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.

Expanding Metabolic Capabilities Using Novel Pathway Designs: Computational Tools and Case Studies

“…Depending on the chosen objective, constraint‐based methods predict steady‐state flux solutions that produce the compound of interest with a bias preference toward short pathways with optimal stoichiometry, thermodynamically plausible pathways, or pathways with minimum enzyme cost . Each of these objective choices determines the nature of the optimization program to be solved (linear programming [LP]/nonlinear programming [NLP] or mixed‐integer linear programming [MILP]), and consequently its complexity.…”

“…Enumeration of all the possible paths (each composed of different enzymatic steps) connecting a set of source metabolites to a target compound is, however, computationally intractable (nondeterministic polynomial‐time [NP]‐hard problem), and so, different requirements and pruning criteria must be employed. For example, criteria such as pathway length, limited number of heterologous or putative enzymes, and thermodynamic realizability have been employed to either reduce the feasible search space or to drive the search to an “optimal” pathway . Notably, the imposition of these criteria for pathway enumeration is not straightforward in all mathematical frameworks (e.g., graph‐based methods) and only stoichiometry‐based optimization methods are capable of naturally accommodating them.…”

Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function

“…Software such as MATLAB COBRA Toolbox [49, 50] or COBRApy [51] that implement Constraint-Based Reconstruction and Analysis (COBRA) methods can then use the information within a GEM to compute predicted metabolic behaviors of the organism subject to specified environmental and physiological limitations [52]. Alternatively, one can create independent analysis tools that simply use GEMs to identify product synthesis pathways [53–56], optimize bioprocessing efficiency [57, 58], predict metabolic engineering targets [58, 59], and elucidate more complex phenomena such as symbiosis in microbial communities [24, 60–63]. …”

A Prospective Study on the Fermentation Landscape of Gaseous Substrates to Biorenewables Using Methanosarcina acetivorans Metabolic Model

“…Using optStoic (Chowdhury and Maranas, 2015) we exhaustively identified all thermodynamically feasible optimal conversion stoichiometries making use of a combination of CH 4 , CO, and CO 2 . Note that there exist many other computational tools for pathway design (Hadadi and Hatzimanikatis, 2015; Long et al, 2015; Nazem-Bokaee and Senger, 2015; Huang et al, 2017).…”