The European network

for cell migration studies

Student: Saransh Vora, Roman Yakobenchuk

Supervisors: Bernhard MoserJulian Mattes,

11 - Speckle analysis of actin and keratin filament dynamics

The pertinent difficulties within automated segmentation of filamentous networks can be avoided by fluorescent labeling of a small random filament fractions for speckle microscopy. We will apply speckle microscopy to study the dynamics of actin and keratin networks. We will work both on the imaging side and on the image processing side and on the interplay of the two to achieve reliable measurements, for example in the form of vector fields describing the dynamics of these networks. We expect that the standard tracking algorithms of the Imaris software can be improved for these applications. We will therefore investigate new and alternative tracking algorithms to deal with the large numbers of particles to be tracked.

Last update: 28.05.2018

incem@rwth-aachen.de

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.