Diversity and environmental distribution of Asgard archaea in shallow saline sediments

. 2025 ; 16 () : 1549128. [epub] 20250318

Status PubMed-not-MEDLINE Jazyk angličtina Země Švýcarsko Médium electronic-ecollection

Typ dokumentu časopisecké články

Perzistentní odkaz   https://www.medvik.cz/link/pmid40170918

In recent years, our understanding of archaeal diversity has greatly expanded, especially with the discovery of new groups like the Asgard archaea. These archaea show diverse phylogenetic and genomic traits, enabling them to thrive in various environments. Due to their close relationship to eukaryotes, a large number of metagenomic studies have been performed on Asgard archaea. Research on the fine scale distribution, diversity and quantification in saline aquatic sediments where they mostly occur, has, however, remained scarce. In this study, we investigated depths of shallow saline sediment cores from three distinct European environments: the Baltic Sea near Hiddensee, the coastal Lake Techirghiol in Romania, and an estuarine canal in Piran, Slovenia. Based on 16S rDNA amplicon sequencing, we observe variation in the relative abundance and occurrence of at least seven different Asgard groups that are distinct between the three environments and in their depth distribution. Lokiarchaeia and Thorarchaeia emerge as dominant Asgard groups across all sites, reaching maximal relative abundances of 2.28 and 2.68% of the total microbial communities respectively, with a maximal abundance of all Asgard reaching approx. 5.21% in Hiddensee. Quantitative PCR assays provide insights into the absolute abundance of Lokiarchaeia, supporting distinct patterns of distribution across depths in different sediments. Co-occurrence network analysis indicates distinct potential microbial partners across different Asgard groups. Overall, our study shows that Asgard archaea are found as a stable component in shallow sediment layers and have considerably diversified on macro- and microscales.

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Adam P., Borrel G., Brochier-Armanet C., Gribaldo S. (2017). The growing tree of Archaea: new perspectives on their diversity, evolution and ecology. ISME J. 11, 2407–2425. doi: 10.1038/ismej.2017.122, PMID: PubMed DOI PMC

Ali A. (2023). DADA2 formatted 16S rRNA gene sequences for both bacteria & archaea (4.4) [Data set]. Geneva, Switzerland: Zenodo.

Austrian Standards International (2019). ÖNORM L 1061–2:2019-03-01. Physical analysis of soils – Determination of particle size distribution in mineral soils used for agriculture and forestry – Part 2: Fine soil. Vienna: Austrian Standards International.

Baker B. J., De Anda V., Seitz K. W., Dombrowski N., Santoro A. E., Lloyd K. G. (2020). Diversity, ecology and evolution of Archaea. Nat. Microbiol. 5, 887–900. doi: 10.1038/s41564-020-0715-z PubMed DOI

Bulzu P. A., Andrei A. Ş., Salcher M. M., Mehrshad M., Inoue K., Kandori H., et al. . (2019). Casting light on Asgardarchaeota metabolism in a sunlit microoxic niche. Nat. Microbiol. 4, 1129–1137. doi: 10.1038/s41564-019-0404-y, PMID: PubMed DOI

Cai M., Liu Y., Yin X., Zhou Z., Friedrich M. W., Richter-Heitmann T., et al. . (2020). Diverse Asgard archaea including the novel phylum Gerdarchaeota participate in organic matter degradation. Sci. China Life Sci. 63, 886–897. doi: 10.1007/s11427-020-1679-1, PMID: PubMed DOI

Cai M., Richter-Heitmann T., Yin X., Huang W. C., Yang Y., Zhang C., et al. . (2021). Ecological features and global distribution of Asgard archaea. Sci. Total Environ. 758:143581. doi: 10.1016/j.scitotenv.2020.143581, PMID: PubMed DOI

Callahan B. J., McMurdie P. J., Rosen M. J., Han A. W., Johnson A. J. A., Holmes S. P. (2016). DADA2: high-resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583. doi: 10.1038/nmeth.3869, PMID: PubMed DOI PMC

Caporaso J. G., Lauber C. L., Walters W. A., Berg-Lyons D., Lozupone C. A., Turnbaugh P. J., et al. . (2011). Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. USA 108, 4516–4522. doi: 10.1073/pnas.1000080107, PMID: PubMed DOI PMC

Eme L., Tamarit D., Caceres E. F., Stairs C. W., de Anda V., Schön M. E., et al. . (2023). Inference and reconstruction of the heimdallarchaeial ancestry of eukaryotes. Nature 618, 992–999. doi: 10.1038/s41586-023-06186-2, PMID: PubMed DOI PMC

Farag I. F., Biddle J. F., Zhao R., Martino A. J., House C. H., León-Zayas R. I. (2020). Metabolic potentials of archaeal lineages resolved from metagenomes of deep Costa Rica sediments. ISME J. 14, 1345–1358. doi: 10.1038/s41396-020-0615-5, PMID: PubMed DOI PMC

