Validation of reference genes for normalization of qPCR mRNA expression levels inStaphylococcus aureusexposed to osmotic and lactic acid stress conditions encountered during food production and preservation

Abstract

Staphylococcus aureus represents the most prevalent cause of food-borne intoxications worldwide. While being repressed by competing bacteria in most matrices, this pathogen exhibits crucial competitive advantages during growth at high salt concentrations or low pH, conditions frequently encountered in food production and preservation. We aimed to identify reference genes that could be used to normalize qPCR mRNA expression levels during growth of S. aureus in food-related osmotic (NaCl) and acidic (lactic acid) stress adaptation models. Expression stability of nine housekeeping genes was evaluated in full (LB) and nutrient-deficient (CYGP w/o glucose) medium under conditions of osmotic (4.5% NaCl) and acidic stress (lactic acid, pH 6.0) after 2-h exposure. Among the set of candidate reference genes investigated, rplD, rpoB,gyrB, and rho were most stably expressed in LB and thus represent the most suitable reference genes for normalization of qPCR data in osmotic or lactic acid stress models in a rich medium. Under nutrient-deficient conditions, expression of rho and rpoB was highly stable across all tested conditions. The presented comprehensive data on changes in expression of various S. aureus housekeeping genes under conditions of osmotic and lactic acid stress facilitate selection of reference genes for qPCR-based stress response models.

Coculture of Staphylococcus aureus with Pseudomonas aeruginosa Drives S. aureus towards Fermentative Metabolism and Reduced Viability in a Cystic Fibrosis Model

“…The qRT-PCR was as follows: 95°C for 3 min and then 95°C for 30 s, annealing temperature (T anneal ) for 30 s, and 72°C for 20 s, for 40 cycles. cDNA to each gene of interest was quantified based on cycle threshold (C T ) compared to a standard curve of purified P. aeruginosa PA14 rplU DNA and normalized from sample to sample based on S. aureus rpoB quantification (56). S. aureus gyrB was used as a second normalization control for initial experiments and showed results consistent with those of rpoB; therefore, a single gene, rpoB, was used for later assays and is reported here.…”

Size-fraction partitioning of community gene transcription and nitrogen metabolism in a marine oxygen minimum zone

“…N gene transcript abundances were normalized based on gene length and expressed as a proportion of the abundance of transcripts matching the gene encoding RNA polymerase subunit B (rpoB), as has been done in studies of diverse bacteria (for example, Schumann et al, 2010;Ceja-Navarro et al, 2014;Dalsgaard et al, 2014;Eldholm et al, 2014). Although rpoB expression can vary (Vandecasteele et al, 2001), rpoB appears to be one of the more stably expressed housekeeping genes (Sue et al, 2004;Sihto et al, 2014). Furthermore, it has been shown that rpoB can be a proxy of bulk mRNA transcription level for bacteria (Milohanic et al, 2003;Sue et al, 2004)-rpoB-normalized values therefore reflect transcription of a target gene relative to a housekeeping gene under a given condition/sample.…”

Validation of reference genes for normalization of gene expression by qRT-PCR in a resveratrol-producing entophytic fungus (Alternaria sp. MG1)

“…MG1 has not been achieved until now, although some traditional reference genes have been used for qRT-PCR data normalization in some other Alternaria sp. (Dankai et al 2015; Sihto et al 2014). …”

“…In recent years, validation of reliable reference genes before their use for normalization has been performed for many species, such as Talaromyces marneffei (Dankai et al 2015), Staphylococcus aureus (Sihto et al 2014), Beauveria bassiana (Zhou et al 2012), Oenococcus oeni (Sumby et al 2012) and others. Commonly used reference genes for these fungi include the genes encoding the 18S ribosomal RNA ( 18S ), ubiquitin fusion degradation protein ( UFD ), ribosomal protein ( RPS ), elongation factor ( EF ), β-actin ( ACTB ), α-tubulin ( TUBA ), ubiquitin-conjugating enzyme ( UBC ), and glyceraldehyde-3-phosphate dehydrogenase ( GAPDH ) (Kozera and Rapacz 2013).…”