The need to account for cell biology in characterizing predatory mixotrophs in aquatic environments

Photosynthesis in eukaryotes first arose through phagocytotic processes wherein an engulfed cyanobacterium was not digested, but instead became a permanent organelle. Other photosynthetic lineages then arose when eukaryotic cells engulfed other already photosynthetic eukaryotic cells. Some of the resulting lineages subsequently lost their ability for phagocytosis, while many others maintained the ability to do both processes. These mixotrophic taxa have more complicated ecological roles, in that they are both primary producers and consumers that can shift more towards producing the organic matter that forms the base of aquatic food chains, or towards respiring and releasing CO2. We still have much to learn about which taxa are predatory mixotrophs as well as about the physiological consequences of this lifestyle, in part, because much of the diversity of unicellular eukaryotes in aquatic ecosystems remains uncultured. Here, we discuss existing methods for studying predatory mixotrophs, their individual biases, and how single-cell approaches can enhance knowledge of these important taxa. The question remains what the gold standard should be for assigning a mixotrophic status to ill-characterized or uncultured taxa—a status that dictates how organisms are incorporated into carbon cycle models and how their ecosystem roles may shift in future lakes and oceans

Viruses infecting a warm water picoeukaryote shed light on spatial co-occurrence dynamics of marine viruses and their hosts

The marine picoeukaryote Bathycoccus prasinos has been considered a cosmopolitan alga, although recent studies indicate two ecotypes exist, Clade BI (B. prasinos) and Clade BII. Viruses that infect Bathycoccus Clade BI are known (BpVs), but not that infect BII. We isolated three dsDNA prasinoviruses from the Sargasso Sea against Clade BII isolate RCC716. The BII-Vs do not infect BI, and two (BII-V2 and BII-V3) have larger genomes (~210 kb) than BI-Viruses and BII-V1. BII-Vs share ~90% of their proteins, and between 65% to 83% of their proteins with sequenced BpVs. Phylogenomic reconstructions and PolB analyses establish close-relatedness of BII-V2 and BII-V3, yet BII-V2 has 10-fold higher infectivity and induces greater mortality on host isolate RCC716. BII-V1 is more distant, has a shorter latent period, and infects both available BII isolates, RCC716 and RCC715, while BII-V2 and BII-V3 do not exhibit productive infection of the latter in our experiments. Global metagenome analyses show Clade BI and BII algal relative abundances correlate positively with their respective viruses. The distributions delineate BI/BpVs as occupying lower temperature mesotrophic and coastal systems, whereas BII/BII-Vs occupy warmer temperature, higher salinity ecosystems. Accordingly, with molecular diagnostic support, we name Clade BII Bathycoccus calidus sp. nov. and propose that molecular diversity within this new species likely connects to the differentiated host-virus dynamics observed in our time course experiments. Overall, the tightly linked biogeography of Bathycoccus host and virus clades observed herein supports species-level host specificity, with strain-level variations in infection parameters

Choanoflagellates alongside diverse uncultured predatory protists consume the abundant open-ocean cyanobacterium Prochlorococcus

Prochlorococcus is a key member of open-ocean primary producer communities. Despite its importance, little is known about the predators that consume this cyanobacterium and make its biomass available to higher trophic levels. We identify potential predators along a gradient wherein Prochlorococcus abundance increased from near detection limits (coastal California) to >200,000 cells mL-1 (subtropical North Pacific Gyre). A replicated RNA-Stable Isotope Probing experiment involving the in situ community, and labeled Prochlorococcus as prey, revealed choanoflagellates as the most active predators of Prochlorococcus, alongside a radiolarian, chrysophytes, dictyochophytes, and specific MAST lineages. These predators were not appropriately highlighted in multiyear conventional 18S rRNA gene amplicon surveys where dinoflagellates and other taxa had highest relative amplicon abundances across the gradient. In identifying direct consumers of Prochlorococcus, we reveal food-web linkages of individual protistan taxa and resolve routes of carbon transfer from the base of marine food webs

Gradients of bacteria in the oceanic water column reveal finely-resolved vertical distributions

Bacterial communities directly influence ecological processes in the ocean, and depth has a major influence due to the changeover in primary energy sources between the sunlit photic zone and dark ocean. Here, we examine the abundance and diversity of bacteria in Monterey Bay depth profiles collected from the surface to just above the sediments (e.g., 2000 m). Bacterial abundance in these Pacific Ocean samples decreased by >1 order of magnitude, from 1.22 ±0.69 ×106 cells ml-1 in the variable photic zone to 1.44 ± 0.25 ×105 and 6.71 ± 1.23 ×104 cells ml-1 in the mesopelagic and bathypelagic, respectively. V1-V2 16S rRNA gene profiling showed diversity increased sharply between the photic and mesopelagic zones. Weighted Gene Correlation Network Analysis clustered co-occurring bacterial amplicon sequence variants (ASVs) into seven subnetwork modules, of which five strongly correlated with depth-related factors. Within surface-associated modules there was a clear distinction between a ‘copiotrophic’ module, correlating with chlorophyll and dominated by e.g., Flavobacteriales and Rhodobacteraceae, and an ‘oligotrophic’ module dominated by diverse Oceanospirillales (such as uncultured JL-ETNP-Y6, SAR86) and Pelagibacterales. Phylogenetic reconstructions of Pelagibacterales and SAR324 using full-length 16S rRNA gene data revealed several additional subclades, expanding known microdiversity within these abundant lineages, including new Pelagibacterales subclades Ia.B, Id, and IIc, which comprised 4–10% of amplicons depending on the subclade and depth zone. SAR324 and Oceanospirillales dominated in the mesopelagic, with SAR324 clade II exhibiting its highest relative abundances (17±4%) in the lower mesopelagic (300–750 m). The two newly-identified SAR324 clades showed highest relative abundances in the photic zone (clade III), while clade IV was extremely low in relative abundance, but present across dark ocean depths. Hierarchical clustering placed microbial communities from 900 m samples with those from the bathypelagic, where Marinimicrobia was distinctively relatively abundant. The patterns resolved herein, through high resolution and statistical replication, establish baselines for marine bacterial abundance and taxonomic distributions across the Monterey Bay water column, against which future change can be assessed

Rarefaction curves of sequencing depth versus number of observed bacterial ASVs per sample.

