An integrated genetic, genomic and systems approach defines gene networks regulated by the interaction of light and carbon signaling pathways in Arabidopsis

<p>Abstract</p> <p>Background</p> <p>Light and carbon are two important interacting signals affecting plant growth and development. The mechanism(s) and/or genes involved in sensing and/or mediating the signaling pathways involving these interactions are unknown. This study integrates genetic, genomic and systems approaches to identify a genetically perturbed gene network that is regulated by the interaction of carbon and light signaling in Arabidopsis.</p> <p>Results</p> <p>Carbon and light insensitive (<it>cli</it>) mutants were isolated. Microarray data from <it>cli186 </it>is analyzed to identify the genes, biological processes and gene networks affected by the integration of light and carbon pathways. Analysis of this data reveals 966 genes regulated by light and/or carbon signaling in wild-type. In <it>cli186</it>, 216 of these light/carbon regulated genes are misregulated in response to light and/or carbon treatments where 78% are misregulated in response to light and carbon interactions. Analysis of the gene lists show that genes in the biological processes "energy" and "metabolism" are over-represented among the 966 genes regulated by carbon and/or light in wild-type, and the 216 misregulated genes in <it>cli186</it>. To understand connections among carbon and/or light regulated genes in wild-type and the misregulated genes in <it>cli186</it>, the microarray data is interpreted in the context of metabolic and regulatory networks. The network created from the 966 light/carbon regulated genes in wild-type, reveals that <it>cli186 </it>is affected in the light and/or carbon regulation of a network of 60 connected genes, including six transcription factors. One transcription factor, HAT22 appears to be a regulatory "hub" in the <it>cli186 </it>network as it shows regulatory connections linking a metabolic network of genes involved in "amino acid metabolism", "C-compound/carbohydrate metabolism" and "glycolysis/gluconeogenesis".</p> <p>Conclusion</p> <p>The global misregulation of gene networks controlled by light and carbon signaling in <it>cli186 </it>indicates that it represents one of the first Arabidopsis mutants isolated that is specifically disrupted in the integration of both carbon and light signals to control the regulation of metabolic, developmental and regulatory genes. The network analysis of misregulated genes suggests that <it>CLI186 </it>acts to integrate light and carbon signaling interactions and is a master regulator connecting the regulation of a host of downstream metabolic and regulatory processes.</p

QQS orphan gene regulates carbon and nitrogen partitioning across species via NF-YC interactions

The allocation of carbon and nitrogen resources to the synthesis of plant proteins, carbohydrates, and lipids is complex and under the control of many genes; much remains to be understood about this process. QQS (Qua-Quine Starch; At3g30720), an orphan gene unique to Arabidopsis thaliana, regulates metabolic processes affecting carbon and nitrogen partitioning among proteins and carbohydrates, modulating leaf and seed composition in Arabidopsis and soybean. Here the universality of QQS function in modulating carbon and nitrogen allocation is exemplified by a series of transgenic experiments. We show that ectopic expression of QQS increases soybean protein independent of the genetic background and original protein content of the cultivar. Furthermore, transgenic QQS expression increases the protein content of maize, a C4 species (a species that uses 4-carbon photosynthesis), and rice, a protein-poor agronomic crop, both highly divergent from Arabidopsis. We determine that QQS protein binds to the transcriptional regulator AtNF-YC4 (Arabidopsis nuclear factor Y, subunit C4). Overexpression of AtNF-YC4 in Arabidopsis mimics the QQS-overexpression phenotype, increasing protein and decreasing starch levels. NF-YC, a component of the NF-Y complex, is conserved across eukaryotes. The NF-YC4 homologs of soybean, rice, and maize also bind to QQS, which provides an explanation of how QQS can act in species where it does not occur endogenously. These findings are, to our knowledge, the first insight into the mechanism of action of QQS in modulating carbon and nitrogen allocation across species. They have major implications for the emergence and function of orphan genes, and identify a nontransgenic strategy for modulating protein levels in crop species, a trait of great agronomic significance

Modeling the global effect of the basic-leucine zipper transcription factor 1 (bZIP1) on nitrogen and light regulation in Arabidopsis

Background: Nitrogen and light are two major regulators of plant metabolism and development. While genes involved in the control of each of these signals have begun to be identified, regulators that integrate gene responses to nitrogen and light signals have yet to be determined. Here, we evaluate the role of bZIP1, a transcription factor involved in light and nitrogen sensing, by exposing wild-type (WT) and bZIP1 T-DNA null mutant plants to a combinatorial space of nitrogen (N) and light (L) treatment conditions and performing transcriptome analysis. We use ANOVA analysis combined with clustering and Boolean modeling, to evaluate the role of bZIP1 in mediating L and N signaling genome-wide. Results: This transcriptome analysis demonstrates that a mutation in the bZIP1 gene can alter the L and/or N-regulation of several gene clusters. More surprisingly, the bZIP1 mutation can also trigger N and/or L regulation of genes that are not normally controlled by these signals in WT plants. This analysis also reveals that bZIP1 can, to a large extent, invert gene regulation (e. g., several genes induced by N in WT plants are repressed by N in the bZIP1 mutant). Conclusion: These findings demonstrate that the bZIP1 mutation triggers a genome-wide de-regulation in response to L and/or N signals that range from i) a reduction of the L signal effect, to ii) unlocking gene regulation in response to L and N combinations. This systems biology approach demonstrates that bZIP1 tunes L and N signaling relationships genome-wide, and can suppress regulatory mechanisms hypothesized to be needed at different developmental stages and/or environmental conditions

