cyano, nitro, ammonium, imidazolium, sulfonium, pyridinium, pyrrolidinium, phosphonium or any combination thereof. In some embodiments, the functional group is an acidic functional group (e.g., sulfonic acid, carboxyl, etc.), a basic functional group, carbamoyl, hydroxyl, aldehyde, etc. In some cases, the polar functional group can include primary amine, secondary amine, tertiary amine, quaternary amine, cyclic secondary amine, primary amide, secondary amide, tertiary amide, imino, pyridyl, pyrimidinyl, pyrrolidinium, imidazolyl, guanidine, guanidine or any combination thereof.

[0209] Small molecule functionalization can include ions or ionizable functional groups. Non-limiting examples of ions or ionizable functional groups include ammonium groups, imidazolium groups, sulfonium groups, pyridinium groups, pyrrolidinium groups, phosphonium groups. Small molecule functionalization can include polymerizable functional groups. Non-limiting examples of polymerizable functional groups include vinyl and (methyl) acrylic acid groups. In some embodiments, the functional group is pyrrolidinyl acrylate, acrylic acid, methacrylic acid, acrylamide, 2-(dimethylamino)ethyl methacrylate, hydroxyethyl methacrylate, etc.

[0210] Surface functionalization can include charge. For example, particles can be functionalized to carry a net neutral surface charge, a net positive surface charge, a net negative surface charge, or a zwitterionic surface. Surface charge can be a determining factor in the type of biomolecules collected on the particles. Therefore, optimizing the particle assembly can include selecting particles with different surface charges, which can not only increase the number of different proteins collected on the particle assembly, but also increase the possibility of identifying the biological state of the sample. The particle assembly can include positively charged particles and negatively charged particles. The particle assembly can include positively charged particles and neutral particles. The particle assembly can include positively charged particles and zwitterionic particles. The particle assembly can include neutral particles and negatively charged particles. The particle assembly can include neutral particles and zwitterionic particles. The particle assembly can include negative particles and zwitterionic particles. The particle assembly can include positively charged particles, negatively charged particles, and neutral particles. The particle assembly can include positively charged particles, negatively charged particles, and zwitterionic particles. The particle assembly can include positively charged particles, neutral particles, and zwitterionic particles. The particle set can include negatively charged particles, neutral particles and zwitterionic particles. In some cases, the positively charged particles can have a zeta potential greater than about 0, 5, 10, 15, 20, 25, 50 or 100 mV. In some cases, the negatively charged particles can have a zeta potential less than about 0, -5, -10, -15, -20, -25, -50 or -100 mV. In some cases, the positively charged particles can have a zeta potential greater than about 0 to 100, 5 to 50, 10 to 25 or 15 to 20 mV.

[0211] The particle can include a single surface, such as a specific small molecule, or multiple surface functionalizations, such as multiple different small molecules. The surface functionalization can affect the composition of the biomolecule corona of the particle. Such surface functionalizations can include small molecule functionalizations or macromolecular functionalizations. The surface functionalization can be coupled to a particle material, such as a polymer, a metal, a metal oxide, an inorganic oxide (e.g., silica), or another surface functionalization.

[0212] Surface functionalization can include small molecule functionalization, macromolecular functionalization or two or more such functionalized combinations. In some cases, macromolecular functionalization can include biomacromolecules, such as proteins or polynucleotides (e.g., 100-mer DNA molecules). Macromolecular functionalization can include proteins, polynucleotides or polysaccharides, or can be comparable to the species of any of the above-mentioned types in size. In some cases, surface functionalization can include ionizable moieties. In some cases, surface functionalization can include at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14 pKa. In some cases, surface functionalization can include up to about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13 or 14 pKa. In some cases, surface functionalization can include about 1 to 14, 2 to 13, 3 to 12, 4 to 11, 5 to 10, 6 to 9 or 7 to 8 pKa. In some cases, small molecule functionalization can include small organic molecules, such as alcohols (e.g., octanol), amines, alkanes, alkenes, alkynes, heterocycles (e.g., piperidinyl), heteroaromatic groups, thiols, carboxylates, carbonyls, amides, esters, thioesters, carbonates, thiocarbonates, carbamates, thiocarbamates, ureas, thioureas, halogens, sulfates, phosphates, monosaccharides, disaccharides, lipids, or any combination thereof. For example, small molecule functionalization can include phosphate sugars, sugar acids, or sulfated sugars.

[0213] In some cases, macromolecular functionalization can include a specific attachment form to the particle. In some cases, the macromolecule can be tethered to the particle via a joint. In some cases, the joint can keep the macromolecule in a position close to the particle, thereby limiting its movement and redirection relative to the particle, or the macromolecule can be extended away from the particle. In some cases, the joint can be rigid (e.g., a polyolefin joint) or flexible (e.g., a nucleic acid joint). In some cases, the length of the joint can be at least about 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25 or 30nm. In some cases, the length of the joint can be at most about 0.5, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25 or 30nm. In some cases, the length of the joint can be about 0.5 to 30, 1 to 25, 2 to 20, 3 to 15, 4 to 9, 5 to 8 or 6 to 7nm. Therefore, the surface functionalization on the particle can protrude beyond the main crown associated with the particle. In some cases, surface functionalization can also be located below or within the biomolecule corona formed on the particle surface. In some cases, macromolecules can be tethered at specific locations, such as the C-terminus of a protein, or can be tethered at many possible sites. For example, a peptide can be covalently attached to a particle via any of its surface exposed lysine residues.

[0214] In some cases, the particles can be contacted with a biological sample (e.g., a biological fluid) to form a biomolecule corona. In some cases, the biomolecule corona can include at least two biomolecules that do not share a common binding motif. The particles and the biomolecule corona can be separated from the biological sample, for example, by centrifugation, magnetic separation, filtration, or gravity separation. A variety of separation techniques can be used to separate the particle type and the biomolecule corona from the biological sample. Non-limiting examples of separation techniques include magnetic separation, column-based separation, filtration, spin column-based separation, centrifugation, ultracentrifugation, density- or gradient-based centrifugation, gravity separation, or any combination thereof. The separated particles and biomolecule corona can be subjected to protein corona analysis. Protein corona analysis can include identifying one or more proteins in the biomolecule corona, for example, by mass spectrometry. In some cases, a single particle type can be contacted with a biological sample. In some cases, multiple particle types can be contacted with a biological sample. In some cases, multiple particle types can be combined and contacted with a biological sample in a single sample volume. In some cases, multiple particle types can be contacted with a biological sample in sequence and separated from the biological sample before contacting a subsequent particle type with the biological sample. In some cases, biomolecules adsorbed on particles can have a compressed (eg, smaller) dynamic range compared to a given original biological sample.

[0215] In some cases, the particles of the present disclosure can be used to serially interrogate a sample by incubating a first particle type with the sample to form a biomolecule corona on the first particle type, isolating the first particle type, incubating a second particle type with the sample to form a biomolecule corona on the second particle type, isolating the second particle type, and repeating the interrogation (by incubation with the sample) and isolation of any number of particle types. In some cases, the biomolecule corona on each particle type used to serially interrogate the sample can be analyzed by protein corona analysis. The supernatant can be analyzed for biomolecule content following serial interrogation with one or more particle types.

[0216] In some cases, the methods of the present disclosure can identify a large number of unique glycoproteins in a biological sample. In some cases, the method can identify at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100 or 200 unique glycoproteins. In some cases, the method can identify up to about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000 or 10000 unique glycoproteins. In some cases, the methods may identify about 1 to 10,000, 2 to 9,000, 3 to 8,000, 4 to 7,000, 5 to 6,000, 6 to 5,000, 7 to 4,000, 8 to 3,000, 9 to 2,000, 10 to 1,000, 20 to 900, 30 to 800, 40 to 700, 50 to 600, 60 to 500, 70 to 400, 80 to 300, 90 to 200, or 100 to 10,000 unique glycoproteins.

