Genotyping and lipid profiling of 601 cultivated sunflower lines reveals novel genetic determinants of oil fatty acid content.

BACKGROUND: Sunflower is an important oilseed crop domesticated in North America approximately 4000 years ago. During the last century, oil content in sunflower was under strong selection. Further improvement of oil properties achieved by modulating its fatty acid composition is one of the main directions in modern oilseed crop breeding. RESULTS: We searched for the genetic basis of fatty acid content variation by genotyping 601 inbred sunflower lines and assessing their lipid and fatty acid composition. Our genome-wide association analysis based on the genotypes for 15,483 SNPs and the concentrations of 23 fatty acids, including minor fatty acids, revealed significant genetic associations for eleven of them. Identified genomic regions included the loci involved in rare fatty acids variation on chromosomes 3 and 14, explaining up to 34.5% of the total variation of docosanoic acid (22:0) in sunflower oil. CONCLUSIONS: This is the first large scale implementation of high-throughput lipidomic profiling to sunflower germplasm characterization. This study contributes to the genetic characterization of Russian sunflower collections, which made a substantial contribution to the development of sunflower as the oilseed crop worldwide, and provides new insights into the genetic control of oil composition that can be implemented in future studies.

Lipidome analysis of milk composition in humans, monkeys, bovids, and pigs.

BACKGROUND: Lipids contained in milk are an essential source of energy and structural materials for a growing neonate. Furthermore, lipids' long-chain unsaturated fatty acid residues can directly participate in neonatal tissue formation. Here, we used untargeted mass spectrometric measurements to assess milk lipid composition in seven mammalian species: humans, two macaque species, cows, goats, yaks, and pigs. RESULTS: Analysis of the main milk lipid class, triacylglycerides (TAGs), revealed species-specific quantitative differences in the composition of fatty acid residues for each of seven species. Overall, differences in milk lipid composition reflect evolutionary distances among species, with each species group demonstrating specific lipidome features. Among them, human milk contained more medium and long-chain unsaturated fatty acids compared to other species, while pig milk was the most distinct, featuring the highest proportion of long-chain polyunsaturated fatty acids. CONCLUSIONS: We show that milk lipidome composition is dynamic across mammalian species, changed extensively in pigs, and contains features particular to humans.

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.

Discovery of novel antimicrobial peptides: A transcriptomic study of the sea anemone Cnidopus japonicus.

As essential conservative component of the innate immune systems of living organisms, antimicrobial peptides (AMPs) could complement pharmaceuticals that increasingly fail to combat various pathogens exhibiting increased resistance to microbial antibiotics. Among the properties of AMPs that suggest their potential as therapeutic agents, diverse peptides in the venoms of various predators demonstrate antimicrobial activity and kill a wide range of microorganisms. To identify potent AMPs, the study reported here involved a transcriptomic profiling of the tentacle secretion of the sea anemone Cnidopus japonicus. An in silico search algorithm designed to discover toxin-like proteins containing AMPs was developed based on the evaluation of the properties and structural peculiarities of amino acid sequences. The algorithm revealed new proteins of the anemone containing antimicrobial candidate sequences, and 10 AMPs verified using high-throughput proteomics were synthesized. The antimicrobial activity of the candidate molecules was experimentally estimated against Gram-positive and -negative bacteria. Ultimately, three peptides exhibited antimicrobial activity against bacterial strains, which suggests that the method can be applied to reveal new AMPs in the venoms of other predators as well.

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.

The Pathogenesis of the Demyelinating Form of Guillain-Barre Syndrome (GBS): Proteo-peptidomic and Immunological Profiling of Physiological Fluids.

