Metabolic Biomarker Panels of Response to Fusarium Head Blight Infection in Different Wheat Varieties

Čuperlović-Culf, Miroslava; Wang, Lipu; Forseille, Lily; Boyle, Kerry; Merkley, Nadine; Burton, Ian W.; Fobert, Pierre R.

doi:10.1371/journal.pone.0153642

Cited by 39 publications

(37 citation statements)

References 37 publications

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“…Separate mentioning needs to made about the appearance of F. langsethiae as a relatively new species on wheat, since it was most often identified earlier on barley and oat. This species is similar in the biology and morphology to F. poae, but differs by a high production of dangerous mycotoxins HT-2 and T-2 (Grabowski et al, 2012;Cuperlovic-Culf et al, 2016;Figueroa et al, 2017). Its appearance on wheat and, in general, in sufficient quantities is a dangerous tendency towards increase in the levels of contamination of the grain with mycotoxins.…”

Section: Discussionmentioning

confidence: 98%

Distribution of species of Fusarium and Alternaria genera on cereals in Ukraine

et al. 2019

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In recent years phytosanitary situation in agrophytocenooses has worsened, and damage caused by diseases increased. In the conditions of field experiments in the vegetative seasons of 2015–2018 the dissemination of Fusarium and Alternaria spp., and composition of Fusarium species in Ukraine were studied. The selection of plant samples was carried out twice – at the beginning of vegetation and before entering into wintering. In autumn the samples of winter wheat with the symptoms of root rot from more than 150 fields from different oblasts of Ukraine were selected. Later these samples were analyzed using PCR method in real time to determine the species composition of Fusarium genus. In the analysis of grain material from different regions of Ukraine we determined high level of Fusarium infection. Fusariosis of grain were observed in several areas in more than 50% of samples from all regions of county. In all oblasts of Ukraine, the high level of Alternarìa infection were identified also. It is found out that the main sources of the root rot are F. tricinctum, F. graminearum, F. poae and F. avenaceum. The role of F. avenaceum, as the pathogen of root rot was at the level of F. graminearum and F. sporotrichioides in most regions of Ukraine. The studies reveiled that the dominant species in the grain material were F. tricinctum and F. graminearum, presence of which exceeded 20–25%. Quite often F. poae and F. sporotrichioides was observed, presence of which in grain equaled 15–20%. In the Central, Eastern and Southern regions, the dominant species was F. avenaceum with a level of identification 15–23%. F. culmorum, F. langsethiae were within 5–7%. The species composition of fusariosis in the grain and the species composition of pathogens that cause fusariosis root rot in general are similar. Fusariosis becomes one of the most common and harmful diseases of grain crops, and cause no less harm than smut diseases. The fact that their danger continues to grow is explained by adverse weather conditions (alternation of wet and arid periods) and reduction of general level of cultivation: distribution of corn fields, decrease of expenses on tillage, and low-quality pesticides, often generics. It should be noted that the best precursors for cereal crops, for example, soy bean, is also vulnerable to fusariosis. Therefore, performing protective measures at preparing of grain for sowing and in the period of vegetation of the crop will contribute to total reduction of the levels of infection of agrophytocenoses with Fusarium species and potential damage to the cultivated plants. The study revealed that species of fungi belonging to the Alternaria and Fusarium genera infect wheat grain in the yields of each year. The results of data analysis of the genera showed antagonistic interaction between them. Perhaps, particularly at such negative interaction in the vegetative season of 2018, during, practically continuous warm rains in the "grain belt" of Ukraine during the generative period of development of wheat, the grain was infected with Alternaria spp. at moderate presence of Fusarium species. These patterns in the interaction of Alternaria and Fusarium spp. are expedient to be taken into account during development of systems of control of fusariosis using fungicides. Absence of contamination of grains with mycotoxins of Fusarium species does not reduce the levels of danger for crops posed by probable increase in the levels of presence of Alternaria mycotoxins – alternariol, alternariol monomethyl ether, tenuazonic acid, etc. Certainly, the results of the vegetation season of 2018 year and the large-scale alternariosis infication require clarifications to the current normative documentation. The conducted researches are important for improvement of protection systems for crops in intensive technologies of cultivation.

