Data from: An essential experimental control for functional connectivity mapping with optogenetics
Data files
Aug 11, 2025 version files 151.13 GB
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IHC_data.zip
5.31 GB
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larval_ca_data.zip
145.83 GB
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README.md
4.40 KB
Abstract
To establish functional connectivity between two candidate neurons that might form a circuit element, a common approach is to activate an optogenetic tool such as Chrimson in the candidate pre-synaptic neuron and monitor fluorescence of the calcium-sensitive indicator GCaMP in a candidate post-synaptic neuron. While performing such experiments in Drosophila, we found that low levels of leaky Chrimson expression can lead to strong artifactual GCaMP signals in presumptive postsynaptic neurons even when Chrimson is not intentionally expressed in any particular neurons. Withholding all-trans retinal, the chromophore required as a co-factor for Chrimson response to light, eliminates GCaMP signal but does not provide an experimental control for leaky Chrimson expression. Leaky Chrimson expression appears to be an inherent feature of current Chrimson transgenes, since artifactual connectivity was detected with Chrimson transgenes integrated into multiple genomic locations. While these false-positive signals may complicate the interpretation of functional connectivity experiments, we illustrate how a no-Gal4 negative control improves interpretability of functional connectivity assays. We also propose a simple but effective procedure to identify experimental conditions that minimize potentially incorrect interpretations caused by leaky Chrimson expression.
Dataset DOI: 10.5061/dryad.t4b8gtj77
Description of the data and file structure
Data from: An essential experimental control for functional connectivity mapping with optogenetics
This repository contains raw data of larval calcium imaging and adult immunohistochemistry files shown in the paper titled 'An essential experimental control for functional connectivity mapping with optogenetics'
Files and variables
High level overview
Folder 'IHC_data.zip' contains both the raw and processed immunohistochemistry data shown in Figure 5.
Folder 'larval_ca_data.zip' contains both the raw and the preprocessed calcium imaging data shown in Figures 1, 3, and 6.
The leaky_expression_publication folder (on Zenodo) contains preprocessed data and the scripts used to create Figures 1, 2, 3, 4, and 6 of the manuscript.
Detailed information about each file type found in this repository
The zip file 'IHC_data' contains the following data:
- folder: 'IHC_data'
- file: imaging file (e.g., attp1_02.czi)
- file: save_UEP_Fiji_macro.ijm -> This file was used to process the imaging files using the program 'Fiji' (https://imagej.net/software/fiji/)
- folder: NC82_jpegs
- processed imaging file of the structural marker NC82 (e.g., MAXattp1_01.jpg)
- folder: tdtomato_jpegs
- processed imaging file of the experimental marker (e.g., MAXattp1_01.jpg)
The zip file larval_ca_data contains the following folder structure and file types:
- folder: larval_ca_data
- folder: genotype and ATR status. (e.g., FDT106xFDT355_ATR-).
- folder: light intensity used (e.g., 8uW_1s)
- folder: experimental folder (e.g., 2021-01-30_18-22-26_0point5V_1s_step) -> This folder contains both 'raw' files created at the time of the experiment and 'preprocessed files'.
- Raw files:
- file: 0point5V_1s_step.npy -> Stimulus file used for this experiment. Values indicate voltage delivered to stimulus LED at a frequency of 1kHz.
- files: XX.tiff -> imaging data from the microscope. Each tiff file is one experiment, the number of tiff files indicates the number of repeats.
- Preprocessed files:
- background_ROI.npy -> manually selected rectangular region used to subtract stimulus light bleedthrough.
- signal_ROI.npy -> manually selected rectangular region of interest
- XX.csv (e.g., 2021-01-30_18-22-26_0point5V_1s_step_dF_over_F.csv) -> csv file with 7 columns:
- Time [s]: time relative to the start of the repeat.
- Stimulation [V]: Stimulation in voltage
- dF/F no 1-5: Change in fluorescence (background subtracted using signal_ROI.npy-background_ROI.npy) of each repeat.
- XX.jpg (e.g., 2021-01-30_18-22-26_0point5V_1s_stepdF_over_F.png) -> overview of what's shown in the XX.csv file, background_ROI.npy and signal_ROI.npy file.
- Raw files:
- folder: experimental folder (e.g., 2021-01-30_18-22-26_0point5V_1s_step) -> This folder contains both 'raw' files created at the time of the experiment and 'preprocessed files'.
- folder: light intensity used (e.g., 8uW_1s)
- folder: genotype and ATR status. (e.g., FDT106xFDT355_ATR-).
The folder leaky_expression_publication contains the following folder structure:
- file: README.md -> Contains information on how to run the scripts contained in this repository
- file: XX.ipynb -> Python Jupyter Notebook used to prepare data (i.e. 'combine_data.ipynb') or to create the plot(s) of the figure indicated in the name of the file (e.g. 'Fig 1BCEF (attP1 traces).ipynb`)
- file: XX.py -> Python modules loaded by the Python Jupyter Notebook. These files contain commonly used functions.
- folder: 'Figure X' (e.g. Figure 1) -> Indicates the Figure in the manuscript the scripts in this folder are referring to.
