Time-resolved decoding of metabolic signatures of in vitro growth of the hemibiotrophic pathogen Colletotrichum sublineolum

Tugizimana, Fidele; Djami-Tchatchou, Arnaud T.; Fahrmann, Johannes F.; Steenkamp, Paul A.; Piater, Lizelle A.; Dubery, Ian A.

doi:10.1038/s41598-019-38692-7

Cited by 15 publications

(17 citation statements)

References 52 publications

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“…Colletotrichum , a class of hemibiotrophic fungal pathogens, is one of the most widespread and economically detrimental genera of plant pathogenic fungi. An untargeted LC-MS metabolomic strategy was performed to elucidate metabolome changes in the anthracnose-causing C. sublineolum [80,81]. The results demonstrated through chemometric modelling revealed a metabolic variation trajectory, comprising three distinct stages that metabolically describe the adaptation of the fungus to diminishing nutrients.…”

Section: Research Progress and Application Of Metabolomics In Fungmentioning

confidence: 99%

Advances of Metabolomics in Fungal Pathogen–Plant Interactions

Chen

2019

Metabolites

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Plant disease caused by fungus is one of the major threats to global food security, and understanding fungus–plant interactions is important for plant disease control. Research devoted to revealing the mechanisms of fungal pathogen–plant interactions has been conducted using genomics, transcriptomics, proteomics, and metabolomics. Metabolomics research based on mass spectrometric techniques is an important part of systems biology. In the past decade, the emerging field of metabolomics in plant pathogenic fungi has received wide attention. It not only provides a qualitative and quantitative approach for determining the pathogenesis of pathogenic fungi but also helps to elucidate the defense mechanisms of their host plants. This review focuses on the methods and progress of metabolomics research in fungal pathogen–plant interactions. In addition, the prospects and challenges of metabolomics research in plant pathogenic fungi and their hosts are addressed.

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Section: Research Progress and Application Of Metabolomics In Fungmentioning

confidence: 99%

Advances of Metabolomics in Fungal Pathogen–Plant Interactions

Chen

2019

Metabolites

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“…This may be either towards successful proliferation of the pathogen or effective immune responses of the host. Furthermore, the establishment and maintenance of the biotrophic stage (which is about 72 h post-infection) is crucial for successful development of the hemibiotrophic Colletotrichum spp., and for an effective infection thereafter [61,62,63]. Thus, this strong defence-related metabolic reprogramming observed in primed plants (compared to naïve plants) as early as 1–3 d.p.i.…”

Section: Resultsmentioning

confidence: 99%

Unravelling the Metabolic Reconfiguration of the Post-Challenge Primed State in Sorghum bicolor Responding to Colletotrichum sublineolum Infection

et al. 2019

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Priming is a natural phenomenon that pre-conditions plants for enhanced defence against a wide range of pathogens. It represents a complementary strategy, or sustainable alternative that can provide protection against disease. However, a comprehensive functional and mechanistic understanding of the various layers of priming events is still limited. A non-targeted metabolomics approach was used to investigate metabolic changes in plant growth-promoting rhizobacteria (PGPR)-primed Sorghum bicolor seedlings infected with the anthracnose-causing fungal pathogen, Colletotrichum sublineolum, with a focus on the post-challenge primed state phase. At the 4-leaf growth stage, the plants were treated with a strain of Paenibacillus alvei at 108 cfu mL−1. Following a 24 h PGPR application, the plants were inoculated with a C. sublineolum spore suspension (106 spores mL−1), and the infection monitored over time: 1, 3, 5, 7 and 9 days post-inoculation. Non-infected plants served as negative controls. Intracellular metabolites from both inoculated and non-inoculated plants were extracted with 80% methanol-water. The extracts were chromatographically and spectrometrically analysed on an ultra-high performance liquid chromatography (UHPLC) system coupled to high-definition mass spectrometry. The acquired multidimensional data were processed to create data matrices for chemometric modelling. The computed models indicated time-related metabolic perturbations that reflect primed responses to the fungal infection. Evaluation of orthogonal projection to latent structure-discriminant analysis (OPLS-DA) loading shared and unique structures (SUS)-plots uncovered the differential stronger defence responses against the fungal infection observed in primed plants. These involved enhanced levels of amino acids (tyrosine, tryptophan), phytohormones (jasmonic acid and salicylic acid conjugates, and zeatin), and defence-related components of the lipidome. Furthermore, other defence responses in both naïve and primed plants were characterised by a complex mobilisation of phenolic compounds and de novo biosynthesis of the flavones, apigenin and luteolin and the 3-deoxyanthocyanidin phytoalexins, apigeninidin and luteolinidin, as well as some related conjugates.

