pFind Studio: a computational solution for mass spectrometry-based proteomics
2013 or earlier
2013 IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE (BIBM)2013. 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 spectrum graph model with multiple types of edges (called a multi-edge graph), and integrate amino acid combination (AAC) information and peptide tags into it for peptide sequencing. In addition, the information about immoniun ions observed particularly in higher-energy collisional dissociation (HCD) spectra are incorporated. Comparisons between the proposed method and another successful de novo peptide sequencing method for HCD spectra, pNovo, were performed. Experiments were conducted on four HCD spectral datasets. Results show that the proposed method outperforms pNovo in terms of full length peptide identification accuracy; specifically, the accuracy increases 7%-13% over all four datasets.
Use: pNovo
Bioinformatics2013. Jeong, K et al.
Univ Calif San Diego, Dept Elect & Comp Engn, San Diego, CA 92093 USA.
ABSTRACT:Motivation: Mass spectrometry (MS) instruments and experimental protocols are rapidly advancing, but de novo peptide sequencing algorithms to analyze tandem mass (MS/MS) spectra are lagging behind. Although existing de novo sequencing tools perform well on certain types of spectra [e.g. Collision Induced Dissociation (CID) spectra of tryptic peptides], their performance often deteriorates on other types of spectra, such as Electron Transfer Dissociation (ETD), Higher-energy Collisional Dissociation (HCD) spectra or spectra of non-tryptic digests. Thus, rather than developing a new algorithm for each type of spectra, we develop a universal de novo sequencing algorithm called UniNovo that works well for all types of spectra or even for spectral pairs (e.g. CID/ETD spectral pairs). UniNovo uses an improved scoring function that captures the dependences between different ion types, where such dependencies are learned automatically using a modified offset frequency function. Results: The performance of UniNovo is compared with PepNovo+, PEAKS and pNovo using various types of spectra. The results show that the performance of UniNovo is superior to other tools for ETD spectra and superior or comparable with others for CID and HCD spectra. UniNovo also estimates the probability that each reported reconstruction is correct, using simple statistics that are readily obtained from a small training dataset. We demonstrate that the estimation is accurate for all tested types of spectra (including CID, HCD, ETD, CID/ETD and HCD/ETD spectra of trypsin, LysC or AspN digested peptides).
Use: pNovo
Journal of Proteome Research2011. Paradela, A et al.
CSIC, Ctr Nacl Biotecnol, Dept Biotecnol Microbiana, Madrid, Spain.
ABSTRACT:The RcsC, RcsD, and RcsB proteins compose a system used by enteric bacteria to sense envelope stress. Signal transmission occurs from the sensor RcsC to the transcriptional regulator RcsB. Accessory proteins, such as IgaA, are known to adjust the response level. In a previous transcriptomic study, we uncovered 85 genes differentially expressed in Salmonella enterica serovar Typhimurium igaA mutants. Here, we extended these observations to proteomics by performing differential isotope-coded protein labeling (ICPL) followed by liquid chromatography-electrospray ionization tandem mass spectrometry. Five-hundred five proteins were identified and quantified, with 75 of them displaying significant changes in response to alterations in the RcsCDB system. Divergent expression at the RNA and protein level was observed for the metabolic genes pckA and metE, involved in gluconeogenesis and methionine synthesis, respectively. When analyzed in diverse environmental conditions, including the intracellular niche of eukaryotic cells, inverse regulation was more evident for metE and in bacteria growing in defined minimal medium or to stationary phase. The RcsCDB system was also shown to repress the synthesis of the small RNA FnrS, previously reported to modulate metE expression. Collectively, these findings provide new insights into post-transcriptional regulatory mechanisms involving the RcsCDB system and its control over metabolic functions.
Use: pScan