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<p>Extracellular vesicles (EVs) are essential for intercellular communication and various physiological processes; however, they are difficult to reliably identify and characterize owing to their inherent heterogeneity. To address this challenge, we adapt the concept of multifactor authentication (MFA) from computer science, and apply it to EV analysis. Similar to requiring multiple credentials to confirm digital identity, MFA in EV research integrates structural and molecular features to validate vesicle identity within heterogeneous mixtures and resolve subpopulations down to the single-EV level. By cross-validating across distinct factors and standardizing a multistep pipeline, MFA has the potential to enhance specificity, reliability, reproducibility and biological interpretability in EV analysis. Although no single approach fulfills all MFA criteria, several existing approaches embody MFA-like features. In this Perspective, we introduce MFA, discuss MFA-like approaches for EV subpopulation and single-EV analyses, highlight implications for EV biology and translational applications, and outline future directions for implementing an idealized MFA framework.</p>

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Multifactor authentication in extracellular vesicle analysis: methods and approaches to address the heterogeneity problem

  • 期刊论文

  • 发表日期：

    2026年4月21日

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  • Quan Zhou,
  • Richard J. Lobb,
  • Alain Wuethrich,
  • Matt Trau

摘要

Extracellular vesicles (EVs) are essential for intercellular communication and various physiological processes; however, they are difficult to reliably identify and characterize owing to their inherent heterogeneity. To address this challenge, we adapt the concept of multifactor authentication (MFA) from computer science, and apply it to EV analysis. Similar to requiring multiple credentials to confirm digital identity, MFA in EV research integrates structural and molecular features to validate vesicle identity within heterogeneous mixtures and resolve subpopulations down to the single-EV level. By cross-validating across distinct factors and standardizing a multistep pipeline, MFA has the potential to enhance specificity, reliability, reproducibility and biological interpretability in EV analysis. Although no single approach fulfills all MFA criteria, several existing approaches embody MFA-like features. In this Perspective, we introduce MFA, discuss MFA-like approaches for EV subpopulation and single-EV analyses, highlight implications for EV biology and translational applications, and outline future directions for implementing an idealized MFA framework.