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Microbial predators form a new supergroup of eukaryotes

Nature volume 612, pages 714–719 (2022)Cite this article

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Abstract

Molecular phylogenetics of microbial eukaryotes has reshaped the tree of life by establishing broad taxonomic divisions, termed supergroups, that supersede the traditional kingdoms of animals, fungi and plants, and encompass a much greater breadth of eukaryotic diversity1. The vast majority of newly discovered species fall into a small number of known supergroups. Recently, however, a handful of species with no clear relationship to other supergroups have been described2,3,4, raising questions about the nature and degree of undiscovered diversity, and exposing the limitations of strictly molecular-based exploration. Here we report ten previously undescribed strains of microbial predators isolated through culture that collectively form a diverse new supergroup of eukaryotes, termed Provora. The Provora supergroup is genetically, morphologically and behaviourally distinct from other eukaryotes, and comprises two divergent clades of predators—Nebulidia and Nibbleridia—that are superficially similar to each other, but differ fundamentally in ultrastructure, behaviour and gene content. These predators are globally distributed in marine and freshwater environments, but are numerically rare and have consequently been overlooked by molecular-diversity surveys. In the age of high-throughput analyses, investigation of eukaryotic diversity through culture remains indispensable for the discovery of rare but ecologically and evolutionarily important eukaryotes.

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Fig. 1: Cell morphology.
Fig. 2: Phylogeny of eukaryotes reconstructed with a concatenated 320-gene dataset.
Fig. 3: Estimated gene family diversity in Provora.
Fig. 4: Mitochondrial genomes support the distinctness and diversity of Provora.

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Data availability

Raw transcriptome reads from Provora are deposited in GenBank (PRJNA866092), along with the SSU rRNA gene sequences of species (OP101998–OP102010). Assembled transcriptomes, mitochondrial genomes, materials of orthogroup and phylogenetic analyses, along with individual gene alignments, concatenated and trimmed alignments, and maximum-likelihood and Bayesian tree files for the phylogenomic dataset are available at Figshare (https://doi.org/10.6084/m9.figshare.20497143). The following databases were used in this study: NCBI nt (https://ftp.ncbi.nlm.nih.gov/blast/db/FASTA/nt.gz), NCBI non-redundant database (https://ftp.ncbi.nlm.nih.gov/blast/db/FASTA/nr.gz), Swiss-Prot (https://ftp.uniprot.org/pub/databases/uniprot/current_release/knowledgebase/complete/uniprot_sprot.fasta.gz), EukProt (https://figshare.com/articles/dataset/EukProt_a_database_of_genome-scale_predicted_proteins_across_the_diversity_of_eukaryotic_life/12417881/2), KEGG (https://www.genome.jp/kegg/), Pfam (http://ftp.ebi.ac.uk/pub/databases/Pfam/releases/Pfam32.0/). The following environmental sequencing datasets were used for 18S rRNA gene analysis: Tara Oceans (https://zenodo.org/record/3768510#.Y1ZtKuzMI1I), protists in European coastal waters and sediments (https://doi.org/10.1111/1462-2920.12955), Autonomous Reef Monitoring Structures (ARMS) in Red Sea (https://doi.org/10.1038/s41598-018-26332-5), Stream biofilm eukaryotic assemblages (https://doi.org/10.1016/j.ecolind.2020.106225), Deep sea basin sediments (https://doi.org/10.1038/s42003-021-02012-5), eukaryotic plankton in reef environments in Panama (https://doi.org/10.1007/s00338-020-01979-7), eukaryote communities in a high-alpine lake (https://doi.org/10.1007/s12275-019-8668-8), mountain lake microbial communities (https://doi.org/10.1111/mec.15469), microbial eukaryotes in Lake Baikal (https://doi.org/10.1093/femsec/fix073). A 320-gene dataset was used for constructing alignments for phylogenomic analyses (https://static-content.springer.com/esm/art%3A10.1038%2Fs41467-021-22044-z/MediaObjects/41467_2021_22044_MOESM5_ESM.zip). The new taxa have been registered with the Zoobank database (http://zoobank.org/) under the following accession codes: urn:lsid:zoobank.org:act:9EE01A01-E294-415B-A36F-0FB4373183D0, urn:lsid:zoobank.org:act:A54BD0FB-7FA3-42CB-9D3D-2211FA657DC0, urn:lsid:zoobank.org:act:F6395E20-7BDF-4CBE-95FB-E4CE1E7B8185, urn:lsid:zoobank.org:act:F1E8545D-BAC1-44FF-9B6B-8FEE4AC028BB, urn:lsid:zoobank.org:act:66A5C066-890F-4F25-AAB6-5CDCE2028034, urn:lsid:zoobank.org:act:830A4372-62D9-4CE1-BFD8-9FE9EED67FED, urn:lsid:zoobank.org:act:DFE7080B-6201-455A-99CE-903103CBB049, urn:lsid:zoobank.org:act:A230EC14-DC4B-4F05-8D69-8FE0BAB3DE09, urn:lsid:zoobank.org:act:B8894608-40D4-4D16-A4D9-6F448614F22C and urn:lsid:zoobank.org:act:97B89F6F-72D6-482A-9EA7-88E5C63E6EB6.

