Subgroups of Extracellular Vesicles: Can They Be Defined by “Labels?”

Abstract

Extracellular vesicles (EVs) are a class of lipid bilayer membranes, containing lipids, nucleic acids (DNA and RNA), proteins, and other substances. They are produced by almost all types of cells and act as signaling intermediaries between cells and/or tissues through different mechanisms involving complex signals. EVs produced by each type of cells are composed of highly heterogeneous and inhomogeneous subgroups with different biological functions. Therefore, in the past few decades, researchers have tried to use different “labels” to define the subgroups of EVs, and explore the differences in them. However, a unified standard for defining the populations of EVs has not yet been established so far. In this study, we review and summarize the use of different “labels” to define subgroups of EVs.

Introduction

“ISEV” endorses ‘extracellular vesicles' (EVs) as the generic term for particles naturally released from the cell, which are delimited by a lipid bilayer and cannot replicate, that is, do not contain a functional nucleus (Théry et al., 2018).” Wolf and his colleagues described EVs for the first time in 1967 as a kind of tiny particles derived from platelets, found in normal plasma and serum. These particles were separated by high-speed centrifugation, but different from platelets, and were described by Wolf as “platelet dust” (Wolf, 2010). In 1981, during the process of culturing normal and tumor cells, Trams and his colleagues discovered that the shed vesicles constituted a selective portion of the plasma membrane (PM) and may be involved in physiological processes.

At the same time, they observed two kinds of vesicles under the electron microscope, one of which was irregular in shape with a diameter of about 500–1000 nm, and another was smaller spherical vesicles with an average size of about 40 nm, called by them as exosomes (Trams et al., 1981). Later, researchers discovered EVs with different sizes and functions from previously found exosomes, such as ectosomes (Hess et al., 1999), microparticles (Kranendonk et al., 2014), and oncosomes (D'Asti et al., 2012). EVs have now been widely recognized to contain a variety of different contents, such as nucleic acids, proteins, and lipid molecules (Valadi et al., 2007; Keerthikumar et al., 2016).

These EVs leave their donor cells and enter the extracellular environment to participate in intercellular communication (Subra et al., 2010) or reach the body's blood (Grant et al., 2011), lymph (Raposo et al., 1996), urine (Pisitkun et al., 2004), and so on. This cluster of EVs is highly heterogeneous and inhomogeneous, varying in size, content, and effect on receptor cell function (van der Pol et al., 2012).

Therefore, how to divide EVs into subgroups has become a hot research topic. International Society for Extracellular Vesicles (ISEV) divides EVs into two subgroups according to the two major cellular sites of EV biogenesis: the PM and the endosomal system. First, the term “Exosome” was initially used for vesicles shed from the PM, later specifically referring to intraluminal vesicles formed in the multivesicular body (MVB), which are released from the cell by fusion of the MVB with the PM. Second, the terms “Microvesicle,” “Ectosome,” and “Microparticle” are used to describe vesicles shed directly from the PM (Russell et al., 2019). Nevertheless, this division of two subgroups is controversial because they cannot be efficiently separated using currently available isolation methods, and EVs are still heterogeneous inside the single subgroup and so on (Tiwari et al., 2021).

In addition to biogenesis pathway, size, shape, and density, surface molecules can also be used for classification (van der Pol et al., 2012). Therefore, for decades, many researches have been carried out on what labels should be used to define EV subgroups, but a unified standard for the defining labels has yet to be established, leading to confusion and conflicting naming. In this study we review and summarize the use of different “labels” to define EV subgroups, as shown in Table 1.

Table 1.

Subgroups of Extracellular Vesicles Defined by Different “Labels”

