CN117723685A - Method for screening specific peptide fragment markers and application thereof - Google Patents
Method for screening specific peptide fragment markers and application thereof Download PDFInfo
- Publication number
- CN117723685A CN117723685A CN202311649423.1A CN202311649423A CN117723685A CN 117723685 A CN117723685 A CN 117723685A CN 202311649423 A CN202311649423 A CN 202311649423A CN 117723685 A CN117723685 A CN 117723685A
- Authority
- CN
- China
- Prior art keywords
- deionized water
- tof
- markers
- analysis
- dispersion liquid
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 23
- 102000007079 Peptide Fragments Human genes 0.000 title claims abstract description 22
- 108010033276 Peptide Fragments Proteins 0.000 title claims abstract description 22
- 238000012216 screening Methods 0.000 title claims abstract description 15
- 108090000765 processed proteins & peptides Proteins 0.000 claims abstract description 86
- 102000004196 processed proteins & peptides Human genes 0.000 claims abstract description 69
- 229920001184 polypeptide Polymers 0.000 claims abstract description 67
- 239000000463 material Substances 0.000 claims abstract description 53
- 238000004458 analytical method Methods 0.000 claims abstract description 31
- 239000012621 metal-organic framework Substances 0.000 claims abstract description 30
- 208000024827 Alzheimer disease Diseases 0.000 claims abstract description 25
- 210000002966 serum Anatomy 0.000 claims abstract description 20
- 238000000074 matrix-assisted laser desorption--ionisation tandem time-of-flight detection Methods 0.000 claims abstract description 13
- 238000001294 liquid chromatography-tandem mass spectrometry Methods 0.000 claims abstract description 10
- 238000000605 extraction Methods 0.000 claims abstract description 4
- 238000010606 normalization Methods 0.000 claims abstract description 4
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Chemical compound O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 claims description 31
- 239000008367 deionised water Substances 0.000 claims description 26
- 229910021641 deionized water Inorganic materials 0.000 claims description 26
- ZMXDDKWLCZADIW-UHFFFAOYSA-N N,N-Dimethylformamide Chemical compound CN(C)C=O ZMXDDKWLCZADIW-UHFFFAOYSA-N 0.000 claims description 24
- 239000007788 liquid Substances 0.000 claims description 22
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 claims description 20
- 239000006185 dispersion Substances 0.000 claims description 20
- 239000000047 product Substances 0.000 claims description 20
- WEVYAHXRMPXWCK-UHFFFAOYSA-N Acetonitrile Chemical compound CC#N WEVYAHXRMPXWCK-UHFFFAOYSA-N 0.000 claims description 15
- LYCAIKOWRPUZTN-UHFFFAOYSA-N Ethylene glycol Chemical compound OCCO LYCAIKOWRPUZTN-UHFFFAOYSA-N 0.000 claims description 14
- QMKYBPDZANOJGF-UHFFFAOYSA-N benzene-1,3,5-tricarboxylic acid Chemical compound OC(=O)C1=CC(C(O)=O)=CC(C(O)=O)=C1 QMKYBPDZANOJGF-UHFFFAOYSA-N 0.000 claims description 10
- 239000000243 solution Substances 0.000 claims description 10
- 238000006243 chemical reaction Methods 0.000 claims description 9
- 239000007983 Tris buffer Substances 0.000 claims description 8
- 239000003550 marker Substances 0.000 claims description 8
- 238000003756 stirring Methods 0.000 claims description 8
- 238000005406 washing Methods 0.000 claims description 8
- 125000003275 alpha amino acid group Chemical group 0.000 claims description 7
- LENZDBCJOHFCAS-UHFFFAOYSA-N tris Chemical compound OCC(N)(CO)CO LENZDBCJOHFCAS-UHFFFAOYSA-N 0.000 claims description 7
- 238000001291 vacuum drying Methods 0.000 claims description 7
- WXTMDXOMEHJXQO-UHFFFAOYSA-N 2,5-dihydroxybenzoic acid Chemical compound OC(=O)C1=CC(O)=CC=C1O WXTMDXOMEHJXQO-UHFFFAOYSA-N 0.000 claims description 6
- DTQVDTLACAAQTR-UHFFFAOYSA-N Trifluoroacetic acid Chemical compound OC(=O)C(F)(F)F DTQVDTLACAAQTR-UHFFFAOYSA-N 0.000 claims description 6
- OPQARKPSCNTWTJ-UHFFFAOYSA-L copper(ii) acetate Chemical compound [Cu+2].CC([O-])=O.CC([O-])=O OPQARKPSCNTWTJ-UHFFFAOYSA-L 0.000 claims description 6
- 238000002156 mixing Methods 0.000 claims description 6
- 238000000513 principal component analysis Methods 0.000 claims description 6
- CTENFNNZBMHDDG-UHFFFAOYSA-N Dopamine hydrochloride Chemical compound Cl.NCCC1=CC=C(O)C(O)=C1 CTENFNNZBMHDDG-UHFFFAOYSA-N 0.000 claims description 5
- VMHLLURERBWHNL-UHFFFAOYSA-M Sodium acetate Chemical compound [Na+].CC([O-])=O VMHLLURERBWHNL-UHFFFAOYSA-M 0.000 claims description 5
- 229960001149 dopamine hydrochloride Drugs 0.000 claims description 5
- 239000011159 matrix material Substances 0.000 claims description 5
- 239000006228 supernatant Substances 0.000 claims description 5
- QGZKDVFQNNGYKY-UHFFFAOYSA-N Ammonia Chemical compound N QGZKDVFQNNGYKY-UHFFFAOYSA-N 0.000 claims description 4
- 238000009007 Diagnostic Kit Methods 0.000 claims description 4
- 229940040526 anhydrous sodium acetate Drugs 0.000 claims description 4
- 239000007853 buffer solution Substances 0.000 claims description 4
- 238000001035 drying Methods 0.000 claims description 4
- 239000012149 elution buffer Substances 0.000 claims description 4
- 235000019441 ethanol Nutrition 0.000 claims description 4
- 238000004108 freeze drying Methods 0.000 claims description 4
- 238000011534 incubation Methods 0.000 claims description 4
- NQXWGWZJXJUMQB-UHFFFAOYSA-K iron trichloride hexahydrate Chemical compound O.O.O.O.O.O.[Cl-].Cl[Fe+]Cl NQXWGWZJXJUMQB-UHFFFAOYSA-K 0.000 claims description 4
- 239000000203 mixture Substances 0.000 claims description 4
- 238000009210 therapy by ultrasound Methods 0.000 claims description 3
- 229910021529 ammonia Inorganic materials 0.000 claims description 2
- 239000003153 chemical reaction reagent Substances 0.000 claims description 2
- 238000001816 cooling Methods 0.000 claims description 2
- 239000003480 eluent Substances 0.000 claims description 2
- 238000010438 heat treatment Methods 0.000 claims description 2
- 239000002245 particle Substances 0.000 claims description 2
- 238000002360 preparation method Methods 0.000 claims description 2
- 230000002194 synthesizing effect Effects 0.000 claims 1
- 238000010801 machine learning Methods 0.000 abstract description 13
- 238000003745 diagnosis Methods 0.000 abstract description 8
- 201000010099 disease Diseases 0.000 abstract description 8
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 abstract description 8