Friedman J., Alm E. J. (2012). Inferring correlation networks from genomic survey data. PLoS Comput. Biol. 8:e1002687. doi: 10.1371/journal.pcbi.1002687, PMID: PubMed DOI PMC

Guindon S., Dufayard J. F., Lefort V., Anisimova M., Hordijk W., Gascuel O. (2010). New algorithms and methods to estimate maximum-likelihood phylogenies: assessing the performance of PhyML 3.0. Syst. Biol. 59, 307–321. doi: 10.1093/sysbio/syq010 PubMed DOI

Hatano T., Palani S., Papatziamou D., Salzer R., Souza D. P., Tamarit D., et al. . (2022). Asgard archaea shed light on the evolutionary origins of the eukaryotic ubiquitin-ESCRT machinery. Nat. Commun. 13:3398. doi: 10.1038/s41467-022-30656-2, PMID: PubMed DOI PMC

Hug L. A., Castelle C. J., Wrighton K. C., Thomas B. C., Sharon I., Frischkorn K. R., et al. . (2013). Community genomic analyses constrain the distribution of metabolic traits across the Chloroflexi phylum and indicate roles in sediment carbon cycling. Microbiome 1, 1–17. doi: 10.1186/2049-2618-1-22, PMID: PubMed DOI PMC

Imachi H., Nobu M. K., Kato S., Takaki Y., Miyazaki M., Miyata M., et al. . (2024). Promethearchaeum syntrophicum gen. Nov., sp. nov., an anaerobic, obligately syntrophic archaeon, the first isolate of the lineage “Asgard” archaea, and proposal of the new archaeal phylum Promethearchaeota phyl. Nov. and kingdom Promethearchaeati regn. Nov. Int. J. Syst. Evol. Microbiol. 74:006435. doi: 10.1099/ijsem.0.006435, PMID: PubMed DOI PMC

Imachi H., Nobu M. K., Nakahara N., Morono Y., Ogawara M., Takaki Y., et al. . (2020). Isolation of an archaeon at the prokaryote–eukaryote interface. Nature 577, 519–525. doi: 10.1038/s41586-019-1916-6, PMID: PubMed DOI PMC

Inagaki F., Suzuki M., Takai K., Oida H., Sakamoto T., Aoki K., et al. . (2003). Microbial communities associated with geological horizons in coastal subseafloor sediments from the Sea of Okhotsk. Appl. Environ. Microbiol. 69, 7224–7235. doi: 10.1128/AEM.69.12.7224-7235.2003, PMID: PubMed DOI PMC

Jorgensen S. L., Hannisdal B., Lanzén A., Baumberger T., Flesland K., Fonseca R., et al. . (2012). Correlating microbial community profiles with geochemical data in highly stratified sediments from the Arctic Mid-Ocean ridge. Proc. Natl. Acad. Sci. USA 109:E2846-55. doi: 10.1073/pnas.1207574109, PMID: PubMed DOI PMC

Jørgensen S. L., Thorseth I. H., Pedersen R. B., Baumberger T., Schleper C. (2013). Quantitative and phylogenetic study of the Deep Sea archaeal group in sediments of the Arctic mid-ocean spreading ridge. Front. Microbiol. 4:299. doi: 10.3389/fmicb.2013.00299, PMID: PubMed DOI PMC

Kalyaanamoorthy S., Minh B. Q., Wong T. K. F., von Haeseler A., Jermiin L. S. (2017). ModelFinder: fast model selection for accurate phylogenetic estimates. Nat. Methods 14, 587–589. doi: 10.1038/nmeth.4285, PMID: PubMed DOI PMC

Katoh K., Standley D. M. (2013). MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol. Biol. Evol. 30, 772–780. doi: 10.1093/molbev/mst010 PubMed DOI PMC

Klindworth A., Pruesse E., Schweer T., Peplies J., Quast C., Horn M., et al. . (2012). Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 41:e1. doi: 10.1093/nar/gks808 PubMed DOI PMC

Lagkouvardos I., Joseph D., Kapfhammer M., Giritli S., Horn M., Haller D., et al. . (2016). IMNGS: a comprehensive open resource of processed 16S rRNA microbial profiles for ecology and diversity studies. Sci. Rep. 6:33721. doi: 10.1038/srep33721, PMID: PubMed DOI PMC

Letunic I., Bork P. (2021). Interactive tree of life (iTOL) v5: an online tool for phylogenetic tree display and annotation. Nucleic Acids Res. 49, W293–W296. doi: 10.1093/nar/gkab301, PMID: PubMed DOI PMC

