Genome-wide patterns of sequence divergence over evolutionary time provide a unique window into the fundamental metabolic costs imposed on cellular life. Purifying selection eliminates mutations that increase costs and/or promote genetic disease. This process can discern minor cost differences, even ones that may not be readily measurable by direct laboratory experiments. This project will identify and interpret the evolutionary signals imprinted into genomes by one specific cost, the cost of erroneously translating proteins. Mistranslation events lead to protein misfolding, misfolded proteins can be cytotoxic or require costly cleanup, and selection operates both on the codon and on the amino-acid level to minimize cellular exposure to misfolded proteins. The working hypothesis for this project is that among the costs linked to translation, mistranslation-induced misfolding is the dominant one, whereas other costs, including mistranslation-induced loss of function and translation at reduced speed, play a minor role. This hypothesis will be tested using a combination of bioinformatics, mathematical modeling, and computer simulation, and the relative importance of the various translation- linked costs will be quantified. There are three specific aims. 1. What makes translationally optimal codons optimal? 2. Does selection against protein misfolding shapes synonymous codon usage? 3. How does protein biophysics interact with translational selection to constrain sequence evolution?
All organisms have to translate proteins accurately and efficiently;mutations that interfere with efficient translation impair cellular function and cause disease states in humans. This project will identify the specific costs associated with mutations that affect translation, and will provide insight into which mutations are most likely to impose meaningful costs on cellular function. This research will impact several health-related areas, including the industrial production of drug compounds in genetically modified microbes and the cause and detection of certain kinds of genetic diseases in humans.
|Paff, Matthew L; Jack, Benjamin R; Smith, Bartram L et al. (2018) Combinatorial Approaches to Viral Attenuation. mSystems 3:|
|Garry, Daniel J; Ellington, Andrew D; Molineux, Ian J et al. (2018) Viral attenuation by engineered protein fragmentation. Virus Evol 4:vey017|
|Bull, James J; Christensen, Kelly A; Scott, Carly et al. (2018) Phage-Bacterial Dynamics with Spatial Structure: Self Organization around Phage Sinks Can Promote Increased Cell Densities. Antibiotics (Basel) 7:|
|Jiang, Qian; Teufel, Ashley I; Jackson, Eleisha L et al. (2018) Beyond Thermodynamic Constraints: Evolutionary Sampling Generates Realistic Protein Sequence Variation. Genetics 208:1387-1395|
|Hockenberry, Adam J; Jewett, Michael C; Amaral, Luís A N et al. (2018) Within-Gene Shine-Dalgarno Sequences Are Not Selected for Function. Mol Biol Evol 35:2487-2498|
|Tom, Eric F; Molineux, Ian J; Paff, Matthew L et al. (2018) Experimental evolution of UV resistance in a phage. PeerJ 6:e5190|
|Smith, Bartram L; Chen, Guifang; Wilke, Claus O et al. (2018) Avian Influenza Virus PB1 Gene in H3N2 Viruses Evolved in Humans To Reduce Interferon Inhibition by Skewing Codon Usage toward Interferon-Altered tRNA Pools. MBio 9:|
|Bull, James J; Barrick, Jeffrey E (2017) Arresting Evolution. Trends Genet 33:910-920|
|Sydykova, Dariya K; Jack, Benjamin R; Spielman, Stephanie J et al. (2017) Measuring evolutionary rates of proteins in a structural context. F1000Res 6:1845|
|Echave, Julian; Wilke, Claus O (2017) Biophysical Models of Protein Evolution: Understanding the Patterns of Evolutionary Sequence Divergence. Annu Rev Biophys 46:85-103|
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