Linda J. Broadbelt

A genome-scale metabolic reconstruction for Escherichia coli K-12 MG1655 that accounts for 1260 ORFs and thermodynamic information.

An updated genome‐scale reconstruction of the metabolic network in Escherichia coli K‐12 MG1655 is presented. This updated metabolic reconstruction includes: (1) an alignment with the latest genome annotation and the metabolic content of EcoCyc leading to the inclusion of the activities of 1260 ORFs, (2) characterization and quantification of the biomass components and maintenance requirements associated with growth of E. coli and (3) thermodynamic information for the included chemical reactions. The conversion of this metabolic network reconstruction into an in silico model is detailed. A new step in the metabolic reconstruction process, termed thermodynamic consistency analysis, is introduced, in which reactions were checked for consistency with thermodynamic reversibility estimates. Applications demonstrating the capabilities of the genome‐scale metabolic model to predict high‐throughput experimental growth and gene deletion phenotypic screens are presented. The increased scope and computational capability using this new reconstruction is expected to broaden the spectrum of both basic biology and applied systems biology studies of E. coli metabolism.

Exploring the diversity of complex metabolic networks

MOTIVATION Metabolism, the network of chemical reactions that make life possible, is one of the most complex processes in nature. We describe here the development of a computational approach for the identification of every possible biochemical reaction from a given set of enzyme reaction rules that allows the de novo synthesis of metabolic pathways composed of these reactions, and the evaluation of these novel pathways with respect to their thermodynamic properties. RESULTS We applied this framework to the analysis of the aromatic amino acid pathways and discovered almost 75,000 novel biochemical routes from chorismate to phenylalanine, more than 350,000 from chorismate to tyrosine, but only 13 from chorismate to tryptophan. Thermodynamic analysis of these pathways suggests that the native pathways are thermodynamically more favorable than the alternative possible pathways. The pathways generated involve compounds that exist in biological databases, as well as compounds that exist in chemical databases and novel compounds, suggesting novel biochemical routes for these compounds and the existence of biochemical compounds that remain to be discovered or synthesized through enzyme and pathway engineering. AVAILABILITY Framework will be available via web interface at http://systemsbiology.northwestern.edu/BNICE (site under construction). CONTACT vassily@northwestern.edu or broadbelt@northwestern.edu SUPPLEMENTARY INFORMATION http://systemsbiology.northwestern.edu/BNICE/publications.

Discovery and analysis of novel metabolic pathways for the biosynthesis of industrial chemicals: 3‐hydroxypropanoate

Sustainable microbial production of high‐value organic compounds such as 3‐hydroxypropanoate (3HP) is becoming an increasingly attractive alternative to organic syntheses that utilize petrochemical feedstocks. We applied the Biochemical Network Integrated Computational Explorer (BNICE) framework to the automated design and evaluation of novel biosynthetic routes for the production of 3HP from pyruvate. Among the pathways generated by the BNICE framework were all of the known pathways for the production of 3HP as well as numerous novel pathways. The pathways generated by BNICE were ranked based on four criteria: pathway length, thermodynamic feasibility, maximum achievable yield to 3HP from glucose, and maximum achievable activity at which 3HP can be produced. Four pathways emerged from this ranking as the most promising for the biosynthesis of 3HP, and three of these pathways, including the shortest pathways discovered, were novel. We also discovered novel routes for the biosynthesis of 28 commercially available compounds that are currently produced exclusively through organic synthesis. Examination of the optimal pathways for the biosynthesis of these 28 compounds in E. coli revealed pyruvate and succinate to be ideal intermediates for achieving high product yields from glucose. Biotechnol. Bioeng. 2010; 106: 462–473.

Unraveling the reactions that unravel cellulose.

