Disease Maps

Here we share resources and best practices to develop a disease map for COVID-19. The project is progressing as a broad community-driven effort. We aim to establish a knowledge repository on virus-host interaction mechanisms specific to the SARS-CoV-2. The COVID-19 Disease Map is an assembly of molecular interaction diagrams established based on literature evidence.

We performed topological analysis on pathways from a harmonised dataset containing pathways from the COVID-19 Disease Map, WikiPathways, and Reactome. The analysis was done using Vanted, SBGN-ED, and LMME which support the import and export of several standard formats (such as SBML, and SBGN-ML).

Multiscale and multicellular simulation of SARS-CoV-2 infection uncover points of intervention to evade apoptosis.

Summary:

Our framework enables the simulation of the dynamics of signaling pathways that include the relevant players in SARS-CoV-2 infection, at the level of the individual cell and of the cell population. These different players encompass the virus, epithelial and immune cells. The model focuses on apoptosis and suggests two knock out alterations that force apoptosis of the ...

The COVIDminer text mining project (https://rupertoverall.net/covidminer/) reads the published literature concerning SARS-CoV-2 and COVID-19 to extract statements about (primarily molecular) interactions. Using the API associated with this project, putative interactors can be automatically retrieved for the existing COVID-19 Disease Maps. New interactions are prioritised based on their frequency in the literature and the topological importance of the interaction targets to provide a focussed set ...

We further used the transcriptome dataset from the GEO database with accession number GSE147507 (Blanco-Melo et al., 2020) to extract the series number 5 from the dataset, consisting of 2 conditions in triplicate, A549 cells treated with a mock and A549 infected with SARS-CoV-2, measured 24 hours after treatment. Phosphoproteomic data of mock-treated and SARS-CoV2 infected cells were extracted from (Stukalov et al., 2020). We then applied our pipeline described in M&M X. This work notably ...

In this investigation, we aim to develop automatic workflows to pinpoint drug targets carrying genomic variants at high frequency in the population

In this investigation we aim to develop automatic workflows to analyze COVID19 Omics data to understand and predict the molecular pathways depicting host-virus interaction.

We develop macrophage logical models to represent the activation/polarization of this immune cell. Interactions are manually curated with available macrophage literature. The models are mainly built and analyzed in GINsim. But other resources are used to integrate specific pathways or small modules (CasQ software) and to analyze the logical models (CoLoMoTo Notebooks).

To allow detailed visual analysis of the overall system and its parts, we used a customised version of our Vanted add-on LMME (Large Metabolic Model Explorer) to construct an overview graph showing one node per pathway and the respective interconnecting species. We performed a comprehensive analysis of node centralities on two levels: on the level of the individual pathways as well as on the level of an aggregated network which is composed of the individual pathways. This allows detailed ...

An exploration on gene expression data was carried out on single-cell RNAseq analyses of bronchoalveolar lavages from nine COVID-19 patients, three moderate cases, one severe case and five critical cases (GSE145826) (doi: 10.1038/s41591-020-0901-9). To these data, single-cell RNA-sequencing from one COVID-19 lung biopsy, ~10 weeks after initial infection was added to represent persistent severe COVID19 patient group (3 weeks after symptom onset) (GSE163919). For this analysis, the epithelial cell ...

Scope: The COVID-19 disease can have gastrointestinal manifestation. The virus replicates in the gut and has potential faecal-oral transmission besides airborne transmission (Lamers et al., 2020). Intestinal organoids are a proven experimental model of the human gut and can help understand the viral infection of the gut without animal models and additional biopsies. Single-cell RNA-seq techniques can distinguish the SARS-CoV-2 replicating cells and thus help to understand how cells respond to the ...

We further used the transcriptome dataset from the GEO database with accession number GSE147507 (Blanco-Melo et al., 2020) to extract the series number 5 from the dataset, consisting of 2 conditions in triplicate, A549 cells treated with a mock and A549 infected with SARS-CoV-2, measured 24 hours after treatment. Phosphoproteomic data of mock-treated and SARS-CoV2 infected cells were extracted from (Stukalov et al., 2020). We then applied our pipeline described in M&M X. This work notably ...

In this study, we developed a workflow to compute a modified version of the Cumulative Allele Probability (CAP) for genes in the COVID-19 disease map and the “Drug Risk Probability” (DRP) score for drugs targeting genes in the map (Schärfe et al., 2017). The CAP score considers the number of pharmacogenomic variants and their frequency in the population for a specific gene. The DRP score combines the CAP scores for all drug target genes for a specific drug. For this, we use allelic frequencies ...

