Assessment of TMT Labeling Efficiency in Large-Scale Quantitative Proteomics: The Critical Effect of Sample pH.
Assessment of TMT Labeling Efficiency in Large-Scale Quantitative Proteomics: The Critical Effect of Sample pH.
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DOI:
10.1021/acsomega.1c00776
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发表时间:
2021-05-18
期刊:
影响因子:
4.1
通讯作者:
Adkins JN
中科院分区:
文献类型:
--
作者:
Hutchinson-Bunch C;Sanford JA;Hansen JR;Gritsenko MA;Rodland KD;Piehowski PD;Qian WJ;Adkins JN
Isobaric labeling via tandem mass tag (TMT) reagents enables sample multiplexing prior to LC–MS/MS, facilitating high-throughput large-scale quantitative proteomics. Consistent and efficient labeling reactions are essential to achieve robust quantification; therefore, embedded in our clinical proteomic protocol is a quality control (QC) sample that contains a small aliquot from each sample within a TMT set, referred to as “Mixing QC.” This Mixing QC enables the detection of TMT labeling issues by LC–MS/MS before combining the full samples to allow for salvaging of poor TMT labeling reactions. While TMT labeling is a valuable tool, factors leading to poor reactions are not fully studied. We observed that relabeling does not necessarily rescue TMT reactions and that peptide samples sometimes remained acidic after resuspending in 50 mM HEPES buffer (pH 8.5), which coincided with low labeling efficiency (LE) and relatively low median reporter ion intensities (MRIIs). To obtain a more resilient TMT labeling procedure, we investigated LE, reporter ion missingness, the ratio of mean TMT set MRII to individual channel MRII, and the distribution of log 2 reporter ion ratios of Mixing QC samples. We discovered that sample pH is a critical factor in LE, and increasing the buffer concentration in poorly labeled samples before relabeling resulted in the successful rescue of TMT labeling reactions. Moreover, resuspending peptides in 500 mM HEPES buffer for TMT labeling resulted in consistently higher LE and lower missing data. By better controlling the sample pH for labeling and implementing multiple methods for assessing labeling quality before combining samples, we demonstrate that robust TMT labeling for large-scale quantitative studies is achievable.
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影响因子:
14.8
作者:
Mertins P;Tang LC;Krug K;Clark DJ;Gritsenko MA;Chen L;Clauser KR;Clauss TR;Shah P;Gillette MA;Petyuk VA;Thomas SN;Mani DR;Mundt F;Moore RJ;Hu Y;Zhao R;Schnaubelt M;Keshishian H;Monroe ME;Zhang Z;Udeshi ND;Mani D;Davies SR;Townsend RR;Chan DW;Smith RD;Zhang H;Liu T;Carr SA
通讯作者:
Carr SA
影响因子:
48
作者:
Mertins, Philipp;Qiao, Jana W.;Patel, Jinal;Udeshi, Namrata D.;Clauser, Karl R.;Mani, D. R.;Burgess, Michael W.;Gillette, Michael A.;Jaffe, Jacob D.;Carr, Steven A.
通讯作者:
Carr, Steven A.
影响因子:
64.5
作者:
Zhang H;Liu T;Zhang Z;Payne SH;Zhang B;McDermott JE;Zhou JY;Petyuk VA;Chen L;Ray D;Sun S;Yang F;Chen L;Wang J;Shah P;Cha SW;Aiyetan P;Woo S;Tian Y;Gritsenko MA;Clauss TR;Choi C;Monroe ME;Thomas S;Nie S;Wu C;Moore RJ;Yu KH;Tabb DL;Fenyö D;Bafna V;Wang Y;Rodriguez H;Boja ES;Hiltke T;Rivers RC;Sokoll L;Zhu H;Shih IM;Cope L;Pandey A;Zhang B;Snyder MP;Levine DA;Smith RD;Chan DW;Rodland KD;CPTAC Investigators
通讯作者:
CPTAC Investigators
影响因子:
7.4
作者:
Thompson, A;Schäfer, J;Hamon, C
通讯作者:
Hamon, C
影响因子:
12.3
作者:
Budnik B;Levy E;Harmange G;Slavov N
通讯作者:
Slavov N