Capacity to multitask limits cellular chemotaxis

Hye-ran Moon, Soutick Saha, Andrew Mugler, Bumsoo Han

Preprint posted on 11 December 2020

Article now published in iScience at

Movement and multitasking

Selected by Mariana De Niz

Categories: cell biology


Cell chemotaxis is the biased migration of cells along a chemical cue, and is key to many physiological as well as pathological processes including immune cell migration, wound healing, embryogenesis, responses to infection, and cancer metastasis. The function of sensing chemical cues is achieved by intracellular signaling molecules, and their downstream networks. Biochemical characterization, quantitative modeling, and biophysical approaches, among other fields, have contributed to our understanding of chemotaxis. Upon migration, however, many cells are exposed to multiple signals within complex chemical and physical environments that might vary in a spatial and temporal manner. Although we know that cell sensory functions are critical to decipher these complex signals in order to migrate, it is still not well understood how cells “multitask” while sensing  complex signals, to decide migratory directions. Recent studies have shown crosstalk in signals and associated signaling pathways, implying a multitasking capability of cells in processing multiple signals, however, the question remains: is there a limit to cellular multitasking capacity, and if so, what happens when cells exceed it? In their work, Moon et al test the hypothesis that the chemotactic performance of cells is constrained by their capacity to ‘multitask’.

Fig. 1. Schematic of cellular multitasking for chemotaxis (From Ref 1).


Key findings and developments

To test their hypothesis, the authors experimentally assessed the chemotaxis of highly metastatic breast cancer cells (MDA-MB-231) in response to multiple signals in various physical and chemical contexts. The multitasking capacity of cells is anticipated to either synergistically or antagonistically affect the cell chemotactic performance. To test this multitasking capacity, the authors presented multiple signals simultaneously. TGF-β and EGF are soluble growth factors towards which MDA-MB-231 cells show a chemotactic response. Cells were simultaneously exposed to both factors in a gradient-like manner, and their migration and chemotactic index were determined. Surprisingly, the chemotactic index in response to the combined gradients of  TGF-β and EGF decreased, compared to the response to each individual gradient, suggesting that multitasking can restrain the chemotactic performance, specifically in terms of directional accuracy. Conversely, cells under combined gradients showed enhanced speed, suggesting that there might be a convergence downstream in the signaling pathway of TGF-β and EGF, that may govern biased migration.

Having observed these behaviours in the metastatic breast cancer cells, the authors went on to evaluate whether this was cell-type specific. For this, they used pancreatic cancer cells of murine origin (eKIC). This cell line is known to be highly responsive to TGF-β. Upon exposure to gradients of both TGF-β and EGF, eKIC cells are highly responsive to both gradients, and the speed of migration is significantly higher than controls. This conserved response between both cell types indicates that the performance is not a cell-specific response.

Based on these observations, the authors proposed a model to describe biased cell migration in response to multiple chemical gradients. This model is based on the saturation of a common pathway component, whereby a specific component common to the TGF-β and EGF pathways that drives the cell migratory response, is converted to an active form by either TGF-β and EGF, and propagates the signal downstream in the pathway. The intuitive reason for an antagonistic response is that if most molecules are converted to their active state, the pathway is close to saturation. While with only one gradient signal (either TGF-β or EGF) the pathway is not fully saturated, with both signals, the pathway becomes saturated and the number of molecules in the active state is close to its maximum value throughout the cell. The model predicts that the direction of movement is chosen according to the distribution of the active molecule on the surface, and the cell moves at a constant speed until the next reaction takes place. Altogether, theoretically modeling of various parameters showed agreement with the experimental data regarding antagonism, and supported the hypothesis that cellular multitasking capacity can be explained by the presence of a common saturating component.

