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Genomic Comparisons of Two Armillaria Species with Different Ecological Behaviors and Their Associated Soil Microbial Communities

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Abstract

Armillaria species show considerable variation in ecological roles and virulence, from mycorrhizae and saprophytes to important root pathogens of trees and horticultural crops. We studied two Armillaria species that can be found in coniferous forests of northwestern USA and southwestern Canada. Armillaria altimontana not only is considered as a weak, opportunistic pathogen of coniferous trees, but it also appears to exhibit in situ biological control against A. solidipes, formerly North American A. ostoyae, which is considered a virulent pathogen of coniferous trees. Here, we describe their genome assemblies and present a functional annotation of the predicted genes and proteins for the two Armillaria species that exhibit contrasting ecological roles. In addition, the soil microbial communities were examined in association with the two Armillaria species within a 45-year-old plantation of western white pine (Pinus monticola) in northern Idaho, USA, where A. altimontana was associated with improved tree growth and survival, while A. solidipes was associated with reduced growth and survival. The results from this study reveal a high similarity between the genomes of the beneficial/non-pathogenic A. altimontana and pathogenic A. solidipes; however, many relatively small differences in gene content were identified that could contribute to differences in ecological lifestyles and interactions with woody hosts and soil microbial communities.

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Data Availability

The datasets generated and/or analyzed during the current study are available in the NCBI database. The corresponding genome assemblies were deposited at the NCBI with accession number JAIWYR000000000 for Armillaria altimontana, and JAIWYQ000000000 for A. solidipes, and microbial dataset is in NCBI SRA database under accession number PRJNA767898.

References

  1. Hess J, Skrede I, Chaib De Mares M, Hainaut M, Henrissat B, Pringle A (2018) Rapid divergence of genome architectures following the origin of an ectomycorrhizal symbiosis in the gene Amanita. Mol Biol Evol 35:2786–2804. https://doi.org/10.1093/molbev/msy179

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Möller M, Stukenbrock EH (2017) Evolution and genome architecture in fungal plant pathogens. Nat Rev Microbiol 15:756–771. https://doi.org/10.1038/nrmicro.2017.76

    Article  CAS  PubMed  Google Scholar 

  3. Ryberg M, Matheny PB (2012) Asynchronous origins of ectomycorrhizal clades of Agaricales. Proc R Soc B 279:2003–2011. https://doi.org/10.1098/rspb.2011.2428

    Article  PubMed  Google Scholar 

  4. Tedersoo L, May TW, Smith ME (2010) Ectomycorrhizal lifestyle in fungi: global diversity, distribution, and evolution of phylogenetic lineages. Mycorrhiza 20:217–263. https://doi.org/10.1007/s00572-009-0274-x

    Article  PubMed  Google Scholar 

  5. Kohler A, Kuo A, Nagy L et al (2015) Convergent losses of decay mechanisms and rapid turnover of symbiosis genes in mycorrhizal mutualists. Nat Genet 47:410–415. https://doi.org/10.1038/ng.3223

    Article  CAS  PubMed  Google Scholar 

  6. Veneault-Fourrey C, Commun C, Kohler A, Morin E, Balestrini R, Plett J, Danchin E, Coutinho P, Wiebenga A, DeVries RP, Henrissat B, Martin F (2014) Genomic and transcriptomic analysis of Laccaria bicolor CAZome reveals insights into polysaccharides remodelling during symbiosis establishment. Fungal Genet Biol 72:168–181. https://doi.org/10.1016/j.fgb.2014.08.007

    Article  CAS  PubMed  Google Scholar 

  7. Dalman K, Himmelstrand K, Olson A, Lind M, Brandstörm-During M, Stenlid J (2013) A genome-wide association study identifies genomic regions for virulence in the non-model organism Heterobasidion annosum s.s. PLoSOne. 8:e53525. https://doi.org/10.1371/journal.pone.0053525

    Article  CAS  Google Scholar 

  8. Zeng Z, Sun H, Vainio EJ, Raffaello T, Kovalchuk A, Morin E, Duplessis S, Asiegbu FO (2018) Intraspecific comparative genomics of isolates of the Norway spruce pathogen (Heterobasidion parviporum) and identification of its potential virulence factors. BMC Genomics 19:220. https://doi.org/10.1186/s12864-018-4610-4

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Castanera R, Borgognone A, Pisbarro AG, Ramírez L (2017) Biology, dynamics and applications of transposable elements in basidiomycete fungi. Appl Microbiol Biotechnol 101:1337–1350. https://doi.org/10.1007/s00253-017-8097-8

    Article  CAS  PubMed  Google Scholar 

  10. Marçais B, Bréda N (2006) Role of an opportunistic pathogen in the decline of stressed oak trees. J Ecol 94:1214–1223. https://doi.org/10.1111/j.1365-2745.2006.01173.x

    Article  Google Scholar 

  11. Baumgartner K, Coetzee MPA, Hoffmeister D (2011) Secrets of the subterranean pathosystem of Armillaria. Mol Plant Pathol 12:515–534. https://doi.org/10.1111/j.1364-3703.2010.00693.x

    Article  PubMed  PubMed Central  Google Scholar 

  12. Cleary MR, van der Kamp BJ, Morrison DJ (2012) Pathogenicity and virulence of Armillaria sinapina and host response to infection in Douglas-fir, western hemlock and western redcedar in the southern Interior of British Columbia. Forest Pathol 42:481–491. https://doi.org/10.1111/j.1439-0329.2012.00782.x

