CN111220690A - Direct mass spectrometry detection method for low-abundance protein posttranslational modification group - Google Patents
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Abstract
The invention relates to a mass spectrum detection method for a low-abundance protein posttranslational modification group based on simulated targeting. The method comprises the steps of firstly, selecting potential, low-abundance and low-reliability posttranslational modified polypeptides in a sample and constructing a target list by using an identification result obtained by a data-dependent mass spectrum acquisition mode; and then a parallel reaction monitoring mode in a targeted proteome technology is used, so that the mass spectrum detection interference of other high-abundance proteins and polypeptides is effectively eliminated, the accumulation degree of the low-abundance modified peptide fragment in the mass spectrum is improved, and the high-flux and high-sensitivity detection of the target peptide fragment is realized. The method realizes the one-stop screening, enrichment and identification online analysis process of the modified peptide fragment in the mass spectrum based on the mass spectrum targeting technology, does not need complex sample pre-enrichment, can avoid sample loss caused by a multi-step sample pretreatment process, and combines the screening effect of high-resolution mass spectrum to carry out high-sensitivity and high-reliability detection on the modified peptide fragment in a trace complex sample.
Description
Technical Field
The invention belongs to the field of mass spectrum acquisition methods in proteomics research directions, and particularly relates to a data-dependent mass spectrum data acquisition method based on a discovery mode and a parallel reaction monitoring mass spectrum data acquisition technology based on a targeting mode, wherein online analysis of low-abundance peptide fragments and phosphopeptides in a trace complex biological sample can be realized without enrichment treatment.
Background
The shotgun method is a mainstream method for proteomics research at present, a complex proteome sample is firstly enzymolyzed into a peptide fragment mixture by enzyme (mainly trypsin), then a one-dimensional or multi-dimensional separation technology is used for separating an enzymolysis product, and a tandem mass spectrum is used for collecting and detecting a Data Dependent Acquisition (DDA) mode; the obtained tandem mass spectrometry spectrum was used to identify proteins by matching peptides by database search (document 1.Yates, J.R., the recommendation and Evolution of Shotgun Proteomics for Large-Scale protein analysis. J Am ChemSoC,2013,135(5), 1629-. However, this method has a problem that the complexity of the sample increases exponentially as complex proteome samples are enzymatically digested to form a peptide fragment mixture. Therefore, a large number of redundant peptide fragments derived from high-abundance proteins will interfere with the collection and detection of low-abundance peptide fragments (reference 2.Nahnsen, s.; Kohlbacher, o.bmc Bioinformatics 2012, 13.). In addition, in the conventional Data Dependent Acquisition (DDA) mode, a Full scan of multiple parent ions eluted simultaneously can be performed on a Full scan of a Full scan, and then the most abundant relative few or more than ten parent ions are sent to a collision cell for fragmentation and fragment ion secondary spectrum acquisition (ref 3.Peterson, a.c.; Russell, j.d.; Bailey, d.j.; westphal, m.s.; Coon, j.j.molecular & cellular proteomics 2012,11, 1475-. Therefore, the data-dependent acquisition mode tends to be high in abundance, and is unfavorable for acquisition of low-abundance peptide fragments.
