Dataset Information

A Smartphone-Based Whole-Cell Array Sensor for Detection of Antibiotics in Milk.

ABSTRACT: We present an integral smartphone-based whole-cell biosensor, LumiCellSense (LCS), which incorporates a 16-well biochip with an oxygen permeable coating, harboring bioluminescent Escherichia coli bioreporter cells, a macro lens, a lens barrel, a metal heater tray, and a temperature controller, enclosed in a light-impermeable case. The luminescence emitted by the bioreporter cells in response to the presence of the target chemicals is imaged by the phone's camera, and a dedicated phone-embedded application, LCS_Logger, is employed to calculate photon emission intensity and plot it in real time on the device's screen. An alert is automatically given when light intensity increases above the baseline, indicating the presence of the target. We demonstrate the efficacy of this system by the detection of residues of an antibiotic, ciprofloxacin (CIP), in whole milk, with a detection threshold of 7.2 ng/mL. This value is below the allowed maximum as defined by European Union regulations.

SUBMITTER: Lu MY

PROVIDER: S-EPMC6767005 | biostudies-literature | 2019 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A Smartphone-Based Whole-Cell Array Sensor for Detection of Antibiotics in Milk.

Lu Mei-Yi MY Kao Wei-Chen WC Belkin Shimshon S Cheng Ji-Yen JY

Sensors (Basel, Switzerland) 20190909 18

We present an integral smartphone-based whole-cell biosensor, LumiCellSense (LCS), which incorporates a 16-well biochip with an oxygen permeable coating, harboring bioluminescent <i>Escherichia coli</i> bioreporter cells, a macro lens, a lens barrel, a metal heater tray, and a temperature controller, enclosed in a light-impermeable case. The luminescence emitted by the bioreporter cells in response to the presence of the target chemicals is imaged by the phone's camera, and a dedicated phone-emb ...[more]

PMID: 31505815

Similar Datasets

Project description:The combination of the generic mobile technology and inherent stability, versatility and cost-effectiveness of the synthetic receptors allows producing optical sensors for potentially any analyte of interest, and, therefore, to qualify as a platform technology for a fast routine analysis of a large number of contaminated samples. To support this statement, we present here a novel miniature sensor based on a combination of molecularly imprinted polymer (MIP) membranes and a smartphone, which could be used for the point-of-care detection of an important food contaminant, oestrogen-like toxin zearalenone associated with Fusarium contamination of cereals. The detection is based on registration of natural fluorescence of zearalenone using a digital smartphone camera after it binds to the sensor recognition element. The recorded image is further processed using a mobile application. It shows here a first example of the zearalenone-specific MIP membranes synthesised in situ using "dummy template"-based approach with cyclododecyl 2, 4-dihydroxybenzoate as the template and 1-allylpiperazine as a functional monomer. The novel smartphone sensor system based on optimized MIP membranes provides zearalenone detection in cereal samples within the range of 1-10 µg mL-1 demonstrating a detection limit of 1 µg mL-1 in a direct sensing mode. In order to reach the level of sensitivity required for practical application, a competitive sensing mode is also developed. It is based on application of a highly-fluorescent structural analogue of zearalenone (2-[(pyrene-l-carbonyl) amino]ethyl 2,4-dihydroxybenzoate) which is capable to compete with the target mycotoxin for the binding to zearalenone-selective sites in the membrane's structure. The competitive mode increases 100 times the sensor's sensitivity and allows detecting zearalenone at 10 ng mL-1. The linear dynamic range in this case comprised 10-100 ng mL-1. The sensor system is tested and found effective for zearalenone detection in maize, wheat and rye flour samples both spiked and naturally contaminated. The developed MIP membrane-based smartphone sensor system is an example of a novel, inexpensive tool for food quality analysis, which is portable and can be used for the "field" measurements and easily translated into the practice.

Dataset Information

A Smartphone-Based Whole-Cell Array Sensor for Detection of Antibiotics in Milk.

Publications

A Smartphone-Based Whole-Cell Array Sensor for Detection of Antibiotics in Milk.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets