Investigating Regulatory Networks that Control Cell Proliferation and Apoptosis

研究控制细胞增殖和凋亡的调控网络

• 批准号: 7965093
• 负责人: KURT KOHN
• 金额: $ 53.76万
• 依托单位: DIVISION OF BASIC SCIENCES - NCI
• 依托单位国家: 美国
• 资助国家: 美国
• 起止时间: 至
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/7965093
• 关键词: Affect; Antineoplastic Agents; Apoptosis; Behavior; Binding; Bioinformatics; Biotechnology; Cell Culture System; Cell Cycle; Cell Cycle Checkpoint; Cell Death; Cell Nucleus; Cell Proliferation; Cell division; Cell physiology; Cells; Chromatin; Clinic; Collaborations; Commit; Complex; Computer Architectures; Computer Assisted; Computer Simulation; Computers; Conceptual Entity; Crowding; DNA; DNA Damage; DNA Repair; DNA replication fork; Databases; Defect; Destinations; Development; Discipline; Electronics; Epigenetic Process; Event; Feedback; Future; Gap Junctions; Gene Mutation; Gene Proteins; Generations; Genes; Genomics; Goals; Human; Individual; International; Internet; Journals; Kinetics; Laboratories; Language; Lesion; Link; Literature; Logic; Malignant Neoplasms; Maps; Mediating; Meleagris gallopavo; Modeling; Molecular; Molecular Models; Mutate; Nature; Nucleosomes; Online Systems; Pathway interactions; Patients; Pattern; Play; Post-Translational Protein Processing; Procedures; Process; Production; Protein p53; Publications; Publishing; Regulation; Reporting; Research Personnel; Role; Scientist; Signal Transduction; Simulate; Source; Stress; Structure; Surveys; System; Systems Biology; TP53 gene; Testing; Time; Turkey bird; Universities; Update; Ursidae Family; Work; cancer cell; cancer therapy; cell behavior; combinatorial; design; information display; interest; member; molecular modeling; network models; novel; novel therapeutics; prevent; research study; response; tool; transcription factor; tumor; web site

An enormous amount of information has accumulated about the molecular components that govern the cell division cycle and apoptosis, information that is crucial to the development of new anti-cancer therapies. However, the relevant molecular interaction networks are so complicated that it is often difficult to understand how they function. Comprehensive network diagrams, using a standardized notation, therefore are essential in the same way that circuit diagrams are essential in electronics. Diagramming bioregulatory networks however presents a major challenge, because of the large role played by multimolecular complexes and protein modifications. Several years ago, we devised a notation for molecular interaction maps (MIM) that many in the field think is the best way to represent network functions and interaction details. We have used MIMs in many publications and examples have been prominently displayed in journal issues (such as being featured on the cover). To generate a MIM, one has to adhere to formal MIM notation rules (described in Kohn et al Mol. Biol. Cell 17:1-13, 2006); this requirement imposes a useful discipline of logic that enforces clear understanding of the available information about a network's structure. The MIM notation has important advantages over other proposed notations and has the unique ability to represent combinatorial complexity in molecular interaction networks (Kohn et al Mol. Systems Biol. doi:10.1038/msb4100088, 2006). In order to make MIMs conveniently accessible, we post them on the internet with links to annotations, references, and to other databases (http://discover.nci.nih.gov/mim/). Recently, we showed for the first time how MIMs can represent network events at the DNA and chromatin levels. We prepared a MIM describing the network involved in nucleosome disassembly in front of a DNA replication fork, assembly behind the replication fork, and the copying of epigenetic information onto the replicated chromatin. We used this MIM in a comprehensive review of the molecular interactions taking place during these events, thereby showing the advantages of systematizing information in this way (Kohn et al Mol. Biol. Cell 19:1-7, 2008). We have now extended that work to show how MIMs can be more informative and easier to interpret by means of a hierarchical representation. We applied that hierarchical procedure to map signaling from stalled replication forks to the controllers of cell cycle checkpoints and trans-lesion DNA repair synthesis. That work was recently published (Kohn et al. Cell Cycle 8:14, 2281-2299; 15 July 2009). Stalled replication forks signal by way of a complex network of