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Record W2294463777 · doi:10.1128/mbio.00166-16

Delineation of Steroid-Degrading Microorganisms through Comparative Genomic Analysis

2016· article· en· W2294463777 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 · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSteroid Chemistry and Biochemistry
Canadian institutionsThompson Rivers UniversityUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaGovernment of CanadaTula Foundation
KeywordsMicroorganismComputational biologyBiologyData scienceMicrobiologyBacteriaComputer scienceGenetics

Abstract

fetched live from OpenAlex

UNLABELLED: Steroids are ubiquitous in natural environments and are a significant growth substrate for microorganisms. Microbial steroid metabolism is also important for some pathogens and for biotechnical applications. This study delineated the distribution of aerobic steroid catabolism pathways among over 8,000 microorganisms whose genomes are available in the NCBI RefSeq database. Combined analysis of bacterial, archaeal, and fungal genomes with both hidden Markov models and reciprocal BLAST identified 265 putative steroid degraders within only Actinobacteria and Proteobacteria, which mainly originated from soil, eukaryotic host, and aquatic environments. These bacteria include members of 17 genera not previously known to contain steroid degraders. A pathway for cholesterol degradation was conserved in many actinobacterial genera, particularly in members of the Corynebacterineae, and a pathway for cholate degradation was conserved in members of the genus Rhodococcus. A pathway for testosterone and, sometimes, cholate degradation had a patchy distribution among Proteobacteria. The steroid degradation genes tended to occur within large gene clusters. Growth experiments confirmed bioinformatic predictions of steroid metabolism capacity in nine bacterial strains. The results indicate there was a single ancestral 9,10-seco-steroid degradation pathway. Gene duplication, likely in a progenitor of Rhodococcus, later gave rise to a cholate degradation pathway. Proteobacteria and additional Actinobacteria subsequently obtained a cholate degradation pathway via horizontal gene transfer, in some cases facilitated by plasmids. Catabolism of steroids appears to be an important component of the ecological niches of broad groups of Actinobacteria and individual species of Proteobacteria. IMPORTANCE: Steroids are ubiquitous growth substrates for environmental and pathogenic bacteria, and bacterial steroid metabolism has important pharmaceutical and health applications. To date, the genetics and biochemistry of microbial steroid degradation have mainly been studied in a few model bacteria, and the diversity of this metabolism remains largely unexplored. Here, we provide a bioinformatically derived perspective of the taxonomic distribution of aerobic microbial steroid catabolism pathways. We identified several novel steroid-degrading bacterial groups, including ones from marine environments. In several cases, we confirmed bioinformatic predictions of metabolism in cultures. We found that cholesterol and cholate catabolism pathways are highly conserved among certain actinobacterial taxa. We found evidence for horizontal transfer of a pathway to several proteobacterial genera, conferring testosterone and, sometimes, cholate catabolism. The results of this study greatly expand our ecological and evolutionary understanding of microbial steroid metabolism and provide a basis for better exploiting this metabolism for biotechnology.

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 score0.017
Threshold uncertainty score0.413

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 head0.020
GPT teacher head0.269
Teacher spread0.249 · 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