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Characterization of Bacterial and Fungal Communities Reveals Novel Consortia in Tropical Oligotrophic Peatlands

  • Elise S. MorrisonEmail author
  • P. Thomas
  • A. Ogram
  • T. Kahveci
  • B. L. Turner
  • J. P. Chanton
Soil Microbiology

Abstract

Despite their importance for global biogeochemical cycles and carbon sequestration, the microbiome of tropical peatlands remains under-determined. Microbial interactions within peatlands can regulate greenhouse gas production, organic matter turnover, and nutrient cycling. Here we analyze bacterial and fungal communities along a steep P gradient in a tropical peat dome and investigate community level traits and network analyses to better understand the composition and potential interactions of microorganisms in these understudied systems and their relationship to peatland biogeochemistry. We found that both bacterial and fungal community compositions were significantly different along the P gradient, and that the low-P bog plain was characterized by distinct fungal and bacterial families. At low P, the dominant fungal families were cosmopolitan parasites and endophytes, including Clavicipitaceae (19%) in shallow soils (0–4 cm), Hypocreaceae (50%) in intermediate-depth soils (4–8 cm), and Chaetothyriaceae (45%) in deep soils (24–30 cm). In contrast, high- and intermediate-P sites were dominated by saprotrophic families at all depths. Bacterial communities were consistently dominated by the acidophilic Koribacteraceae family, with the exception of the low-P bog site, which was dominated by Acetobacteraceae (19%) and Syntrophaceae (11%). These two families, as well as Rhodospirillaceae, Syntrophobacteraceae, Syntrophorhabdaceae, Spirochaetaceae, and Methylococcaceae appeared within low-P bacterial networks, suggesting the presence of a syntrophic-methanogenic consortium in these soils. Further investigation into the active microbial communities at these sites, when paired with CH4 and CO2 gas exchange, and the quantification of metabolic intermediates will validate these potential interactions and provide insight into microbially driven biogeochemical cycling within these globally important tropical peatlands.

Keywords

Metabarcoding Microbial networks Bacterial and fungal communities Peat Phosphorus 

Notes

Acknowledgments

We thank Plinio Gondola and Gabriel Jacome for coordinating sampling, and Dr. Joseph Knellmann for guidance on estimation of rrn operon copy numbers.

Funding Information

This research was supported by grants from the National Science Foundation (DEB 0841596), the UF Informatics Institute, the Smithsonian Tropical Research Institute, and the UF Tropical Conservation and Development Program.

Compliance with Ethical Standards

Conflict of Interest

The authors declare that they have no conflicts of interest.

Supplementary material

248_2020_1483_MOESM1_ESM.pdf (1.9 mb)
ESM 1 (PDF 1974 kb).

