The IMEx coronavirus interactome: an evolving map of Coronaviridae-host molecular interactions

Abstract

The current coronavirus disease of 2019 (COVID-19) pandemic, caused by the severe acute respiratory syndrome coronavirus (SARS-CoV)-2, has spurred a wave of research of nearly unprecedented scale. Among the different strategies that are being used to understand the disease and develop effective treatments, the study of physical molecular interactions can provide fine-grained resolution of the mechanisms behind the virus biology and the human organism response. We present a curated dataset of physical molecular interactions focused on proteins from SARS-CoV-2, SARS-CoV-1 and other members of the Coronaviridae family that has been manually extracted by International Molecular Exchange (IMEx) Consortium curators. Currently, the dataset comprises over 4400 binarized interactions extracted from 151 publications. The dataset can be accessed in the standard formats recommended by the Proteomics Standards Initiative (HUPO-PSI) at the IntAct database website (https://www.ebi.ac.uk/intact) and will be continuously updated as research on COVID-19 progresses.

Figure 1.

SARS-CoV-1–human and SARS-CoV-2–human network. The network includes only interactions between SARS-CoV-1/2 proteins and human targets. Human targets are annotated with level-one Reactome ontology, as shown in legend. Only targets with degree equal or higher than 5 are labeled. Diamond SARS-CoV-1 nodes represent RNA molecules. SARS-CoV-1 specific strains include strains PC4-145, Frankfurt 1, Urbani, TJF, HB and GZ02. Gray nodes are annotated with pathways that are not enriched in this network. In the network, the leftmost arc shows human proteins targeted only by SARS-CoV-1 proteins, the vertical line made of yellow nodes indicates SARS-CoV-1 proteins, the S-shaped arc shows human proteins targeted both by SARS-CoV-1 and SARS-CoV-2 proteins, the vertical line made of red nodes indicates SARS-CoV-2 proteins, and the two right arcs show proteins targeted only by SARS-CoV-2, with the rightmost arc including only proteins with degree equal or higher than 5.

Figure 2.

Timeline showing data captured in IMEx resources since COVID-19 outbreak (March 2020). (A) Cumulative interactions, mutation features and binding regions annotated for SARS-CoV-2 (red), SARS-CoV1 (orange) and other Coronaviridae family members proteins (gray). Interactions include spoke-expanded binary relationships. Dots represent the date when the interaction was curated. (B) Amount of cumulative experimental evidence associated with unique binary pairs, captured over time, in each of the three datasets: SARS-CoV-1, SARS-CoV-2 and other Coronaviridae family members. Interactions include spoke-expanded binary relationships.

Figure 3.

SARS-CoV-2 HT datasets comparison. SARS-CoV-2 datasets include Gordon et al., Li et al. and Stukalov et al. (A) Distribution of HT/LT-derived interactions in the Coronavirus dataset. The number on top of each bar indicates the number of publications per category. HT publications are defined as those hosting more than 50 unique interacting pairs. (B-D) Overlap of viral proteins (B), human targets (C) and viral to human edges (D) across datasets. Numbers outside the circles indicate the size of the sets. (E) Distribution of number of interactions between viral proteins and human targets. In the y-scale, 1 indicates that one human protein interacts only with one viral protein, while 16 indicates that one human protein interacts with 16 viral proteins.

Figure 4.

Pathway enrichment analysis of SARS-CoV-1, SARS-CoV-2 and Gordon_LT (Gordon plus low throughput), Li_LT (Li plus low throughput) and Stukalov_LT (Stukalov plus low throughput) datasets. Enrichment was performed using pathDIP (a database integrating 24 different pathway databases). Only human proteins were considered. The majority of enriched pathways were from Reactome database, so a mapping of each Reactome pathway to the parent pathway ontology was performed, and the heat map shows the percentage of pathways in each parent pathway over the total of pathways.