Labels	Source of EVs	Separation of EVs	Subgroups	References
Size	All cell types		sEVs<100 or <200 nm	Théry et al. (2009); van der Pol et al. (2012); Théry et al. (2018)
	All cell types		m/lEVs>200 nm	Théry et al. (2009); van der Pol et al. (2012)
	B16-F10, 4T1, Pan02, AsPC-1, 4175	Differential ultracentrifugation +40% Sucrose density gradient centrifugation+ AF4	Exo-S:60–80 nmExo-L: 90–120 nm	Zhang et al. (2018)
	NRK cell	Differential ultracentrifugation (1000 g, 10 min, 2000 g, 20 min, and 150,000 g, 4 h)+Sucrose density gradient centrifugation	Migrasomes: 500–3000 nm	Ma et al. (2015); Melentijevic et al. (2017)
	PCa cells, human plasma	Differential ultracentrifugation (2800 g, 10 min, 10,000 g, 30 min, and 100,000 g, 1 h)+Optiprep™iodixanol density gradient	Oncosomes: 1.0–5.5 μm	Vagner et al. (2018)
Density	Most cell types	Ultracentrifugation (100,000–200,000 g)	1.13–1.19 g/cm³: Exos	Raposo et al. (1996); Escola et al. (1998)
	Most cell types	Ultracentrifugation (100,000–200,000 g)	1.032–1.068 g/cm³: sEVs	Marzesco et al. (2005)
	The human mast cell line HMC-1, B16-F10 cells	Differential ultracentrifugation (300 g, 10 min, 16,500 g, 20 min, and 120,000 g, 70 min)+Sucrose density gradient centrifugation	High-density (1.26–1.29 g/cm³) and low-density (1.12–1.19 g/cm³)	Willms et al. (2016); Lässer et al. (2017)
Morphology	Human mast cell line HMC-1	Differential ultracentrifugation (300 g, 10 min, 16,500 g, 20 min, and 118,000 g, 3.5 h)+Density gradient centrifugation (178,000 g, 16 h)	Single vesicles, double vesicles, triple vesicles or more, small double vesicles, oval vesicles, small tube vesicles, and large tubes Vesicles, incomplete vesicles, polymorphic vesicles	Zabeo et al. (2017)
Morphology	Brain EVs	High-resolution density gradients	Single-, double-, and triple-membrane–bound vesicles	D'Acunzo et al. (2021)
Protein	B16-F10 cells, A431 cells, N2a, H5V, hTERT immortalized mesenchymal stem cells	Differential ultracentrifugation (10,000 g, 30 min, and 1,100,000 g, 70 min)+Sucrose density gradient centrifugation	Commonly marked with ALIX, TSG101, CD9, CD81, and CD63	Willms et al. (2016)
	The human mast cell line HMC-1, B16-F10 cells	Differential ultracentrifugation (300 g, 10 min, 16,500 g, 20 min, and and 120,000 g, 70 min)+Sucrose density gradient centrifugation	Ribosome proteins: HD-EVs, Mitochondrial proteins: LD-EVs	Willms et al. (2016); Lässer et al. (2017)
	B16-F10 cells, A431 cells, N2a, H5V, hTERT immortalized mesenchymal stem cells	Differential ultracentrifugation (10,000 g, 30 min, and 1,100,000 g, 70 min)+Sucrose density gradient centrifugation	“Oxidoreductases,” “Dehydrogenases”: MV and LD-Exo“Translation,” “Ribonucleoproteins” and “Ribosomal proteins”: HD-Exo“G-proteins”: HD-Exo and LD-Exo“G-protein modulators”: LD-Exo	Willms et al. (2016)
Nucleic acid (DNA, RNA)	LNCaP and PC-3 cell line, human Plasma	Differential ultracentrifugation (1000 g, 10 min, 1200 g, 30 min, and 1,100,000 g, 1 h)	gDNA	Lázaro-Ibáñez et al. (2014)
	PC3 and U87 cell line	Differential ultracentrifugation (2800 g, 10 min, 10,000 g, 30 min, and 1,000,000 g, 1 h)+Optiprep™iodixanol density gradient	2 million bp DNA fragmentation: L-EV	Vagner et al. (2018)
	B16-F10 cells, A431 cells, N2a, H5V, hTERT immortalized mesenchymal stem cells	Differential ultracentrifugation (10,000 g, 30 min, and 1,100,000 g, 70 min)+Sucrose density gradient centrifugation	SLC38A1 upregulation: LD-Exo	Willms et al. (2016)
	B16-F10 cells, A431 cells, N2a, H5V, hTERT immortalized mesenchymal stem cells	Differential ultracentrifugation (10,000 g, 30 min, and 1,100,000 g, 70 min)+Sucrose density gradient centrifugation	18S and 28S rRNA: MV and LD-Exo30–150 nt RNA: HD-Exo	Willms et al. (2016)
Small molecule metabolic label	TPE and MPE	Differential ultracentrifugation (500 g, 15 min, 2000 g, 15 min, 20,000 g, 60 min, and 110,000 g, 90 min) (lEVs, pelleted at 20,000 g) and sEVs (pelleted at 110,000 g)	Phenylalanine, leucine, phosphatidylcholine 35:0, and sphingomyelin 44:3: LEVs	Luo et al. (2020)
	Human BMSC, human ASC, and human UCSC ECM plates	Differential ultracentrifugation (500 g, 10 min, 2500 g, 20 min, and 10,000 g, 30 min)	LPA and LPG: ExosmCL and LPI: MVBs	Hussey et al. (2020)
	Urinary EVs	Differential centrifugation (10,000 g, 30 min; and 100,000 g, 90 min)	CerP, HexSph, LacCer, M(IP)2 C, SHexCer, SHexSph: ExosPI-Cer: MVs	Singhto et al. (2019)

