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Droplet microfluidics based platform technology for continuous chemical sensing

Droplet microfluidics based platform technology for continuous chemical sensing
Droplet microfluidics based platform technology for continuous chemical sensing
Continuous monitoring of biomarkers such as metabolites and hormones can be extremely useful in understanding physiological processes, for drug development, personalised therapy, and many other applications. In environmental analysis, continuous monitoring can help generate nutrient profiles necessary for identifying short-term events, cyclic variations, thereby has potential in expanding our knowledge of aquatic ecosystems and guiding us in taking appropriate remedial actions. Droplet microfluidics, which is the compartmentalization of liquids into nano-litre droplets, provides advantages such as small volumes of sample and reagents consumption, improved sensitivity and temporal resolution, short analysis time, high throughput and parallelisation compared with conventional laboratory assays. In recent times, continuous measurement of analytes in droplets indicates it as a potential new sensor platform in continuous biochemical analysis resulting in a new class of dataset for dynamics to be captured. The most up-to-date systems however address mostly homogenous, single step “mix-and-read” assays. This thesis presents the technology development of advanced droplet platforms for multiple step assays and autonomous analysis for continuous monitoring. Heterogeneous assays such as enzyme-linked immunosorbent assays (ELISA) are commonly used to measure antibodies, antigens, proteins and glycoproteins in biological samples, and with wide applications in disease diagnostics and treatment. ELISA normally requires multiple assay steps to be carried out with complex laboratory equipment. This thesis presents a miniaturised magnetic bead based platform, where a multitude of assays can be implemented using a versatile droplet generation method. The platform incorporates a phased peristaltic micropump and microfluidic chip for droplet generation, a pair of ‘electromagnetic tweezers’ for manipulation of magnetic beads and a spectrophotometer for colorimetric detection. This platform automates the entire process from sample collection to detection. As a proof-of-concept, the platform was used to carry out a heterogeneous assay and analysis of cortisol, a stress related hormone implicated in many diseases including dementia and Cushing’s syndrome. The prototype device is able to analyse sample containing free bioactive cortisol every 10 seconds and has an initial sample-to-signal time of 10 minutes. It is able to measure in the analytical range of 3.175-100 ng/mL with less variability than the well plate-based assay. Droplet microfluidics based platform technology for continuous chemical sensing W. Bhuiyan 3 Ammonium is one of the most important macronutrients and intermediates of the nitrogen cycle. Increased concentrations of ammonium could lead to nutrient enrichment, oxygen depletion and toxicity to aquatic ecosystems. This thesis reports the first of its kind droplet microfluidics ammonium sensor. The sensor miniaturizes the widely adopted indophenol blue assay and can perform high frequency measurement and long-term monitoring with low sample consumption. The sensor has been implemented for two separate applications, which displays its versatility, with the first measuring ammonium in river water samples. Another application of this sensor prototype has been in a sequential batch bioreactor enriched with PHA accumulating bacteria. The sensor can autonomously collect samples (via filter) from the bioreactor, produce droplet trains, regulate temperature for completion of reaction and provide colorimetric measurements (5 per minute) via an in-line spectrophotometer, thus removing human intervention. The preliminary data obtained over a four-day period demonstrates high resolution monitoring and reveals the fast-feeding behaviour of the bacteria. This kind of monitoring data could lead to feedback-controlled bioprocessing and the development of more efficient bioreactors. This thesis further presents the development of a multiple micropump platform for the robust generation of droplet trains, based on phased droplet generation technology. The multiple micropump platform can generate droplet trains containing different sizes, compositions, and sequences on-demand. This setup does not require any change in pump hardware for different assays, therefore making the platform truly versatile. The 3D printed micropumps are robust with low footprint and the platform can be taken to point of care. Latest design can generate droplets from 120 nL upwards with a coefficient of variation of less than 0.7%. Overall, the developments and research findings in this thesis paves the way for a new generation of droplet microfluidic sensors for continuous monitoring.
University of Southampton
Bhuiyan, Wahida, Taskin
726b7804-d43d-4516-b7e5-e63f60f03135
Bhuiyan, Wahida, Taskin
726b7804-d43d-4516-b7e5-e63f60f03135
Niu, Xize
f3d964fb-23b4-45db-92fe-02426e4e76fa

Bhuiyan, Wahida, Taskin (2022) Droplet microfluidics based platform technology for continuous chemical sensing. University of Southampton, Doctoral Thesis, 213pp.

Record type: Thesis (Doctoral)

Abstract

Continuous monitoring of biomarkers such as metabolites and hormones can be extremely useful in understanding physiological processes, for drug development, personalised therapy, and many other applications. In environmental analysis, continuous monitoring can help generate nutrient profiles necessary for identifying short-term events, cyclic variations, thereby has potential in expanding our knowledge of aquatic ecosystems and guiding us in taking appropriate remedial actions. Droplet microfluidics, which is the compartmentalization of liquids into nano-litre droplets, provides advantages such as small volumes of sample and reagents consumption, improved sensitivity and temporal resolution, short analysis time, high throughput and parallelisation compared with conventional laboratory assays. In recent times, continuous measurement of analytes in droplets indicates it as a potential new sensor platform in continuous biochemical analysis resulting in a new class of dataset for dynamics to be captured. The most up-to-date systems however address mostly homogenous, single step “mix-and-read” assays. This thesis presents the technology development of advanced droplet platforms for multiple step assays and autonomous analysis for continuous monitoring. Heterogeneous assays such as enzyme-linked immunosorbent assays (ELISA) are commonly used to measure antibodies, antigens, proteins and glycoproteins in biological samples, and with wide applications in disease diagnostics and treatment. ELISA normally requires multiple assay steps to be carried out with complex laboratory equipment. This thesis presents a miniaturised magnetic bead based platform, where a multitude of assays can be implemented using a versatile droplet generation method. The platform incorporates a phased peristaltic micropump and microfluidic chip for droplet generation, a pair of ‘electromagnetic tweezers’ for manipulation of magnetic beads and a spectrophotometer for colorimetric detection. This platform automates the entire process from sample collection to detection. As a proof-of-concept, the platform was used to carry out a heterogeneous assay and analysis of cortisol, a stress related hormone implicated in many diseases including dementia and Cushing’s syndrome. The prototype device is able to analyse sample containing free bioactive cortisol every 10 seconds and has an initial sample-to-signal time of 10 minutes. It is able to measure in the analytical range of 3.175-100 ng/mL with less variability than the well plate-based assay. Droplet microfluidics based platform technology for continuous chemical sensing W. Bhuiyan 3 Ammonium is one of the most important macronutrients and intermediates of the nitrogen cycle. Increased concentrations of ammonium could lead to nutrient enrichment, oxygen depletion and toxicity to aquatic ecosystems. This thesis reports the first of its kind droplet microfluidics ammonium sensor. The sensor miniaturizes the widely adopted indophenol blue assay and can perform high frequency measurement and long-term monitoring with low sample consumption. The sensor has been implemented for two separate applications, which displays its versatility, with the first measuring ammonium in river water samples. Another application of this sensor prototype has been in a sequential batch bioreactor enriched with PHA accumulating bacteria. The sensor can autonomously collect samples (via filter) from the bioreactor, produce droplet trains, regulate temperature for completion of reaction and provide colorimetric measurements (5 per minute) via an in-line spectrophotometer, thus removing human intervention. The preliminary data obtained over a four-day period demonstrates high resolution monitoring and reveals the fast-feeding behaviour of the bacteria. This kind of monitoring data could lead to feedback-controlled bioprocessing and the development of more efficient bioreactors. This thesis further presents the development of a multiple micropump platform for the robust generation of droplet trains, based on phased droplet generation technology. The multiple micropump platform can generate droplet trains containing different sizes, compositions, and sequences on-demand. This setup does not require any change in pump hardware for different assays, therefore making the platform truly versatile. The 3D printed micropumps are robust with low footprint and the platform can be taken to point of care. Latest design can generate droplets from 120 nL upwards with a coefficient of variation of less than 0.7%. Overall, the developments and research findings in this thesis paves the way for a new generation of droplet microfluidic sensors for continuous monitoring.

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Submitted date: 2021
Published date: 2022

Identifiers

Local EPrints ID: 457199
URI: http://eprints.soton.ac.uk/id/eprint/457199
PURE UUID: 306d4f4d-b6c1-42f7-a6a7-b18b5234e80c

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Date deposited: 26 May 2022 16:38
Last modified: 06 Sep 2022 04:01

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