Fluigi: an end-to-end software workflow for microfluidic design

One goal of synthetic biology is to design and build genetic circuits in living cells for a range of applications with implications in health, materials, and sensing. Computational design methodologies allow for increased performance and reliability of these circuits. Major challenges that remain include increasing the scalability and robustness of engineered biological systems and streamlining and automating the synthetic biology workflow of “specify-design-build-test.” I summarize the advances in microfluidic technology, particularly microfluidic large scale integration, that can be used to address the challenges facing each step of the synthetic biology workflow for genetic circuits. Microfluidic technologies allow precise control over the flow of biological content within microscale devices, and thus may provide more reliable and scalable construction of synthetic biological systems. However, adoption of microfluidics for synthetic biology has been slow due to the expert knowledge and equipment needed to fabricate and control devices. I present an end-to-end workflow for a computer-aided-design (CAD) tool, Fluigi, for designing microfluidic devices and for integrating biological Boolean genetic circuits with microfluidics. The workflow starts with a ``netlist" input describing the connectivity of microfluidic device to be designed, and proceeds through placement, routing, and design rule checking in a process analogous to electronic computer aided design (CAD). The output is an image of the device for printing as a mask for photolithography or for computer numerical control (CNC) machining. I also introduced a second workflow to allocate biological circuits to microfluidic devices and to generate the valve control scheme to enable biological computation on the device. I used the CAD workflow to generate 15 designs including gradient generators, rotary pumps, and devices for housing biological circuits. I fabricated two designs, a gradient generator with CNC machining and a device for computing a biological XOR function with multilayer soft lithography, and verified their functions with dye. My efforts here show a first end-to-end demonstration of an extensible and foundational microfluidic CAD tool from design concept to fabricated device. This work provides a platform that when completed will automatically synthesize high level functional and performance specifications into fully realized microfluidic hardware, control software, and synthetic biological wetware

World-to-digital microfluidics for transformation and enzymatic assays

Digital microfluidics (DMF) is a technique for the manipulation of discrete droplets on an array of electrodes, which allows the controlled movement of fluids and represents an alternative from the conventional microfluidic paradigm of transporting fluids in enclosed channels. One of the major benefits of DMF is that fluid motion and control is achieved without external pumps and fabricated valves – it only requires the use of electric fields. The automation component of DMF has pushed the barriers of this ‘lab-on-chip’ technology; however, integration with external components (i.e. world-to-chip) interfaces has been a challenge. For example, the delivering of the biological fluids to the chip and integrating temperature control on a single platform are considered as two world-to-chip challenges in DMF. To address these two challenges, my thesis describes two world-to-chip components that are integrated with the DMF device: reagent delivery and temperature control. This new platform enables us to perform a variety of biological or chemical experiments on a chip with reduced manual intervention. Specifically, the new platform enabled an increase in reservoir volume on the chip by 40-fold from ~10 µL to 400 µL which allowed more reproducible dispensing and eliminated the need to refill the reservoirs during the biological assay. In addition, we integrated a closed-loop temperature control system that enabled fast and rapid changes in temperature on the chip. To show the utility of the world-to-chip interfaces, we validated the system by automating bacterial transformation and enzymatic assay procedures, which show that both procedures require world-to-chip interfaces for accurate and precise implementation. Overall, we propose that this system has the potential to be integrated for other types of biological assays and experiments which require fluidic control, automation, and temperature control

Optimisation of microfluidic experiments for model calibration of a synthetic promoter in S. cerevisiae

