Credit: Photoalto

As the list of genetic variants that are implicated in disease gets longer, the challenge is to understand how they contribute to disease phenotypes. A recent study describes a high-throughput yeast system for detecting the effects of disease alleles on protein stability.

Pittman et al. developed a system — known as intra-DHFR enzyme stability assay (IDESA) — in which the allele to be characterized is inserted within a dihydrofolate reductase (DHFR) reporter gene. If the resulting mutant protein is unstable, it will also destabilize the DHFR protein. When the construct is placed in a yeast strain that lacks DHFR, this instability can be detected by a reduction in growth compared with yeast expressing stable DHFR.

The authors tested IDESA using mutant alleles of the gene alanine–glyoxylate aminotransferase (AGT) that cause the condition primary hyperoxaluria type 1 (PH1) and that have a known effect on protein stability. Clear reductions in yeast growth were seen for two mutations, one with a severe effect on protein stability and one with a milder effect.

The system was then put to use in characterizing a wider range of disease alleles. Starting with additional AGT alleles, previously unknown effects on protein stability were identified for some mutations, and IDESA successfully discriminated between alleles that reduce stability versus those that confer loss of function for other reasons. The authors then used the system to examine disease variants that are involved in four other conditions: familial amyotrophic lateral sclerosis, Parkinson's disease, spinal muscular atrophy and cancer. In each case, by either modifying the temperature or adding a destabilizing mutation to DHFR (thus making it more sensitive to the destabilizing effects of disease proteins), they were able to tune the system to detect reductions in growth caused by destabilizing mutations.

IDESA is amenable to high-throughput screening and, it seems, can be used for a wide range of proteins, providing a valuable tool for characterizing disease mutations. As the authors demonstrate, the system can also be used to screen for small molecules that restore protein stability — a step towards being able to reverse disease phenotypes.