Menolascina Filippo, Rusconi Roberto, Fernandez Vicente I, Smriga Steven, Aminzare Zahra, Sontag Eduardo D, Stocker Roman
Institute for Bioengineering, School of Engineering, The University of Edinburgh, Scotland, UK.
SynthSys-Centre for Synthetic and Systems Biology, The University of Edinburgh, Scotland, UK.
NPJ Syst Biol Appl. 2017 Jan 19;3:16036. doi: 10.1038/npjsba.2016.36. eCollection 2017.
Aerotaxis, the directed migration along oxygen gradients, allows many microorganisms to locate favorable oxygen concentrations. Despite oxygen's fundamental role for life, even key aspects of aerotaxis remain poorly understood. In for example, there is conflicting evidence of whether migration occurs to the maximal oxygen concentration available or to an optimal intermediate one, and how aerotaxis can be maintained over a broad range of conditions. Using precisely controlled oxygen gradients in a microfluidic device, spanning the full spectrum of conditions from quasi-anoxic to oxic (60 n mol/l-1 m mol/l), we resolved 'oxygen preference conundrum' by demonstrating consistent migration towards maximum oxygen concentrations ('monotonic aerotaxis'). Surprisingly, the strength of aerotaxis was largely unchanged over three decades in oxygen concentration (131 n mol/l-196 μ mol/l). We discovered that in this range responds to the logarithm of the oxygen concentration gradient, a rescaling strategy called 'log-sensing' that affords organisms high sensitivity over a wide range of conditions. In these experiments, high-throughput single-cell imaging yielded the best signal-to-noise ratio of any microbial taxis study to date, enabling the robust identification of the first mathematical model for aerotaxis among a broad class of alternative models. The model passed the stringent test of predicting the transient aerotactic response despite being developed on steady-state data, and quantitatively captures both monotonic aerotaxis and log-sensing. Taken together, these results shed new light on the oxygen-seeking capabilities of and provide a blueprint for the quantitative investigation of the many other forms of microbial taxis.
趋氧性,即沿氧梯度的定向迁移,使许多微生物能够找到适宜的氧浓度。尽管氧气对生命起着至关重要的作用,但即使是趋氧性的关键方面仍知之甚少。例如,关于迁移是朝着可获得的最大氧浓度还是朝着最佳中间氧浓度发生,以及趋氧性如何在广泛的条件下得以维持,存在相互矛盾的证据。我们在微流控装置中使用精确控制的氧梯度,涵盖从准缺氧到有氧(60纳摩尔/升 - 1毫摩尔/升)的全范围条件,通过证明朝着最大氧浓度的一致迁移(“单调趋氧性”)解决了“氧偏好难题”。令人惊讶的是,在氧浓度的三个数量级(131纳摩尔/升 - 196微摩尔/升)范围内,趋氧性的强度基本保持不变。我们发现,在此范围内,(微生物)对氧浓度梯度的对数做出反应,这是一种称为“对数感知”的重新缩放策略,使生物体在广泛的条件下具有高灵敏度。在这些实验中,高通量单细胞成像产生了迄今为止任何微生物趋化性研究中最佳的信噪比,从而能够在众多替代模型中稳健地识别出趋氧性的首个数学模型。尽管该模型是基于稳态数据开发的,但它通过了预测瞬态趋氧反应的严格测试,并定量地捕捉了单调趋氧性和对数感知。综上所述,这些结果为(微生物的)寻氧能力提供了新的见解,并为定量研究许多其他形式的微生物趋化性提供了蓝图。