Abstract
The Fiji Islands is an archipelago of more than 330 islands located in the tropics of the South Pacific Ocean. Microbial diversity and biogeography in this region is still not understood. Here, we present the first molecular characterization of fungal, bacterial, and archaeal communities in soils from different habitats within the largest Fijian island, Viti Levu. Soil samples were collected from under native vegetation in maritime-, forest-, stream-, grassland-, and casuarina-dominated habitats, as well as from under the introduced agricultural crops sugarcane, cassava, pine, and mahogany. Soil microbial diversity was analyzed through MiSeq amplicon sequencing of 16S (for prokaryotes), ITS, LSU ribosomal DNA (for fungi). Prokaryotic communities were dominated by Proteobacteria (~ 25%), Acidobacteria (~ 19%), and Actinobacteria (~ 17%), and there were no indicator species associated with particular habitats. ITS and LSU were congruent in β-diversity patterns of fungi, and fungal communities were dominated by Ascomycota (~ 57–64%), followed by Basidiomycota (~ 20–23%) and Mucoromycota (~ 10%) according to ITS, or Chytridiomycota (~ 9%) according to LSU. Indicator species analysis of fungi found statistical associations of Cenococcum, Wilcoxina, and Rhizopogon to Pinus caribaea. We hypothesize these obligate biotrophic fungi were co-introduced with their host plant. Entoloma was statistically associated with grassland soils, and Fusarium and Lecythophora with soils under cassava. Observed richness varied from 65 (casuarina) to 404 OTUs (cassava) for fungi according to ITS region, and from 1268 (pine) to 2931 OTUs (cassava) for bacteria and archaea. A major finding of this research is that nearly 25% of the fungal OTUs are poorly classified, indicative of novel biodiversity in this region. This preliminary survey provides important baseline data on fungal, bacterial, and archaeal diversity and biogeography in the Fiji Islands.
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References
Neall VE, Trewick SA (2008) The age and origin of the Pacific islands: a geological overview. Philos Trans R Soc Lond Ser B Biol Sci 363:3293–3308. https://doi.org/10.1098/rstb.2008.0119
Neall VE, Trewick SA (2008) The age and origin of the Pacific islands: a geological overview. Philos Trans R Soc Lond Ser B Biol Sci 363:3293–3308. https://doi.org/10.1098/rstb.2008.0119
Ash J (1992) Vegetation ecology of Fiji: past, present, and future perspectives. Retrieved from http://scholarspace.manoa.hawaii.edu/bitstream/10125/718/1/v46n2-111-127.pdf
Cown DJ (1981) Wood density of Pinus caribaea var. hondurensis grown in Fiji. N Z J For Sci 11(3):244–253
Keppel G, Rounds IA, Thomas NT (2006) The flora, vegetation, and conservation value of mesic forest at Dogotuki, Vanua Levu, Fiji Islands. N Z J Bot 44:273–292. https://doi.org/10.1080/0028825X.2006.9513024
Dingley JM (1981) Records of fungi, bacteria, algae, and angiosperms pathogenic on plants in Cook Islands, Fiji, Kiribati, Niue, Tonga, Tuvalu, and Western Samoa. Survey of agricultural pests and diseases. Tech Rep NAVTRADEVCEN 2:1–470
Marín DH, Romero RA, Guzmán M, Sutton TB (2003) Black Sigatoka: an increasing threat to banana cultivation. Plant Dis 87:208–222. https://doi.org/10.1094/PDIS.2003.87.3.208
Kohlmeyer J, Volkmann-Kohlmeyer B (1987) Marine fungi from Aldabra, the Galapagos, and other tropical islands. Can J Bot 65:571–582. https://doi.org/10.1139/b87-073
Kohlmeyer J (1984) Tropical marine fungi. Mar Ecol 5:329–378
Hall N (2007) Advanced sequencing technologies and their wider impact in microbiology. J Exp Biol 210:1518–1525. https://doi.org/10.1242/jeb.001370
Tedersoo L, Bahram M, Põlme S et al (2014) Global diversity and geography of soil fungi. Science 346:1256688. https://doi.org/10.1126/science.1256688
Talbot JM, Bruns TD, Taylor JW, Smith DP, Branco S, Glassman SI, Erlandson S, Vilgalys R, Liao HL, Smith ME, Peay KG (2014) Endemism and functional convergence across the North American soil mycobiome. Proc Natl Acad Sci U S A 111:6341–6346. https://doi.org/10.1073/pnas.1402584111
Nemergut DR, Costello EK, Hamady M et al (2011) Global patterns in the biogeography of bacterial taxa. Environ Microbiol 13:135–144. https://doi.org/10.1111/J.1462-2920.2010.02315.X
