Confinement, jamming, and adhesion in cancer cells dissociating from a collectively invading strand.

When cells in a primary tumor work together to invade into nearby tissue, this can lead to cell dissociations-cancer cells breaking off from the invading front-leading to metastasis. What controls the dissociation of cells, and whether they break off singly or in small groups? Can this be determined by cell-cell adhesion or chemotactic cues given to cells? We develop a physical model for this question, based on experiments that mimic aspects of cancer cell invasion using microfluidic devices with microchannels of different widths. Experimentally, most dissociation events ("ruptures") involve single cells breaking off, but we observe some ruptures of large groups ( ∼ 20 cells) in wider channels. The rupture probability is nearly independent of channel width. We recapitulate the experimental results with a phase field cell motility model by introducing three different cell states (follower, guided, and high-motility metabolically active leader cells) based on their spatial position. These leader cells may explain why single-cell rupture is the universal most probable outcome. Our simulation results show that cell-channel adhesion is necessary for cells in narrow channels to invade, and strong cell-cell adhesion leads to fewer but larger ruptures. Chemotaxis also influences the rupture behavior: Strong chemotaxis strength leads to larger and faster ruptures. Finally, we study the relationship between biological jamming transitions and cell dissociations. Our results suggest unjamming is necessary but not sufficient to create ruptures.

Deposited footprints let cells switch between confined, oscillatory, and exploratory migration.

For eukaryotic cells to heal wounds, respond to immune signals, or metastasize, they must migrate, often by adhering to extracellular matrix (ECM). Cells may also deposit ECM components, leaving behind a footprint that influences their crawling. Recent experiments showed that some epithelial cell lines on micropatterned adhesive stripes move persistently in regions they have previously crawled over, where footprints have been formed, but barely advance into unexplored regions, creating an oscillatory migration of increasing amplitude. Here, we explore through mathematical modeling how footprint deposition and cell responses to footprint combine to allow cells to develop oscillation and other complex migratory motions. We simulate cell crawling with a phase field model coupled to a biochemical model of cell polarity, assuming local contact with the deposited footprint activates Rac1, a protein that establishes the cell's front. Depending on footprint deposition rate and response to the footprint, cells on micropatterned lines can display many types of motility, including confined, oscillatory, and persistent motion. On two-dimensional (2D) substrates, we predict a transition between cells undergoing circular motion and cells developing an exploratory phenotype. Small quantitative changes in a cell's interaction with its footprint can completely alter exploration, allowing cells to tightly regulate their motion, leading to different motility phenotypes (confined vs. exploratory) in different cells when deposition or sensing is variable from cell to cell. Consistent with our computational predictions, we find in earlier experimental data evidence of cells undergoing both circular and exploratory motion.

Secreted footprints let cells switch between confined, oscillatory, and exploratory migration.

For eukaryotic cells to heal wounds, respond to immune signals, or metastasize, they must migrate, often by adhering to extracellular matrix. Cells may also secrete matrix factors, leaving behind a footprint that influences their crawling. Recent experiments showed that epithelial cells on micropatterned adhesive stripes move persistently in regions they have previously crawled over, where footprints have been formed, but barely advance into unexplored regions, creating an oscillatory migration of increasing amplitude. Here, we explore through mathematical modeling how footprint secretion and cell responses to footprint combine to allow cells to develop oscillation and other complex migratory motions. We simulate cell crawling with a phase field model coupled to a biochemical model of cell polarity, assuming local contact with the secreted footprint activates Rac1, a polarity protein at the front of the cell. Depending on the footprint secretion rate and the response to the footprint, cells on micropatterned lines can display a variety of types of motility, including confined, oscillatory, and persistent motion. On 2D substrates, we predict a transition between cells undergoing circular motion and cells developing a more exploratory phenotype. Our model shows how minor changes in a cell's interaction with its footprint can completely alter exploration, allowing cells to tightly regulate their motion, as well as leading to a wide spectrum of behaviors when secretion or sensing is variable from cell to cell. Consistent with our computational predictions, we find in earlier experimental data evidence of cells undergoing both circular and exploratory motion. Our work proposes a new paradigm for how cells regulate their own motility.

Cytokinesis machinery promotes cell dissociation from collectively migrating strands in confinement.

