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Investigation of Reference Genes in Vibrio parahaemolyticus for Gene Expression Analysis Using Quantitative RT-PCR.

ABSTRACT: Vibrio parahaemolyticus is a significant human pathogen capable of causing foodborne gastroenteritis associated with the consumption of contaminated raw or undercooked seafood. Quantitative RT-PCR (qRT-PCR) is a useful tool for studying gene expression in V. parahaemolyticus to characterize its virulence factors and understand the effect of environmental conditions on its pathogenicity. However, there is not a stable gene in V. parahaemolyticus that has been identified for use as a reference gene for qRT-PCR. This study evaluated the stability of 6 reference genes (16S rRNA, recA, rpoS, pvsA, pvuA, and gapdh) in 5 V. parahaemolyticus strains (O3:K6-clinical strain-tdh+, ATCC33846-tdh+, ATCC33847-tdh+, ATCC17802-trh+, and F13-environmental strain-tdh+) cultured at 4 different temperatures (15, 25, 37 and 42°C). Stability values were calculated using GeNorm, NormFinder, BestKeeper, and Delta CT algorithms. The results indicated that recA was the most stably expressed gene in the V. parahaemolyticus strains cultured at different temperatures. This study examined multiple V. parahaemolyticus strains and growth temperatures, hence the finding provided stronger evidence that recA can be used as a reference gene for gene expression studies in V. parahaemolyticus.

SUBMITTER: Ma YJ

PROVIDER: S-EPMC4676679 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

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Investigation of Reference Genes in Vibrio parahaemolyticus for Gene Expression Analysis Using Quantitative RT-PCR.

Ma Yue-Jiao YJ Sun Xiao-Hong XH Xu Xiao-Yan XY Zhao Yong Y Pan Ying-Jie YJ Hwang Cheng-An CA Wu Vivian C H VC

PloS one 20151211 12

Vibrio parahaemolyticus is a significant human pathogen capable of causing foodborne gastroenteritis associated with the consumption of contaminated raw or undercooked seafood. Quantitative RT-PCR (qRT-PCR) is a useful tool for studying gene expression in V. parahaemolyticus to characterize its virulence factors and understand the effect of environmental conditions on its pathogenicity. However, there is not a stable gene in V. parahaemolyticus that has been identified for use as a reference gen ...[more]

PMID: 26659406

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Project description:BackgroundNormalization in real-time qRT-PCR is necessary to compensate for experimental variation. A popular normalization strategy employs reference gene(s), which may introduce additional variability into normalized expression levels due to innate variation (between tissues, individuals, etc). To minimize this innate variability, multiple reference genes are used. Current methods of selecting reference genes make an assumption of independence in their innate variation. This assumption is not always justified, which may lead to selecting a suboptimal set of reference genes.ResultsWe propose a robust approach for selecting optimal subset(s) of reference genes with the smallest variance of the corresponding normalizing factors. The normalizing factor variance estimates are based on the estimated unstructured covariance matrix of all available candidate reference genes, adjusting for all possible correlations. Robustness is achieved through bootstrapping all candidate reference gene data and obtaining the bootstrap upper confidence limits for the variances of the log-transformed normalizing factors. The selection of the reference gene subset is optimized with respect to one of the following criteria: (A) to minimize the variability of the normalizing factor; (B) to minimize the number of reference genes with acceptable upper limit on variability of the normalizing factor, (C) to minimize the average rank of the variance of the normalizing factor. The proposed approach evaluates all gene subsets of various sizes rather than ranking individual reference genes by their stability, as in the previous work. In two publicly available data sets and one new data set, our approach identified subset(s) of reference genes with smaller empirical variance of the normalizing factor than in subsets identified using previously published methods. A small simulation study indicated an advantage of the proposed approach in terms of sensitivity to identify the true optimal reference subset in the presence of even modest, especially negative correlation among the candidate reference genes.ConclusionsThe proposed approach performs comprehensive and robust evaluation of the variability of normalizing factors based on all possible subsets of candidate reference genes. The results of this evaluation provide flexibility to choose from important criteria for selecting the optimal subset(s) of reference genes, unless one subset meets all the criteria. This approach identifies gene subset(s) with smaller variability of normalizing factors than current standard approaches, particularly if there is some nontrivial innate correlation among the candidate genes.

