Model-based confirmation of alternative substrates of mitochondrial electron transport chain

Dark-Induced Barley Leaf Senescence - A Crop System for Studying Senescence and Autophagy Mechanisms

This review synthesizes knowledge on dark-induced barley, attached, leaf senescence (DILS) as a model and discusses the possibility of using this crop system for studying senescence and autophagy mechanisms. It addresses the recent progress made in our understanding of DILS. The following aspects are discussed: the importance of chloroplasts as early targets of DILS, the role of Rubisco as the largest repository of recoverable nitrogen in leaves senescing in darkness, morphological changes of these leaves other than those described for chloroplasts and metabolic modifications associated with them, DILS versus developmental leaf senescence transcriptomic differences, and finally the observation that in DILS autophagy participates in the circulation of cell components and acts as a quality control mechanism during senescence. Despite the progression of macroautophagy, the symptoms of degradation can be reversed. In the review, the question also arises how plant cells regulate stress-induced senescence via autophagy and how the function of autophagy switches between cell survival and cell death.

Integrative transcriptomics and proteomics analysis constructs a new molecular model for ovule abortion in the female-sterile line of Pinus tabuliformis Carr

Ovule development is critical to plant reproduction and free nuclear mitosis of megagametophyte (FNMM) is vital for ovule development. However, most results of ovule development were based on the studies in angiosperms, and its molecular regulation remained largely unknown in gymnosperms, particularly, during FNMM. In this context, we studied the genome-wide difference between sterile line (SL) and fertile line (FL) ovules using transcriptomics and proteomics approaches in Pinus tabuliformis Carr. Comparative analyses revealed that genes involved in DNA replication, DNA damage repair, Cell cycle, Apoptosis and Energy metabolism were highlighted. Further results showed the low expressions of MCM 2-7, RRM1, etc. perhaps led to abnormal DNA replication and damage repair, and the significantly different expressions of PARP2, CCs1, CCs3, etc. implied that the accumulated DNA double-stranded breaks were failed to be repaired and the cell cycle was arrested at G2/M in SL ovules, potentially resulting in the occurrence of apoptosis. Moreover, the deficiency of ETF-QO might hinder FNMM. Consequently, FNMM stopped and ovule aborted in SL ovules. Our results suggested a selective regulatory mechanism led to FNMM half-stop and ovule abortion in P. tabuliformis and these insights could be exploited to investigate the molecular regulations of ovule development in woody gymnosperms.

Differential impact of amino acids on OXPHOS system activity following carbohydrate starvation in Arabidopsis cell suspensions

Plant respiration mostly depends on the activity of glycolysis and the oxidation of organic acids in the tricarboxylic acid cycle to synthesize ATP. However, during stress situations plant cells also use amino acids as alternative substrates to donate electrons through the electron-transfer flavoprotein (ETF)/ETF:ubiquinone oxidoreductase (ETF/ETFQO) complex to the mitochondrial electron transport chain (mETC). Given this, we investigated changes of the oxidative phosphorylation (OXPHOS) system in Arabidopsis thaliana cell culture under carbohydrate starvation supplied with a range of amino acids. Induction of isovaleryl-CoA dehydrogenase (IVDH) activity was observed under carbohydrate starvation which was associated with increased amounts of IVDH protein detected by immunoblotting. Furthermore, activities of the protein complexes of the mETC were reduced under carbohydrate starvation. We also observed that OXPHOS system activity behavior is differently affected by different amino acids and that proteins associated with amino acids catabolism are upregulated in cells following carbohydrate starvation. Collectively, our results support the contention that ETF/ETFQO is an essential pathway to donate electrons to the mETC and that amino acids are alternative substrates to maintain respiration under carbohydrate starvation.

Differential proteomic analysis revealing the ovule abortion in the female-sterile line of Pinus tabulaeformis Carr

