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. 2019 May 27;16:230–241. doi: 10.1016/j.isci.2019.05.029

Serum Deprivation of Mesenchymal Stem Cells Improves Exosome Activity and Alters Lipid and Protein Composition

Reka Agnes Haraszti 1,8,9,∗, Rachael Miller 1,2, Michelle L Dubuke 3, Hannah E Rockwell 4, Andrew H Coles 1, Ellen Sapp 5, Marie-Cecile Didiot 1, Dimas Echeverria 1, Matteo Stoppato 6, Yves Y Sere 6, John Leszyk 3, Julia F Alterman 1, Bruno MDC Godinho 1, Matthew R Hassler 1, Justice McDaniel 4, Niven R Narain 4, Rachel Wollacott 6, Yang Wang 6, Scott A Shaffer 3, Michael A Kiebish 4, Marian DiFiglia 5, Neil Aronin 1,2,∗∗, Anastasia Khvorova 1,7,∗∗∗
PMCID: PMC6562145  PMID: 31195240

Summary

Exosomes can serve as delivery vehicles for advanced therapeutics. The components necessary and sufficient to support exosomal delivery have not been established. Here we connect biochemical composition and activity of exosomes to optimize exosome-mediated delivery of small interfering RNAs (siRNAs). This information is used to create effective artificial exosomes. We show that serum-deprived mesenchymal stem cells produce exosomes up to 22-fold more effective at delivering siRNAs to neurons than exosomes derived from control cells. Proteinase treatment of exosomes stops siRNA transfer, indicating that surface proteins on exosomes are involved in trafficking. Proteomic and lipidomic analyses show that exosomes derived in serum-deprived conditions are enriched in six protein pathways and one lipid class, dilysocardiolipin. Inspired by these findings, we engineer an “artificial exosome,” in which the incorporation of one lipid (dilysocardiolipin) and three proteins (Rab7, Desmoplakin, and AHSG) into conventional neutral liposomes produces vesicles that mimic cargo delivering activity of natural exosomes.

Subject Areas: Biochemistry, Biological Sciences, Lipidomics, Molecular Biology, Proteomics

Graphical Abstract

graphic file with name fx1.jpg

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Highlights

  • •

    Source cell stress augments exosome activity but reduces microvesicle activity

  • •

    Source cell stress alters exosome lipid and protein composition

  • •

    DSP, Rab7, AHSG an dilysocardiolipin enhances exosome activity

Biochemistry; Biological Sciences; Lipidomics; Molecular Biology; Proteomics

Introduction

Extracellular vesicles (EVs), including exosomes (small EVs) and microvesicles (large EVs), transfer molecules, such as therapeutic RNAs (Lener et al., 2015, Kramer-Albers, 2017, Kamerkar et al., 2017), to induce phenotype change in recipient cells (Valadi et al., 2007, Zomer et al., 2015, Fruhbeis et al., 2013, Monguio-Tortajada et al., 2017, Zhang et al., 2018). The following critical issues have impeded the use of exosomes for clinical applications: (1) production of exosomes from cells is tedious, has low yield, and is difficult to control; (2) the essential components of active exosomes are not established; and (3) the fundamental mechanisms of exosomal delivery need to be clarified to produce artificial exosomes in bulk. We optimized conditions to improve the delivery of exosomal cargo (small interfering RNA [siRNAs]) and used these optimized exosomes to find molecules that may affect exosomal activity. We constructed artificial exosomes inspired by these findings. Our strategy aims to substitute natural exosomes with artificial exosomes appropriate for large-scale production.

Cellular stress increases the activity of EVs (Han et al., 2018, Mleczko et al., 2018, Guitart et al., 2016), possibly by altering their protein (Xie et al., 2018, Guitart et al., 2016, Sun et al., 2014, Li et al., 2015) and RNA composition (King et al., 2012, Pope and Lasser, 2013). Therefore relating the change in composition of EVs to the change in their activity under stressed and control conditions can establish a composition-activity relationship. Serum deprivation is a common means of inducing cellular stress (Oskowitz et al., 2011), is widely used in extracellular vesicle production, and has been found to alter EV number (Aubertin et al., 2016, Sun et al., 2014, Taverna et al., 2003), activity (Sun et al., 2014, Oskowitz et al., 2011, Taverna et al., 2003), and composition (Kowal et al., 2016, Li et al., 2015). Surface (Sun et al., 2014) and intravesicular proteins (Taverna et al., 2003) have been linked to improved EV activity upon serum deprivation. We speculated that the membrane composition (proteins and lipids) of EVs is responsible for EV intercellular trafficking activity. We showed that upon serum deprivation, producer cells release exosomes that are more efficient at delivering siRNAs to neurons (a model for intercellular trafficking). This activity change was accompanied by substantial protein and lipid composition changes. We then screened several proteins and lipids, which were enriched in stressed exosomes, for enhancement in vesicle-mediated siRNA delivery to neurons. Subsequently we combined a candidate lipid (dilysocardiolipin) and three candidate proteins (Rab7, AHSG, and Desmoplakin) from the screen into liposomes to construct “artificial exosomes.” These artificial exosomes mimicked the siRNA delivery activity of natural stressed exosomes both in vitro and in vivo.

