Plate growth assay.

<p>Colony diameter was measured after 18 days growth with n = 3. Standard error bars are shown. MM, minimal media; N-GABA, minimal media with GABA as the sole nitrogen source; C-GABA, minimal media with GABA as the sole carbon source; N-Glu, minimal media with glutamate as the sole nitrogen source; C-Glu, minimal media with glutamate as the sole carbon source; MM+GABA, minimal media with 1 mM GABA; MM+Glu, minimal media with 1 mM glutamate.</p

Characterising the Role of GABA and Its Metabolism in the Wheat Pathogen <i>Stagonospora nodorum</i>

<div><p>A reverse genetics approach was used to investigate the role of γ-aminobutyric acid metabolism in the wheat pathogenic fungus <i>Stagonospora nodorum</i>. The creation of mutants lacking <i>Sdh1</i>, the gene encoding succinic semialdehyde dehydrogenase, resulted in strains that grew poorly on γ-aminobutyric acid as a nitrogen source. The <i>sdh1</i> mutants were more susceptible to reactive oxygen stress but were less affected by increased growth temperatures. Pathogenicity assays revealed that the metabolism of γ-aminobutyric acid is required for complete pathogenicity. Growth assays of the wild-type and mutant strains showed that the inclusion of γ-aminobutyric acid as a supplement in minimal media (i.e., not as a nitrogen or carbon source) resulted in restricted growth but increased sporulation. The addition of glutamate, the precursor to GABA, had no effect on either growth or sporulation. The γ-aminobutyric acid effect on sporulation was found to be dose dependent and not restricted to <i>Stagonospora nodorum</i> with a similar effect observed in the dothideomycete <i>Botryosphaeria</i> sp. The positive effect on sporulation was assayed using isomers of γ-aminobutyric acid and other metabolites known to influence asexual development in <i>Stagonospora nodorum</i> but no effect was observed. These data demonstrate that γ-aminobutyric acid plays an important role in <i>Stagonospora nodorum</i> in responding to environmental stresses while also having a positive effect on asexual development.</p></div

Plate growth assays of <i>S. nodorum</i> SN15 growing on minimal media supplemented with different compounds.

<p>All compounds were added to a final concentration of 1</p

A genome-wide survey of the secondary metabolite biosynthesis genes in the wheat pathogen <i>Parastagonospora nodorum</i>

<div><p>The model pathogen <i>Parastagonospora nodorum</i> is a necrotroph and the causal agent of the wheat disease Septoria nodorum blotch (SNB). The sequenced <i>P. nodorum</i> genome has revealed that the fungus harbours a large number of secondary metabolite genes. Secondary metabolites are known to play important roles in the virulence of plant pathogens, but limited knowledge is available about the SM repertoire of this wheat pathogen. Here, we review the secondary metabolites that have been isolated from <i>P. nodorum</i> and related species of the same genus and provide an in-depth genome-wide overview of the secondary metabolite gene clusters encoded in the <i>P. nodorum</i> genome. The secondary metabolite gene survey reveals that <i>P. nodorum</i> is capable of producing a diverse range of small molecules and exciting prospects exist for discovery of novel virulence factors and bioactive molecules.</p></div

An analysis of the role of <i>Sdh1</i> during temperature and reactive oxygen species (ROS) stress.

<p>(A) Plate growth assays of the <i>S. nodorum</i> wild-type SN15 strain and the <i>sdh1-9</i> mutant at 21°C and 25°C. (B) Spores collected and counted from the plate sporulation in (A). (C) Growth assays of the SN15 (solid lines) and <i>sdh1-9</i> (broken lines) strains on different concentrations of H₂O₂.</p

The GABA shunt.

<p>The GABA shunt.</p

Pathogenicity scores for the wheat leaf infection assays.

<p>N = 5 and standard error bars are shown.</p

Growth and sporulation assays of <i>S. nodorum</i> SN15 growing in increasing GABA concentrations.

<p>(A) Images of <i>S. nodorum</i> growing at different GABA concentrations captured at eight days post-inoculation. Increasing levels of pycnidia (small dark spots) are clearly evident with higher concentrations of GABA. (B) Colony diameter; (C) Total number of spores per mL produced; (D) Number of spores produced divided by the area of colony growth. N = 6 and standard error bars are shown. The letters shown above each of the bars represent the statistical significance for that treatment with different letters representing treatments that are statistically different (p<0.05).</p

Sporulation assay for each of the strains grown under different nutritional conditions.

<p>MM, minimal media; N-GABA, minimal media with GABA as the sole nitrogen source; C-GABA, minimal media with GABA as the sole carbon source; MM+GABA, minimal media with 1 mM GABA; MM+GABA, minimal media with 1 mM GABA; MM+Glu, minimal media with 1 mM glutamate.</p

Coverage and Consistency: Bioinformatics Aspects of the Analysis of Multirun iTRAQ Experiments with Wheat Leaves

The hexaploid genome of bread wheat (<i>Triticum aestivum</i>) is large (17 Gb) and repetitive, and this has delayed full sequencing and annotation of the genome, which is a prerequisite for effective quantitative proteomics analysis. Aware of these constraints we investigated the most effective approaches for shotgun proteomic analyses of bread wheat that would support large-scale quantitative comparisons using iTRAQ reagents. We used a data set that was generated by two-dimensional LC–MS of iTRAQ labeled peptides from wheat leaves. The main items considered in this study were the choice of sequence database for matching LC–MS data, the consistency of identification when multiple LC–MS runs were acquired, and the options for downstream functional analysis to generate useful insight. For peptide identification we examined the extensive NCBInr plant database, a smaller composite cereals database, the <i>Brachypodium distachyon</i> model plant genome, the EST-based SuperWheat database, as well as the genome sequence from the recently sequenced D-genome progenitor <i>Aegilops tauschii.</i> While the most spectra were assigned by using the SuperWheat database, this extremely large database could not be readily manipulated for the robust protein grouping that is required for large-scale, multirun quantitative experiments. We demonstrated a pragmatic alternative of using the composite cereals database for peptide spectra matching. The stochastic aspect of protein grouping across LC–MS runs was investigated using the smaller composite cereals database where we found that attaching the <i>Brachypodium</i> best BLAST hit reduced this problem. Further, assigning quantitation to the best <i>Brachypodium</i> locus yielded promising results enabling integration with existing downstream data mining and functional analysis tools. Our study demonstrated viable approaches for quantitative proteomics analysis of bread wheat samples and shows how these approaches could be similarly adopted for analysis of other organisms with unsequenced or incompletely sequenced genomes