Combined Salivary Proteome Profiling and Machine Learning Analysis Provides Insight into Molecular Signature for Autoimmune Liver Diseases Classification.

Autoimmune hepatitis (AIH) and primary biliary cholangitis (PBC) are autoimmune liver diseases that target the liver and have a wide spectrum of presentation. A global overview of quantitative variations on the salivary proteome in presence of these two pathologies is investigated in this study. The acid-insoluble salivary fraction of AIH and PBC patients, and healthy controls (HCs), was analyzed using a gel-based bottom-up proteomic approach combined with a robust machine learning statistical analysis of the dataset. The abundance of Arginase, Junction plakoglobin, Desmoplakin, Hexokinase-3 and Desmocollin-1 decreased, while that of BPI fold-containing family A member 2 increased in AIHp compared to HCs; the abundance of Gelsolin, CD14, Tumor-associated calcium signal transducer 2, Clusterin, Heterogeneous nuclear ribonucleoproteins A2/B1, Cofilin-1 and BPI fold-containing family B member 2 increased in PBCp compared to HCs. The abundance of Hornerin decreased in both AIHp and PBCp with respect to HCs and provided an area under the ROC curve of 0.939. Machine learning analysis confirmed the feasibility of the salivary proteome to discriminate groups of subjects based on AIH or PBC occurrence as previously suggested by our group. The topology-based functional enrichment analysis performed on these potential salivary biomarkers highlights an enrichment of terms mostly related to the immune system, but also with a strong involvement in liver fibrosis process and with antimicrobial activity.

Long-Term Exposure to Supraphysiological Levels of Testosterone Impacts Rat Submandibular Gland Proteome.

The salivary glands play a central role in the secretion of saliva, whose composition and volume affect oral and overall health. A lesser-explored dimension encompasses the possible changes in salivary gland proteomes in response to fluctuations in sex hormone levels. This study aimed to examine the effects of chronic exposure to testosterone on salivary gland remodeling, particularly focusing on proteomic adaptations. Therefore, male Wistar rats were implanted with subcutaneous testosterone-releasing devices at 14 weeks of age. Their submandibular glands were histologically and molecularly analyzed 47 weeks later. The results underscored a significant increase in gland mass after testosterone exposure, further supported by histologic evidence of granular duct enlargement. Despite increased circulating sex hormones, there was no detectable shift in the tissue levels of estrogen alpha and androgen receptors. GeLC-MS/MS and subsequent bioinformatics identified 308 proteins in the submandibular glands, 12 of which were modulated by testosterone. Of note was the pronounced upregulation of Klk3 and the downregulation of Klk6 and Klk7 after testosterone exposure. Protein-protein interaction analysis with the androgen receptor suggests that Klk3 is a potential target of androgenic signaling, paralleling previous findings in the prostate. This exploratory analysis sheds light on the response of salivary glands to testosterone exposure, providing proteome-level insights into the associated weight and histological changes.

What can urinary exosomes tell us?

Exosomes are involved in a wide variety of biochemical processes in human body homeostasis. Exosomes also provide important information regarding communications among several organ systems. Additionally, they can serve as molecular vehicles to deliver drugs. Therefore, exosomes have received wide attention in current biomedical research for unraveling pathogenic mechanisms of diseases, searching for novel biomarkers, and discovering new drugs. This paper reviews and discusses the significance of urinary exosomes for a better understanding of human disease pathophysiology and their potential use as therapeutic targets. Isolation methods of exosomes and the latest technological advances are also discussed. Furthermore, novel urinary exosomal biomarkers are highlighted with special emphasis on their clinical applicability (particularly sensitivity, specificity, reliability, and other aspects). Finally, future trends for this field are analyzed and our perspectives are provided.

The role of micropeptides in biology.

Micropeptides are small polypeptides coded by small open-reading frames. Progress in computational biology and the analyses of large-scale transcriptomes and proteomes have revealed that mammalian genomes produce a large number of transcripts encoding micropeptides. Many of these have been previously annotated as long noncoding RNAs. The role of micropeptides in cellular homeostasis maintenance has been demonstrated. This review discusses different types of micropeptides as well as methods to identify them, such as computational approaches, ribosome profiling, and mass spectrometry.

Tracking Prostate Carcinogenesis over Time through Urine Proteome Profiling in an Animal Model: An Exploratory Approach.

