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1、精品论文A Novel LC-MS/MS Method for Large-scale Detection andQuantification of Widely-targeted MetabolitesLUO Jie, CHEN Wei5(College of Life Science and Technology, Huazhong Agricultural Univeristy, WuHan 430070) Abstract: A novel LC/MS/MS method was establised for the large scale detection and quntific
2、ation of secondary metabolites in plants. The multiple ion monitoring (MIM) scan which served as a survey scan to trigger information-dependent acquisition (IDA) of enhanced product ions (EPI) scan model was carried out to screen metabolites.A modified MIM-EPI strategy, called stepwise scan MIM-EPI1
3、0was adopted, in which Q1 (Q3) was set from 100.1 to 1000.0 Da by positive scan mode, and the mass step is 0.3 Da, such as 100.1/100.1, 100.4/100.4, 100.7/100.7,1000.0/1000.0. This method can beused as a high-throughput and highly sensitive method for the quantification of metabolites, especially se
4、condary metabolites in plants. The method establised in the paper can be used for the metabolomics in plants.15Keywords: LC/MS/MS; MRM; secondary metablism; metabolomics0IntroductionMetabolomics is defined as the analysis of all metabolites in anorganism and simultaneous measurement of all metabolit
5、es in a given biological system1. In the process of getting depth20comprehensive knowledge of plants biological system, metabolomics played an indispensable rolein bridging the phenotypegenotype gap, plant physiology, plant biotechnology and agriculture2-6. With the development of metabolite profili
6、ng technologies suitable for large scale measurement, metabolomics has been emerging as a new omics tool for functional genomics and other studies, and now plays a significant role in fundamental plant biology and applied biotechnology7-8.25However, the technical challenge of processing complex raw
7、GC-MS chromatography data and the need of derivatization for sample preparation have made it less attractive when dealing with large number of samples. Owing to the sensitivity, broad response and speed, LC-MS is a promising alternative to GC-MS as metabolomics tool for the profiling of plant second
8、ary metabolites9-12. In addition to the use in secondary metabolism, recent advance has made it30suitable for the determination of primary metabolites such as amino acids, phospholipids and even some phytohormones, although few method has been developed to measure large number of metabolites of all
9、these different catalogues in one run. In this study, we adopted a new strategy called stepwise-scan MIM-EPI to construct MS2T library for rice leaf. By integration of the data gathered from our MS2T library and other public available MS2T and MRM information, we35developed a new widely targeted met
10、abolomics method in which the relative levels of almost 300 metabolites can be measured simultaneously, including primary metabolites, secondary metabolites and some phytohormones. Natural variations of these metabolites in different varieties from rice core germplasms were evaluated.1Methods401.1 P
11、lant MaterialThe rice plants examined under natural field conditions were grown in normal rice growing seasons in the Experimental Station of Huazhong Agricultural University, Wuhan, China. AllFoundations: Research Fund for the Doctoral Program of Higher Education of China (RFDP) (No.20090146110021)
12、Brief author introduction:LUO Jie, (1971-), Male, Professor, mainly focus on plant secondary metabolism and metabolomics. E-mail: jie.luo- 8 -seeds were planted in a seed bed in mid-May, and transplanted to the field in mid-June. The planting density was 16.5 cm between plants in a row, and the rows
13、 were 26 cm apart. Field45management, including irrigation, fertilizer application and pest control, followed essentially the normal agricultural practice. In 2011, flag leaves were harvested using liquid nitrogen from 3 different plants per line grown in the field for metabolite extraction.1.2 Chem
14、icalsMethanol, Acetonitrile and Acetic Acid used in this study were purchased from Merck50Company, Germany, they are the gradient grade for liquid chromatography. The internal standardLidocaine bought from Shanghai New Asiatic Pharmaceuticals Co., Ltd.1.3Sample Preparation and ExtractionThe freeze-d
15、ried leaves were crushed using a mixer mill (MM 400, Retsch) with a zirconia bead for 1.5 min at 30 Hz, 100mg powder was weighted and extracted with 1.0 ml 70% aqueous55methanol containing 0.1mg/l lidocaine. Following centrifugation at 10, 000g for 10 min, the lipid-solubility extracts were absorbed
