Pareto Optimality Explanation of the Glycolytic Alternatives in Nature.

The Entner-Doudoroff (ED) and Embden-Meyerhof-Parnas (EMP) glycolytic pathways are largely conserved across glycolytic species in nature. Is this a coincidence, convergent evolution or there exists a driving force towards either of the two pathway designs? We addressed this question by first employing a variant of the optStoic algorithm to exhaustively identify over 11,916 possible routes between glucose and pyruvate at different pre-determined stoichiometric yields of ATP. Subsequently, we analyzed the thermodynamic feasibility of all the pathways at physiological metabolite concentrations and quantified the protein cost of the feasible solutions.

Exploring the combinatorial space of complete pathways to chemicals.

Computational pathway design tools often face the challenges of balancing the stoichiometry of co-metabolites and cofactors, and dealing with reaction rule utilization in a single workflow. To this end, we provide an overview of two complementary stoichiometry-based pathway design tools optStoic and novoStoic developed in our group to tackle these challenges. optStoic is designed to determine the stoichiometry of overall conversion first which optimizes a performance criterion (e.

A review of computational tools for design and reconstruction of metabolic pathways.

Metabolic pathways reflect an organism's chemical repertoire and hence their elucidation and design have been a primary goal in metabolic engineering. Various computational methods have been developed to design novel metabolic pathways while taking into account several prerequisites such as pathway stoichiometry, thermodynamics, host compatibility, and enzyme availability. The choice of the method is often determined by the nature of the metabolites of interest and preferred host organism, along with computational complexity and availability of software tools.

Pathway design using de novo steps through uncharted biochemical spaces.

Existing retrosynthesis tools generally traverse production routes from a source to a sink metabolite using known enzymes or de novo steps. Generally, important considerations such as blending known transformations with putative steps, complexity of pathway topology, mass conservation, cofactor balance, thermodynamic feasibility, microbial chassis selection, and cost are largely dealt with in a posteriori fashion. The computational procedure we present here designs bioconversion routes while simultaneously considering any combination of the aforementioned design criteria.

Multilevel engineering of the upstream module of aromatic amino acid biosynthesis in Saccharomyces cerevisiae for high production of polymer and drug precursors.

A multilevel approach was implemented in Saccharomyces cerevisiae to optimize the precursor module of the aromatic amino acid biosynthesis pathway, which is a rich resource for synthesizing a great variety of chemicals ranging from polymer precursor, to nutraceuticals and pain-relief drugs. To facilitate the discovery of novel targets to enhance the pathway flux, we incorporated the computational tool YEASTRACT for predicting novel transcriptional repressors and OptForce strain-design for identifying non-intuitive pathway interventions. The multilevel approach consisted of (i) relieving the pathway from strong transcriptional repression, (ii) removing competing pathways to ensure high carbon capture, and (iii) rewiring precursor pathways to increase the carbon funneling to the desired target.

Metabolic modeling of clostridia: current developments and applications.

Anaerobic Clostridium spp. is an important bioproduction microbial genus that can produce solvents and utilize a broad spectrum of substrates including cellulose and syngas. Genome-scale metabolic (GSM) models are increasingly being put forth for various clostridial strains to explore their respective metabolic capabilities and suitability for various bioconversions.

Advances in de novo strain design using integrated systems and synthetic biology tools.

Recent efforts in expanding the range of biofuel and biorenewable molecules using microbial production hosts have focused on the introduction of non-native pathways in model organisms and the bio-prospecting of non-model organisms with desirable features. Current challenges lie in the assembly and coordinated expression of the (non-)native pathways and the elimination of competing pathways and undesirable regulation. Several systems and synthetic biology approaches providing contrasting top-down and bottom-up strategies, respectively, have been developed.

Rational design of a synthetic Entner-Doudoroff pathway for improved and controllable NADPH regeneration.

NADPH is an essential cofactor for the biosynthesis of several high-value chemicals, including isoprenoids, fatty acid-based fuels, and biopolymers. Tunable control over all potentially rate-limiting steps, including the NADPH regeneration rate, is crucial to maximizing production titers. We have rationally engineered a synthetic version of the Entner-Doudoroff pathway from Zymomonas mobilis that increased the NADPH regeneration rate in Escherichia coli MG1655 by 25-fold.

Production of 2,3-butanediol in Saccharomyces cerevisiae by in silico aided metabolic engineering.

Background: 2,3-Butanediol is a chemical compound of increasing interest due to its wide applications. It can be synthesized via mixed acid fermentation of pathogenic bacteria such as Enterobacter aerogenes and Klebsiella oxytoca. The non-pathogenic Saccharomyces cerevisiae possesses three different 2,3-butanediol biosynthetic pathways, but produces minute amount of 2,3-butanediol.

Deletion of lactate dehydrogenase in Enterobacter aerogenes to enhance 2,3-butanediol production.

2,3-Butanediol is an important bio-based chemical product, because it can be converted into several C4 industrial chemicals. In this study, a lactate dehydrogenase-deleted mutant was constructed to improve 2,3-butanediol productivity in Enterobacter aerogenes. To delete the gene encoding lactate dehydrogenase, λ Red recombination method was successfully adapted for E.