References

  1. 1.
    Pérez-Valera E, Goberna M, Verdú M (2015) Phylogenetic structure of soil bacterial communities predicts ecosystem functioning. FEMS Microbiol Ecol 91:1–9.  https://doi.org/10.1093/femsec/fiv031 CrossRefGoogle Scholar
  2. 2.
    Espenberg M, Truu M, Mander Ü, Kasak K, Nõlvak H, Ligi T, Oopkaup K, Maddison M, Truu J (2018) Differences in microbial community structure and nitrogen cycling in natural and drained tropical peatland soils. Sci Rep 8:4742.  https://doi.org/10.1038/s41598-018-23032-y CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Sjögersten S, Black CR, Evers S, Hoyos-Santillan J, Wright EL, Turner BL (2014) Tropical wetlands: a missing link in the global carbon cycle? Glob Biogeochem Cycles 28:1371–1386.  https://doi.org/10.1002/2014GB004844 CrossRefGoogle Scholar
  4. 4.
    Page SE, Rieley JO, Banks CJ (2011) Global and regional importance of the tropical peatland carbon pool. Glob Chang Biol 17:798–818.  https://doi.org/10.1111/j.1365-2486.2010.02279.x CrossRefGoogle Scholar
  5. 5.
    Troxler TG, Ikenaga M, Scinto L, Boyer JN, Condit R, Perez R, Gann GD, Childers DL (2012) Patterns of soil bacteria and canopy community structure related to tropical peatland development. Wetlands 32:769–782.  https://doi.org/10.1007/s13157-012-0310-z CrossRefGoogle Scholar
  6. 6.
    Sjögersten S, Cheesman AW, Lopez O, Turner BL (2011) Biogeochemical processes along a nutrient gradient in a tropical ombrotrophic peatland. Biogeochemistry 104:147–163.  https://doi.org/10.1007/s10533-010-9493-7 CrossRefGoogle Scholar
  7. 7.
    Holmes ME, Chanton JP, Tfaily MM, Ogram A (2015) CO2 and CH4 isotope compositions and production pathways in a tropical peatland. Glob Biogeochem Cycles 29:1–18.  https://doi.org/10.1002/2014GB004951 CrossRefGoogle Scholar
  8. 8.
    Wright EL, Black CR, Cheesman AW et al (2011) Contribution of subsurface peat to CO2 and CH4 fluxes in a neotropical peatland. Glob Chang Biol 17:2867–2881.  https://doi.org/10.1111/j.1365-2486.2011.02448.x CrossRefGoogle Scholar
  9. 9.
    Yao Q, Li Z, Song Y, Wright SJ, Guo X, Tringe SG, Tfaily MM, Paša-Tolić L, Hazen TC, Turner BL, Mayes MA, Pan C (2018) Community proteogenomics reveals the systemic impact of phosphorus availability on microbial functions in tropical soil. Nat Ecol Evol 2:499–509.  https://doi.org/10.1038/s41559-017-0463-5 CrossRefPubMedGoogle Scholar
  10. 10.
    Hoyos-Santillan J, Lomax BH, Large D, Turner BL, Boom A, Lopez OR, Sjögersten S (2015) Getting to the root of the problem: litter decomposition and peat formation in lowland Neotropical peatlands. Biogeochemistry 126:115–129.  https://doi.org/10.1007/s10533-015-0147-7 CrossRefGoogle Scholar
  11. 11.
    Briones MJI, Öpik M (2020) Fungal diversity in peatlands and its contribution to carbon cycling. Appl Soil Ecol 146:103393.  https://doi.org/10.1016/j.apsoil.2019.103393 CrossRefGoogle Scholar
  12. 12.
    You YH, Park JM, Park JH, Kim JG (2016) Endophyte distribution and comparative analysis of diversity in wetlands showing contrasting geomorphic conditions. Symbiosis 69:21–36.  https://doi.org/10.1007/s13199-015-0363-x CrossRefGoogle Scholar
  13. 13.
