Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Sanguinarine, putative anticancer therapeutic, interacts,modulates and transcripts in the context of chromatin

ABSTRACT: DNA binding anticancer agents cause alteration in chromatin structure and dynamics. Here, we report the dynamic interaction of the DNA intercalator and potential anticancer, plant alkaloid, Sanguinarine (SGR) with chromatin. Association of SGR with different levels of chromatin structure was found to be enthalpydriven. Apart from DNA it binds with comparable affinity to histones and induces chromatin aggregation. The dual binding property of SGR leads to inhibition of core histone modifications. Although, it potently inhibits H3K9 methylation by G9a in vitro, H3K4 and H3R17 methylation are more profoundly inhibited in cells. SGR inhibits histone acetylation both in vitro and in vivo. It does not affect the in vitro transcription from DNA template but significantly represses acetylation dependent chromatin transcription. SGR mediated repression of epigenetic marks and the alteration of chromatin geography, also result in modulation of global gene expression. These data conclusively, show the anticancer DNA binding intercalator as a modulator of chromatin modifications and transcription in the chromatin context. The total RNA was isolated from control and treated cells using TRIZOL (Invitrogen) method. The Micromax direct labeling kit, MPS502 (PerkinElmer) was used to synthesize the labeled cDNA from 70 ug of total RNA and further process the hybridized cDNA on the array. All the steps were carried out according to manufacturerâs instructions (www.perkinelmer.com/lifesciences). The array slides were scanned immediately by PerkinElmer Scan array Gx Microarray scanner. The Scan array software (PerkinElmer) was used for grid wise normalization of array images. Two arrays were used with at least one biological treatment of cells and dye swap experiment were included in the final analysis. . The data was analysed by GeneSpring GX and Biointerpreter software from Genotypic Technology, Bangalore. The differential expression was considered if the Log 2 mean of at least -1 for the down regulated genes and +1 for the upregulated genes. We considered only the genes that were reproducible from both replicates.

ORGANISM(S): Homo sapiens

SUBMITTER: Tapas Kundu

PROVIDER: E-GEOD-14314 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Sanguinarine interacts with chromatin, modulates epigenetic modifications, and transcription in the context of chromatin.

Selvi B Ruthrotha R Pradhan Suman Kalyan SK Shandilya Jayasha J Das Chandrima C Sailaja Badi Sri BS Shankar G Naga N Gadad Shrikanth S SS Reddy Ashok A Dasgupta Dipak D Kundu Tapas K TK

Chemistry & biology 20090201 2

DNA-binding anticancer agents cause alteration in chromatin structure and dynamics. We report the dynamic interaction of the DNA intercalator and potential anticancer plant alkaloid, sanguinarine (SGR), with chromatin. Association of SGR with different levels of chromatin structure was enthalpy driven with micromolar dissociation constant. Apart from DNA, it binds with comparable affinity with core histones and induces chromatin aggregation. The dual binding property of SGR leads to inhibition o ...[more]

PMID: 19246011

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Project description:DNA-binding anticancer agents cause alteration in chromatin structure and dynamics. Here, we report the dynamic interaction of the DNA intercalator and potential anticancer, plant alkaloid, sanguinarine (SGR) with chromatin. Association of SGR with different levels of chromatin structure was found to be enthalpy driven. Apart from DNA, it binds with comparable affinity to histones and induces chromatin aggregation. The dual binding property of SGR leads to inhibition of core histone modifications. Although it potently inhibits H3K9 methylation by G9a in vitro, H3K4 and H3R17 methylation are more profoundly inhibited in cells. SGR inhibits histone acetylation both in vitro and in vivo. It does not affect the in vitro transcription from DNA template but significantly represses acetylation-dependent chromatin transcription. SGR mediated repression of epigenetic marks and the alteration of chromatin geography also result in modulation of global gene expression. These data conclusively show that the anticancer DNA-binding intercalator as a modulator of chromatin modifications and transcription in the chromatin context. The total RNA was isolated from control and treated cells using the TRIzol (Invitrogen) method. The Micromax direct labeling kit, MPS502 (PerkinElmer), was used to synthesize the labeled cDNA from 70 ug of total RNA and further process the hybridized cDNA on the array. All the steps were carried out according to manufacturer’s instructions (www.perkinelmer.com/lifesciences). The array slides were scanned immediately by the PerkinElmer Scan array Gx Microarray scanner. The Scan array software (PerkinElmer) was used for grid wise normalization of array images. Five arrays were used with at least two biological treatments of cells, and dye-swap experiments were included in the final analysis. The data was analysed by GeneSpring GX and Biointerpreter software from Genotypic Technology, Bangalore. The differential expression was considered if the Log 2 mean of at least -1 for the downregulated genes and +1 for the upregulated genes. We considered only the genes that were reproducible from all five replicates.

Project description:Intracellular Ca2+ release through the Inositol 1,4,5-Triphosphate Receptor (InsP3R) is a feature of all multicellular organisms in which it shapes the temporal and spatial aspects of calcium signaling in cells, affecting several developmental and physiological processes. Mutants in the InsP3R gene of Drosophila (itpr) exhibit a range of defects which include growth defects and larval lethality.The Drosophila Insulin-like peptides (ILPs) are encoded by multigene families that are expressed in the brain and other tissues. Upon secretion, these peptides likely serve as hormones, neurotransmitters, and growth factors. In Drosophila melanogaster, molecular genetic studies have revealed Drosophila ILPs as elements of a conserved insulin signaling pathway, and as in other animal models, it appears to play a key role in metabolism, growth, reproduction, and aging. Previous work from our group has shown that InsP3R function can be rescued by ectopically expressing InsP3R in dilp cells or can be compensated by altering the activity of Sarco-Endoplasmic Reticulum Calcium-ATPase (SERCA). To understand the molecular basis of larval lethality and growth defect in Drosophila InsP3R mutants and to decipher possible cross talk of itpr gene with other signaling pathways we have carried out genome wide microarray experiments. We have compared the transcript profiles of i) itpr mutant larvae and wild type larvae, ii) dilp rescue larvae with itpr mutant larvae iii) itpr and SERCA double mutant larvae with itpr mutant larvae. By this we have identified genes whose levels are altered in itpr mutants and are restored towards wild type in dilp rescue larvae with itpr mutant larvae and itpr and SERCA double mutants. Our experiments help in identify genes that are regulated by changes in intracellular Ca2+ in the context of larval viability may contribute to the better understanding of the major human pathologies caused by calcium misbalance or by dysregulation of the insulin/IGF pathway. The 8x60k array AMADID: 27326 slide was scanned immediately by PerkinElmer Scan array Gx Microarray scanner. The Scan array software (PerkinElmer) was used for grid wise normalization of array images. Three were used with Mutant, three for Dilp Rescue and two for Kum Rescue experiments . The data was analysed by GeneSpring GX Agilent . The differential expression was considered if the Log 2 mean of at least -1 for the down regulated genes and +1 for the upregulated genes. We considered only the genes that were reproducible from biological triplicates for Mutant, biological treplicates for Dilp Rescue and biological duplicates for Kum Rescue.

Project description:Salmonella is an important enteric pathogen that causes a spectrum of diseases varying from mild gastroenteritis to life threatening typhoid fever. Salmonella does not have lac operon. However, E. Coli, Salmonellaâs close relative, has lac operon. Being an enteric pathogen like E. coli, Salmonella will also benefit from lac operon. Then, why Salmonella has lost lac operon?. To address this question, lacI, an important component of lac operon was expressed in Salmonella via pTrc99A plasmid. As a control, pTrc99A without lacI was also expressed in Salmonella. The effect of LacI on the transcription profile of Salmonella was analyzed using microarray technique. Overall design The total RNA was isolated from Salmonella using âRNeasy Mini Kitâ (QIAGEN). Organism used: Salmonella enterica serovar Typhimurium LT2 * Slides: Agilentâs arrays (8x15k) AMADID: NO: 17809 * Starting material: Salmonella RNA in nuclease-free water * RNA Samples used: Wild type (WT), WT + pTrc99A+LacI (PTRC), WT + pTrc99A-LacI(Delta lac) * Labeling kit: MessageAmpâ¢ II-Bacteria RNA Amplification Kit from Ambion Cat # AM1790 * Labeling Method: T7 promoter based-linear amplification to generate labeled complementary RNA * Total RNA and cRNA Purification Kit: Qiagenâs RNeasy minikit Cat#74104 * Hybridization Kit: Agilentâs In situ Hybridzation kit 5184-3568 * RNA quality was checked using Bioanalyzer. The array slides were scanned immediately by PerkinElmer Scan array Gx Microarray scanner. The Scan array software (PerkinElmer) was used for grid wise normalization of array images. Two arrays were used with mutant and rescue experiments and dye swap experiments were included in the final analysis. The data was analysed by GeneSpring GX and Biointerpreter software from Genotypic Technology, Bangalore. The differential expression was considered if the Log 2 mean of at least -1 for the down regulated genes and +1 for the upregulated genes. We considered only the genes that were reproducible from both replicates.

