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Selection and evaluation of reference genes for improved interrogation of microbial transcriptomes: case study with the extremophile Acidithiobacillus ferrooxidans.

Nieto PA, Covarrubias PC, Jedlicki E, Holmes DS, Quatrini R - BMC Mol. Biol. (2009)

Bottom Line: Suitability of these and other previously reported reference genes to monitor the expression of four selected target genes from A. ferrooxidans grown with different energy sources was investigated.This investigation provides a validated set of reference genes for studying A. ferrooxidans gene expression under typical biological conditions and an initial point of departure for exploring new experimental setups in this microorganism and eventually in other closely related Acidithiobacilli.The information could also be of value for future transcriptomic experiments in other bacterial systems.

View Article: PubMed Central - HTML - PubMed

Affiliation: ICBM, Universidad de Chile, Santiago, Chile. pamelanietop@gmail.com

ABSTRACT

Background: Normalization is a prerequisite for accurate real time PCR (qPCR) expression analysis and for the validation of microarray profiling data in microbial systems. The choice and use of reference genes that are stably expressed across samples, experimental conditions and designs is a key consideration for the accurate interpretation of gene expression data.

Results: Here, we evaluate a carefully selected set of reference genes derived from previous microarray-based transcriptional profiling experiments performed on Acidithiobacillus ferrooxidans and identify a set of genes with minimal variability under five different experimental conditions that are frequently used in Acidithiobacilli research. Suitability of these and other previously reported reference genes to monitor the expression of four selected target genes from A. ferrooxidans grown with different energy sources was investigated. Utilization of reference genes map, rpoC, alaS and era results in improved interpretation of gene expression profiles in A. ferrooxidans.

Conclusion: This investigation provides a validated set of reference genes for studying A. ferrooxidans gene expression under typical biological conditions and an initial point of departure for exploring new experimental setups in this microorganism and eventually in other closely related Acidithiobacilli. The information could also be of value for future transcriptomic experiments in other bacterial systems.

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Comparison of different normalization strategies. Mean relative expression levels of four differentially expressed genes using different normalization strategies. Black: stable reference genes used individually, light grey: geometric mean of three stable reference genes selected by geNorm (NF1: rpoC, map and alaS), dark grey: geometric mean of four stable reference genes selected by geNorm (NF2: rpoC, map and era) and white: classical reference genes used individually. (*) Significantly different according to a two tailed unpaired t-test at 95% confidence.
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Figure 4: Comparison of different normalization strategies. Mean relative expression levels of four differentially expressed genes using different normalization strategies. Black: stable reference genes used individually, light grey: geometric mean of three stable reference genes selected by geNorm (NF1: rpoC, map and alaS), dark grey: geometric mean of four stable reference genes selected by geNorm (NF2: rpoC, map and era) and white: classical reference genes used individually. (*) Significantly different according to a two tailed unpaired t-test at 95% confidence.

Mentions: Expression of the four genes of interest in iron versus sulfur grown cells was evaluated using the relative expression analysis software qBase v1.3.5 [48]. Figure 4 shows a significant increase in the expression of the sdrA1 and cbbOIa genes in cells grown in ferrous iron and of the cyoB and mntH genes in cells grown in sulfur. In all cases, normalization by individual reference genes outlined here (rpoC, era or alaS), by the geNorm derived NF1 (rpoC plus map plus alaS), by the combined NF2 (rpoC plus map plus era) and by rrs gave similar results. For example, sdrA1 was up-regulated 60–100 fold depending on whether the normalization strategy was a single stable reference gene or the normalization factors. Conversely, normalization by the recA gene dramatically altered the relative expression ratio of the target gene, revealing an up-regulation of less than 50.


Selection and evaluation of reference genes for improved interrogation of microbial transcriptomes: case study with the extremophile Acidithiobacillus ferrooxidans.

Nieto PA, Covarrubias PC, Jedlicki E, Holmes DS, Quatrini R - BMC Mol. Biol. (2009)

Comparison of different normalization strategies. Mean relative expression levels of four differentially expressed genes using different normalization strategies. Black: stable reference genes used individually, light grey: geometric mean of three stable reference genes selected by geNorm (NF1: rpoC, map and alaS), dark grey: geometric mean of four stable reference genes selected by geNorm (NF2: rpoC, map and era) and white: classical reference genes used individually. (*) Significantly different according to a two tailed unpaired t-test at 95% confidence.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2713239&req=5

Figure 4: Comparison of different normalization strategies. Mean relative expression levels of four differentially expressed genes using different normalization strategies. Black: stable reference genes used individually, light grey: geometric mean of three stable reference genes selected by geNorm (NF1: rpoC, map and alaS), dark grey: geometric mean of four stable reference genes selected by geNorm (NF2: rpoC, map and era) and white: classical reference genes used individually. (*) Significantly different according to a two tailed unpaired t-test at 95% confidence.
Mentions: Expression of the four genes of interest in iron versus sulfur grown cells was evaluated using the relative expression analysis software qBase v1.3.5 [48]. Figure 4 shows a significant increase in the expression of the sdrA1 and cbbOIa genes in cells grown in ferrous iron and of the cyoB and mntH genes in cells grown in sulfur. In all cases, normalization by individual reference genes outlined here (rpoC, era or alaS), by the geNorm derived NF1 (rpoC plus map plus alaS), by the combined NF2 (rpoC plus map plus era) and by rrs gave similar results. For example, sdrA1 was up-regulated 60–100 fold depending on whether the normalization strategy was a single stable reference gene or the normalization factors. Conversely, normalization by the recA gene dramatically altered the relative expression ratio of the target gene, revealing an up-regulation of less than 50.

Bottom Line: Suitability of these and other previously reported reference genes to monitor the expression of four selected target genes from A. ferrooxidans grown with different energy sources was investigated.This investigation provides a validated set of reference genes for studying A. ferrooxidans gene expression under typical biological conditions and an initial point of departure for exploring new experimental setups in this microorganism and eventually in other closely related Acidithiobacilli.The information could also be of value for future transcriptomic experiments in other bacterial systems.

View Article: PubMed Central - HTML - PubMed

Affiliation: ICBM, Universidad de Chile, Santiago, Chile. pamelanietop@gmail.com

ABSTRACT

Background: Normalization is a prerequisite for accurate real time PCR (qPCR) expression analysis and for the validation of microarray profiling data in microbial systems. The choice and use of reference genes that are stably expressed across samples, experimental conditions and designs is a key consideration for the accurate interpretation of gene expression data.

Results: Here, we evaluate a carefully selected set of reference genes derived from previous microarray-based transcriptional profiling experiments performed on Acidithiobacillus ferrooxidans and identify a set of genes with minimal variability under five different experimental conditions that are frequently used in Acidithiobacilli research. Suitability of these and other previously reported reference genes to monitor the expression of four selected target genes from A. ferrooxidans grown with different energy sources was investigated. Utilization of reference genes map, rpoC, alaS and era results in improved interpretation of gene expression profiles in A. ferrooxidans.

Conclusion: This investigation provides a validated set of reference genes for studying A. ferrooxidans gene expression under typical biological conditions and an initial point of departure for exploring new experimental setups in this microorganism and eventually in other closely related Acidithiobacilli. The information could also be of value for future transcriptomic experiments in other bacterial systems.

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