- 238000004422 calculation algorithm Methods 0.000 abstract description 5
- 230000015572 biosynthetic process Effects 0.000 abstract description 3
- 230000008569 process Effects 0.000 abstract description 3
- 238000003786 synthesis reaction Methods 0.000 abstract description 3
- 239000003814 drug Substances 0.000 abstract description 2
- 238000003759 clinical diagnosis Methods 0.000 abstract 1
- 238000010828 elution Methods 0.000 abstract 1
- 230000004907 flux Effects 0.000 abstract 1
- 238000002203 pretreatment Methods 0.000 abstract 1
- 238000012549 training Methods 0.000 description 13
- 150000002500 ions Chemical class 0.000 description 12
- 238000001819 mass spectrum Methods 0.000 description 8
- BDAGIHXWWSANSR-UHFFFAOYSA-N methanoic acid Natural products OC=O BDAGIHXWWSANSR-UHFFFAOYSA-N 0.000 description 8
- 239000011148 porous material Substances 0.000 description 7
- 239000012071 phase Substances 0.000 description 6
- 239000012634 fragment Substances 0.000 description 5
- OSWFIVFLDKOXQC-UHFFFAOYSA-N 4-(3-methoxyphenyl)aniline Chemical compound COC1=CC=CC(C=2C=CC(N)=CC=2)=C1 OSWFIVFLDKOXQC-UHFFFAOYSA-N 0.000 description 4
- IJGRMHOSHXDMSA-UHFFFAOYSA-N Atomic nitrogen Chemical compound N#N IJGRMHOSHXDMSA-UHFFFAOYSA-N 0.000 description 4
- 241000282414 Homo sapiens Species 0.000 description 4
- 238000010494 dissociation reaction Methods 0.000 description 4
- 230000005593 dissociations Effects 0.000 description 4
- 235000019253 formic acid Nutrition 0.000 description 4
- 238000001840 matrix-assisted laser desorption--ionisation time-of-flight mass spectrometry Methods 0.000 description 4
- 239000012472 biological sample Substances 0.000 description 3
- 239000000090 biomarker Substances 0.000 description 3
- 208000010877 cognitive disease Diseases 0.000 description 3
- 229910052751 metal Inorganic materials 0.000 description 3
- 238000012986 modification Methods 0.000 description 3
- 230000004048 modification Effects 0.000 description 3
- 238000010239 partial least squares discriminant analysis Methods 0.000 description 3
- 239000000523 sample Substances 0.000 description 3
- 238000000926 separation method Methods 0.000 description 3
- 239000013148 Cu-BTC MOF Substances 0.000 description 2
- JPVYNHNXODAKFH-UHFFFAOYSA-N Cu2+ Chemical compound [Cu+2] JPVYNHNXODAKFH-UHFFFAOYSA-N 0.000 description 2
- 108010026552 Proteome Proteins 0.000 description 2
- 238000003917 TEM image Methods 0.000 description 2
- 238000002441 X-ray diffraction Methods 0.000 description 2
- 238000013528 artificial neural network Methods 0.000 description 2
- 150000001768 cations Chemical class 0.000 description 2
- 229910001431 copper ion Inorganic materials 0.000 description 2
- 230000004927 fusion Effects 0.000 description 2
- 238000011068 loading method Methods 0.000 description 2
- 238000007477 logistic regression Methods 0.000 description 2
- 238000010197 meta-analysis Methods 0.000 description 2
- 239000002184 metal Substances 0.000 description 2
- 229910052757 nitrogen Inorganic materials 0.000 description 2
- 230000008506 pathogenesis Effects 0.000 description 2
- 231100000915 pathological change Toxicity 0.000 description 2
- 230000036285 pathological change Effects 0.000 description 2
- 230000001575 pathological effect Effects 0.000 description 2
- 108090000623 proteins and genes Proteins 0.000 description 2
- 238000007637 random forest analysis Methods 0.000 description 2
- 238000001179 sorption measurement Methods 0.000 description 2
- 230000003595 spectral effect Effects 0.000 description 2
- 238000012706 support-vector machine Methods 0.000 description 2
- 238000004885 tandem mass spectrometry Methods 0.000 description 2
- 208000028698 Cognitive impairment Diseases 0.000 description 1
- 108090000790 Enzymes Proteins 0.000 description 1
- 102000004190 Enzymes Human genes 0.000 description 1
- 238000005033 Fourier transform infrared spectroscopy Methods 0.000 description 1
- 238000001157 Fourier transform infrared spectrum Methods 0.000 description 1
- 241000282412 Homo Species 0.000 description 1
- 230000001133 acceleration Effects 0.000 description 1
- PQLVXDKIJBQVDF-UHFFFAOYSA-N acetic acid;hydrate Chemical compound O.CC(O)=O PQLVXDKIJBQVDF-UHFFFAOYSA-N 0.000 description 1
- 239000003463 adsorbent Substances 0.000 description 1
- 150000001413 amino acids Chemical class 0.000 description 1
- 230000003941 amyloidogenesis Effects 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008827 biological function Effects 0.000 description 1
- 239000012620 biological material Substances 0.000 description 1
- 210000001124 body fluid Anatomy 0.000 description 1
- 239000010839 body fluid Substances 0.000 description 1
- 125000003178 carboxy group Chemical group [H]OC(*)=O 0.000 description 1
- 210000001175 cerebrospinal fluid Anatomy 0.000 description 1
- 239000013522 chelant Substances 0.000 description 1
- 230000009920 chelation Effects 0.000 description 1
- 238000007374 clinical diagnostic method Methods 0.000 description 1
- 230000003930 cognitive ability Effects 0.000 description 1
- 239000011258 core-shell material Substances 0.000 description 1
- 239000013078 crystal Substances 0.000 description 1
- 230000007423 decrease Effects 0.000 description 1
- 230000001066 destructive effect Effects 0.000 description 1
- 238000002405 diagnostic procedure Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 238000013399 early diagnosis Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000001027 hydrothermal synthesis Methods 0.000 description 1
- WGCNASOHLSPBMP-UHFFFAOYSA-N hydroxyacetaldehyde Natural products OCC=O WGCNASOHLSPBMP-UHFFFAOYSA-N 0.000 description 1
- 238000001727 in vivo Methods 0.000 description 1
- 208000015181 infectious disease Diseases 0.000 description 1
- 230000003993 interaction Effects 0.000 description 1
- 238000004895 liquid chromatography mass spectrometry Methods 0.000 description 1
- 238000009593 lumbar puncture Methods 0.000 description 1
- 238000004949 mass spectrometry Methods 0.000 description 1
- 206010027175 memory impairment Diseases 0.000 description 1
- 208000027061 mild cognitive impairment Diseases 0.000 description 1
- 239000011259 mixed solution Substances 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000004770 neurodegeneration Effects 0.000 description 1
- 208000015122 neurodegenerative disease Diseases 0.000 description 1
