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Designing overall stoichiometric conversions and intervening metabolic reactions.

ABSTRACT: Existing computational tools for de novo metabolic pathway assembly, either based on mixed integer linear programming techniques or graph-search applications, generally only find linear pathways connecting the source to the target metabolite. The overall stoichiometry of conversion along with alternate co-reactant (or co-product) combinations is not part of the pathway design. Therefore, global carbon and energy efficiency is in essence fixed with no opportunities to identify more efficient routes for recycling carbon flux closer to the thermodynamic limit. Here, we introduce a two-stage computational procedure that both identifies the optimum overall stoichiometry (i.e., optStoic) and selects for (non-)native reactions (i.e., minRxn/minFlux) that maximize carbon, energy or price efficiency while satisfying thermodynamic feasibility requirements. Implementation for recent pathway design studies identified non-intuitive designs with improved efficiencies. Specifically, multiple alternatives for non-oxidative glycolysis are generated and non-intuitive ways of co-utilizing carbon dioxide with methanol are revealed for the production of C2+ metabolites with higher carbon efficiency.

SUBMITTER: Chowdhury A

PROVIDER: S-EPMC4632160 | biostudies-literature | 2015 Nov

REPOSITORIES: biostudies-literature

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Designing overall stoichiometric conversions and intervening metabolic reactions.

Chowdhury Anupam A Maranas Costas D CD

Scientific reports 20151104

Existing computational tools for de novo metabolic pathway assembly, either based on mixed integer linear programming techniques or graph-search applications, generally only find linear pathways connecting the source to the target metabolite. The overall stoichiometry of conversion along with alternate co-reactant (or co-product) combinations is not part of the pathway design. Therefore, global carbon and energy efficiency is in essence fixed with no opportunities to identify more efficient rout ...[more]

PMID: 26530953

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Project description:To secure a sustainable food supply for the rapidly growing global population, great efforts towards a plant-based diet are underway. However, the use of plant proteins comes with several challenges, such as improvement or removal of undesired flavours, and generation of desired texture properties. Fermentation holds large potential to alter these properties, but compared to dairy fermentations, our knowledge on strain properties in different plant-based substrates is still limited. Here, we explored different lactic acid bacteria for their ability to grow, produce flavour compounds, or remove off-flavour compounds from different plant proteins. For this, 151 LAB strains from dairy and non-dairy origins were cultured in plant protein plus coconut oil emulsions supplemented with glucose. Pea, chickpea, mung, fava, and soybean proteins were used in the study and bacterial strains for screening included the genera Streptococcus, Lactococcus, Lactobacillus, and Leuconostoc. Efficient, high throughput, screening on plant proteins was developed and strains were assessed for their ability to (i) acidify and decrease the pH; (ii) express key enzymes involved in the formation of amino acid derived flavours, which included PepN (aminopeptidase N), PepXP (X-prolyl dipeptidyl peptidase), EstA (esterase), BcAT (branched chain aminotransferase), CBL (cystathione beta lyase), and ArAT (aromatic aminotransferase); and (iii) improve the overall aroma profile by generating dairy/cheesy notes and decreasing off flavours. Suitable screening conditions were determined, and highlighted the importance that a sufficient heat treatment must be applied to samples containing plant proteins, prior to fermentation, as an outgrowth of spore forming Bacillus cereus was observed if the material was only pasteurised. Enzyme activities for strains measured in rich broth vs. a buffered protein solution showed little-to-no correlation, which illustrated the importance of screening conditions to obtain predictive enzyme measurements. Aroma formation analysis allowed to identify strains that were able to increase key aromas such as diacetyl, acetoin, 2- and 3-methyl butanol, and 2,3-pentanedione, as well as decrease the off-flavours hexanal, pentanal, and nonanal. Our findings illustrate the importance of strain specific differences in the assessed functionalities and how a methodical approach to screening LAB can be applied to select suitable microorganisms that show promise in fermentation of plant proteins when applied in non-dairy cheese applications.

Dataset Information

Designing overall stoichiometric conversions and intervening metabolic reactions.

Publications

Designing overall stoichiometric conversions and intervening metabolic reactions.

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