Computational protocol: Transcriptional profiling of Actinobacillus pleuropneumoniae under iron-restricted conditions

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Protocol publication

[…] The draft genome sequence of A. pleuropneumoniae serotype 5b strain L20 [GenBank: CP000569] was used as a source of the genes used in this study. ORFs were identified using the Glimmer software package [], and used to search for homologs among the bacterial gene subset of Genbank [] using the BLASTP program []. PCR primers were designed for each of the 2025 ORFs of the genome of A. pleuropneumoniae using the Primer3 program [] controlled by an automated script as described previously []. Primer-selection parameters were standardized and included a similar predicted melting temperature (60 ± 3°C), uniform length (25 nt), and a minimum amplicon size of 160 bp. Generation of PCR amplicons and fabrication of DNA microarrays were as described []. Details on the construction of this microarray (AppChip1) are available on the Institute for Biological Sciences website []. [...] The TM4 suite of software from The Institute of Genomic Research was used for the whole microarray analysis []. First, raw data were generated using SpotFinder v.3.0.0 beta. The integrated intensities of each spot, equivalent to the sum of intensities of all unsaturated pixels in a spot, were quantified and the integrated intensity of the local background was subtracted for each spot. The same operation was performed with the median spot intensities. The spot detection threshold was set so that spots for which the integrated intensity was less than one standard deviation above the background median intensity were set to zero. Raw spot data were converted from integrated intensities to median spot intensities using TIGR's Express Converter software, the latter being less influenced by outlier values than integrated intensities.Data were normalized with TIGR's MIDAS software tool using locally weighted linear regression (lowess) [-]. Spots with median intensities lower than 1000 were removed from the normalized data set. Intensities for duplicate spots were merged to generate the final normalized data set, subsequently analyzed using TIGR's TMEV microarray analysis tool. The Significance Analysis of Microarray (SAM) algorithm [], which is implemented in TMEV, was used to generate a list of differentially expressed genes. During SAM analysis, a false discovery rate of 3.22% was estimated for the iron-depleted versus BHI broth experiment, while a FDR of 2.51% was estimated for the iron-supplemented versus BHI broth experiment; this value estimates the proportion of genes likely to have been identified by chance. Functional classification of these genes was conducted using TIGR's Comprehensive Microbial Resource (CMR) []. Proteins were assigned to their corresponding pathways using the MetaCyc Metabolic Pathway Database []. Homologies were assessed using Blast tools [] hosted on the NCBI and TIGR servers. Additional subcellular localization was determined with PSORTb []. Protein sequence alignments were performed using the ClustalW multiple sequence alignment algorithm []. […]

Pipeline specifications

Software tools TM4, Spotfinder, PSORTb, Clustal W
Databases Comprehensive Microbial Resource MetaCyc
Application Protein sequence analysis
Organisms Actinobacillus pleuropneumoniae, Neisseria meningitidis
Chemicals Heme, Iron