Analysis of the genomic basis of functional diversity in dinoflagellates using a transcriptome-based sequence similarity network

Beyond the limits of the unassigned protist microbiome: inferring large-scale spatio-temporal patterns of Syndiniales marine parasites

Marine protists are major components of the oceanic microbiome that remain largely unrepresented in culture collections and genomic reference databases. The exploration of this uncharted protist diversity in oceanic communities relies essentially on studying genetic markers from the environment as taxonomic barcodes. Here we report that across 6 large scale spatio-temporal planktonic surveys, half of the genetic barcodes remain taxonomically unassigned at the genus level, preventing a fine ecological understanding for numerous protist lineages. Among them, parasitic Syndiniales (Dinoflagellata) appear as the least described protist group. We have developed a computational workflow, integrating diverse 18S rDNA gene metabarcoding datasets, in order to infer large-scale ecological patterns at 100% similarity of the genetic marker, overcoming the limitation of taxonomic assignment. From a spatial perspective, we identified 2171 unassigned clusters, i.e., Syndiniales sequences with 100% similarity, exclusively shared between the Tropical/Subtropical Ocean and the Mediterranean Sea among all Syndiniales orders and 25 ubiquitous clusters shared within all the studied marine regions. From a temporal perspective, over 3 time-series, we highlighted 39 unassigned clusters that follow rhythmic patterns of recurrence and are the best indicators of parasite community's variation. These clusters withhold potential as ecosystem change indicators, mirroring their associated host community responses. Our results underline the importance of Syndiniales in structuring planktonic communities through space and time, raising questions regarding host-parasite association specificity and the trophic mode of persistent Syndiniales, while providing an innovative framework for prioritizing unassigned protist taxa for further description.

Vitamin B12-auxotrophy in dinoflagellates caused by incomplete or absent cobalamin-independent methionine synthase genes (metE)

Dinoflagellates are responsible for most marine harmful algal blooms (HABs) and play vital roles in many ocean processes. More than 90% of dinoflagellates are vitamin B12 auxotrophs and that B12 availability can control dinoflagellate HABs, yet the genetic basis of B12 auxotrophy in dinoflagellates in the framework of the ecology of dinoflagellates and particularly HABs, which was the objective of this work. Here, we investigated the presence, phylogeny, and transcription of two methionine synthase genes (B12-dependent metH and B12-independent metE) via searching and assembling transcripts and genes from transcriptomic and genomic databases, cloning 38 cDNA isoforms of the two genes from 14 strains of dinoflagellates, measuring the expression at different scenarios of B12, and comprehensive phylogenetic analyses of more than 100 organisms. We found that 1) metH was present in all 58 dinoflagellates accessible and metE was present in 40 of 58 species, 2) all metE genes lacked N-terminal domains, 3) metE of dinoflagellates were phylogenetically distinct from other known metE genes, and 4) expression of metH in dinoflagellates was responsive to exogenous B12 levels while expression of metE was not responding as that of genuine metE genes. We conclude that most, hypothetically all, dinoflagellates have either non-functional metE genes lacking N-terminal domain for most species, or do not possess metE for other species, which provides the genetic basis for the widespread nature of B12 auxotrophy in dinoflagellates. The work elucidated a fundamental aspect of the nutritional ecology of dinoflagellates.

Mechanistic insights into the key marine dimethylsulfoniopropionate synthesis enzyme DsyB/DSYB

Marine algae and bacteria produce approximately eight billion tonnes of the organosulfur molecule dimethylsulfoniopropionate (DMSP) in Earth's surface oceans annually. DMSP is an antistress compound and, once released into the environment, a major nutrient, signaling molecule, and source of climate-active gases. The methionine transamination pathway for DMSP synthesis is used by most known DMSP-producing algae and bacteria. The S-directed S-adenosylmethionine (SAM)-dependent 4-methylthio-2-hydroxybutyrate (MTHB) S-methyltransferase, encoded by the dsyB/DSYB gene, is the key enzyme of this pathway, generating S-adenosylhomocysteine (SAH) and 4-dimethylsulfonio-2-hydroxybutyrate (DMSHB). DsyB/DSYB, present in most haptophyte and dinoflagellate algae with the highest known intracellular DMSP concentrations, is shown to be far more abundant and transcribed in marine environments than any other known S-methyltransferase gene in DMSP synthesis pathways. Furthermore, we demonstrate in vitro activity of the bacterial DsyB enzyme from Nisaea denitrificans and provide its crystal structure in complex with SAM and SAH-MTHB, which together provide the first important mechanistic insights into a DMSP synthesis enzyme. Structural and mutational analyses imply that DsyB adopts a proximity and desolvation mechanism for the methyl transfer reaction. Sequence analysis suggests that this mechanism may be common to all bacterial DsyB enzymes and also, importantly, eukaryotic DSYB enzymes from e.g., algae that are the major DMSP producers in Earth's surface oceans.

