Kimchi's lab
Our project uses Programmed Cell Death as a model system to analyze the global structure/function of protein networks in human cells. In Programmed Cell Death, the network is being turned on by a well defined input signal (e.g., a cytokine, a drug causing DNA damage) and its performance determines the probability of a cell to enter into 'a point of no return' (the network's output). By working with large cell populations, changes in probabilities can be translated into numbers of viable/dead cells, and if the assay is sensitive enough, it should assess the network's performance with high accuracy. Over the last two decades many of the network's individual nodes (i.e., 150-200 proteins) have been identified and small portions of the static map were constructed by defining some of the inter-protein connections. The main challenge now is to provide a global functional view of the network, to try to model the process and ultimately simulate the output dynamics as a function of the input signal. Here we propose two major parallel approaches both introducing the functional insight into the network's study.
1. The first strategy which we name: Multiple Silencing Analysis (MSA) is based on measuring the effects of RNA interference on the network's final performance. To this end, a new method which measures the 'functional weight' of nodes within the network has been recently developed in our laboratory. This is being achieved by applying single and multiple silencing perturbations, at different combinations, using the RNA interference (RNAi) technology, and then measuring the impact of this silencing on the network's performance. The method is being scaled up to enable high throughput data collection with high degree of accuracy and sensitivity. The large amount of data which will be gathered by this combinatorial knock down experiments will be coupled to the development of new algorithms capable of computing the contribution of each node to the function in a precise and rigorous manner. Novel principles in the network's function, the basis of its robustness, as well as its possible dissection into modules with some degree of hierarchy between them, will be discovered.
2. In the second approach we will introduce the functional dimension into the proteomic dynamics approach which will be provided by the YFP-tagged H1299 cell libraries constructed by Uri Alon. To this end, we will combine the dynamic microscopic measures of protein levels and intracellular localization with the numeric data and the molecular analysis which will be achieved by the specific RNAi-mediated perturbations described in section 1 of the plan. A selected series of annotated cell lines which carry various YFP- labeled apoptotic genes will be exposed to different apoptotic stimuli and the outcome of the RNAi-mediated perturbations will be examined microscopically. Of note, the two main sections of this proposal are interconnected. The data sets emerging from the effects of various RNAi-mediated perturbations on the final network's output, on the one hand, and on the proteomic dynamics on the other hand, should accelerate the modeling and dissection of the apoptotic network.
Single and multiple silencing perturbations, in different combinations, RNAi is used to measure the impact of the silencing on the total cell death network's performance, and the inter-modular and intra-modular connections between proteins. A high-throughput quantitive system was developed in our lab to enable data collection with high degree of accuracy and sensitivity.
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