Design automation of microfluidic droplet sorting platforms

Both basic research and biological design require high throughput screening to parse through the massive amounts of variants generated in experiments. However, the cost and expertise needed for use of such technology limit accessibility. Simple and reproducible designs of a sorting platform would reduce the barrier for implementation of affordable bench-top screening platforms. Droplet microfluidics present a promising approach for automating biology, reducing reaction volumes to picoliter droplets and allowing for deterministic manipulation of samples. Droplet microfluidics have been used extensively for high throughput screening and directed evolution, yet limitations in fabrication have prevented the characterization needed for a design tool and subsequent widespread adoption. Here, we present a finite element analysis (FEA) model-based design framework for dielectrophoretic droplet microfluidic sorters and its preliminary experimental validation. This framework extends previous work from our group creating microfluidic designs tools, increasing their usability in the lab

Automating functional enzyme screening & characterization

This work has been presented in the 10th IWBDA workshop.Microfluidics continue to gain traction as an inexpensive alternative to standard multi-well plate-based, and flow cytometry- based, assay platforms. These devices are especially useful for the types of ultra-high throughput screens needed for enzyme discovery applications where large numbers (>106) of unique samples must be screened rapidly1. Coupled with cell-free protein synthesis2, microfluidics are being used to identify novel enzymes useful for a variety of applications with unprecedented speed. However, these devices are typically produced using PDMS, and require considerable infrastructure and artisanal skill to fabricate, limiting their accessibility. Likewise, enzyme hits obtained from a screen are often validated manually and would benefit from automation of downstream validation processes. To address these limitations, we propose a workflow which leverages software tools to automate the rapid design and fabrication of low-cost polycarbonate microfluidic devices for use as high-throughput screening platforms for enzyme discovery, as well as an automated DNA assembly tool to streamline validation of screening candidates. Using this workflow, we aim to identify novel oxidoreductase enzymes from environmental metagenomic DNA libraries, for use in electrochemical biosensors

A reverse predictive model towards design automation of microfluidic droplet generators

This work has been presented in the 10th IWBDA workshop.Droplet-based microfluidic devices in comparison to test tubes can reduce reaction volumes 10^9 times and more due to the encapsulation of reactions in micro-scale droplets [4]. This volume reduction, alongside higher accuracy, higher sensitivity and faster reaction time made droplet microfluidics a superior platform particularly in biology, biomedical, and chemical engineering. However, a high barrier of entry prevents most of life science laboratories to exploit the advantages of microfluidics. There are two main obstacles to the widespread adoption of microfluidics, high fabrication costs, and lack of design automation tools. Recently, low-cost fabrication methods have reduced the cost of fabrication significantly [7]. Still, even with a low-cost fabrication method, due to lack of automation tools, life science research groups are still reliant on a microfluidic expert to develop any new microfluidic device [3, 5]. In this work, we report a framework to develop reverse predictive models that can accurately automate the design process of microfluidic droplet generators. This model takes prescribed performance metrics of droplet generators as the input and provides the geometry of the microfluidic device and the fluid and flow settings that result in the desired performance. We hope this automation tool makes droplet-based microfluidics more accessible, by reducing the time, cost, and knowledge needed for developing a microfluidic droplet generator that meets certain performance requirement

Design automation based on fluid dynamics

This article was accepted and presented at the 9th International Workshop on Bio-Design Automation, Pittsburgh, Pennsylvania (2017).Microfluidic devices provide researchers with numerous advantages such as high throughput, increased sensitivity and accuracy, lower cost, and reduced reaction time. However, design, fabrication, and running a microfluidic device are still heavily reliant on expertise. Recent studies suggest micro-milling can be a semi-automatic, inexpensive, and simple alternative to common fabrication methods. Micro-milling does not require a clean-room, mask aligner, spin-coater, and Plasma bonder, thus cutting down the cost and time of fabrication significantly. Moreover, through this protocol researchers can easily fabricate microfluidic devices in an automated fashion eschewing levels of expertise required for typical fabrication methods, such as photolithography, soft-lithography, and etching. However, designing a microfluidic chip that meets a certain set of requirements is still heavily dependent on a microfluidic expert, several days of simulation, and numerous experiments to reach the required performance. To address this, studies have reported random automated design of microfluidic devices based on numerical simulations for micro-mixing. However, random design generation is heavily reliant on time-consuming simulations carried out beforehand, and is prone to error due to the accuracy limitations of the numerical method. On the other hand, by using micro-milling for ultra-fast and inexpensive fabrication of microfluidic devices and Taguchi design of experiments for state-space exploration of all of the geometric parameters, we are able to generate a database of geometries, flow rates, and flow properties required for a single primitive to carry out a specified microfluidic task

