Tasseff Ryan, Bheda-Malge Anjali, DiColandrea Teresa, Bascom Charles C, Isfort Robert J, Gelinas Richard
Institute for Systems Biology, Seattle, Washington, United States of America.
Procter and Gamble, Mason, Ohio, United States of America.
PLoS Comput Biol. 2014 Nov 6;10(11):e1003914. doi: 10.1371/journal.pcbi.1003914. eCollection 2014 Nov.
The hair cycle is a dynamic process where follicles repeatedly move through phases of growth, retraction, and relative quiescence. This process is an example of temporal and spatial biological complexity. Understanding of the hair cycle and its regulation would shed light on many other complex systems relevant to biological and medical research. Currently, a systematic characterization of gene expression and summarization within the context of a mathematical model is not yet available. Given the cyclic nature of the hair cycle, we felt it was important to consider a subset of genes with periodic expression. To this end, we combined several mathematical approaches with high-throughput, whole mouse skin, mRNA expression data to characterize aspects of the dynamics and the possible cell populations corresponding to potentially periodic patterns. In particular two gene clusters, demonstrating properties of out-of-phase synchronized expression, were identified. A mean field, phase coupled oscillator model was shown to quantitatively recapitulate the synchronization observed in the data. Furthermore, we found only one configuration of positive-negative coupling to be dynamically stable, which provided insight on general features of the regulation. Subsequent bifurcation analysis was able to identify and describe alternate states based on perturbation of system parameters. A 2-population mixture model and cell type enrichment was used to associate the two gene clusters to features of background mesenchymal populations and rapidly expanding follicular epithelial cells. Distinct timing and localization of expression was also shown by RNA and protein imaging for representative genes. Taken together, the evidence suggests that synchronization between expanding epithelial and background mesenchymal cells may be maintained, in part, by inhibitory regulation, and potential mediators of this regulation were identified. Furthermore, the model suggests that impairing this negative regulation will drive a bifurcation which may represent transition into a pathological state such as hair miniaturization.
毛发周期是一个动态过程,毛囊会反复经历生长、收缩和相对静止阶段。这个过程是时间和空间生物学复杂性的一个例子。对毛发周期及其调节的理解将有助于阐明许多与生物学和医学研究相关的其他复杂系统。目前,尚未有在数学模型背景下对基因表达进行系统表征和总结的研究。鉴于毛发周期的周期性本质,我们认为考虑具有周期性表达的基因子集很重要。为此,我们将几种数学方法与高通量全小鼠皮肤mRNA表达数据相结合,以表征动力学方面以及与潜在周期性模式相对应的可能细胞群体。特别地,我们鉴定出了两个表现出异相同步表达特性的基因簇。一个平均场相位耦合振荡器模型被证明能够定量地重现数据中观察到的同步现象。此外,我们发现只有一种正负耦合配置是动态稳定的,这为调节的一般特征提供了见解。随后的分岔分析能够基于系统参数的扰动识别和描述交替状态。一个双群体混合模型和细胞类型富集分析被用于将这两个基因簇与背景间充质群体和快速扩张的毛囊上皮细胞的特征联系起来。RNA和蛋白质成像也显示了代表性基因独特的表达时间和定位。综合来看,这些证据表明,扩张的上皮细胞和背景间充质细胞之间的同步可能部分通过抑制调节来维持,并且确定了这种调节的潜在介质。此外,该模型表明,破坏这种负调节将导致分岔,这可能代表向诸如毛发小型化等病理状态的转变。