Journal of Molecular Biology
Databases/Web ServersExoCarta: A Web-Based Compendium of Exosomal Cargo
Graphical Abstract
Introduction
Exosomes are small (30–150 nm) membranous vesicles secreted by a variety of cells into the extracellular microenvironment [1], [2]. During physiological and pathological conditions, inward budding of late endosomal membranes results in the accumulation of intraluminal vesicles within the multivesicular bodies [3], [4]. Fusion of the multivesicular bodies with the plasma membrane results in the release of intraluminal vesicles into the extracellular microenvironment and from here on referred to as exosomes [5]. During their biogenesis, exosomes are packaged with proteins, RNA and lipids that is reflective of the host cell [6]. As exosomes are secreted by many cell types, conserved in most organisms and transport signaling molecules between cells, they have been implicated in intercellular communication [3], [7], [8]. More importantly, exosomes are detected in bodily fluids and are known to be highly stable reservoirs of disease biomarkers [9], [10], [11] prompting numerous studies aimed at cataloguing the exosomal proteins, RNAs and lipids using integrated high-throughput OMICS techniques [12]. Here, we describe ExoCarta, an online database that catalogues exosome specific data pertaining to proteins, RNAs and lipids. ExoCarta† was initially described in 2009 [13], and since its launch, two more databases (Vesiclepedia [12] and EVpedia [14]) have been described. While both Vesiclepedia and EVpedia catalogue data from multiple types of extracellular vesicles, ExoCarta is a primary resource of exosomal cargo [15] and contains annotations on the isolation and characterization methods. The new version of ExoCarta database has more than 2-fold data compared to the last release in 2012 and has new additional features including the annotation of International Society for Extracellular Vesicles (ISEV) standards and dynamic protein–protein interaction networks. Since its launch, ExoCarta has been visited by > 54,000 users from more than 135 countries.
Section snippets
Database design and structure
ExoCarta is developed using Zope‡, a leading open source Web application server written in object-oriented programming language Python. MySQL is used as a backend data storage system. The D3JS (Data-Driven Document Java Script) module coupled with the JSON (Java Script Object Notation) module for data exchange§ is used in developing dynamic protein–protein interaction networks. ExoCarta has a user-friendly Web-based graphical query system (Fig. 1) that can
ExoCarta datasets
In the last 3 years alone, the studies on exosomes have significantly increased (Fig. 2a) giving rise to multidimensional data [1], [16]. Hence, these publicly available datasets have been manually curated by expert biologists and uploaded into the ExoCarta database. In addition, many researchers have contributed data to ExoCarta aiding in community annotation. Currently, ExoCarta hosts 41,860 protein, > 7540 RNA and 1116 lipid entries catalogued from 10 different species.
ExoCarta as a reservoir of candidate exosomal markers and mutant oncogenic proteins
Over the past decade,
Conclusions
ExoCarta is a manually curated, Web-based and freely accessible database that hosts exosome specific proteins, RNAs and lipid contents from 10 different organisms. Since its launch, ExoCarta has been accessed by > 54,000 visitors from 135 countries. We believe that ExoCarta would serve as a discovery resource tool and aid researchers in understanding the molecular mechanisms of exosomal biogenesis, sorting and secretion under normal and diseases conditions.
Acknowledgements
S.M. is supported by the Australian Research Council Discovery project grant (DP130100535), Australian Research Council Discovery Early Career Researcher Award (DE150101777) and U54-DA036134 supported by the National Institutes of Health Common Fund through the Office of Strategic Coordination/Office of the National Institutes of Health Director. The funders had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.
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