pFind Studio: a computational solution for mass spectrometry-based proteomics
2014
BIOCHIMICA ET BIOPHYSICA ACTA-GENE REGULATORY MECHANISMS2014. Zhao, L et al.
Beijing Inst Radiat Med, 27 Taiping Rd, Beijing 100850, Peoples R China.
ABSTRACT:Hepatocyte nuclear factor-1 alpha (HNF1 alpha) exerts important effects on gene expression in multiple tissues. Several studies have directly or indirectly supported the role of phosphorylation processes in the activity of HNF1 alpha. However, the molecular mechanism of this phosphorylation remains largely unknown. Using microcapillary liquid chromatography MS/MS and biochemical assays, we identified a novel phosphorylation site in HNF1 alpha at Ser249. We also found that the ATM protein kinase phosphorylated HNF1 alpha at Ser249 in vitro in an ATM-dependent manner and that ATM inhibitor KU55933 treatment inhibited phosphorylation of HNF1 alpha at Ser249 in vivo. Coimmunoprecipitation assays confirmed the association between HNF1 alpha and ATM. Moreover, ATM enhanced HNF1 alpha transcriptional activity in a dose-dependent manner, whereas the ATM kinase-inactive mutant did not. The use of KU55933 confirmed our observation. Compared with wild-type HNF1 alpha, a mutation in Ser249 resulted in a pronounced decrease in HNF1 alpha transactivation, whereas no dominant-negative effect was observed. The HNF1 alpha Ser249 mutant also exhibited normal nuclear localization but decreased DNA-binding activity. Accordingly, the functional studies of HNF1 alpha Ser249 mutant revealed a defect in glucose metabolism. Our results suggested that ATM regulates the activity of HNF1 alpha by phosphorylation of serine 249, particularly in glucose metabolism, which provides valuable insights into the undiscovered mechanisms of ATM in the regulation of glucose homeostasis. (C) 2014 Elsevier B.V. All rights reserved.
Use: pXtract
Journal of Molecular Cell Biology2014. Su, ZD et al.
Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Biochem & Cell Biol, Key Lab Syst Biol, Shanghai 200031, Peoples R China.
ABSTRACT:The detection of single amino-acid variants (SAVs) usually depends on single-nucleotide polymorphisms (SNPs) database. Here, we describe a novel method that discovers SAVs at proteome level independent of SNPs data. Using mass spectrometry-based de novo sequencing algorithm, peptide-candidates are identified and compared with theoretical protein database to generate SAVs under pairing strategy, which is followed by database re-searching to control false discovery rate. In human brain tissues, we can confidently identify known and novel protein variants with diverse origins. Combined with DNA/RNA sequencing, we verify SAVs derived from DNA mutations, RNA alternative splicing, and unknown post-transcriptional mechanisms. Furthermore, quantitative analysis in human brain tissues reveals several tissue-specific differential expressions of SAVs. This approach provides a novel access to high-throughput detection of protein variants, which may offer the potential for clinical biomarker discovery and mechanistic research.
Use: pNovo
IEEE Transactions on Nanobioscience2014. Yan, Y et al.
Univ Saskatchewan, Div Biomed Engn, Saskatoon, SK S7N 5A9, Canada.
ABSTRACT:In recent years, de novo peptide sequencing from mass spectrometry data has developed as one of the major peptide identification methods with the emergence of new instruments and advanced computational methods. However, there are still limitations to this method; for example, the typically used spectrum graph model cannot represent all the information and relationships inherent in tandem mass spectra (MS/MS spectra). Here, we present a new method named NovoHCD which applies a spectrum graph model with multiple types of edges (called a multi-edge graph), and integrates into it amino acid combination (AAC) information and peptide tags. In addition, information on immonium ions observed particularly in higher-energy collisional dissociation (HCD) spectra is incorporated. Comparisons between NovoHCD and another successful de novo peptide sequencing method for HCD spectra, pNovo, were performed. Experiments were conducted on five HCD spectral datasets. Results show that NovoHCD outperforms pNovo in terms of full length peptide identification accuracy; specifically, the accuracy increases 13%-21% over the five datasets.
Use: pNovo
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS2014. Yan, Y et al.
Univ Saskatchewan, Div Biomed Engn, Saskatoon, SK S7N 5A9, Canada.
ABSTRACT:De novo peptide sequencing using tandem mass spectrometry (MS/MS) data has become a major computational method for sequence identification in recent years. With the development of new instruments and technology, novel computational methods have emerged with enhanced performance. However, there are only a few methods focusing on ECD/ETD spectra, which mainly contain variants of c-ions and z-ions. Here, a de novo sequencing method for ECD/ETD spectra, NovoExD, is presented. NovoExD applies a new form of spectrum graph with multiple edge types (called a GMET), considers multiple peptide tags, and integrates amino acid combination (AAC) and fragment ion charge information. Its performance is compared with another successful de novo sequencing method, pNovo+, which has an option for ECD/ETD spectra. Experiments conducted on three different datasets show that the average full length peptide identification accuracy of NovoExD is as high as 88.70 percent, and that NovoExD's average accuracy is more than 20 percent greater on all datasets than that of pNovo+.
Use: pNovo
IEEE Transactions on Nanobioscience2014. Yan, Y et al.
Univ Saskatchewan, Div Biomed Engn, Saskatoon, SK S7N 5A9, Canada.
ABSTRACT:In recent years, de novo peptide sequencing from mass spectrometry data has developed as one of the major peptide identification methods with the emergence of new instruments and advanced computational methods. However, there are still limitations to this method; for example, the typically used spectrum graph model cannot represent all the information and relationships inherent in tandem mass spectra (MS/MS spectra). Here, we present a new method named NovoHCD which applies a spectrum graph model with multiple types of edges (called a multi-edge graph), and integrates into it amino acid combination (AAC) information and peptide tags. In addition, information on immonium ions observed particularly in higher-energy collisional dissociation (HCD) spectra is incorporated. Comparisons between NovoHCD and another successful de novo peptide sequencing method for HCD spectra, pNovo, were performed. Experiments were conducted on five HCD spectral datasets. Results show that NovoHCD outperforms pNovo in terms of full length peptide identification accuracy; specifically, the accuracy increases 13%-21% over the five datasets.
Use: pNovo
Journal of Proteome Research2014. Ma, CWM et al.
Hong Kong Univ Sci & Technol, Div Biomed Engn, Hong Kong, Hong Kong, Peoples R China.
ABSTRACT:Discovering novel post-translational modifications (PTMS) to proteins and detecting specific modification sites on proteins is one of the last frontiers of proteomics. At present, hunting for post-translational modifications remains challenging in widely practiced shotgun proteomics workflows due to the typically low abundance of modified peptides and the greatly inflated search space as more potential mass shifts are considered by the search engines. Moreover, most popular search methods require that the user specifies the modification(s) for which to search; therefore, unexpected and novel PTMs will not be detected. Here a new algorithm is proposed to apply spectral library searching to the problem of open modification searches, namely, hunting for PTMs without prior knowledge of what PTMs are in the sample. The proposed tier-wise scoring method intelligently looks for unexpected PTMs by allowing mass-shifted peak matches but only when the number of matches found is deemed statistically significant. This allows the search engine to search for unexpected modifications while maintaining its ability to identify unmodified peptides effectively at the same time. The utility of the method is demonstrated using three different data sets, in which the numbers of spectrum identifications to both unmodified and modified peptides were substantially increased relative to a regular spectral library search as well as to another open modification spectral search method, pMatch.
Use: pMatch