«Connectivity, Organization, and Network Coordination of the Drosophila Central Circadian Clock by Zepeng Yao A dissertation submitted in partial ...»
For each neuron within an optical section, ROIs were drawn over somata using Fluoview software (Olympus). Raw intensity values for GCaMP3.0 emission or Epac1-camps CFP and YFP emission were recorded as mean pixel intensities (value range: 0—4,095) for each ROI at each time point and exported from Fluoview. Data transformations (see details in the following text) were conducted using custom software developed in Matlab (The MathWorks, Natick MA).
For GCaMP3.0 experiments, raw intensity traces were filtered with a 10-point moving average to remove high-frequency noise and then normalized to percentage fluorescence changes (ΔF/F0) using the following equation
where Fn is a raw intensity value recorded at each point in time and F0 is the baseline fluorescence value, calculated from the average of the raw intensity values in the first 10 s of recording from each trace. Maximum GCaMP3.0 fluorescence change values (max ΔF/F0) were determined as the maximum percentage change observed for each trace over the entire duration of each imaging experiment. Maximum values for each treatment and genotype were averaged to calculate the mean maximum change from baseline. To remove the direct excitatory effects of 488-nm light on Bolwig's Nerve (BN) (Yuan et al. 2011) from our analysis, which we observed during the start of a subset of our 488-nm scans, the F0 for all larval BN experiments was calculated from the average fluorescent intensities observed during the 15 s preceding the stimulus onset, by which time the baseline GCaMP3.0 fluorescence had stabilized following the light-induced excitation of the nerve.
For Epac1-camps data processing, we corrected YPF intensity values for spillover from the CFP channel by the following equation
where YFPSOC is the spillover—corrected YFP intensity, YFP and CFP are the raw intensity values, and 0.444 is the proportion of CFP emission that spills over into the YFP channel on our imaging system. The inverse FRET ratio, which is proportional to increases in cAMP, was calculated by taking the ratio of CFP/YFPSOC at all time points for each ROI. Each ratio trace was filtered with a 10-point moving average. All spillover-corrected and filtered Epac1-camps inverse FRET traces were normalized to the first time point to an initial value of “1.0.” Filtered, corrected, and normalized inverse FRET traces were expressed as percentage inverse FRET changes and averaged for each treatment and neuron type to create mean inverse FRET traces.
The maximum percentage inverse FRET change was determined for every neuron based on the entire duration of the experiment. Such maximum inverse FRET changes were averaged for each treatment and neuron type to determine the mean maximum inverse FRET change. For most Epac1-camps inverse FRET traces, a spontaneous and gradual increase in inverse FRET was observed due to a slow photobleaching of YFP, as has been described previously for this sensor (Börner et al. 2011; Shafer et al. 2008). To correct for these spontaneous changes, we determined the mean inverse FRET increase for 10—20 untreated or vehicle treated neurons of a particular genotype, depending on the nature of the experiment. This mean trace was then subtracted from each individual experimental trace to generate corrected inverse FRET traces.
To statistically compare maximum changes in GCaMP3.0 fluorescence or Epac1-camps inverse FRET ratio between the vehicle and test compounds, we used a Kruskal—Wallis oneway ANOVA with a Dunn's multiple comparison test. Pairwise comparisons of maximum changes in GCaMP3.0 fluorescence or inverse Epac1-camps FRET in response to test compound or vehicle perfusion were made using the Mann—Whitney U test. All plots and statistical tests were generated and performed using Prism 5 (GraphPad, San Diego CA). Figures were constructed in Adobe Illustrator and Photoshop (Adobe Systems, San Jose, CA). To obtain intensity-mapped images representing select time points before, during, and after ATP/P2X2 stimulation, single frames were captured from intensity-mapped still images using Fluoview.
These images were imported to Photoshop (Adobe Systems, San Diego CA), and trimmed to size.
2.4 Results 2.4.1 Controlled excitation of P2X2-expressing deep brain neurons with perfused ATP is compatible with high-resolution live imaging.
Previous work has established that neurons expressing transgenic P2X2 receptor in Drosophila can be excited at biologically relevant levels through the global uncaging of ATP in freely moving flies (Lima and Miesenböck 2005) or through the puffing of ATP on explanted brains during electrophysiologic recordings of superficial brain neurons (Hu et al. 2010). We wondered if the simple perfusion of ATP across the explanted brain could provide a reliable and technically facile means of exciting deeply situated adult neurons in a manner compatible with high-resolution live imaging. We therefore used a Pdf-Gal4 driver to coexpress UASGCaMP3.0 (Tian et al. 2009) and UAS-P2X2 (Lima and Miesenböck 2005) in the small ventral lateral neurons (s-LNvs). These cells are critical circadian pacemaker neurons whose small somata and deep position within the central brain make them difficult neurons to investigate electrophysiologically (Cao and Nitabach 2008). Compared with vehicle controls (Fig. 2.2A), 30s perfusions of 1 or 2.5 mM ATP resulted in significant GCaMP3.0 fluorescence increases, thereby revealing acute excitation of the s-LNvs (Fig. 2.2, B, C, E, F). In contrast, 30-s perfusions of 2.5 mM GTP did not result in significant increases in on GCaMP3.0 fluorescence, instead causing very small decreases in fluorescence during perfusion (Fig. 2.2, D and E). The latencies of the s-LNv responses to 1 mM ATP were less consistent compared with the responses to 2.5 mM, although a few s-LNvs did display relatively late responses to the higher dose (Fig.
2.2, B and C). Many of the GCaMP3.0 fluorescence increases displayed by the s-LNvs following 1 mM ATP perfusion were markedly bimodal, unlike the majority of responses to 2.5 mM (Fig.
2.2, B and C). This was reminiscent of s-LNv GCaMP3.0 responses to nicotinic acetylcholine receptor activation. Carbachol (CCh) excitation of s-LNv nicotinic acetylcholine receptors (nAChRs), which like P2X2 are expected to gate both Na+ and Ca2+ upon ligand binding, results in bimodal GCaMP3.0 responses at low CCh concentrations but in single fluorescence peaks at high concentrations (Lelito and Shafer 2012). It is possible that, in the case of bimodal responses, the first peak reflects the direct gating of Ca2+ through P2X2, whereas the second peak represents Ca2+ entry through voltage-gated Ca2+ channels or the release of intracellular Ca2+.
The Drosophila genome does not encode a P2X2 receptor homolog and previous studies suggest that there are no acute behavioral or physiologic effects of ATP in the absence of transgenic P2X2 (Lima and Miesenböck 2005; Littleton and Ganetzky 2000). Nevertheless, it is still possible that bath-applied ATP might have previously uncharacterized effects on the physiology of fly neurons, possibly through effects on the conserved ATP sensitive K+ channel (Kim and Rulifson 2004), or might have effects on properties of the genetically encoded sensors themselves (Willemse et al. 2007). We therefore treated brains expressing UASGCaMP3.0 or UAS-Epac1-camps in the absence of transgenic P2X2 expression with 30-s perfusions of 2.5 mM ATP to determine if ATP had measurable effects on GCaMP3.0 fluorescence or the inverse Epac1-camps FRET ratio (CFP/YFP), which are directly proportional to Ca2+ and cAMP levels, respectively. The 30-s perfusions of 2.5 mM ATP resulted in very small but consistent transient decreases in GCaMP3.0 fluorescence relative to vehicle controls (Fig. 2.2, G and H). Bath-applied ATP also caused a consistent increase in Epac1-camps inverse FRET values relative to vehicle controls (Fig. 2.2, I and J). However, the evaluation of raw CFP and YFP traces revealed that this change was not due to bona fide FRET changes, but rather to decreases in YFP fluorescence, reminiscent of GCaMP3.0 fluorescence loss (Fig. 2.2J and data not shown). We therefore conclude that bath-applied ATP has only small and easily accounted for effects on GCaMP3.0 fluorescence and Epac1-camps inverse FRET.
Taken together, these results indicate that deeply situated P2X2-expressing neurons can be excited by the controlled perfusion of ATP across the explanted brain in a manner compatible with high-resolution GCaMP3.0 and Epac1-camps live imaging within single neuronal somata.
Furthermore, the absence of ATP excitation in neurons lacking transgenic P2X2 expression confirms that, as expected from previous work (Lima and Miesenböck 2005), ATP did not excite the s-LNvs in the absence of specifically directed P2X2 expression and had only minor effects on genetically encoded sensors.
2.4.2 LexA operator-driven sensors and P2X2 for dual binary expression experiments.
Our proposed method of circuit interrogation requires the independent expression of the P2X2 receptor and genetically encoded sensors in neurons of interest and their putative follower neurons (Fig. 2.1). To complement existing UAS-Sensor and UAS-P2X2lines and the large number of existing GAL4 and LexA drivers, we have created a series of transgenic flies containing GCaMP3.0, Epac1-camps, and P2X2 elements under the control of the LexA operator (LexAop) (Lai and Lee 2006). We tested the functionality of our LexAopGCaMP3.0 and LexAop-Epac1-camps elements within s-LNvs using the previously described Pdf-LexA element (Shang et al. 2008). The adult s-LNvs respond to the general cholinergic agonist carbachol (CCh) with rapid Ca2+ and cAMP increases (Lelito and Shafer 2012). LexAop-driven GCaMP3.0 and Epac1-camps were indeed capable of detecting significant increases in Ca2+ and cAMP in response to 30-s perfusions of 10−4 M CCh (Fig. 2.3, A—D).
Along with evidence presented below, these results indicate that our LexAopGCaMP3.0 andLexAop-Epac1-camps elements are suitable for the observation of Ca2+ and cAMP dynamics within single somata of deeply situated neurons of the adult brain.
We tested the functionality of our LexAop-P2X2 element by coexpressing it with LexAopGCaMP3.0 in the s-LNvs using Pdf-LexA. The s-LNvs of Pdf-LexA,LexAopGCaMP3.0/+;LexAop-P2X2/+ brains displayed clear increases in GCaMP3.0 fluorescence in response to 30-s perfusions of 1 mM ATP, indicating that the LexAop-driven P2X2 element had
rendered the s-LNvs sensitive to bath-applied ATP (Fig. 2.3, E and F). Importantly, the LexAopP2X2 element rendered the s-LNvs sensitive to ATP only when driven by the Pdf-LexA driver:
when UAS-GCaMP3.0 was driven in the s-LNvs with Pdf-GAL4 in flies carrying the LexAopP2X2 element, ATP had no significant effects on GCaMP3.0 fluorescence (Fig. 2.3, E and F).
This observation, along with work presented in the following text, indicates that the presence of theLexAop-P2X2 element does not cause significant P2X2 expression in the absence of LexA drivers. The same was true for the previously described UAS-P2X2 element (Fig. 2.3, E and F;
Lima and Miesenböck 2005). We conclude that, like its UAS counterpart, our LexAopP2X2 element is capable of specifically rendering deeply situated adult neurons excitable by bath-applied ATP.
2.4.3 Bath-applied ATP reliably and repeatedly activates P2X2-expressing neurons of the adult brain.
Having acquired the genetic elements necessary for dual binary control of P2X2 and sensor expression, we sought to determine the most reliable means of exciting deep brain neurons expressing UAS-P2X2 and LexAop-P2X2 elements using bath-applied ATP. We first imaged the somata of three different classes of neuron coexpressing P2X2 and GCaMP3.0: the sLNvs and DN1p clock neurons [usingPdf(bmrj)-GAL4 and Clock(4.1M)-Gal4, respectively] and the olfactory projection neurons [PNs; using Cha(7.4)-Gal4] and compared the effects of 30-s perfusions of a range of ATP concentrations on GCaMP3.0 fluorescence (Fig. 2.4A). For all three neuron types, 30-s perfusions of 0.1 mM ATP had no significant effects on GCaMP3.0 fluorescence. Higher concentrations resulted in dose-dependent increases in Ca2+ responses, with the s-LNvs and DN1ps displaying sigmoidal response curves and the PNs (the most superficial of the neurons tested) displaying a biphasic response curve with diminished response magnitudes at doses 5 mM (Fig. 2.4A). We also compared the effects of these ATP concentrations between sLNvs expressing GCaMP3.0 and P2X2 using either the GAL4 or LexA expression system. The LexA-expressing s-LNvs displayed significant GCaMP3.0 responses over the same range of ATP concentrations as their GAL4-expressing counterparts, but did so with lower response amplitudes, most likely due to lower levels of transgene expression (Fig. 2.4E). Nevertheless, the LexA-expressing s-LNvs displayed maximum fluorescence changes (ΔF/F0) approaching 100%, amplitudes on par with the GCaMP3.0 responses displayed by fly sensory neurons subjected to acute sensory excitation (Tian et al. 2009). As shown in Fig. 2.4, C and D, the excitatory responses of single P2X2-expressing neurons to a series of increasing ATP doses were proportional to the concentration of perfused ATP. Thus, the excitatory responses of single neurons can be controlled through the manipulation of ATP dose, thereby making it possible to excite neurons at a range of intensities.