ArticlePloS one2015
Programmed evolution for optimization of orthogonal metabolic output in bacteria.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
What it found
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Who cites it
6 citing papers in PubMed, 26 citations in OpenAlex.
- Next-level riboswitch development-implementation of Capture-SELEX facilitates identification of a new synthetic riboswitch.Nucleic acids research · 2019Article
- Attempted use of PACE for riboswitch discovery generates three new translational theophylline riboswitch side products.BMC research notes · 2018Article
- In vivo biosensors: mechanisms, development, and applications.Journal of industrial microbiology & biotechnology · 2018Article
- rClone Red facilitates bacterial gene expression research by undergraduates in the teaching laboratory.Synthetic biology (Oxford, England) · 2018Article
- What is Proof of Concept Research and how does it Generate Epistemic and Ethical Categories for Future Scientific Practice?Science and engineering ethics · 2016Article
- Global characterization of in vivo enzyme catalytic rates and their correspondence to in vitro kcat measurements.Proceedings of the National Academy of Sciences of the United States of America · 2016Article
Corrections and comments
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Authors and funding
55 authors at 2 institutions in 1 country.
Funding
Abstract
Current use of microbes for metabolic engineering suffers from loss of metabolic output due to natural selection. Rather than combat the evolution of bacterial populations, we chose to embrace what makes biological engineering unique among engineering fields - evolving materials. We harnessed bacteria to compute solutions to the biological problem of metabolic pathway optimization. Our approach is called Programmed Evolution to capture two concepts. First, a population of cells is programmed with DNA code to enable it to compute solutions to a chosen optimization problem. As analog computers, bacteria process known and unknown inputs and direct the output of their biochemical hardware. Second, the system employs the evolution of bacteria toward an optimal metabolic solution by imposing fitness defined by metabolic output. The current study is a proof-of-concept for Programmed Evolution applied to the optimization of a metabolic pathway for the conversion of caffeine to theophylline in E. coli. Introduced genotype variations included strength of the promoter and ribosome binding site, plasmid copy number, and chaperone proteins. We constructed 24 strains using all combinations of the genetic variables. We used a theophylline riboswitch and a tetracycline resistance gene to link theophylline production to fitness. After subjecting the mixed population to selection, we measured a change in the distribution of genotypes in the population and an increased conversion of caffeine to theophylline among the most fit strains, demonstrating Programmed Evolution. Programmed Evolution inverts the standard paradigm in metabolic engineering by harnessing evolution instead of fighting it. Our modular system enables researchers to program bacteria and use evolution to determine the combination of genetic control elements that optimizes catabolic or anabolic output and to maintain it in a population of cells. Programmed Evolution could be used for applications in energy, pharmaceuticals, chemical commodities, biomining, and bioremediation.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.