Prostate cancer (PCa) is one of the most lethal diseases in men, which justifies the search for new diagnostic tools. The aim of the present study was to gain new insights into the progression of prostate carcinogenesis by analyzing the urine proteome. To this end, urine from healthy animals and animals with prostate adenocarcinoma was analyzed at two time points: 27 and 54 weeks. After 54 weeks, the incidence of pre-neoplastic and neoplastic lesions in the PCa animals was 100%. GeLC-MS/MS and subsequent bioinformatics analyses revealed several proteins involved in prostate carcinogenesis. Increased levels of retinol-binding protein 4 and decreased levels of cadherin-2 appear to be characteristic of early stages of the disease, whereas increased levels of enolase-1 and T-kininogen 2 and decreased levels of isocitrate dehydrogenase 2 describe more advanced stages. With increasing age, urinary levels of clusterin and corticosteroid-binding globulin increased and neprilysin levels decreased, all of which appear to play a role in prostate hyperplasia or carcinogenesis. The present exploratory analysis can be considered as a starting point for studies targeting specific human urine proteins for early detection of age-related maladaptive changes in the prostate that may lead to cancer.

Elucidating Citrullination by Mass Spectrometry and Its Role in Disease Pathogenesis.

This review focuses on discussing key mechanisms in disease pathogenesis mediated by the protein post-translational modification citrullination. These processes are discussed in depth in the context of complex diseases such as rheumatoid arthritis, cancer, central nervous system disorders, and cardiovascular disease. Additionally, a critical evaluation of challenges in laboratory detection of citrullination sites is also outlined. In this context, the role of mass spectrometry is discussed with a focus on contemporary techniques that offer promising options to detect the exact site of protein citrullination. Novel methods described in the paper have the potential to detect and quantify the occurrence of post-translational modification sites for diagnosis and therapeutic purposes with a high degree of specificity and sensitivity. Furthermore, they offer a much faster performance than traditional techniques making them ideal for large-scale experimentation.

The potential impact of salivary peptides in periodontitis.

Periodontitis is a complex immune-inflammatory condition characterized by the disruption of the periodontal ligament and subsequent formation of periodontal pockets, and by alveolar bone loss, often resulting in tooth loss. A myriad of factors, namely, genetic, metabolic, immunological, and inflammatory, is associated with progression of periodontitis. Periodontitis is also associated with systemic conditions such as neoplastic disorders, obesity, and diabetes. The current diagnosis of this disease relies on clinical measurements such as clinical attachment loss and probing depth, which have poor precision due to patient, operator and probe-related factors. Thus, there is a need to develop reliable, objective, and reproducible biomarkers for early diagnosis of periodontitis. In this regard, saliva, with contributions from the gingival crevicular fluid, holds great potential. However, most of the information on biomarkers of periodontium-related salivary proteins has come from studies on the molecular pathogenesis of periodontitis. In periodontitis, a more holistic approach, such as the use of -omics technologies, for biomarker discovery, is needed. Herein, we review the biomarkers proposed to date for the assessment of periodontitis, with emphasis on the role of salivary peptides in periodontitis and their assessment by high-throughput saliva proteomics. We also discuss the challenges pertaining to the identification of new periodontitis biomarkers in saliva.

Insights and clinical potential of proteomics in understanding spermatogenesis.

Introduction: With the worldwide decline on male fertility potential, the importance of the insight of the spermatogenic process has been increasing. In recent years, proteomic methodologies have been applied to seminal fluid of infertile men to search for infertility potential biomarkers. However, to understand the spermatogenic event and to search for treatment to spermatogenic impairment, comparative analysis of testicular proteomics is considered a powerful methodology.Areas covered: Herein, we present a critical overview of the studies addressing proteomic alterations in the development of spermatogenesis during puberty, as well as during the different phases of the spermatogenic event. The comparative studies of the proteomic testicular profile of men with and without spermatogenic impairment are also discussed and key proteins and pathways involved highlighted.Expert opinion: The usage of whole human testicular tissue with its heterogeneous cellular composition makes proteome data interpretation particularly challenging. This may be minimized by controlled experiments involving the collection of testicular tissue and sperm from the same individuals, integrated in a clinically characterized cohort of healthy and infertile men. The analysis of specific subcellular proteomes can add more information to the proteomic puzzle, opening new treatment possibilities for infertile/subfertile men.

Peptidomics and proteogenomics: background, challenges and future needs.

INTRODUCTION: With available genomic data and related information, it is becoming possible to better highlight mutations or genomic alterations associated with a particular disease or disorder. The advent of high-throughput sequencing technologies has greatly advanced diagnostics, prognostics, and drug development. AREAS COVERED: Peptidomics and proteogenomics are the two post-genomic technologies that enable the simultaneous study of peptides and proteins/transcripts/genes. Both technologies add a remarkably large amount of data to the pool of information on various peptides associated with gene mutations or genome remodeling. Literature search was performed in the PubMed database and is up to date. EXPERT OPINION: This article lists various techniques used for peptidomic and proteogenomic analyses. It also explains various bioinformatics workflows developed to understand differentially expressed peptides/proteins and their role in disease pathogenesis. Their role in deciphering disease pathways, cancer research, and biomarker discovery using biofluids is highlighted. Finally, the challenges and future requirements to overcome the current limitations for their effective clinical use are also discussed.

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).

COVID-19 in chronic hemodialysis patients: A report of 9 cases in Madrid, Spain.

INTRODUCTION: In December 2019, a new respiratory disease, named COVID-19, caused by a novel coronavirus, emerged in Wuhan and since then spread rapidly throughout China and worldwide. Hemodialysis patients are an especially vulnerable subgroup of the general population. However, there are only a few reports on the course of COVID-19 in maintenance hemodialysis patients. CASE REPORT: We describe in depth the clinical, analytical, and radiological details of 9 hemodialysis patients from a single center in Madrid (Spain) diagnosed with COVID-19. Furthermore, we describe and discuss the therapeutic aspects and the patients' outcomes. DISCUSSION: We present one of the first case series of chronic hemodialysis patients with COVID-19. Between March 14 and April 8, 2020, out of 76 prevalent patients in our hemodialysis unit, 9 (11.8%) patients were diagnosed with COVID-19. The most common symptoms were fever (77.8%), asthenia (77.8%), cough (55.6%), and dyspnea (33.3%). A total of 3 patients developed severe pneumonia, whereas 4 patients developed mild pneumonia. In 2 patients, no pathologic changes were found on chest radiography. All patients presented lymphopenia. While 6 (66.7%) patients required hospitalization, none of them was admitted to intensive care unit. The most common treatments used were azithromycin (100%), hydroxychloroquine (66.7%), lopinavir/ritonavir (55.6%) and ß-interferon (22.2%). In general, we observed a mild to moderate severity of disease in our case series. One patient died, however due to a cause not related to COVID-19.

Mining the Biomarker Potential of the Urine Peptidome: From Amino Acids Properties to Proteases.

Native biofluid peptides offer important information about diseases, holding promise as biomarkers. Particularly, the non-invasive nature of urine sampling, and its high peptide concentration, make urine peptidomics a useful strategy to study the pathogenesis of renal conditions. Moreover, the high number of detectable peptides as well as their specificity set the ground for the expansion of urine peptidomics to the identification of surrogate biomarkers for extra-renal diseases. Peptidomics further allows the prediction of proteases (degradomics), frequently dysregulated in disease, providing a complimentary source of information on disease pathogenesis and biomarkers. Then, what does urine peptidomics tell us so far? In this paper, we appraise the value of urine peptidomics in biomarker research through a comprehensive analysis of all datasets available to date. We have mined > 50 papers, addressing > 30 different conditions, comprising > 4700 unique peptides. Bioinformatic tools were used to reanalyze peptide profiles aiming at identifying disease fingerprints, to uncover hidden disease-specific peptides physicochemical properties and to predict the most active proteases associated with their generation. The molecular patterns found in this study may be further validated in the future as disease biomarker not only for kidney diseases but also for extra-renal conditions, as a step forward towards the implementation of a paradigm of predictive, preventive and personalized (3P) medicine.

Top-Down Proteomics of Human Saliva Discloses Significant Variations of the Protein Profile in Patients with Mastocytosis.

Mastocytosis is a myeloproliferative neoplasm causing abnormal clonal mast cell accumulation in different tissues, such as skin and bone marrow. A cutaneous subtype (CM) is distinguished from a systemic one (SM); SM patients can be grouped into SM with (SM+C) or without (SM-C) additional cutaneous lesions, and their classification is often challenging. This study was purposed to highlight variations in the salivary proteome of patients with different mastocytosis subtypes and compared to healthy controls. A top-down proteomics approach coupled to a label-free quantitation revealed salivary profiles in patients different from those of controls and a down-regulation of peptides/proteins involved in the mouth homeostasis and defense, such as statherin, histatins, and acidic proline-rich proteins (aPRPs), and in innate immunity and inflammation, such as the cathepsin inhibitors, suggesting a systemic condition associated with an exacerbated inflammatory state. The up-regulation of antileukoproteinase and S100A8 suggested a protective role against the disease status. The two SM forms were distinguished by the lower levels of truncated forms of aPRPs, statherin, P-B peptide, and cystatin D and the higher levels of thymosin ß4 and α-defensins 1 and 4 in SM-C patients with respect to SM+C. Data are available via ProteomeXchange with identifier PXD017759.