Fierer N, Jackson RB (2006) The diversity and biogeography of soil bacterial communities. Proc Natl Acad Sci U S A 103:626–631. https://doi.org/10.1073/pnas.0507535103
Hejda M, Pyšek P, Pergl J, Sádlo J, Chytrý M, Jarošík V (2009) Invasion success of alien plants: do habitat affinities in the native distribution range matter? Glob Ecol Biogeogr 18:372–382. https://doi.org/10.1111/j.1466-8238.2009.00445.x
Robertson SJ, Rutherford PM, Massicotte HB (2011) Plant and soil properties determine microbial community structure of shared Pinus-Vaccinium rhizospheres in petroleum hydrocarbon contaminated forest soils. Plant Soil 346:121–132. https://doi.org/10.1007/s11104-011-0802-2
Bonito G, Reynolds H, Robeson 2nd MS et al (2014) Plant host and soil origin influence fungal and bacterial assemblages in the roots of woody plants. Mol Ecol 23:3356–3370. https://doi.org/10.1111/mec.12821
Coats VC, Rumpho ME (2014) The rhizosphere microbiota of plant invaders: an overview of recent advances in the microbiomics of invasive plants. Front Microbiol 5:368. https://doi.org/10.3389/fmicb.2014.00368
Lundberg DS, Yourstone S, Mieczkowski P, Jones CD, Dangl JL (2013) Practical innovations for high-throughput amplicon sequencing. Nat Methods 10:999–1002. https://doi.org/10.1038/nmeth.2634
Zhang J, Kobert K, Flouri T, Stamatakis A (2014) PEAR: a fast and accurate Illumina Paired-End reAd mergeR. Bioinformatics 30:614–620. https://doi.org/10.1093/bioinformatics/btt593
Caporaso JG, Gregory Caporaso J, Kuczynski J et al (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336. https://doi.org/10.1038/nmeth.f.303
Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnetjournal 17:10. https://doi.org/10.14806/ej.17.1.200
Edgar RC, Flyvbjerg H (2015) Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics 31:3476–3482. https://doi.org/10.1093/bioinformatics/btv401
Edgar, R. (2016). UCHIME2: improved chimera prediction for amplicon sequencing. https://doi.org/10.1101/074252
Edgar RC (2013) UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nat Methods 10:996–998. https://doi.org/10.1038/nmeth.2604
Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rDNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267. https://doi.org/10.1128/AEM.00062-07
Kõljalg U, Larsson K-H, Abarenkov K, Nilsson RH, Alexander IJ, Eberhardt U, Erland S, Høiland K, Kjøller R, Larsson E, Pennanen T, Sen R, Taylor AF, Tedersoo L, Vrålstad T, Ursing BM (2005) UNITE: a database providing web-based methods for the molecular identification of ectomycorrhizal fungi. New Phytol 166:1063–1068. https://doi.org/10.1111/j.1469-8137.2005.01376.x
DeSantis TZ, Hugenholtz P, Larsen N et al (2006) Greengenes, a chimera-checked 16S rDNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72:5069–5072. https://doi.org/10.1128/AEM.03006-05
Nguyen NH, Song Z, Bates ST, Branco S, Tedersoo L, Menke J, Schilling JS, Kennedy PG (2016) FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol 20:241–248. https://doi.org/10.1016/j.funeco.2015.06.006
McDonald D, Clemente JC, Kuczynski J, Rideout JR, Stombaugh J, Wendel D, Wilke A, Huse S, Hufnagle J, Meyer F, Knight R, Caporaso JG (2012) The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome. Gigascience 1:7. https://doi.org/10.1186/2047-217X-1-7
R Core Team (2017) R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria Retrieved from https://www.R-project.org/
Oliver AK, Callaham MA, Jumpponen A (2015) Soil fungal communities respond compositionally to recurring frequent prescribed burning in a managed southeastern US forest ecosystem. For Ecol Manag 345:1–9. https://doi.org/10.1016/j.foreco.2015.02.020
Lindahl BD, Henrik Nilsson R, Tedersoo L et al (2013) Fungal community analysis by high-throughput sequencing of amplified markers - a user’s guide. New Phytol 199:288–299. https://doi.org/10.1111/nph.12243
Simpson EH (1949) Measurement of diversity. Nature 163:688–688. https://doi.org/10.1038/163688a0
Hill MO (1973) Diversity and evenness: a unifying notation and its consequences. Ecology 54:427–432. https://doi.org/10.2307/1934352
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
Langfeldt D, Neulinger SC, Heuer W, Staufenbiel I, Künzel S, Baines JF, Eberhard J, Schmitz RA (2014) Composition of microbial oral biofilms during maturation in young healthy adults. PLoS One 9:e87449. https://doi.org/10.1371/journal.pone.0087449
Clarke KR, Ainsworth M (1993) A method of linking multivariate community structure to environmental variables. Mar Ecol Prog Ser 92:205–219. https://doi.org/10.3354/meps092205
Anderson MJ, Willis TJ (2003) Canonical analysis of principal coordinates: a useful method of constrained ordination for ecology. Ecology 84:511–525. https://doi.org/10.1890/0012-9658(2003)084[0511:caopca]2.0.co;2
Peres-Neto PR, Jackson DA (2001) How well do multivariate data sets match? The advantages of a Procrustean superimposition approach over the Mantel test. Oecologia 129:169–178. https://doi.org/10.1007/s004420100720
De Cáceres M, Legendre P, Moretti M (2010) Improving indicator species analysis by combining groups of sites. Oikos 119:1674–1684. https://doi.org/10.1111/j.1600-0706.2010.18334.x
Fierer N (2017) Embracing the unknown: disentangling the complexities of the soil microbiome. Nat Rev Microbiol 15:579–590. https://doi.org/10.1038/nrmicro.2017.87
Deshpande V, Wang Q, Greenfield P, Charleston M, Porras-Alfaro A, Kuske CR, Cole JR, Midgley DJ, Tran-Dinh N (2016) Fungal identification using a Bayesian classifier and the Warcup training set of internal transcribed spacer sequences. Mycologia 108:1–5. https://doi.org/10.3852/14-293
Fernandez CW, Kennedy PG (2016) Revisiting the “Gadgil effect”: do interguild fungal interactions control carbon cycling in forest soils? New Phytol 209:1382–1394. https://doi.org/10.1111/nph.13648
Trocha LK, Kałucka I, Stasińska M, Nowak W, Dabert M, Leski T, Rudawska M, Oleksyn J (2011) Ectomycorrhizal fungal communities of native and non-native Pinus and Quercus species in a common garden of 35-year-old trees. Mycorrhiza 22:121–134. https://doi.org/10.1007/s00572-011-0387-x
Pringle A, Vellinga EC (2006) Last chance to know? Using literature to explore the biogeography and invasion biology of the death cap mushroom Amanita phalloides (Vaill. Ex fr. : Fr.) link. Biol Invasions 8:1131–1144. https://doi.org/10.1007/s10530-005-3804-2
Healy RA, Zurier H, Bonito G, Smith ME, Pfister DH (2016) Mycorrhizal detection of native and non-native truffles in a historic arboretum and the discovery of a new North American species, Tuber arnoldianum sp. nov. Mycorrhiza 26:781–792. https://doi.org/10.1007/s00572-016-0713-4
Tedersoo L, Suvi T, Beaver K, Kõljalg U (2007) Ectomycorrhizal fungi of the Seychelles: diversity patterns and host shifts from the native Vateriopsis seychellarum (Dipterocarpaceae) and Intsia bijuga (Caesalpiniaceae) to the introduced Eucalyptus robusta (Myrtaceae), but not Pinus caribea (Pinaceae). New Phytol 175:321–333. https://doi.org/10.1111/j.1469-8137.2007.02104.x
Bonito G, Trappe JM, Donovan S, Vilgalys R (2011) The Asian black truffle Tuber indicum can form ectomycorrhizas with North American host plants and complete its life cycle in non-native soils. Fungal Ecol 4:83–93. https://doi.org/10.1016/j.funeco.2010.08.003
Nuñez MA, Dickie IA (2014) Invasive belowground mutualists of woody plants. Biol Invasions 16:645–661. https://doi.org/10.1007/s10530-013-0612-y
Nikles DG (2006) The domestication of African mahogany (Khaya senegalensis) in northern Australia. Aust For 69:68–69. https://doi.org/10.1080/00049158.2006.10674989
Norghauer JM, Martin AR, Mycroft EE, James A, Thomas SC (2011) Island invasion by a threatened tree species: evidence for natural enemy release of mahogany (Swietenia macrophylla) on Dominica, Lesser Antilles. PLoS One 6:e18790. https://doi.org/10.1371/journal.pone.0018790
Ibrahim D, Lee CC, Sheh-Hong L (2014) Antimicrobial activity of endophytic fungi isolated from Swietenia macrophylla leaves. Nat Prod Commun 9:247–250
Dewanjee S, Kundu M, Maiti A, Majumdar R, Majumdar A, Mandel SC (2007) In vitro evaluation of antimicrobial activity of crude extract from plants Diospyros peregrina, Coccinia grandis and Swietenia macrophylla. Trop J Pharm Res 6:773–778. https://doi.org/10.4314/tjpr.v6i3.14658
Wang CJK, Wilcox HE (1985) New species of ectendomycorrhizal and pseudomycorrhizal fungi: Phialophora finlandia, Chloridium paucisporum, and Phialocephala fortinii. Mycologia 77:951–958. https://doi.org/10.2307/3793308
Rodríguez-Morelos VH, Soto-Estrada A, Pérez-Moreno J, Franco-Ramírez A, Díaz-Rivera P (2014) Arbuscular mycorrhizal fungi associated with the rhizosphere of seedlings and mature trees of Swietenia macrophylla (Magnoliophyta: Meliaceae) in Los Tuxtlas, Veracruz, Mexico. Rev Chil Hist Nat. 87. https://doi.org/10.1186/s40693-014-0009-z
de Souza RSC, Okura VK, Armanhi JSL et al (2016) Unlocking the bacterial and fungal communities assemblages of sugarcane microbiome. Sci Rep 6:28774. https://doi.org/10.1038/srep28774
Bredeson JV, Lyons JB, Prochnik SE, Wu GA, Ha CM, Edsinger-Gonzales E, Grimwood J, Schmutz J, Rabbi IY, Egesi C, Nauluvula P, Lebot V, Ndunguru J, Mkamilo G, Bart RS, Setter TL, Gleadow RM, Kulakow P, Ferguson ME, Rounsley S, Rokhsar DS (2016) Sequencing wild and cultivated cassava and related species reveals extensive interspecific hybridization and genetic diversity. Nat Biotechnol 34:562–570. https://doi.org/10.1038/nbt.3535
De Boer AJ, Chandra S (1978) A model of crop selection in semi-subsistence agriculture and an application to mixed agriculture in Fiji. Am J Agric Econ 60:436–444. https://doi.org/10.2307/1239940
Straker CJ, Hilditch AJ, Rey MEC (2010) Arbuscular mycorrhizal fungi associated with cassava (Manihot esculenta Crantz) in South Africa. S Afr J Bot 76:102–111. https://doi.org/10.1016/j.sajb.2009.09.005
Acknowledgements
We are grateful to the Fijian land-owning clans of the Vanua Davutukia, Korolevu-i-wai who allowed us access to their land to collect samples. We thank Jon Dahl from the Soil and Plant Nutrient Laboratory at Michigan State University for assistance.
Funding
GMNB and GB acknowledge support from Michigan State University AgBioResearch NIFA project MICL02416 and National Science Foundation (NSF) DEB1737898.
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G. B. and V. B. designed the research, sampled the soils in Fiji, and wrote the manuscript. G. M. N. B. extracted DNA, prepared the Illumina library, analyzed the data, and wrote the manuscript. All authors approved the final version for submission.
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Figure S1
Bar plots of relative abundance, based on ITS, LSU and 16S rDNA genes, at ordinal-level. For 16S only the first 50 taxa are shown. Habitats dominated by introduced plant hosts are denoted in bold. (PDF 68 kb)
Figure S2
Shepard diagrams for ITS, LSU and 16S NMDS graphs reported in Fig. 3. The plot shows of ordination distances against original dissimilarities. Non-metric fit is based on stress value of the NMDS ordination and calculated as R2 = 1-S*S. Linear fit is the squared correlation between fitted values and ordination distances. (PDF 234 kb)
Figure S3
ITS and LSU NMDS ordinations (Bray-Curtis distance) comparison using Procrustes rotation. Superimposition and residual plots are showed. (PDF 9.97 kb)
Figure S4
Boxplot of distance to centroids of every sampling location (i.e., site) for ITS, LSU and 16S rDNA. A p value from ANOVA of the distances to group centroids is also reported (perm. = 9999), to test if one or more sample group at each site is more variable than the others. Sites dominated by introduced plant hosts are denoted in bold. (PDF 29.3 kb)
Table S1
List of the first 10 top abundant fungal OTUs detected in each of the 18 sites sampled. Taxonomy assignment using RDP classifiers against the UNITE database, taxonomy assignment using BLAST against GenBank database (https://www.ncbi.nlm.nih.gov/genbank/), max score, total score, query coverage, % sequence identity, e-value and sequence reference ID of the best match are reported. (XLSX 14.5 kb)
Dataset 1
ITS rDNA otu_table (XLSX 321 kb)
Dataset 2
LSU rDNA otu_table (XLSX 247 kb)
Dataset 3
16S rDNA otu_table (XLSX 1499 kb)
Database 1
Herbarium fungal specimen collections of Fiji. (XLSX 359 kb)
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Benucci, G.M.N., Bonito, V. & Bonito, G. Fungal, Bacterial, and Archaeal Diversity in Soils Beneath Native and Introduced Plants in Fiji, South Pacific. Microb Ecol 78, 136–146 (2019). https://doi.org/10.1007/s00248-018-1266-1
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DOI: https://doi.org/10.1007/s00248-018-1266-1