Skip to main content

Metabarcoding Approaches for Soil Eukaryotes, Protists, and Microfauna

  • Protocol
  • First Online:
Microbial Environmental Genomics (MEG)

Part of the book series: Methods in Molecular Biology ((MIMB,volume 2605))

Abstract

There have been major developments in the molecular characterization of soil protist and micrometazoan diversity, leading to a better understanding of these minute soil eukaryotes. Like in all newly developing research fields, several approaches are currently used in parallel to study these organisms. Here, we synthesize these various approaches and propose a best practice manual that should help researchers to efficiently target soil eukaryotic diversity as a whole. We cover the whole working pipeline, ranging from sampling to nucleic acids extraction to bioinformatic processing and sequence identification. Synchronous approaches to molecularly survey microbial-sized eukaryotes and other soil biodiversity groups are needed in order to provide a cumulative knowledge of soil biodiversity, as here shown for the soil eukaryome. This will be crucial in understanding the important ecosystem functions provided by soil biodiversity.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 169.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 249.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. FAO, ITPS, CBD, et al (2020) State of knowledge of soil biodiversity - status, challenges and potentialities: report 2020. FAO, Rome, Italy

    Google Scholar 

  2. Geisen S, Briones MJI, Gan H et al (2019) A methodological framework to embrace soil biodiversity. Soil Biol Biochem 136:107536

    Article  CAS  Google Scholar 

  3. Bahram M, Hildebrand F, Forslund SK et al (2018) Structure and function of the global topsoil microbiome. Nature 560:233

    Article  CAS  Google Scholar 

  4. Delgado-Baquerizo M, Oliverio AM, Brewer TE et al (2018) A global atlas of the dominant bacteria found in soil. Science 359:320–325

    Article  CAS  Google Scholar 

  5. Tedersoo L, Bahram M, Põlme S et al (2014) Global diversity and geography of soil fungi. Science 346:1256688

    Article  Google Scholar 

  6. Thompson LR, Sanders JG, McDonald D et al (2017) A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551:457

    Article  CAS  Google Scholar 

  7. Mahé F, de Vargas C, Bass D et al (2017) Parasites dominate hyperdiverse soil protist communities in Neotropical rainforests. Nat Ecol Evol 1:0091

    Article  Google Scholar 

  8. Oliverio AM, Geisen S, Delgado-Baquerizo M et al (2020) The global-scale distributions of soil protists and their contributions to belowground systems. Sci Adv 6:eaax8787

    Article  CAS  Google Scholar 

  9. Singer D, Seppey CVW, Lentendu G et al (2021) Protist taxonomic and functional diversity in soil, freshwater and marine ecosystems. Environ Int 146:106262

    Article  CAS  Google Scholar 

  10. Xiong W, Jousset A, Li R et al (2021) A global overview of the trophic structure within microbiomes across ecosystems. Environ Int 151:106438

    Article  Google Scholar 

  11. Zhao Z-B, He J-Z, Geisen S et al (2019) Protist communities are more sensitive to nitrogen fertilization than other microorganisms in diverse agricultural soils. Microbiome 7:33

    Article  Google Scholar 

  12. Guo S, Xiong W, Hang X et al (2021) Protists as main indicators and determinants of plant performance. Microbiome 9:64

    Article  CAS  Google Scholar 

  13. Xiong W, Song Y, Yang K et al (2020) Rhizosphere protists are key determinants of plant health. Microbiome 8:27

    Article  Google Scholar 

  14. Adl SM, Bass D, Lane CE et al (2019) Revisions to the classification, nomenclature, and diversity of eukaryotes. J Eukaryot Microbiol 66:4–119

    Article  Google Scholar 

  15. de Groot AG, Laros I, Geisen S (2016) Molecular identification of soil Eukaryotes and focused approaches targeting Protist and Faunal Groups using high-throughput Metabarcoding. In: Martin F, Uroz S (eds) Microbial environmental genomics (MEG). Springer, New York, pp 125–140

    Chapter  Google Scholar 

  16. Geisen S, Vaulot D, Mahé F et al (2019) A user guide to environmental protistology: primers, metabarcoding, sequencing, and analyses. bioRxiv:850610

    Google Scholar 

  17. Vaulot D, Geisen S, Mahé F et al (2022) pr2-primers: an 18S rRNA primer database for protists. Mol Ecol Resour 22:168–179