De novo sequencing of proteins by mass spectrometry.

INTRODUCTION: Proteins are crucial for every cellular activity and unraveling their sequence and structure is a crucial step to fully understand their biology. Early methods of protein sequencing were mainly based on the use of enzymatic or chemical degradation of peptide chains. With the completion of the human genome project and with the expansion of the information available for each protein, various databases containing this sequence information were formed. AREAS COVERED: De novo protein sequencing, shotgun proteomics and other mass-spectrometric techniques, along with the various software are currently available for proteogenomic analysis. Emphasis is placed on the methods for de novo sequencing, together with potential and shortcomings using databases for interpretation of protein sequence data. EXPERT OPINION: As mass-spectrometry sequencing performance is improving with better software and hardware optimizations, combined with user-friendly interfaces, de-novo protein sequencing becomes imperative in shotgun proteomic studies. Issues regarding unknown or mutated peptide sequences, as well as, unexpected post-translational modifications (PTMs) and their identification through false discovery rate searches using the target/decoy strategy need to be addressed. Ideally, it should become integrated in standard proteomic workflows as an add-on to conventional database search engines, which then would be able to provide improved identification.

Taste sensitivity and lifestyle are associated with food preferences and BMI in children.

Oral food perception together with lifestyle may affect food preferences and choices, influencing weight gain and obesity development. The present study was designed to evaluate the association of biological (taste sensitivity) and lifestyle variables with children food preferences, assessing whether all these variables contribute to explain BMI percentile. After anthropometric evaluation, 387 children were classified for bitter and sweet taste sensitivities. Socioeconomic/lifestyle aspects and hedonics for 36 foods were collected. Watching TV during meals associate with lower preference for several vegetables, as well as being sweet taste low sensitive, in the case of girls. Moreover, regression analysis showed that bitter taste sensitivity is one of the variables contributing to explain high BMI percentiles. These results present evidences that both biological and socioeconomic and the attention that is given to food (eating in the presence or absence of distractors) are aspects that should be considered in children nutrition to prevent obesity.

FGF2 induces breast cancer growth through ligand-independent activation and recruitment of ERα and PRBΔ4 isoform to MYC regulatory sequences.

Progression to hormone-independent growth leading to endocrine therapy resistance occurs in a high proportion of patients with estrogen receptor alpha (ERα) and progesterone receptors (PR) positive breast cancer. We and others have previously shown that estrogen- and progestin-induced tumor growth requires ERα and PR interaction at their target genes. Here, we show that fibroblast growth factor 2 (FGF2)-induces cell proliferation and tumor growth through hormone-independent ERα and PR activation and their interaction at the MYC enhancer and proximal promoter. MYC inhibitors, antiestrogens or antiprogestins reverted FGF2-induced effects. LC-MS/MS identified 700 canonical proteins recruited to MYC regulatory sequences after FGF2 stimulation, 397 of which required active ERα (ERα-dependent). We identified ERα-dependent proteins regulating transcription that, after FGF2 treatment, were recruited to the enhancer as well as proteins involved in transcription initiation that were recruited to the proximal promoter. Also, among the ERα-dependent and independent proteins detected at both sites, PR isoforms A and B as well as the novel protein product PRBΔ4 were found. PRBΔ4 lacks the hormone-binding domain and was able to induce reporter gene expression from estrogen-regulated elements and to increase cell proliferation when cells were stimulated with FGF2 but not by progestins. Analysis of the Cancer Genome Atlas data set revealed that PRBΔ4 expression is associated with worse overall survival in luminal breast cancer patients. This discovery provides a new mechanism by which growth factor signaling can engage nonclassical hormone receptor isoforms such as PRBΔ4, which interacts with growth-factor activated ERα and PR to stimulate MYC gene expression and hence progression to endocrine resistance.

Comparison of salivary proteome of children with different sensitivities for bitter and sweet tastes: association with body mass index.

