Milo Lin, a physicist and Assistant Professor in the Department of Bioinformatics at the University of Texas Southwestern Medical Center, has developed a "mapping” that, when combined with thermodynamic circuit theory, allows one to transform a biochemical network into an equivalent electrical circuit that obeys Ohm’s law. This allows the theorems and powerful quantitative methods of electrical-network-analysis developed over the past century to be applied to biochemical networks. These electrical engineering tools have -for the electronics industry- enabled large-scale system prediction and design through abstraction and modularity as opposed to simulation of all the components and interactions in a given system. Funds from this grant support efforts by Professor Lin to deploy this framework in the analysis of biochemical systems. Lin will begin by systematically mapping a wide variety of biochemical networks found in organisms (regulatory networks, metabolic pathways, molecular motors, etc.) to equivalent electric circuits and then using electrical engineering tools to obtain the simplest circuit of that type. He will then use computer simulations to “evolve” this simple circuit to meet various targets, including determining circuits necessary and sufficient to execute arbitrary computations, circuits that exhibit robustness to input noise, and circuits that exhibit robustness to changes in the fitness landscape.  Lin will then explore the possible existence of a threshold thermodynamic force above which biomolecular computational capacity is dramatically increased, which, if there is a such a threshold, may shed some light on the puzzling observation that living systems overwhelmingly choose nonequilibrium over equilibrium chemistry for computation. If successful, Lin’s project will facilitate our understanding of complex biochemical networks and therefore of how organisms use chemistry to achieve life-sustaining functions. More speculatively, characterizing the computational capacity of a wide range of biochemical networks may provide insights that allow one to delineate living from nonliving matter.

This grant supports research by Chunte (Sam) Peng, an Assistant Professor of Chemistry at Massachusetts Institute of Technology (MIT) and a member of the MIT-Harvard Broad Institute, which will focus on creating novel probes for single particle tracking to quantitatively study the nonequilibrium dynamics of molecular motors in vivo, using these dynamics as a window into the functioning of living systems and far-from-equilibrium physics. Professor Peng proposes to learn about intracellular dynamics by making movies of molecular motors ‘tagged’ with fluorescent probes. The probes—called Up Conversion NanoParticles (UCNPs)—have three features that make them superior to existing fluorescent probes and which suit them for intracellular single particle tracking. First, UCNPs fluoresce at different colors than the light emitted by other cellular components, thus offering superior contrast relative to nearby objects. Second, UCNP fluorescence is spectrally much narrower than that of commonly used fluorescent probes, allowing a larger number of distinct cellular components—each tagged with a different color—to be simultaneously tracked. Third, UCNPs can be used to track a cellular object for much longer (hours or days) than is typical using existing fluorescent probes (a few minutes). Peng will use UCNPs to study the nonequilibrium dynamics of two molecular motors, dynein and kinesin, as they transport ‘cargo’ from place to place within a cell along intracellular protein polymers. The research team will attach probes to cargo and/or motors and then record movies that track probe position as revealed by the UCNP fluorescence. The plan is to begin by quantifying motor dynamics at various points in a motor’s traversal of a cell and then explore why motor behavior varies by gaining an ever-increasing level of detail about the local cellular environment. Particular experimental attention will be paid to how motor efficiency varies in relation to varying cellular conditions, efficiency-affecting interactions between motors and between motors and cargo, and the relation of observed motor efficiency to efficiency constraints predicted by thermodynamic theory. 

Multicellular organisms operate through cell differentiation.  What begins as an initial pool of uniform, isogenic cells eventually develops into a suite of distinct cell types, each performing specialized functions in the organism as a whole. This specialization process can be thought of as a form of information processing . A simplified overall picture of this information processing is that a receptor -for instance at the cell membrane- detects a signal molecule and a signaling network then acts as 'wiring' to relay information to downstream components, which then produce an appropriate cellular response. The signaling network is a chain of biochemical events which link an upstream molecular signal to a downstream 'cis-regulation' system in order to achieve a particular gene-expression pattern that--in this case--specifies cell type.  This grant supports work by Michael Elowitz, Professor of Biology and of Bioengineering at Caltech, to create a synthetic cell fate control system. The system, if successful, will allow one to begin with a pool of genetically identical cells and then -using a small number of 'input' signals- direct various subsets of the pool to differentiate and develop into distinct, predetermined cell types. Elowitz proposes to achieve this goal by using the tools of synthetic biology to develop the two core subsystems briefly sketched above: a 'signaling network'; a complex network of proteins to process chemical 'signals' and relay them downstream and a downstream 'cis-regulation' system that drives expression of a specific gene or set of genes. The signaling network and gene regulation system will be integrated into natural cells to demonstrate cell fate control and differentiation into targeted cell types. If successful, this project will advance our understanding of and control over cellular information processing and provide a foundation for extending synthetic biology into multicellularity.