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Publié par | johannes_gutenberg-universitat_mainz |
Publié le | 01 janvier 2010 |
Nombre de lectures | 36 |
Poids de l'ouvrage | 25 Mo |
Extrait
Dynamics of epithelial monolayers assessed
by acoustic and impedimetric whole cell
biosensors
Quartz crystal microbalance (QCM) and electrical cell‐
substrate impedance sensing (ECIS) as novel tools to
address cell motility and nanocytotoxicity
Dissertation
zur Erlangung des Grades
"Doktor der Naturwissenschaften"
am Fachbereich
Chemie, Pharmazie und Geowissenschaften
der Johannes Gutenberg‐Universität Mainz
vorgelegt von
Marco Tarantola
geboren in Wiesbaden
Mainz 2010
| II
Meinen Eltern und meiner Familie
Dosis sola venenum facit
Paracelsus (1493‐1541)
| III
Abstract
The central aim of this work was focused on scrutinizing migration dynamics of epithelial
monolayers by two novel in vitro biosensors: electrical cell‐substrate impedance sensing
(ECIS) and quartz crystal microbalance (QCM). Both proved to be suitable to address cell
motility and nanocytotoxicity.
The first focus was put on fingerprinting cancer cells by their cell body dynamics
and the generated electrical or acoustic fluctuations in ECIS and QCM (termed F‐QCM)
readouts. Here, the classical cancer cell motility in‐vitro assays for migration and
invasion relying on Boyden chambers are compared to real‐time biosensors that analyze
the dynamic properties of adherent cells with a time resolution in the order of seconds.
Signatures of long‐memory correlations in motility as well as fractal, self‐similarity and
collective motion were analyzed by variance determination, power density estimation
and detrended fluctuation analysis. Long‐memory stochastic processes were found to
govern the response of the adherent cells displayed in both F‐QCM and ECIS
micromotion measurements, with variance analysis of QCM frequency fluctuations
providing the strongest correlation to classical Boyden invasion assays. Furthermore, we
studied the impact of small molecule inhibitors on the dynamics of the cytoskeleton:
effects of cytochalasin D, phalloidin and blebbistatin as well as taxol, nocodazol and
colchicin were quantified by detecting changes in the noise pattern. We were able to
identify actin‐polymerization as well as microtubule depolymerization to be the main
contributors of viscoelastic or impedimetric fluctuations.
As a second project, a comprehensive interfacial analysis enabled us to record
both adhesion and desorption processes and cell‐cell contacts degradation upon
nanoparticles application. We followed cell‐substrate dynamics via micromotility and
viscoelastic fluctuations as a measure for nanotoxicity, related to shape,
functionalization, intracellular stability and charge of particles.
In summary, the novel real time biosensor approach based on fluctuation
analysis of acoustic and impedimetric readouts of F‐QCM and ECIS displays a high
cellular specifity and sensitivity for the dynamics of the cellular cytoskeleton and may
serve also as a very sensitive measure for cellular viability.
| IV
Table of contents
1 Introduction: molecular biology of cell motility ......................................................... 1
1.1 Cytoskeleton: cellular components determenining motility ..................................... 2
1.1.1 Actin .................................................................................................................... 2
1.1.2 Microtubules ....................................................................................................... 4
1.1.3 Intermediate filaments ....................................................................................... 6
1.1.4 Motor proteins and intracellular motility ........................................................... 7
1.2. Cell adhesion and ‐motility 9
1.2.1 Extracellular matrix ............................................................................................. 9
1.2.2 Cell‐substrate adhesion .................................................................................... 11
1.2.3 Cell‐cell adhesion .............................................................................................. 14
1.2.4 Whole cell motility and migration regulation ................................................... 16
1.3 References and notes 22
2 Thesis objectives and general concepts .................................................................... 25
2.1 Developmental objectives ....................................................................................... 25
2.2 General application concepts .................................................................................. 26
3 Dynamics of human cancer cell lines monitored by electrical and acoustic noise
analysis ....................................................................................................................... 29
3.1 Introduction ............................................................................................................. 30
3.2 Experimental section ............................................................................................... 33
3.2.1 Cell culture conditions ...................................................................................... 33
| V
3.2.2 Boyden chamber migration and invasion assays .............................................. 33
3.2.3 QCM resonator preparation and phase contrast microscopy .......................... 34
3.2.4 QCM setup and data acquisition ...................................................................... 36
3.2.5 ECIS setup and data acquisition ........................................................................ 36
3.2.6 D‐QCM and ECIS noise analysis......................................................................... 37