Periodic Reporting for period 2 - KIWIsome (Kiwellins in the plant defense against pathogenic invaders)
Période du rapport: 2023-02-01 au 2024-07-31
Plant diseases caused by pathogenic fungi threaten global food security. Ustilago maydis, or corn smut, plays a dual role in agriculture. It reduces crop yields by infecting maize and causing tumor-like growths, devastating fields. However, in several South American countries, these tumors are a delicacy known as "huitlacoche," prized for their flavor and culinary versatility.
This dual significance creates differing agricultural goals. There is a general interest in breeding corn varieties resistant to this fungal infection to protect crop yields. Conversely, in regions where huitlacoche is valued, the focus shifts to selecting corn lines that produce large tumors without succumbing entirely to the infection, balancing yield and quality of the edible fungus.
The severity of the U. maydis infection results from a complex interplay of molecules released by the host plant and the fungus. We hypothesize that Kiwellin proteins, with their antibody-like characteristics, play a pivotal role in this defense. Exploring the evolutionary journey of these proteins and their diverse functionalities is central to our investigation. Through the ERC proposal KIWIsome, we aim to enhance plant resistance by deepening our understanding of the molecular mechanisms that enable plants to withstand pathogenic threats. This endeavor is vital for ensuring the sustenance of a growing global population.
This dual significance creates differing agricultural goals. There is a general interest in breeding corn varieties resistant to this fungal infection to protect crop yields. Conversely, in regions where huitlacoche is valued, the focus shifts to selecting corn lines that produce large tumors without succumbing entirely to the infection, balancing yield and quality of the edible fungus.
The severity of the U. maydis infection results from a complex interplay of molecules released by the host plant and the fungus. We hypothesize that Kiwellin proteins, with their antibody-like characteristics, play a pivotal role in this defense. Exploring the evolutionary journey of these proteins and their diverse functionalities is central to our investigation. Through the ERC proposal KIWIsome, we aim to enhance plant resistance by deepening our understanding of the molecular mechanisms that enable plants to withstand pathogenic threats. This endeavor is vital for ensuring the sustenance of a growing global population.
Since the project's inception, significant progress has been made in understanding the interactions between maize and Ustilago maydis. One key discovery is the identification of kiwellins, a class of plant defense proteins. When maize is attacked by this fungus, a specific kiwellin protein, ZmKWL1, is produced in large amounts. ZmKWL1 acts as a specific inhibitor of chorismate mutase 1 (Cmu1), a protein secreted by the fungus to manipulate the host plant. By inhibiting Cmu1, ZmKWL1 prevents the fungus from disrupting the plant's defense program, limiting the infection.
Our genomic data analysis revealed that kiwellins likely originated primarily in land plants. Examining functional transcriptome data showed that kiwellin genes are upregulated in response to pathogen contact in many plant species, indicating that kiwellins may have evolved as a broad group of immune proteins in land plants.
We observed that early in infection, U. maydis uses trans-aconitate (TA) as a significant food source. This metabolic intermediate, derived from the tri-carboxylic acid cycle (TCA), is abundant in maize, and U. maydis has a specific gene cluster to break down TA. Moreover, we characterized a new type of decarboxylase in U. maydis, which interferes with the TCA by producing itaconate through an unconventional mechanism, highlighting the importance of metabolic adaptation during infection.
We also characterized a kiwellin-related protein family called cerato-platanin-like proteins (CPL1). These plant proteins target the cell wall of U. maydis by binding to chitin in a unique manner. The biological consequence of this interaction remains to be elucidated. Structural analysis of a prevalent fungal effector protein, UMAG_00027, revealed a lectin-type structure present on the fungal cell surface during infection. This protein is upregulated under starvation conditions, suggesting that infection and survival under nutrient scarcity share common traits.
Thaumatin-like proteins (TLPs) are another group of plant proteins known for their intense sweetness. Maize produces three different TLPs, differentially regulated upon U. maydis infection. Using a "Trojan Horse" approach, we found that TLP1 inhibits infection, TLP2 reduces infection, and TLP3 has no effect. Subtle structural differences in these proteins suggest regions critical for their functional diversification.
The "Trojan Horse" approach allows rapid and reliable screening of plant defense proteins' effects on disease outcomes. This method employs a standardized genetic toolkit, enabling efficient testing of protein functions.
