Exploiting the kernel trick to correlate fragment ions for peptide identification via tandem mass spectrometry

Fu, Yan; Yang, Qiang; Sun, Rui-Xiang; Li, Dequan; Zeng, Rong; Ling, Charles X.; Gao, Wen

doi:10.1093/bioinformatics/bth186

Cited by 108 publications

(99 citation statements)

References 22 publications

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“…In all of the experiments, the most widely used software for peptide identification, Mascot (version 2.2) (7), was used to identify the spectra. Two other search engines, SEQUEST (version 2.7) (6) and pFind (version 2.6) (8,26,27), were additionally used to demonstrate the linearity of the ␥ k ͑x͒ function (Fig. 1).…”

Section: Resultsmentioning

confidence: 99%

Transferred Subgroup False Discovery Rate for Rare Post-translational Modifications Detected by Mass Spectrometry

Qian

2014

Molecular & Cellular Proteomics

122

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In shotgun proteomics, high-throughput mass spectrometry experiments and the subsequent data analysis produce thousands to millions of hypothetical peptide identifications. The common way to estimate the false discovery rate (FDR) of peptide identifications is the target-decoy database search strategy, which is efficient and accurate for large datasets. However, the legitimacy of the target-decoy strategy for protein-modification-centric studies has rarely been rigorously validated. It is often the case that a global FDR is estimated for all peptide identifications including both modified and unmodified peptides, but that only a subgroup of identifications with a certain type of modification is focused on. As revealed recently, the subgroup FDR of modified peptide identifications can differ dramatically from the global FDR at the same score threshold, and thus the former, when it is of interest, should be separately estimated. However, rare modifications often result in a very small number of modified peptide identifications, which makes the direct separate FDR estimation inaccurate because of the inadequate sample size. This paper presents a method called the transferred FDR for accurately estimating the FDR of an arbitrary number of modified peptide identifications. Through flexible use of the empirical data from a targetdecoy database search, a theoretical relationship between the subgroup FDR and the global FDR is made computable. Through this relationship, the subgroup FDR can be predicted from the global FDR, allowing one to avoid an inaccurate direct estimation from a limited amount of data. The effectiveness of the method is demonstrated with both simulated and real mass spectra. Molecular & Cellular

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Section: Resultsmentioning

confidence: 99%

Transferred Subgroup False Discovery Rate for Rare Post-translational Modifications Detected by Mass Spectrometry

Qian

2014

Molecular & Cellular Proteomics

122

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“…Supernatant was analyzed by LC/MS-MS using an Orbitrap Elite high-resolution mass spectrometer. MS-MS spectra were searched against the human database using pFind software (21).…”

Section: Immunoprecipitationmentioning

confidence: 99%

Triptolide Induces Cell Killing in Multidrug-Resistant Tumor Cells via CDK7/RPB1 Rather than XPB or p44

Huan

Song

et al. 2016

Molecular Cancer Therapeutics

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Multidrug resistance (MDR) is a major cause of tumor treatment failure; therefore, drugs that can avoid this outcome are urgently needed. We studied triptolide, which directly kills MDR tumor cells with a high potency and a broad spectrum of cell death. Triptolide did not inhibit P-glycoprotein (P-gp) drug efflux and reduced P-gp and MDR1 mRNA resulting from transcription inhibition. Transcription factors including c-MYC, SOX-2, OCT-4, and NANOG were not correlated with triptolide-induced cell killing, but RPB1, the largest subunit of RNA polymerase II, was critical in mediating triptolide's inhibition of MDR cells. Triptolide elicited antitumor and anti-MDR activity through a universal mechanism: by activating CDK7 by phosphorylating Thr170 in both parental and MDR cell lines and in SK-OV-3 cells. The CDK7-selective inhibitor BS-181 partially rescued cell killing induced by 72-hour treatment of triptolide, which may be due to partial rescue of RPB1 degradation. We suggest that a precise phosphorylation site on RPB1 (Ser1878) was phosphorylated by CDK7 in response to triptolide. In addition, XPB and p44, two transcription factor TFIIH subunits, did not contribute to triptolide-driven RPB1 degradation and cell killing, although XPB was reported to covalently bind to triptolide. Several clinical trials are underway to test triptolide and its analogues for treating cancer and other diseases, so our data may help expand potential clinical uses of triptolide, as well as offer a compound that overcomes tumor MDR. Future investigations into the primary molecular target(s) of triptolide responsible for RPB1 degradation may suggest novel anti-MDR target(s) for therapeutic development.

