Seminar: Extracellular Vesicles as Mediators of Environmental Stress in Human Disease.

BACKGROUND: Extracellular vesicles (EVs), membrane-bound particles containing a variety of RNA types, DNA, proteins, and other macromolecules, are now appreciated as an important means of communication between cells and tissues, both in normal cellular physiology and as a potential indicator of cellular stress, environmental exposures, and early disease pathogenesis. Extracellular signaling through EVs is a growing field of research for understanding fundamental mechanisms of health and disease and for the potential for biomarker discovery and therapy development. EVs are also known to play important roles in mediating the effects of exposure to environmental stress. OBJECTIVES: This seminar addresses the application of new tools and approaches for EV research, developed in part through the National Institutes of Health (NIH) Extracellular RNA Communication Program, and reflects presentations and discussions from a workshop held 27-28 September 2021 by the National Institute of Environmental Health Sciences (NIEHS) and the National Center for Advancing Translational Sciences (NCATS) on "Extracellular Vesicles, Exosomes, and Cell-Cell Signaling in Response to Environmental Stress." The panel of experts discussed current research on EVs and environmental exposures, highlighted recent advances in EV isolation and characterization, and considered research gaps and opportunities toward identifying and characterizing the roles for EVs in environmentally related diseases, as well as the current challenges and opportunities in this field. DISCUSSION: The authors discuss the application of new experimental models, particularly organ-on-chip (OOC) systems and in vitro approaches and how these have the potential to extend findings in population-based studies of EVs in exposure-related diseases. Given the complex challenges of identifying cell-specific EVs related to environmental exposures, as well as the general heterogeneity and variability in EVs in blood and other accessible biological samples, there is a critical need for rigorous reporting of experimental methods and validation studies. The authors note that these efforts, combined with cross-disciplinary approaches, would ensure that future research efforts in environmental health studies on EV biomarkers are rigorous and reproducible. https://doi.org/10.1289/EHP12980.

exRNA-eCLIP intersection analysis reveals a map of extracellular RNA binding proteins and associated RNAs across major human biofluids and carriers.

Although the role of RNA binding proteins (RBPs) in extracellular RNA (exRNA) biology is well established, their exRNA cargo and distribution across biofluids are largely unknown. To address this gap, we extend the exRNA Atlas resource by mapping exRNAs carried by extracellular RBPs (exRBPs). This map was developed through an integrative analysis of ENCODE enhanced crosslinking and immunoprecipitation (eCLIP) data (150 RBPs) and human exRNA profiles (6,930 samples). Computational analysis and experimental validation identified exRBPs in plasma, serum, saliva, urine, cerebrospinal fluid, and cell-culture-conditioned medium. exRBPs carry exRNA transcripts from small non-coding RNA biotypes, including microRNA (miRNA), piRNA, tRNA, small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), Y RNA, and lncRNA, as well as protein-coding mRNA fragments. Computational deconvolution of exRBP RNA cargo reveals associations of exRBPs with extracellular vesicles, lipoproteins, and ribonucleoproteins across human biofluids. Overall, we mapped the distribution of exRBPs across human biofluids, presenting a resource for the community.

Glioma-Derived miRNA-Containing Extracellular Vesicles Induce Angiogenesis by Reprogramming Brain Endothelial Cells.

Glioblastoma (GBM) is characterized by aberrant vascularization and a complex tumor microenvironment. The failure of anti-angiogenic therapies suggests pathways of GBM neovascularization, possibly attributable to glioblastoma stem cells (GSCs) and their interplay with the tumor microenvironment. It has been established that GSC-derived extracellular vesicles (GSC-EVs) and their cargoes are proangiogenic in vitro. To further elucidate EV-mediated mechanisms of neovascularization in vitro, we perform RNA-seq and DNA methylation profiling of human brain endothelial cells exposed to GSC-EVs. To correlate these results to tumors in vivo, we perform histoepigenetic analysis of GBM molecular profiles in the TCGA collection. Remarkably, GSC-EVs and normal vascular growth factors stimulate highly distinct gene regulatory responses that converge on angiogenesis. The response to GSC-EVs shows a footprint of post-transcriptional gene silencing by EV-derived miRNAs. Our results provide insights into targetable angiogenesis pathways in GBM and miRNA candidates for liquid biopsy biomarkers.

The Extracellular RNA Communication Consortium: Establishing Foundational Knowledge and Technologies for Extracellular RNA Research.