For over 90 years, researchers have postulated mechanisms for the cleavage of celluloses glycosidic bonds and resulting formation of levoglucosan without reaching consensus. These reactions are key primary reactions in thermal processes for the production of carbon-neutral, renewable transportation fuels. Previous literature reports have proposed a variety of mainly heterolytic and homolytic mechanisms, but there has been insufficient evidence to settle the debate. Using density functional theory (DFT) methods and implicit solvent, we compared the likelihood of forming either radical or ionic intermediates. We discovered a concerted reaction mechanism that is more favorable than previously proposed mechanisms and is in better alignment with experimental findings. This new understanding of the mechanism of cellulose thermal decomposition opens the door to accurate process modeling and educated catalyst design, which are vital steps toward producing more cost-efficient renewable energy.

Applications of molecular modeling in heterogeneous catalysis research

Abstract The application of molecular modeling in heterogeneous catalysis research as a complement to experimental studies has grown rapidly in recent years. This review summarizes methodologies for probing catalytic phenomena in terms of a hierarchical approach. The elements of the hierarchy are different computational methods at different time and length scales that may be linked together to answer questions spanning from the atomic to the macroscopic. At the most detailed level of description, quantum chemical calculations are used to predict the energies, electronic structures, and spectroscopic properties of small arrangements of atoms and even periodic structures. Atomistic simulations, using systems of hundreds or thousands of molecules, can be used to predict macroscopic thermodynamic and transport properties, as well as preferred molecular geometries. At the longest time and length scales, continuum engineering modeling approaches such as microkinetic modeling are used to calculate reaction rates, reactant conversion, and product yields and selectivities, using model parameters predicted by the other levels of the hierarchy. We highlight some interesting recent results for each of these approaches, stress the need for integrating modeling at widely varying time and length scales, and discuss current challenges and areas for future development.

Effects of Nanoscale Confinement and Interfaces on the Glass Transition Temperatures of a Series of Poly(n-methacrylate) Films

We use fluorescence from dye-labelled polymer to measure the glass transition temperatures (Tgs) across single-layer films and near surfaces and silica interfaces in bilayer films for a series of poly(n-methacrylate)s. With nanoscale confinement, the average Tg across a film supported on silica increases for poly(methyl methacrylate) (PMMA), decreases for poly(ethyl methacrylate) (PEMA) and poly(propyl methacrylate), and is nearly invariant for poly(iso-butyl methacrylate) (PIBMA). These trends are consistent with the relative strengths of local perturbations to Tg caused by surfaces and substrates as measured in bilayer films. The substrate effect, which increases Tg via hydrogen-bonding interactions between the polymer and hydroxyl groups on the silica surface, is stronger than the free-surface effect in PMMA. The free-surface effect, which reduces Tg via a reduction in the required cooperativity of the glass transition dynamics, is stronger than the substrate effect in PEMA. The substrate and free-surface effects have similar strengths in perturbing the local Tg in PIBMA, resulting in a net cancellation of effects when measurements are made across single-layer films.

Glass transition and α-relaxation dynamics of thin films of labeled polystyrene

The glass transition temperature and relaxation dynamics of the segmental motions of thin films of polystyrene labeled with a dye, 4-[N-ethyl-N-(hydroxyethyl)]amino-4-nitroazobenzene (Disperse Red 1, DR1) are investigated using dielectric measurements. The dielectric relaxation strength of the DR1-labeled polystyrene is approximately 65 times larger than that of the unlabeled polystyrene above the glass transition, while there is almost no difference between them below the glass transition. The glass transition temperature of the DR1-labeled polystyrene can be determined as a crossover temperature at which the temperature coefficient of the electric capacitance changes from the value of the glassy state to that of the liquid state. The glass transition temperature of the DR1-labeled polystyrene decreases with decreasing film thickness in a reasonably similar manner to that of the unlabeled polystyrene thin films. The dielectric relaxation spectrum of the DR1-labeled polystyrene is also investigated. As the thickness decreases, the alpha -relaxation time becomes smaller, and the distribution of the alpha -relaxation times becomes broader. These results show that thin films of DR1-labeled polystyrene are a suitable system for investigating confinement effects of the glass transition dynamics using dielectric relaxation spectroscopy.

