As part of Perlara’s collaboration with the Undiagnosed Disease Network (UDN) and Harvard Medical School on the GNAO1 PerlQuest – which our Director of R&D, Nina DiPrimio, introduced in a previous post – I have been working with the yeast team headed by Jessica Lao on developing a GNAO1 yeast model. This post on The Ark details how we went about developing the model, and our next steps.

Introducing GNAO1

GNAO1 is a gene that encodes for the alpha subunit of a G protein, and is abundant in the central nervous system. Mutations in GNAO1 are associated with a range of neurodevelopmental disorders. Some of the most common symptoms include seizures, movement disorders, and intellectual disability. The patient diagnosed by the UDN is a 16-year-old girl with dystonia, muscle weakness, and slurred speech with an A221D mutation. In yeast, the GNAO1 ortholog is GPA1, which is involved in the mating response pathway. As shown below in Figure 1, ligand binding to the G protein-coupled receptor stimulates a GDP for GTP exchange by Gpa1. This causes Gpa1 to dissociate from Ste4 and Ste18 and free them to associate with Ste20. This stimulates a signaling cascade and activates the mating response pathway. A mating response that is left on perpetually within a cell will lead to cell cycle arrest and, eventually, cell death. This is true when GPA1 is deleted in yeast cells and gpa1∆ cells are not viable.

GNAO1 yeast model mating response pathway 435x627px

Figure 1. Yeast Mating Response Pathway. Adapted from Schmidt, 2013. Alpha factor acts as the appropriate ligand that binds to the G-protein coupled receptor (GPCR) to begin the mating response as described in text

Generating GPA1 variants

In developing the GNAO1 yeast model, we generated five different variants in GPA1 that are associated with GNAO1 pathogenic mutations: G48W (G40R), G53E (G45E), R327G (R209G), E364K (E246K), and A339D (A221D). We made these mutations in plasmids and integrated them directly into the genome of a gpa1∆ cell. One problem with this approach is that gpa1∆ is lethal, so we bypassed this by using a uracil (URA3) conditional rescue plasmid expressing wild type GPA1 (Figure 2).

GNAO1 yeast model bypassing lethality of gpa1 800x253pxFigure 2. Bypassing the lethality of gpa1∆. We made gpa1∆ in a cell carrying a plasmid with wild type GPA1 and URA3. When 5-FOA is introduced, only cells that have lost the URA3 plasmid will survive. The cell is then left with only the GPA1 variant that we introduced

Figuring out the phenotype of each of our five GPA1 mutations is a crucial first step in our overall goal of a workable drug screen. To do this, I grew yeast cells in media containing 5-FOA and used our SpectraMax, a tool that measures optical density, to measure growth over time. 5-FOA selects against the URA3 rescue plasmid, leaving us to see the phenotype of the mutations. I used gpa1∆ as my negative control and a strain expressing wild type GPA1 as my positive control.

GNAO1 yeast model results

G48W and G53E grew similarly to gpa1∆, while R327G and E364K grew like wild type cells (Figure 3). After repeating the growth assay multiple times, we are confident that these are the growth phenotypes associated with these mutations.

GNAO1 Yeast Models Growth of GPA1 Variants2 862x531pxFigure 3: Growth of GPA1 variants. This chart shows representative data from one of three biological replicates

At the time of our first growth assay (Figure 3), three biological replicates of A339D were also included. There were variations between the three strains that prompted us to test more independent strains. Figure 4 illustrates the growth variation we see with 7 of our A339D strains. As of now, we know that there is a growth defect with this mutation, but the degree of defect varies across strains. Our next step is to figure out where the variability lies: is it between strains or is it within each strain itself? This is an important question to answer as we choose which strains of the GNAO1 yeast model to use for our drug screen.

GNAO1 yeast model growth variability A339D strains A 752x452 GNAO1 yeast model growth variability A339D strains B 752x452px

Figure 4: Growth variability of A339D strains. Independent biological replicates of A339D are marked (A339D-1, -2, etc.) Top panel shows the growth assay from July 5. Bottom panel shows the growth assay from August 23

Moving Forward

Along with trying to determine which strains of the GNAO1 yeast model to use in our drug screen, we want to understand how the mutations affect GPA1 function. The role of GPA1 in mating allows us to look at cell morphology. Haploid yeast cells have two mating types, MATa and MAT⍺. Each type releases its own mating factor or pheromone that attracts the opposite cell type and when that happens, the cells themselves undergo a morphological change called a shmoo as they attempt to conjugate and make a diploid (Figure 5).

GNAO1 yeast model - yeast mating 500x777px

Figure 5. Yeast Mating. Fijałkowski, 2006. Two cells of different mating types are illustrated along with their specific pheromones (1). Specific receptors on each cell respond to the opposite mating factors and they begin to take on a schmoo shape (2) until they eventually conjugate together to make a diploid (3)

The strains we are working with in the GNAO1 yeast model are mating type a, so we can introduce the pheromone released by the other cell type called alpha factor to induce a morphological change in our variants. We know that in gpa1∆ cells, the mating pathway is always on and cells arrest in a shmoo state, even in the absence of pheromone. G48W and G53E are also inviable, and we hypothesize that they also arrest in a shmoo state. On the other hand, R327G and E364K have no growth defect, but we wonder if they would respond to pheromone as wild type cells would. This could help us better understand how the mutations affect GPA1 function.


Ananth, A. L. (2016). Clinical Course of Six Children With GNAO1 Mutations Causing a Severe and Distinctive Movement Disorder. Pediatric Neurology,59, 81-84. doi:10.1016/j.pediatrneurol.2016.02.018

Danti, F. R. (2017). GNAO1encephalopathy. Neurology Genetics,3(2), 1-8. doi:10.1212/nxg.0000000000000143

GNAO1 encephalopathy. (2017, October 3). Retrieved from

GNAO1 Gene – Undiagnosed Diseases Network (UDN). (2017). Retrieved from

Helbig, I., & Kiel. (2013, September 8). G proteins, GNAO1 mutations and Ohtahara Syndrome


Translate »