Individual vs. combinatorial effect of elevated CO2 conditions and salinity stress on Arabidopsis thaliana liquid cultures: Comparing the early molecular response using time-series transcriptomic and metabolomic analyses

<p>Abstract</p> <p><b>Background</b></p> <p>In this study, we investigated the individual and combinatorial effect of elevated CO₂conditions and salinity stress on the dynamics of both the transcriptional and metabolic physiology of <it>Arabidopsis thaliana </it>liquid hydroponic cultures over the first 30 hours of continuous treatment. Both perturbations are of particular interest in plant and agro-biotechnological applications. Moreover, within the timeframe of this experiment, they are expected to affect plant growth to opposite directions. Thus, a major objective was to investigate whether this expected "divergence" was valid for the individual perturbations and to study how it is manifested under the combined stress at two molecular levels of cellular function, using high-throughput analyses.</p> <p><b>Results</b></p> <p>We observed that a) high salinity has stronger effect than elevated CO₂at both the transcriptional and metabolic levels, b) the transcriptional responses to the salinity and combined stresses exhibit strong similarity, implying a robust transcriptional machinery acting to the salinity stress independent of the co-occurrence of elevated CO₂, c) the combinatorial effect of the two perturbations on the metabolic physiology is milder than of the salinity stress alone. Metabolomic analysis suggested that the beneficial role of elevated CO₂on salt-stressed plants within the timeframe of this study should be attributed to the provided additional resources; these allow the plants to respond to high salinity without having to forfeit other major metabolic functions, and d) 9 h-12 h and 24 h of treatment coincide with significant changes in the metabolic physiology under any of the investigated stresses. Significant differences between the acute and longer term responses were observed at both molecular levels.</p> <p><b>Conclusions</b></p> <p>This study contributes large-scale dynamic omic data from two levels of cellular function for a plant system under various stresses. It provides an additional example of the power of integrated omic analyses for the comprehensive study of the molecular physiology of complex biological systems. Moreover, taking into consideration the particular interest of the two investigated perturbations in plant biotechnology, enhanced understanding of the molecular physiology of the plants under these conditions could lead to the design of novel metabolic engineering strategies to increase the resistance of commercial crops to salinity stress.</p

The QQS orphan gene of Arabidopsis modulates carbon and nitrogen allocation in soybean

The genome of each species contains as high as 8% of genes that are uniquely present in that species. Little is known about the functional significance of these so-called species specific or orphan genes. The Arabidopsis thaliana gene Qua-Quine Starch (QQS) is species specific. Here, we show that altering QQS expression in Arabidopsis affects carbon partitioning to both starch and protein. We hypothesized QQS may be conserved in a feature other than primary sequence, and as such could function to impact composition in another species. To test the potential of QQS in affecting composition in an ectopic species, we introduced QQS into soybean. Soybean T1 lines expressing QQS have up to 80% decreased leaf starch and up to 60% increased leaf protein; T4 generation seeds from field-grown plants contain up to 13% less oil, while protein is increased by up to 18%. These data broaden the concept of QQS as a modulator of carbon and nitrogen allocation, and demonstrate that this species-specific gene can affect the seed composition of an agronomic species thought to have diverged from Arabidopsis 100 million years ago

Correlation Network Analysis reveals a sequential reorganization of metabolic and transcriptional states during germination and gene-metabolite relationships in developing seedlings of Arabidopsis

<p>Abstract</p> <p>Background</p> <p>Holistic profiling and systems biology studies of nutrient availability are providing more and more insight into the mechanisms by which gene expression responds to diverse nutrients and metabolites. Less is known about the mechanisms by which gene expression is affected by endogenous metabolites, which can change dramatically during development. Multivariate statistics and correlation network analysis approaches were applied to non-targeted profiling data to investigate transcriptional and metabolic states and to identify metabolites potentially influencing gene expression during the heterotrophic to autotrophic transition of seedling establishment.</p> <p>Results</p> <p>Microarray-based transcript profiles were obtained from extracts of Arabidopsis seeds or seedlings harvested from imbibition to eight days-old. ¹H-NMR metabolite profiles were obtained for corresponding samples. Analysis of transcript data revealed high differential gene expression through seedling emergence followed by a period of less change. Differential gene expression increased gradually to day 8, and showed two days, 5 and 7, with a very high proportion of up-regulated genes, including transcription factor/signaling genes. Network cartography using spring embedding revealed two primary clusters of highly correlated metabolites, which appear to reflect temporally distinct metabolic states. Principle Component Analyses of both sets of profiling data produced a chronological spread of time points, which would be expected of a developmental series. The network cartography of the transcript data produced two distinct clusters comprising days 0 to 2 and days 3 to 8, whereas the corresponding analysis of metabolite data revealed a shift of day 2 into the day 3 to 8 group. A metabolite and transcript pair-wise correlation analysis encompassing all time points gave a set of 237 highly significant correlations. Of 129 genes correlated to sucrose, 44 of them were known to be sucrose responsive including a number of transcription factors.</p> <p>Conclusions</p> <p>Microarray analysis during germination and establishment revealed major transitions in transcriptional activity at time points potentially associated with developmental transitions. Network cartography using spring-embedding indicate that a shift in the state of nutritionally important metabolites precedes a major shift in the transcriptional state going from germination to seedling emergence. Pair-wise linear correlations of transcript and metabolite levels identified many genes known to be influenced by metabolites, and provided other targets to investigate metabolite regulation of gene expression during seedling establishment.</p