ECM, extracellular matrix protein; EVs, extracellular vesicles; LPA, lysophosphatidic acid; LPG, lysophosphatidylglycerol; LPI, lysophosphoinositol; mCL, monolysocardiolipin; m/lEVs, medium/large EVs; MPE, malignancy pleural effusion; MVBs, multivesicular bodies; MVs, microvesicles; sEVs, small EVs; rRNA, ribosomal RNA; TPE, tuberculosis pleural effusion.

Physical label

Size label

EVs are composed of vesicles of different sizes. According to Minimal Information for Studies of Extracellular Vesicles (MISEV) 2018 (Théry et al., 2018), EVs can be divided into subgroups according to their diameter, one of which is called small EVs (sEVs), with a diameter <100 or <200 nm, and another that is called medium/large EVs (M/lEVs), with a diameter >200 nm. By employing asymmetric flow field-flow fractionation (AF4), researchers identified two exosome subgroups (large exosome vesicles, Exo-L, 90–120 nm; and small exosome vesicles, Exo-S, 60–80 nm) and discovered an abundant population of nonmembranous nanoparticles termed “exomeres” (35 nm).

These discrete and abnormally small nanoparticles, ∼35 nm in diameter, exhibit different protein, lipid, RNA, and DNA profiles compared to exosomes (Zhang et al., 2018). Several laboratories have also discovered other vesicles of different sizes, such as exophers (Melentijevic et al., 2017) with a diameter of 1000–7800 nm, migrasomes (Ma et al., 2015) with a diameter of 500–3000 nm, and large oncosomes (Vagner et al., 2018) with a diameter of 1.0–5.5 μm.

Density label

EVs can be divided into different subgroups according to their density by combining differential centrifugation with density gradient centrifugation. Exosomes are present in the density of 1.13–1.19 g/cm³ (Raposo et al., 1996; Escola et al., 1998). sEVs are present in the density of 1.032–1.068 g/cm³ (Marzesco et al., 2005). Researchers have found that EV subgroups characterized by different densities contain different proteins, lipids, and RNA, as well as exert different biological functions (Aalberts et al., 2012; Brouwers et al., 2013; Kowal et al., 2016; Willms et al., 2016; Collino et al., 2017; Lässer et al., 2017).

In the two EVs subgroups of different densities released by human mast cells and human breast cancer cells, microRNA and mRNA are present in the low-density EV subgroup, but not in the high-density EV subgroup (Palma et al., 2012; Lässer et al., 2017), which shows that the RNA content in EVs of different densities is different. Also, the DNA content differs in EVs of different densities (Lázaro-Ibáñez et al., 2019). There are also differences in the proteins between high-density and low-density EVs released from mast cells and B16-F10 melanoma cells. High-density (1.26–1.29 g/cm³) EVs are rich in proteins associated with the nucleus and ribosomes, while low-density (1.12–1.19 g/cm³) EVs from mast cells are rich in proteins associated with the mitochondrion (Willms et al., 2016; Lässer et al., 2017).

Morphology label

EVs also vary in morphology. EVs have long been thought as spherical, but they appear cup shaped under the transmission electron microscope (TEM) as the consequence of the fixation step in the negative staining technique. With the development of technology, cryogenic transmission electron microscopy (Cryo-TEM) is used for the detection of EVs because it can maintain the natural form of EVs (Gould and Raposo, 2013).

Zabeo (Zabeo et al., 2017) classified EVs released by human mast cell lines by separating them at densities of 1.11–1.12 g/cm³. Most of the isolated vesicles (75%) were monolayer membranes with a diameter of less than 100 nm; however, nine different forms were observed, including single vesicles, double vesicles, triple vesicles or more, small double vesicles, oval vesicles, small tube vesicles and large tubes vesicles, incomplete vesicles, and polymorphic vesicles, which indicates that vesicles can be divided into different subgroups under a certain density gradient.

