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ABSTRACT: 2-Amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (PhIP) is a heterocyclic aromatic amine that is formed during the cooking of meats. PhIP is a potential human carcinogen: it undergoes metabolic activation to form electrophilic metabolites that bind to DNA and proteins, including serum albumin (SA). The structures of PhIP-SA adducts formed in vivo are unknown and require elucidation before PhIP protein adducts can be implemented as biomarkers in human studies. We previously examined the reaction of genotoxic N-oxidized metabolites of PhIP with human SA in vitro and identified covalent adducts formed at cysteine(34) (Cys(34)); however, other adduction products were thought to occur. We have now identified adducts of PhIP formed at multiple sites of SA reacted with isotopic mixtures of electrophilic metabolites of PhIP and 2-amino-1-methyl-6-[(2)H(5)]-phenylimidazo[4,5-b]pyridine ([(2)H(5)]-PhIP). The metabolites used for study were 2-nitro-1-methyl-6-phenylimidazo[4,5-b]pyridine (NO(2)-PhIP), 2-hydroxyamino-1-methyl-6-phenylimidazo[4,5-b]pyridine (HONH-PhIP), or N-acetyloxy-2-amino-1-methyl-6-phenylimidazo[4,5-b]pyridine (N-acetoxy-PhIP). Following proteolytic digestion, PhIP-adducted peptides were separated by ultra performance liquid chromatography and characterized by ion trap mass spectrometry, employing isotopic data-dependent scanning. Analysis of the tryptic or tryptic/chymotryptic digests of SA modified with NO(2)-PhIP revealed that adduction occurred at Cys(34), Lys(195), Lys(199), Lys(351), Lys(541), Tyr(138), Tyr(150), Tyr(401), and Tyr(411), whereas the only site of HONH-PhIP adduction was detected at Cys(34). N-Acetoxy-PhIP, a penultimate metabolite of PhIP that reacts with DNA to form covalent adducts, did not appear to form stable adducts with SA; instead, PhIP and 2-amino-1-methyl-6-(5-hydroxy)-phenylimidazo[4,5-b]pyridine, an aqueous reaction product of the proposed nitrenium ion of PhIP, were recovered during the proteolysis of N-acetoxy-PhIP-modified SA. Some of these SA adduction products of PhIP may be implemented in molecular epidemiology studies to assess the role of well-done cooked meat, PhIP, and the risk of cancer.
Chemical Research in Toxicology 07/2012; 25(10):2179-93. · 3.78 Impact Factor
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ABSTRACT: LC-MS/MS-based proteomics studies rely on stable analytical system performance that can be evaluated by objective criteria. The National Institute of Standards and Technology (NIST) introduced the MSQC software to compute diverse metrics from experimental LC-MS/MS data, enabling quality analysis and quality control (QA/QC) of proteomics instrumentation. In practice, however, several attributes of the MSQC software prevent its use for routine instrument monitoring. Here, we present QuaMeter, an open-source tool that improves MSQC in several aspects. QuaMeter can directly read raw data from instruments manufactured by different vendors. The software can work with a wide variety of peptide identification software for improved reliability and flexibility. Finally, QC metrics implemented in QuaMeter are rigorously defined and tested. The source code and binary versions of QuaMeter are available under Apache 2.0 License at http://fenchurch.mc.vanderbilt.edu.
Analytical Chemistry 06/2012; 84(14):5845-50. · 5.86 Impact Factor
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ABSTRACT: Spectral libraries have emerged as a viable alternative to protein sequence databases for peptide identification. These libraries contain previously detected peptide sequences and their corresponding tandem mass spectra (MS/MS). Search engines can then identify peptides by comparing experimental MS/MS scans to those in the library. Many of these algorithms employ the dot product score for measuring the quality of a spectrum-spectrum match (SSM). This scoring system does not offer a clear statistical interpretation and ignores fragment ion m/z discrepancies in the scoring. We developed a new spectral library search engine, Pepitome, which employs statistical systems for scoring SSMs. Pepitome outperformed the leading library search tool, SpectraST, when analyzing data sets acquired on three different mass spectrometry platforms. We characterized the reliability of spectral library searches by confirming shotgun proteomics identifications through RNA-Seq data. Applying spectral library and database searches on the same sample revealed their complementary nature. Pepitome identifications enabled the automation of quality analysis and quality control (QA/QC) for shotgun proteomics data acquisition pipelines.
