An improved method for eliminating or creating intragenic bacterial promoters

Ellina Trofimova, Dominic Y. Logel, Paul R. Jaschke*

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)

Abstract

Recent advances in genomic refactoring have been hindered by the ever-present complication of internal or cryptic transcriptional regulation. Typical approaches to these features have been to randomize or perform mass alterations to the gene sequences thought to contain the regulatory motifs; however, this approach can cause problems by altering translational speeds, introducing long distance DNA-DNA interaction effects, and inducing RNA toxicity. Previously, we developed a rational design approach named COdon Restrained Promoter SilEncing (CORPSE) which takes externally identified promoter sequences and uses position-specific scoring matrices as proxy promoter strengths to make minimal changes to promoter sequences to disable their activity. Additionally, through inverting our system we were also able to modify weak internal promoters to increase their activity. In this chapter, we augment our previous process with the biophysical model Promoter Calculator v1.0 developed by LaFleur et al. to combine promoter identification and activity prediction, with our algorithm to silently modify promoter sequences, to provide more robust promoter elimination and creation.

Original languageEnglish
Title of host publicationSynthetic Biology
Subtitle of host publicationMethods and Protocols
EditorsJeffrey Carl Braman
Place of PublicationNew York
PublisherSpringer, Springer Nature
Chapter12
Pages199-207
Number of pages9
Edition2nd
ISBN (Electronic)9781071636589
ISBN (Print)9781071636572
DOIs
Publication statusPublished - 2024

Publication series

NameMethods in Molecular Biology
Volume2760
ISSN (Print)1064-3745
ISSN (Electronic)1940-6029

Keywords

  • Internal regulation
  • Model-predictive design
  • Overlapping genes
  • Refactoring
  • Sigma factor
  • Synthetic genomics
  • Transcription initiation

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