Mapping metabolic fluxes in plant cells to understand carbon-nitrogen interactions and nitrogen storage and cycling

Plants provide commodities like food, fiber, fuel and chemicals. Understanding plant metabolism will help find genetic engineering targets that enhance production of these commodities. Interactions between the macronutrients - carbon (C) and nitrogen (N) determine growth and developmental functions in plants (Nunes-Nesi, Fernie, and Stitt 2010; Sakakibara, Takei, and Hirose 2006) and are regulated by complex mechanisms that need systems-level analyses. Metabolic fluxes, the rates of C flow in metabolic pathways, provide a system-wide view of metabolism and are quantified by steady state metabolic flux analysis (MFA) wherein isotopic tracers (13C, 15N) are fed to the cells and the resulting labeling patterns of biomass components are used to fit the fluxes. In this study we i) statistically designed isotope labeling experiments (ILEs) in silico to enhance accuracy of flux estimates through the pentose phosphate pathway (PPP) ii) conducted MFA on heterotrophic cell suspensions of Arabidopsis thaliana (Arabidopsis), a model plant, to investigate regulatory role of light in cell metabolism and iii) conducted MFA on cell suspensions of poplar (Populus tremula &times; Populus alba; clone N 717-B4), a potential biofuel crop, to understand C-N interactions. In silico label design studies determined that accuracy of flux estimates in the PPP improves by ILEs with 1,2-13C glucose and measuring labeling patterns of sugars, especially ribose. Metabolic fluxes, estimated by the designed ILEs on Arabidopsis cells, under continuous light or dark, showed negligible changes between treatments indicating that light does not regulate central carbon metabolism in heterotrophic Arabidopsis cells. The designed ILEs improved confidences of non-oxidative PPP flux estimates by 40-80% from previous studies (Masakapalli et al. 2009a). ILEs on poplar cell suspensions, grown in batch cultures, displayed unexpected back-mixing between unlabeled seed biomass and newly synthesized labeled biomass. Novel metabolic network models were developed that successfully account for observed back-mixing. ILEs on poplar cells, subjected to different C-N supply treatments to understand C-N interactions showed significant differences in phenylalanine labeling which may implicate role of flavonoid biosynthesis pathway in C-N interactions. Design of ILEs and subsequent improvement in flux estimates and the improvements in modeling metabolic networks are the novel contributions of this work

A clade-specific Arabidopsis gene connects primary metabolism and senescence

Plants have to deal with environmental insults as they cannot move to escape from stressful conditions. To do so, they have evolved novel components that respond to the changing environment. The Qua Quine Starch (QQS) gene is an Arabidopsis-specific orphan gene that connects primary metabolism and adaptation to environment changes. AT1G64360, which we term an SAQR (Senescence-associated and QQS-related) gene, respond to oxidative stress. Here, we show that SAQR is up-regulated in high-starch QQS-RNAi mutants. Bioinformatics analyses indicates that SAQR is unique to six species within the family Brassicaceae; the gene may have arisen about 20 million years ago (MYA). Meta-analysis of public microarray data, in combination with histochemical experiments using transgenic Arabidopsis SAQR promoter-GUS lines, indicate that SAQR’s expression is correlated with expression of genes involved in senescence, defense, and stress responses. SAQR expression increases in leaf vasculature as tissues mature and senesce. SAQR expression is expression is not increased in true leaves under experimentally-induced senescence of thirty day-old plants. However, SAQR expression increases in cotyledons of seven day-old seedlings in response to experimentally-induced senescence. Furthermore, starch accumulation is increased in the leaves of transgenic SAQR-overexpression lines, and conversely starch levels are decreased in a T-DNA SAQR knockout line. Levels of metabolites and transcripts involved in biotic and abiotic stress responses and chlorophyll metabolism are altered in these T-DNA knockout mutants. These data may imply changes to processes that occur in senescent leaves. SAQR may function in the QQS network, playing a role in its integration of primary metabolism and adaptation to internal and environmental changes, specifically those that affect the process of senescence

INTEGRATED GENOMIC MARKERS FOR CHEMOTHERAPEUTICS

Ph.DDOCTOR OF PHILOSOPH