Results

Characterization of Extracellular Vesicles Produced from Control and Serum-Deprived Mesenchymal Stem Cells

We incubated mesenchymal stem cells derived from umbilical cord, adipose tissue, and bone marrow in either the recommended stem cell medium depleted of EVs (Control) or serum-free RPMI medium for 24 h (Stressed). We used differential ultracentrifugation to generate two EV populations, small and large EVs, enriched based on their sedimentation properties (Thery et al., 2006). We refer to the EVs from the 10,000 × g pellet as microvesicles and EVs from the 100,000 × g pellet as exosomes. Throughout this study we compare stressed conditions with control conditions within the same sample type: stressed cells versus control cells, microvesicles from stressed versus from control cells, and exosomes from stressed versus from control cells.

Mesenchymal stem cells tolerated serum deprivation for up to 4 days (Figure S1A) without loss of viability. EVs showed homogeneous size distribution (Figure S1B). Exosomes and microvesicles isolated from both the control and stressed (serum deprived for 24 h) conditions displayed positive protein markers and were devoid of negative protein markers of EVs (Figure S1C) and appeared as lipid bilayer-surrounded vesicles on transmission electron microscopy (Figure S1D). Serum deprivation did not affect the exosome yield from umbilical cord-derived cells (p = 0.3), but significantly decreased the exosome yield from both adipose- and bone marrow-derived cells (6-fold, p = 0.04, and 10-fold, p = 0.002, respectively, Figure S2A). Serum deprivation did not alter the amount of microvesicles (Figure S2B). Exosomes derived from umbilical cord mesenchymal stem cells were slightly larger than exosomes from either adipose tissue or bone marrow cells (142 ± 14 nm, 110 ± 19 nm, and 117 ± 10 nm, respectively). Serum deprivation did not affect EV size (Figures S2C and S2D). Protein-to-particle ratio varied substantially between vesicles from different sources and was affected by serum deprivation for some EV populations (Figures S2E and S2F). Umbilical cord-derived exosomes had the lowest protein-to-particle ratio, which remained unchanged upon serum deprivation (Figures S2E and S2F).

Serum Deprivation of Mesenchymal Stem Cells Improves Exosome Activity but Impairs Microvesicle Activity

Extracellular vesicles transport RNA between cells (Valadi et al., 2007, Zomer et al., 2015, Yang et al., 2017). We previously have shown that exosomes can productively transfer loaded cholesterol-conjugated siRNAs to neurons (Didiot et al., 2016). We loaded Huntingtin-targeting, cholesterol-conjugated siRNA (Alterman et al., 2015) to exosomes and treated primary neurons as a model for exosome trafficking. We evaluated the rates of exosome uptake to neurons using confocal microscopy and quantified the level of guide strand accumulation and target mRNA silencing in neurons.

First, exosomes isolated from serum-deprived cells (ExosomesStressed) could be loaded with equal amount of siRNA as ExosomesControl (Figure S3). Second, ExosomesStressed delivered more siRNA to target neurons than ExosomesControl across all mesenchymal stem cell origins tested (Figures 1A–1C). Third, when loaded with fluorescently labeled siRNA, ExosomesStressed showed an approximately 2-fold faster neuronal uptake kinetic (half-time 1.7 h versus 3.8 h, p < 0.0001) (Figures S4A and S4B). Finally, siRNA-containing ExosomesStressed were 5- to 22-fold more efficient at inducing Huntingtin mRNA silencing than ExosomesControl (Figures 1D–1F). A similar effect was observed with siRNAs targeting Ppib mRNA (Figure S4C).

Figure 1.

Figure 1

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Serum Deprivation of Mesenchymal Stem Cells Improves Exosome Activity but Impairs Microvesicle Activity

Primary neurons were treated with fluorescent siRNA-containing exosomes or microvesicles derived from control or stressed (serum deprived) cells. After 7 days of incubation, siRNA levels and target mRNA levels were quantified in neurons. mRNA levels were normalized to housekeeping gene and to untreated control. N = 3, mean ± SEM, curves were compared using two-way ANOVA.

(A–C) Uptake of siRNA into neurons delivered via exosomes and microvesicle.

(D–F) mRNA silencing induced by treatment of siRNA-containing exosomes and microvesicles.

(A and D) EVs enriched from umbilical cord-derived mesenchymal stem cells. (B and E) EVs enriched from adipose tissue-derived mesenchymal stem cells. (C and F) EVs enriched from bone marrow-derived mesenchymal stem cells.

Stress-dependent enhancement in activity was characteristic of exosomes and not of microvesicles, where serum deprivation impaired activity (Figures 1A–1F). These data pointed toward specific characteristics between exosomes and microvesicles that may be related to different vesicle trafficking: protein composition (Haraszti et al., 2016, Kowal et al., 2016).

Serum Deprivation of Mesenchymal Stem Cells Substantially Alters Protein Composition of Exosomes

To evaluate serum deprivation-induced changes in the protein composition of exosomes, we performed liquid chromatography-tandem mass spectrometry (LC-MS/MS) proteomic analysis. We collected data from three independent repeats of (1) control or serum-deprived mesenchymal stem cells (derived from umbilical cord, adipose tissue, or bone marrow), (2) microvesicles from control or serum-deprived cells, and (3) exosomes from control or serum-deprived cells.

As expected, serum deprivation had a profound effect on the proteome of cells, microvesicles, and exosomes, consistent in biological replicates (Figures 2A–2C and S5–S8). Protein composition differed substantially between exosomes and microvesicles (Figures S5–S8). Proteins enriched in stressed exosomes were either unchanged or depleted in corresponding microvesicles and source cells (Figures S5–S8 and 2D–2F).

Figure 2.

Figure 2

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Serum Deprivation of Source Cells Alters Protein Content of Released Exosomes

Exosomes, microvesicles, and cells derived from control conditions or stress conditions (serum deprivation) underwent liquid chromatography-MS/MS proteomics analysis. N = 3 biological replicates were analyzed and label-free quantification carried out using intensity-based absolute quantification method.

(A–C) Volcano plots of proteins detected in exosome. Orange dots represent proteins enriched at least 2-fold in ExosomesStressed, and blue dots represent proteins enriched at least 2-fold in ExosomesControl. Dashed line marks the threshold of significance (p = 0.05, t test with Benjamini-Hochberg correction for multiple comparison). Proteins above the dashed line significantly differ between ExosomesStressed and ExosomesControl. Proteins detected in one group and absent in the other group were arbitrarily assigned a fold change of 20 or -20.

(D–F) Heatmaps of proteins different (p < 0.1) in ExosomesStressed versus ExosomesControl. Orange represents enrichment in stressed conditions versus control conditions (ExosomesStressed versus ExosomesControl, MicrovesiclesStressed versus MicrovesiclesControl, and CellsStressed versus CellsControl), whereas blue represents enrichment in control conditions versus stress conditions.

(G–I) Gene Ontology analysis of proteins at least 2-fold enriched in ExosomesStressed or ExosomesControl (e.g., proteins labeled orange or blue in panels A–C).

(A, D, and G) Umbilical cord-derived mesenchymal stem cells. (B, E, and H) Adipose tissue-derived mesenchymal stem cells. (C, F, and I) Bone marrow-derived mesenchymal stem cells.

Gene Ontology analysis showed enrichment of extracellular exosome, proteasome, membrane, desmosome, cell-cell adhesion, ribosome, and Golgi protein pathways in ExosomesStressed fractions throughout all cell sources tested (Figures 2G–2I). We hypothesized that proteins involved in membrane, desmosome, and cell-cell adhesion may be related to vesicle trafficking. In addition, categories frequently found in exosomes (multivesicular body, endosome, histone, tetraspanins) as well as categories non-canonical to exosomes (endoplasmic reticulum [ER], ER-to-Golgi transport, and chaperone proteins) were enriched in ExosomesStressed derived from at least two of three cell sources tested (Figures 2G–2I).

Several Proteins Enriched in Stressed Exosomes Contribute to Improved siRNA Transfer to Neurons

Altered protein composition may explain the enhanced activity of ExosomesStressed. Proteinase K treatment (degrades surface proteins) impaired the exosome-mediated siRNA transfer and resulted in less Huntingtin silencing (Figures 3A and 3B), confirming that exosomes' surface proteins are essential for the delivery of cargo into neurons. The difference in the activity of ExosomesStressed over ExosomesControl is not related to potential inhibition by serum proteins present, as incubation with serum-containing (EV-depleted) media had no effect on ExosomesStressed activity (Figure 3A).

Figure 3.

Figure 3

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Proteins Enriched in Stressed Exosomes Contribute to Improved siRNA Transfer to Neurons

(A and B) Exosomes were enriched from serum-starved (A) or control (B) umbilical cord-derived mesenchymal stem cells and either not further treated or treated with proteinase K or EV-depleted serum-containing medium (serum). Primary neurons were then treated with the above exosome variants containing siRNAs, and mRNA levels in neurons were quantified after 7 days of incubation. N = 5, mean ± SEM, curves compared using two-way ANOVA.

(C) Enrichment of selected proteins in ExosomesStressed versus ExosomesControl (orange) or in CellsStressed versus CellsControl (gray). Proteins detected in stressed conditions but absent in control conditions were arbitrarily assigned the fold change of 20. N = 3, mean ± SEM. Two-way ANOVA, ****p < 0.0001, ***p < 0.001, **p < 0.01, *p < 0.05.

(D) Primary neurons were treated with siRNA containing liposomes alone or liposomes incorporating purified proteins from (C), and target mRNA levels in neurons were quantified after 7 days of incubation. N = 4, mean ± SEM, two-way ANOVA.

To establish a protein composition-activity relationship in exosomes, we selected proteins that (1) have an established role in vesicle trafficking or membrane adhesion and (2) were enriched in stressed exosomes derived from at least two of three mesenchymal stem cell sources. Based on these criteria, the shortlist included proteins from endosomal pathways (Rab5 and Rab7; Kummel and Ungermann, 2014), plasma membrane budding (ARRDC1; Nabhan et al., 2012), secreted proteins interacting with membranes (dermcidin; Paulmann et al., 2012), desmosome (Desmocollin, Desmoplakin; Delva et al., 2009), and nucleoextracellular shuttles (AHSG and histone 1; Watson et al., 2012) (Figure 3C). AHSG has been reported to shuttle histones from the nucleus to exosomes (Watson et al., 2012) and was consistently enriched in stressed cells (not present in EVs) (Figure 3C), whereas histones were specifically enriched in stressed exosomes (Figures 2G–2I and 3C).

Purified proteins were chemically palmitoylated and co-incubated with neutral liposomes (dioleoyl-phosphatidylcholine: cholesterol, 7:3) to promote association with the liposome membrane. Palmitoylation has been reported as a strategy to enrich proteins associated with exosomal membranes (Lai et al., 2015). Incorporation of Rab7, Desmoplakin, and AHSG improved liposome-mediated siRNA transfer to neurons and improved Huntingtin mRNA silencing (p < 0.0001 two-way ANOVA, Figure 3D). Incorporation of Rab5, Desmocollin, ARRDC1, Dermcidin, and histone 1 had no effect (Figure 3D). Thus incorporation of at least three candidate proteins from the proteomic analysis to the liposome surface affected the efficiency of vesicle transfer to neurons.

Dilysocardiolipin Enrichment in Stressed Exosomes Contributes to Improved Trafficking to Neurons

Membrane composition is a likely contributor to the enhanced trafficking activity of stressed exosomes. Membrane trafficking is regulated by both proteins and lipids (Ikonen, 2001, Huijbregts et al., 2000). To evaluate the effect of serum deprivation on the lipid composition of exosomes, we performed MS/MSALL lipidomic analysis. Among all lipid classes detected, only cardiolipins showed significant enrichment in exosomes derived from serum-deprived cells (p = 0.004, two-way ANOVA) (Figures 4A and S8A). Similar to protein enrichment, cardiolipin enrichment was specific to stressed exosomes and did not occur in corresponding cells and microvesicles (Figure 4A). In addition, we have observed a modest but statistically significant enrichment in unsaturated and long-tailed cardiolipins in stressed exosomes (Figures S8B and S8C).

Figure 4.

Figure 4

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Dilysocardiolipin Enrichment in Stressed Exosomes Contributes to Improved Trafficking to Neurons

Exosomes purified from umbilical cord-derived mesenchymal stem cells under control conditions or stress conditions (serum deprivation) underwent MS/MSALL lipidomics analysis. N = 2–5 biological replicates were analyzed per group.

(A) Heatmap of lipid classes in stressed conditions versus control conditions. Orange represents enrichment in ExosomesStressed versus ExosomesControl, MicrovesiclesStressed versus MicrovesiclesControl, and CellsStressed versus CellsControl, whereas blue represents enrichment in control conditions versus stress conditions.

