An Analysis of Postharvest Fungal Pathogens Reveals Temporal-Spatial and Host-Pathogen Associations with Fungicide Resistance-Related Mutations

• Published in: Phytopathology 2021-11, Vol.111 (11), p.1942-1951
• Main Authors: Bradshaw, Michael J, Bartholomew, Holly P, Hendricks, Dylan, Maust, Autumn, Jurick, 2nd, Wayne M
• Format: Article
• Language: English
• Subjects: Drug Resistance, Fungal - genetics; Fungi; Fungicides, Industrial - pharmacology; Mutation; Plant Diseases; Plant Sciences
• ISSN: 0031-949X; 1943-7684
• DOI: 10.1094/PHYTO-03-21-0119-R

Fungicides are the primary tools to control a wide range of postharvest fungal pathogens. Fungicide resistance is a widespread problem that has reduced the efficacy of fungicides. Resistance to FRAC-1 (Fungicide Resistance Action Committee-1) chemistries is associated with mutations in amino acid position 198 in the β-tubulin gene. In our study, we conducted a meta-analysis of β-tubulin sequences to infer temporal, spatial, plant host, and pathogen genus patterns of fungicide resistance in postharvest fungal pathogens. In total, data were acquired from 2,647 specimens from 12 genera of fungal phytopathogens residing in 53 countries on >200 hosts collected between 1926 and 2020. The specimens containing a position 198 mutation were globally distributed in a variety of pathosystems. Analyses showed that there are associations among the mutation and the year an isolate was collected, the pathogen genus, the pathogen host, and the collection region. Interestingly, fungicide-resistant β-tubulin genotypes have been in a decline since their peak between 2005 and 2009. FRAC-1 fungicide usage data followed a similar pattern in that applications have been in a decline since their peak between 1997 and 2003. The data show that, with the reduction of selection pressure, FRAC-1 fungicide resistance in fungal populations will decline within 5 to 10 years. Based on this line of evidence, we contend that a β-tubulin position 198 mutation has uncharacterized fitness cost(s) on fungi in nature. The compiled dataset can inform end users on the regions and hosts that are most prone to contain resistant pathogens and assist decisions concerning fungicide resistance management strategies.