Department of Mathematics, University of California Irvine, Irvine, California, United States of America.
PLoS One. 2013 Sep 3;8(9):e72847. doi: 10.1371/journal.pone.0072847. eCollection 2013.
Identifying the exact regulatory circuits that can stably maintain tissue homeostasis is critical for our basic understanding of multicellular organisms, and equally critical for identifying how tumors circumvent this regulation, thus providing targets for treatment. Despite great strides in the understanding of the molecular components of stem-cell regulation, the overall mechanisms orchestrating tissue homeostasis are still far from being understood. Typically, tissue contains the stem cells, transit amplifying cells, and terminally differentiated cells. Each of these cell types can potentially secrete regulatory factors and/or respond to factors secreted by other types. The feedback can be positive or negative in nature. This gives rise to a bewildering array of possible mechanisms that drive tissue regulation. In this paper, we propose a novel method of studying stem cell lineage regulation, and identify possible numbers, types, and directions of control loops that are compatible with stability, keep the variance low, and possess a certain degree of robustness. For example, there are exactly two minimal (two-loop) control networks that can regulate two-compartment (stem and differentiated cell) tissues, and 20 such networks in three-compartment tissues. If division and differentiation decisions are coupled, then there must be a negative control loop regulating divisions of stem cells (e.g. by means of contact inhibition). While this mechanism is associated with the highest robustness, there could be systems that maintain stability by means of positive divisions control, coupled with specific types of differentiation control. Some of the control mechanisms that we find have been proposed before, but most of them are new, and we describe evidence for their existence in data that have been previously published. By specifying the types of feedback interactions that can maintain homeostasis, our mathematical analysis can be used as a guide to experimentally zero in on the exact molecular mechanisms in specific tissues.
确定能够稳定维持组织内稳态的精确调控回路，对于我们深入理解多细胞生物具有重要意义，同样对于鉴定肿瘤如何规避这种调控以提供治疗靶点也至关重要。尽管在理解干细胞调控的分子组成方面取得了重大进展，但协调组织内稳态的总体机制仍远未被理解。通常，组织包含干细胞、过渡扩增细胞和终末分化细胞。这些细胞类型中的每一种都可能分泌调节因子，或对其他类型细胞分泌的因子做出反应。这种反馈可能是正反馈或负反馈。这就产生了一系列令人困惑的可能机制，这些机制推动了组织的调节。在本文中，我们提出了一种研究干细胞谱系调控的新方法，并确定了可能的数量、类型和控制回路的方向，这些回路与稳定性兼容，使方差保持较低水平，并具有一定的鲁棒性。例如，有两个精确的（两回路）控制网络可以调节两室（干细胞和分化细胞）组织，而在三室组织中有 20 个这样的网络。如果分裂和分化决策是耦合的，那么必须有一种负反馈回路来调节干细胞的分裂（例如通过接触抑制）。虽然这种机制与最高的鲁棒性相关，但也可能存在通过正分裂控制维持稳定性的系统，同时伴有特定类型的分化控制。我们发现的一些控制机制以前已经提出过，但大多数是新的，我们描述了在以前发表的数据中存在这些机制的证据。通过指定能够维持内稳态的反馈相互作用的类型，我们的数学分析可以作为指导，用于在特定组织中实验性地确定确切的分子机制。
