Design Automation in Synthetic Biology

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Abstract

Design automation refers to a category of software tools for designing systems that work together in a workflow for designing, building, testing, and analyzing systems with a target behavior. In synthetic biology, these tools are called bio-design automation (BDA) tools. In this review, we discuss the BDA tools areas—specify, design, build, test, and learn—and introduce the existing software tools designed to solve problems in these areas. We then detail the functionality of some of these tools and show how they can be used together to create the desired behavior of two types of modern synthetic genetic regulatory networks.

Abstract

Engineering biological systems is a complex undertaking and requires computational approaches. Bio-design automation tools in five areas—specification, design, building, testing, and learning—will accelerate progress.

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Most cited references 74

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Improved tools for biological sequence comparison.

W R Pearson, D J Lipman (1988)

We have developed three computer programs for comparisons of protein and DNA sequences. They can be used to search sequence data bases, evaluate similarity scores, and identify periodic structures based on local sequence similarity. The FASTA program is a more sensitive derivative of the FASTP program, which can be used to search protein or DNA sequence data bases and can compare a protein sequence to a DNA sequence data base by translating the DNA data base as it is searched. FASTA includes an additional step in the calculation of the initial pairwise similarity score that allows multiple regions of similarity to be joined to increase the score of related sequences. The RDF2 program can be used to evaluate the significance of similarity scores using a shuffling method that preserves local sequence composition. The LFASTA program can display all the regions of local similarity between two sequences with scores greater than a threshold, using the same scoring parameters and a similar alignment algorithm; these local similarities can be displayed as a "graphic matrix" plot or as individual alignments. In addition, these programs have been generalized to allow comparison of DNA or protein sequences based on a variety of alternative scoring matrices.

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ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules.

Andrew Leaver-Fay, Michael Tyka, Steven M. Lewis … (2011)

We have recently completed a full re-architecturing of the ROSETTA molecular modeling program, generalizing and expanding its existing functionality. The new architecture enables the rapid prototyping of novel protocols by providing easy-to-use interfaces to powerful tools for molecular modeling. The source code of this rearchitecturing has been released as ROSETTA3 and is freely available for academic use. At the time of its release, it contained 470,000 lines of code. Counting currently unpublished protocols at the time of this writing, the source includes 1,285,000 lines. Its rapid growth is a testament to its ease of use. This chapter describes the requirements for our new architecture, justifies the design decisions, sketches out central classes, and highlights a few of the common tasks that the new software can perform. © 2011 Elsevier Inc. All rights reserved.

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Programming cells by multiplex genome engineering and accelerated evolution.

Harris Wang, Farren J. Isaacs, Peter A Carr … (2009)

The breadth of genomic diversity found among organisms in nature allows populations to adapt to diverse environments. However, genomic diversity is difficult to generate in the laboratory and new phenotypes do not easily arise on practical timescales. Although in vitro and directed evolution methods have created genetic variants with usefully altered phenotypes, these methods are limited to laborious and serial manipulation of single genes and are not used for parallel and continuous directed evolution of gene networks or genomes. Here, we describe multiplex automated genome engineering (MAGE) for large-scale programming and evolution of cells. MAGE simultaneously targets many locations on the chromosome for modification in a single cell or across a population of cells, thus producing combinatorial genomic diversity. Because the process is cyclical and scalable, we constructed prototype devices that automate the MAGE technology to facilitate rapid and continuous generation of a diverse set of genetic changes (mismatches, insertions, deletions). We applied MAGE to optimize the 1-deoxy-D-xylulose-5-phosphate (DXP) biosynthesis pathway in Escherichia coli to overproduce the industrially important isoprenoid lycopene. Twenty-four genetic components in the DXP pathway were modified simultaneously using a complex pool of synthetic DNA, creating over 4.3 billion combinatorial genomic variants per day. We isolated variants with more than fivefold increase in lycopene production within 3 days, a significant improvement over existing metabolic engineering techniques. Our multiplex approach embraces engineering in the context of evolution by expediting the design and evolution of organisms with new and improved properties.

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Author and article information

Journal

Journal ID (nlm-ta): Cold Spring Harb Perspect Biol

Journal ID (iso-abbrev): Cold Spring Harb Perspect Biol

Journal ID (publisher-id): cshperspect

Journal ID (hwp): cshperspect

Title: Cold Spring Harbor Perspectives in Biology

Publisher: Cold Spring Harbor Laboratory Press (Cold Spring Harbor, New York )

ISSN (Electronic): 1943-0264

Publication date (Print): April 2017

Volume: 9

Issue: 4

Electronic Location Identifier: a023978

Affiliations

[1 ]Department of Genetics, Harvard Medical School, Harvard University, Boston, Massachusetts 02115

[2 ]Biological Design Center, Boston University, Boston, Massachusetts 02215

[3 ]Department of Electrical and Computer Engineering, Boston University, Boston, Massachusetts 02215

Author notes

Correspondence: dougd@ 123456bu.edu

Article

Accession ID: PMC5378053 Pmcid ID: PMC5378053 Pmc-uid ID: 5378053 Publisher ID: a023978

DOI: 10.1101/cshperspect.a023978

PMC ID: 5378053

PubMed ID: 28246188

SO-VID: b009eb67-70a7-4221-bd72-72f920f89510

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Pages: 27

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Design Automation in Synthetic Biology

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Most cited references 74

Improved tools for biological sequence comparison.

ROSETTA3: an object-oriented software suite for the simulation and design of macromolecules.

Programming cells by multiplex genome engineering and accelerated evolution.

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