Metabolic marker gene mining provides insight in global mcrA diversity and, coupled with targeted genome reconstruction, sheds further light on metabolic potential of the Methanomassiliicoccales
- Creators
-
Speth, Daan R.
-
Orphan, Victoria J.
Abstract
Over the past years, metagenomics has revolutionized our view of microbial diversity. Moreover, extracting near-complete genomes from metagenomes has led to the discovery of known metabolic traits in unsuspected lineages. Genome-resolved metagenomics relies on assembly of the sequencing reads and subsequent binning of assembled contigs, which might be hampered by strain heterogeneity or low abundance of a target organism. Here we present a complementary approach, metagenome marker gene mining, and use it to assess the global diversity of archaeal methane metabolism through the mcrA gene. To this end, we have screened 18,465 metagenomes for the presence of reads matching a database representative of all known mcrA proteins and reconstructed gene sequences from the matching reads. We use our mcrA dataset to assess the environmental distribution of the Methanomassiliicoccales and reconstruct and analyze a draft genome belonging to the 'Lake Pavin cluster', an uncultivated environmental clade of the Methanomassiliicoccales. Analysis of the 'Lake Pavin cluster' draft genome suggests that this organism has a more restricted capacity for hydrogenotrophic methylotrophic methanogenesis than previously studied Methanomassiliicoccales, with only genes for growth on methanol present. However, the presence of the soluble subunits of methyltetrahydromethanopterin:CoM methyltransferase (mtrAH) provide hypothetical pathways for methanol fermentation, and aceticlastic methanogenesis that await experimental verification. Thus, we show that marker gene mining can enhance the discovery power of metagenomics, by identifying novel lineages and aiding selection of targets for in-depth analyses. Marker gene mining is less sensitive to strain heterogeneity and has a lower abundance threshold than genome-resolved metagenomics, as it only requires short contigs and there is no binning step. Additionally, it is computationally cheaper than genome resolved metagenomics, since only a small subset of reads needs to be assembled. It is therefore a suitable approach to extract knowledge from the many publicly available sequencing projects.
Additional Information
© 2018 Speth and Orphan. Distributed under Creative Commons CC-BY 4.0. The authors declare there are no competing interests. Author Contributions: Daan R. Speth conceived and designed the experiments, performed the experiments, analyzed the data, contributed reagents/materials/analysis tools, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft. Victoria J. Orphan conceived and designed the experiments, authored or reviewed drafts of the paper, approved the final draft. Data Availability: The following information was supplied regarding data availability: https://github.com/dspeth/bioinfo_scripts/tree/master/metagenome_screening. This manuscript is based upon work supported by the US Department of Energy, Office of Science, Office of Biological and Environmental Research under award number DE-SC0016469 to Victoria J. Orphan. In addition, Daan R. Speth was supported by NWO Rubicon 019.153LW.039. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. We thank Woody Fischer and Connor Skennerton for helpful discussion and Grayson Chadwick for critically reading the manuscript.Attached Files
Published - peerj-5614.pdf
Submitted - 328906.full.pdf
Supplemental Material - Supplemental_figure_1.pdf
Supplemental Material - Supplemental_figure_2.pdf
Supplemental Material - Supplemental_figure_3.pdf
Supplemental Material - Supplemental_figure_4.pdf
Supplemental Material - Supplemental_file_1_2016_06_16_metagenomes_NOT_human_gut_oral_SRR_Acc_List.txt
Supplemental Material - Supplemental_file_2_2016_06_21_MGRAST_public_MT_WGS_IDs.txt
Supplemental Material - Supplemental_file_3_reconstructed_mcrA_Nuc_seq.fna.txt
Supplemental Material - Supplemental_file_4_reconstructed_mcrA_AA_seq.faa.txt
Supplemental Material - Supplemental_file_5_MALP_prokka.tar.gz
Files
Name | Size | Download all |
---|---|---|
md5:af7014b417746344c93f0d4eb06f5911
|
1.3 MB | Preview Download |
md5:b404e0b67acd6eb77ef19a338b8a46fb
|
6.0 MB | Preview Download |
md5:c9218d9930071ed4cd49a14da943c0bf
|
2.1 MB | Preview Download |
md5:e3a31422d5215b2c163ab23a6d560ba6
|
2.4 MB | Preview Download |
md5:5b5866449c681d376008d1539aac2296
|
946.1 kB | Preview Download |
md5:604df13cd841f5b871a00017dd326099
|
5.8 MB | Preview Download |
md5:a25e6914bcdb3921a41b703d698c8eb4
|
469.7 kB | Preview Download |
md5:64fb81f21cefbb821862877c045c163f
|
113.2 kB | Preview Download |
md5:95d7a28fda4906e99562b9922ade792b
|
93.8 kB | Preview Download |
md5:fbd722e3f15a1b51aa640f0183aa1e64
|
4.7 MB | Download |
md5:11fd508b726b7cdbf30d11f4ce3c189e
|
1.9 MB | Preview Download |
Additional details
- Alternative title
- Metabolic marker gene mining provides insight in global mcrA diversity and, coupled with targeted genome reconstruction, sheds light on metabolic versatility of the Methanomassiliicoccales
- PMCID
- PMC6147122
- Eprint ID
- 89965
- Resolver ID
- CaltechAUTHORS:20180926-133207423
- Department of Energy (DOE)
- DE-SC0016469
- Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO)
- 019.153LW.039
- Created
-
2018-09-26Created from EPrint's datestamp field
- Updated
-
2023-06-02Created from EPrint's last_modified field
- Caltech groups
- Division of Geological and Planetary Sciences (GPS)