Valence Parity to Distinguish c′ and z• Ions from Electron Capture Dissociation/Electron Transfer Dissociation of Peptides: Effects of Isomers, Isobars, and Proteolysis Specificity

Lys-Sequencer: An algorithm for de novo sequencing of peptides by paired single residue transposed Lys-C and Lys-N digestion coupled with high-resolution mass spectrometry

RATIONALE

Database-dependent identification of proteins by mass spectrometry is well established, but has limitations when there are novel proteins, mutations, splice variants, and post-translational modifications (PTMs) not available in the established reference database. De novo sequencing as a database-independent approach could address these limitations by deducing peptide sequences directly from experimental tandem mass spectrometry spectra, while concomitantly yielding residue-by-residue confidence metrics.

METHODS

Equal amounts of bovine serum albumin (BSA) sample aliquots were digested separately with Lys-C and Lys-N complementary peptidases, separated by reversed-phase ultra-high-performance liquid chromatography (UPLC), and analyzed by collision-induced dissociation (CID)-based mass spectrometry on an Orbitrap mass spectrometer. In the Lys-Sequencer algorithm, matched tandem mass spectra with equal precursor ion mass from complementary digestions were paired, and fragment ion types were identified based on the unique mass relationship between fragment ions extracted from a spectrum pair followed by de novo sequencing of peptides with identification confidence assigned at the residue level.

RESULTS

In all the matched spectrum pairs, 34 top-ranked BSA peptides were identified, from which 391 amino acid residues were identified correctly, covering ~67% of the full sequence of BSA (583 residues) with only ~6% (35 residues) exhibiting ambiguity in the sequence order (although amino acid compositions were still correctly assigned). Of note, this approach identified peptide sequences up to 17 amino acids in length without ambiguity, with the exception of the N-terminal or C-terminal peptides containing lysine (18-mer).

CONCLUSIONS

The algorithm ("Lys-Sequencer") developed in this work achieves high precision for de novo sequencing of peptides. This method facilitates the identification of point mutation and new PTMs in the protein characterization and discovery of new peptides and proteins with varying levels of confidence.

Periodic patterns in distributions of peptide masses

We are investigating the distribution of the number of peptides for given masses, and especially the observation that peptide density reaches a local maximum approximately every 14Da. This wave pattern exists across species (e.g. human or yeast) and enzyme digestion techniques. To analyze this phenomenon we have developed a mathematical method for computing the mass distributions of peptides, and we present both theoretical and empirical evidence that this 14-Da periodicity does not arise from species selection of peptides but from the number- theoretic properties of the masses of amino acid residues. We also describe other, more subtle periodic patterns in the distribution of peptide masses. We also show that these periodic patterns are robust under a variety of conditions, including the addition of amino acid modifications and selection of mass accuracy scale. The method used here is also applicable to any family of sequential molecules, such as linear hydrocarbons, RNA, single- and double-stranded DNA.

Improved mass defect model for theoretical tryptic peptides

Improvements in the mass accuracy and resolution of mass spectrometers have greatly aided mass spectrometry-based proteomics in profiling complex biological mixtures. With the use of innovative bioinformatics approaches, high mass accuracy and resolution information can be used for filtering chemical noise in mass spectral data. Using our recent algorithmic developments, we have generated the mass distributions of all theoretical tryptic peptides composed of 20 natural amino acids and with masses limited to 3.5 kDa. Peptide masses are distributed discretely, with well-defined peak clusters separated by empty or sparsely populated trough regions. Accurate models for peak centers and widths can be used to filter peptide signals from chemical noise. We modeled mass defects, the difference between monoisotopic and nominal masses, and peak centers and widths in the peptide mass distributions. We found that peak widths encompassing 95% of all peptide sequences are substantially smaller than previously thought. The result has implications for filtering out larger stretches of the mass axis. Mass defects of peptides exhibit an oscillatory behavior which is damped at high mass values. The periodicity of the oscillations is about 14 Da which is the most common difference between the masses of the 20 natural amino acids. To determine the effects of amino acid modifications on our findings, we examined the mass distributions of peptides composed of the 20 natural amino acids, oxidized Met, and phosphorylated Ser, Thr, and Tyr. We found that extension of the amino acid set by modifications increases the 95% peak width. Mass defects decrease, reflecting the fact that the average mass defect of natural amino acids is larger than that of oxidized Met. We propose that a new model for mass defects and peak widths of peptides may improve peptide identifications by filtering chemical noise in mass spectral data.