[0217] In some cases, the methods of the present disclosure can identify a large number of unique biomolecules (e.g., proteins) in a biological sample (e.g., a biological fluid). In some cases, the surfaces disclosed herein can be incubated with the biological sample to adsorb at least about 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 unique biomolecules. In some cases, the surfaces disclosed herein can be incubated with the biological sample to adsorb up to about 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 unique biomolecules. In some cases, the surfaces disclosed herein can be incubated with a biological sample to adsorb at least about 1000 to 10000, 2000 to 9000, 3000 to 8000, 4000 to 7000, or 5000 to 6000 unique biomolecules. In some cases, the surfaces disclosed herein can be incubated with a biological sample to adsorb at least about 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 unique biomolecule groups. In some cases, the surfaces disclosed herein can be incubated with a biological sample to adsorb up to about 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 unique biomolecule groups. In some cases, the surfaces disclosed herein can be incubated with a biological sample to adsorb about 1000 to 10000, 2000 to 9000, 3000 to 8000, 4000 to 7000, or 5000 to 6000 unique sets of biomolecules. In some cases, several different types of surfaces can be used alone or in combination to identify a large number of proteins in a particular biological sample. In other words, the surface can be multiplexed to bind and identify a large number of biomolecules in a biological sample.

[0218] In some cases, the methods of the present disclosure can identify a large number of unique protein variants (proteoforms) in a biological sample. In some cases, the methods can identify at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000 or 10000 unique protein variants. In some cases, the methods may identify up to about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 unique protein variants. In some cases, the methods may identify between about 1 to 10,000, 2 to 9,000, 3 to 8,000, 4 to 7,000, 5 to 6,000, 6 to 5,000, 7 to 4,000, 8 to 3,000, 9 to 2,000, 10 to 1,000, 20 to 900, 30 to 800, 40 to 700, 50 to 600, 60 to 500, 70 to 400, 80 to 300, 90 to 200, or 100 to 10,000 unique protein variants. In some cases, the surfaces disclosed herein can be incubated with a biological sample to adsorb at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 unique protein variants. In some cases, the surfaces disclosed herein can be incubated with a biological sample to adsorb up to about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 unique protein variants.In some cases, the surfaces disclosed herein can be incubated with a biological sample to adsorb about 1 to 10,000, 2 to 9,000, 3 to 8,000, 4 to 7,000, 5 to 6,000, 6 to 5,000, 7 to 4,000, 8 to 3,000, 9 to 2,000, 10 to 1,000, 20 to 900, 30 to 800, 40 to 700, 50 to 600, 60 to 500, 70 to 400, 80 to 300, 90 to 200, or 100 to 10,000 unique protein variants. In some cases, several different types of surfaces can be used alone or in combination to identify a large number of proteins in a particular biological sample. In other words, the surface can be multiplexed to bind and identify a large number of biomolecules in a biological sample.

[0219] In some cases, the panels disclosed herein can be used to identify a plurality of proteins, peptides, proteomes, or classes of proteins using a protein analysis workflow described herein (e.g., a protein corona analysis workflow). In some cases, the panels disclosed herein can be used to identify at least about 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 20000, 30000, 40000, 50000, 60000, 70000, 80000, 90000, or 100000 unique proteins. In some cases, the panels disclosed herein can be used to identify up to about 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 20000, 30000, 40000, 50000, 60000, 70000, 80000, 90000, or 100000 unique proteins. In some cases, the panels disclosed herein can be used to identify about 100 to 100,000, 200 to 90,000, 300 to 80,000, 400 to 70,000, 500 to 60,000, 600 to 50,000, 700 to 40,000, 800 to 30,000, 900 to 20,000, 1,000 to 10,000, 2,000 to 9,000, 3,000 to 8,000, 4,000 to 7,000, or 5,000 to 6,000 unique proteins. In some cases, the panels disclosed herein can be used to identify at least about 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 20000, 30000, 40000, 50000, 60000, 70000, 80000, 90000, or 100000 protein groups. In some cases, the panels disclosed herein can be used to identify up to about 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 20000, 30000, 40000, 50000, 60000, 70000, 80000, 90000, or 100000 protein groups.In some cases, the panels disclosed herein can be used to identify about 100 to 100,000, 200 to 90,000, 300 to 80,000, 400 to 70,000, 500 to 60,000, 600 to 50,000, 700 to 40,000, 800 to 30,000, 900 to 20,000, 1,000 to 10,000, 2,000 to 9,000, 3,000 to 8,000, 4,000 to 7,000, or 5,000 to 6,000 protein groups. In some cases, the panels disclosed herein can be used to identify at least about 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 20000, 30000, 40000, 50000, 60000, 70000, 80000, 90000, 100000, 200000, 300000, 400000, 500000, 600000, 700000, 800000, 900000, or 1000000 peptides. In some cases, the panels disclosed herein can be used to identify up to about 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10000, 20000, 30000, 40000, 50000, 60000, 70000, 80000, 90000, 100000, 200000, 300000, 400000, 500000, 600000, 700000, 800000, 900000, or 1000000 peptides. In some cases, the panels disclosed herein can be used to identify about 100 to 100,000, 200 to 90,000, 300 to 80,000, 400 to 70,000, 500 to 60,000, 600 to 50,000, 700 to 40,000, 800 to 30,000, 900 to 20,000, 1,000 to 10,000, 2,000 to 9,000, 3,000 to 8,000, 4,000 to 7,000, or 5,000 to 6,000 peptides.

[0220] In some cases, the peptide may be a tryptic peptide. In some cases, the peptide may be a semi-tryptic peptide. In some cases, protein analysis may include contacting the sample with different types of surfaces (e.g., particle sets), forming adsorbed biomolecule layers on different types of surfaces, and identifying biomolecules in the adsorbed biomolecule layers (e.g., by mass spectrometry). As disclosed herein, feature intensity may refer to the intensity of discrete peaks ("features") seen on a mass-to-charge ratio versus intensity graph in a mass spectrometry run of a sample. In some cases, these features may correspond to variable ionization fragments of peptides and / or proteins. In some cases, using the data analysis methods described herein, feature intensities may be classified into protein groups. In some cases, a protein group may refer to two or more proteins identified by a shared peptide sequence. In some cases, a protein group may refer to a protein identified using a unique identification sequence. For example, if in a sample, a peptide sequence shared between two proteins (protein 1: XYZZX and protein 2: XYZYZ) is determined, the protein group may be a "XYZ protein group" with two members (protein 1 and protein 2). In some cases, if the peptide sequence is unique to a single protein (protein 1), the proteome can be a "ZZX" proteome with one member (protein 1). In some cases, each proteome can be supported by more than one peptide sequence. In some cases, proteins detected or identified according to the present disclosure can refer to different proteins detected in a sample (e.g., different proteins relative to other proteins detected using mass spectrometry). In some cases, analysis of proteins present in different coronas corresponding to different surface types in the set generates a large number of feature intensities. In some cases, this number decreases as the feature intensities are processed into different peptides, further decreases as different peptides are processed into different proteins, and further decreases as peptides are grouped into proteomes (two or more proteins that share different peptide sequences).

[0221] In some cases, the methods disclosed herein include separating one or more particle types from one sample or more than one sample (e.g., biological samples or samples of continuous interrogation). Magnets can be used to quickly isolate or separate particle types from samples. In addition, multiple samples isolated in space can be processed in parallel. In some cases, the methods disclosed herein are used to isolate or separate particle types from unbound proteins in samples. In some cases, particle types can be separated in a variety of ways, including but not limited to magnetic separation, centrifugation, filtration, or gravity separation. In some cases, the particle set can be incubated with multiple spatially isolated samples, wherein each spatially isolated sample is located in a hole of a well plate (e.g., a 96-well plate). In some cases, the particles in each hole of the well plate can be separated from the unbound proteins present in the spatially isolated samples by placing the entire plate on a magnet. In some cases, this can simultaneously pull down the superparamagnetic particles in the particle set. In some cases, the supernatant in each sample can be removed to remove unbound proteins. In some cases, these steps (incubation, pull down) can be repeated to effectively wash the particles, thereby removing the residual background unbound proteins that may exist in the sample.

[0222] In some cases, the systems and methods disclosed herein can also elucidate interactions between protein classes or protein classes. In some cases, protein classes can include a collection of proteins that share a common function (e.g., amine oxidases or proteins involved in angiogenesis); proteins that share a common physiological, cellular or subcellular localization (e.g., peroxisomal proteins or membrane proteins); proteins that share a common cofactor (e.g., heme or flavoprotein); proteins that correspond to a specific biological state (e.g., hypoxia-related proteins); proteins containing specific structural motifs (e.g., cup folds); functionally related proteins (e.g., part of the same metabolic pathway); or proteins with post-translational modifications (e.g., ubiquitinated or citrullinated proteins). In some cases, a protein class may include at least about 2 proteins, 5 proteins, 10 proteins, 20 proteins, 40 proteins, 60 proteins, 80 proteins, 100 proteins, 150 proteins, 200 proteins or more. In some cases, a class of proteins may include up to about 2 proteins, 5 proteins, 10 proteins, 20 proteins, 40 proteins, 60 proteins, 80 proteins, 100 proteins, 150 proteins, 200 proteins, or more. In some cases, a class of proteins may include about 2 proteins to 200 proteins, 5 proteins to 150 proteins, 10 proteins to 100 proteins, 20 proteins to 80 proteins, 40 proteins to 60 proteins, or more.

