CN113325181A - Application of serine protease inhibitor in marker for early warning of sepsis - Google Patents
Application of serine protease inhibitor in marker for early warning of sepsis Download PDFInfo
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- CN113325181A CN113325181A CN202110445815.0A CN202110445815A CN113325181A CN 113325181 A CN113325181 A CN 113325181A CN 202110445815 A CN202110445815 A CN 202110445815A CN 113325181 A CN113325181 A CN 113325181A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/68—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids
- G01N33/6893—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing involving proteins, peptides or amino acids related to diseases not provided for elsewhere
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
- G01N33/50—Chemical analysis of biological material, e.g. blood, urine; Testing involving biospecific ligand binding methods; Immunological testing
- G01N33/53—Immunoassay; Biospecific binding assay; Materials therefor
- G01N33/569—Immunoassay; Biospecific binding assay; Materials therefor for microorganisms, e.g. protozoa, bacteria, viruses
- G01N33/56911—Bacteria
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2333/00—Assays involving biological materials from specific organisms or of a specific nature
- G01N2333/81—Protease inhibitors
- G01N2333/8107—Endopeptidase (E.C. 3.4.21-99) inhibitors
- G01N2333/811—Serine protease (E.C. 3.4.21) inhibitors
- G01N2333/8121—Serpins
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/26—Infectious diseases, e.g. generalised sepsis
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N2800/00—Detection or diagnosis of diseases
- G01N2800/52—Predicting or monitoring the response to treatment, e.g. for selection of therapy based on assay results in personalised medicine; Prognosis
Abstract
The invention provides the use of a serine protease inhibitor (SERPINA10) in a marker for early warning of sepsis. The invention also provides a kit for diagnosing the severity or prognosis of sepsis, which contains a reagent for detecting the serine protease inhibitor in a body fluid sample, and can solve the problem that whether sepsis complication or complication trend occurs after burn cannot be judged in the prior art.
Description
[ technical field ] A method for producing a semiconductor device
The invention belongs to the field of bioengineering, and relates to a biomarker, in particular to application of a serine protease inhibitor in a marker for early warning of sepsis.
[ background of the invention ]
Sepsis (sepsis) refers to the Systemic Inflammatory Response Syndrome (SIRS) caused by infection with clinically proven presence of bacteria or highly suspicious foci of infection. Although sepsis is caused by infection, once it occurs, its development follows its own pathological course and laws, so it is essentially the body's response to infectious agents. Sepsis has a high incidence of over 1800 million severe sepsis cases annually worldwide and 75 million sepsis patients annually in the united states, and this figure has also risen at a rate of 1.5% to 8.0% annually. Sepsis is highly morbid and highly fatal, with about 14,000 deaths worldwide per day from its complications and about 21.5 million deaths annually in the united states. According to foreign epidemiological investigation, the mortality rate of sepsis exceeds that of myocardial infarction, and becomes a main cause of death of non-cardiac patients in intensive care units. In recent years, despite significant advances in anti-infective therapy and organ function support technologies, sepsis has still suffered from a mortality rate of up to 30% to 70%. Sepsis treatment costs high, medical resources are consumed greatly, the quality of life of human beings is seriously affected, and great threats are already caused to human health.
However, the existing sepsis primary component detection has great limitation in the use of China, no scientific acquisition method and detection technology appear in China, and the difficulty is increased for further diagnosis and treatment.
Accordingly, there is a need for improvements in the art that overcome the deficiencies in the prior art.
[ summary of the invention ]
The object of the present invention is to provide the use of a serine protease inhibitor in a marker for early warning of sepsis, which can solve the above-mentioned problems of the prior art.
The invention provides the use of a serine protease inhibitor (SERPINA10) in a marker for early warning of sepsis.
In one embodiment, the sepsis is sepsis after a severe burn.
The invention also provides a kit for diagnosing the severity or prognosis of sepsis, which is characterized in that the kit contains a reagent for detecting the serine protease inhibitor in a body fluid sample.
In one embodiment, the body fluid sample is selected from serum.
The SERPINA10(ZPI) protein is a Z-dependent protease inhibitor and constitutes a protein Z/Z-dependent protease inhibitor (PZ/ZPI) system. Protein Z (PZ) is a vitamin K-dependent coagulation Protein, Protein Z-dependent protease inhibitor (ZPI) is a serine protease inhibitor, Protein Z-dependent protease inhibitor (ZPI) inhibits the activated factor x (fxa) in the presence of phospholipids and calcium ions, whereas PZ enhances the action of ZPI 1000-fold and PZ exerts an anticoagulant effect by enhancing the function of ZPI.