Many specific enrichment methods for different properties of target peptides have been developed to eliminate the interference of high-abundance redundant peptides on the identification of low-abundance peptides. For example, a peptide fragment that is post-translationally modified can be enriched from a large number of redundant unmodified peptide fragments by virtue of its hydrophilicity and the property of varying charge number. For example, immobilized metal ion affinity chromatography specifically enriches phosphorylated peptide fragments (reference 4.Zhou, H.; Ye M.; Dong, J.; Corradini, E.; Cristabal, A.; Heck, A.J.; Zou, H.; Mohammed, S.Nature protocols 2013,8, 461-. Hydrophilic interaction chromatography enriches glycosylated modified peptides (ref 5.Selman, M.H.; Hemayattkar, M.; Delader, A.M.; Wuhrer, M.anal Chem 2011,83, 2492-. However, the above mentioned sample pre-enrichment methods usually require a relatively large initial amount of sample (>100 μ g), and are not applicable for certain micro biological samples (<10 μ g) which are difficult to obtain. In order to solve the problems, a quasi-target mass spectrum acquisition strategy is provided, and a mass spectrum data dependent acquisition method (DDA) based on a discovery mode is combined with a target proteome method parallel reaction monitoring technology (PRM). And (3) performing library search on data acquired by the DDA by using proteome identification software, and identifying a series of peptide fragments and score values thereof, wherein the score values of the peptide fragments are related to the matching degree of the acquired secondary spectrum and a theoretical spectrogram. Many low abundance peptides have a low score because of their low relative abundance in the sample, which results in a low probability of being sent to the collision cell and subsequent tandem mass spectrometry analysis. Therefore, some real low-abundance peptide fragments exist in the low-score region, and the identification of the low-abundance peptide fragments can be effectively improved by extracting corresponding liquid phase/mass spectrum information (chromatographic retention time, mass and charge number) of the low-score peptide fragments as a potential analysis target and analyzing the low-score peptide fragments in a targeted manner in the mass spectrum analysis process. Parallel reaction monitoring detection (PRM) is a high-resolution and high-sensitivity targeted proteome method, which has the advantages that a peptide fragment target to be analyzed can be preset and a target peptide fragment can be selectively accumulated in the process of mass spectrum acquisition (6. Bourmaud, A.; Gallien, S.; Domon, B. proteomics 2016,16, 2146-. In addition, compared with Multiple Reaction Monitoring (MRM), ion pairs (one parent ion corresponds to 3-5 daughter ions) need to be preset, PRM can acquire all fragment ion information of a target peptide fragment only by presetting the parent ion (a peptide fragment of interest), which provides a basis for subsequent proteome identification software retrieval (document 7.Sherman, J.; McKay, M.J.; Ashman, K.; Molloy, M.P. proteomics 2009,9, 1120-.
The invention combines the advantages of a proteome discovery mode and a targeting mode, and develops a quasi-targeting proteome method for identifying low-abundance peptide fragments from trace samples in real time without sample pretreatment. Potential low-abundance peptide fragments are searched through data-dependent acquired data, and chromatographic and mass spectrum characteristic information of the peptide fragments is extracted to form a simulated target list to be verified. Finally, peptide fragments in a simulated target set are selectively enriched in a mass spectrum by a target proteome PRM method, richer fragment ion information is obtained, and finally the enriched fragment ion information is used for searching by proteome identification software to obtain an identification result. By the quasi-target mass spectrum method, a large number of high-abundance peptide fragments which are fully identified can be eliminated, potential low-abundance peptide fragments can be analyzed at high sensitivity, a complex sample pretreatment process is not needed, the time cost of sample preparation is saved, and the sample loss is greatly reduced.
Disclosure of Invention
The invention aims to develop a simple, convenient, efficient and high-sensitivity simulated target mass spectrum method for low-abundance peptide fragments in a trace complex sample.
The method for directly detecting the low-abundance protein, the low-abundance polypeptide and the post-translational modified peptide fragment thereof by using the analog targeted proteomics technology improves the detection sensitivity and the reliability of the identification of the low-abundance peptide fragment without the sample pretreatment steps such as enrichment and the like.
According to the identification method of the quasi-target proteome low-abundance peptide fragment, provided by the invention, the low-credible peptide fragment identified by a conventional shotgun method is used as a simulation target by combining shotgun proteomics and a target proteome method, the target peptide fragment is accumulated on line by using the target protein composition method, and the low-abundance peptide fragment can be simultaneously enriched and identified without sample pretreatment.
The invention adopts the following technical scheme:
(1) taking a trypsin enzymolysis freeze-dried peptide fragment sample to be redissolved by 0.1% formic acid, and carrying out RPLC-MS/MS analysis. Injecting 1 mu g of peptide fragment sample, effective gradient range is 5% -45% acetonitrile, and effective gradient time is 30-70 minutes. Mass spectrometer instrument type: a combined mass spectrum containing quadrupole rods and electrostatic field orbitrap. Mass spectrum acquisition mode: collecting parameters of Full MS-ddMS mass spectrum, Full MS resolution, 30000-; AGC target,1e 5-5e 6; max IT, 10-100 ms; ddMS Mass Spectrometry acquisition parameters: resolution, 15000-; AGC target,5e4-5e 6; max IT,20-100 ms; loop count, 1-80; isolation window,0.5-2.0 m/z; NCE,23-35.