Ovule abortion affects the yield and quality of Pinus tabulaeformis Carr. seeds. Research into ovule abortion has importance for improving the seed setting rate and establishing artificial seed production techniques. Fertile line (FL) ovules (FL-E) and sterile line (SL) ovules (SL-E) in the early stage of free nuclear mitosis of megagametophyte (FNMM), FL ovules (FL-L) and SL ovules (SL-L) in the late stage of FNMM of P. tabulaeformis were collected as materials. 4192 proteins were identified by isobaric tags for relative and absolute quantitation (iTRAQ)-based analysis. Bioinformatics analysis implied that in SL ovules, substances and energy might be deficient, perhaps leading to abnormal DNA replication. Because the incomplete antioxidant system and the abnormal expression levels of enzymes involved in cell signal transduction, DNA DSBs probably occurs. Facing the abnormities of DNA replication and damage, the cell cycle was arrested and the DNA damage failed to be repaired, potentially resulting in the occurrence of PCD. Taken together, an inference can be drawn from our study - substance and energy deficiencies, reactive oxygen stress, and the failure of both cell cycle progression and DNA damage repair, which possibly hinder FNMM, leading to ovule abortion in the female-sterile line of P. tabulaeformis.

Traditional and novel tools to probe the mitochondrial metabolism in health and disease

Mitochondrial metabolism links energy production to other essential cellular processes such as signaling, cellular differentiation, and apoptosis. In addition to producing adenosine triphosphate (ATP) as an energy source, mitochondria are responsible for the synthesis of a myriad of important metabolites and cofactors such as tetrahydrofolate, α-ketoacids, steroids, aminolevulinic acid, biotin, lipoic acid, acetyl-CoA, iron-sulfur clusters, heme, and ubiquinone. Furthermore, mitochondria and their metabolism have been implicated in aging and several human diseases, including inherited mitochondrial disorders, cardiac dysfunction, heart failure, neurodegenerative diseases, diabetes, and cancer. Therefore, there is great interest in understanding mitochondrial metabolism and the complex relationship it has with other cellular processes. A large number of studies on mitochondrial metabolism have been conducted in the last 50 years, taking a broad range of approaches. In this review, we summarize and discuss the most commonly used tools that have been used to study different aspects of the metabolism of mitochondria: ranging from dyes that monitor changes in the mitochondrial membrane potential and pharmacological tools to study respiration or ATP synthesis, to more modern tools such as genetically encoded biosensors and trans-omic approaches enabled by recent advances in mass spectrometry, computation, and other technologies. These tools have allowed the large number of studies that have shaped our current understanding of mitochondrial metabolism. WIREs Syst Biol Med 2017, 9:e1373. doi: 10.1002/wsbm.1373 For further resources related to this article, please visit the WIREs website.

Inference and Prediction of Metabolic Network Fluxes

In this Update, we cover the basic principles of the estimation and prediction of the rates of the many interconnected biochemical reactions that constitute plant metabolic networks. This includes metabolic flux analysis approaches that utilize the rates or patterns of redistribution of stable isotopes of carbon and other atoms to estimate fluxes, as well as constraints-based optimization approaches such as flux balance analysis. Some of the major insights that have been gained from analysis of fluxes in plants are discussed, including the functioning of metabolic pathways in a network context, the robustness of the metabolic phenotype, the importance of cell maintenance costs, and the mechanisms that enable energy and redox balancing at steady state. We also discuss methodologies to exploit 'omic data sets for the construction of tissue-specific metabolic network models and to constrain the range of permissible fluxes in such models. Finally, we consider the future directions and challenges faced by the field of metabolic network flux phenotyping.

2-Hydroxy Acids in Plant Metabolism

Glycolate, malate, lactate, and 2-hydroxyglutarate are important 2-hydroxy acids (2HA) in plant metabolism. Most of them can be found as D- and L-stereoisomers. These 2HA play an integral role in plant primary metabolism, where they are involved in fundamental pathways such as photorespiration, tricarboxylic acid cycle, glyoxylate cycle, methylglyoxal pathway, and lysine catabolism. Recent molecular studies in Arabidopsis thaliana have helped elucidate the participation of these 2HA in in plant metabolism and physiology. In this chapter, we summarize the current knowledge about the metabolic pathways and cellular processes in which they are involved, focusing on the proteins that participate in their metabolism and cellular/intracellular transport in Arabidopsis.

Utilizing systems biology to unravel stomatal function and the hierarchies underpinning its control

Stomata control the concomitant exchange of CO2 and transpiration in land plants. While a constant supply of CO2 is need to maintain the rate of photosynthesis, the accompanying water losses must be tightly regulated to prevent dehydration and undesired metabolic changes. The factors affecting stomatal movement are directly coupled with the cellular networks of guard cells. Although the guard cell has been used as a model for characterization of signaling pathways, several important questions about its functioning remain elusive. Current modeling approaches describe the stomatal conductance in terms of relatively few easy-to-measure variables being unsuitable for in silico design of genetic manipulation strategies. Here, we argue that a system biology approach, combining modeling and high-throughput experiments, may be used to elucidate the mechanisms underlying stomata control and to determine targets for modulation of stomatal responses to environment. In support of our opinion, we review studies demonstrating how high-throughput approaches have provided a systems-view of guard cells. Finally, we emphasize the opportunities and challenges of genome-scale modeling and large-scale data integration for in silico manipulation of guard cell functions to improve crop yields, particularly under stress conditions which are of pertinence both to climate change and water use efficiency.

