A FRET sensor for the real-time detection of long chain acyl-CoAs and synthetic ABHD5 ligands

Direct effects of adipocyte lipolysis on AMPK through intracellular long-chain acyl-CoA signaling

Long-chain acyl-CoAs (LC-acyl-CoAs) are important intermediary metabolites and are also thought to function as intracellular signaling molecules; however, the direct effects of LC-acyl-CoAs have been difficult to determine in real-time and dissociate from Protein Kinase A (PKA) signaling. Here, we examined the direct role of lipolysis in generating intracellular LC-acyl-CoAs and activating AMPK in white adipocytes by pharmacological activation of ABHD5 (also known as CGI-58), a lipase co-activator. Activation of lipolysis in 3T3-L1 adipocytes independent of PKA with synthetic ABHD5 ligands, resulted in greater activation of AMPK compared to receptor-mediated activation with isoproterenol, a β-adrenergic receptor agonist. Importantly, the effect of pharmacological activation of ABHD5 on AMPK activation was blocked by inhibiting ATGL, the rate-limiting enzyme for triacylglycerol hydrolysis. Utilizing a novel FRET sensor to detect intracellular LC-acyl-CoAs, we demonstrate that stimulation of lipolysis in 3T3-L1 adipocytes increased the production of LC-acyl-CoAs, an effect which was blocked by inhibition of ATGL. Moreover, ATGL inhibition blocked AMPKβ1 S108 phosphorylation, a site required for allosteric regulation. Increasing intracellular LC-acyl-CoAs by removal of BSA in the media and pharmacological inhibition of DGAT1 and 2 resulted in greater activation of AMPK. Finally, inhibiting LC-acyl-CoA generation reduced activation of AMPK; however, did not lower energy charge. Overall, results demonstrate that lipolysis in white adipocytes directly results in allosteric activation of AMPK through the generation of LC-acyl-CoAs.

Applications and Tuning Strategies for Transcription Factor-Based Metabolite Biosensors

Transcription factor (TF)-based biosensors are widely used for the detection of metabolites and the regulation of cellular pathways in response to metabolites. Several challenges hinder the direct application of TF-based sensors to new hosts or metabolic pathways, which often requires extensive tuning to achieve the optimal performance. These tuning strategies can involve transcriptional or translational control depending on the parameter of interest. In this review, we highlight recent strategies for engineering TF-based biosensors to obtain the desired performance and discuss additional design considerations that may influence a biosensor's performance. We also examine applications of these sensors and suggest important areas for further work to continue the advancement of small-molecule biosensors.