In studies of the pathogenesis of Alzheimer's disease and Down syndrome, the application of novel high-resolution density gradients to isolated brain EVs has demonstrated the isolation of various brain EV subgroups and the existence of a previously unknown EV group of mitochondrial origin. Morphologically, it differs from typical EVs. CryoEM reveals extensive heterogeneity of the brain EVs, including single-, double-, and triple-membrane–bound vesicles, with different luminal contents (D'Acunzo et al., 2021).

Chemical label

Protein label

Depending on the kind of EVs we want to discuss, their protein markers are not the same. According to MISEV 2018 recommendations, all prepared EVs should be analyzed for transmembrane or glycosyl-phosphatidyl-inositol-anchored proteins associated to PM and/or endosomes and cytosolic proteins, such as tetraspanins (CD63, CD81, and CD82), MHC class I, ESCRT-I/II/III, heat shock protein, and so on, so as to prove the existence of EVs and non-EV structural proteins for purity control. These proteins can be more or less identified in different subgroups of EVs, although they have not been published as negative control proteins for identifying subgroups of EVs (Théry et al., 2018).

Around 100,000 g EVs enrich the classical exosome marker proteins CD63, CD9, and CD81, compared with 2000 g EVs and 10,000 g EVs. However, these proteins (CD9, CD63, and CD81) also appear in other subgroups of EVs, such as microvesicles (MV) and apoptotic bodies (ABs), but with different expression of proteins (Crescitelli et al., 2013; Kowal et al., 2016).

CD9, CD63, CD81, and other marker proteins such as ALIX and TSG101 can be identified in both high-density and low-density EV subgroups (Willms et al., 2016). In addition, the researchers identified MBVs (matrix-bound nanobubbles), a subgroup of EVs in extracellular matrix biomaterials and exosomes, contain CD63, CD81, CD9, and Hsp70 markers, but Western blot analysis showed that the content of these proteins was significantly reduced in the MVB subgroup (Hussey et al., 2020). Jeppesen et al. (2014) compared the vesicles of embryonic kidney HEK293 cells and bladder cancer FL3 cells isolated at different centrifugal forces (33,000 g to 200,000 g), and found relative expression of exosome markers (TSG101, CD81, and syntenin) indicates the existence of a subgroup of exosomes characterized by variable sedimentation.

Théry (Kowal et al., 2016) proved that MHC II, HSC70, and flotillin can also be found in three subgroups (2K pellet, 10K pellet, and 100K pellet) under different centrifugal forces, which shows that these markers cannot be used to distinguish the subgroups of EVs alone. Their study also proved that ribosome proteins, mitochondrial proteins, ER proteins, and proteasome proteins have specific accumulations in different subgroups, but in different amounts. At a specific centrifugal force of 100,000 g, the extracellular matrix proteins were present in the high-density components, while PM and endosomal proteins were present in the low-density components. Especially, Willms et al. (2016) used density gradient centrifugation to separate exosomes and revealed the existence of two different subgroups.

The differences in the proteomics of these subgroups reveal their functional differences. Commonly enriched terms in MV and two exosome subgroups, LD-EXO and HD-EXO, included “vesicle mediated transport,” “translation,” “cytoskeleton,” “G-protein,” “ribosomal protein,” “small GTPase,” and “chaperones.” However, there were some proteins that differed among the three subgroups. “Oxidoreductases” and their subgroup “dehydrogenases” were enriched in MV, and slightly enriched in LD-Exo, but not in HD-Exo, potentially reflecting the presence of mitochondrial components in MV and LD-Exo. “Translation,” “ribonucleoproteins,” and “ribosomal proteins” displayed higher enrichment in HD-Exo than in LD-Exo. “G-proteins” were enriched in both HD-Exo and LD-Exo, while only LD-Exo reached significant enrichment for “G-protein modulators.”

For proteins uniquely identified in one of the EV subgroups, LD-Exo showed enrichment in “small GTPase regulatory activity” and “vesicle mediated transport.” HD-Exo unique proteins did not show any enrichment in a Gene Ontology-specific category. In contrast, MV unique proteins displayed enrichment in “oxidoreductase,” “oxidative phosphorylation,” and “respiratory electron transport chain.” Thus, LD-Exo and HD-Exo represent two distinct subgroups of exosomes with different unique protein compositions, both differing from larger MVs.

