Anti-inflammatory compounds in SCI
Ontology highlight
ABSTRACT:
ORGANISM(S): Rattus norvegicus
SUBMITTER: Rebecka Jornsten
PROVIDER: E-GEOD-633 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Publications
Screening anti-inflammatory compounds in injured spinal cord with microarrays: a comparison of bioinformatics analysis approaches.
Pan Jonathan Z JZ Jörnsten Rebecka R Hart Ronald P RP
Physiological genomics 20040413 2
Inflammatory responses contribute to secondary tissue damage following spinal cord injury (SCI). A potent anti-inflammatory glucocorticoid, methylprednisolone (MP), is the only currently accepted therapy for acute SCI but its efficacy has been questioned. To search for additional anti-inflammatory compounds, we combined microarray analysis with an explanted spinal cord slice culture injury model. We compared gene expression profiles after treatment with MP, acetaminophen, indomethacin, NS398, an ...[more]
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Project description:Genetic analyses suggest that alterations in gene expression at the molecular and tissue levels can have profound effects on aging for multi-cellular organisms. However, much remains unknown about the normal pattern of genetic changes in different tissues and how these tissues interact during aging. To investigate tissue-specific aging systematically, we measured expression profiles of aging in Drosophila melanogaster in seven tissues representing nervous, muscular, digestive, renal, reproductive, and storage systems. In each tissue, we identified hundreds of age-related genes mostly showing gradual changes of transcript levels with age. Age-relatedgenes showed clear tissue-specific transcriptional patterns; less than 10% of age-related genes in each tissue shared expression patterns with any other tissue; less than 20% of age-related biological processes were shared between tissues. A significant portion of tissue-specific age-related genes are those involved in physiological functions regulated by the corresponding tissue. However, limited overlaps of age-related function groups among tissues particularly those involved in proteasome function suggest some common mechanisms of transcription regulation in aging across tissues. This study defined global, temporal and spatial changes associated withaging at the molecular and tissue levels. Analyses indicated that different tissues might age in different patterns or at different rates. This study addressed comprehensively the relationship of age-related changes among different tissues in one organism, providing a foundation to address tissue-specific regulation in aging. RNA was then amplified by a one-step linear amplification protocol to generate amplified RNA (aRNA). Experiment aRNA refers to amplified RNA from flies of 15, 20, 30, 45 and 60 days old, and reference aRNA refers to amplified RNA from flies of 3 days old, and experiment and reference aRNAs were labeled with fluorescent dye Cy3 and Cy5, respectively. For each tissue, RNA from the corresponding tissue of 3-day old flies was used as the reference RNA and expression profiles at each of the five age-points was measured twice by using independently prepared duplicated samples. Seven types of tissues or organs of the male fly strain w1118 , accessory gland, testis, brain, gut, malpighian tubule, dorsal thoracic muscle and abdominal fat body were hand dissected out of flies at age of 3, 15, 20, 30, 45 and 60 days old. Tissues or organs from four males of the same age were pooled together and used for each RNA sample preparation.
