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Proteins and Carbs – The Balanced Diet of a Complex and Unusual Enzyme Family

2016· article· en· W4389022860 on OpenAlexaff
A.B. Boraston, Ilit Noach, Elizabeth Ficko‐Blean, C.P. Stuart, Denis Brochu, Michel Gilbert

Bibliographic record

VenueThe FASEB Journal · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEnzyme Production and Characterization
Canadian institutionsNational Research Council CanadaUniversity of Victoria
Fundersnot available
KeywordsMucinBacteroides thetaiotaomicronGlycoproteinProteasesProteaseBacteriaMicrobiologyBiologyBiochemistryGlycanMetalloproteinaseMucusEnzymeBacteroidesClostridium perfringensGenetics

Abstract

fetched live from OpenAlex

Many host‐adapted bacteria have the capability to colonize mucosal layers. To do so, these bacteria have often developed the capacity to breakdown the mucin component of the protective layers that cover epithelial cells. As mucins are glycoproteins that are up to 80% carbohydrate by mass the most common feature of bacterial mucin degrading systems is an arsenal of enzymes that breakdown carbohydrates. However, how such bacteria may target the protein backbone of mucins remains a poorly investigated question. We have identified mucin‐degrading proteins in Clostridium perfringens, Bacteroides thetaiotaomicron , and Pseudomonas aeruginosa , which are all host‐adapted a bacteria notable their ability to colonize the mucus rich environments of human and animal tissues. These proteins are zinc‐metalloproteases and thus cleave the peptide backbone. Remarkably, our structural and functional analyses of these enzymes reveal that O‐linked glycans accommodated in the zinc‐metalloprotease active site is a determinant of specificity, and this is dependent on the particular protease. This work provides the first detailed molecular insight into a large family of glycoproteases found in host‐adapted microbes and highlights the potential complexity of substrate specificity in glycoprotein specific proteases.

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 score0.044
Threshold uncertainty score0.093

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 head0.015
GPT teacher head0.234
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
Published2016
Admission routes1
Has abstractyes

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