UniNovo : A Universal Tool for de Novo Peptide Sequencing

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 PepNovoþ, 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). Availability: UniNovo is implemented in JAVA and tested on Windows, Ubuntu and OS X machines. UniNovo is available at http://proteomics. ucsd.edu/Software/UniNovo.html along with the manual.

Algorithms and design strategies towards automated glycoproteomics analysis

“…Given an unmodified peptide with perfect fragmentation (high coverage and few spurious peaks), the peptide sequence can be assembled immediately by connecting the product ion pairs whose mass difference matches the mass value of certain Comparison on spectra level SEQUEST (Eng et al 1994) • Compares experimental spectra with theoretical spectra through cross-correlation function Comet (Eng et al 2013) • Academic (open-source) version of SEQUEST • Optimized for high resolution tandem mass spectra • Support multiple fragmentation types (HCD, ETD, and CID) • Probability-based scoring (cumulative binomial distribution) • Included in SearchGUI and node in Proteome Discover Universal MS-GF+ (Kim and Pevzner, 2014) • Support for data from multiple fragmentation methods, multiple enzyme digestion, and phosphoproteomics • Bioconductor, SearchGUI de novo sequencing Naïve approach PEAKS (Zhang, Xin, et al 2012) • Widely used commercial tool for de novo sequencing • Generates consensus sequences based on comparison of experimental spectrum with a large pool of randomly sampled sequences • Now a full-featured software suite for proteomics study Spectrum graph (dynamic programming) pNovo+ (Chi et al 2012) • Integrates complementary HCD and ETD spectral information. • pDAG algorithm looking for the top k longest paths • 0.018s for sequencing / spectrum pepNovo+ (Frank 2009a) • Boosting-based PSM ranking algorithm integrating multiple PSM features UniNovo (Jeong et al 2013) • Independent of specific spectral type • Estimates the probability that a constructed sequence is correct Novor (Ma 2015) • Currently the fastest sequencing tool for de novo searches • Contains two large decision trees built from NIST • Open source windows client for targeted proteomics methods creation • Supports creation and use of tandem MS spectral libraries amino acid residue, which is actually independent of the size of the overall sequence space. As the consistent improvement of instrument accuracy and experimental design, researchers are gradually approaching the ideal data quality required for de novo sequencing.…”

Bacterial Electron Transfer Chains Primed by Proteomics

“…This spectrum is easily interpreted, but manual interpretation of fragmentation spectra is challenging and time-consuming in general since each spectral peak in the MS n spectrum can be any of the expected fragment ion types (eg, b-or y-ion). The processing of large tandem MS data sets is facilitated by de novo sequencing software programmes (Allmer, 2011), including PEAKS (Zhang et al, 2012), Lutefisk (Taylor & Johnson, 1997), PepNovo (Frank & Pevzner, 2005), NovoHMM (Pevtsov, Fedulova, Mirzaei, Buck, & Zhang, 2006), AUDENS (Grossmann et al, 2005), Novor (Ma, 2015), Sherenga (Dancik, Addona, Clauser, Vath, & Pevzner, 1999), UniNovo (Jeong, Kim, & Pevzner, 2013) and pNovo + (Chi, Chen, et al, 2013). In these programmes, high-throughput automated interpretation of MS 2 spectra is supported by different algorithms.…”

Proteogenomics from a bioinformatics angle: A growing field

“…These have been successfully applied in many proteogenomics studies, especially for non‐model species where a comprehensive genome annotation is still unavailable or incomplete. Multiple tools to derive these partial sequence stretches or complete de novo sequences are available:, e.g., PepNovo+ (Frank & Pevzner, ), DirecTag (Tabb et al, ) (both bundled in a graphical user interface called DenovoGui (Muth et al, )) and UniNovo (Jeong et al, ). Special about the latter is that it can cope with all types of fragmentation (CID, ETD and/or HCD).…”