2010-06-25 | E-GEOD-6314 | biostudies-arrayexpress
Project description:Histone modifications affect DNA-templated processes ranging from transcription to genomic replication. In this study, we examine the cell cycle dynamics of the trimethylated form of histone H3 lysine 4 (H3K4me3), a mark of active chromatin that is viewed as â??long-livedâ?? [1], and that is involved in memory during cell state inheritance in metazoans [2]. We synchronized yeast using two different protocols, then followed H3K4me3 patterns as yeast passed through subsequent cell cycles. While most H3K4me3 patterns were conserved from one generation to the next, we found that methylation patterns induced by alpha factor or high temperature were erased within one cell cycle, during S phase. Early-replicating regions were erased before late-replicating regions, implicating replication in H3K4me3 loss. However, incomplete H3K4me3 erasure occurred at the majority of loci even when replication was prevented, suggesting that most erasure results from an active process. Indeed, deletion of the demethylase Jhd2 slowed erasure at most loci. Together, these results indicate overlapping roles for passive dilution and active enzymatic demethylation in erasing ancestral histone methylation states in yeast. References: [1] Ng HH, Robert F, Young RA, Struhl K (2003) Targeted recruitment of Set1 histone methylase by elongating Pol II provides a localized mark and memory of recent transcriptional activity. Mol Cell 11: 709-719. [2] Ringrose L, Paro R (2004) Epigenetic regulation of cellular memory by the Polycomb and Trithorax group proteins. Annu Rev Genet 38: 413-443. The overall design of the experiment consists of two cell cycle experiments, each consisting of the following subsets: gene expression, ChIP with anti-H3K4Me3 antibody, and ChIP input. The experiments are as follows: CCA - BY4741 bar1- cells synchronized by alpha factor arrest; CCTS - BY4741 cdc28(ts) cells synchronized by arrest at non-permissive temperature. The individual time courses are enumerated as follows: CCA gene expression (array title "Synchronized cells, xxx min, cell cycle CCA"), 18 arrays; CCA ChIP for anti-H3K4Me3 (array title "H3K4Me3 ChIP cell cycle CCA, xxx min"), 17 arrays, 1 replicate; CCA ChIP input (array title "ChIP Input cell cycle CCA, xxx min"), 18 arrays, 1 replicate; CCTS gene expression (appears in a different dataset as biological replicate "I"; array title "Synchronized cells, xxx min, biological replicate I"), 18 arrays; CCTS ChIP for anti-H3K4Me3 (array title "H3K4Me3 cell cycle CCTS, xxx min"), 2 technical replicates, 18 arrays per replicate; CCTS ChIP input (array title "ChIP Input cell cycle CCTS, xxx min"), 2 technical replicates, 18 arrays per replicate. Gene expression arrays were run against a reference of unsynchronized cells, ChIP-chip anti-H3K4Me3 samples were run against an IP (of the same epitope) of unsynchronized cells, and ChIP input samples were run against either a pool of all the time points in the time course (CCTS) or against sonicated DNA isolated from unsynchronized cells (CCA). Four additional experiments have been performed. They are referred to as series X in the title. Series 1: anti H3K4me3 CHIP time course of BY4741 bar1 delete cells (wt) synchronized with alpha factor and released in the cell cycle, 9 arrays, 1 replicate. Series 2: anti H3K4me3 CHIP time course of BY4741 bar1 jhd2 delete cells (jhd2 delete) synchronized with alpha factor and released in the cell cycle, 7 arrays, 1 replicate. Series 3: anti H3K4me3 CHIP time course of CYM36 cells (cdc7ts) synchronized with alpha factor and released in the cell cycle at the permissive 24C or at the restrictive 37C temperature, 22 arrays, 2 replicates. Series 4: anti H3K4me3 CHIP time course of BY4741 bar1 delete cells (wt) grown in galactose and synchronized with alpha factor and either released in the cell cycle in glucose media or alpha factor arrested and switched to glucose media, 6 arrays, 1 replicate.
2010-06-24 | E-GEOD-14565 | biostudies-arrayexpress
Project description:These arrays were done in the context of a study to probe gene expression variation across Y-chromosome substitution lines of Drosophila melanogaster Keywords: polymorphism, evolution, chromosome substitution This series contains all the arrays and designs described in Lemos et al.