Nucleic acid (DNA and RNA) label

EV subgroups are different in their nucleic acid (DNA and RNA) composition. DNA, an important genetic material, was first proved in 1999 to exist in exosomes (García-Olmo et al., 1999). Thakur observed the exosomes secreted by B16-F10 cells under EM and found that only about 10% of the exosomes contained DNA, indicating not all EVs contain DNA (Thakur et al., 2014). Jeppesen reassessed the composition of exosomes and found that sEVs are not vehicles of active DNA release (Jeppesen et al., 2019). Later, DNA was widely proven to exist in EVs, and the distribution of DNA in EVs was random and different (Chang et al., 2020).

Among EVs from PC3 cell line, the content of gDNA in each subgroup of exosomes, MVs and Abs, is different (Lázaro-Ibáñez et al., 2014). In two different cell lines of PC3 and U87, two subgroups of L-EVs (oncosome, d:1.0–5.5 μm) and S-EVs (exosome, d:100–400 nm) were separated by differential centrifugation and density gradient centrifugation, which proves that in comparison with S-EVs, L-EVs are the subpopulation of vesicles enriched in large-size dsDNA. The pronounced discrepancy in the DNA content of L-EVs and S-EVs was even more obvious when the amount of DNA in L-EVs and S-EVs was compared to the relative amount of protein; in addition, the DNA fragments in L-EVs are larger, including 2 million bp DNA fragmentation, but not observed in S-EVs.

That is to say, the DNA content in the large subgroups is larger and the fragments are longer (Vagner et al., 2018). Willms et al. (2016) assessed differences in gene expression in the three separated subgroups, which were MV, LD-Exo, and HD-Exo, isolated from B16F10 melanoma cells. Compared with the control cells, 257 and 1116 genes were differentially expressed in LD-Exo and HD-Exo, respectively.

Further analysis of 42 genes with greater than 1.5-fold expression changes showed upregulation in 11 genes and downregulation in 31 genes. In the two isolated exosome subgroups, glutathione peroxidase 1 (GPX1) was upregulated, while zinc finger protein 101 (ZFP101) and centromere protein Q (CENPQ) were downregulated. Furthermore, LD-Exo upregulated SLC38A1 more significantly compared with HD-Exo. SLC38A1 is involved in the membrane transport of glutamine, and cancer cells show increased uptake of glutamine. At the same time, these different genes can exhibit different functions.

EVs also contain different RNAs, including mRNAs (and their fragments), long and small noncoding RNAs, and ribosomal RNA (rRNA) (Yanez-Mo et al., 2015). In 2007, Valadi (Valadi et al., 2007) discovered that exosomes carry both mRNA and miRNA, and mRNA can produce new proteins when it enters the recipient cell. Later, researchers also discovered that miRNAs in exosomes can transfer functions to recipient cells (Pegtel et al., 2010). In larger EVs, such as ABs and MVs, RNA also exists (Biggiogera et al., 1998; Ratajczak et al., 2006; Pegtel et al., 2010).

In other words, RNA is widely distributed in EVs. MicroRNA and mRNA are present in low-density EVs released by human mast cells and human breast cancer cells, but not in high-density EVs of these cell lines (Palma et al., 2012; Lässer et al., 2017), which indicates that the RNA content differs in EVs of different densities. Willms et al. (2016) found that MV and LD-Exo isolated from B16F10 melanoma cells contain only 18S and 28S rRNAs, while HD-Exo contains various RNAs ranging from 30 to 150 nt, proving that different subgroups have different amounts of RNA.

Small molecule metabolic label

There are also differences in small molecule metabolites among different subgroups of EVs. Metabolomic and lipidomic analyses were used to investigate the metabolic characteristics of two EV subsets derived from pleuric effusions: large EV (lEVs, pelleted at 20,000 g) and sEVs (pelleted at 110,000 g) by LC-MS/MS analysis. To assess their metabolite differences between tuberculosis and malignancy, the two subgroups of EVs in tuberculosis pleural effusion and malignancy pleural effusion were separated by differential centrifugation. A total of 579 metabolites, including amino acids, acylcarnitine, organic acids, steroids, amides, and various lipid species, were detected.

The results showed that the metabolic composition of lEVs and sEVs overlapped with and difference from each other but significantly differed from those of pleural effusion. In addition, different subgroups of vesicles and pleural effusion showed unique metabolic enrichments. Four candidate metabolic small molecular markers were identified in pleural LEVs, including phenylalanine, leucine, phosphatidylcholine 35:0, and sphingomyelin 44:3 (Luo et al., 2020).