16、, 0.4ml of each extract was mixed and filtrated, the sample extracts were served for LC-MS /MS analysis.1.4Metabolite Screening by MIM-EPIThe triple quadrupole-linear ion trap mass spectrometer (Q TRAP) (API 4000 Q TRAP) was60applied to detect metabolites. The multiple ion monitoring (MIM) scan whic
17、h served as a survey scan to trigger information-dependent acquisition (IDA) of enhanced product ions (EPI) scan model was carried out to screen metabolites. MIM scan used a minimal CE (5eV) in Q2 so that metabolite ions isolated in Q1 passed through Q2 with minimal fragmentation. Q3 was monitored a
18、t the same metabolite ions as Q1 instead of fragment ions. A modified MIM-EPI strategy, called65stepwise scan MIM-EPI was adopted, in which Q1 (Q3) was set from 100.1 to 1000.0 Da by positive scan mode, and the mass step is 0.3 Da, such as 100.1/100.1, 100.4/100.4,100.7/100.7,1000.0/1000.0. Each MIM
19、 transition was performed with a 5-ms Dwell time and a5-ms pause time. We monitored each MIM-EPI experiment with 80 MIM transitions, product ions of each metabolite ion were scanned from 50 Da to 1000 Da in Q3, and the total cycle time for one70scan was approximately 1.8s. All together 38 LC/MS runs
20、 were screened.1.5Chromatographic and Mass Spectral ConditionsThe sample extracts were analyzed using an LC-ESI-MS/MS system equipped (HPLC, Shim-pack UFLC shimADZU CBM20A system; MS, Applied Biosystems 4000 Q TRAP). The analytical conditions were as follows. HPLC: column, shim-pack VP-ODS C18 (pore
21、 size 5.0m,75length 2150mm); solvent system, water (0.04% acetic acid): acetonitrile (0.04% acetic acid);gradient program, 100:0 V/V at 0 min, 5:95 V/V at 20.0 min, 5:95 V/V at 22.0 min, 95:5 V/V at22.1 min, 95:5 V/V at 28.0 min; flow rate, 0.25ml/min; temperature, 40. Injection volume, 5l. Informat
22、ion-dependent acquisition (IDA) mode was used to acquire the MS/MS spectra of the metabolites. MS conditions: Ion source, Turbo Spray; source temperature500.0 ; ionspray80voltage (IS) 5500.0V; The ion source gas I (GSI), gas II (GSII),curtain gas (CUR) were set at 55.0,60.0, 25.0 respectively; the c
23、ollision gas (CAD) was high. In the multiple reaction monitoring(MRM) experiment, the declustering potential (DP) was 40.0V, and the collision energy (CE)30.0V; in the Enhanced Product ion (EPI) experiment, the declustering potential (DP) 40.0V, and the collision energy (CE) 40.0V. The mass range wa
24、s from m/z 50 to 1000.852Results2.1Creation of Rice Flag Leaf MS2T LibraryThe triple quadrupole-linear ion trap mass spectrometer (Q TRAP) (API 4000 Q TRAP) was applied to detect metabolites. To take the advantage of the high sensitivity of MIM-EPI for generating the MS2T data of endogenous metaboli
25、tes, a strategy called stepwise-scan MIM-EPI90was adopted (see Methods). The main process showed in Fig. 1 and the details of the procedure were described in Methods. By applying the stepwise scanned MIM-EPI strategy, we obtained more than 8000 signals with MS/MS spectral in total from about 3000 MI
26、M-EPI transitions (data not shown). Real peaks were checked manually, and after redundancy detection by looking for the metabolites with similar retention time (RT) and fragmentation pattern, a MS2T library of about95300 (almost) non-redundant, highly reproducible and high quality (s/n10) MIM-EPI tr
27、ansitionswith the product ion spectra (MS2) and RT were obtained (Fig. 2).MIM scan (Multiple Ion Monitoring)EPI scan (Enhanced Product Ion)IDAcritetiaQ1Q2Q3Q1 Q2 LIT100.1100.410.0.7.1000.0(CE=5eV)7.49100.1100.410.0.7.1000.0100.1100.410.0.7.1000.0(CE=30eV)141.2249.291.0189.17.2 7.5 7.8 8.1Time, min10
28、0 150 200 250 m/z, DaMRM scan (MultipleReaction Monitoring)Using precursor ion and the most abundand product ionPeak annotation MS/MS spectural tags (MS2T Library)Standard compound Literature search Database search MassBankKNAPSAcK MoTo DB METLIN HMDBFig. 1. The main process of mass spectrometer acq
29、uisition method8e+7AIntensity6e+77.144e+72e+709.0716.02 21.060 5 10 15 20 25Time, min4e+6Intensity3e+62e+61e+60B 7.184.860 5 10152025Time, min8e+6Intensity6e+64e+62e+60C165.2299.0329.1448.9100105110115120125200300400 m/z, DaFig. 2. Detection of metabolites by MIM-EPI. (A) TIC of EPI with 80 MIM tran
30、sitions, the mass range from 442.1Da to 459.8 Da. (B) XIC of m/z 449.0/449.0 constructed from the MIM dataset. (C) MS/MS spectra of 449.0 Da detected in 7.18 min, and the metabolite was identified as Luteolin 8-C-glucoside with standard compounds.2.2Metabolite Analysis and IdentificationFor the anno
