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Using Tn-Seq to Determine, Model and Modify Microbial Metabolism
Tn-Seq: Bacterial Genetics in the 21st Century
The current inventory of genes known to be involved in extracellular respiration in Shewanella oneidensis are limited to genes that, when inactivated, result in a drastic (strong) phenotype. Alternatively, one would like to be able to systematically examine every gene in the genome looking for those involved in the process, resulting in a comprehensive understanding of all facets of a process. Recently, transposon mutagenesis combined with high-throughput next-generation sequencing was used to determine the fitness effect of the deletion of every gene in the Streptococcus pneumoniea genome. The resulting reports published in the journals Nature Methods and Current Protocols in Microbiology describe Tn-seq, a technique invented by the group of Andrew Camilli at Tufts University that allows the determination of fitness of almost every gene in an organism in a sensitive, yet high throughput way. Briefly, a saturating transposon library is generated in an organism of interest and the library is subjected to two different growth conditions for 5-10 generations. Changes in the frequency of each insertion mutant during the selection outgrowth are determined by sequencing of the flanking genomic regions en masse. The change in frequency of each insertion mutant is calculated and given a fitness score. Using this method the fitness for each gene in an entire genome for any given condition can be determined in one experiment. Genes are identified that have both positive and negative fitness scores. Traditionally experiments of this nature have been analyzed using microarray technology, however, Tn-seq eliminates some inherent biases and regulation is taken out of the equation all together. These researchers are using Tn-seq to evaluate and manipulate metabolism of Shewanella. Analysis of these Illumina datasets requires MSI resources.
A bibliography of this group’s publications acknowledging MSI is attached.