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Record W2789312467 · doi:10.1128/mbio.02345-17

Metagenomes Reveal Global Distribution of Bacterial Steroid Catabolism in Natural, Engineered, and Host Environments

2018· article· en· W2789312467 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenuemBio · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSteroid Chemistry and Biochemistry
Canadian institutionsUniversity of WaterlooUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaTula Foundation
KeywordsActinobacteriaBiologyMetagenomicsSteroidBacteriaHost (biology)ProteobacteriaSpongeMicroorganismRhizosphereMicrobiologyEcologyGene16S ribosomal RNABotanyGeneticsBiochemistry

Abstract

fetched live from OpenAlex

ABSTRACT Steroids are abundant growth substrates for bacteria in natural, engineered, and host-associated environments. This study analyzed the distribution of the aerobic 9,10-seco steroid degradation pathway in 346 publically available metagenomes from diverse environments. Our results show that steroid-degrading bacteria are globally distributed and prevalent in particular environments, such as wastewater treatment plants, soil, plant rhizospheres, and the marine environment, including marine sponges. Genomic signature-based sequence binning recovered 45 metagenome-assembled genomes containing a majority of 9,10-seco pathway genes. Only Actinobacteria and Proteobacteria were identified as steroid degraders, but we identified several alpha- and gammaproteobacterial lineages not previously known to degrade steroids. Actino- and proteobacterial steroid degraders coexisted in wastewater, while soil and rhizosphere samples contained mostly actinobacterial ones. Actinobacterial steroid degraders were found in deep ocean samples, while mostly alpha- and gammaproteobacterial ones were found in other marine samples, including sponges. Isolation of steroid-degrading bacteria from sponges confirmed their presence. Phylogenetic analysis of key steroid degradation proteins suggested their biochemical novelty in genomes from sponges and other environments. This study shows that the ecological significance as well as taxonomic and biochemical diversity of bacterial steroid degradation has so far been largely underestimated, especially in the marine environment. IMPORTANCE Microbial steroid degradation is a critical process for biomass decomposition in natural environments, for removal of important pollutants during wastewater treatment, and for pathogenesis of bacteria associated with tuberculosis and other bacteria. To date, microbial steroid degradation was mainly studied in a few model organisms, while the ecological significance of steroid degradation remained largely unexplored. This study provides the first analysis of aerobic steroid degradation in diverse natural, engineered, and host-associated environments via bioinformatic analysis of an extensive metagenome data set. We found that steroid-degrading bacteria are globally distributed and prevalent in wastewater treatment plants, soil, plant rhizospheres, and the marine environment, especially in marine sponges. We show that the ecological significance as well as the taxonomic and biochemical diversity of bacterial steroid degradation has been largely underestimated. This study greatly expands our ecological and evolutionary understanding of microbial steroid degradation.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.527

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.209
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it