Dataset Information

Microfluidic detection of movements of Escherichia coli for rapid antibiotic susceptibility testing.

ABSTRACT: Various nanomechanical movements of bacteria provide a signature of bacterial viability. Most notably, bacterial movements have been observed to subside rapidly and dramatically when the bacteria are exposed to effective antibiotics. Thus, monitoring bacterial movements, if performed with high fidelity, could offer a path to various clinical microbiological applications, including antibiotic susceptibility tests. Here, we introduce a robust and ultrasensitive electrical transduction technique for detecting the nanomechanical movements of bacteria. The technique is based on measuring the electrical fluctuations in a microfluidic channel, which the bacteria populate. The swimming of planktonic bacteria and the random oscillations of surface-immobilized bacteria both cause small but detectable electrical fluctuations. We show that this technique provides enough sensitivity to detect even the slightest movements of a single cell; we also demonstrate an antibiotic susceptibility test in a biological matrix. Given that it lends itself to smooth integration with other microfluidic methods and devices, the technique can be developed into a functional antibiotic susceptibility test, in particular, for urinary tract infections.

SUBMITTER: Kara V

PROVIDER: S-EPMC5829026 | biostudies-literature | 2018 Feb

REPOSITORIES: biostudies-literature

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Microfluidic detection of movements of Escherichia coli for rapid antibiotic susceptibility testing.

Kara Vural V Duan Chuanhua C Gupta Kalpana K Kurosawa Shinichiro S Stearns-Kurosawa Deborah J DJ Ekinci Kamil L KL

Lab on a chip 20180201 5

Various nanomechanical movements of bacteria provide a signature of bacterial viability. Most notably, bacterial movements have been observed to subside rapidly and dramatically when the bacteria are exposed to effective antibiotics. Thus, monitoring bacterial movements, if performed with high fidelity, could offer a path to various clinical microbiological applications, including antibiotic susceptibility tests. Here, we introduce a robust and ultrasensitive electrical transduction technique fo ...[more]

PMID: 29387860

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Project description:Flow cytometry holds promise to accelerate antibiotic susceptibility determinations; however, without robust multidimensional statistical analysis, general discrimination criteria have remained elusive. In this study, a new statistical method, probability binning signature quadratic form (PB-sQF), was developed and applied to analyze flow cytometric data of bacterial responses to antibiotic exposure. Both sensitive lab strains (Escherichia coli and Pseudomonas aeruginosa) and a multidrug resistant, clinically isolated strain (E. coli) were incubated with the bacteria-targeted dye, maltohexaose-conjugated IR786, and each of many bactericidal or bacteriostatic antibiotics to identify changes induced around corresponding minimum inhibition concentrations (MIC). The antibiotic-induced damages were monitored by flow cytometry after 1-h incubation through forward scatter, side scatter, and fluorescence channels. The 3-dimensional differences between the flow cytometric data of the no-antibiotic treated bacteria and the antibiotic-treated bacteria were characterized by PB-sQF into a 1-dimensional linear distance. A 99% confidence level was established by statistical bootstrapping for each antibiotic-bacteria pair. For the susceptible E. coli strain, statistically significant increments from this 99% confidence level were observed from 1/16x MIC to 1x MIC for all the antibiotics. The same increments were recorded for P. aeruginosa, which has been reported to cause difficulty in flow-based viability tests. For the multidrug resistant E. coli, significant distances from control samples were observed only when an effective antibiotic treatment was utilized. Our results suggest that a rapid and robust antimicrobial susceptibility test (AST) can be constructed by statistically characterizing the differences between sample and control flow cytometric populations, even in a label-free scheme with scattered light alone. These distances vs paired controls coupled with rigorous statistical confidence limits offer a new path toward investigating initial biological responses, screening for drugs, and shortening time to result in antimicrobial sensitivity testing.

Dataset Information

Microfluidic detection of movements of Escherichia coli for rapid antibiotic susceptibility testing.

Publications

Microfluidic detection of movements of Escherichia coli for rapid antibiotic susceptibility testing.

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