According to the invention, a series of researches show that the serine protease inhibitor has statistical difference one day after burn and can be used as an early warning marker for severe burn sepsis.
The invention collects the blood plasma of normal people, patients without combined sepsis due to burn and patients with combined sepsis due to burn on the first day, the third day, the fifth day and the seventh day respectively, extracts the supernatant in the blood plasma, carries out protein quantification on the supernatant by adopting a BCA method, then subpackages the samples, carries out SDS-PAGE electrophoresis, FASP enzymolysis, High PH RP classification, DDA mass spectrum library building and DIA mass spectrum analysis processing on the samples, finds that the protein SERPINA10 has statistical difference one day after burn, is verified to be a significant difference protein, and has no statistical difference on the third day, the fifth day and the seventh day. Thus, when there is a statistical difference in the serpin, it is indicated that sepsis after burn has been complicated or tends to be complicated.
Compared with the prior art, the invention has obvious technical progress, provides the application of the serine protease inhibitor in the marker for early warning of the sepsis, and is used for solving the problem that whether the complication or the complication trend of the sepsis occurs after the burn cannot be judged in the prior art.
[ description of the drawings ]
Figure 1 shows the results before normalization after DIA analysis of a sample of case plasma proteins.
Figure 2 shows the results of the normalization process after DIA analysis of a sample of case plasma proteins.
Figure 3 shows the results of analysis of case plasma proteomics PCA of healthy control group, patients with burn complicated sepsis, patients without burn complicated sepsis at different time points on day 1, day 3, day 5 and day 7, respectively.
Figure 4 shows the results of the analysis in figure 3 validated by the PRM-differential protein SERPINA10 on day 1.
Figure 5 shows the results of the analysis in figure 3 validated by the PRM-differential protein SERPINA10 on day 3.
[ detailed description ] embodiments
The first embodiment is as follows:
1. collecting sample information
Plasma was collected from normal persons, patients with burns without sepsis and patients with burns with sepsis, and collected on the first, third, fifth and seventh days, respectively. Specific sample information is shown in table 1.
TABLE 1
2. Preparing the sample
Taking a proper amount of sample, adding SDT lysate with three times of volume, carrying out boiling water bath for 10min, centrifuging for 15min at 14000g, and taking supernatant solution. Protein quantification was performed by BCA method. Samples were aliquoted and stored at-80 ℃.
3. SDS-PAGE electrophoresis
20 mu g of protein of each sample is respectively added into 6 Xloading buffer solution, and 12% SDS-PAGE electrophoresis is carried out in boiling water bath for 5min, wherein the constant pressure is 250V, the time length is 40min, and Coomassie brilliant blue staining is carried out.
4. Enzymatic hydrolysis of FASP
200ug of protein solution was taken from each sample, DTT was added to a final concentration of 100mM, and the mixture was cooled to room temperature in a boiling water bath for 5 min. Adding 200 μ LUA buffer, mixing, transferring into 30kD ultrafiltration centrifuge tube, centrifuging at 12500g for 25min, discarding filtrate, and repeating the above steps twice.
Add 100 μ LIAA buffer (100m MIAA in UA), shake at 600rpm for 1min, react at room temperature in the dark for 30min, centrifuge 12500g for 25 min. 100 μ LUA buffer was added and centrifuged 12500g for 15min and the procedure was repeated twice. Add 100. mu.L of 40mM NH4HCO3The solution was centrifuged 12500g for 15min and the procedure was repeated twice. 40 μ L of Trypsin buffer (4 μ g of Trypsin 40 μ L of 40mM NH) was added4HCO3Solution) at 600rpm for 1min, and standing at 37 deg.C for 16-18 h. Replacing the collecting pipe, and centrifuging for 12500g for 15 min; then 20 is addedμL 40mM NH4HCO3The solution was centrifuged at 12500g for 15min and the filtrate was collected. Desalting the peptide fragment by using C18 cartidge, freeze-drying the peptide fragment, adding 40 mu L of 0.1% formic acid solution for redissolving, and quantifying the peptide fragment.
5. High pH RP fractionation
All samples peptide fragment mixtures were taken and fractionated using an Agilent 1260 definition II HPLC system. The buffer solution A is 10mM HCOONH4, 5% ACN, pH 10.0, and the buffer solution B is 10mM HCOONH485% CAN, pH 10.0. The Column was equilibrated with solution a, and a sample was applied to the Column by an autosampler (Waters, XBridge Peptide BEH C18 Column,
5 μm,4.6mm X100 mm) at a flow rate of 1 mL/min. The liquid phase gradient was as follows: a linear gradient was used, 5% B to 45% B over 40min, with the column temperature maintained at 30 ℃. 36 fractions were collected and each fraction was dried in a vacuum concentrator for use. After freeze-drying, the sample is re-dissolved by 0.1% formic acid water solution to generate 12 fractions.
