Comprehensive characterization of protein modifications using mass spectrometry and dry blood spots.

PURPOSE: The main objective of this study is to characterize and analyze modified peptides in DBS samples. This includes deciphering their specific PTMs and understanding their potential impact on the population or disease cohort under study. EXPERIMENTAL DESIGN: Using mass spectrometry-based proteomic approaches, we performed a comprehensive analysis of DBS samples. Our focus was on the identification and quantification of modified peptides. We also took advantage of recent advances in DBS mass spectrometry to ensure accurate detection and quantification. RESULTS: A comprehensive analysis identified 972 modified peptides in DBS samples. Of these, a subset of 211 peptides was consistently present in all samples, highlighting their potential biological importance and relevance. This indicates a diverse spectrum of PTMs in the proteome of DBS samples. CONCLUSIONS AND CLINICAL RELEVANCE: Integration of mass spectrometry and proteomics has revealed a broad spectrum of modified peptides in DBS samples and highlighted their importance in biological processes and disease progression. Accurate detection of these PTMs may be critical for risk stratification and disease management. This study improves the understanding of molecular mechanisms underlying biological processes and disease development, providing important insights for clinical applications.

Galectin-3 in prostate cancer and heart diseases: a biomarker for these two frightening pathologies?

Galectin-3 (Gal-3) belongs to galectin protein family, a type of ß-galactose-binding lectin having more than one evolutionarily conserved domain of carbohydrate recognition. Gal-3 is mainly located in the cytoplasm, but it also enters the nucleus and is secreted into the extracellular environment and biological fluids such as urine, saliva, and serum. It plays an important role in many biological functions, such as angiogenesis, apoptosis, cell differentiation, cell growth, fibrosis, inflammation, host defense, cellular modification, splicing of pre-mRNA, and transformation. Many previous studies have shown that Gal-3 can be used as a diagnostic or prognostic biomarker for heart ailments, kidney diseases, and other major illnesses including cancer. Moreover, it may also play a major role in risk stratification in different diseases, and in this review, we have summarized the potential roles and application of Gal-3 as diagnostic, prognostic, and risk stratifying biomarker from previously reported studies in heart diseases and cancer, with special emphasis on prostate cancer.

Integration of Liver Glycogen and Triglyceride NMR Isotopomer Analyses Provides a Comprehensive Coverage of Hepatic Glucose and Fructose Metabolism.

Dietary glucose and fructose are both efficiently assimilated by the liver but a comprehensive measurement of this process starting from their conversion to sugar phosphates, involvement of the pentose phosphate pathway (PPP), and conversion to glycogen and lipid storage products, remains incomplete. Mice were fed a chow diet supplemented with 35 g/100 mL drinking water of a 55/45 fructose/glucose mixture for 18 weeks. On the final night, the sugar mixture was enriched with either [U-13C]glucose or [U-13C]fructose, and deuterated water (2H2O) was also administered. 13C-isotopomers representing newly synthesized hepatic glucose-6-phosphate (glucose-6-P), glycerol-3-phosphate, and lipogenic acetyl-CoA were quantified by 2H and 13C NMR analysis of post-mortem liver glycogen and triglyceride. These data were applied to a metabolic model covering glucose-6-P, PPP, triose-P, and de novo lipogenesis (DNL) fluxes. The glucose supplement was converted to glucose-6-P via the direct pathway, while the fructose supplement was metabolized by the liver to gluconeogenic triose-P via fructokinase-aldolase-triokinase. Glucose-6-P from all carbohydrate sources accounted for 40-60% of lipogenic acetyl-CoA and 10-12% was oxidized by the pentose phosphate pathway (PPP). The yield of NADPH from PPP flux accounted for a minority (~30%) of the total DNL requirement. In conclusion, this approach integrates measurements of glucose-6-P, PPP, and DNL fluxes to provide a holistic and informative assessment of hepatic glucose and fructose metabolism.

Urinary exosomes: Diagnostic impact with a bioinformatic approach.

