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Record W6981972239

Genomic Enzymology Study of the Aminoglycoside Antibiotic Acetyltransferases

2022· dissertation· en· W6981972239 on OpenAlexaboutno aff

Bibliographic record

VenueMacSphere (McMaster University) · 2022
Typedissertation
Languageen
FieldEconomics, Econometrics and Finance
TopicHistorical Economic and Social Studies
Canadian institutionsnot available
Fundersnot available
KeywordsAcetyltransferasesAcetyltransferaseAntibiotic resistanceSUPERFAMILYAntibioticsDrug resistanceArchaea
DOInot available

Abstract

fetched live from OpenAlex

Since their discovery over 40 years ago, considerable knowledge has been obtained on the diversity, and structure-function relationships of aminoglycoside acetyltransferases (AACs), responsible for antibiotic resistance among priority clinical pathogens. In recent years, investigations have expanded to biochemical characterizations of AACs found in environmental reservoirs. The successful design of next-generation aminoglycosides (AGs) depends on an up-to-date understanding of the broader AG resistome. Towards this goal, I present the first structural analysis for the unique apramycin modifying enzyme, ApmA. Apramycin is a veterinary antibiotic that is in development for clinical use. The atypical chemical scaffold provides inherent protection from many clinically relevant resistance mechanisms. Prior to the work presented herein, apmA was an uncharacterized apramycin resistance element among environmental species. I heterologously expressed and subsequently purified ApmA to characterize the nature of resistance towards this unique aminoglycoside. The results report the first acetyltransferase of the left-handed β-helix (LβH) superfamily involved in AG detoxification. Secondly, I completed a comprehensive characterization of ApmA utilizing a structurally diverse panel of AGs for susceptibility testing, protein engineering, steady-state kinetics, and x-ray crystallography. Through these approaches, I establish the structural and functional features that define ApmA’s place within the LβH superfamily and set it apart from other known AACs. The biochemical data presented describes a chemical mechanism dependent on the substrate specificity. Furthermore, I describe the molecular determinants behind AG-modification of clinically relevant AGs. Lastly, I describe the first comprehensive structural and functional study of clinical and environmental Antibiotic_NAT (A_NAT) inactivating enzymes. A pan-family antibiogram was obtained and mapped to the reconstructed phylogeny for the A_NAT family. Crystallographic analysis of representatives from each clade was completed with our collaborators from the University of Toronto. Through the analysis of several ligand-bound A_NAT complexes, I contributed to the elucidation of structural features responsible for substrate specificity. The collective findings from these chapters have extended the protein landscape involved in AG-acetylation from one commonly used fold to three distinct architectures, each unique in underlying chemical mechanism and dissemination.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.022
GPT teacher head0.195
Teacher spread0.173 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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