Ecological dynamics and co-occurrence among marine phytoplankton, bacteria and myoviruses shows microdiversity matters

Abstract

Numerous ecological processes, such as bacteriophage infection and phytoplankton-bacterial interactions, often occur via strain-specific mechanisms. Therefore, studying the causes of microbial dynamics should benefit from highly resolving taxonomic characterizations. We sampled daily to weekly over 5 months following a phytoplankton bloom off Southern California and examined the extent of microdiversity, that is, significant variation within 99% sequence similarity clusters, operational taxonomic units (OTUs), of bacteria, archaea, phytoplankton chloroplasts (all via 16S or intergenic spacer (ITS) sequences) and T4-like-myoviruses (via g23 major capsid protein gene sequence). The extent of microdiversity varied between genes (ITS most, g23 least) and only temporally common taxa were highly microdiverse. Overall, 60% of taxa exhibited microdiversity; 59% of these had subtypes that changed significantly as a proportion of the parent taxon, indicating ecologically distinct taxa. Pairwise correlations between prokaryotes and myoviruses or phytoplankton (for example, highly microdiverse Chrysochromulina sp.) improved when using single-base variants. Correlations between myoviruses and SAR11 increased in number (172 vs 9, Spearman>0.65) and became stronger (0.61 vs 0.58, t-test: P<0.001) when using SAR11 ITS single-base variants vs OTUs. Whole-community correlation between SAR11 and myoviruses was much improved when using ITS single-base variants vs OTUs, with Mantel rho=0.49 vs 0.27; these results are consistent with strain-specific interactions. Mantel correlations suggested >1 μm (attached/large) prokaryotes are a major myovirus source. Consideration of microdiversity improved observation of apparent host and virus networks, and provided insights into the ecological and evolutionary factors influencing the success of lineages, with important implications to ecosystem resilience and microbial function.

Figure 1

Number of ASVs associated with OTUs of various temporal ubiquity for (a) prokaryotes (b) phytoplankton via chloroplasts and (c) T4-like-myoviruses. Each data set was subsampled 10 times to the minimum number of sequences observed for a given OTU within the data set, and the average number of ASVs per OTU is shown along with the s.e.m. ASV data for prokaryotes include reads from both 1–80 and 0.22–1 μm size fractions. Occurrence for prokaryotes can be in either small and free-living or large and particle-attached size fractions. Data are plotted with a slight vertical jitter to help with over-plotted points. One chloroplast OTU was omitted (fraction dates observed=0.95) because no ASV exceeded the minimum number of sequences required to be considered (that is, the OTU was very microdiverse). Inset graphs show relationship between ASV and relative abundance of each OTU, showing the patterns in the large graphs are not due to OTU abundance.

Figure 2

Dynamics of phytoplankton OTUs, which had >2 ASVs that became more than 50% of the sequences of a given OTU for at least one date (in which OTU abundance was >0.1%). The red, blue, green, purple or gold segments of bargraphs represent the proportion that each ASV made up of an OTU on a given day. That is, if a ‘red’ ASV is made up of 25% of the sequences of the OTU on a given day, the red bar is 25%. The black line represents the relative abundance over time of each OTU as a proportion of the whole community; the colored lines (which correspond to the colors of the bar segments) are the estimated relative abundance of each ASV as a proportion of the whole community of chloroplast sequences (that is, ASV proportion of OTU *OTU relative abundance of all chloroplast sequences). Only the top five most abundant ASVs estimated abundances, that is, lines, are shown for each OTU. All ASVs proportions making up >1% on average of an OTU, but not in the top five, are shown as individual gray bar segments (for example, at the top left of the ‘Thalassiosira oceanica a’ panel). The letter following the taxon name corresponds to the average abundance of the taxa relative to other OTUs taxa with that name (a, most abundant; b, second most abundant and so on).

