There is growing interest in understanding the biological implications of single cell heterogeneity and heteroplasmy of mitochondrial DNA (mtDNA), but current methodologies for single-cell mtDNA analysis limit the scale of analysis to small cell populations. Although droplet microfluidics have increased the throughput of single-cell genomic, RNA, and protein analysis, their application to sub-cellular organelle analysis has remained a largely unsolved challenge. Here, we introduce an agarose-based droplet microfluidic approach for single-cell, single-mtDNA analysis, which allows simultaneous processing of hundreds of individual mtDNA molecules within >10,000 individual cells. Our microfluidic chip encapsulates individual cells in agarose beads, designed to have a sufficiently dense hydrogel network to retain mtDNA after lysis and provide a robust scaffold for subsequent multi-step processing and analysis. To mitigate the impact of the high viscosity of agarose required for mtDNA retention on the throughput of microfluidics, we developed a parallelized device, successfully achieving ~95 % mtDNA retention from single cells within our microbeads at >700,000 drops/minute. To demonstrate utility, we analyzed specific regions of the single-mtDNA using a multiplexed rolling circle amplification (RCA) assay. We demonstrated compatibility with both microscopy, for digital counting of individual RCA products, and flow cytometry for higher throughput analysis.

We develop a high-throughput droplet-based extracellular vesicle analysis (DEVA) assay for ultrasensitive quantification of EVs in plasma that are positive for both PD-L1 and tetraspanins.

Background Mitochondrial (mt) heteroplasmy can cause adverse biological consequences when deleterious mtDNA mutations accumulate disrupting "normal" mt-driven processes and cellular functions. To investigate the heteroplasmy of such mtDNA changes, we developed a moderate throughput mt isolation procedure to quantify the mt single-nucleotide variant (SNV) landscape in individual mouse neurons and astrocytes. In this study, we amplified mt-genomes from 1645 single mitochondria isolated from mouse single astrocytes and neurons to (1) determine the distribution and proportion of mt-SNVs as well as mutation pattern in specific target regions across the mt-genome, (2) assess differences in mtDNA SNVs between neurons and astrocytes, and (3) study co-segregation of variants in the mouse mtDNA. Results (1) The data show that specific sites of the mt-genome are permissive to SNV presentation while others appear to be under stringent purifying selection. Nested hierarchical analysis at the levels of mitochondrion, cell, and mouse reveals distinct patterns of inter- and intra-cellular variation for mt-SNVs at different sites. (2) Further, differences in the SNV incidence were observed between mouse neurons and astrocytes for two mt-SNV 9027:G > A and 9419:C > T showing variation in the mutational propensity between these cell types. Purifying selection was observed in neurons as shown by the Ka/Ks statistic, suggesting that neurons are under stronger evolutionary constraint as compared to astrocytes. (3) Intriguingly, these data show strong linkage between the SNV sites at nucleotide positions 9027 and 9461. Conclusions This study suggests that segregation as well as clonal expansion of mt-SNVs is specific to individual genomic loci, which is important foundational data in understanding of heteroplasmy and disease thresholds for mutation of pathogenic variants.

Extracellular vesicles (EVs) have attracted enormous attention for their diagnostic and therapeutic potential. However, it has proven challenging to achieve the sensitivity to detect individual nanoscale EVs, the specificity to distinguish EV subpopulations, and a sufficient throughput to study EVs among an enormous background. To address this fundamental challenge, we developed a droplet-based optofluidic platform to quantify specific individual EV subpopulations at high throughput. The key innovation of our platform is parallelization of droplet generation, processing, and analysis to achieve a throughput (∼20 million droplets/min) more than 100× greater than typical microfluidics. We demonstrate that the improvement in throughput enables EV quantification at a limit of detection = 9EVs/μL, a >100× improvement over gold standard methods. Additionally, we demonstrate the clinical potential of this system by detecting human EVs in complex media. Building on this work, we expect this technology will allow accurate quantification of rare EV subpopulations for broad biomedical applications.