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Record W2621433465 · doi:10.1073/pnas.1619660114

Crystal structures of the <i>Burkholderia multivorans</i> hopanoid transporter HpnN

2017· article· en· W2621433465 on OpenAlexfundno aff
Nitin Kumar, Chih‐Chia Su, Tsung‐Han Chou, Abhijith Radhakrishnan, Jared A. Delmar, Kanagalaghatta R. Rajashankar, Edward Yu

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
FundersBasic Energy SciencesNational Institutes of HealthQueen's UniversityNational Institute of Allergy and Infectious DiseasesQueen's University BelfastOffice of Extramural Research, National Institutes of HealthU.S. Department of Energy
KeywordsMicrobiologyBiologyBurkholderia cepacia complexATP-binding cassette transporterEffluxBacteriaBacterial outer membraneMultiple drug resistanceTransporterBurkholderiaAntibioticsBiochemistryGeneGeneticsEscherichia coli

Abstract

fetched live from OpenAlex

Significance Bcc bacteria are intrinsically resistant to multiple antibiotics. They are major pathogens in patients with cystic fibrosis (CF) and can cause severe necrotizing pneumonia, which is often fatal. Hopanoid biosynthesis is one of the major mechanisms involved in multiple antimicrobial resistance of Bcc pathogens. The hpnN gene of B. multivorans encodes an integral membrane protein of the HpnN family of transporters, which is responsible for shuttling hopanoids to the outer membrane. Here, we report crystal structures of B. multivorans HpnN that indicate a plausible pathway for hopanoid transport. Overall our data suggest a novel mechanism for hopanoid transport involved in cell wall remodeling, which is critical for mediating multidrug resistance in Burkholderia .

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.009
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.292
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), 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

Citations57
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the National Academy of SciencesSame topicAntibiotic Resistance in BacteriaFrench-language works237,207