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Record W4398202801 · doi:10.1186/s12864-024-10410-2

Potential involvement of beta-lactamase homologous proteins in resistance to beta-lactam antibiotics in gram-negative bacteria of the ESKAPEE group

2024· article· en· W4398202801 on OpenAlexaff
Joyce de Souza, Alexandre Zanatta Vieira, Hellen Geremias dos Santos, Helisson Faoro

Bibliographic record

VenueBMC Genomics · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsUniversité Laval
FundersFundação Oswaldo CruzConselho Nacional de Desenvolvimento Científico e TecnológicoCoordenação de Aperfeiçoamento de Pessoal de Nível Superior
KeywordsBiologyMicrobiologyGeneticsEnterobacterAntibiotic resistanceBeta-lactamaseBacteriaPeptide sequenceGenomeAcinetobacterPseudomonas aeruginosaConserved sequenceEscherichia coliGene

Abstract

fetched live from OpenAlex

BACKGROUND: Enzymatic degradation mediated by beta-lactamases constitutes one of the primary mechanisms of resistance to beta-lactam antibiotics in gram-negative bacteria. This enzyme family comprises four molecular classes, categorized into serine beta-lactamases (Classes A, C, and D) and zinc-dependent metallo-beta-lactamases (Class B). Gram-negative bacteria producing beta-lactamase are of significant concern, particularly due to their prevalence in nosocomial infections. A comprehensive understanding of the evolution and dissemination of this enzyme family is essential for effective control of these pathogens. In this study, we conducted the prospecting, phylogenetic analysis, and in silico analysis of beta-lactamases and homologous proteins identified in 1827 bacterial genomes with phenotypic data on beta-lactam resistance. These genomes were distributed among Klebsiella pneumoniae (45%), Acinetobacter baumannii (31%), Pseudomonas aeruginosa (14%), Escherichia coli (6%), and Enterobacter spp. (4%). Using an HMM profile and searching for conserved domains, we mined 2514, 8733, 5424, and 2957 proteins for molecular classes A, B, C, and D, respectively. This set of proteins encompasses canonical subfamilies of beta-lactamases as well as hypothetical proteins and other functional groups. Canonical beta-lactamases were found to be phylogenetically distant from hypothetical proteins, which, in turn, are closer to other representatives of the penicillin-binding-protein (PBP-like) and metallo-beta-lactamase (MBL) families. The catalytic amino acid residues characteristic of beta-lactamases were identified from the sequence alignment and revealed that motifs are less conserved in homologous groups than in beta-lactamases. After comparing the frequency of protein groups in genomes of resistant strains with those of sensitive ones applying Fisher's exact test and relative risk, it was observed that some groups of homologous proteins to classes B and C are more common in the genomes of resistant strains, particularly to carbapenems. We identified the beta-lactamase-like domain widely distributed in gram-negative species of the ESKAPEE group, which highlights its importance in the context of beta-lactam resistance. Some hypothetical homologous proteins have been shown to potentially possess promiscuous activity against beta-lactam antibiotics, however, they do not appear to expressly determine the resistance phenotype. The selective pressure due to the widespread use of antibiotics may favor the optimization of these functions for specialized resistance enzymes.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.237
Teacher spread0.226 · 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

Citations6
Published2024
Admission routes1
Has abstractyes

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