Ultramicro proteomics analysis method

Abstract

The invention provides an ultramicro proteomics analysis method, which comprises the following steps: adding multi-channel Carrier samples into a sample to be detected, placing each Carrier sample in different TMT channels, and optimizing the number of channels of the multi-channel Carrier samples and the sample size of each channel, so as to obtain the ultramicro proteomics analysis result of the sample to be detected, wherein the Carrier sample of each channel only contains one single-cell sample, and each Carrier sample is placed in different TMT channels. After protein extraction, Trypsin / Lys-C double enzymolysis and TMT labeling, liquid chromatography-mass spectrometry analysis and detection are carried out, each Carrier sample can also be used as an internal reference, and semi-supervised clustering analysis of ultramicro samples is realized. The method is used for ultramicro proteomics analysis, so that the identification depth can be improved, and the quantitative accuracy of a single cell sample can be ensured.

Description

Technical Field

[0001] The invention belongs to the technical field of protein sample processing, and in particular relates to an ultra-micro proteomics analysis method. Background Art

[0002] With the development of proteomics technology, proteomics has begun to move into the study of ultra-trace samples. Among them, single-cell proteomics and spatial proteomics are particularly representative. For the convenience of description, the following description will only use single-cell proteomics analysis technology. However, ultra-trace samples are not limited to single-cell samples.

[0003] Cells are the smallest unit of life. Genetic and environmental factors make single cell heterogeneity widely present in many organisms. Tissues and organs are composed of functionally specialized cells. This specialization of single cells usually stems from the differences in proteins that mediate physiological functions. However, the ability to comprehensively quantify these proteins in single cells is still relatively limited.

[0004] There are currently two mainstream single-cell analysis methods based on mass spectrometry technology. The first method directly extracts proteins from single-cell samples, performs enzymatic hydrolysis, and performs mass spectrometry analysis. The process is relatively simple, but the identification depth is relatively low, generally around 1,000-1,500 proteins. The second method has currently developed into SCoPE (Single Cell ProtEomics) technology (single-cell proteomics technology).

[0005] The overall workflow of SCoPE technology is shown in Figure 1. Single cells are isolated in separate wells, lysed, and their proteins digested into peptides. Peptides from each single cell are covalently labeled with a tandem mass tag (TMT), so labeled peptides with the same sequence (and mass) appear as peaks of the same m / z in the MS1 scan, and the mass spectrometer separates these peaks and further fragments them. In addition to generating fragments that aid in peptide identification, fragments also generate reporter ions whose abundance reflects the abundance of proteins in the corresponding sample (single cell). In addition to single-cell samples, the concept of carrier was introduced, adding 50-100 times the labeled peptides of the same cells (such as the literature [Budnik B, Levy E, Harmange G, Slavov N. SCoPE-MS: mass spectrometry of single mammalian cells quantifies proteome heterogeneityduring cell differentiation. Genome Biol. 2018 Oct 22; 19(1): 161. doi: 10.1186 / s13059-018-1547-5. PMID: 30343672; PMCID: PMC6196420.], the single cells to be tested are Jurkat and U-937, and the carrier is a mixture of cells from the same source, that is, a mixture of Jurkat and U-937 cells). It has three important functions: (i) reducing sample loss; (ii) enhancing the detectability of ions during MS1 survey scanning and improving identification depth; (iii) providing fragment ions for peptide sequence identification. By combining this concept with MS-compatible cell lysis, a multiplexed LC-ESI-MS / MS technique was developed to enable high-throughput and high-depth qualitative and quantitative proteome analysis of single cells.

[0006] However, the existing SCoPe method uses single-channel Carrier technology. Due to reagent purity issues, single-channel Carrier samples interfere with the quantitative results of the TMT channel of single-cell samples. Because the TMT isotope reagent itself has purity issues, assuming that the purity of the isotope reagent reaches 99%, after adding 50-100 times the amount of labeled peptides from the same cell, the 1% impact on one cell to be tested will be limited by 50-100 times. It can be seen that single-channel Carrier samples will affect the quantitative accuracy of single-cell samples. In addition, the current single-channel Carrier technology only uses Carrier samples as a method to improve the depth of identification. Its quantitative information is useless and can only be used for unsupervised analysis.