We also collaborated with local farmers to study real-world scenarios in the field. In 2023, this collaboration led to an investigation into the susceptibility of various maize varieties to U. maydis under field conditions. This study provided kinetic data on infection progression and samples for analyzing the impact of bacterial species on U. maydis infection. The study will continue through 2024 and 2025, with plans for publication afterward.
To address the need for rapid and accurate quantification of disease symptoms, we partnered with the engineering department of the Technische Hochschule Mittelhessen to develop a "plant scanner." This device creates three-dimensional images of infected plants, preserving them electronically for future analysis. An artificial intelligence (AI) model is being trained to assess infection symptoms automatically, currently achieving about 90% accuracy.
Our genomic data analysis revealed that kiwellins likely originated primarily in land plants. Examining functional transcriptome data showed that kiwellin genes are upregulated in response to pathogen contact in many plant species, indicating that kiwellins may have evolved as a broad group of immune proteins in land plants.
We observed that early in infection, U. maydis uses trans-aconitate (TA) as a significant food source. This metabolic intermediate, derived from the tri-carboxylic acid cycle (TCA), is abundant in maize, and U. maydis has a specific gene cluster to break down TA. Moreover, we characterized a new type of decarboxylase in U. maydis, which interferes with the TCA by producing itaconate through an unconventional mechanism, highlighting the importance of metabolic adaptation during infection.
We also characterized a kiwellin-related protein family called cerato-platanin-like proteins (CPL1). These plant proteins target the cell wall of U. maydis by binding to chitin in a unique manner. The biological consequence of this interaction remains to be elucidated. Structural analysis of a prevalent fungal effector protein, UMAG_00027, revealed a lectin-type structure present on the fungal cell surface during infection. This protein is upregulated under starvation conditions, suggesting that infection and survival under nutrient scarcity share common traits.
Thaumatin-like proteins (TLPs) are another group of plant proteins known for their intense sweetness. Maize produces three different TLPs, differentially regulated upon U. maydis infection. Using a "Trojan Horse" approach, we found that TLP1 inhibits infection, TLP2 reduces infection, and TLP3 has no effect. Subtle structural differences in these proteins suggest regions critical for their functional diversification.
The "Trojan Horse" approach allows rapid and reliable screening of plant defense proteins' effects on disease outcomes. This method employs a standardized genetic toolkit, enabling efficient testing of protein functions.
We also collaborated with local farmers to study real-world scenarios in the field. In 2023, this collaboration led to an investigation into the susceptibility of various maize varieties to U. maydis under field conditions. This study provided kinetic data on infection progression and samples for analyzing the impact of bacterial species on U. maydis infection. The study will continue through 2024 and 2025, with plans for publication afterward.
To address the need for rapid and accurate quantification of disease symptoms, we partnered with the engineering department of the Technische Hochschule Mittelhessen to develop a "plant scanner." This device creates three-dimensional images of infected plants, preserving them electronically for future analysis. An artificial intelligence (AI) model is being trained to assess infection symptoms automatically, currently achieving about 90% accuracy.
Our work has significantly advanced the understanding of maize and U. maydis interactions. The discovery of kiwellins and their role in inhibiting fungal effectors is a major breakthrough in understanding plant resistance. Identifying the metabolic adaptations of U. maydis provides new targets for disrupting the infection process. Developing tools like the "plant scanner" and AI-based symptom assessment marks a significant leap in precision and efficiency for plant disease studies.
By the project's conclusion, we expect to advance our understanding of key proteins in maize defense and U. maydis infection. We aim to publish a comprehensive study on U. maydis pathophysiology field data, provide open-source plans for the plant scanner, and refine AI models for plant disease symptom identification. These advancements will offer valuable tools and knowledge for managing corn smut, benefiting agricultural productivity and cultural practices.
By the project's conclusion, we expect to advance our understanding of key proteins in maize defense and U. maydis infection. We aim to publish a comprehensive study on U. maydis pathophysiology field data, provide open-source plans for the plant scanner, and refine AI models for plant disease symptom identification. These advancements will offer valuable tools and knowledge for managing corn smut, benefiting agricultural productivity and cultural practices.