SUMMARY Fungal plant pathologists have for many decades attempted to classify pathogens into groups called necrotrophs, biotrophs and, more recently, hemibiotrophs. Although these terms are well known and frequently used, disagreements about which pathogens fall into which classes, as well as the precise definition of these terms, has conspired to limit their usefulness. Dogmas concerning the properties of the classes have been progressively eroded. However, the genetic analysis of disease resistance, particularly in the model plant Arabidopsis thaliana, has provided a biologically meaningful division based on whether defence against fungal pathogens is controlled via the salicylate or jasmonate/ethylene pathways. This mode-of-defence division distinguishes necrotrophs and biotrophs but it limits the biotroph class to pathogens that possess haustoria. The small number and limited range of pathogens that infect Arabidopsis means that several interesting questions are still unanswered. Do hemibiotrophs represents a distinct class or a subclass of the necrotrophs? Does the division apply to other plant families and particularly to cereals? and does this classification help us understand the intricacies of either fungal pathogenicity or plant defence?

SUMMARYPeer-reviewed literature is today littered with exciting new tools and techniques that are being used in all areas of biology and medicine. Transcriptomics, proteomics and, more recently, metabolomics are three of these techniques that have impacted on fungal plant pathology. Used individually, each of these techniques can generate a plethora of data that could occupy a laboratory for years. When used in combination, they have the potential to comprehensively dissect a system at the transcriptional and translational level. Transcriptomics, or quantitative gene expression profiling, is arguably the most familiar to researchers in the field of fungal plant pathology. Microarrays have been the primary technique for the last decade, but others are now emerging. Proteomics has also been exploited by the fungal phytopathogen community, but perhaps not to its potential. A lack of genome sequence information has frustrated proteomics researchers and has largely contributed to this technique not fulfilling its potential. The coming of the genome sequencing era has partially alleviated this problem. Metabolomics is the most recent of these techniques to emerge and is concerned with the non-targeted profiling of all metabolites in a given system. Metabolomics studies on fungal plant pathogens are only just beginning to appear, although its potential to dissect many facets of the pathogen and disease will see its popularity increase quickly. This review assesses the impact of transcriptomics, proteomics and metabolomics on fungal plant pathology over the last decade and discusses their futures. Each of the techniques is described briefly with further reading recommended. Key examples highlighting the application of these technologies to fungal plant pathogens are also reviewed.

The Stagonospora nodorum StuA transcription factor gene SnStuA was identified by homology searching in the genome of the wheat pathogen Stagonospora nodorum. Gene expression analysis revealed that SnStuA transcript abundance increased throughout infection and in vitro growth to peak during sporulation. To investigate its role, the gene was deleted by homologous recombination. The growth of the resulting mutants was retarded on glucose compared to the wild-type growth, and the mutants also failed to sporulate. Glutamate as a sole carbon source restored the growth rate defect observed on glucose, although sporulation remained impaired. The SnstuA strains were essentially nonpathogenic, with only minor growth observed around the point of inoculation. The role of SnstuA was investigated using metabolomics, which revealed that this gene's product played a key role in regulating central carbon metabolism, with glycolysis, the TCA cycle, and amino acid synthesis all affected in the mutants. SnStuA was also found to positively regulate the synthesis of the mycotoxin alternariol. Gene expression studies on the recently identified effectors in Stagonospora nodorum found that SnStuA was a positive regulator of SnTox3 but was not required for the expression of ToxA. This study has uncovered a multitude of novel regulatory targets of SnStuA and has highlighted the critical role of this gene product in the pathogenicity of Stagonospora nodorum.

Plants and animals detect bacterial presence through Microbe-Associated Molecular Patterns (MAMPs) which induce an innate immune response. The field of fungal–bacterial interaction at the molecular level is still in its infancy and little is known about MAMPs and their detection by fungi. Exposing Fusarium graminearum to bacterial MAMPs led to increased fungal membrane hyperpolarization, a putative defense response, and a range of transcriptional responses. The fungus reacted with a different transcript profile to each of the three tested MAMPs, although a core set of genes related to energy generation, transport, amino acid production, secondary metabolism, and especially iron uptake were detected for all three. Half of the genes related to iron uptake were predicted MirA type transporters that potentially take up bacterial siderophores. These quick responses can be viewed as a preparation for further interactions with beneficial or pathogenic bacteria, and constitute a fungal innate immune response with similarities to those of plants and animals.

The wheat pathogen Stagonospora nodorum, causal organism of the wheat disease Stagonospora nodorum blotch, has emerged as a model for the Dothideomycetes, a large fungal taxon that includes many important plant pathogens. The initial annotation of the genome assembly included 16,586 nuclear gene models. These gene models were used to design a microarray that has been interrogated with labelled transcripts from six cDNA samples: four from infected wheat plants at time points spanning early infection to sporulation, and two time points taken from growth in artificial media. Positive signals of expression were obtained for 12,281 genes. This represents strong corroborative evidence of the validity of these gene models. Significantly differential expression between the various time points was observed. When infected samples were compared with axenic cultures, 2882 genes were expressed at a higher level in planta and 3630 were expressed more highly in vitro. Similar numbers were differentially expressed between different developmental stages. The earliest time points in planta were particularly enriched in differentially expressed genes. A disproportionate number of the early expressed gene products were predicted to be secreted, but otherwise had no obvious sequence homology to functionally characterized genes. These genes are candidate necrotrophic effectors. We have focused attention on genes for carbohydrate metabolism and the specific biosynthetic pathways active during growth in planta. The analysis points to a very dynamic adjustment of metabolism during infection. Functional analysis of a gene in the coenzyme A biosynthetic pathway showed that the enzyme was dispensable for growth, indicating that a precursor is supplied by the plant.