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1 Extracellular vesicles (EVs) are membranous structures derived from the endosomal system or generated by plasma membrane shedding, rich in DNA, RNA, proteins, and lipids, which serve in cell-to-cell communication. + 3334 word(s) 3334 2020-11-18 10:57:04 |
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Chitoiu, L.; Dobranici, A.; Gherghiceanu, M.; Dinescu, S.; Costache, M. Extracellular Vesicles Cargo and Roles. Encyclopedia. Available online: https://encyclopedia.pub/entry/3249 (accessed on 18 November 2024).
Chitoiu L, Dobranici A, Gherghiceanu M, Dinescu S, Costache M. Extracellular Vesicles Cargo and Roles. Encyclopedia. Available at: https://encyclopedia.pub/entry/3249. Accessed November 18, 2024.
Chitoiu, Leona, Alexandra Dobranici, Mihaela Gherghiceanu, Sorina Dinescu, Marieta Costache. "Extracellular Vesicles Cargo and Roles" Encyclopedia, https://encyclopedia.pub/entry/3249 (accessed November 18, 2024).
Chitoiu, L., Dobranici, A., Gherghiceanu, M., Dinescu, S., & Costache, M. (2020, November 26). Extracellular Vesicles Cargo and Roles. In Encyclopedia. https://encyclopedia.pub/entry/3249
Chitoiu, Leona, et al. "Extracellular Vesicles Cargo and Roles." Encyclopedia. Web. 26 November, 2020.
Extracellular Vesicles Cargo and Roles
Edit

Extracellular vesicles (EVs) are membranous structures produced in the endosomal system or generated by plasma membrane shedding, which have been identified as an important hallmark for intercellular communication. Among them, a particular category of EVs are the exosomes, which are nanovesicles of approximately 30-150 nm, produced in the endosomal pathway. 

extracellular vesicles exosomes exosomal cargo exosomal RNA exosomal markers

1. Introduction

In the past 10 years, the scientific community’s perspective toward extracellular vesicles (EVs) has markedly focused on their role as mediators of intercellular communication, adding more insights to their known diversity and functions [1][2]. Underestimated in terms of heterogeneity, these membranous structures carry a diverse pool of functional biomolecules, most of them having unknown roles. So far, many attempts to screen these molecules or to construct reliable and reproducible molecular profiles of EV load have begun. Simultaneously, the rise of high-throughput applications in EV biology has enabled the collection of biological data at faster rates. These data are reported in various formats across a plethora of repositories, making searching and comparing results increasingly difficult. Computational methods can be used to provide integration strategies so that biological data can be observed in a system-wide manner, thus reflecting the elaborate interplay among biological variation at different levels of regulation [3].

The interest in multi-omics data integration emerges from the nature of a cell’s response to different conditions, which is best explained mechanistically when corroborating all omics levels [4]. Previous successful attempts of integrating multi-omics data have led to the characterization of informationally dense networks that accurately model human pathologies. By integrating genes and their known phenotypic profiles, groups of molecules that are involved in the same biological process (functional modules) have been identified [5]. Using a network-based data analysis approach, one could quantify how these modules are shared by similar diseases. According to how interconnected these modules are, disease-related genes having high association rates with a wide array of biomolecules may have a central role in the human interactome, often coding proteins acting as hubs in modulating systemic responses [6].

2. Biological Diversity of EVs

EVs are membranous structures produced in the endosomal system or generated by plasma membrane shedding. They are mainly found in biological fluids and are considered a viable way of cell-to-cell communication, with various implications in physiological and pathological processes [8][9]. So far, EVs have been isolated from a large variety of biological fluids such as plasma [10], urine [11], saliva [12], cerebrospinal fluid [13], breast milk [14], ascitic fluid [15], gastric juice [16], bile [17], sputum [18], bronchoalveolar lavage fluid [19], epididymal fluid [20], and tears [21]. EVs are a highly heterogeneous population, not only by means of size and biogenesis, but also composition and biomarkers, having specific DNA, RNA, protein, lipid, and metabolite cargo (figure 1). For a long period of time, size was the main characteristic used to classify EVs into exosomes and microvesicles (MVs), but contradictory results made it difficult and confusing, creating the need for alternative criteria [22][23][24][25]. As the EV biogenesis involves two main pathways that generate MVs and exosomes by membrane-trafficking processes, differentially expressed markers started being taken into consideration for a more accurate classification. Exosomes derive from the endosomal system, being synthesized as intraluminal vesicles within multivesicular bodies. Their sorting machineries are either dependent or independent of the endosomal sorting complex required for transport (ESCRT) proteins. MV generation is simpler, by plasma membrane shedding. In spite of the different packing mechanisms, the molecular profiles derived from both biogenesis processes overlap, making the MVs–exosomes dichotomy no longer useful [8][23][26] (Table 1).

Figure 1. EVs content in RNA, protein, lipid, and metabolites. Several areas of biology and medical research (input) generate complex genomics, transcriptomics, proteomics, lipidomics, and metabolomics analysis that can contribute to understanding several biological processes and functions (output).

Table 1. Evolution of extracellular vesicles (EV) dichotomous classification according to the accumulation of recent knowledge.

Historical Criteria

Early Knowledge

Current Knowledge

Size

MVs range between 100 and 1000 nm, while exosomes have dimeters smaller than 100 nm [23][27]

Classification no longer in use, MVs can be smaller than 100 nm, exosomes have an upper limit based on endosomal size (up to 150 nm or larger); “small EVs” and “medium/large EVs” nomenclature is preferred [25]

Protein content

Different marker profiles due to biogenesis: GTP-binding proteins (ARF6), vesicle-associated membrane protein 3 (VAMP3), proteasomes, mitochondria-related proteins for MVs, transduction or scaffolding proteins (Syntenin 1), extracellular matrix, cell adhesion, receptor binding proteins and endosome-binding proteins (TSG101) for exosomes [24][28][29]

No molecular markers that could characterize specifically each EV subtype, yet validation with three markers from three different classes is required in order to evaluate tissue specificity, lipid, or membrane-binding ability and purity [25]

Lipid content

Enriched contents according to the EV subtype: ceramides and sphingomyelins in MVs, cardiolipins in exosomes [29]

Lipid ratios in EVs are not yet established [25]; more studies are needed in order to compare the lipid profiles of EVs with co-isolated lipoproteins and validate characteristic EV lipid contents such as lysoglycerophospholipids [30]

Nucleic acid content

DNA, mRNA, ncRNA, and especially miRNA in both MVs and exosomes; origin-specific miRNA profiles for exosomes [8][31]

Confirmed specific incorporation of RNAs into subtypes of EVs [25]

Isolation and purification methods

Differential centrifugation or ultracentrifugation (10,000–20,000× g for MVs, 100,000–125,000× g for exosomes), size exclusion chromatography, immunoaffinity capture [32][33][34][35][36]

No “golden standard” method to isolate and/or purify EVs, the choice is to be made based on the downstream applications, recovery, and specificity rates [24][25]

EVs exert various biological roles, being involved in the immune response [37][38], regeneration [32], and as components of the extracellular matrix [39]. Early studies of EV function suggested antigen-presenting properties and the ability to stimulate T cell responses [34][40][41][42]. More recent studies indicate that EVs participate as well in autoimmune modulation processes in type 1 diabetes, as islets of Langerhans release EVs that are capable of activating peripheral blood mononuclear cells (PBMCs) [43]. In cancer, EVs are exchanged by cells within the tumor microenvironment in order to promote tumor growth and metastasis [44], vascularization [45], dormancy [46], chemoresistance [47], and metabolic reprogramming [48], mainly by transferring non-coding RNA molecules, such as miRNAs. Recently, EVs have been described as agents in modulating the spread of cancer cells toward their preferred metastases locations. Before invading other tissues and organs, tumors assure their growth by promoting the formation of a favorable micro-environment named the pre-metastatic niche (PMN) [49]. In colorectal and lung cancer, EVs enriched in small RNA species participate in activating pro-inflammatory processes through Toll-like receptor (TRL) pathways [50][51]. Other mechanisms that support metastasis are the mesothelial to mesenchymal transition and the promotion of angiogenesis through delivering miR-21-5p and miR-25-3p [52][53]. PMN formation as a result of cell-to-cell communication mediated by EVs was also observed in pancreatic, ovarian, and lung cancer [54][55][56].

As EVs play an important role in tumor growth and metastasis, it is fair to consider that they may represent therapeutic targets as well. For this matter, three strategies that might alleviate the EV contribution to tumor development were postulated: the elimination of circulating EVs based on specific surface markers, the inhibition of EV release, and the impairment of EV absorption [57]. For example, targeting the gene for the autophagy related 5 (ATG5) protein that stimulates in vivo metastasis through EV production might have promising results in holding tumor progression [58]. Drug repurposing is another promising alternative, as FDA-approved compounds such as the antibiotic sulfisoxazole impair EV secretion in breast cancer cells [59]. Taken together, EVs are of great interest not only for their crucial implications in physiological and pathological processes but also for their clinical promise.

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