Cells tune adherens junction dynamics to regulate epithelial integrity in diverse (patho)physiological processes, including cancer metastasis. We hypothesized that the spatially confining architecture of peritumor stroma promotes metastatic cell dissemination by remodeling cell-cell adhesive interactions. By combining microfluidics with live-cell imaging, FLIM/FRET biosensors, and optogenetic tools, we show that confinement induces leader cell dissociation from cohesive ensembles. Cell dissociation is triggered by myosin IIA (MIIA) dismantling of E-cadherin cell-cell junctions, as recapitulated by a mathematical model. Elevated MIIA contractility is controlled by RhoA/ROCK activation, which requires distinct guanine nucleotide exchange factors (GEFs). Confinement activates RhoA via nucleocytoplasmic shuttling of the cytokinesis-regulatory proteins RacGAP1 and Ect2 and increased microtubule dynamics, which results in the release of active GEF-H1. Thus, confining microenvironments are sufficient to induce cell dissemination from primary tumors by remodeling E-cadherin cell junctions via the interplay of microtubules, nuclear trafficking, and RhoA/ROCK/MIIA pathway and not by down-regulating E-cadherin expression.

Correction: Fluctuations, Correlations and the Estimation of Concentrations inside Cells.

[This corrects the article DOI: 10.1371/journal.pone.0151132.].

Fluctuations, Correlations and the Estimation of Concentrations inside Cells.

Information transmission in cells occurs quite accurately even when concentration changes are "read" by individual binding sites. In this paper we study ligand number and site occupancy fluctuations when ligands diffuse and react going beyond the analyses that focus on their asymptotic decay. In this way we show that, for immobile binding sites, fluctuations in the number of bound molecules decay on a relatively fast scale before the asymptotic behavior kicks in. This result can explain the observed co-existence of highly fluctuating instantaneous transcriptional activities with accumulated mRNA concentrations that have relatively small noise levels. We also show that the initial stages of the decay in the bound molecule number fluctuations have one or two characteristic timescales depending on the concentration of free molecules. This transition can explain the changes in enzyme activity observed at the single molecule level.

How long should a system be observed to obtain reliable concentration estimates from the measurement of fluctuations?

The interior of cells is a highly fluctuating environment. Fluctuations set limits to the accuracy with which endogenous processes can occur. The physical principles that rule these limits also affect the experimental quantification of biophysical parameters in situ. The characterization of fluctuations, on the other hand, provides a way to quantify biophysical parameters. But as with any random process, enough data has to be collected to achieve a reliable quantitative description. In this article we study the accuracy with which intracellular concentrations can be estimated using fluorescence correlation spectroscopy. We show that, when the observed molecules interact with immobile species or experience other restrictions to their movement, the hypotheses commonly used to estimate concentrations are no longer valid. The interactions with immobile sites reduce the fluorescence variance by a finite amount. The time that is necessary to obtain an accurate concentration estimate, on the other hand, is hundreds of times larger than the slowest correlation time and is much larger when the sites move slowly than when they are immobile. Our analysis is applicable to other related techniques and it also sheds light on the way in which effector concentrations are read by target molecules in cells.

Fluorescence fluctuations and equivalence classes of Ca²âº imaging experiments.

Ca²âº release into the cytosol through inositol 1,4,5-trisphosphate receptors (IP3Rs) plays a relevant role in numerous physiological processes. IP3R-mediated Ca²âº signals involve Ca²âº-induced Ca²âº-release (CICR) whereby Ca²âº release through one open IP3R induces the opening of other channels. IP3Rs are apparently organized in clusters. The signals can remain localized (i.e., Ca²âº puffs) if CICR is limited to one cluster or become waves that propagate between clusters. Ca²âº puffs are the building blocks of Ca²âº waves. Thus, there is great interest in determining puff properties, especially in view of the current controversy on the spatial distribution of activatable IP3Rs. Ca²âº puffs have been observed in intact cells with optical techniques proving that they are intrinsically Ca²âº dyes, slow exogenous buffers (e.g., EGTA) to disrupt inter-cluster CICR and UV-photolyzable caged IP3. Single-wavelength dyes increase their fluorescence upon calcium binding producing images that are strongly dependent on their kinetic, transport and photophysical properties. Determining the artifacts that the imaging setting introduces is particularly relevant when trying to analyze the smallest Ca²âº signals. In this paper we introduce a method to estimate the expected signal-to-noise ratio of Ca²âº imaging experiments that use single-wavelength dyes. The method is based on the Number and rightness technique. It involves the performance of a series of experiments and their subsequent analysis in terms of a fluorescence fluctuation model with which the model parameters are quantified. Using the model, the expected signal-to-noise ratio is then computed. Equivalence classes between different experimental conditions that produce images with similar signal-to-noise ratios can then be established. The method may also be used to estimate the smallest signals that can reliably be observed with each setting.