Recent advances in platelet proteomics

Platelets are the fundamental players in primary hemostasis, but are also involved in several pathological conditions. The remarkable advances in proteomic methodologies have allowed a better understanding of the basic physiological pathways underlying platelet biology. In addition, recent platelet proteomics focused on disease conditions, helping to elucidate the molecular mechanisms of complex and/or unknown human disorders and to find novel biomarkers for early diagnosis and drug targets. The most common and innovative proteomic techniques, both gel-based and gel-free, used in platelet proteomics will be reviewed here. A particular focus will be given to studies that used a subproteomic strategy to analyze specific platelet conditions (resting or activated), compartments (membrane, granules and microparticles) or fractions (phosphoproteome or glycoproteome). The thousands of platelet proteins and interactions discovered so far by these different powerful proteomic approaches represent a precious source of information for both basic science and clinical applications in the field of platelet biology.     

Analysis of organelles within the nervous system: impact on brain and organelle functions

Currently, neuroproteomic approaches aimed at the profiling of total brain areas generally mirror the expression of the most abundant proteins, but fail to uncover less abundant proteins. By contrast, the focus on typical brain subproteomes, (e.g., synaptic vesicles, synaptic terminal membranes or the postsynaptic density), may give a more specific insight into brain function. Subproteomes are accessible via several strategies, including subcellular fractionation or affinity-based pull-down approaches. Combined with mass spectrometric quantification approaches, subcellular proteomics is expected to reveal differences in the protein constitution of related cellular organelles. Focusing on novel functions and mechanistic models, we review recent data on the analysis of brain-derived organelles and subproteomes, including presynaptic termini, synaptic vesicles, neuronal plasma membranes, postsynaptic density and neuromelanin granules, which were identified as novel lysosome-related organelles within the human brain.     

Chemical proteomics from a nuclear magnetic resonance spectroscopy perspective

Proteomics is the study of the protein complement of a genome and employs a number of newly emerging tools. One such tool is chemical proteomics, which is a branch of proteomics devoted to the exploration of protein function using both in vitro and in vivo chemical probes. Chemical proteomics aims to define protein function and mechanism at the level of directly observed protein–ligand interactions, whereas chemical genomics aims to define the biological role of a protein using chemical knockouts and observing phenotypic changes. Chemical proteomics is therefore traditional mechanistic biochemistry performed in a systems-based manner, using either activity- or affinity-based probes that target proteins related by chemical reactivities or by binding site shape/properties, respectively. Systems are groups of proteins related by metabolic pathway, regulatory pathway or binding to the same ligand. Studies can be based on two main types of proteome samples: pooled proteins (1 mixture of N proteins) or isolated proteins in a given system and studied in parallel (N single protein samples). Although the field of chemical proteomics originated with the use of covalent labeling strategies such as isotope-coded affinity tagging, it is expanding to include chemical probes that bind proteins noncovalently, and to include more methods for observing protein–ligand interactions. This review presents an emerging role for nuclear magnetic resonance spectroscopy in chemical proteomics, both in vitro and in vivo. Applications include: functional proteomics using cofactor fingerprinting to assign proteins to gene families; gene family-based structural characterizations of protein–ligand complexes; gene family-focused design of drug leads; and chemical proteomic probes using nuclear magnetic resonance SOLVE and studies of protein–ligand interactions in vivo.     

Systemic sclerosis biomarkers discovered using mass-spectrometry-based proteomics: a systematic review

Abstract

Context: Systemic sclerosis (SSc) is an autoimmune disease with incompletely known physiopathology. There is a great challenge to predict its course and therapeutic response using biomarkers.

Objective: To critically review proteomic biomarkers discovered from biological specimens from systemic sclerosis patients using mass spectrometry technologies.

Methods: Medline and Embase databases were searched in February 2014.

Results: Out of the 199 records retrieved, a total of 20 records were included, identifying 116 candidate proteomic biomarkers.

Conclusion: Research in SSc proteomic biomarkers should focus on biomarker validation, as there are valuable mass-spectrometry proteomics studies in the literature.     

Peroxisomal proteomic approach for protein profiling in blue mussels (Mytilus edulis) exposed to crude oil

Peroxisomal proteomic protein profiles of exposure to marine pollution have been recently introduced in biomonitoring experiments. However, laboratory experiments to study the independent effect of common pollutants are needed to define a minimal protein expression signature (PES) of exposure to a specific pollutant. The aim of this study was to obtain PESs in blue mussels (Mytilus edulis) exposed to two different crude oil mixtures for future application in biomonitoring areas affected by oil spills. In the study, peroxisome-enriched fractions from digestive gland of M. edulis (L., 1758) were analysed by two-dimensional fluorescence difference electrophoresis (DIGE) and mass spectrometry (MS) after 3 weeks of exposure to crude oil mixtures: crude oil or crude oil spiked with alkylated phenols (AP) and extra polycyclic aromatic hydrocarbons (PAH) in a laboratory flow-through system. A minimal PES composed by 13 protein spots and unique PESs of exposure to the two different mixtures were identified. A total of 22 spots from the two-dimensional maps that had shown a significant increase or decrease in abundance in each of the exposed groups exposed were analysed. The hierarchical clustering analysis succeeded in discriminating the exposed groups from the control groups based on the unique PES. The PESs obtained were consistent with protein patterns obtained in previous field experiments. The results suggest that the protein profiles obtained by peroxisomal proteomics could be used to assess oil exposure in marine pollution assessments.     

