Extracellular vesicles (EVs) have the potential to provide new insights into skeletal muscle (SM) physiology and pathophysiology. However, current isolation protocols often do not eliminate co-isolated components such as lipoproteins and RNA binding proteins that could confound outcomes and hinder downstream clinical translation. In this study, we validated an EV isolation protocol that combined size-exclusion chromatography (SEC) with ultrafiltration (UF) to increase sample throughput, scalability and purity, while providing the very first analysis of the effects of UF column choice and fraction window on EV recovery. C2C12 myotube conditioned medium was pre-concentrated using either Amicon ® Ultra 15 or Vivaspin ® 20 100 KDa UF columns and processed by SEC (IZON, qEV 70 nm). The resulting thirty fractions obtained were individually analysed to identify an optimal fraction window for EV recovery. The EV marker TSG101 could be detected from fractions 5 to 14, while CD9 and Annexin A2 only up to fraction 6. ApoA1 + lipoprotein co-isolates were detected from fraction 6 onwards for both protocols. Strikingly, Amicon and Vivaspin UF concentration protocols led to qualitative and quantitative variations in EV marker profiles and purity. Eliminating lipoprotein co-isolation by reducing the SEC fraction window resulted in a net loss of particles, but increased measures of sample purity and had only a negligible impact on the presence of EV marker proteins. In conclusion, our study developed an effective UF+SEC protocol for the isolation of EVs based on sample purity (fractions 1-5) and total EV abundance (fractions 2-10). We provide evidence to demonstrate that the choice of UF column can affect the composition of the resulting EV preparation and needs to be considered when being applied in EV isolation studies in SM. The resulting protocols will be valuable in isolating highly pure EV preparations for applications in a range of therapeutic and diagnostic studies.

Extracellular vesicles (EVs) continue to gain interest across the scientific community for diagnostic and therapeutic applications. As EV applications diversify, it is essential that researchers are aware of challenges, in particular the compatibility of EV isolation methods with downstream applications and their clinical translation. We report outcomes of the first cross-comparison study looking to determine parameters (EV source, starting volume, operator experience, application and implementation parameters such as cost and scalability) governing the selection of popular EV isolation methods across disciplines. Our findings highlighted an increased clinical focus, with 36% of respondents applying EVs in therapeutics and diagnostics. Data indicated preferential selection of ultracentrifugation for therapeutic applications, precipitation reagents in clinical settings and size exclusion chromatography for diagnostic applications utilising biofluids. Method selection was influenced by operator experience, with increased method diversity when EV research was not the respondents primary focus. Application and implementation criteria were indicated to be major influencers in method selection, with UC and SEC chosen for their abilities to process large and small volumes, respectively. Overall, we identified parameters influencing method selection across the breadth of EV science, providing a valuable overview of practical considerations for the effective translation of research outcomes.

Background: Skeletal muscle extracellular vesicles (SM-EVs) regulate gene expression events in myogenic differentiation. Optimising effective SM-EV isolation methods offering high levels of purity will be important to accurately define their composition and functionality. Size-exclusion chromatography (SEC) applied in combination with ultrafiltration (UF) has the potential to increase sample throughput, scalability and selectivity. However, an optimal UF+SEC methodology has not been tested for the isolation of myotube derived EVs. Our aim was to compare two different UF protocols and define an optimal window of SEC fractions to maximise SM-EVs recovery and sample purity. Methods: C2C12 myotube conditioned medium was pre-concentrated using Amicon® Ultra 15 or Vivaspin®20, 100KDa UF columns and processed by SEC (IZON, qEV 70nm). The resulting thirty fractions obtained were individually analysed to identify an optimal fraction window for EV recovery. Results: EV markers Alix and TSG101 could be detected up to fraction 13, while CD9 and Annexin A2 only up to fraction 6. ApoA1+ lipoprotein contaminants were detected from fraction 6 onwards for both protocols. Amicon and Vivaspin UF preconcentration protocols led to qualitative and quantitative variations in EV marker profiles and purity. Eliminating lipoprotein co-isolation by reducing the SEC fraction window resulted in a net loss of particles, but increased measures of sample purity and had only a negligible impact on the presence of EV marker proteins. Conclusion: In conclusion, this study developed optimal UF+SEC protocols for the isolation of SM-EVs based on sample purity (fractions 1-5) and total abundance (fractions 2-10). The resulting protocols will be valuable in isolating highly pure SM-EV preparations for biomarker studies.