Center for Cell Dynamics, University of Washington, 620 University Road, Friday Harbor, WA 98250, USA.
Curr Biol. 2011 Apr 12;21(7):527-38. doi: 10.1016/j.cub.2011.02.040. Epub 2011 Mar 31.
Biological networks experience quantitative change in response to environmental and evolutionary variation. Computational modeling allows exploration of network parameter space corresponding to such variations. The intercellular signaling network underlying Caenorhabditis vulval development specifies three fates in a row of six precursor cells, yielding a quasi-invariant 3°3°2°1°2°3° cell fate pattern. Two seemingly conflicting verbal models of vulval precursor cell fate specification have been proposed: sequential induction by the EGF-MAP kinase and Notch pathways, or morphogen-based induction by the former.
To study the mechanistic and evolutionary system properties of this network, we combine experimental studies with computational modeling, using a model that keeps the network architecture constant but varies parameters. We first show that the Delta autocrine loop can play an essential role in 2° fate specification. With this autocrine loop, the same network topology can be quantitatively tuned to use in the six-cell-row morphogen-based or sequential patterning mechanisms, which may act singly, cooperatively, or redundantly. Moreover, different quantitative tunings of this same network can explain vulval patterning observed experimentally in C. elegans, C. briggsae, C. remanei, and C. brenneri. We experimentally validate model predictions, such as interspecific differences in isolated vulval precursor cell behavior and in spatial regulation of Notch activity.
Our study illustrates how quantitative variation in the same network comprises developmental patterning modes that were previously considered qualitatively distinct and also accounts for evolution among closely related species.
生物网络会针对环境和进化变化发生定量改变。计算模型可用于探索对应于这些变化的网络参数空间。线虫腹侧发育的细胞间信号网络在一排六个前体细胞中指定了三个命运,产生了近乎不变的 3°3°2°1°2°3°细胞命运模式。两种看似相互矛盾的线虫腹侧前体细胞命运指定的口头模型已经被提出:EGF-MAP 激酶和 Notch 途径的顺序诱导,或者以前者为基础的形态发生素诱导。
为了研究这个网络的机制和进化系统特性,我们将实验研究与计算模型相结合,使用一个保持网络架构不变但改变参数的模型。我们首先表明,Delta 自分泌环可以在 2°命运指定中发挥重要作用。有了这个自分泌环,相同的网络拓扑结构可以进行定量调整,以用于六细胞行形态发生素基础或顺序模式形成机制,这些机制可能单独、合作或冗余地发挥作用。此外,相同网络的不同定量调整可以解释在秀丽隐杆线虫、C. briggsae、C. remanei 和 C. brenneri 中观察到的实验性腹侧模式形成。我们实验验证了模型预测,例如孤立的腹侧前体细胞行为和 Notch 活性的空间调节的种间差异。
我们的研究说明了相同网络中的定量变化如何包含以前被认为是定性不同的发育模式,并且还解释了密切相关物种之间的进化。