[0007] Therefore, it is urgent to find a new type of ultra-trace proteomics analysis method that can reduce or avoid the impact of the carrier channel on single-cell samples, which can not only improve the identification depth but also ensure the quantitative accuracy of single-cell samples. Summary of the invention

[0008] To solve the above problems, the object of the present invention is to provide an ultra-trace proteomics analysis method, by adding a multi-channel carrier sample to the sample to be tested, the carrier sample of each channel contains only one single cell sample, each carrier sample is placed in a different TMT channel, and the number of channels of the multi-channel carrier sample is optimized, and the sample amount of each channel is then subjected to protein extraction, Trypsin / Lys-C double enzymatic hydrolysis and TMT labeling, and then liquid chromatography-mass spectrometry analysis is performed, wherein each carrier sample can also be used as an internal reference to achieve semi-supervised cluster analysis of ultra-trace samples. The method provided by the present invention performs ultra-trace proteomics analysis, which can not only improve the identification depth, but also ensure the quantitative accuracy of single cell samples.

[0009] On the one hand, the present invention provides a kind of ultra-micro proteomics analysis method, and said method comprises the following steps:

[0010] (1) adding a multi-channel carrier sample to the sample to be tested, wherein the multi-channel carrier sample refers to a carrier sample containing more than two channels, and the carrier sample contains only one single cell sample;

[0011] (2) Enzymatic hydrolysis;

[0012] (3) Add labeling reagent for labeling.

[0013] Since the existing SCoPe method uses single-channel Carrier technology, it interferes with the quantitative results of the TMT channel of single-cell samples. Although it can improve the identification depth, it is difficult to ensure the quantitative accuracy of single-cell samples.

[0014] The present invention establishes a multi-channel carrier technology that can reduce or avoid the impact of the carrier channel on single-cell samples. For the convenience of description, it is referred to as the "mScope" technology.

[0015] Each channel contains only one single-cell sample, that is, the carrier sample in the channel is a pure single-cell sample, rather than a mixture of multiple single-cell samples.

[0016] The present invention adopts a multi-channel carrier, which can increase the amount of carrier samples used and enhance the identification depth of single-cell samples without affecting the accuracy of quantification.

[0017] The existing single-channel carrier technology only uses carrier samples as a method to improve the depth of identification, and its quantitative information is useless, and only unsupervised analysis can be performed. The present invention uses multi-channel carrier technology, which can use multiple carrier samples to achieve semi-supervised identification.

[0018] Furthermore, the sample to be tested in step (1) is a single cell sample.

[0019] In some embodiments, the single cell sample can be obtained by flow sorting technology.

[0020] Furthermore, the labeling reagent in step (3) is TMT; and each carrier sample in the multi-channel carrier sample in step (1) is placed in a different TMT channel.

[0021] The present invention places carrier samples of different channels in different TMT channels, respectively, performs TMT labeling, mixes with labeled single cell samples, and then performs liquid chromatography-mass spectrometry analysis and detection.

[0022] Compared with the existing SCoPe technology, the method provided by the present invention can be used to increase the actual total carrier multiples and reduce the quantitative interference of each single carrier channel on the TMT channel of the single-cell sample. For example, a mixed sample of 100 cells in the original single-channel carrier sample is divided into 4 different carrier channels (25 separate types of cells in each channel). Compared with the single-cell sample to be tested, the original impact can be reduced to 25%, the interference is significantly reduced, and a better identification depth can be achieved.

[0023] In addition, since each channel in the multi-channel Carrier sample contains only one single-cell sample, it can also be used as an internal reference to achieve semi-supervised clustering analysis of ultra-trace samples.

[0024] It is understandable that in the application of this method, each channel does not necessarily target different types of cells, but can also target two or three different states of the same cell, such as different cell cycles, etc., which can all be identified using the multi-channel Carrier sample method provided by the present invention.

[0025] Furthermore, the number of channels of the multi-channel carrier sample in step (1) is consistent with the number of cell types in the single-cell sample.

[0026] Furthermore, the number of channels of the multi-channel carrier sample in step (1) is 3.

[0027] Studies have shown that compared with single-channel carrier samples and 2-channel carrier samples, 3-channel carrier samples can significantly increase the number of identified proteins and improve the identification depth, while also ensuring the accuracy of the identification results. However, the more channels there are, the greater the interference of TMT isotope reagent concentration on single-cell samples will be, so the most preferred number of channels is 3.

[0028] Furthermore, the sample size of each channel in the multi-channel Carrier sample in step (1) is 60 cells.