(B) Scheme of cardiolipin. Length and saturation of fatty acid tails depicted is representative only and varies between natural cardiolipin species.

(C) Scheme of monolysocardiolipin. Differences to cardiolipin are shown in red. Length and saturation of fatty acid tails depicted are representative only and vary between natural monolysocardiolipin species.

(D) Scheme of dilysocardiolipin. Differences to cardiolipin are shown in red. Length and saturation of fatty acid tails depicted are representative only and vary between natural dilysocardiolipin species.

(E) Enrichment of cardiolipin subclasses from (B–D) in ExosomesStressed versus ExosomesControl (dark orange), MicrovesiclesStressed versus MicrovesiclesControl (light orange), and in CellsStressed versus CellsControl (gray). Two-way ANOVA, ****p < 0.0001. N = 3, mean ± SEM.

(F) Primary neurons were treated with siRNA containing liposomes alone or liposomes incorporating lipids from panel (E) and target mRNA levels in neurons quantified after 7 days of incubation. N = 4, mean ± SEM, two-way ANOVA.

Cardiolipin is a diphosphatidylglycerol lipid with four fatty acid tails (Figure 4B). Hydrolytic removal of one or two fatty acid tails results in the formation of monolysocardiolipin (Figure 4C) or dilysocardiolipin (Figure 4D), known intermediates in cardiolipin remodeling (Cao et al., 2004). Cardiolipin remodeling has been associated with highly curved membranes (Schlame et al., 2012).

Among different cardiolipin subclasses, dilysocardiolipins showed the highest enrichment in stressed exosomes (16-fold, p < 0.0001), followed by intact cardiolipins (9-fold, p < 0.0001) and monolysocardiolipins (6-fold, p < 0.0001) (Figure 4E), compared with control exosomes. Cardiolipin subclass enrichment was specific to stressed exosomes and was not observed in corresponding microvesicles and cells (Figure 4E).

To test whether cardiolipins play a role in vesicle trafficking to neurons, we incorporated intact cardiolipin, monolysocardiolipin, or dilysocardiolipin (30% of total lipid amount) in conventional liposomes (dioleoyl-phosphatidylcholine, cholesterol). Incorporation of dilysocardiolipin, but not other variants, into liposomes improved siRNA transfer to neurons and resulted in enhanced Huntingtin silencing (p = 0.007, two-way ANOVA) (Figure 4F). Thus dilysocardiolipin enrichment in stressed exosomes might be a contributing factor to enhanced neuronal uptake.

Artificial Exosomes Are Equally Active at siRNA Delivery as Natural Exosomes In Vitro and In Vivo

Having identified three proteins and one lipid class to be enriched in ExosomesStressed and improve vesicle uptake into neurons, we explored whether we can engineer an artificial exosome displaying similar activity to that of ExosomesStressed. We combined common liposome components (dioleoylphosphatidylcholine and cholesterol) with dilysocardiolipin and palmitoylated Rab7, Desmoplakin, and AHSG in a proteoliposome (ExosomeArtificial). Incorporation of three proteins and one lipid to liposomes significantly improved liposome-mediated siRNA transfer to neurons (p < 0.0001, two-way ANOVA) (Figure 5A). The efficiency of siRNA-containing artificial exosomes in Huntingtin silencing was indistinguishable from that of stressed exosomes (Figure 5A).

Figure 5.

Figure 5

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Artificial Exosomes Recapitulate the Activity of Stressed Exosomes

(A) Primary neurons were treated with siRNA containing ExosomesStressed, ExosomeLarge-Scale, or ExosomesArticial and target mRNA levels in neurons quantified after 7 days of incubation. ExosomesStressed and ExosomeLarge-Scale were enriched from umbilical cord-derived mesenchymal stem cells via differential ultracentrifugation or tangential flow filtration, respectively. ExosomesArticial consisted of dioleoylphosphatidylcholine, cholesterol, dilysocardiolipin, Rab7, Desmoplakin, and AHSG. N = 5, mean ± SEM, two-way ANOVA.

(B and C) Huntingtin (HTT)-targeting or non-targeting control (NTC) siRNAs were infused into the lateral ventricle of mice either alone or in liposomes, ExosomeLarge-Scale, or ExosomesArticial. Huntingtin mRNA were quantified 4 weeks after infusion in striatum (B) and motor cortex (C). N = 5–7, mean ± SD, one-way ANOVA.

To evaluate if siRNA-containing artificial exosomes will support Huntingtin silencing in vivo, we compared siRNA-containing natural exosomes and artificial exosomes infused into mouse brain. For the in vivo study, natural exosomes were produced using a combination of three-dimensional xenofree mesenchymal stem cell culture and tangential flow filtration-based exosome isolation (ExosomesLarge-Scale) (Haraszti et al., 2018). This method enabled us to collect a sufficient number of exosomes necessary to power the in vivo studies. Natural exosomes (ExosomesLarge-Scale) showed an activity indistinguishable from that of ExosomesStressed and ExosomesArtificial in vitro in primary neurons (Figure 5A). When infused to the lateral ventricle of the mouse brain, both ExosomesLarge-Scale and ExosomeArtifical loaded with siRNAs induced Huntingtin mRNA (Figures 5B and 5C) silencing, whereas control liposomes, non-targeting-control siRNA containing vesicles, and non-formulated siRNA were inactive (Figures 5B and 5C).

Discussion

EVs exhibit specific and efficient intercellular trafficking activity (Valadi et al., 2007, Zomer et al., 2015, Fruhbeis et al., 2013, Monguio-Tortajada et al., 2017, Zhang et al., 2018) and therefore are promising delivery vehicles of various classes of therapeutic proteins and RNAs (Lener et al., 2015, Kramer-Albers, 2017, Kamerkar et al., 2017). However, the mechanisms imparting specific trafficking activity to EVs are unknown. The identification of components necessary and sufficient to make a vesicle behave like an EV would open a new chapter to overcome the delivery challenge of protein- and nucleic acid-based advanced therapeutics.

Serum deprivation of source cells may differentially influence the yield and activity of released EVs. Here we find that serum deprivation of mesenchymal stem cells increases the activity but decreases the yield of exosomes. In contrast, serum deprivation decreases the activity, but does not change the yield of microvesicles. The concept that serum deprivation may alter the yield of different EV subclasses into different directions has been raised before (Kowal et al., 2016). However, the notion that serum deprivation may increase the activity of one EV subclass but decrease the activity of another EV subclass produced from the same cells has not been described before. This observation indicates that exosome and microvesicle production pathways are differentially regulated in stress conditions.

Exosomes released from stressed cells exhibit a specific enhancement in activity and a specific protein composition. Therefore, stressed exosomes are ideally suited for composition-activity relationship studies. The protein content of EVs from serum-deprived and control cells has been shown to differ (Kowal et al., 2016, Li et al., 2015). The functional 20S proteasome, all subunits of which we find specifically enriched in stressed exosomes, has been detected in EVs before (Bochmann et al., 2014, Kowal et al., 2016) and has been proposed to be of therapeutic value (Lai et al., 2012). We also observe enrichment in desmosomal proteins, ribosomal proteins, histones, and endosomal proteins, all of which have been reported in EVs and are proposed to play a role in an EV release mechanism (Choi et al., 2012, Overmiller et al., 2017, Dozio and Sanchez, 2017, Keerthikumar et al., 2015, Willms et al., 2016, Nemeth et al., 2017, Watson et al., 2012). Several strategies have been successfully applied to modulate the surface of EVs: expressing proteins fused to palmitoylation signals (Lai et al., 2014), transmembrane domains (Lai et al., 2014), or exosomal marker proteins (Yim et al., 2016, Alvarez-Erviti et al., 2011) in producer cells; CLICK chemistry-based conjugation (Smyth et al., 2014); fusing EVs with liposomes (Lee et al., 2015, Sato et al., 2016); and loading cholesterol-conjugated aptamers onto the surface of EVs (Pi et al., 2018). Here we show that three of eight proteins (Desmoplakin, AHSG, and Rab7) enhance vesicle trafficking to neurons. We used chemical palmitoylation to enable protein loading into the vesicle membrane. Different proteins may have different sensitivity to this treatment (i.e., high pH and palmitoylation on lysine residues instead of the naturally occurring cysteine, serine, and threonine residues). Thus the lack of enhancement in liposome neuronal uptake may not indicate a lack of contribution to vesicle trafficking. Further advancement of the technology presented here will require combinatorial optimization of protein loading to membrane as well as lipid-to-protein ratios.

A main finding of this study is the identification of dilysocardiolipin as an essential component of exosomes. We previously have reported on cardiolipin enrichment in exosomes compared with cells and microvesicles (Haraszti et al., 2016). Lysocardiolipins are substrates of a cardiolipin-remodeling enzyme residing in the ER (acyl-coA:lysocardiolipin acyltransferase 1) (Cao et al., 2004). The ER-Golgi secretory pathway (also enriched in stressed exosomes) may overlap with the release of exosomes from the multivesicular body (Friend, 1969, Kolesnikova et al., 2004, Nilsson et al., 2015). Thus dilysocardiolipin may use this overlapping secretory pathway to enter exosomes under stress conditions.

Artificial exosomes constructed from purified lipid and protein components would have several advantages over natural exosomes. First, the manufacture of proteoliposomes is an easily scalable process and may be more cost-effective than manufacturing cell-derived exosomes. Second, the quality control of cell-free artificial exosomes could follow established guidelines from the liposome field, whereas the quality control requirements of natural therapeutic exosomes remain unclear (Lener et al., 2015, Reiner et al., 2017). Third, loading therapeutic cargo (proteins or RNA) into or onto artificial exosomes could be a simple step added to the manufacturing process, whereas efficient loading of therapeutic cargo to natural exosomes is still challenging.

Limitations of the Study

The activity of artificial exosome composition identified here might be limited to neuronal uptake and alteration or optimization of this composition likely is necessary to tune artificial exosomes for delivery to other cell types. The mechanism of action of dilysocardiolipin, Rab7, Desmoplakin, and AHSG may differ in natural and artificial exosomes. The method used here to load proteins onto liposomes (chemical palmitoylation) may have different efficiency for different proteins and may not be suited for all proteins. Loading proteins on the surface of neutral liposomes may alter the surface charge, which in turn may influence cellular uptake. Optimization of the loading method is needed to control the protein-to-lipid ratio in artificial exosomes.

Methods

All methods can be found in the accompanying Transparent Methods supplemental file.

Acknowledgments

This publication is part of the NIH Extracellular RNA Communication Consortium paper package and was supported by the NIH Common Fund's exRNA Communication Program. This work was supported by the NIH UH3 grant TR 000888 05 and the UMass CCTS UL1 TR000161 grant to N.A. and A.K.; NIH grants RO1GM10880304, RO1NS10402201, and S10 OD020012 to A.K.; and the CHDI Foundation (Research Agreement A-6119, JSC A6367) to N.A. M.-C.D. was supported by a Huntington's Disease Society of America Postdoctoral Fellowship and B.M.D.C.G. was supported by a Milton-Safenowitz Fellowship (17-PDF-363) from the Amyotrophic Lateral Sclerosis Association.

Author Contributions

Conceptualization, R.A.H., N.A., and A.K.; Methodology & Investigation, R.A.H. (primary neurons, silencing measurements, PNA hybridization assay, confocal microscopy, EV, liposomes and artificial exosome preparations, western blots, nanoparticle tracking analysis, siRNA loading to vesicles, mouse harvest); R.M. (EV preparations), M.-C.D. (EV preparations, cholesterol-siRNA loading to EVs), M.L.D. (proteomics), J.L. (proteomics), S.A.S. (proteomics), H.E.R. (lipidomics), J.M. (lipidomics), N.R.N. (lipidomics), M.A.K. (lipidomics), E.S. (electron microcopy), M.D. (electron microscopy), A.H.C. (mouse surgeries), M.S. (large-scale exosomes), Y.Y.S. (large-scale exosomes), R.W. (large-scale exosomes), Y.W. (large-scale exosomes), J.F.A. (mouse brain harvest), B.M.D.C.G. (mouse brain harvest); Validation, R.A.H. and A.K.; Formal Analysis, R.A.H.; Resources, D.E. (synthesis of siRNAs), M.R.H. (maintenance of oligonucleotide synthesizers and HPLCs); Writing – Original Draft, R.A.H and A.K.; Visualization, R.A.H.; Writing – Review & Editing, N.A.; Supervision, S.A.S., M.A.K., Y.W., M.D., N.A. and A.K.; Project Administration, R.A.H.; Funding Acquisition: N.A. and A.K.

Declaration of Interests

R.A.H., N.A., and A.K. are filing a patent application related to artificial exosomes. Other authors do not have a conflict of interest.

Published: June 28, 2019

Footnotes

Supplemental Information can be found online at https://doi.org/10.1016/j.isci.2019.05.029.

Contributor Information

Reka Agnes Haraszti, Email: rharaszti@gmail.com.

Neil Aronin, Email: neil.aronin@umassmed.edu.

Anastasia Khvorova, Email: anastasia.khvorova@umassmed.edu.

Supplemental Information

Document S1. Transparent Methods and Figures S1–S8
mmc1.pdf (1.6MB, pdf)
Table S1 Umbilical Cord-Derived Mesenchymal Stem Cell Proteomics, Related to Figures 2 and 3
mmc2.zip (95.8KB, zip)
Table S2 Adipose Tissue-Derived Mesenchymal Stem Cell Proteomics, Related to Figures 2 and 3
mmc3.zip (86.4KB, zip)
Table S3 Bone Marrow-Derived Mesenchymal Stem Cell Proteomics, Related to Figures 2 and 3
mmc4.zip (91.5KB, zip)
Table S4 Umbilical Cord-Derived Mesenchymal Stem Cell Lipidomics: Lipid Classes, Related to Figure 4

Numbers represent nmol lipid/mg protein. AC, acyl carnitines; Cer, ceramides; CE, cholesteryl esters; CoQ, coenzyme Q10; CL, cardiolipins; DAG, diacylglycerols; FFA, free fatty acids; LPA, lysophosphatidic acids; PA, phosphatidic acids; LPC, lysophosphatidylcholines; PC, phosphatidylcholines; LPE, lysophosphatidylethanolamines; PE, phosphatidylethanolamines; LPG, lysophosphatidylglycerols; PG, phosphatidylglycerols; LPI, lysophosphatidylinositols; PI, phosphatidylinositols; LPS, lysophosphatidylserines; PS, phosphatidylserines; SM, sphingomyelins; TAG, triacylglycerols.

mmc5.zip (3.6KB, zip)
Table S5 Umbilical Cord-Derived Mesenchymal Stem Cells Lipidomics: Lipid Species, Related to Figure 4

Numbers represent nmol lipid/mg protein. AC, acyl carnitines; Cer, ceramides; CE, cholesteryl esters; CoQ, coenzyme Q10; CL, cardiolipins; Des, desmosterol; DAG, diacylglycerols; FFA, free fatty acids; LPA, lysophosphatidic acids; PA, phosphatidic acids; LPC, lysophosphatidylcholines; PC, phosphatidylcholines; LPE, lysophosphatidylethanolamines; PE, phosphatidylethanolamines; LPG, lysophosphatidylglycerols; PG, phosphatidylglycerols; LPI, lysophosphatidylinositols; PI, phosphatidylinositols; LPS, lysophosphatidylserines; PS, phosphatidylserines; SM, sphingomyelins; TAG, triacylglycerols.

mmc6.zip (186.5KB, zip)

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Transparent Methods and Figures S1–S8
mmc1.pdf (1.6MB, pdf)
Table S1 Umbilical Cord-Derived Mesenchymal Stem Cell Proteomics, Related to Figures 2 and 3
mmc2.zip (95.8KB, zip)
Table S2 Adipose Tissue-Derived Mesenchymal Stem Cell Proteomics, Related to Figures 2 and 3
mmc3.zip (86.4KB, zip)
Table S3 Bone Marrow-Derived Mesenchymal Stem Cell Proteomics, Related to Figures 2 and 3
mmc4.zip (91.5KB, zip)
Table S4 Umbilical Cord-Derived Mesenchymal Stem Cell Lipidomics: Lipid Classes, Related to Figure 4

Numbers represent nmol lipid/mg protein. AC, acyl carnitines; Cer, ceramides; CE, cholesteryl esters; CoQ, coenzyme Q10; CL, cardiolipins; DAG, diacylglycerols; FFA, free fatty acids; LPA, lysophosphatidic acids; PA, phosphatidic acids; LPC, lysophosphatidylcholines; PC, phosphatidylcholines; LPE, lysophosphatidylethanolamines; PE, phosphatidylethanolamines; LPG, lysophosphatidylglycerols; PG, phosphatidylglycerols; LPI, lysophosphatidylinositols; PI, phosphatidylinositols; LPS, lysophosphatidylserines; PS, phosphatidylserines; SM, sphingomyelins; TAG, triacylglycerols.

mmc5.zip (3.6KB, zip)
Table S5 Umbilical Cord-Derived Mesenchymal Stem Cells Lipidomics: Lipid Species, Related to Figure 4

Numbers represent nmol lipid/mg protein. AC, acyl carnitines; Cer, ceramides; CE, cholesteryl esters; CoQ, coenzyme Q10; CL, cardiolipins; Des, desmosterol; DAG, diacylglycerols; FFA, free fatty acids; LPA, lysophosphatidic acids; PA, phosphatidic acids; LPC, lysophosphatidylcholines; PC, phosphatidylcholines; LPE, lysophosphatidylethanolamines; PE, phosphatidylethanolamines; LPG, lysophosphatidylglycerols; PG, phosphatidylglycerols; LPI, lysophosphatidylinositols; PI, phosphatidylinositols; LPS, lysophosphatidylserines; PS, phosphatidylserines; SM, sphingomyelins; TAG, triacylglycerols.

mmc6.zip (186.5KB, zip)

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