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Updated: Nov 11, 2025
Using Ustilago maydis as a Trojan Horse for In Situ Delivery of Maize Proteins
Published on: February 8, 2019
A Novel In Silico Method for Molecular Mimicry Detection Finds a Formin with the Potential to Manipulate the Maize
Vinicio Armijos-Jaramillo1,2, Nicole Espinosa1, Karla Vizcaíno1
1Carrera de Ingeniería en Biotecnología, Facultad de Ingeniería y Ciencias Aplicadas, Universidad de Las Américas, Quito, Ecuador.
Abstract:
Molecular mimicry is one of the evolutionary strategies that parasites use to manipulate the host metabolism and perform an effective infection. This phenomenon has been observed in several animal and plant pathosystems. Despite the relevance of this mechanism in pathogenesis, little is known about it in fungus-plant interactions. For that reason, we performed an in silico method to select plausible mimicry candidates for the Ustilago maydis-maize interaction. Our methodology used a tripartite sequence comparison between the parasite, the host, and nonparasitic organisms' genomes. Furthermore, we used RNA sequencing information to identify gene coexpression, and we determined subcellular localization to detect potential cases of colocalization in the imitator-imitated pairs. With these approximations, we found a putative extracellular formin in U. maydis with the potential to rearrange the host cell cytoskeleton. In parallel, we detected at least two maize genes involved in the cytoskeleton rearrangement differentially expressed under U. maydis infection; thus, this find increases the expectation for the potential mimicry role of the fungal protein. The use of several sources of data led us to develop a strict and replicable in silico methodology to detect molecular mimicry in pathosystems with enough information available. Furthermore, this is the first time that a genomewide search has been performed to detect molecular mimicry in a U. maydis-maize system. Additionally, to allow the reproducibility of this experiment and the use of this pipeline, we created a Web server called Molecular Mimicry Finder.[Formula: see text] Copyright © 2021 The Author(s). This is an open access article distributed under the CC BY-NC-ND 4.0 International license.
Insights
Parasitic fungi like Ustilago maydis may use molecular mimicry to infect maize by manipulating host cell cytoskeleton. This study developed a computational method to identify potential mimicry candidates in fungus-plant interactions.
Area of Science:
- Plant Pathology
- Molecular Biology
- Bioinformatics
Background:
- Molecular mimicry is a parasitic strategy to manipulate host metabolism and infection.
- This phenomenon is well-documented in animal and plant systems but less understood in fungus-plant interactions.
- Ustilago maydis is a significant pathogen of maize.
Purpose of the Study:
- To identify potential molecular mimicry candidates in the Ustilago maydis-maize pathosystem.
- To develop and validate a robust in silico methodology for detecting molecular mimicry.
- To investigate the role of fungal proteins in manipulating host cytoskeleton.
Main Methods:
- In silico tripartite sequence comparison of parasite, host, and non-parasitic organism genomes.
- RNA sequencing to identify gene co-expression patterns between U. maydis and maize.
- Subcellular localization analysis to predict colocalization of potential mimicry pairs.
Main Results:
- A putative extracellular formin in U. maydis was identified with the potential to rearrange the maize cytoskeleton.
- Two maize genes involved in cytoskeleton rearrangement were found to be differentially expressed during U. maydis infection.
- A novel computational pipeline, Molecular Mimicry Finder, was developed for genomewide mimicry searches.
Conclusions:
- The study presents the first genomewide search for molecular mimicry in the Ustilago maydis-maize system.
- The findings suggest a potential role for fungal formin in manipulating the host cytoskeleton during infection.
- The developed methodology and web server facilitate future research on molecular mimicry in plant-pathogen interactions.
