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Rapid identification of bacterial isolates using microfluidic adaptive channels and multiplexed fluorescence microscopy.

Authors :
Chatzimichail, Stelios
Turner, Piers
Feehily, Conor
Farrar, Alison
Crook, Derrick
Andersson, Monique
Oakley, Sarah
Barrett, Lucinda
El Sayyed, Hafez
Kyropoulos, Jingwen
Nellåker, Christoffer
Stoesser, Nicole
Kapanidis, Achillefs N.
Source :
Lab on a Chip; 10/21/2024, Vol. 24 Issue 20, p4843-4858, 16p
Publication Year :
2024

Abstract

We demonstrate the rapid capture, enrichment, and identification of bacterial pathogens using Adaptive Channel Bacterial Capture (ACBC) devices. Using controlled tuning of device backpressure in polydimethylsiloxane (PDMS) devices, we enable the controlled formation of capture regions capable of trapping bacteria from low cell density samples with near 100% capture efficiency. The technical demands to prepare such devices are much lower compared to conventional methods for bacterial trapping and can be achieved with simple benchtop fabrication methods. We demonstrate the capture and identification of seven species of bacteria with bacterial concentrations lower than 1000 cells per mL, including common Gram-negative and Gram-positive pathogens such as Escherichia coli and Staphylococcus aureus. We further demonstrate that species identification of the trapped bacteria can be undertaken in the order of one-hour using multiplexed 16S rRNA-FISH with identification accuracies of 70–98% with unsupervised classification methods across 7 species of bacteria. Finally, by using the bacterial capture capabilities of the ACBC chip with an ultra-rapid antimicrobial susceptibility testing method employing fluorescence imaging and convolutional neural network (CNN) classification, we demonstrate that we can use the ACBC chip as an imaging flow cytometer that can predict the antibiotic susceptibility of E. coli cells after identification. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
14730197
Volume :
24
Issue :
20
Database :
Complementary Index
Journal :
Lab on a Chip
Publication Type :
Academic Journal
Accession number :
180176701
Full Text :
https://doi.org/10.1039/d4lc00325j