Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/163665
Title: A technique for rapid bacterial-density enumeration through membrane filtration and differential pressure measurements
Authors: Shen, Xinhui
Teo, Ting Wei
Kong, Tian Fook
Marcos
Keywords: Engineering::Mechanical engineering
Issue Date: 2022
Source: Shen, X., Teo, T. W., Kong, T. F. & Marcos (2022). A technique for rapid bacterial-density enumeration through membrane filtration and differential pressure measurements. Micromachines, 13(8), 1198-. https://dx.doi.org/10.3390/mi13081198
Project: RT04/19(S)
Journal: Micromachines
Abstract: In this article, we present a microfluidic technique for the rapid enumeration of bacterial density with a syringe filter to trap bacteria and the quantification of the bacterial density through pressure difference measurement across the membrane. First, we established the baseline differential pressure and hydraulic resistance for a filtration membrane by fully wetting the filter with DI water. Subsequently, when bacteria were infused and trapped at the pores of the membrane, the differential pressure and hydraulic resistance also increased. We characterized the infusion time required for the bacterial sample to achieve a normalized hydraulic resistance of 1.5. An equivalent electric-circuit model and calibration data sets from parametric studies were used to determine the general form of a calibration curve for the prediction of the bacterial density of a bacterial sample. As a proof of concept, we demonstrated through blind tests with Escherichia coli that the device is capable of determining the bacterial density of a sample ranging from 7.3 × 106 to 2.2 × 108 CFU/mL with mean and median accuracies of 87.21% and 91.33%, respectively. The sample-to-result time is 19 min for a sample with lower detection threshold, while for higher-bacterial-density samples the measurement time is further shortened to merely 8 min.
URI: https://hdl.handle.net/10356/163665
ISSN: 2072-666X
DOI: 10.3390/mi13081198
Rights: © 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:MAE Journal Articles

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