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High-throughput Generation and Evaluation of Genetic Circuit Libraries

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What:
Poster
When:
5:00 PM, Saturday 15 Oct 2022 (1 hour 30 minutes)
Breaks:
Break: Tours of Concordia Genome Foundry   05:00 PM to 07:00 PM (2 hours)
Dinner   06:30 PM to 08:30 PM (2 hours)
Where:
RF building - Loyola Jesuit Hall and Conference Centre (ground floor) - RF building - Loyola Jesuit Hall and Conference Centre   Virtual session
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Theme:
Poster

Haseong Kim1),2),4) Byung-Kwan Cho1),3) Seong-Goo Lee1),2),4)

 

1)K-Biofoundryβ, Korea Research Institute of Bioscience and Biotechnology, Daejeon, Republic of Korea

2)Synthetic Biology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea

3)Department of Biological Sciences, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea

4)Biosystems and Bioengineering Program, University of Science and Technology (UST), Daejeon, Republic of Korea

 

This study presents a high-throughput part library characterization technique by using solid plate-based quantitative fluorescence assay for phenotyping, and barcode tagging-based long-read sequencing for genotyping. High concentration of DNA parts in the form of duplex oligo were directly used for part library assembly which can generate diverse phenotypes. The barcode tagging-based long-read sequencing technique enabled rapid identification of all DNA part combinations with a single sequencing experiment. We confirmed that fluorescence intensities of colonies on plates were comparable to single-cell level fluorescence from a high-end flow-cytometry device and developed high-throughput image analysis pipeline. Using this techniques, forty-four DNA parts (21 promoters and 23 RBSs) were successfully characterized in 72 h. K-biofoundry beta is building a part repository, Partbank, for storing the quantitatively characterized parts and providing a circuit design software tool. We anticipate that this high-throughput technique with automated machines will contribute to increase the speed and scale in optimizing genetic circuits and metabolic pathways. 

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