Discovery and Evaluation of Novel Pathways for Production of the Second Generation of Biofuels

In an effort of overcoming the limited availability of fossil energy resources the focus of the research and development in the area of biofuels has moved towards developing the second generation of fuels that should be produced via microbial fermentation. The idea is to use as a feedstock inexpensive and abundant waste materials such as lignocellulosic biomass. The second generation biofuels should satisfy several criteria such as lower emission, higher energy density and should be less corrosive to engines. However, currently used industrial workhorses such as E. coli and S. cerevisiae do not produce many of these molecules naturally. Furthermore, for majority of these molecules there are no known biochemical pathways. The need for discovery of novel biosynthetic pathways towards desired molecules sparked the development of computational tools that are capable of reconstructing feasible reaction steps between a given set of starting compounds (precursors) and a molecule of interest (a target compound). In this study, we performed the retrobiosynthesis analysis for all the candidates applying Biochemical Network Integrated Computational Explorer (BNICE.ch) and we reconstructed the metabolic network for 69 fuel compounds. We analyzed compounds (biological or chemical) and reactions one-step away from these target molecules and the appearance of the potential substrates in their reconstructed metabolic network. Based on the results of this analysis, coupled with other criteria such as the Gibes free energy of formation, combustion potential and expert opinion, we chose the 5 highest ranked fuel candidates for further pathway reconstruction studies. For these 5 fuel candidates we have created 1.8 million de novo pathways with different number of reaction steps for further evaluation. We have then embedded the reconstructed pathways in the genome-°©‐scale models of the two chassis organisms E. coli and P. putida and we performed the pathway evaluation with respect to their maximum theoretical yield using two methods (i) Flux Balance Analysis (FBA), and (ii) Thermodynamic-based Flux Analysis (TFA). All the pathways that did not satisfy the thermodynamic constraints were rejected. Our results indicated that in the evaluation and ranking of the pathways the thermodynamics is a necessary consideration. Specifically, we showed that the majority of the pathways that were determined as feasible based on FBA, they were not feasible based on TFA. Moreover, we also showed that some pathways that were determined as feasible in both organisms based on FBA, they were not feasible in both of them based on TFA. Also, the yield of the feasible pathways can differ depending on the organism. These results demonstrate how TFA can also guide the selection of a suitable chassis organism. For all discovered reactions in the feasible pathways we have also identified known enzymes from the KEGG database with the closest reaction similarity that could be engineered for the implementation of novel reactions. This study shows the full potential of computational tools for discovery and design of novel synthetic pathways and their relevance for future developments in the area of metabolic engineering and synthetic biology.

Discovery and evaluation of novel pathways for production of methyl ethyl ketone

Meriç Ataman, Noushin Hadadi, Vassily Hatzimanikatis, Ljubisa Miskovic, Milenko Tokic

The limited supply of fossil fuels and environmental reasons shifted research in industry and academia towards finding their replacements. An important part of these efforts is focused on a sustainable production of the 2nd generation of biofuels. Among many proposed molecules, one of the most prominent fuel candidates is Methyl Ethyl Ketone (MEK). MEK, also referred in the literature as 2-butanone, is the most important commercially produced ketone with a broad application as a solvent for paints and adhesives. MEK shows superior characteristics compared the existing fuels regarding thermo-physical and transport properties, increased combustion stability at low engine load and cold boundary conditions while overcoming their limitations on the particle emissions. There is no known native producer of MEK, and there were recent attempts to introduce biosynthetic pathways and produce this molecule in E. coli and yeast. However, none of these attempts resulted in commercially viable amounts of produced MEK. In this study, we used Biochemical Network Integrated Computational Explorer (BNICE.ch) to explore the space of potential biotransformations around MEK. Out of 1325 identified compounds one reaction step away from MEK, we chose 3-oxopentanoic acid, But-3-en-2-one, But-1-en-2-olate and Butylamine for further study as they can: (i) easily be chemically converted to MEK; (ii) be used as precursor metabolites for a range of other valuable chemicals. We have also chosen (2R)-2-Hydroxy-2-methylbutanenitrile for further analysis as it was the only compound with known biotransformation to MEK. We reconstructed 3’679’610 novel biosynthetic pathways up to a length of 4 reaction steps from 157 central carbon metabolites of E. coli toward these 5 compounds. We then embedded the reconstructed pathways in the genome-scale model of the E. coli, and we performed the pathway evaluation with respect to their maximum theoretical yield using first Flux Balance Analysis (FBA) and then Thermodynamic-based Flux Analysis (TFA). Our results showed that thermodynamics is a necessary step in pathway feasibility analysis because a majority of FBA feasible pathways were infeasible in TFA due to the thermodynamic constraints. More precisely, 13.25% (487’411) of all reconstructed pathways were FBA feasible, whereas only 0.51% (18’925) were TFA feasible. We next identified enzymes from the KEGG database with the closest reaction similarity to the novel reactions in the TFA feasible pathways as candidates for direct implementation or enzyme engineering of novel reactions. Furthermore, we classified the TFA feasible pathways depending on the reactions and precursors that were essential for production of the target molecules. Finally, all the feasible pathways were ranked based on the yield, length, number of known reaction steps and enzyme similarity score. In this way, the highest ranked pathways can be considered for experimental implementation. In this study, we illustrated the application of BNICE.ch for discovery and design of novel synthetic pathways and its potential for future developments in the area of metabolic engineering and synthetic biology.

