Cells are the basic units of life. They function by receiving signals from the outside and processing these signals to regulate cellular behavior. Signal processing is a complex process involving tens if not hundreds of cellular components (referred to as signaling intermediates) that must interact with each other to regulate cellular behavior. The amounts of such signaling intermediates inside each cell vary as a function of time after receiving a signal from the outside and as a function of their location in the cell. Jointly, these are referred to as spatiotemporal patterns. Spatiotemporal patterns are critical for understanding signaling efficiency in live cells, as enrichment of two proteins in the same location at the same time increases the likelihood that they will interact, i.e. their efficiency. Thus, an understanding of spatiotemporal pattering is essential if we are to unravel the complex interaction network of tens to hundreds of signaling intermediates, a great challenge in current biology. The goals of this project are: 1) To acquire comparative image data sets on many protein signaling intermediates under varying conditions of cellular activation and to develop and apply image analysis methods to accurately define the amount and location of the signaling intermediates within a cell (the T lymphocyte). In addition, these methods will be applied to define how the amount and location of these signaling intermediates vary with time as T cells respond to the different stimuli. 2) Because the data and methods that will be developed in this project will be of general interest and value for understanding cellular signaling, they will be made publicly available on servers. Other investigators will be given the opportunity to use these methods to analyze their image data. T cell microscopy experiments will be executed for collaborators, and the visual appeal of imaging data will be used to enrich high school education.
Broader impacts: In addition to providing the research community access to the resources and data that will be developed, this project will engage high school, graduate and medical students, as well as two postdoctoral fellows. Undergraduate students from around the US will be given opportunities to work on this project through the University of Texas Southwestern Summer Undergraduate Research Fellowship program (which places an emphasis on recruiting underrepresented minorities). Dr. Murphy will train and mentor minority students through a Research Experiences for Undergraduates program at Carnegie-Mellon University.
Scientific accomplishments: Cells are the basic units of life. They function by receiving signals from the outside and processing these signals to regulate cellular behavior. Signal processing is a complex process involving tens if not hundreds of cellular components (referred to as signaling intermediates) that must interact with each other to regulate cellular behavior. The amounts of such signaling intermediates at different location within each cell vary as a function of time after receiving a signal from the outside. Jointly, these are referred to as spatiotemporal patterns. Spatiotemporal patterns are critical for understanding signaling efficiency in live cells, as enrichment of two proteins in the same location at the same time increases the likelihood that they will interact, i.e. their efficiency. Thus, an understanding of spatiotemporal pattering is essential if we are to unravel the complex interaction network of tens to hundreds of signaling intermediates, a great challenge in current biology. We address this challenge by studying the activation of T lymphocytes (or T cells). Previous work across many laboratories has already identified a large number of signaling intermediates required for successful T cell activation, allowing us to focus on the localization of these signaling intermediates inside the T cell. T cells are also of substantial medical importance, allowing for potential future therapeutic applications of our work. The major accomplishments of the project are: 1) We have acquired comparative image data sets on up to 20 signaling intermediates under four conditions of T cell activation, T cells receiving a strong stimulus and three conditions of reduced stimulation. This constitutes thousands of time-lapse videos of individual T cells undergoing activation with representative examples e.g. accessible on our website cited below. The broad scope of our image data allowed for effective testing of computational image analysis methods to accurately define the amount of the signaling intermediates at different locations within a cell (the T lymphocyte) that were developed in a parallel project in the Murphy laboratory. Subsequently, we have applied these methods to the first two data sets allowing a comparison of how T cell signaling is organized inside a T cell in time and space in unprecedented detail. In parallel we have refined approaches to study how the localization of a signaling intermediate inside the T cell can be related to the execution of T cell effector functions. Using these approaches, the relevance of emerging differences in the localization of proteins as learned from our comparison of the large image data sets will be tested in the future. 2) Because the data and methods we developed in this project are of general interest and value for understanding cellular signaling, we made them widely available. Initial data are already accessible on a dedicated website (www.bristol.ac.uk/cellmolmed/infect-immune/wuelfing/). Upon completion of our first round of computational image analysis underlying data and analysis results will be made accessible through the servers of the Protein Subcellular Localization Image Database (PSLID, http://pslid.org). In addition, we have acquired and analyzed T cell imaging data for six outside collaborators thus providing them access to our unique imaging approaches and contributing to the progress of research projects across the scientific community. Broader impacts: In addition to providing the research community access to the resources, methods and data as discussed above, this project has engaged four undergraduate students (one from an underrepresented minority), one graduate student, and one postdoctoral fellow.
