INSPIRE: Modeling and Optimization of DNA Manufacturing Processes

Source of Support: NSF

Abstract: This INSPIRE award is partially funded by the Advances in Biological Informatics Program in the Division of Biological Infrastructure in the Directorate for Biological Sciences, the Manufacturing Enterprise Systems Program in the Division of Civil, Mechanical and Manufacturing Innovation in the Directorate for Engineering and the Networks and Regulation Cluster in the Division of Molecular Cellular Biology in the Directorate for Biological Sciences. Virginia Polytechnic University is awarded a grant to evaluate the feasibility and benefits of analyzing DNA fabrication processes by using techniques from Industrial and Systems Engineering (ISE). The premise is that these techniques can be used to better design, plan, execute, and control DNA fabrication processes and that this change of paradigm will help identify preferred manufacturing strategies for DNA fabrication. Adapting approaches used in other industries will lead to new strategies for process planning, monitoring, and control that meet the need of DNA fabrication. The project has four complementary objectives: (1) explore the goals and requirements of the process, conduct functional analysis, and investigate resource and workflow strategies for DNA fabrication; (2) implement laboratory pipelines to generate different types of constructs illustrating a broad range of fabrication problems and biological domains; (3) evaluate algorithms to estimate high-error rates in low volume processes, implement monitoring strategies, and compare the performance of different manufacturing strategies applicable to specific DNA manufacturing problems; and (4) provide cross-training opportunities in molecular biology and ISE for undergraduate students, graduate students, and post-doctoral fellows.

DNA fabrication is the process of combining natural and chemically synthetized DNA fragments together in order to make larger DNA molecules that conform to computer-designed sequences. DNA fabrication includes gene synthesis, the process of assembling chemically synthesized oligonucleotides into double- stranded DNA fragments. DNA fabrication also includes more traditional activities, such as the development of mutant collections, plasmid libraries, and refactored genomes. In this broad perspective, most biologists practice DNA fabrication, although they are more likely to call it molecular biology or genetic engineering. DNA fabrication projects rely on low-cost instruments and laboratory infrastructure commonly available to life scientists. Unfortunately, the lack of a suitable framework to analyze DNA fabrication is limiting its effectiveness, requiring tools to manage the complex flows of information and materials typically needed in these projects.

There is no evidence of previous application of ISE methods to the fabrication of DNA or other laboratory processes in the life sciences. This new interdisciplinary opportunity reprises the revolution that hit the life sciences 15 years ago with the emergence of systems biology. Biologists have traditionally assumed that biological processes were too complicated to be modeled mathematically like physical systems. Challenges to this assumption among physicists and engineers has catalyzed a renewal of biological interest in analyzing laboratory processes with ISE tools. The goal of this project is to anticipate, and prepare for, the next 15 years when biologists will use engineering methods to perform experiments orders of magnitude larger than is possible today.

Improving quality, avoiding delays and errors, and substantially decreasing the time to implementation of biomedical discoveries are prime objectives of the National Institutes of Health Roadmap for Medical Research. DNA fabrication processes are representative of processes across many life science specialties that will benefit from the results of this project. The reward of this project is a much-needed increase in productivity of the life science research enterprise. The national R&D infrastructure needs to be more fiscally responsible in these times of constrained budgets; in order to enhance U.S competitiveness, it is necessary to find ways of producing more data, more discoveries, and more applications with stable or shrinking resources.


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