Rowland Institute at Harvard University, Cambridge, MA, USA.
Commun Biol. 2021 Jun 3;4(1):669. doi: 10.1038/s42003-021-02190-2.
How motile bacteria navigate environmental chemical gradients has implications ranging from health to climate science, but the underlying behavioral mechanisms are unknown for most species. The well-studied navigation strategy of Escherichia coli forms a powerful paradigm that is widely assumed to translate to other bacterial species. This assumption is rarely tested because of a lack of techniques capable of bridging scales from individual navigation behavior to the resulting population-level chemotactic performance. Here, we present such a multiscale 3D chemotaxis assay by combining high-throughput 3D bacterial tracking with microfluidically created chemical gradients. Large datasets of 3D trajectories yield the statistical power required to assess chemotactic performance at the population level, while simultaneously resolving the underlying 3D navigation behavior for every individual. We demonstrate that surface effects confound typical 2D chemotaxis assays, and reveal that, contrary to previous reports, Caulobacter crescentus breaks with the E. coli paradigm.
运动细菌如何在环境化学梯度中导航具有广泛的意义,从健康到气候科学,但对于大多数物种来说,潜在的行为机制尚不清楚。研究得很好的大肠杆菌导航策略形成了一个强大的范例,人们普遍认为它可以转化为其他细菌物种。由于缺乏能够从个体导航行为跨越到种群水平趋化性能的技术,这种假设很少得到检验。在这里,我们通过结合高通量 3D 细菌跟踪和微流控创建的化学梯度,提出了这样一种多尺度 3D 趋化性测定法。大量的 3D 轨迹数据集提供了评估种群水平趋化性能所需的统计能力,同时为每个个体解析潜在的 3D 导航行为。我们证明了表面效应对典型的 2D 趋化性测定法产生干扰,并揭示了与之前的报告相反的是,新月柄杆菌与大肠杆菌范式相悖。