Dataset Information

Inferring single-cell behaviour from large-scale epithelial sheet migration patterns.

ABSTRACT: Cell migration plays an important role in a wide variety of biological processes and can incorporate both individual cell motion and collective behaviour. The emergent properties of collective migration are receiving increasing attention as collective motion's role in diseases such as metastatic cancer becomes clear. Yet, how individual cell behaviour influences large-scale, multi-cell collective motion remains unclear. In this study, we provide insight into the mechanisms behind collective migration by studying cell migration in a spreading monolayer of epithelial MCF10A cells. We quantify migration using particle image velocimetry and find that cell groups have features of motion that span multiple length scales. Comparing our experimental results to a model of collective cell migration, we find that cell migration within the monolayer can be affected in qualitatively different ways by cell motion at the boundary, yet it is not necessary to introduce leader cells at the boundary or specify other large-scale features to recapitulate this large-scale phenotype in simulations. Instead, in our model, collective motion can be enhanced by increasing the overall activity of the cells or by giving the cells a stronger coupling between their motion and polarity. This suggests that investigating the activity and polarity persistence of individual cells will add insight into the collective migration phenotypes observed during development and disease.

SUBMITTER: Lee RM

PROVIDER: S-EPMC5454303 | biostudies-literature | 2017 May

REPOSITORIES: biostudies-literature

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Inferring single-cell behaviour from large-scale epithelial sheet migration patterns.

Lee Rachel M RM Yue Haicen H Rappel Wouter-Jan WJ Losert Wolfgang W

Journal of the Royal Society, Interface 20170501 130

Cell migration plays an important role in a wide variety of biological processes and can incorporate both individual cell motion and collective behaviour. The emergent properties of collective migration are receiving increasing attention as collective motion's role in diseases such as metastatic cancer becomes clear. Yet, how individual cell behaviour influences large-scale, multi-cell collective motion remains unclear. In this study, we provide insight into the mechanisms behind collective migr ...[more]

PMID: 28490603

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Project description:Polyelectrolyte multilayers (PEMUs) are tunable thin films that could serve as coatings for biomedical implants. PEMUs built layer by layer with the polyanion poly(acrylic acid) (PAA) modified with a photosensitive 4-(2-hydroxyethoxy) benzophenone (PAABp) group and the polycation poly(allylamine hydrochloride) (PAH) are mechanically tunable by UV irradiation, which forms covalent bonds between the layers and increases PEMU stiffness. PAH-terminated PEMUs (PAH-PEMUs) that were uncrosslinked, UV-crosslinked to a uniform stiffness, or UV-crosslinked with an edge mask or through a neutral density optical gradient filter to form continuous compliance gradients were used to investigate how differences in PEMU stiffness affect the adhesion and migration of epithelial cell sheets from scales of the fish Poecilia sphenops (Black Molly) and Carassius auratus (Comet Goldfish). During the progressive collective cell migration, the edge cells (also known as 'leader' cells) in the sheets on softer uncrosslinked PEMUs and less crosslinked regions of the gradient formed more actin filaments and vinculin-containing adherens junctions and focal adhesions than formed in the sheet cells on stiffer PEMUs or glass. During sheet migration, the ratio of edge cell to internal cell (also known as 'follower' cells) motilities were greater on the softer PEMUs than on the stiffer PEMUs or glass, causing tension to develop across the sheet and periods of retraction, during which the edge cells lost adhesion to the substrate and regions of the sheet retracted toward the more adherent internal cell region. These retraction events were inhibited by the myosin II inhibitor Blebbistatin, which reduced the motility velocity ratios to those for sheets on the stiffer PEMUs. Blebbistatin also caused disassembly of actin filaments, reorganization of focal adhesions, increased cell spreading at the leading edge, as well as loss of edge cell-cell connections in epithelial cell sheets on all surfaces. Interestingly, cells throughout the interior region of the sheets on uncrosslinked PEMUs retained their actin and vinculin organization at adherens junctions after treatment with Blebbistatin. Like Blebbistatin, a Rho-kinase (ROCK) inhibitor, Y27632, promoted loss of cell-cell connections between edge cells, whereas a Rac1 inhibitor, NSC23766, primarily altered the lamellipodial protrusion in edge cells. Compliance gradient PAH-PEMUs promoted durotaxis of the cell sheets but not of individual keratocytes, demonstrating durotaxis, like plithotaxis, is an emergent property of cell sheet organization.

Project description:BACKGROUND:Cancer cells reprogram their metabolism to survive and propagate. Thus, targeting metabolic rewiring in tumors is a promising therapeutic strategy. Genome-wide RNAi and CRISPR screens are powerful tools for identifying genes essential for cancer cell proliferation and survival. Integrating loss-of-function genetic screens with genomics and transcriptomics datasets reveals molecular mechanisms that underlie cancer cell dependence on specific genes; though explaining cell line-specific essentiality of metabolic genes was recently shown to be especially challenging. RESULTS:We find that variability in tissue culture medium between cell lines in a genetic screen is a major confounding factor affecting cell line-specific essentiality of metabolic genes-while, quite surprisingly, not being previously accounted for. Additionally, we find that altered expression level of a metabolic gene in a certain cell line is less indicative of its essentiality than for other genes. However, cell line-specific essentiality of metabolic genes is significantly correlated with changes in the expression of neighboring enzymes in the metabolic network. Utilizing a machine learning method that accounts for tissue culture media and functional association between neighboring enzymes, we generated predictive models for cancer cell line-specific dependence on 162 metabolic genes (representing a ~?2.2-fold increase compared to previous studies). The generated predictive models reveal numerous novel associations between molecular features and cell line-specific dependency on metabolic genes. Specifically, we demonstrate how cancer cell dependence on one-carbon metabolic enzymes is explained based on cancer lineage, oncogenic mutations, and RNA expression of neighboring enzymes. CONCLUSIONS:Considering culture media as well as accounting for molecular features of functionally related metabolic enzymes in a metabolic network significantly improves our understanding of cancer cell line-specific dependence on metabolic genes. We expect our approach and predictive models of metabolic gene essentiality to be a useful tool for investigating metabolic abnormalities in cancer.

Dataset Information

Inferring single-cell behaviour from large-scale epithelial sheet migration patterns.

Publications

Inferring single-cell behaviour from large-scale epithelial sheet migration patterns.

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