    Article  Google Scholar 

  13. Heinzelmann R, Prospero S, Rigling D (2017) Virulence and stump colonization ability of Armillaria borealis on Norway spruce seedlings in comparison to sympatric Armillaria species. Plant Dis 101:470–479. https://doi.org/10.1094/PDIS-06-16-0933-RE

    Article  CAS  PubMed  Google Scholar 

  14. Morrison DJ, Pellow KW (2002) Variation in virulence among isolates of Armillaria ostoyae. Forest Pathol 32:99–107. https://doi.org/10.1046/j.1439-0329.2002.00275.x

    Article  Google Scholar 

  15. Morrison DJ (2004) Rhizomorph growth habit, saprophytic ability and virulence of 15 Armillaria species. Forest Pathol 34:15–26. https://doi.org/10.1046/j.1439-0329.2003.00345.x

    Article  Google Scholar 

  16. Prospero S, Holdenrieder O, Rigling D (2004) Comparison of the virulence of Armillaria cepistipes and Armillaria ostoyae on four Norway spruce provenances. Forest Pathol 34:1–14. https://doi.org/10.1046/j.1437-4781.2003.00339.x

    Article  Google Scholar 

  17. Brazee NJ, Ortiz-Santana B, Banik MT, Lindner DL (2012) Armillaria altimontana, a new species from the western interior of North America. Mycologia 104(5):1200–1205. https://doi.org/10.3852/11-409

    Article  PubMed  Google Scholar 

  18. Ferguson BA, Dreisbach TA, Parks CG, Filip G, Schmitt CL (2003) Coarse-scale population structure of pathogenic Armillaria species in a mixed conifer forest in the Blue Mountains of northeast Oregon. Can J For Res 33:612–633. https://doi.org/10.1139/x03-065

    Article  Google Scholar 

  19. Kim M-S, Klopfenstein NB, McDonald GI, Arumuganathan K, Vidaver AK (2000) Characterization of North America Armillaria species by nuclear DNA content and RFLP analysis. Mycologia 92:874–883. https://doi.org/10.1080/00275514.2000.12061232

    Article  CAS  Google Scholar 

  20. Warwell MV, McDonald GI, Hanna JW, Kim MS, Lalande BM, Stewart JE, Hudak AT, Klopfenstein NB (2019) Armillaria altimontana is associated with healthy western white pine (Pinus monticola): potential in situ biological control of Armillaria root disease pathogen, A. solidipes. Forests.10:294. https://doi.org/10.3390/f10040294

  21. Rizzo DM, Harrington TC (1993) Delineation and biology of clones of Armillaria ostoyae, A. gemina and A. calvescens. Mycologia, 85(2):164-174. https://doi.org/10.2307/3760452.

  22. Klopfenstein NB, Stewart JE, Ota Y, Hanna JW, Richardson BA, Ross-Davis AL, Elías-Román RD, Korhonen K, Keča N, Iturritxa E, Alvarado-Rosales D, Solheim H, Brazee NJ, Łakomy P, Cleary MR, Hasegawa E, Kikuchi T, Garza-Ocañas F, Tsopelas P, Rigling D, Prospero S, Tsykun T, Bérubé JA, Stefani FOP, Jafarpour S, Antonín V, Tomšovský M, McDonald GI, Woodward S, Kim MS (2017) Insights into the phylogeny of Northern Hemisphere Armillaria: neighbor-net and Bayesian analyses of translation elongation factor 1-α gene sequences. Mycologia 109:75–91. https://doi.org/10.1080/00275514.2017.1286572

    Article  CAS  PubMed  Google Scholar 

  23. Koch RA, Wilson AW, Séné O, Henkel TW, Aime MC (2017) Resolved phylogeny and biogeography of the root pathogen Armillaria and its gasteroid relative, Guyanagaster. BMC Evolutionary Biology. 17:33–48. https://doi.org/10.1186/s12862-017-0877-3

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Heinzelmann R, Dutech C, Tsykun T, Labbé F, Soularue J-P, Prospero S (2019) Latest advances and future perspectives in Armillaria research. Can J Plant Path 41:1–23. https://doi.org/10.1080/07060661.2018.1558284

    Article  Google Scholar 

  25. Devkota P, Hammerschmidt R (2020) The infection process of Armillaria mellea and Armillaria solidipes. Physiol Mol Plant Pathol 112:101543. https://doi.org/10.1016/j.pmpp.2020.101543

    Article  CAS  Google Scholar 

  26. Collins C, Keane TM, Turner DJ, O’Keefe G, Fitzpatrick DA, Doyle S (2013) Genomic and proteomic dissection of the ubiquitous plant pathogen, Armillaria mellea: toward a new infection model system. J Proteome Res 12:2552–2570. https://doi.org/10.1021/pr301131t

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Ross-Davis AL, Stewart JE, Hanna JW, Kim M-S, Cronn R, Rai H, Richardson BR, McDonald GI, Klopfenstein NB (2013) Transcriptome characterization of an Armillaria root disease pathogen reveals candidate pathogenicity-related genes. Forest Pathol 43:468–477. https://doi.org/10.1111/efp.12056