[0029] The sample volume in each channel cannot be too high or too low. Excessive use of carrier samples increases the identification depth of single-cell samples, but affects the accuracy of quantification. The present invention has been shown through research that for multi-channel carrier samples, the optimal sample volume for each channel is 60 times that of a single cell, which has less impact on the accuracy of quantification and can significantly increase the identification depth.

[0030] Furthermore, in step (1), a protein extract solution is added to the sample to be tested and the multi-channel carrier sample, mixed and then incubated; and in step (2), the enzymatic hydrolysis adopts a Trypsin / Lys-C dual enzymatic hydrolysis system.

[0031] The present invention adopts the Trypsin / Lys-C double enzyme digestion system, which can significantly improve the enzyme digestion efficiency and shorten the enzyme digestion time.

[0032] The cleavage sites of Trypsin are arginine (R) and lysine (K), but the cleavage efficiency of R is higher than that of K; the cleavage site of Lys-C is K, which can make up for the defect of low cleavage efficiency of Trypsin on K. At the same time, the cleavage conditions of Trypsin and Lys-C are almost the same, so they can be used together to improve the cleavage efficiency and shorten the cleavage time, which has a synergistic effect.

[0033] Of course, the present invention can also use a single enzyme for enzymolysis, but it is necessary to extend the enzymatic cleavage time or increase the number of enzymatic cleavages.

[0034] Furthermore, steps (1) to (3) are all completed in the same centrifuge tube, and the solvent contains TCEP, CAA, Tris-HCl and TEAB.

[0035] On the other hand, the present invention provides the use of TMT for preparing a labeled preparation that improves the identification depth of proteomic analysis of ultra-trace samples without affecting the quantitative accuracy, wherein the ultra-trace samples contain a multi-channel carrier sample, wherein the multi-channel carrier sample refers to a carrier sample containing more than two channels, wherein the carrier sample contains only one single cell sample, and each carrier sample in the multi-channel carrier sample is placed in a different TMT channel.

[0036] Compared with other labeling reagents, TMT isotope reagents have less influence on purity and are more suitable for using multi-channel carrier samples to ensure the accuracy of identification results.

[0037] In another aspect, the present invention provides a use of a multi-channel carrier sample for preparing an internal reference for proteomic analysis of ultra-trace samples, wherein the multi-channel carrier sample refers to a carrier sample containing more than two channels, and the carrier sample contains only one single cell sample.

[0038] On the other hand, the present invention provides the use of a multi-channel carrier sample for preparing a preparation that improves the identification depth of a single cell sample without affecting the quantitative accuracy, wherein the multi-channel carrier sample refers to a carrier sample containing more than two channels, and the carrier sample contains only one single cell sample.

[0039] The beneficial effects of the present invention are:

[0040] (1) A multi-channel carrier technology has been established, which can increase the amount of carrier samples used and enhance the identification depth of single-cell samples. At the same time, it can reduce or avoid the impact of the carrier channel on single-cell samples without affecting the accuracy of quantification.

[0041] (2) Each channel in the multi-channel Carrier sample contains only one single-cell sample, which can also be used as an internal reference to achieve semi-supervised clustering analysis of ultra-trace samples;

[0042] (3) Each carrier sample is placed in a different TMT channel, and the number of channels of multi-channel carrier samples and the sample volume of each channel are optimized to maximize the identification depth while ensuring the accuracy of the identification results;

[0043] (4) The use of the Trypsin / Lys-C double enzyme digestion system can significantly improve the digestion efficiency and shorten the digestion time. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] Figure 1This is the overall workflow diagram of SCoPE technology;

[0045] Figure 2 is a flow chart of the ultra-trace proteomics analysis method in Example 1 and a schematic diagram comparing it with existing methods;

[0046] Figure 3 The diagrams are result diagrams of data analysis performed using the two methods in Example 1, wherein the left diagram is an unsupervised data analysis result diagram obtained using the existing method, and the right diagram is a semi-supervised data analysis result diagram obtained using the method provided in this example. DETAILED DESCRIPTION

[0047] The preferred embodiments of the present invention are further described in detail below in conjunction with the accompanying drawings. It should be pointed out that the following embodiments are intended to facilitate the understanding of the present invention and do not have any limiting effect on it. All features disclosed in the embodiments of the present invention, or all steps in the methods or processes disclosed, except for mutually exclusive features and / or steps, can be combined in any way.

[0048] Example 1: Ultra-micro proteomics analysis method provided by the present invention

[0049] The flowchart of the ultra-micro proteomics analysis method provided in this embodiment and its comparison with existing methods are as follows: Figure 2 shown.

[0050] The specific process of the ultra-micro proteomics analysis method provided in this embodiment is as follows:

[0051] 1) Single cell sorting: Use flow cytometry to separate cultured A549 cells and Hela cells into a single cell state; for Carrier samples, they are divided into 60 A549 cells and 60 Hela cells respectively;

[0052] 2) Protein extraction: add 1 ul of protein extraction solution (10 mM TCEP, 40 mM CAA, 100 mM Tris-HCl, 0.5 M TEAB, pH 8.0, 1% protease inhibitor (PMSF)) to the sample, mix well and incubate at 95°C for 5 min;

[0053] 3) Enzymatic hydrolysis: For single cell samples, add 10 ng Trypsin / Lys-C and perform enzymatic hydrolysis at 37°C for 60 min; for carrier samples, add 500 ng Trypsin / Lys-C and perform enzymatic hydrolysis at 37°C for 60 min;

[0054] 4) Stable isotope labeling: The peptides were labeled according to the TMT kit operating instructions. The operation was as follows: the labeling reagent was thawed and dissolved in acetonitrile, mixed with the peptides and incubated at room temperature for 1 h. The labeled peptides were mixed and desalted and vacuum freeze-dried;

[0055] 5) C18 desalting: add TFA to a final concentration of 0.1%, vortex thoroughly, centrifuge at 12000g for 10 min, take the supernatant, desalt using a Strata X desalting column or C18 Stagetip, and drain for later use.

[0056] 6) Redissolve with 4ul 0.1% FA and perform mass spectrometry detection.

[0057] In this example, protein extraction, enzymatic hydrolysis and labeling were all completed in the same centrifuge tube.

[0058] The mass spectrometry detection method is as follows: the peptides are dissolved in liquid chromatography mobile phase A (0.1% (v / v) formic acid aqueous solution) and then separated using the EASY-nLC 1000 ultra-high performance liquid phase system. Mobile phase A is an aqueous solution containing 0.1% formic acid and 2% acetonitrile; mobile phase B is an aqueous solution containing 0.1% formic acid and 90% acetonitrile. The liquid phase gradient is set as follows: 0-40min, 9%-26% B; 40-54min, 26%-35% B; 54-57min, 35%-80% B; 57-60min, 80% B, and the flow rate is maintained at 500nL / min. After the peptides are separated by the ultra-high performance liquid phase system, they are injected into the NSI ion source for ionization and then subjected to Q Exactive TMThe peptide precursor ions and their secondary fragments were analyzed by mass spectrometry. The ion source voltage was set to 2.0 kV, and the peptide precursor ions and their secondary fragments were detected and analyzed using a high-resolution Orbitrap. The primary mass spectrometry scan range was set to 350-1800 m / z, and the scan resolution was set to 70,000; the secondary mass spectrometry scan range was fixed at 100 m / z, and the secondary scan resolution was set to 35,000. The data acquisition mode used a data-dependent scan (DDA) program, that is, after the primary scan, the top 10 peptide precursor ions with the highest signal intensity were selected to enter the HCD collision cell in turn and use 28% fragmentation energy for fragmentation, and the secondary mass spectrometry analysis was also performed in turn. In order to improve the effective utilization of the mass spectrometry, the automatic gain control (AGC) was set to 5E4, the signal threshold was set to 20,000 ions / s, the maximum injection time was set to 100 ms, and the dynamic exclusion time of the tandem mass spectrometry scan was set to 30 seconds to avoid repeated scanning of the precursor ions. The secondary mass spectrometry data were retrieved using Maxquant (v1.5.2.8). Search parameter settings: the database is SwissProt Homo sapiens, a reverse library is added to calculate the false positive rate (FDR) caused by random matching, and a common contamination library is added to the database to eliminate the influence of contaminating proteins in the identification results; the enzyme cleavage mode is set to Trypsin / P; the number of missed cleavage sites is set to 2; the minimum length of the peptide is set to 7 amino acid residues; the maximum number of peptide modifications is set to 5; the mass error tolerance of the primary parent ion of the First search and Main search is set to 20ppm and 5ppm respectively, and the mass error tolerance of the secondary fragment ion is 0.02Da. Cysteine ​​alkylation is set as a fixed modification, and the variable modification is methionine oxidation and protein N-terminal acetylation. The FDR of protein identification and PSM identification is set to 1%. The detection method of the effective spectrum ratio: the ratio of "MS / MSIdentified" to "MS / MS" in the summary document of the search result.