Project description:BACKGROUND: Reference genes, which are often referred to as housekeeping genes are frequently used to normalize mRNA levels between different samples in quantitative reverse transcription polymerase chain reaction (qRT-PCR). The selection of reference genes is critical for gene expression studies because the expression of these genes may vary among tissues or cells and may change under certain circumstances. Here, a systematic evaluation of six putative reference genes for gene expression studies in human hepatocellular carcinoma (HCC) is presented. METHODS: Six genes, beta-2-microglobulin (B2M), glyceraldehyde-3-phosphate dehydrogenase (GAPDH), hydroxymethyl-bilane synthase (HMBS), hypoxanthine phosphoribosyl-transferase 1 (HPRT1), succinate dehydrogenase complex, subunit A (SDHA) and ubiquitin C (UBC), with distinct functional characteristics and expression patterns were evaluated by qRT-PCR. Inhibitory substances in RNA samples were quantitatively assessed and controlled using an external RNA control. The stability of selected reference genes was analyzed using both geNorm and NormFinder software. RESULTS: HMBS and GAPDH were identified as the optimal reference genes for normalizing gene expression data between paired tumoral and adjacent non-tumoral tissues derived from patients with HCC. HMBS, GAPDH and UBC were identified to be suitable for the normalization of gene expression data among tumor tissues; whereas the combination of HMBS, B2M, SDHA and GAPDH was suitable for normalizing gene expression data among five liver cancer cell lines, namely Hep3B, HepG2, HuH7, SK-HEP-1 and SNU-182. The determined gene stability was increased after exclusion of RNA samples containing relatively higher inhibitory substances. CONCLUSION: Of six genes studied, HMBS was found to be the single best reference gene for gene expression studies in HCC. The appropriate choice of combination of more than one reference gene to improve qRT-PCR accuracy depends on the kind of liver tissues or cells under investigation. Quantitative assessment and control of qRT-PCR inhibitors using an external RNA control can reduce the variation of qRT-PCR assay and facilitate the evaluation of gene stability. Our results may facilitate the choice of reference genes for expression studies in HCC.

Project description:BackgroundQuantitative real-time reverse-transcription polymerase chain reaction is frequently used as research tool in experimental oncology. There are some studies of valid endogenous control genes in the field of human glioma research, which, however, only focus on the comparison between normal brain with tumor tissue and malignant transformation toward secondary glioblastomas. Aim of this study was to validate a more general reference gene also suitable for pre- and posttreatment analysis and other evaluations (eg, primary vs secondary glioblastoma).MethodsThis quantitative polymerase chain reaction analysis was performed to test a panel of the 6 most suitable reference genes from other studies representing different physiological pathways (ACTB, GAPDH, POLR2A, RPL13A, SDHA, and TBP) in all common glioma groups, namely: diffuse astrocytoma World Health Organization II, anaplastic astrocytoma World Health Organization III, secondary glioblastoma World Health Organization IV with and without chemotherapy, primary glioblastoma, recurrent glioblastoma, and gliomas before and after radiation. Expression stability was tested during the longitudinal course of the disease in 8 single patients.ResultsEvaluation of the expression levels of the 6 target genes showed that ACTB, GAPDH, and RPL13A show higher expression compared to SDHA, POLR2A, and TBP. ACTB, GAPDH, and RPL13A showed different expression levels between astrozytoma grade II and primary glioblastoma. Except for this difference, the candidate genes were not differentially expressed between primary and secondary glioblastomas and between the World Health Organization tumor grades. Furthermore, they remained stable before and after radiotherapy and/or chemotherapy. Therefore, they are adequate references for glioblastoma gene expression studies. The comparison of all tested genes resulted in SDHA and ACTB as most stable reference genes determined by the NormFinder software. Our data revealed lowest intragroup variation in the SDHA, highest in the RPL13A gene.ConclusionsAll tested genes may be recommended as universal reference genes for data normalization in gene expression studies under different treatment regimens both in primary glioblastomas and astrocytomas of different grades (World Health Organization grades II-IV), respectively. In summary, ACTB and SDHA exhibited the best stability values and showed the lowest intergroup expression variability.

Project description:BackgroundReal-time RT-PCR is the recommended method for quantitative gene expression analysis. A compulsory step is the selection of good reference genes for normalization. A few genes often referred to as HouseKeeping Genes (HSK), such as ACT1, RDN18 or PDA1 are among the most commonly used, as their expression is assumed to remain unchanged over a wide range of conditions. Since this assumption is very unlikely, a geometric averaging of multiple, carefully selected internal control genes is now strongly recommended for normalization to avoid this problem of expression variation of single reference genes. The aim of this work was to search for a set of reference genes for reliable gene expression analysis in Saccharomyces cerevisiae.ResultsFrom public microarray datasets, we selected potential reference genes whose expression remained apparently invariable during long-term growth on glucose. Using the algorithm geNorm, ALG9, TAF10, TFC1 and UBC6 turned out to be genes whose expression remained stable, independent of the growth conditions and the strain backgrounds tested in this study. We then showed that the geometric averaging of any subset of three genes among the six most stable genes resulted in very similar normalized data, which contrasted with inconsistent results among various biological samples when the normalization was performed with ACT1. Normalization with multiple selected genes was therefore applied to transcriptional analysis of genes involved in glycogen metabolism. We determined an induction ratio of 100-fold for GPH1 and 20-fold for GSY2 between the exponential phase and the diauxic shift on glucose. There was no induction of these two genes at this transition phase on galactose, although in both cases, the kinetics of glycogen accumulation was similar. In contrast, SGA1 expression was independent of the carbon source and increased by 3-fold in stationary phase.ConclusionIn this work, we provided a set of genes that are suitable reference genes for quantitative gene expression analysis by real-time RT-PCR in yeast biological samples covering a large panel of physiological states. In contrast, we invalidated and discourage the use of ACT1 as well as other commonly used reference genes (PDA1, TDH3, RDN18, etc) as internal controls for quantitative gene expression analysis in yeast.

Dataset Information

Investigation of Reference Genes in Vibrio parahaemolyticus for Gene Expression Analysis Using Quantitative RT-PCR.

Publications

Investigation of Reference Genes in Vibrio parahaemolyticus for Gene Expression Analysis Using Quantitative RT-PCR.

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