Exosomes are tiny membrane-enveloped vesicles of endosomal origin, typically 40-120nm in diameter, produced by most cells in both normal and pathological situations. These exosomes can be isolated from all biofluids, including urine. In this context, many researchers have focused on the analysis of urinary exosomes because urine can be collected in large quantities, regularly, and with minimal effort. Exosomes contain phospholipids, cholesterol, proteins, glycoconjugates, nucleic acids, and metabolites. Because all organs and tissues produce exosomes, their molecular cargo can provide first-hand information about the physiological and biological state of the site of origin. Many potential disease biomarker candidates have already been identified in urinary exosomes. In this chapter, we performed a bibliometric analysis of the keywords "exosome(s)" and "urine" to identify related terms, diseases and molecular/biological processes, and other related terms. This yielded interesting results suggesting that exosomes in urine may play a role in the pathogenesis of various diseases. Moreover, this chapter discusses exosomes isolation and characterization methodologies and highlight the importance of urinary exosomes and their role in the diagnosis, prognosis and therapy of various diseases. We offer a bibliometric approach and an in-depth analysis on several exosomes' isolation techniques, diagnostic potential for urogenital and specific non-urogenital diseases, as well as an overview of miRNAs significance on urinary exosomes, conferring a more complete status to this review, something that was still lacking in the current literature.

Coronary Artery Disease and Aortic Valve Stenosis: A Urine Proteomics Study.

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).

Re-Analysis of Published Datasets in Search of Novel Urogenital Diseases Biomarkers.

BACKGROUND: Exosome research is a current trend in functional proteomics as it provides important data on the pathophysiology and pathogenesis of diseases. The scientific outputs regarding these topics often only approach disease-protein/peptide/exosome or mechanismprotein/ peptide/exosome association. Approaching all three aspects could be the key to a better understanding of the pathophysiology and uncovering novel biomarkers for urogenital diseases. The focus of this work is to study exosome datasets to understand the possible role of underlying proteins in disease manifestation. We also attempt to link 4 different diseases that affect renal functions and are genetically inherited. METHODS: For this purpose, the existing literature is consulted to understand the importance of exosomes in disease prediction, diagnosis and therapy. Available biotechnological methods of exosome analysis and the tools of proteomic analysis, data mining and visualization are discussed. The database PRIDE is selected to query the information of several datasets related to urinary exosome analysis. RESULTS: We have obtained a list of 19 proteins/genes involved in the mentioned diseases. On this list, we found a proteomic fingerprint consisting of Rab-7a, PDCD6, and CDC42, among others, and we are exploring their biological significance and underlying processes. CONCLUSION: APOA1, CD59, CD9, IGHG1, RAB7A, RAP1A, SEMG1 and SEMG2 are common in four urogenital diseases, and are involved in interactions with podosomes and endosomes, remodeling of chylomicrons, regulation of interleukin production, regulation of endopeptidase activity, and establishment of apical/basal polarity of epithelial cells.

How can artificial intelligence be used for peptidomics?

INTRODUCTION: Peptidomics is an emerging field of omics sciences using advanced isolation, analysis, and computational techniques that enable qualitative and quantitative analyses of various peptides in biological samples. Peptides can act as useful biomarkers and as therapeutic molecules for diseases. AREAS COVERED: The use of therapeutic peptides can be predicted quickly and efficiently using data-driven computational methods, particularly artificial intelligence (AI) approach. Various AI approaches are useful for peptide-based drug discovery, such as support vector machine, random forest, extremely randomized trees, and other more recently developed deep learning methods. AI methods are relatively new to the development of peptide-based therapies, but these techniques already become essential tools in protein science by dissecting novel therapeutic peptides and their functions (Figure 1). EXPERT OPINION: Researchers have shown that AI models can facilitate the development of peptidomics and selective peptide therapies in the field of peptide science. Biopeptide prediction is important for the discovery and development of successful peptide-based drugs. Due to their ability to predict therapeutic roles based on sequence details, many AI-dependent prediction tools have been developed (Figure 1).

Automatic text-mining as an unbiased approach to uncover molecular associations between periodontitis and coronary artery disease.