Integration of performance metrics into microfluidic design automation

Accepted manuscripthttps://www.iwbdaconf.org/2019/docs/IWBDA19Proceedings.pd

Automated robotic liquid handling assembly of modular DNA devices

Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available "design space" represented by "devices" created as combinations of individual genetic components. However, manual assembly of such large numbers of devices is time-intensive, error-prone, and costly. The increasing sophistication and scale of synthetic biology research necessitates an efficient, reproducible way to accommodate large-scale, complex, and high throughput device construction. Here, a DNA assembly protocol using the Type-IIS restriction endonuclease based Modular Cloning (MoClo) technique is automated on two liquid-handling robotic platforms. Automated liquid-handling robots require careful, often times tedious optimization of pipetting parameters for liquids of different viscosities (e.g. enzymes, DNA, water, buffers), as well as explicit programming to ensure correct aspiration and dispensing of DNA parts and reagents. This makes manual script writing for complex assemblies just as problematic as manual DNA assembly, and necessitates a software tool that can automate script generation. To this end, we have developed a web-based software tool, http://mocloassembly.com, for generating combinatorial DNA device libraries from basic DNA parts uploaded as Genbank files. We provide access to the tool, and an export file from our liquid handler software which includes optimized liquid classes, labware parameters, and deck layout. All DNA parts used are available through Addgene, and their digital maps can be accessed via the Boston University BDC ICE Registry. Together, these elements provide a foundation for other organizations to automate modular cloning experiments and similar protocols. The automated DNA assembly workflow presented here enables the repeatable, automated, high-throughput production of DNA devices, and reduces the risk of human error arising from repetitive manual pipetting. Sequencing data show the automated DNA assembly reactions generated from this workflow are ~95% correct and require as little as 4% as much hands-on time, compared to manual reaction preparation

Standardizing design performance comparison in microfluidic manufacturing

Microfluidic devices published in literature today lack sufficient information for automating the physical design process. Moreover, the constantly changing landscape of manufacturing and technological requirements poses a large problem in the physical design automation space. In this talk, we discuss some of the methodologies and standards formulated by CIDAR at BU and CARES at UC Riverside that allow not only allow the researchers in the physical design automation space to share and compare their results but also provide means for capturing the Specify, Design and Build lifecycle in microfluidic design

mLSI design with MINT

Fluigi is a microfluidic design framework that allows researchers to realize abstract descriptions of liquid flow relationships automatically as physical devices and corresponding control software. Its goal is to provide synthetic biology researchers with the tools to use microfluidics for novel computation, discovery, and test applications. A critical component of this work-flow is MINT, a format for describing the microfluidic components and the connectivity of the control and flow layers in the microfluidic device. This work describes MINT and where it falls in the larger Fluigi software flow in design mLSI system for Synthetic Biology

Function-driven, graphical design tool for microfluidic chips: 3DuF

The use of microfluidic chips for applications in biology to reduce the cost, time, and difficulty of automating experiments, while promising, has proven to have barriers to entry. In particular, the cost of the equipment required for manufacturing techniques like soft lithography, the difficulty in designing functional microfluidic chips, and the time associated with manufacturing them have made rapid production for prototyping and iterative design difficult. Our lab’s microfluidics design flow is capable of automating much of the design process of microfluidic chips using the paradigm of defining them as primitives placed on a layout grid and exporting standard formats for use in fabrication. 3DuF, a design tool that allows the user to carry out the placement and connection of primitives through a browser-based GUI, simplifies the design process to specifying the primitives through parameters and using a pointer to connect them with channels. But this approach assumes that the designer knows exactly what physical dimensions the primitives need for the chip to perform adequately for experiments, which may not be the case if sufficient literature or a fluid dynamics expertise are not present. By communicating with DAFD, our lab’s currently in-development database and model-fitting framework, 3DuF will be able to define microfluidic primitives for placement on chip layouts not only through physical dimensions, but also by specific performance metrics desired of the primitives’ functions, which will result in automatically generated dimensions for those primitives. This will allow chip design through the simple paradigm of using a GUI to place primitives and connect them with channels, while also making a useful definition of those primitives for the designer’s needs less reliant on their fluid dynamics expertise

MINT - Microfluidic Netlist

Fluigi is a microfluidic design framework that allows researchers to realize abstract descriptions of liquid flow relationships automatically as physical devices and corresponding control software. Its goal is to provide synthetic biology researchers with the tools to use microfluidics for novel computation, discovery, and test applications. A critical component of this work-flow is MINT, a format for describing the microfluidic components and the connectivity of the control and flow layers in the microfluidic device. This work describes MINT and where it falls in the larger Fluigi software flow