6. DDA mass spectrum library construction
6ul of each Fraction was taken out and 2ul of 10X iRT peptide fragment was added, mixed and then 2ul of sample was injected, separated by nano-LC and analyzed by on-line electrospray tandem mass spectrometry. The whole liquid-mass series system comprises: 1) liquid phase system: UltiMate 3000RSLCnano system (Thermo Fisher Scientific)2) mass spectrometry system: q-active HF-X (thermo Fisher scientific). The buffer solution A was 0.1% formic acid aqueous solution, and the buffer solution B was 0.1% formic acid acetonitrile aqueous solution (acetonitrile: 80%). The samples were fractionated through analytical columns (Thermo Fisher Scientific, Acclaim PepMap RSLC 50um X15cm, nano viper, P/N164943) at a flow rate of 300nL/min with a non-linear growth gradient: 0-5min, 1% B; 5-95min, 1% B to 28% B; 95-110min, 28% B to 38% B; 110-. The electrospray voltage was 2.0 kV.
The mass spectrum parameters were set as follows: (1) MS: scan range (m/z) 350-; resolution ═ 60,000; AGC target 3e 6; maximum injection time is 50 ms; include charge states 2-7; filter Dynamic Exclusion: the exception duration is 30 s; (2) dd-MS 2: isolation window 2m/z, resolution 15,000; AGC target 2e 5; maximum injection time is 45 ms; NCE is 27%.
Mass spectra raw data spectral database was created by spectronart Pulsar X (version 12, Biognosys AG) closing and opening analysis library, Swissprot _ human _ isoform _201806(42356entries), download link: http: // www.uniprot.org. Trypsin enzymatic was set to allow two leaky cleavage sites. And (3) fixed modification of library searching parameters: carbamidomethyl (c), variable modification: oxidation (M), acetylation of acetyl (Protein N-term) Protein N-terminal. The library building standard is 1% Precursor FDR and 1% Peptide FDR.
The samples in the experimental group are divided into 2 groups according to the sample sources, and the total number of the samples is 54. Using the constructed database, DIA analysis was performed on each sample and the quantitative information obtained is shown in table 2.
TABLE 2
| Precursors | Peptides | Protein Groups | |
| Mean quantification of | 4781 | 3071 | 395 |
| Total basis weight | 6951 | 4409 | 663 |
| Co-quantification of | 2667 | 1844 | 240 |
7. DIA Mass Spectrometry
6ul of each sample was taken out and 2ul of peptide fragment of 10X iRT was added, mixed and then 2ul of sample was injected, separated by nano-LC, and analyzed by on-line electrospray tandem mass spectrometry. The whole liquid-mass series system comprises: 1) and a liquid phase system: UltiMate 3000RSLCnano system (Thermo Fisher Scientific); 2) and a mass spectrometry system: q-active HF-X (thermo Fisher scientific). The buffer solution A was 0.1% formic acid aqueous solution, and the buffer solution B was 0.1% formic acid acetonitrile aqueous solution (acetonitrile: 80%). The samples were separated in a non-linearly increasing gradient through an analytical column (Thermo Fisher Scientific, Acclaim PepMap RSLC 50um X15cm, nano viper, P/N164943) at a flow rate of 300 nL/min: 0-5min, 1% B; 5-95min, 1% B to 28% B; 95-110min, 28% B to 38% B; 110-.
The mass spectrum parameters were set as follows: (1) MS, scan range (m/z) is 350-; resolution ═ 60,000; AGC target 3e 6; maximum injection time is 50 ms; (2) DIA: resolution 30,000; AGC target 1e 6; maximum injectiontime auto; NCE is 27%.
Wherein the DIA window setting parameters are as follows:
through evaluation, the DDA library aiming at the two groups of samples is successfully established in the experiment; DIA analysis is carried out on the sample on the basis of library building, the consistency of DIA quantitative results is ideal, the overall identification quantity is expected, the LCMS separation analysis effect is ideal, and subsequent difference quantitative screening can be carried out. To ensure the accuracy of the quantification, we first performed normalization (normalization) on the obtained DIA results. As shown in fig. 1 and 2, the left graph is before normalization, the right graph is after normalization, and after quantitative normalization of each group of samples, systematic errors were eliminated to some extent.
