School of BioSciences - Research Publications

Permanent URI for this collection

Search Results

Now showing 1 - 6 of 6
  • Item
    Thumbnail Image
    De novo transcriptome assembly and analysis of differentially expressed genes of two barley genotypes reveal root-zone-specific responses to salt exposure
    Hill, CB ; Cassin, A ; Keeble-Gagnere, G ; Doblin, MS ; Bacic, A ; Roessner, U (NATURE PORTFOLIO, 2016-08-16)
    Plant roots are the first organs sensing and responding to salinity stress, manifested differentially between different root types, and also at the individual tissue and cellular level. High genetic diversity and the current lack of an assembled map-based sequence of the barley genome severely limit barley research potential. We used over 580 and 600 million paired-end reads, respectively, to create two de novo assemblies of a barley landrace (Sahara) and a malting cultivar (Clipper) with known contrasting responses to salinity. Generalized linear models were used to statistically access spatial, treatment-related, and genotype-specific responses. This revealed a spatial gene expression gradient along the barley root, with more differentially expressed transcripts detected between different root zones than between treatments. The root transcriptome also showed a gradual transition from transcripts related to sugar-mediated signaling at the root meristematic zone to those involved in cell wall metabolism in the elongation zone, and defense response-related pathways toward the maturation zone, with significant differences between the two genotypes. The availability of these additional transcriptome reference sets will serve as a valuable resource to the cereal research community, and may identify valuable traits to assist in breeding programmes.
  • Item
    Thumbnail Image
    A Quantitative Profiling Method of Phytohormones and Other Metabolites Applied to Barley Roots Subjected to Salinity Stress
    Cao, D ; Lutz, A ; Hill, CB ; Callahan, DL ; Roessner, U (Frontiers Media, 2017-01-10)
    As integral parts of plant signaling networks, phytohormones are involved in the regulation of plant metabolism and growth under adverse environmental conditions, including salinity. Globally, salinity is one of the most severe abiotic stressors with an estimated 800 million hectares of arable land affected. Roots are the first plant organ to sense salinity in the soil, and are the initial site of sodium (Na+) exposure. However, the quantification of phytohormones in roots is challenging, as they are often present at extremely low levels compared to other plant tissues. To overcome this challenge, we developed a high-throughput LC-MS method to quantify ten endogenous phytohormones and their metabolites of diverse chemical classes in roots of barley. This method was validated in a salinity stress experiment with six barley varieties grown hydroponically with and without salinity. In addition to phytohormones, we quantified 52 polar primary metabolites, including some phytohormone precursors, using established GC-MS and LC-MS methods. Phytohormone and metabolite data were correlated with physiological measurements including biomass, plant size and chlorophyll content. Root and leaf elemental analysis was performed to determine Na+ exclusion and K+ retention ability in the studied barley varieties. We identified distinct phytohormone and metabolite signatures as a response to salinity stress in different barley varieties. Abscisic acid increased in the roots of all varieties under salinity stress, and elevated root salicylic acid levels were associated with an increase in leaf chlorophyll content. Furthermore, the landrace Sahara maintained better growth, had lower Na+ levels and maintained high levels of the salinity stress linked metabolite putrescine as well as the phytohormone metabolite cinnamic acid, which has been shown to increase putrescine concentrations in previous studies. This study highlights the importance of root phytohormones under salinity stress and the multi-variety analysis provides an important update to analytical methodology, and adds to the current knowledge of salinity stress responses in plants at the molecular level.
  • Item
    Thumbnail Image
    Spatio-Temporal Metabolite and Elemental Profiling of Salt Stressed Barley Seeds During Initial Stages of Germination by MALDI-MSI and mu-XRF Spectrometry
    Gupta, S ; Rupasinghe, T ; Callahan, DL ; Natera, SHA ; Smith, PMC ; Hill, CB ; Roessner, U ; Boughton, BA (Frontiers Media, 2019-09-25)
    Seed germination is the essential first step in crop establishment, and can be severely affected by salinity stress which can inhibit essential metabolic processes during the germination process. Salt stress during seed germination can trigger lipid-dependent signalling cascades that activate plant adaptation processes, lead to changes in membrane fluidity to help resist the stress, and cause secondary metabolite responses due to increased oxidative stress. In germinating barley (Hordeum vulgare), knowledge of the changes in spatial distribution of lipids and other small molecules at a cellular level in response to salt stress is limited. In this study, mass spectrometry imaging (MSI), liquid chromatography quadrupole time-of-flight mass spectrometry (LC-QToF-MS), inductively coupled plasma mass spectrometry (ICP-MS), and X-ray fluorescence (XRF) were used to determine the spatial distribution of metabolites, lipids and a range of elements, such as K+ and Na+, in seeds of two barley