Synthetic biologists are able to co-opt the cellular translation machinery to produce large libraries of designed peptides in vitro to screen for desired functions. The quality of discovered peptides from these libraries is limited by the amount and complexity of sequence space explored. Currently, the sequence space accessible to in vitro translation reactions is a very small subset of the theoretical space as synthetic biologists are unable to incorporate the full array of unnatural amino acid species. A key step limiting the use of unnatural amino acids for in vitro translation is their delivery to the ribosome by tRNAs and elongation factors. While a single elongation factor (EF-Tu) is responsible for delivering all twenty natural amino acids to the ribosome, there remains a high level of specificity, as EF-Tu does not efficiently deliver tRNAs misacylated with non-cognate amino acids. This specificity is due to the tight range of binding affinities between correctly acylated tRNAs (aa- tRNAs) and EF-Tu. Interestingly, an ancient duplication of EF-Tu led to the evolution of an elongation factor (SelB) and tRNA (tRNASel) that are used exclusively for delivery of the twenty-first amino acid, Selenocysteine, to the ribosome. The evolution of EF-Tu and the more restrictive SelB, as well as the evolution of diverse tRNA sequences, can be used in molecular evolutionary analyses to computationally identify sites within tRNAs and EF-Tu that may govern binding affinity. Analyses that incorporate evolutionary information are able to identify sequence signatures that are associated with specific functions. In this case, analyses will identify sites in tRNAs associated with weak or strong binding to EF-Tu and will also identify sites in EF-Tu associated with recognition of amino acids and tRNAs. Candidate sites will then be experimentally tested using an in vitro translation reaction and querying mutant tRNAs or EF-Tu for delivery of a variety of aa-tRNAs. Thus, candidate sites that functionally affect binding/recognition of aa-tRNAs by EF-Tu will be identified. These experiments will lead to a better understanding both for how aa-tRNA specificity is achieved as well as how tRNAs and EF-Tu can be manipulated to control aa-tRNA recognition. From this, mutant tRNAs and EF-Tus capable of delivering unnatural amino acids to the ribosome will be designed and experimentally tested. Overall, this work will lead to a better understanding of the biological process of aa-tRNA delivery to the ribosome, which can inform manipulations of this system to expand the repertoire of amino acids that can be efficiently used by synthetic biologists for in vitro translation reactions.

Public Health Relevance

Peptides can be used to treat conditions ranging from infection to cancer but screens for medically useful peptides are currently limited in the synthesis of diverse peptides. I will exploit evolutionary analyses to advance the creation of peptide libraries that can be used in drug screens for therapeutic compounds.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Postdoctoral Individual National Research Service Award (F32)
Project #
5F32GM095182-03
Application #
8322047
Study Section
Special Emphasis Panel (ZRG1-F08-E (20))
Program Officer
Janes, Daniel E
Project Start
2010-08-23
Project End
2013-05-31
Budget Start
2012-08-23
Budget End
2013-05-31
Support Year
3
Fiscal Year
2012
Total Cost
$45,002
Indirect Cost
Name
Georgia Institute of Technology
Department
Biology
Type
Schools of Arts and Sciences
DUNS #
097394084
City
Atlanta
State
GA
Country
United States
Zip Code
30332
Cacan, Ercan; Kratzer, James T; Cole, Megan F et al. (2013) Interchanging functionality among homologous elongation factors using signatures of heterotachy. J Mol Evol 76:4-12
Cole, Megan F; Gaucher, Eric A (2011) Utilizing natural diversity to evolve protein function: applications towards thermostability. Curr Opin Chem Biol 15:399-406
Cole, Megan F; Gaucher, Eric A (2011) Exploiting models of molecular evolution to efficiently direct protein engineering. J Mol Evol 72:193-203