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Microbial Ecology

, Volume 62, Issue 3, pp 655–668 | Cite as

Diversity and Spatial Distribution of Prokaryotic Communities Along A Sediment Vertical Profile of A Deep-Sea Mud Volcano

  • Maria G. Pachiadaki
  • Argyri Kallionaki
  • Anke Dählmann
  • Gert J. De Lange
  • Konstantinos Ar. KormasEmail author
Microbiology of Aquatic Systems

Abstract

We investigated the top 30-cm sediment prokaryotic community structure in 5-cm spatial resolution, at an active site of the Amsterdam mud volcano, East Mediterranean Sea, based on the 16S rRNA gene diversity. A total of 339 and 526 sequences were retrieved, corresponding to 25 and 213 unique (≥98% similarity) phylotypes of Archaea and Bacteria, respectively, in all depths. The Shannon–Wiener diversity index H was higher for Bacteria (1.92–4.03) than for Archaea (0.99–1.91) and varied differently between the two groups. Archaea were dominated by anaerobic methanotrophs ANME-1, -2 and -3 groups and were related to phylotypes involved in anaerobic oxidation of methane from similar habitats. The much more complex Bacteria community consisted of 20 phylogenetic groups at the phylum/candidate division level. Proteobacteria, in particular δ-Proteobacteria, was the dominant group. In most sediment layers, the dominant phylotypes of both the Archaea and Bacteria communities were found in neighbouring layers, suggesting some overlap in species richness. The similarity of certain prokaryotic communities was also depicted by using four different similarity indices. The direct comparison of the retrieved phylotypes with those from the Kazan mud volcano of the same field revealed that 40.0% of the Archaea and 16.9% of the Bacteria phylotypes are common between the two systems. The majority of these phylotypes are closely related to phylotypes originating from other mud volcanoes, implying a degree of endemicity in these systems.

Keywords

Archaea Clone Library Chloroflexi Prokaryotic Community Common Phylotypes 
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.

Notes

Acknowledgements

This research project is co-financed by EU-European Social Fund (75%) and the Greek Ministry of Development-GSRT (25%). This work was partly supported by the European Commission projects ANAXIMANDER (contract no. EVK3-CT-2002-00068) and HERMIONE (contract no 226354). Captain, crew and participants of the R/V AEGAEO are gratefully acknowledged for their contribution to the field work, sampling and analyses. The authors thank the three anonymous reviewers for their valuable comments.

Supplementary material

248_2011_9855_MOESM1_ESM.doc (6.9 mb)
ESM 1 (DOC 6.88 mb)

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Copyright information

© Springer Science+Business Media, LLC 2011

Authors and Affiliations

  • Maria G. Pachiadaki
    • 1
  • Argyri Kallionaki
    • 2
  • Anke Dählmann
    • 3
  • Gert J. De Lange
    • 3
  • Konstantinos Ar. Kormas
    • 1
    Email author
  1. 1.Department of Ichthyology and Aquatic Environment, School of Agricultural SciencesUniversity of ThessalyVolosGreece
  2. 2.Environmental Engineering DepartmentTechnical University of CreteChaniaGreece
  3. 3.Department of Earth SciencesUtrecht UniversityUtrechtThe Netherlands

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