(502b) Synthetic Electron Transfer Pathways As High-Throughput Selections for the Design of Protein Electron Carriers

Silberg, J. J., Rice University
Iron-sulfur cluster containing ferredoxin (Fd) proteins function as electron carriers in biochemical pathways important for energy transduction, with roles ranging from hydrogen and alcohol production to carbon and nitrogen fixation. While it is clear that many microbes use multiple Fd protein electron carriers to regulate electron flow, we do not yet fully understand what controls the proportion of electrons relayed by individual Fds among different oxidoreductases within cells. In addition, we do not understand Fd sequence-structure-function sufficiently to design Fds that control electron flow for metabolic and bioelectronics applications. We will describe our efforts developing high throughput bacterial selections as cellular assays for the design of low potential Fds with altered electron transfer properties. Our initial efforts have focused on comparing 2Fe-2S Fd homologs using an Escherhichia coli auxotroph that only grows in minimal medium containing sulfate as the sole sulfur source if a Fd is present that effectively transfers electrons from a Fd-NADP+ reductase (FNR) to Fd-dependent sulfite reductase (SIR). We will describe our efforts using this selection to analyze the electron transfer properties of two-fragment Fds that display AND gate logic. In addition, we will describe how these split Fds can be fused to ligand-binding proteins to create allosteric protein electron carriers that display chemical-dependent electron transfer. We will also describe the results from our ongoing efforts where we are creating combinatorial libraries of Fd mutants using transposase mutagenesis and analyzing their sequence diversity before and after selection by subjecting the libraries to deep sequencing. We have developed a new method, called Circular Permutation Profiling with DNA sequencing (CPP-seq), which combines a one-step transposon mutagenesis protocol for creating libraries with a functional selection, deep sequencing, and computational analysis to obtain unbiased insight into a protein’s tolerance to circular permutation.