Liu Y., Makarova K. S., Huang W. C., Huang W. C., Wolf Y. I., Nikolskaya A. N., et al. . (2021). Expanded diversity of Asgard archaea and their relationships with eukaryotes. Nature 593, 553–557. doi: 10.1038/s41586-021-03494-3, PMID: PubMed DOI PMC

Liu Y., Zhou Z., Pan J., Baker B. J., Gu J. D., Li M. (2018). Comparative genomic inference suggests mixotrophic lifestyle for Thorarchaeota. ISME J. 12, 1021–1031. doi: 10.1038/s41396-018-0060-x, PMID: PubMed DOI PMC

Lopez-Garcia P., Moreira D. (2020). The Syntrophy hypothesis for the origin of eukaryotes revisited. Nat. Microbiol. 5, 655–667. doi: 10.1038/s41564-020-0710-4 PubMed DOI

Lu R., Gao Z. M., Li W. L., Wei Z. F., Wei T. S., Huang J. M., et al. . (2021). Asgard archaea in the Haima cold seep: spatial distribution and genomic insights. Deep Sea Res. I Oceanogr. Res. Pap. 170:103489. doi: 10.1016/j.dsr.2021.103489 DOI

MacLeod F., Kindler G. S., Wong H. L., Chen R., Burns B. P. (2019). Asgard archaea: diversity, function, and evolutionary implications in a range of microbiomes. AIMS Microbiol. 5, 48–61. doi: 10.3934/microbiol.2019.1.48 PubMed DOI PMC

Manoharan L., Kozlowski J. A., Murdoch R. W., Löffler F. E., Sousa F. L., Schleper C. (2019). Metagenomes from coastal marine sediments give insights into the ecological role and cellular features of Loki – and Thorarchaeota. MBio 10, 1–15. doi: 10.1128/mBio.02509-19, PMID: PubMed DOI PMC

Martin M. (2011). Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12. doi: 10.14806/ej.17.1.200 DOI

McMurdie P. J., Holmes S. (2013). Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8:e61217. doi: 10.1371/journal.pone.0061217, PMID: PubMed DOI PMC

Minh B. Q., Schmidt H. A., Chernomor O., Schrempf D., Woodhams M. D., von Haeseler A., et al. . (2020). IQ-TREE 2: new models and efficient methods for phylogenetic inference in the genomic era. Mol. Biol. Evol. 37, 1530–1534. doi: 10.1093/molbev/msaa015 PubMed DOI PMC

Orsi W. D., Vuillemin A., Rodriguez P., Coskun Ö. K., Gomez-Saez G. V., Lavik G., et al. . (2020). Metabolic activity analyses demonstrate that Lokiarchaeon exhibits homoacetogenesis in sulfidic marine sediments. Nat. Microbiol. 5, 248–255. doi: 10.1038/s41564-019-0630-3, PMID: PubMed DOI

Parks D. H., Chuvochina M., Rinke C., Mussig A. J., Chaumeil P. A., Hugenholtz P. (2022). GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. Nucleic Acids Res. 50, D785–D794. doi: 10.1093/nar/gkab776, PMID: PubMed DOI PMC

Ramírez G. A., McKay L. J., Fields M. W., Buckley A., Mortera C., Hensen C., et al. . (2020). The Guaymas Basin subseafloor sedimentary archaeome reflects complex environmental histories. iScience 23:101459. doi: 10.1016/j.isci.2020.101459, PMID: PubMed DOI PMC

Rinke C., Chuvochina M., Mussig A. J., Chaumeil P. A., Davín A. A., Waite D. W., et al. . (2021). A standardized archaeal taxonomy for the genome taxonomy database. Nat. Microbiol. 6, 946–959. doi: 10.1038/s41564-021-00918-8, PMID: PubMed DOI

Rodrigues-Oliveira T., Wollweber F., Ponce-Toledo R. I., Xu J., Rittmann S. K. M. R., Klingl A., et al. . (2023). Actin cytoskeleton and complex cell architecture in an Asgard archaeon. Nature 613, 332–339. doi: 10.1038/s41586-022-05550-y, PMID: PubMed DOI PMC

Saghaï A., Gutiérrez-Preciado A., Deschamps P., Moreira D., Bertolino P., Ragon M., et al. . (2017). Unveiling microbial interactions in stratified mat communities from a warm saline shallow pond. Environ. Microbiol. 19, 2405–2421. doi: 10.1111/1462-2920.13754 PubMed DOI PMC

Seitz K. W., Dombrowski N., Eme L., Spang A., Lombard J., Sieber J. R., et al. . (2019). Asgard archaea capable of anaerobic hydrocarbon cycling. Nat. Commun. 10:1822. doi: 10.1038/s41467-019-09364-x, PMID: PubMed DOI PMC