- 238000002610 neuroimaging Methods 0.000 description 1
- 239000013110 organic ligand Substances 0.000 description 1
- 210000002381 plasma Anatomy 0.000 description 1
- 238000002600 positron emission tomography Methods 0.000 description 1
- 125000002924 primary amino group Chemical group [H]N([H])* 0.000 description 1
- 230000000750 progressive effect Effects 0.000 description 1
- 230000017854 proteolysis Effects 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000004044 response Effects 0.000 description 1
- 230000004043 responsiveness Effects 0.000 description 1
- 238000005070 sampling Methods 0.000 description 1
- 238000001878 scanning electron micrograph Methods 0.000 description 1
- 238000001338 self-assembly Methods 0.000 description 1
- 230000035945 sensitivity Effects 0.000 description 1
- 239000001632 sodium acetate Substances 0.000 description 1
- 235000017281 sodium acetate Nutrition 0.000 description 1
- 239000007787 solid Substances 0.000 description 1
- 239000007790 solid phase Substances 0.000 description 1
- 238000001228 spectrum Methods 0.000 description 1
- 238000012360 testing method Methods 0.000 description 1
- 210000002700 urine Anatomy 0.000 description 1
- 238000010200 validation analysis Methods 0.000 description 1
Landscapes
- Other Investigation Or Analysis Of Materials By Electrical Means (AREA)
Abstract
The application relates to the field of biological medicine, and particularly discloses a method for screening specific peptide fragment markers and application thereof. Firstly, a target sample is pretreated by using a magnetic metal organic framework material, and then MALDI-TOF/TOF MS analysis is directly carried out without any elution process to extract serum peptide fingerprint. And (3) carrying out peak extraction and normalization on the mass spectrogram, and carrying out orthogonal partial least square discriminant analysis and screening of characteristic polypeptide markers. Serum peptides closely related to Alzheimer's disease were then determined and diagnostic models were built by integrating machine learning algorithms, nano-LC-MS/MS and Uniprot search libraries. The sample pretreatment method provided by the synthesis of the invention greatly simplifies the diagnosis process, has the advantages of high flux, accuracy and low cost, and has great application prospect in the aspect of large-scale clinical diagnosis of complex diseases.
Description
Technical Field
The application relates to the field of biological medicine, in particular to a method for screening specific peptide fragment markers and application thereof.
Background
Endogenous polypeptide mainly comprises protein degradation fragments, gene codes and in-vivo gene independent enzymes, and is widely existing in body fluids such as human serum, plasma, urine and the like. The expression level of the polypeptide in the body can reflect the physiological and pathological states of the organism, and has wide clinical application prospect in the aspect of being used as a biomarker. The peptide group analysis is a comprehensive research analysis of endogenous polypeptides in biological samples, can directly reflect the physiological and pathological states of individuals from the small molecular peptide level, and has important clinical significance. For example, changes in aβ42/aβ40 levels in human plasma samples may show pathological changes in amyloid deposition before significant plaque pathological changes appear in brain imaging. The polypeptides (amino acids 151-166) will increase progressively with increasing severity of cognitive impairment in patients with Alzheimer's disease, mild cognitive impairment and subjective decline in cognitive ability. Thus, monitoring the expression level of endogenous peptides of a disease has great potential in establishing diagnostic methods for alzheimer's disease.
The magnetic porous material has the advantages of easy separation, flexible modification, large specific surface area, high stability and the like, and has certain advantages of extracting endogenous polypeptide with low abundance in complex biological samples. It is noted that a metal-organic framework porous material formed by self-assembly of an inorganic metal center and an organic ligand has been widely used in the field of life sciences and has been shown to have excellent properties in extracting peptide fragments as an emerging porous material. Wherein, the metal organic framework HKUST-1 with copper ions can chelate carboxyl and amino on the peptide through copper ions, and has stronger enrichment capability on endogenous peptide. Matrix assisted laser desorption/ionization time of flight mass spectrometry (MALDI-TOF MS) is a fast, high throughput, high resolution and high sensitivity technique. To date, efforts have been made to combine magnetic porous materials with MALDI-TOF MS for peptide histology. Differential expression patterns are revealed by comparing the peptide histology information between disease patients and healthy people, aiming at finding biomarkers of complex diseases. Therefore, it is necessary to combine the advantages of abundant active metal sites and easy modification of the magnetic metal organic framework to prepare the magnetic biological material capable of efficiently extracting endogenous polypeptides in biological samples, and simultaneously, the MALDI-TOF MS technology is adopted to facilitate rapid and accurate diagnosis and typing of specific diseases.
Alzheimer's disease is a destructive and progressive neurodegenerative disease characterized by distinct clinical manifestations of memory impairment and cognitive dysfunction, usually manifested in advanced stages of the disease. The disease progresses slowly, irreversibly and the pathogenesis is not clear, and an effective radical treatment method is still lacking at present. Therefore, it is important to early discovery and accurate diagnosis of Alzheimer's disease. However, the current clinical diagnostic methods for alzheimer's disease mostly employ invasive lumbar puncture cerebrospinal fluid analysis or expensive positron emission tomography, and the sampling process is extremely painful and is prone to cause infection. Thus, serum biomarkers for diagnosing alzheimer's disease were found to be critical for early diagnosis and timely intervention in the pathogenesis.