    Klappenbach JA, Dunbar JM, Schmidt TM (2000) rRNA operon copy number reflects ecological strategies of bacteria. Appl Environ Microbiol 66:1328–1333.  https://doi.org/10.1128/AEM.66.4.1328-1333.2000 CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Nemergut DR, Knelman JE, Ferrenberg S, Bilinski T, Melbourne B, Jiang L, Violle C, Darcy JL, Prest T, Schmidt SK, Townsend AR (2016) Decreases in average bacterial community rRNA operon copy number during succession. ISME J 10:1147–1156.  https://doi.org/10.1038/ismej.2015.191 CrossRefPubMedGoogle Scholar
  15. 15.
    Kurtz ZD, Müller CL, Miraldi ER, Littman DR, Blaser MJ, Bonneau RA (2015) Sparse and compositionally robust inference of microbial ecological networks. PLoS Comput Biol 11:e1004226.  https://doi.org/10.1371/journal.pcbi.1004226 CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Drake HL, Horn MA, Wüst PK (2009) Intermediary ecosystem metabolism as a main driver of methanogenesis in acidic wetland soil. Environ Microbiol Rep 1:307–318.  https://doi.org/10.1111/j.1758-2229.2009.00050.x CrossRefPubMedGoogle Scholar
  17. 17.
    Ihrmark K, Bödeker ITM, Cruz-Martinez K, Friberg H, Kubartova A, Schenck J, Strid Y, Stenlid J, Brandström-Durling M, Clemmensen KE, Lindahl BD (2012) New primers to amplify the fungal ITS2 region - evaluation by 454-sequencing of artificial and natural communities. FEMS Microbiol Ecol 82:666–677.  https://doi.org/10.1111/j.1574-6941.2012.01437.x CrossRefPubMedGoogle Scholar
  18. 18.
    Wright EL, Black CR, Turner BL, Sjögersten S (2013) Environmental controls of temporal and spatial variability in CO2 and CH4 fluxes in a neotropical peatland. Glob Chang Biol 19:3775–3789.  https://doi.org/10.1111/gcb.12330 CrossRefPubMedGoogle Scholar
  19. 19.
    Gardner RC, Davidson NC (2011) LePage BA (ed) Wetlands: Integrating Multidisciplinary Concepts. Springer Netherlands.  https://doi.org/10.1007/978-94-007-0551-7 Google Scholar
  20. 20.
    Hoyos-santillan J, Lomax BH, Large D, Turner BL (2016) Quality not quantity : Organic matter composition controls of CO2 and CH4 fluxes in neotropical peat profiles. Soil Biol Biochem 103:86–96CrossRefGoogle Scholar
  21. 21.
    Cheesman AW, Turner BL, Ramesh Reddy K (2012) Soil phosphorus forms along a strong nutrient gradient in a tropical ombrotrophic wetland. Soil Sci Soc Am J 76:1496–1506.  https://doi.org/10.2136/sssaj2011.0365 CrossRefGoogle Scholar
  22. 22.
    Phillips S, Bustin RM (1996) Sedimentology of the Changuinola peat deposit: organic and clastic sedimentary response to punctuated coastal subsidence. Bull Geol Soc Am 108:794–814.  https://doi.org/10.1130/0016-7606(1996)108<0794:SOTCPD>2.3.CO;2 CrossRefGoogle Scholar
  23. 23.
    Cohen AD, Raymond Jr R, Thayer G, Ramirez A (1987) Physical and chemical characteristics and development of the Changuinola peat deposit of northwestern Panama. Los Alamos National Lab., NM (USA), Panama CityGoogle Scholar
  24. 24.
    Phillips S, Rouse GE, Bustin RM (1997) Vegetation zones and diagnostic pollen profiles of a coastal peat swamp, Bocas del Toro, Panama. Palaeogeogr Palaeoclimatol Palaeoecol 128:301–338.  https://doi.org/10.1016/S0031-0182(97)81129-7 CrossRefGoogle Scholar
  25. 25.
    Gweon HS, Oliver A, Taylor J, Booth T, Gibbs M, Read DS, Griffiths RI, Schonrogge K (2015) PIPITS: an automated pipeline for analyses of fungal internal transcribed spacer sequences from the Illumina sequencing platform. Methods Ecol Evol 6:973–980.  https://doi.org/10.1111/2041-210X.12399 CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Herlemann DPR, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF (2011) Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J 5:1571–1579.  https://doi.org/10.1038/ismej.2011.41 CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Bengtsson-Palme J, Ryberg M, Hartmann M et al (2013) Improved software detection and extraction of ITS1 and ITS 2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods Ecol Evol 4:914–919Google Scholar
