Presence ≠ problem: pathogenicity decoupled from active pathogen abundance

Abstract Background and aims Pre-season detection of common scab, caused by Streptomyces scabies , is essential for mitigating economic losses before tuber infection occurs. Current detection methods rely on DNA-based assays, which cannot distinguish between viable and dead S. scabies . RNA-based assays may provide a more reliable indication of pathogen activity in soil. This experiment evaluated whether RNA-based detection improves prediction of disease severity. Methods In a growth chamber experiment, soils were artificially infested with S. scabies and seeded with radish. Soil collected prior to radish transplant and following harvest was extracted for both DNA and RNA. Both qPCR and rt-qPCR were used to quantify: i ) the constitutively expressed 16S rRNA, and ii ) the facultatively expressed txtAB , which facilitates tuber infection. Disease severity was evaluated against pre-season and post-harvest gene abundances. Results A clear gradient in S. scabies density was detected using genomic txtAB and genomic and transcribed 16S rRNA abundances. Transcribed txtAB was not detected. Despite a clear gradient in S. scabies , no assay reliably predicted disease severity. Conclusions Our results suggest two fundamental constraints at the intersection of plant pathology and soil science: i ) the success of RNA-based assays for detecting pathogen activity is constrained by gene copy number and sampling time, especially when virulence factors are facultatively expressed, and ii ) detection of pathogens, even in a metabolically active state, does not necessarily provide sufficient information to predict virulence expression, decoupling active pathogen presence from disease severity.

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Publication Details

Journal
Plant and Soil
Published
2026-09-29
DOI
https://doi.org/10.1007/s11104-026-09150-x
Primary Topic
Plant Disease Resistance and Genetics
Type
article
Field-Weighted Citation Impact
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article

Presence ≠ problem: pathogenicity decoupled from active pathogen abundance

R. Clarkson, Kim Zitnick-Anderson, Kirsten Butcher, Miranda Vanderhyde et al.
Plant and Soil
Plant Disease Resistance and Genetics
article

Presence ≠ problem: pathogenicity decoupled from active pathogen abundance

R. Clarkson, Kim Zitnick-Anderson, Kirsten Butcher, Miranda Vanderhyde, Sage M. Longtin
article en

Abstract

Abstract Background and aims Pre-season detection of common scab, caused by Streptomyces scabies , is essential for mitigating economic losses before tuber infection occurs. Current detection methods rely on DNA-based assays, which cannot distinguish between viable and dead S. scabies . RNA-based assays may provide a more reliable indication of pathogen activity in soil. This experiment evaluated whether RNA-based detection improves prediction of disease severity. Methods In a growth chamber experiment, soils were artificially infested with S. scabies and seeded with radish. Soil collected prior to radish transplant and following harvest was extracted for both DNA and RNA. Both qPCR and rt-qPCR were used to quantify: i ) the constitutively expressed 16S rRNA, and ii ) the facultatively expressed txtAB , which facilitates tuber infection. Disease severity was evaluated against pre-season and post-harvest gene abundances. Results A clear gradient in S. scabies density was detected using genomic txtAB and genomic and transcribed 16S rRNA abundances. Transcribed txtAB was not detected. Despite a clear gradient in S. scabies , no assay reliably predicted disease severity. Conclusions Our results suggest two fundamental constraints at the intersection of plant pathology and soil science: i ) the success of RNA-based assays for detecting pathogen activity is constrained by gene copy number and sampling time, especially when virulence factors are facultatively expressed, and ii ) detection of pathogens, even in a metabolically active state, does not necessarily provide sufficient information to predict virulence expression, decoupling active pathogen presence from disease severity.

Plant and Soil
North Dakota State University (US)
Openalex Percentile: Top 14%
Plant Disease Resistance and Genetics
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