[0223] In some cases, a variety of different analytical techniques can be used to identify, measure, and quantify proteomic data of biological samples. For example, proteomic data can be generated using SDS-PAGE or any gel-based separation technique. In some cases, immunoassays (such as ELISA) can also be used to identify, measure, and quantify peptides and proteins. In some cases, mass spectrometry, high performance liquid chromatography, LC-MS / MS, Edman degradation, immunoaffinity techniques, and other protein separation techniques can be used to identify, measure, and quantify proteomic data.

[0224] In some cases, determination can include protein particle collection, protein digestion and mass spectrometry (e.g., MS, LC-MS, LC-MS / MS). In some cases, digestion can include chemical digestion, such as by cyanogen bromide or 2-nitro-5-thiocyanatobenzoic acid (NTCB). In some cases, digestion can include enzymatic digestion, such as by trypsin or pepsin. In some cases, digestion can include enzymatic digestion by multiple proteases. In some cases, digestion can include a protease selected from the group consisting of trypsin, chymotrypsin, Glu C, Lys C, elastase, subtilisin, proteinase K, thrombin, factor X, Arg C, papain, Asp N, thermolysin, pepsin, aspartyl protease, cathepsin D, zinc metalloproteinase, glycoprotein endopeptidase, proline, aminopeptidase, isopentenyl protease, caspase, kex2 endoproteinase or any combination thereof. In some cases, digestion can cut peptides at random positions. In some cases, digestion can cut peptides at specific positions (e.g., at methionine) or sequences (e.g., glutamic acid-histidine-glutamic acid). In some cases, digestion can distinguish similar proteins. For example, a determination can be made that 8 different proteins are broken down into a single protein group with a first digestion method, and broken down into 8 independent proteins with different signals with a second digestion method. In some cases, digestion can generate an average peptide fragment length of about 8 to 15 amino acids. In some cases, digestion can generate an average peptide fragment length of about 12 to 18 amino acids. In some cases, digestion can generate an average peptide fragment length of about 15 to 25 amino acids. In some cases, digestion can generate an average peptide fragment length of about 20 to 30 amino acids. In some cases, digestion can generate an average peptide fragment length of about 30 to 50 amino acids.

[0225] In some cases, digestion can generate an average peptide fragment length of at least about 8, 10, 15, 20, 25, 30, 35, 40, 45, 50 amino acids. In some cases, digestion can generate an average peptide fragment length of at most about 8, 10, 15, 20, 25, 30, 35, 40, 45, 50 amino acids.

[0226] In some cases, the protein or peptide can be prepared for mass spectrometry. In some cases, the protein or peptide can be treated with an alkylating agent. For example, the protein or peptide can be treated with N-ethylmaleimide and iodoacetamide. In some cases, the protein or peptide can be treated with a reducing agent. For example, the protein or peptide is treated with dithiothreitol (DTT) or tris (2-carboxyethyl) phosphine (TCEP). In some cases, the protein or peptide is digested, alkylated and reduced before analysis. In some cases, the protein or peptide is digested, alkylated and reduced before using mass spectrometry analysis.

[0227] In some cases, determination can generate and analyze proteomic data quickly. In some cases, starting from the input biological sample (e.g., oral or nasal smear, plasma or tissue), the method of the present disclosure can generate and analyze proteomic data in less than about 1, 2, 3, 4, 5, 6, 7, 8, 12, 16, 20, 24 or 48 hours. In some cases, analysis may include identifying proteomic groups. In some cases, analysis may include identifying protein classes. In some cases, analysis may include quantifying the abundance of biomolecules, peptides, proteins, proteomes or protein classes. In some cases, analysis may include identifying the abundance ratio of two biomolecules, peptides, proteins, proteomes or protein classes. In some cases, analysis may include identifying biological states.

[0228] Examples of the particle types disclosed herein may be carboxylate (citrate) superparamagnetic iron oxide nanoparticles (SPIONs), phenol-formaldehyde coated SPIONs, silica coated SPIONs, polystyrene coated SPIONs, carboxylated poly(styrene-co-methacrylic acid) coated SPIONs, N-(3-trimethoxysilylpropyl)diethylenetriamine coated SPIONs, poly(N-(3-(dimethylamino)propyl)methacrylamide) (PDMAPMA) coated SPIONs, 1,2,4,5-pyromellitic acid coated SPIONs, poly(vinylbenzyltrimethylammonium chloride) (PVBTMAC) coated SPIONs, carboxylate, PAA coated SPIONs. ON, poly(oligo(ethylene glycol) methyl ether methacrylate) (POEGMA) coated SPION, carboxylate microparticles, polystyrene carboxyl functionalized particles, carboxylic acid coated particles, silica particles, carboxylic acid particles of about 150 nm in diameter, amino surface microparticles of about 0.4-0.6 μm in diameter, silica amino functionalized microparticles of about 0.1-0.39 μm in diameter, Jeffamine surface particles of about 0.1-0.39 μm in diameter, polystyrene microparticles of about 2.0-2.9 μm in diameter, silica particles, carboxylated particles with a pristine coating of about 50 nm in diameter, particles coated with a dextran-based coating of about 0.13 μm in diameter, or low acidity silica silanol coated particles. In some cases, the particles may lack functionalized specific binding moieties for specific binding on their surface. In some cases, the particles may lack functionalized proteins for specific binding on their surface. In some cases, the surface functionalized particles do not contain antibodies or T cell receptors, chimeric antigen receptors, receptor proteins, or variants or fragments thereof. In some cases, the ratio between surface area and mass can determine the properties of the particles. The particles disclosed herein can have a surface area of ​​3 to 30 cm 2 / mg, 5 to 50cm 2 / mg, 10 to 60cm 2 / mg, 15 to 70cm 2 / mg, 20 to 80cm 2 / mg, 30 to 100 cm 2 / mg, 35 to 120cm 2 / mg, 40 to 130cm 2 / mg, 45 to 150cm 2 / mg, 50 to 160cm 2 / mg, 60 to 180cm 2 / mg, 70 to 200cm 2 / mg, 80 to 220cm 2 / mg, 90 to 240cm 2 / mg, 100 to 270cm 2 / mg, 120 to 300cm 2 / mg, 200 to 500cm 2 / mg, 10 to 300cm 2 / mg, 1 to 3000cm 2 / mg, 20 to 150cm 2 / mg, 25 to 120cm 2 / mg or 40 to 85cm 2 / mg surface area to mass ratio. Small particles (e.g., 50 nm in diameter or less) can have significantly higher surface area to mass ratios, in part because diameter depends more on mass than on surface area. In some cases (e.g., for small particles), particles can have a surface area to mass ratio of 200 to 1000 cm 2 / mg, 500 to 2000cm 2 / mg, 1000 to 4000cm 2 / mg, 2000 to 8000cm 2 / mg or 4000 to 10000cm 2 / mg of surface area to mass ratio. In some cases (e.g., for large particles), the particles may have a surface area of ​​1 to 3 cm 2 / mg, 0.5 to 2cm 2 / mg, 0.25 to 1.5 cm 2 / mg or 0.1 to 1cm 2 The particle can include a plurality of physical properties. The physical properties of the particle can include composition, size, surface charge, hydrophobicity, hydrophilicity, amphiphilicity, surface functionality, surface morphology, surface curvature, porosity, core material, shell material, shape, zeta potential and any combination thereof. The particle can have a core-shell structure. In some cases, the core material can include metal, polymer, magnetic material, paramagnetic material, oxide and / or lipid. In some cases, the shell material can include metal, polymer, magnetic material, oxide and / or lipid.

[0229] In some cases, the particles can include nanoparticles. In some cases, the particles can include microparticles. In some cases, the first particle, the second particle, or both particles in the particle set are nanoparticles. In some cases, the first particle, the second particle, or both particles in the particle set are microparticles. In some cases, the first particle can be a nanoparticle, and the second particle can be a microparticle.