    Article  Google Scholar 

  28. Sipos G, Prasanna AN, Walter MC, O’Connor E, Bálint B, Krizsán K, Kiss B, Hess J, Varga T, Slot J, Riley R, Bóka B, Rigling D, Barry K, Lee J, Mihaltcheva S, LaButti K, Lipzen A, Waldron R, Moloney NM, Sperisen C, Kredics L, Vágvölgyi C, Patrignani A, Fitzpatrick D, Nagy I, Doyle S, Anderson JB, Grigoriev IV, Güldener U, Münsterkötter M, Nagy LG (2017) Genome expansion and lineage-specific genetic innovations in the forest pathogenic fungi Armillaria. Nat Ecol Evol 1:1931–1941. https://doi.org/10.1038/s41559-017-0347-8

    Article  PubMed  Google Scholar 

  29. Azul AM, Nunes J, Ferreira I, Coehlo AS, Verissmo P, Trovao J, Campos A, Castro O, Freitas H (2014) Valuing native ectomycorrhizal fungi as a Mediterranean forestry component for sustainable and innovative solutions. Botany 92:161–171. https://doi.org/10.1139/cjb-2013-0170

    Article  CAS  Google Scholar 

  30. Baldrian P (2017) Forest microbiome: diversity, complexity, and dynamics. FEMS Microbiology Reviews. 41:109-130. https://doi.org/10.1093/femsre/fuw040

  31. Leake J, Johnson D, Donnelly D, Muckle G, Boddy L, Read D (2004) Networks of power and influence: the role of mycorrhizal mycelium in controlling plant communities and agroecosystem functioning. Can J Bot 82:1016–1045. https://doi.org/10.1139/b04-060

    Article  Google Scholar 

  32. Lee Taylor D, Sinsabaugh RL (2014) Chapter 4: the soil fungi: occurrence, phylogeny, and ecology. In E.A. Paul (4th ed.), Soil microbiology, ecology and biochemistry. Cambridge, MA: Academic Press. p. 339–382. eBook ISBN: 9780123914118. https://doi.org/10.1016/C2011-0-05497-2.

  33. Saif SR, Khan AG (1975) The influence of season and stage of development of plant on endogone mycorrhiza of field-grown wheat. Can J Microbiol 82:1020–1024. https://doi.org/10.1139/m75-151

    Article  Google Scholar 

  34. Cardenas E, Kranabetter JM, Hope G, Maas KR, Hallam S, Mohn WM (2015) Forest harvesting reduces the soil metagenomic potential for biomass decomposition. ISME 9:2465–2476. https://doi.org/10.1038/ismej.2015.57

    Article  CAS  Google Scholar 

  35. Chapman SK, Koch GW (2007) What type of diversity yields synergy during mixed litter decomposition in a natural forest ecosystem? Plant Soil 299:153–162. https://doi.org/10.1007/s11104-007-9372-8

    Article  CAS  Google Scholar 

  36. Davidson EA, Janssens IA (2006) Temperature sensitivity of soil carbon decomposition and feedbacks to climate change. Nature 440:165–173. https://doi.org/10.1038/nature04514

    Article  CAS  PubMed  Google Scholar 

  37. Robertson GP, Groffman PM (2014) Chapter 14: nitrogen transformation. In E.A. Paul (4th ed.), Soil microbiology, ecology and biochemistry. Cambridge, MA: Academic Press. p. 339–382. eBook ISBN: 9780123914118. https://doi.org/10.1016/C2011-0-05497-2.

  38. Schloter M, Dilly O, Munch JC (2003) Indicators for evaluating soil quality. Agr Ecosyst Environ 98:255–262. https://doi.org/10.1016/S0167-8809(03)00085-9

    Article  Google Scholar 

  39. Allison SD, Martiny JBH (2008) Resistance, resilience, and redundancy in microbial communities. PNAS 105(1):11512–11519. https://doi.org/10.1073/pnas.0801925105

    Article  PubMed  PubMed Central  Google Scholar 

  40. Horwath W (2014) Chapter 12: carbon cycling: the dynamics and formation of organic matter. In E.A. Paul (4th ed.), Soil microbiology, ecology and biochemistry. Cambridge, MA: Academic Press. p. 339–382. eBook ISBN: 9780123914118. https://doi.org/10.1016/C2011-0-05497-2.

  41. Kile GA, McDonald GI, Byler JW (1991) Ecology and disease in natural forests. In: C.G. Shaw and G.A. Kile, Armillaria root disease. United States Department of Agriculture Forest Service. Agricultural Handbook No. 691. Washington D.C. p. 102–121.

  42. Kim MS, Ross-Davis AL, Stewart JE, Hanna JW, Warwell MV, Zambino PJ, Cleaver C, McDonald GI, Page-Dumroese DS, Moltzan B, Klopfenstein NB (2016) Can metagenomic studies of soil microbial communities provide novel insights toward develo** novel management approaches for Armillaria root disease? Ramsey, A. and Palacios, P., compilers. Proceedings of the 63rd annual Western International Forest Disease Work Conference, Sept. 21–25, 2015. Newport, OR, USA.

  43. Stewart JE, Kim M-S, Lalande, BM, Klopfenstein NB (2021) Pathobiome and microbial communities associated with forest tree root diseases [Chapter 15]. In: Asiegbu, Fred O.; Kovalchuk, Andriy, eds. Forest microbiology - tree microbiome: phyllosphere, endosphere, and rhizosphere, Volume 1. London, UK: Academic Press, Elsevier, Inc. p. 277–292. https://doi.org/10.1016/C2019-0-03562-5.