Exposure of barley plants to low Pi leads to rapid changes in root respiration that correlate with specific alterations in amino acid substrates

The majority of inorganic phosphate (Pi ) stress studies in plants have focused on the response after growth has been retarded. Evidence from transcript analysis, however, shows that a Pi -stress specific response is initiated within minutes of transfer to low Pi and in crop plants precedes the expression of Pi transporters and depletion of vacuolar Pi reserves by days. In order to investigate the physiological and metabolic events during early exposure to low Pi in grain crops, we monitored the response of whole barley plants during the first hours following Pi withdrawal. Lowering the concentration of Pi led to rapid changes in root respiration and leaf gas exchange throughout the early phase of the light course. Combining amino and organic acid analysis with (15) N labelling we show a root-specific effect on nitrogen metabolism linked to specific substrates of respiration as soon as 1 h following Pi withdrawal; this explains the respiratory responses observed and was confirmed by stimulation of respiration by exogenous addition of these respiratory substrates to roots. The rapid adjustment of substrates for respiration in roots during short-term Pi -stress is highlighted and this could help guide roots towards Pi -rich soil patches without compromising biomass accumulation of the plant.

Integration of transcriptomics and metabolomics data specifies the metabolic response of Chlamydomonas to rapamycin treatment

Flux phenotypes predicted by constraint-based methods can be refined by the inclusion of heterogeneous data. While recent advances facilitate the integration of transcriptomics and proteomics data, purely stoichiometry-based approaches for the prediction of flux phenotypes by considering metabolomics data are lacking. Here we propose a constraint-based method, termed TREM-Flux, for integrating time-resolved metabolomics and transcriptomics data. We demonstrate the applicability of TREM-Flux in the dissection of the metabolic response of Chlamydomonas reinhardtii to rapamycin treatment by integrating the expression levels of 982 genes and the content of 45 metabolites obtained from two growth conditions. The findings pinpoint cysteine and methionine metabolism to be most affected by the rapamycin treatment. Our study shows that the integration of time-resolved unlabeled metabolomics data in addition to transcriptomics data can specify the metabolic pathways involved in the system's response to a studied treatment.

Integration of metabolomics data into metabolic networks

Metabolite levels together with their corresponding metabolic fluxes are integrative outcomes of biochemical transformations and regulatory processes and they can be used to characterize the response of biological systems to genetic and/or environmental changes. However, while changes in transcript or to some extent protein levels can usually be traced back to one or several responsible genes, changes in fluxes and particularly changes in metabolite levels do not follow such rationale and are often the outcome of complex interactions of several components. The increasing quality and coverage of metabolomics technologies have fostered the development of computational approaches for integrating metabolic read-outs with large-scale models to predict the physiological state of a system. Constraint-based approaches, relying on the stoichiometry of the considered reactions, provide a modeling framework amenable to analyses of large-scale systems and to the integration of high-throughput data. Here we review the existing approaches that integrate metabolomics data in variants of constrained-based approaches to refine model reconstructions, to constrain flux predictions in metabolic models, and to relate network structural properties to metabolite levels. Finally, we discuss the challenges and perspectives in the developments of constraint-based modeling approaches driven by metabolomics data.

Mitochondrial 2-hydroxyglutarate metabolism

2-Hydroxyglutarate (2-HG) is a five-carbon dicarboxylic acid with a hydroxyl group at the alpha position, which forms a stereocenter in this molecule. Although the existence of mitochondrial D- and L-2HG metabolisms has long been known in different eukaryotes, the biosynthetic pathways, especially in plants, have not been completely elucidated. While D-2HG is involved in intermediary metabolism, L-2HG may not have a cellular function but it needs to be recycled through a metabolic repair reaction. Independent of their metabolic origin, D- and L-2HG are oxidized in plant mitochondria to 2-ketoglutarate through the action of two stereospecific enzymes, D- and L-2-hydroxyacid dehydrogenases. While plants are to a large extent unaffected by high cellular concentrations of D-2HG, deficiencies in the metabolism of D- and L-2HG result in fatal disorders in humans. We present current data gathered on plant D- and L-2HG metabolisms and relate it to existing knowledge on 2HG metabolism in other organisms. We focus on the metabolic origin of these compounds, the mitochondrial catabolic steps catalyzed by the stereospecific dehydrogenases, and phylogenetic relationships between different studied 2-hydroxyacid dehydrogenases.

