Design of computational retrobiosynthesis tools for the design of de novo synthetic pathways

Hadadi, Noushin; Hatzimanikatis, Vassily

doi:10.1016/j.cbpa.2015.06.025

Cited by 118 publications

(107 citation statements)

References 48 publications

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“…This makes it a versatile tool to study the characteristics of industrial chemical production strains [47], since it identifies all the enzymes, either linearly connected or nested that participate in the biosynthesis of the target compound. This approach can be used to compare the similarities and differences between the host organisms to produce a target chemical, since lumpGEM can compare the metabolic costs and capabilities of different organisms for the biosynthesis of an industrially relevant molecule.…”

Section: Resultsmentioning

confidence: 99%

lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites

Ataman

Hatzimanikatis

2017

PLoS Comput Biol

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In the post-genomic era, Genome-scale metabolic networks (GEMs) have emerged as invaluable tools to understand metabolic capabilities of organisms. Different parts of these metabolic networks are defined as subsystems/pathways, which are sets of functional roles to implement a specific biological process or structural complex, such as glycolysis and TCA cycle. Subsystem/pathway definition is also employed to delineate the biosynthetic routes that produce biomass building blocks. In databases, such as MetaCyc and SEED, these representations are composed of linear routes from precursors to target biomass building blocks. However, this approach cannot capture the nested, complex nature of GEMs. Here we implemented an algorithm, lumpGEM, which generates biosynthetic subnetworks composed of reactions that can synthesize a target metabolite from a set of defined core precursor metabolites. lumpGEM captures balanced subnetworks, which account for the fate of all metabolites along the synthesis routes, thus encapsulating reactions from various subsystems/pathways to balance these metabolites in the metabolic network. Moreover, lumpGEM collapses these subnetworks into elementally balanced lumped reactions that specify the cost of all precursor metabolites and cofactors. It also generates alternative subnetworks and lumped reactions for the same metabolite, accounting for the flexibility of organisms. lumpGEM is applicable to any GEM and any target metabolite defined in the network. Lumped reactions generated by lumpGEM can be also used to generate properly balanced reduced core metabolic models.

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Section: Resultsmentioning

confidence: 99%

lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites

Ataman

Hatzimanikatis

2017

PLoS Comput Biol

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“…We generated a reconstructed biochemical reaction network (Tables S1 and S2 in the supplementary data) for MEG using the BNICE.ch algorithm (Hadadi and Hatzimanikatis, 2015;Hatzimanikatis et al, 2005;Li et al, 2004). The algorithm, as well as its functionality and applications have been described in details elsewhere (Finley et al, 2009;Hadadi et al, 2016;Hatzimanikatis et al, 2005;Li et al, 2004).…”

Section: Generation Of the Mono-ethylene Glycol (Meg)-producing Pathwaysmentioning

confidence: 99%

“…Almost all of these cheminformatics tools are based on the retrobiosynthesis principle (Carbonell et al, 2013;Hadadi and Hatzimanikatis, 2015;Medema et al, 2012), in which a set of defined biotransformation rules are iteratively applied to connect a target compound "retrosynthetically" to the metabolites of either a host organism's metabolic network, or a biochemical database such as KEGG (Kanehisa et al, 2016), MetaCyc (Caspi et al, 2014), and PubChem (Kim et al, 2016). Although these cheminformatics tools are capable of generating both novel and biologically well-known biotransformations, almost all of them suffers from the combinatorial explosion of pathway generation resulting in hundreds and thousands of generated pathways; thereby, posing an important challenge of postprocessing of the pathways to decipher and select useful and meaningful ones from the redundant pathways.…”

Section: Introductionmentioning

confidence: 99%

Exploring biochemical pathways for mono-ethylene glycol (MEG) synthesis from synthesis gas

Islam

Hadadi

Ataman

et al. 2017

Metabolic Engineering

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Mono-ethylene glycol (MEG) is an important petrochemical with widespread use in numerous consumer products. The current industrial MEG-production process relies on non-renewable fossil fuel-based feedstocks, such as petroleum, natural gas, and naphtha; hence, it is useful to explore alternative routes of MEG-synthesis from gases as they might provide a greener and more sustainable alternative to the current production methods. Technologies of synthetic biology and metabolic engineering of microorganisms can be deployed for the expression of new biochemical pathways for MEG-synthesis from gases, provided that such promising alternative routes are first identified. We used the BNICE.ch algorithm to develop novel and previously unknown biological pathways to MEG from synthesis gas by leveraging the Wood-Ljungdahl pathway of carbon fixation of acetogenic bacteria. We developed a set of useful pathway pruning and analysis criteria to systematically assess thousands of pathways generated by BNICE.ch. Published genome-scale models of Moorella thermoacetica and Clostridium ljungdahlii were used to perform the pathway yield calculations and in-depth analyses of seven (7) newly developed biological MEG-producing pathways from gases, including CO, CO, and H. These analyses helped identify not only better candidate pathways, but also superior chassis organisms that can be used for metabolic engineering of the candidate pathways. The pathway generation, pruning, and detailed analysis procedures described in this study can also be used to develop biochemical pathways for other commodity chemicals from gaseous substrates.

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“…thermodynamic balance analysis, genome-model metabolic flux balance analysis), scoring and ranking the pathways and the most optimal pathways then can be verified experimentally [53][54][55]. GEM-Path, RetroPath) are helpful for designing numerous pathways in silico combing both known and hypothetical reactions, analyzing the designed pathways in multiple aspects (e.g.…”

Section: Comparison Of Different Dca Synthetic Pathways and Computatimentioning

confidence: 99%

Advances in bio‐based production of dicarboxylic acids longer than C4

Qian

Zhong

2018

Engineering in Life Sciences

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Growing concerns of environmental pollution and fossil resource shortage are major driving forces for bio‐based production of chemicals traditionally from petrochemical industry. Dicarboxylic acids (DCAs) are important platform chemicals with large market and wide applications, and here the recent advances in bio‐based production of straight‐chain DCAs longer than C4 from biological approaches, especially by synthetic biology, are reviewed. A couple of pathways were recently designed and demonstrated for producing DCAs, even those ranging from C5 to C15, by employing respective starting units, extending units, and appropriate enzymes. Furthermore, in order to achieve higher production of DCAs, enormous efforts were made in engineering microbial hosts that harbored the biosynthetic pathways and in improving properties of biocatalytic elements to enhance metabolic fluxes toward target DCAs. Here we summarize and discuss the current advantages and limitations of related pathways, and also provide perspectives on synthetic pathway design and optimization for hyper‐production of DCAs.

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Design of computational retrobiosynthesis tools for the design of de novo synthetic pathways

Cited by 118 publications

References 48 publications

lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites

lumpGEM: Systematic generation of subnetworks and elementally balanced lumped reactions for the biosynthesis of target metabolites

Exploring biochemical pathways for mono-ethylene glycol (MEG) synthesis from synthesis gas

Advances in bio‐based production of dicarboxylic acids longer than C4

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