Towards omics-based predictions of planktonic functional composition from environmental data

Marine microbes play a crucial role in climate regulation, biogeochemical cycles, and trophic networks. Unprecedented amounts of data on planktonic communities were recently collected, sparking a need for innovative data-driven methodologies to quantify and predict their ecosystemic functions. We reanalyze 885 marine metagenome-assembled genomes through a network-based approach and detect 233,756 protein functional clusters, from which 15% are functionally unannotated. We investigate all clusters' distributions across the global ocean through machine learning, identifying biogeographical provinces as the best predictors of protein functional clusters' abundance. The abundances of 14,585 clusters are predictable from the environmental context, including 1347 functionally unannotated clusters. We analyze the biogeography of these 14,585 clusters, identifying the Mediterranean Sea as an outlier in terms of protein functional clusters composition. Applicable to any set of sequences, our approach constitutes a step towards quantitative predictions of functional composition from the environmental context.

Species specific gene expression dynamics during harmful algal blooms

Harmful algal blooms are caused by specific members of microbial communities. Understanding the dynamics of these events requires comparing the strategies developed by the problematic species to cope with environmental fluctuations to the ones developed by the other members of the community. During three consecutive years, the meta-transcriptome of micro-eukaryote communities was sequenced during blooms of the toxic dinoflagellate Alexandrium minutum. The dataset was analyzed to investigate species specific gene expression dynamics. Major shifts in gene expression were explained by the succession of different species within the community. Although expression patterns were strongly correlated with fluctuation of the abiotic environment, and more specifically with nutrient concentration, transcripts specifically involved in nutrient uptake and metabolism did not display extensive changes in gene expression. Compared to the other members of the community, A. minutum displayed a very specific expression pattern, with lower expression of photosynthesis transcripts and central metabolism genes (TCA cycle, glucose metabolism, glycolysis…) and contrasting expression pattern of ion transporters across environmental conditions. These results suggest the importance of mixotrophy, cell motility and cell-to-cell interactions during A. minutum blooms.

Core genes in diverse dinoflagellate lineages include a wealth of conserved dark genes with unknown functions

Dinoflagellates are a diverse group of unicellular primary producers and grazers that exhibit some of the most remarkable features known among eukaryotes. These include gigabase-sized nuclear genomes, permanently condensed chromosomes and highly reduced organelle DNA. However, the genetic inventory that allows dinoflagellates to thrive in diverse ecological niches is poorly characterised. Here we systematically assess the functional capacity of 3,368,684 predicted proteins from 47 transcriptome datasets spanning eight dinoflagellate orders. We find that 1,232,023 proteins do not share significant sequence similarity to known sequences, i.e. are "dark". Of these, we consider 441,006 (13.1% of overall proteins) that are found in multiple taxa, or occur as alternative splice variants, to comprise the high-confidence dark proteins. Even with unknown function, 43.3% of these dark proteins can be annotated with conserved structural features using an exhaustive search against available data, validating their existence and importance. Furthermore, these dark proteins and their putative homologs are largely lineage-specific and recovered in multiple taxa. We also identified conserved functions in all dinoflagellates, and those specific to toxin-producing, symbiotic, and cold-adapted lineages. Our results demonstrate the remarkable divergence of gene functions in dinoflagellates, and provide a platform for investigations into the diversification of these ecologically important organisms.

A de novo approach to disentangle partner identity and function in holobiont systems

BACKGROUND

Study of meta-transcriptomic datasets involving non-model organisms represents bioinformatic challenges. The production of chimeric sequences and our inability to distinguish the taxonomic origins of the sequences produced are inherent and recurrent difficulties in de novo assembly analyses. As the study of holobiont meta-transcriptomes is affected by challenges invoked above, we propose an innovative bioinformatic approach to tackle such difficulties and tested it on marine models as a proof of concept.

RESULTS

We considered three holobiont models, of which two transcriptomes were previously published and a yet unpublished transcriptome, to analyze and sort their raw reads using Short Read Connector, a k-mer based similarity method. Before assembly, we thus defined four distinct categories for each holobiont meta-transcriptome: host reads, symbiont reads, shared reads, and unassigned reads. Afterwards, we observed that independent de novo assemblies for each category led to a diminution of the number of chimeras compared to classical assembly methods. Moreover, the separation of each partner's transcriptome offered the independent and comparative exploration of their functional diversity in the holobiont. Finally, our strategy allowed to propose new functional annotations for two well-studied holobionts (a Cnidaria-Dinophyta, a Porifera-Bacteria) and a first meta-transcriptome from a planktonic Radiolaria-Dinophyta system forming widespread symbiotic association for which our knowledge is considerably limited.

CONCLUSIONS

In contrast to classical assembly approaches, our bioinformatic strategy generates less de novo assembled chimera and allows biologists to study separately host and symbiont data from a holobiont mixture. The pre-assembly separation of reads using an efficient tool as Short Read Connector is an effective way to tackle meta-transcriptomic challenges and offers bright perpectives to study holobiont systems composed of either well-studied or poorly characterized symbiotic lineages and ultimately expand our knowledge about these associations.