With Professor David Sivak and Dr Jannik Ehrich
Within the cells of every plant and animal on earth, countless microscopic molecular machines are in constant motion. These machines convert between different types of energy, transport materials, and assemble complex structures. These machines transduce energy between different external reservoirs, and also within themselves between internally coupled subsystems. We are working to identify and understand the internal flows of energy and information within biological molecular machines, with the goal of uncovering design principles for the future engineering of multi-component synthetic nanomachines.
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With Professor David Sivak
Important molecular cargo like vesicles and organelles are moved around within cells by molecular transport motors like kinesin and myosin. These motors burn chemical “fuel” in order to achieve directed motion, and often work collectively to transport large cargo. Depending on the context, anywhere from only one to over 200 motors can be attached to a single cargo. We studied the dynamics and thermodynamics of these collective motor-driven transport systems, outlining scaling laws and performance trade-offs as the number of motors is varied, and ultimately deriving theoretical bounds on their performance which are totally independent of the number and types of motors present.
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With Professors Andrew Rutenberg and Laurent Kreplak
Collagen is the single most abundant protein in the human body. Individual collagen molecules spontaneously self-assemble in vivo into fibrils: long molecular ropes which are a key structural component in many different animal tissues (the prototypical example is tendons, but collagen fibrils can also be found in tissues such as skin, bone, cartilage, and cornea). Within these fibrils collagen molecules are highly ordered, leading to microscopically visible features such as periodic axial density modulations and high angular surface twist. To understand the self-assembly of collagen fibrils in vivo we derived a nonequilibrium growth model for cross-linked fibrils, which predicts internal structure and radius control mechanisms consistent with experimental observations. We also extended results from the neoclassical theory of nematic rubber elasticity to the double-twist molecular director field of collagen fibrils in order to model the effects of applied strain on the complex macromolecular structures predicted by our growth model.
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With Professor Andrew Rutenberg
Salmonella bacteria are a prototypical labaratory pathogen exhibiting a particularly interesting behavioural trait: the ruffling mechanism. To better understand the impact of the ruffling on the statistics and dynamics of bacterial invasion, we developed an agent-based stochastic model for invasion of host cells by Salmonella bacteria. Using this model we were able to explain recent experimental data, determine environmental conditions under which stochastic effects are most significant, and gain quantitative insight into cooperative invasion behaviour.