[0059] Repeat three times, each time as N1, N2, and N3.

[0060] The mass spectrometry method used in the existing method is the same as that mentioned above.

[0061] Repeat three times, each time as S1, S2, and S3.

[0062] By comparing the existing method with the method provided in this embodiment, it can be seen that:

[0063] 1. The existing method first mixes cells from different sources and places them in only one TMT channel. The actual carrier amount is 50 cells.

[0064] The method of this embodiment divides cells from different sources into 2 TMT channels, each channel contains 60 cells, but the total carrier volume is 100 cells. It can significantly increase the number of proteins identified in single-cell samples. Of course, it is understandable that practical applications are not limited to 2 TMT channels, and this embodiment and flowchart are only examples.

[0065] 2. The existing method only performs data analysis on the TMT channel of one cell (the one cell in the flowchart is random and unknown); the carrier channel is a mixed sample and has no reference value.

[0066] The method of this embodiment analyzes the two carrier channels together, thereby using the known information of the two carrier channels as an internal reference to perform semi-supervised data analysis.

[0067] The analysis results are shown in Table 1, where the recovery rate is calculated as: number of identified proteins / theoretical number of proteins in a human (according to the public database records at https: / / www.uniprot.org / uniprotkb, there are 20,426 known proteins in the human body).

[0068] Table 1. Comparison of analysis results between existing methods and this method

[0069]

[0070] As can be seen from Table 1, by comparing the single-cell sample identification depth results obtained by the two methods, the use of multi-channel Carrier can significantly increase the number of identified proteins compared to single-channel Carrier.

[0071] The results of the two methods of data analysis are as follows Figure 3 As shown, the left figure is the unsupervised data analysis result obtained by the existing method, and the right figure is the semi-supervised data analysis result obtained by the method provided in this embodiment. It can be seen that although the existing method can also achieve classification, it is difficult to clearly determine which type of cell is which. This method can well determine the internal reference coordinates and achieve semi-supervised cell classification and cell type annotation.

[0072] The identification recovery rates of each protein by the two methods were calculated at the same time (relative to the theoretical number of proteins). It can be seen that the identification results obtained by the method provided in this embodiment have a higher identification depth.

[0073] Example 2: Effect of the number of channels of a multi-channel carrier sample on identification accuracy

[0074] In order to evaluate the accuracy of the method, this example compares the existing method and the single cell sample provided by the present invention for methodological verification, and uses the method provided in Example 1 to perform ultra-trace proteomics analysis. The specific channels of the two methods are shown in Table 2.

[0075] Table 2. Channel settings of existing methods and this method

[0076]

[0077] The quantitative CV value (protein quantitative coefficient of variation) of the same single cell is used to characterize the accuracy of quantification. The detection method of the CV value is (a normalized measure of the discrete degree of probability distribution, which is defined as the ratio of the standard deviation (of 3 repeated test results) to the mean): the lower the CV value, the higher the accuracy.

[0078] The identification results are shown in Table 3.

[0079] Table 3. Analysis of identification results of existing methods and this method

[0080]

[0081] It can be seen from Table 3 that compared with the existing methods, this method significantly reduces the CV value and significantly improves the accuracy on the basis of improving the average identification depth of single cells.

[0082] Example 3: Effect of the number of channels of a multi-channel carrier sample on the identification results

[0083] This example uses the method provided in Example 1 to perform an ultra-trace proteomics analysis method, wherein the number of channels of the carrier sample is 1, 2, 3, 4, 5, and 6 (as shown in Table 4, where 1 cell in the table can be a random cell):

[0084] 1. The sample contains only one type of single cell and a carrier sample of one channel;

[0085] 2. The sample contains two types of single cells and two channels of carrier samples (such as Example 1);

[0086] 3. The sample contains three types of single cells and three channels of carrier samples;

[0087] 4. The sample contains four types of single cells and four channels of carrier samples;

[0088] 5. The sample contains five types of single cells and five channels of carrier samples;

[0089] 6. The sample contains five types of single cells and five channels of carrier samples;

[0090] Table 4. Channel quantity settings for Carrier samples

[0091]

[0092] The identification results of proteomic analysis under these six conditions were examined separately, as shown in Table 5.