[0230] In some cases, the particles may comprise a diameter of at least about 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 nm. In some cases, the particles may comprise a diameter of at most about 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 nm. In some cases, the particles may comprise a diameter of about 10 to 1000, 20 to 900, 30 to 800, 40 to 700, 50 to 600, 60 to 500, 70 to 400, 80 to 300, 90 to 200, or 100 to 1000 nm. In some cases, the particles may comprise a diameter of at least about 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 μm. In some cases, the particles may comprise a diameter of at most about 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 μm. In some cases, the particles may comprise a diameter of about 10 to 1000, 20 to 900, 30 to 800, 40 to 700, 50 to 600, 60 to 500, 70 to 400, 80 to 300, 90 to 200, or 100 to 1000 μm.

[0231] In some cases, a first size of a first particle is at least about 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 times larger than a second size of a second particle. In some cases, a first dimension of a first particle is at most about 1.1, 1.2, 1.3, 1.4, 1.5, 1.6, 1.7, 1.8, 1.9, 2, 3, 4, 5, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 times larger than a second dimension of a second particle. In some cases, the first dimension of the first particle is about 1.1 to 1000, 1.2 to 900, 1.3 to 800, 1.4 to 700, 1.5 to 600, 1.6 to 500, 1.7 to 400, 1.8 to 300, 1.9 to 200, 2 to 100, 3 to 90, 4 to 80, 5 to 70, 10 to 60, 20 to 50, or 30 to 40 times the second dimension of the second particle. In some cases, the dimension of the first particle is within ±40% of the dimension of the second particle, the dimension of the first particle is within ±30% of the dimension of the second particle, the dimension of the first particle is within ±25% of the dimension of the second particle, the dimension of the first particle is within ±20% of the dimension of the second particle, the dimension of the first particle is within ±15% of the dimension of the second particle, or the dimension of the first particle is within ±10% of the dimension of the second particle. In some cases, the size of the first particle is within at least about ±10%, ±15%, ±20%, ±25%, ±30%, ±35%, ±40% of the size of the second particle. In some cases, the size of the first particle is within at most about ±10%, ±15%, ±20%, ±25%, ±30%, ±35%, ±40% of the size of the second particle. In some cases, the size of the first particle is within about ±10% to ±40%, ±15% to ±35%, ±20% to ±30%, ±25% to ±40% of the size of the second particle. In some cases, the first size is a first diameter and the second size is a second diameter. In some cases, the first size is a first average size and the second size is a second average size. In some cases, the first average size and the second average size are average sizes or median sizes.

[0232] In some cases, the particle set comprises at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 parts of the first particles and about 1 part of the second particles. In some cases, the particle set comprises at most about 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 parts of the first particles and about 1 part of the second particles. In some cases, the particle set comprises about 1 to 10, 2 to 9, 3 to 8, 4 to 7, 5 to 6 parts of the first particles and about 1 part of the second particles. In some cases, the particle set comprises about 15 parts of the first particles and about 6 parts of the second particles. In some cases, the part is a part by weight, a part by volume, or a part by surface area. In some cases, the part is a part by weight.

[0233] Nonspecific binding

[0234] The surface can bind biomolecules by variable selective adsorption (e.g., adsorption of a biomolecule or a group of biomolecules when the particle is in contact with a biological sample containing the biomolecule or the group of biomolecules, the adsorption having variable selectivity depending on factors including, for example, the physicochemical properties of the particle) or non-specific binding. Non-specific binding can refer to a class of binding interactions that exclude specific binding. Examples of specific binding can include protein-ligand binding interactions, antigen-antibody binding interactions, nucleic acid hybridization, or binding interactions between a template molecule and a target molecule, wherein the sequence or three-dimensional structure provided by the template molecule favors the binding of a target molecule containing a complementary sequence or a complementary three-dimensional structure, and disfavors the binding of non-target molecules that do not contain a complementary sequence or a complementary three-dimensional structure.

[0235] Nonspecific binding can comprise one or combination of various chemical and physical interactions and effects.Nonspecific binding can comprise electromagnetic force, such as electrostatic interaction, London dispersion, van der Waals interaction or dipole-dipole interaction (for example, between permanent dipole and induced dipole).Nonspecific binding can be mediated by covalent bond, such as disulfide bond.Nonspecific binding can be mediated by hydrogen bond.Nonspecific binding can comprise solvophobic effect (for example, hydrophobic effect), in which one object is repelled by solvent environment and is forced to reach the boundary of solvent, such as the surface of another object.Nonspecific binding can comprise entropy effect, such as in consumption power, or heat energy is raised to above critical solution temperature (for example, lower critical solution temperature).Nonspecific binding can comprise kinetic effect, in which one binding molecule can have faster binding kinetics than another binding molecule.

[0236] Non-specific binding can include multiple non-specific binding affinities for multiple targets (e.g., at least about 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, 10,000, 20,000, 30,000, 40,000, 50,000 different targets adsorbed to a single particle). Multiple targets can have similar non-specific binding affinities that are within about one, two, or three orders of magnitude (e.g., as measured by non-specific binding free energy, equilibrium constant, competitive adsorption, etc.). This can be contrasted with specific binding, which can involve a higher binding affinity for a given target molecule compared to a non-target molecule.

[0237] Biomolecules can be adsorbed onto a surface at various densities via non-specific binding. In some cases, a biomolecule or protein can be adsorbed onto a surface at a density of at least about 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 fg / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 pg / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 ng / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 μg / mm 2In some cases, the biomolecule or protein can be adsorbed at a density of at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 mg / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of up to about 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 fg / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of up to about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 pg / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of up to about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 ng / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of up to about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 μg / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of up to about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 mg / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of about 0.1 to 1000, 0.2 to 900, 0.3 to 800, 0.4 to 700, 0.5 to 600, 0.6 to 500, 0.7 to 400, 0.8 to 300, 0.9 to 200, 1 to 100, 2 to 90, 3 to 80, 4 to 70, 5 to 60, 6 to 50, 7 to 40, 8 to 30, 9 to 20, or 10 to 1000 fg / mm 2In some cases, the biomolecule or protein can be adsorbed at a density of about 0.1 to 1000, 0.2 to 900, 0.3 to 800, 0.4 to 700, 0.5 to 600, 0.6 to 500, 0.7 to 400, 0.8 to 300, 0.9 to 200, 1 to 100, 2 to 90, 3 to 80, 4 to 70, 5 to 60, 6 to 50, 7 to 40, 8 to 30, 9 to 20, or 10 to 1000 pg / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of about 0.1 to 1000, 0.2 to 900, 0.3 to 800, 0.4 to 700, 0.5 to 600, 0.6 to 500, 0.7 to 400, 0.8 to 300, 0.9 to 200, 1 to 100, 2 to 90, 3 to 80, 4 to 70, 5 to 60, 6 to 50, 7 to 40, 8 to 30, 9 to 20, or 10 to 1000 ng / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of about 0.1 to 1000, 0.2 to 900, 0.3 to 800, 0.4 to 700, 0.5 to 600, 0.6 to 500, 0.7 to 400, 0.8 to 300, 0.9 to 200, 1 to 100, 2 to 90, 3 to 80, 4 to 70, 5 to 60, 6 to 50, 7 to 40, 8 to 30, 9 to 20, or 10 to 1000 μg / mm 2 In some cases, the biomolecule or protein can be adsorbed at a density of about 0.1 to 1000, 0.2 to 900, 0.3 to 800, 0.4 to 700, 0.5 to 600, 0.6 to 500, 0.7 to 400, 0.8 to 300, 0.9 to 200, 1 to 100, 2 to 90, 3 to 80, 4 to 70, 5 to 60, 6 to 50, 7 to 40, 8 to 30, 9 to 20, or 10 to 1000 mg / mm 2 Density adsorption.

[0238] The adsorbed biomolecules can include various types of proteins. In some cases, the adsorbed proteins can include at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 types of proteins. In some cases, the adsorbed proteins may include up to about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9000, or 10000 types of proteins. In some cases, the adsorbed proteins may include about 1 to 10,000, 2 to 9,000, 3 to 8,000, 4 to 7,000, 5 to 6,000, 6 to 5,000, 7 to 4,000, 8 to 3,000, 9 to 2,000, 10 to 1,000, 20 to 900, 30 to 800, 40 to 700, 50 to 600, 60 to 500, 70 to 400, 80 to 300, 90 to 200, or 100 to 10,000 types of proteins.

