LAUSR

Analysis of data, curated over 3 years of sediment sampling, improves our understanding of microbiota assembly in marine sediment. Furthermore, we demonstrate the importance of cross-kingdom integration of information in the study of microbial community ecology. Finally, the urgent need to propose an applicable approach for environmental health monitoring is addressed here by establishment of sediment microbiota as a robust and sensitive model. ABSTRACT Sedimentary marine habitats are the largest ecosystem on our planet in terms of area. Marine sediment microbiota govern most of the benthic biological processes and therefore are responsible for much of the global biogeochemical activity. Sediment microbiota respond, even rapidly, to natural change in environmental conditions as well as disturbances of anthropogenic sources. The latter greatly impact the continental shelf. Characterization and monitoring of the sediment microbiota may serve as an important tool for assessing environmental health and indicate changes in the marine ecosystem. This study examined the suitability of marine sediment microbiota as a bioindicator for environmental health in the eastern Mediterranean Sea. Integration of information from Bacteria, Archaea, and Eukaryota enabled robust assessment of environmental factors controlling sediment microbiota composition: seafloor-depth (here representing sediment grain size and total organic carbon), core depth, and season (11%, 4.2%, and 2.5% of the variance, respectively). Furthermore, inter- and intrakingdom cooccurrence patterns indicate that ecological filtration as well as stochastic processes may control sediment microbiota assembly. The results show that the sediment microbiota was robust over 3 years of sampling, in terms of both representation of region (outside the model sites) and robustness of microbial markers. Furthermore, anthropogenic disturbance was reflected by significant transformations in sediment microbiota. We therefore propose sediment microbiota analysis as a sensitive approach to detect disturbances, which is applicable for long-term monitoring of marine environmental health. IMPORTANCE Analysis of data, curated over 3 years of sediment sampling, improves our understanding of microbiota assembly in marine sediment. Furthermore, we demonstrate the importance of cross-kingdom integration of information in the study of microbial community ecology. Finally, the urgent need to propose an applicable approach for environmental health monitoring is addressed here by establishment of sediment microbiota as a robust and sensitive model.