Genome-Scale Metabolic Network Validation of Shewanella oneidensis Using Transposon Insertion Frequency Analysis

Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency a...

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Published inPLoS computational biology Vol. 10; no. 9; p. e1003848
Main Authors Yang, Hong, Krumholz, Elias W., Brutinel, Evan D., Palani, Nagendra P., Sadowsky, Michael J., Odlyzko, Andrew M., Gralnick, Jeffrey A., Libourel, Igor G. L.
Format Journal Article
LanguageEnglish
Published United States Public Library of Science 01.09.2014
Public Library of Science (PLoS)
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Summary:Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA). TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1) previous genome-wide direct gene-essentiality assignments; and, 2) flux balance analysis (FBA) predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.
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Conceived and designed the experiments: HY AMO JAG IGLL. Performed the experiments: HY EWK EDB NPP JAG IGLL. Analyzed the data: HY EWK EDB NPP JAG IGLL. Contributed to the writing of the manuscript: HY NPP MJS JAG AMO IGLL.
The authors have declared that no competing interests exist.
ISSN:1553-7358
1553-734X
1553-7358
DOI:10.1371/journal.pcbi.1003848