[0239] In some cases, the concentration of the protein in the biological sample can comprise at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, or 30 orders of magnitude. In some cases, the concentration of the protein in the biological sample can comprise at most about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, or 30 orders of magnitude. In some cases, the concentration of the protein in the biological sample can comprise about 1 to 30, 2 to 25, 3 to 20, 4 to 15, 5 to 10, 6 to 9, or 7 to 8 orders of magnitude.

[0240] Classification using machine learning

[0241] In some cases, biomolecule identification using the methods disclosed herein can be processed using a machine learning algorithm. In some cases, the identification of biomolecules can include the identification of nucleic acids, variants thereof, proteins, variants thereof, and any combination thereof. In some cases, the machine learning algorithm can be an unsupervised or self-supervised learning algorithm. In some cases, the machine learning algorithm can be trained to learn the potential representation of biomolecule identification. In some cases, the machine learning algorithm can be a supervised learning algorithm. In some cases, the machine learning algorithm can be trained to learn to associate a given identification set with a value, which is associated with a predetermined task. For example, the predetermined task can include determining a disease state associated with a given identification set, wherein the value can indicate the probability that the disease state is present in an object associated with a given identification set.

[0242] In some cases, methods of determining a set of biomolecules associated with a disease or condition and / or disease state may include analyzing the biomolecule coronas of at least two samples. Such determination, analysis, or statistical classification may be performed by methods including, but not limited to, various supervised and unsupervised data analysis, machine learning, deep learning, and clustering methods, including hierarchical cluster analysis (HCA), principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), random forests, logistic regression, decision trees, support vector machines (SVM), k-nearest neighbors, naive Bayes, linear regression, polynomial regression, SVM for regression, K-means clustering, and hidden Markov models, among others. In other words, the biomolecules in the coronas of each sample are compared / analyzed with each other to determine statistically significant patterns that are common between the coronas, thereby determining a set of biomolecules associated with a disease or condition or disease state.

[0243] In some cases, a machine learning algorithm can be used to build a model that accurately assigns class labels to examples based on input features that describe the examples. In some cases, it can be advantageous to employ machine learning and / or deep learning methods with the methods described herein. For example, machine learning can be used to associate biomolecular coronas with various disease states (e.g., disease-free, precursors to disease, in the early or late stages of disease, etc.). For example, in some cases, one or more machine learning algorithms can be used in conjunction with the methods disclosed herein to analyze data detected and obtained by biomolecular coronas and sets of biomolecules derived therefrom. For example, machine learning can be combined with genomic and proteomic information obtained using the methods described herein to not only determine whether a subject has a precancerous stage, cancer, or does not have or has not developed cancer, but also to distinguish the type of cancer.

[0244] In some cases, machine learning algorithms can also be used to correlate results from protein corona analysis with results from nucleic acid sequencing analysis, and further correlate any trends or correlations between proteins and nucleic acids with biological states (e.g., disease state, healthy state, disease subtype, such as stage of disease is a cancer subtype).

[0245] In some cases, machine learning can be used to cluster proteins detected using multiple surfaces. In some cases, a surface set can be used to measure proteins from one or more biological samples. In some cases, the surface in the surface set can contain different physicochemical properties. In some cases, a clustering algorithm can be used to cluster proteins detected by the surface set. In some cases, the proteins detected by the surface set can be clustered based at least in part on the intensity of the detected protein signal, the particle chemistry, the protein structure and / or the functional group or any combination thereof.

[0246] The surface set can include any number of surfaces. In some cases, the surface set can include at least about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 surfaces. In some cases, the surface set can include at most about 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 200, 300, 400, 500, 600, 700, 800, 900, or 1000 surfaces.

[0247] The input of the machine learning algorithm can include various types of inputs. In some cases, the input can include a value representing the physicochemical properties of the surface for determining the biomolecule. The physicochemical properties of the particles can include various properties disclosed herein, including: charge, hydrophobicity, hydrophilicity, amphipathicity, coordination, reaction class, surface free energy, various functional groups / modifications (e.g., sugars, polymers, amines, amides, epoxies, crosslinkers, hydroxyls, aromatics or phosphate groups). In some cases, the input can include a value representing a parameter of a given determination. Parameters can include incubation conditions, including temperature, incubation time, pH, buffer type and any variable when performing the determination disclosed herein.

[0248] In some cases, a clustering algorithm may refer to a method of grouping samples in a data set by some similarity measure. In some cases, samples may be grouped in a set space, e.g., element "a" is in set "A". In some cases, samples may be grouped in a continuous space, e.g., element "a" is a point in Euclidean space that is "l" away from the centroid of the elements that make up cluster "A". In some cases, samples may be grouped in a graphical space, e.g., element "a" is highly connected to the elements that make up cluster "A". In some cases, clustering may refer to the principle of organizing multiple elements into groups in a mathematical space based on some similarity measure.

[0249] In some cases, clustering may include grouping any number of biomolecules in a data set by any quantitative measure of similarity. In some cases, clustering may include K-means clustering. In some cases, clustering may include hierarchical clustering. In some cases, clustering may include using a random forest model. In some cases, clustering may include a boosted tree model. In some cases, clustering may include using a support vector machine. In some cases, clustering may include calculating one or more N-1 dimensional surfaces in an N-dimensional space that partitions a data set into clusters. In some cases, clustering may include distribution-based clustering. In some cases, clustering may include fitting multiple prior distributions to data distributed in an N-dimensional space. In some cases, clustering may include using density-based clustering. In some cases, clustering may include using fuzzy clustering. In some cases, clustering may include calculating a probability value that a data point belongs to a cluster. In some cases, clustering may include using constraints. In some cases, clustering may include using supervised learning. In some embodiments, clustering may include using unsupervised learning.

[0250] In some cases, clustering may include grouping biomolecules based on similarity. In some cases, clustering may include grouping biomolecules based on quantitative similarity. In some cases, clustering may include grouping biomolecules based on one or more features of each protein. In some cases, clustering may include grouping biomolecules based on one or more tags of each protein. In some cases, clustering may include grouping biomolecules based on Euclidean coordinates in the numerical representation of biomolecules. In some cases, clustering may include grouping biomolecules based on protein structure groups or functional groups (e.g., protein structures, substructures or functional groups from protein databases such as Protein Data Bank or CATH Protein Structure Classification databases). In some cases, protein structure groups or functional groups may include protein primary structure, secondary structure, tertiary structure or quaternary structure. In some cases, protein structure groups or functional groups may be based at least in part on alpha helices, beta sheets, relative distributions of amino acids with different properties (e.g., aliphatic, aromatic, hydrophilic, acidic, alkaline, etc.), structural families (e.g., TIM barrels and beta barrel folds), protein domains (e.g., death effector domains). In some cases, protein structural or functional groups may be based at least in part on functional or spatial properties (eg, functional groups - immunoglobulin groups, cytokine groups, cytoskeletal biomolecule groups, etc.).

[0251] definition

[0252] As used herein, the term "biomolecule corona" generally refers to a plurality of different biomolecules bound to a surface. The term "protein corona" generally refers to proteins and optionally other plasma components that bind to a surface (e.g., nanoparticles) when in contact with a biological sample or biological system. As used herein, the term "protein corona" also encompasses soft and hard protein coronas, as in Milani et al., "Reversible versus Irreversible Binding of Transferring to Polystyrene Nanoparticles: Soft and Hard Corona" ACS NANO, 2012, 6(3), pp. 2532-2541; Mirshafiee et al., "Impact of protein pre-coating on the protein corona composition and nanoparticle cellular uptake" Biomaterials, Vol. 75, January 2016, pp. 295-304; Mahmoudi et al., "Emerging understanding of the protein corona at nano-bio interfaces" Nanotoday 11(6), December 2016, pp. 817-832; and Mahmoudi et al., "Protein-Nanoparticle Interactions: Opportunities and Challenges” Chem. Rev., 2011, 111 (9), pp. 5610-5637, the contents of which are incorporated herein by reference in their entirety. As described herein, the adsorption curve can show the accumulation of a strongly bound monolayer until the monolayer saturation point (at a geometrically defined protein to NP ratio), beyond which a second weakly bound layer is formed. Although the first layer is irreversibly bound (hard corona), the second layer (soft corona) can exhibit dynamic exchange. Proteins adsorbed with high affinity can form a "hard" corona, which includes tightly bound proteins that are not easily desorbed, and proteins adsorbed with low affinity can form a "soft" corona, which includes loosely bound proteins. Soft and hard coronas can also be characterized based on their exchange time. The hard corona can show a much larger exchange time, on the order of several hours. See, for example, M. Rahman et al., Protein-Nanoparticle Interactions, Spring Series in Biophysics 15, 2013, incorporated by reference in its entirety.

