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In the quest to fully comprehend the proteolytic events leading to the generation of the salivary peptidome, we have developed a method for the sequential elution of salivary peptides throughout progressive endogenous proteolysis. By screening the time-dependent changes in the salivary peptidome we can predict the activity pattern of salivary proteases responsible for such peptide fingerprint and identify susceptible protein targets. Herein, we describe a step-by-step tutorial based on a filter-aided sample preparation (FASP) method, taking advantage of the endogenous salivary proteases armamentarium (endoProteoFASP), to produce new peptides from the salivary proteins, adding to those present in the sample at the time of collection. In this protocol, the different sets of peptides retrieved after sample elution are identified following a liquid chromatography-tandem mass spectrometry approach. The likelihood of a large set of endogenous proteases (collected from several public sources) to be responsible for the generation of such peptides can be predicted by the analysis of the cleavage site specificity by Proteasix ( http://proteasix.cs.man.ac.uk /) algorithm. The attained peptidome-protease profile can be useful to elucidate the peptidome dynamics and the proteolytic events underpinning pathophysiological phenomena taking place locally within the oral cavity. This may help clinicians to diagnose oral pathologies and develop preventive therapeutic plans.

Urine is a highly attractive source of biological information and disease biomarkers, whose proteome characterization is ongoing. To that end, depletion/enrichment strategies for protein analysis can be of great convenience. We have thus developed a method based on the use of EDTA-functionalized magnetic nanoparticles (NPs@EDTA), to fractionate urine samples before liquid chromatography-mass spectrometry analysis and compared the identified proteins with those obtained from ultrafiltrated/unfractionated (UF) urine samples. NPs@EDTA allowed larger urine volumes to be processed, resulting in a greater number of protein identifications (~2-fold) at a lower cost when compared to UF samples. Proteins of greater abundance (such as albumin and uromodulin) were, at least partially, depleted with NPs@EDTA while those of lower abundance were enriched. Bioinformatics analysis showed that approximately 27% of NPs@EDTA-enriched proteins were annotated as displaying enzymatic activity, most of these being hydrolytic enzymes (56%), particularly proteases/peptidases (48%). Also, post-translational modifications were prominently predicted across NPs@EDTA-enriched proteins (90%), particularly glycosylation (52%), phosphorylation (47%) and acetylation (30%). NPs@EDTA allowed the identification of 109 proteins in urine for the first time, showing high potential as a platform for urine's fractionation prior to proteomic analysis., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Coronary artery disease (CAD) and the frequently coexisting aortic valve stenosis (AVS) are heart diseases accounting for most cardiac surgeries. These share many risk factors, such as age, diabetes, hypertension, or obesity, and similar pathogenesis, including endothelial disruption, lipid and immune cell infiltration, inflammation, fibrosis, and calcification. Unsuspected CAD and AVS are sometimes detected opportunistically through echocardiography, coronary angiography, and magnetic resonance. Routine biomarkers for early detection of either of these atherosclerotic-rooted conditions would be important to anticipate the diagnosis. With a noninvasive collection, urine is appealing for biomarker assessment. We conducted a shotgun proteomics exploratory analysis of urine from 12 CAD and/or AVS patients and 11 controls to identify putative candidates to differentiate these diseases from healthy subjects. Among the top 20 most dysregulated proteins, TIMP1, MMP2 and vWF stood out, being at least 2.5× increased in patients with CAD/AVS and holding a central position in a network of protein-protein interactions. Moreover, their assessment in an independent cohort (19 CAD/AVS and 10 controls) evidenced strong correlations between urinary TIMP1 and vWF levels and a common cardiovascular risk factor - HDL (r = 0.59, p < 0.05, and r = 0.64, p < 0.01, respectively). [ABSTRACT FROM AUTHOR]

Introduction:The proper folding of native proteins is critical and dynamic, but inherently unstable. Therefore, proteins eventually end up adopting misfolded conformations which compromise their function and may even trigger aggregation. Risk factors for neurodegenerative, metabolic and heart diseases compromise cellular protein quality-control systems, promoting protein aggregation. Multiple protein post-translational modifications dynamically regulate protein aggregation and disaggregation in a very complex, intricate and delicate balance. Areas covered:Herein, we overview the more promising techniques and approaches for the elucidation of the biological implications of protein aggregation. The particular insights provided by different techniques were discriminated and several examples of post-translational modifications together with their targets were pooled and critically discussed, representing promising future therapeutic targets. Expert commentary:In the years to come, differences between physiological and pathological protein aggregation will certainly become easier to determine. Techniques such as hydrogen/deuterium exchange, circular dichroism spectroscopy and novel mass spectrometry-based approaches are being optimized and are expected to introduce inhibitors of protein aggregation into the clinic. However, protein aggregation is not an isolated phenomenon, but rather influenced by multiple cellular components which complete knowledge is still far. [ABSTRACT FROM PUBLISHER]

Atrial fibrillation (AF) is the most common arrhythmia with adverse clinical outcomes. Pericardial fluid (PF) mirrors the heart's pathophysiological status due to its proximity. This study aimed to characterise the PF proteome to identify new biomarkers of disease. Eighty-three patients submitted to aortic valve replacement surgery with severe aortic stenosis were selected, and their baseline echocardiographic and clinical variables were documented. Thirteen samples were selected blindly for proteome characterisation following a shotgun (GeLC–MS/MS) and a label-free quantification approach (LFQ). According to previous AF history, a partial least squares discriminant analysis (PLS-DA) was conducted, and the top 15 variables important in projection were identified. To inquire potential biomarkers, ROC curves were designed using LFQ data. Target proteins were further validated by ELISA, in both pericardial fluid and serum. Proteome analysis uncovered nine proteins up- and downregulated ≥2-fold. Annexin A1, annexin A2, and vimentin were among the top 15 most important variables for group discrimination in PLS-DA. Protein—protein interaction and gene ontology enrichment analysis presented functional interaction among identified proteins, which were all part of focal adhesion sites. Annexin A1 was increased in the pericardial fluid of AF patients but not in serum when quantified by ELISA. Annexin A1 is a novel pericardial fluid biomarker of AF in patients with severe aortic stenosis. [ABSTRACT FROM AUTHOR]