Computer generated reaction modelling: Decomposition and encoding algorithms for determining species uniqueness

Abstract The concept of computer generated reaction modelling was broadened through the development of a general planar graph algorithm for determination of isomorphism. The previous capability was limited by its inability to determine the uniqueness of ring-containing species unambiguously, restricting the application of automatic network generation to non-cyclic species or cyclic species where the ring was not involved in the chemical transformation. In this work, the systematic identification of both noncyclic and cyclic species was carried out by constructing the structurally explicit decomposition tree, an assembly of the biconnected components of the graph, from which a graph invariant unique string code was obtained by iteratively encoding and ordering the subtrees of the decomposition tree. A lexicographical comparison of the unique string code of the candidate species with the string codes of all previously generated species with the same empirical formula allowed unambiguous determination of species uniqueness.

MINEs: open access databases of computationally predicted enzyme promiscuity products for untargeted metabolomics

BackgroundIn spite of its great promise, metabolomics has proven difficult to execute in an untargeted and generalizable manner. Liquid chromatography–mass spectrometry (LC–MS) has made it possible to gather data on thousands of cellular metabolites. However, matching metabolites to their spectral features continues to be a bottleneck, meaning that much of the collected information remains uninterpreted and that new metabolites are seldom discovered in untargeted studies. These challenges require new approaches that consider compounds beyond those available in curated biochemistry databases.DescriptionHere we present Metabolic In silico Network Expansions (MINEs), an extension of known metabolite databases to include molecules that have not been observed, but are likely to occur based on known metabolites and common biochemical reactions. We utilize an algorithm called the Biochemical Network Integrated Computational Explorer (BNICE) and expert-curated reaction rules based on the Enzyme Commission classification system to propose the novel chemical structures and reactions that comprise MINE databases. Starting from the Kyoto Encyclopedia of Genes and Genomes (KEGG) COMPOUND database, the MINE contains over 571,000 compounds, of which 93% are not present in the PubChem database. However, these MINE compounds have on average higher structural similarity to natural products than compounds from KEGG or PubChem. MINE databases were able to propose annotations for 98.6% of a set of 667 MassBank spectra, 14% more than KEGG alone and equivalent to PubChem while returning far fewer candidates per spectra than PubChem (46 vs. 1715 median candidates). Application of MINEs to LC–MS accurate mass data enabled the identity of an unknown peak to be confidently predicted.ConclusionsMINE databases are freely accessible for non-commercial use via user-friendly web-tools at http://minedatabase.mcs.anl.gov and developer-friendly APIs. MINEs improve metabolomics peak identification as compared to general chemical databases whose results include irrelevant synthetic compounds. Furthermore, MINEs complement and expand on previous in silico generated compound databases that focus on human metabolism. We are actively developing the database; future versions of this resource will incorporate transformation rules for spontaneous chemical reactions and more advanced filtering and prioritization of candidate structures.

Detailed mechanistic modeling of polymer degradation: application to polystyrene

The degradation of polystyrene was modeled at the mechanistic level using population balance equations formulated via the method of moments. Five degradation models of varying complexity were developed. For all models, the conversion among the species was described using typical free radical reaction types, including hydrogen abstraction, mid-chain β-scission, end-chain β-scission, 1,5-hydrogen transfer, radical addition, bond fission, radical recombination, and disproportionation. The five models differed in their resolution of the structural characteristics of the “dead” and “live” polymeric species and whether they explicitly tracked low molecular weight species. The most complex model included over 4500 reactions and tracked 93 polymeric and low molecular weight species, both dead and live species. To facilitate model construction, programs were developed using the programming language Perl to assemble population balance equations from specific reaction mechanism input. The intrinsic kinetic parameters (a frequency factor and activation energy for each reaction) were obtained from previous modeling work in which the decomposition of a polystyrene mimic was described at the mechanistic level (Woo, Ph.D. dissertion, Northwestern University, 1999; Woo and Broadbelt, 1998, Catal. Today 40, 121) to link reactivity directly to structure. As the complexity of the models increased to include branching reactions and branched species, the model predictions improved. The separation between Mn and Mw observed experimentally was reproduced well for the three most complex models. The general modeling framework established may be easily extended to other single-component and multicomponent polymeric systems.