  28. 28.
    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 CrossRefPubMedPubMedCentralGoogle Scholar
  29. 29.
    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336CrossRefGoogle Scholar
  30. 30.
    McMurdie PJ, Holmes S (2013) Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8:e61217.  https://doi.org/10.1371/journal.pone.0061217 CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Wickham H, Francois R (2015) dplyr: a grammar of data manipulation. R Package version 042 3Google Scholar
  32. 32.
    Dixon P (2003) VEGAN, a package of R functions for community ecology. J Veg Sci 14:927–930CrossRefGoogle Scholar
  33. 33.
    R Development Core Team R (2011) R: a language and environment for statistical computingGoogle Scholar
  34. 34.
    Wickham H (2016) ggplot2: elegant graphics for data analysis. Springer-Verlag, New YorkGoogle Scholar
  35. 35.
    Harrell FE (2017) CRAN - Package Hmisc. Hmisc Harrell MiscGoogle Scholar
  36. 36.
    Csardi G, Nepusz T (2006) The igraph software package for complex network research. InterJ Complex Syst 1695:1–9.  https://doi.org/10.3724/SP.J.1087.2009.02191 CrossRefGoogle Scholar
  37. 37.
    Langille MGI, Zaneveld J, Caporaso JG, McDonald D, Knights D, Reyes JA, Clemente JC, Burkepile DE, Vega Thurber RL, Knight R, Beiko RG, Huttenhower C (2013) Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nat Biotechnol 31:814–821.  https://doi.org/10.1038/nbt.2676 CrossRefPubMedPubMedCentralGoogle Scholar
  38. 38.
    Knight R, Navas J, Quinn RA et al (2018) Best practices for analysing microbiomes. Nat Rev Microbiol 16:410–422.  https://doi.org/10.1038/s41579-018-0029-9 CrossRefPubMedGoogle Scholar
  39. 39.
    Cannon PF, Kirk PM (2007) Fungal families of the world. Cabi, CambridgeCrossRefGoogle Scholar
  40. 40.
    Thormann AMN, Currah RS, Bayley E et al (2001) Microfungi isolated from Sphagnum fuscum from a Southern Boreal Bog in Alberta, Canada. Bryologist 104:548–559CrossRefGoogle Scholar
  41. 41.
    Laiho R, Moilanen M, Fritze H (2016) Microbial communities after wood ash fertilization in a boreal drained peatland forest. Eur J Soil Biol 76:95–102.  https://doi.org/10.1016/j.ejsobi.2016.08.004 CrossRefGoogle Scholar
  42. 42.
    Uehling J, Gryganskyi A, Hameed K, Goldstein AH, Labb J (2017) Comparative genomics of Mortierella elongata and its bacterial endosymbiont Mycoavidus cysteinexigens. Environ Microbiol 19:2964–2983CrossRefGoogle Scholar
  43. 43.
    Usuki F, Narisawa K (2007) A mutualistic symbiosis between a dark septate endophytic fungus, Heteroconium chaetospira, and a nonmycorrhizal plant, Chinese cabbage. Mycologia 99:175–184.  https://doi.org/10.3852/mycologia.99.2.175 CrossRefPubMedGoogle Scholar
  44. 44.
    Narisawa K, Hambleton S, Currah RS (2007) Heteroconium chaetospira, a dark septate root endophyte allied to the Herpotrichiellaceae (Chaetothyriales) obtained from some forest soil samples in Canada using bait plants. Mycoscience 48:274–281.  https://doi.org/10.1007/s10267-007-0364-6 CrossRefGoogle Scholar
  45. 45.
    Pinruan U, Rungjindamai N, Sakayaroj J et al (2010) Baipadisphaeria gen. nov., a freshwater ascomycete (Hypocreales, Sordariomycetes) from decaying palm leaves in Thailand. Mycosphere 1:53–63.  https://doi.org/10.1007/s10267-007-0364-6 CrossRefGoogle Scholar
  46. 46.
    Ali SRA, Safari S, Thakib MS et al (2016) Soil fungal community associated with peat in Sarawak identified using 18S rDNA marker. J Oil Palm Res 28:161–171CrossRefGoogle Scholar
  47. 47.
    Kemler M, Garnas J, Wingfield MJ, Gryzenhout M, Pillay KA, Slippers B (2013) Ion Torrent PGM as tool for fungal community analysis : a case study of endophytes in Eucalyptus grandis reveals high taxonomic diversity. PLoS One 8, e81718.  https://doi.org/10.1371/journal.pone.0081718 CrossRefGoogle Scholar
  48. 48.
    Hujslová M, Kubátová A, Kostov M, Kola M (2013) Acidiella bohemica gen. et sp. nov. and Acidomyces spp.(Teratosphaeriaceae), the indigenous inhabitants of extremely acidic soils in Europe. Fungal Divers 58:33–45.  https://doi.org/10.1007/s13225-012-0176-7 CrossRefGoogle Scholar
  49. 49.
    Zhang Y, Crous PW, Schoch CL (2011) A molecular , morphological and ecological re-appraisal of Venturiales ― a new order of Dothideomycetes. Fungal Divers 51:249–277.  https://doi.org/10.1007/s13225-011-0141-x CrossRefPubMedPubMedCentralGoogle Scholar
  50. 50.
    Clay K (1986) Induced vivipary in the sedge Cyperus virens and the transmission of the fungus Balansia cyperi (Clavicipitaceae). Can J Bot 64:2984–2988CrossRefGoogle Scholar
  51. 51.
    Tsitko I, Lusa M, Lehto J et al (2014) The variation of microbial communities in a depth profile of an acidic, nutrient-poor boreal bog in southwestern Finland. Open J Ecol 4:832–859CrossRefGoogle Scholar
  52. 52.
    Nusantara RW, Aspan A (2017) Differentiation of soil organisms at different types of peatland in West Kalimantan, Indonesia. Bonorowo Wetlands 7:26–30.  https://doi.org/10.13057/bonorowo/w070106
  53. 53.
    Pankratov TA (2012) Acidobacteria in microbial communities of the bog and tundra lichens. Microbiology 81:51–58.  https://doi.org/10.1134/s0026261711060166 CrossRefGoogle Scholar
  54. 54.
    Pankratov TA, Kirsanova LA, Kaparullina EN et al (2012) Telmatobacter bradus gen. nov., sp. nov., a cellulolytic facultative anaerobe from subdivision 1 of the Acidobacteria, and emended description of Acidobacterium capsulatum Kishimoto et al. 1991. Int J Syst Evol Microbiol 62:430–437.  https://doi.org/10.1099/ijs.0.029629-0 CrossRefPubMedGoogle Scholar
  55. 55.
    Eichorst SA, Breznak JA, Schmidt TM (2007) Isolation and characterization of soil bacteria that define Terriglobus gen. nov., in the phylum Acidobacteria. Appl Environ Microbiol 73:2708–2717.  https://doi.org/10.1128/AEM.02140-06 CrossRefPubMedPubMedCentralGoogle Scholar
  56. 56.
    Zhou X, Zhang Z, Tian L, Li X, Tian C (2017) Microbial communities in peatlands along a chronosequence on the Sanjiang Plain, China. Sci Rep 7:1–11.  https://doi.org/10.1038/s41598-017-10436-5 CrossRefGoogle Scholar
  57. 57.
    Mamlouk D, Gullo M (2013) Acetic acid bacteria: physiology and carbon sources oxidation. Indian J Microbiol 53:377–384.  https://doi.org/10.1007/s12088-013-0414-z CrossRefPubMedPubMedCentralGoogle Scholar
  58. 58.
    Pedraza RO (2008) Recent advances in nitrogen-fixing acetic acid bacteria. Int J Food Microbiol 125:25–35.  https://doi.org/10.1016/j.ijfoodmicro.2007.11.079 CrossRefPubMedGoogle Scholar
