DISMS2: A flexible algorithm for direct proteome- wide distance calculation of LC-MS/MS runs

Abstract

BackgroundThe classification of samples on a molecular level has manifold applications, from patient classification regarding cancer treatment to phylogenetics for identifying evolutionary relationships between species. Modern methods employ the alignment of DNA or amino acid sequences, mostly not genome-wide but only on selected parts of the genome. Recently proteomics-based approaches have become popular. An established method for the identification of peptides and proteins is liquid chromatography-tandem mass spectrometry (LC-MS/MS). First, protein sequences from MS/MS spectra are identified by means of database searches, given samples with known genome-wide sequence information, then sequence based methods are applied. Alternatively, de novo peptide sequencing algorithms annotate MS/MS spectra and deduce peptide/protein information without a database. A newer approach independent of additional information is to directly compare unidentified tandem mass spectra. The challenge then is to compute the distance between pairwise MS/MS runs consisting of thousands of spectra.MethodsWe present DISMS2, a new algorithm to calculate proteome-wide distances directly from MS/MS data, extending the algorithm compareMS2, an approach that also uses a spectral comparison pipeline.ResultsOur new more flexible algorithm, DISMS2, allows for the choice of the spectrum distance measure and includes different spectra preprocessing and filtering steps that can be tailored to specific situations by parameter optimization.ConclusionsDISMS2 performs well for samples from species with and without database annotation and thus has clear advantages over methods that are purely based on database search.Electronic supplementary materialThe online version of this article (doi:10.1186/s12859-017-1514-2) contains supplementary material, which is available to authorized users.

'Palaeoshellomics’ reveals the use of freshwater mother-of-pearl in prehistory

“…Multidimensional scaling (MDS; Gower, 1966) was used to visualise the similarity of observations (Figure 5) and confirmed that the Havnø set and the freshwater reference unionoids display the higher degree of proteome similarity, while the samples from Hornstaad and PesB fall in a different area of the plot from each other and from the marine reference shells. The results were also in accordance with those obtained from another database-independent approach Appendix 1—figure 25, based on direct product ion spectra comparison (Rieder et al, 2017), which was adapted for this study (Appendix 1, section 3.6). Overall, our study, which represents one of the few that attempts to compare molluscan proteomes within the same clade (genus, family or order), shows that unionoid shells exhibit very similar proteome profiles, sharing many sequences between species Appendix 1—figure 23.…”

“…However, database-dependant search algorithms of DNA and/or protein sequences cannot take into account peptides and proteins that do not yet exist in databases. In recent years, as shotgun proteomics has become a routine tool for biochemistry, and huge amounts of data have been generated on novel systems and organisms (including extinct), there has been an increasing interest in developing methods enabling to compare proteome-wide measurements that would be flexible and allow database-free workflows (Palmblad and Deelder, 2012; Rieder et al, 2017; Yılmaz et al, 2016).…”

“…We attempted to perform comparative shell proteome analysis based solely on the proteome-wide distance calculation of different product ion spectra using a DISMS2 algorithm implemented in R language (Rieder et al, 2017). The algorithm is a four-step procedure, consisting of spectra filtering, checking constraints for matching, matching of product ion spectra and calculation of the distance matrix with pairwise distances between runs.…”

Morph-specific protein patterns in the femoral gland secretions of a colour polymorphic lizard

“…To further assess the effective distinctness of morph-specific spots, a pairwise spectrum-to-spectrum comparison was performed 154–156 . The set of spectra from each MS run was compared to all the others belonging to a different morph, and the cosine distance computed 155 . The minimum of this distances for each spot (minimum non-self-distance) was retained and compared to the one computed between each spot and itself (self-distance).…”

Abiotic and past climatic conditions drive protein abundance variation among natural populations of the caddisfly Crunoecia irrorata

“…Geographic distances between springs were calculated based on longitude and latitude of springs using package geosphere v.1.5.10 66 and the implemented function distm (Vincentry great circle distances). Pairwise spectrum distances (cosine distances) between MS/MS runs (proteome-wide distances independent of peptide-identification and therefore of the homology-based protein database) were computed in R using the DISMS2 algorithm 67 .…”