Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Summary

Time-lapse microscopy allows the visualization of developmental processes. Growth or drift of samples during image acquisition reduces the ability to accurately follow and measure cell movements during development. We describe the use of open source image processing software to correct for three dimensional sample drift over time.

Abstract

The generation of four-dimensional (4D) confocal datasets; consisting of 3D image sequences over time; provides an excellent methodology to capture cellular behaviors involved in developmental processes.  The ability to track and follow cell movements is limited by sample movements that occur due to drift of the sample or, in some cases, growth during image acquisition. Tracking cells in datasets affected by drift and/or growth will incorporate these movements into any analysis of cell position. This may result in the apparent movement of static structures within the sample. Therefore prior to cell tracking, any sample drift should be corrected. Using the open source Fiji distribution ¹  of ImageJ ^2,3 and the incorporated LOCI tools ⁴, we developed the Correct 3D drift plug-in to remove erroneous sample movement in confocal datasets. This protocol effectively compensates for sample translation or alterations in focal position by utilizing phase correlation to register each time-point of a four-dimensional confocal datasets while maintaining the ability to visualize and measure cell movements over extended time-lapse experiments.

Introduction

Confocal imaging is widely used in cell and developmental biology to follow cell movements and changes in morphology. Capturing a series of optical sections at different focal planes allows the generation of a three-dimensional (3D) model of a sample, which can then be extended into four-dimensions (4D) by creating a time-lapse series of 3D datasets. The generation of 4D datasets allows detailed measurement of cell movements and behaviors. In long-term time-lapse experiments it is common to observe sample movement. This can be caused by slight inaccuracies in the hardware controlling stage and focal positions. While in others cases, drift is a result of movements induced by sample growth or flexibility within the sample mounting media. Methods exist to compensate or limit these movements including improvements to hardware focusing systems and increased rigidity of the mounting medium. However, these approaches cannot be applied in many cases due to the imaging set up required to provide suitable conditions for the samples maintenance and growth. Open source software solutions do exist for the correction of movement in 2D over time, through the use of the StackReg and TurboReg (http://bigwww.epfl.ch/thevenaz/stackreg/) ⁵ plugins in ImageJ or Fiji, but these cannot be applied to 4D datasets.

To correct for the sample drift we have developed a plug-in (Correct 3D drift) to utilize the open-source imaging-processing platform, Fiji ¹. Our plug-in is able to perform phase correlation registration to correct movement that occurs as a result of sample drift in three-dimensional time-lapse experiments. Phase correlation ⁶ is a computational efficient method to determine translation between images. The plug-in described here utilizes the phase-correlation library developed by Preibisch et al. ⁷. In multi-channel experiments, the plug-in utilizes one channel to determine the required correction. This correction is then applied to any additional channels resulting in registration of the 4D dataset.  

In the zebrafish model system it is possible to carry out time-lapse imaging over a period of many hours, or even several days ⁸. A common method for mounting the zebrafish is to embed the anaesthetized live embryo in low melting point agarose (0.8-1.5%), restricting its movement ^9-11. Whilst movement is restricted growth of the sample still occurs, resulting in the cells within the field of view shifting position. In order to follow movement of the cells within the embryo it is necessary to first correct for movement of the entire sample. This protocol was developed with zebrafish specimens, and has been utilized to image somite development¹² but can be applied to any 4D confocal dataset.

Protocol

1. 4D Time-lapse Imaging Experiments

The settings used for image acquisition will differ depending on the equipment used. The ability of confocal microscopy to optically section a sample depends on a number of factors: the wavelength of excitation, pinhole size, numerical aperture of the objective, the refractive index of the sample and the medium in which the sample is embedded. The size of the confocal pinhole selected will determine the thickness of the optical section collected. A smaller pinhole will produce a thinner optical section increasing the z-axis resolution but reducing the amount of light captured. A larger pinhole will increase the thickness of the optical section, reducing z-axis resolution but increasing the amount of light captured.

