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Dimethylsulfoniopropionate (DMSP) is an abundant organic sulfur metabolite produced by many phytoplankton species and degraded by bacteria via two distinct pathways with climate‐relevant implications. We assessed the diversity and abundance of bacteria possessing these pathways in the context of phytoplankton community composition over a 3‐week time period spanning September–October, 2014 in Monterey Bay, CA. The dmdA gene from the DMSP demethylation pathway dominated the DMSP gene pool and was harboured mostly by members of the alphaproteobacterial SAR11 clade and secondarily by the Roseobacter group, particularly during the second half of the study. Novel members of the DMSP‐degrading community emerged from dmdA sequences recovered from metagenome assemblies and single‐cell sequencing, including largely uncharacterized gammaproteobacteria and alphaproteobacteria taxa. In the DMSP cleavage pathway, the SAR11 gene dddK was the most abundant early in the study, but was supplanted by dddP over time. SAR11 members, especially those harbouring genes for both DMSP degradation pathways, had a strong positive relationship with the abundance of dinoflagellates, and DMSP‐degrading gammaproteobacteria co‐occurred with haptophytes. This in situ study of the drivers of DMSP fate in a coastal ecosystem demonstrates for the first time correlations between specific groups of bacterial DMSP degraders and phytoplankton taxa.

Metagenomic and metatranscriptomic time-series data covering a 52-day period in the fall of 2016 provide an inventory of bacterial and archaeal community genes, transcripts, and taxonomy during an intense dinoflagellate bloom in Monterey Bay, CA, USA. The dataset comprises 84 metagenomes (0.8 terabases), 82 metatranscriptomes (1.1 terabases), and 88 16S rRNA amplicon libraries from samples collected on 41 dates. The dataset also includes 88 18S rRNA amplicon libraries, characterizing the taxonomy of the eukaryotic community during the bloom. Accompanying the sequence data are chemical and biological measurements associated with each sample. These datasets will facilitate studies of the structure and function of marine bacterial communities during episodic phytoplankton blooms.