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.

Multi‐year dynamics of fine‐scale marine cyanobacterial populations are more strongly explained by phage interactions than abiotic, bottom‐up factors

“…Spurious, non-specific correlations are always a problem with co-variation analyses, but nevertheless this study utilizes some of the best available data to analyse both host and viral genotypic data at multiple diversity levels, along with bottom-up factors. Our results are also consistent with a recent paired analysis of host (16S rDNA) and viral ( g23 sequences) variants at SPOT that likewise saw that viral variants correlated better with finescale level 16S rDNA ASVs than broader taxa defined by 99% 16S rDNA identity (Needham et al 2017). As more viral metagenomic sequences or high-throughput viral marker gene data become available, we will be better equipped to more definitively test these proposed models and virus-host dynamics.…”

“…Our results are also consistent with a recent paired analysis of host (16S rDNA) and viral ( g23 sequences) variants at SPOT that likewise saw that viral variants correlated better with fine‐scale level 16S rDNA ASVs than broader taxa defined by 99% 16S rDNA identity (Needham et al . ). As more viral metagenomic sequences or high‐throughput viral marker gene data become available, we will be better equipped to more definitively test these proposed models and virus–host dynamics.…”

“…An emergent theme among such studies is that taxa defined as clusters of 16S rRNA or other gene sequences occupy distinct niches defined by environmental conditions or differences in resource utilization Martiny et al 2009;Chase et al 2017). Another common theme in this field is that using more fine-resolved metrics for defining taxa continues to uncover larger numbers of taxa that appear to be biologically and ecologically distinct (Eren et al 2013;Eren et al 2015;Tikhonov et al 2015;Needham et al 2017;Ward et al 2017). Finer level resolution is achieved, for example, by increasing percent identity cutoffs (e.g.…”

A common garden experiment with Porphyra umbilicalis (Rhodophyta) evaluates methods to study spatial differences in the macroalgal microbiome

“…, Needham et al. ). In our analysis, core community members are equivalent, with sequences matching within 1 bp.…”

Identification of Bacterial Genes Expressed During Diatom-Bacteria Interactions Using an in Vivo Expression Technology Approach

“…Initially mediated by either simple collision events or diverse chemical reactions, diatom-bacteria interactions initialize, or reinforce these processes by formation of extra-cellular polysaccharides affecting the stickiness and hence size of aggregates Logan et al, 1995;Passow, 2002). In the last decade, considerable progress has been made in understanding algae-bacteria interactions at both, the ecological as well as the cellular and molecular levels (Wang et al, 2014;Amin et al, 2015;Durham et al, 2015Durham et al, , 2017Needham et al, 2017;van Tol et al, 2017). In this way, different types of interactions were discovered, which were either microbial population driven or dictated by individual bacterial organisms.…”