2017

The design of “Super E. coli” through automated reaction network generation and genome scale models

Noushin Hadadi, Vassily Hatzimanikatis, Keng Cher Soh

Genome-scale metabolic reconstructions capture the known metabolic capabilities of organisms and their analysis have provided many insights into complex biochemical networks. However, this approach relies on a database of known biochemical reactions and hence may fail to take into account unique novel metabolic reactions. Even for well-characterized model organisms like E. coli, new reactions remain to be discovered. Starting from the known biochemistry of E. coli metabolism, we investigated how many more reactions could be evolved and if these reactions could give extra potential to this organism for industrial application in the production of fuels and chemicals. We utilized the BNICE (Biochemical Network Integrated Computational Explorer) methodology which applies known biotransformation rules to generate a “super” network which captures all the possible reactions given a set of E. coli core metabolites and known biotransformation rules in E. coli. This super network is found to capture all the known E. coli reactions as well as novel pathways that can serve as potential novel biosynthesis pathways to valuable chemicals. In order to identify the role of these novel reactions in E. coli metabolic network, we embedded them within the genome scale model of E. coli and performed a thermodynamics flux balance analysis (TFBA) to investigate the feasibility of the novel pathways in the context of the genome scale model. By performing a Flux Variability Analysis (FVA), subject to thermodynamic constraints, the reliable sets of reactions that increase the yield through biomass were identified. To further investigate the feasibility of the novel proposed reactions, we used the BridgIT computational framework for the identification of candidate gene sequences. BridgIT has a database of all the known biochemical reactions and it makes associations between novel predicted reactions and known reactions by using a chemical similarity metrics and it links the novel reactions with known genes in genomes and organisms.

2014

Discovery and Evaluation of Biosynthetic Pathways for the Production of Five Methyl Ethyl Ketone Precursors

Meriç Ataman, Noushin Hadadi, Vassily Hatzimanikatis, Ljubisa Miskovic, Milenko Tokic

The limited supply of fossil fuels and the establishment of new environmental policies shifted research in industry and academia towards sustainable production of the 2nd generation of biofuels, with Methyl Ethyl Ketone (MEK) being one promising fuel candidate. MEK is a commercially valuable petrochemical with an extensive application as a solvent. However, as of today, a sustainable and economically viable production of MEK has not yet been achieved despite several attempts of introducing biosynthetic pathways in industrial microorganisms. We used BNICE.ch as a retrobiosynthesis tool to discover all novel pathways around MEK. Out of 1’325 identified compounds connecting to MEK with one reaction step, we selected 3-oxopentanoate, but-3-en-2-one, but-1-en-2-olate, butylamine, and 2-hydroxy-2-methyl-butanenitrile for further study. We reconstructed 3’679’610 novel biosynthetic pathways towards these 5 compounds. We then embedded these pathways into the genome-scale model of E. coli, and a set of 18’622 were found to be most biologically feasible ones based on thermodynamics and their yields. For each novel reaction in the viable pathways, we proposed the most similar KEGG reactions, with their gene and protein sequences, as candidates for either a direct experimental implementation or as a basis for enzyme engineering. Through pathway similarity analysis we classified the pathways and identified the enzymes and precursors that were indispensable for the production of the target molecules. These retrobiosynthesis studies demonstrate the potential of BNICE.ch for discovery, systematic evaluation, and analysis of novel pathways in synthetic biology and metabolic engineering studies.

2018

Discovery and evaluation of novel pathways for production of methyl ethyl ketone

Meriç Ataman, Noushin Hadadi, Vassily Hatzimanikatis, Ljubisa Miskovic, Milenko Tokic

2017

The design of “Super E. coli” through automated reaction network generation and genome scale models

Noushin Hadadi, Vassily Hatzimanikatis, Keng Cher Soh

2014