The increasing prevalence of periodontal and cardiovascular diseases is the result of a sedentary lifestyle associated with poor diet, obesity, hypercholesterolaemia, smoking habits, alcohol consumption and stress. The present study aims to uncover molecular associations between periodontitis and coronary heart disease using an unbiased strategy of automatic text mining traditionally applied to bibliometric studies. A total of 1590 articles on these diseases were retrieved from the Web of knowledge database and searched using the VOS viewer to create a network of keywords associated with both diseases. These data were supplemented with data from DisGeNET, which stores known associations to either periodontitis or coronary heart disease. Overall, the automated text mining approach presented here highlighted inflammatory molecules as common associations between periodontitis and coronary heart disease. Specifically, this study showed that molecules such as C-reactive protein, interleukins 6 and 1-ß, myeloperoxidase, and matrix metalloproteinase 9 are simultaneously associated with periodontitis and coronary artery disease by both text mining and DisGeNET analyses. This association validates the multiplex assessment of salivary inflammatory markers as a tool to assess cardiovascular disease risk and could become an important tool to identify common molecular targets to monitor both diseases simultaneously. In addition, the text mining protocol and subsequent data processing and methods using bioinformatics tools could be useful to uncover links between other diseases.

Ghrelin and adipokines: An overview of their physiological role, antimicrobial activity and impact on cardiovascular conditions.

The human body has many different hormones that interact with each other and with other factors such as proteins, cell receptors and metabolites. There is still a limited understanding of some of the underlying biological mechanisms of some hormones. In the past decades, science and technology have made major advancements in regard to innovation and knowledge in fields such as medicine. However, some conditions are complex and have many variables that their full picture is still unclear, even though some of these conditions have an alarming rate of incidence and serious health consequences. Conditions such as type 2 diabetes, obesity, nonalcoholic liver disease (NAFLD), cancer in its different forms and even mental conditions, such as Alzheimer's disease, are some of the most common diseases in the 21st century. These conditions are relevant not only because of their high incidence on the general population, but also because of their severity. In this chapter, we present an overview of cardiovascular (CV) diseases. According to the World Health Organization (WHO), cardiovascular diseases, such as coronary artery disease (CAD), heart attack, cardiomyopathy and heart failure (among others), are the number one cause of death worldwide. In 2016, it was estimated that 17.9 million people died from CV diseases, representing more than 30% of all global deaths. Approximately 95% of people who died from CV diseases were so-called "premature deaths" because were referenced to individuals under the age of 70 years old. In this chapter we described some of the hormones that may have an impact on CV diseases, including ghrelin, a peptide that is mostly produced in the stomach, known to induce hunger. Ghrelin is linked to an increase in body fat, i.e., adipose tissue in animals. For this reason, we also included the adipokines leptin, adiponectin and resistin. The main objectives of this chapter are to present the state of the art knowledge concerning the mechanisms of each hormone relevant to CV diseases; to compile data and results that further elucidate the relevance of these peptides for several physiological events, conditions and diseases; and to discuss the metabolic impact of each hormone. We established connections between multiple peptides and the underlying condition/disease with tools such as STRING, referring to research using databases, such as UniProt, DisGeNET and Proteomics DB. Fig. 1 shows a network that summarizes the information presented in this chapter, which serves as a visual representation.

A new scale measuring adaptive perceived control for people with Parkinson's: Initial construction and further validation.

INTRODUCTION: Perceived control is an important concept in understanding adjustment to chronic conditions such as Parkinson's. While generic measures have been used to measure the construct in Parkinson's, no Parkinson's-specific scale currently exists. This study outlines the initial development and further validation of a free-to-use scale, the Parkinson's UK Scale of Perceived Control (PUKSoPC). METHOD: Focus groups were used to create items for the new scale. Potential items were then subject to screening for readability and coherence by people affected by the condition. This left 49 items that were then completed, along with other measures, by 231 people with Parkinson's. Exploratory factor analysis then created a 15-item scale with five distinct subscales. This initial structure was then further tested using confirmatory factor analysis with 2032 people with Parkinson's. Structural equation modelling confirmed the acceptability of the total scale and subscale structures. RESULTS: The final scale is concluded to be a psychometrically robust measure of perceived control. It has good face validity, evidence of convergent and criterion (concurrent and divergent) validity, good test-retest reliability and is internally coherent, with a demonstrably solid factor structure. While further testing would be useful to assess the scale's predictive ability, it is currently considered robust enough for more widespread use. CONCLUSION: The PUKSoPC is an appropriate scale to provide a more comprehensive measure of perceived control. It is preferable to single item, non-validated measures and can provide evidence of perceptions of control across a number of domains important in the measurement of the construct.