Reconstruction, Analysis and Redesign of Metabolic Networks
The C. Maranas group current research focuses on the use of modeling and computations to reconstruct analyze and redesign metabolism and facilitate bio-production. Of particular emphasis is the development of metabolic models for photosynthesizing and carbon dioxide capturing organisms such as cyanobacteria and plants. These efforts are funded by the US Department of Energy and the National Science Foundation. We have developed a (semi)automated pipeline for the rapid construction of high-quality metabolic models. The goal here is to contrast the metabolic repertoire of different strains and identify unique pathways that could enhance specific bio-production projects. In a collaborative effort with the Pakrasi group (Wash. U.), we are also exploring the metabolic impact of introducing the nitrogen fixation complex (i.e., nitrogenase) into cyanobacteria that do not have a native nitrogen fixation capability. The goal here is to learn how to introduce, regulate and fuel nitrogen fixation in cyanobacteria with the ultimate goal of introducing nitrogen fixation capabilities in plants. This would have far reaching environmental and crop yield implications by reducing nitrogen fertilizer needs worldwide. In the context of plant metabolism, we have published the first genome-scale maize (i.e., corn) model that captures photosynthetic, carbon fixation and many secondary metabolism pathways. We are in the process of completing a second-generation maize model that will account for different tissue types (i.e., leaf, tassel, seed, etc.), full compartment designation of metabolic functions and intra- inter-metabolic flows. This model will be a blueprint for addressing ways to improve nitrogen utilization efficiency, starch storage in the seed and/or lignin degradability for lignocellulosic bioethanol production.
In addition to deploying computations to harness the challenge of utilizing sunlight to fix carbon dioxide our group is pursuing ways to biologically convert methane to liquid biofuels. This is an important goal as abundant, though geographically dispersed shale gas deposits are transforming the energy landscape worldwide. We are pursuing the reversal of a methanogenesis pathway found in archaea, with the ultimate goal of converting methane to a liquid biofuel in in situ bio-reactors. We have already constructed a genome-scale model for the archaea Methanosarcina acetivorans and we are currently working towards reversing the anaerobic methanogenesis pathway using a set of co-reactants. This effort is pursued in collaboration with Profs. Ferry and Wood (PSU) and is funded by Arpa-E. Other efforts geared towards contributing towards the bio-production challenge include reconstructing and understanding the response of Clostridium acetobutylicum in response to organic acid stresses in collaboration with the Papoutsakis group (U. Delaware) and the development of Ensemble Modeling kinetic models of metabolism with the Liao lab (UCLA). A common theme in all our efforts has been the need for well-curated compilations of metabolites and reactions with consistent naming conventions and common standards. To this end, we have developed the MetRxn knowledge base that allows for the query of metabolic content across databases and metabolic models. This has been used by the community for completing, correcting and contrasting genome-scale metabolic models and prospecting for novel pathways to enable bio-production.
Our group has pioneered the development of computational methods for strain design for overproduction. We started with OptKnock which focused on knock-outs leading to coupling of growth to the production of the target bio-product. This computational workflow was applied to a variety of overproduction studies by our group and others. More recently we developed the OptForce strain design procedure which allows for not just knock-outs but also knock-ins, up-regulations and down-regulations. We are currently working towards incorporating kinetics whenever available into the metabolic model. These frameworks have led to collaborative efforts for the production of flavanones (Koffas, RPI) and fatty acids (Shanks, Iowa St.). In addition to metabolic modeling and redesign our group has developed computational frameworks for protein design (IPRO), complementary determining regions of antibodies (OptCDR) and enzymes (OptZyme). All these tools and models are available for download at maranas.che.psu.edu.