  44. Kedves O, Shahab D, Champramary S, Chen L, Indic G, Bóka B, Nagy VD, Vágvölgyi C, Kredics L, Sipos G (2021) Epidemiology, biotic interactions, and biological control of armillarioids in the Northern Hemisphere. Pathogens 10:76. https://doi.org/10.3390/pathogens10010076

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Ross-Davis A, Settles M, Hanna JW, Shaw JD, Hudak AT, Page-Dumroese DS, Klopfenstein NB (2015) Using a metagenomic approach to improve our understanding of Armillaria root disease. pp. 73–78 in: Murray, M. and Palacios, P., compilers. Proceedings of the 62nd annual Western International Forest Disease Work Conference, Sept. 8–12, 2014. Cedar City, UT, USA.

  46. Gurevich A, Saveliev V, Vyahhi N, Tesler G (2013) QUAST: quality assessment tool for genome assemblies. Bioinformatics 29(8):1072–1075. https://doi.org/10.1093/bioinformatics/btt086

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  47. Simão FA, Waterhouse RM, Ioannidis P, Kriventseva EV, Zdobnov EM (2015) BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31(19):3210–3212. https://doi.org/10.1093/bioinformatics/btv351

    Article  CAS  PubMed  Google Scholar 

  48. Bertels F, Silander OK, Pachkov M, Rainey PB, van Nimwegen E (2014) Automated reconstruction of whole genome phylogenies from short sequence reads. Mol Biol Evol 31(5):1077–1088. https://doi.org/10.1093/molbev/msu088

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  49. Langmead B, Salzberg SL (2012) Fast gapped-read alignment with Bowtie 2. Nat Methods 9:357–359. https://doi.org/10.1038/nmeth.1923

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  50. Guindon S, Dufayard JF, Lefort V, Anisimova M, Hordijk W, Gascuel O (2010) New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Systematic Biology. 59(3):307–21. https://doi.org/10.1093/sysbio/syq010

    Article  CAS  PubMed  Google Scholar 

  51. Smit AFA, Hubley R (2015) RepeatModeler Open-1.0. 2013–2015. Available from: https://www.repeatmasker.org. Accessed Mar 2021

  52. Cantarel BL, Korf I, Robb SMC, Parra G, Ross E, Moore B, Holt C, Sánchez Alvarado A, Yandell M (2008) MAKER: an easy-to-use annotation pipeline designed for emerging model organism genomes. Genome Res 18(1):188–196. https://doi.org/10.1101/gr.6743907

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Smit AR, Hubley R, Green P (2013) RepeatMasker Open-4.0. http://www.repeatmasker.org. Accessed Mar 2021

  54. Keller O, Kollmar M, Stanke M, Waack S (2011) A novel hybrid gene prediction method employing protein multiple sequence alignments. Bioinformatics 27(6):757–763. https://doi.org/10.1093/bioinformatics/btr010

    Article  CAS  PubMed  Google Scholar 

  55. Ter-Hovhannisyan V, Lomsadze A, Chernoff Y, Borodovsky M (2008) Gene prediction in novel fungal genomes using an ab initio algorithm with unsupervised training. Genome Res 18:1979–1990. https://doi.org/10.1101/gr.081612.108

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  56. Zaharia M, Bolosky WJ, Curtis K, Fox A, Patterson D, Shenker S, Stoica I, Karp RM, Sittler T (2011) Faster and more accurate sequence alignment with SNAP. ar**v:1111.5572v1.

  57. Lowe TM, Eddy SR (1997) tRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res 25:955–964. https://doi.org/10.1093/nar/25.5.955

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL (2009) BLAST+: architecture and applications. BMC Bioinformatics 10:421–429. https://doi.org/10.1186/1471-2105-10-421

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  59. Jones P, Binns D, Chang H, Fraser M, Li W, McAnulla C, McWilliam H, Maslen J, Mitchell A, Nuka G, Pesseat S, Quinn AF, Sangrador-Vegas A, Scheremetjew M, Yong S, Lopez R, Hunter S (2014) InterProScan 5: genome-scale protein function classification. Bioinformatics 30(9):1236–1240. https://doi.org/10.1093/bioinformatics/btu031

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  60. Zhang H, Yohe T, Huang L, Entwistle S, Wu P, Yang Z, Busk PK, Xu Y, Yin Y (2018) dbCAN2: a meta server for automated carbohydrate-active enzyme annotation. Nucleic Acids Res 46:W95–W101. https://doi.org/10.1093/nar/gky418

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  61. Urban M, Cuzick A, Seager J, Wood V, Rutherford K, Venkatesh SY, De Silva N, Martinez MC, Pedro H, Yates AD, Hassani-Pak K, Hammond-Kosack KE (2020) PHI-base: the pathogen–host interactions database. Nucleic Acids Res 48:D613–D620. https://doi.org/10.1093/nar/gkz904

    Article  CAS  PubMed  Google Scholar 

  62. Blin K, Shaw S, Steinke K, Villebro R, Ziemert N, Lee SY, Medema MH, Weber T (2019) antiSMASH 5.0: updates to the secondary metabolite genome mining pipeline. Nucleic Acids Research. Volume 47, Issue W1:W81–W87. https://doi.org/10.1093/nar/gkz310.