Additional factors to consider during collection of 4D data prior to correction include:

1. Optimize scanning speed to remove, or limit, drift during the capture of a single time-point. Therefore the time taken for the image collection should be a small fraction of the interval between time-points.
2. Perfectly repeating structures, or grids, are not suitable as structures for registration as it is not possible to determine the required correction. Randomly distributed beads or uneven structures will allow unambiguous registration.
3. If drift is expected, increase the scanning area and upper and lower focus limits in order to ensure the area of interest remains within the image stack.
4. In addition to ensuring there is appropriate spatial resolution to resolve the structures of interest, set the sampling rate to provide temporal resolution for the dynamic events being studied.
   Note: The time between image time-points should therefore be at least half the time-interval between regular repeating events and decrease for irregular events.

2. Opening the Confocal Dataset

The open source package Fiji is a distribution of the ImageJ program, which contains pre-installed plug-ins to perform numerous processes on data collected from microscopy experiments. The software provides easier plug-in update architecture and includes a copy of the Correct 3D drift plug-in used for this protocol. The software supports the import of a vast array of proprietary microscopy image formats through the use of the Open Microscopy Environment’s Bio-Formats import plug-in.

1. Install the Fiji program (http://fiji.sc/Downloads).
2. Load the acquired dataset using the LOCI Bio-Formats Importer plugin.
3. If the dataset is larger than the memory allocated to the program, select the "Use virtual stack option" within the Memory management section.

3. Correcting Drift of a 3D Object in Post Processing

During the course of an extended time-lapse experiment a sample may move even when embedded. To correct any movement and to allow the migration events imaged to be analyzed, post processing of images can be performed. All image post processing must be clearly described in the methodology of any analysis derived from this work.

1. Once the dataset has loaded, run the Correct 3D drift plugin.
2. If there are multiple image channels, select the channel to be used to register the images. This should ideally represent a static structure within the sample rather than any migratory or mobile elements. However, if this is not possible the channel with the least movement should be chosen.
3. If the available RAM on the system used for this analysis is less than twice the size of the original dataset, select the use virtual stack option. This will store the registered hyperstack as an image sequence, rather than saving the file to RAM.
   1. Select a folder for the plug-in to output individual corrected images files. A separate image file will be created for each channel at each z position.
4. The plugin will then conduct a pair-wise phase correlation analysis between each time-point to determine the required correction which is then applied to the dataset.

Results

In the developing zebrafish, fast muscle cells fuse into multinucleated fibers from 19 hours post-fertilization (20- somite stage) ¹³. In order to visualize the movement of nuclei and fusion of muscle cells we carried out 4D confocal time-lapse imaging using a transgenic strain that expresses green fluorescent protein (GFP) under the control of the skeletal α-actin promoter to label all of the muscle cells ¹⁴ and injected RNA encoding the red fluorescent protein mCherry tagged with a nuclear localiz...

Discussion

Our ability to use post-processing software to correct sample drift of datasets derived from extended time-lapse microscopy experiments is restricted by a number of factors. The ability to discern drift versus migratory movement of a sample is dependent on the cellular markers used. Cellular markers that are either widely expressed within a sample or are not involved in migratory events during image acquisition provide the best source for drift correction. The plugin uses a single channel to register the movement between...

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Ethyl 3-aminobenzoate methanesulfonate (Tricaine)	Sigma-Aldrich	A5040
Low gelling temperature agarose	Sigma-Aldrich	A9414-25G
Dumont #4 Forceps	Electron Microscopy Sciences	0208-4-PO
Disposable 3 ml graduated	Samco	212
Polyethylene transfer pipette
9cm bacterial grade Petri dishes	Greiner Bio One	632180
Fluorinated ethylene propylene (FEP) tubing	Bola	S1815-04
Zeiss LSM-710 Confocal microscope	Zeiss
W Plan-Apochromat 20x/1.0 DIC Objective	Zeiss	421452-9600-000