Effects of phytoplankton, viral communities, and warming on free-living and particle-associated marine prokaryotic community structure

Abstract

Free-living and particle-associated marine prokaryotes have physiological, genomic, and phylogenetic differences, yet factors influencing their temporal dynamics remain poorly constrained. In this study, we quantify the entire microbial community composition monthly over several years, including viruses, prokaryotes, phytoplankton, and total protists, from the San-Pedro Ocean Time-series using ribosomal RNA sequencing and viral metagenomics. Canonical analyses show that in addition to physicochemical factors, the double-stranded DNA viral community is the strongest factor predicting free-living prokaryotes, explaining 28% of variability, whereas the phytoplankton (via chloroplast 16S rRNA) community is strongest with particle-associated prokaryotes, explaining 31% of variability. Unexpectedly, protist community explains little variability. Our findings suggest that biotic interactions are significant determinants of the temporal dynamics of prokaryotes, and the relative importance of specific interactions varies depending on lifestyles. Also, warming influenced the prokaryotic community, which largely remained oligotrophic summer-like throughout 2014-15, with cyanobacterial populations shifting from cold-water ecotypes to warm-water ecotypes.

Fig. 1. Temporal variation of multivariate ENSO index (MEI), sea surface temperature (SST), monthly average satellite chlorophyll-a concentration (Chla), and monthly average satellite primary productivity (PP) at the SPOT location.

MEI index is used to characterize the intensity of the El Niño/Southern Oscillation (ENSO) event; large positive MEI values indicate El Niño conditions, whereas large negative MEI values indicate La Niña conditions. In 2014–2015 (red box), probably due to El Niño (MEI > 0) and a marine heatwave known as the “Blob”, this location experienced reduced productivity and unusually warm temperatures (particularly winters), which also persisted to a lesser extent through the end of the study. Source data are provided as a Source data file.

Fig. 2. Temporal variation of the entire community composition at the SPOT location.

Order level taxonomic composition of (a) free-living prokaryotes (0.2–1 μm), (b) particle-associated or large-celled (1–80 μm) prokaryotes, (c) chloroplast 16S (representing phototrophic eukaryotes), and (d) eukaryotic 18S communities (excluding Metazoa and Syndiniales sequences to better show the phytoplankton and protistan phagotrophs; see text). Note that for clarity, this shows only the most abundant taxonomic groups, with relative abundance >10% in any month. Source data are provided as a Source data file.

Fig. 3. Canonical correspondence analysis (CCA) ordination illustrating the seasonal succession of the free-living and particle-associated prokaryotes, respectively.

a CCA biplot for free-living (0.2–1 μm) and particle-associated or large-celled (1–80 μm) prokaryotes. The environmental variables analyzed are indicated as vectors, specifically water temperature and monthly average satellite chlorophyll-a concentration (chlorophyll-a). The prokaryotic communities for each sampling month are represented as circles and color-coded with the sampling months. b Temporal variation of the first CCA scores, which are measures of the incidence of particular community components, with higher (positive) numbers reflecting summer-like (warm, lower chlorophyll) communities, and lower (negative) numbers indicating nominal winter and spring-like communities (lower temperatures, higher chlorophyll). Note that prokaryotic communities in both size fractions were mainly summer-like in 2014–2015 (red box), corresponding to warmer years with reduced productivity and no pronounced spring bloom (Fig. 1). Source data are provided as a Source data file.

Fig. 4. Mantel test showing correlations among different microbial components.

Scatterplots of each pair of beta-diversity (i.e., Bray–Curtis similarity) are shown on the left part of the figure. The results of each Mantel test are shown on the right. The distribution of beta-diversity of each component is shown on the diagonal. The results show that free-living and particle-associated prokaryotic communities were correlated most closely (r = 0.880), followed by chloroplasts and attached & large prokaryotes (r = 0.643). Viruses were much better correlated to prokaryotes than eukaryotes (rightmost column). The statistical significance of each component was evaluated by a permutation test with 9999 permutations, and the P-value of all tests is 0.0001. Source data are provided as a Source data file.

Fig. 5. Variation partitioning of components influencing prokaryotic community composition.

Percentages indicate the portion of the variance in free-living (a, c) and larger or particle-associated (b, d) prokaryotic community composition statistically explained by the respective variable. Environmental variables include temperature and chlorophyll-a. Virus data (in c, d) are available for only 2009–2014.

Fig. 6. Relative abundance of major ASVs within SAR11 and Synechococcales cyanobacteria.

Gray areas in the top graphs represent rarer ASVs of the clades not specifically included in the lower graphs. Note the appearance of Prochlorococcus HLII clade (red) only in the warmest years, 2014–2015. Source data are provided as a Source data file.