Comparing Sanger sequencing and high-throughput metabarcoding for inferring photobiont diversity in lichens
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The implementation of HTS (high-throughput sequencing) approaches is rapidly changing our understanding of the lichen symbiosis, by uncovering high bacterial and fungal diversity, which is often host-specific. Recently, HTS methods revealed the presence of multiple photobionts inside a single thallus in several lichen species. This differs from Sanger technology, which typically yields a single, unambiguous algal sequence per individual. Here we compared HTS and Sanger methods for estimating the diversity of green algal symbionts within lichen thalli using 240 lichen individuals belonging to two species of lichen-forming fungi. According to HTS data, Sanger technology consistently yielded the most abundant photobiont sequence in the sample. However, if the second most abundant photobiont exceeded 30% of the total HTS reads in a sample, Sanger sequencing generally failed. Our results suggest that most lichen individuals in the two analyzed species,
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Aylagas, E., Borja, Á., Irigoien, X. & Rodríguez-Ezpeleta, N. Benchmarking DNA Metabarcoding for Biodiversity-Based Monitoring and Assessment. Front Mar Sci 3 (2016).
Kennedy, P. G., Cline, L. C. & Song, Z. Probing promise versus performance in longer read fungal metabarcoding. New Phytol 217, 973–976 (2018).
Zhou, J. et al. High-throughput metagenomic technologies for complex microbial community analysis: Open and closed formats. MBio 6 (2015).
Bálint, M. et al. Millions of reads, thousands of taxa: Microbial community structure and associations analyzed via marker genesa. FEMS Microbiology Reviews 40, 686–700 (2016).
Dickie, I. A. & John, M. G. In Molecular Mycorrhizal Symbiosis 473–491, https://doi.org/10.1002/9781118951446.ch26 (2016).
Tedersoo, L., Tooming-Klunderud, A. & Anslan, S. PacBio metabarcoding of Fungi and other eukaryotes: Errors, biases and perspectives. New Phytol 217, 1370–1385 (2017).
Ainsworth, T. D. et al. The coral core microbiome identifies rare bacterial taxa as ubiquitous endosymbionts. ISME J 9, 2261–2274 (2015).
Divakar, P. K. et al. Evolution of complex symbiotic relationships in a morphologically derived family of lichen-forming fungi. New Phytol 208, 1217–1226 (2015).
Wedin, M. et al. Microbiome change by symbiotic invasion in lichens. Environ Microbiol 18, 1428–1439 (2016).
Baker, C. C. M., Bittleston, L. S., Sanders, J. G. & Pierce, N. E. Dissecting host-associated communities with DNA barcodes. Philos Trans R Soc B Biol Sci 371, 20150328 (2016).
Martin, F. M., Uroz, S. & Barker, D. G. Ancestral alliances: Plant mutualistic symbioses with fungi and bacteria. Science 356 (2017).
Selosse, M.-A., Schneider-Maunoury, L. & Martos, F. Time to re-think fungal ecology? Fungal ecological niches are often prejudged. New Phytol 217, 968–972 (2018).
Grube, M. et al. In The Ecological Genomics of Fungi 191–212, https://doi.org/10.1002/9781118735893.ch9 (John Wiley & Sons, Inc, 2013).
Greshake, B. et al. Potential and pitfalls of eukaryotic metagenome skimming: A test case for lichens. Mol Ecol Resour 16, 511–523 (2016).
Meiser, A., Otte, J., Schmitt, I. & Grande, F. D. Sequencing genomes from mixed DNA samples - Evaluating the metagenome skimming approach in lichenized fungi. Sci Rep 7 (2017).
Bates, S. T., Cropsey, G. W. G., Caporaso, J. G., Knight, R. & Fierer, N. Bacterial communities associated with the lichen symbiosis. Appl Environ Microbiol 77, 1309–1314 (2011).
Fernández-Mendoza, F., Fleischhacker, A., Kopun, T., Grube, M. & Muggia, L. ITS1 metabarcoding highlights low specificity of lichen mycobiomes at a local scale. Mol Ecol 26, 4811–4830 (2017).