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Acknowledgements

We thank M. Vermeij and the staff at the CARMABI research station for field sampling support; and N. Kosolapova for help with sample collection in the Arctic. This research was supported by grants from the Russian Foundation for Basic Research (to D.V.T., grant no. 20-34-70049), the Tyumen Oblast Government, as part of the West-Siberian Interregional Science and Education Center’s project no. 89-DON (2) (to D.V.T.), the Ministry of Science and Higher Education of the Russian Federation within the framework of the Federal Scientific and Technical Program for the Development of Genetic Technologies for 2019-2027 (agreement no. 075-15-2021-1345, unique identifier RF-193021X0012), the Gordon and Betty Moore Foundation (to P.J.K., https://doi.org/10.37807/GBMF9201), GenomeBC and the Natural Sciences and Engineering Research Council of Canada (to P.J.K., grant no. 2019-03994), and was carried out within the framework of state assignment no. 121051100102-2.

Author information

Author notes

  1. These authors contributed equally: Denis V. Tikhonenkov, Kirill V. Mikhailov, Ryan M. R. Gawryluk

  2. Deceased: Alexander P. Mylnikov

Authors and Affiliations

  1. Papanin Institute for Biology of Inland Waters, Russian Academy of Sciences, Borok, Russian Federation

    Denis V. Tikhonenkov, Artem O. Belyaev, Dmitry G. Zagumyonnyi, Anastasia S. Borodina, Kristina I. Prokina & Alexander P. Mylnikov

  2. AquaBioSafe Laboratory, University of Tyumen, Tyumen, Russian Federation

    Denis V. Tikhonenkov & Dmitry G. Zagumyonnyi

  3. Belozersky Institute for Physico-Chemical Biology, Lomonosov Moscow State University, Moscow, Russian Federation

    Kirill V. Mikhailov & Vladimir V. Aleoshin

  4. Kharkevich Institute for Information Transmission Problems, Russian Academy of Sciences, Moscow, Russian Federation

    Kirill V. Mikhailov & Vladimir V. Aleoshin

  5. Department of Biology, University of Victoria, Victoria, British Columbia, Canada

    Ryan M. R. Gawryluk

  6. Department of Zoology and Ecology, Penza State University, Penza, Russian Federation

    Artem O. Belyaev

  7. Department of Botany, University of British Columbia, Vancouver, British Columbia, Canada

    Varsha Mathur & Patrick J. Keeling

  8. Department of Zoology, University of Oxford, Oxford, UK

    Varsha Mathur

  9. Zoological Institute, Russian Academy of Sciences, Saint Petersburg, Russian Federation

    Sergey A. Karpov

  10. Department of Invertebrate Zoology, Faculty of Biology, Saint Petersburg State University, Saint Petersburg, Russian Federation

