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. 2019 Aug 6;28(6):1635-1647.e5.
doi: 10.1016/j.celrep.2019.07.019.

Landscape of the Plasmodium Interactome Reveals Both Conserved and Species-Specific Functionality

Charles Hillier  1 , Mercedes Pardo  2 , Lu Yu  3 , Ellen Bushell  4 , Theo Sanderson  5 , Tom Metcalf  5 , Colin Herd  5 , Burcu Anar  5 , Julian C Rayner  5 , Oliver Billker  6 , Jyoti S Choudhary  7
Affiliations

Landscape of the Plasmodium Interactome Reveals Both Conserved and Species-Specific Functionality

Charles Hillier et al. Cell Rep. .

Abstract

Malaria represents a major global health issue, and the identification of new intervention targets remains an urgent priority. This search is hampered by more than one-third of the genes of malaria-causing Plasmodium parasites being uncharacterized. We report a large-scale protein interaction network in Plasmodium schizonts, generated by combining blue native-polyacrylamide electrophoresis with quantitative mass spectrometry and machine learning. This integrative approach, spanning 3 species, identifies >20,000 putative protein interactions, organized into 600 protein clusters. We validate selected interactions, assigning functions in chromatin regulation to previously unannotated proteins and suggesting a role for an EELM2 domain-containing protein and a putative microrchidia protein as mechanistic links between AP2-domain transcription factors and epigenetic regulation. Our interactome represents a high-confidence map of the native organization of core cellular processes in Plasmodium parasites. The network reveals putative functions for uncharacterized proteins, provides mechanistic and structural insight, and uncovers potential alternative therapeutic targets.

Keywords: Plasmodium; Plasmodium berghei; Plasmodium falciparum; Plasmodium knowlesi; blue native-PAGE; interaction network; interactome; malaria; protein-protein interactions.

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Conflict of interest statement

The authors declare no competing interests.

Figures

None
Graphical abstract
Figure 1
Figure 1
Identification of Plasmodium Protein Complexes (A) Schematic overview of the blue native polyacrylamide gel electrophoresis (BN-PAGE) strategy used to derive a protein interaction network. Plasmodium schizont lysates were subjected to BN-PAGE and migration profiles generated for each protein using MS1 peak intensities measured by quantitative LC-MS/MS. Two biological replicates were carried out for each condition. Profiles were correlated to generate pairwise co-migration scores, which were then used to build a network. (B) Representative heatmaps derived from hierarchical clustering of protein migration profiles for P. berghei (green), P. falciparum (red), and P. knowlesi (purple). Dendrograms are shown at left. Clustering was performed with Pearson correlation, complete linkage, and pre-processing with K-means. Protein markers (molecular weight) are shown at the top. Scale bars represent normalized intensity. The dotted box indicates the ribosome. (C) Migration profiles of select examples of known complexes. Protein descriptions from PlasmoDB are shown. (D) Network graphs of protein complexes shown in (C). Colored nodes represent co-migrating proteins identified here. White nodes represent other known interactors annotated in STRING. Solid edges are found in StringDB. Dashed edges are derived from co-migration only. See also Tables S1 and S2 and Figure S1.
Figure 2
Figure 2
Generation of a High-Confidence Plasmodium Protein Interaction Network (A) Schematic of the machine learning pipeline applied to the BN-PAGE fractionation data. Pairwise co-migration scores were supported with functional association information using a random forest classifier trained with a gold standard set derived from STRING. (B) Global Plasmodium PPI network derived through BN-PAGE correlation profiling (GBC-MS) and machine learning. (C) Receiver operating characteristic analysis of BN-PAGE fractionation experiments (brown, mean area under the curve [AUC] = 0.63, SD = 0.023) and the random forest classifier output (blue, AUC = 0.94). Performance was assessed against a gold standard set derived from STRING. (D) Protein clusters representing putative protein complexes. Conserved Plasmodium proteins of unknown function are shown with a thick border. For (C) and (D), the examples of well-known complexes are colored. The red edges represent interactions annotated in STRING. See also Tables S3, S4, S5, S6, and S7 and Figure S2.
Figure 3
Figure 3
Protein Complex Membership for Predicting the Function of Malaria Uncharacterized Proteins (A) Examples of clusters representing known malaria-specific protein complexes PTEX (de Koning-Ward et al., 2009), AP-1 (Kaderi Kibria et al., 2015), and glideosome (Frénal et al., 2017) found in this study. (B) Examples of clusters containing conserved Plasmodium proteins of unknown function (in orange). Red edges represent interactions annotated in STRING. (C) The ApiAP2 transcription factor interaction network. Relevant first-order interactions involving ApiAP2 transcription factors were extracted from the PPI network. Nodes labeled cPpuf are conserved Plasmodium proteins of unknown function. Orange nodes are essential proteins, and yellow nodes represent proteins whose mutation results in slow growth. (D) Validation of interactions by affinity purification-mass spectrometry from tagged P. berghei lines. Represented are subsections of the PPI network. The baits are surrounded by a circle. The proteins identified specifically in the immunoprecipitate of each bait are in green. The data are from two independent biological repeats. The dotted line represents an indirect link in the network. The numeric part of P. falciparum gene names is shown in (B)–(D). See also Table S8.
Figure 4
Figure 4
A Conserved Malaria Interaction Network (A) Clusters were generated from the protein interactions common to all three Plasmodium species studied, visualized as network graphs. The essential proteins are shown as red nodes, the blue nodes are proteins whose absence leads to slow growth, and the green nodes are proteins that cause no growth phenotype when absent. (B) Examples of conserved clusters detected in all three Plasmodium species. Interactions between the green nodes were detected in all of the species; the interactions with the blue nodes were not detected in P. knowlesi. The red edges represent the interactions annotated in STRING. (C) Density distribution and boxplots of relative evolutionary rates of OrthoMCL protein families to P. falciparum. The plots for the high-confidence PPI network and of protein families in the clusters from (A) are shown. The differences in distribution were assessed with a Wilcoxon rank-sum test (∗∗∗p < 2.9e−14). See also Table S9.
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