Unlocking the
Mysteries of
Extracellular RNA
Communication

Once thought to exist only inside cells, RNA is
known to travel outside of cells and play a role in newly
discovered mechanisms of cell-to-cell communication.

Secreted RNAs leave the intracellular environment by associating with diverse vesicular and protein components. Secreted vesicles are heterogeneous and follow various routes of egress from the cell (1). Subclasses of such vesicles contain distinct cell surface proteins (2). In order to fully understand the diversity of vesicles that contain RNA, it is necessary to analyze and sort vesicle populations (3). One way to do this is by flow sorting such vesicles based on the presence of distinct vesicular surface proteins.

The ability to perform flow cytometric analysis and sorting of exosomes has been an ongoing area of controversy due to the small size of exosomes, which range in size from 40-130nm, near or below the diffraction limit of light. Nevertheless, a variety of groups have used this technique to analyze different subsets of small vesicles successfully (4-14), including proteomic analyses (4, 15-17). The efficacy of these flow-sorting experiments has been cross-validated by a variety of means, including western blots and co-localization of coincidently expressed factors. Fluorescence-Activated Vesicle Sorting (FAVS) uses light scattering properties of vesicles to analyze and sort individual exosomes using fluorescent labels. (See a previous blog on FAVS here.)

In the paper, “Identification and Characterization of EGF Receptor in Individual Exosomes by Fluorescence-Activated Vesicle Sorting (FAVS)”, published in the Journal of Extracellular Vesicles (JEV), Higginbotham and colleagues have used FAVS to analyze exosomal subsets that express varying amounts of EGFR in different cell-culture and in vivo contexts. This was done using DiFi cells, a human colorectal cancer (CRC) cell line, and A431, an epidermoid cancer cell line, which express approximately 5×106 and 2.5×106 EGFRs per cell, respectively (18, 19). The FAVS results showed that DiFi exosomes contain far more EGFR than do A431 exosomes, far exceeding the two-fold difference in EGFR levels present in these cell lines. Furthermore, using an antibody that recognizes an active form of EGFR, mAb806 (20-22), the amount of active EGFR was also found to be dramatically higher in DiFi exosomes than in A431 exosomes.

FAVS was also used to sort EGFR/CD9 double-positive and double-negative exosome populations, allowing enrichment of both subsets by post-sort analysis as well as western blot validation of the sorted exosomes (see Figure). Using human-specific reagents, FAVS was able to detect DiFi exosomes in the plasma of mice bearing DiFi xenografts. FAVS was also used to demonstrate that EGFR and one of its ligands, amphiregulin (AREG) are present in the plasma of normal individuals.

 

Results from the JEV paper derived from Fig 2. DiFi exosomes were flow sorted using antibodies to EGFR and CD9. Sorted purified double-negative vesicles (blue box/arrow) and double-positive vesicles (red box/arrow) were probed by western blot for markers as shown. These results validate the flow sorting enrichment of these different classes of vesicles.  Also shown is a STORM image of an individual flow sorted double-positive vesicle.

Results from the JEV paper derived from Fig 2. DiFi exosomes were flow sorted using antibodies to EGFR and CD9. Sorted purified double-negative vesicles (blue box/arrow) and double-positive vesicles (red box/arrow) were probed by western blot for markers as shown. These results validate the flow sorting enrichment of these different classes of vesicles. Also shown is a STORM image of an individual flow sorted double-positive vesicle.

 

This work joins flow-sorting work done by other labs using somewhat different techniques (6-14) and has implications for similar kinds of work done by other members of this consortium (23-25). Common to all these techniques was the use of lipid and/or specific extracellular vesicle markers to identify classes of secreted vesicles. Unlike FAVS, many sorting methods trigger vesicular events based on fluorescence rather than scatter. In all of these cases, analysis of secreted vesicle populations was performed. In some cases vesicle sorting was also achieved.

Thus, FAVS appears to be a promising technique to identify and purify distinct subsets of exosomes for discovery studies. It also holds promise for the detection of biomarkers in disease states including subsets of associated secreted RNAs.

References

1. Yang JM, Gould SJ. The cis-acting signals that target proteins to exosomes and microvesicles. Biochem Soc Trans (2013) 41:277-82. PMID 23356297.

2. Kowal J, et al. Proteomic comparison defines novel markers to characterize heterogeneous populations of extracellular vesicle subtypes. Proc Natl Acad Sci USA (2016) 113:E968-77. PMID 26858453.

3. Lunavat TR, et al. Small RNA deep sequencing discriminates subsets of extracellular vesicles released by melanoma cells–Evidence of unique microRNA cargos. RNA Biol (2015) 12:810-23. PMID 26176991.

4. Cao Z, et al. Use of fluorescence-activated vesicle sorting for isolation of Naked2-associated, basolaterally targeted exocytic vesicles for proteomics analysis. Mol Cell Proteomics (2008) 7:1651-67. PMID 18504258.

5. Higginbotham JN, et al. Amphiregulin exosomes increase cancer cell invasion. Curr Biol (2011) 21:779-86. PMID 21514161.

6. Poncelet P, et al. Standardized counting of circulating platelet microparticles using currently available flow cytometers and scatter-based triggering: Forward or side scatter? Cytometry A (2016) 89:148-58. PMID 25963580.

7. Erdbrugger U, Lannigan J. Analytical challenges of extracellular vesicle detection: A comparison of different techniques. Cytometry A (2016) 89:123-34. PMID 26651033.

8. Chandler WL, Yeung W, Tait JF. A new microparticle size calibration standard for use in measuring smaller microparticles using a new flow cytometer. J Thromb Haemost (2011) 9:1216-24. PMID 21481178.

9. van der Pol E, et al. Single vs. swarm detection of microparticles and exosomes by flow cytometry. J Thromb Haemost (2012) 10:919-30. PMID 22394434.

10. Arraud N, Gounou C, Turpin D, Brisson AR. Fluorescence triggering: A general strategy for enumerating and phenotyping extracellular vesicles by flow cytometry. Cytometry A (2016) 89:184-95. PMID 25857288.

11. Pospichalova V, et al. Simplified protocol for flow cytometry analysis of fluorescently labeled exosomes and microvesicles using dedicated flow cytometer. J Extracell Vesicles (2015) 4:25530. PMID 25833224.

12. Nolte-‘t Hoen EN, et al. Quantitative and qualitative flow cytometric analysis of nanosized cell-derived membrane vesicles. Nanomedicine (2012) 8:712-20. PMID 22024193.

13. van der Vlist EJ, et al. Fluorescent labeling of nano-sized vesicles released by cells and subsequent quantitative and qualitative analysis by high-resolution flow cytometry. Nat Protoc (2012) 7:1311-26. PMID 22722367.

14. Groot Kormelink T, et al. Prerequisites for the analysis and sorting of extracellular vesicle subpopulations by high-resolution flow cytometry. Cytometry A (2016) 89:135-47. PMID 25688721.

15. Demory Beckler M, et al. Proteomic analysis of exosomes from mutant KRAS colon cancer cells identifies intercellular transfer of mutant KRAS. Mol Cell Proteomics (2013) 12:343-55. PMID 23161513.

16. McConnell RE, et al. The enterocyte microvillus is a vesicle-generating organelle. J Cell Biol (2009) 185:1285-98. PMID 19564407.

17. Shifrin DA, et al. Enterocyte microvillus-derived vesicles detoxify bacterial products and regulate epithelial-microbial interactions. Curr Biol (2012) 22:627-31. PMID 22386311.

18. Gross ME, et al. Cellular growth response to epidermal growth factor in colon carcinoma cells with an amplified epidermal growth factor receptor derived from a familial adenomatous polyposis patient. Cancer Res (1991) 51:1452-9. PMID 1847663.

19. Kawamoto T, et al. Growth stimulation of A431 cells by epidermal growth factor: identification of high-affinity receptors for epidermal growth factor by an anti-receptor monoclonal antibody. Proc Natl Acad Sci USA (1983) 80:1337-41. PMID 6298788.

20. Walker F, et al. Ligand binding induces a conformational change in epidermal growth factor receptor dimers. Growth Factors (2012) 30:394-409. PMID 23163584.

21. Gan HK, et al. Targeting of a conformationally exposed, tumor-specific epitope of EGFR as a strategy for cancer therapy. Cancer Res (2012) 72:2924-30. PMID 22659454.

22. Reilly EB, et al. Characterization of ABT-806, a Humanized Tumor-Specific Anti-EGFR Monoclonal Antibody. Mol Cancer Ther (2015) 14:1141-51. PMID 25731184.

23. Stoner SA, et al. High sensitivity flow cytometry of membrane vesicles. Cytometry A (2016) 89:196-206. PMID 26484737.

24. Nolan JP. Flow Cytometry of Extracellular Vesicles: Potential, Pitfalls, and Prospects. Curr Protoc Cytom (2015) 73:13.4.1-6. PMID 26132176.

25. Danielson KM, et al. Diurnal Variations of Circulating Extracellular Vesicles Measured by Nano Flow Cytometry. PLoS ONE (2016) 11:e0144678. PMID 26745887.

For researchers who have just begun studying extracellular vesicles (EVs) and their contents, including extracellular RNA, the Extracellular RNA Communication consortium (ERCC) published a protocols decision tree today, designed to help select a set of protocols for isolating EVs and exRNA from several biofluids of interest. Some of the protocols in the decision tree have been developed by ERCC researchers, but many relevant methods were published before the ERCC existed, and the versions on the ExRNA Portal include modifications and comments made by ERCC members in the course of their experiments, and are being periodically updated. In this blog, we introduce the ERCC protocols decision tree and discuss some of the nuanced differences between classes of EV isolation methods, highlighting methods that have existed in the field for some time.

There are several methods and commercial kits available to isolate extracellular vesicles (EVs) and extracellular RNA (exRNA) from human biofluids. Multiple studies have reported on a variety of these methods, but to date there is not one method or kit that suits all studies. The type of biofluid, the sample volume, and the fraction of exRNAs of interest are some of the criteria used to determine what method should be used for a particular study. Here, we have compiled a list of methods and kits most widely reported in the literature for isolation of EVs, exRNA or other components of biofluids. Broadly speaking, all methods can be classified into five categories (see Table), the most widely used being ultracentrifugation.

Drawbacks of ultracentrifugation include the need for expensive instrumentation (ultracentrifuges and rotors) and the belief that the EV population after ultracentrifugation will be contaminated with cell-free DNA and proteins. Depending on the speed and time of ultracentrifugation, some ribonucleoprotein (RNP) and lipoprotein (LPP) complexes may also sediment. After ultracentrifugation, some researchers further purify the EV population using density gradients or size exclusion chromatography. Sucrose gradients have been used widely for several years but are being replaced more recently by iodixanol (OptiPrep) gradients because some groups have reported that sucrose may inhibit the biological effects of EVs, while EVs prepared with OptiPrep better retain their biological activity.

Size exclusion chromatography is also widely used and is suitable for fractionation of sedimented EVs, as well as unprocessed biofluids. Recently Izon introduced a commercial kit to speed up this method, with relatively good results. Size exclusion chromatography yields a very clean population of EVs with the drawback being loss of EVs during the multi-step purification process.

The first commercial EV isolation kit (ExoquickTM) was launched on the market about six years ago, and is based on the principle of polyethylene glycol/sodium chloride precipitation, which has long been used for concentration of viruses. Since that time, several other kits using a precipitation strategy were launched by other manufacturers. Each of these kits (SBI, Life Technologies, Norgen Biotek, and Exiqon) have slightly different proprietary approaches to EV precipitation. Drawbacks to EV precipitation kits include co-precipitation of other unwanted molecules found in the biofluids and the difficulty of isolating EVs from large volumes of starting material. Ultrafiltration (e.g. using Millipore Amicon filters) is often used by researchers to concentrate large volumes, either before or after EV purification.

Filtration based methods which isolate specific size ranges of EVs can also be performed using commercially available devices. In addition, several kits and protocols for affinity purification have been developed by biotechnology companies and academic research laboratories. Antibody-based affinity methods (ExoCap, Microfluids, µNMR), and heparin-coated agarose or magnetic beads have been shown to bind subpopulations of EVs from cell culture media, plasma and serum efficiently. Another affinity kit, the METE kit, includes a proprietary peptide that, according to the manufacturer, binds to heat shock proteins found on the surface of the plasma membrane, suggesting a possible method to enrich for EVs with high levels of heat shock proteins. All of these methods yield a pure sample of EVs and can be scaled up, although scale-up costs can be significant, particularly in the case of antibody-based methods. These methods are limited to isolating a subset of EVs that express a specific antigen. For researchers who are interested in targeting a specific population EVs that displays one of these antigens, this may be a good option. However, at this point, for most cases, the biology is unclear on the diversity of EVs released by cells. Therefore, one antibody, or a pool of three to four antibodies, may not isolate all relevant EVs present in the sample.

ExoRNeasy isolates EVs based on their affinity to a proprietary membrane. ERCC members using this kit have reported that it can efficiently separate EVs (they bind to the membrane with high affinity) from other exRNA-containing particles, such as RNP complexes, which can be collected in the flow through, so this kit offers the extra advantage of efficiently separating EVs from RNP complexes. The ExoRNeasy/exoEasy kit yields a pure EV population and can isolate EVs from a volume as low as 200 μL or as high as 4 mL of plasma or serum with one loading per column, and up to 100 mL of cultured media per column by loading the column 3-4 times. Larger volumes require loading multiple filters.

Two kits available on the market are based on a two-step procedure where the sample is first either filtered (e.g. PureExo) or concentrated (e.g. Exo-Spin) and then resuspended and allowed to bind to proprietary beads. Intact EVs are then eluted in PBS and can be used for a variety of downstream assays. These kits do not offer feasible approaches to scale up to larger volumes.

Many other combinations and variations on these methods have also been reported in the literature, and this list is not meant to comprehensively encompass all reports in the field. It is a simple overview of the major classes of EV and RNA isolation methods present in the EV isolation field.

EV protocols table

Thery C. et al. 2006 Lobb et al. 2015 Boing et al. 2014 Lobb et al. 2015 Taylor DD. et al. 2011 Vlassov AV. et al. 2012 Hudson MB. et al. 2014 Lasser C. et al. 2012 Bryant, R. J. et al. 2012 jsrmicro.com Chen C. et al. 2010 Shao H. et al. 2012 Balaj et al. 2015 Enderle et al. 2015 Korbelik et al. 2015 cellgs.com Ghosh et al. 2014

Extracellular vesicles (EVs) play an important role in cell-to-cell communication. Recently, EVs have been shown to be involved in immune modulation, tumor biology, and tissue regeneration. The mechanisms of action of EVs are associated with their ability to stimulate target cells directly and to transfer proteins, biologically active lipids, and nucleic acids to the target cells. In fact, mRNAs, long non-coding RNAs (lncRNAs), and microRNAs (miRNAs) can be compartmentalized into EVs, escape enzymatic degradation, and be delivered to target cells. This horizontal transfer of extracellular RNAs carried by EVs can induce epigenetic alterations in recipient cells. The result is a change of phenotype or even a genetic and functional reprogramming of the recipient cells. Furthermore, EVs carry a selection of miRNAs different from the miRNAs most expressed in the cells of origin. However, little is known about the mechanisms of miRNA enrichment in EVs.

Argonaute2

Argonaute2


 
Alix

Alix

We hypothesized a possible interaction between the Alix and Argonaute 2 (Ago2) proteins. The resulting complex may have a role in miRNA transport into EVs. Ago2 is a reasonable candidate to play a role in miRNA packaging within multivesicular bodies during EV biogenesis because of its central role in miRNA maturation. We observed that Ago2, as well as several other ribonucloproteins involved in RNA storage and stability, is expressed in EVs derived from adult human liver stem-like cells (HLSCs). Cells which express mesenchymal and embryonic markers.
 

Alix Figure 1

Alix is a multifunctional protein commonly used as a marker of EVs. It is an accessory protein of the Endosomal Sorting Complex Required for Transport (ESCRT), and several studies indicate that ESCRT is involved in the biogenesis of EVs.

We observed that HLSC-derived EVs express both Alix and Ago2. Co-immunoprecipitation (Co-IP) experiments with Alix or Ago2 antibody showed that the two proteins are associated. We also found that the miRNAs enriched in HLSC-EVs precipitate with the Alix – Ago2 complex. After the incubation of HLSC-EVs with human endothelial cells, we observed that miRNAs from HLSC-EVs are transferred to these cells.
 

Alix Figure 4

After the silencing of Alix expression in HLSCs, we observed the absence of both Alix and Ago2 proteins in EVs derived from the knockdown HLSCs and a strong reduction in the number of miRNAs normally enriched in HLSC-EVs. On the other hand, EV size, surface expression of CD63 and Tsg101, and the number of released EVs were not affected. After incubation with endothelial cells, EVs derived from Alix-knockdown HLSC do not transfer miRNAs to cells.

Alix is known to be involved in endocytic membrane trafficking and cytoskeletal remodeling. It is also associated with the ESCRT machinery, which participates in processes of vesiculation and cargo sorting, including multivesicular body biogenesis. Our data suggest that Alix binds Ago2 and drives it into EVs together with the associated miRNAs.
 

Alix Figure 5

This might be a general mechanism of miRNA transport into EVs, common to other cell types. Enrichment of a selected set of miRNAs might also depend on the affinity of miRNAs for carrier proteins such as Ago2.

Source: Iavello A, Frech VS, Gai C, Deregibus MC, Quesenberry PJ, Camussi G. Role of Alix in miRNA packaging during extracellular vesicle biogenesis. Int J Mol Med. 2016 37:958-966. doi: 10.3892/ijmm.2016.2488. PMID: 26935291.