scholarly journals Rapid identification of pathogenic bacteria using Raman spectroscopy and deep learning

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Chi-Sing Ho ◽  
Neal Jean ◽  
Catherine A. Hogan ◽  
Lena Blackmon ◽  
Stefanie S. Jeffrey ◽  
...  
Keyword(s):  
Deep Learning ◽  
Antibiotic Susceptibility ◽  
Pathogenic Bacteria ◽  
Susceptibility Testing ◽  
Bacterial Species ◽  
Raman Signal ◽  
Bacterial Cells ◽  
Learning Approaches ◽  
Antibiotic Susceptibility Testing ◽  
Label Free

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.

scholarly journals Potential Role of Door Handles in the Spread of Drug Resistant Bacteria in Makerere University.

2021 ◽  
Author(s):  
◽  
Immaculate Nabawanuka
Keyword(s):  
Escherichia Coli ◽  
Antibiotic Susceptibility ◽  
Pathogenic Bacteria ◽  
Susceptibility Testing ◽  
Bacterial Load ◽  
Plate Count ◽  
Diffusion Method ◽  
Resistant Bacteria ◽  
Antibiotic Susceptibility Testing ◽  
Makerere University

Background: The transmission of diseases caused by pathogenic bacteria is still a threat. One of the potential sources of bacterial diseases is the door handles. This study aimed at isolating, identifying bacteria, determining total bacterial load, and determining antibiotic susceptibility patterns of bacteria obtained from door handles in Makerere university. Methodology:  A total of 60 samples randomly scattered within the university were swabbed and analyzed for bacterial growth. Samples were inoculated on MacConkey and blood agar and then incubated at 37 ºC for 24 hours. All sample isolates were sub cultured and identified based on macro and micromorphology, and standard biochemical tests. The establishment of the total bacterial load was done using the standard plate count method. Antibiotic susceptibility testing was done using the disc diffusion method on Muller Hilton agar. Results: The following bacterial species and genera were obtained from door handles, staphylococcus aureus (30.8%), Coagulase-negative staphylococcus (12.0%), Streptococcus species (24.2%), Escherichia coli (7.7%), Pseudomonas aeruginosa (14.3%), bacilli species (11.0%). The study showed that there was a significant difference in the prevalence of bacilli species (p= 0.017) and E. coli (p= 0.015) among the study group. The results from total bacterial count indicated that toilet door handles had the highest bacterial load compared to office door handles and classrooms. Antibiotic susceptibility testing of isolates showed that all bacteria were resistant and intermediately resistant to commonly used antibiotics except for Escherichia coli that was susceptible to amoxicillin Conclusion and recommendations: The study reveals that door handles are a considerable source of pathogenic bacteria thus play a major role in the transmission of diseases caused by such bacteria. Further studies could be done and different study groups could be included for example routinely opened doors and the doors which are not routinely opened.

Rapid Antibiotic Susceptibility Testing of UropathogenicE. coliby Tracking Submicron Scale Motion of Single Bacterial Cells

ACS Sensors ◽  
2017 ◽  
Vol 2 (8) ◽  
pp. 1231-1239 ◽  
Author(s):  
Karan Syal ◽  
Simon Shen ◽  
Yunze Yang ◽  
Shaopeng Wang ◽  
Shelley E. Haydel ◽  
...  
Keyword(s):  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Bacterial Cells ◽  
Antibiotic Susceptibility Testing ◽  
Submicron Scale ◽  
Scale Motion

scholarly journals Rapid antibiotic susceptibility testing and species identification for mixed infections

2021 ◽  
Author(s):  
Vinodh Kandavalli ◽  
Praneeth Karempudi ◽  
Jimmy Larsson ◽  
Johan Elf
Keyword(s):  
Species Identification ◽  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Mixed Infections ◽  
Single Cell Level ◽  
Bacterial Cells ◽  
Antibiotic Susceptibility Testing ◽  
Cell Level ◽  
Proof Of Principle

Antimicrobial resistance is an increasing problem globally. Rapid antibiotic susceptibility testing (AST) is urgently needed in the clinic to enable personalized prescription in high-resistance environments and limit the use of broad-spectrum drugs. Previously we have described a 30 min AST method based on imaging of individual bacterial cells. However, current phenotypic AST methods do not include species identification (ID), leaving time-consuming plating or culturing as the only available option when ID is needed to make the sensitivity call. Here we describe a method to perform phenotypic AST at the single-cell level in a microfluidic chip that allows subsequent genotyping by in situ FISH. By stratifying the phenotypic AST response on the species of individual cells, it is possible to determine the susceptibility profile for each species in a mixed infection sample in 1.5 h. In this proof-of-principle study, we demonstrate the operation with four antibiotics and a mixed sample with four species.

