Related Experiment Video

Updated: May 8, 2026

Genetic Manipulation of the Plant Pathogen Ustilago maydis to Study Fungal Biology and Plant Microbe Interactions
11:42

Genetic Manipulation of the Plant Pathogen Ustilago maydis to Study Fungal Biology and Plant Microbe Interactions

Published on: September 30, 2016

15.0K

BmSdhBS231L or BmSdhCR76C Mutations Derived from Pydiflumetofen and Fluopyram Domestication Confer Differential

Haiping Shi1, Xiujuan Li1, Shuzhou Liu1

  • 1College of Plant Protection, Nanjing Agricultural University, Nanjing, Jiangsu 210095, China.

Journal of Agricultural and Food Chemistry
|December 1, 2025
PubMed

Insights

Southern corn leaf blight pathogen Bipolaris maydis shows resistance to new SDHI fungicides pydiflumetofen and fluopyram. Specific mutations confer differential resistance, impacting fungicide efficacy and posing a resistance risk.

Area of Science:

  • Plant Pathology
  • Fungal Genetics
  • Biochemistry

Background:

  • Bipolaris maydis causes southern corn leaf blight, a significant threat to corn production in China.
  • Succinate dehydrogenase inhibitor (SDHI) fungicides, including pydiflumetofen (Pyd) and fluopyram (Flu), are crucial for managing this disease.

Purpose of the Study:

  • To determine the baseline sensitivity of B. maydis to Pyd and Flu.
  • To investigate the genetic basis and fitness consequences of resistance to these SDHI fungicides.
  • To elucidate the structural mechanisms underlying SDHI fungicide resistance in B. maydis.

Main Methods:

  • Mycelial growth assays to determine baseline sensitivity.
  • Generation and genetic validation of fungicide-resistant mutants.
  • Structural modeling using AlphaFold3 and molecular docking.

Main Results:

  • Baseline sensitivities to Pyd and Flu were established. Resistant mutants were generated, with mutations BmSdhBS231L and BmSdhCR76C conferring distinct resistance profiles.
  • Fitness penalties were observed in some mutants, suggesting a moderate to high resistance risk.
  • Structural analysis revealed mutations affect fungicide binding at the Qp site of BmSdh, reducing affinity.

Conclusions:

  • The study provides critical insights into the resistance mechanisms of B. maydis to SDHI fungicides.
  • Understanding these mechanisms is essential for developing effective resistance management strategies to preserve fungicide efficacy.
Keywords:
Bipolaris maydisSDHIfluopyrampydiflumetofensouthern corn leaf blight

More Related Videos

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii11:37

QTL Mapping and CRISPR/Cas9 Editing to Identify a Drug Resistance Gene in Toxoplasma gondii

Published on: June 22, 2017

16.7K
Whole Genome Sequencing of Candida glabrata for Detection of Markers of Antifungal Drug Resistance08:45

Whole Genome Sequencing of Candida glabrata for Detection of Markers of Antifungal Drug Resistance

Published on: December 28, 2017

14.2K

Related Concept Videos

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu01:29

Pharmacogenetic Phenotypes: Alterations in Pharmacokinetics, Drug Targets and Biologic Milieu

Genetic variations significantly influence drug response through pharmacokinetics, receptor interactions, and biologic milieu modifications. Pharmacokinetic alterations impact drug metabolism and clearance, affecting efficacy and toxicity. Variants in drug-metabolizing enzymes, such as CYP2C9 and CYP2C19, alter drug activation and elimination. For example, CYP2C9 loss-of-function variants require lower warfarin doses to prevent excessive bleeding, while CYP2C19 variants reduce clopidogrel...
Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase01:11

Pharmacogenetics of Drug Targets: β₂-Adrenergic Receptors, Apo E, Thymidylate Synthase

Genetic polymorphisms in drug targets have emerged as critical determinants of interindividual variability in drug response and toxicity. Pharmacogenomic investigations increasingly focus on identifying these variations to personalize and optimize therapeutic interventions. A drug target may be a receptor, enzyme, or signaling protein involved in pharmacologic responses or disease-related pathways. While early pharmacogenetic studies focused primarily on drug metabolism, current research...
Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure (CHF).