Peptidome profiling dataset of ovarian cancer and non-cancer proximal fluids: Ascites and blood sera

Despite a large number of proteomic studies of biological fluids from ovarian cancer patients, there is a lack of sensitive screening methods in clinical practice (Kim et al., 2016) (DOI:https://doi.org/10.1111/cas.12987 [1]). Low molecular weight endogenous peptides more easily diffuse across endothelial barriers than proteins and can be more relevant biomarker candidates (Meo et al., 2016) (DOI:https://doi.org/10.18632/oncotarget.8931 [2], (Bery et al., 2014) DOI:https://doi.org/10.1186/1559-0275-11-13 [3], (Huang et al., 2018) DOI:https://doi.org/10.1097/IGC.0000000000001166 [4]). Detailed peptidomic analysis of 26 ovarian cancer and 15 non-cancer samples of biological fluids (ascites and sera) were performed using TripleTOF 5600+ mass-spectrometer. Prior to LC-MS/MS analysis, peptides were extracted from biological fluids using anion exchange sorbent with subsequent peptide desorption from the surface of highly abundant proteins. In total, we identified 4874 peptides; 3123 peptides were specific for the ovarian cancer samples. The mass-spectrometry peptidomics data presented in this data article have been deposited to the ProteomeXchange Consortium (Deutsch et al., 2017) (DOI:https://doi.org/10.1093/nar/gkw936 [5]) via the PRIDE partner repository with the dataset identifier PXD009382 and https://doi.org/10.6019/PXD009382, http://www.ebi.ac.uk/pride/archive/projects/PXD009382

Peptidomics dataset: Blood plasma and serum samples of healthy donors fractionated on a set of chromatography sorbents

Blood as connective tissue potentially contains evidence of all processes occurring within the organism, at least in trace amounts (Petricoin et al., 2006) [1]. Because of their small size, peptides penetrate cell membranes and epithelial barriers more freely than proteins. Among the peptides found in blood, there are both fragments of proteins secreted by various tissues and performing their function in plasma and receptor ligands: hormones, cytokines and mediators of cellular response (Anderson et al., 2002) [2]. In addition, in minor amounts, there are peptide disease markers (for example, oncomarkers) and even foreign peptides related to pathogenic organisms and infection agents. To propose an approach for detailed peptidome characterization, we carried out an LC–MS/MS analysis of blood serum and plasma samples taken from 20 healthy donors on a TripleTOF 5600+ mass-spectrometer. We prepared samples based on our previously developed method of peptide desorption from the surface of abundant blood plasma proteins followed by standard chromatographic steps (Ziganshin et al., 2011) [3]. The mass-spectrometry peptidomics data presented in this article have been deposited to the ProteomeXchange Consortium (Deutsch et al., 2017) [4] via the PRIDE partner repository with the dataset identifier PXD008141 and 10.6019/PXD008141

Large scale analysis of amino acid substitutions in bacterial proteomics

Background: Proteomics of bacterial pathogens is a developing field exploring microbial physiology, gene expression and the complex interactions between bacteria and their hosts. One of the complications in proteomic approach is micro- and macro-heterogeneity of bacterial species, which makes it impossible to build a comprehensive database of bacterial genomes for identification, while most of the existing algorithms rely largely on genomic data. Results: Here we present a large scale study of identification of single amino acid polymorphisms between bacterial strains. An ad hoc method was developed based on MS/MS spectra comparison without the support of a genomic database. Whole-genome sequencing was used to validate the accuracy of polymorphism detection. Several approaches presented earlier to the proteomics community as useful for polymorphism detection were tested on isolates of Helicobacter pylori, Neisseria gonorrhoeae and Escherichia coli. Conclusion: The developed method represents a perspective approach in the field of bacterial proteomics allowing to identify hundreds of peptides with novel SAPs from a single proteome

Additional file 2 of Large scale analysis of amino acid substitutions in bacterial proteomics

Table with identifications of MS/MS spectra of H. pylori E48 and H-13 in classical Mascot search against sequence database and speptide search. (XLSX 89.6 kb

Additional file 1 of Large scale analysis of amino acid substitutions in bacterial proteomics

Supplementary materials with Figures S1-S12 and Tables S1-S5. (PDF 855 kb