Assessing the potential of culture-independent 16S rRNA microbiome analysis in disease diagnostics: the example of Dianthus gratianopolitanus and Robbsia andropogonis
The goal of this study was to determine if culture-independent 16S rRNA sequencing of plant-associated microbiomes could facilitate disease diagnosis of cheddar pinks (Dianthus gratianopolitanus) with symptoms of leaf spotting at a Virginia nursery. The microbiome composition of cheddar pinks at the same nursery and at a second nursery in the absence of any disease outbreak was determined as well. After the pathogen was identified as Burkholderia andropogonis (synonym: Robbsia andropogonis) in a parallel culture-dependent study, the microbiome of plants artificially inoculated with R. andropogonis was also analyzed. The genus Robbsia was found to be ubiquitously present on all Dianthus gratianopolitanus nursery plants. However, because of the low resolution of 16S rRNA sequencing, it was not possible to determine the presence or absence of the pathogen at the species level. While relative abundance of Robbsia sequences had slightly increased during the disease outbreak, symptomatic plants did not have a significantly higher abundance of Robbsia than asymptomatic plants. Only microbiomes of artificially inoculated plants were dominated by Robbsia. We conclude that culture-independent microbiome analysis using 16S rRNA sequencing was unable to aid disease diagnosis in this specific case. Limitations and potential of the approach in disease diagnosis in general are discussed.
Keywords16S rRNA amplicon sequencing Dianthus Robbsia andropogonis Pathogen identification Disease diagnostics
This work was supported by the Virginia Agricultural Experiment Station and the Hatch Program of the National Institute of Food and Agriculture, US Department of Agriculture, the College of Agriculture and Life Sciences, Virginia Tech, and by the National Science Foundation, grant IOS-1354215. Funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
Research involving human participants and/or animals
Not applicable. The study did not involve either humans or animals.
Not applicable. The study did not involve human participants.
- Adams, I. P., Miano, D. W., Kinyua, Z. M., Wangai, A., Kimani, E., Phiri, N., et al. (2013). Use of next-generation sequencing for the identification and characterization of maize chlorotic mottle virus and sugarcane mosaic virus causing maize lethal necrosis in Kenya. Plant Pathology, 62(4), 741–749. https://doi.org/10.1111/j.1365-3059.2012.02690.x.CrossRefGoogle Scholar
- Chalupowicz, L., Dombrovsky, A., Gaba, V., Luria, N., Reuven, M., Beerman, A., et al. (2018). Diagnosis of plant diseases using the Nanopore sequencing platform. Plant Pathology. Google Scholar
- Clarke, C. R., Studholme, D. J., Hayes, B., Runde, B., Weisberg, A., Cai, R., et al. (2015). Genome-enabled phylogeographic investigation of the quarantine pathogen Ralstonia solanacearum race 3 Biovar 2 and screening for sources of resistance against its core effectors. Phytopathology, 105(5), 597–607. https://doi.org/10.1094/PHYTO-12-14-0373-R.CrossRefPubMedGoogle Scholar
- Flight, W. G., Smith, A., Paisey, C., Marchesi, J. R., Bull, M. J., Norville, P. J., et al. (2015). Rapid detection of emerging pathogens and loss of microbial diversity associated with severe lung disease in cystic fibrosis. Journal of Clinical Microbiology, 53(7), 2022–2029. https://doi.org/10.1128/jcm.00432-15.CrossRefPubMedPubMedCentralGoogle Scholar
- Hill, T. C., Walsh, K. A., Harris, J. A., & Moffett, B. F. (2003). Using ecological diversity measures with bacterial communities. FEMS Microbiology Ecology, 43(1), 1–11. https://doi.org/10.1111/j.1574-6941.2003.tb01040.x.CrossRefPubMedGoogle Scholar
- Huang, A. D., Luo, C., Pena-Gonzalez, A., Weigand, M. R., Tarr, C. L., & Konstantinidis, K. T. (2017). Metagenomics of two severe foodborne outbreaks provides diagnostic signatures and signs of coinfection not attainable by traditional methods. Applied and Environmental Microbiology, 83(3), e02577–e02516. https://doi.org/10.1128/AEM.02577-16.CrossRefPubMedPubMedCentralGoogle Scholar
- Ivy, M. I., Thoendel, M. J., Jeraldo, P. R., Greenwood-Quaintance, K. E., Hanssen, A. D., Abdel, M. P., et al. (2018). Direct detection and identification of prosthetic joint infection pathogens in synovial fluid by metagenomic shotgun sequencing. Journal of Clinical Microbiology, 56(9), e00402–e00418. https://doi.org/10.1128/jcm.00402-18.CrossRefPubMedPubMedCentralGoogle Scholar
- Lopes-Santos, L., Castro, D. B. A., Ferreira-Tonin, M., Correa, D. B. A., Weir, B. S., Park, D., et al. (2017). Reassessment of the taxonomic position of Burkholderia andropogonis and description of Robbsia andropogonis gen. Nov., comb. nov. Antonie Van Leeuwenhoek, 110(6), 727–736. https://doi.org/10.1007/s10482-017-0842-6.CrossRefPubMedGoogle Scholar
- Peiffer, J. A., Spor, A., Koren, O., Jin, Z., Tringe, S. G., Dangl, J. L., et al. (2013). Diversity and heritability of the maize rhizosphere microbiome under field conditions. Proceedings of the National Academy of Sciences of the United States of America, 110(16), 6548–6553. https://doi.org/10.1073/pnas.1302837110.CrossRefPubMedPubMedCentralGoogle Scholar
- Ranjan, R., Rani, A., Metwally, A., McGee, H. S., & Perkins, D. L. (2016). Analysis of the microbiome: Advantages of whole genome shotgun versus 16S amplicon sequencing. Biochemical and Biophysical Research Communications, 469(4), 967–977. https://doi.org/10.1016/j.bbrc.2015.12.083.CrossRefPubMedGoogle Scholar
- Riley, M., Williamson, M., & Maloy, O. (2002). Plant disease diagnosis. https://doi.org/10.1094/PHI-I-2002-1021-01
- Shade, A., McManus, P. S., & Handelsman, J. (2013). Unexpected diversity during community succession in the apple flower microbiome. MBio, 4(2). https://doi.org/10.1128/mBio.00602-12.
- Thorburn, F., Bennett, S., Modha, S., Murdoch, D., Gunson, R., & Murcia, P. R. (2015). The use of next generation sequencing in the diagnosis and typing of respiratory infections. Journal of Clinical Virology, 69, 96–100. https://doi.org/10.1016/j.jcv.2015.06.082.CrossRefPubMedPubMedCentralGoogle Scholar
- Yagi, M., Kimura, T., Yamamoto, T., Isobe, S., Tabata, S., & Onozaki, T. (2012). QTL analysis for resistance to bacterial wilt (Burkholderia caryophylli) in carnation (Dianthus caryophyllus) using an SSR-based genetic linkage map. [journal article]. Molecular Breeding, 30(1), 495–509. https://doi.org/10.1007/s11032-011-9639-x.CrossRefGoogle Scholar