Disclosure of Invention
The invention aims at providing a method for screening specific peptide fragment markers and application thereof.
In a first aspect, the present application proposes a method for screening specific peptide markers, which adopts the following technical scheme:
a method of screening for specific peptide fragment markers comprising the steps of:
step 1: mixing a magnetic metal organic framework material with deionized water to prepare a material dispersion liquid, adding the material dispersion liquid and a target sample into the deionized water for incubation, discarding supernatant after incubation is finished to obtain a material enriched in peptide fragments, and redispersing the material enriched in peptide fragments into the deionized water to obtain a dispersion liquid;
step 2, mixing the dispersion liquid obtained in the step 1 with a base particle target, and carrying out MALDI-TOF/TOF MS analysis;
step 3, carrying out peak extraction and normalization on the mass spectrogram of the MALDI-TOF/TOF MS obtained in the step 2, carrying out orthogonal partial least square discriminant analysis and principal component analysis, and selecting characteristic polypeptide markers;
step 4, eluting the materials enriched to the peptide fragments in the step 1 by using an elution buffer, and freeze-drying the eluent to analyze and identify the polypeptides by nano-LC-MS/MS;
and 5, matching the mass-to-charge ratio of the characteristic polypeptide marker obtained in the step 3 with the polypeptide identified in the nano-LC-MS/MS analysis in the step 4, and determining the amino acid sequence of the characteristic polypeptide marker.
Preferably, the synthesis steps of the magnetic metal organic framework material used in the step 1 are as follows:
step (1): dissolving ferric trichloride hexahydrate in ethylene glycol until the solution is clear and transparent, adding anhydrous sodium acetate, fully stirring and ultrasonically transferring into a reaction kettle, heating at 100-450 ℃ for 10-20 hours, cooling the reaction kettle to room temperature after the reaction is finished, fully washing the obtained product with deionized water and absolute ethyl alcohol, and vacuum drying at 40-75 ℃;
the mass volume ratio of the ferric trichloride hexahydrate to the ethylene glycol to the anhydrous sodium acetate is 1.35g:75mL:3.6g;
step (2): dispersing the product obtained in the step (1) and dopamine hydrochloride into Tris buffer solution, uniformly stirring for 9 hours at room temperature after ultrasonic treatment for 5min, fully washing the obtained product with deionized water and absolute ethyl alcohol, and vacuum drying the obtained product at 40-75 ℃;
the Tris buffer solution contains the following components in mass volume ratio of 0.05g:40mL:40mL of buffer solution of tris, ethanol and deionized water;
the product obtained in the step (1) contains dopamine hydrochloride and Tris buffer solution with the mass volume ratio of 120mg:320mg:80mL;
step (3): uniformly dispersing the product obtained in the step (2), copper acetate and trimesic acid in N, N-dimethylformamide, continuously stirring for 45 minutes at 70 ℃ after ultrasonic uniformity, fully washing the obtained product with N, N-dimethylformamide and absolute ethyl alcohol, and vacuum drying at 40-75 ℃;
the mass volume ratio of the product obtained in the step (2) to copper acetate, trimesic acid and N, N-dimethylformamide is 100mg:160mg:168mg:80mL.
Preferably, the target sample in step 1 is serum.
Preferably, the step 1 is: the weight volume ratio of the magnetic metal organic framework material to deionized water is 20g:1L of the materials are mixed to prepare a material dispersion liquid, 20 mu L of the material dispersion liquid and 2 mu L of a target sample are added into 250 mu L of deionized water, the mixture is incubated for 60 minutes at 37 ℃, then the supernatant liquid is removed with the help of a magnet, the materials enriched in peptide fragments are obtained, and the materials enriched in peptide fragments are redispersed into 40 mu L of deionized water to obtain the dispersion liquid.
Preferably, the step 2 is: mixing 1 mu L of the dispersion liquid obtained in the step 1 with 1 mu L of a matrix dot target, naturally drying, and carrying out MALDI-TOF/TOF MS analysis;
wherein, the matrix comprises the following components in volume ratio of 50:49.9:0.1 acetonitrile, water, trifluoroacetic acid in 20mg/mL 2, 5-dihydroxybenzoic acid buffer solution.
Preferably, the elution buffer in the step 4 has a volume ratio of 1:33.45 of concentrated ammonia and deionized water.
Preferably, the specific conditions for the MALDI-TOF/TOF MS analysis in the step 2 are as follows: using BrukerUltrafleXtreme MALDI-TOF/TOF mass spectrum, adopting a 355nm Nd:YAG laser source, wherein the laser frequency is 2000Hz, the acceleration voltage is 20kV, the voltage at the ion source 1 is 20kV, and the voltage at the ion source 2 is 17.6kV; the collection mode is a reflection cation mode, and the collection range m/z is 700-5000Da; mass spectral data were obtained from Flexcontrol 3.4 and data were derived in Flexanalysis 3.4.
Preferably, the specific conditions for the nano-LC-MS/MS analysis in the step 4 are as follows: using EASY-nLC 1000 liquid chromatograph (Thermo Fisher Scientific) combined with Orbitrap Fusion mass spectrometer (Thermo FisherScientific), phase a and phase B of liquid chromatograph being water containing 0.1% formic acid and acetonitrile containing 0.1% formic acid respectively, redissolving the eluate obtained in step 1 in phase a after lyophilization, analyzing by linear gradient, wherein 5%A-30% B,50min, loading it into analytical column (Thermo Scientific Acclaim PepMap C, 75 μm×25 cm); the voltage of electrospray is 2.3kV, the scanning range of parent ions in the primary spectrogram is m/z=350-1600, the resolution is 60000 (m/z=200, the resolution is 15000, m/z=200 is obtained through high-energy collision dissociation, the high-energy collision dissociation mode is selected to sequentially fragment parent ions with charges of +2, +3 and +4, and the normalized collision energy is 28%;
tandem mass spectrometry was extracted from Proteome Discoverer (Thermo Fisher Scientific, version 2.4.0.305) and database search was performed using Uniprot-SwissProt database (taxonomies: homo sapiens, 20386 entries), setting a parent ion mass tolerance of 10ppm and a fragment ion mass tolerance of 0.020Da.
