European Journal of Plant Pathology

, Volume 155, Issue 4, pp 1211–1223 | Cite as

Assessing the potential of culture-independent 16S rRNA microbiome analysis in disease diagnostics: the example of Dianthus gratianopolitanus and Robbsia andropogonis

  • Marco Enrique Mechan-Llontop
  • Long Tian
  • Vivian Bernal-Galeano
  • Ella Reeves
  • Mary Ann Hansen
  • Elizabeth Ann Bush
  • Boris Alexander VinatzerEmail author


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.


16S rRNA amplicon sequencing Dianthus Robbsia andropogonis Pathogen identification Disease diagnostics 


Funding information

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.

Informed consent

Not applicable. The study did not involve human participants.

Supplementary material

10658_2019_1850_MOESM1_ESM.pdf (771 kb)
Figure S1 Rarefaction curves of all individual samples drawn from raw data. (PDF 771 kb)
10658_2019_1850_MOESM2_ESM.pdf (3.4 mb)
ESM 2 (PDF 3470 kb)
10658_2019_1850_MOESM3_ESM.xlsx (655 kb)
ESM 3 (XLSX 655 kb)


  1. 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. Scholar
  2. Berg, M., & Koskella, B. (2018). Nutrient- and dose-dependent microbiome-mediated protection against a plant pathogen. Current Biology, 28(15), 2487–2492.e2483. Scholar
  3. Boonham, N., Kreuze, J., Winter, S., van der Vlugt, R., Bergervoet, J., Tomlinson, J., et al. (2014). Methods in virus diagnostics: From ELISA to next generation sequencing. Virus Research, 186, 20–31. Scholar
  4. Boxriker, M., Boehm, R., Krezdorn, N., Rotter, B., & Piepho, H.-P. (2017). Comparative transcriptome analysis of vase life and carnation type in Dianthus caryophyllus L. Scientia Horticulturae, 217(Supplement C), 61–72. Scholar
  5. Bronzato Badial, A., Sherman, D., Stone, A., Gopakumar, A., Wilson, V., Schneider, W., et al. (2018). Nanopore sequencing as a surveillance tool for plant pathogens in plant and insect tissues. Plant Disease, 102(8), 1648–1652. Scholar
  6. Campisano, A., Albanese, D., Yousaf, S., Pancher, M., Donati, C., & Pertot, I. (2017). Temperature drives the assembly of endophytic communities' seasonal succession. Environmental Microbiology, 19(8), 3353–3364. Scholar
  7. Caporaso, J. G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F. D., Costello, E. K., et al. (2010). QIIME allows analysis of high-throughput community sequencing data. Nature Methods, 7(5), 335–336. Scholar
  8. Casanova, E., Valdes, A. E., Fernandez, B., Moysset, L., & Trillas, M. I. (2004). Levels and immunolocalization of endogenous cytokinins in thidiazuron-induced shoot organogenesis in carnation. Journal of Plant Physiology, 161(1), 95–104.CrossRefGoogle Scholar
  9. 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
  10. 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. Scholar
  11. Fang, Y., & Ramasamy, R. P. (2015). Current and prospective methods for plant disease detection. Biosensors (Basel), 5(3), 537–561. Scholar
  12. 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. Scholar
  13. 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. Scholar
  14. 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. Scholar
  15. 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. Scholar
  16. Khater, M., de la Escosura-Muniz, A., & Merkoci, A. (2017). Biosensors for plant pathogen detection. Biosensors & Bioelectronics, 93, 72–86. Scholar
  17. 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. Scholar
  18. Lozupone, C., & Knight, R. (2005). UniFrac: A new phylogenetic method for comparing microbial communities. Applied and Environmental Microbiology, 71(12), 8228–8235. Scholar
  19. Massart, S., Olmos, A., Jijakli, H., & Candresse, T. (2014). Current impact and future directions of high throughput sequencing in plant virus diagnostics. Virus Research, 188, 90–96. Scholar
  20. McMurdie, P. J., & Holmes, S. (2013). Phyloseq: An R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One, 8(4), e61217. Scholar
  21. 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. Scholar
  22. Quast, C., Pruesse, E., Yilmaz, P., Gerken, J., Schweer, T., Yarza, P., et al. (2013). The SILVA ribosomal RNA gene database project: Improved data processing and web-based tools. Nucleic Acids Research, 41(Database issue), D590–D596. Scholar
  23. 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. Scholar
  24. Raszek, M. M., Guanle, L., & Plastow, G. S. (2016). Use of genomic tools to improve cattle health in the context of infectious diseases. Frontiers in Genetics, 7, 30. Scholar
  25. Reeves, E., Hansen, M. A., & Bush, E. (2017). First report of bacterial leaf spot of a hardy pink (Dianthus gratianopolitanus hybrid) caused by Burkholderia andropogonis in Virginia. Plant Disease, 101(8), 1540–1540. Scholar
  26. Riley, M., Williamson, M., & Maloy, O. (2002). Plant disease diagnosis.
  27. Schubert, T., Jeyaprakash, A., & Harmon, C. (2018). Fundamentals and advances in plant problem diagnostics. In R. J. McGovern & W. H. Elmer (Eds.), Handbook of Florists' crops diseases (pp. 13–39). Cham: Springer International Publishing.CrossRefGoogle Scholar
  28. Sergaki, C., Lagunas, B., Lidbury, I., Gifford, M. L., & Schäfer, P. (2018). Challenges and approaches in microbiome research: From fundamental to applied. Frontiers in Plant Science, 9, 1205–1205. Scholar
  29. Shade, A., McManus, P. S., & Handelsman, J. (2013). Unexpected diversity during community succession in the apple flower microbiome. MBio, 4(2).
  30. 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. Scholar
  31. Wickham, H. (2009). Ggplot2: Elegant graphics for data analysis: Springer. CrossRefGoogle Scholar
  32. 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. Scholar

Copyright information

© Koninklijke Nederlandse Planteziektenkundige Vereniging 2019

Authors and Affiliations

  1. 1.School of Plant and Environmental SciencesVirginia TechBlacksburgUSA

Personalised recommendations