RIM-DB: a taxonomic framework for community structure analysis of methanogenic archaea from the rumen and other intestinal environments
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Methane is formed by methanogenic archaea in the rumen as one of the end products of feed fermentation in the ruminant digestive tract. To develop strategies to mitigate anthropogenic methane emissions due to ruminant farming, and to understand rumen microbial differences in animal feed conversion efficiency, it is essential that methanogens can be identified and taxonomically classified with high accuracy. Currently available taxonomic frameworks offer only limited resolution beyond the genus level for taxonomic assignments of sequence data stemming from high throughput sequencing technologies. Therefore, we have developed a QIIME-compatible database (DB) designed for species-level taxonomic assignment of 16S rRNA gene amplicon data targeting methanogenic archaea from the rumen, and from animal and human intestinal tracts. Called RIM-DB (Rumen and Intestinal Methanogen-DB), it contains a set of 2,379 almost full-length chimera-checked 16S rRNA gene sequences, including 20 previously unpublished sequences from isolates from three different orders. The taxonomy encompasses the recently-proposed seventh order of methanogens, the Methanomassiliicoccales, and allows differentiation between defined groups within this order. Sequence reads from rumen contents from a range of ruminant-diet combinations were taxonomically assigned using RIM-DB, Greengenes and SILVA. This comparison clearly showed that taxonomic assignments with RIM-DB resulted in the most detailed assignment, and only RIM-DB taxonomic assignments allowed methanogens to be distinguished taxonomically at the species level. RIM-DB complements the use of comprehensive databases such as Greengenes and SILVA for community structure analysis of methanogens from the rumen and other intestinal environments, and allows identification of target species for methane mitigation strategies.
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Construction of rumen microbiome databases such as RIM-DB, the ureC database, and AF-RefSeq drastically improves ability to monitor rumen microbial diversity.
“Also the construction of rumen microbiome databases to aid accurate taxonomical assignment, such as RIM-DB (for methanogens; Seedorf et al., 2014), the ureC database (ureolytic bacteria; Jin et al., 2017), and AF-RefSeq (anaerobic fungi; Paul et al., 2018) drastically improve our ability to monitor rumen microbial diversity.”
From Addressing global ruminant agricultural challenges through understanding the rumen microbiome: past, present, and future (2018) · cites this paper as Seedorf et al., 2014
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References 59 · Cited by 168
- Authors
- Seedorf, H., Kittelmann, S., Henderson, G., & Janssen, P. H.
- Affiliations
- AgResearch (NZ)
- Corresponding author
- Janssen, Peter H.
- Venue
- PeerJ
- Publisher
- PeerJ
- Published
- 2014-08-05
- Volume
- 2
- Pages
- e494
- ISSN
- 2167-8359 (ISSN-L)
- PMC
- PMC4137658
- OpenAlex
- W2070993857
- Cited by
- 168
- References
- 59
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 12 · 2023: 11 · 2022: 21 · 2021: 19 · 2020: 15 · 2019: 16 · 2018: 14 · 2017: 18 · 2016: 13 · 2015: 11 · 2014: 1
- FWCI
- 21.26
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- cc-by
- Locations
- PeerJ (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Topics
- Physical Sciences › Engineering › Building and Construction › Anaerobic Digestion and Biogas Production
- Life Sciences › Agricultural and Biological Sciences › Agronomy and Crop Science › Ruminant Nutrition and Digestive Physiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Keywords
- methanogenic archaea, rumen microbiome, 16S rRNA gene sequences, Methanomassiliicoccales, methane mitigation, ruminant methane emissions, gut microbiota, Greengenes, SILVA
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