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 Copyright policy )Abstract Dimethylsulfoniopropionate (DMSP) is produced mainly by phytoplankton and bacteria. It is relatively abundant and ubiquitous in the marine environment, where bacterioplankton make use of it readily as both carbon and sulfur sources. In one transformation pathway, part of the molecule becomes dimethylsulfide (DMS), which escapes into the atmosphere and plays an important role in the sulfur exchange between oceans and atmosphere. Through its other dominant catabolic pathway, bacteria are able to use it as sulfur source. During the past few years, a number of genes involved in its transformation have been characterized. Identifying genes in taxonomic groups not amenable to conventional methods of cultivation is challenging. Indeed, functional annotation of genes in environmental studies is not straightforward, considering that particular taxa are not well represented in the available sequence databases. Furthermore, many genes belong to families of paralogs with similar sequences but perhaps different functions. In this study, we develop in silico approaches to infer protein function of an environmentally important gene (dmdA) that carries out the first step in the sulfur assimilation from DMSP. The method combines a set of tools to annotate a targeted gene in genome databases and metagenome assemblies. The method will be useful to identify genes that carry out key biochemical processes in the environment.
Water microbiology, Microbial ecology, Next-generation sequencing, Bacteria, Oceans and Seas, Sulfonium Compounds, Molecular Sequence Annotation, Plankton, Genes, Bacterial, Bacterial genetics, Phytoplankton, Metagenome, Computer Simulation, Seawater, Sequence Alignment, Sulfur
Water microbiology, Microbial ecology, Next-generation sequencing, Bacteria, Oceans and Seas, Sulfonium Compounds, Molecular Sequence Annotation, Plankton, Genes, Bacterial, Bacterial genetics, Phytoplankton, Metagenome, Computer Simulation, Seawater, Sequence Alignment, Sulfur
| citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 20 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Top 10% | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% | 
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