Human gut archaea collection from Estonian population

References

Almeida, A. et al. A unified catalog of 204,938 reference genomes from the human gut microbiome. Nat. Biotechnol. 39, 105–114, https://doi.org/10.1038/s41587-020-0603-3 (2021).

Google Scholar
Chibani, C. M. et al. A catalogue of 1,167 genomes from the human gut archaeome. Nat Microbiol 7, 48–61 (2021).

Google Scholar
Kumpitsch, C. et al. Reduced B12 uptake and increased gastrointestinal formate are associated with archaeome-mediated breath methane emission in humans. Microbiome 9, 193 (2021).

Google Scholar
Attaluri, A., Jackson, M., Valestin, J. & Rao, S. S. Methanogenic Flora Is Associated With Altered Colonic Transit but Not Stool Characteristics in Constipation Without IBS. American Journal of Gastroenterology 105, 1407–1411 (2010).

Google Scholar
Kuehnast, T. et al. Exploring the human archaeome: its relevance for health and disease, and its complex interplay with the human immune system. The FEBS Journal febs. 17123, https://doi.org/10.1111/febs.17123 (2024).
Basseri, R. J. et al. Intestinal Methane Production in Obese Individuals Is Associated with a Higher Body Mass Index.
Ghoshal, U., Shukla, R., Srivastava, D. & Ghoshal, U. C. Irritable Bowel Syndrome, Particularly the Constipation-Predominant Form, Involves an Increase in Methanobrevibacter smithii, Which Is Associated with Higher Methane Production. Gut and Liver 10, 932–938 (2016).

Google Scholar
Li, T. et al. Multi-Cohort Analysis Reveals Altered Archaea in Colorectal Cancer Fecal Samples Across Populations. Gastroenterology 168(3), 525–538.e2 (2025).

Google Scholar
Mathur, R. et al. Methane and Hydrogen Positivity on Breath Test Is Associated With Greater Body Mass Index and Body Fat. The Journal of Clinical Endocrinology & Metabolism 98, E698–E702 (2013).

Google Scholar
Ghavami, S. B. et al. Alterations of the human gut Methanobrevibacter smithii as a biomarker for inflammatory bowel diseases. Microbial Pathogenesis 117, 285–289 (2018).

Google Scholar
Mbakwa, C. A. et al. Gut colonization with methanobrevibacter smithii is associated with childhood weight development. Obesity 23, 2508–2516 (2015).

Google Scholar
Aasmets, O., Krigul, K. L., Lüll, K., Metspalu, A. & Org, E. Gut metagenome associations with extensive digital health data in a volunteer-based Estonian microbiome cohort. Nat. Commun. 13, 869, https://doi.org/10.1038/s41467-022-28464-9 (2022).

Google Scholar
Li, D., Liu, C.-M., Luo, R., Sadakane, K. & Lam, T.-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics 31, 1674–1676, https://doi.org/10.1093/bioinformatics/btv033 (2015).

Google Scholar
Kang, D. D. et al. MetaBAT 2: an adaptive binning algorithm for robust and efficient genome reconstruction from metagenome assemblies. PeerJ 7, e7359, https://doi.org/10.7717/peerj.7359 (2019).

Google Scholar
Nissen, J. N. et al. Improved metagenome binning and assembly using deep variational autoencoders. Nat. Biotechnol. 39, 555–560, https://doi.org/10.1038/s41587-020-00777-4 (2021).

Google Scholar
Sieber, C. M. K. et al. Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy. Nat. Microbiol. 3, 836–843, https://doi.org/10.1038/s41564-018-0171-1 (2018).

Google Scholar
Olm, M. R., Brown, C. T., Brooks, B. & Banfield, J. F. dRep: a tool for fast and accurate genomic comparisons that enables improved genome recovery from metagenomes through de-replication. ISME J. 11, 2864–2868, https://doi.org/10.1038/ismej.2017.126 (2017).

Google Scholar
Chaumeil, P.-A., Mussig, A. J., Hugenholtz, P. & Parks, D. H. GTDB-Tk v2: memory friendly classification with the Genome Taxonomy Database. http://biorxiv.org/lookup/doi/10.1101/2022.07.11.499641, https://doi.org/10.1101/2022.07.11.499641 (2022).
Parks, D.H., et al GTDB: an ongoing census of bacterial and archaeal diversity through a phylogenetically consistent, rank normalized and complete genome-based taxonomy. Nucleic Acids Res. https://doi.org/10.1093/nar/gkab776 (2021).
Nayfach, S., Shi, Z. J., Seshadri, R., Pollard, K. S. & Kyrpides, N. C. New insights from uncultivated genomes of the global human gut microbiome. Nature 568, 505–510, https://doi.org/10.1038/s41586-019-1058-x (2019).

Google Scholar
Chklovski, A., Parks, D. H., Woodcroft, B. J. & Tyson, G. W. CheckM2: a rapid, scalable and accurate tool for assessing microbial genome quality using machine learning. http://biorxiv.org/lookup/doi/10.1101/2022.07.11.499243, https://doi.org/10.1101/2022.07.11.499243 (2022).
Elkins, J. G. et al. A korarchaeal genome reveals insights into the evolution of the Archaea. Proc. Natl. Acad. Sci. USA. 105, 8102–8107 (2008).

Google Scholar
Orakov, A. N. et al. GUNC: detection of chimerism and contamination in prokaryotic genomes. Genome Biology 22, 178–178 (2021).

Google Scholar
Shen, W., Le, S., Li, Y. & Hu, F. SeqKit: A Cross-Platform and Ultrafast Toolkit for FASTA/Q File Manipulation. PLoS ONE 11, e0163962 (2016).

Google Scholar
Lü, Z. & Lu, Y. Methanocella conradii sp. nov., a Thermophilic, Obligate Hydrogenotrophic Methanogen, Isolated from Chinese Rice Field Soil. PLoS ONE 7, e35279 (2012).

Google Scholar
Seemann, T. Prokka: rapid prokaryotic genome annotation. Bioinformatics 30, 2068–2069 (2014).

Google Scholar
McKinney, W. Data Structures for Statistical Computing Python. 56–61, https://doi.org/10.25080/Majora-92bf1922-00a (Austin, Texas, 2010).
Hunter, J. D. Matplotlib: A 2D Graphics Environment. Comput. Sci. Eng. 9, 90–95 (2007).

Google Scholar
Waskom, M. seaborn: statistical data visualization. JOSS 6, 3021 (2021).

Google Scholar
ENA European Nucleotide Archive https://identifiers.org/ena.embl:PRJEB81541 (2024).
Pantiukh, P. & Org, E. EstMB MAGdb Archaea-273. Figshare https://doi.org/10.6084/m9.figshare.30920087 (2025).
Pantiukh, P. & Org, E. Archaea ESTrep-21. Figshare https://doi.org/10.6084/m9.figshare.30920126 (2025).
Pantiukh, P. & Org, E. Archaea. Prokka annotation. Figshare https://doi.org/10.6084/m9.figshare.29329166 (2025).