TRACE-seq: A transgenic system for unbiased and non-invasive transcriptome profiling of living cells

Transcriptomic analysis of intracellular RNA granules and small extracellular vesicles: Unmasking their overlap in a cell model of Huntington's disease

Huntington's disease (HD) arises from the abnormal expansion of a CAG repeat in the HTT gene. The mutant CAG repeat triggers aberrant RNA-protein interactions and translates into toxic aggregate-prone polyglutamine protein. These aberrant RNA-protein ineractions also seed the formation of cytoplasmic liquid-like granules, such as stress granules. Emerging evidence demonstrates that granules formed via liquid-liquid phase separation can mature into gel-like inclusions that persist within the cell and may act as precursor to aggregates that occur in patients' tissue. Thus, deregulation of RNA granules is an important component of neurodegeneration. Interestingly, both the formation of intracellular membrane-less organelles like stress granules and the secretion of small extracellular vesicles (sEVs) increase upon stress and under disease conditions. sEVs are lipid membrane-bound particles that are secreted from all cell types and may participate in the spreading of misfolded proteins and aberrant RNA-protein complexes across the central nervous system in neurodegenerative diseases like HD. In this study, we performed a comparative transcriptomic analysis of sEVs and RNA granules in an HD model. RNA granules and sEVs were isolated from an inducible HD cell model. Both sEVs and RNA granules were isolated from induced (HD) and non-induced (control) cells and analyzed by RNA sequencing. Our comparative analysis between the transcriptomics data of HD RNA granules and sEVs showed that: (I) intracellular RNA granules and extracellular RNA vesicles share content, (II) several non-coding RNAs translocate to RNA granules, and (III) the composition of RNA granules and sEVs is affected in HD cells. Our data showing common transcripts in intracellular RNA granules and extracellular sEVs suggest that formation of RNA granules and sEV loading may be related. Moreover, we found a high abundance of lncRNAs in both control and HD samples, with several transcripts under REST regulation, highlighting their potential role in HD pathogenesis and selective incorporation into sEVs. The transcriptome cargo of RNA granules or sEVs may serve as a source for diagnostic strategies. For example, disease-specific RNA-signatures of sEVs can serve as biomarker of central nervous system diseases. Therefore, we compared our dataset to transcriptomic data from HD patient sEVs in blood. However, our data suggest that the cell-type specific signature of sEV-secreted RNAs as well as their high variability may make it difficult to detect these biomarkers in blood.

The extracellular vesicle transcriptome provides tissue-specific functional genomic annotation relevant to disease susceptibility in obesity

We characterized circulating extracellular vesicles (EVs) in obese and lean humans, identifying transcriptional cargo differentially expressed in obesity. Since circulating EVs may have broad origin, we compared this obesity EV transcriptome to expression from human visceral adipose tissue derived EVs from freshly collected and cultured biopsies from the same obese individuals. Using a comprehensive set of adipose-specific epigenomic and chromatin conformation assays, we found that the differentially expressed transcripts from the EVs were those regulated in adipose by BMI-associated SNPs from a large-scale GWAS. Using a phenome-wide association study of the regulatory SNPs for the EV-derived transcripts, we identified a substantial enrichment for inflammatory phenotypes, including type 2 diabetes. Collectively, these findings represent the convergence of the GWAS (genetics), epigenomics (transcript regulation), and EV (liquid biopsy) fields, enabling powerful future genomic studies of complex diseases.

Expanding the horizon of EV-RNAs: LncRNAs in EVs as biomarkers for disease pathways

Extracellular vesicles (EVs) are membrane-bound nanoparticles with different types of cargo released by cells and postulated to mediate functions such as intercellular communications. Recent studies have shown that long non-coding RNAs (lncRNAs) or their fragments are present as cargo within EVs. LncRNAs are a heterogeneous group of RNA species with a length exceeding 200 nucleotides with diverse functions in cells based on their localization. While lncRNAs are known for their important functions in cellular regulation, their presence and role in EVs have only recently been explored. While certain studies have observed EV-lncRNAs to be tissue-and disease-specific, it remains to be determined whether or not this is a global observation. Nonetheless, these molecules have demonstrated promising potential to serve as new diagnostic and prognostic biomarkers. In this review, we critically evaluate the role of EV-derived lncRNAs in several prevalent diseases, including cancer, cardiovascular diseases, and neurodegenerative diseases, with a specific focus on their role as biomarkers.

Single Extracellular VEsicle Nanoscopy

Extracellular vesicles (EVs) and their cargo constitute novel biomarkers. EV subpopulations have been defined not only by abundant tetraspanins (e.g., CD9, CD63 and CD81) but also by specific markers derived from their source cells. However, it remains a challenge to robustly isolate and characterize EV subpopulations. Here, we combined affinity isolation with super-resolution imaging to comprehensively assess EV subpopulations from human plasma. Our Single Extracellular VEsicle Nanoscopy (SEVEN) assay successfully quantified the number of affinity-isolated EVs, their size, shape, molecular tetraspanin content, and heterogeneity. The number of detected tetraspanin-enriched EVs positively correlated with sample dilution in a 64-fold range (for SEC-enriched plasma) and a 50-fold range (for crude plasma). Importantly, SEVEN robustly detected EVs from as little as ∼0.1 μL of crude plasma. We further characterized the size, shape and molecular tetraspanin content (with corresponding heterogeneities) for CD9-, CD63- and CD81-enriched EV subpopulations. Finally, we assessed EVs from the plasma of four pancreatic ductal adenocarcinoma patients with resectable disease. Compared to healthy plasma, CD9-enriched EVs from patients were smaller while IGF1R-enriched EVs from patients were larger, rounder and contained more tetraspanin molecules, suggestive of a unique pancreatic cancer-enriched EV subpopulation. This study provides the method validation and demonstrates that SEVEN could be advanced into a platform for characterizing both disease-associated and organ-associated EV subpopulations.