Literature DB >> 28372723

Review: Microbial analysis in dielectrophoretic microfluidic systems.

Renny E Fernandez1, Ali Rohani1, Vahid Farmehini1, Nathan S Swami2.   

Abstract

Infections caused by various known and emerging pathogenic microorganisms, including antibiotic-resistant strains, are a major threat to global health and well-being. This highlights the urgent need for detection systems for microbial identification, quantification and characterization towards assessing infections, prescribing therapies and understanding the dynamic cellular modifications. Current state-of-the-art microbial detection systems exhibit a trade-off between sensitivity and assay time, which could be alleviated by selective and label-free microbial capture onto the sensor surface from dilute samples. AC electrokinetic methods, such as dielectrophoresis, enable frequency-selective capture of viable microbial cells and spores due to polarization based on their distinguishing size, shape and sub-cellular compositional characteristics, for downstream coupling to various detection modalities. Following elucidation of the polarization mechanisms that distinguish bacterial cells from each other, as well as from mammalian cells, this review compares the microfluidic platforms for dielectrophoretic manipulation of microbials and their coupling to various detection modalities, including immuno-capture, impedance measurement, Raman spectroscopy and nucleic acid amplification methods, as well as for phenotypic assessment of microbial viability and antibiotic susceptibility. Based on the urgent need within point-of-care diagnostics towards reducing assay times and enhancing capture of the target organism, as well as the emerging interest in isolating intact microbials based on their phenotype and subcellular features, we envision widespread adoption of these label-free and selective electrokinetic techniques.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  Antibiotics; Bacteria; Dielectrophoresis; Microfluidics; Phenotype; Sensor

Mesh:

Substances:

Year:  2017        PMID: 28372723      PMCID: PMC5424535          DOI: 10.1016/j.aca.2017.02.024

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  200 in total

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