Empowering peptidomics: utilizing computational tools and approaches.

Bioinformatics plays a critical role in the advancement of peptidomics by providing powerful tools for data analysis, interpretation and integration. Peptidomics is concerned with the study of peptides, short chains of amino acids with diverse biological functions. This area includes peptide identification and characterization, database construction, de novo sequencing, functional annotation, omics data integration and systems biology. Artificial intelligence techniques, such as machine learning and natural language processing, aid in the interpretation of peptide sequence data and the generation of biological insights. By using bioinformatics approaches, peptidomics researchers can accelerate peptide discovery, understand their functions and gain insights into complex molecular interactions.

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.

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.

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.

Insights on the molecular targets of cardiotoxicity induced by anticancer drugs: A systematic review based on proteomic findings.

Several anticancer agents have been associated with cardiac toxic effects. The currently proposed mechanisms to explain cardiotoxicity differ among anticancer agents, but in fact, the specific modulation is not completely elucidated. Thus, this systematic review aims to provide an integrative perspective of the molecular mechanisms underlying the toxicity of anticancer agents on heart muscle while using a high-throughput technology, mass spectrometry (MS)-based proteomics. A literature search using PubMed database led to the selection of 27 studies, of which 13 reported results exclusively on animal models, 13 on cardiomyocyte-derived cell lines and only one included both animal and a cardiomyocyte line. The reported anticancer agents were the proteasome inhibitor carfilzomib, the anthracyclines daunorubicin, doxorubicin, epirubicin and idarubicin, the antimicrotubule agent docetaxel, the alkylating agent melphalan, the anthracenedione mitoxantrone, the tyrosine kinase inhibitors (TKIs) erlotinib, lapatinib, sorafenib and sunitinib, and the monoclonal antibody trastuzumab. Regarding the MS-based proteomic approaches, electrophoretic separation using two-dimensional (2D) gels coupled with tandem MS (MS/MS) and liquid chromatography-MS/MS (LC-MS/MS) were the most common. Overall, the studies highlighted 1826 differentially expressed proteins across 116 biological processes. Most of them were grouped in larger processes and critically analyzed in the present review. The selection of studies using proteomics on heart muscle allowed to obtain information about the anticancer therapy-induced modulation of numerous proteins in this tissue and to establish connections that have been disregarded in other studies. This systematic review provides interesting points for a comprehensive understanding of the cellular cardiotoxicity mechanisms of different anticancer drugs.

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.

Novel Exosome Biomarker Candidates for Alzheimer's Disease Unravelled Through Mass Spectrometry Analysis.

Exosomes are small extracellular vesicles (EVs) present in human biofluids that can transport specific disease-associated molecules. Consequently blood-derived exosomes have emerged as important peripheral biomarker sources for a wide range of diseases, among them Alzheimer's disease (AD). Although there is no effective cure for AD, an accurate diagnosis, relying on easily accessible peripheral biofluids, is still necessary to discriminate this disease from other dementias, test potential therapies and even monitor rate of disease progression. The ultimate goal is to produce a cost-effective and widely available alternative, which can also be employed as a first clinical screen. In this study, EVs with exosome-like characteristics were isolated from serum of Controls and AD cases through precipitation- and column-based methods, followed by mass spectrometry analysis. The resulting proteomes were characterized by Gene Ontology (GO) and multivariate analyses. Although GO terms were similar for exosomes' proteomes of Controls and ADs, using both methodologies, a clear segregation of disease cases was obtained when using the precipitation-based method. Nine significantly different abundant proteins were identified between Controls and AD cases, representing putative biomarker candidate targets. Among them are AACT and C4BPα, two Aß-binding proteins, whose exosome levels were further validated in individuals from independent cohorts using antibody-based approaches. The findings discussed represent an important contribution to the identification of novel exosomal biomarker candidates useful as potential blood-based tools for AD diagnosis.

Sexual dimorphism in cardiac remodeling: the molecular mechanisms ruled by sex hormones in the heart.

Heart failure (HF) is growing in prevalence, due to an increase in aging and comorbidities. Heart failure with reduced ejection fraction (HFrEF) is more common in men, whereas heart failure with preserved ejection fraction (HFpEF) has a higher prevalence in women. However, the reasons for these epidemiological trends are not clear yet. Since HFpEF affects mostly postmenopausal women, sex hormones should play a pivotal role in HFpEF development. Furthermore, for HFpEF, contrary to HFrEF, effective therapeutic approaches are missing. Interestingly, studies evidenced that some therapies can have better results in women than in HFpEF men, emphasizing the necessity of understanding these observations at a molecular level. Thus, herein, we review the molecular mechanisms of estrogen and androgen actions in the heart in physiological conditions and explain how its dysregulation can lead to disease development. This clarification is essential in the road for an effective personalized management of HF, particularly HFpEF, towards the development of sex-specific therapeutic approaches.

Exploring the Role of Oxidative Stress in Sperm Motility: A Proteomic Network Approach.