[0253] The use of absolute or sequential terms, such as “will,” “will not,” “should,” “should not,” “must,” “must not,” “first,” “initially,” “next,” “subsequently,” “before,” “after,” “last,” and “ultimately,” are not meant to limit the scope of the present embodiments disclosed herein, but are intended to be exemplary.

[0254] As used herein, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. In addition, if the terms "including," "having," "having," or variations thereof are used in the detailed description and / or claims, such terms are intended to be inclusive in a manner similar to the term "comprising."

[0255] As used herein, the phrases "at least one", "one or more", and "and / or" are open-ended expressions that are both conjunctions and separators in operation. For example, each of the expressions "at least one of A, B, and C", "at least one of A, B, or C", "one or more of A, B, and C", "one or more of A, B, or C", and "A, B, and / or C" means A alone, B alone, C alone, A and B together, A and C together, B and C together, or A, B, and C together.

[0256] As used herein, "or" may mean "and", "or", or "and / or", and may be used both exclusively and inclusively. For example, the term "A or B" may mean "A or B", "A but not B", "B but not A", and "A and B". In some cases, the context may determine the specific meaning.

[0257] Any systems, methods, software, and platforms described herein are modular. Therefore, terms such as "first" and "second" do not necessarily imply priority, order of importance, or order of action.

[0258] The term "about" when referring to a number or a numerical range means that the number or numerical range mentioned is an approximate value within experimental variability (or within statistical experimental error), and the number or numerical range can vary from, for example, 1% to 15% of the number or numerical range. In an example, the term "about" refers to ±10% of the number or value.

[0259] As used herein, the term "increase" or "improve" generally means to increase a statistically significant amount. In some aspects, the term "increase" or "improve" means to increase by at least 10% compared to a reference level, such as an increase of at least about 10%, at least about 20%, at least about 30%, at least about 40%, at least about 50%, at least about 60%, at least about 70%, at least about 80%, at least about 90% or up to and including 100% increase or any increase between 10-100% compared to a reference level. Other examples of "increase" include an increase to at least 2 times, at least 5 times, at least 10 times, at least 20 times, at least 50 times, at least 100 times, at least 1000 times or more compared to a reference level.

[0260] As used herein, the term "reduce" or "reduce" generally means to reduce a statistically significant amount. In some aspects, "reduce" or "reduce" means to reduce at least 10% compared to a reference level, for example, to reduce at least about 20%, or at least about 30%, or at least about 40%, or at least about 50%, or at least about 60%, or at least about 70%, or at least about 80%, or at least about 90%, or up to and including 100% reduction (for example, a level that does not exist or an undetectable level compared to a reference level), or any reduction between 10-100% compared to a reference level. In the context of a marker or symptom, these terms mean a statistically significant reduction of such levels. For example, reduction can be at least 10%, at least 20%, at least 30%, at least 40% or more, and is preferably reduced to an acceptable level, which is within the normal range of an individual not suffering from a given disease.

[0261] Although preferred embodiments of the present invention have been shown and described herein, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. The present invention is not intended to be limited by the specific examples provided in the specification. Although the present invention has been described with reference to the above description, the description and illustration of the embodiments herein are not intended to be interpreted in a limiting sense. Those skilled in the art will now think of many variations, changes and substitutions without departing from the present invention. In addition, it should be understood that all aspects of the present invention are not limited to the specific descriptions, configurations or relative proportions described herein, which depend on various conditions and variables. It should be understood that in practicing the present invention, various alternatives to the embodiments of the present invention described herein may be adopted. Therefore, the present invention should also cover any such alternatives, modifications, variations or equivalents. It is intended that the scope of the present invention is defined by the following claims, and methods and structures within the scope of these claims and their equivalents are thus covered.

[0262] Example

[0263] The following illustrative examples represent embodiments of the stimulation, systems, and methods described herein and are not meant to be limiting in any way.

[0264] Example 1. Direct Injection MS / MS Analysis of Four Extracted Proteomes

[0265] The four extracted protein groups ((1) KQTALVELVK (SEQ ID NO: 1); (2) YTCLPGYVR (SEQ ID NO: 2); (3) ESDTSYVSLK (SEQ ID NO: 3); and (4) DCHLAQVPSHTVVAR (SEQ ID NO: 4)) were analyzed by direct infusion MS / MS. Figure 3 and Figure 4A-4D ).

[0266] Example 2. Discovery of unique peptides at different resolutions by using nanoparticles and direct injection

[0267] By using direct injection of nanoparticles at 60k resolution ( Figure 5A and Table 1) and 120k resolution ( Figure 5B and Table 2) were used to find unique peptides.

[0268] Table 1. Number of unique peptides found by nanoparticles at 60 K (means from one-way ANOVA; standard errors using pooled estimates of error variance.)

[0269]

[0270]

[0271] Table 2. Number of unique peptides found by nanoparticles at 120 k (means from one-way ANOVA; standard errors using pooled estimates of error variance.)

[0272]

[0273] Table 3. Conditions of the experimental matrix

[0274]

[0275]

[0276] Example 3. Protein analysis of plasma samples without chromatographic separation

[0277] Plasma samples were processed using a commercially available PROTEOGRAPH assay kit (v 1.2). Five peptide samples (one for each nanoparticle) were obtained and each peptide sample was analyzed by direct injection mass spectrometry (MS-MS with ion mobility fractionation; 2 minutes ESI injection time). The resulting mass spectrometry data were demultiplexed using linear algebraic techniques (such as matrix-based multiple regression, convex optimization or LU decomposition) to identify the proteome in the plasma sample. By analyzing the peptide samples in the absence of chromatographic separation, the present embodiment can significantly reduce the mass spectrometry run time for each sample.

[0278] Although the aforementioned disclosure has been described in detail for the purpose of clarity and understanding, it will be clear to those skilled in the art from reading this disclosure that various changes in form and detail can be made without departing from the true scope of the disclosure. For example, all of the above-mentioned techniques and equipment can be used in various combinations. All publications, patents, patent applications and / or other documents cited in this application are incorporated herein by reference in their entirety for all purposes, to the extent that each individual publication, patent, patent application and / or other document is individually and independently indicated to be incorporated by reference for all purposes.

Claims

1. A method comprising: (a) contacting a plurality of biomolecules with a surface to adsorb the plurality of biomolecules on the surface; as well as (b) performing mass spectrometry on the plurality of biomolecules to generate a mass spectrum, wherein the mass spectrometry is performed (i) without chromatographic separation, or (ii) using chromatographic separation with a gradient length of up to 30 minutes.

2. The method of claim 1, wherein the gradient length is at most 25, 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2 or 1 minute.

3. The method of claim 1, wherein the chromatographic separation uses a chromatographic column comprising a length of at most 30, 25, 20, 15, 10, 5, 4, 3, 2, 1, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, or 0.1 centimeters. The method of claim 1 , wherein said performing said mass spectrometry comprises performing ion mobility separation. The method according to claim 4 , wherein the ion mobility separation is performed using traveling wave ion mobility separation. The method of claim 5 , wherein the traveling wave ion mobility separation is performed along a distance greater than 5 m or greater than 10 m.

7. The method according to claim 5 or 6, wherein the traveling wave ion mobility separation is performed along a serpentine path.

8. The method of claim 4, wherein the ion mobility separation is performed using high field asymmetric waveform ion mobility spectrometry (FAIMS).

9. The method of claims 1 or 4-8, wherein said performing said mass spectrometry comprises performing direct infusion mass spectrometry.

10. The method of claim 9, wherein the direct infusion mass spectrometry is performed in less than about 10 minutes, less than about 5 minutes, less than about 3 minutes, or less than about 2 minutes.

11. The method of any one of claims 1-10, wherein the mass spectrometry is performed with an isolation width of about 0.4, 0.6, 0.8, 1 or 2 m / z.

12. The method of any one of claims 1-11, wherein the mass spectrometry is performed with a maximum injection time of about 500 ms, 1 s, 5 s, 30 s, 1 min, 2 min, 3 min, 4 min, 5 min, or 10 min.

13. The method of any one of claims 1-12, wherein the mass spectrometry is performed at a resolution of about 120, 240, or 500K.

