Author
Listed:
- Donghui Choe
(Korea Advanced Institute of Science and Technology
Korea Advanced Institute of Science and Technology)
- Jun Hyoung Lee
(Korea Advanced Institute of Science and Technology
Korea Advanced Institute of Science and Technology
Intelligent Synthetic Biology Center)
- Minseob Yoo
(Korea Advanced Institute of Science and Technology
Korea Advanced Institute of Science and Technology)
- Soonkyu Hwang
(Korea Advanced Institute of Science and Technology
Korea Advanced Institute of Science and Technology)
- Bong Hyun Sung
(Intelligent Synthetic Biology Center
Korea Research Institute of Bioscience and Biotechnology)
- Suhyung Cho
(Korea Advanced Institute of Science and Technology
Korea Advanced Institute of Science and Technology)
- Bernhard Palsson
(University of California San Diego
University of California San Diego)
- Sun Chang Kim
(Korea Advanced Institute of Science and Technology
Korea Advanced Institute of Science and Technology
Intelligent Synthetic Biology Center)
- Byung-Kwan Cho
(Korea Advanced Institute of Science and Technology
Korea Advanced Institute of Science and Technology
Intelligent Synthetic Biology Center)
Abstract
Synthetic biology aims to design and construct bacterial genomes harboring the minimum number of genes required for self-replicable life. However, the genome-reduced bacteria often show impaired growth under laboratory conditions that cannot be understood based on the removed genes. The unexpected phenotypes highlight our limited understanding of bacterial genomes. Here, we deploy adaptive laboratory evolution (ALE) to re-optimize growth performance of a genome-reduced strain. The basis for suboptimal growth is the imbalanced metabolism that is rewired during ALE. The metabolic rewiring is globally orchestrated by mutations in rpoD altering promoter binding of RNA polymerase. Lastly, the evolved strain has no translational buffering capacity, enabling effective translation of abundant mRNAs. Multi-omic analysis of the evolved strain reveals transcriptome- and translatome-wide remodeling that orchestrate metabolism and growth. These results reveal that failure of prediction may not be associated with understanding individual genes, but rather from insufficient understanding of the strain’s systems biology.
Suggested Citation
Donghui Choe & Jun Hyoung Lee & Minseob Yoo & Soonkyu Hwang & Bong Hyun Sung & Suhyung Cho & Bernhard Palsson & Sun Chang Kim & Byung-Kwan Cho, 2019.
"Adaptive laboratory evolution of a genome-reduced Escherichia coli,"
Nature Communications, Nature, vol. 10(1), pages 1-14, December.
Handle:
RePEc:nat:natcom:v:10:y:2019:i:1:d:10.1038_s41467-019-08888-6
DOI: 10.1038/s41467-019-08888-6
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Citations
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Cited by:
- Alaksh Choudhury & Benoit Gachet & Zoya Dixit & Roland Faure & Ryan T. Gill & Olivier Tenaillon, 2023.
"Deep mutational scanning reveals the molecular determinants of RNA polymerase-mediated adaptation and tradeoffs,"
Nature Communications, Nature, vol. 14(1), pages 1-16, December.
- Pavel Dvořák & Barbora Burýšková & Barbora Popelářová & Birgitta E. Ebert & Tibor Botka & Dalimil Bujdoš & Alberto Sánchez-Pascuala & Hannah Schöttler & Heiko Hayen & Víctor Lorenzo & Lars M. Blank & , 2024.
"Synthetically-primed adaptation of Pseudomonas putida to a non-native substrate D-xylose,"
Nature Communications, Nature, vol. 15(1), pages 1-18, December.
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