The Extracellular RNA Communication Consortium (ERCC) was launched to accelerate progress in the new field of extracellular RNA (exRNA) biology and to establish whether exRNAs and their carriers, including extracellular vesicles (EVs), can mediate intercellular communication and be utilized for clinical applications. Phase 1 of the ERCC focused on exRNA/EV biogenesis and function, discovery of exRNA biomarkers, development of exRNA/EV-based therapeutics, and construction of a robust set of reference exRNA profiles for a variety of biofluids. Here, we present progress by ERCC investigators in these areas, and we discuss collaborative projects directed at development of robust methods for EV/exRNA isolation and analysis and tools for sharing and computational analysis of exRNA profiling data.

Extending gene ontology in the context of extracellular RNA and vesicle communication.

BACKGROUND: To address the lack of standard terminology to describe extracellular RNA (exRNA) data/metadata, we have launched an inter-community effort to extend the Gene Ontology (GO) with subcellular structure concepts relevant to the exRNA domain. By extending GO in this manner, the exRNA data/metadata will be more easily annotated and queried because it will be based on a shared set of terms and relationships relevant to extracellular research. METHODS: By following a consensus-building process, we have worked with several academic societies/consortia, including ERCC, ISEV, and ASEMV, to identify and approve a set of exRNA and extracellular vesicle-related terms and relationships that have been incorporated into GO. In addition, we have initiated an ongoing process of extractions of gene product annotations associated with these terms from Vesiclepedia and ExoCarta, conversion of the extracted annotations to Gene Association File (GAF) format for batch submission to GO, and curation of the submitted annotations by the GO Consortium. As a use case, we have incorporated some of the GO terms into annotations of samples from the exRNA Atlas and implemented a faceted search interface based on such annotations. RESULTS: We have added 7 new terms and modified 9 existing terms (along with their synonyms and relationships) to GO. Additionally, 18,695 unique coding gene products (mRNAs and proteins) and 963 unique non-coding gene products (ncRNAs) which are associated with the terms: "extracellular vesicle", "extracellular exosome", "apoptotic body", and "microvesicle" were extracted from ExoCarta and Vesiclepedia. These annotations are currently being processed for submission to GO. CONCLUSIONS: As an inter-community effort, we have made a substantial update to GO in the exRNA context. We have also demonstrated the utility of some of the new GO terms for sample annotation and metadata search.

Integration of extracellular RNA profiling data using metadata, biomedical ontologies and Linked Data technologies.

The large diversity and volume of extracellular RNA (exRNA) data that will form the basis of the exRNA Atlas generated by the Extracellular RNA Communication Consortium pose a substantial data integration challenge. We here present the strategy that is being implemented by the exRNA Data Management and Resource Repository, which employs metadata, biomedical ontologies and Linked Data technologies, such as Resource Description Framework to integrate a diverse set of exRNA profiles into an exRNA Atlas and enable integrative exRNA analysis. We focus on the following three specific data integration tasks: (a) selection of samples from a virtual biorepository for exRNA profiling and for inclusion in the exRNA Atlas; (b) retrieval of a data slice from the exRNA Atlas for integrative analysis and (c) interpretation of exRNA analysis results in the context of pathways and networks. As exRNA profiling gains wide adoption in the research community, we anticipate that the strategies discussed here will increasingly be required to enable data reuse and to facilitate integrative analysis of exRNA data.

Expression profiling using a hexamer-based universal microarray.

We describe a transcriptional analysis platform consisting of a universal micro-array system (UMAS) combined with an enzymatic manipulation step that is capable of generating expression profiles from any organism without requiring a priori species-specific knowledge of transcript sequences. The transcriptome is converted to cDNA and processed with restriction endonucleases to generate low-complexity pools (approximately 80-120) of equal length DNA fragments. The resulting material is amplified and detected with the UMAS system, comprising all possible 4,096 (4(6)) DNA hexamers. Ligation to the arrays yields thousands of 14-mer sequence tags. The compendium of signals from all pools in the array-of-universal arrays comprises a full-transcriptome expression profile. The technology was validated by analysis of the galactose response of Saccharomyces cerevisiae, and the resulting profiles showed excellent agreement with the literature and real-time PCR assays. The technology was also used to demonstrate expression profiling from a hybrid organism in a proof-of-concept experiment where a T-cell receptor gene was expressed in yeast.