Inferring Biological Mechanism from Mutational Interactions

智力价值：遗传学是研究生物特征如何从父母传给后代的学科。100多年来，人们一直认识到，由于生物学上的复杂性，突变效应可能会因发生突变的遗传背景而异。例如，想象一下下面的生化途径。在这里，一些化合物X被酶1(由一个基因编码)转化为化合物Y，然后Y被酶2(由另一个基因编码)转化为第三个化合物Z。在这种情况下，使酶2失活的突变也会使整个途径失活，即使在酶1起作用的生物体中也是如此。另一方面，同样的突变在酶1以前被灭活的生物体中不会产生任何影响。这种相互作用使问题变得复杂起来，既然在这些情况下突变的影响是上下文相关的，那么这种突变会做什么？但与此同时，这种相互作用为实验提供了机会，以剖析潜在的生物机制。在我们的简单例子中，观察到当酶1被灭活时，突变使酶2失活没有作用，这意味着酶2以某种共同的途径机械地作用于酶1的下游。这个项目使用两种理论方法来形式化这些直观的概念，一种是基于单个酶如何工作的定量模型，另一种是基于整个有机体新陈代谢的定量模型。这项工作将产生一个分析框架，将突变对分为通过共同机制起作用的突变和通过不同机制起作用的突变。此外，它还将提供对影响生物特征的不同机制的数量的估计。这项研究是非常及时的，因为最近的高通量基因组学技术创新正在产生关于几个微生物模型系统(E.Coli、S.cerevisiae和S.pombe)中突变相互作用的大量数据集，并且在多细胞模式生物中的类似数据集的前景也很好，例如D.Blackogaster和C.elegans。因此，这些实验性的创新为更复杂的机械分析打开了大门。关键是，对特定机制相互作用的直接实验攻击仍然昂贵得令人望而却步，进一步推动了目前的理论方法。这项工作也有望在生物组织的多个水平上做出贡献，从酶学到整个生物体的繁殖成功，再到生态和生物地球化学资源通量。这是因为单一酶的理论模型也可以应用于整个生物体，因为新陈代谢模型可以应用于任何化学通量网络。除了可以对生物机制作出推断外，突变相互作用还对一系列生物过程有理论上的影响，包括对适应、性别进化和物种形成的限制。PI在其中几个领域有活跃的研究计划，因此这项研究直接补充了他正在进行的工作。此外，该项目还直接支持培养一名数学和生物学相结合的研究生，以发展在这个基因组和后基因组时代所必需的专业知识。计划在每个学期和暑假期间，让一些本科生在PIS实验室从事研究工作。PI还一直致力于通过现有的NSF资助的GK-12计划，让普罗维登斯公立学校的学生和教师进行智力参与。这项外展工作解决了目前在美国理解遗传学和进化思维的影响的文化障碍。

Intellectual Merit: Genetics is the study of how biological traits are transmitted from parents to offspring. For over 100 years it has been appreciated that owing to biological complexities, a mutations effect may vary with the genetic background in which it occurs. For example, imagine the following biochemical pathway. Here some compound X is converted by Enzyme 1 (coded by one gene) into compound Y and then Y is converted by Enzyme 2 (coded by another gene) into a third compound Z. In this case, a mutation that inactivates Enzyme 2 also inactivates the entire pathway, even in an organism in which Enzyme 1 is functional. On the other hand, the same mutation would have no effect in an organism in which Enzyme 1 was previously inactivated. Such interactions complicate the question, what does this mutation do since the effects of mutations in these cases are context-dependent? But at the same time, such interactions provide opportunities for experimentation to dissect underlying biological mechanisms. In our simple example, the observation that mutations inactivating Enzyme 2 have no effect when Enzyme 1 has been inactivated implies that Enzyme 2 mechanistically acts downstream of Enzyme 1 in some common pathway. This project formalizes these intuitive notions using two theoretical approaches, one based on a quantitative model of how single enzymes operate and the other based on a quantitative model of whole-organism metabolism. This work will yield an analytic framework to sort pairs of mutations into those that act by a shared mechanism and those that act by distinct mechanisms. In addition it will provide an estimate of the number of distinct mechanisms influencing a biological trait. This research is extremely timely because recent high-throughput technical innovations in genomics are yielding vast datasets on mutational interactions in several microbial model systems (E. coli, S. cerevisiae and S. pombe), and prospects are good for similar datasets in multicellular model organisms such as D. melanogaster and C. elegans. These experimental innovations thus open the door to far more sophisticated mechanistic analyses. Critically, direct experimental attack on specific mechanistic interactions remains prohibitively expensive, further motivating the present theoretical approach. This work also promises to make contributions at several levels of biological organization, from enzymatics to whole organism reproductive success to ecological and biogeochemical resource fluxes. This follows because the theoretical model of single enzymes can also be applied to whole organisms, and because the model of metabolism can be applied to any network of chemical fluxes.Broader Impacts. Beyond allowing inferences to be made regarding biological mechanisms, mutational interactions have theoretical implications for a diversity of biological processes, including constraints on adaptation, the evolution of sex and speciation. The PI has active research programs in several of these areas and so this research directly complements his ongoing work. Moreover this project directly supports the training of a graduate student at the interface of mathematics and biology, to develop expertise essential in this genomic and post-genomic era. Spin-off projects are planned to engage a number of undergraduate students in research working in the PIs laboratory each term and during the summer. The PI also has an ongoing commitment to the intellectual engagement of Providence public school students and teachers through an existing NSF-funded GK-12 program. This outreach work addresses current cultural barriers to understanding genetics and the implications of evolutionary thinking in the United States.