BACKGROUND/OBJECTIVES: Oral sensorial perception is a key aspect in food choices and knowing the mechanisms modulating such perception is of major importance in the context of child obesity, which is reaching high rates in Mediterranean countries. Salivary proteome has been linked to taste sensitivity in adults. The aim of this study was to search for differences in salivary proteomes of children with different bitter or sweet taste sensitivities and to assess if these potential differences are associated with their body mass index percentile (BMI percentile). SUBJECTS/METHODS: 387 children aged 8-9 years old were assessed for BMI percentile and classified according to their sensitivity to bitter and sweet tastes, according to their caffeine and sucrose detection thresholds, respectively. Saliva protein composition was compared among taste sensitivity groups, taking into account BMI percentile and gender, using gel-based proteomics approaches, coupled to mass spectrometry for protein identification. RESULTS: Among the salivary proteins related to bitter taste sensitivity, higher levels of cystatins were observed in bitter-sensitive children, in the case of those of normal weight, and in bitter low-sensitive, in the case of overweight children. For sweetness, the relationship between saliva and taste perception was also dependent on BMI percentile, with several proteins (including salivary cystatins) differing between taste sensitivity groups, with disparities arising between normal-weight and overweight children. Cystatin isoforms A, B and SA were observed to be considerably increased in saliva from obese children. CONCLUSIONS: Salivary proteome is related with sensitivities to bitter and sweet tastes in children, but the association is dependent on BMI percentile and gender.

Sample Treatment for Saliva Proteomics.

The preanalytical phase of saliva proteomics/peptidomics, which includes sample collection, handling, and storage, represents a major challenge for any researcher that envisions sensitive and high-throughput analyses, coupled to well-controlled study design. The methodology used to collect saliva determines the contribution of each salivary gland to saliva composition with impact on data retrieved from proteomics/peptidomics. The awareness of the importance of this step in the analysis of saliva has prompted the proposal of several collection strategies. Moreover, numerous commercial devices are available in an attempt to routine the procedures. However, whatever the chosen method, procedures should be kept simple, standardized to get better reproducibility and repeatability on saliva proteomics analysis. Sample preservation is also a key step in saliva proteomics/peptidomics, and the implemented lab procedures should avoid posttranslational modifications such as proteolysis, as well as protein precipitation.In this chapter, we provide recommendations for saliva sampling and preservation, envisaging to standardize procedures that facilitate the use of saliva in clinical applications and the translation of proteomics data to diagnosis and/or definition of therapeutic targets.

Reviewing Mechanistic Peptidomics in Body Fluids Focusing on Proteases.

The comprehension of how protease networks sculpt proteomes might help to disclose the functional annotation of the peptidome in health and disease. Envisioning to add new insights on the protease networks involved in the regulation of body fluid peptidomes, the authors apply Proteasix software to predict the proteases involved in the generation of the naturally occurring peptides present in six of the most studied human body fluids. Peptidome data is collected from the databases and from experimental studies. The analysis highlights 132 putative proteases from four families with the predominance of serine proteases and metalloproteases. From these, 49 proteases seem to be common to all fluids and are mostly associated to extracellular matrix organization as well as protein/peptide hormone processing. Data analysis also emphasizes: i) the similarity between plasma and CSF protease profiles; ii) that saliva and tears share proteases involved in the generation of peptides with antimicrobial activity; iii) that urine is the body fluid with the highest number of unique putative proteases, precluding an easy tracing of proteolytic events in this case. Taken together, the analysis emphasizes the intricate modus operandi of proteases, challenged by the interconnected pathways and amplification cascades in which they are involved.

Uncovering the exercise-related proteome signature in skeletal muscle.

Exercise training has been recommended as a nonpharmacological strategy for the prevention and attenuation of skeletal muscle atrophy in distinct pathophysiological conditions. Despite the well-established phenotypic alterations, the molecular mechanisms underlying exercise-induced skeletal muscle remodeling are poorly characterized. Proteomics based on mass spectrometry have been successfully applied for the characterization of skeletal muscle proteome, representing a pivotal approach for the wide characterization of the molecular networks that lead to skeletal muscle remodeling. Nevertheless, few studies were performed to characterize the exercise-induced proteome remodeling of skeletal muscle, with only six research papers focused on the cross-talk between exercise and pathophysiological conditions. In order to add new insights on the impact of distinct exercise programs on skeletal muscle proteome, molecular network analysis was performed with bioinformatics tools. This analysis highlighted an exercise-related proteome signature characterized by the up-regulation of the capacity for ATP generation, oxygen delivery, antioxidant capacity and regulation of mitochondrial protein synthesis. Chronic endurance training up-regulates the tricarboxylic acid cycle and oxidative phosphorylation system, whereas the release of calcium ion into cytosol and amino acid metabolism are the biological processes up-regulated by a single bout of exercise. Other issues as exercise intensity, load, mode and regimen as well as muscle type also influence the exercise-induced proteome signature. The comprehensive analysis of the molecular networks modulated by exercise training in health and disease, taking in consideration all these variables, might not only support the therapeutic effect of exercise but also highlight novel targets for the development of enhanced pharmacological strategies.