Dataset Information

Transcription factor control of virulence in phytopathogenic fungi.

ABSTRACT: Plant-pathogenic fungi are a significant threat to economic and food security worldwide. Novel protection strategies are required and therefore it is critical we understand the mechanisms by which these pathogens cause disease. Virulence factors and pathogenicity genes have been identified, but in many cases their roles remain elusive. It is becoming increasingly clear that gene regulation is vital to enable plant infection and transcription factors play an essential role. Efforts to determine their regulatory functions in plant-pathogenic fungi have expanded since the annotation of fungal genomes revealed the ubiquity of transcription factors from a broad range of families. This review establishes the significance of transcription factors as regulatory elements in plant-pathogenic fungi and provides a systematic overview of those that have been functionally characterized. Detailed analysis is provided on regulators from well-characterized families controlling various aspects of fungal metabolism, development, stress tolerance, and the production of virulence factors such as effectors and secondary metabolites. This covers conserved transcription factors with either specialized or nonspecialized roles, as well as recently identified regulators targeting key virulence pathways. Fundamental knowledge of transcription factor regulation in plant-pathogenic fungi provides avenues to identify novel virulence factors and improve our understanding of the regulatory networks linked to pathogen evolution, while transcription factors can themselves be specifically targeted for disease control. Areas requiring further insight regarding the molecular mechanisms and/or specific classes of transcription factors are identified, and direction for future investigation is presented.

SUBMITTER: John E

PROVIDER: S-EPMC8232033 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:BACKGROUND: Leaf-cutting (attine) ants use their own fecal material to manure fungus gardens, which consist of leaf material overgrown by hyphal threads of the basidiomycete fungus Leucocoprinus gongylophorus that lives in symbiosis with the ants. Previous studies have suggested that the fecal droplets contain proteins that are produced by the fungal symbiont to pass unharmed through the digestive system of the ants, so they can enhance new fungus garden growth. RESULTS: We tested this hypothesis by using proteomics methods to determine the gene sequences of fecal proteins in Acromyrmex echinatior leaf-cutting ants. Seven (21%) of the 33 identified proteins were pectinolytic enzymes that originated from the fungal symbiont and which were still active in the fecal droplets produced by the ants. We show that these enzymes are found in the fecal material only when the ants had access to fungus garden food, and we used quantitative polymerase chain reaction analysis to show that the expression of six of these enzyme genes was substantially upregulated in the fungal gongylidia. These unique structures serve as food for the ants and are produced only by the evolutionarily advanced garden symbionts of higher attine ants, but not by the fungi reared by the basal lineages of this ant clade. CONCLUSIONS: Pectinolytic enzymes produced in the gongylidia of the fungal symbiont are ingested but not digested by Acromyrmex leaf-cutting ants so that they end up in the fecal fluid and become mixed with new garden substrate. Substantial quantities of pectinolytic enzymes are typically found in pathogenic fungi that attack live plant tissue, where they are known to breach the cell walls to allow the fungal mycelium access to the cell contents. As the leaf-cutting ant symbionts are derived from fungal clades that decompose dead plant material, our results suggest that their pectinolytic enzymes represent secondarily evolved adaptations that are convergent to those normally found in phytopathogens.

Project description:BACKGROUND: Inappropriate taxon definitions may have severe consequences in many areas. For instance, biologically sensible species delimitation of plant pathogens is crucial for measures such as plant protection or biological control and for comparative studies involving model organisms. However, delimiting species is challenging in the case of organisms for which often only molecular data are available, such as prokaryotes, fungi, and many unicellular eukaryotes. Even in the case of organisms with well-established morphological characteristics, molecular taxonomy is often necessary to emend current taxonomic concepts and to analyze DNA sequences directly sampled from the environment. Typically, for this purpose clustering approaches to delineate molecular operational taxonomic units have been applied using arbitrary choices regarding the distance threshold values, and the clustering algorithms. METHODOLOGY: Here, we report on a clustering optimization method to establish a molecular taxonomy of Peronospora based on ITS nrDNA sequences. Peronospora is the largest genus within the downy mildews, which are obligate parasites of higher plants, and includes various economically important pathogens. The method determines the distance function and clustering setting that result in an optimal agreement with selected reference data. Optimization was based on both taxonomy-based and host-based reference information, yielding the same outcome. Resampling and permutation methods indicate that the method is robust regarding taxon sampling and errors in the reference data. Tests with newly obtained ITS sequences demonstrate the use of the re-classified dataset in molecular identification of downy mildews. CONCLUSIONS: A corrected taxonomy is provided for all Peronospora ITS sequences contained in public databases. Clustering optimization appears to be broadly applicable in automated, sequence-based taxonomy. The method connects traditional and modern taxonomic disciplines by specifically addressing the issue of how to optimally account for both traditional species concepts and genetic divergence.

Dataset Information

Transcription factor control of virulence in phytopathogenic fungi.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets