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University of Pennsylvania

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Adv. Sci., Oct 06 2023, | https://doi.org/10.1002/advs.202303619 Double Digital Assay for Single Extracellular Vesicle and Single Molecule Detection.

David E Reynolds ¹, Menghan Pan ¹, Jingbo Yang ², George Galanis ¹, Yoon Ho Roh ¹, Renee-Tyler T Morales¹, Shailesh Senthil Kumar¹, Su-Jin Heo ^{1 3}, Xiaowei Xu ², Wei Guo ⁴, Jina Ko ^{1 2 *}

¹Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, 19104, USA.
²Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
³Department of Orthopaedic Surgery, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 19104, USA.
⁴Department of Biology, School of Arts and Sciences, University of Pennsylvania, Philadelphia, PA, 19104, USA.

^*Corresponding author: correspondence to Jina Ko

Abstract

Extracellular vesicles (EVs) have emerged as a promising source of biomarkers for disease diagnosis. However, current diagnostic methods for EVs present formidable challenges, given the low expression levels of biomarkers carried by EV samples, as well as their complex physical and biological properties. Herein, a highly sensitive double digital assay is developed that allows for the absolute quantification of individual molecules from a single EV. Because the relative abundance of proteins is low for a single EV, tyramide signal amplification (TSA) is integrated to increase the fluorescent signal readout for evaluation. With the integrative microfluidic technology, the technology's ability to compartmentalize single EVs is successfully demonstrated, proving the technology's digital partitioning capacity. Then the device is applied to detect single PD-L1 proteins from single EVs derived from a melanoma cell line and it is discovered that there are ≈2.7 molecules expressed per EV, demonstrating the applicability of the system for profiling important prognostic and diagnostic cancer biomarkers for therapy response, metastatic status, and tumor progression. The ability to accurately quantify protein molecules of rare abundance from individual EVs will shed light on the understanding of EV heterogeneity and discovery of EV subtypes as new biomarkers.

논문정보

형식Research article
게재일2023년 10월 (BRIC 등록일 2023-11-15)
연구진국외 연구진
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