    Sergey A. Karpov

  11. Department of Zoology and Parasitology, Voronezh State University, Voronezh, Russian Federation

    Anastasia S. Borodina

  12. Ecologie Systématique Evolution, CNRS, Université Paris-Saclay, AgroParisTech, Gif-sur-Yvette, France

    Kristina I. Prokina

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  1. Denis V. Tikhonenkov
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Contributions

D.V.T., K.V.M., R.M.R.G. and P.J.K. designed the study. D.V.T. and A.P.M. discovered the organisms and isolated the cultures. D.V.T. generated material for sequencing. A.O.B., S.A.K., D.G.Z., A.S.B., K.I.P. and D.V.T. performed light and electron microscopy and cultured the cells. K.V.M. and R.M.R.G. performed transcriptomic analyses and phylogenetic analyses. V.M. and V.V.A. performed the environmental distribution analysis and phylogenetic analysis of the SSU rRNA. D.V.T., K.V.M., R.M.R.G. and P.J.K. wrote the manuscript with input from all of the authors.

Corresponding author

Correspondence to Denis V. Tikhonenkov.

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Extended data figures and tables

Extended Data Fig. 1 Outline of tree topologies obtained in the phylogenomic analyses and the geographical distribution of Provora.

(a) Maximum-likelihood tree topology obtained with the 320-gene dataset; nodes with support values below 100% (PMSF model, 100 replicates) are labelled red, and the corresponding values are provided next to the tree nodes; established eukaryotic groups with full support in the analysis are collapsed and shown in the tree schematically with triangles. (b) PhyloBayes consensus tree topology obtained using four analysis chains with the native 320-gene dataset; posterior probabilities are shown for tree nodes that fail to achieve full support in the analysis. (c) PhyloBayes consensus tree topology obtained with the Dayhoff 6-recoded 320-gene dataset; the low posterior probability (0.58 pp) for the union of Provora and Haptista reflects the marginal support for this group in all four analysis chains, rather than the lack of convergence between the chains (maxdiff = 0.27). (d) PhyloBayes consensus tree topology obtained with the SR4-recoded 320-gene dataset. (e) Geographical distribution of environmental sequences of 18S rRNA belonging to Provora.

Extended Data Fig. 2 Phylogenies with variable regions of 18S rRNA featuring identified environmental sequences belonging to Provora.

(a) Phylogenetic tree based on the V4 region of the 18S rRNA gene showing the diversity of environmental lineages of Provora. (b) Phylogenetic tree based on the V9 region of the 18S rRNA gene. The 18S rRNA of Provora described in this paper are shown in red. Environmental sequences related to the members of Provora are labelled in blue. Bootstrap values ≥ 90% are indicated with black circles at the tree nodes.

Extended Data Fig. 3 Conservation of functional categories and trophic mode prediction for the transcriptomes of Provora.

(a) Heatmap of annotated KEGG orthology entry counts (presence/absence data) for functional categories defined by BRITE in the transcriptomic data of Provora isolates and the genomic data of eukaryotic organisms; the counts only include entries inferred to be ancestral for eukaryotes by the Dollo parsimony principle: entries that only have hits in one of the major eukaryotic subdivisions (Diaphoretickes, Discoba or Amorphea) were excluded; the counts were normalized to the inferred ancestral eukaryotic KEGG orthologs. (b) Principal component analysis plot with gene ontology category scores for categories associated with free-living phagocytic organisms; (c) Prediction probabilities of trophic modes (phagocytosis, prototrophy, photosynthesis) in Provora isolates, conducted by the Trophic Mode Prediction Tool.

Extended Data Fig. 4 Maximum likelihood phylogenetic tree with eukaryotic members of the inositol trisphosphate receptor family, identified by the presence of a RyR and IP3R homology associated domain (RIHa, PF08454) and an ion channel domain (PF00520).

