A new model for the pathozone of the take‐all pathogen, <i>Gaeumannomyces graminis</i> var. <i>tritici</i>

Gosme, Marie; Lebreton, Lionel; Sarniguet, Alain; Lucas, Philippe; Gilligan, C. A.; Bailey, D. J.

doi:10.1111/aab.12060

Cited by 3 publications

(6 citation statements)

References 24 publications

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“…The mechanisms of pathogenicity of Ggt to wheat roots are still not well understood as most research on wheat– Ggt interactions has focused on biological characteristics of the disease [ 15 ], pathogen distribution [ 16 ], pathogen genetic diversity [ 17 ], and the use of antagonists [ 18 ]. One approach to elucidating the mechanisms of fungal plant pathogenicity is to conduct large scale transcipt sequencing (RNA-seq analysis) of infected plant tissues.…”

Section: Introductionmentioning

confidence: 99%

Comparative Transcriptome Profiling of the Early Infection of Wheat Roots by Gaeumannomyces graminis var. tritici

Yang¹,

Xie²,

Bao-guo³

et al. 2015

PLoS ONE

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Take-all, which is caused by the fungal pathogen, Gaeumannomyces graminis var. tritici (Ggt), is an important soil-borne root rot disease of wheat occurring worldwide. However, the genetic basis of Ggt pathogenicity remains unclear. In this study, transcriptome sequencing for Ggt in axenic culture and Ggt-infected wheat roots was performed using Illumina paired-end sequencing. Approximately 2.62 and 7.76 Gb of clean reads were obtained, and 87% and 63% of the total reads were mapped to the Ggt genome for RNA extracted from Ggt in culture and infected roots, respectively. A total of 3,258 differentially expressed genes (DEGs) were identified with 2,107 (65%) being 2-fold up-regulated and 1,151 (35%) being 2-fold down-regulated between Ggt in culture and Ggt in infected wheat roots. Annotation of these DEGs revealed that many were associated with possible Ggt pathogenicity factors, such as genes for guanine nucleotide-binding protein alpha-2 subunit, cellulase, pectinase, xylanase, glucosidase, aspartic protease and gentisate 1, 2-dioxygenase. Twelve DEGs were analyzed for expression by qRT-PCR, and could be generally divided into those with high expression only early in infection, only late in infection and those that gradually increasing expression over time as root rot developed. This indicates that these possible pathogenicity factors may play roles during different stages of the interaction, such as signaling, plant cell wall degradation and responses to plant defense compounds. This is the first study to compare the transcriptomes of Ggt growing saprophytically in axenic cultures to it growing parasitically in infected wheat roots. As a result, new candidate pathogenicity factors have been identified, which can be further examined by gene knock-outs and other methods to assess their true role in the ability of Ggt to infect roots.

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Section: Introductionmentioning

confidence: 99%

Comparative Transcriptome Profiling of the Early Infection of Wheat Roots by Gaeumannomyces graminis var. tritici

Yang¹,

Xie²,

Bao-guo³

et al. 2015

PLoS ONE

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“…, Gosme et al. ). However, patch dynamic and partial differential equation models could not only further our understanding of these patterns, but could also be applied to a wider range of gradients (Table ).…”

Section: Paths For Increasing the Future Potential Of Mathematical Momentioning

confidence: 98%

“…, Gosme and Lucas , Gosme et al. ), and this lopsided emphasis may have limited the use of models to describe processes across both managed and unmanaged systems. Many practical models (calibrated to specific data sets), such as soil–plant–atmosphere models (SPAM), often focus on abiotic instead of biotic factors (reviewed in Manzoni et al.…”

Section: Overcome Challenges To the Application Of Mathematical Modelmentioning

confidence: 99%

“…Historically, the majority of mathematical modeling in soil has focused on organisms of economic interest, such as pathogens of crops (e.g., take-all fungus in winter wheat; Brassett and Gilligan 1989, Heritage et al 1989, Gilligan and Brassett 1990, Werker et al 1991, Gilligan 1994, 1995, Colbach and Huet 1995, Bailey and Gilligan 1999, Schoeny and Lucas 1999, Ennaifar et al 2007, Bailey et al 2009, Gosme and Lucas 2009, Gosme et al 2013, and this lopsided emphasis may have limited the use of models to describe processes across both managed and unmanaged systems. Many practical models (calibrated to specific data sets), such as soil-plant-atmosphere models (SPAM), often focus on abiotic instead of biotic factors (reviewed in Manzoni et al 2013).…”

Section: Overcome Challenges To the Application Of Mathematical Modelmentioning

confidence: 99%

“…Spatial and temporal gradients in the availability of root exudates provide illustrative examples (Table 1). Neighborhood models identified how nematodes and a fungal pathogen responded to patterns in rhizosphere gradients (Anderson et al 1997, Feltham et al 2002, Gosme et al 2013). However, patch dynamic and partial differential equation models could not only further our understanding of these patterns, but could also be applied to a wider range of gradients (Table 1).…”

Section: Paths For Increasing the Future Potential Of Mathematical Momentioning

confidence: 99%

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Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

et al. 2019

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Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution.

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Melanin Induction Restores the Pathogenicity of Gaeumannomyces graminis var. tritici in Wheat Plants

Aranda

Méndez

Barra

et al. 2023

JoF

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One of the most challenging aspects of long-term research based on microorganisms is the maintenance of isolates under ex situ conditions, particularly the conservation of phytopathological characteristics. Our research group has worked for more than 10 years with Gaumannomyces graminis var. tritici (Ggt), the main biotic factor affecting wheat. In this sense we preserved the microorganisms in oil overlaid. However, several strains preserved for a long time lost their pathogenicity. These strains show white and non-infective mycelia. In this sense, we hypothesized that this is attributable to low melanin content. Melanin is a natural pigment mainly involved in UV protection, desiccation, salinity, oxidation, and fungal pathogenicity. Therefore, understanding the melanin role on Ggt pathogenicity is fundamental to developing melanin activation strategies under laboratory studies. In this study, we induce melanin activation by UV-A light chamber, 320 to 400 nm (T1) and temperature changes of 30 °C, 15 °C, and 20 °C (T2). Fungal pathogenicity was evaluated by determination of blackening roots and Ggt was quantified by real-time PCR in inoculated wheat plants. Results revealed that Ggt grown under UV-A (T1) conditions showed around 40% higher melanin level with a concomitant effect on root infection (98% of blackened roots) and 4-fold more Ggt genome copy number compared with the control (non-infective mycelia) being T1, a more inductor factor compared with T2. These findings would support the role of melanin in pathogenicity in darkly pigmented fungi such as Ggt and could serve as a basis for activating pathogenicity under laboratory conditions.

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A new model for the pathozone of the take‐all pathogen, Gaeumannomyces graminis var. tritici

Cited by 3 publications

References 24 publications

Comparative Transcriptome Profiling of the Early Infection of Wheat Roots by Gaeumannomyces graminis var. tritici

Comparative Transcriptome Profiling of the Early Infection of Wheat Roots by Gaeumannomyces graminis var. tritici

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

Melanin Induction Restores the Pathogenicity of Gaeumannomyces graminis var. tritici in Wheat Plants

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