2008-04-29 | E-GEOD-9457 | biostudies-arrayexpress
Project description:Significant insight about biological networks arises from the study of network motifs âoverly abundant network subgraphs, but such wiring patterns do not specify when and how potential routes within a cellular network are used. To address this limitation, we introduce activity motifs, which capture patterns in the dynamic use of a network. Using this framework to analyze transcription in Saccharomyces cerevisiae metabolism, we find that cells use different timing activity motifs to optimize transcription timing in response to changing conditions: forward activation to produce metabolic compounds efficiently, backward shutoff to rapidly stop production of a detrimental product and synchronized activation for co-production of metabolites required for the same reaction Measuring protein abundance over a time course reveals that mRNA timing motifs also occur at the protein level. Timing motifs significantly overlap with binding activity motifs, where genes in a linear chain have ordered binding affinity to a transcription factor, suggesting a mechanism for ordered transcription. Finely timed transcriptional regulation is therefore abundant in yeast metabolism, optimizing the organism's adaptation to new environmental conditions. We generated a set of 13 time courses by measuring gene expression after a metabolic change. Yeast strain KCN118 (MATalpha ade2) was grown at 28 °C in 400 ml of synthetic complete media with 2% dextrose (SCD) to an OD600 of 0.6. Synthetic complete was prepared using the standard recipe, except 75 uM inositol was included. At OD600 of 0.6, 100 ml of cells were collected by centrifugation and frozen as a reference sample, and the remaining cells were rapidly collected by filtration, washed with distilled water and resuspended in 300 ml of one of the following media: SCE (SC + 2% ethanol), SCG (SC + 2% galactose), SM1 (SCD lacking amino acids A, R, N, C, Q, G, K, P, S, F and T), SM2 (SCD lacking amino acids L, I, V, W, H and M), S0 (SCD lacking all amino acids), S0G (no amino acids, 2% galactose) or S0E (no amino acids, 2% ethanol). The data appears in Figures 2 and 4 of the manuscript, as it relates to the global analysis of all the arrays used in the dataset. All time courses consist of the following time points (in min): 15, 30, 60, 120, 240, and were hybridized against the t = 0 time point of cells grown in SCD. Each time course was performed as one single biological replicate and one technological replicate, except where noted below. Specifically, the 13 time courses break down into the following groups: Media key: SCD (synthetic complete, not including inositol) SCE (SC + 2% ethanol) SCG (SC + 2% galactose) SM1 (SCD lacking amino acids A, R, N, C, Q, G, K, P, S, F and T) SM2 (SCD lacking amino acids L, I, V, W, H and M) S0 (SCD lacking all amino acids) S0G (no amino acids, 2% galactose) S0E (no amino acids, 2% ethanol). ino = inositol aa = all amino acids supplemented The following group descriptions are the media as described above, followed by the description as indicated in the long title of the individual arrays: 1. S0 (5 arrays) = SD 2. SCD (6 arrays, t = 240 min has 2 tech replicates) = SD+aa 3. SM2 (5 arrays) = SD+aa:ARNCQGKPSDEFTY+ino 4. SM1 + ino (5 arrays) = SD+aa:LIVWHM+ino 5. S0 + ino (6 arrays, t = 240 min has 2 tech replicates) = SD+ino 6. S0E (5 arrays) = SEtOH 7. S0E + aa (7 arrays, t = 240 min and 60 min each have 2 tech replicates) = SEtOH+aa 8. S0E + aa + ino (5 arrays) = SEtOH+aa+ino 9. S0E + ino (8 arrays, t = 240 min, 15 min and 30 min each have 2 tech replicates) = SEtOH+ino 10. S0G (5 arrays) = Sgal 11. S0G + aa (5 arrays) = Sgal+aa 12. S0G + aa + ino (5 arrays) = Sgal+aa+ino 13. S0G + ino (6 arrays, t = 60 min has 2 tech replicates) = Sgal+ino
2010-06-25 | E-GEOD-13219 | biostudies-arrayexpress
Project description:The use of genome-wide RNA abundance profiling by microarrays and deep sequencing has spurred a revolution in our understanding of transcriptional control. However, changes in mRNA abundance reflect the combined effect of changes in RNA production, processing, and degradation, and thus, mRNA levels provide an occluded view of transcriptional regulation. To partially disentangle these issues, we carry out genome-wide RNA Polymerase II (“Pol2”) localization profiling in budding yeast in two different stress response time courses. While mRNA changes largely reflect changes in transcription, there remains a great deal of variation in mRNA levels that is not accounted for by changes in Pol2 abundance. We find that genes exhibiting “excess” mRNA produced per Pol2 are enriched for those with overlapping cryptic transcripts, indicating a pervasive role for nonproductive or regulatory transcription in control of gene expression. Finally, we characterize changes in Pol2 localization when Pol2 is genetically inactivated using the rpb1-1 temperature-sensitive mutation. We find that Pol2 is lost from chromatin after roughly an hour at the restrictive temperature, and that there is a great deal of variability in the rate of Pol2 loss at different loci. Together, these results provide a global perspective on the relationship between Pol2 and mRNA production in budding yeast. The array studies consisted of 4 time courses in which the genome-wide location of RNA Polymerase II was mapped via chromatin immunoprecipitation (ChIP) in BY4741 S. cerevisiae cells or in such cells bearing the temperature sensitive mutation rpb1, in response to heat shock at 37 degrees C and/or 1.5 mM diamide. All samples were hybridized as the ChIP sample (Cy3 labeled, channel 1) versus its cognate ChIP input sample (Cy5 labeled, channel 2). The first time course was a heat shock in wild-type BY4741 cells. The second time course was a heat shock in BY4741 rpd1 cells. The third time course was a diamide treatment of BY4741 rpd1 cells. The fourth time course was a 10 minute heat shock in BY4741 rpd1 cells followed by treatment from 15-60 minutes with diamide (3 samples). In the first three time courses the time range is 0-120 minutes (5 samples). A total of 18 arrays were used in this study. No additional replicates or dye-flip experiments were performed.