(2) Using a proteome database of a corresponding source species as a background library, the mass spectrum data collected in (1) is searched in proteome identification software MASCOT and a score of the identified peptide fragment is obtained. Setting parameters: peptidecolelance 5-20 ppm; MS/MS tolerance 0.001-0.500 Da; enzyme: trypsin; miss clearance: modification, namely one or more than two of Phosphorylation, Methylation and Acetylation;
(3) and (3) generating a new database by using the protein identified in the step (2), using the new database as a background protein database, and performing database searching software again. And obtaining a series of peptide fragment identification results and score values.
(4) And (4) extracting the chromatographic Retention Time (RT), the mass (M), the charge number (Z), the sequence information (Ssequence) and the like of the peptide fragment with the score value lower than 40 in the step (3) to generate a target set which is used as a simulated target for subsequent analysis.
(5) And (5) taking the simulated target peptide fragment list obtained in the step (4) as a target to be analyzed, importing the target to a mass spectrum acquisition method setting file, and editing to form the target acquisition method. Mass spectrum acquisition mode: full MS-PRM; full MS parameter setting: resolution30000-60000, AGC target1e 5-5e6, Max IT 10-100 ms; setting PRM parameters: resolution 15000-; loop count, 1-80; isolation window,0.5-2.0 m/z; NCE,23-35.
(6) And (3) searching the mass spectrum data acquired in the step (5) by using proteome identification software, and setting parameters to be the same as those in the step (2).
Drawings
FIG. 1 is a conceptual diagram of a quasi-target mass spectrometry method of low-abundance peptide fragments in the complex proteome sample. Extracting low-credibility peptide fragment information acquired in a data dependent mode (DDA) to generate a target list (inclusion list), and performing in-mass spectrum on-line accumulation and fragmentation on the target peptide fragment in a targeted proteomics parallel reaction monitoring mode, thereby realizing high-sensitivity identification of the low-abundance peptide fragment.
Fig. 2a shows that after the quasi-target mass spectrometry method is used for collection, the score of most peptide fragments is increased, thereby demonstrating that the quasi-target mass spectrometry method developed herein can effectively improve the identification of low-abundance peptide fragments in a complex sample system. The fragment ions obtained by the peptide fragment with the sequence of APFGSPSAEAVSSR in the conventional shotgun method are few, the Score of the peptide fragment given after database retrieval is low (Score: 6), and the reliability is low. After the collection by the quasi-target mass spectrum method, fragment ions are rich, and the Score value given by database retrieval software is greatly improved (Score: 34).
FIG. 3 is a graph comparing conventional data-dependent acquisition patterns (DDA) with phosphorylation sites identified by a simulated target mass spectrometry method (PRM) developed by the present method.
Detailed Description
The invention is further illustrated by the following examples, which are not intended to limit the scope of the invention.
Example 1
The method for analyzing the low-abundance peptide fragment in the microsystem is used for analyzing the phosphoproteomics of the co-immunoprecipitation sample:
(1) taking 6ug of a human EGFR protein complex sample, dissolving the 6ug in 20 mu L of 50mM HEPES buffer solution (pH 8.0), adding 0.06 mu g of trypsin, and carrying out enzymolysis for 16h in 37-degree water bath;
(2) adding 100 μ L of 3% formic acid (v/v), centrifuging at 20000g, recovering supernatant, and lyophilizing with centrifugal concentrating drier;
(3) lyophilized peptide fragment samples were reconstituted with 40 μ L of 0.1% formic acid (v/v) and analyzed by RPLC-MS/MS. Injecting 6 mu L of peptide fragment sample, and carrying out liquid phase mobile phase A phase of 0.1% formic acid (v/v), 80% acetonitrile (v/v), effective gradient range of 5% -45% B phase, and effective gradient time of 30-70 minutes. Mass spectrometer: q-active hf mass spectrum acquisition mode: full MS resolution, 60000, Mass Spectrometry acquisition parameters; AGC target,5e 6; max IT, 30 ms; ddMS Mass Spectrometry acquisition parameters: resolution, 15000; AGC target,1e 5; max IT,55 ms; loop count, 25; isolation window,1.6 m/z; NCE, 27;
(4) combining the mass spectrum data collected in (3) with a human proteome database, analyzing by using a proteome identification software MASOCT and obtaining a protein identification result. Setting parameters: 10ppm of peptide tolerance; MS/MStolerance 0.02 Da; modification: phosphorus (STY), oxidation (M); enzyme: trypsin; misclean: 2.