  59. 59.
    Hunger S, Schmidt O, Hilgarth M, Horn MA, Kolb S, Conrad R, Drake HL (2011) Competing formate- and carbon dioxide-utilizing prokaryotes in an anoxic methane-emitting fen soil. Appl Environ Microbiol 77:3773–3785.  https://doi.org/10.1128/AEM.00282-11 CrossRefPubMedPubMedCentralGoogle Scholar
  60. 60.
    Schmidt O, Hink L, Horn MA, Drake HL (2016) Peat: home to novel syntrophic species that feed acetate- and hydrogen-scavenging methanogens. ISME J 10:1954–1966.  https://doi.org/10.1038/ismej.2015.256 CrossRefPubMedPubMedCentralGoogle Scholar
  61. 61.
    Chauhan A, Reddy KR, Ogram AV (2006) Syntrophic-archaeal associations in a nutrient-impacted freshwater marsh. J Appl Microbiol 100:73–84.  https://doi.org/10.1111/j.1365-2672.2005.02751.x CrossRefPubMedGoogle Scholar
  62. 62.
    Hunger S, Gößner AS, Drake HL (2015) Anaerobic trophic interactions of contrasting methane-emitting mire soils: processes versus taxa. FEMS Microbiol Ecol 91.  https://doi.org/10.1093/femsec/fiv045
  63. 63.
    Lau E, IV E, Dillard Z et al (2015) High throughput sequencing to detect differences in methanotrophic Methylococcaceae and Methylocystaceae in surface peat, forest soil, and sphagnum moss in Cranesville Swamp Preserve, West Virginia, USA. Microorganisms 3:113–136.  https://doi.org/10.3390/microorganisms3020113 CrossRefPubMedPubMedCentralGoogle Scholar
  64. 64.
    Sheng R, Chen A, Zhang M et al (2016) Transcriptional activities of methanogens and methanotrophs vary with methane emission flux in rice soils under chronic nutrient constraints of phosphorus and potassium. Biogeosciences 13:6507–6518.  https://doi.org/10.5194/bg-13-6507-2016 CrossRefGoogle Scholar
  65. 65.
    Chauhan A, Pathak A, Ogram A (2012) Composition of methane-oxidizing bacterial communities as a function of nutrient loading in the Florida Everglades. Microb Ecol 64:750–759.  https://doi.org/10.1007/s00248-012-0058-2 CrossRefPubMedGoogle Scholar
  66. 66.
    Fierer N, Barberán A, Laughlin DC (2014) Seeing the forest for the genes: using metagenomics to infer the aggregated traits of microbial communities. Front Microbiol 5:614.  https://doi.org/10.3389/fmicb.2014.00614 CrossRefPubMedPubMedCentralGoogle Scholar
  67. 67.
    Klappenbach JA, Saxman PR, Cole JR, Schmidt TM (2001) rrndb: the ribosomal RNA operon copy number database. Nucleic Acids Res 29:181–184CrossRefGoogle Scholar
  68. 68.
    Nemergut DR, Schmidt SK, Fukami T et al (2013) Patterns and processes of microbial community assembly. Microbiol Mol Biol Rev 10:1147–1156.  https://doi.org/10.1128/MMBR.00051-12 CrossRefGoogle Scholar
  69. 69.
    Fegatella F, Lim J, Kjelleberg S, Cavicchioli R (1998) Implications of rRNA operon copy number and ribosome content in the marine oligotrophic ultramicrobacterium Sphingomonas sp. strain RB2256. Appl Environ Microbiol 64:4433–4438CrossRefGoogle Scholar

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Authors and Affiliations

  1. 1.Soil and Water Sciences DepartmentUniversity of FloridaGainesvilleUSA
  2. 2.Department of Geological SciencesUniversity of FloridaGainesvilleUSA
  3. 3.Department of Computer and Information Science and EngineeringUniversity of FloridaGainesvilleUSA
  4. 4.Smithsonian Tropical Research InstituteBalboaRepublic of Panama
  5. 5.Earth, Ocean, and Atmospheric ScienceFlorida State UniversityTallahasseeUSA

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