[0093] Table 5. The impact of the number of channels of multi-channel carrier samples on the identification results

[0094] Number of channels Depth of identification Recovery rate CV value (accuracy) 1 1703 8.3％ 13.4％ 2 2128 10.4％ 10.4％ 3 2563 12.5％ 10.2％ 4 2998 14.6％ 9.9％ 5 3406 16.6％ 10.1％ 6 3896 19.0％ 10.2

[0095] It can be seen from Table 5 that as the number of channels increases, more proteins are identified. However, when the number of channels exceeds 3, it will affect the number of single-cell analyses (because the total number of channels for a single test is limited, the more channels a carrier has, the fewer channels are left for sample testing). Therefore, the most preferred number of channels is 2-3.

[0096] Example 4: Effect of sample volume per channel on identification results

[0097] This example uses the method provided in Example 1 to perform ultra-trace proteomics analysis. The number of channels for carrier samples is 2, and the sample size of each carrier sample is 30, 40, 50, 60, 70, and 80, respectively. The effect of the sample size of each carrier sample on the identification result is investigated. The results are shown in Table 6.

[0098] Table 6. Effect of sample size of each channel on identification results

[0099]

[0100]

[0101] According to Table 3, although too high a sample size of carrier samples improves the identification depth of single-cell samples, it will affect the accuracy of quantification (the lower the CV value, the higher the quantitative accuracy). For multi-channel carrier samples, the most preferred sample size is 60, which can maximize the identification depth of the sample while ensuring accuracy.

[0102] Example 5: Effects of different labeling agents on multi-channel carrier technology

[0103] This example uses the method provided in Example 1 to perform ultra-trace proteomics analysis, wherein the labeling reagents are labeled with TMT or iTRAQ, respectively, to investigate the effects of different labeling reagents on the identification results. The results are shown in Table 7.

[0104] Table 7. Effects of different labeling reagents on multi-channel carrier technology

[0105] Labeling reagents Depth of identification Recovery (Accuracy) TMT 2563 12.5％ iTRAQ 2163 10.6％

[0106] It can be seen from Table 7 that labeling with TMT reagent is more helpful to improve the accuracy of ultra-trace proteomics analysis using multi-channel Carrier technology. The reason may be that the purity of TMT reagent is higher and the impact is smaller.

[0107] The embodiments described above provide a detailed description of the technical solutions of the present invention. It should be understood that the above are only specific embodiments of the present invention and are not intended to limit the present invention. Any modifications, supplements or similar substitutions made within the scope of the principles of the present invention should be included in the protection scope of the present invention.

Claims

1. An ultra-micro proteomics analysis method, characterized in that: The following steps are involved: (1) adding a multi-channel carrier sample to the sample to be tested, wherein the multi-channel carrier sample refers to a carrier sample containing more than two channels, and the carrier sample contains only one single cell sample; (2) Enzymatic hydrolysis; (3) Add labeling reagent for labeling.

2. The method according to claim 1, characterized in that The sample to be tested in step (1) is a single cell sample.

3. The method according to claim 2, characterized in that The labeling reagent in step (3) is TMT; each carrier sample in the multi-channel carrier sample in step (1) is placed in a different TMT channel.

4. The method according to claim 3, characterized in that The number of channels of the multi-channel carrier sample in step (1) is consistent with the number of cell types in the single-cell sample.

5. The method according to claim 4, characterized in that The number of channels of the multi-channel carrier sample in step (1) is 3.

6. The method according to claim 5, characterized in that The sample size of each channel in the multi-channel carrier sample in step (1) is 60 cells.

7. The method according to claim 6, characterized in that In step (1), a protein extract solution is added to the sample to be tested and the multi-channel carrier sample, mixed and then incubated; in step (2), the enzymatic hydrolysis adopts a Trypsin / Lys-C dual enzymatic hydrolysis system.

8. The method according to claim 7, characterized in that The steps (1) to (3) are all completed in the same centrifuge tube, and the solvent contains TCEP, CAA, Tris-HCl and TEAB.

9. Use of multi-channel carrier samples for preparing internal references for proteomics analysis of ultra-trace samples, characterized in that: The multi-channel carrier sample refers to a carrier sample containing more than two channels, and the carrier sample contains only one single cell sample.

10. Use of a multi-channel carrier sample for preparing a preparation that improves the identification depth of a single cell sample without affecting the quantitative accuracy, characterized in that: The multi-channel carrier sample refers to a carrier sample containing more than two channels, and the carrier sample contains only one single cell sample.

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