Muller Nicolas, Piel Matthieu, Calvez Vincent, Voituriez Raphaël, Gonçalves-Sá Joana, Guo Chin-Lin, Jiang Xingyu, Murray Andrew, Meunier Nicolas
MAP5, CNRS UMR 8145, Université Paris Descartes, Paris, France.
Institut Curie, CNRS UMR 144, Paris, France.
PLoS Comput Biol. 2016 Apr 14;12(4):e1004795. doi: 10.1371/journal.pcbi.1004795. eCollection 2016 Apr.
Budding yeast cells exist in two mating types, a and α, which use peptide pheromones to communicate with each other during mating. Mating depends on the ability of cells to polarize up pheromone gradients, but cells also respond to spatially uniform fields of pheromone by polarizing along a single axis. We used quantitative measurements of the response of a cells to α-factor to produce a predictive model of yeast polarization towards a pheromone gradient. We found that cells make a sharp transition between budding cycles and mating induced polarization and that they detect pheromone gradients accurately only over a narrow range of pheromone concentrations corresponding to this transition. We fit all the parameters of the mathematical model by using quantitative data on spontaneous polarization in uniform pheromone concentration. Once these parameters have been computed, and without any further fit, our model quantitatively predicts the yeast cell response to pheromone gradient providing an important step toward understanding how cells communicate with each other.
出芽酵母细胞存在两种交配类型,a型和α型,它们在交配过程中使用肽类信息素来相互交流。交配取决于细胞沿信息素梯度极化的能力,但细胞也会通过沿单一轴极化来响应空间均匀的信息素场。我们对a型细胞对α因子的反应进行了定量测量,以建立酵母向信息素梯度极化的预测模型。我们发现,细胞在出芽周期和交配诱导的极化之间会发生急剧转变,并且它们仅在对应于这种转变的狭窄信息素浓度范围内才能准确检测到信息素梯度。我们通过使用关于均匀信息素浓度下自发极化的定量数据来拟合数学模型的所有参数。一旦计算出这些参数,且无需进一步拟合,我们的模型就能定量预测酵母细胞对信息素梯度的反应,这为理解细胞如何相互交流迈出了重要一步。