Orthologous grouping and comparison of prokaryotic and eukaryotic EV proteomes

Abstract

Introduction: Most prokaryotic and eukaryotic cells secrete Extracellular vesicles (EVs) with bioactive molecules, including proteins and nucleic acid. Protein cargos important for EV biogenesis and/or biological functions can be found using proteomic analyses.

Methods: To analyze the similarity and difference between prokaryotic and eukaryotic EVs, EV protein databases was obtained from EVPedia (http://evpedia.info), regardless of EV sources and analysing platforms. EV proteins were catalogued into orthologous groups and annotated these groups using eggNOG database. Gene set enrichment analysis (GSEA) was employed to determine how much the orthologous groups are enriched in EVs of prokaryotic or eukaryotic species. The core network of prokaryotic and eukaryotic EV orthologous groups were explored by Generalized HotNet analysis. Only hot clusters with more than four orthologous groups were visualized by Cytoscape.

Results: A total of 6,634 proteomic orthologous groups were identified from 33 prokaryotes and 22 and separated into two distinct groups. Each orthologous group was annotated with gene symbols, GO terms, as well as functional interactions. Frequently detected orthologous groups were related with mainly membrane-associated compartments. The GSEA analysis showed some common and specific proteins to prokaryote or eukaryote in the categories of biological process and cellular component. The correlation network analysis clearly provided a domain-specific terms such as intracellular organelle cilium, cytoplasm ribosome, and ribosome proteasome complex for eukaryotes, and cytoplasm envelope, extracellular exosome, and cell outer membrane for prokayrotes.

Summary/Conclusion: Our comprehensive EV proteome analysis could provide a functional modules related with characteristic biological mechanisms in prokayrotes and eukaryotes. This analytical strategy will also provide a new integrative method to investigate EV proteins and propose an evolutionary protein repertoire of EV.