Computational protocol: Hyperexpression of α-hemolysin explains enhanced virulence of sequence type 93 community-associated methicillin-resistant Staphylococcus aureus

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Protocol publication

[…] A read mapping approach was used to compare the sequences from all isolates used in this study, as previously described [,]. Briefly, the reads from all genomes were aligned to the JKD6159 reference using SHRiMP 2.0 []. SNPs were identified using Nesoni v0.60 [ http://www.bioinformatics.net.au]. Using the whole genome sequence of JKD6159 as a reference, a global SNP analysis was performed, and allelic variability at any nucleotide position was tallied to generate a global SNP analysis for every genome compared to JKD6159. [...] Staphylococcus aureus strains JKD6159 and JKD6159_AraCr were grown to early stationary culture as described above. For RNA protection, 0.5 volumes of RNAlater® RNA stabilization reagent (Qiagen) was added immediately to the liquid culture and allowed to incubate with the bacterial suspension for 15 minutes at room temperature. Cells were pelleted at 5,000 × g for 5 minutes followed by RNA extraction using RNeasy mini kit (Qiagen) and two rounds of DNase I digestion (Qiagen) according to the manufacturer’s instruction. RNA concentration was quantified using Qubit® 2.0 Fluorometer and RNA quality assessed using Agilent 2100 Bioanalyzer. Ten μg of total RNA from the stationary growth phase with RNA intergrity number (RIN) greater than 7 was used in RNA-seq. Ribosomal depletion, cDNA library preparation and pair ended sequencing using HiSeq2000 sequencing platform was performed by Beijing Genome Institute (Hong Kong, China). RNAseq was performed on two biological samples for each strain.RNAseq reads were mapped onto the JKD6159 reference genome [], using SHRiMP 2.2.2 []. Alignment to CDS features from each biological replicate of each strain provided counts that were a measure of mRNA levels. Counts were normalized using the trimmed-mean normalization function in edgeR, part of the BioConductor package []. A heat map was created based on log2 transformed counts to identify consistent changes in expression profiles between strains. To be included in the heat map, genes were required to have at least 1000 counts, totaled over all samples, where and the standard deviation of the log2 expression levels had to exceed two. […]

Pipeline specifications

Software tools Nesoni, edgeR
Applications Phylogenetics, RNA-seq analysis
Organisms Mus musculus, Staphylococcus aureus, Epipremnum aureum
Diseases Skin Diseases
Chemicals Methicillin