Genetic Barcodes Enable Quantitative Mapping of Operator Mutants to Gene Expression

Abstract

Every organism has intricate regulatory networks that enable them to sense, move, and interact with complex environments. In E. coli, transcription factors (TFs) bind to short sequences upstream of genes, called operators, to repress or activate gene expression. Our lab has previously derived and validated a biophysical model of transcription regulation -the repression of a gene by LacI - demonstrating that repressorcopy number, the energy of TF:operator binding, and genome size all play crucial roles in determining the quantitative features of gene expression. But LacI is a small fish in the cellular pond; we must develop experimental methods that enable us to map how any TF:operator pair imparts predictable gene expression, and do so in a high-throughput manner without sacrificing quantitation. We report a high-throughput method to randomly mutagenize large libraries of operator sequences and quantify their resulting gene expression. Briefly, mutagenized binding sites for a TF are "mapped" to a random DNA barcode using next-generation sequencing. The native gene regulated by that TF is then inserted between the mutated operators and barcodes, and these libraries are genomically-integrated into E. coli. The relative abundance of cells carrying each operator mutant can be determined via DNA-sequencing of the barcodes, while their gene expression can be measured by quantitative RNA-sequencing of barcodes using a mixture of Unique Molecular Identifiers and other methods to minimize bias. These data will inform mathematical models for the de novo prediction of gene expression from regulatory sequences.

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