(5) generating a new database of the proteins identified in (4), and performing the MASCOT analysis again by using the proteome identification software. Obtaining a series of peptide fragment identification results, wherein the peptide fragment identification results comprise peptide fragment sequences, mass, charge number, chromatographic retention time, credibility score values and the like;
(6) extracting information such as chromatographic Retention Time (RT), mass (M), charge number (Z), sequence information (Ssequence) and the like of the phosphorylated peptide segment with the score value lower than 40 in the step (5) to generate a target set which is used as a simulated target list for subsequent analysis;
(7) and (4) importing the simulated target peptide fragment list obtained in the step (6) into a mass spectrum parameter setting file, and editing the target mass spectrum acquisition method. Mass spectrum acquisition mode: full MS-PRM; full MS parameter setting: resolution 360000, AGC target1e6, Max IT 50 ms; setting ddMS parameters: resolution 15000, AGC target1e 5, Max IT 247 ms; loop count, 45; isolation window,1.6 m/z; NCE, 27;
(8) and (4) performing peptide fragment and spectrogram matching on the mass spectrum data acquired in the step (7) by using proteome identification software. The parameter setting is the same as (4).
FIG. 2a is a comparison of the identification result of phosphorylated peptide fragments identified by the method with the identification result of a common shotgun method. Through the treatment of the method, scoring values of most target peptide fragments are greatly improved, wherein a large part of the scoring values are predicted phosphorylated peptide fragments, which shows that the simulation target analysis method can enrich and identify low-abundance target peptide fragments on line in the mass spectrometry process, and improve fragment ion information of the low-abundance target peptide fragments, thereby improving identification number and reliability.
FIG. 2b is a comparison of fragment ion information and score values of a phosphorylated peptide segment of sequence SPFGS (p) PSAEAVSSR before and after treatment according to the method of the present invention. As can be seen from the figure, the fragment ions of the peptide fragment are few under the shotgun method; after the treatment of the method, the fragment ion information of the phosphorylated peptide segment becomes extremely rich, more peptide segment information is provided for database retrieval, and therefore the score value of the phosphorylated peptide segment is increased from 6 to 34.
FIG. 3 is a graph comparing conventional data-dependent acquisition patterns (DDA) with phosphorylation sites identified by a simulated target mass spectrometry method (PRM) developed by the present method. As can be seen from the figure, 43 phosphorylation sites can be identified by combining the three-needle DDA acquisition results, 17 new sites can be additionally identified by using the simulated target mass spectrometry method, the reproducibility of the two methods is good, and the overlap of the three internal acquired data is high. Using our developed simulated targeted mass spectrometry approach, the identification of phosphorylation sites was improved by about 40%.
Table 1 shows that the method provided by the invention is applied to co-immunoprecipitation protein complexes under different stimulation states, and the result shows that the application of the simulated targeting method can greatly improve the low-abundance phosphorylation modification identification. In the group with the most phosphorylation stimulation, the simulated targeting method can improve identification by up to 50% compared to the conventional data-dependent acquisition pattern.
TABLE 1
In conclusion, the invention is a high-sensitivity analysis method for low-abundance peptide fragments in a microsystem, based on the combination of two mass spectrum acquisition modes of data-dependent acquisition and targeted analysis, and complex sample pretreatment and enrichment steps are not needed, and screening, enrichment, fragmentation and acquisition can be carried out in a one-stop manner in the mass spectrum acquisition process. The method has small demand on sample amount and low requirement on sample pretreatment, so that the sample loss is greatly reduced, and the high-sensitivity identification of the low-abundance peptide fragment can be realized only by a few micrograms of peptide fragment samples.