The use of biomarkers for improved retrospective exposure assessment in epidemiological studies: summary of an ECETOC workshop

During a scientific workshop the use of biological monitoring in characterization of retrospective exposure assessment was discussed. The workshop addressed currently available methodology and also novel approaches such as in different fields of ‘omics’. For use in epidemiology requiring retrospective exposure assessment, biomarker levels should not vary too much over time. If variability in exposure over time is large and differences in exposure between individuals are relatively small, this may lead to underestimation of the exposure–response relationship. This means that, for a sound assessment of health risk, biomarkers that reflect cumulative exposure over a long period of time are preferred over biomarkers with short half-lives. Most of the existing biomarkers such as metabolites in body fluids usually have rather short half-lives, typically less than 1–2 days. Some adducts to DNA show somewhat longer half-lives. The current limit to persistence of biomarkers reflecting cumulative exposure over time is from adducts to haemoglobin with a half-life of 4 months. Some specific organic substances may be more persistent due to storage in adipose tissue or metals in kidneys, nails and hair. The metabonomics, proteomics and present gene expression profiling approaches do not provide a perspective to the availability of more persistent biomarkers and most approaches discussed to date show that it is difficult to interpret study outcomes in terms of exposure to a specific xenobiotic factor. Research efforts should focus on improvement and validation of currently available approaches in the field of addition products to DNA and proteins. Promising new developments may be phosphotriester DNA adducts and adducts to more long-lived proteins such as histones.     

Identification of factors that function in Drosophila salivary gland cell death during development using proteomics

Proteasome inhibitors induce cell death and are used in cancer therapy, but little is known about the relationship between proteasome impairment and cell death under normal physiological conditions. Here, we investigate the relationship between proteasome function and larval salivary gland cell death during development in Drosophila. Drosophila larval salivary gland cells undergo synchronized programmed cell death requiring both caspases and autophagy (Atg) genes during development. Here, we show that ubiquitin proteasome system (UPS) function is reduced during normal salivary gland cell death, and that ectopic proteasome impairment in salivary gland cells leads to early DNA fragmentation and salivary gland condensation in vivo. Shotgun proteomic analyses of purified dying salivary glands identified the UPS as the top category of proteins enriched, suggesting a possible compensatory induction of these factors to maintain proteolysis during cell death. We compared the proteome following ectopic proteasome impairment to the proteome during developmental cell death in salivary gland cells. Proteins that were enriched in both populations of cells were screened for their function in salivary gland degradation using RNAi knockdown. We identified several factors, including trol, a novel gene CG11880, and the cop9 signalsome component cop9 signalsome 6, as required for Drosophila larval salivary gland degradation.     

Trait vs. phylogenetic diversity as predictors of competition and community composition in herbivorous marine amphipods

Field studies of community assembly patterns increasingly use phylogenetic relatedness as a surrogate for traits. Recent experiments appear to validate this approach by showing effects of correlated trait and phylogenetic distances on coexistence. However, traits governing resource use in animals are often labile. To test whether feeding trait or phylogenetic diversity can predict competition and production in communities of grazing amphipods, we manipulated both types of diversity independently in mesocosms. We found that increasing the feeding trait diversity of the community increased the number of species coexisting, reduced dominance and changed food availability. In contrast, phylogenetic diversity had no effect, suggesting that whatever additional ecological information it represents was not relevant in this context. Although community phylogenetic structure in the field may result from multiple traits with potential for phylogenetic signal, phylogenetic effects on species interactions in controlled experiments may depend on the lability of fewer key traits.     

Advanced nanoscale separations and mass spectrometry for sensitive high-throughput proteomics

Recent developments in combined separations with mass spectrometry for sensitive and high-throughput proteomic analyses are reviewed herein. These developments primarily involve high-efficiency (separation peak capacities of ~10³) nanoscale liquid chromatography (flow rates extending down to approximately 20 nl/min at optimal liquid mobile-phase separation linear velocities through narrow packed capillaries) in combination with advanced mass spectrometry and in particular, high-sensitivity and high-resolution Fourier transform ion cyclotron resonance mass spectrometry. Such approaches enable analysis of low nanogram level proteomic samples (i.e., nanoscale proteomics) with individual protein identification sensitivity at the low zeptomole level. The resultant protein measurement dynamic range can approach 10⁶ for nanogram-sized proteomic samples, while more abundant proteins can be detected from subpicogram-sized (total) proteome samples. These qualities provide the foundation for proteomics studies of single or small populations of cells. The instrumental robustness required for automation and providing high-quality routine performance nanoscale proteomic analyses is also discussed.