Lysophospholipids (LPLs), hydrolytic metabolites of phospholipids created by phospholipase A, are bioactive signaling molecules that modulate a variety of physiological responses. Exosomes and MVBs of different biogenesis include seven types of LPLs (lysophosphatidylethanolamine [LPE], lysophosphatidylcholine [LPC], lysophosphatidylserine [LPS], lysophosphoinositol [LPI], lysophosphatidic acid [LPA], lysophosphatidylglycerol [LPG], and monolysocardiolipin [mCL]).

Among them, the contents of LPA and LPG in MBVs were significantly higher than those in exosomes. The contents of mCL and LPI in MBVs were 3 times and 6.3 times as those in exosomes, respectively. The contents of LPE, LPC, and LPS did not differ significantly in MBVs and exosomes (Hussey et al., 2020). In addition, urinary EVs, including MVs and exosomes, are not identical in lipid composition.

The recovered lipids were resolved by thin layer liquid chromatography (TLC) and analyzed by MALDI-TOF MS. Some researchers found that their sphingolipid profiles were unique. Ceramide phosphates (CerP), hexosyl sphingoid bases (HexSph), lactosyl ceramides (LacCer), mannosyl di-PI-ceramides (M(IP)2 C), sulfatides hexosyl ceramide (SHexCer), and sulfatides hexoxyl sphingoid bases (SHexSph) were detectable only in urinary exosomes, whereas phosphatidylinositol ceramides (PI-Cer) were detectable only in urinary microvesicles. CerP was successfully verified to exist only in urine vesicles (Singhto et al., 2019).

Conclusions and Perspectives

Researchers have done many studies about EVs with inspiring thoughts and findings. The most important staring point in the study of EVs is to understand the heterogeneity of EVs and its subsets among different subgroups. The study from Ramirez et al. (2018) revealed that the physical and biomolecular properties of exosomes, microvesicles, and apoptotic bodies overlap, although exosomes can be extracted through isolation protocols, which indicates that any study targeting exosomes may also contain other EVs as pollutants, and it is difficult to unify the full name of vesicles (Ramirez et al., 2018; Théry et al., 2018).

This is an issue that should not be neglected in any subsequent omics characterization. Differences in sample preparation may also result in controversial understanding of EV subgroups. Many experiments have proved different isolation and analysis methods will produce different results in downstream characterization. The study from Freitas et al. revealed that if you use five different techniques to separate urine EVs (uEVs), you will obtain five different mixtures of uEVs, expressing different protein markers.

Different separation methods also lead to a variety of glycosylated EV subgroups (Royo et al., 2016; Freitas et al., 2019). Using the colorectal cancer cell line LIM1863 as a cell model, exosomes were isolated by ultracentrifugation (UC-Exos), OptiPrep™density-based separation (DG-Exos), and immunoaffinity capture using anti-EpCAM-coated magnetic beads (IAC-Exos). These exosomes were all 40–100 nm in size and similar in morphology. Western blotting analysis of exosomes was positive for the markers Alix, TSG101, and HSP70.

Based on the number of MS/MS spectra identified for exosome markers and proteins associated with their biogenesis, trafficking, and release, IAC-Exos was found to be the most effective method to isolate exosomes, obtaining significantly higher (at least twofold) Alix, TSG101, CD9, and CD81 than UG-Exos and DG-Exos (Tauro et al., 2012).

EVs are highly heterogeneous and inhomogeneous, so researchers can use different labels to define EV subgroups. Till now, there has been no unified standard for definition; however, the labels with respect to genetic information, proteins, metabolites, and so on characterize the functional and biochemical properties of different subgroups of EVs. Take for example, the surface of a coated vesicle contains protrusions that other vesicles do not have.

These protrusions can be composed of proteins with specific functions, such as promoting membrane fusion so as to allow substances to enter the cytoplasm of potential target cells (Zeev-Ben-Mordehai et al., 2014). Similarly, only small double vesicles were found to contain rounded incomplete structures that were thinner than the membranous bilayer. The nature of this structure is unknown but may be specific to lumen cargo (Zabeo et al., 2017). Among the EV subgroups defined by morphological labels, different morphological EVs show different functions or structures, leading to different grades of subgroups of EVs.

In conclusion, EV subgroup cannot be defined in only one specific way; otherwise the nature of EVs cannot be fully understood. EVs, then, have yet to be graded in the right way to interpret the value of their existence.

Footnotes

Acknowledgments

We thank Prof. Wang Yan for modifying language of this article.

Disclosure Statement

No competing financial interests exist.

Funding Information

No funding was received for this article.

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