Characterizing long-range propagation of injury information during regeneration

项目总结/摘要 有些动物在受损后可以再生复杂的器官或附属物。在以下方面取得了重大进展： 干细胞分化的分子生物学，这有助于解释新的细胞结构单元的起源， 组织.然而，关于新的增长如何与身体的其他部分协调， 大小、形状和位置，以及整个系统如何知道缺少什么以及何时完成（以便它可以停止 增殖和重塑）。该项目利用了高度再生和易于处理的模型系统- 日本三角涡虫-这是一个原则的证明，修复复杂的大脑，周围神经系统， 肌肉和内脏是可能的最近在真涡虫再生方面的大多数进展都集中在伤口，新生长， 和干细胞库。然而，莱文实验室在青蛙腿再生和大脑修复方面的工作，以及其他在 小鼠的研究表明，存在长距离信号，让健康组织知道已经发生了损伤， 确实腐败例如，当青蛙的腿被截肢时，另一侧（未受影响的）腿的细胞表现出戏剧性的生物电 在与另一条腿中发生的截肢平面相同的位置处进行去极化。同样，当青蛙的四肢 在截肢和治疗后，大脑改变基因表达谱，这些基因表达谱根据所应用的治疗而不同。 这些数据表明，有关解剖缺陷的重要信息可能会传播到其他器官， 协调系统一级的综合反应。他们还提出了将这些知识转化为生物医学的可能性 作为替代部位诊断和治疗离患者困难部位一定距离处的细胞的技术 (as已经在宿主实验室的大脑修复和癌症正常化的青蛙模型中显示）。然而，这种远程 再生期间的信号的特征非常差。在这里，我建议使用涡虫模型1）发现一个可靠的 长距离损伤信息的分子标记，以及2）构建和测试如何 信息传播。具体来说，我将使用候选方法和无偏见的转录组学方法来询问 当扁形虫的尾部被切断时，扁形虫头部的基因被上调/下调，反之亦然。使用减材 分析，我们将寻找转录本，特别是揭示了蠕虫的一端已经检测到什么是失踪的， 其他.我将把这些知识纳入现有的神经和非神经生物电信号的工作， 分子遗传级联，在构成主义生物物理模型的涡虫远程信号。这一模式将 然后，我将验证这些预测并改进模型。这项工作将使 我想用新的计算和生物物理方法来增强我的分子生物学背景， 在追求远程诊断和生物医学背景下的功能修复信号的独立职业生涯。

Project Summary/Abstract Some animals can regenerate complex organs or appendages after damage. Significant progress has been made on the molecular biology of stem cell differentiation, which helps explain the origin of the cellular building blocks of new tissue. However, major knowledge gaps remain about how new growth is coordinated with the rest of the body with respect to size, shape, and location, and how the whole system knows what's missing and when it is complete (so that it can stop proliferation and remodeling). This project takes advantage of the highly regenerative and tractable model system – the planarian Dugesia japonica – which serves as a proof of principle that repair of complex brains, peripheral nervous systems, muscle, and gut is possible. Most of the recent advances in planarian regeneration have focused on the wound, new growth, and stem cell pool. However, work in the Levin lab on frog leg regeneration and brain repair, and other groups working in mice, have suggested the presence of long-range signals that let healthy tissue know that damage has occurred and what it was. For example, when a frog leg is amputated, cells in the opposite side (untouched) leg exhibit a dramatic bioelectric depolarization at the same location as the amputation plane that occurred in the other leg. Similarly, when a frog limb is amputated and treated, the brain changes gene expression profiles that are different depending on the treatment applied. These kinds of data suggest that important information about anatomical defects may propagate to other organs and help coordinate system-level integrated responses. They also raise the possibility of translating this knowledge to biomedicine as techniques for surrogate site diagnostics and treatments of cells at some distance from a difficult location in the patient (as has been shown in the frog model for brain repair and cancer normalization by the host lab). However, such long-range signals during regeneration are very poorly characterized. Here, I propose to use the planarian model to 1) discover a reliable molecular marker of long-range damage information, and 2) construct and test a quantitative, biophysical model of how the information propagates. Specifically, I will use a candidate approach and an unbiased transcriptomic approach to ask which genes are up/down-regulated in the head of the flatworm when the tail is amputated, and vice-versa. Using subtractive analysis, we will look for transcripts that specifically reveal that one end of the worm has detected what is missing at the other. I will incorporate this knowledge into the existing body of work on neural and non-neural bioelectric signaling, and molecular-genetic cascades, in a constructivist biophysical model of planarian long-range signaling. This model will be analyzed for specific predictions, and I will then validate those predictions and improve the model. This work will allow me to augment my background of molecular biology with novel computational and biophysical approaches and set me up for an independent career in pursuing long-range diagnostics and functional repair signals in biomedical contexts.