The phylogeny was reconstructed by IQ-TREE using an alignment with 396 eukaryotic sequences, spanning the RIHa and ion channel regions of the proteins; reconstruction was done under the best-fitting LG+F+R10 model of evolution, and node support was evaluated with 1000 UFBoot replicates; nodes with over 95% support are marked with black circles; clades uniting members of a single taxon are collapsed in the tree and labelled in accordance with their taxonomy; branches that belong to Provora are coloured red; protein domain architectures are displayed for the IP3R family sequences in Provora: Ins145_P3_rec (PF08709), MIR (PF02815), RIH (PF01365), RIHa (PF08454), Ion channel (PF00520).

Extended Data Fig. 5 Maximum likelihood phylogenetic tree with MACPF domain-containing proteins in Provora.

The phylogeny was reconstructed by IQ-TREE with the best-fitting WAG+F+R5 model of evolution; node support was evaluated with 1000 UFBoot replicates, and nodes with over 95% support are marked with black circles; clades uniting putatively orthologous MACPF sequences in Nibbleromonas species are collapsed; species name abbreviations: At – Ancoracysta twista, Nm – Nebulomonas marisrubri, Uf – Ubysseya fretuma, Na – Nibbleromonas arcticus, Nk – Nibbleromonas kosolapovi, Nc – Nibbleromonas curacaus, Nq – Nibbleromonas quarantinus; the domain architectures of MACPF proteins identified using SMART searches are shown; MACPF domains outlined with dotted lines correspond to findings below the default detection threshold.

Extended Data Fig. 6 Proportions of shared to total orthogroup counts in pairwise comparisons of eukaryotic organisms.

Arithmetic means of the proportions of shared orthogroups between pairs of genomes or transcriptomes are shown using a heatmap; the organisms are grouped using a tree, which summarizes the current concept of eukaryotic phylogeny; orthogroup inference for members of the Provora lineage relied on the transcriptomic data; the Provora species are labelled in red, and the corresponding intragroup comparisons are outlined with a red square in the heatmap.

Extended Data Fig. 7 Mitochondrial genome maps of nibblerids.

Nibblerid mitochondrial genomes are typically circular-mapping, and gene-rich. All maps were edited to arbitrarily start at the ccmA gene. Genes are colour-coded according to their functional classification, as shown in the legend.

Extended Data Fig. 8 Mitochondrial genome maps of the nebulids, Ancoracysta twista and Nebulomonas marisrubri.

Nebulid mitochondrial genomes are circular-mapping, but are presented in a linear format to facilitate comparison of gene order. Mitochondrial genomes of A. twista (NC_036491.1) and N. marisrubri each contain duplications due to the presence of inverted repeats. All maps were edited to arbitrarily start at the ccmA gene. Genes are colour-coded according to their functional classification, as shown in the legend.

Extended Data Fig. 9 Provoran mitochondrial genomes retain ancestral features, but their sizes are variable due to group-I intron accumulation.

(a) Secondary structure predictions of mitochondrion-encoded RNAse P RNAs from Ubysseya fretuma, Nibbleromonas quarantinus, and N. curacaus; genes encoding rnpB have been identified in a small and phylogenetically disparate collection of eukaryotes, and are often very dissimilar from their counterparts in Alphaproteobacteria. All nibblerid mitochondrial genomes described here encode rnpB, and bear a strong resemblance to bacterial and jakobid rnpB homologs. Nucleotides with black borders indicate positions that are found in eubacterial consensus and jakobid rnpB homologs, and conserved helices are noted (P1-19). (b) Group-I introns that encode LAGLIDADG homing endonucleases are present in mitochondrial genomes in the genus Nibbleromonas; phylogenetic relationships between intron-encoded homing endonucleases of cox1 are shown as an exemplar of introns presence in nibblerid mitochondrial genomes. Some homologous homing endonucleases are present in the same position of N. kosolapovi, N. quarantinus and N. curacaus cox1 (e.g., intron 1 of each species), indicating that they were present in their common ancestor and have been broadly retained. Other introns are found in only N. kosolapovi, and one of N. quarantinus or N. curacaus, suggesting lineage-specific intron loss. In contrast, the endonuclease encoded in intron 6 of N. kosolapovi cox1 was likely gained via lateral transfer from fungi, where the endonuclease is also encoded by cox1 introns.

Extended Data Fig. 10 Maximum likelihood phylogenetic tree of nucleus-encoded holocytochrome c synthase (HCCS) from diverse eukaryotes (140 sites, LG+R7 model, 1000 ultrafast bootstraps).

A prior report demonstrated that the nebulid Ancoracysta twista retains both mitochondrion-encoded type-I and nucleus-encoded type-III cytochrome c maturation systems. Although nibblerids retain only the former, multiple strains of the newly described nebulid, Nebulomonas marisrubri, also have both types of cytochrome c maturation systems. In our phylogenetic reconstruction, N. marisrubri and A. twista HCCS proteins are monophyletic, though with only moderate statistical support. One thousand ultrafast bootstrap replicates were performed as a measure of statistical support. For clarity, bipartitions receiving full statistical support are represented by black circles and values less than 70 are not presented.

Supplementary information

Supplementary Discussion

Formal taxonomic descriptions and details of morphology. This file provides formal taxonomic descriptions of the new supergroup of eukaryotes Provora and all its taxa.

Reporting Summary

Supplementary Table 1

Support values (PMSF bootstrap with 100 replicates) for important tree bipartitions in the maximum-likelihood analysis with datasets generated by progressive removal of fast-evolving sites.

Supplementary Table 2

Approximately unbiased test P values for hypotheses, summarizing possible phylogenetic placements of Provora and Hemimastigophora, evaluated in a series of datasets generated by progressive removal of fast-evolving sites.

Supplementary Table 3

Mitochondrial genome characteristics across Provora. Statistics relating to the size, composition and content of nibblerid and nebulid mitochondrial genomes are presented. All genomes encode a similar number of proteins and RNAs, and are compositionally biased towards A + T, as frequently observed in mitochondria. The conformation of the N. kosolapovi mitochondrial genome could not be determined due to incomplete coverage.

Supplementary Data 1

List of 18S rRNA surveys from diverse environments used for analysis.

Supplementary Data 2

Table of KEGG orthologues identified by the KEGG automatic annotation server in the transcriptomic data of Provora isolates and the proteomes of other eukaryotic species; the KEGG orthology entries are defined and arranged according to the KEGG BRITE classification system; a measure of over- or under-representation is provided for each entry to highlight entries enriched (positive) or depleted (negative) in Provora relative to other eukaryotes.

Supplementary Data 3

Table of Pfam domains identified in the transcriptomic data of Provora isolates and the collection of proteomes in the EukProt database; the numbers in the table represent the counts of proteins with the corresponding Pfam domain rather than the total counts of the domain itself; a measure of over- or under-representation is provided for each Pfam entry to highlight entries enriched (positive) or depleted (negative) in Provora relative to the EukProt proteomes.

Supplementary Data 4

List of OTUs used in the analyses and the corresponding sources of sequencing data.

Supplementary Video 1

Feeding of N. kosolapovi on stramenopile prey. The video is accelerated by a factor of 2.

Supplementary Video 2

Biting off and engulfing part of the prey’s cell (P. sorokini) by the cell of N. quarantinus. The video is accelerated 10 times from the 20th second.

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Tikhonenkov, D.V., Mikhailov, K.V., Gawryluk, R.M.R. et al. Microbial predators form a new supergroup of eukaryotes. Nature 612, 714–719 (2022). https://doi.org/10.1038/s41586-022-05511-5

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