Top and Middle Down of p53 Modification Codes

Over the past year, we have been pursuing p53 in collaboration with this dual PI team at Harvard Medical School. This DBP seeks to build on this foundation. This well-known transcription factor and tumor suppressor is often described as the “guardian of the genome” [9] and many cancers subvert its protective functions, either by direct mutation or by dysregulation of its supporting network. p53 has emerged as a pleiotropic cellular hub, which responds to a variety of physiological conditions to orchestrate a variety of cellular responses, including cell-cycle arrest, DNA repair, apoptosis, autophagy, senescence, metabolic regulation and development [10-13]. It is post-translationally modified at over 100 sites by a veritable zoo of modifications [14-16]. The effects of these PTMs are heterogeneous and context dependent [11] . The classical model of p53 regulation has been revised to suggest that this complex functionality may be implemented by a PTM “code”, in which distinct patterns of modification across the whole protein elicit distinct responses [17-18]. Although correlations between patterns and responses have been observed, causality has not been established. Does such a code exist in a causal sense? If so, how is it maintained and regulated?


The experimental and mathematical foundations that have been laid in previous work from the Gunawardena Lab provide a starting point from which to address such questions in the context of p53. By taking on such a challenging exemplar, we will learn a great deal about p53 itself; our findings will also establish concepts and technologies by which other PTM-dependent cellular proteins can be studied. This project has 4 main aspects: (1) We bring together an inter-disciplinary group with expertise in mathematics, cell biology and mass-spectrometry to study how cellular information is processed by PTMs. (2) We introduce new concepts – “mod-form”, “mod-form distribution”, “mod-form region” – for quantifying combinatorial PTM states on whole proteins. (3) We develop mass spectrometry and computational software for determining mod-form regions of proteins with molecular weights >40 kDa, which are typically found in cellular processes. (4) We show that the combinatorial complexity of PTM systems shrinks drastically at steady state and introduce mathematical methods for analyzing such systems which overcome the explosion of combinatorial PTMs.

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