In this study, we developed an automated and reproducible workflow for transcriptomics data analysis using network biology approaches. The analyses are fully automated in R with clusterProfiler and RCy3 to connect to the widely adopted network analysis software Cytoscape including the CyTargetLinker app for network extension. For demonstration, we use a publicly available dataset from Blanco-Melo et al., GSE147507 obtained from GEO. After pre-processing with DESeq2, the dataset contains log2 fold ...

In this study, we integrate COVID19 Disease Maps curated regulatory information in a macrophage logical model. This allows logical simulations of the effects of acute inflammation caused by the SARS-CoV-2 virus, both in general and in a cell-specific perspective. Moreover, understanding the regulatory network behavior of macrophages following infection opens new ways to test and predict drug and drug combination effects, as a first step towards the development of new treatments.

In response to the COVID-19 pandemic, the Allen Institute for AI has partnered with leading research groups to prepare and distribute the COVID-19 Open Research Dataset (CORD-19), a free resource of over 45,000 scholarly articles, including over 33,000 with full text, about COVID-19 and the coronavirus family of viruses for use by the global research community.

This dataset is intended to mobilize researchers to apply recent advances in natural language processing to generate new insights in ...

NLRP3 inflammasome activation

Thrombotic complications and coagulopathy in COVID-19

Kynurenine synthesis pathway

TGF beta signalling

The role of the interaction between the SARS-CoV-2 Spike protein and the renin-angiotensin pathway, in particular human ACE2 in pulmonary blood pressure regulation

The Interferon-lambda (IFNL) map describes the action of the drug candidate IFNL on intra- and intercellular signal transduction under SARS-CoV-2.

The relation of the interferon 2 pathway and SARS-CoV-2.

The pathway of heme metabolism under COVID-19, involving Orf3a and Orf9c

The impact of SARS-CoV-2 on the apoptosis pathway

The pathways focused on SARS-CoV infections curated in Reactome. These pathways are work-in-progress.

Interactions of Nsp4 and Nsp6 proteins of SARS-CoV-2.

Interactions of the SARS-CoV-2 Orf3a with human proteins, especially in the context of the HOPS Complex.

A diagram of Nsp9 interactions.

Orf10 of SARS-CoV-2 and its interaction with the Cul2 pathway.

Pyrimidine deprivation and immune response related to human coronavirus infection

The mechanisms of the Electron Transport Chain under COVID-19, including Nsp7, Nsp8 and Orf9c

SARS-CoV-2 impact on the ER stress

COVID-19 Causal Networks: The SIGNOR team has curated the causal relationships that, according to available evidence, are likely to be relevant for the COVID-19 pathology. The perturbations caused by viral infection are integrated into the cell networks. Evidence obtained using related human coronaviruses diseases such as SARS and MERS are also mapped to the networks. Most of these are indirect relationships as few mechanistic details are clarified to date. As new evidence will be published, it ...

Pathway: Assembly of the Replication Transcription Complex and Transcription

Metabolic interactions of the SARS-CoV-2 Nsp14 with the human galactose, nicotinate and nicotinamide, and purine metabolism.

This document outlines next steps in biocuration of COVID-19 Disease Map diagrams.

The document is based on the preprint "COVID-19 Disease Map, a computational knowledge repository of SARS-CoV-2 virus-host interaction mechanisms" (doi:10.1101/2020.10.26.356014).

This document helps to harmonise the curation efforts for the COVID-19 Disease Map.

The Research Data Alliance (RDA) is a volunteer community of over 10,500 professionals from 145 countries across the globe. In less than two months, the community responded to an urgent call for action and defined much needed, comprehensive recommendations and guidelines for data sharing under the present COVID-19 circumstances.

This is the fifth and final draft of the Recommendations and Guidelines from the RDA COVID-19 working group, and is open for public comment until 8th of June 2020. Following the open period, feedback will be considered and then the WG will seek endorsement of the document from the RDA governance bodies prior to final publication.

Draft guidelines and recommendations; fourth release, 15 May 2020, version for public review

Open listing of contributors to the COVID-19 disease maps

Presentations and notes from the COVID19 Disease Map curation telephone conferences.

Here we share and organize the literature used to build the components of the COVID-19 DIsease Map