Duccio Migliorini, Maria Vivas, Michael J. Wingfield, Christopher Shaw, Treena I. Burgess
{"title":"Oomycete composition in Proteaceae orchards and natural stands on three continents","authors":"Duccio Migliorini, Maria Vivas, Michael J. Wingfield, Christopher Shaw, Treena I. Burgess","doi":"10.1007/s11557-023-01925-1","DOIUrl":null,"url":null,"abstract":"Abstract The Proteaceae , a diverse family of woody flowering plants in the Southern Hemisphere, contains many species known to be susceptible to Phytophthora cinnamomi , both in the natural environment and in cut-flower orchards. Very little is known about the prevalence of P. cinnamomi and other oomycetes across these landscapes. To address this knowledge gap, we used a double ITS1 and RPS10 gene metabarcoding approach and traditional isolation protocols to investigate oomycetes in orchards and natural stands of Proteaceae across South Africa, South Africa (eastern and western), Australia, and Europe. The RPS10 primers amplified more samples, including various Pythium species, while the ITS primers detected more Phytophthora phylotypes. Both datasets showed that geographic regions influenced oomycete species richness and community composition, while they did not show any variation between orchards and natural vegetation. RPS10 metabarcoding detected the largest number of species and provided greater statistical confidence than ITS1 when considering oomycete species composition. Metabarcoding also showed that orchards had a higher abundance of P. cinnamomi compared to native stands, although this was not found when isolating through baiting of roots and rhizosphere soil. Direct isolation and metabarcoding are complementary, with metabarcoding serving as an early detection tool. However, it cannot distinguish living viable propagules from residual DNA of dead propagules, limiting its use for diagnostic purposes related to Phytophthora management and control. These results, along with those of other recent studies, show that metabarcoding offers an effective tool to describe the dynamics of soil oomycetes in different ecosystems.","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2023-10-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1007/s11557-023-01925-1","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
Abstract The Proteaceae , a diverse family of woody flowering plants in the Southern Hemisphere, contains many species known to be susceptible to Phytophthora cinnamomi , both in the natural environment and in cut-flower orchards. Very little is known about the prevalence of P. cinnamomi and other oomycetes across these landscapes. To address this knowledge gap, we used a double ITS1 and RPS10 gene metabarcoding approach and traditional isolation protocols to investigate oomycetes in orchards and natural stands of Proteaceae across South Africa, South Africa (eastern and western), Australia, and Europe. The RPS10 primers amplified more samples, including various Pythium species, while the ITS primers detected more Phytophthora phylotypes. Both datasets showed that geographic regions influenced oomycete species richness and community composition, while they did not show any variation between orchards and natural vegetation. RPS10 metabarcoding detected the largest number of species and provided greater statistical confidence than ITS1 when considering oomycete species composition. Metabarcoding also showed that orchards had a higher abundance of P. cinnamomi compared to native stands, although this was not found when isolating through baiting of roots and rhizosphere soil. Direct isolation and metabarcoding are complementary, with metabarcoding serving as an early detection tool. However, it cannot distinguish living viable propagules from residual DNA of dead propagules, limiting its use for diagnostic purposes related to Phytophthora management and control. These results, along with those of other recent studies, show that metabarcoding offers an effective tool to describe the dynamics of soil oomycetes in different ecosystems.