Multi-omics of extracellular vesicles: An integrative representation of functional mediators and perspectives on lung disease study

Abstract

Extracellular vesicles are secreted by almost all cell types. EVs include a broader component known as exosomes that participate in cell–cell and tissue–tissue communication via carrying diverse biological signals from one cell type or tissue to another. EVs play roles as communication messengers of the intercellular network to mediate different physiological activities or pathological changes. In particular, most EVs are natural carriers of functional cargo such as DNA, RNA, and proteins, and thus they are relevant to advancing personalized targeted therapies in clinical practice. For the application of EVs, novel bioinformatic models and methods based on high-throughput technologies and multi-omics data are required to provide a deeper understanding of their biological and biomedical characteristics. These include qualitative and quantitative representation for identifying cargo markers, local cellular communication inference for tracing the origin and production of EVs, and distant organ communication reconstruction for targeting the influential microenvironment and transferable activators. Thus, this perspective paper introduces EVs in the context of multi-omics and provides an integrative bioinformatic viewpoint of the state of current research on EVs and their applications.

Clinical Theragnostic Signature of Extracellular Vesicles in Traumatic Brain Injury (TBI)

“…By identifying patterns and associations between different variables, machine learning algorithms can provide personalized recommendations for treatment based on individual patient characteristics. 116,117 The current research suggests mild TBIs may increase the risk of neurodegenerative diseases later in life if not given sufficient time to recover. 118 These repetitive injuries are common in athletes and military personnel and remain underreported.…”

“… , The next level of complexity lies in exosome toxicity. Exosome toxicity needs more clear scientific investigation for affordable and efficient exosome-based therapeutic approach development for TBI. ,− Therefore, it is important to develop standardized methods for EVs isolation, purification, and analysis to ensure the reproducibility and comparability of results across different studies …”

“…These models can integrate multiple types of omics data, such as transcriptomics, proteomics, and metabolomics, to comprehensively understand disease and treatment response. By identifying patterns and associations between different variables, machine learning algorithms can provide personalized recommendations for treatment based on individual patient characteristics. , …”

Exploring the role of urinary extracellular vesicles in kidney physiology, aging, and disease progression

“…Generally, surface and luminal markers shared by EV types are commonly used for EV characterization, including tetraspanins (CD9, CD63, and CD81), surface proteins that organize membrane microdomains and are involved in EV biogenesis process, heat shock protein 70 (HSP70), a chaperone protein, ALG-2-interacting protein X (Alix) and tumor susceptibility gene 101 (TSG101) [auxiliary proteins involved in the endosomal sorting complexes required for transport (ESCRT) pathway] ( 9 ). EV cargo was also extensively characterized by adopting bioinformatic methods and reported in comprehensive databases such as ExoCarta, EVpedia, and Vesiclepedia that elucidate molecular content of EVs isolated in physiological or pathological conditions ( 10 ). In addition, dedicated databases such as EVatlas or exoRBase describe all the RNA species present in EVs ( 11 ).…”

“…The overall EV number resulted inversely proportional to age, with a specific decrease of uEVs derived from juxtaglomerular cells and podocytes ( 39 ). For instance, the level of miR-21, a miRNA involved in profibrotic and aging signaling pathways, resulted upregulated in uEVs from old rats, as compared with those of young rats ( 10 ). Interestingly, caloric restriction prevented this upregulation ( 10 ).…”