Cerebellar ataxias form a large group of movement and balance disorders that result from degeneration of Purkinje cells. Nearly two dozen individual genes have been identified to date that, if mutated, can cause various cerebellar ataxias in humans or mice. But even with such a wealth of genetic clues, the causes of cell death are hard to pin down because of the difficulty identifying the normal functions of disease-related proteins and the pathways they are involved in. The same problem plagues research in all types of neurodegenerative diseases.
That’s where the interactome can help, according to a new study in today’s issue of Cell. Starting with over 50 proteins involved in 23 different inherited ataxias, researchers in the labs of Huda Zoghbi at Baylor College of Medicine in Houston, Texas, and Marc Vidal at the Dana-Farber Cancer Institute in Boston, Massachusetts, used high-throughput yeast two-hybrid screens to construct a disease-related protein-protein interaction network. Their work shows that the apparently unrelated ataxia gene products organize into a highly connected interaction network that can provide clues to the underlying pathology of this group of related diseases.
By zeroing in on this little corner of the global interactome terrain, the researchers showed they could identify novel candidate disease genes as well as genetic modifiers and potential pathological pathways. Their technique is certain to be useful for other neurodegenerative diseases like Parkinson disease, where multiple genes have been implicated in causing or modulating a common clinical phenotype of neurodegeneration. At present, there do not seem to be enough candidate genes or modifiers for Alzheimer disease to generate a network, but that could change.
To link the many known ataxia genes, Baylor postdoctoral fellow and first author Janghoo Lim took advantage of the Vidal lab’s high-throughput yeast two-hybrid assays to identify the interaction partners for the protein products of 23 ataxia-causing genes plus 31 other ataxia-associated proteins. When they tested the proteins against either a whole-genome expression library or an adult brain library, they came up with 770 interactions, of which 96 percent were novel.
Of course, the interactome is only as good as the underlying interactions, and the yeast two-hybrid screen is notorious for generating false positive and negatives. To try to minimize false positives, the researchers used a two-hybrid screen that did not rely on overexpression of proteins. To gauge their success, a representative sample of interactions was tested in biochemical pull-down experiments, with an 83 percent confirmation rate. The interactions were also confirmed by a high rate of concordance in their subcellular distribution annotation in the Gene Ontogeny database.
Analysis of the interactions showed that 13 of the 23 disease-causing proteins organized into a single dominant network, revealing that the proteins were associated directly or indirectly through common intermediates. The 10 proteins with no connections to the main network had fewer interactions than the others. It turns out these 10 were screened using one full-length expression clone each, in contrast to the others which were expressed as multiple overlapping partial clones. Isolated domains are known to pick up more interactions in the yeast two-hybrid screen than full-length proteins. Consistent with this, the 10 outliers did have fewer partners, raising the possibility that a more extensive analysis would reveal more links that would tie them into the larger network. Alternatively, they could represent proteins involved in unrelated pathogenic pathways.
To their own interaction data, the researchers added additional interactions culled from other studies of the same proteins, or their relatives, to produce an extended map network that included all 23 ataxia proteins. Analysis of the extended network showed it was tighter and more interconnected than a model network formed from 30 random disease genes. Many ataxia-causing proteins were linked by shared partners. Some of these shared partners were familiar as disease modifiers previously identified in genetic screens in Drosophila and mouse models of ataxia. In some cases, these genetic modifiers showed up as hubs that linked multiple ataxia genes. Such hubs make interesting jumping-off points for studies aimed at understanding commonalities among different types of ataxia. They also represent potential therapeutic targets.
In their summary, the authors propose that “phenotype-based protein-protein interaction studies can be applied to many human diseases, particularly common disorders that are sporadic in the majority of cases but do result from single gene defects in a small subset of patients,” including Parkinson disease, diabetes, and hypertension.—Pat McCaffrey
No Available References
- Lim J, Hao T, Shaw C, Patel AJ, Szabó G, Rual JF, Fisk CJ, Li N, Smolyar A, Hill DE, Barabási AL, Vidal M, Zoghbi HY. A protein-protein interaction network for human inherited ataxias and disorders of Purkinje cell degeneration. Cell. 2006 May 19;125(4):801-14. PubMed.