A novel and simple mechanism by which cells can sense enzymatic flux

项目摘要 新陈代谢是一个严格控制的复杂过程，在这个过程中，不同的营养物质被吸收和加工 以满足不同的需求。吸收和加工的调节需要许多营养物质和代谢物 被感知到了这提出了一个挑战，因为一些被感测的分子同时 进行处理。这导致人们怀疑代谢途径可能直接感受到通过 该途径，而不是仅感测营养物或代谢物的浓度。最近的研究证实 这是通过识别细菌中的通量传感系统来实现的，尽管所使用的机制很复杂， 翻译到其他系统。在酵母菌半乳糖利用途径的初步研究中， 酿酒酵母，我们已经确定了一种新的推定机制，连接酶活性的信号， 提供了一种测量代谢通量的简单方法。因为这个机制很简单，我们怀疑它 可能发生在许多途径中。我们现在建议详细研究这个假设的机制。的GAL 通道是一个理想的系统，在其中识别和机械表征通量感测。这是一个经典的模式 真核生物中的信号系统，我们有广泛的方法和遗传工具可用。系统性高- 吞吐量定量测量将用于开发和完善计算模型， 将用于指导和解释实验，并深入了解通量的生理作用， 浓度传感器。我们从GAL途径获得的见解将简化通量的发现 其他途径的传感器。接下来，我们将带来我们开发的用于表征GAL信号传导的工具和模型 对负责代谢的途径中的传感器模态进行识别和表征 S.啤酒。基于文献的发现，我们怀疑这条通路也包含一个通量传感器。 我们预计，在这些途径中识别通量传感器将立即提供对潜在的洞察力 用于人体代谢途径中的通量传感，并导致有前途的新治疗靶点的鉴定。

Project Summary Metabolism is a tightly controlled and complex process in which different nutrients are taken up and processed to meet variable needs. The regulation of uptake and processing requires that many nutrients and metabolites are sensed. This poses a challenge since some of the molecules that are being sensed are simultaneously subject to processing. This has led to the suspicion that metabolic pathways may directly sense the flux through the pathway, instead of sensing only the concentration of nutrients or metabolites. Recent work has confirmed this by identifying a flux-sensing system in bacteria, although the mechanism used is complex and may not translate to other systems. In preliminary work on the galactose utilization (GAL) pathway of Saccharomyces cerevisiae, we have identified a novel putative mechanism for connecting enzymatic activity to signaling, providing a simple way for metabolic flux to be measured. Because this mechanism is simple, we suspect that it may occur in many pathways. We now propose to investigate this hypothetical mechanism in detail. The GAL pathway is an ideal system in which to identify and mechanistically characterize flux sensing. It is a classic model system for signaling in eukaryotes, and we have extensive methods and genetic tools available. Systematic high- throughput quantitative measurements will be used to develop and refine computational models, which in turn will be used to both guide and interpret experiments and to give insight into the physiological role of both flux and concentration sensors. The insights we gain from the GAL pathway will then simplify the discovery of flux sensors in other pathways. Next, we will bring the tools and models we develop to characterize GAL signaling to bear on identifying and characterizing the sensor modalities in the pathway responsible for metabolizing nitrogen in S. cerevisiae. Based on literature findings, we suspect that this pathway also contains a flux sensor. We anticipate that identifying flux sensors in these pathways will immediately provide insight into the potential for flux sensing in human metabolic pathways, and lead to the identification of promising new therapeutic targets.