Rarefaction curve final slope vs. (A) depth and (B) total number of amplicons. Colored shapes indicate the station (color) and sampling date (shape) of each sample. (C) Rarefaction curve of number of ASVs vs. amplicons. Each station (color) plotted separately. (PDF)</p

Pelagibacterales 16S rRNA gene Maximum Likelihood phylogenetic reconstruction with accession numbers.

A total of 137 near full-length 16S rRNA gene sequences representing Pelagibacterales were retrieved from the SILVA database (release 128) and through blastn (v2.6.0) [48] searches of GenBank using sequences from previously published studies. The 137 sequences plus one Escherichia coli and one Magnetococcus marinus (as an outgroup) sequence were aligned using MAFFT (v7.402) [49] with default parameters and ambiguously aligned sites were removed using trimAl (v1.4) with a no gap threshold [50]. Phylogenetic inferences were performed using Maximum Likelihood methods implemented in RAxML (v8.2.10) [51] under gamma-corrected GTR model of evolution with 1,000 bootstrap replicates based on 1,303 homologous positions. (PDF)</p

Community and taxonomic patterns in bacterial communities along the depth gradient.

The right side shows hierarchical clustering performed on Bray-Curtis dissimilarities of bacterial communities based on the 1000 most relatively abundant ASVs of bacteria (both non-photosynthetic and cyanobacteria (i.e., photosynthetic); see S4 Fig for non-photosynthetic bacteria only). Stations (color) and sampling dates (shape) are indicated as is the depth sampled (m). The left side shows relative abundance of the 50 most relatively abundant ASVs (columns) per sample from the five main depth zones as defined herein. Ordering along the X-axis is by phyla (indicated by horizontal gray bars at the base of figure) and rows represent individual water samples–corresponding to those immediately adjacent (i.e., to the right). ASV relative abundances, sequences, and taxonomic classification are detailed in S3 Table. The four groups with the overall highest relative abundances are indicated (boxes overlaying heat map) and were alphaproteobacterial ASVs assigned to the Rhodobacteraceae and Pelagibacterales Ia in the photic zone, whereas in mesopelagic and bathypelagic samples ASVs from SAR324 and Gammaproteobacteria Oceanospirillales exhibited the highest relative abundances. Taxonomic assignment for ASVs is based on the SILVA database.</p

Taxonomic patterns of highly abundant ASVs in bacterial communities along the depth gradient.

(A) Heat map of bacterial ASV relative abundances with cyanobacterial ASVs excluded (149 in total). (B) Hierarchical clustering based on the top 1,000 most relatively abundant ASVs in samples with cyanobacterial ASVs excluded. (PDF)</p

Abundance and diversity of bacteria and cyanobacteria across depth and sample periods.

(A) Cell abundance of Prochlorococcus (closed symbols) and Synechococcus (open symbols) in the upper 200 m as enumerated by flow cytometry; cyanobacterial cells were not detected below this depth. (B) Heterotrophic bacterial cell abundance (i.e., non-pigmented; analyzed by flow cytometry after SYBR Green I staining) decreased with depth by 1.5 orders of magnitude. Replicates from individual sampling dates revealed a variance of 16% (n = 8) that can be attributed to methodology. (C) Shannon diversity indices for all sequenced samples and depth profiles as calculated from V1-V2 16S rRNA gene ASV data. September 2015 (squares), May 2016 (triangles), and September 2016 (circles) sampling dates are indicated, while stations are represented by color for all panels. Horizontal dotted lines (plots B and C) represent the bottom depth for the respective stations.</p

Phylogeny and distributions of Pelagibacterales.

The 16S rRNA gene phylogenetic reconstruction utilized full-length sequences and identifies 10 recognized subclades and 3 previously unrecognized subclades, all with bootstrap support >90% (1,000 replicates) except subclade IIb (86% support; see also S4 Fig). Note that dashed lines indicate LCA placements at unsupported nodes, some with relatively few amplicons. For example, that demarked ‘Clade V’—with a dashed line comprised >0.01% of amplicons . Some others with dashed lines were notable, but lacked full length sequences and therefore references sequences were not in the reconstruction. Also shown is the relative abundance of Pelagibacterales subclades as percent of all Pelagibacterales ASVs in each sample for the Monterey Bay Stations and depths sampled. Pelagibacter amplicons were first retrieved using PhyloAssigner and a global 16S rRNA gene reference tree [17]. These amplicons were then run in PhyloAssigner using the above Pelagibacterales reference tree. Heat map columns represent individual samples ordered by hierarchical clustering based on the Bray-Curtis similarities of the Pelagibacterales community composition. White in the heat map indicates not detected. Stations (color) and sampling dates (shape) are indicated as is sample depth (m) for each column.</p