Acute inflammatory demyelinating polyneuropathy (AIDP) - the main form of Guillain-Barre syndrome-is a rare and severe disorder of the peripheral nervous system with an unknown etiology. One of the hallmarks of the AIDP pathogenesis is a significantly elevated cerebrospinal fluid (CSF) protein level. In this paper CSF peptidome and proteome in AIDP were analyzed and compared with multiple sclerosis and control patients. A total protein concentration increase was shown to be because of even changes in all proteins rather than some specific response, supporting the hypothesis of protein leakage from blood through the blood-nerve barrier. The elevated CSF protein level in AIDP was complemented by activization of protein degradation and much higher peptidome diversity. Because of the studies of the acute motor axonal form, Guillain-Barre syndrome as a whole is thought to be associated with autoimmune response against neurospecific molecules. Thus, in AIDP, autoantibodies against cell adhesion proteins localized at Ranvier's nodes were suggested as possible targets in AIDP. Indeed, AIDP CSF peptidome analysis revealed cell adhesion proteins degradation, however no reliable dependence on the corresponding autoantibodies levels was found. Proteome analysis revealed overrepresentation of Gene Ontology groups related to responses to bacteria and virus infections, which were earlier suggested as possible AIDP triggers. Immunoglobulin blood serum analysis against most common neuronal viruses did not reveal any specific pathogen; however, AIDP patients were more immunopositive in average and often had polyinfections. Cytokine analysis of both AIDP CSF and blood did not show a systemic adaptive immune response or general inflammation, whereas innate immunity cytokines were up-regulated. To supplement the widely-accepted though still unproven autoimmunity-based AIDP mechanism we propose a hypothesis of the primary peripheral nervous system damaging initiated as an innate immunity-associated local inflammation following neurotropic viruses egress, whereas the autoantibody production might be an optional complementary secondary process.

Bovine serum albumin as a universal suppressor of non-specific peptide binding in vials prior to nano-chromatography coupled mass-spectrometry analysis.

Non-specific binding (NSB) is a well-known problem for any application that deals with ultralow analyte quantities. The modern nano-flow chromatography coupled tandem mass-spectrometry (nanoLC-MS/MS) works with the lowest conceivable analyte concentrations. However, while the NSB problem is widely accepted and investigated for metabolomics and single-peptide medicine-related assays, its impact is not studied for complex peptide mixtures in proteomic applications. In this work peptide NSB to a common plastic autosampler vial was studied for a model mixture of 46 synthetic peptides. A significant NSB level was demonstrated for total peptide concentrations of up to 1 mg mL(-1). Different agents were tried for NSB suppression and compatibility with nanoLC-MS/MS analysis: a chaotropic agent, an amino acid mixture, a peptide mixture and a protein solution. The first two were inefficacious. The peptide matrix blocked NSB, however, it also led to analyte ionization suppression in nanoLC-MS/MS. The protein solution (0.1% BSA) efficiently eliminated NSB, while a trap-elute nanoHPLC configuration together with a small-pore reverse-phased sorbent effectively and quantitatively extracted the model peptides and depleted protein material from the sample. Higher protein concentration partially impeded peptide extraction. Thus, the 0.1% BSA solution might be regarded as an effective non-interfering blockader of NSB for sample resuspension and storage in an autosampler prior to LC-MS/MS analysis.

Proteome-metabolome profiling of ovarian cancer ascites reveals novel components involved in intercellular communication.

Ovarian cancer ascites is a native medium for cancer cells that allows investigation of their secretome in a natural environment. This medium is of interest as a promising source of potential biomarkers, and also as a medium for cell-cell communication. The aim of this study was to elucidate specific features of the malignant ascites metabolome and proteome. In order to omit components of the systemic response to ascites formation, we compared malignant ascites with cirrhosis ascites. Metabolome analysis revealed 41 components that differed significantly between malignant and cirrhosis ascites. Most of the identified cancer-specific metabolites are known to be important signaling molecules. Proteomic analysis identified 2096 and 1855 proteins in the ovarian cancer and cirrhosis ascites, respectively; 424 proteins were specific for the malignant ascites. Functional analysis of the proteome demonstrated that the major differences between cirrhosis and malignant ascites were observed for the cluster of spliceosomal proteins. Additionally, we demonstrate that several splicing RNAs were exclusively detected in malignant ascites, where they probably existed within protein complexes. This result was confirmed in vitro using an ovarian cancer cell line. Identification of spliceosomal proteins and RNAs in an extracellular medium is of particular interest; the finding suggests that they might play a role in the communication between cancer cells. In addition, malignant ascites contains a high number of exosomes that are known to play an important role in signal transduction. Thus our study reveals the specific features of malignant ascites that are associated with its function as a medium of intercellular communication.