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“…Growth stage distinction and temporal regulation. An alternative technique of untargeted liquid-chromatography MS (LC-MS) elucidated temporal metabolome changes of the distinct lifestyle of the hemibiotrophic pathogen Colletotrichum sublineola (95). Colletotrichum spp.…”

Section: Metabolomicsmentioning

confidence: 99%

“…Metabolomics profiles networks of small low-molecular-weight metabolites as the culmination of cellular processes representing the entire physiology of genomics, transcriptomics, and proteomics within an organism or cell. Chromatography-based MS is a critical analytic tool for establishing comprehensive metabolic profiles, chemical signaling, and underlying regulatory mechanisms, and for comparing the characteristics of metabolic profiles of different species ( 94 – 96 ). For example, secondary metabolites (SecMets) and biosynthetic gene clusters (BGCs) commonly produced by filamentous fungi are of high-interest due to their multivariate capabilities in pharmaceutical and agricultural research as well as in fungal pathogenesis, including host colonization and interactions with other microbes ( 97 ).…”

Section: Metabolomicsmentioning

confidence: 99%

Fun(gi)omics: Advanced and Diverse Technologies to Explore Emerging Fungal Pathogens and Define Mechanisms of Antifungal Resistance

Ball

Langille

Geddes‐McAlister

2020

mBio

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The landscape of infectious fungal agents includes previously unidentified or rare pathogens with the potential to cause unprecedented casualties in biodiversity, food security, and human health. The influences of human activity, including the crisis of climate change, along with globalized transport, are underlying factors shaping fungal adaptation to increased temperature and expanded geographical regions. Furthermore, the emergence of novel antifungal-resistant strains linked to excessive use of antifungals (in the clinic) and fungicides (in the field) offers an additional challenge to protect major crop staples and control dangerous fungal outbreaks. Hence, the alarming frequency of fungal infections in medical and agricultural settings requires effective research to understand the virulent nature of fungal pathogens and improve the outcome of infection in susceptible hosts. Mycology-driven research has benefited from a contemporary and unified approach of omics technology, deepening the biological, biochemical, and biophysical understanding of these emerging fungal pathogens. Here, we review the current state-of-the-art multi-omics technologies, explore the power of data integration strategies, and highlight discovery-based revelations of globally important and taxonomically diverse fungal pathogens. This information provides new insight for emerging pathogens through an in-depth understanding of well-characterized fungi and provides alternative therapeutic strategies defined through novel findings of virulence, adaptation, and resistance.

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Time-resolved decoding of metabolic signatures of in vitro growth of the hemibiotrophic pathogen Colletotrichum sublineolum

Cited by 15 publications

References 52 publications

Advances of Metabolomics in Fungal Pathogen–Plant Interactions

Advances of Metabolomics in Fungal Pathogen–Plant Interactions

Unravelling the Metabolic Reconfiguration of the Post-Challenge Primed State in Sorghum bicolor Responding to Colletotrichum sublineolum Infection

Fun(gi)omics: Advanced and Diverse Technologies to Explore Emerging Fungal Pathogens and Define Mechanisms of Antifungal Resistance

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