Comparing Top-Down Proteoform Identification: Deconvolution, PrSM Overlap, and PTM Detection.
Comparing Top-Down Proteoform Identification: Deconvolution, PrSM Overlap, and PTM Detection.
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比较自上而下的蛋白质相识别:反卷积,PRSM重叠和PTM检测。
DOI:
10.1021/acs.jproteome.2c00673
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发表时间:
2023-07-07
影响因子:
4.4
通讯作者:
Chamot-Rooke, Julia
中科院分区:
文献类型:
--
作者:
Tabb, David L.;Jeong, Kyowon;Druart, Karen;Gant, Megan S.;Brown, Kyle A.;Nicora, Carrie;Zhou, Mowei;Couvillion, Sneha;Nakayasu, Ernesto;Williams, Janet E.;Peterson, Haley K.;McGuire, Michelle K.;McGuire, Mark A.;Metz, Thomas O.;Chamot-Rooke, Julia
关键词:
Generating top-down tandem mass spectra (MS/MS) from complex mixtures of proteoforms benefits from improvements in fractionation, separation, fragmentation, and mass analysis. The algorithms to match MS/MS to sequences have undergone a parallel evolution, with both spectral alignment and match-counting approaches producing high-quality proteoform-spectrum matches (PrSMs). This study assesses state-of-the-art algorithms for top-down identification (ProSight PD, TopPIC, MSPathFinderT, and pTop) in their yield of PrSMs while controlling false discovery rate. We evaluated deconvolution engines (ThermoFisher Xtract, Bruker AutoMSn, Matrix Science Mascot Distiller, TopFD, and FLASHDeconv) in both ThermoFisher Orbitrap-class and Bruker maXis Q-TOF data (PXD033208) to produce consistent precursor charges and mass determinations. Finally, we sought post-translational modifications (PTMs) in proteoforms from bovine milk (PXD031744) and human ovarian tissue. Contemporary identification workflows produce excellent PrSM yields, although approximately half of all identified proteoforms from these four pipelines were specific to only one workflow. Deconvolution algorithms disagree on precursor masses and charges, contributing to identification variability. Detection of PTMs is inconsistent among algorithms. In bovine milk, 18% of PrSMs produced by pTop and TopMG were singly phosphorylated, but this percentage fell to 1% for one algorithm. Applying multiple search engines produces more comprehensive assessments of experiments. Top-down algorithms would benefit from greater interoperability.
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影响因子:
14.9
作者:
Harshman SW;Young NL;Parthun MR;Freitas MA
通讯作者:
Freitas MA
影响因子:
--
作者:
Holman JD;Ma ZQ;Tabb DL
通讯作者:
Tabb DL
影响因子:
4.4
作者:
Peng Y;Chen X;Zhang H;Xu Q;Hacker TA;Ge Y
通讯作者:
Ge Y
DOI:
10.1016/j.jasms.2007.01.010
发表时间:
2007-05-01
影响因子:
3.2
作者:
Falkner, Jayson A.;Kachman, Maureen;Andrews, Philip C.
通讯作者:
Andrews, Philip C.
影响因子:
7
作者:
Frottin, Frederic;Martinez, Aude;Meinnel, Thierry
通讯作者:
Meinnel, Thierry