Brian A. Camley

Eukaryotic cells generally sense chemical gradients using the binding of chemical ligands to membrane receptors. To perform chemotaxis effectively in different environments, cells need to adapt to different concentrations. We present a model of gradient sensing where the affinity of receptor-ligand binding is increased when a protein binds to the receptor's cytosolic side. This interior protein (allosteric factor) alters the sensitivity of the cell, allowing the cell to adapt to different ligand concentrations. We propose a reaction scheme where the cell alters the allosteric factor's availability to adapt the average fraction of bound receptors to 1/2. We calculate bounds on the chemotactic accuracy of the cell and find that the cell can reach near-optimal chemotaxis over a broad range of concentrations. We find that the accuracy of chemotaxis depends strongly on the diffusion of the allosteric compound relative to other reaction rates. From this, we also find a tradeoff between adaptation time and gradient sensing accuracy.

Cells are constantly exposed to diverse stimuli-chemical, mechanical, or electrical-that guide their movement. In physiological conditions, these signals often overlap, as seen during infections, where neutrophils and dendritic cells navigate through multiple chemotactic fields. How cells integrate and prioritize competing signals remains unclear. For instance, in the presence of opposing chemoattractant gradients, how do cells decide which direction to go? When should local signals dominate distant ones? A key factor in these processes is the precision with which cells sense each gradient, which depends nonmonotonically on concentrations. Here, we study how gradient sensing accuracy shapes cell navigation in the presence of two distinct chemoattractant sources. We model cells as active random walkers that sense local gradients and combine these estimates to reorient their movement. Our results show that cells sensing multiple gradients can display a range of chemotactic behaviors, including anisotropic spatial patterns and varying degrees of confinement, depending on gradient shape and source location. The model also predicts cases where cells exhibit multistep navigation across sources or a hierarchical response toward one source, driven by disparities in their sensitivity to each chemoattractant. These findings highlight the role of gradient sensing in shaping spatial organization and navigation strategies in multifield chemotaxis.

Groups of cells, including clusters of cancerous cells, multicellular organisms, and developing organs, may both grow and break apart. What physical factors control these fractures? In these processes, what sets the eventual size of clusters? We first develop a one-dimensional framework for understanding cell clusters that can fragment due to cell motility using an active particle model. We compute analytically how the break rate of cell-cell junctions depends on cell speed, cell persistence, and cell-cell junction properties. Next, we find the cluster size distributions, which differ depending on whether all cells can divide or only the cells on the edge of the cluster divide. Cluster size distributions depend solely on the ratio of the break rate to the growth rate-allowing us to predict how cluster size and variability depend on cell motility and cell-cell mechanics. Our results suggest that organisms can achieve better size control when cell division is restricted to the cluster boundaries or when fracture can be localized to the cluster center. Additionally, we derive a universal survival probability for an intact cluster S(t)=e^{-k_{d}t} at steady state if all cells can divide, which is independent of the rupture kinetics and depends solely on the cell division rate k_{d}. Finally, we further corroborate the one-dimensional analytics with two-dimensional simulations, finding quantitative agreement with some-but not all-elements of the theory across a wide range of cell motility. Our results link the general physics problem of a collective active escape over a barrier to size control, providing a quantitative measure of how motility can regulate organ or organism size.

White blood cells can be guided to targets by chemoattractant signals, but this response is complicated, including guidance toward and away from inflammation sites. We model how cells can switch between being attracted and repelled by a chemical signal. We study experiments on malignant B cell lines, which find that depending on their environment, B cells can either be attracted or repelled by signals like CCL19. The presence of chemorepulsion is also dependent on whether the receptors for CCL19 can be internalized via endocytosis. We develop a stochastic model of receptor-ligand binding and internalization where bound receptors drive a nonlinear feed-forward loop of intracellular signaling molecules, which determine the cell’s direction. We recapitulate key experimental results: changing CCL19 concentration or inhibiting receptor internalization can switch the cell’s direction. Our model implies that cells can navigate toward a target concentration of a signal, regulating that target by receptor internalization. We propose experiments to test this idea.

When cells attached to parallel nanofibers collide, they can form a train, reverse from the collision, or walk past each other. Simulations and linear stability analysis show the outcome depends on cell deformability, positive feedback of polarity, and fiber spacing.

Collective response to external directional cues like electric fields helps guide tissue development, regeneration, and wound healing. In this study we focus on the impact of anisotropy in cell shape and local cell alignment on the collective response to electric fields. We model elongated cells that have a different accuracy sensing the field depending on their orientation with respect to the field. With this framework, we assume cells are better sensors if they can align their long axes perpendicular to the field. Elongated cells often line up with their long axes in the same direction — “nematic order” – does a nematic cell-cell interaction allow groups of cells to share information about their orientation to sense fields more accurately? We use simulations of a simple model to show that if cells orient themselves perpendicular to their average velocity, alignment of a cell’s long axis to its nearest neighbors’ orientation can in some circumstances enhance the directional response to electric fields. We also show that cell-cell adhesion modulates the accuracy of cells in the group.

Cells sense and respond to electric fields, using these fields as a guidance cue in wound healing and development. This sensing is done by redistribution of charged membrane proteins on the cell’s surface (“sensors”) via electrophoresis and electroosmotic flow. If membrane proteins have to physically rearrange on the cell’s surface, how quickly can a cell respond to an applied signal? What limits the cell’s ability to respond? Are galvanotaxing cells, like chemotaxing cells, limited by stochasticity from the finite number of molecules? Here, we develop a model for the response dynamics of galvanotaxing cells and show that, for weak enough field strengths, two relevant timescales emerge: the time for the cell’s sensors to rearrange, which depends on their diffusion across the cell, and the time for the cell’s orientation to respond to an applied field, which may be very different. We fit this model to experimental measurements on the recently-identified sensor galvanin (TMEM154) in neutrophil-like HL-60 cells, finding that given the dynamics of a cell responding to an applied field, we can predict the dynamics of the cell after the field is turned off. This fit constrains the noise of the galvanotaxis process, demonstrating that HL-60 is not limited by the stochasticity of finite sensor number. Our model also allows us to explain the effect of media viscosity on cell dynamics, and predict how cells respond to pulsed DC fields. These results place constraints on the ability to guide cells with pulsed fields, predicting that a field on half of the time is no better than a field that is always on with half the magnitude.

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 “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.