molecular interactions. To clarify those complexities, we designed a novel hierarchical assembly procedure in which the molecular components of the network are mapped at hierarchical levels according to interaction step distance from the DNA region of stalled replication. The hierarchical MIM allowed us to disentangle the networks interlocking pathways and loops and to suggest functionally significant features of network architecture. The MIM shows how parallel pathways and multiple feedback loops can provide failsafe and robust switch-like responses to replication stress. Within the central level of hierarchy ATR and Claspin together appear to function as a nexus that conveys signals from many sources to many destinations. We noted a division of labor between those two molecules that separates enzymatic and structural roles. In addition, the network architecture disclosed by the hierarchical map suggested a model for how molecular crowding and the granular localization of network components in the cell nucleus can facilitate function. This work was recently published (Kohn et al. Cell Cycle 8:14, 2281-2299; 15 July 2009). Currently we are developing new and updated MIMs of the complex and intricate signaling systems that determine whether and when cells commit to replication, either during the cell cycle or from quiescence, as well as the signaling connections of those systems to DNA repair processes and the checkpoint responses to DNA damage. A key component of the DNA damage response system is the p53 tumor suppressor, a commonly mutated gene in human cancer. In response to DNA damage or uncontrolled proliferation signals from cancer cells, p53 arrests the progress cells through the cell cycle or causes cells to die by apoptosis. Those responses are governed in large part by the activity of p53 as a transcription factor, controlled through interactions with Mdm2 and MdmX. Although the action of Mdm2 on the control of p53 is well understood, the role of Mdmx on this control network is not. We therefore assembled an updated MIM of the interactions that comprise the p53 control network. From that MIM, we extracted for computer simulation an explicit model network that we thought could be the core of the control system involving both Mdm2 and MdmX. Continuing our work during the previous report period, we carried out computer simulations, in which we surveyed the kinetic parameter space for the possible DNA damage-induced p53 response patterns. The results further support our inference that MdmX may amplify or stabilize DNA damage-induced p53 responses and that the effects of MdmX are mediated by accumulated reservoirs of p53:MdmX and Mdm2:MdmX heterodimers. Regions of oscillatory and switch-like responses were mapped to the kinetic parameter space. Of particular interest was the ability of MdmX to dampen or prevent oscillations. A possible role of MdmX therefore may be to prevent uncontrolled oscillations that could produce erratic cell behavior or unnecessary cell death. The mathematical aspects of this work are assisted by collaboration with Dr. Geoffrey McFadden of NIST. We are conducting experiments to look for such effects in cell culture systems. We are collaborating with an international consortium of researchers to develop systems biology gaphics notations (SBGN) that may a serve as a standard. The SBGN effort was recently summarized by Le Novere et al (38 co-authors, including M. I. Aladjem and K. W. Kohn from our Laboratory) in Nature Biotechnology 27, 735 - 741 (2009). SBGN includes MIM-like entity-relationship diagrams, a formal description of which can be accessed on line at http://www.sbgn.org/Documents/Specifications, under the sections entitled Entity Relationship language. Our LMP group is independently developing computer facilities specific to MIMs, which, for technical reasons, differs in some respects from SBGNs entity-relationship language. SBGNs language may be more amenable to some computer application and integration with other parts of SBGN. Our MIM notation however seems better suited for depicting network functions for biologists. We are therefore developing a formal computer-readable structure specifically for MIM, while allowing for future compatibility with the SBGN language. In that development, we collaborate with members of the Genomics and Bioinformatics group in our Laboratory, and with Dr. Ruth Nussinov at NCI/Frederick and her computer scientist associates at Bogazici University in Turkey.

