Techniques for improving activity based biosensors: a Kuhl platform for engineering

Abstract

According to Kuhn, ''there are three classes of problems - determination of significant facts, matching of facts with theory, and articulation of that theory (Kuhn 2012).'' The current paradigm in molecular neuroscience is that there is a need for revolutionary tool development in neuroscience. Interestingly, the need for better tools in neuroscience is to answer neuroscience theories and provide the determination and articulation of those theories. Currently, the neuroscientist's toolbox is growing and the ways in which those tools are used is rapidly changing. Neuroscience underwent a revolution when we were able to take single-cell recording in vivo and then assign field properties to individual neurons based upon those responses (O'Keefe and Bouma 1969; O'Keefe and Dostrovsky 1971; Moser et al. 1995). Scientists became adept at imaging increasingly smaller regions of the functioning human brain (Price 2012). We have since been able to genetically encode and manipulate proteins and pathways while recording from them using fluorescence (Southern and Berg 1982; Chalfie 2009). In vitro and in vivo we have harnessed the use of light to stimulate or inhibit specific neurons or ligands (Boyden 2011; Adamantidis et al. 2007). These tools are just the beginning and by no means is this an exhaustive list. We introduce the Kuhl synthetic cell system that provides a customizable de-novo excitable cell. The Kuhl system is activated using a blue light photo activated cyclase bPAC. It can be used to create better tools to image the brain and can be used to screen multi-color fluorescent sensors. Interestingly, sensors that are within bPACs activation spectrum can be used in these synthetic cells. We show that both red and green Ca 2+ sensors can be imaged simultaneously, and both Ca 2+ and Voltage sensors can be screened in the Kuhl system. The Kuhl system has the potential to be used to screen for drug compounds and in theory, they could be used in studying pathways that are less understood, such as the mTOR pathway.