Claims (6)
1. A direct mass spectrometric detection method for a post-translational modification group of low-abundance proteins is characterized by comprising the following steps: a method for directly detecting low-abundance proteins, polypeptides and post-translational modified peptide fragments thereof by using a simulated targeted proteomics technology is characterized by comprising the following steps of:
(1) constructing a target list of target peptide fragments: acquiring data of enzymolysis peptide segments in a proteolysis sample by using a data-dependent mass spectrum scanning mode, and retrieving by proteomics database searching software to obtain a series of polypeptide identification results with scoring values; dividing the peptide fragments into a high credibility interval and a low credibility interval according to the score, selecting low-abundance peptide fragments and post-translational modified peptide fragments in the low credibility interval, and constructing a target peptide fragment target list;
(2) identification of a target list of target peptide fragments: by utilizing the target recognition function of the mass spectrum, the peptide fragment in the target list of the target peptide fragment is specifically cracked and subsequently scanned, so that the proteolysis polypeptide and the post-translational modification peptide in the list can be cracked and scanned, and the interference of the high-abundance non-target peptide fragment can be effectively avoided; the method obtains a high-quality peptide fragment spectrogram, and uses proteomics library searching software for retrieval, thereby remarkably improving the identification reliability and identification number of low-abundance peptide fragments and post-translational modified peptide fragments in the sample.
2. The method of claim 1, wherein:
the process of step (1):
1) carrying out in-situ protein enzymolysis (including but not limited to one or more of pancreatin, pepsin and the like) on a protein sample, desalting, and freeze-drying the sample;
2) performing mass spectrum scanning of a data-dependent mode on an enzymolysis sample, using a proteome database of a sample source species as a background protein database, searching the database by using proteome identification software (such as MASCOT), using all identified proteins as a new background protein database, and reusing the new database as the background protein database to perform software database searching;
3) selecting low-abundance peptide segments and post-translational modified peptide segments in a low-confidence interval, and constructing a target peptide segment target list; dividing the identification result into two credibility intervals of high and low according to the database searching result; the division of the credible interval can be adjusted according to the requirements of actual samples; when the number of fragment ions matched with the peptide segment given by the library searching software is less than 5, the peptide segment can be regarded as a low-abundance peptide segment, when the fragment ions at the modification site of the post-translational modified peptide segment are identified in a missing manner, the post-translational modified peptide segment can be regarded as a low-credibility peptide segment, and one or more than two peptide segments in the conditions can be divided into low-credibility intervals; and extracting retention time, mass, charge number, sequence information and the like of the peptide fragment in the low-confidence interval, and constructing a target list containing the peptide fragment in the low-confidence interval for subsequent target confirmation.
3. The method of claim 1, wherein:
the step (2) process:
1) importing the constructed target peptide fragment target list into a mass spectrometer acquisition method, and establishing a parallel reaction monitoring acquisition method containing a preset target peptide fragment list; carrying out one-stop analysis steps of screening, accumulating, fragmenting, collecting and the like on an enzymolysis peptide fragment sample subjected to chromatographic separation in a mass spectrum by a preset parallel reaction monitoring method;
when the mass spectrum scans peptide fragment parent ions which accord with information in a preset target list in a first-stage spectrum full scan, the peptide fragment parent ions which accord with conditions are accumulated in a quadrupole, and then a target peptide fragment is sent to a collision pool for fragmentation and then sent to an electrostatic field orbit trap for high resolution scanning and corresponding fragment ion secondary spectrum acquisition;
2) the acquired spectrogram is searched by proteomics database searching software again to obtain a peptide fragment identification result, so that the interference of high-abundance protein enzymolysis peptide fragments is avoided, the accumulation time of the target peptide fragments in the mass spectrum is prolonged, low-credible peptide fragments in a preset target list are specifically screened, enriched and identified, and the identification sensitivity or the identification efficiency of the low-abundance peptide fragments and the post-translational modified peptide fragments is improved.