Project description:Retinoblastoma Y79 cell line was treated with specific siRNA to silence EpCAM gene expression in vitro and RNA was isolated for microarray experiment to study the changes in the whole gene expression profiling in the Y79 cell line. The study identified 465 up-regulated genes (>1.0 fold) and 205 down-regulated genes (<0.5 fold) in response to knockdown of Ep-CAM. Organism used: Homo Sapiens ï Slides: Whole genome Human 4x44k array ï Starting material: Cells in RNA Later ï RNA Samples used: Control, siRNA1 ï Labeling kit: Agilent Low Input RNA Linear amplification kit ï Labeling Method: T7 promoter based-linear amplification to generate labelled complementary RNA ï Total RNA and cRNA Purification Kit: Qiagenâs RNeasy minikit ï Hybridization Kit: Agilent Insitu Hybridization Kit Hybridization protocol The fragmented cRNA were mixed with 25ul of 2x GE Hybridization Buffer (Agilent). About 45ul of the resulting mixture was applied to the Microarray and hybridized at 65degC for 17 hours in an Agilent Microarray Hybridization Chamber (SureHyb: G2534A) with Hybridization Oven. After hybridization, slides were washed with Agilent Gene expression Wash Buffer I for 1 minute at room temperature followed by a 1 min wash with Agilent Gene expression Wash Buffer II for 37C. Slides were finally rinsed with Acetonitrile for cleaning up and drying. Scan protocol Laser detection of Cyanine 3 and Cyanine 5 fluorescence is performed using a confocal scanning instrument containing two tuned lasers, which excite Cyanine dyes at the appropriate wavelengths. Description Microarrays were scanned on an Agilent scanner (G2565AA) at 100% laser power, 30% PMT.Data extraction was carried out with Agilent Feature Extraction software (version 9.1), and normalization was done using linear per array algorithm according to the manufacturerâs protocol. Data processing Feature extracted data was analyzed using GeneSpring GX v 7.3.1 software from Agilent. Normalization of the data was done in GeneSpring GX using the recommended one color Per Chip and Per Gene Data Transformation: Set measurements less than 0.01 to 0.01, Per Chip: Normalize to 50th percentile, Per Gene: Normalize to Specific Samples. Further quality control of normalized data was done using correlation based condition tree to eliminate bad experiments. Differentially regulated Genes were filtered with cutoff of > 1.5 for Up regulation and < 0.55 for Down Regulation were obtained. Differentially regulated genes were clustered using gene tree to identify significant gene expression patterns.

Project description:Retinoblastoma Y79 cell line was treated with scopoletin in vitro and RNA was isolated for microarray experiment to study the changes in the whole gene expression profiling in the Y79 cell line. The study identified 1675 up-regulated genes (>1.0 fold) and 1879 down-regulated genes (<-1 fold) in response to scopoletin treatment Slides:Whole genome Human 4x44k array ï Starting material: Cells in RNA Later ï RNA Samples used: Y79_c_Noni Extract,Control ï Labeling kit: Agilentâs Quick-Amp labeling Kit ï Labeling Method: T7 promoter based-linear amplification to generate labeled complementary RNA ï Total RNA and cRNA Purification Kit: Qiagenâs RNeasy minikit Cat ï Hybridization Kit: Agilentâs In situ Hybridzation kit Hybridization protocol The fragmented cRNA were mixed with 25ul of 2x GE Hybridization Buffer (Agilent). About 45ul of the resulting mixture was applied to the Microarray and hybridized at 65degC for 17 hours in an Agilent Microarray Hybridization Chamber (SureHyb: G2534A) with Hybridization Oven. After hybridization, slides were washed with Agilent Gene expression Wash Buffer I for 1 minute at room temperature followed by a 1 min wash with Agilent Gene expression Wash Buffer II for 37C. Slides were finally rinsed with Acetonitrile for cleaning up and drying. Scan protocol Laser detection of Cyanine 3 and Cyanine 5 fluorescence is performed using a confocal scanning instrument containing two tuned lasers, which excite Cyanine dyes at the appropriate wavelengths. Description Microarrays were scanned on an Agilent scanner (G2565AA) at 100% laser power, 30% PMT.Data extraction was carried out with Agilent Feature Extraction software (version 9.1), and normalization was done using linear per array algorithm according to the manufacturerâs protocol. Data processing Feature extracted data was analyzed using GeneSpring GX v 7.3.1 software from Agilent. Normalization of the data was done in GeneSpring GX using the recommended one color Per Chip and Per Gene Data Transformation: Set measurements less than 0.01 to 0.01, Per Chip: Normalize to 50th percentile, Per Gene: Normalize to Specific Samples. Further quality control of normalized data was done using correlation based condition tree to eliminate bad experiments. Differentially regulated Genes were filtered with cutoff of > 1.5 for Up regulation and < 0.55 for Down Regulation were obtained. Differentially regulated genes were clustered using gene tree to identify significant gene expression patterns.