  63. Almagro Armenteros JJ, Sønderby CK, Sønderby SK, Nielsen H, Winther O (2017) DeepLoc: prediction of protein subcellular localization using deep learning. Bioinformatics 33:3387–3395. https://doi.org/10.1093/bioinformatics/btx431

    Article  CAS  PubMed  Google Scholar 

  64. Soderlund C, Nelson W, Shoemaker A, Paterson A (2006) SyMAP: a system for discovering and viewing syntenic regions of FPC maps. Genome Res 16:1159–1168. https://doi.org/10.1101/gr.5396706

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Soderlund C, Bomhoff M, Nelson W (2011) SyMAP: a turnkey synteny system with application to plant genomes. Nucleic Acids Res 39(10):e68. https://doi.org/10.1093/nar/gkr123

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Xu L, Dong Z, Fang L, Luo Y, Wei Z, Guo H, Zhang G, Gu YQ, Coleman-Derr D, **a Q, Wang Y (2019) OrthoVenn2: a web server for whole-genome comparison and annotation of orthologous clusters across multiple species. Nucleic Acids Res 47:W52–W58. https://doi.org/10.1093/nar/gkz333

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Rehner SA, Buckley E (2005) A Beauveria phylogeny inferred from nuclear ITS and EF1-a sequences: evidence for cryptic diversification and links to Cordyceps teleomorphs. Mycologia 97:84–98. https://doi.org/10.3852/mycologia.97.1.84

    Article  CAS  PubMed  Google Scholar 

  68. White TJ, Bruns T, Taylor J (1990) Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: A guide to molecular methods and applications (Innis MA, Gelfand DH, Sninsky JJ, White JW, eds). Academic Press, New York: 315–322. https://doi.org/10.1016/B978-0-12-372180-8.50042-1.

  69. Walters W, Hyde ER, Berg-Lyons D, Ackermann G, Humphrey G, Parada A, Gilbert JA, Jansson JK, Caporaso JG, Fuhrman JA, Apprill A, Knight B (2015) Improved bacterial 16S rRNA gene (V4 and V4–5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. mSystems 1(1):e00009–15. doi: https://doi.org/10.1128/mSystems.00009-15.

  70. Bolger AM, Lohse M, Usadel B (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30:2114–2120. https://doi.org/10.1093/bioinformatics/btu170

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  71. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75:7537–7541. https://doi.org/10.1128/AEM.01541-09

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD (2013) Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79:5112–5120. https://doi.org/10.1128/AEM.01043-13

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200. https://doi.org/10.1093/bioinformatics/btr381

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  74. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26(19):2460–2461. https://doi.org/10.1093/bioinformatics/btq461

    Article  CAS  PubMed  Google Scholar 

  75. Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acid Res 41:D590–D596. https://doi.org/10.1093/nar/gks1219

    Article  CAS  PubMed  Google Scholar 

  76. Nilsson RH, Larsson K-H, Taylor AFS, Bengtsson-Palme J, Jeppesen JS, Schigel D, Kennedy P, Picard K, Glöckner FO, Tedersoo L, Saar I, Kõljalg U, Abarenkov K (2019) The UNITE database for molecular identification of fungi: handling dark taxa and parallel taxonomic classifications. Nucleic Acids Res 47:D259–D264. https://doi.org/10.1093/nar/gky1022

    Article  CAS  PubMed  Google Scholar 

  77. Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267. https://doi.org/10.1128/AEM.00062-07

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  78. Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Szoecs E, Wagner H (2017) vegan: Community Ecology Package. R package version 2.4–2.

  79. Olofsson TC, Vásquez A (2008) Detection and identification of a novel lactic acid bacterial flora within the honey stomach of the honeybee Apis mellifera. Curr Microbiol 57:356–363. https://doi.org/10.1007/s00284-008-9202-0

    Article  CAS  PubMed  Google Scholar 

  80. Hill TCJ, Walsh KA, Harris JA, Moffett BF (2006) Using ecological diversity measures with bacterial communities. FEMS Microbiol Ecol 43:1–11. https://doi.org/10.1111/j.1574-6941.2003.tb01040.x

    Article  Google Scholar 

  81. Nagendra H (2002) Opposite trends in response to Shannon and Simpson indices of landscape diversity. Appl Geogr 22:175–186. https://doi.org/10.1016/S0143-6228(02)00002-4

    Article  Google Scholar 

  82. Zhang H, John R, Peng Z, Yuan J, Chu C, Du G, Zhou S (2012) The relationship between species richness and evenness in plant communities along a successional gradient: a study from sub-alpine meadows of the eastern Qinghai-Tibetan Plateau. China PLoS ONE 7:e49024. https://doi.org/10.1371/journal.pone.0049024

    Article  CAS  PubMed  Google Scholar 

  83. Paulson JN, Talukder H, Pop M, Bravo HC (2021) metagenomeSeq: statistical analysis for sparse high-throughput sequencing. Bioconductor package: 1.16.0.

  84. Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer-Verlag New York. ISBN 978–3–319–24277–4. https://ggplot2.tidyverse.org. Accessed Mar 2021

  85. Santana MF, Queiroz MV (2015) Transposable elements in fungi: a genomic approach. Sci J Genet Gene Ther 1(1):012–016

    Article  Google Scholar 

  86. Coleman JJ, Mylonakis E (2009) Efflux in fungi: La Pièce de Résistance. PLoS Pathog 5(6):e1000486. https://doi.org/10.1371/journal.ppat.1000486

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  87. Macheleidt J, Mattern DJ, Fischer J, Netzker T, Weber J, Schroeckh V, Valiantem V, Brakhage AA (2016) Regulation and role of fungal secondary metabolites. Annu Rev Genet 50:371–392. https://doi.org/10.1146/annurev-genet-120215-035203

