Bilateral NSF/BIO-BBSRC - Linking Cell Growth with Proliferation in the Plant Root Meristem

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The goal of this collaborative US/UK project that engages researchers at the University of Tennessee and the University of London is to better understand how plants coordinate the biosynthesis (production) of proteins with cell division as they grow. This is important because plants must carefully integrate information about available nutrients and their energy supply before deciding whether or not to invest limited resources into growth and the irreversible production of new cells. The work will lead to insights into the physiological and molecular processes that underpin the agricultural productivity of crop plants and will help to optimize plant function and crop productivity by genetic improvement. The project will develop the scientific workforce by training postdoctoral scientists, PhD students, as well as affiliated junior investigators with advanced multi-disciplinary skills at the interface of experimental and computational systems biology, skills that are highly portable in the academic and industrial sectors of the life sciences. Outreach to the general public will also be performed, in collaboration with an artist that uses plant life-related themes in her installations.Protein synthesis (translation) is a major sink for the carbon and nitrogen compounds that, once assimilated through photosynthesis, drive cell growth and proliferation. The project seeks to decipher how protein synthesis-driven cell growth is connected to cell proliferation in meristematic plant cells, using the root tip of the plant reference species Arabidopsis as an experimental system. An underlying hypothesis that shall be tested is that growth regulatory signaling pathways coordinate both the cell cycle and protein synthesis in response to growth stimulating signals. To this end, cell biological markers of cell proliferation will be imaged over time in strains harboring genetic lesions in key signaling pathways. Data on translational efficiency will be collected using genome-wide techniques in order to identify the targets of translational regulation in actively growing tissues. Translation data will be fitted to an emergent computational model of mRNA translation in order to derive biochemical parameters of translation such as the initiation rate. Finally, a network model will integrate new and published data to predict cell cycle transitions in response to the signals that drive cell proliferation and translation. The project is a collaboration between two experimental labs, who have complementary expertise in the regulatory processes that underpin cell division and protein translation. The two teams are joined by two computational investigators, who likewise contribute complementary expertise in machine learning, statistical modeling, pattern recognition and dynamic modeling using deterministic and probabilistic algorithms. This collaborative US/UK project is supported by the US National Science Foundation and the UK Biotechnology and Biological Sciences Research Council.