- file:
Fig X.ipnyb(i.e.Fig 1BCEF (attP1 traces).ipynb): Python Jupyter Notebook used to create the plot(s) in the figure(s) indicated in the name of the file. - file
FigS4A - klapoetke 2014 addendum Fig 1b digizelt.dig: File to be used with the software DigiZeit (https://www.digitizeit.xyz/) to extract datapoints from Klapoetke et al., 2014 as indicated in the Methods of the paper. - folder:
FigX_data-> Preprocessed data created bycombine_data.ipynbused by the Python Jupyter notebook in the parent folder- file:
FigX.txt-> Metadata for the correspondingFigX.npy - file
FigX.npy-> data refered to by Python Jupyter notebook in parent folder.
- file:
- file:
Calcium imaging in the larva
The CNS of larvae at the 3rd instar developmental stage was dissected in saline (135 mM NaCl, 5 mM KCl, 4 mM MgCl2, 1.8 mM Trehalose, 12.6mM Sucrose, 2mM CaCl2) and placed dorsal side down on a lysine-coated coverslip. We used a Hyperscope two-photon scanning microscope (Scientifica, UK) with a MaiTai laser (Spectra Physics, CA, USA). For imaging, we used a two-photon excitation wavelength of 920 nm. When CsChrimson was stimulated with 590nm (e.g., Figure 1b), an amber LED (LCS-0590-03-22, Mightex, Canada) with peak wavelength at 590 nm and a 605/55 bandpass filter (Chroma, VT, US) was used. In Figure 3, CsChrimson was activated with a red LED (LCS-0656-03-22, Mightex, Canada) with peak wavelength at 656 nm and a 650/10 bandpass filter (Chroma, VT, US). To feed the CsChrimson excitation light into the light path, we used a 560LP dichroic (T560LPXRXT-UF1, Chroma, VT, USA). The power of the LED from the objective was measured with a PM100D Power meter with an S170C Power sensor (Thorlabs, NJ, USA). To estimate the power at the larval brain, we divided the measured total LED power by the area of the field of view of the objective (XLPLN25XWMP2, Olympus, Japan).
For each trial, the neuron was observed for 20 seconds. Each trial was repeated 5 times. Data was analyzed using custom python scripts. Raw data was first filtered using a Savitzky-Golay filter (1-second window length, 2nd order polynomial). The signal was calculated as described previously (Jia et al., 2011). Briefly, an ROI was chosen to contain a segment of the axonal branch. A second ROI away from the neuron was defined as the background. The background was subtracted from the ROI to correct for stimulus light bleed-through. Next, for each frame Fi, signals were computed as the relative change in fluorescence intensity from the baseline: ΔF/F0 = (Fi-F0)/F0. Baseline fluorescence F0 was defined as the mean pixel intensity of the 3-second time window preceding the optogenetic stimulus.
Preliminary experiments showed that many but not all preparations show calcium transients. For the larva (Figures 1, 3, and 6), the experiments were performed using the algorithm described in Figure S1: each dissected brain was stimulated using the same 2-second 73 uW/mm2 step stimulus. If an obvious response was detected the whole dataset was acquired. If no obvious response was detected, the brain was discarded, and another brain was dissected and tested. For the 6th preparation in a row, imaging was performed irrespective of the presence of a response to initial 2-second step stimulus at one of the four chosen ROIs at random. This allowed us to efficiently scan through 30 samples to minimize the chances of missing false positives in unexpected conditions. Table 5 shows the number of brains dissected and recorded.
Immunostaining
Female flies (10 days post-eclosion) were dissected for analysis. Samples were dissected in 4 °C 1X PBS (10173433, Fisher Scientific, UK) after a quick passage through EtOH (4146052, Carlo Elba), and were then transferred to formaldehyde solution (4% paraformaldehyde, P6148, Sigma-Aldrich in 1X PBS + 10% Triton-X, X100, Sigma-Aldrich) and incubated for 20–30 min at room temperature. Samples were then washed three times in PBST (0.5% Triton-X in PBS) and then blocked with 10% normal goat serum (16210-064, Invitrogen) in PBST for 15–60 min at room temperature. Samples were then incubated in primary antibody solutions (Rabbit anti-dsRed, 632496, Takara at 1:500 and Mouse anti-NC82, Developmental Studies Hybridoma Bank at 1:10 in 5% normal goat serum in PBST). Primary antibody incubations were performed for 3 days at 4 °C with rocking. They were then washed in PBST 3 times for 15 min at room temperature. The secondary antibodies were applied (Anti-mouse A594, A11032, Invitrogen at 1:500 and Anti-rabbit A488, A11008, Invitrogen at 1:500 in 5% normal goat serum in PBST) and brains were then incubated for 3 days at 4 °C with rocking. They were again washed in PBST 3 times for 15 min at room temperature. Samples were mounted in Vectashield Mounting Medium (H-1000, Vector Laboratories). Images were captured on an inverted Zeiss LSM 980 (Carl Zeiss Co., Oberkochen, Germany) using a Plan-ApoChromat 20X/0.8 air lens objective (Carl Zeiss Co., Oberkochen, Germany) and A GaAsP detector. The same laser intensity and detector gain were used to scan both the Gal4+ and Gal4- conditions. z-Correction was performed to compensate for the signal loss due to section depth.
