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Analysis of transcript changes in a heme-deficient mutant of Escherichia coli in response to CORM-3 [Ru(CO)3Cl(glycinate)].

Wilson JL, McLean S, Begg R, Sanguinetti G, Poole RK - Genom Data (2015)

Bottom Line: Importantly, we also tested inactive CORM-3 (iCORM-3), a ruthenium co-ligand fragment that does not release CO, in order to differentiate between CO- and compound-related effects.Relevant regulatory proteins for each gene were identified, where available, using regulonDB and EcoCyc (World Wide Web).Statistical data modelling was performed on the gene expression data to infer transcription factor activities.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biology and Biotechnology, The University of Sheffield, Sheffield S10 2TN, UK.

ABSTRACT

This article describes in extended detail the methodology applied for acquisition of transcriptomic data, and subsequent statistical data modelling, published by Wilson et al. (2015) in a study of the effects of carbon monoxide-releasing molecule-3 (CORM-3 [Ru(CO)3Cl(glycinate)]) on heme-deficient bacteria. The objective was to identify non-heme targets of CORM action. Carbon monoxide (CO) interacts with heme-containing proteins, in particular respiratory cytochromes; however, CORMs have been shown to elicit multifaceted effects in bacteria, suggesting that the compounds may have additional targets. We therefore sought to elucidate the activity of CORM-3, the first water-soluble CORM and one of the most characterised CORMs to date, in bacteria devoid of heme synthesis. Importantly, we also tested inactive CORM-3 (iCORM-3), a ruthenium co-ligand fragment that does not release CO, in order to differentiate between CO- and compound-related effects. A well-established hemA mutant of Escherichia coli was used for the study and, for comparison, parallel experiments were performed on the corresponding wild-type strain. Global transcriptomic changes induced by CORM-3 and iCORM-3 were evaluated using a Two-Color Microarray-Based Prokaryote Analysis (FairPlay III Labeling) by Agilent Technologies (Inc. 2009). Data acquisition was carried out using Agilent Feature Extraction software (v6.5) and data normalisation, as well as information about gene products and their function was obtained from GeneSpring GX v7.3 (Agilent Technologies). Functional category lists were created using KEGG (Kyoto Encyclopedia of Genes and Genomes). Relevant regulatory proteins for each gene were identified, where available, using regulonDB and EcoCyc (World Wide Web). Statistical data modelling was performed on the gene expression data to infer transcription factor activities. The transcriptomic data can be accessed through NCBI's Gene Expression Omnibus (GEO): series accession number GSE55097 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55097).

No MeSH data available.


Related in: MedlinePlus

Differential expression of notable genes altered in hemA mutant or wild-type bacteria in response to CORM-3 or iCORM-3. The colour-scale bar shows mean fold changes in individual genes of the hemA mutant of E. coli and the corresponding wild-type grown anaerobically in a defined medium after the addition of 100 μM CORM-3 or, for the mutant only, 100 μM iCORM-3. Unless otherwise stated, p values were ≤ 0.05; * indicates a p value that exceeds 0.05.
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f0005: Differential expression of notable genes altered in hemA mutant or wild-type bacteria in response to CORM-3 or iCORM-3. The colour-scale bar shows mean fold changes in individual genes of the hemA mutant of E. coli and the corresponding wild-type grown anaerobically in a defined medium after the addition of 100 μM CORM-3 or, for the mutant only, 100 μM iCORM-3. Unless otherwise stated, p values were ≤ 0.05; * indicates a p value that exceeds 0.05.

Mentions: Data acquisition was carried out using Agilent Feature Extraction software (v6.5), which allows measurement of the Cy3 and Cy5 fluorescence of each feature in the scanned microarray image. Data were normalised using GeneSpring GX v7.3 (Agilent Technologies) by dividing the experimental channel by the control channel and applying a global LOWESS normalisation, which removes dye intensity-dependent artefacts caused by non-linearity of Cy5 and Cy3 fluorescence at low levels. Identification of statistically significant gene expression changes was achieved by applying a t-test with a 2-fold cut-off and p < 0.05. Four replicates were obtained for each condition tested: two biological repeats of CORM-3- or iCORM-3-treated samples hybridised against an untreated control, each with two technical (dye-swap) repeats. Information about gene products and their function was obtained from GeneSpring GX v7.3 (Agilent Technologies). Functional category lists were created using KEGG (Kyoto Encyclopedia of Genes and Genomes) [1,2]. Relevant regulatory proteins for each gene were identified, where available, using regulonDB and EcoCyc (World Wide Web). The functional categories that contained the most highly altered genes are presented in Fig. 1: differential expression and the function of notable genes within these categories are also shown, along with the transcription factors (TFs) involved in their regulation.