Preferably, the condition for selecting the characteristic polypeptide marker in step 3 is VIP value >2, P value <0.05 and FC value >2 or <0.5.
Preferably, the polypeptide matching condition in the step 5 is that the mass-to-charge ratio of the characteristic polypeptide marker selected by MALDI-TOF/TOF MS analysis is consistent with that of the polypeptide identified by nano-LC-MS/MS analysis within 100 ppm.
Preferably, in the step 5, matching the mass-to-charge ratio of the MALDI-TOF/TOF MS characteristic polypeptide marker in the step 3 with the polypeptide identified in the nano-LC-MS/MS in the step 4, and determining the amino acid sequence of 15 characteristic polypeptide markers: the values of m/z 4215.41 to HNVYINGITYTPVSSTNEKDMYSFLEDMGLKAFTNSK, m/z 2884.77 to DQTVSDNELQEMSNQGSKYVNKEIQ, m/z 2704.61 to REKPRVQEKQHPVPPPAQNQNQV, m/z 2930.55 to SSSYSKQFTSSTSYNRGDSTFESKSY, m/z 4192.66 to LPAVDEKL RDLYSKSTAAM (+15.99) STYTGIFTDQVLSVLKGEE, m/z 2955.34 to GPRRYTIAALLSPYS YSTTAVVTNPKE, m/z 3605.01 to VSETESRGSESGIFTNTKESSSHHPGIAEFPSRG, m/z 2510.05 to FTSSTSYNRGDSTFESKSYKMA, m/z 2784.80 to ILRQQQHLFGSNVTDCS GNFCLFR, m/z 2541.30 to DAHKSEVAHRFKDLGEENFKAL, m/z 2680.93 to AD RSGKDGVMEMNSIEPAKETTTNV, m/z 3314.60 to SVPPSASHVAPTETFTYEWTVPKEVGPTNA D, m/z 2379.03 to SYSKQFTSSTSYNRGDSTFES, m/z 2328.42 to SQEEEKTEA LTSAKRYIETD, and m/z 2354.68 to DNELQEMSNQGSKYVNKEIQ.
In a second aspect, the present application provides the use of the above method for the preparation of a diagnostic kit for Alzheimer's disease.
In a third aspect, the present application provides a diagnostic kit for alzheimer's disease comprising reagents for detecting 15 specific peptide markers;
the amino acid sequences of the 15 specific peptide fragment markers are shown in SEQ ID NO: 1-15.
SEQ ID NO：1：HNVYINGITYTPVSSTNEKDMYSFLEDMGLKAFTNSK，
SEQ ID NO：2：DQTVSDNELQEMSNQGSKYVNKEIQ，
SEQ ID NO：3：REKPRVQEKQHPVPPPAQNQNQV，
SEQ ID NO：4：SSSYSKQFTSSTSYNRGDSTFESKSY，
SEQ ID NO：5：LPAVDEKLRDLYSKSTAAM(+15.99)STYTGIFTDQVLSVLKGEE，
SEQ ID NO：6：GPRRYTIAALLSPYSYSTTAVVTNPKE，
SEQ ID NO：7：VSETESRGSESGIFTNTKESSSHHPGIAEFPSRG，
SEQ ID NO：8：FTSSTSYNRGDSTFESKSYKMA，
SEQ ID NO：9：LRQQQHLFGSNVTDCSGNFCLFR，
SEQ ID NO：10：DAHKSEVAHRFKDLGEENFKAL，
SEQ ID NO：11：ADRSGKDGVMEMNSIEPAKETTTNV，
SEQ ID NO：12：SVPPSASHVAPTETFTYEWTVPKEVGPTNAD，
SEQ ID NO：13：SYSKQFTSSTSYNRGDSTFES，
SEQ ID NO：14：SQEEEKTEALTSAKRYIETD，
SEQ ID NO：15：DNELQEMSNQGSKYVNKEIQ。
The application has the following beneficial effects:
1. the magnetic metal organic framework material provided by the invention contains rich active metal sites, has large specific surface area and good magnetic response, and has strong chelation with endogenous polypeptide, so that the method can separate and enrich the endogenous polypeptide more sensitively and more widely;
2. according to the method, the expression difference of the endogenous polypeptide between healthy people and Alzheimer disease patients can be analyzed through a machine learning algorithm, so that characteristic polypeptide markers are screened, the endogenous hydrophilic polypeptide can be identified on a large scale by combining nano-LC MS/MS, and the biological function is deeply analyzed;
3. in the method, a plurality of machine learning diagnosis models are established through screening the selected polypeptide markers and are used for preparing Alzheimer disease diagnosis kits.
In conclusion, the magnetic metal organic framework material prepared by the invention has high polypeptide affinity, unique pore structure and excellent magnetic responsiveness, can be successfully used for specifically separating and enriching endogenous polypeptides in serum of Alzheimer disease patients and healthy people, and screening out 15 characteristic hydrophilic polypeptides as potential Alzheimer disease markers, and successfully realizes high-precision diagnosis of Alzheimer disease patients based on a machine learning algorithm, thus indicating that the magnetic metal organic framework material has great application prospects in large-scale crowd screening, disease diagnosis and other aspects.
Drawings
FIG. 1 is a scanning electron micrograph of the magnetic metal-organic framework material of example 1;
FIG. 2 is a transmission electron micrograph of the magnetic metal-organic framework material of example 1;
FIG. 3 is an X-ray diffraction pattern of the magnetic metal-organic framework material of example 1;
FIG. 4 is a graph showing the nitrogen adsorption isotherm and pore size distribution of the magnetic metal-organic framework material of example 1;
FIG. 5 is a Fourier transform infrared spectrum of the magnetic metal-organic framework material of example 1;
FIG. 6 is a mass spectrum of the magnetic metal organic framework material of example 2 for separation and enrichment of endogenous polypeptides in serum;
FIG. 6 (a) is a representative mass spectrum of endogenous polypeptides in serum of Alzheimer's disease patients enriched in the present material;
FIG. 6 (b) is a representative mass spectrum of endogenous polypeptides in serum of healthy humans enriched in the subject material;
FIG. 7 is a training set-based orthorhombic least squares discriminant analysis model of example 3;
FIG. 8 is a heat map of 15 feature polypeptides based on training set of example 3;
FIG. 9 is a model of 15 characteristic polypeptides principal component analysis based on all samples of example 4;
FIG. 10 is a machine learning model constructed from 15 feature polypeptides based on training set of example 5;
FIG. 11 is a machine learning model constructed based on 3 feature polypeptides of example 6.
Detailed Description
The present invention utilizes the interaction of magnetic metal organic framework material and endogenous polypeptide to realize the enrichment and analysis of serum endogenous peptide, and the present application is further described in detail with reference to the accompanying drawings and examples.
Example 1
The synthesis of the magnetic metal organic framework material comprises the following steps:
step (1): 1.35g FeCl 3 ·6H 2 After O is stirred in 75mL of glycol by magnetic force until the solid is completely dissolved, 3.6g of sodium acetate is added, the mixture is fully stirred and ultrasonically treated and then transferred into a hydrothermal reaction kettle, the mixture is heated for 16 hours at 200 ℃, after the reaction kettle is cooled, the product is respectively washed three times by deionized water and ethanol, and is dried in vacuum at 50 ℃;
step (2): uniformly dispersing 120mg and 320mg of dopamine hydrochloride obtained in the step (1) in a mixed solution of 40mL of ethanol and 40mL of deionized water containing 0.05g of tris (hydroxymethyl) aminomethane, stirring at room temperature for 9 hours under the condition of continuous ultrasonic treatment until uniform, fully washing the obtained product with deionized water and absolute ethanol after the reaction is finished, and vacuum drying the obtained product at 50 ℃;
step (3): uniformly dispersing 100mg of copper acetate, 160mg of copper acetate and 168mg of trimesic acid in 80mL of N, N-dimethylformamide, continuously stirring for 45 minutes at 70 ℃ under the condition of continuous ultrasonic until uniformity, respectively washing the product obtained in the step (2) with N, N-dimethylformamide and absolute ethyl alcohol three times after the reaction is finished, and drying in vacuum at 50 ℃; the magnetic metal organic framework material is obtained and named as Mag HKUST-1.
A scanning electron microscope photograph of the magnetic metal organic framework material is shown in fig. 1; a transmission electron micrograph of the magnetic metal-organic framework material is shown in fig. 2; the X-ray diffraction spectrum of the magnetic metal organic framework material is shown in figure 3; the nitrogen adsorption isotherm and the pore size distribution diagram of the magnetic metal organic framework material are shown in fig. 4; the Fourier transform infrared spectrogram of the magnetic metal organic framework material is shown in figure 5.
Analysis results: as can be seen from fig. 1 to 5: the magnetic metal organic framework material presents a uniform spherical shape and a core-shell structure, and the surface can observe a rough geometric crystal shape with 126.9m 2 g -1 And 0.27cm 3 g -1 And specific surface area and porosity of (c).
Example 2
The magnetic metal organic framework material obtained in the example 1 is used as a solid phase adsorbent for separating and enriching endogenous polypeptides in serum samples of 110 Alzheimer disease patients and serum of 120 healthy people, and the steps are as follows:
(1) Serum from 110 patients with alzheimer's disease and 120 healthy controls was taken at 7: the ratio of 3 was randomly divided into training and test sets, corresponding to 161 and 69 samples, respectively.
(2) 2mg of the magnetic metal-organic framework material obtained in example 1 was mixed with 100. Mu.L of deionized water to prepare a material dispersion, 20. Mu.L of the material dispersion and 2. Mu.L of serum were added to 250. Mu.L of deionized water, incubated at 37℃for 60 minutes, then the supernatant was discarded with the aid of a magnet, and the material enriched in peptide fragments was redispersed in 40. Mu.L of deionized water to obtain a dispersion.
(3) Mass spectrometry: 1. Mu.L of the dispersion in step (2) was mixed with 1. Mu.L of 20mg mL -1 A 2, 5-dihydroxybenzoic acid (DHB) matrix (acetonitrile/water/trifluoroacetic acid volume ratio=50/49.9/0.1) is subjected to MALDI-TOF/TOF MS analysis after natural drying, a Bruker UltrafleXtreme MALDI-TOF/TOF mass spectrum is used, a 355nm Nd: YAG laser source is adopted, the laser frequency is 2000Hz, the accelerating voltage is 20kV (the voltage at the ion source 1 is 20kV and the voltage at the ion source 2 is 17.6 kV), the collecting mode is a reflective cation mode, and the collecting range m/z is 700-5000Da; mass spectral data were obtained from Flexcontrol 3.4 and data were derived in Flexanalysis 3.4. The mass spectrum is shown in fig. 6.
Analysis results: from fig. 6, it can be seen that the endogenous peptide in the serum is captured by the material, and the serum peptide mass spectrum of the patient with alzheimer disease has obvious difference from that of the healthy person.
Example 3
Peak extraction and normalization are carried out on the serum endogenous peptide spectrogram obtained in the example 2, orthogonal partial least squares discriminant analysis is carried out on a training set by using Metaboanalytics 5.0 and SIMCA, the VIP value, the P value and the FC value of each polypeptide are calculated, and characteristic polypeptide markers are screened, wherein the steps are as follows:
(1) The serum hydrophilic peptide mass spectra were peak extracted and normalized using R package MALDIquant, MALDIquantForeign and limma.
(2) Orthogonal partial least squares discriminant analysis and principal component analysis are performed on the training set and the validation set, respectively, using metaanalysis 5.0 and SIMCA to select characteristic polypeptide markers, specifically, VIP value, P value and FC value of each polypeptide are calculated using metaanalysis 5.0 and SIMCA, and polypeptides with VIP value >2, P value <0.05 and FC value >2 or <0.5 are selected as characteristic polypeptide markers.
(3) And drawing a heat map of the training set based on the characteristic polypeptide markers.
The orthogonal partial least square discriminant analysis model based on the training set is shown in fig. 7; a heatmap of 15 signature polypeptides based on the training set is shown in figure 8.
Analysis results: as can be seen from fig. 7, in the orthorhombic partial least squares discriminant analysis model, the serum endogenous polypeptide separation effect of the alzheimer disease patients and healthy people is better. As can be seen from fig. 8, 15 characteristic polypeptide markers play an important role in distinguishing alzheimer's disease patients from healthy people.
Example 4
The 15 characteristic polypeptide markers obtained in example 3 were subjected to principal component analysis for all samples.
A model of principal component analysis of 15 characteristic polypeptides based on all samples is shown in FIG. 9.
