Abstract:
:The deluge of data generated by genome sequencing has led to an increasing reliance on bioinformatic predictions, since the traditional experimental approach of characterizing gene function one at a time cannot possibly keep pace with the sequence-based discovery of novel genes. We have utilized Biolog phenotype MicroArrays to identify phenotypes of gene knockout mutants in the opportunistic pathogen and versatile soil bacterium Pseudomonas aeruginosa in a relatively high-throughput fashion. Seventy-eight P. aeruginosa mutants defective in predicted sugar and amino acid membrane transporter genes were screened and clear phenotypes were identified for 27 of these. In all cases, these phenotypes were confirmed by independent growth assays on minimal media. Using qRT-PCR, we demonstrate that the expression levels of 11 of these transporter genes were induced from 4- to 90-fold by their substrates identified via phenotype analysis. Overall, the experimental data showed the bioinformatic predictions to be largely correct in 22 out of 27 cases, and led to the identification of novel transporter genes and a potentially new histamine catabolic pathway. Thus, rapid phenotype identification assays are an invaluable tool for confirming and extending bioinformatic predictions.
journal_name
PLoS Genetjournal_title
PLoS geneticsauthors
Johnson DA,Tetu SG,Phillippy K,Chen J,Ren Q,Paulsen ITdoi
10.1371/journal.pgen.1000211subject
Has Abstractpub_date
2008-10-03 00:00:00pages
e1000211issue
10eissn
1553-7390issn
1553-7404journal_volume
4pub_type
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