8. Principal component analysis
Principal Component Analysis (PCA), a statistical method. A group of variables which are possibly correlated are converted into a group of linearly uncorrelated variables through orthogonal transformation, and the group of converted variables are called principal components. And performing spatial dimension reduction on the researched data, and analyzing the integrity of the data on a two-dimensional layer, so as to judge the discrimination of different groups and further perform the next analytical research. As can be seen from the view in figure 3,
9. screening for significant analysis of differential proteins
Significant differential analysis was performed on BD1 vs AD1 in this study, and proteins that met the screening criteria of a fold greater than 1.5 fold difference in expression (up-down regulation) and a P value (t test) less than 0.05 were considered differentially expressed proteins.
Wherein BD is a patient suffering from burn and sepsis; AD is a patient with burns that do not develop sepsis.
10. PRM protein validation
Parallel Reaction Monitoring (PRM) is based on a high-resolution and high-precision mass spectrometry platform represented by Orbitrap and the like, firstly, a quadrupole mass analyzer is used for selecting parent ions of a target peptide fragment, then, the parent ions are fragmented in a collision cell, and finally, the Orbitrap analyzer is used for detecting all fragment information of the selected parent ions in a secondary mass spectrometry. Thus, the target protein/peptide fragment in the complex sample can be selectively and quantitatively analyzed. And carrying out PRM verification on the screened differential protein to further ensure the accuracy of the differential protein.
11. Results of PCA analysis
The whole of all groups was analyzed using PCA analysis, the analysis results are shown in fig. 3. According to the PCA analysis result, the plasma proteomics of two groups of patients with concurrent sepsis and without concurrent sepsis are not greatly different from 5 th and 7 th after burn, and only the proteomic results of 1 st and 3 rd after burn are included for analysis when trend analysis is subsequently performed.
Wherein, upper left: 1 day after burn; upper right: 3 days after burn; left lower: 5 days after burn; right lower: 7 days after burn. Group AD: patients with uncomplicated burns with sepsis; BD group: patients with sepsis complicated with burns; group C: healthy human controls.
The PCA analysis results showed the most significant variability of BD1 vs AD1, so we mainly selected one day samples from patients with severe burns for analysis of significantly different proteins (two samples with large differences in group B were removed). As shown in table 3: BD1 vs AD1 had a total of 54 distinct proteins, 42 of which were up-regulated and 12 were down-regulated.
TABLE 3
| Comparisons | Up- | Down- | All- |
| BD1 VS AD1 | 42 | 12 | 54 |
Based on the 54 differential proteins selected in table 3 above, we selected the most significant 26 proteins for PRM validation. This stage included new case samples for a total of 48 patients with post-burn concurrent sepsis (group B); a total of 32 patients with no concurrent sepsis after burn (group a); referring specifically to fig. 4 and 5, the protein SERPINA10 was statistically different on one day after burn, and was identified as a significantly different protein, with no statistical difference on the third day.
The invention also provides a kit for diagnosing the severity or prognosis of sepsis, which is characterized in that the kit contains a reagent for detecting the serine protease inhibitor in a body fluid sample. The body fluid sample is selected from serum.
The above is only one embodiment of the present invention, and any other modifications based on the concept of the present invention are considered as the protection scope of the present invention.
Claims (4)
1. Use of a serine protease inhibitor (SERPINA10) in a marker for early warning of sepsis.
2. Use according to claim 1, wherein the sepsis is sepsis after a severe burn.
3. A kit for diagnosing the severity or prognosis of sepsis, comprising reagents for detecting a serine protease inhibitor in a body fluid sample.
4. A kit for diagnosing the severity or prognosis of sepsis according to claim 3, characterised in that said body fluid sample is selected from serum.
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Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107206257A (en) * | 2014-10-27 | 2017-09-26 | 英伊布里克斯有限合伙公司 | Serpin fusion polypeptide and its application method |
| US20200069817A1 (en) * | 2018-08-09 | 2020-03-05 | Bioverativ Therapeutics Inc. | Nucleic acid molecules and uses thereof for non-viral gene therapy |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107206257A (en) * | 2014-10-27 | 2017-09-26 | 英伊布里克斯有限合伙公司 | Serpin fusion polypeptide and its application method |
| US20200069817A1 (en) * | 2018-08-09 | 2020-03-05 | Bioverativ Therapeutics Inc. | Nucleic acid molecules and uses thereof for non-viral gene therapy |
Non-Patent Citations (2)
| Title |
|---|
| ANTJE BUTSCHKAU等: "Contribution of protein Z and protein Z-dependent protease inhibitor in generalized Whwartzman reaction.", 《CRIT. CARE. MED.》 * |
| 黄方等: "蛋白质Z在临床疾病中的研究进展", 《血栓与止血学》 * |
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