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doi: 10.15389/agrobiology.2019.5.990eng

UDC: 635.21:632.4:577.21

Acknowledgements:
Supported financially by Russian Science Foundation, grant No. 18-16-00073. Sample collecting and description were financially supported by Ministry of Education and Science of the Russian Federation (Agreement No. 14.607.21.0178, RFMEFI60717X0178).

 

ANALYSIS OF MYCOBIOME IN DAMAGED POTATO (Solanum tuberosum L.) LEAVES BY USING METAGENOMIC APPROACHES

A.A. Kichko1, T.S. Aksenova1, V.M. Shapkin1, A.O. Zverev1,
A.V. Khiutti2, E.E. Andronov1, 3, 4

1All-Russian Research Institute for Agricultural Microbiology, 3, sh. Podbel’skogo, St. Petersburg, 196608 Russia, e-mail arriam2008@yandex.ru (✉ corresponding author);
2All-Russian Research Institute of Plant Protection, 3, sh. Podbel’skogo, St. Petersburg, 196608 Russia, e-mail info@vizr.spb.ru;
3Dokuchaev Soil Science Institute, 7/2, Pyzhyovskiy per., Moscow, 397463 Russia, e-mail info@esoil.ru;
4Saint Petersburg State University, 7/9, Universitetskaya nab., St. Petersburg, 199034 Russia, e-mail spbu@spbu.ru

ORCID:
Kichko A.A. orcid.org/0000-0002-8482-6226
Zverev A.O. orcid.org/0000-0002-5315-8632
Aksenova T.S. orcid.org/0000-0002-7294-8410
Khiutti A.V. orcid.org/0000-0003-1479-7746
Shapkin V.M. orcid.org/0000-0002-8394-3009
Andronov E.E. orcid.org/0000-0002-5204-262X

Received March 21, 2019

 

The problem of potato diseases caused by fungi and fungi-like organisms is relevant for all regions of the world cultivating this crop, since it is mycoses that cause the most significant damage to plants (A. Bernreiter, 2017). The traditional approaches for identification of potato pathogens are aimed at identifying a specific pathogen and do not take into account neither other, often unknown pathogens, nor the other most important component — the beneficial microbiota of the phyllosphere community whose alterations can also become one of the causes of diseases. The novelty of this work lies in the fact that the high-throughput sequencing methods we used here is free of this disadvantages and makes it possible to identify virtually all plant microorganisms, including the phyllosphere and endosphere. The purpose of this study was to use metagenomic approaches to analyze the total fungal and fungi-like community in potato leaves that have morphological markers of damage by pathogens of the genus Alternaria and Phytophthora which are the causative agents of early blight and late blight. For fungal and fungi-like communities analysis, DNA samples was extracted from leaves of potato (Solanum tuberosum L.) cultivar Nikulinsky, affected by “alternaria” and “phytophthora” diseases types, which were later used to create amplicon libraries of ITS1 and ITS2 fragments and high-throughput sequencing on the Illumina MiSeq platform (Illumina, Inc., USA). During the bioinformatic data processing with the Illumina software and the PIPITS software package (H.S. Gweon et al, 2015), 187 OTE, 113 phylotypes for the ITS1 library and 249 OTE, 127 phylotypes for ITS2 were identified. Subsequent annotation of OTE and taxonomic analysis of the resulting communities were carried out with the QIIME program (J.G. Caporaso et al., 2010), the diversity coefficients within the community were calculated using the PAST software package (Ø. Hammer et al., 2001). Comparison of the fungal communities obtained for both types of lesion using different universal primers for the ITS1 regions (M. Usyk et al., 2017) and ITS2 (T.J. White et al., 1990) showed that only the first pair is suitable for the detection of phytophthora, and in general gives a more even community structure. The tools of automatic annotation turned out to be insufficient for objective identification of alternaria in samples, as a result we had to use the methods of manual search with the BLASTn program (S.F. Altschul et al., 1990). Since the primer pair ITS2 does not allow identification of Phytophthora in the samples, the further comparative analysis of the fungal communities of the two types of lesion was carried out using data only from the ITS1 library. The data of taxonomic analysis showed that in the affected areas for both types of mycoses a rich fungal community is formed, and, in the case of “late blight”, the fraction of the pathogen is about 30 % in the community, and in the variant with “early blight”, only 2.07 % with a significant part (about 15 %) accounted for by Phytophthora, which does not exclude the case of secondary lesion. Thus, it was shown that in the fungal and fungi-like communities formed in the areas affected by disease, the proportion of pathogens is no more than 30 %, which indicates a pronounced dynamics of the taxonomic composition of fungi in the affected area. It is obvious that high-throughput sequencing methods have a very high potential in fundamental and applied research on plant diseases of a microbiological nature.

