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    Automated Random Motility Assay

Highlights

•    High-contrast label-free imaging for robust single cell segmentation
•    Automated tracking of individual cells in response to migratory stimulators & inhibitors
•    Extract additional migration metrics such as cell speed and confinement ratio
•    Build comprehensive cell migration profiles through Livecyte’s Motility Application Dashboard

Introduction

Cell migration is an essential and highly regulated process involved in embryonic development, tissue homeostasis and regeneration. Cell migration also plays a key role in cancer, where it drives tumour metastasis [1-5].

 
2D models of cell migration are well established and are valuable tools for understanding the complex mechanisms that regulate normal and abnormal cell migration [6]. The wound closure and random cell migration assays are the most commonly studied with the former being highly relevant for the analysis of wound healing and collective migration of cell types that form tight junctions (e.g. melanocytes), whilst the latter is more applicable for cell types that migrate as individual cells such as fibroblast-like cancer cell lines. Thus, researchers should consider which assay is the most applicable for their cell model in order to yield relevant data. 


The random cell migration assay requires the analysis of single cells and provides a greater depth of information in form of cell speed, velocity, displacement, amongst others, however, there are challenges associated with obtaining this data reliably and efficiently. 


Traditional label-free imaging lacks inherent contrast to perform automated cell segmentation and tracking and whilst the introduction of fluorescent labels to increase contrast has potential to alter normal cell function and influence cell migration [6-10]. Automated cell tracking algorithms have been developed and reported elsewhere [11, 12], however, a complete and efficient workflow encompassing image analysis, cell tracking and data visualisation for microwell plate assays has been lacking. 


In this study we sought to directly quantify the random migration of individual MDA-MB-231 cells over a 24-hour period using the Phasefocus Livecyte. Automated measurement of single cell migration was performed using Livecyte’s label-free, quantitative phase imaging (QPI) mode and integrated Cell Motility Dashboard.

Method

Cell Culture

MDA-MB-231 cells were maintained in DMEM + 10% FBS complete medium at 37°C with 5% CO2/95% humidity prior to experiments. Cells were harvested using standard techniques, and cell count and viability determined by trypan blue exclusion (ViCell; Beckman Coulter) prior to seeding into a 96-well plate at 1500 cells/well and cultured overnight. Media was replaced with serum free DMEM (SFM) and cells were serum starved for 24 hours. Prior to imaging, media was replaced with either SFM only, or SFM with EGF (1 – 30ng/ml), 10% FBS or Cytochalasin D (300ng/ml).  

Resources

•    MDA-MB-231 cell line (ATCC HTB-26) 
•    Epidermal Growth Factor (EGF; Gibco PHG0313) 
•    Cytochalasin D (Thermo Fisher PHZ1063) 
•    DMEM (Gibco) 
•    Foetal Bovine Serum (FBS; Gibco) 
•    96 well culture plate (Corning 3603) 
•    Livecyte Kinetic Cytometer (Phasefocus) 
•    Livecyte Acquire & Analyse software (Phasefocus)

Time-Lapse Imaging

Label-free QPI images were generated via Livecyte’s automated Acquire software and Ptychographic reconstruction algorithm. Cells were imaged with a PLN 10X/0.25NA objective and 1mm x 1mm field of view (FOV) per well for 24 hours at 12-minute intervals. During imaging, cells were maintained in an environmental chamber at 37°C with 5% CO2 and 95% humidity. 

Analysis

The effects of serum starvation, 10% FBS (complete medium), EGF and Cytochalasin D on MDA-MB-231 cell migration were examined over 24 hours using the Livecyte Kinetic Cytometer.  Image processing, automated cell segmentation and tracking were performed fully automatically with Livecyte Analyse software. Single-cell metrics were extracted using the Cell Motility Dashboard in Analyse.

