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 Anti-GMO activists counter that GMOs are unsafe since substantial equivalence is unscientific and outdated since it originates in the 1970s to assess safety of medical devices, which are not comparable to the complexity of biological systems, and contend that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.

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.

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.

From Chemical Langevin Equations to Fokker-Planck Equation: Application of Hodge Decomposition and Klein-Kramers Equation

没有详细平衡的随机的系统在各种各样的化学反应系统是普通的，例如新陈代谢的网络系统。在这些系统的研究，潜在的风景的概念是有用的。然而，是潜在的功能的存在的足够、必要的条件的，仍然是一个开的问题。在微分表格理论的使用农夫分解定理，我们集中于一般化学 Langevin 方程，它反映复杂化学反应系统。我们为潜力的存在的条件系统美化的分析。由印射随机的微分方程到一个 Hamiltonian 机械系统，我们获得化学反应系统的 FokkerPlanck 方程。获得的 FokkerPlanck 方程能在复杂化学反应系统的另外的稳定的性质的进一步的研究被使用，例如他们的稳定的州的熵。

Microenvironment promotes cytoskeleton remodeling and adaptive phenotypic transition

The cytoskeleton includes three main classes of networked filaments behaving as a coherent and complex structure that confers stability to cell shape while serving as sensor of internal/extracellular changes.Microenvironmental stimuli interfere with the non-linear dynamics that govern cytoskeleton architecture,namely by fostering symmetry breakings and transitions across different phenotypic states.Such process induces a wholecoherent adaptive response,involving the reprogramming of biochemical and gene-expression patterns.These characteristics are especially relevant during development,and in those conditions in which a deregulated crosstalk between cells and the stroma is at the core of the pathological process.Therefore,studying how the cytoskeleton can be modified–both pharmacologically and/or through microenvironment-dependent changes–has become a major area of interest in cancer and developmental biology.

On the Great Informational Domain：New Ways of Thinking in Information Science

An increasing variety of research practices are converging into information science mainstream—potentially.They are accompanied by astounding new uses of knowledge and even more astounding social transformations that revolve around information technologies.Whether a robust information science will finally emerge may not only-depend on successful discussions about the philosophy of information and the social impact of the new technologies.The most important adjustment to make is about framing a"new way of thinking"within information science itself:an inner philosophy interconnecting research practices in fundamental areas of the new science.Like in the historical birth of other major sciences,the empirical,comparative understanding of informational phenomena and informational entities should take place first.In the end,crafting a great scientific domain around information science should be a common ambition for all the scholars and researchers involved in these new studies.

<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.

盐生海藻杜氏盐藻的转录组测序以及注释（英文）

目的:解析杜氏盐藻代谢过程,主要关注盐胁迫下累积的代谢物(渗透平衡产物、多胺和类胡萝卜素)的代谢。创新点:本研究通过高通量测序产生了大量来自杜氏盐藻整个生长周期的转录组数据,描述了杜氏盐藻在盐胁迫下累积的渗透平衡产物、多胺和类胡萝卜素的代谢过程。另外通过该手段也进一步分析了盐胁迫处理下,抑制精胺合成底物的供应可能会缓解盐藻增殖对胡萝卜素含量的影响。方法:以来自3个不同生长时期的杜氏盐藻为材料,进行大规模转录组测序。在转录组功能注释的基础上,预测了杜氏盐藻盐胁迫下累积的渗透平衡产物(图3)、多胺(图4)和类胡萝卜素(图5)的代谢路径。利用相对定量聚合酶链反应(qP CR)技术构建了相关代谢路径中关键基因的表达谱(图6)。结论:通过杜氏盐藻转录组测序共获取了39 820条单一序列。在功能注释和聚类分析的基础上预测了杜氏盐藻盐胁迫下累积的渗透平衡产物(甘油和脯氨酸)、多胺以及类胡萝卜素的代谢路径。相关代谢途径的关键酶的表达谱分析,说明盐能够调节甘油、脯氨酸以及多胺的代谢过程。抑制精胺合成底物的供应可能会缓解盐藻增殖对胡萝卜素含量的影响。

Integrating impedance-based growth-rate monitoring into a microfluidic cell culture platform for live-cell microscopy

Growth rate is a widely studied parameter for various cell-based biological studies.Growth rates of cell populations can be monitored in chemostats and micro-chemostats,where nutrients are continuously replenished.Here,we present an integrated microfluidic platform that enables long-term culturing of non-adherent cells as well as parallel and mutually independent continuous monitoring of(i)growth rates of cells by means of impedance measurements and of(ii)specific other cellular events by means of high-resolution optical or fluorescence microscopy.Yeast colonies were grown in a monolayer under culturing pads,which enabled high-resolution microscopy,as all cells were in the same focal plane.Upon cell growth and division,cells leaving the culturing area passed over a pair of electrodes and were counted through impedance measurements.The impedance data could then be used to directly determine the growth rates of the cells in the culturing area.The integration of multiple culturing chambers with sensing electrodes enabled multiplexed long-term monitoring of growth rates of different yeast strains in parallel.As a demonstration,we modulated the growth rates of engineered yeast strains using calcium.The results indicated that impedance measurements provide a label-free readout method to continuously monitor the changes in the growth rates of the cells without compromising high-resolution optical imaging of single cells.

Criticality, adaptability and early-warning signals in time series in a discrete quasispecies model

Complex systems from different fields of knowledge often do not allow a mathematical description or modeling, because of their intricate structure composed of numerous interacting components. As an alternative approach, it is possible to study the way in which observables associated with the system fluctuate in time. These time series may provide valuable information about the underlying dynamics. It has been suggested that complex dynamic systems, ranging from ecosystems to financial markets and the climate, produce generic early-warning signals at the ＂tipping points,＂ where they announce a sudden shift toward a different dynamical regime, such as a population extinction, a systemic market crash, or abrupt shifts in the weather. On the other hand, the framework of Self- Organized Criticality （SOC）, suggests that some complex systems, such as life itself, may spontaneously converge toward a critical point. As a particular example, the quasispecies model suggests that RNA viruses self-organize their mutation rate near the error-catastrophe threshold, where robustness and evolvability are balanced in such a way that survival is optimized. In this paper, we study the time series associated to a classical discrete quasispecies model for different mutation rates, and identify early-warning signals for critical mutation rates near the error-catastrophe threshold, such as irregularities in the kurtosis and a significant increase in the autocorrelation range, reminiscent of 1/f noise. In the present context, we find that the early-warning signals, rather than broadcasting the collapse of the system, are the fingerprint of survival optimization.

Defining cell identity beyond the premise of differential gene expression

Identifying genes that define cell identity is a requisite step for characterising cell types and cell states and predicting cell fate choices.By far,the most widely used approach for this task is based on differential expression(DE)of genes,whereby the shift of mean expression are used as the primary statistics for identifying gene transcripts that are specific to cell types and states.While DE-based methods are useful for pinpointing genes that discriminate cell types,their reliance on measuring difference in mean expression may not reflect the biological attributes of cell identity genes.Here,we highlight the quest for non-DE methods and provide an overview of these methods and their applications to identify genes that define cell identity and functionality.