A model of strongly biased chemotaxis reveals the trade-offs of different bacterial migration strategies

R N Bearon;W M Durham
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引用次数: 3

Abstract

Many bacteria actively bias their motility towards more favourable nutrient environments. In liquid, cells rotate their corkscrew-shaped flagella to swim, but in surface attached biofilms cells instead use grappling hook-like appendages called pili to pull themselves along. In both forms of motility, cells selectively alternate between relatively straight 'runs' and sharp reorientations to generate biased random walks up chemoattractant gradients. However, recent experiments suggest that swimming and biofilm cells employ fundamentally different strategies to generate chemotaxis: swimming cells typically suppress reorientations when moving up a chemoattractant gradient, whereas biofilm cells increase reorientations when moving down a chemoattractant gradient. The reason for this difference remains unknown. Here we develop a mathematical framework to understand how these different chemotactic strategies affect the distribution of cells at the population level. Current continuum models typically assume a weak bias in the reorientation rate and are not able to distinguish between these two strategies, so we derive a model for strong chemotaxis that resolves how both the drift and diffusive components depend on the underlying chemotactic strategy. We then test predictions from our continuum model against individual-based simulations and identify further refinements that allow our continuum model to resolve boundary effects. Our analyses reveal that the strategy employed by swimming cells yields a larger chemotactic drift, but the strategy used by biofilm cells allows them to more tightly aggregate where the chemoattractant is most abundant. This new modelling framework provides new quantitative insights into how the different chemical landscapes experienced by swimming and biofilm cells might select for divergent ways of generating chemotaxis.
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一个强烈偏向趋化的模型揭示了不同细菌迁移策略的权衡
许多细菌主动地将它们的运动倾向于更有利的营养环境。在液体中,细胞旋转螺旋状的鞭毛游泳,但在表面附着的生物膜中,细胞反而使用称为菌毛的抓钩状附属物来拉动自己。在这两种运动形式中,细胞选择性地在相对笔直的“运行”和尖锐的重新定向之间交替,以产生有偏差的随机向上行走的化学引诱剂梯度。然而,最近的实验表明,游泳细胞和生物膜细胞采用根本不同的策略来产生趋化性:游泳细胞通常在向上移动化学引诱剂梯度时抑制重定向,而生物膜细胞在向下移动化学引诱物梯度时增加重定向。造成这种差异的原因仍然未知。在这里,我们开发了一个数学框架来了解这些不同的趋化策略如何影响细胞在群体水平上的分布。目前的连续体模型通常假设重新定向率存在弱偏差,并且无法区分这两种策略,因此我们推导了一个强趋化性模型,该模型解决了漂移和扩散成分如何依赖于潜在的趋化策略。然后,我们将连续体模型的预测与基于个体的模拟进行比较,并确定进一步的改进,使我们的连续体模型能够解决边界效应。我们的分析表明,游泳细胞采用的策略产生了更大的趋化漂移,但生物膜细胞使用的策略使它们能够在化学引诱剂最丰富的地方更紧密地聚集。这一新的建模框架为游泳和生物膜细胞所经历的不同化学景观如何选择产生趋化性的不同方式提供了新的定量见解。
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