This thesis explores, implements, and examines the methods to improve the efficiency of model calibration experiments for synthetic biological circuits in three aspects: experimental technique, optimal experimental design (OED), and automatic experiment abnormality screening (AEAS). Moreover, to obtain a specific benchmark that provides clear-cut evidence of the utility, an integrated synthetic orthogonal promoter in yeast (S. cerevisiae) and a corresponded model is selected as the experiment object. This work first focuses on the “wet-lab” part of the experiment. It verifies the theoretical benefit of adopting microfluidic technique by carrying out a series of in-vivo experiments on a developed automatic microfluidic experimental platform. Statistical analysis shows that compared to the models calibrated with flow-cytometry data (a representative traditional experimental technique), the models based on microfluidic data of the same experiment time give significantly more accurate behaviour predictions of never-encountered stimuli patterns. In other words, compare to flow-cytometry experiments, microfluidics can obtain models of the required prediction accuracy within less experiment time. The next aspect is to optimise the “dry-lab” part, i.e., the design of experiments and data processing. Previous works have proven that the informativeness of experiments can be improved by optimising the input design (OID). However, the amount of work and the time cost of the current OID approach rise dramatically with large and complex synthetic networks and mathematical models. To address this problem, this thesis introduces the parameter clustering analysis and visualisation (PCAV) to speed up the OID by narrowing down the parameters of interest. For the first time, this thesis proposes a parameter clustering algorithm based on the Fisher information matrix (FIMPC). Practices with in-silico experiments on the benchmarking promoter show that PCAV reduces the complexity of OID and provides a new way to explore the connections between parameters. Moreover, the analysis shows that experiments with FIMPC-based OID lead to significantly more accurate parameter estimations than the current OID approach. Automatic abnormality screening is the third aspect. For microfluidic experiments, the current identification of invalid microfluidic experiments is carried out by visual checks of the microscope images by experts after the experiments. To improve the automation level and robustness of this quality control process, this work develops an automatic experiment abnormality screening (AEAS) system supported by convolutional neural networks (CNNs). The system learns the features of six abnormal experiment conditions from images taken in actual microfluidic experiments and achieves identification within seconds in the application. The training and validation of six representative CNNs of different network depths and design strategies show that some shallow CNNs can already diagnose abnormal conditions with the desired accuracy. Moreover, to improve the training convergence of deep CNNs with small data sets, this thesis proposes a levelled-training method and improves the chance of convergence from 30% to 90%. With a benchmark of a synthetic promoter model in yeast, this thesis optimises model calibration experiments in three aspects to achieve a more efficient procedure: experimental technique, optimal experimental design (OED), and automatic experiment abnormality screening (AEAS). In this study, the efficiency of model calibration experiments for the benchmarking model can be improved by: adopting microfluidics technology, applying CAVP parameter analysis and FIMPC-based OID, and setting up an AEAS system supported by CNN. These contributions have the potential to be exploited for designing more efficient in-vivo experiments for model calibration in similar studies

A Microfluidic System for Pathogen Detection Based on DNA Hybridization

With the great development of the microfluidics, the applications of microfluidic devices in conducting biomedical research have been drawn substantial interests from scientists and researchers all over the world. These microfluidic lab-on-a-chip systems create clinically useful technologies and have a number of competitive advantages over the conventional biomedical instruments due to the reduced reagents/samples consumption, decreased analysis times and operational costs. In addition, the microfluidic lab-on-a-chip systems facilitate the development of the portable devices and have the ability of automatically performing the multiple assay processes. At the present, increasing attention has been paid to the preventive detection of foodborne pathogens as the foodborne illness becomes a serious concern to the public health throughout the world. Early detection and notification of foodborne pathogenic bacteria is therefore of considerable significance in food safety control. DNA-based hybridization technique, as a rapid diagnosis tool for detecting foodborne pathogens, has presented distinctive advantages over the conventional microbiological culture-based methods for pathogen detection such as high sensitivity, specificity and rapidity, especially in the detection of the bacteria samples of low concentrations. In this thesis, a microfluidic platform combining DNA hybridization assay technique to detect foodborne pathogens is investigated. As the hybridization assay involves sequential loading and washing processes, magnetic beads are used as the matrix to immobilize the hybridization product; meanwhile microvalves are designed in the microfluidic chip to manage the sequential flow loading. In the first two designs, gravity force is used to drive the flow in the microchannels. A pair of electrokinetically-controlled oil droplet valves and electrothermally actuated phase change microvalves are used in these two microfluidic system, respectively. LabVIEW program was coded to implement the automatic operations of the assay. In the further improved microfluidic system, electrokinetics is applied to drive the flow, and a programmable High Voltage Sequencer is used to achieve the flow transportation automatically in an assay analysis cycle. Since no microvalves are required, this electrokinetics-based assay simplifies the preparation process of the microfluidic chip. Light absorption detection is used to analyze the quantified concentrations of the samples. This optical detection is verified firstly by a microscope. Later, a low-cost, miniaturized optical module is developed, which consists of a photo-detector and LED. The optical detection module is controlled by self-made circuit and coded LabVIEW program. iv To examine the performance of the microfluidic system, Salmonella and Listeria monocytogenes are used as a sample pathogen models. Based on the obtained results, the presented system successfully achieve the significantly reduction in reagent / sample consumption (up to 40 folds) compared with using the commercial test kit following the same protocol in conventional labs. In addition, the quantitative detection can be obtained in approximately 20 min, and the detection limit is as low as 103~104 CFU/mL. The microfluidic DNA hybridization assay chip demonstrated in this thesis presents an excellent potential in the development of a portable device for point-of-testing applications

Optimization of Continuous Flow Polymerase Chain Reaction with Microfluidic Reactors

The polymerase chain reaction (PCR) is an enzyme catalyzed technique, used to amplify the number of copies of a specific ~gion ofDNA. This technique can be used to identify, with high-probability, disease-causing viruses and/or bacteria, the identity of a deceased person, or a criminal suspect. Even though PCR has had a tremendous impact in clinical diagnostics, medical sciences and forensics, the technique presents several drawbacks. For example, the costs associated with each reaction are high and the reaction is prone to cont,amination due its inherent efficiency and high sensitivity. By employing microfluidic' systems to perform PCR these advantages can be circumvented. This thesis addresses implementation issues that adversely affect PCR . in microdevices and aims to improve the efficiency of the reaction by introducing novel materials and methods to existing protocols. Molecule-surface-interactions and ,' temperature control/determination are the main focus within this work. Microchannels and microreactors are char:acterized by extremely high surface-tovolume ratios. This dictates that surfaces play a dominant role in defining the efficiency ofPCR (and other synthetic processes) through increased molecule-surface interactions. In a multicomponent reaction system where the concentration of several components needs to be maintained the situation is particularly complicated. For example, inhibition of PCR is commonly observed due to polymerase adsorption on channel walls. Within??????? this work a number of different surface treatments have been investigated with a view to minimizing adsorption effects on microfluidic channels. In addition, novel studies introducing the use of superhydrophobic coatings on microfluidic channels are presented. Specifically superhydrophobic surfaces exhibiting contact angles in excess of 1500 have been created by growing Copper oxide and Zinc oxide' nanoneedles and silica-sol gel micropores on microfluidic channels. Such surfaces utilize additional surface roughness to promote hydrophobicity. Aqueous solutions in contact with superhydrophobic surfaces are suspended by bridging-type wetting, and therefore the fraction of the surface in contact with the aqueous layer is significantly lower than for a flat surface. An additional difficulty associated with PCR on microscale is the detennination and control of temperature. When perfonning PCR, the ability to accurately control system temperatures is especially important since both primer annealing to singlestranded DNA and the catalytic extension of this primer to fonn the complementary strand will only proceed in an efficient manner within relatively narrow temperature ranges. It is therefore imperative to be able to accurately monitor the temperature distributions in such microfluidic channels. In this thesis, fluorescence lifetime imaging (FLIM) is used as a novel method to directly quantify temperature within microchannel environments. The approach, which includes the use of multiphoton e'xcitation to achieve optical sectioning, allows for high spatial and temporal resolution, operates over a wide temperature range and can be used to rapidly quantify local temperatures with high precision.Imperial Users onl

Micro- and Nanofluidics for Bionanoparticle Analysis

Bionanoparticles such as microorganisms and exosomes are recoganized as important targets for clinical applications, food safety, and environmental monitoring. Other nanoscale biological particles, includeing liposomes, micelles, and functionalized polymeric particles are widely used in nanomedicines. The recent deveopment of microfluidic and nanofluidic technologies has enabled the separation and anslysis of these species in a lab-on-a-chip platform, while there are still many challenges to address before these analytical tools can be adopted in practice. For example, the complex matrices within which these species reside in create a high background for their detection. Their small dimension and often low concentration demand creative strategies to amplify the sensing signal and enhance the detection speed. This Special Issue aims to recruit recent discoveries and developments of micro- and nanofluidic strategies for the processing and analysis of biological nanoparticles. The collection of papers will hopefully bring out more innovative ideas and fundamental insights to overcome the hurdles faced in the separation and detection of bionanoparticles

An Outlook on Design Technologies for Future Integrated Systems

The economic and social demand for ubiquitous and multifaceted electronic systems-in combination with the unprecedented opportunities provided by the integration of various manufacturing technologies-is paving the way to a new class of heterogeneous integrated systems, with increased performance and connectedness and providing us with gateways to the living world. This paper surveys design requirements and solutions for heterogeneous systems and addresses design technologies for realizing them

Factories of the Future

Engineering; Industrial engineering; Production engineerin