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Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning.
- Source :
-
Nature communications [Nat Commun] 2019 Oct 30; Vol. 10 (1), pp. 4927. Date of Electronic Publication: 2019 Oct 30. - Publication Year :
- 2019
-
Abstract
- Raman optical spectroscopy promises label-free bacterial detection, identification, and antibiotic susceptibility testing in a single step. However, achieving clinically relevant speeds and accuracies remains challenging due to weak Raman signal from bacterial cells and numerous bacterial species and phenotypes. Here we generate an extensive dataset of bacterial Raman spectra and apply deep learning approaches to accurately identify 30 common bacterial pathogens. Even on low signal-to-noise spectra, we achieve average isolate-level accuracies exceeding 82% and antibiotic treatment identification accuracies of 97.0±0.3%. We also show that this approach distinguishes between methicillin-resistant and -susceptible isolates of Staphylococcus aureus (MRSA and MSSA) with 89±0.1% accuracy. We validate our results on clinical isolates from 50 patients. Using just 10 bacterial spectra from each patient isolate, we achieve treatment identification accuracies of 99.7%. Our approach has potential for culture-free pathogen identification and antibiotic susceptibility testing, and could be readily extended for diagnostics on blood, urine, and sputum.
- Subjects :
- Bacteria chemistry
Bacterial Infections drug therapy
Bacterial Infections microbiology
Bacterial Typing Techniques
Candida chemistry
Candida classification
Enterococcus chemistry
Enterococcus classification
Escherichia coli chemistry
Escherichia coli classification
Humans
Klebsiella chemistry
Klebsiella classification
Logistic Models
Methicillin-Resistant Staphylococcus aureus chemistry
Methicillin-Resistant Staphylococcus aureus classification
Microbial Sensitivity Tests
Neural Networks, Computer
Principal Component Analysis
Proteus mirabilis chemistry
Proteus mirabilis classification
Pseudomonas aeruginosa chemistry
Pseudomonas aeruginosa classification
Salmonella enterica chemistry
Salmonella enterica classification
Single-Cell Analysis
Staphylococcus aureus chemistry
Staphylococcus aureus classification
Streptococcus chemistry
Streptococcus classification
Support Vector Machine
Anti-Bacterial Agents therapeutic use
Bacteria classification
Bacterial Infections diagnosis
Deep Learning
Spectrum Analysis, Raman methods
Subjects
Details
- Language :
- English
- ISSN :
- 2041-1723
- Volume :
- 10
- Issue :
- 1
- Database :
- MEDLINE
- Journal :
- Nature communications
- Publication Type :
- Academic Journal
- Accession number :
- 31666527
- Full Text :
- https://doi.org/10.1038/s41467-019-12898-9