The European network

for cell migration studies

1  -  Advanced cell migration assays

Student: Lea Tomášová

Supervisors: Zeno Guttenberg, Valentin Kahl,  Rudiolf MerkelBernd Hoffmann

With existing migration assays the acquisition of cell migration data can normally only be observed in relation to one physical parameter such as a chemical gradient or surface topology. Relevant information for the understanding of cell behaviour, however, requires observations to be performed in the presence of several precisely adjusted parameters. In the project we aim to establish (i) new cell migration assays in which movement of cells can be correlated to several fixed parameters at the same time, (ii) a microscope slide that allows investigating cell migration in a chemical gradient, and (iii) track and analyse cell shapes to obtain additional information on overall cell motility as well as to calculate the forces of the cells applied to a matrix of defined stiffness.

Last update: 28.05.2018

Advanced cell migration assays (P1)

Chemotaxis and 2D/3D Migration (P2)

Analysis of keratin dynamics during migration (P3)

Impact of keratin network regulation on migrating cells (P4)

Correlation analyses of migration structure components and front-rear interplay (P5)

Life cycle analysis of actin, focal adhesions and force measurements (P6)

Monitoring of cancer cell migration in living animals  (P7)

Principles of the filopodia structure, dynamics and mechanics (P8)

Mechanisms of downstream signalling from the Rho GTPase network to

cell morphogenesis and cell motility (P9)

Real-time tracking of keratinocyte migration and analysis of cell membrane shape changes (P10)

Image analysis of integrated cytoskeletal network dynamics (P11)

Coupling bulk-surface models for cell migration (P12)

Shaping membranes and actin fibres by forces (P13)

Integrating shape change models and imaging – inverse problem solving and model validation (P14)

Understanding spatio-temporal dynamics of the cytosol network during cell migration  (P15)

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No 642866.