Differential Responses of a Coastal Prokaryotic Community to Phytoplanktonic Organic Matter Derived from Cellular Components and Exudates

Abstract

The phytoplanktonic production and prokaryotic consumption of organic matter significantly contribute to marine carbon cycling. Organic matter released from phytoplankton via three processes (exudation of living cells, cell disruption through grazing, and viral lysis) shows distinct chemical properties. We herein investigated the effects of phytoplanktonic whole-cell fractions (WF) (representing cell disruption by grazing) and extracellular fractions (EF) (representing exudates) prepared from Heterosigma akashiwo, a bloom-forming Raphidophyceae, on prokaryotic communities using culture-based experiments. We analyzed prokaryotic community changes for two weeks. The shift in cell abundance by both treatments showed similar dynamics, reaching the first peak (~4.1×10 6 cells mL-1) on day 3 and second peak (~1.1×10 6 cells mL-1) on day 13. We classified the sequences obtained into operational taxonomic units (OTUs). A Bray-Curtis dissimilarity analysis revealed that the OTU-level community structure changed distinctively with the two treatments. Ten and 13 OTUs were specifically abundant in the WF and EF treatments, respectively. These OTUs were assigned as heterotrophic bacteria mainly belonging to the Alteromonadales (Gammaproteobacteria) and Bacteroidetes clades and showed successive dynamics following the addition of organic matter. We also analyzed the dynamics of these OTUs in the ocean using publicly available metagenomic data from a natural coastal bloom in Monterey Bay, USA. At least two WF treatment OTUs showed co-occurrence with H. akashiwo, indicating that the blooms of H. akashiwo also affect these OTUs in the ocean. The present results strongly suggest that the thriving and dead cells of uninfected phytoplankton differentially influence the marine prokaryotic community.

Taxonomic difference in marine bloom-forming phytoplanktonic species affects dynamics of both bloom-responding prokaryotes and prokaryotic viruses

“…For community composition in original seawater, prokaryotic cells in 100 mL of seawater were collected on polycarbonate filters (47 mm diameter, 0.2 μm pore size; ADVANTEC Toyo Kaisha, Ltd.), and the filters were stored at −30 °C until DNA extraction. DNA was extracted using previously published methods (Takebe et al, 2020). The 16S rRNA genes were amplified using a primer set for the V3-V4 hypervariable region of prokaryotic 16S rRNA genes (Takahashi et al, 2014) concentrated via FeCl 3 precipitation and purified by CsCl density centrifugation, followed by DNase treatment as described in a previous study (Hurwitz et al, 2013).…”

“…Raw amplicon reads of 16S rRNA gene sequences obtained from natural seawater samples collected monthly in Osaka Bay between May, 2015, andNovember, 2016 (Tominaga et al, in press), were retrieved from the DNA Data Bank of Japan (DDBJ) under project number PRJDB10879. These reads were quality-trimmed and merged, and chimeras were removed following the pipeline described in a previous study (Takebe et al, 2020). Quality-controlled reads were mapped on ASVs of our interest with 100% identity using VSEARCH (Rognes et al, 2016).…”

“…Of these, ASV_3512, ASV_1069, and ASV_3313 had 100% nucleotide sequence identity with Pseudoalteromonas marina (NR_042981), Vibrio splendidus (NR_114888), and Vibrio gigantis (NR_114910), respectively (Table 1); V. splendidus causes mortality in mussels and oysters (Balbi et al, 2013;Romero et al, 2014). P. marina and the genus Vibrio were appeared to respond to the organic matter of H. akashiwo in our previous microcosm experiments (Takebe et al, 2020). Although not specific to H. akashiwo, the abundance of Psychrobium and NS9 marine groups of uncultured Flavobacteriales members is also known to be associated with the dynamics of marine phytoplankton in natural environments (Liu et al, 2019;John et al, 2022).…”

Prevalence of viral frequency-dependent infection in coastal marine prokaryotes revealed using monthly time series virome analysis

“…For prokaryotic community analysis, DNA was extracted from the stored filtration units as previously described [31,32]. Total 16S rDNA was amplified using a primer set based on the V3-V4 hypervariable region of prokaryotic 16 S rRNA genes [33] Paired-end 16S rDNA amplicon sequences were merged using VSEARCH with the "-M 1000" option [34].…”

Metabolic Potential of the Superphylum <i>Patescibacteria</i> Reconstructed from Activated Sludge Samples from a Municipal Wastewater Treatment Plant

“…Large metagenomic data obtained from samples in various environments revealed the existence of a large group of bacteria, called Patescibacteria or candidate phyla radiation (CPR) (Rinke et al, 2013;Brown et al, 2015). The Patescibacteria or CPR (hereafter called Patescibacteria) group includes 35 phyla, accounts for 15-50% of all bacterial phyla, and has been reported to exist in various environments (Brown et al, 2015;Hug et al, 2016;Takebe et al, 2020). To date, only a few of its members (i.e., phyla Saccharimonadia and Gracilibacteria) have been cultured (Soro et al, 2014;He et al, 2015;Ibrahim et al, 2021;Yakimov et al, 2021).…”