DOI: 10.5281/zenodo.3257654
title: Microscopy image sequences and annotated kymographs of laser ablation experiments in Drosophila embryos

description: <strong>Content</strong>

This dataset contains 15 2D time-lapse fluorescence microscopy image sequences recorded with confocal laser-scanning microscopy. Each movie shows an epithelial tissue laser nanoablation experiment conducted in a Drosophila embryo.

For each sequence, the dataset contains kymographs (one-dimensional space-time plots) of a supracellular cable that is cut during the ablation, and manually created tracks of visible features, such as the resulting cut ends. These tracks allow to estimate, for instance, recoil velocities of the cut tissue and may be used to evaluate automated methods for estimating said velocities.

This dataset is used in the manuscript to evaluate various variational approaches for joint motion estimation and source identification:

L. F. Lang, N. Dutta, E. Scarpa, B. Sanson, C.-B. Schönlieb, and J. Étienne. Joint Motion Estimation and Source Identification using Convective Regularisation with an Application to the Analysis of Laser Nanoablations. 2019.

<strong>Description</strong>

The movies depict a square region of approximately \(42.2 \times 42.2 \, \mathrm{\mu m}^{2}\) at a spatial resolution of \(250 \times 250\) pixels. A typical sequence contains between 60 and 100 frames. They temporal interval between recorded frames was \(727.67 \, \mathrm{ms}\).

Each sequence features cell membranes labelled with E-cadherin:GFP and shows a single plasma-induced laser nanoablation. The destructed tissue region is roughly of \(2 \, \mathrm{\mu m}\) length. This ablation is expected to have a width of the order of the size of one pixel. During the ablation the acquisition is paused, resulting in a black image.

For the used microscopy techniques and for the preparation of flies, as well as for the details of the laser ablation method, see the paper:

E. Scarpa, C. Finet, G. B. Blanchard, and B. Sanson. Actomyosin-driven tension at compartmental boundaries orients cell division independently of cell geometry In Vivo. Dev. Cell, 47(6):727–740.e6, December 2018. URL: https://doi.org/10.1016/j.devcel.2018.10.029

The kymographs and the manually created annotations (tracks) of features were created using Fiji (https://fiji.sc/).

<strong>Content</strong>

The dataset contains 15 sequences placed in the following folder structure:


	SqAX3_SqhGFP42_GAP43_TM6B
	
		190216E4PSB1
		190216E5PSB1
		190216E5PSB2
		190216E6PSB1
		190216E8PSB1
		E2PSB1
		E5PSB2
		E8PSB1
		PSB1E1
		PSB4
	
	
	SqhGFP40
	
		e1_PSB8
		e3_PSB9
		e3_PSB10
		e4_PSB11
		e4_PSB12
	
	


Each folder contains:


	The sequence itself in TIF format, e.g. "190216E4PSB1PMT - PMT [560-] _C1.ome.tif".
	A file "reslice.roi" that indicates the location/direction of the cut supracellular cable.
	3 different kymographs for each sequence obtained by taking avg/max/sum projections in Fiji orthogonal to the line specified in "reslice.roi", e.g.
	
		"AVG_Reslice of 190216E4PSB1PMT.tif",
		"MAX_Reslice of 190216E4PSB1PMT.tif",
		"SUM_Reslice of 190216E4PSB1PMT.tif".
	
	
	Text files that state the time/space coordinates of manually tracked features in the kymographs, e.g.
	
		"cutend_L.txt" (coordinates of the left cut end after the ablation),
		"cutend_R.txt" (coordiantes of the right cut end),
		"feat_X.txt" (coordinates of additional features, where X is a number and L or R).
	
	
	A ZIP file "manual_ROIs.zip" that contains all the coordinates of tracked features of the kymograph in ROI format (e.g. "cutend_L.roi").


<strong>Usage</strong>

The sequences, kymographs, and the tracks can be viewed using, for example, Fiji.

For the automated analysis, see the Python code that accompanies the manuscript above. It is available at https://dx.doi.org/XXX

<strong>License information</strong>

This dataset is released under Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. See CC BY-NA-SC 4.0.

<strong>How to cite this dataset</strong>

If you use this dataset in an academic publication, please consider citing the paper:

L. F. Lang, N. Dutta, E. Scarpa, B. Sanson, C.-B. Schönlieb, and J. Étienne. Joint Motion Estimation and Source Identification using Convective Regularisation with an Application to the Analysis of Laser Nanoablations. 2019.

To cite solely the dataset, please use:

L. F. Lang, N. Dutta, E. Scarpa, B. Sanson, C.-B. Schönlieb, and J. Étienne. (2019). Microscopy image sequences and annotated kymographs of laser ablation experiments in Drosophila embryos [Data set]. Zenodo. http://doi.org/10.5281/zenodo.3257654
description: LFL and CBS acknowledge support from the Leverhulme Trust project "Breaking the non-convexity barrier", the EPSRC grant EP/M00483X/1, the EPSRC Centre Nr.\ EP/N014588/1, the RISE projects ChiPS and NoMADS, the Cantab Capital Institute for the Mathematics of Information, and the Alan Turing Institute. ND and JE were supported by ANR-11-LABX-0030 "Tec21", by a CNRS Momentum grant, and by IRS "AnisoTiss" of Idex Univ. Grenoble Alpes. ND and JE are members of GDR 3570 MecaBio and GDR 3070 CellTiss of CNRS. Overall laboratory work was supported by Wellcome Trust Investigator Awards to BS (099234/Z/12/Z and 207553/Z/17/Z). ES was also supported by a University of Cambridge Herchel Smith Fund Postdoctoral Fellowship.
description: {"references": ["E. Scarpa, C. Finet, G. B. Blanchard, and B. Sanson. Actomyosin-driven tension at compartmental boundaries orients cell division independently of cell geometry In Vivo. Dev. Cell, 47(6):727\u2013740.e6, December 2018."]}