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Record W2579931127 · doi:10.1093/ofid/ofw172.51

Rapid and Reagent-Free Method for Identification of Enterobacteriaceae Using Attenuated Total Reflectance-Fourier Transform Infrared Spectroscopy

2016· article· en· W2579931127 on OpenAlexaff
Pierre Lebel, M Langella, Lisa M. T. Lam, Hayline Kim, Jacqueline Sedman, Ashraf A. Ismail, Clifford Clark, Irène Iugovaz

Bibliographic record

VenueOpen Forum Infectious Diseases · 2016
Typearticle
Languageen
FieldEngineering
TopicAdvanced Chemical Sensor Technologies
Canadian institutionsHealth CanadaCanadian Science Centre for Human and Animal HealthMcGill UniversityMcGill University Health Centre
Fundersnot available
KeywordsAttenuated total reflectionMedicineInfraredFourier transformEnterobacteriaceaeFourier transform infrared spectroscopyReagentOpticsChemistryMathematicsBiochemistryEscherichia coliPhysics

Abstract

fetched live from OpenAlex

Background. Fourier transform infrared (FTIR) spectroscopy is a rapid, reagent-free technique for bacterial identification and classification. When implemented in the attenuated total reflectance ([ATR] as opposed to the commonly used transmission) mode of spectral acquisition, bacterial colonies from culture plates can be analyzed directly without any sample preparation steps, allowing for identification within minutes after initial culture. In this study, we evaluated for the first time the discriminatory power of ATR-FTIR spectroscopy for the rapid classification of Enterobacteriaceae. We demonstrate that this phenotypic fingerprinting technique can complement matrix-assisted laser desorption ionization time-of-flight mass spectrometry by providing additional discriminatory capabilities. Methods. The ATR-FTIR spectra were acquired by transferring isolated colonies from MacConkey agar plates onto the ATR sampling surface of a portable ATR-FTIR spectrometer. The ATR-FTIR spectral acquisition time was ∼1 minute. Four spectra were collected for each isolate from different colonies on the same culture plate, yielding a spectral database containing approximately 1400 ATR-FTIR spectra of Enterobacteriaceae. Spectral data analysis was performed by hierarchical cluster analysis and principal component analysis in conjunction with the use of a feature selection algorithm. Results. Approximately 350 clinical isolates of Enterobacteriaceae, including Enterobacter, Klebsiella, Proteus, Citrobacter, Salmonella, and Shigella spp as well as pathogenic (Shiga toxin-producing Escherichia coli, enterohemorrhagic E coli, enteropathogenic E coli, and uropathogenic E coli) and nonpathogenic E coli, were used in this study. Genus-level and species-level classification of all the clinical isolates was achieved by multivariate statistical analysis of the FTIR data with an overall rate of correct classification exceeding 98%, including complete differentiation between E coli and Shigella spp. Further multivariate statistical analysis of the ATR-FTIR spectra of the E coli isolates yielded complete differentiation between pathogenic and non-pathogenic strains and discrimination among the 4 E coli pathotypes included in this study. Conclusion. The ATR-FTIR spectroscopy can provide a simple and rapid method for species identification of Enterobacteriaceae as well as for discrimination between E coli and Shigella spp within minutes after initial culture. Disclosures. All authors: No reported disclosures.

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 score0.170
Threshold uncertainty score0.636

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 head0.014
GPT teacher head0.285
Teacher spread0.271 · 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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