Label free quantification of time evolving morphologies using time-lapse video microscopy enables identity control of cell lines and discovery of chemically induced differential activity in iso-genic cell line pairs
2015 (English)In: Chemometrics and Intelligent Laboratory Systems, ISSN 0169-7439, E-ISSN 1873-3239, Vol. 141, 24-32 p.Article in journal (Refereed) Published
Label free time-lapse video microscopy based monitoring of time evolving cell population morphology has potential to offer a simple and cost effective method for identity control of cell lines. Such morphology monitoring also has potential to offer discovery of chemically induced differential changes between pairs of cell lines of interest, for example where one in a pair of cell lines is normal/sensitive and the other malignant/resistant. A new simple algorithm, pixel histogram hierarchy comparison (PHHC), for comparison of time evolving morphologies (TEM) in phase contrast time-lapse microscopy movies was applied to a set of 10 different cell lines and three different iso-genic colon cancer cell line pairs, each pair being genetically identical except for a single mutation. PHHC quantifies differences in morphology by comparing pixel histogram intensities at six different resolutions. Unsupervised clustering and machine learning based classification methods were found to accurately identify cell lines, including their respective iso-genic variants, through time-evolving morphology. Using this experimental setting, drugs with differential activity in iso-genic cell line pairs were likewise identified. Thus, this is a cost effective and expedient alternative to conventional molecular profiling techniques and might be useful as part of the quality control in research incorporating cell line models, e.g. in any cell/tumor biology or toxicology project involving drug/agent differential activity in pairs of cell line models.
Place, publisher, year, edition, pages
2015. Vol. 141, 24-32 p.
Time evolving morphology, quality control, iso-genic cell line, cancer pharmacology, time-lapse microsopcy, video microscopy
Computer Science Cancer and Oncology
IdentifiersURN: urn:nbn:se:uu:diva-234563DOI: 10.1103/PhysRevC.91.024602ISI: 000350096200003OAI: oai:DiVA.org:uu-234563DiVA: diva2:757067