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A Predictive Model for Yeast Cell Polarization in Pheromone Gradients

机译:信息素梯度中酵母细胞极化的预测模型。

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摘要

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.
机译:出芽酵母细胞以两种> a 和α的交配类型存在,它们在交配过程中使用肽信息素相互通讯。交配取决于细胞极化信息素梯度的能力,但细胞也会通过沿单个轴极化来响应空间均匀的信息素场。我们对> a 细胞对α因子的反应进行了定量测量,以生成酵母朝着信息素梯度极化的预测模型。我们发现细胞在萌芽周期和交配诱导的极化之间进行了急剧的转变,并且它们仅在对应于这种转变的信息素浓度的狭窄范围内准确地检测信息素梯度。我们通过使用均匀信息素浓度下的自发极化的定量数据来拟合数学模型的所有参数。一旦计算了这些参数,并且没有任何进一步的拟合,我们的模型就可以定量预测酵母细胞对信息素梯度的反应,为理解细胞之间如何通信提供了重要的一步。

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