Why This Is Cool – Populations of E. coli cells can migrate collectively up chemoattractant gradients and they do so with a biased random walk produced by straight “runs” and random “tumbles.” It has also been previously established that E. coli that are genetically identical present with variable swimming phenotypes i.e. some cells run more and some cells tumble more than others. What Fu et al. set out to answer was how do these groups of cells travel together despite their individual differences in chemotactic ability? To answer this, they had to observe both collective and individual behaviors, so they used the smartly designed microfluidic device pictured below. The narrow channel allowed E. coli cells to migrate in bands up a gradient, towards an open chamber where cells could disperse and individual behavior could be tracked. Using this set-up, they were able to establish that although there is some selection for less tumbling in collectively migrating bands, phenotypic diversity is definitely still present. They then expanded a classic mathematical model1 for collective chemotaxis to account for individual diversities. This expanded model allowed them to predict how different swimming phenotypes could still travel together. Spatial sorting of cells, so that high tumbling coincides with a steeper gradient, allows the group to compensate for diversity. So the less efficient, more tumbley cells get sorted to the back of the group where the gradient is steeper, because the front runner cells, which perform better with small changes in gradient, metabolize a certain amount of the attractant, leaving a steeper gradient behind them. The steeper gradient keeps the tumblers more focused and they are able to keep up to a certain cut-off point. Fu et al. were then able to confirm these predictions experimentally with mixed levels of expression of the chemotaxis regulating phosphatase CheZ. In addition, they identified a possible role for oxygen availability in controlling this spatial sorting. E. coli need oxygen to metabolize these chemoattractants, but oxygen becomes less available with more cells, such as the conditions of the middle of the band (Figure 1). More oxygen is available at the back due to lower cell density, which increases metabolism, thus increasing the local gradient steepness even more and possibly allowing even the worst tumblers to keep up.
Why I Selected It – I was looking for preprints on the collective migration of eukaryotic cells when I “tumbled” across this work from Fu et al., but I am so glad I stuck with it. I didn’t know bacteria even underwent collective migrations. This work uses an excellent and high-throughput model system for studying phenotypic diversity and I think their results are widely applicable, as they state – “For example in migrating neural crest cells and in fish shoals, many organisms may follow a few more informed individuals2.” Reading this preprint made me question the phenotypic diversity I see in my own research, a phenomenon not often addressed in eukaryotic cell biology.
Open Questions –
Would you expect the spatial sorting of cells to be any different based on the type of chemotactic cue? Are there any non-consumable cues that could be tested, presumably to see a disruption in this process?
Do you think this spatial sorting is an active process? If you reversed the direction of the gradient mid-migration, would the organization of the band change?
If you continually removed a certain phenotype, say removed all the cells that fell off the band over multiple cycles of migration, would you eventually get a homogenous band with no spatial sorting? Would this impede or improve collective migration?
Related References –
Classic model of collective bacteria cell chemotaxis
We expect spatial sorting to be a generic outcome when cells of different gradient-climbing abilities climb the same gradient, whether it be a gradient of consumable chemoattractant, non-consumable chemoattractant, oxygen, temperature, etc. However, spatial sorting in an attractant gradient created by consumption is special in that the fastest cells can’t run far ahead of the slower ones because they need those cells to help create the gradient; without them, there is no gradient to climb.
We think this spatial sorting is active in the sense that if the gradient reversed direction (not too fast), then the direction of sorting would reverse, as well. Any fast gradient climbers located at the bottom of the new gradient would quickly catch up with and pass the slow gradient climbers ahead of them, leading to reorientation of the sorting. However, although this is an active process, it is not hard-coded in the cells; spatial sorting emerges from the differences in individual gradient-climbing capabilities.
Eliminating phenotypic diversity would be very difficult because every time a cell divides it will give rise to daughter cells that are not entirely identical. If under special circumstances we managed to form a band composed of a narrow distribution of phenotypes that is nearly homogeneous, we would expect cell diffusion to smear out spatial sorting, making the band effectively well-mixed. To what extend this band might perform better than a more diverse one is unclear and a question we are actively investigating.
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