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“…The highest-scoring site is considered the modification site. The scoring function used here is the one employed by the pFind search engine (7). Obviously, the accuracy of peptide propagation relies on both the accuracy of input peptide identifications and the reliability of detected spectral pairs.…”

Section: Methodsmentioning

confidence: 99%

DeltAMT: A Statistical Algorithm for Fast Detection of Protein Modifications From LC-MS/MS Data

Xiu

Jia

et al. 2011

Molecular & Cellular Proteomics

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Identification of proteins and their modifications via liquid chromatography-tandem mass spectrometry is an important task for the field of proteomics. However, because of the complexity of tandem mass spectra, the majority of the spectra cannot be identified. The presence of unanticipated protein modifications is among the major reasons for the low spectral identification rate. The conventional database search approach to protein identification has inherent difficulties in comprehensive detection of protein modifications. In recent years, increasing efforts have been devoted to developing unrestrictive approaches to modification identification, but they often suffer from their lack of speed. This paper presents a statistical algorithm named DeltAMT (Delta Accurate Mass and Time) for fast detection of abundant protein modifications from tandem mass spectra with high-accuracy precursor masses. The algorithm is based on the fact that the modified and unmodified versions of a peptide are usually present simultaneously in a sample and their spectra are correlated with each other in precursor masses and retention times. By representing each pair of spectra as a delta mass and time vector, bivariate Gaussian mixture models are used to detect modification-related spectral pairs. Unlike previous approaches to unrestrictive modification identification that mainly rely upon the fragment information and the mass dimension in liquid chromatography-tandem mass spectrometry, the proposed algorithm makes the most of precursor information. Thus, it is highly efficient while being accurate and sensitive. On two published data sets, the algorithm effectively detected various modifications and other interesting events, yielding deep insights into the data. Based on these discoveries, the spectral identification rates were significantly increased and many modified peptides were identified. Molecular & Cellular Proteomics 10: 10.1074/ mcp.M110.000455, 1-15, 2011.Liquid chromatography coupled with tandem mass spectrometry (LC-MS/MS) 1 is currently the predominant technology used to identify proteins and their modifications (1-3). The most successful approach for interpreting tandem mass spectra involves searching the database of known protein sequences (4 -9). Other approaches include the databaseindependent de novo peptide sequencing (10 -13) and the hybrid sequence tag-based approach (14 -16). However, in a typical shotgun proteomics experiment, only ϳ10 -30% of the tandem mass spectra can be successfully identified, and the remaining majority is discarded (17). Many factors contribute to the complexity of protein digests and the low identification rate of tandem mass spectra (18). Understanding the origin and identity of the unidentified spectra is of great importance in expanding our knowledge about biological systems and sample processing protocols. Nesvizhskii et al. (19) have shown that by properly mining the unidentified spectra, insights can be gained that are of interest to biologists, such as identification of post-transl...

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Exploiting the kernel trick to correlate fragment ions for peptide identification via tandem mass spectrometry

Abstract: http://www.jdl.ac.cn/user/yfu/pfind/index.html

Cited by 108 publications

References 22 publications

Transferred Subgroup False Discovery Rate for Rare Post-translational Modifications Detected by Mass Spectrometry

Transferred Subgroup False Discovery Rate for Rare Post-translational Modifications Detected by Mass Spectrometry

Triptolide Induces Cell Killing in Multidrug-Resistant Tumor Cells via CDK7/RPB1 Rather than XPB or p44

DeltAMT: A Statistical Algorithm for Fast Detection of Protein Modifications From LC-MS/MS Data

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