Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

Hay, Jordan O.; Shi, Hai Ning; Heinzel, Nicolas; Hebbelmann, Inga; Rolletschek, Hardy; Schwender, Jörg

doi:10.3389/fpls.2014.00724

Cited by 33 publications

(28 citation statements)

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“…FBA represents an established technique to generate quantitative models of optimal steady-state flux distributions at large-scale metabolic networks. Appropriate FBA models involving seed metabolism (GrafahrendBelau et al, 2009;Hay and Schwender, 2011;Hay et al, 2014) and even individual seed organs/tissues Borisjuk et al, 2013) have been elaborated. As yet, however, these seed models cannot account for the exchange of materials between the individual tissues/organs.…”

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confidence: 99%

Metabolic architecture of the cereal grain and its relevance to maximize carbon use efficiency

et al. 2015

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Here, we have characterized the spatial heterogeneity of the cereal grain's metabolism and demonstrated how, by integrating a distinct set of metabolic strategies, the grain has evolved to become an almost perfect entity for carbon storage. In vivo imaging revealed light-induced cycles in assimilate supply toward the ear/grain of barley (Hordeum vulgare) and wheat (Triticum aestivum). In silico modeling predicted that, in the two grain storage organs (the endosperm and embryo), the light-induced shift in solute influx does cause adjustment in metabolic flux without changes in pathway utilization patterns. The enveloping, leaf-like pericarp, in contrast, shows major shifts in flux distribution (starch metabolism, photosynthesis, remobilization, and tricarboxylic acid cycle activity) allow to refix 79% of the CO 2 released by the endosperm and embryo, allowing the grain to achieve an extraordinary high carbon conversion efficiency of 95%. Shading experiments demonstrated that ears are autonomously able to raise the influx of solutes in response to light, but with little effect on the steady-state levels of metabolites or transcripts or on the pattern of sugar distribution within the grain. The finding suggests the presence of a mechanism(s) able to ensure metabolic homeostasis in the face of short-term environmental fluctuation. The proposed multicomponent modeling approach is informative for predicting the metabolic effects of either an altered level of incident light or a momentary change in the supply of sucrose. It is therefore of potential value for assessing the impact of either breeding and/or biotechnological interventions aimed at increasing grain yield.Raising the productivity of a given crop genotype requires an increase in the plant's ability to efficiently respond to a changeable environment. At the physiological level, this involves adjustments to the photosynthetic activity of its leaves, to the control of assimilate movement from source to sink, and to the efficiency of assimilate storage. The manipulation of the plant's efficiency to fix carbon, to use energy and nutrients, and to utilize water has been suggested as a route for improving crop productivity (Amthor 2010;De Block and Van Lijsebettens, 2011). Particular attention has been devoted to the cereals, given their central role in the human diet. While the necessary integration of physiological and developmental processes in all plants relies on the transmission of hormonal, metabolic, and other signals through the vascular system (van Bel et al., 2013), this is not the case in the cereal grain, because this network does not extend beyond the pericarp, a maternal structure that encloses the filial storage organs (embryo and endosperm; Radchuk and Borisjuk, 2014). The isolation of the filial from the maternal tissues in the cereal grain creates a complex metabolic system, involving, at the least, a tripartite interaction between the pericarp, endosperm, and embryo. These three grain components in effect form an interactive system of autonomous...

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Metabolic architecture of the cereal grain and its relevance to maximize carbon use efficiency

et al. 2015

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“…In this case, the pre-processing time was similar in these two models using both solvers, highlighting the dependence on both factors. We further compared the performance of Fast-SNP against a previous method for generation of a minimal null space basis (Hay et al , 2014). This method is based on the identification of reactions involved in infeasible loops through FVA and extreme pathway analysis.…”

Section: Resultsmentioning

confidence: 99%

Fast-SNP: a fast matrix pre-processing algorithm for efficient loopless flux optimization of metabolic models

Saa

Nielsen

2016

Bioinformatics

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Motivation: Computation of steady-state flux solutions in large metabolic models is routinely performed using flux balance analysis based on a simple LP (Linear Programming) formulation. A minimal requirement for thermodynamic feasibility of the flux solution is the absence of internal loops, which are enforced using ‘loopless constraints’. The resulting loopless flux problem is a substantially harder MILP (Mixed Integer Linear Programming) problem, which is computationally expensive for large metabolic models.Results: We developed a pre-processing algorithm that significantly reduces the size of the original loopless problem into an easier and equivalent MILP problem. The pre-processing step employs a fast matrix sparsification algorithm—Fast- sparse null-space pursuit (SNP)—inspired by recent results on SNP. By finding a reduced feasible ‘loop-law’ matrix subject to known directionalities, Fast-SNP considerably improves the computational efficiency in several metabolic models running different loopless optimization problems. Furthermore, analysis of the topology encoded in the reduced loop matrix enabled identification of key directional constraints for the potential permanent elimination of infeasible loops in the underlying model. Overall, Fast-SNP is an effective and simple algorithm for efficient formulation of loop-law constraints, making loopless flux optimization feasible and numerically tractable at large scale.Availability and Implementation: Source code for MATLAB including examples is freely available for download at http://www.aibn.uq.edu.au/cssb-resources under Software. Optimization uses Gurobi, CPLEX or GLPK (the latter is included with the algorithm).Contact: lars.nielsen@uq.edu.auSupplementary information: Supplementary data are available at Bioinformatics online.

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“…Recently, fluxes obtained from 13 C-MFA have been used to validate the quality of FBA or FBA-based models (Chen, Alonso, Allen, Reed, & Shachar-Hill, 2011;Schultz & Qutub, 2015). In addition, flux information derived from 13 C-MFA can be used as a constraint to FBA models to improve the accuracy of the intracellular fluxes prediction (Choi, Kim, Lee, & Lee, 2007;Hay et al, 2014 techniques have been proposed (Tepeli & Hortaçsu, 2008). For a detailed view on these dynamic approaches, readers can refer to (Antoniewicz, 2013b).…”

Section: Fba-estimation Of Fluxes For Underdetermined Systemmentioning

confidence: 99%

Quantitative intracellular flux modeling and applications in biotherapeutic development and production using CHO cell cultures

Huang

Lee

Yoon

2017

Biotech & Bioengineering

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Chinese hamster ovary (CHO) cells have been widely used for producing many recombinant therapeutic proteins. Constraint-based modeling, such as flux balance analysis (FBA) and metabolic flux analysis (MFA), has been developing rapidly for the quantification of intracellular metabolic flux distribution at a systematic level. Such methods would produce detailed maps of flows through metabolic networks, which contribute significantly to better understanding of metabolism in cells. Although these approaches have been extensively established in microbial systems, their application to mammalian cells is sparse. This review brings together the recent development of constraint-based models and their applications in CHO cells. The further development of constraint-based modeling approaches driven by multi-omics datasets is discussed, and a framework of potential modeling application in cell culture engineering is proposed. Improved cell culture system understanding will enable robust developments in cell line and bioprocess engineering thus accelerating consistent process quality control in biopharmaceutical manufacturing.

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Integration of a constraint-based metabolic model of Brassica napus developing seeds with 13C-metabolic flux analysis

Cited by 33 publications

References 93 publications

Metabolic architecture of the cereal grain and its relevance to maximize carbon use efficiency

Metabolic architecture of the cereal grain and its relevance to maximize carbon use efficiency

Fast-SNP: a fast matrix pre-processing algorithm for efficient loopless flux optimization of metabolic models

Quantitative intracellular flux modeling and applications in biotherapeutic development and production using CHO cell cultures

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