Description:

Brynna Webb
PhD Candidate in the Laboratory of Geoffrey Swanson, PhD

"Motor phenotype of a mouse model for a human kainate receptor genetic disorder"

Deleterious mutations in ionotropic glutamate receptor genes are causative for numerous non-syndromic neurodevelopmental disorders (NDDs). Individuals with NDD caused by a point mutation in the glutamatergic kainate receptor subunit 2 (GRIK2 p.A657T) exhibit imbalanced to ataxic gait. We are interested in identifying the mechanistic basis for this impaired motor control using a mouse model with the same mutation. A657T mice demonstrate alterations in motor coordination and posture that we have characterized using a battery of behavioral tests including ataxia scoring (ledge test, clasping, kyphosis, gait). We aim to elucidate the neural correlates of the motor deficits observed in A657T animals using electrophysiological techniques and anticipate that our findings will enhance our understanding of the role of kainate receptors in motor control and developmental disease.

Cydney Martell
PhD Candidate in the Laboratory of Gabriel Rocklin, PhD

"High-throughput discovery of the sequence and structure determinants for stress-induced aggregation of miniproteins"

Miniproteins (< 10 kDa) are emerging as a promising therapeutic alternative to small molecule inhibitors and larger antibodies. One major challenge in developing protein therapeutics is they can aggregate when exposed to physical stresses during storage, transport, and in the body. The ability to design aggregation-resistant miniproteins would increase their applications in treating disease. I aim to learn design rules for hyper-stable proteins that remain folded when exposed to aggregation-promoting stresses. We are developing a mass spectrometry-based approach to quantitatively measure the aggregation resistance after stress exposure for thousands of miniproteins at one time. The large-scale aggregation data will be integrated with protein sequence and structural features to develop a quantitative model to predict aggregation. The lessons from this analysis will allow us to rationally design proteins with unprecedented resistance to stress.