Generalized framework for context-specific metabolic model extraction methods

Genome-scale metabolic models (GEMs) are increasingly applied to investigate the physiology not only of simple prokaryotes, but also eukaryotes, such as plants, characterized with compartmentalized cells of multiple types. While genome-scale models aim at including the entirety of known metabolic reactions, mounting evidence has indicated that only a subset of these reactions is active in a given context, including: developmental stage, cell type, or environment. As a result, several methods have been proposed to reconstruct context-specific models from existing genome-scale models by integrating various types of high-throughput data. Here we present a mathematical framework that puts all existing methods under one umbrella and provides the means to better understand their functioning, highlight similarities and differences, and to help users in selecting a most suitable method for an application.

Flux balance analysis as an alternative method to estimate fluxes without labeling

The analysis of plant metabolic networks essentially contributes to the understanding of the efficiency of plant systems in terms of their biotechnological usage. Metabolic fluxes are determined by biochemical parameters such as metabolite concentrations as well as enzyme properties and activities, which in turn are the result of various regulatory events at various levels between control of transcription and posttranslational regulation of enzyme protein activity. Thus, knowledge about metabolic fluxes on a large scale provides an integrated view on the functional state of a metabolically active cell, organ, or system. In this chapter, we introduce flux balance analysis as a constraint-based method for the prediction of optimal metabolic fluxes in a given metabolic network. Furthermore, we provide a step-by-step protocol for metabolic network reconstruction and constraint-based analysis using the COBRA Toolbox.

Metabolic control and regulation of the tricarboxylic acid cycle in photosynthetic and heterotrophic plant tissues

The tricarboxylic acid (TCA) cycle is a crucial component of respiratory metabolism in both photosynthetic and heterotrophic plant organs. All of the major genes of the tomato TCA cycle have been cloned recently, allowing the generation of a suite of transgenic plants in which the majority of the enzymes in the pathway are progressively decreased. Investigations of these plants have provided an almost complete view of the distribution of control in this important pathway. Our studies suggest that citrate synthase, aconitase, isocitrate dehydrogenase, succinyl CoA ligase, succinate dehydrogenase, fumarase and malate dehydrogenase have control coefficients flux for respiration of -0.4, 0.964, -0.123, 0.0008, 0.289, 0.601 and 1.76, respectively; while 2-oxoglutarate dehydrogenase is estimated to have a control coefficient of 0.786 in potato tubers. These results thus indicate that the control of this pathway is distributed among malate dehydrogenase, aconitase, fumarase, succinate dehydrogenase and 2-oxoglutarate dehydrogenase. The unusual distribution of control estimated here is consistent with specific non-cyclic flux mode and cytosolic bypasses that operate in illuminated leaves. These observations are discussed in the context of known regulatory properties of the enzymes and some illustrative examples of how the pathway responds to environmental change are given.

Functional genomics tools applied to plant metabolism: a survey on plant respiration, its connections and the annotation of complex gene functions

The application of post-genomic techniques in plant respiration studies has greatly improved our ability to assign functions to gene products. In addition it has also revealed previously unappreciated interactions between distal elements of metabolism. Such results have reinforced the need to consider plant respiratory metabolism as part of a complex network and making sense of such interactions will ultimately require the construction of predictive and mechanistic models. Transcriptomics, proteomics, metabolomics, and the quantification of metabolic flux will be of great value in creating such models both by facilitating the annotation of complex gene function, determining their structure and by furnishing the quantitative data required to test them. In this review, we highlight how these experimental approaches have contributed to our current understanding of plant respiratory metabolism and its interplay with associated process (e.g., photosynthesis, photorespiration, and nitrogen metabolism). We also discuss how data from these techniques may be integrated, with the ultimate aim of identifying mechanisms that control and regulate plant respiration and discovering novel gene functions with potential biotechnological implications.