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Cell-Free Translation Is More Variable than Transcription
Fabio Chizzolini1, Michele Forlin1, Noël Yeh Martín1
1Center for Integrative Biology (CIBIO), University of Trento , via Sommarive 9, 38123 Povo TN, Italy.
ACS Synthetic Biology
|January 20, 2017
Summary
Controlling protein synthesis in cell-free systems is complex. Ribosome binding site strength impacts protein levels, but other factors like coding sequence GC content also play a significant role.
Area of Science:
- Molecular Biology
- Synthetic Biology
- Biotechnology
Background:
- Cell-free gene expression systems, like the PURE system, allow for controlled RNA synthesis using T7 transcriptional promoters.
- However, achieving precise control over protein synthesis levels in these systems remains a challenge.
Purpose of the Study:
- To investigate methods for better controlling protein synthesis levels in cell-free gene expression.
- To identify factors beyond ribosome binding site (RBS) strength that influence protein expression variability.
Main Methods:
- Systematic investigation of various ribosome binding sites (RBSs) with different strengths.
- Analysis of protein synthesis in cell-free systems (PURE system and E. coli cell extract).
- Assessment of factors such as RBS sequence and coding sequence GC content on protein expression.
Main Results:
- RBS strength significantly affects protein synthesis, but explains less than half of the observed variability.
- Protein expression is influenced by additional factors, including the GC content of the coding sequence.
- Protein synthesis exhibits higher variability compared to RNA synthesis, a complexity observed in both T7 and E. coli RNA polymerase systems.
Conclusions:
- Achieving precise control over protein synthesis in cell-free systems requires considering factors beyond RBS strength.
- The inherent complexity of protein synthesis leads to greater variability than RNA synthesis.
- E. coli RNA polymerase systems demonstrate increased variability compared to T7 RNA polymerase systems, reflecting higher biological complexity.
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