Protein homeostasis in human cells

It’s tough to be a protein. From the moment of birth in the ribosomal exit tunnel until the very last squeeze through the proteasomal channel, they are often harassed by various stresses like heat, ionizing radiation, and reactive oxygen species. To cope with this, cells have evolved an elaborate network of proteins that maintain protein homeostasis, or proteostasis. This evolutionary ancient network consists of chaperones and co-chaperones, E3 ligases and deubiquitinases, trafficking proteins, and hundreds of other quality-control factors. In turn, these factors associate with and regulate essentially all cellular proteins.

We are interested in deciphering how this network is physically organized in human cells. We use diverse high-throughput protein/protein interaction assays to characterize the network and identify the key players. However, the network itself is not the goal. Rather, we use the large-scale data to ask specific questions. Why has the eukaryotic chaperone machinery evolved such a large cohort of regulatory factors and co-chaperones? How are these cofactors regulating chaperone function? How do chaperone/client interaction networks change in response to cellular conditions, or during evolution? Why do proteins need chaperones in the first place?

 

 

Rare diseases

There are about 7,000 known rare diseases. While each of them is rare, together they affect millions of people around the world. In the next 5 years, we will essentially know all the genes underlying Mendelian diseases, which account for most rare diseases. But what then? There is no cure nor treatment for most of these diseases, and pharmaceutical companies have no financial incentives to develop drugs for them.

The traditional approach has been to use multiple assays and techologies to study a particular Mendelian disease. But what if we turned the question upside down? What if we studied all rare diseases at the same time but with very specific assays. For example, instead of screening thousands of different drugs to treat one disease, could we screen thousands of diseases with one drug?

As a collaboration between Marc Vidal’s lab at the Center for Cancer Systems Biology and Sue Lindquist’s lab at the Whitehead Institute, we have created a Gateway-compatible collection of almost 3,000 mutant alleles for 1,100 Mendelian diseases (Sahni, Song, Taipale et al. Cell 2015). Our aim is to systematically phenotype this collection of disease-causing alleles in order to find novel connections between poorly-studied rare diseases and known pathways.

rare diseases discovered

%

have existing therapies

Can we do better?

Technology development

We believe that technology drives innovation as much as the other way around. On the one hand, restriction enzymes, RNAi, reprogramming, and CRISPR are all fascinating biological phenomena in their own right, but this is dwarfed by their impact as enabling technologies. On the other, although technologies such as next-gen sequencing were originally developed with specific applications in mind, researchers have exploited and repurposed the platforms for their own research.

Our aim is to develop methods and tools to investigate biomolecular interactions that have not been amenable to traditional methods. These include interactions between E3 ligases and their targets; secreted ligands and their receptors; and small molecule drugs and their cellular targets. For example, we have shown that chaperones can be exploited as “thermodynamic sensors” to detect drug/target interactions in living cells (Taipale et al. 2013). Systematic characterization of the chaperone/client interaction network enables us to expand the scope of this method to novel drug target classes.

Although we are certainly interested in fundamental biological questions, our aim here is to let the results guide us and take us to new research avenues.