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Section: Discussionmentioning

confidence: 98%

Distribution of species of Fusarium and Alternaria genera on cereals in Ukraine

et al. 2019

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“…NMR-based metabolic analysis indicated the higher accumulation of some disease-resistant biomarkers, such as trehalose, asparagine, phenylalanine, myoinositol, 3-hydroxybutarate, and L-alanine [21]. Likewise, in an effort to identify other disease-resistant biomarkers in wheat against Fusarium graminearum, metabolic analysis was conducted via NMR and revealed the enhanced production of spermine, putrescine, GABA, inositols, galactose, and lactic acid [180]. Comparative metabolomics analysis has been carried out to study the metabolome of resistant and susceptible varieties of wheat infected by wheat streak mosaic virus.…”

Section: Elucidation Of Biotic Stress Resistance In Plantsmentioning

confidence: 99%

Metabolomics: A Way Forward for Crop Improvement

et al. 2019

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Metabolomics is an emerging branch of “omics” and it involves identification and quantification of metabolites and chemical footprints of cellular regulatory processes in different biological species. The metabolome is the total metabolite pool in an organism, which can be measured to characterize genetic or environmental variations. Metabolomics plays a significant role in exploring environment–gene interactions, mutant characterization, phenotyping, identification of biomarkers, and drug discovery. Metabolomics is a promising approach to decipher various metabolic networks that are linked with biotic and abiotic stress tolerance in plants. In this context, metabolomics-assisted breeding enables efficient screening for yield and stress tolerance of crops at the metabolic level. Advanced metabolomics analytical tools, like non-destructive nuclear magnetic resonance spectroscopy (NMR), liquid chromatography mass-spectroscopy (LC-MS), gas chromatography-mass spectrometry (GC-MS), high performance liquid chromatography (HPLC), and direct flow injection (DFI) mass spectrometry, have sped up metabolic profiling. Presently, integrating metabolomics with post-genomics tools has enabled efficient dissection of genetic and phenotypic association in crop plants. This review provides insight into the state-of-the-art plant metabolomics tools for crop improvement. Here, we describe the workflow of plant metabolomics research focusing on the elucidation of biotic and abiotic stress tolerance mechanisms in plants. Furthermore, the potential of metabolomics-assisted breeding for crop improvement and its future applications in speed breeding are also discussed. Mention has also been made of possible bottlenecks and future prospects of plant metabolomics.

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“…Canadian genotypes Stettler (ST) and Muchmore (MM) have high quality and yield of wheat grain [18,19,20], but display moderate susceptibility to FHB. The last Canadian elite genotype, FL62R1 (FL), has FHB resistance [21,22]. Each genotype was point inoculated with one of the two Fg strains producing different trichothecene chemotypes [3-O-acetyl DON (3ADON) and 15-O-acetyl DON (15ADON)] or mock-inoculated with water as described previously [16].…”

Section: The Datasetsmentioning

confidence: 99%

Differential expression feature extraction (DEFE) and its application in RNA-seq data analysis

Pan

Liu

et al. 2019

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In differential gene expression data analysis, one objective is to identify groups of co-expressed genes from a large dataset to detect the association between such a group of genes and a phenotypic trait. This is often done through a clustering approach, such as k-means or bipartition hierarchical clustering, based on particular similarity measures in the grouping process. In such a dataset, the gene differential expression itself is an innate attribute that can be used in the feature extraction process. For example, in a dataset consisting of multiple treatments versus their controls, the expression of a gene in each treatment would have three possible behaviors, up-, down-regulated, or unchanged. We propose here a differential expression feature extraction (DEFE) method by using a string consisting of three numerical values at each character to denote such behavior, i.e. 1=up, 2=down, and 0=unchanged, which results in up to 3 B differential expression patterns across all B comparisons. This approach has been successfully applied in many datasets, of which we present in this study two sets of RNA-sequencing (RNA-seq) data on wheat challenged with stress related phytohormones or Fusarium graminearum, the causal agent of fusarium head blight (FHB), a devastating wheat disease to illustrate the algorithm. Combinations of multiple schemes of DEFE patterns revealed groups of genes putatively associated with resistance or susceptibility to FHB. DEFE enabled discovery of genes closely associated with defense related signaling molecules such as JAZ10, shikimate and chorismate biosynthesis pathway and groups of wheat genes with differential effects between more or less virulent strains of Fusarium graminearum.

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Metabolic Biomarker Panels of Response to Fusarium Head Blight Infection in Different Wheat Varieties

Cited by 39 publications

References 37 publications

Distribution of species of Fusarium and Alternaria genera on cereals in Ukraine

Distribution of species of Fusarium and Alternaria genera on cereals in Ukraine

Metabolomics: A Way Forward for Crop Improvement

Differential expression feature extraction (DEFE) and its application in RNA-seq data analysis

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