Project description:Gene expression analysis study in curcumin treated (20ÂµM curcumin treated Y79 cells ) and control Y79 cells (Suspension Y79 cells). Source were Y79 retinoblastoma cell line from human. Organism used: Homo sapiens ï Slides: Gene Expression Whole Human Genome 4x44k ï Starting material: Cells in RNA later ï RNA Samples used: :Control Y79 and Treated_Curcumin ï Labeling kit: Agilents Low input RNA linear amplification Kit one color Labeling Method: T7 promoter based-linear amplification to generate labeled complementary RNA ï Total RNA and cRNA Purification Kit: Qiagenâs RNeasy minikit ï Hybridization Kit: Agilentâs In situ Hybridzation kit Hybridization protocol The fragmented cRNA were mixed with 25ul of 2x GE Hybridization Buffer (Agilent). About 45ul of the resulting mixture was applied to the Microarray and hybridized at 65degC for 17 hours in an Agilent Microarray Hybridization Chamber (SureHyb: G2534A) with Hybridization Oven. After hybridization, slides were washed with Agilent Gene expression Wash Buffer I for 1 minute at room temperature followed by a 1 min wash with Agilent Gene expression Wash Buffer II for 37C. Slides were finally rinsed with Acetonitrile for cleaning up and drying. Scan protocol Laser detection of Cyanine 3 and Cyanine 5 fluorescence is performed using a confocal scanning instrument containing two tuned lasers, which excite Cyanine dyes at the appropriate wavelengths. Description Microarrays were scanned on an Agilent scanner (G2565AA) at 100% laser power, 30% PMT.Data extraction was carried out with Agilent Feature Extraction software (version 9.1), and normalization was done using linear per array algorithm according to the manufacturerâs protocol. Data processing Feature extracted data was analyzed using GeneSpring GX v 7.3.1 software from Agilent. Normalization of the data was done in GeneSpring GX using the recommended one color Per Chip and Per Gene Data Transformation: Set measurements less than 0.01 to 0.01, Per Chip: Normalize to 50th percentile, Per Gene: Normalize to Specific Samples. Further quality control of normalized data was done using correlation based condition tree to eliminate bad experiments. Differentially regulated Genes were filtered with cutoff of > 1.5 for Up regulation and < 0.55 for Down Regulation were obtained. Differentially regulated genes were clustered using gene tree to identify significant gene expression patterns.

Project description:Gene expression analysis study in cerulenin treated - 7Âµg/ml cerulenin treated Y79 cells and control Y79 cells Organism used: Homo sapiens ï Slides: Gene Expression Whole Human Genome 4x44k ï Starting material: Cells in RNA later ï RNA Samples used: :Control Y79 and Treated_Cerulenin ï Labeling kit: Agilents Low input RNA linear amplification Kit one color ï Labeling Method: T7 promoter based-linear amplification to generate labeled complementary RNA ï Total RNA and cRNA Purification Kit: Qiagenâs RNeasy minikit ï Hybridization Kit: Agilentâs In situ Hybridzation kit Hybridization protocol The fragmented cRNA were mixed with 25ul of 2x GE Hybridization Buffer (Agilent). About 45ul of the resulting mixture was applied to the Microarray and hybridized at 65degC for 17 hours in an Agilent Microarray Hybridization Chamber (SureHyb: G2534A) with Hybridization Oven. After hybridization, slides were washed with Agilent Gene expression Wash Buffer I for 1 minute at room temperature followed by a 1 min wash with Agilent Gene expression Wash Buffer II for 37C. Slides were finally rinsed with Acetonitrile for cleaning up and drying. Scan protocol Laser detection of Cyanine 3 and Cyanine 5 fluorescence is performed using a confocal scanning instrument containing two tuned lasers, which excite Cyanine dyes at the appropriate wavelengths. Description Microarrays were scanned on an Agilent scanner (G2565AA) at 100% laser power, 30% PMT.Data extraction was carried out with Agilent Feature Extraction software (version 9.1), and normalization was done using linear per array algorithm according to the manufacturerâs protocol. Data processing Feature extracted data was analyzed using GeneSpring GX v 7.3.1 software from Agilent. Normalization of the data was done in GeneSpring GX using the recommended one color Per Chip and Per Gene Data Transformation: Set measurements less than 0.01 to 0.01, Per Chip: Normalize to 50th percentile, Per Gene: Normalize to Specific Samples. Further quality control of normalized data was done using correlation based condition tree to eliminate bad experiments. Differentially regulated Genes were filtered with cutoff of > 1.5 for Up regulation and < 0.55 for Down Regulation were obtained. Differentially regulated genes were clustered using gene tree to identify significant gene expression patterns.

Dataset Information

Sanguinarine, putative anticancer therapeutic, interacts,modulates and transcripts in the context of chromatin

Publications

Sanguinarine interacts with chromatin, modulates epigenetic modifications, and transcription in the context of chromatin.

Similar Datasets

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