Novel multiparametric bulk and single EV pipeline for adipose cell-specific biomarker discovery in paired human biospecimens.

Obesity is a global health crisis that contributes to morbidity and mortality worldwide. Obesity's comorbid association with a variety of diseases, from metabolic syndrome to neurodegenerative disease, underscores the critical need to better understand the pathobiology of obesity. Adipose tissue, once seen as an inert storage depot, is now recognized as an active endocrine organ, regulating metabolic and systemic homeostasis. Recent studies spotlight the theranostic utility of extracellular vesicles (EVs) as novel biomarkers and drivers of disease, including obesity-related complications. Adipose-derived EVs (ADEVs) have garnered increased interest for their roles in diverse diseases, however robust isolation and characterization protocols for human, cell-specific EV subsets are limited. Herein, we directly address this technical challenge by establishing a multiparametric analysis framework that leverages bulk and single EV characterization, mRNA phenotyping and proteomics of human ADEVs directly from paired visceral adipose tissue, cultured mature adipocyte conditioned media, and plasma from obese subjects undergoing bariatric surgery. Importantly, rigorous EV phenotyping at the tissue and cell-specific level identified top 'adipose liquid biopsy' candidates that were validated in circulating plasma EVs from the same patient. In summary, our study paves the way toward a tissue and cell-specific, multiparametric framework for studying tissue and circulating adipose EVs in obesity-driven disease.

Engineering a tunable micropattern-array assay to sort single extracellular vesicles and particles to detect RNA and protein in situ.

The molecular heterogeneity of extracellular vesicles (EVs) and the co-isolation of physically similar particles, such as lipoproteins (LPs), confounds and limits the sensitivity of EV bulk biomarker characterization. Herein, we present a single-EV and particle (siEVP) protein and RNA assay (siEVP PRA) to simultaneously detect mRNAs, miRNAs, and proteins in subpopulations of EVs and LPs. The siEVP PRA immobilizes and sorts particles via positive immunoselection onto micropatterns and focuses biomolecular signals in situ. By detecting EVPs at a single-particle resolution, the siEVP PRA outperformed the sensitivities of bulk-analysis benchmark assays for RNA and protein. To assess the specificity of RNA detection in complex biofluids, EVs from various glioma cell lines were processed with small RNA sequencing, whereby two mRNAs and two miRNAs associated with glioblastoma multiforme (GBM) were chosen for cross-validation. Despite the presence of single-EV-LP co-isolates in serum, the siEVP PRA detected GBM-associated vesicular RNA profiles in GBM patient siEVPs. The siEVP PRA effectively examines intravesicular, intervesicular, and interparticle heterogeneity with diagnostic promise.

MPAPASS software enables stitched multiplex, multidimensional EV repertoire analysis and a standard framework for reporting bead-based assays.

Extracellular vesicles (EVs) of various types are released or shed from all cells. EVs carry proteins and contain additional protein and nucleic acid cargo that relates to their biogenesis and cell of origin. EV cargo in liquid biopsies is of widespread interest owing to its ability to provide a retrospective snapshot of cell state at the time of EV release. For the purposes of EV cargo analysis and repertoire profiling, multiplex assays are an essential tool in multiparametric analyte studies but are still being developed for high-parameter EV protein detection. Although bead-based EV multiplex analyses offer EV profiling capabilities with conventional flow cytometers, the utilization of EV multiplex assays has been limited by the lack of software analysis tools for such assays. To facilitate robust EV repertoire studies, we developed multiplex analysis post-acquisition analysis (MPAPASS) open-source software for stitched multiplex analysis, EV database-compatible reporting, and visualization of EV repertoires.

Pediatric brain tumor cell lines exhibit miRNA-depleted, Y RNA-enriched extracellular vesicles.

BACKGROUND: Medulloblastoma (MB) and diffuse infiltrative pontine glioma (DIPG) are malignant pediatric tumors. Extracellular vesicles (EVs) and their bioactive cargoes have been implicated in tumorigenesis. Most studies have focused on adult tumors, therefore the role of EVs and the noncoding RNA (ncRNA) landscape in pediatric brain tumors is not fully characterized. The overall aim of this pilot study was to isolate EVs from MB and DIPG patient-derived cell lines and to explore the small ncRNA transcriptome. METHODS: EVs from 3 DIPG and 4 MB patient-derived cell lines were analyzed. High-throughput next generation sequencing interrogated the short non-coding RNA (ncRNA) transcriptome. Known and novel miRNAs were quantified. Differential expression analysis, in silico target prediction, and functional gene enrichment were performed. RESULTS: EV secretomes from MB and DIPG patient-derived cell lines demonstrated discrete ncRNA biotypes. Notably, miRNAs were depleted and Y RNAs were enriched in EV samples. Hierarchical cluster analysis revealed high discrimination in miRNA expression between DIPG and MB cell lines and RNA-Seq identified novel miRNAs not previously implicated in MB or DIPG pathogenesis. Known and putative target genes of dysregulated miRNAs were identified. Functional annotation analysis of the target genes for differentially expressed EV-and parental-derived miRNAs revealed significant cancer-related pathway involvement. CONCLUSIONS: This hypothesis-generating study demonstrated that pediatric brain tumor-derived cell lines secrete EVs comprised of various ncRNA cargoes. Validation of these findings in patient samples may provide new insights into the pediatric brain tumor microenvironment and identification of novel therapeutic candidates.