Seitz K., Lazar C., Hinrichs K. U., Teske A. P., Baker B. J. (2016). Genomic reconstruction of a novel, deeply branched sediment archaeal phylum with pathways for acetogenesis and sulfur reduction. ISME J. 10, 1696–1705. doi: 10.1038/ismej.2015.233, PMID: PubMed DOI PMC

Shannon P., Markiel A., Ozier O., Baliga N. S., Wang J. T., Ramage D., et al. . (2003). Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res. 13, 2498–2504. doi: 10.1101/gr.1239303, PMID: PubMed DOI PMC

Spang A., Saw J. H., Jørgensen S. L., Zaremba-Niedzwiedzka K., Martijn J., Lind A. E., et al. . (2015). Complex archaea that bridge the gap between prokaryotes and eukaryotes. Nature 521, 173–179. doi: 10.1038/nature14447, PMID: PubMed DOI PMC

Spang A., Stairs C. W., Dombrowski N., Eme L., Lombard J., Caceres E. F., et al. . (2019). Proposal of the reverse flow model for the origin of the eukaryotic cell based on comparative analyses of Asgard archaeal metabolism. Nat. Microbiol. 4, 1138–1148. doi: 10.1038/s41564-019-0406-9, PMID: PubMed DOI

Sun J., Evans P. N., Gagen E. J., Woodcroft B. J., Hedlund B. P., Woyke T., et al. . (2021). Recoding of stop codons expands the metabolic potential of two novel Asgardarchaeota lineages. ISME Commun. 1:30. doi: 10.1038/s43705-021-00032-0, PMID: PubMed DOI PMC

Tahon G., Geesink P., Ettema T. G. (2021). Expanding archaeal diversity and phylogeny: past, present, and future. Ann. Rev. Microbiol. 75, 359–381. doi: 10.1146/annurev-micro-040921-050212, PMID: PubMed DOI

Tamarit D., Köstlbacher S., Appler K. E., Panagiotou K., de Anda V., Rinke C., et al. . (2024). Description of Asgardarchaeum abyssi gen. Nov. spec. Nov., a novel species within the class Asgardarchaeia and phylum Asgardarchaeota in accordance with the SeqCode. Syst. Appl. Microbiol. 47:126525. doi: 10.1016/j.syapm.2024.126525, PMID: PubMed DOI

Tang Z.-Z., Chen G., Alekseyenko A. V. (2016). PERMANOVA-S: association test for microbial community composition that accommodates confounders and multiple distances. Bioinformatics 32, 2618–2625. doi: 10.1093/bioinformatics/btw311, PMID: PubMed DOI PMC

Vitorino I. R., Lage O. M. (2022). The Planctomycetia: an overview of the currently largest class within the phylum Planctomycetes. Antonie Van Leeuwenhoek 115, 169–201. doi: 10.1007/s10482-021-01699-0, PMID: PubMed DOI

Wickham H. (2011). ggplot2. WIREs Comp Stat. 3, 180–185. doi: 10.1002/wics.147 DOI

Wong H. L., White R. A., Visscher P. T., Charlesworth J. C., Vázquez-Campos X., Burns B. P. (2018). Disentangling the drivers of functional complexity at the metagenomic level in Shark Bay microbial mat microbiomes. ISME J. 12, 2619–2639. doi: 10.1038/s41396-018-0208-8, PMID: PubMed DOI PMC

Yin X., Cai M., Liu Y., Zhou G., Richter-Heitmann T., Aromokeye D. A., et al. . (2021). Subgroup level differences of physiological activities in marine Lokiarchaeota. ISME J. 15, 848–861. doi: 10.1038/s41396-020-00818-5, PMID: PubMed DOI PMC

Zaremba-Niedzwiedzka K., Caceres E. F., Saw J. H., Bäckström D., Juzokaite L., Vancaester E., et al. . (2017). Asgard archaea illuminate the origin of eukaryotic cellular complexity. Nature 541, 353–358. doi: 10.1038/nature21031, PMID: PubMed DOI

Zhang C. J., Chen Y. L., Sun Y. H., Pan J., Cai M. W., Li M. (2021). Diversity, metabolism and cultivation of archaea in mangrove ecosystems. Mar. Life Sci. Technol. 3, 252–262. doi: 10.1007/s42995-020-00081-9, PMID: PubMed DOI PMC

Zhao R., Biddle J. F. (2021). Helarchaeota and co-occurring sulfate-reducing bacteria in subseafloor sediments from the Costa Rica margin. ISME Commun. 1:25. doi: 10.1038/s43705-021-00027-x, PMID: PubMed DOI PMC

Zou D., Liu H., Li M. (2020). Community, distribution, and ecological roles of estuarine Archaea. Front. Microbiol. 11:2060. doi: 10.3389/fmicb.2020.02060, PMID: PubMed DOI PMC

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