Multiplex qPCR assay for simultaneous quantification of CYP51‐S524T and SdhC‐H152R substitutions in European populations of Zymoseptoria tritici

Abstract

Demethylation inhibitor (DMI) and succinate dehydrogenase inhibitor (SDHI) fungicides are currently relied upon for the control of septoria tritici blotch (STB) in European wheat fields. However, multiple mutations have occurred over time in the genes encoding the targeted proteins that have led to a practical loss of fungicide efficacies. Among the different amino acid substitutions in Zymoseptoria tritici associated with resistance to these fungicides, S524T in CYP51 (DMI target) and H152R in SdhC (SDHI target) are regarded as conferring the highest resistance factors to DMI and SDHI, respectively. To facilitate further studies on the monitoring and selection of these substitutions in Z. tritici populations, a multiplex allele‐specific quantitative PCR (qPCR) assay allowing for estimation of both allele frequencies in bulk DNA matrices was developed. The assay was then used on complex DNA samples originating from a spore trap network set up in Belgium, Denmark, Sweden, and Ireland in 2017 and 2018, as well as on leaf samples with symptoms. The S524T allele was present in all field samples and its proportion was significantly higher in Ireland than in Belgium, whereas the proportion of H152R was only sporadically present in both countries. The frequency of S524T varied greatly in the airborne inoculum of all four countries; however, the H152R allele was never detected in the airborne inoculum. The method developed in this study can be readily adopted by other laboratories and used for multiple applications including resistance monitoring in field populations of Z. tritici.

Development of a PacBio Long-Read Sequencing Assay for High Throughput Detection of Fungicide Resistance in Zymoseptoria tritici

“…Furthermore, in all instances, the populations were collected from fields that were previously planted to a non-cereal which suggests initial infections would primarily have resulted from airborne ascospore inoculum. As identified by Hellin et al (2020) Z. tritici ascospores are abundant in Ireland in late autumn and early winter and the frequencies of alterations conferring fungicide resistance in these can vary over this period. Further research is required to dissect these differences in fungicide sensitivity.…”

“…Full haplotype determination is increasingly required for resistance monitoring, as highlighted by the complexity of accumulation of CYP51 alterations (Leroux and Walker, 2011;Kildea et al, 2019b;Garnault et al, 2021). Whilst it is possible to augment these assays to capture multiple alterations (e.g., multiplexing of different dual-labelled probes to capture multiple alterations in a single qPCR assay as described by Hellin et al, 2020) or indeed entire genes greater than 1 kb (e.g., Frey et al, 2018), these are often either limited in their capacity to capture the diversity present or are highly complex and as such difficult to readily implement. The PacBio longread sequencing methods based on Single-Molecule Real-Time (SMRT) sequencing technology provides a potential opportunity to overcome both these limitations.…”

Monitoring airborne inoculum for improved plant disease management. A review

“…(Carisse et al 2014). In addition, when aerobiological data are combined with genetic analyzes, it become possible to study fungal community and ecology of different pathogen genotypes including those related to fungicide resistance or aggressiveness (Fraaije et al 2005;Hellin et al 2020;Nicolaisen et al 2017).…”

“…Similarly, tools for simultaneous monitoring of Plasmopara viticola clade riparia and clade aestivalis was recently developed (Carisse et al 2021). Another example of such an approach is provided for Z. tritici, for which molecular markers have been developed to monitor specific DNA substitutions associated with fungicide resistance to demethylation inhibitors and succinate dehydrogenase (Hellin et al 2020). Hence, it is expected that aerobiology will continue to evolve through the integration of new technologies such as metagenomics, but also through other knowledge such as deep learning, neural networks or more automated methods of sample analysis.…”

Changes in DMI, SDHI, and QoI Fungicide Sensitivity in the Estonian Zymoseptoria tritici Population between 2019 and 2020

“…Moreover, in 2015 the first Zt isolates showing a strong decrease in sensitivity to SDHIs with mutations C-H152R and D-R47W were isolated from Ireland [ 8 ]. Since then, each year isolates with moderate resistance factors and bearing the mutation C-H152R have been detected from Germany, Belgium, Ireland, the Netherlands, France, and the United Kingdom [ 26 , 27 ]. Amino acid exchange C-H152R is still rarely detected in the field, although, of all field mutants, it confers the highest level of resistance to all SDHIs [ 8 , 24 ].…”