Open Access Highly Accessed Open Badges Research article

Construction of a large scale integrated map of macrophage pathogen recognition and effector systems

Sobia Raza12, Neil McDerment12, Paul A Lacaze1, Kevin Robertson13, Steven Watterson13, Ying Chen1, Michael Chisholm1, George Eleftheriadis1, Stephanie Monk1, Maire O'Sullivan1, Arran Turnbull1, Douglas Roy1, Athanasios Theocharidis12, Peter Ghazal13 and Tom C Freeman12*

Author Affiliations

1 Division of Pathway Medicine, University of Edinburgh, The Chancellor's Building, College of Medicine, 49 Little France Crescent, Edinburgh EH16 4SB, UK

2 The Roslin Institute and Royal (Dick) School of Veterinary Studies, University of Edinburgh, Roslin, Midlothian EH25 9PS, UK

3 Centre for Systems Biology, University of Edinburgh, Darwin Building, King's Building Campus, Mayfield Road, Edinburgh EH9 3JU, UK

For all author emails, please log on.

BMC Systems Biology 2010, 4:63  doi:10.1186/1752-0509-4-63

Published: 14 May 2010



In an effort to better understand the molecular networks that underpin macrophage activation we have been assembling a map of relevant pathways. Manual curation of the published literature was carried out in order to define the components of these pathways and the interactions between them. This information has been assembled into a large integrated directional network and represented graphically using the modified Edinburgh Pathway Notation (mEPN) scheme.


The diagram includes detailed views of the toll-like receptor (TLR) pathways, other pathogen recognition systems, NF-kappa-B, apoptosis, interferon signalling, MAP-kinase cascades, MHC antigen presentation and proteasome assembly, as well as selected views of the transcriptional networks they regulate. The integrated pathway includes a total of 496 unique proteins, the complexes formed between them and the processes in which they are involved. This produces a network of 2,170 nodes connected by 2,553 edges.


The pathway diagram is a navigable visual aid for displaying a consensus view of the pathway information available for these systems. It is also a valuable resource for computational modelling and aid in the interpretation of functional genomics data. We envisage that this work will be of value to those interested in macrophage biology and also contribute to the ongoing Systems Biology community effort to develop a standard notation scheme for the graphical representation of biological pathways.