Towards High-Throughput Phenotypic and Systemic Profiling of in vitro Growing Cell Populations using Label-Free Microscopy and Spectroscopy: Applications in Cancer Pharmacology
2014 (English)Doctoral thesis, comprehensive summary (Other academic)
Modern techniques like automated microscopy and spectroscopy now make it possible to study quantitatively, across multiple phenotypic and molecular parameters, how cell populations are affected by different treatments and/or environmental disturbances. As the technology development at the instrument level often is ahead of the data analytical tools and the scientific questions, there is a large and growing need for computational algorithms enabling desired data analysis. These algorithms must have capacity to extract and process quantitative dynamic information about how the cell population is affected by different stimuli with the final goal to transform this information into development of new powerful therapeutic strategies. In particular, there is a great need for automated systems that can facilitate the analysis of massive data streams for label-free methods such as phase contrast microscopy (PCM) imaging and spectroscopy (NMR). Therefore, in this thesis, algorithms for quantitative high-throughput phenotypic and systemic profiling of in vitro growing cell populations via label-free microscopy and spectroscopy are developed and evaluated. First a two-dimensional filter approach for high-throughput screening for drugs inducing autophagy and apoptosis from phase contrast time-lapse microscopy images is studied. Then new methods and applications are presented for label-free extraction and comparison of time-evolving morphological features in phase-contrast time-lapse microscopy images recorded from in vitro growing cell populations. Finally, the use of dynamic morphology and NMR/MS spectra for implementation of a reference database of drug induced changes, analogous to the outstanding mRNA gene expression based Connectivity Map database, is explored. In conclusion, relatively simple computational methods are useful for extraction of very valuable biological and pharmacological information from time-lapse microscopy images and NMR spectroscopy data offering great potential for biomedical applications in general and cancer pharmacology in particular.
Place, publisher, year, edition, pages
Uppsala: Acta Universitatis Upsaliensis, 2014. , 50 p.
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Medicine, ISSN 1651-6206 ; 1045
label free vesicle detector, high-throughput, phase contrast microscopy, Library of Pharmacologically Active Compounds, High Content Screening, fluorometric microculture cytotoxicity assay, nuclear magnetic resonance, mass spectrometry
Medical and Health Sciences
IdentifiersURN: urn:nbn:se:uu:diva-234565ISBN: 978-91-554-9082-9OAI: oai:DiVA.org:uu-234565DiVA: diva2:757069
2014-11-25, Robergsalen, entrance 40, 4th floor, Akademiska Sjukhuset, Uppsala, 09:30 (English)
Gustafsson, Mats, Prof
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