14. The method of any one of claims 1-13, wherein the mass spectrometry is performed at a resolution of about 30K to about 800K.

15. The method of any one of claims 1-14, wherein the contacting the plurality of biomolecules with the surface to adsorb the plurality of biomolecules on the surface comprises contacting a biological sample with the surface.

16. The method of claim 15, wherein the biological sample comprises blood, plasma, serum, urine, cerebrospinal fluid, synovial fluid, tears, saliva, whole blood, breast milk, nipple aspirate, ductal lavage, vaginal fluid, nasal fluid, ear fluid, gastric fluid, pancreatic fluid, trabecular fluid, lung lavage fluid, sweat, gingival crevicular fluid, semen, prostatic fluid, sputum, stool, bronchial lavage fluid, fluid from a swab, bronchial aspirate, fluidized solids, fine needle aspiration sample, tissue homogenate, lymph fluid, cell culture sample, or any combination thereof.

17. The method of claim 15, wherein the biological sample comprises blood, serum or plasma.

18. The method of any one of claims 15-17, wherein the biological sample is a biological fluid.

19. The method of claim 15, wherein the biological sample comprises a cell lysate.

20. The method of any one of claims 1-18, wherein the surface is a particle.

21. The method of any one of claims 1-20, wherein said contacting the plurality of biomolecules with the surface to adsorb the plurality of biomolecules on the surface comprises incubating the biomolecules with the surface for at least 15 minutes.

22. The method of claim 21, wherein the incubating is performed at a temperature of about 5°C to about 40°C.

23. The method of any one of claims 1-22, wherein the mass spectrometry comprises tandem mass spectrometry.

24. The method of any one of claims 1-23, wherein the mass spectrometry comprises Fourier transform mass spectrometry.

25. The method of any one of claims 1-24, wherein the mass spectrometry comprises time-of-flight mass spectrometry.

26. The method of any one of claims 1-25, wherein said performing mass spectrometry identifies at least about 300 protein groups.

27. The method of any one of claims 1-26, wherein said performing mass spectrometry comprises data independent acquisition (DIA).

28. The method of any one of claims 1-27, wherein the surface comprises a plurality of particles having a polydispersity index greater than 0.5, greater than 0.75, or greater than 1.

0.

29. The method of any one of claims 1-27, wherein the surface comprises a plurality of particles having a polydispersity index less than 0.

1.

30. The method of any one of claims 1-29, wherein the plurality of biomolecules comprises a plurality of proteins.

31. The method of any one of claims 1-30, wherein the surface selectively adsorbs extracellular vesicles.

32. The method of claim 31 , wherein the surface is ammonium functionalized.

33. The method of claim 32, wherein the surface comprises polyethyleneimine.

34. The method of claim 32, wherein the surface comprises cross-linked polyethyleneimine.

35. The method of claim 31 , wherein the surface comprises polyethylene oxide and aromatic groups.

36. A method comprising: (a) contacting a plurality of biomolecules with a surface to adsorb the plurality of biomolecules on the surface; (b) performing mass spectrometry on the plurality of biomolecules to generate a multiplexed mass spectrum; as well as (c) deconvolving the multiplexed mass spectrum to generate a plurality of deconvoluted MS signals, wherein the deconvolution is based on the type of the surface.

37. The method of claim 36, wherein the deconvolution is based on genomic information associated with a plurality of biomolecules.

38. The method of claim 37, wherein the genomic information comprises a library of polyamino acids expressible by a plurality of organisms.

39. The method of any one of claims 36-38, wherein the spectral library comprises a plurality of mass spectrometry signals of the plurality of expressible polyamino acids.

40. The method of any one of claims 36-39, wherein said performing said mass spectrometry comprises scanning said plurality of biomolecules across a plurality of mass windows.

41. The method of claim 40, wherein the scanning is performed at a frequency between 20 and 80 Hz.

42. The method of any one of claims 40-41, wherein the plurality of mass windows are between 400 and 1600 Daltons.

43. The method of any one of claims 40-42, wherein the plurality of mass windows comprises a window of about 2 Daltons.

44. The method of any one of claims 40-43, wherein the multiplexed mass spectrum comprises signals within the window.

45. The method of any one of claims 40-44, wherein the plurality of mass spectrometry signals in the spectral library are within the window.

46. ​​The method of any one of claims 36-45, wherein the deconvolution is based on a library of a subset of the plurality of expressible polyamino acids, wherein the subset is configured to preferentially adsorb to the surface compared to expressible polyamino acids not in the subset.

47. The method of any one of claims 36-46, wherein the abundance of the plurality of biomolecules is at most about 6 orders of magnitude lower than the most abundant biomolecule in the sample.

48. The method of any one of claims 36-47, wherein the plurality of biomolecules are at least about 5 orders of magnitude and at most about 8 orders of magnitude less abundant than the most abundant biomolecule in the sample.

49. The method of any one of claims 36-48, wherein the plurality of biomolecules are at least about 7 orders of magnitude less abundant than the most abundant biomolecule in the sample.

50. The method of any one of claims 36-49, wherein said contacting the plurality of biomolecules with the surface to adsorb the plurality of biomolecules on the surface comprises contacting a biological sample with the surface.

51. The method of claim 50, wherein the biological sample comprises blood, plasma, serum, urine, cerebrospinal fluid, synovial fluid, tears, saliva, whole blood, breast milk, nipple aspirate, ductal lavage, vaginal fluid, nasal fluid, ear fluid, gastric fluid, pancreatic fluid, trabecular fluid, lung lavage fluid, sweat, gingival crevicular fluid, semen, prostatic fluid, sputum, stool, bronchial lavage fluid, fluid from a swab, bronchial aspirate, fluidized solids, fine needle aspiration sample, tissue homogenate, lymph fluid, cell culture sample, or any combination thereof.

52. The method of claim 50, wherein the biological sample comprises blood, serum or plasma.

53. The method of claim 50, wherein the biological sample comprises a cell lysate.

54. The method of any one of claims 50-52, wherein the biological sample is a biological fluid.

55. The method of any one of claims 36-54, wherein the surface is a particle.

56. The method of any one of claims 36-55, wherein said contacting the plurality of biomolecules with the surface to adsorb the plurality of biomolecules on the surface comprises incubating the biomolecules with the surface for at least 15 minutes.

57. The method of claim 56, wherein the incubating is performed at a temperature of about 5°C to about 40°C.

58. The method of any one of claims 36-57, wherein the mass spectrometry comprises tandem mass spectrometry.

59. The method of any one of claims 36-58, wherein the mass spectrometry comprises Fourier transform mass spectrometry.

60. The method of any one of claims 36-59, wherein the mass spectrometry comprises time-of-flight mass spectrometry.

61. The method of any one of claims 36-60, wherein the mass spectrometry comprises data independent acquisition (DIA).

62. The method of any one of claims 36-61, wherein the mass spectrometry comprises targeted mass spectrometry.

63. The method of claim 62, wherein the targeted mass spectrometry comprises multiple reaction monitoring (MRM).

64. The method of any one of claims 36-63, wherein the surface selectively adsorbs extracellular vesicles.

65. The method of claim 64, wherein the surface is ammonium functionalized.

66. The method of claim 65, wherein the surface comprises polyethyleneimine.

67. The method of claim 65, wherein the surface comprises cross-linked polyethyleneimine.

68. The method of claim 64, wherein the surface comprises polyethylene oxide and aromatic groups.

69. A method comprising: (a) incubating a biological sample with one or more surfaces to form a biomolecule corona on the one or more surfaces; as well as (b) performing mass spectrometry on the biomolecules from the biomolecule corona to generate a mass spectrum, wherein the mass spectrometry is performed (i) without chromatographic separation, or (ii) using chromatographic separation with a gradient length of up to 10 minutes.

70. The method of claim 69, wherein the gradient length is at most 9, 8, 7, 6, 5, 4, 3, 2, or 1 minute.

71. The method of claim 69 or 70, wherein the chromatographic separation uses a chromatographic column comprising a length of at most 30, 25, 20, 15, 10, 5, 4, 3, 2, 1, 0.9, 0.8, 0.7, 0.6, 0.5, 0.4, 0.3, 0.2, or 0.1 centimeters.

72. The method of claim 69, wherein said performing said mass spectrometry comprises performing ion mobility separation.

73. The method of claim 72, wherein the ion mobility separation is performed using high field asymmetric waveform ion mobility spectrometry (FAIMS).

