Margaret Johnson joined the Biophysics faculty at Johns Hopkins University in 2013. She received her B.S. in Applied Math from Columbia University and her PhD in BioEngineering from UC Berkeley. She completed postdoctoral training in the Laboratory of Chemical Physics at the National Institutes of Health in Bethesda, MD. Her research focuses on understanding how the individual interactions between thousands of diverse components in the cell generate order and collective function at the right time and the right place. She develops theoretical and computational approaches to study the evolution and mechanics of dynamic systems of interacting and assembling proteins.
In 2011 she received an NIH Pathway to Independence Award (K99/R00).
The dynamic assembly of multiple proteins into large functional complexes at specific times and places in the cell is a crucial step in cellular functions ranging from endocytic trafficking of membrane cargo to DNA transcription and actin polymerization. The protein-protein interactions that control such cellular processes are diverse and dynamic, forming a network of connections that can nucleate and stabilize extended protein complexes. Despite much experimental studies on the details of the proteins involved, their binding reactions, and the structure of completed assemblies, the evolution and mechanisms of many multi-protein assembly processes remains unresolved. Using computer simulation and theoretical models, we are able to build detailed models of the dynamics of protein assembly and provide predictions of how the timing of these events in the cell are controlled by the concentrations of proteins in the cytosol and membrane. Our approach combines systems level research on protein networks that investigates both general, governing principles of protein dynamics, and applications to several specific protein assembly systems.
A major research focus is on developing accurate physical models to describe the spatio-temporal dynamics of populations of proteins in the cell and developing computational tools to analyze these multi-scale simulations. Building accurate models of biological systems requires accounting for the network of protein-interface interactions. We are also using coarse-grained models to characterize more generally how the topology of protein interaction networks affects the specificity and dynamics of protein binding. These network based studies complement the more detailed computer simulations by establishing how the connectivity of a protein within a larger network affects its local dynamic.
Clathrin-mediated endocytosis is one central pathway in the cell that relies on multi-protein assembly of a clathrin protein coat at the plasma membrane to successfully internalize extracellular cargo into the cell. Endocytosis is essential for life, not only because it transports nutrients for cell growth, but also because it regulates signal communication between cells. Characterizing the steps leading up to cargo internalization is critical for understanding how endocytic function is controlled in healthy and diseased cells as, for example, viral infections can result when pathogens hijack the endocytic machinery to deliver genetic material into the cell. Through computer simulation, we are able to perform detailed studies of the types of protein association pathways and their dependence on individual protein concentration that leads to clathrin coat formation. A long-term goal is to test the role of distinct cargo proteins in determining the successful nucleation and composition of the clathrin coat.