Pub Date : 2021-08-12DOI: 10.5772/intechopen.98278
Luís Perpétuo, R. Ferreira, Sofia Guedes, Francisco Amado, R. Vitorino
Recently, proteomics has emerged as an important tool for understanding biological systems, protein–protein interactions, and networks that ultimately lead to a deeper understanding of the underlying mechanisms of certain diseases. More recently, the study of secretomes, a type of proteomics, has also been highlighted as a potential next step in the field of diagnosis/prognosis. The secretome is the set of proteins expressed by an organism and secreted into the extracellular space, comprising 13–20% of all proteins. Since almost all, if not all, organs produce secretomes, this means that it is possible to study secretomes and trace these proteins back to their origin, supporting the idea that this could indeed be very important in diagnosing certain diseases. This is often combined with techniques such as mass spectrometry to measure the secretome of, for example, a particular tissue, and bioinformatics tools and databases to give us an idea of what to expect (prediction). In this paper, we will give a general overview of this world, but with a focus on the new bioinformatics tools and databases, their advantages and disadvantages, as well as a deeper look at isolation systems for proteomes, specifically salivary secretomes. Indeed, the salivary secretome represents a valuable new tool capable of providing insights into immunopathology and potentially aiding in diagnostics. Furthermore, we will explore applications of these methods and give an idea of what the future holds for such promising techniques: Salivary secretome in conjunction with bioinformatics tools/databases in the diagnosis of diseases (such as diabetes, Sjogren’s syndrome, and cardiovascular disease).
{"title":"The Salivary Secretome","authors":"Luís Perpétuo, R. Ferreira, Sofia Guedes, Francisco Amado, R. Vitorino","doi":"10.5772/intechopen.98278","DOIUrl":"https://doi.org/10.5772/intechopen.98278","url":null,"abstract":"Recently, proteomics has emerged as an important tool for understanding biological systems, protein–protein interactions, and networks that ultimately lead to a deeper understanding of the underlying mechanisms of certain diseases. More recently, the study of secretomes, a type of proteomics, has also been highlighted as a potential next step in the field of diagnosis/prognosis. The secretome is the set of proteins expressed by an organism and secreted into the extracellular space, comprising 13–20% of all proteins. Since almost all, if not all, organs produce secretomes, this means that it is possible to study secretomes and trace these proteins back to their origin, supporting the idea that this could indeed be very important in diagnosing certain diseases. This is often combined with techniques such as mass spectrometry to measure the secretome of, for example, a particular tissue, and bioinformatics tools and databases to give us an idea of what to expect (prediction). In this paper, we will give a general overview of this world, but with a focus on the new bioinformatics tools and databases, their advantages and disadvantages, as well as a deeper look at isolation systems for proteomes, specifically salivary secretomes. Indeed, the salivary secretome represents a valuable new tool capable of providing insights into immunopathology and potentially aiding in diagnostics. Furthermore, we will explore applications of these methods and give an idea of what the future holds for such promising techniques: Salivary secretome in conjunction with bioinformatics tools/databases in the diagnosis of diseases (such as diabetes, Sjogren’s syndrome, and cardiovascular disease).","PeriodicalId":346822,"journal":{"name":"Secretomics [Working Title]","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134221907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-06-19DOI: 10.5772/intechopen.97544
Yanling Cai, Di sWu
Extracellular vesicles (EVs) are heterogeneous due to their cell of origins, biogenesis, stimuli in the microenvironment and so on. Single EV analysis is required for the study of EV heterogeneity. Besides the investigation of EV biology, single EV analysis technologies are promising approach for liquid biopsy, which relies on the detection of biomarker EVs readily available in body fluids but in trace amount. However, EVs are nano-scaled structures, which beyond the resolution of conventional technologies like optical microscopes, flow cytometers and so on. In this chapter, we will discuss advanced strategies for studying single EVs, including single EV imaging systems, flow cytometers, nano-sensing technologies and single EV barcoding assay.
{"title":"High-Throughput Single Extracellular Vesicle Profiling","authors":"Yanling Cai, Di sWu","doi":"10.5772/intechopen.97544","DOIUrl":"https://doi.org/10.5772/intechopen.97544","url":null,"abstract":"Extracellular vesicles (EVs) are heterogeneous due to their cell of origins, biogenesis, stimuli in the microenvironment and so on. Single EV analysis is required for the study of EV heterogeneity. Besides the investigation of EV biology, single EV analysis technologies are promising approach for liquid biopsy, which relies on the detection of biomarker EVs readily available in body fluids but in trace amount. However, EVs are nano-scaled structures, which beyond the resolution of conventional technologies like optical microscopes, flow cytometers and so on. In this chapter, we will discuss advanced strategies for studying single EVs, including single EV imaging systems, flow cytometers, nano-sensing technologies and single EV barcoding assay.","PeriodicalId":346822,"journal":{"name":"Secretomics [Working Title]","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121084735","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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