4. The method of claim 2, wherein:
the low abundance peptide fragment comprises one or more than two of the conditions that the amount of the peptide fragment substances is less than 0.1 picomole, the ionization efficiency of the peptide fragment is less than 50 percent, the fragmentation efficiency of the peptide fragment is less than 50 percent and the like;
the source of the post-translational modified peptide segment comprises but is not limited to one or more of post-translational modifications such as phosphorylation, methylation, acetylation, and the like on the peptide segment;
the relative abundance of the peptide fragments in a complex proteome sample is low, so that mass spectrum signals are weak, the result identified by a common method is likely to be poor due to the interference of high-abundance proteins, and the reliability is low; therefore, the conventional proteomics method cannot realize high-sensitivity and high-reliability detection;
the proteome identification software comprises one or more than two of MASCOT, protein discovery, MaxQuant, Pflag and other software.
5. The method of claim 3, wherein: identifying a target list of the low-reliability peptide fragment and the post-translational modified peptide fragment;
aiming at the peptide segment with low reliability and the post-translational modification peptide segment in the target list, the pretreatment steps such as sample enrichment and the like are not needed, so that the loss of the sample can be reduced, the artificial error introduced in the operation process can be avoided, and the reliability of the identification and analysis of the sample can be improved; and for the peptide fragment collected and identified in the targeting mode, the integral sum of the response intensities of all fragment ions can be used as a quantitative basis for comparing the quantitative difference of the target peptide fragment among different samples;
the proteome identification software comprises one or more than two of MASCOT, protein discovery, MaxQuant, Pflag and other software.
6. The method of claim 1, wherein:
(1) taking a proteolysis sample (the sample species source includes but is not limited to a human source), and performing RPLC-MS/MS analysis:
mass spectrum acquisition mode: collecting parameters of Full MS-ddMS mass spectrum, Full MS resolution, 30000-; AGCtarget, 1e5-5e 6; max IT, 10-100 ms; ddMS Mass Spectrometry acquisition parameters: resolution, 15000-; AGCtarget,5e4-5e 6; max IT,20-100 ms; loop count, 1-80; isolation window,0.5-2.0 m/z; NCE, 23-35;
(2) using a proteome database of a source species corresponding to the protein as a background library, searching the mass spectrum data acquired in the step (1) in proteome identification software MASCOT and obtaining a score of identified peptide fragments; setting parameters: peptide tolerance 5-20 ppm; MS/MS tolerance 0.001-0.500 Da; enzyme: trypsin; misclean: 0 to 3; modification, one or more of Phosphorylation, Methylation and Acetylation;
(3) generating the protein identified in the step (2) into a new database, using the new database as a background protein database, and searching database searching software again; obtaining a series of peptide fragment identification results and scores;
(4) extracting the chromatographic Retention Time (RT), the mass (M), the charge number (Z), the sequence information (Ssequence) and the like of the peptide fragment with the score value lower than 40 in the step (3) to generate a target set which is used as a simulation target for subsequent analysis;
(5) taking the simulated target peptide fragment list obtained in the step (4) as a target to be analyzed, importing the target to a mass spectrum acquisition method setting file, and editing to form a target acquisition method; mass spectrum acquisition mode: full MS-PRM; full MS parameter setting: resolution30000-60000, AGC target1e 5-5e6, Max IT 10-100 ms; setting PRM parameters: resolution 15000-; loop count, 1-80; isolation window,0.5-2.0 m/z; NCE, 23-35;
(6) and (3) searching the mass spectrum data acquired in the step (5) by using proteome identification software, and setting parameters in the same step (2).
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| CN113567533A (en) * | 2021-07-22 | 2021-10-29 | 上海市口腔医院(上海市口腔健康中心) | Quantitative detection method of plant histone variant H3.3 based on MRM |
| CN113687003A (en) * | 2021-09-14 | 2021-11-23 | 谱天（天津）生物科技有限公司 | Method for improving identification number of protein and/or peptide fragment group mass spectrum |
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