2010-07-16 | E-GEOD-22675 | biostudies-arrayexpress
Project description:Acetylation of histone H3 lysine 56 is a covalent modification best-known as a mark of newly-replicated chromatin, but has also been linked to replication-independent histone replacement. Here, we measured H3K56ac levels at single-nucleosome resolution in asynchronously growing yeast cultures, as well as in yeast proceeding synchronously through the cell cycle. We developed a quantitative model of H3K56ac kinetics, which shows that H3K56ac is largely explained by the genomic replication timing and the turnover rate of each nucleosome, suggesting that cell cycle profiles of H3K56ac should reveal most first-time nucleosome incorporation events. However, since the deacetylases Hst3/4 prevent use of H3K56ac as a marker for histone deposition during M phase, we also directly measured M phase histone replacement rates. We report a global decrease in turnover rates during M phase, and a further specific decrease in turnover among early origins of replication, which switch from rapidly-replaced in G1 phase to stable-bound during M phase. Finally, by measuring H3 replacement in yeast deleted for the H3K56 acetyltransferase Rtt109 and its two co-chaperones Asf1 and Vps75, we find evidence that Rtt109 and Asf1 preferentially enhance histone replacement at rapidly-replaced nucleosomes, whereas Vps75 appears to inhibit histone turnover at those loci. These results provide a broad perspective on histone replacement/incorporation throughout the cell cycle, and suggest that H3K56 acetylation provides a positive feedback loop by which replacement of a nucleosome enhances subsequent replacement at the same location. To characterize incorporation of H3K56ac in yeast, several sets of ChIP-chip experiments were performed, along with a set of gene expression microarrays. The following describes each individual set, the number of biological and array replicates performed, dye-flip replicates if performed, the total number of arrays, and the applicable figures in the manuscript. Except for Item D (gene expression), all arrays were ChIP-chip experiments. A. Mid-log H3K56ac measurement. 3 biological replicates, 1 array replicate each of K56Ac ChIP with Grunstein Lab antibody. 2 biological replicates, 2 array replicates each of K56Ac ChIP with Upstate antibody. 7 total arrays. Figure 1A-C, 3, S1, S2A, S6, S7. B. Cell cycle - H3K56ac measurements. 1 biological replicate, 3 array replicates each of K56Ac ChIP with Upstate antibody. 17 time points (10 min. unavailable in third array replicate). 50 total arrays. Figures 2, 3, 4, S4, S5, S7, S8. C. G1 phase turnover. 1 biological replicate (3 time points) with 1 dye-flip replicate each time point (45 minutes replaced with 60 minutes for dye-flip replicate). 6 total arrays. Tables S2, S3. D. Cell cycle - mRNA measurements. 2 biological replicates, 1 array replicate each. 34 total arrays. Figure S3. E. M phase turnover rates. 2 biological replicates, second biological replicate has one dye-flip replicate. 17 total arrays. Figure 5. F. Deletion mutants in H3K56ac pathway for G1-arrested cells. Strains: wild-type parental strain (PKY4212; 2 biological replicates), asf1D (strain 2 biological replicates), vps75D (3 biological replicates, third biological replicate having two array replicates), rtt109D (2 biological replicates, each with one dye-flip replicate). 12 total arrays. Figure 6.