Analysis results: as can be seen from FIG. 9, the 15 signature polypeptide markers have the ability to distinguish Alzheimer's disease patients from healthy people under the principle component analysis of this unsupervised machine learning algorithm
Example 5
Machine learning diagnosis model establishment is carried out on the training set by 15 characteristic polypeptide markers obtained in the embodiment 3.
A machine learning model constructed based on 15 feature polypeptides of the training set is shown in fig. 10.
Analysis results: as can be seen from fig. 10, the 15 characteristic polypeptide markers have the capability of diagnosing alzheimer's disease under the model established by six machine learning algorithms, namely Random Forest (RF), logistic Regression (LR), neural Network (NN), support Vector Machine (SVM), naive Bayes (NB), and k-nearest neighbor (kNN).
Example 6
Six machine learning diagnostic models in example 6 were constructed for the training set using the 3 characteristic polypeptide markers (m/z values 4215.4, 2884.77, 2704.61) with the highest scores among the 15 characteristic polypeptide markers obtained in example 3.
A machine learning model constructed based on 3 feature polypeptides of the training set is shown in fig. 11.
Analysis results: as can be seen from fig. 11, the machine learning model established with only 3 signature polypeptide markers also has the ability to diagnose alzheimer's disease patients.
Example 7
The eluate obtained in example 2 was subjected to nano-LC-MS/MS analysis to identify the polypeptide sequence, as follows:
(1) Using EASY-nLC 1000 liquid chromatograph (Thermo Fisher Scientific) combined with Orbitrap Fusion mass spectrometer (Thermo Fisher Scientific), phase a and phase B of liquid chromatograph being water containing 0.1% formic acid and acetonitrile containing 0.1% formic acid respectively, redissolving the eluate obtained in step (1) in phase a after lyophilization, loading it into analytical column (Thermo Scientific Acclaim PepMap C, 75 μm x 25 cm) for analysis by linear gradient, wherein 5% a-30% B,50 min; the voltage of electrospray is 2.3kV, the scanning range of parent ions in the primary spectrogram is m/z=350-1600, the resolution is 60000 (m/z=200, the resolution is 15000, m/z=200 is obtained through high-energy collision dissociation, the high-energy collision dissociation mode is selected to sequentially fragment parent ions with charges of +2, +3 and +4, and the normalized collision energy is 28%;
(2) Tandem mass spectrometry was extracted from Proteome Discoverer (Thermo Fisher Scientific, version 2.4.0.305) and database search was performed using Uniprot-SwissProt database (taxonomies: homo sapiens, 20386 entries), setting a parent ion mass tolerance of 10ppm and a fragment ion mass tolerance of 0.020Da.
(3) Matching the mass-to-charge ratio of the characteristic polypeptide marker obtained in example 3 with the polypeptide identified by nano-LC-MS/MS, and determining the amino acid sequence of 15 characteristic polypeptide markers according to the principle of coincidence within 100 ppm.
Analysis results: the amino acid sequences of the 15 signature polypeptide markers are as follows:
an m/z value of 4215.41 corresponds to HNVYINGITYTPVSSTNEKDMYSFLEDMGLKAFTNSK,
an m/z value of 2884.77 corresponds to DQTVSDNELQEMSNQGSKYVNKEIQ,
an m/z value of 2704.61 corresponds to REKPRVQEKQHPVPPPAQNQNQV,
an m/z value of 2930.55 corresponds to SSSYSKQFTSSTSYNRGDSTFESKSY,
an m/z value of 4192.66 corresponds to LPAVDEKLRDLYSKSTAAM (+ 15.99) STYTGIFTDQVLSVLKGEE,
an m/z value of 2955.34 corresponds to GPRRYTIAALLSPYSYSTTAVVTNPKE,
an m/z value of 3605.01 corresponds to VSETESRGSESGIFTNTKESSSHHPGIAEFPSRG,
an m/z value of 2510.05 corresponds to FTSSTSYNRGDSTFESKSYKMA,
an m/z value of 2784.80 corresponds to ILRQQQHLFGSNVTDCSGNFCLFR,
an m/z value of 2541.30 corresponds to DAHKSEVAHRFKDLGEENFKAL,
an m/z value of 2680.93 corresponds to ADRSGKDGVMEMNSIEPAKETTTNV,
an m/z value of 3314.60 corresponds to SVPPSASHVAPTETFTYEWTVPKEVGPTNAD,
an m/z value of 2379.03 corresponds to SYSKQFTSSTSYNRGDSTFES,
an m/z value of 2328.42 corresponds to SQEEEKTEALTSAKRYIETD,
the m/z value 2354.68 corresponds to DNELQEMSNQGSKYVNKEIQ.
The present embodiment is merely illustrative of the present application and is not intended to be limiting, and those skilled in the art, after having read the present specification, may make modifications to the present embodiment without creative contribution as required, but is protected by patent laws within the scope of the claims of the present application.
Claims (8)
1. A method of screening for specific peptide markers comprising the steps of:
step 1: mixing a magnetic metal organic framework material with deionized water to prepare a material dispersion liquid, adding the material dispersion liquid and a target sample into the deionized water for incubation, discarding supernatant after incubation is finished to obtain a material enriched in peptide fragments, and redispersing the material enriched in peptide fragments into the deionized water to obtain a dispersion liquid;
step 2, mixing the dispersion liquid obtained in the step 1 with a base particle target, and carrying out MALDI-TOF/TOF MS analysis;
step 3, carrying out peak extraction and normalization on the mass spectrogram of the MALDI-TOF/TOF MS obtained in the step 2, carrying out orthogonal partial least square discriminant analysis and principal component analysis, and selecting characteristic polypeptide markers;
step 4, eluting the materials enriched to the peptide fragments in the step 1 by using an elution buffer, and freeze-drying the eluent to analyze and identify the polypeptides by nano-LC-MS/MS;
and 5, matching the mass-to-charge ratio of the characteristic polypeptide marker obtained in the step 3 with the polypeptide identified in the nano-LC-MS/MS analysis in the step 4, and determining the amino acid sequence of the characteristic polypeptide marker.
