Automated apparatus and system

Abstract

The present disclosure provides sensor arrays for detecting biomolecules and methods of use. In some embodiments, the sensor arrays are capable of determining a disease state in a subject.

1 . An automated apparatus for generating a subset of biomolecules from a complex biological sample, the automated apparatus comprising:
 a plurality of particles, wherein the plurality of particles differ from each other in at least one physiocochemical property, wherein each particle has a distinct biomolecule corona signature from the other; and   the complex biological sample,   wherein the automated apparatus is configured to generate the subset of biomolecules by contacting the plurality of particles with the complex biological sample to form a plurality of biomolecule coronas comprising the subset of biomolecules, and   wherein a dynamic range of the subset of biomolecules is compressed relative to a dynamic range of biomolecules present in the complex biological sample.   
     
     
         2 . The automated apparatus of  claim 1 , wherein the compressed dynamic range comprises an altered concentration of the subset of biomolecules. 
     
     
         3 . The automated apparatus of  claim 1 , wherein the compressed dynamic range comprises a concentration of low abundance biomolecules whose concentrations in the complex biological sample are within 10 orders of magnitude of the most abundant biomolecule in the in the complex biological sample. 
     
     
         4 . The automated apparatus of  claim 1 , wherein the compressed dynamic range comprises a concentration of low abundance biomolecules whose concentrations in the complex biological sample are within 4-6 orders of magnitude of the most abundant biomolecule in the in the complex biological sample. 
     
     
         5 . The automated apparatus of  claim 1 , wherein the compressed dynamic range comprises a concentration of low abundance biomolecules whose concentrations in the complex biological sample are <100 ng/ml. 
     
     
         6 . The automated apparatus of  claim 1 , wherein the compressed dynamic range comprises a concentration of low abundance biomolecules whose concentrations in the complex biological sample are <10 ng/ml. 
     
     
         7 . The automated apparatus of  claim 1 , wherein the concentration of the subset of biomolecules are <100 ng/ml in the complex biological sample. 
     
     
         8 . The automated apparatus of  claim 1 , wherein the concentration of the subset of biomolecules are <10 ng/ml in the complex biological sample. 
     
     
         9 . The automated apparatus of  claim 1 , wherein the compressed dynamic range of the subset of biomolecules enhances the detectability of the subset of biomolecules. 
     
     
         10 . The automated apparatus of  claim 1 , wherein the automated apparatus comprises a computer system configured to associate the subset of biomolecules with a biological state. 
     
     
         11 . The automated apparatus of  claim 1 , wherein the automated apparatus is configured to remove loosely attached biomolecules from the particles. 
     
     
         12 . The automated apparatus of  claim 1 , wherein the automated apparatus is configured to detect the subset of biomolecules. 
     
     
         13 . The automated apparatus of  claim 1 , wherein the biomolecules comprise proteins. 
     
     
         14 . The automated apparatus of  claim 1 , wherein the biological sample has not been subjected to depletion. 
     
     
         15 . The automated apparatus of  claim 1 , wherein the complex biological sample comprises a plasma sample. 
     
     
         16 . The automated apparatus of  claim 1 , wherein the different physiocochemical property differ by one or more properties selected from the group consisting of: composition, size, charge, hydrophobicity, hydrophilicity, functionality, topography, curvature, shape, conductivity, and any combination thereof. 
     
     
         17 . The automated apparatus of  claim 1 , wherein the plurality of particles comprises at least two materials. 
     
     
         18 . The automated apparatus of  claim 1 , wherein the plurality of particles comprises nanoparticles, and wherein the nanoparticles are selected from the group consisting of micelles, liposomes, iron oxide nanoparticles, silver nanoparticles, gold nanoparticles, palladium nanoparticles, quantum dots, platinum nanoparticles, titanium nanoparticles, silica nanoparticles, metal or inorganic oxide nanoparticles, synthetic polymer nanoparticles, copolymer nanoparticles, terpolymer nanoparticles, polymeric nanoparticles with metal cores, polymeric nanoparticles with metal oxide cores, polystyrene sulfonate nanoparticles, polyethylene oxide nanoparticles, polyoxyethylene glycol nanoparticles, polyethylene imine nanoparticles, polylactic acid nanoparticles, polycaprolactone nanoparticles, polyglycolic acid nanoparticles, poly(lactide-co-glycolide polymer nanoparticles, cellulose ether polymer nanoparticles, polyvinylpyrrolidone nanoparticles, polyvinyl acetate nanoparticles, polyvinylpyrrolidone-vinyl acetate copolymer nanoparticles, polyvinyl alcohol nanoparticles, acrylate nanoparticles, polyacrylic acid nanoparticles, crotonic acid copolymer nanoparticles, polyethlene phosphonate nanoparticles, polyalkylene nanoparticles, carboxy vinyl polymer nanoparticles, sodium alginate nanoparticles, carrageenan nanoparticles, xanthan gum nanoparticles, gum acacia nanoparticles, Arabic gum nanoparticles, guar gum nanoparticles, pullulan nanoparticles, agar nanoparticles, chitin nanoparticles, chitosan nanoparticles, pectin nanoparticles, karaya tum nanoparticles, locust bean gum nanoparticles, maltodextrin nanoparticles, amylose nanoparticles, corn starch nanoparticles, potato starch nanoparticles, rice starch nanoparticles, tapioca starch nanoparticles, pea starch nanoparticles, sweet potato starch nanoparticles, barley starch nanoparticles, wheat starch nanoparticles, hydroxypropylated high amylose starch nanoparticles, dextrin nanoparticles, levan nanoparticles, elsinan nanoparticles, gluten nanoparticles, collagen nanoparticles, whey protein isolate nanoparticles, casein nanoparticles, milk protein nanoparticles, soy protein nanoparticles, keratin nanoparticles, polyethylene nanoparticles, polycarbonate nanoparticles, polyanhydride nanoparticles, polyhydroxyacid nanoparticles, polypropylfumerate nanoparticles, polycaprolactone nanoparticles, polyamine nanoparticles, polyacetal nanoparticles, polyether nanoparticles, polyester nanoparticles, poly(orthoester) nanoparticles, polycyanoacrylate nanoparticles, polyurethane nanoparticles, polyphosphazene nanoparticles, polyacrylate nanoparticles, polymethacrylate nanoparticles, polycyanoacrylate nanoparticles, polyurea nanoparticles, polyamine nanoparticles, polystyrene nanoparticles, poly(lysine) nanoparticles, chitosan nanoparticles, dextran nanoparticles, poly(acrylamide) nanoparticles, derivatized poly(acrylamide) nanoparticles, gelatin nanoparticles, starch nanoparticles, chitosan nanoparticles, dextran nanoparticles, gelatin nanoparticles, starch nanoparticles, poly-β-amino-ester nanoparticles, poly(amido amine) nanoparticles, poly lactic-co-glycolic acid nanoparticles, polyanhydride nanoparticles, bioreducible polymer nanoparticles, and 2-(3-aminopropylamino)ethanol nanoparticles, or any combination thereof. 
     
     
         19 . The automated apparatus of  claim 1 , wherein the particles comprise a polymer. 
     
     
         20 . The automated apparatus of  claim 1 , wherein the particles comprises a metal.