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Composition and predicted functional ecology of mussel-associated bacteria in Indonesian marine lakes

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Abstract

In the present study, we sampled bacterial communities associated with mussels inhabiting two distinct coastal marine ecosystems in Kalimantan, Indonesia, namely, marine lakes and coastal mangroves. We used 16S rRNA gene pyrosequencing and predicted metagenomic analysis to compare microbial composition and function. Marine lakes are small landlocked bodies of seawater isolated to varying degrees from the open sea environment. They contain numerous endemic taxa and represent natural laboratories of speciation. Our primary goals were to (1) use BLAST search to identify closely related organisms to dominant bacterial OTUs in our mussel dataset and (2) to compare bacterial communities and enrichment in the predicted bacterial metagenome among lakes. Our sequencing effort yielded 3553 OTUs belonging to 44 phyla, 99 classes and 121 orders. Mussels in the largest marine lake (Kakaban) and the coastal mangrove habitat were dominated by bacteria belonging to the phylum Proteobacteria whereas smaller lakes, located on the island of Maratua, were dominated by bacteria belonging to the phyla Firmicutes and Tenericutes. The single most abundant OTU overall was assigned to the genus Mycoplasma. There were several significant differences among locations with respect to metabolic pathways. These included enrichment of xenobiotic biodegradation pathways in the largest marine lake and coastal mangrove. These locations were also the most enriched with respect to nitrogen metabolism. The presence of genes related to isoquinoline alkaloids, polyketides, hydrolases, mono and dioxygenases in the predicted analysis of functional pathways is an indication that the bacterial communities of Brachidontes mussels may be potentially important sources of new marine medicines and enzymes of industrial interest. Future work should focus on measuring how mussel microbial communities influence nutrient dynamics within the marine lake environment and isolating microbes with potential biotechnological applications.

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Acknowledgments

The research was sponsored by the Indonesian Institute of Sciences (LIPI) and funded by the Netherlands Organization for Scientific Research (ALW Grant No. 825.12.007) and the Portuguese Foundation for Science and Technology, FCT, project LESS CORAL, PTDC/AAC-AMB/115304/2009. We are grateful to the Indonesian State Ministry of Research and Technology (RISTEK) for providing research permits. We thank the following people for their help in various ways: N. de Voogd, B. Hoeksema, Suharsono, Y. Tuti, E. Oberhauser, R. Suhr, and the staff of Nabucco Island Dive Resort. We would also like to thank the reviewers for suggestions, which helped to improve the quality of this article.

Conflict of interest

The authors declare that they have no conflict of interest.

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Authors and Affiliations

  1. Department of Biology, CESAM, Universidade de Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal

    Daniel F. R. Cleary, Ana R. M. Polónia, Rossana M. Freitas & Newton C. M. Gomes

  2. Department of Marine Zoology, Naturalis Biodiversity Center, Darwinweg 2, 2333 CR, Leiden, The Netherlands

    Leontine E. Becking

  3. Institute for Marine Resources and Ecosystem Studies (IMARES), Wageningen UR, P.O. Box 57, 1780 AB, Den Helder, The Netherlands

    Leontine E. Becking

  4. Department of Environmental Science, Policy, and Management, University of California Berkeley, 130 Mulford Hall, Berkeley, CA, 94720-3114, USA

    Leontine E. Becking

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  1. Daniel F. R. Cleary
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Correspondence to Daniel F. R. Cleary.

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Supplementary material 1 (PDF 106 kb)

10482_2014_375_MOESM2_ESM.pdf

Cladogram generated using LEfSe showing significant differences in gene counts of the KEGG PATHWAY hierarchy between the bacterial communities of the biotopes. KEGG categories, subcategories and individual pathways coloured indicate significant enrichment

10482_2014_375_MOESM3_ESM.xls

Table of summary statistics from LEfSe analysis. Highest mean: logarithm value of the highest mean among all locations, Location: Sample location (Opn, Kak, Mbu and Mta), LDA: Linear Discriminant Analysis statistic, P: significance based on Kruskall-Wallis test assessing whether values in different categories and pathways are differentially distributed among habitats

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Cleary, D.F.R., Becking, L.E., Polónia, A.R.M. et al. Composition and predicted functional ecology of mussel-associated bacteria in Indonesian marine lakes. Antonie van Leeuwenhoek 107, 821–834 (2015). https://doi.org/10.1007/s10482-014-0375-1

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