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The yeast Saccharomyces cerevisiae was used to express a medically relevant G-protein coupled receptor (GPCR), the human adenosine (A2a) receptor, with a C-terminal green fluorescent protein (GFP) fusion tag. In prior studies, we established an expression system for A2a-GFP. Here, we quantified the total A2a-GFP expression levels by correlating GFP levels as detected by fluorescence and densitometry to A2a-GFP molecules overexpressed in the system. We also quantified A2a-GFP functional levels by classical radioligand binding assays. Approximately, 120,000 functional A2a-GFP molecules per cell were present on the plasma membrane as determined by radioligand binding. Using whole cell GFP fluorescence, 340,000 A2a-GFP molecules per cell were detected; approximately 70% of those molecules were plasma membrane localized, as determined by using confocal microscopy analysis. These results show that a significant portion of the total expressed protein is functional. In addition, the quick and inexpensive whole cell fluorescence appears to provide a good approximation of functional receptor numbers for this case. Importantly, the amount of functionally expressed A2a-GFP per culture ( approximately 4 mg/L) is among the highest reported for any GPCR in any expression system.

This report describes a method to culture insects cells in 24 deep-well blocks for the routine small-scale optimisation of baculovirus-mediated protein expression experiments. Miniaturisation of this process provides the necessary reduction in terms of resource allocation, reagents, and labour to allow extensive and rapid optimisation of expression conditions, with the concomitant reduction in lead-time before commencement of large-scale bioreactor experiments. This therefore greatly simplifies the optimisation process and allows the use of liquid handling robotics in much of the initial optimisation stages of the process, thereby greatly increasing the throughput of the laboratory. We present several examples of the use of deep-well block expression studies in the optimisation of therapeutically relevant protein targets. We also discuss how the enhanced throughput offered by this approach can be adapted to robotic handling systems and the implications this has on the capacity to conduct multi-parallel protein expression studies.