Keywords: fungi, fungi-like organisms, pathogens, potato, Phytophthora infestans, Alternaria sp., high throughput sequencing.

 

REFERENCES

  1. Bernreiter A. Molecular diagnostics to identify fungal plant pathogens — a review of current methods. Revista Científica Ecuatoriana, 2017, 4: 26-35.
  2. Gannibal F.B., Orina A.S., Levitin M.M. Zashchita i karantin rastenii, 2010, 5: 30-32 (in Russ.). 
  3. Zhang Z., Luo L., Tan X., Kong X., Yang J., Wang D., Zhang D., Jin D., Liu Y. Pumpkin powdery mildew disease severity influences the fungal diversity of the phyllosphere. PeerJ, 2018, 6: e4559 CrossRef
  4. Kozlovskii B.E., Fillipov A.V. Zashchita ikarantinrastenii, 2007, 5: 12-13 (in Russ.). 
  5. Poshtarenko A.Yu., Smirnov A.N. Zashchita i karantin rastenii, 2011, 12: 40-42 (in Russ.). 
  6. Nikolaev A.V., Sezonova N.P., Lyubimskaya I.G., Lange F. Agrarnaya nauka Evro-Severo-Vostoka, 2014, 3(40): 19-24 (in Russ.).  
  7. Bourke A. The Visitation of God?: The Potato and the Great Irish Famine. Dublin, Lilliput Press, Ltd., 1993.
  8. Denisenkov I.A. Dostizheniya nauki i tekhniki APK, 2018, 32(3): 76-78 CrossRef (in Russ.). 
  9. Kiru S.D., Kostina L.I., Rogozina E.V., Yas'ko A.A., Chalaya N.A., Zhigadlo T.E. Trudy po prikladnoi botanike, genetike i selektsii, 2013, 173: 91-101 (in Russ.). 
  10. Pobedinskaya M.A., Plutalov P.N., Romanova S.S., Kokaeva L.Yu., Nikolaev A.V., Aleksandrova A.V., Elanskii S.N. Mikologiya i fitopatologiya, 2012, 46(6): 401-408 (in Russ.). 
  11. Smirnov A.N., Bibik T.S., Prikhod'ko E.S., Beloshapkina O.O., Kuznetsov S.A. Izvestiya TSKHA, 2015, 3: 36-46 (in Russ.). 
  12. Kowalik M. Diversity of fungi colonizing and damaging leaves of pontic azalea Azalea pontica. Acta Mycologica, 2013, 48(2): 227-236 CrossRef
  13. Russo M.L., Pelizza S.A., Cabello M.N., Stenglein S.A., Vianna M.F., Scorsetti A.C. Endophytic fungi from selected varieties of soybean (Glycine max L. Merr.) and corn (Zea mays L.) grown in an agricultural area of Argentina. Revista Argentina de Microbiología, 2016, 48(2): 154-160 CrossRef
  14. Yang H., Ye W., Ma J., Zeng D., Rong Z., Xu M., Wang Y., Zheng X. Endophytic fungal communities associated with field-grown soybean roots and seeds in the Huang-Huai region of China. PeerJ, 2018, 6: e4713 CrossRef
  15. Qin S., Yeboah S., Xu X., Liu Y., Yu B. Analysis on fungal diversity in rhizosphere soil of continuous cropping potato subjected to different furrow-ridge mulching managements. Frontiers in Microbiology, 2017, 8: 845 CrossRef
  16. Xu L. Soil fungal communities associated with plant health as revealed by next-generation sequencing. PhD thesis. Slagelse, 2011.
  17. Youssuf G., Gashgari R.M. Mycobiota associated with superficial blemishes of potato tubers. Food Biotechnology, 2013, 27(2): 137-151 CrossRef
  18. Mazur S., Kurzavińska H., Nadziakiewicz M., Nawrocki J. Redroot pigweed as a host for Alternaria alternata — the causal agent of Alternaria leaf blight in potato. Zemdirbyste-Agriculture, 2015, 102(1): 115-118 CrossRef
  19. Cwalina-Ambroziak B., Trojak A. Effectiveness of selected fungicides in potato protection against Phytophthora Infestans and Alternaria spp. Polish Journal of Natural Science, 2011, 26(4): 275-284.
  20. Cwalina-Ambroziak B., Damszel M.M., Głosek-Sobieraj M. The effect of biological and chemical control agents on the health status of the very early potato cultivar Rosara. Journal of Plant Protection Research, 2015, 55(4): 389-395 CrossRef
  21. Prikhod'ko E.S., Selitskaya O.V., Smirnov A.N. Izvestiya TSKHA, 2016, 5: 68-78 (in Russ.). 
  22. Vutto N.L., Gapeeva T.A., Pundik A.N., Tretyakova T.G., Volotovski I.D. Transgenic Belarusian-bred potato plants expressing the genes for antimicrobial peptides of the cecropin-melittin type. Russian Journal of Genetics, 2010, 46(12): 1626-1634 CrossRef
  23. Raja H.A., Miller A.N., Pearce C.J., Oberlies N.H. Fungal identification using molecular tools: a primer for the natural products research community. Journal of Natural Products, 2018, 80(3): 756-770 CrossRef
  24. Riley M.B., Williamson M.R., Maloy O. Plant disease diagnosis. Plant Health Instructor, 2002 CrossRef. Available https://www.apsnet.org/edcenter/disimpact-mngmnt/casestudies/Pages/PlantDiseaseDiagnosis.aspx. Accessed 19.06.2019.
  25. Ray M., Ray A., Dash S., Mishra A., Achary K.G., Nayak S., Singh S. Fungal disease detection in plants: Traditional assays, novel diagnostic techniques and biosensors. Biosensors and Bioelectronics, 2017, 87: 708-723 CrossRef
  26. Sankaran S., Mishra A., Ehsani R., Davis C. A review of advanced techniques for detecting plant diseases. Computers and Electronics in Agriculture, 2010, 72(1): 1-13 CrossRef
  27. Kumbhar N.P., Patil S.B. A review for agricultural plant diseases detection using different techniques. International Journal of Electrical and Electronics Engineers, 2017, 9(1): 891-901.
  28. Gagkaeva T.Yu., Gannibal F.B., Gavrilova O.P. V sbornike: Vysokoproizvoditel'nye i vysokotochnye tekhnologii i metody fitosanitarnogo monitoring [High-performance and high-precision technologies and methods of phytosanitary monitoring]. St. Petersburg, 2009: 4-14 (in Russ.). 
  29. Lau H.Y., Botella J.R. Advanced DNA-based point-of-care diagnostic methods for plant diseases detection. Front. Plant Sci., 2017, 8: 2016 CrossRef
  30. Lees A.K., Sullivan L., Cullen D.W. A quantitative polymerase chain reaction assay for the detection of Polyscytalum pustulans, the cause of skin spot disease of potato. Journal of Phytopathology, 2009, 157(3): 154-158 CrossRef
  31. Kokaeva L.Yu., Khusnetdinova T.I., Berezov Yu.I., Balabko P.N., Elanskii S.N. Zashchita kartofelya, 2017, 2: 8-11 (in Russ.).
  32. Pavlovskaya N.E., Solokhina I.Yu., Lushnikov A.V. Biologiya v sel'skom khozyaistve, 2015, 4: 7-11 (in Russ.). 
  33. Schmidt P.A., Bálint M., Greshake B., Bandow C., Römbke J., Schmitt I. Illumina metabarcoding of a soil fungal community. Soil Biology and Biochemistry, 2013, 65: 128-132 CrossRef
  34. Motooka D., Fujimoto K., Tanaka R., Yaguchi T., Gotoh K., Maeda Y., Furuta Y., Kurakawa T., Goto N., Yasunaga T., Narazaki M., Kumanogoh A., Horii T., Iida T., Takeda K., Nakamura S. Fungal ITS1 deep-sequencing strategies to reconstruct the composition of a 26-species community and evaluation of the gut mycobiota of healthy Japanese individuals. Frontiers in Mycrobiology, 2017, 8: 238 CrossRef
  35. Usyk M., Zolnik C.P., Patel H., Levi M.H., Burk R.D. Novel ITS1 fungal primers for characterization of the mycobiome. mSphere, 2017, 2(6): e00488-17 CrossRef
  36. White T.J., Bruns T., Lee S., Taylor J. Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: PCR Protocols: Aguide to methods and applications. M.A. Innis, D.H. Gelfand, J.J. Sninsky, T.J. White (eds.). San Diego, Academic Press, 1990: 315-322 CrossRef
  37. Blaalid R., Kumar S., Nilsson R.H., Abarenkov K., Kirk P.M., Kauserud H. ITS1 versus ITS2 as DNA metabarcodes for fungi. Molecular Ecology Resources, 2013, 13(2): 218-224 CrossRef
  38. Seifert K.A. Progress towards DNA barcoding of fungi. Molecular Ecology Resources, 2009, 9(s1): 83-89 CrossRef
  39. Caporaso J.G, Kuczynski J., Stombaugh J., Bittinger K., Bushman F.D., Costello E.K.,  Fierer N., Peña A.G., Goodrich J.K., Gordon J.I., Huttley G.A., Kelley S.T., Knights D., Koenig J.E., Ley R.E., Lozupone C.A., McDonald D., Muegge B.D., Pirrung M., Reeder J., Sevinsky J.R., Turnbaugh P.J., Walters W.A., Widmann J., Yatsunenko T., Zaneveld J., Knight R. QIIME allows analysis of high-throughput community sequencing data. Nature Methods, 2010, 7(5): 335-336 CrossRef
  40. Gweon H.S., Oliver A., Taylor J., Booth T., Gibbs M., Read D.S., Schonrogge K. PIPITS: an automated pipeline for analyses of fungal internal transcribed spacer sequences from the Illumina sequencing platform. Methods in Ecology and Evolution, 2015, 6(8): 973-980 CrossRef
  41. Hammer Ø., Harper D.A.T., Ryan P.D. PAST: Paleontological statistics software package for education and data analysis. Palaeontologia Electronica, 2001, 4(1): 9.
  42. Altschul S.F., Gish W., Miller W., Myers E.W., Lipman D.J. Basic local alignment search tool. Journal of Molecular Biology, 1990, 215(3): 403-410 CrossRef
  43. Halwachs B., Madhusudhan N., Krause R., Nilsson R.H., Moissl-Eichinger C., Högenauer C., Thallinger G.G., Gorkiewicz G. Critical issues in mycobiota analysis. Frontiers in Mycrobiology, 2017, 8: 180 CrossRef

 

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