Dissecting spatio‐temporal protein networks driving human heart development and related disorders

Abstract

Aberrant organ development is associated with a wide spectrum of disorders, from schizophrenia to congenital heart disease, but systems-level insight into the underlying processes is very limited. Using heart morphogenesis as general model for dissecting the functional architecture of organ development, we combined detailed phenotype information from deleterious mutations in 255 genes with high-confidence experimental interactome data, and coupled the results to thorough experimental validation. Hereby, we made the first systematic analysis of spatio-temporal protein networks driving many stages of a developing organ identifying several novel signaling modules. Our results show that organ development relies on surprisingly few, extensively recycled, protein modules that integrate into complex higher-order networks. This design allows the formation of a complicated organ using simple building blocks, and suggests how mutations in the same genes can lead to diverse phenotypes. We observe a striking temporal correlation between organ complexity and the number of discrete functional modules coordinating morphogenesis. Our analysis elucidates the organization and composition of spatio-temporal protein networks that drive the formation of organs, which in the future may lay the foundation of novel approaches in treatments, diagnostics, and regenerative medicine.

Cilia and coordination of signaling networks during heart development

“…20,21 Lage et al (2010) performed a genome-wide systematic mapping of protein-protein interaction networks involved in different stages of heart development based on mouse models. 212 In this study, high-confidence experimental interactome data suggested that heart development is controlled by communication within and between a defined set of signaling pathways (Fig. 5).…”

Genetics and Genetic Testing in Congenital Heart Disease

“…Studies employing a diverse array of model organisms including mice, frogs, and zebrafish, have facilitated major insight into normal and abnormal cardiogenesis. Furthermore, systems biology approaches designed to assess functional convergence of causative CHD genes and associated transcriptional responders (genes with altered cardiac expression) have suggested that multiple CHD risk factors are more likely to act on different components of a common functional network than to directly converge on a common genetic or molecular target 6,7 . These findings, coupled with an ever-expanding list of CHD-associated gene mutations 8 , chromosomal abnormalities 9 , environmental causes 10,11 , and epigenetic insults 12,13 hint at a significant complexity to both normal heart development and CHD pathogenesis.…”

Applicability of Computational Systems Biology in Toxicology

“…The first example of such a human protein-protein interaction network is Rual's protein-protein interaction network that is based on a high-throughput yeast two-hybrid system applied to test human binary protein-protein interactions [24]. Another such approach is InWeb developed by Lage et al [25][26][27] with data compiled from various sources. InWeb allows the user to retrieve and predict a network of interacting genes/proteins based on an input gene list.…”