CABO-16S—a Combined Archaea, Bacteria, Organelle 16S rRNA database framework for amplicon analysis of prokaryotes and eukaryotes in environmental samples

Eitel, Eryn M.; Utter, Daniel R.; Connon, Stephanie A.; Orphan, Victoria J.; Murali, Ranjani

doi:10.1093/nargab/lqaf061

CABO-16S—a Combined Archaea, Bacteria, Organelle 16S rRNA database framework for amplicon analysis of prokaryotes and eukaryotes in environmental samples

Journal Article · Mon May 19 00:00:00 EDT 2025 · NAR Genomics and Bioinformatics

DOI:https://doi.org/10.1093/nargab/lqaf061· OSTI ID:2567082

; Utter, Daniel R.; Connon, Stephanie A.; Orphan, Victoria J.; Murali, Ranjani

Abstract

Identification of both prokaryotic and eukaryotic microorganisms in environmental samples is currently challenged by the need for additional sequencing to obtain separate 16S and 18S ribosomal RNA (rRNA) amplicons or the constraints imposed by “universal” primers. Organellar 16S rRNA sequences are amplified and sequenced along with prokaryote 16S rRNA and provide an alternative method to identify eukaryotic microorganisms. CABO-16S combines bacterial and archaeal sequences from the SILVA database with 16S rRNA sequences of plastids and other organelles from the PR2 database to enable identification of all 16S rRNA sequences. Comparison of CABO-16S with SILVA 138.2 results in equivalent taxonomic classification of mock communities and increased classification of diverse environmental samples. In particular, identification of phototrophic eukaryotes in shallow seagrass environments, marine waters, and lake waters was increased. The CABO-16S framework allows users to add custom sequences for further classification of underrepresented clades and can be easily updated with future releases of reference databases. Addition of sequences obtained from Sanger sequencing of methane seep sediments and curated sequences of the polyphyletic SEEP-SRB1 clade resulted in differentiation of syntrophic and non-syntrophic SEEP-SRB1 in hydrothermal vent sediments. CABO-16S highlights the benefit of combining and amending existing training sets when studying microorganisms in diverse environments.

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Sponsoring Organization:: USDOE Office of Science (SC), Biological and Environmental Research (BER)

Grant/Contract Number:: SC0020373

OSTI ID:: 2567082

Journal Information:: NAR Genomics and Bioinformatics, Journal Name: NAR Genomics and Bioinformatics Journal Issue: 2 Vol. 7; ISSN 2631-9268

Publisher:: Oxford University PressCopyright Statement

Country of Publication:: United Kingdom

Language:: English

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