31、tation of detected metabolites by our widely targeted metbaolomics approach, the retention time and the fragmentation pattern of the commercially available standards were obtained by the same profiling procedure. By comparing the m/z value (unit mass data), the retention time and the fragmentation p
32、attern with the standards, 38 metabolites were indentified, including amino acids, flavonoids, lysoPCs and fatty acid (such as -linolenic acid), and some phytohormones. To facilitate the annotation of the metabolites that couldnt be identified by available standards, peaks in the MS2T library, espec
33、ially the peaks that have similar fragmentation patterns with the metabolites identified by authentic standards, was used to query the MS/MS spectral data taken from the literature or to search the databases (MassBank, KNApSAcK, HMDB, MoTo DB and METLIN). Best matches were then searched in the Dicti
34、onary of Natural products and KEGG for possible structures. More than eighty metabolites were putatively identified, most of them are (C- or O-) glycosylflavonoids, including derivatives of apigenin, luteolin, chrysoeriol, and tricin (Supplemental Table S1). Several flavonolignans,such as tricin 4-O
35、- (erythro - -guaiacylglyceryl) ether and tricin 4-O- (threo - -guaiacylglyceryl) ether were also identified putatively. Most of the metabolites elucidated (identified or putatively annotated) have been reported separately by different targeted metabolic profiling approaches, suggesting the reproduc
36、ibility of the current method (data not shown).2.3High-throughput Quantification of MetabolitesWith the MS2T library created, high-throughput quantification of metabolites was carried out by MRM for widely targeted metabolomics analysis. To produce maximal signal for each130precursor-product ion tra
37、nsition, the most abundant precursor ion and product ion fragmentations for each transition were selected to carry out the MRM scans. In addition to the MRM transitions from the MS2T library, MRM transitions for some phytohormones also included in our method by optimizing the MS conditions using aut
38、hentic standards. Approximately 300 metabolites were quantified simultaneously by MRM in one injection. The detection of more than 60 flavonoids in rice mature leaf was shown in Fig. 3A and 3B and the detection of several phytohormones with authentic standards was shown in Fig. 3C.To evaluate the ab
39、ility of this analytical method to detect and quantify metabolites in biological samples, the following studies were carried out.A4e+53e+5Intensity2e+51e+55.07.09.011.0Time, minB5e+6Intensity4e+63e+62e+61e+67.09.011.0Time, minP8C6e+55e+5Intensity4e+5P3P6P9P11P123e+52e+51e+5P2P4P1P5 P7P10135140Time,
40、minFig. 3. About 70 favonoids detected by MRM. (A) Detection of flavonoids with intensity below 5e+5 cps. (B) Detection of flavonoids with intensity between 5e+5 and 5e+6 cps. (C) 12 phytohormones standards detected by MRM. P1: JA-Met; P2: I5CA; P3: I3CA; P4: BA; P5: SA: P6: IAA; P7: ABA; P8: ICA; P
41、9: JA; P10: NAA; P11: DH-JA; P12: OPDA. 30ng/g of ABA; 30ng/g of JA-Met, BA, SA and NAA; 40ng/g of I5CA, I3CA, IAA, ICA, JA, DH-JA, OPDA were analyzed.1452.4Analysis of Metabolites Accumulation Patterns of Rice Leaf Blade in CoreGermplasm ResourcesWe analysed the metabolite accumulation patterns of
42、rice flag leaves in 38 rice varieties randomly chosen from the core germplasm collections of rice. Clustering analysis clearly grouped these varieties into two distinguish clusters (Fig. 4). All twenty-two varieties in the first cluster are Indica subspecies except Dom Sufid (an Aromatic variety). T
43、he other cluster contains sixteen varieties belong to Japonica subspecies. This result indicates distinct metabotype difference between Indica and Japonica type in O. sativa.Color Key16 18 20 22150R025R030R147R001R033R046R006R040R060R042R010R099R148R105R007R053R024R020R104R012R002R141R057R152R028R15
44、0R034R149R085R054R093R146R011R071R004R023R153m0474 m0821 m0467 m0506 m0864 m0885 m0815 m0507 m0558 m0605 m0814 m0817 m0442 m0644 m0845 m0287m0940 m0917 m0884 m0723 m1091 m0033 m0008 m0781 m0758 m0045SA m0278 m0016 m0809 m0850 m0903 m0832 m0704m0968 m0021 m0476m0736m0505 m0802 m0790 m0898 m0475 m0004
45、 m0472 m0618 m0253 m0706 m0187 m0700 m0114 m0142m0762 m0926 m1021 m0584 m0958 m0634 m0780m0003m0761 m0854 m0439 m0005 m0754 m0530 m0946 m0921 m0895 m0887m0911 m0819 m0793 m0689 m0509 m0058 m0017 m0076 m0590 m0727 m0411m0071m0057 m0835 m1096 m0186 m0659 m0542m0535 m0639 m1046 m0718 m0616 m0446 m0716 m0113 m0092 m0001 m0441 m0503 m0010 m0915 m0937 m0042m0123 m1083m0247 m0741 m0705 m0691 m0687 m0424 m0873 m0977 m1042 m0775 m1082IA AAsp m1069 m0932 m1013 m0966 m0769 m0543 m0900I3CA CA m10
