research-article

Fluigi: Microfluidic Device Synthesis for Synthetic Biology

Authors:

Douglas DensmoreAuthors Info & Claims

ACM Journal on Emerging Technologies in Computing Systems (JETC), Volume 11, Issue 3

Article No.: 26, Pages 1 - 19

https://doi.org/10.1145/2660773

Published: 30 December 2014 Publication History

Abstract

One goal of synthetic biology is to design and build genetic circuits in living cells for a range of applications. Our incomplete knowledge of the effects of metabolic load and biological “crosstalk” on the host cell make it difficult to construct multilevel genetic logic circuits in a single cell, limiting the scalability of engineered biological systems. Microfluidic technologies provide reliable and scalable construction of synthetic biological systems by allowing compartmentalization of cells encoding simple genetic circuits and the spatiotemporal control of communication among these cells. This control is achieved via valves on the microfluidics chip which restrict fluid flow when activated. We describe a Computer Aided Design (CAD) framework called “Fluigi” for optimizing the layout of genetic circuits on a microfluidic chip, generating the control sequence of the associated signaling fluid valves, and simulating the behavior of the configured biological circuits. We demonstrate the capabilities of Fluigi on a set of Boolean algebraic benchmark circuits found in both synthetic biology and electrical engineering and a set of assay-based benchmark circuits. The integration of microfluidics and synthetic biology has the capability to increase the scale of engineered biological systems for applications in DNA assembly, biosensors, and screening assays for novel orthogonal genetic parts.

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Cited By

Lashkaripour AMcIntyre DCalhoun SKrauth KDensmore DFordyce P(2024)Design automation of microfluidic single and double emulsion droplets with machine learningNature Communications10.1038/s41467-023-44068-315:1Online publication date: 2-Jan-2024
https://doi.org/10.1038/s41467-023-44068-3
Oliveira SDensmore D(2022)Hardware, Software, and Wetware Codesign Environment for Synthetic BiologyBioDesign Research10.34133/2022/97945102022Online publication date: Jan-2022
https://doi.org/10.34133/2022/9794510
Lashkaripour ARodriguez CMehdipour NMardian RMcIntyre DOrtiz LCampbell JDensmore D(2021)Machine learning enables design automation of microfluidic flow-focusing droplet generationNature Communications10.1038/s41467-020-20284-z12:1Online publication date: 4-Jan-2021
https://doi.org/10.1038/s41467-020-20284-z
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Index Terms

Fluigi: Microfluidic Device Synthesis for Synthetic Biology
1. Applied computing
  1. Physical sciences and engineering
    1. Engineering

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Published In

cover image ACM Journal on Emerging Technologies in Computing Systems

ACM Journal on Emerging Technologies in Computing Systems Volume 11, Issue 3

Special Issue on Computational Synthetic Biology and Regular Papers

December 2014

219 pages

ISSN:1550-4832

EISSN:1550-4840

DOI:10.1145/2711453

Editor:
Krishnendu Chakrabarty
Duke University, USA

Issue’s Table of Contents

Copyright © 2014 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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ACM Journals for the Design of Smart and Connected Systems

Publication History

Published: 30 December 2014

Accepted: 01 August 2014

Revised: 01 June 2014

Received: 01 January 2014

Published in JETC Volume 11, Issue 3

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Cited By

Lashkaripour AMcIntyre DCalhoun SKrauth KDensmore DFordyce P(2024)Design automation of microfluidic single and double emulsion droplets with machine learningNature Communications10.1038/s41467-023-44068-315:1Online publication date: 2-Jan-2024
https://doi.org/10.1038/s41467-023-44068-3
Oliveira SDensmore D(2022)Hardware, Software, and Wetware Codesign Environment for Synthetic BiologyBioDesign Research10.34133/2022/97945102022Online publication date: Jan-2022
https://doi.org/10.34133/2022/9794510
Lashkaripour ARodriguez CMehdipour NMardian RMcIntyre DOrtiz LCampbell JDensmore D(2021)Machine learning enables design automation of microfluidic flow-focusing droplet generationNature Communications10.1038/s41467-020-20284-z12:1Online publication date: 4-Jan-2021
https://doi.org/10.1038/s41467-020-20284-z
Tsur E(2020)Computer-Aided Design of Microfluidic CircuitsAnnual Review of Biomedical Engineering10.1146/annurev-bioeng-082219-03335822:1(285-307)Online publication date: 4-Jun-2020
https://doi.org/10.1146/annurev-bioeng-082219-033358
Lakin MPhillips A(2020)Domain-Specific Programming Languages for Computational Nucleic Acid SystemsACS Synthetic Biology10.1021/acssynbio.0c000509:7(1499-1513)Online publication date: 26-Jun-2020
https://doi.org/10.1021/acssynbio.0c00050
Sanka RLippai JSamarasekera DNemsick SDensmore D(2019)3DμF - Interactive Design Environment for Continuous Flow Microfluidic DevicesScientific Reports10.1038/s41598-019-45623-z9:1Online publication date: 24-Jun-2019
https://doi.org/10.1038/s41598-019-45623-z
Tsur EShamir A(2018)Computer-aided design of resistance micro-fluidic circuits for 3D printingComputer-Aided Design10.1016/j.cad.2017.12.00498:C(12-23)Online publication date: 1-May-2018
https://dl.acm.org/doi/10.1016/j.cad.2017.12.004
Chen YSharma SRoy SHo T(2017)Scheduling and optimization of genetic logic circuits on flow-based microfluidic biochipsProceedings of the Conference on Design, Automation & Test in Europe10.5555/3130379.3130799(1809-1814)Online publication date: 27-Mar-2017
https://dl.acm.org/doi/10.5555/3130379.3130799
Chen YSharma SRoy SHo T(2017)Scheduling and optimization of genetic logic circuits on flow-based microfluidic biochipsDesign, Automation & Test in Europe Conference & Exhibition (DATE), 201710.23919/DATE.2017.7927285(1805-1810)Online publication date: Mar-2017
https://doi.org/10.23919/DATE.2017.7927285
Appleton EMadsen CRoehner NDensmore D(2017)Design Automation in Synthetic BiologyCold Spring Harbor Perspectives in Biology10.1101/cshperspect.a0239789:4(a023978)Online publication date: 28-Feb-2017
https://doi.org/10.1101/cshperspect.a023978

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