To evaluate this hypothesis, the authors developed two experimentally testable predictions. Both are based on the fact that saturation presents a tradeoff: the benefit of adding an EGF gradient to the TGF-β gradient is that it presents a stronger directional cue. The cost is that it overloads the signaling network by pushing the number of activated molecules on each side of the cell, closer to its maximal value. The cost wins, causing antagonism. Intuitively, it would be expected that if a uniform EGF signal is used instead of the EGF gradient, then the benefit is removed. This is indeed supported by the simulation. However this does not rule out the possibility that the EGF pathway represses the TGF-β pathway to create antagonism. To test this, the authors overloaded the cell by adding to the TGF-β gradient, a uniform background of TGF-β. The simulation showed a similar result to that obtained with a uniform EGF background, consistent with an overloaded signal environment being the cause of the antagonism. Upon testing these theoretical results experimentally, the authors obtained results supporting the hypothesis that the antagonism is not due to repressive crosstalk, but rather due to the saturation of a common pathway component.

What I like about this preprint

I think the topic of chemotaxis is fascinating in many contexts of immunology, physiology and pathology. I find it a particularly interesting topic for infectious diseases, and so found it interesting to see what the authors had found in terms of multitasking in chemotaxis, and what their model could explain.


  1. Moon et al, Capacity to multitask limits cellular chemotaxis, bioRxiv, 2020.


Posted on: 22 December 2020 , updated on: 2 January 2021


Read preprint (No Ratings Yet)

Author's response

Andrew Mugler, Hye Ran Moon, Soutick Saha shared

Open questions

1.One of your conclusions is that the model predicted accurately the response of both cancer cell types, and you conclude that the model is not cancer type-specific and that it can be extended to other cells. Did you test this on non-cancer cells? Could you frame this conclusion within what is known in terms of signal saturation, signaling pathways and migration differences of cancer cell lines, and non-cancer cells of different types?

Although we have not tested the response of non-cancer cells, we anticipate that the presented model is applicable to other cell types. Our model addresses the cell capacity to process multiple signals to decide its migration direction. Regardless of the cell type, the intracellular mechanism to modulate the cell chemotaxis is associated with structural dynamics of actin, myosin, and adhesion molecules. Our model addresses physical aspects of the intracellular signaling processes to regulate such cell functions, suggesting that it is not for cell type-specific responses. Although participating signals or the cellular signaling networks may vary depending on the cell types, the presented model describes how the physical limit of the far-end downstream molecules activated by multiple signals could constrain cellular response, not because of the cell-type specific characteristics. In this context, the presented model could address non-cancer cell behaviors, provided that we consider the cell types are intrinsically capable of chemotaxis.

2.You tested in your work the responses to TGF-β or EGF specifically. However, there are many other chemotactic signals. What would be your prediction upon using alternative chemotactic signals?

We anticipate that the cellular response would be constrained if the other signals also meet the intracellular signaling molecule’s saturation point, as we showed with TGF-β and EGF. Although the presented model was developed and tested only with TGF-β and EGF, our results suggest that the saturation of a downstream signaling molecule causes the antagonism, not cross-talk between specific chemical signals.

3.In your introduction you expand on the fact that a complex set of signals (physical as well as chemical) exist in a living organism where cell migration occurs. If we take as an example, migration of a leukocyte across tissues through the vascular endothelium, the amount of signals is vast. In your model, can you also test how multiple chemical signals as well as physical factors (for instance, sheer flow, viscosity, temperature) influence cell motility?

The presented model was developed for chemotaxis based on the chemical signal processing, not addressing how cells sense physical signals. However, as mentioned in the question, migrating cells experience a highly complex signal environment, including multiple chemical and physical signals such as shear flow. In this context, we are currently working on the cellular response to a complex signal environment with shear flow as one of the signals.

4.A very broad question: Taking the previous question as a basis, what is your definition of multitasking, considering a cell within a living organism?

The term cellular multitasking we used can be defined as a cellular capability to simultaneously process multiple signals in determining their behaviors. In a living organism, cellular behaviors such as migration are regulated by various signals (chemical and physical signals, as mentioned in the previous questions). In the complex signal environment, the cellular decision to show a specific behavior is a consequence of the complex signal transductions involved, not in a one-to-one correspondence. In this context, this study presents evidence that cellular multitasking capability can be physically constrained.

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