Predicting Evolution with Ribozymes: A Kinetic Characterization of Azoarcus Group I Ribozyme Mutants
Additional Funding Sources
The project described was supported by the Center of Excellence in Biomedical Research through the Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under Grant Nos. P20GM109095 and P20GM103408 and the National Science Foundation S-STEM Gateway Scholarships in Biological Sciences under Grant Award No. DUE-1644233. The project was further supported by an Institutional Development Award (IDeA) from the National Institute of General Medical Sciences of the National Institutes of Health under Grant No. P20GM103408.
Abstract
Because ribozymes carry genetic information and are capable of catalysis, they provide a simplified model for an evolving organism. Our lab has previously worked with Azoarcus ribozyme mutants using their activity levels to make fitness landscapes, which can be used to simulate and predict evolution. In this work we aimed to establish parameters for a future kinetics (k-seq) study, which we believe will improve and standardize our RNA fitness landscapes, by measuring the enzyme kinetics of a small set of these mutants using more traditional methods.
Predicting Evolution with Ribozymes: A Kinetic Characterization of Azoarcus Group I Ribozyme Mutants
Because ribozymes carry genetic information and are capable of catalysis, they provide a simplified model for an evolving organism. Our lab has previously worked with Azoarcus ribozyme mutants using their activity levels to make fitness landscapes, which can be used to simulate and predict evolution. In this work we aimed to establish parameters for a future kinetics (k-seq) study, which we believe will improve and standardize our RNA fitness landscapes, by measuring the enzyme kinetics of a small set of these mutants using more traditional methods.