Abstract
Sequence rewriting enables low-cost genome synthesis and the design of biological systems with orthogonal genetic codes. The error-free, robust rewriting of nucleotide sequences can be achieved with a complete annotation of gene regulatory elements. Here, we compare transcription in Caulobacter crescentus to transcription from plasmid-borne segments of the synthesized genome of C. ethensis 2.0. This rewritten derivative contains an extensive amount of supposedly neutral mutations, including 123’562 synonymous codon changes. The transcriptional landscape refines 60 promoter annotations, exposes 18 termination elements and links extensive transcription throughout the synthesized genome to the unintentional introduction of sigma factor binding motifs. We reveal translational regulation for 20 CDS and uncover an essential translational regulatory element for the expression of ribosomal protein RplS. The annotation of gene regulatory elements allowed us to formulate design principles that improve design schemes for synthesized DNA, en route to a bright future of iteration-free programming of biological systems.
Highlights
Sequence rewriting enables low-cost genome synthesis and the design of biological systems with orthogonal genetic codes
We compared the transcriptional landscapes of C. crescentus and C. eth-2.0, a rewritten derivative in which we retained only annotated control elements and the amino acid sequence of protein-coding genes
Of the C. eth-2.0 genes, 60% are transcribed at an absolute LOG2 FC ≤ 1 and 58% show a match to the native transcription curve
Summary
Sequence rewriting enables low-cost genome synthesis and the design of biological systems with orthogonal genetic codes. We can rewrite non-coding sequences and synonymously recode protein coding sequences only with a complete map of the sequence-based information space This space consists of the collection of transcriptional and translational regulatory features and the collection of stochastic processes that underlie RNA degradation, collectively employed in a cell to control gene expression[1]. We reasoned that the in-depth comparison of the transcriptional landscape of the rewritten and native genomes would reveal gene regulatory features and, due to the scale of the analysis, allow us to formulate principles to improve design schemes that allow rewriting DNA molecules whilst preserving biological functionality. We contribute to a precise understanding of how to encode biological information into DNA, which will, in due time, enable a transition to the iteration-free programming of biological systems with synthesized information
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