2. The method of screening for specific peptide fragment markers according to claim 1, wherein the step of synthesizing the magnetic metal-organic framework material used in the step 1 is as follows:
step (1): dissolving ferric trichloride hexahydrate in ethylene glycol until the solution is clear and transparent, adding anhydrous sodium acetate, fully stirring and ultrasonically transferring into a reaction kettle, heating at 100-450 ℃ for 10-20 hours, cooling the reaction kettle to room temperature after the reaction is finished, fully washing the obtained product with deionized water and absolute ethyl alcohol, and vacuum drying at 40-75 ℃;
the mass volume ratio of the ferric trichloride hexahydrate to the ethylene glycol to the anhydrous sodium acetate is 1.35g:75mL:3.6g;
step (2): dispersing the product obtained in the step (1) and dopamine hydrochloride into Tris buffer solution, uniformly stirring for 9 hours at room temperature after ultrasonic treatment for 5min, fully washing the obtained product with deionized water and absolute ethyl alcohol, and vacuum drying the obtained product at 40-75 ℃;
the Tris buffer solution contains the following components in mass volume ratio of 0.05g:40mL:40mL of buffer solution of tris, ethanol and deionized water;
the product obtained in the step (1) contains dopamine hydrochloride and Tris buffer solution with the mass volume ratio of 120mg:320mg:80mL;
step (3): uniformly dispersing the product obtained in the step (2), copper acetate and trimesic acid in N, N-dimethylformamide, continuously stirring for 45 minutes at 70 ℃ after ultrasonic uniformity, fully washing the obtained product with N, N-dimethylformamide and absolute ethyl alcohol, and vacuum drying at 40-75 ℃;
the mass volume ratio of the product obtained in the step (2) to copper acetate, trimesic acid and N, N-dimethylformamide is 100mg:160mg:168mg:80mL.
3. The method of claim 1, wherein the target sample in step 1 is serum.
4. The method of screening for specific peptide fragment markers according to claim 1, wherein the step 1 is: the weight volume ratio of the magnetic metal organic framework material to deionized water is 20g:1L of the materials are mixed to prepare a material dispersion liquid, 20 mu L of the material dispersion liquid and 2 mu L of a target sample are added into 250 mu L of deionized water, the mixture is incubated for 60 minutes at 37 ℃, then the supernatant liquid is removed with the help of a magnet, the materials enriched in peptide fragments are obtained, and the materials enriched in peptide fragments are redispersed into 40 mu L of deionized water to obtain the dispersion liquid.
5. The method of screening for specific peptide markers according to claim 1, wherein step 2 is: mixing 1 mu L of the dispersion liquid obtained in the step 1 with 1 mu L of a matrix dot target, naturally drying, and carrying out MALDI-TOF/TOF MS analysis;
wherein, the matrix comprises the following components in volume ratio of 50:49.9:0.1 acetonitrile, water, trifluoroacetic acid in 20mg/mL 2, 5-dihydroxybenzoic acid buffer solution.
6. The method of claim 1, wherein the elution buffer in step 4 comprises a volume ratio of 1:33.45 of concentrated ammonia and deionized water.
7. Use of the method of any one of claims 1-6 for the preparation of a diagnostic kit for alzheimer's disease.
8. A diagnostic kit for alzheimer's disease comprising reagents for detecting 15 specific peptide markers;
the amino acid sequences of the 15 specific peptide fragment markers are shown in SEQ ID NO: 1-15.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311649423.1A CN117723685A (en) | 2023-12-04 | 2023-12-04 | Method for screening specific peptide fragment markers and application thereof |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311649423.1A CN117723685A (en) | 2023-12-04 | 2023-12-04 | Method for screening specific peptide fragment markers and application thereof |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117723685A true CN117723685A (en) | 2024-03-19 |
Family
ID=90208046
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311649423.1A Pending CN117723685A (en) | 2023-12-04 | 2023-12-04 | Method for screening specific peptide fragment markers and application thereof |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117723685A (en) |
-
2023
- 2023-12-04 CN CN202311649423.1A patent/CN117723685A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| JP6668415B2 (en) | Apparatus and method for microbiological analysis | |
| CN109884302B (en) | Lung cancer early diagnosis marker based on metabonomics and artificial intelligence technology and application thereof | |
| US8778695B2 (en) | Methods and apparatuses for analyzing biological samples by mass spectrometry | |
| CN109946390B (en) | Lung cancer diagnosis marker combination and application | |
| AU2002362961A1 (en) | Methods and apparatuses for analyzing biological samples by mass spectrometry | |
| CN102323246B (en) | One group for detecting the characteristic protein of pulmonary carcinoma | |
| US20080006581A1 (en) | method for separation and enrichment of phosphopeptides | |
| Magni et al. | Biomarkers discovery by peptide and protein profiling in biological fluids based on functionalized magnetic beads purification and mass spectrometry | |
| CN106732409B (en) | Synthesis method and application of sulfonic group modified metal organic framework nano composite material | |
| US10197576B2 (en) | Mass spectrometry imaging with substance identification | |
| US20030124606A1 (en) | Protein mixture analysis by mass spectrometry | |
| Zhao et al. | Zirconium arsenate-modified silica nanoparticles for specific capture of phosphopeptides and direct analysis by matrix-assisted laser desorption/ionization mass spectrometry | |
| CN108020669B (en) | Application of urinary osteopontin and polypeptide fragment thereof in lung adenocarcinoma | |
| Kienzl-Wagner et al. | Biomarker discovery in transplantation—proteomic adventure or mission impossible? | |
| CN117723685A (en) | Method for screening specific peptide fragment markers and application thereof | |
| KR20130066481A (en) | Method for analyzing cancer-specific glycan and use of it for diagnosing cancer | |
| CN116577403A (en) | Separation detection method and application of exosomes | |
| CN116813920A (en) | Preparation method and application of beta-cyclodextrin functionalized covalent organic framework composite material | |
| CN116413432A (en) | Pancreatic cancer diagnosis marker based on intestinal flora metabonomics, screening method and application thereof | |
| WO2013067750A1 (en) | Polyclonal antibody immunologic mass spectrometry kit of liver cancer marker | |
| CN112782403B (en) | Composition, application and diagnostic kit | |
| Zhang et al. | A non-targeting magnetic metal-organic framework probe for highly specific peptide-mediated precise disease monitoring | |
| CN114942286A (en) | Detection method of hydrophilic polypeptide | |
| CN109870580B (en) | Application of serum protein marker group in preparation of detection kit for identifying schistosomiasis and detection kit | |
| CN113092768A (en) | Application of urine keratin, II type cytoskeleton 1 and polypeptide fragment thereof in allergic diseases |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |