RNA Sequencing at Single Vesicle Resolution via 3D Printed Embedded Droplet Arrays

Single-cell RNA sequencing has transformed our understanding of cellular heterogeneity; however, comparable methods for studying individual extracellular vesicles (EVs) remain scarce. To address the heterogeneity of RNA cargo contained within EVs, we developed a platform that 3D prints droplet arrays that generate cDNA for sequencing single EVs. The printing method leverages the interfacial instability between a hydrocarbon-based support material and printed aqueous solutions, driving printed features to break up into controllable, homogeneous droplets of a desired size that become stably trapped in 3D space. We printed picoliter aqueous droplets of EVs, DNA barcoded oligonucleotide beads, and biochemicals and performed a variety of reactions within the organogel support medium including PCR and synthesis of poly(A)<sup>+</sup> RNA sequencing compatible cDNA. Printing conditions were optimized to ensure ideal droplet loading of individual barcoded beads and single EVs within each droplet. Following collection of aqueous cDNA material from the organogel, additional biochemical reactions were performed in tubes in order to generate sequencable RNA libraries. Individual CD9, CD63, and CD81 positive EVs contained a wide variety of poly(A)<sup>+</sup> RNAs including mRNA, mitochondrial RNA, and noncoding RNAs. Poly(A)<sup>+</sup> RNAs of individual 100 nm immunopurified THP-1 EVs were sequenced using the 3D printing method and identified 3689 unique barcodes with at least two corresponding reads of poly(A)<sup>+</sup> RNA per EV, and the average amount of poly(A)<sup>+</sup> RNA per EV was 3.32. The developed platform resolves EV poly(A)<sup>+</sup> RNA heterogeneity with potential implications for biomarker discovery and other clinical applications.

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Publication Details

Journal
ACS Applied Materials & Interfaces
Published
2025-09-12
DOI
https://doi.org/10.1021/acsami.5c09959
Citations
1
Primary Topic
Extracellular vesicles in disease
Type
article
Field-Weighted Citation Impact
0.81
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article

RNA Sequencing at Single Vesicle Resolution via 3D Printed Embedded Droplet Arrays

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1 citations
ACS Applied Materials & Interfaces
Extracellular vesicles in disease
0.81
article

RNA Sequencing at Single Vesicle Resolution via 3D Printed Embedded Droplet Arrays

Thomas D. Schmittgen, Thomas E. Angelini, Senthilkumar Duraivel, Andrew A. Brock, Jonathan Fischer, Mei He, Zachary Greenberg, Jinmai Jiang
article en
1 citations

Abstract

Single-cell RNA sequencing has transformed our understanding of cellular heterogeneity; however, comparable methods for studying individual extracellular vesicles (EVs) remain scarce. To address the heterogeneity of RNA cargo contained within EVs, we developed a platform that 3D prints droplet arrays that generate cDNA for sequencing single EVs. The printing method leverages the interfacial instability between a hydrocarbon-based support material and printed aqueous solutions, driving printed features to break up into controllable, homogeneous droplets of a desired size that become stably trapped in 3D space. We printed picoliter aqueous droplets of EVs, DNA barcoded oligonucleotide beads, and biochemicals and performed a variety of reactions within the organogel support medium including PCR and synthesis of poly(A)<sup>+</sup> RNA sequencing compatible cDNA. Printing conditions were optimized to ensure ideal droplet loading of individual barcoded beads and single EVs within each droplet. Following collection of aqueous cDNA material from the organogel, additional biochemical reactions were performed in tubes in order to generate sequencable RNA libraries. Individual CD9, CD63, and CD81 positive EVs contained a wide variety of poly(A)<sup>+</sup> RNAs including mRNA, mitochondrial RNA, and noncoding RNAs. Poly(A)<sup>+</sup> RNAs of individual 100 nm immunopurified THP-1 EVs were sequenced using the 3D printing method and identified 3689 unique barcodes with at least two corresponding reads of poly(A)<sup>+</sup> RNA per EV, and the average amount of poly(A)<sup>+</sup> RNA per EV was 3.32. The developed platform resolves EV poly(A)<sup>+</sup> RNA heterogeneity with potential implications for biomarker discovery and other clinical applications.

ACS Applied Materials & InterfacesVol. 17(38)
Cornell University (US), University of Florida (US), Liberal Arts University (RU), New York College of Health Professions (US)
Openalex Percentile: Top 24%
Extracellular vesicles in disease
0.81
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