Genetic Circuit Manipulation
A deeper understanding of brain function requires experiments in which the circuit elements are probed and manipulated in a specific, controlled and reproducible fashion. The highly complex connectivity patterns and densely intermingled neuronal processes in central nervous systems pose a great challenge to this objective.
Drosophila transgenic approaches provide opportunities for non-invasive cell-specific manipulations of neuronal function that are not limited by anatomical constraints (Borst, 2009; Venken et al., 2011). The existence of cell-specific DNA regulatory elements is exploited to generate stable transgenic fly lines in which a transcription factor derived from other organisms (usually Gal4 from yeast) is targeted specifically to the neurons of interest. Arbitrary transgenes can now be reliably expressed in this pattern by crossing in Gal4-activatable UAS (upstream activating sequence) responder elements from other stable lines. The use of this modular system is highly versatile and hinges merely on the existence of suitable cell-specific Gal4 and other drivers. For many visual interneurons of interest, we have such specific driver lines at our disposal that can be crossed to actuator lines for cell-specific visualization and manipulation. Silencing of neurons can be achieved for instance by expressing the inwardly rectifying potassium channel Kir2.1 (Baines et al., 2001), the temperature-inducible synaptic inhibitor shibirets (Kitamoto, 2001), synaptobrevin-cleaving tetanus toxin light chain (Sweeney et al., 1995), or the photo-activatable chloride pump Halorhodopsin. As a complementary approach, neurons can be activated with heat using the TrpA1 channel (Marella et al., 2006) or with light using photo-activatable Channelrhodopsin2 (Pulver et al., 2009; Haikala et al., 2013).
If combined with a suitable behavioral readout (Rister et al., 2007) or whole-cell patch-clamp recordings from LPTCs (Joesch et al., 2008), detailed circuit information and function can be inferred from such manipulations (Joesch et al., 2010; Schnell et al., 2012; Bahl et al., 2013; Joesch et al., 2013; Maisak et al., 2013). Alternatively, the cell-specific expression of calcium indicators like TN-XXL (Mank et al., 2008; Reiff et al., 2010) or GCaMP (Maisak et al., 2013) can be used to image neuronal activity and establish visual response properties of neurons that are not accessible to electrodes.
By integrating the outcome from different experimental strategies into detailed models we want to understand the fundamental mechanisms that underlie the detection of visual motion. We thereby also hope to obtain some general insights into how information is processed in brains at the level of circuits, neurons, synapses and molecules.
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