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Sixt, M.

Publications and source records attributed to Sixt, M..

21 records · Page 2Linked to original sources

Microtubules coordinate protrusion-retraction dynamics in migrating dendritic cells

Cells navigating through tissues face a fundamental challenge: while multiple cellular protrusions explore different paths through the complex geometry of an interstitial matrix the cell needs to avoid becoming too long or ramified, which might ultimately lead to a loss of physical coherence. How a cell surveys its own shape to inform the actomyosin system to retract entangled or stretched protrusions is not understood. Here, we demonstrate that spatially distinct microtubule (MT) dynamics regulate amoeboid cell migration by locally specifying the retraction of explorative protrusions. In migrating dendritic cells (DCs), the microtubule organizing center (MTOC) guides the path through a three dimensional (3D) interstitium and local MT depolymerization in protrusions remote from the MTOC triggers myosin II dependent contractility via the RhoA exchange factor Lfc. Depletion of Lfc leads to aberrant myosin localization, thereby causing two effects that rate-limit locomotion: i) impaired cell edge coordination during path-finding and ii) defective adhesion-resolution. Such compromised cell shape control is particularly hindering when cells navigate through geometrically complex microenvironments, where it leads to entanglement and ultimately fragmentation of the cell body. Our data demonstrate that MTs control cell shape and coherence by locally controlling protrusion-retraction dynamics of the actomyosin system.

cell biology↗

Mechanistic description of spatial processes using integrative modelling of noise-corrupted imaging data

Spatial patterns are ubiquitous on the subcellular, cellular and tissue level, and can be studied using imaging techniques such as light and fluorescence microscopy. Imaging data provide quantitative information about biological systems, however, mechanisms causing spatial patterning often remain illusive. In recent years, spatio-temporal mathematical modelling helped to overcome this problem. Yet, outliers and structured noise limit modelling of whole imaging data, and models often consider spatial summary statistics. Here, we introduce an integrated data-driven modelling approach that can cope with measurement artefacts and whole imaging data. Our approach combines mechanistic models of the biological processes with robust statistical models of the measurement process. The parameters of the integrated model are calibrated using a maximum likelihood approach. We used this integrated modelling approach to study in vivo gradients of the chemokine (C-C motif) ligand 21 (CCL21). CCL21 gradients guide dendritic cells and are important in the adaptive immune response. Using artificial data, we verified that the integrated modelling approach provides reliable parameter estimates in the presence of measurement noise and that bias and variance of these estimates are reduced compared to conventional approaches. The application to experimental data allowed the parameterisation and subsequent refinement of the model using additional mechanisms. Among others, model-based hypothesis testing predicted lymphatic vessel dependent concentration of heparan sulfate, the binding partner of CCL21. The selected model provided an accurate description of the experimental data and was partially validated using published data. Our findings demonstrate that integrated statistical modelling of whole imaging data is computationally feasible and can provide novel biological insights.

systems biology↗

Dual Phenotype Of MDA-MB-468 Cancer Cells Reveals Mutual Regulation Of Tensin3 And Adhesion Plasticity

Plasticity between adhesive and less-adhesive states is important for mammalian cell behaviour. To investigate adhesion plasticity, we have selected a stable isogenic subpopulation of MDA-MB-468 breast carcinoma cells which grows in suspension. These suspension cells are unable to re-adhere to various matrices or to contract three-dimensional collagen lattices. By transcriptome analysis, we identified the focal adhesion protein tensin3 (Tns3) as a determinant of adhesion plasticity. Tns3 is strongly reduced on mRNA and protein level in suspension cells. Furthermore, challenging breast cancer cells transiently with non-adherent conditions markedly reduces Tns3 expression, which is regained upon re-adhesion. Stable knockdown of Tns3 in parental cells results in defective adhesion, spreading and migration. Tns3 knockdown cells display impaired structure and dynamics of focal adhesion complexes as determined by immunostaining. Restoration of Tns3 expression in suspension cells partially rescues adhesion and focal contact composition. Our work identifies Tns3 as a critical focal adhesion component regulated by, and functionally contributing to, the switch between adhesive and non-adhesive states in MDA-MB-468 cancer cells.\n\nSummary statementWe identify the cell-matrix adapter protein tensin3 as a determinant of adhesion plasticity, using cancer cells selected for non-adherent growth. Tensin3 expression constitutes a feedback loop controlling adhesion and motility.

cell biology↗