Abstract

Metabolic flux augmentation via glucose transport activation may be desirable in Glucose transporter 1 (Glut1) deficiency (G1D) and dementia, whereas suppression might prove useful in cancer. Using lung adenocarcinoma cells that predominantly express Glut1 relative to other glucose transporters, we screened 11,613 compounds for effects on the accumulation of an extracellularly-applied fluorescent glucose analog. 5 drugs currently prescribed for unrelated indications or preclinically-characterized robustly enhanced intracellular fluorescence. Additionally identified were 37 novel activating and 9 inhibitory compounds lacking previous biological characterization. Because few glucose-related mechanistic or pharmacological studies were available for these compounds, we developed a method to quantify G1D mouse behavior to infer potential therapeutic value. To this end, we designed a 5-track apparatus to record and evaluate spontaneous locomotion videos. We applied this to a G1D mouse model that replicates the ataxia and other manifestations cardinal to the human disorder. Because the first two drugs that we examined in this manner (baclofen and acetazolamide) exerted various impacts on several gait aspects, we used deep learning neural networks to more comprehensively assess drug effects. Using this method, 49 locomotor parameters differentiated G1D from control mice. Thus, we used parameter modifiability to quantify efficacy on gait. We tested this by measuring the effects of saline as control and glucose as G1D therapy. The results indicate that this in vivo approach can estimate preclinical suitability from the perspective of G1D locomotion. This justifies the use of this method to evaluate our drugs or other interventions and sort candidates for further investigation.

Significance Statement One approach to Glucose transporter I (Glut1) deficiency syndrome (G1D), dementia and cancer treatment is modulation of glucose transport. Using lung adenocarcinoma cells rich in Glut1, we identified, in high-throughput fashion, activators and inhibitors of fluorescent glucose analog transport. We also developed a gait testing platform for the deep learning neural network analysis of G1D mice that quantifies drug impact on 49 gait parameters, thus evaluating the potential preclinical efficacy of these drugs and other interventions via analysis of locomotion.