关于控制细胞分裂周期和细胞凋亡的分子成分的大量信息已经积累起来，这些信息对开发新的抗癌疗法至关重要。然而，相关的分子相互作用网络是如此复杂，以至于很难理解它们是如何起作用的。因此，使用标准化符号的综合网络图就像电路图在电子学中必不可少一样，是必不可少的。然而，由于多分子复合物和蛋白质修饰所起的重要作用，绘制生物调节网络的图表提出了一个重大挑战。几年前，我们为分子相互作用图（MIM）设计了一种符号，许多业内人士认为这是表示网络功能和相互作用细节的最佳方式。我们已经在许多出版物中使用了mim，并且已经在期刊中突出展示了一些例子（例如在封面上出现）。要生成MIM，必须遵守正式的MIM符号规则（在Kohn等人Mol. Biol中描述）。Cell 17:1-13, 2006)；这个要求强加了一个有用的逻辑规则，强制对有关网络结构的可用信息有清晰的理解。与其他提出的符号相比，MIM符号具有重要的优势，并且具有表示分子相互作用网络中组合复杂性的独特能力（Kohn等人Mol. Systems Biol.）。doi: 10.1038 / msb4100088, 2006)。为了方便地访问mim，我们将它们发布在互联网上，并附有注释、参考文献和其他数据库的链接（http://discover.nci.nih.gov/mim/）。最近，我们首次展示了MIMs如何在DNA和染色质水平上代表网络事件。我们制备了一个MIM，描述了DNA复制叉前核小体拆卸、复制叉后组装以及表观遗传信息复制到复制的染色质上所涉及的网络。我们使用该MIM对这些事件中发生的分子相互作用进行了全面回顾，从而显示了以这种方式将信息系统化的优势（Kohn等人Mol. Biol）。细胞19:1- 7,2008)。我们现在已经扩展了这项工作，以展示如何通过分层表示来提供更多信息并更容易解释MIMs。我们应用该分级程序将信号从停滞的复制分叉映射到细胞周期检查点和跨损伤DNA修复合成的控制器。这项工作最近发表（Kohn等人）。细胞周期8:14,2281-2299；二零零九年七月十五日)。停滞的复制通过复杂的分子相互作用网络分叉信号。为了澄清这些复杂性，我们设计了一种新的分层组装程序，其中网络的分子成分根据与DNA区域的相互作用步距在分层水平上进行映射。分层的MIM使我们能够解开网络互锁的路径和循环，并提出网络架构的功能显著特征。MIM展示了并行路径和多个反馈回路如何为复制压力提供故障安全和健壮的类似开关的响应。在层次结构的中心层面，ATR和Claspin一起作为一个纽带，将信号从许多来源传递到许多目的地。我们注意到这两个分子之间的分工，分离酶和结构的作用。此外，分层图揭示的网络结构为细胞核中分子拥挤和网络组件的颗粒定位如何促进功能提供了一个模型。这项工作最近发表（Kohn et al.）。细胞周期8:14,2281-2299；二零零九年七月十五日)。目前，我们正在开发新的和更新的复杂和复杂的信号系统的mim，这些信号系统决定细胞是否以及何时在细胞周期中或从静止状态进行复制，以及这些系统与DNA修复过程的信号连接和DNA损伤的检查点反应。DNA损伤反应系统的一个关键组成部分是p53肿瘤抑制因子，这是人类癌症中一种常见的突变基因。在对DNA损伤或来自癌细胞的不受控制的增殖信号作出反应时，p53会阻止细胞在细胞周期中的进展或导致细胞凋亡死亡。这些反应在很大程度上是由p53作为一种转录因子的活性控制的，通过与Mdm2和MdmX的相互作用来控制。虽然Mdm2对p53的控制作用已被充分了解，但Mdmx在该控制网络中的作用尚不清楚。因此，我们组装了包含p53控制网络的相互作用的更新MIM。从该MIM中，我们为计算机模拟提取了一个明确的模型网络，我们认为它可能是涉及Mdm2和MdmX的控制系统的核心。继续我们在上一个报告期间的工作，我们进行了计算机模拟，其中我们调查了可能的DNA损伤诱导的p53反应模式的动力学参数空间。这些结果进一步支持了我们的推断，即MdmX可能会放大或稳定DNA损伤诱导的p53反应，MdmX的作用是由p53:MdmX和Mdm2:MdmX异源二聚体的蓄积库介导的。振荡和开关响应的区域被映射到动力学参数空间。特别令人感兴趣的是MdmX抑制或防止振荡的能力。因此，MdmX的一个可能作用可能是防止可能产生不稳定细胞行为或不必要的细胞死亡的不受控制的振荡。这项工作的数学方面得到了NIST的Geoffrey McFadden博士的协助。我们正在进行实验，在细胞培养系统中寻找这种效应。我们正在与一个国际研究联盟合作，开发可以作为标准的系统生物学图形符号（SBGN）。最近，Le Novere等人（38位共同作者，包括我们实验室的M. I. Aladjem和K. W. Kohn）在《自然生物技术》27,735 - 741（2009）上总结了SBGN的工作。SBGN包括类似mimm的实体关系图，其正式描述可以在http://www.sbgn.org/Documents/Specifications上在线访问，在标题为实体关系语言的部分下。我们的LMP小组正在独立开发针对MIMs的计算机设施，由于技术原因，这些设施在某些方面与sbgn的实体关系语言不同。SBGN语言可能更适合于某些计算机应用程序和与SBGN其他部分的集成。然而，我们的MIM符号似乎更适合描述生物学家的网络功能。因此，我们正在专门为MIM开发一种正式的计算机可读结构，同时允许将来与SBGN语言兼容。在这一发展过程中，我们与我们实验室基因组学和生物信息学小组的成员，以及NCI/Frederick的Ruth Nussinov博士和她在土耳其Bogazici大学的计算机科学家同事合作。