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
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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
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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
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2010-06-05 | E-GEOD-1808 | biostudies-arrayexpress
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2015-05-01 | E-GEOD-13232 | biostudies-arrayexpress
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2010-06-25 | E-GEOD-3643 | biostudies-arrayexpress