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Modelling Chemotactic Motion of Cells in Biological Tissues.

ABSTRACT: Developmental processes in biology are underlined by proliferation, differentiation and migration of cells. The latter two are interlinked since cellular differentiation is governed by the dynamics of morphogens which, in turn, is affected by the movement of cells. Mutual effects of morphogenetic and cell movement patterns are enhanced when the movement is due to chemotactic response of cells to the morphogens. In this study we introduce a mathematical model to analyse how this interplay can result in a steady movement of cells in a tissue and associated formation of travelling waves in a concentration field of morphogen. Using the model we have identified four chemotactic scenarios for migration of single cell or homogeneous group of cells in a tissue. Such a migration can take place if moving cells are (1) repelled by a chemical produced by themselves or (2) attracted by a chemical produced by the surrounding cells in a tissue. Furthermore, the group of cells can also move if cells in surrounding tissue are (3) repelled by a chemical produced by moving cells or (4) attracted by a chemical produced by surrounding cells themselves. The proposed mechanisms can underlie migration of cells during embryonic development as well as spread of metastatic cells.

SUBMITTER: Vasiev B

PROVIDER: S-EPMC5087904 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Modelling Chemotactic Motion of Cells in Biological Tissues.

Vasiev Bakhtier B

PloS one 20161031 10

Developmental processes in biology are underlined by proliferation, differentiation and migration of cells. The latter two are interlinked since cellular differentiation is governed by the dynamics of morphogens which, in turn, is affected by the movement of cells. Mutual effects of morphogenetic and cell movement patterns are enhanced when the movement is due to chemotactic response of cells to the morphogens. In this study we introduce a mathematical model to analyse how this interplay can res ...[more]

PMID: 27798687

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Project description:Precise spatiotemporal regulation is the foundation for the healthy development and maintenance of living organisms. All cells must correctly execute their function in the right place at the right time. Cellular motion is thus an important dynamic readout of signaling in key disease-relevant molecular pathways. However despite the rapid advancement of imaging technology, a comprehensive quantitative description of motion imaged under different imaging modalities at all spatiotemporal scales; molecular, cellular and tissue-level is still lacking. Generally, cells move either 'individually' or 'collectively' as a group with nearby cells. Current computational tools specifically focus on one or the other regime, limiting their general applicability. To address this, we recently developed and reported a new computational framework, Motion Sensing Superpixels (MOSES). Incorporating the individual advantages of single cell trackers for individual cell and particle image velocimetry (PIV) for collective cell motion analyses, MOSES enables 'mesoscale' analysis of both single-cell and collective motion over arbitrarily long times. At the same time, MOSES readily complements existing single-cell tracking workflows with additional characterization of global motion patterns and interaction analysis between cells and also operates directly on PIV extracted motion fields to yield rich motion trajectories analogous for single-cell tracks suitable for high-throughput motion phenotyping. This protocol provides a step-by-step practical guide for those interested in applying MOSES to their own datasets. The protocol highlights the salient features of a MOSES analysis and demonstrates the ease-of-use and wide applicability of MOSES to biological imaging through demo experimental analyses with ready-to-use code snippets of four datasets from different microscope modalities; phase-contrast, fluorescent, lightsheet and intra-vital microscopy. In addition we discuss critical points of consideration in the analysis.

Project description:Escherichia coli chemotactic motion in spatiotemporally varying environments is studied by using a computational model based on a coarse-grained description of the intracellular signaling pathway dynamics. We find that the cell's chemotaxis drift velocity v(d) is a constant in an exponential attractant concentration gradient [L] proportional, variantexp(Gx). v(d) depends linearly on the exponential gradient G before it saturates when G is larger than a critical value G(C). We find that G(C) is determined by the intracellular adaptation rate k(R) with a simple scaling law: G(C) infinity k(1/2)(R). The linear dependence of v(d) on G = d(ln[L])/dx directly demonstrates E. coli's ability in sensing the derivative of the logarithmic attractant concentration. The existence of the limiting gradient G(C) and its scaling with k(R) are explained by the underlying intracellular adaptation dynamics and the flagellar motor response characteristics. For individual cells, we find that the overall average run length in an exponential gradient is longer than that in a homogeneous environment, which is caused by the constant kinase activity shift (decrease). The forward runs (up the gradient) are longer than the backward runs, as expected; and depending on the exact gradient, the (shorter) backward runs can be comparable to runs in a spatially homogeneous environment, consistent with previous experiments. In (spatial) ligand gradients that also vary in time, the chemotaxis motion is damped as the frequency omega of the time-varying spatial gradient becomes faster than a critical value omega(c), which is controlled by the cell's chemotaxis adaptation rate k(R). Finally, our model, with no adjustable parameters, agrees quantitatively with the classical capillary assay experiments where the attractant concentration changes both in space and time. Our model can thus be used to study E. coli chemotaxis behavior in arbitrary spatiotemporally varying environments. Further experiments are suggested to test some of the model predictions.

Project description:Background Non-small cell lung cancer is the most common cause of early casualty from malignant disease in western countries. The heterogeneous nature of these cells has been identified by histochemical and microarray biomarker analyses. Unfortunately, the morphological, molecular and biological variation within cell lines used as models for invasion and metastasis are not well understood. In this study, we test the hypothesis that heterogeneous cancer cells exhibit variable motility responses such as chemokinesis and chemotaxis that can be characterized molecularly. Methods A subpopulation of H460 lung cancer cells called KINE that migrated under chemokinetic (no gradient) conditions was harvested from Boyden chambers and cultured. Time-lapsed microscopy, immunofluorescence microscopy and microarray analyses were then carried out comparing chemokinetic KINE cells with the unselected CON cell population. Results Time-lapsed microscopy and analysis showed that KINE cells moved faster but less directionally than the unselected control population (CON), confirming their chemokinetic character. Of note was that chemokinetic KINE cells also chemotaxed efficiently. KINE cells were less adhesive to substrate than CON cells and demonstrated loss of mature focal adhesions at the leading edge and the presence of non-focalized cortical actin. These characteristics are common in highly motile amoeboid cells that may favour faster motility speeds. KINE cells were also significantly more invasive compared to CON. Gene array studies and real-time PCR showed the downregulation of a gene called, ROM, in highly chemokinetic KINE compared to mainly chemotactic CON cells. ROM was also reduced in expression in a panel of lung cancer cell lines compared normal lung cells. Conclusions This study shows that cancer cells that are efficient in both chemokinesis and chemotaxis demonstrate high invasion levels. These cells possess different morphological, cytoskeletal and adhesive properties from another population that are only efficient at chemotaxis, indicating a loss in polarity. Understanding the regulation of polarity in the context of cell motility is important in order to improve control and inhibition of invasion and metastasis. Keywords: Cancer cells, chemotaxis, chemokinesis, motility, gene regulation.

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Modelling Chemotactic Motion of Cells in Biological Tissues.

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Modelling Chemotactic Motion of Cells in Biological Tissues.

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