Synthetic genomes unveil the effects of synonymous recoding.

Engineering the genetic code of an organism provides the basis for (i) making any organism safely resistant to natural viruses and (ii) preventing genetic information flow into and out of genetically modified organisms while (iii) allowing the biosynthesis of genetically encoded unnatural polymers1-4. Achieving these three goals requires the reassignment of multiple of the 64 codons nature uses to encode proteins. However, synonymous codon replacement-recoding-is frequently lethal, and how recoding impacts fitness remains poorly explored. Here, we explore these effects using whole-genome synthesis, multiplexed directed evolution, and genome-transcriptome-translatome-proteome co-profiling on multiple recoded genomes. Using this information, we assemble a synthetic Escherichia coli genome in seven sections using only 57 codons to encode proteins. By discovering the rules responsible for the lethality of synonymous recoding and developing a data-driven multi-omics-based genome construction workflow that troubleshoots synthetic genomes, we overcome the lethal effects of 62,007 synonymous codon swaps and 11,108 additional genomic edits. We show that synonymous recoding induces transcriptional noise including new antisense RNAs, leading to drastic transcriptome and proteome perturbation. As the elimination of select codons from an organism's genetic code results in the widespread appearance of cryptic promoters, we show that synonymous codon choice may naturally evolve to minimize transcriptional noise. Our work provides the first genome-scale description of how synonymous codon changes influence organismal fitness and paves the way for the construction of functional genomes that provide genetic firewalls from natural ecosystems and safely produce biopolymers, drugs, and enzymes with an expanded chemistry.

Characterization of antibiotic resistomes by reprogrammed bacteriophage-enabled functional metagenomics in clinical strains.

Functional metagenomics is a powerful experimental tool to identify antibiotic resistance genes (ARGs) in the environment, but the range of suitable host bacterial species is limited. This limitation affects both the scope of the identified ARGs and the interpretation of their clinical relevance. Here we present a functional metagenomics pipeline called Reprogrammed Bacteriophage Particle Assisted Multi-species Functional Metagenomics (DEEPMINE). This approach combines and improves the use of T7 bacteriophage with exchanged tail fibres and targeted mutagenesis to expand phage host-specificity and efficiency for functional metagenomics. These modified phage particles were used to introduce large metagenomic plasmid libraries into clinically relevant bacterial pathogens. By screening for ARGs in soil and gut microbiomes and clinical genomes against 13 antibiotics, we demonstrate that this approach substantially expands the list of identified ARGs. Many ARGs have species-specific effects on resistance; they provide a high level of resistance in one bacterial species but yield very limited resistance in a related species. Finally, we identified mobile ARGs against antibiotics that are currently under clinical development or have recently been approved. Overall, DEEPMINE expands the functional metagenomics toolbox for studying microbial communities.