    Google Scholar 

  18. Luan L, Jiang Y, Cheng M et al (2020) Organism body size structures the soil microbial and nematode community assembly at a continental and global scale. Nat Commun 11:6406

    Article  CAS  Google Scholar 

  19. van den Hoogen J, Geisen S, Routh D et al (2019) Soil nematode abundance and functional group composition at a global scale. Nature 572:194–198

    Article  Google Scholar 

  20. Geisen S, Snoek LB, ten Hooven FC et al (2018) Integrating quantitative morphological and qualitative molecular methods to analyse soil nematode community responses to plant range expansion. Methods Ecol Evol 9:1366–1378

    Article  Google Scholar 

  21. Chen XY, Daniell TJ, Neilson R et al (2010) A comparison of molecular methods for monitoring soil nematodes and their use as biological indicators. Eur J Soil Biol 46:319–324

    Article  Google Scholar 

  22. Porazinska DL, Giblin-Davis RM, Faller L et al (2009) Evaluating high-throughput sequencing as a method for metagenomic analysis of nematode diversity. Mol Ecol Resour 9:1439–1450

    Article  CAS  Google Scholar 

  23. Wilschut RA, Geisen S, Martens H et al (2019) Latitudinal variation in soil nematode communities under climate warming-related range-expanding and native plants. Glob Change Biol 25:2714–2726

    Article  Google Scholar 

  24. Ji Y, Ashton L, Pedley SM et al (2013) Reliable, verifiable and efficient monitoring of biodiversity via metabarcoding. Ecol Lett 16:1245–1257

    Article  Google Scholar 

  25. Yu DW, Ji Y, Emerson BC et al (2012) Biodiversity soup: metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring. Methods Ecol Evol 3:613–623

    Article  Google Scholar 

  26. Oliverio AM, Gan H, Wickings K et al (2018) A DNA metabarcoding approach to characterize soil arthropod communities. Soil Biol Biochem 125:37–43

    Article  CAS  Google Scholar 

  27. George PBL, Lallias D, Creer S et al (2019) Divergent national-scale trends of microbial and animal biodiversity revealed across diverse temperate soil ecosystems. Nat Commun 10:1107

    Article  Google Scholar 

  28. Fontaneto D, Eckert EM, Anicic N et al (2019) We are ready for faunistic surveys of bdelloid rotifers through DNA barcoding: the example of Sphagnum bogs of the Swiss Jura Mountains. Limnetica 38:213–225

    Article  Google Scholar 

  29. Lentendu G, Wubet T, Chatzinotas A et al (2014) Effects of long-term differential fertilization on eukaryotic microbial communities in an arable soil: a multiple barcoding approach. Mol Ecol 23:3341–3355

    Article  CAS  Google Scholar 

  30. Forster D, Lentendu G, Filker S et al (2019) Improving eDNA-based protist diversity assessments using networks of amplicon sequence variants. Environ Microbiol 21:4109–4124

    Article  CAS  Google Scholar 

  31. Geisen S, Tveit AT, Clark IM et al (2015) Metatranscriptomic census of active protists in soils. ISME J 9:2178–2190

    Article  CAS  Google Scholar 

  32. Thompson AR, Geisen S, Adams BJ (2020) Shotgun metagenomics reveal a diverse assemblage of protists in a model Antarctic soil ecosystem. Environ Microbiol 22:4620–4632

    Article  Google Scholar 

  33. Stoeck T, Bass D, Nebel M et al (2010) Multiple marker parallel tag environmental DNA sequencing reveals a highly complex eukaryotic community in marine anoxic water. Mol Ecol 19:21–31

    Article  CAS  Google Scholar 

  34. Hajibabaei M, Spall JL, Shokralla S et al (2012) Assessing biodiversity of a freshwater benthic macroinvertebrate community through non-destructive environmental barcoding of DNA from preservative ethanol. BMC Ecol 12:28

    Article  CAS  Google Scholar 

  35. Gibson J, Shokralla S, Porter TM et al (2014) Simultaneous assessment of the macrobiome and microbiome in a bulk sample of tropical arthropods through DNA metasystematics. Proc Natl Acad Sci 111:8007–8012