Figure 3

Dynamics of bacterial OTUs which had >2 ASVs that became more than 50% of the sequences for a given OTU for at least one date in both size fractions (not necessarily on the same day), in which OTU abundance was >0.1%. As in Figure 2, the black line represents the total abundance over time of each OTU; the colored lines (corresponding to bar segments) are the estimated relative abundance of each ASV (that is, ASV proportion of OTU *OTU relative abundance). Only the top five most abundant ASVs estimated abundances, that is, lines, are shown for each OTU. All ASVs proportions making up >1% on average of an OTU, but not in the top five, are shown as individual gray bar segments. The letter following the taxon name corresponds to the average abundance of the taxon relative to other taxa with that name (a, most abundant; b, second most abundant and so on).

Figure 4

Dynamics and underlying diversity of T4-like-myovirus ASVs from San Pedro Ocean Time-series March–August 2011. (a) Dynamics of all T4-like-virus ASVs that were most abundant for at least 1 day during 12 March–1 April, along with chlorophyll concentration as the gray background (values along the secondary y-axis) and (b) for all ASVs that were >1% on average over the full-time series. (c) Underlying Shannon entropy and (d) dynamics are shown for three g23 OTUs (>1% on average) that showed significant changes in abundance of ASVs as proportion of the parent OTU during the time series (Mann–Kendall test, <0.005). For d, as in Figures 2 and 3, the black line represents the total abundance over time of each OTU; the colored lines (corresponding to bar segments) are the estimated relative abundance of each ASV (that is, ASV proportion of OTU *OTU relative abundance). g23 OTUs that had more than one ASV become most abundant are shown in Supplementary Figure 10. T4-like-myovirus OTUs did not have high sequence similarities to cultured representatives, so were assigned generic names (a, most abundant on average; b, second most abundant and so on).

Figure 5

Dynamics of SAR11 (a) 16S and (b) ITS OTUs, and ASVs March–September 2011. The black line represents the overall relative abundance of SAR11 (all SAR11 OTUs cumulatively). Lines represent the ASV relative abundances (cumulative SAR11 16S relative abundance *ASV relative abundance) over time. Only the top five most abundant ASVs are shown. Note the y-axis on the left of each panel corresponds to the SAR11 total abundance and the y-axis on the right corresponds to ASV relative abundance. SAR11 16S taxonomy is from the SILVA taxonomy and the ITS taxonomy comes from Brown et al. (2012). The letter (16S) and number (ITS) following the last underscore in the taxon name correspond to the average abundance of the taxon relative to other OTUs with the same taxon name.

Figure 6

Pairwise correlation networks show correlations (Spearman >0.85, P<0.001) between prokaryotes and phytoplankton or T4-like-myoviruses for (a) ASVs and (b) OTUs over the full-time series. Slightly lower correlations are shown between (c) phytoplankton and prokaryotes ASVs (Spearman >0.8, P<0.001) and (d) OTUs over the full-time series. In each network, gray-filled circles represent phytoplankton, gray filled-squares represent bacteria from the 1-80μm size fraction, unfilled squares represent bacteria from 0.2-1μm size fraction, and 'V' symbols represents T4-like-viruses. Thick outline surrounding nodes indicates the node that represents the dynamics of a taxon within the large or particle-attached fraction. The size of the symbols represents the average relative abundance of each taxon. Solid and dashed lines represent positive and negative, respectively, correlations between the connected nodes. As in Figures 2 and 3, the letters following taxon name correspond to the average abundance of the taxon relative to other OTUs with the same name. The number following these letters (a and c) corresponds to the average abundance of the ASV within a given OTU. A full color version of this figure is available at the The ISME Journal online.

Figure 7

Correlation network between T4-like-myovirus ASV and (a) SAR11 ITS ASVs and (b) SAR11 ITS OTUs showing many more and higher correlations at the ASV level. (c) The total number of significant positive correlations (P<0.001, Q<0.001) between SAR11 (ITS and 16S) OTUs and ASVs to virus OTUs and ASVs. All SAR11 data from 0.22 to 1 μm size fraction. As in Figure 5, ITS taxonomy comes from Brown et al. (2012) and the number following the first underscore in the taxon names, corresponds to the average abundance of the taxon relative to other OTUs with the same taxon name. The value following these numbers (a), corresponds to the average abundance of the ASV within a given OTU.