    Article  CAS  PubMed  Google Scholar 

  88. Syed K, Yadav JS (2012) P450 monooxygenases (P450ome) of the model white rot fungus Phanerochaete chrysosporium. Crit Rev Microbiol 38(4):339–363. https://doi.org/10.3109/1040841X.2012.682050

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  89. Ichinose H (2013) Cytochrome P450 of wood-rotting basidiomycetes and biotechnological applications. Biotechnol Appl Biochem 60:71–81. https://doi.org/10.1002/bab.1061

    Article  CAS  PubMed  Google Scholar 

  90. Qhanya LB, Matowane G, Chen W, Sun Y, Letsimo EM, Parvez M, Yu J-H, Mashele SS, Syed K (2015) Genome-wide annotation and comparative analysis of cytochrome P450 monooxygenases in basidiomycete biotrophic plant pathogens. PLoS ONE 10(11):e0142100. https://doi.org/10.1371/journal.pone.0142100

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  91. Durairaj P, Hur J-S, Yun H (2016) Versatile biocatalysis of fungal cytochrome P450 monooxygenases. Microb Cell Fact 15:125. https://doi.org/10.1186/s12934-016-0523-6

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  92. Gonçalves AP, Heller J, Daskalov A, Videra A, Glass NL (2017) Regulated forms of cell death in fungi. Front Microbiol 8:1837. https://doi.org/10.3389/fmicb.2017.01837

    Article  PubMed  PubMed Central  Google Scholar 

  93. Schmidt-Dannert C (2014) Biosynthesis of terpenoid natural products in fungi. In: Schrader J., Bohlmann J. (eds) Biotechnology of isoprenoids. Advances in biochemical engineering/biotechnology, vol 148. Springer, Cham. DOI: https://doi.org/10.1007/10_2014_283.

  94. Quin MB, Flynn CM, Schmidt-Dannert C (2014) Traversing the fungal terpenome. Nat Prod Rep 31(10):1449–1473. https://doi.org/10.1039/c4np00075g

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  95. Shaw CG III, Roth L (1978) Control of Armillaria root rot in managed coniferous forests. Eur J For Pathol 8:163–174. https://doi.org/10.1111/j.1439-0329.1978.tb01463.x

    Article  Google Scholar 

  96. Coetzee MPA, Wingfield BD, Wingfield MJ (2018) Armillaria root-rot pathogens: species boundaries and global distribution. MDPI Pathogens 7:83. https://doi.org/10.3390/pathogens7040083

    Article  CAS  Google Scholar 

  97. Burdsall HH, Volk TJ (2008) Armillaria solidipes, an older name for the fungus called Armillaria ostoyae. North American Fungi 3:261–267. https://doi.org/10.2509/naf2008.003.00717

    Article  Google Scholar 

  98. Presti LL, Lanver D, Schweizer G, Tanaka S, Liang L, Tollot M, Zuccaro A, Reissmann S, Kahmann R (2015) Fungal effectors and plant susceptibility. Annu Rev Plant Biol 66:513–545. https://doi.org/10.1146/annurev-arplant-043014-114623

    Article  CAS  PubMed  Google Scholar 

  99. Kim K, Jeon J, Choi J, Cheong K, Song H, Choi G, Kang S, Lee Y (2016) Kingdom-wide analysis of fungal small secreted proteins (SSPs) reveals their potential role in host association. Front Plant Sci 7:186. https://doi.org/10.3389/fpls.2016.00186

    Article  PubMed  PubMed Central  Google Scholar 

  100. Zhao Z, Liu H, Wang C, Xu J-R (2013) Comparative analysis of fungal genomes reveals different plant cell wall degrading capacity in fungi. BMC Genomics 14:274–288. https://doi.org/10.1186/1471-2164-14-274

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  101. Krijger J-J, Thon MR, Deising HB, Wirsel SGR (2014) Compositions of fungal secretomes indicate a greater impact of phylogenetic history than lifestyle adaptation. BMC Genomics 15:722–739. https://doi.org/10.1186/1471-2164-15-722

    Article  PubMed  PubMed Central  Google Scholar 

  102. Varrot A, Basheer SM, Imberty A (2013) Fungal lectins: structure, function and potential applications. Curr Opin Struct Biol 23:678–685. https://doi.org/10.1016/j.sbi.2013.07.007

    Article  CAS  PubMed  Google Scholar 

  103. Sahu N, Merényi Z, Bálint B, Kiss B, Sipos G, Owens R, Nagy LG (2020) Hallmarks of basidiomycete soft- and white-rot in wood-decay-omics data of Armillaria. bioRxiv 2020.05.04.075879. https://doi.org/10.1101/2020.05.04.075879.

  104. Neuwald AF, Aravind L, Altschul SF (2018) Inferring joint sequence-structural determinants of protein functional specificity. eLIFE 7:e29880. https://doi.org/10.7554/eLife.29880.001.

  105. Palma-Guerrero J, Ma X, Torriani SFF, Zala M, Francisco CS, Hartmann FE, Croll D, McDonald BA (2017) Comparative transcriptome analyses in Zymoseptoria tritici reveal significant differences in gene expression among strains during plant infection. Mol Plant Microbe Interact 30:231–244. https://doi.org/10.1094/MPMI-07-16-0146-R

    Article  CAS  PubMed  Google Scholar 

  106. Kimura M, Takai T, Takahashi-Ando N, Ahsato S, Fujimura M (2007) Molecular and genetic studies of Fusarium trichothecene biosynthesis: pathways, genes, and evolution. Biosci Biotechnol Biochem 71:1–19. https://doi.org/10.1271/bbb.70183

    Article  CAS  Google Scholar 

  107. Schmidt R, Etalo DW, de Jager V, Gerards S, Zweers H, de Boer W, Garbeva P (2016) Microbial small talk: volatiles in fungal–bacterial interactions. Front Microbiol 6:1495. https://doi.org/10.3389/fmicb.2015.01495

    Article  PubMed  PubMed Central  Google Scholar 

  108. Deveau A, Bonito G, Uehling J, Paoletti M, Becker M, Bindschedler S, Hacquard S, Hervé V, Labbé J, Lastovetsky OA, Mieszkin S, Millet LJ, Vajna B, Junier P, Bonfante P, Krom BP, Olsson S, Dirk van Elsas J, Wick LY (2018) Bacterial–fungal interactions: ecology, mechanisms and challenges. FEMS Microbiol Rev 42:335–352. https://doi.org/10.1093/femsre/fuy008

    Article  CAS  PubMed  Google Scholar 

  109. Huang AC, Osbourn A (2019) Plant terpenes that mediate below-ground interactions: prospects for bioengineering terpenoids for plant protection. Pest Manag Sci 75:2368–2377. https://doi.org/10.1002/ps.5410

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  110. Farh ME, Jeon J (2020) Roles of fungal volatiles from perspective of distinct lifestyles in filamentous fungi. Plant Pathol J 36:193–203. https://doi.org/10.5423/PPJ.RW.02.2020.0025

    Article  PubMed  PubMed Central  Google Scholar 

  111. Proctor RH, McCormick SP, Kim H, Cardoza RE, Stanley AM, Lindo L, Kelly A, Brown DW, Lee T, Vaughan MM, Alexander NJ, Busman M, Gutiérrez S (2018) Evolution of structural diversity of trichothecenes, a family of toxins produced by plant pathogenic and entomopathogenic fungi. PLoS Pathog 14(4):e1006946. https://doi.org/10.1371/journal.ppat.1006946

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  112. Holmes AJ, Tujula NA, Holley M, Contos A, James JM, Rogers P, Gillings MR (2001) Phylogenetic structure of unusual aquatic microbial formations in Nullarbor caves, Australia. Environ Microbiol 3:256–264. https://doi.org/10.1046/j.1462-2920.2001.00187.x

    Article  CAS  PubMed  Google Scholar 

  113. Schabereiter-Gurtner C, Saiz-Jimenez C, Piñar G, Lubitz W, Rölleke S (2002) Phylogenetic 16S rRNA analysis reveals the presence of complex and partly unknown bacterial communities in Tito Bustillo cave, Spain, and on its Paleolithic paintings. Environ Microbiol 4:392–400. https://doi.org/10.1046/j.1462-2920.2002.00303.x

    Article  CAS  PubMed  Google Scholar 

  114. Zhu H-Z, Zhang ZF, Zhou N, Jiang CY, Wang BJ, Cai L, Liu S-J (2019) Diversity, distribution and co-occurrence patterns of bacterial communities in a karst cave system. Front Microbiol 10:1726. https://doi.org/10.3389/fmicb.2019.01726

    Article  PubMed  PubMed Central  Google Scholar 

  115. Sjöberg S, Stairs CW, Allard B, Homa F, Martin T, Sjöberg V, Ettema TJG, Dupraz C. (2020) Microbiomes in a manganese oxide producing ecosystem in the Ytterby mine, Sweden: impact on metal mobility. FEMS Microbiology Ecology. 96. https://doi.org/10.1093/femsec/fiaa169

  116. Barriuso J, Márin S, Mellado RP (2010) Effects of the herbicide glyphosate-tolerant maize rhizobacteria communities: a comparison with pre-emergency applied herbicide consisting of a combination of acetochlor and terbuthylazine. Environ Microbiol 12:1021–1030. https://doi.org/10.1111/j.1462-2920.2009.02146.x

    Article  CAS  PubMed  Google Scholar 

  117. Bian X, **ao S, Zhao Y, Xu Y, Yang H, Zhang L (2020) Comparative analysis of rhizosphere soil physiochemical characteristics and microbial communities between rusty and healthy ginseng root. Sci Rep 10:15756. https://doi.org/10.1038/s41598-020-71024-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  118. Nusslein K, Tiedje JM (1999) Soil bacterial community shift correlated with change from forest to pasture vegetation in a tropical soil. Appl Environ Microbiol 65:3622–3626. https://doi.org/10.1128/AEM.65.8.3622-3626.1999

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  119. Köberl M, Dita M, Martinuz A, Staver C, Berg G (2017) Member of Gammaproteobacteria as indicator species of healthy banana plants on Fusarium wilt-infested fields in Central America. Sci Rep 7:45318. https://doi.org/10.1038/srep45318

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  120. Byers A-K, Condron L, O’Callaghan M, Waipara N, Black A (2020) Soil microbial community restructuring and functional changes in ancient kauri (Agathis australis) forest impacted by the invasive pathogen Phytophthora agathidicida. Soil Biol Biochem 150:108016. https://doi.org/10.1016/j.soilbio.2020.108016

    Article  CAS  Google Scholar 

  121. Przemieniecki SW, Damszel M, Ciesielski S, Kubiak K, Mastalerz J, Sierota Z, Gorczyca A (2021) Bacterial microbiome in Armillaria ostoyae rhizomorphs inhabiting the root zone during progressively dying Scots pine. Appl Soil Ecol 164:103929. https://doi.org/10.1016/j.apsoil.2021.103929

