Microbial Ecology

, Volume 67, Issue 1, pp 13–23 | Cite as

Winter–Summer Succession of Unicellular Eukaryotes in a Meso-eutrophic Coastal System

  • Urania Christaki
  • Konstantinos A. Kormas
  • Savvas Genitsaris
  • Clément Georges
  • Télesphore Sime-Ngando
  • Eric Viscogliosi
  • Sébastien Monchy
Microbiology of Aquatic Systems
First Online:
Received:
Accepted:

Abstract

The objective of this study was to explore the succession of planktonic unicellular eukaryotes by means of 18S rRNA gene tag pyrosequencing in the eastern English Channel (EEC) during the winter to summer transition. The 59 most representative (>0.1 %, representing altogether 95 % of total reads), unique operational taxonomic units (OTUs) from all samples belonged to 18 known high-level taxonomic groups and 1 unaffiliated clade. The five most abundant OTUs (69.2 % of total reads) belonged to Dinophyceae, Cercozoa, Haptophyceae, marine alveolate group I, and Fungi. Cluster and network analysis between samples distinguished the winter, the pre-bloom, the Phaeocystis globosa bloom and the post-bloom early summer conditions. The OTUs-based network revealed that P. globosa showed a relatively low number of connections—most of them negative—with all other OTUs. Fungi were linked to all major taxonomic groups, except Dinophyceae. Cercozoa mostly co-occurred with the Fungi, the Bacillariophyceae and several of the miscellaneous OTUs. This study provided a more detailed exploration into the planktonic succession pattern of the EEC due to its increased depth of taxonomic sampling over previous efforts based on classical monitoring observations. Data analysis implied that the food web concept in a coastal system based on predator–prey (e.g. grazer–phytoplankton) relationships is just a part of the ecological picture; and those organisms exploiting a variety of strategies, such as saprotrophy and parasitism, are persistent and abundant members of the community.

Keywords

Dinoflagellate Unicellular Eukaryote Abundant OTUs Unique OTUs June Sample 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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Notes

Acknowledgements

This study was supported by the INSU/CNRS/EC2CO-IMMERSE (EC2CO_2011), the ‘Nord-Pas de Calais’ Region and FRB-DEMO (FRB_2013), the ANR-ROME (ANR 12 BSV7 0019 02), the BQR-ULCO 2012 projects and the SOMLIT network. We are grateful to Eric Lecuyer and JD Grattepanche for the sampling assistance. www.englisheditor.webs.com is acknowledged for the paper’s English proofing. Finally, we are grateful to four anonymous reviewers for their constructive comments, which improved our work.

Supplementary material

248_2013_290_MOESM1_ESM.doc (140 kb)
ESM 1 (DOC 139 kb)

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Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Urania Christaki
    • 1
  • Konstantinos A. Kormas
    • 2
  • Savvas Genitsaris
    • 1
  • Clément Georges
    • 1
  • Télesphore Sime-Ngando
    • 3
  • Eric Viscogliosi
    • 4
  • Sébastien Monchy
    • 1
  1. 1.Laboratoire d’Océanologie et Géosciences (LOG), UMR CNRS 8187Université du Littoral Côte d’Opale (ULCO)WimereuxFrance
  2. 2.Department of Ichthyology and Aquatic EnvironmentUniversity of ThessalyNea IoniaGreece
  3. 3.Laboratoire Microorganismes: Génome et Environnement (LMGE), UMR CNRS 6023Clermont Université Blaise PascalAubière CedexFrance
  4. 4.Center for Infection and Immunity of Lille (CIIL), Institut Pasteur of Lille, Inserm U1019, CNRS UMR 8204, Biology and Diversity of Emerging Eukaryotic Pathogens, EA4547Université Lille Nord de FranceLilleFrance

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