An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts.
An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts.
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DOI:
10.1021/acs.jproteome.7b00061
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发表时间:
2017-07-07
影响因子:
4.4
通讯作者:
Qu J
中科院分区:
文献类型:
--
作者:
Shen X;Shen S;Li J;Hu Q;Nie L;Tu C;Wang X;Orsburn B;Wang J;Qu J
In-depth and reproducible protein measurement in many biological samples is often critical for pharmaceutical/biomedical proteomics but remains challenging. MS1-based quantification using quadrupole/ultrahigh-field Orbitrap (Q/UHF-Orbitrap) holds great promise, but the critically important experimental approaches enabling reliable large-cohort analysis have long been overlooked. Here we described an IonStar experimental strategy achieving excellent quantitative quality of MS1 quantification. Key features include: (i) an optimized, surfactant-aided sample preparation approach provides highly efficient (>75% recovery) and reproducible (<15% CV) peptide recovery across large cell/tissue cohorts; (ii) a long column with modest gradient length (2.5 h) yields the optimal balance of depth/throughput on a Q/UHF-Orbitrap; (iii) a large-ID trap not only enables highly reproducible gradient delivery as for the first time observed via real-time conductivity monitoring, but also increases quantitative loading capacity by >8-fold and quantified >25% more proteins; (iv) an optimized HCD-OT markedly outperforms HCD-IT when analyzing large cohorts with high loading amounts; (v) selective removal of hydrophobic/hydrophilic matrix components using a novel selective trapping/delivery approach enables reproducible, robust LC–MS analysis of >100 biological samples in a single set, eliminating batch effect; (vi) MS1 acquired at higher resolution (fwhm = 120 k) provides enhanced S/N and quantitative accuracy/precision for low-abundance species. We examined this pipeline by analyzing a 5 group, 20 samples biological benchmark sample set, and quantified 6273 unique proteins (≥2 peptides/protein) under stringent cutoffs without fractionation, 6234 (>99.4%) without missing data in any of the 20 samples. The strategy achieved high quantitative accuracy (3–6% media error), low intragroup variation (6–9% media intragroup CV) and low false-positive biomarker discovery rates (3–8%) across the five groups, with quantified protein abundances spanning >6.5 orders of magnitude. Finally, this strategy is straightforward, robust, and broadly applicable in pharmaceutical/biomedical investigations.
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影响因子:
64.8
作者:
Kim, Min-Sik;Pinto, Sneha M.;Getnet, Derese;Nirujogi, Raja Sekhar;Manda, Srikanth S.;Chaerkady, Raghothama;Madugundu, Anil K.;Kelkar, Dhanashree S.;Isserlin, Ruth;Jain, Shobhit;Thomas, Joji K.;Muthusamy, Babylakshmi;Leal-Rojas, Pamela;Kumar, Praveen;Sahasrabuddhe, Nandini A.;Balakrishnan, Lavanya;Advani, Jayshree;George, Bijesh;Renuse, Santosh;Selvan, Lakshmi Dhevi N.;Patil, Arun H.;Nanjappa, Vishalakshi;Radhakrishnan, Aneesha;Prasad, Samarjeet;Subbannayya, Tejaswini;Raju, Rajesh;Kumar, Manish;Sreenivasamurthy, Sreelakshmi K.;Marimuthu, Arivusudar;Sathe, Gajanan J.;Chavan, Sandip;Datta, Keshava K.;Subbannayya, Yashwanth;Sahu, Apeksha;Yelamanchi, Soujanya D.;Jayaram, Savita;Rajagopalan, Pavithra;Sharma, Jyoti;Murthy, Krishna R.;Syed, Nazia;Goel, Renu;Khan, Aafaque A.;Ahmad, Sartaj;Dey, Gourav;Mudgal, Keshav;Chatterjee, Aditi;Huang, Tai-Chung;Zhong, Jun;Wu, Xinyan;Shaw, Patrick G.;Freed, Donald;Zahari, Muhammad S.;Mukherjee, Kanchan K.;Shankar, Subramanian;Mahadevan, Anita;Lam, Henry;Mitchell, Christopher J.;Shankar, Susarla Krishna;Satishchandra, Parthasarathy;Schroeder, John T.;Sirdeshmukh, Ravi;Maitra, Anirban;Leach, Steven D.;Drake, Charles G.;Halushka, Marc K.;Prasad, T. S. Keshava;Hruban, Ralph H.;Kerr, Candace L.;Bader, Gary D.;Iacobuzio-Donahue, Christine A.;Gowda, Harsha;Pandey, Akhilesh
通讯作者:
Pandey, Akhilesh
DOI:
10.1074/mcp.m113.034769
发表时间:
2014-01
期刊:
Molecular & cellular proteomics : MCP
影响因子:
--
作者:
Hebert AS;Richards AL;Bailey DJ;Ulbrich A;Coughlin EE;Westphall MS;Coon JJ
通讯作者:
Coon JJ
DOI:
10.1074/mcp.m111.011015
发表时间:
2011-09
期刊:
Molecular & cellular proteomics : MCP
影响因子:
--
作者:
Michalski A;Damoc E;Hauschild JP;Lange O;Wieghaus A;Makarov A;Nagaraj N;Cox J;Mann M;Horning S
通讯作者:
Horning S
影响因子:
3.3
作者:
Lott K;Li J;Fisk JC;Wang H;Aletta JM;Qu J;Read LK
通讯作者:
Read LK
影响因子:
82.9
作者:
通讯作者:
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