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Record W4232864138 · doi:10.32920/14638806.v1

Proteomic Analysis of the Secretome of Cellulomonas fimi ATCC 484 and Cellulomonas flavigena ATCC 482

2021· preprint· en· W4232864138 on OpenAlexafffund
Warren W. Wakarchuk, Denis Brochu, Simon J. Foote, Anna Robotham, Hirak Saxena, Tamara Erak, John Kelly

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsNational Research Council CanadaToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCellulaseXylanCelluloseCell wallMicrobiologyGenomeBiologyChemistryBiochemistryGene

Abstract

fetched live from OpenAlex

The bacteria in the genus Cellulomonas are known for their ability to degrade plant cell wall biomass. Cellulomonas fimi ATCC 484 and C. flavigena ATCC 482 have been the subject of much research into secreted cellulases and hemicellulases. Recently the genome sequences of both C. fimi ATCC 484 and C. flavigena ATCC 482 were published, and a genome comparison has revealed their full spectrum of possible carbohydrate-active enzymes (CAZymes). Using mass spectrometry, we have compared the proteins secreted by C. fimi and C. flavigena during growth on the soluble cellulose substrate, carboxymethylcellulose (CMC), as well as a soluble xylan fraction. Many known C. fimi CAZymes were detected, which validated our analysis, as were a number of new CAZymes and other proteins that, though identified in the genome, have not previously been observed in the secretome of either organism. Our data also shows that many of these are co-expressed on growth of either CMC or xylan. This analysis provides a new perspective on Cellulomonas enzymes and provides many new CAZyme targets for characterization.

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.

How this classification was reachedexpand

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 score0.010
Threshold uncertainty score0.840

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 science0.0000.001
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 head0.008
GPT teacher head0.227
Teacher spread0.219 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2021
Admission routes2
Has abstractyes

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