Exosome proteomics reveals transcriptional regulator proteins with potential to mediate downstream pathways

Abstract

Exosomes are virus-sized, membrane-enclosed vesicles with origins in the cellular endosomal system, but are released extracellularly. As a population, these tiny vesicles carry relatively enormous amounts of information in their protein, lipid and nucleic acid content, and the vesicles can have profound impacts on recipient cells. This review employs publically-available data combined with gene ontology applications to propose a novel concept, that exosomes transport transcriptional and translational machinery that may have direct impacts on gene expression in recipient cells. Here, we examine the previously published proteomic contents of medulloblastoma-derived exosomes, focusing on transcriptional regulators; we found that there are numerous proteins that may have potential roles in transcriptional and translational regulation with putative influence on downstream, cancer-related pathways. We expanded this search to all of the proteins in the Vesiclepedia database; using gene ontology approaches, we see that these regulatory factors are implicated in many of the processes involved in cancer initiation and progression. This information suggests that some of the effects of exosomes on recipient cells may be due to the delivery of protein factors that can directly and fundamentally change the transcriptional landscape of the cells. Within a tumor environment, this has potential to tilt the advantage towards the cancer.

Keywords: Cancer; exosomes; gene ontology; proteomics; transcriptional regulators.

Fig 1

Top Ingenuity Pathway Analysis (IPA) “interactome” derived from transcriptional regulators found in medulloblastoma exosome proteomics. Proteins clustered within the Top Network/Associated Functions as derived from IPA algorithms are shown as members of this “interactome,” which was entitled “Connective Tissue Disorders, Developmental Disorder, Hereditary Disorder.” Proteins identified during that work(73) are labeled in larger bold font, with the protein symbol in gold fill. Direct connections between/among proteins are shown in solid lines; indirect interactions are shown as dashed lines (also called “edges”). Connections between proteins identified in this proteomic screen are shown in dark blue; interactions between proteins we identified and proteins not identified in our proteomics are shown in turquoise. Protein shapes are indicative of function, and that legend is to the right.

Fig 2

Top Ingenuity Pathway Analysis (IPA) interactome derived from transcriptional regulators found in the Vesiclepedia database. Proteins clustered within the Top Networks/Associated Functions as derived from IPA algorithms are shown as members of this interactome, which was entitled “Gene Expression, Cell Cycle, Infectious Disease.” Details of the symbols and edges are described in the legend for Figure 1.

Fig 3

Top 12 Canonical pathways derived from Ingenuity Pathway Analysis (IPA) gene ontology analysis of transcriptional regulators found in the Vesiclepedia database. Following IPA “Core Analysis,” these 12 Canonical Pathways emerged. Graph shows category scores; “Threshold” indicates the minimum significance level (scored as –log [P-value] from Fisher's exact test, set here at 1.25). “Ratio” indicates the number of molecules from the data set that map to the pathway listed divided by the total number of molecules that map to the canonical pathway from within the IPA database.