Spribille, T. et al. Basidiomycete yeasts in the cortex of ascomycete macrolichens. Science 353, 488–492 (2016).
Aschenbrenner, I. A., Cernava, T., Berg, G. & Grube, M. Understanding microbial multi-species symbioses. Front Microbiol 7, 1–9 (2016).
Hodkinson, B. P., Gottel, N. R., Schadt, C. W. & Lutzoni, F. Photoautotrophic symbiont and geography are major factors affecting highly structured and diverse bacterial communities in the lichen microbiome. Environ Microbiol 14, 147–161 (2012).
Grube, M. et al. Exploring functional contexts of symbiotic sustain within lichen-associated bacteria by comparative omics. ISME J 9, 412–24 (2015).
Cernava, T. et al. Deciphering functional diversification within the lichen microbiota by meta-omics. Microbiome 5, 82 (2017).
Moya, P., Molins, A., Martinez-Alberola, F., Muggia, L. & Barreno, E. Unexpected associated microalgal diversity in the lichen Ramalina farinacea is uncovered by pyrosequencing analyses. PLoS One 12 (2017).
Dal Grande, F. et al. Environment and host identity structure communities of green algal symbionts in lichens. New Phytol 217, 277–289 (2018).
Molins, A., Moya, P., García-Breijo, F. J., Reig-Armiñana, J. & Barreno, E. A multi-tool approach to assess microalgal diversity in lichens: isolation, Sanger sequencing, HTS and ultrastructural correlations. Lichenol 50, 123–138 (2018).
del Campo, E. M. et al. The genetic structure of the cosmopolitan three-partner lichen Ramalina farinacea evidences the concerted diversification of symbionts. FEMS Microbiol Ecol 83, 310–323 (2013).
Sadowska-Deś, A. D. et al. Integrating coalescent and phylogenetic approaches to delimit species in the lichen photobiont Trebouxia. Mol Phylogenet Evol 76, 202–10 (2014).
Škaloud, P., Friedl, T., Hallmann, C., Beck, A. & Dal Grande, F. Taxonomic revision and species delimitation of coccoid green algae currently assigned to the genus Dictyochloropsis (Trebouxiophyceae, Chlorophyta). J Phycol 52, 599–617 (2016).
Dal Grande, F. et al. Molecular phylogeny and symbiotic selectivity of the green algal genus Dictyochloropsis s.l. (Trebouxiophyceae): A polyphyletic and widespread group forming photobiont-mediated guilds in the lichen family Lobariaceae. New Phytol 202, 455–470 (2014).
Werth, S. & Sork, V. L. Ecological specialization in Trebouxia (Trebouxiophyceae) photobionts of Ramalina menziesii (Ramalinaceae) across six range-covering ecoregions of western North America. Am J Bot 101, 1127–1140 (2014).
Singh, G. et al. Fungal–algal association patterns in lichen symbiosis linked to macroclimate. New Phytol 214, 317–329 (2017).
Fernández-Mendoza, F. et al. Population structure of mycobionts and photobionts of the widespread lichen Cetraria aculeata. Mol Ecol 20, 1208–1232 (2011).
Rolshausen, G., Dal Grande, F., Sadowska-Deś, A. D., Otte, J. & Schmitt, I. Quantifying the climatic niche of symbiont partners in a lichen symbiosis indicates mutualist-mediated niche expansions. Ecography, https://doi.org/10.1111/ecog.03457 (2017).
Casano, L. M. et al. Two Trebouxia algae with different physiological performances are ever-present in lichen thalli of Ramalina farinacea. Coexistence versus Competition? Environ Microbiol 13, 806–818 (2011).
Dal Grande, F. et al. Insights into intrathalline genetic diversity of the cosmopolitan lichen symbiotic green alga Trebouxia decolorans Ahmadjian using microsatellite markers. Mol Phylogenet Evol 72, 54–60 (2014).
Catalá, S. et al. Coordinated ultrastructural and phylogenomic analyses shed light on the hidden phycobiont diversity of Trebouxia microalgae in Ramalina fraxinea. Mol Phylogenet Evol 94, 765–777 (2016).
Piercey-Normore, M. Vegetatively reproducing fungi in three genera of the Parmeliaceae share divergent algal partners. Bryologist 112, 773–785 (2009).
Nyati, S., Werth, S. & Honegger, R. Genetic diversity of sterile cultured Trebouxia photobionts associated with the lichen-forming fungus Xanthoria parietina visualized with RAPD-PCR fingerprinting techniques. Lichenol 45, 825–840 (2013).
Leavitt, S. D. et al. Fungal specificity and selectivity for algae play a major role in determining lichen partnerships across diverse ecogeographic regions in the lichen-forming family Parmeliaceae (Ascomycota). Mol Ecol 24, 3779–3797 (2015).
Grime, J. P. Benefits of plant diversity to ecosystems: Immediate, filter and founder effects. J Ecol 86, 902–910 (1998).
Connolly, S. R. et al. Commonness and rarity in the marine biosphere. Proc Natl Acad Sci 111, 8524–8529 (2014).
Houadria, M. & Menzel, F. What determines the importance of a species for ecosystem processes? Insights from tropical ant assemblages. Oecologia 184, 885–899 (2017).
Jiguet, F. et al. Population trends of European common birds are predicted by characteristics of their climatic niche. Glob Chang Biol 16, 497–505 (2010).
Marcelino, V. R. & Verbruggen, H. Multi-marker metabarcoding of coral skeletons reveals a rich microbiome and diverse evolutionary origins of endolithic algae. Sci Rep 6 (2016).
Jousset, A. et al. Where less may be more: How the rare biosphere pulls ecosystems strings. ISME Journal 11, 853–862 (2017).
Yachi, S. & Loreau, M. Biodiversity and ecosystem productivity in a fluctuating environment: The insurance hypothesis. Proc Natl Acad Sci 96, 1463–1468 (1999).
Dal Grande, F. et al. Adaptive differentiation coincides with local bioclimatic conditions along an elevational cline in populations of a lichen-forming fungus. BMC Evol Biol 17, 93 (2017).
Cubero, O. F. & Crespo, A. In Protocols in Lichenology SE – 23 (eds Kranner, I., Beckett, R. & Varma, A.) 381–391, https://doi.org/10.1007/978-3-642-56359-1_23 (Springer Berlin Heidelberg, 2002).
Mahé, F., Rognes, T., Quince, C., De Vargas, C. & Dunthorn, M. Swarmv2: highly-scalable and high-resolution amplicon clustering. PeerJ 3, e1420 (2015).
Bokulich, N. A. et al. Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat Methods 10, 57–9 (2013).
Callahan, B. J. et al. DADA2: High resolution sample inference from amplicon data. Nat Methods 13, 581–583 (2016).
Krohn, A. et al. Optimization of 16S amplicon analysis using mock communities: implications for estimating community diversity. PeerJ 219 (2016).
Kroken, S. & Taylor, J. W. Phylogenetic species, reproductive mode, and specificity of the green alga Trebouxia forming lichens with the fungal genus Letharia. Bryologist 103, 645–660 (2000).
Katoh, K. & Standley, D. M. MAFFT multiple sequence alignment software version 7: Improvements in performance and usability. Mol Biol Evol 30, 772–780 (2013).
Bengtsson-Palme, J. et al. Improved software detection and extraction of ITS1 and ITS2 from ribosomal ITS sequences of fungi and other eukaryotes for analysis of environmental sequencing data. Methods Ecol Evol 4, 914–919 (2013).
Altschul, S. F. et al. Blast and Psi-Blast: Protein Database Search Programs. Nucleid Acid Res 25, 2289–4402 (1997).
R Core Team. R Core Team (2017). R: A language and environment for statistical computing. R Found Stat Comput Vienna, Austria URL http//wwwR-projectorg/R Foundation for Statistical Computing (2017).