Analysis of transcript changes in a heme-deficient mutant of Escherichia coli in response to CORM-3 [Ru(CO)3Cl(glycinate)].

Wilson JL, McLean S, Begg R, Sanguinetti G, Poole RK - Genom Data (2015)

Differential expression of notable genes altered in hemA mutant or wild-type bacteria in response to CORM-3 or iCORM-3. The colour-scale bar shows mean fold changes in individual genes of the hemA mutant of E. coli and the corresponding wild-type grown anaerobically in a defined medium after the addition of 100 μM CORM-3 or, for the mutant only, 100 μM iCORM-3. Unless otherwise stated, p values were ≤ 0.05; * indicates a p value that exceeds 0.05.
© Copyright Policy - CC BY
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4543538&req=5

f0005: Differential expression of notable genes altered in hemA mutant or wild-type bacteria in response to CORM-3 or iCORM-3. The colour-scale bar shows mean fold changes in individual genes of the hemA mutant of E. coli and the corresponding wild-type grown anaerobically in a defined medium after the addition of 100 μM CORM-3 or, for the mutant only, 100 μM iCORM-3. Unless otherwise stated, p values were ≤ 0.05; * indicates a p value that exceeds 0.05.
Mentions: Data acquisition was carried out using Agilent Feature Extraction software (v6.5), which allows measurement of the Cy3 and Cy5 fluorescence of each feature in the scanned microarray image. Data were normalised using GeneSpring GX v7.3 (Agilent Technologies) by dividing the experimental channel by the control channel and applying a global LOWESS normalisation, which removes dye intensity-dependent artefacts caused by non-linearity of Cy5 and Cy3 fluorescence at low levels. Identification of statistically significant gene expression changes was achieved by applying a t-test with a 2-fold cut-off and p < 0.05. Four replicates were obtained for each condition tested: two biological repeats of CORM-3- or iCORM-3-treated samples hybridised against an untreated control, each with two technical (dye-swap) repeats. Information about gene products and their function was obtained from GeneSpring GX v7.3 (Agilent Technologies). Functional category lists were created using KEGG (Kyoto Encyclopedia of Genes and Genomes) [1,2]. Relevant regulatory proteins for each gene were identified, where available, using regulonDB and EcoCyc (World Wide Web). The functional categories that contained the most highly altered genes are presented in Fig. 1: differential expression and the function of notable genes within these categories are also shown, along with the transcription factors (TFs) involved in their regulation.

Bottom Line: Importantly, we also tested inactive CORM-3 (iCORM-3), a ruthenium co-ligand fragment that does not release CO, in order to differentiate between CO- and compound-related effects.Relevant regulatory proteins for each gene were identified, where available, using regulonDB and EcoCyc (World Wide Web).Statistical data modelling was performed on the gene expression data to infer transcription factor activities.

View Article: PubMed Central - PubMed

Affiliation: Department of Molecular Biology and Biotechnology, The University of Sheffield, Sheffield S10 2TN, UK.

ABSTRACT

This article describes in extended detail the methodology applied for acquisition of transcriptomic data, and subsequent statistical data modelling, published by Wilson et al. (2015) in a study of the effects of carbon monoxide-releasing molecule-3 (CORM-3 [Ru(CO)3Cl(glycinate)]) on heme-deficient bacteria. The objective was to identify non-heme targets of CORM action. Carbon monoxide (CO) interacts with heme-containing proteins, in particular respiratory cytochromes; however, CORMs have been shown to elicit multifaceted effects in bacteria, suggesting that the compounds may have additional targets. We therefore sought to elucidate the activity of CORM-3, the first water-soluble CORM and one of the most characterised CORMs to date, in bacteria devoid of heme synthesis. Importantly, we also tested inactive CORM-3 (iCORM-3), a ruthenium co-ligand fragment that does not release CO, in order to differentiate between CO- and compound-related effects. A well-established hemA mutant of Escherichia coli was used for the study and, for comparison, parallel experiments were performed on the corresponding wild-type strain. Global transcriptomic changes induced by CORM-3 and iCORM-3 were evaluated using a Two-Color Microarray-Based Prokaryote Analysis (FairPlay III Labeling) by Agilent Technologies (Inc. 2009). Data acquisition was carried out using Agilent Feature Extraction software (v6.5) and data normalisation, as well as information about gene products and their function was obtained from GeneSpring GX v7.3 (Agilent Technologies). Functional category lists were created using KEGG (Kyoto Encyclopedia of Genes and Genomes). Relevant regulatory proteins for each gene were identified, where available, using regulonDB and EcoCyc (World Wide Web). Statistical data modelling was performed on the gene expression data to infer transcription factor activities. The transcriptomic data can be accessed through NCBI's Gene Expression Omnibus (GEO): series accession number GSE55097 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE55097).

No MeSH data available.


Related in: MedlinePlus