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The potential of hydrocarbon biodegradation in marine sediments was determined through the detection of a functional biomarker, the bssA gene, coding for benzylsuccinate synthase, the key enzyme of anaerobic toluene degradation. Eight bssA clone libraries (409 sequences) were constructed from polluted sediments affected by the Prestige oil spill in the Atlantic Islands National Park and from hydrocarbon-amended sediment microcosms in Mallorca. The amplified products and database-derived bssA-like sequences grouped into four major clusters, as determined by phylogenetic reconstruction, principal coordinate analysis (PCoA), and a subfamily prediction tool. In addition to the classical bssA sequences that were targeted, we were able to detect sequences homologous to the naphthylmethylsuccinate synthase gene (nmsA) and the alkylsuccinate synthase gene (assA), the bssA homologues for anaerobic 2-methylnaphthalene and alkane degradation, respectively. The detection of bssA-like variants was determined by the persistence and level of pollution in the marine samples. The observed level of gene diversity was lower in the Mallorca sediments, which were dominated by assA-like sequences. In contrast, the Atlantic Islands samples, which were highly contaminated with methylnaphthalene-rich crude oil, showed a high proportion of nmsA-like sequences. Some of the detected genes were phylogenetically related to Deltaproteobacteria communities, previously described as the predominant hydrocarbon degraders at these sites. Differences between all detected bssA-like genes described to date indicate separation between marine and terrestrial sequences and further subgrouping according to taxonomic affiliation. Global analysis suggested that bssA homologues appeared to cluster according to substrate specificity. We observed undetected divergent gene lineages of bssA homologues, which evidence the existence of new degrader groups in these environments.

Diversity of Benzylsuccinate Synthase-Like ( bssA ) Genes in Hydrocarbon-Polluted Marine Sediments Suggests Substrate-Dependent Clustering