    Article  CAS  Google Scholar 

  36. Hajibabaei M, Porter TM, Wright M et al (2019) COI metabarcoding primer choice affects richness and recovery of indicator taxa in freshwater systems. PLoS One 14:e0220953

    Article  CAS  Google Scholar 

  37. Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J 17:10–12

    Article  Google Scholar 

  38. Rognes T, Flouri T, Nichols B et al (2016) VSEARCH: a versatile open source tool for metagenomics. PeerJ 4:e2584

    Article  Google Scholar 

  39. Callahan BJ, McMurdie PJ, Rosen MJ et al (2016) DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods 13:581–583

    Article  CAS  Google Scholar 

  40. Charif D, Lobry JR (2007) SeqinR 1.0-2: a contributed package to the R project for statistical computing devoted to biological sequences retrieval and analysis. In: Bastolla U, Porto M, Roman HE et al (eds) Structural approaches to sequence evolution: molecules, networks, populations. Springer, Berlin, Heidelberg, pp 207–232

    Chapter  Google Scholar 

  41. Eddelbuettel D (2020) digest: Create Compact Hash Digests of R Objects, 0.6.27, digest

    Google Scholar 

  42. Guillou L, Bachar D, Audic S et al (2013) The Protist Ribosomal Reference database (PR2): a catalog of unicellular eukaryote Small Sub-Unit rRNA sequences with curated taxonomy. Nucleic Acids Res 41:D597–D604

    Article  CAS  Google Scholar 

  43. McDonald D, Clemente JC, Kuczynski J et al (2012) The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome. GigaScience 1:7

    Article  Google Scholar 

  44. Quast C, Pruesse E, Yilmaz P et al (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596

    Article  CAS  Google Scholar 

  45. Leray M, Knowlton N, Machida RJ (2022) MIDORI2: A collection of quality controlled preformatted and regularly updated reference databases for taxonomic assignment of eukaryotic mitochondrial sequences. Environmental DNA 4(4):894–907. 10.1002/edn3.303

    Google Scholar 

  46. Cordier T, Esling P, Lejzerowicz F et al (2017) Predicting the ecological quality status of marine environments from eDNA metabarcoding data using supervised machine learning. Environ Sci Technol 51:9118–9126

    Google Scholar 

  47. Caporaso JG, Lauber CL, Walters WA et al (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6:1621–1624

    Article  CAS  Google Scholar 

  48. Amaral-Zettler LA, McCliment EA, Ducklow HW et al (2009) A method for studying protistan diversity using massively parallel sequencing of V9 hypervariable regions of small-subunit ribosomal RNA genes. PLoS One 4:e6372–e6372

    Google Scholar 

  49. Jamy M, Foster R, Barbera P et al (2020) Long-read metabarcoding of the eukaryotic rDNA operon to phylogenetically and taxonomically resolve environmental diversity. Mol Ecol Resour 20:429–443

    Article  CAS  Google Scholar 

  50. Jensen EA, Berryman DE, Murphy ER et al (2019) Heterogeneity spacers in 16S rDNA primers improve analysis of mouse gut microbiomes via greater nucleotide diversity. BioTechniques 67:55–62

    Article  CAS  Google Scholar 

  51. Carøe C, Bohmann K (2020) Tagsteady: a metabarcoding library preparation protocol to avoid false assignment of sequences to samples. Mol Ecol Resour 20:1620–1631

    Article  Google Scholar 

  52. Marquina D, Andersson AF, Ronquist F (2019) New mitochondrial primers for metabarcoding of insects, designed and evaluated using in silico methods. Mol Ecol Resour 19:90–104

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Stefan Geisen .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature

About this protocol

Check for updates. Verify currency and authenticity via CrossMark

Cite this protocol

Lentendu, G., Lara, E., Geisen, S. (2023). Metabarcoding Approaches for Soil Eukaryotes, Protists, and Microfauna. In: Martin, F., Uroz, S. (eds) Microbial Environmental Genomics (MEG). Methods in Molecular Biology, vol 2605. Humana, New York, NY. https://doi.org/10.1007/978-1-0716-2871-3_1

Download citation

  • DOI: https://doi.org/10.1007/978-1-0716-2871-3_1

  • Published:

  • Publisher Name: Humana, New York, NY

  • Print ISBN: 978-1-0716-2870-6

  • Online ISBN: 978-1-0716-2871-3

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics