BioScript: programming safe chemistry on laboratories-on-a-chip

This paper introduces BioScript, a domain-specific language (DSL) for programmable biochemistry which executes on emerging microfluidic platforms. The goal of this research is to provide a simple, intuitive, and type-safe DSL that is accessible to life science practitioners. The novel feature of the language is its syntax, which aims to optimize human readability; the technical contributions of the paper include the BioScript type system and relevant portions of its compiler. The type system ensures that certain types of errors, specific to biochemistry, do not occur, including the interaction of chemicals that may be unsafe. The compiler includes novel optimizations that place biochemical operations to execute concurrently on a spatial 2D array platform on the granularity of a control flow graph, as opposed to individual basic blocks. Results are obtained using both a cycle-accurate microfluidic simulator and a software interface to a real-world platform

A Framework for Automated Correctness Checking of Biochemical Protocol Realizations on Digital Microfluidic Biochips

Recent advances in digital microfluidic (DMF) technologies offer a promising platform for a wide variety of biochemical applications, such as DNA analysis, automated drug discovery, and toxicity monitoring. For on-chip implementation of complex bioassays, automated synthesis tools have been developed to meet the design challenges. Currently, the synthesis tools pass through a number of complex design steps to realize a given biochemical protocol on a target DMF architecture. Thus, design errors can arise during the synthesis steps. Before deploying a DMF biochip on a safety critical system, it is necessary to ensure that the desired biochemical protocol has been correctly implemented, i.e., the synthesized output (actuation sequences for the biochip) is free from any design or realization errors. We propose a symbolic constraint-based analysis framework for checking the correctness of a synthesized biochemical protocol with respect to the original design specification. The verification scheme based on this framework can detect several post-synthesis fluidic violations and realization errors in 2D-array based or pin-constrained biochips as well as in cyberphysical systems. It further generates diagnostic feedback for error localization. We present experimental results on the polymerase chain reaction (PCR) and in-vitro multiplexed bioassays to demonstrate the proposed verification approach

Droplet routing for digital microfluidic biochips based on microelectrode dot array architecture

A digital microfluidic biochip (DMFB) is a device that digitizes fluidic samples into tiny droplets and operates chemical processes on a single chip. Movement control of droplets can be realized by using electrowetting-on-dielectric (EWOD) technology. DMFBs have high configurability, high sensitivity, low cost and reduced human error as well as a promising future in the applications of point-of-care medical diagnostic, and DNA sequencing. As the demands of scalability, configurability and portability increase, a new DMFB architecture called Microelectrode Dot Array (MEDA) has been introduced recently to allow configurable electrodes shape and more precise control of droplets. The objective of this work is to investigate a routing algorithm which can not only handle the routing problem for traditional DMFBs, but also be able to route different sizes of droplets and incorporate diagonal movements for MEDA. The proposed droplet routing algorithm is based on 3D-A* search algorithm. The simulation results show that the proposed algorithm can reduce the maximum latest arrival time, average latest arrival time and total number of used cells. By enabling channel-based routing in MEDA, the equivalent total number of used cells can be significantly reduced. Compared to all existing algorithms, the proposed algorithm can achieve so far the least average latest arrival time

A microwell array coated with dopaminergic cell adhesive film for single cell analysis in drug discovery

Drug discovery requires prompt decision-making to identify which new chemical entities constitute viable new drug candidates and have a high likelihood of market success. Conventional in vitro cell-based screens sometimes provide misleading data that may not represent in vivo responses. We developed an array of microcellular platforms to provide a uniform environment for single-cell suspension, mimic in vivo functions, and demonstrate the biological effects of a drug on the chemistry of a single cell at the molecular level. Dopaminergic mesoporous inorganic-organic hybrid resin (HR4-DOPA) was used to coat the wells of 200-microwell plates fabricated for these experiments. The biocompatibility of HR4-DOPA was demonstrated by cell adhesion and viability assays. HeLa cell adhesion to the HR4-DOPA film was comparable to the controls: mesoporous inorganic-organic hybrid resin (HR4), ECM proteins (fibronectin and collagen IV), and glass. HeLa cell viability on HR4-DOPA was 86.1%, indicating insignificant growth inhibition. We also investigated the optimal microwell depth and cell concentration for HeLa single-cell occupancy: 25-µm-deep microwells at 1.0 × 10^6 cells/ml demonstrated 67.5% single-cell occupancy while providing sufficient cell-adhesive surface area for long-term cell culture (≥ 3000 µm^2). We obtained singly occupied microwells with only 5.9% array-to-array variation, thus providing adequate throughput for accurate quantification in advanced single-cell analyses. Arrays of HR4-DOPA-coated microwells can be used for high-throughput single-cell-based assays for drug discovery as a “bio-cell processor.” Given that the microwell arrays are integrated in a microfluidic biochip, they can mimic the in vivo microenvironment; we can thus predict in vivo responses through high-throughput, isolated single-cell analysis to assess cellular chemistry at the molecular level.In der Medikamentenforschung ist eine schnelle Entscheidungsfindung erforderlich, um neue chemische Stoffe aus einem Kandidaten-Pool möglicher neuer Medikamente zu finden, die eine Chance auf Markteinführung haben. Konventionelle, in vitro, zell-basierte Methoden liefern oft irreführende Ergebnisse, die nicht der in vivo Antwort entsprechen. Wir haben ein Einzelzell Array in einer mikrofluidischen Platform entwickelt, das ein gleichförmiges Millieu für die Zellen bereit stellt, in vivo Funktionalität imitieren kann und biologische Effekte eines Medikaments auf die Chemie einer einzelnen Zelle auf molekularer Ebene demonstrieren kann. Ein dopaminerges, mesopores, inorganisches/organisches Harz (HR4-DOPA) wurde benutzt um die Microwells einer 200-Microwell-Platte zu beschichten. Die Biokompatibilität dieses Harzes wurde durch Zell-Adhäsions- und Viabilitäts-Experimente nachgewiesen. Die Anlagerung von HeLa Zellen an HR4-DOPA war vergleichbar mit der an den Vergleichssubstanzen: mit HR4 (Hybrides, mesoporöses, inorganisches/organisches Harz), mit Proteinen der extrazellulären Matrix (Fibronectin, Collagen IV) und mit biologischem Glas. Die Viabilität der HeLa Zellen auf HR4-DOPA lag dabei bei 86,1%, was auf eine geringe Wachstumshemmung hindeutet. Die optimale Tiefe der Wells und die optimal Anzahl der Zellen wurden ebenfalls untersucht, wobei eine Zellzahl von 1,0 × 106 Zellen/ml und eine Tiefe der Microwells von 25 µm die besten Ergebnisse lieferten mit einer Einzel-Zell Belegung der Wells von 67,5% und eine genügend große Fläche (≥ 3000 µm2) für die Zellanlagerung und Langzeit-Kultivierung bereit stellt. Die Reproduzierbarkeit der Ergebnisse war dabei hoch, lediglich 5,9% Abweichung wurde festgestellt. Somit liefert dieser Ansatz eine geeignete Methode für die exakte Bestimmung und Quantifizierung verschiedener zellulärer Prozesse bei der state-of-the-art Einzel-Zell Analyse. Anordnungen von HR4-DOPA beschichteten Microwells können für Hochdurchsatz Untersuchungen in der Medikamentenforschung als „Bio-Zell Prozessor“ verwendet werden. Vorausgesetzt die Microwells sind integriert in einen mikrofluidischen Biochip, können diese eine in vivo ähnliche Mikroumgebung bereit stellen für weiterführende Versuche. Somit wird es möglich, in vivo Reaktionen akkurat und in einem Hochdurchsatz Verfahren voraus zu sagen und zelluläre Reaktionen auf der molekularen Ebene zu testen

Autonomous capillary systems for life science research and medical diagnostics

In autonomous capillary systems (CS) minute amounts of liquid are transported owing to capillary forces. Such CSs are appealing due to their portability, flexibility, and the exceptional physical behavior of liquids in micrometer sized microchannels, in particular, capillarity and short diffusion times. CSs have shown to be a promising technology for miniaturized immunoassays in life science research and diagnostics. Building on existing experimental demonstrations of immunoassays in CSs, a theoretical model of such immunoassays is implemented, tools and CSs for performing immunoassays are developed, key functional elements of CSs such as capillary pumps and valves are explored experimentally, and a proof-of-concept of the ultimate goal of one-step immunoassays are given in this work. For the theoretical modeling of immunoassays in CSs a finite difference algorithm is applied to delineate the role of the transport of analyte molecules in the microchannel (convection and diffusion), the kinetics of binding between the analyte and the capture antibodies, and the surface density of the capture antibody on the assay. The model shows that assays can be greatly optimized by varying the flow velocity of the solution of analyte in the microchannels. The model also shows how much the analyte-antibody binding constant and the surface density of the capture antibodies influence the performance of the assay. We derive strategies to optimize assays toward maximal sensitivity, minimal sample volume requirement or fast performance. A method using evaporation for controlling the flow rate in CSs was developed for maximum flexibility for developing assays. The method allows to use small CSs that initially are filled by capillary forces and then provide a well defined area of the liquid-air interface from which liquid can evaporate. Temperature and humidity are continuously measured and Peltier-elements are used to adjust the temperatures in multiple areas of the CSs relative to the dew-point. Thereby flow rates in the range from ~1.2 nL s−1 to ~30 pL s−1 could be achieved in the microchannels. This method was then used for screening cells for surface receptors. CSs, that do not need any peripherals for controlling flow rates become even more appealing. We explored the filling behavior of such CSs having microchannels of various length and large capillary pumps. The capillary pumps comprise microstructures of various sizes and shapes, which are spaced to encode certain capillary pressures. The spacing and shape of the microstructures is also used to orient the filling front to obtain a reliable filling behavior and to minimize the risk of entrapping air. We show how two capillary pumps having different hydrodynamic properties can be connected to program a sequence of slow and fast flow rates in CSs. Liquid filling CSs can hardly be stopped, but in some cases it might be beneficial to do so. In a separate chapter we explore how microstructures need to be designed to use capillary forces to stop, time, or trigger liquids. Besides well-defined flow rates in CSs accurately patterned capture antibodies (cAbs) are key for performing high-sensitive surface immunoassays in CSs. We present a method compatible with mass fabrication for patterning cAbs in dense lines of up to 8 lines per millimeter. These cAbs are used with CSs that are optimized for convenient handling, pipetting of solutions, pumping of liquids such as human serum, and visualization of signals for fluorescence immunoassays to detect c-reactive protein (CRP) with a sensitivity of 0.9 ng mL−1 (7.8 pM) from 1 uL of CRP-spiked human serum, within 11 minutes, with 4 pipetting steps, and a total volume of sample and reagents of <1.5 uL. CSs for diagnostic applications have different requirements than CSs that are used as a research tool in life sciences, where a high flexibility and performance primes over the ease of use and portability of the CSs. We give a proof-of-concept for one-step immunoassays based on CSs which we think can be the base for developing portable diagnostics for point-of-care applications. All reagents are preloaded in the CSs. A sample loaded in the CSs redissolves and reconstitutes the detection antibodies (dAbs), analyte-dAb-complexes are formed and detected downstream in the CSs. A user only needs to load a sample and measure the result using a fluorescence microscope or scanner. C-reactive protein was detected in human serum at clinical concentrations within 10 minutes and using only 2 uL of sample

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

Inexpensive and fast pathogenic bacteria screening using field-effect transistors

While pathogenic bacteria contribute to a large number of globally important diseases and infections, current clinical diagnosis is based on processes that last a few days, employing complex and expensive techniques. Therefore, innovative, simple, rapid and low-cost solutions to effectively reduce the burden of bacterial infections are urgently needed. Here we demonstrate a label-free sensor for fast bacterial detection based on metal–oxide–semiconductor field-effect transistors (MOSFETs). The electric charge of bacteria binding to the glycosylated gates of a MOSFET enables quantification in a straightforward manner. We show that the limit of quantitation is 1.9 × 105 CFU/ml with this simple device, which is more than 10,000-times lower than is possible with existing techniques such as matrix-assisted laser desorption ionisation time-of-flight mass spectrometry (MALDI-ToF) on the same modified surfaces. Moreover, the measurements are extremely fast and the sensor can be mass produced at trivial cost as a tool for initial screening of pathogens