title: Microarray-based genetic footprinting strategy to identify strain improvement genes after competitive selection of transposon libraries.
abstract: Successful strain engineering involves perturbing key nodes within the cellular network. How the -network's connectivity affects the phenotype of interest and the ideal nodes to modulate, however, are frequently not readily apparent. To guide the generation of a list of candidate nodes for detailed investigation, designers often examine the behavior of a representative set of strains, such as a library of transposon insertion mutants, in the environment of interest. Here, we first present design principles for creating a maximally informative competitive selection. Then, we describe how to globally quantify the change in distribution of strains within a transposon library in response to a competitive selection by amplifying the DNA adjacent to the transposons and hybridizing it to a microarray. Finally, we detail strategies for analyzing the resulting hybridization data to identify genes and pathways that contribute both negatively and positively to fitness in the desired environment.
authors.affiliation: Department of Molecular Biology, Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.
authors.forename: Alison K
authors.initials: AK
authors.lastname: Hottes
authors.forename: Saeed
authors.initials: S
authors.lastname: Tavazoie
mesh_terms: D018983:DNA Footprinting; D004251:DNA Transposable Elements / Q000235:genetics*; D015723:Gene Library; D016254:Mutagenesis, Insertional / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D012641:Selection, Genetic
chemical_list: D004251:DNA Transposable Elements