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Abstract
Ribonucleoprotein complexes are composed of RNA, RNA-dependent proteins (RDPs) and RNA-binding proteins (RBPs), and play fundamental roles in RNA regulation. However, in the human malaria parasite, Plasmodium falciparum, identification and characterization of these proteins are particularly limited. In this study, we use an unbiased proteome-wide approach, called R-DeeP, a method based on sucrose density gradient ultracentrifugation, to identify RDPs. Quantitative analysis by mass spectrometry identifies 898 RDPs, including 545 proteins not yet associated with RNA. Results are further validated using a combination of computational and molecular approaches. Overall, this method provides the first snapshot of the Plasmodium protein-protein interaction network in the presence and absence of RNA. R-DeeP also helps to reconstruct Plasmodium multiprotein complexes based on co-segregation and deciphers their RNA-dependence. One RDP candidate, PF3D7_0823200, is functionally characterized and validated as a true RBP. Using enhanced crosslinking and immunoprecipitation followed by high-throughput sequencing (eCLIP-seq), we demonstrate that this protein interacts with various Plasmodium non-coding transcripts, including the var genes and ap2 transcription factors.
Ribonucleoprotein complexes play fundamental roles in many cellular processes. Here, the authors used a proteome-wide approach, R-DeeP, to identify protein complexes associated with RNA in the deadliest human malaria parasite, Plasmodium falciparum.
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1 University of California Riverside, Department of Molecular, Cell and Systems Biology, Riverside, USA (GRID:grid.266097.c) (ISNI:0000 0001 2222 1582)
2 Stowers Institute for Medical Research, Kansas City, USA (GRID:grid.250820.d) (ISNI:0000 0000 9420 1591)
3 University of Washington, Department of Genome Sciences, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657)
4 University of Washington, Department of Genome Sciences, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657); University of Washington, Paul G. Allen School of Computer Science and Engineering, Seattle, USA (GRID:grid.34477.33) (ISNI:0000 0001 2298 6657)