Results

Individual Cell Segmentation & Tracking

The high-contrast label-free images generated by Livecyte allows for robust individual cell segmentation (Figure 1; Top). Livecyte’s analysis algorithms utilise multiple values from segmentation data to provide reliable individual cell tracking data as shown in Figure 1 (Bottom). 

Cell Motility Dashboard

Livecyte automatically collates image, single cell segmentation and cell tracking data into an interactive Cell Motility Dashboard (Figure 2). Data across multiple wells are ordered by treatment group and tangible cell migration metrics are generated in the form of average cell speed, instantaneous velocity and displacement, amongst others. Multi-panel videos are also available to preview cell migration under each treatment condition. 

Average Cell Speed

MDA-MB-231 cells exhibited an EGF dose-response increase in mean migratory speed and instantaneous velocity (Figure 3 & 4). As expected, the highest mean migratory speed and velocities were observed in complete media (10% serum) whilst cells exposed to the microfilament disrupter, Cytochalasin D, exhibited the lowest mean migratory speed and velocities (Figure 3 & 4).

Random Migration Profiles

Livecyte also calculates Cell Displacement and Cell Confinement Ratio for random migration studies. These metrics represent the distance a cell migrates relative to their point of origin and also considers the degree in which a cell meanders from its starting and end point. 
While cells in complete media had the highest mean migratory speed, their confinement ratio was lower than that of 10 & 30ng/ml EGF-treated cells. These outcomes were also observed in the cell displacement plots suggesting that 10 & 30ng/ml EGF-treated cells, on average, migrated further from their point of origin than complete medium-treated cells (Figure 5 & 6) and highlights differing migration profiles between these groups. As anticipated, Cytochalasin D-treated cells exhibited the lowest confinement ratio and displacement, indicating they migrated very little from their point of origin (Figure 5 & 6).
 

 

Figures

Figure 1

Figure 1: Representative Quantitative Phase Images of MDA-MB-231 cells with segmentation masks (Top) and individual cell tracks over 24 hours (Bottom). Scale bar = 200µm.

Motility Dashboard

Figure 2: Representative image of the Cell Motility Dashboard. Image analysis, cell segmentation and tracking data across multiple wells are automatically curated into tangible cell migration metrics.

Figure 3: Average migratory speed of MDA-MB-231 cells over 24 hours under each treatment condition.

Figure 4. Average instantaneous velocity of MDA-MB-231 cells over 24 hours under each treatment condition. Error bars represent the inter-quartile range.

Figure 5: Plot of mean dry mass per cell for unlabelled (top) and SiR-DNA labelled (bottom) cells. The average dry mass of individual SiR-DNA-labelled cells increased over time, relative to unlabelled cells.

Figure 6: Average confinement ratio of MDA-MB-231 cells over 24 hours under each treatment condition.

Download the Application Note PDF

Summary

The extraction of individual cell migration data without the use of perturbing fluorescent labels can be challenging with traditional label-free imaging approaches due to a lack of inherent cell contrast and inefficient analysis workflows from image acquisition through to data visualisation.

Livecyte combines high-contrast label-free imaging with single cell tracking algorithms to automatically generate and visualise migration metrics through the Cell Motility Dashboard. 

Using the random cell migration assay, we report an EGF dose-response increase in MDA-MB-231 cell speed and velocity compared to SFM and Cytochalsin D groups whilst the highest cell speed and velocity was observed in the complete medium group. We also observed that 10ng/ml and 30ng/ml EGF treated cells, on average, migrated further from their point of origin than the complete medium group despite migrating at a slower speed, suggesting differing migration patterns.

This study demonstrates how Livecyte’s QPI imaging mode and Cell Motility Dashboard can be used to automatically extract and visualise single cell migration data whilst avoiding the limitations of fluorescence-based tracking and data processing bottlenecks created by manual analysis. Livecyte provides an intuitive workflow that enables users to simplify random cell migration assays and reliably examine the pathways involved in regulating cell migration.


References

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