Integrative Modeling of Oxidative Stress and C1 Metabolism Reveals Upregulation of Formaldehyde and Downregulation of Glutathione

This research provides, to the authors’ knowledge, the first integrative model of oxidative stress and C1 metabolism in plants. Increased oxidative stress can cause irreversible damage to photosynthetic components and is harmful to plants. Perturbations at the genetic level may increase oxidative stress and upregulate antioxidant systems in plants. One of the key mechanisms involved in oxidative stress regulation is the ascorbate-glutathione cycle which operates in chloroplasts as well as the mitochondria and is responsible for removal of reactive oxygen species (ROS) generated during photosynthetic operations and respiration. In this research, the complexity of molecular pathway systems of oxidative stress is modeled and then integrated with a previously developed in silico model of C1 metabolism system. This molecular systems integration provides two important results: 1) demonstration of the scalability of the CytoSolve&#174?Collaboratory&#153, a computational systems biology platform that allows for modular integration of molecular pathway models, by coupling the in silico model of oxidative stress with the in silico model of C1 metabolism, and 2) derivation of new insights on the effects of oxidative stress on C1 metabolism relative to formaldehyde (HCHO), a toxic molecule, and glutathione (GSH), an important indicator of oxidative homeostasis in living systems. Previous in silico modeling of C1 metabolism, without oxidative stress, observed complete removal of formaldehyde via formaldehyde detoxification pathway and no change in glutathione concentrations. The results from this research of integrative oxidative stress with C1 metabolism, however, demonstrate significant upregulation of formaldehyde concentrations, with concomitant downregulation and depletion of glutathione. Sensitivity analysis indicates that kGSH-HCHO, the rate constant of GSH-HCHO binding, VSHMT, the rate of formation of sarcosine from glycine, and , the rate of superoxide formation significantly affect formaldehyde homeostasis in the C1 metabolism. Future research may employ this integrative model to explore which conditions initiate oxidative stress and the resultant upregulation and downregulation of formaldehyde and glutathione.

<i>In Silico</i>Modeling of C1 Metabolism

An integrative computational, in silico, model of C1 metabolism is developed from molecular pathway systems identified from a recent, comprehensive systematic bioinformatics review of C1 metabolism. C1 metabolism is essential for all organisms to provide one-carbon units for methylation and other types of modifications, as well as for nucleic acid, amino acid, and other biomolecule syntheses. C1 metabolism consists of three important molecular pathway systems: 1) methionine biosynthesis, 2) methylation cycle, and 3) formaldehyde detoxification. Each of the three molecular pathway systems is individually modeled using the CytoSolve?? Collaboratory?, a proven and scalable computational systems biology platform for in silico modeling of complex molecular pathway systems. The individual models predict the temporal behavior of formaldehyde, formate, sarcosine, glutathione (GSH), and many other key biomolecules involved in C1 metabolism, which may be hard to measure experimentally. The individual models are then coupled and integrated dynamically using CytoSolve to produce, to the authors’ knowledge, the first comprehensive computational model of C1 metabolism. In silico modeling of the individual and integrated C1 metabolism models enables the identification of the most sensitive parameters involved in the detoxification of formaldehyde. This integrative model of C1 metabolism, giving its systems-based nature, can likely serve as a platform for: 1) generalized research and study of C1 metabolism, 2) hypothesis generation that motivates focused and specific in vitro and in vivo testing in perhaps a more efficient manner, 3) expanding a systems biology understanding of plant bio-molecular systems by integrating other known molecular pathway systems associated with C1 metabolism, and 4) exploring and testing the potential effects of exogenous inputs on the C1 metabolism system.

In-Silico Analysis &In-Vivo Results Concur on Glutathione Depletion in Glyphosate Resistant GMO Soy, Advancing a Systems Biology Framework for Safety Assessment of GMOs

This study advances previous efforts towards development of computational systems biology, in silico, methods for biosafety assessment of genetically modified organisms (GMOs). C1 metabolism is a critical molecular system in plants, fungi, and bacteria. In our previous research, critical molecular systems of C1 metabolism were identified and modeled using CytoSolve?, a platform for in silico analysis. In addition, multiple exogenous molecular systems affecting C1 metabolism such as oxidative stress, shikimic acid metabolism, glutathione biosynthesis, etc. were identified. Subsequent research expanded the C1 metabolism computational models to integrate oxidative stress, suggesting glutathione (GSH) depletion. Recent integration of data from the EPSPS genetic modification of Soy, also known as Roundup Ready Soy (RRS), with C1 metabolism predicts similar GSH depletion and HCHO accumulation in RRS. The research herein incorporates molecular systems of glutathione biosynthesis and glyphosate catabolism to expand the extant in silico models of C1 metabolism. The in silico results predict that Organic Soy will have a nearly 250% greater ratio of GSH and GSSG, a measure of glutathione levels, than in RRS that are glyphosate-treated glyphosate-resistant Soy versus the Organic Soy. These predictions also concur with in vivo greenhouse results. This concurrence suggests that these in silico models of C1 metabolism may provide a viable and validated platform for biosafety assessment of GMOs, and aid in selecting rational criteria for informing in vitro and in vivo efforts to more accurately decide in the problem formulation phase whose parameters need to be assessed so that conclusion on “substantial equivalence” or material difference of a GMO and its non-GMO counterpart can be drawn on a well-grounded basis.

Do GMOs Accumulate Formaldehyde and Disrupt Molecular Systems Equilibria? Systems Biology May Provide Answers

Safety assessment of genetically modified organisms (GMOs) is a contentious topic. Proponents of GMOs assert that GMOs are safe since the FDA’s policy of substantial equivalence considers GMOs “equivalent” to their non-GMO counterparts, and argue that genetic modification (GM) is simply an extension of a “natural” process of plant breeding, a form of “genetic modification”, though done over longer time scales. Anti-GMO activists counter that GMOs are unsafe since substantial equivalence is unscientific and outdated since it originates in the 1970s to assess safety of medical devices, which are not comparable to the complexity of biological systems, and contend that targeted GM is not plant breeding. The heart of the debate appears to be on the methodology used to determine criteria for substantial equivalence. Systems biology, which aims to understand complexity of the whole organism, as a system, rather than just studying its parts in a reductionist manner, may provide a framework to determine appropriate criteria, as it recognizes that GM, small or large, may affect emergent properties of the whole system. Herein, a promising computational systems biology method couples known perturbations on five biomolecules caused by the CP4 EPSPS GM of Glycine max L. (soybean), with an integrative model of C1 metabolism and oxidative stress (two molecular systems critical to plant function). The results predict significant accumulation of formaldehyde and concomitant depletion of glutathione in the GMO, suggesting how a “small” and single GM creates “large” and systemic perturbations to molecular systems equilibria. Regulatory agencies, currently reviewing rules for GMO safety, may wish to adopt a systems biology approach using a combination of in silico, computational methods used herein, and subsequent targeted experimental in vitro and in vivo designs, to develop a systems understanding of “equivalence” using biomarkers, such as formaldehyde and glutathione, which predict metabolic disruptions, towards modernizing the safety assessment of GMOs.