Keratinocytes to Study Cell Migration
Keratinocytes are the most abundant cell type found in the epidermis, the outermost layer of the skin. Their primary function is to form a protective barrier against environmental damage as well as playing a key role in wound healing where they, along with endothelial and stem cells can migrate to the site for re-epithelialization to close the wound.
The ability of cells to move and migrate is a fundamental process essential to life and is not only important for wound healing, but is also linked to other important physiological and pathological events such as the immune response, tissue differentiation, embryogenesis, and tumor invasion.
Recently, Yang and Colleagues published a paper utilizing Lifeline’s Normal Neonatal Human Epidermal Keratinocyte Cells, (nHEK’s) cultured in Dermalife K cell culture medium to test their fully-automated algorithm to track the migration of slow-moving cell populations.
New Research Using Lifeline Keratinocytes
The advent of high-throughput, high-resolution microscopy, and imaging techniques has enabled researchers to identify and track movement of many cell types in response to stimuli. However, many of the images are collected in the absence of a monitoring segmentation and tracking algorithm, which means that the images captured during monitoring need to be manually assessed by a human operator in order to track the cell of interest. Due to the sheer magnitude of the data involved, this is labor-intensive and time-consuming making the development of a fully-automated computer algorithm for cell tracking highly desirable. This process is exacerbated further when studying slow-moving cell types.
Yang and Colleagues sought to use a novel approach to develop their fully-automated cell tracking system wherein a crucial parameter for their algorithm was setting a specific time interval for image acquisition. The researchers cautioned against capturing constant and frequent images for accurate cell tracking because every time an image is acquired, the cells are exposed to light for clear visualization, which can damage or even kill the cells. Therefore, optimizing this time interval, balanced against the quality of data to ensure high accuracy in tracking cell trajectories by the computer software, is essential.
Here, the researchers used two cell types known for their slow motility, HT1080, a fibrosarcoma cell line, and Normal Neonatal Keratinocytes from Lifeline® in multiple experiments to generate four new datasets with directed (i.e. chemotactically induced) and random cell migration in order to test their tracking algorithm. Phase-contrast microscopy was chosen to record the experimental data to reduce the impact on the cells since the light intensity is much lower than other microscopy methods.
The researchers demonstrated their algorithm was capable of determining and characterizing the migration directions in chemotaxis adequately for quantitative statistical analysis for all 4 datasets. The interplay between the time step interval parameter and the accuracy of their cell tracking algorithm could be established by direct comparisons to the manual cell tracking performed on the same datasets.
Ultimately, the results of their experiments highlight the need to optimize the time step interval for image acquisition that yields the best quality dataset with high accuracy in cell tracking for the cell type of interest. While Yang and Colleagues realize there are improvements to be made in their software, but they are nevertheless hopeful that this work enables further interdisciplinary research to improve all relevant areas of cell tracking.
Lifeline Keratinocytes for Your Research Needs
Lifeline keratinocytes are optimized for growth in DermaLife K cell culture medium and are available from multiple primary sites:
- Oral Keratinocytes from Gingiva
- Neonatal Epidermal Keratinocytes
- Adult Epidermal Keratinocytes
- Epidermal Keratinocytes, 10-Donor Pool
Are you using Lifeline cells or cell culture medium in your research? If so, we’d love to hear from you – your research could be featured in a future blog.