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Assembling the interactome of human extracellular matrix
to understand its role in health and disease
Graham L. Cromar and John Parkinson
Program in Molecular Structure and Function, Hospital for Sick Children, Toronto, Ontario
Introduction
Results
Conclusions
The extracellular matrix (ECM) is composed of a variety of proteins
secreted by the cell and self-organized into a complex mesh of fibres
and soluble components. These materials are capable of forming a
diverse set of structures (e.g. bone, blood vessels). A number of
biological processes are influenced by the surrounding matrices
including cell adhesion, migration, proliferation and differentiation.
Changes in the structure and function of ECM components are known
to be associated with a number of complex and diverse diseases such
as arthritis, atherosclerosis and cancer [3].
Although there has been considerable growth in databases
concerned with metabolic proteins, kinases or other signaling
elements, very little attention has been devoted to structural proteins
and the role of network connectivity in their self-organization.
Comparing the ECM of several
Sponge
metazoans (Fig. 1) allows us to explore
Hydra
the evolution of self-organization and
its normal role in the development and
Fly
maintenance of multi-cellularity. Evolutionary conservation, for instance, can
identify functionally important network
components. A proper understanding of
Worm
such functions, will shed light on the
ECM’s role in health and disease.
Our initial network representing human ECM proteins and their
interactors consists of 361 nodes and 547 edges (inset top right).
There remain 61 proteins, identified as matrix components based
on Gene Ontology (GO) for which no known interactions were
present in BioGRID (40%).
We have created the first interaction map of the extracellular matrix
and estimate that the catalogue of human ECM proteins and their
interactors may exceed 2500 proteins. If current estimates for the
number of genes in the human genome are true (approximately
30,000) this implies that approaching 10% of the human genome is
dedicated to dealing with extracellular organization. This level of
complexity goes well beyond typical conceptual representations of the
extracellular matrix (e.g. Fig. 4) and justifies comprehensive analysis
of this system.
Our efforts demonstrate that the observed lack of attention paid to
structural proteins in databases in general also extends to GO
annotations. Consequently, additional terms will need to be included to
capture all of the known ECM components including all related
biological process and molecular function terms. Mapping of
annotated proteins from mouse and rat will aid considerably in
addressing the surprisingly incomplete human annotations. We found
that the total number of rat proteins annotated as ECM components
was 2402 (as compared to 1682 for humans).
Since 40% of the ECM proteins we identified so far have no
known interactions in BioGRID there is considerable opportunity to
extend the network by examining additional datasets (e.g. MINT,
Intact, BIND, DIP, HPRD) for which there appear to be only minimal
overlap [1].
Figure 1. A phylogeny derived primarily from
morphological features (after [2]) emphasizing the
common names of some organisms we hope to
include in our study.
ELN
Future Work
Human,Mouse,Fish
Materials and methods
The Gene Ontology (GO) project [6] addresses the need for a consistent
vocabulary in describing biological processes, cellular components and
molecular functions associated with gene products. We derived a list of
ECM proteins matching cellular component terms: extracellular matrix
part, middle lamella-containing extracellular matrix and, proteinaceous
extracellular matrix. These proteins were cross-referenced in BioGRID
[5], a database containing over 116,000 literature-curated interactions.
The network was rendered in Cytoscape [4].
Figure 2. ECM interactions were derived by filtering The Gene Ontology [6]
and cross-referencing to BioGRID [5]. Cytoscape [4] was used to render the
network.
Literature cited
1. Cesareni et al. 2005. FEBS Lett. 579(8):1828-1833.
2. Nielsen 2001. Animal Evolution. Second ed. Oxford University Press.
3. Online Mendelian Inheritance in Man, OMIM (TM). Johns Hopkins University,
Baltimore, MD. MIM Number: {#123700}: {4/19/2006}: . World Wide Web
URL: http://www.ncbi.nlm.nih.gov/omim/
 Enlarge the human ECM map based on orthology and an expanded
Careful examination of sub-graphs
such as that of elastin (ELN) and its nearest
neighbours (Fig. 3 main) demonstrates that
many of the interactors identified from the
BioGRID dataset are known ECM
components missed in the initial GO search
due to incomplete annotation of these proteins
in the Gene Ontology.
It is apparent that the corresponding
orthologues in rat and mouse are much more
completely annotated (data not shown). A
subsequent attempt to pull down proteins
matching all possible cellular component,
biological process and molecular function
terms associated with the extracellular matrix
shows that the ECM graph can be expanded to
at least 1682 nodes.
The network appears to be rooted to
core structural components, key amongst
these are various collagens which are either
adjacent, or interconnected by short path
lengths (Fig. 3 inset left).
4. Shannon et al. 2003. Genome Res 11:2498–2504. World Wide Web URL:
http://www.cytoscape.org/
5. Stark et al. 2006. Nuc Acids Res 34:535-539. World Wide Web URL:
http://www.thebiogrid.org/
6. The Gene Ontology Consortium. 2000. Gene Ontology: tool for the unification of
biology. Nature Genet. 25: 25-29 {accessed March 2007}. World Wide Web
URL: http://wiki.geneontology.org/
list of GO terms.
 Include interaction data from additional databases.
 Provide a detailed functional annotation of the resulting network.
 Construct ECM networks of other metazoans as a basis for
determining adaptation and evolutionary conservation.
Figure 3 (Inset top right): A physical protein-protein interaction map of the human extracellular matrix
based on interactions from curated literature sources deposited in BioGRID [5]. A list of ECM proteins was
derived from Gene Ontology [6] (all nodes shown in blue). Interactors resulting from the BioGRID search
are shown in yellow. (Main figure): A sub-network showing elastin (ELN) and its nearest neighbours.
Many of the interactors are known ECM proteins that should have been picked up in the initial search of
the GO data. (Inset left): The ECM network appears to be rooted in core structural components such as
various collagens featured in the sub-network shown here.
Figure 4. Typical representations of the extracellular matrix, such as this one,
include perhaps a dozen components which grossly under-represent the true
complexity of this system. Based on our findings we estimate that approaching
10% of the 30,000 genes in the human proteome may be involved in extracellular
organization. Image from: www.e22.physik.tu-muenchen.de/bausch/Oli_ECM.html
Acknowledgments
For further information
Thanks to my supervisory committee: Johanna Rommens, Andrew Emili, Gary Bader and my
supervisor, John Parkinson, for advice and encouragement. James Wasmuth, David He and
members of the Parkinson Lab for copious amounts of tea, advice and discussions. Funding
for this project was generously provided by the Heart and Stroke Foundation.
Please contact [email protected]. A copy of this poster as well as more
information on this and related projects can be obtained at www.compsysbio.org/lab/.