Significance: Infertility is a major global health problem, with nearly half of the cases being associated with male factors. Although reactive oxygen species (ROS) are crucial for sperm cell normal physiological processes, an imbalance between ROS production and antioxidants can lead to oxidative stress that can impair sperm function. Indeed, high semen ROS levels are reported in 30%-80% of infertile men. Recent Advances: Male oxidative stress infertility is an uprising classification for idiopathic infertility. Proteomic approaches, including quantitative mass spectrometry (MS)-based proteomics, are being utilized to explore the molecular mechanisms associated with oxidative stress in male infertility. Critical Issues: In this review, proteome data were collected from articles available on PubMed centered on MS-based proteomic studies, performed in seminal plasma and sperm cell samples, and enrolling men with impaired semen parameters. The bioinformatic analysis of proteome data with Cytoscape (ClueGO+CluePedia) and STRING tools allowed the identification of the biological processes more prevalent in asthenozoospermia, with focus on the ones related to oxidative stress. Future Directions: The identification of the antioxidant proteins in seminal plasma and sperm cells that can protect sperm cells from oxidative stress is crucial not only for a better understanding of the molecular mechanisms associated with male infertility but specially to guide new therapeutic possibilities. Antioxid. Redox Signal. 37, 501-520.

Association Between Estrogen Receptors and GATA3 in Bladder Cancer: A Systematic Review and Meta-Analysis of Their Clinicopathological Significance.

Background: Estrogen receptors alpha (ERα) and beta (ERß) and the cooperating protein GATA-binding factor 3 (GATA3) have been implicated in bladder carcinogenesis and tumour progression. GATA3 and ER have been functionally linked in the establishment of luminal fate in breast tissue, but to date their relationship in bladder cancer has not been established. This information will be useful to advance diagnostic and prognostic markers. Aim: To determine the relationship between the expression of ERα, ERß and GATA3 in bladder cancer, disclose their prognostic and diagnostic value and their association with clinicopathological characteristics. Methods: A comprehensive literature search in PubMed database was performed for all immunohistochemical studies of ERα, ERß and/or GATA3 in bladder cancer patients. We selected eligible studies in accordance with the PRISMA guidelines and evaluated methodological quality and risk of bias based on quality criteria from the reporting recommendations for tumour MARKer (REMARK) prognostic studies. Risk of bias assessment was performed using Review Manager 5. R software was used for all statistical analysis, the packages used were meta and dmetar for the standard meta-analysis, and netmeta for the network meta-analysis. Results: Thirteen studies were eligible for ERα, 5 for ERß and 58 for GATA3 meta-analysis. Low grade tumours showed significantly lower ERα expression. GATA3 was widely expressed in bladder tumours, especially urothelial carcinomas, with higher expression of GATA3 in low grade and low stage tumours. Data was insufficient to determine the prognostic value of either ERα or ERß, but GATA3-positivity was associated with higher recurrence free survival. A negative correlation between ERα or ERß positivity and GATA3 expression was disclosed. Additionally, several sources of heterogeneity were identified, which can be used to improve future studies. Conclusion: The clinicopathological value of ERα and ERß was inconclusive due to low availability of studies using validated antibodies. Still, this meta-analysis supports GATA3 as good prognostic marker. On the contrary, ERα-positivity was associated to higher grade tumours; while ERα and ERß were inversely correlated with GATA3 expression. Considering that it has previously been shown that bladder cancer cell lines have functional ERs, this suggests that ERα could be activated in less differentiated cells and independently of GATA3. Therefore, a comprehensive analysis of ERα and ERß expression in BlaCa supported by complete patient clinical history is required for the identification of BlaCa subtypes and subgroups of patients expressing ERα, to investigate if they could benefit from treatment with hormonal therapy. Systematic Review Registration: Prospero, CRD42021226836.

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).

Protein Aggregation Patterns Inform about Breast Cancer Response to Antiestrogens and Reveal the RNA Ligase RTCB as Mediator of Acquired Tamoxifen Resistance.

The protein quality control network, including autophagy, the proteasome and the unfolded protein response (UPR), is triggered by stress and is overactive in acquired antiestrogen therapy resistance. We show for the first time that the aggresome load correlates with apoptosis and is increased in antiestrogen-sensitive cells compared to endocrine-resistant variants. LC-MS/MS analysis of the aggregated proteins obtained after 4OH-tamoxifen and Fulvestrant treatment identified proteins with essential function in protein quality control in antiestrogen-sensitive cells, but not in resistant variants. These include the UPR modulators RTCB and PDIA6, as well as many proteasome proteins such as PSMC2 and PSMD11. RTCB is a tRNA and XBP1 ligase and its aggregation induced by antiestrogens correlated with impaired XBP1s expression in sensitive cells. Knock down of RTCB was sufficient to restore sensitivity to tamoxifen in endocrine-resistant cells and increased the formation of aggresomes, leading to apoptotic cell death. Analysis of primary human breast cancer samples and their metastases appearing after endocrine treatment showed that RTCB is only localized to aggresomes in the primary tumors, while total aggresomes, including aggregated RTCB, were significantly reduced in the metastases. Therefore, different protein aggregation patterns may indicate loss of function of essential proteins resulting in enhanced protein aggregation that can be used to identify antiestrogen-resistant breast cancer cells and improve the response to antiestrogenic therapy.

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.

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.

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.

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.

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.