    Article  Google Scholar 

  122. Saccá ML, Manici LM, Caputo F, Frisullo S (2019) Changes in rhizosphere bacterial communities associated with tree decline: grapevine esca syndrome case study. Can J Microbiol 65:930–943. https://doi.org/10.1139/cjm-2019-0384

    Article  CAS  PubMed  Google Scholar 

  123. Liu J, He X, Sun J, Ma Y (2021) A degeneration gradient of poplar trees contributes to the taxonomic, functional, and resistome diversity of bacterial communities in rhizosphere soils. Int J Mol Sci 22:3438. https://doi.org/10.3390/ijms22073438

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  124. Tong A-Z, Liu W, Liu Q, **a G-Q, Zhu J-Y (2021) Diversity and composition of the Panax ginseng rhizosphere microbiome in various cultivation modes and ages. BMC Microbiol 21:18. https://doi.org/10.1186/s12866-020-02081-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  125. Balestrini R, Lumini E, Borriello R, Biancotto V (2014) Plant-soil biota interactions. In: E.A. Paul (4th ed.), Soil microbiology, ecology, and biochemistry. Cambridge, MA: Academic Press. p. 311–338. eBook ISBN: 9780123914118. https://doi.org/10.1016/C2011-0-05497-2.

  126. Horton BW, Glen M, Davidson NJ, Ratkowsky D, Close DC, Wardlaw TJ, Mohammed C (2013) Temperate eucalypt forest decline is linked to altered mycorrhizal communities mediated by soil chemistry. For Ecol Manage 302:329–337. https://doi.org/10.1016/j.foreco.2013.04.006

    Article  Google Scholar 

  127. Kipfer T, Egli S, Ghazoul J, Moser B, Wohlgemuth T (2010) Susceptibility of ectomycorrhizal fungi to soil heating. Fungal Biol 114:467–472. https://doi.org/10.1016/j.funbio.2010.03.008

    Article  PubMed  Google Scholar 

  128. Rudawska M, Leski T, Stasinska M (2011) Species and functional diversity of ectomycorrhizal fungal communities on Scots pine (Pinus sylvestris L.) trees on three different sites. Annual of Forest Science 68:5–15. https://doi.org/10.1007/s13595-101-0002-x

    Article  Google Scholar 

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Funding

This study was funded in part by the USDA Forest Service, State & Private forestry, Forest Health Protection, Special Technology Development Program and Joint Venture Agreements (19-JV-11221633–093 and 20-JV-11221633–141) to Colorado State University (JES).

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Author notes

  1. Jorge R. Ibarra Caballero and Bradley M. Lalande contributed equally to this work.

Authors and Affiliations

  1. Department of Agricultural Biology, Colorado State University, Fort Collins, CO, 80523, USA

    Jorge R. Ibarra Caballero, Bradley M. Lalande & Jane E. Stewart

  2. Forest Health Protection, USDA Forest Service, Gunnison, CO, 81230, USA

    Bradley M. Lalande

  3. Rocky Mountain Research Station, USDA Forest Service, Moscow, ID, 83843, USA

    John W. Hanna & Ned B. Klopfenstein

  4. Pacific Northwest Research Station, USDA Forest Service, Corvallis, OR, 97331, USA

    Mee-Sook Kim

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  1. Jorge R. Ibarra Caballero
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  4. Ned B. Klopfenstein
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  5. Mee-Sook Kim
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Contributions

All authors contributed to the study conception and design. Material preparation and data collection were performed by Bradley Lalande, John Hanna, Mee-Sook Kim, Ned Klopfenstein, and Jane Stewart. Analyses were performed by Jorge Ibarra Caballero, Bradley Lalande, and Jane Stewart. The first draft of the manuscript was written by Jorge Ibarra Caballero, Bradley Lalande, and Jane Stewart, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

Corresponding authors

Correspondence to Ned B. Klopfenstein, Mee-Sook Kim or Jane E. Stewart.

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The authors declare no competing interests.

Supplementary Information

Below is the link to the electronic supplementary material.

Supplementary file1 (GFF 410228 KB)

Supplementary file 2 (GFF 353622 KB)

248_2022_1989_MOESM3_ESM.pdf

Supplementary Fig. S1 Comparison of numbers of putativepathogenicity-related secreted proteins in the Armillaria altimontana and A.solidipes (PDF 41 KB)

Supplementary Fig. S2 Distribution of non-secreted CAZymes in Armillaria altimontana and A. solidipes (PDF 42 KB)

248_2022_1989_MOESM5_ESM.pdf

Supplementary Fig. S3 Rarefaction curves to assess species richnessand sequencing depth for individual samples meta-barcoded at the 16S (A) andITS (B) for bacterial and fungal communities, respectively (PDF 4925 KB)

248_2022_1989_MOESM6_ESM.pdf

Supplementary Fig. S4 Principal component analyses of themeta-barcode 16S (A) and ITS (B) data for bacterial and fungal communitiesassociated with A. solidipes (red) and A. altimontana (black),respectively (PDF 168 KB)

Supplementary file 3 (CSV 3239 KB)

Supplementary file 4 (CSV 2821 KB)

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Caballero, J.R.I., Lalande, B.M., Hanna, J.W. et al. Genomic Comparisons of Two Armillaria Species with Different Ecological Behaviors and Their Associated Soil Microbial Communities. Microb Ecol 85, 708–729 (2023). https://doi.org/10.1007/s00248-022-01989-8

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