Single-cell genomics revealed Candidatus Grellia alia sp. nov. as an endosymbiont of Eutreptiella sp. (Euglenophyceae)

Though endosymbioses between protists and prokaryotes are widespread, certain host lineages have received disproportionate attention what may indicate either a predisposition to such interactions or limited studies on certain protist groups due to lack of cultures. The euglenids represent one such group in spite of microscopic observations showing intracellular bacteria in some strains. Here, we perform a comprehensive molecular analysis of a previously identified endosymbiont in the Eutreptiella sp. CCMP3347 using a single cell approach and bulk culture sequencing. The genome reconstruction of this endosymbiont allowed the description of a new endosymbiont Candidatus Grellia alia sp. nov. from the family Midichloriaceae. Comparative genomics revealed a remarkably complete conjugative type IV secretion system present in three copies on the plasmid sequences of the studied endosymbiont, a feature missing in the closely related Grellia incantans. This study addresses the challenge of limited host cultures with endosymbionts by showing that the genomes of endosymbionts reconstructed from single host cells have the completeness and contiguity that matches or exceeds those coming from bulk cultures. This paves the way for further studies of endosymbionts in euglenids and other protist groups. The research also provides the opportunity to study the diversity of endosymbionts in natural populations.

Tiara: deep learning-based classification system for eukaryotic sequences

MOTIVATION

With a large number of metagenomic datasets becoming available, eukaryotic metagenomics emerged as a new challenge. The proper classification of eukaryotic nuclear and organellar genomes is an essential step toward a better understanding of eukaryotic diversity.

RESULTS

We developed Tiara, a deep-learning-based approach for the identification of eukaryotic sequences in the metagenomic datasets. Its two-step classification process enables the classification of nuclear and organellar eukaryotic fractions and subsequently divides organellar sequences into plastidial and mitochondrial. Using the test dataset, we have shown that Tiara performed similarly to EukRep for prokaryotes classification and outperformed it for eukaryotes classification with lower calculation time. In the tests on the real data, Tiara performed better than EukRep in analyzing the small dataset representing eukaryotic cell microbiome and large dataset from the pelagic zone of oceans. Tiara is also the only available tool correctly classifying organellar sequences, which was confirmed by the recovery of nearly complete plastid and mitochondrial genomes from the test data and real metagenomic data.

AVAILABILITY AND IMPLEMENTATION

Tiara is implemented in python 3.8, available at https://github.com/ibe-uw/tiara and tested on Unix-based systems. It is released under an open-source MIT license and documentation is available at https://ibe-uw.github.io/tiara. Version 1.0.1 of Tiara has been used for all benchmarks.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Analyses of environmental sequences and two regions of chloroplast genomes revealed the presence of new clades of photosynthetic euglenids in marine environments

Euglenophyceae are unicellular algae with the majority of their diversity known from small freshwater reservoirs. Only two dozen species have been described to occur in marine habitats, but their abundance and diversity remain unexplored. Phylogenetic studies revealed marine prasinophyte green alga, Pyramimonas parkeae, as the closest extant relative of the euglenophytes' plastid, but similarly to euglenophytes, our knowledge about the diversity of Pyramimonadales is limited. Here we explored Euglenophyceae and Pyramimonadales phylogenetic diversity in marine environmental samples. We yielded 18S rDNA and plastid 16S rDNA sequences deposited in public repositories and reconstructed Euglenophyceae reference trees. We searched high-throughput environmental sequences from the TARA Oceans expedition and Ocean Sampling Day initiative for 18S rDNA and 16S rDNA, placed them in the phylogenetic context and estimated their relative abundances. To avoid polymerase chain reaction (PCR) bias, we also exploited metagenomic data from the TARA Oceans expedition for the presence of rRNA sequences from these groups. Finally, we targeted these protists in coastal samples by specific PCR amplification of two parts of the plastid genome uniquely shared between euglenids and Pyramimonadales. All approaches revealed previously undetected, but relatively low-abundant lineages of marine Euglenophyceae. Surprisingly, some of those lineages are branching within the freshwater or brackish genera.