scholarly journals Rapid antibiotic susceptibility testing and species identification for mixed infections

2021 ◽  
Author(s):  
Vinodh Kandavalli ◽  
Praneeth Karempudi ◽  
Jimmy Larsson ◽  
Johan Elf
Keyword(s):  
Species Identification ◽  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Mixed Infections ◽  
Single Cell Level ◽  
Bacterial Cells ◽  
Antibiotic Susceptibility Testing ◽  
Cell Level ◽  
Proof Of Principle

Abstract Antimicrobial resistance is an increasing problem globally. Rapid antibiotic susceptibility testing (AST) is urgently needed in the clinic to enable personalized prescription in high-resistance environments and limit the use of broad-spectrum drugs. Previously we have described a 30 min AST method based on imaging of individual bacterial cells. However, current phenotypic AST methods do not include species identification (ID), leaving time-consuming plating or culturing as the only available option when ID is needed to make the sensitivity call. Here we describe a method to perform phenotypic AST at the single-cell level in a microfluidic chip that allows subsequent genotyping by in situ FISH. By stratifying the phenotypic AST response on the species of individual cells, it is possible to determine the susceptibility profile for each species in a mixed infection sample in 1.5 h. In this proof-of-principle study, we demonstrate the operation with four antibiotics and a mixed sample with four species.

scholarly journals Rapid Antibiotic Susceptibility Testing on Pathogenic Bacteria in Solid Growth Medium Using a Real-Time and Contactless Planar Microwave Resonator Sensor

2021 ◽  
Author(s):  
Mandeep Chhajer Jain ◽  
Anupama Pillai ◽  
Rakesh Narang ◽  
Mohammad Zarifi
Keyword(s):  
High Throughput ◽  
Antibiotic Susceptibility ◽  
Pathogenic Bacteria ◽  
Susceptibility Testing ◽  
Dielectric Materials ◽  
Great Promise ◽  
Microwave Resonator ◽  
Antibiotic Susceptibility Testing ◽  
Bacterial Strains ◽  
Non Invasive

Abstract Infection diagnosis and antibiotic susceptibility testing (AST) are pertinent clinical microbiology practices that are in dire need of improvement, as current standards are not able to keep up with the mutations and resistance development of certain bacterial strains. This paper presents a novel way to conduct AST which hybridizes disk diffusion AST with microwave resonators for rapid, contactless, non-invasive and high-throughput testing. This work uses Escherichia coli (E. coli) cultured on solid agar and places bacteria samples on a microwave split-ring resonator along with antibiotic disks (erythromycin) of various doses to demonstrate the viability of this sensing method in a clinical microbiological setting. The microwave resonator, operating at a 1.76 GHz resonant frequency, boasted a 5 mm2 sensitive sensing region. A one-port sensor was designed and optimized for detecting dielectric property variations of lossy dielectric materials accurately. This sensor was calibrated to detect uninhibited growth of the bacteria at 0.005 dB/hr, with a maximum change of 0.07 dB over the course of 15 hrs. The transient resonant amplitude change was subsequently dampened for each increasing dosage of antibiotic tested, with 45 µg of erythromycin showing negligible change indicating complete inhibited growth. This AST sensor demonstrated decisive results of antibiotic susceptibility in under 6 hours and shows great promise to further automate the intricate workflow of AST in clinical settings, while providing rapid, sensitive, non-invasive and high-throughput detection capabilities.

scholarly journals Fast Antibiotic Susceptibility Testing via Raman Microspectrometry on Single Bacteria: An MRSA Case Study

ACS Omega ◽  
2021 ◽  
Author(s):  
Armelle Novelli Rousseau ◽  
Nicolas Faure ◽  
Fabian Rol ◽  
Zohreh Sedaghat ◽  
Joël Le Galudec ◽  
...  
Keyword(s):  
Antibiotic Susceptibility ◽  
Susceptibility Testing ◽  
Antibiotic Susceptibility Testing ◽  
Raman Microspectrometry
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