2008-10-03 | E-GEOD-12822 | biostudies-arrayexpress
Project description:The light-organ symbiosis between the squid Euprymna scolopes and the luminous bacterium Vibrio fischeri offers the opportunity to decipher the hour-by-hour events that occur during the natural colonization of an animal's epithelial surface by its microbial partners. To determine the genetic basis of these events, a glass-slide microarray was used to characterize the light-organ transcriptome of juvenile squid in response to the initiation of symbiosis. Patterns of gene expression were compared between animals not exposed to the symbiont, exposed to the wild-type symbiont, or exposed to a mutant symbiont defective in either of two key characters of this association: bacterial luminescence or autoinducer (AI) production. Hundreds of genes were differentially regulated as a result of symbiosis initiation, and a hierarchy existed in the magnitude of the host's response to three symbiont features: bacterial presence > luminescence > AI production. Putative host receptors for bacterial surface molecules known to induce squid development are up-regulated by symbiont light production, suggesting that bioluminescence plays a key role in preparing the host for bacteria-induced development. Further, because the transcriptional response of tissues exposed to AI in the natural context (i.e., with the symbionts) differed from that to AI alone, the presence of the bacteria potentiates the role of quorum signals in symbiosis. Comparison of these microarray data with those from other symbioses, such as germ-free/conventionalized mice and zebrafish, revealed a set of shared genes that may represent a core set of ancient host responses conserved throughout animal evolution. Six experimental treatments of juvenile animals were performed for the microarray matrix: uncolonized (Apo); uncolonized, but supplemented with AI (Apo + AI); colonized by wild-type V. fischeri (wild type); colonized by a mutant defective in luciferase synthesis (luxA); colonized by a mutant defective in AI synthesis (luxI); and, colonized by the luxI mutant, but supplemented with AI (luxI + AI). At 18 h postinoculation, animals were anesthetized in 2% ethanol in HOSW, and the light organs were removed into RNAlater (Ambion Biosystems).
2008-11-10 | E-GEOD-13533 | biostudies-arrayexpress
Project description:Omeprazole stimulated gene expression in rats Samples and RNA preparation: The series is composed of 9 hybridizations for analysis of differentially expressed genes in the gastric mucosa of omeprazole dosed vs. control rats. Nine rats (200-250 g) were given (by gavage) 400 micromol/kg of the proton pump inhibitor omeprazole (Astra AB, Gothenburg, Sweden) in Methocel (Dow Corning, Midland, MI) daily for 10 weeks. Seven rats received vehicle only. After 10 weeks the stomachs were removed for sampling of full-thickness corpus from the upper part of the greater curvature. Total RNA extraction was performed first by ultrasentrifugation on a cesium chloride cushion and then using TRIZOL Reagent (GIBCO BRL Life Technologies, New York, NY). Labeling and hybridization: Total RNA from 7 untreated rats were pooled and used as a common control. Three micrograms of total RNA from the control pool, and three micrograms of total RNA from each omeprazole dosed rat were reverse transcribed and labeled with capture sequences for subsequent attachment of Cy3- and Cy5-attached dendrimer, respectively, using 3DNA Array 350 Expression Array Detection kit as described in the manufacturer's protocols (Genisphere, Montvale, NJ). The labeling reactions were also spiked with exogenous control RNAs (Stratagene) at ratios of 1.0, 2.0, 3.0, 4.0, 5.0, 6.0, 0.5, 0.33, 0.25 and 0.125 for control spike 1, 2, 3, 4, 5, 6, 8, 9, 10 and 7, respectively. The slides were pre-washed in 2xSSC, 0.2% SDS at 55oC for 20 min, then 0.2x SSC at room temperature for 3 min, and deionized sterile filtered H2O at room temperature for 2 min. The Cy3 and Cy5 labeled samples (combined volume 9 microliter) were mixed with 25 microliter of the hybridization solution containing 0.25 M NaPO4, 1 mM EDTA, 4.5% SDS, 1 x SSC, 2 x Denhardt's solution and 2 microliter LNA dT Blocking reagent (Genisphere). A total hybridization volume of 50 microliter was added onto the array and covered with 24 x 60 mm cover slip. The array was assembled into humidified