74. The method of claim 72, wherein the ion mobility separation is performed using traveling wave ion mobility separation.

75. The method of claim 74, wherein the traveling wave ion mobility separation is performed along a distance greater than 5 m or greater than 10 m.

76. The method of claim 74 or 75, wherein the traveling wave ion mobility separation is performed along a serpentine path.

77. The method of any one of claims 69-72, wherein performing mass spectrometry comprises performing direct infusion mass spectrometry.

78. The method of any one of claims 69-77, wherein said performing mass spectrometry is performed without chromatographic separation.

79. The method of any one of claims 69-78, wherein said performing mass spectrometry comprises tandem mass spectrometry.

80. The method of any one of claims 69-79, wherein said performing mass spectrometry comprises data independent acquisition (DIA).

81. The method of any one of claims 69-79, wherein said performing mass spectrometry comprises targeted mass spectrometry.

82. The method of claim 81, wherein the targeted mass spectrometry comprises multiple reaction monitoring (MRM).

83. The method of any one of claims 69-82, wherein said performing mass spectrometry comprises electrospray injection.

84. The method of any one of claims 69-83, wherein the biomolecule from the biomolecule corona comprises a protein.

85. The method of claim 84, wherein said performing mass spectrometry comprises detecting at least 50, 100, 200, 250, 300, 400, 500, or 1000 proteins in the biological sample.

86. The method of claim 84, wherein said performing mass spectrometry comprises detecting at least 50, 100, 200, 250, 300, 400, 500, or 1000 protein groups in said biological sample.

87. The method of any one of claims 69-86, further comprising removing biomolecules from the biomolecule corona prior to (b).

88. The method of claim 87, wherein said removing biomolecules from the biomolecule corona comprises enzymatically digesting the biomolecule corona.

89. The method of claim 88, wherein the enzyme is a protease, such as trypsin.

90. The method of any one of claims 69-86, further comprising alkylating and reducing the biomolecule from the biomolecule corona prior to (b).

91. The method of any one of claims 69-87, further comprising alkylating, reducing and digesting the biomolecules from the biomolecule corona prior to (b).

92. The method of any one of claims 69-91, further comprising applying one or more washing steps to the biomolecules from the biomolecule corona prior to (b).

93. The method of any one of claims 69-92, wherein the incubating comprises maintaining the biological sample at a temperature of 20°C to 50°C for at least 15 minutes.

94. The method of any one of claims 69-92, wherein the biological sample comprises blood, plasma, serum, urine, cerebrospinal fluid, synovial fluid, tears, saliva, whole blood, breast milk, nipple aspirate, ductal lavage, vaginal fluid, nasal fluid, ear fluid, gastric fluid, pancreatic fluid, trabecular fluid, lung lavage fluid, sweat, gingival crevicular fluid, semen, prostatic fluid, sputum, feces, bronchial lavage fluid, fluid from a swab, bronchial aspirate, fluidized solids, fine needle aspiration sample, tissue homogenate, lymph fluid, cell culture sample, or any combination thereof.

95. The method of any one of claims 69-94, wherein the biological sample comprises blood, serum, or plasma.

96. The method of any one of claims 69-92, wherein the biological sample comprises a cell lysate.

97. The method of any one of claims 69-95, wherein the one or more surfaces comprise particles.

98. The method of claim 97, wherein the particles are porous particles.

99. The method of claim 97 or 98, wherein the particles are microparticles.

100. The method of claim 97 or 98, wherein the particles are nanoparticles.

101. The method of any one of claims 97-100, wherein the particles comprise a paramagnetic material.

102. The method of claim 101, wherein the paramagnetic material is a superparamagnetic material.

103. The method of claim 101 or 102, wherein the paramagnetic material comprises iron oxide.

104. The method of any one of claims 69-103, wherein the biological sample is incubated with a first surface and a second surface having different physicochemical properties such that different protein coronas are formed on each surface.

105. The method of claim 104, wherein the first surface and the second surface comprise different charge signatures.

106. The method of claim 104, wherein the first surface and the second surface comprise different zeta potential signatures.

107. The method of claim 104, wherein the first surface and the second surface comprise the same charge signature.

108. The method of claim 104, wherein the first surface and the second surface comprise the same zeta potential signature.

109. The method of any one of claims 104-108, wherein the first surface, the second surface, or both comprises carboxylate groups, acrylate groups, methacrylate groups, acetal groups, hemiacetal groups, hemiketal groups, sulfonic acid groups, sulfinic acid groups, thiocarboxylic acid groups, phosphonic acid groups, phosphate groups, phosphodiester groups, boric acid groups, boric acid ester groups, boric acid groups, boric acid ester groups, silica groups, silanol groups, polymers, or any combination thereof.

110. The method of any one of claims 104-109, wherein the first surface and the second surface are incubated in separate aliquots of the biological sample.

111. The method according to claim 110, wherein: In (b), mass spectrometry is performed on the biomolecular corona from the first surface and the biomolecular corona from the second surface, respectively.

112. The method of any one of claims 104-109, wherein the first surface and the second surface are incubated in a single volume of the biological sample.

113. The method of any one of claims 69-112, further comprising washing the biomolecule corona with a washing composition prior to (b).

114. The method of any one of claims 69-113, further comprising determining a biological state of the subject using the mass spectrometer.

115. The method of any one of claims 69-114, wherein the biological sample is incubated with at least 2, 3, 4, 5, 6, 7, 8, 9 or 10 surfaces having different physicochemical properties.

116. The method of any one of claims 69-114, wherein the biological sample is incubated with 3 to 8 surfaces having different physicochemical properties.

117. The method of claim 115 or 116, wherein performing mass spectrometry comprises at least 2, 3, 4, 5, 6, 7, 8, 9 or 10 separate injections.

118. The method of claim 115 or 116, wherein performing mass spectrometry comprises 3-8 separate injections.

119. The method of claim 117 or 118, wherein each of the separate injections corresponds to a biomolecular corona obtained from a different surface.

120. The method of any one of claims 69-119, wherein at least one of the surfaces selectively adsorbs extracellular vesicles.

121. The method of claim 120, wherein at least one of the surfaces is ammonium functionalized.

122. The method of claim 121, wherein said at least one of said surfaces comprises polyethyleneimine.

123. The method of claim 121, wherein said at least one of said surfaces comprises cross-linked polyethyleneimine.

124. The method of claim 120, wherein said at least one of said surfaces comprises polyethylene oxide and aromatic groups.

125. A method comprising: (a) incubating a biological sample with first magnetic particles to form a first protein corona; (b) incubating the biological sample with second magnetic particles to form a second protein corona, wherein the first magnetic particles and the second magnetic particles have different physicochemical properties, and wherein the first magnetic particles and the second magnetic particles are incubated with separate volumes of the biological sample; as well as (c) performing mass spectrometry on proteins from the first protein corona and the second protein corona using direct injection to generate a mass spectrum, wherein separate injections are performed for the first protein corona and the second protein corona.

126. The method of claim 125, wherein at least 500 different protein groups are detected.

127. The method of claim 125, wherein at least 1000 different protein groups are detected.

128. The method of any one of claims 125-127, wherein the biological sample is blood, serum or plasma.

129. The method of any one of claims 125-128, wherein the first magnetic particles and the second magnetic particles have different zeta potential signatures.

130. The method of any one of claims 125-129, wherein the outer surface of the first magnetic particles comprises amine functional groups and the outer surface of the second magnetic particles comprises carboxyl functional groups.

131. The method of any one of claims 125-130, wherein the first magnetic particles comprise a polymeric outer surface and the second magnetic particles comprise a non-polymeric outer surface.

132. The method of any one of claims 125-131, wherein at least 50 unique protein groups are detected from the first protein corona that are not detected from the second protein corona.

133. The method of any one of claims 125-131, wherein at least 100 unique protein groups are detected from the first protein corona that are not detected from the second protein corona.

134. The method of any one of claims 125-133, wherein the first magnetic particles and the second magnetic particles each have a polydispersity index less than 0.

25.

135. The method of any one of claims 125-133, wherein the first magnetic particles and the second magnetic particles each have a polydispersity index less than 0.

1.

136. The method of any one of claims 125-135, wherein the first magnetic particles and the second magnetic particles are nanoparticles.

137. The method of any one of claims 125-136, wherein the first magnetic particles and the second magnetic particles have a diameter less than 500 nm.

138. The method of any one of claims 125-137, wherein the mass spectrometry is performed in less than 10 minutes.

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