Journal of Proteome Research 01/2012; 11(3):1686-95. · 5.11 Impact Factor
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ABSTRACT: The standard shotgun proteomics data analysis strategy relies on searching MS/MS spectra against a context-independent protein sequence database derived from the complete genome sequence of an organism. Because transcriptome sequence analysis (RNA-Seq) promises an unbiased and comprehensive picture of the transcriptome, we reason that a sample-specific protein database derived from RNA-Seq data can better approximate the real protein pool in the sample and thus improve protein identification. In this study, we have developed a two-step strategy for building sample-specific protein databases from RNA-Seq data. First, the database size is reduced by eliminating unexpressed or lowly expressed genes according to transcript quantification. Second, high-quality nonsynonymous coding single nucleotide variations (SNVs) are identified based on RNA-Seq data, and corresponding protein variants are added to the database. Using RNA-Seq and shotgun proteomics data from two colorectal cancer cell lines SW480 and RKO, we demonstrated that customized protein sequence databases could significantly increase the sensitivity of peptide identification, reduce ambiguity in protein assembly, and enable the detection of known and novel peptide variants. Thus, sample-specific databases from RNA-Seq data can enable more sensitive and comprehensive protein discovery in shotgun proteomics studies.
Journal of Proteome Research 11/2011; 11(2):1009-17. · 5.11 Impact Factor
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David L Tabb,
Lorenzo Vega-Montoto,
Paul A Rudnick,
Asokan Mulayath Variyath,
Amy-Joan L Ham,
David M Bunk,
Lisa E Kilpatrick,
Dean D Billheimer,
Ronald K Blackman,
Helene L Cardasis, [......],
Susan J Fisher,
Bradford W Gibson,
Christopher R Kinsinger,
Mehdi Mesri,
Henry Rodriguez,
Stephen E Stein,
Paul Tempst,
Amanda G Paulovich,
Daniel C Liebler,
Cliff Spiegelman
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ABSTRACT: The complexity of proteomic instrumentation for LC-MS/MS introduces many possible sources of variability. Data-dependent sampling of peptides constitutes a stochastic element at the heart of discovery proteomics. Although this variation impacts the identification of peptides, proteomic identifications are far from completely random. In this study, we analyzed interlaboratory data sets from the NCI Clinical Proteomic Technology Assessment for Cancer to examine repeatability and reproducibility in peptide and protein identifications. Included data spanned 144 LC-MS/MS experiments on four Thermo LTQ and four Orbitrap instruments. Samples included yeast lysate, the NCI-20 defined dynamic range protein mix, and the Sigma UPS 1 defined equimolar protein mix. Some of our findings reinforced conventional wisdom, such as repeatability and reproducibility being higher for proteins than for peptides. Most lessons from the data, however, were more subtle. Orbitraps proved capable of higher repeatability and reproducibility, but aberrant performance occasionally erased these gains. Even the simplest protein digestions yielded more peptide ions than LC-MS/MS could identify during a single experiment. We observed that peptide lists from pairs of technical replicates overlapped by 35-60%, giving a range for peptide-level repeatability in these experiments. Sample complexity did not appear to affect peptide identification repeatability, even as numbers of identified spectra changed by an order of magnitude. Statistical analysis of protein spectral counts revealed greater stability across technical replicates for Orbitraps, making them superior to LTQ instruments for biomarker candidate discovery. The most repeatable peptides were those corresponding to conventional tryptic cleavage sites, those that produced intense MS signals, and those that resulted from proteins generating many distinct peptides. Reproducibility among different instruments of the same type lagged behind repeatability of technical replicates on a single instrument by several percent. These findings reinforce the importance of evaluating repeatability as a fundamental characteristic of analytical technologies.
Journal of Proteome Research 11/2009; 9(2):761-76. · 5.11 Impact Factor
