2019/01/30 by Alon Diament, Iddo Weiner, Noam Shahar +7 · 1 citation
Biochemistry, Genetics and Molecular Biology · Energy · #Gene Regulatory Network Analysis #Bioinformatics and Genomic Networks #Algal biology and biofuel production
paper · doi:10.1093/bioinformatics/btz080
openalex publication_date 2019/01/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29
MOTIVATION: Regulation of the amount of protein that is synthesized from genes has proved to be a serious challenge in terms of analysis and prediction, and in terms of engineering and optimization, due to the large diversity in expression machinery across species. RESULTS: To address this challenge, we developed a methodology and a software tool (ChimeraUGEM) for predicting gene expression as well as adapting the coding sequence of a target gene to any host organism. We demonstrate these methods by predicting protein levels in seven organisms, in seven human tissues, and by increasing in vivo the expression of a synthetic gene up to 26-fold in the single-cell green alga Chlamydomonas reinhardtii. The underlying model is designed to capture sequence patterns and regulatory signals with minimal prior knowledge on the host organism and can be applied to a multitude of species and applications. AVAILABILITY AND IMPLEMENTATION: Source code (MATLAB, C) and binaries are freely available for download for non-commercial use at http://www.cs.tau.ac.il/~tamirtul/ChimeraUGEM/, and supported on macOS, Linux and Windows. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.