Adaptive laboratory evolution of a genome-reduced Escherichia coli

• Published in: Nature communications 2019-02, Vol.10 (1), p.935-935, Article 935
• Main Authors: Choe, Donghui, Lee, Jun Hyoung, Yoo, Minseob, Hwang, Soonkyu, Sung, Bong Hyun, Cho, Suhyung, Palsson, Bernhard, Kim, Sun Chang, Cho, Byung-Kwan
• Format: Article
• Language: English
• Subjects: 45/15; 45/23; 45/91; 631/553/1833; 631/553/552; Bacteria; Biological evolution; Biology; DNA-directed RNA polymerase; E coli; Escherichia coli - classification; Escherichia coli - genetics; Escherichia coli - growth & development; Escherichia coli - metabolism; Escherichia coli Proteins - genetics; Escherichia coli Proteins - metabolism; Evolution, Molecular; Gene expression; Gene Expression Regulation, Bacterial; Genes; Genome Size; Genome, Bacterial; Genomes; Humanities and Social Sciences; Laboratories; Metabolism; multidisciplinary; Mutation; Phenotype; Phenotypes; Ribonucleic acid; RNA; RNA polymerase; Science; Science (multidisciplinary); Transcriptome
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-019-08888-6

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. Genome-reduced bacteria often show impaired growth under laboratory conditions. Here the authors use adaptive laboratory evolution to optimise growth performance and show transcriptome and translatome-wide remodeling of the organism.