hybridization chamber (Corning) and hybridized at 60 oC for 18 h by submerging in a water bath. Post-hybridization washes were done once in 2 x SSC, 0.2% SDS at 55 oC for 15 min, then in 2 x SSC at room temperature for 15 min, and finally with 0.2 x SSC at room temperature for 15 min. After washing the fluorescent 3DNA reagent was hybridized to the cDNA at 60 oC for 3 h as described in the manufacturer's protocols. After dendrimer hybridization the slides were washed as described above. Scanning, image analysis and data processing: Arrays were scanned at 10 micrometer resolution with a ScanArray Express HT scanner (Packard BioSciences, Billerica, MA). The microarrays were analyzed using GenePix⢠Pro 4.1 (Axon Instruments, Inc., Union City, CA). All subsequent statistical analyses were performed using the statistical package R, R Development Core Team. A signal intensity based criterion was applied to remove the spots with median spot signal intensity less than 200. A spot area based criterion was applied to remove the spots with the area less than 50 pixels in either channel. Spots with more than 40% of the pixels saturated in either channel were also removed. Print tip-dependent normalization was applied to the data in order to compensate for systematic errors. The normalized ratios of the duplicated spots were averaged. Further analysis was done on the log2 transformed ratios. In order to assess the significance of up- or downregulation of the genes, tests for differential expression were performed using moderated T-tests, as implemented in the Limma R package of Smyth.
2010-06-05 | E-GEOD-1808 | biostudies-arrayexpress
Project description:Gene expression data for cdc28-13 yeast released synchronously into the cell cycle. cdc28-13 yeast were arrested in G1 for 3 hours at 37 degrees. Cells were rapidly cooled to 25 C by mixing with an equal volume of media at 13 C, and time points were taken every 10 minutes. Cells were rapidly pelleted, and mRNA was isolated and hybridized against midlog mRNA.
2015-05-01 | E-GEOD-13232 | biostudies-arrayexpress
Project description:Algal photo-bio hydrogen production, a promising method for producing clean and renewable fuel in the form of hydrogen gas, has been studied extensively over the last few decades. In this study, microarray analyses were used to obtain a global expression profile of mRNA abundance in the green alga Chlamydomonas reinhardtii at five different time points before the onset and during the course of sulphur depleted hydrogen production. The present work confirms previous findings on the impacts of sulphur deprivation but also provides new insights into photosynthesis, sulphur assimilation and carbon metabolism under sulphur starvation towards hydrogen production. For instance, while a general trend towards repression of transcripts encoding photosynthetic genes was observed, the abundance of Lhcbm9 (encoding a major light harvesting polypeptide) and LhcSR1 (encoding a chlorophyll binding protein) was strongly elevated throughout the experiment, suggesting remodeling of the photosystem II light harvesting complex as well as an important function of Lhcbm9 under sulphur starvation. This study presents the first global transcriptional analysis of C. reinhardtii during hydrogen production using five major time points at Peak Oxygen, Mid Oxygen, Zero Oxygen, Mid Hydrogen and Peak Hydrogen. Keywords: Time course, sulfur deprivation, hydrogen production. Time course microarray analyses were used to analyze the global gene expression in sulfur depleted hydrogen producing C. reinhardtii. When depleted of sulfur, a sealed an illuminated C. reinhardtii culture slowly becomes anaerobic and produces hydrogen gas. Based on the changes in the dissolved O2 level and H2 production rate, the whole course of H2 production from the starting of S deprivation to the end of H2 production can be divided into five phases including an Aerobic Phase (I) in which the dissolved O2 level goes up (I), an O2 Consumption Phase (II), an Anaerobic Phase (III), a H2 Production Phase (IV) and a Termination phase (V). Samples were taken from three different bioreactors (biological replicates) at the following time points after the start of S depletion: 6 h, 16 h, 21 h, 37 h and 52 h corresponding to Peak O2, Mid O2, Zero O2, Mid H2 and Peak H2.
2010-05-18 | E-GEOD-9165 | biostudies-arrayexpress