University Library
  • Login
A gateway to Melbourne's research publications
Minerva Access is the University's Institutional Repository. It aims to collect, preserve, and showcase the intellectual output of staff and students of the University of Melbourne for a global audience.
View Item 
  • Minerva Access
  • Science
  • School of Mathematics and Statistics
  • School of Mathematics and Statistics - Research Publications
  • View Item
  • Minerva Access
  • Science
  • School of Mathematics and Statistics
  • School of Mathematics and Statistics - Research Publications
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.

    How much information can be obtained from tracking the position of the leading edge in a scratch assay?

    Thumbnail
    Download
    Published version (1.263Mb)

    Citations
    Scopus
    Web of Science
    Altmetric
    37
    35
    Author
    Johnston, ST; Simpson, MJ; McElwain, DLS
    Date
    2014-08-06
    Source Title
    Journal of the Royal Society Interface
    Publisher
    The Royal Society
    University of Melbourne Author/s
    Johnston, Stuart
    Affiliation
    School of Mathematics and Statistics
    Metadata
    Show full item record
    Document Type
    Journal Article
    Citations
    Johnston, S. T., Simpson, M. J. & McElwain, D. L. S. (2014). How much information can be obtained from tracking the position of the leading edge in a scratch assay?. J R Soc Interface, 11 (97), pp.20140325-. https://doi.org/10.1098/rsif.2014.0325.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/256077
    DOI
    10.1098/rsif.2014.0325
    Open Access at PMC
    http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4208362
    Abstract
    Moving cell fronts are an essential feature of wound healing, development and disease. The rate at which a cell front moves is driven, in part, by the cell motility, quantified in terms of the cell diffusivity D, and the cell proliferation rate λ. Scratch assays are a commonly reported procedure used to investigate the motion of cell fronts where an initial cell monolayer is scratched, and the motion of the front is monitored over a short period of time, often less than 24 h. The simplest way of quantifying a scratch assay is to monitor the progression of the leading edge. Use of leading edge data is very convenient because, unlike other methods, it is non-destructive and does not require labelling, tracking or counting individual cells among the population. In this work, we study short-time leading edge data in a scratch assay using a discrete mathematical model and automated image analysis with the aim of investigating whether such data allow us to reliably identify D and λ. Using a naive calibration approach where we simply scan the relevant region of the (D, λ) parameter space, we show that there are many choices of D and λ for which our model produces indistinguishable short-time leading edge data. Therefore, without due care, it is impossible to estimate D and λ from this kind of data. To address this, we present a modified approach accounting for the fact that cell motility occurs over a much shorter time scale than proliferation. Using this information, we divide the duration of the experiment into two periods, and we estimate D using data from the first period, whereas we estimate λ using data from the second period. We confirm the accuracy of our approach using in silico data and a new set of in vitro data, which shows that our method recovers estimates of D and λ that are consistent with previously reported values except that that our approach is fast, inexpensive, non-destructive and avoids the need for cell labelling and cell counting.

    Export Reference in RIS Format     

    Endnote

    • Click on "Export Reference in RIS Format" and choose "open with... Endnote".

    Refworks

    • Click on "Export Reference in RIS Format". Login to Refworks, go to References => Import References


    Collections
    • Minerva Elements Records [45689]
    • School of Mathematics and Statistics - Research Publications [680]
    Minerva AccessDepositing Your Work (for University of Melbourne Staff and Students)NewsFAQs

    BrowseCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects
    My AccountLoginRegister
    StatisticsMost Popular ItemsStatistics by CountryMost Popular Authors