genotypes with contrasting germination phenology (Australian barley varieties Mundah and Keel). We detected and tentatively identified more than 200 lipid species belonging to seven major lipid classes (fatty acyls, glycerolipids, glycerophospholipids, sphingolipids, prenol lipids, sterol lipids, and polyketides) that differed in their spatial distribution based on genotype (Mundah or Keel), time post-imbibition (0 to 72 h), or treatment (control or salt). We found a tentative flavonoid was discriminant in post-imbibed Mundah embryos under saline conditions, and a delayed flavonoid response in Keel relative to Mundah. We further employed MSI-MS/MS and LC-QToF-MS/MS to explore the identity of the discriminant flavonoid and study the temporal pattern in five additional barley genotypes. ICP-MS was used to quantify the elemental composition of both Mundah and Keel seeds, showing a significant increase in Na+ in salt treated samples. Spatial mapping of elements using µ-XRF localized the elements within the seeds. This study integrates data obtained from three mass spectrometry platforms together with µ-XRF to yield information on the localization of lipids, metabolites and elements improving our understanding of the germination process under salt stress at a molecular level.
  • Item
    Thumbnail Image
    High-mass-resolution MALDI mass spectrometry imaging reveals detailed spatial distribution of metabolites and lipids in roots of barley seedlings in response to salinity stress
    Sarabia, LD ; Boughton, BA ; Rupasinghe, T ; van de Meene, AML ; Callahan, DL ; Hill, CB ; Roessner, U (SPRINGER, 2018-05)
    INTRODUCTION: Mass spectrometry imaging (MSI) is a technology that enables the visualization of the spatial distribution of hundreds to thousands of metabolites in the same tissue section simultaneously. Roots are below-ground plant organs that anchor plants to the soil, take up water and nutrients, and sense and respond to external stresses. Physiological responses to salinity are multifaceted and have predominantly been studied using whole plant tissues that cannot resolve plant salinity responses spatially. OBJECTIVES: This study aimed to use a comprehensive approach to study the spatial distribution and profiles of metabolites, and to quantify the changes in the elemental content in young developing barley seminal roots before and after salinity stress. METHODS: Here, we used a combination of liquid chromatography-mass spectrometry (LC-MS), inductively coupled plasma mass spectrometry (ICP-MS), and matrix-assisted laser desorption/ionization (MALDI-MSI) platforms to profile and analyze the spatial distribution of ions, metabolites and lipids across three anatomically different barley root zones before and after a short-term salinity stress (150 mM NaCl). RESULTS: We localized, visualized and discriminated compounds in fine detail along longitudinal root sections and compared ion, metabolite, and lipid composition before and after salt stress. Large changes in the phosphatidylcholine (PC) profiles were observed as a response to salt stress with PC 34:n showing an overall reduction in salt treated roots. ICP-MS analysis quantified changes in the elemental content of roots with increases of Na+ and decreases of K+ content. CONCLUSION: Our results established the suitability of combining three mass spectrometry platforms to analyze and map ionic and metabolic responses to salinity stress in plant roots and to elucidate tolerance mechanisms in response to abiotic stress, such as salinity stress.
  • Item
    Thumbnail Image
    Metabolomics, standards, and metabolic modeling for synthetic biology in plants
    Hill, CB ; Czauderna, T ; Klapperstuck, M ; Roessner, U ; Schreiber, F (FRONTIERS MEDIA SA, 2015)
    Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions.
  • Item
    Thumbnail Image
    Detection of QTL for metabolic and agronomic traits in wheat with adjustments for variation at genetic loci that affect plant phenology
    Hill, CB ; Taylor, JD ; Edwards, J ; Mather, D ; Langridge, P ; Bacic, A ; Roessner, U (ELSEVIER IRELAND LTD, 2015-04)
    Mapping of quantitative trait loci associated with levels of individual metabolites (mQTL) was combined with the mapping of agronomic traits to investigate the genetic basis of variation and co-variation in metabolites, agronomic traits, and plant phenology in a field-grown bread wheat population. Metabolome analysis was performed using liquid chromatography-mass spectrometry resulting in identification of mainly polar compounds, including secondary metabolites. A total of 558 metabolic features were obtained from the flag leaves of 179 doubled haploid lines, of which 197 features were putatively identified, mostly as alkaloids, flavonoids and phenylpropanoids. Coordinated genetic control was observed for several groups of metabolites, such as organic acids influenced by two loci on chromosome 7A. Five major phenology-related loci, which were introduced as cofactors in the analyses, differed in their impact upon metabolic and agronomic traits with QZad-aww-7A having more impact on the expression of both metabolite and agronomic QTL than Ppd-B1, Vrn-A1, Eps, and QZad-aww-7D. This QTL study validates the utility of combining agronomic and metabolomic traits as an approach to identify potential trait enhancement targets for breeding selection and reinforces previous results that demonstrate the importance of including plant phenology in the assessment of useful traits in this wheat mapping population.