Profiling of Hepatic Gene Expression of Mice Fed with Edible Japanese Mushrooms by DNA Microarray Analysis: Comparison amongPleurotus ostreatus,Grifola frondosa, andHypsizigus marmoreus

2011 ◽  
Vol 59 (19) ◽  
pp. 10723-10731 ◽  
Author(s):  
Mayumi Sato ◽  
Yoshihiko Tokuji ◽  
Shozo Yoneyama ◽  
Kyoko Fujii-Akiyama ◽  
Mikio Kinoshita ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Grifola Frondosa ◽  
Hepatic Gene Expression ◽  
Dna Microarray Analysis

scholarly journals DNA microarray analysis of hepatic gene expression in mice exposed to cadmium for 30 days

2013 ◽  
Vol 38 (1) ◽  
pp. 155-157 ◽  
Author(s):  
Maki Tokumoto ◽  
Tomoaki Ohtsu ◽  
Shunji Imai ◽  
Akiko Honda ◽  
Hisamitsu Nagase ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Hepatic Gene Expression ◽  
Dna Microarray Analysis

scholarly journals The Potential of 2-aza-8-Oxohypoxanthine as a Cosmetic Ingredient

Cosmetics ◽  
2021 ◽  
Vol 8 (3) ◽  
pp. 60
Author(s):  
Hisae Aoshima ◽  
Masayuki Ito ◽  
Rinta Ibuki ◽  
Hirokazu Kawagishi
Keyword(s):  
Gene Expression ◽  
Cell Proliferation ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Cell Activation ◽  
Skin Barrier ◽  
Efficacy Evaluation ◽  
Activation Effect ◽  
Expression Levels ◽  
Dna Microarray Analysis

In this study, we verified the effects of 2-aza-8-oxohypoxanthine (AOH) on human epidermal cell proliferation by performing DNA microarray analysis. Cell proliferation was assessed using the 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, which measures mitochondrial respiration in normal human epidermal keratinocyte (NHEK) cells. Gene expression levels were determined by DNA microarray analysis of 177 genes involved in skin aging and disease. AOH showed a significant increase in cell viability at concentrations between 7.8 and 31.3 μg/mL and a significant decrease at concentrations above 250 μg/mL. DNA microarray analysis showed that AOH significantly increased the gene expression of CLDN1, DSC1, DSG1, and CDH1 (E-cadherin), which are involved in intercellular adhesion and skin barrier functioning. AOH also up-regulated the expression of KLK5, KLK7, and SPIMK5, which are proteases involved in stratum corneum detachment. Furthermore, AOH significantly stimulated the expression of KRT1, KRT10, TGM1, and IVL, which are considered general differentiation indicators, and that of SPRR1B, a cornified envelope component protein. AOH exerted a cell activation effect on human epidermal cells. Since AOH did not cause cytotoxicity, it was considered that the compound had no adverse effects on the skin. In addition, it was found that AOH stimulated the expression levels of genes involved in skin barrier functioning by DNA microarray analysis. Therefore, AOH has the potential for practical use as a cosmetic ingredient. This is the first report of efficacy evaluation tests performed for AOH.

scholarly journals DNA microarray analysis of global gene regulation by A-factor in Streptomyces griseus

Microbiology ◽  
2009 ◽  
Vol 155 (7) ◽  
pp. 2197-2210 ◽  
Author(s):  
Hirofumi Hara ◽  
Yasuo Ohnishi ◽  
Sueharu Horinouchi
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Streptomyces Griseus ◽  
Exponential Growth Phase ◽  
Mobility Shift ◽  
Dna Microarray Analysis ◽  
Regulatory Cascade ◽  
Transcriptional Units ◽  
Inducible Genes

A-factor (2-isocapryloyl-3R-hydroxymethyl-γ-butyrolactone) is a microbial hormone that triggers morphological differentiation and secondary metabolism in Streptomyces griseus. The effects of A-factor on global gene expression were determined by DNA microarray analysis of transcriptomes obtained with the A-factor-deficient mutant ΔafsA. A-factor was added at a concentration of 25 ng ml−1 to mutant ΔafsA at the middle of the exponential growth phase, and RNA samples were prepared from the cells grown after A-factor addition for a further 5, 15 and 30 min, and 1, 2, 4, 8 and 12 h. The effects of A-factor on transcription of all protein-coding genes of S. griseus were evaluated by comparison of the transcriptomes with those obtained from cells grown in the absence of A-factor. Analysis of variance among the transcriptomes revealed that 477 genes, which were dispersed throughout the chromosome, were differentially expressed during the 12 h after addition of A-factor, when evaluated by specific criteria. Quality threshold clustering analysis with regard to putative polycistronic transcriptional units and levels of upregulation predicted that 152 genes belonging to 74 transcriptional units were probable A-factor-inducible genes. Competitive electrophoretic mobility shift assays using DNA fragments including putative promoter regions of these 74 transcriptional units suggested that AdpA bound 37 regions to activate 72 genes in total. Many of these A-factor-inducible genes encoded proteins of unknown function, suggesting that the A-factor regulatory cascade of S. griseus affects gene expression at a specific time point more profoundly than expected.

DNA microarray analysis of cortical gene expression during early recirculation after focal brain ischemia in rat

2002 ◽  
Vol 108 (1-2) ◽  
pp. 81-93 ◽  
Author(s):  
Rainald Schmidt-Kastner ◽  
Baotong Zhang ◽  
Ludmila Belayev ◽  
Larissa Khoutorova ◽  
Rupen Amin ◽  
...  
Keyword(s):  
Gene Expression ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Brain Ischemia ◽  
Dna Microarray Analysis ◽  
Focal Brain Ischemia

Novel Stratification Scheme for AML Based on a Large-Scale DNA Microarray Analysis of CD133-Positive Blasts.

Blood ◽  
2004 ◽  
Vol 104 (11) ◽  
pp. 2043-2043
Author(s):  
Hiroyuki Mano ◽  
Yoshihiro Yamashita
Keyword(s):  
Gene Expression ◽  
Gene Expression Profile ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Expression Profile ◽  
Treatment Strategy ◽  
Large Scale ◽  
Dna Microarray Analysis ◽  
Wide Range ◽  
Microarray Analyses

Abstract AML is a clonal disorder of immature hematopoietic blasts and has a variable clinical outcome. Current classification of AML is based predominantly on the cytogenetic abnormalities and morphology of the malignant blasts and is not always helpful for optimization of treatment strategy. It is, for instance, very difficult to predict the prognosis of AML patients with a normal karyotype, who constitute ~50% of the AML population. DNA microarray analysis has the potential to provide a novel stratification scheme for AML patients, which is based on gene expression profile, and might help to predict the prognosis of, and optimize the treatment strategy for, each affected individual. However, leukemic blasts derived from bone marrow (BM) of AML-related disorders, are not homogeneous. The blasts may constitute from 20% to almost 100% of mononuclear cells (MNCs) in the marrow. Furthermore, given that many leukemic blasts possess the ability to differentiate to a certain extent, the marrow of AML patients contains not only the immature blasts (leukemic stem clone) but also differentiated blasts. A simple comparison of BM MNCs among heterogeneous AML patients is thus likely to reveal a large number of changes in gene expression that only reflect differences either in the percentage of blasts or in the differentiation ability of the blasts. To minimize such population-shift effects in microarray analyses, we established a large-scale cell depository “Blast Bank” for the storage of CD133 (AC133)-positive hematopoietic stem cell-like fractions from individuals with a wide range of hematopoietic disorders. In the present study, we have used Affymetrix HGU133 A&B microarrays to measure the expression profiles of ~33,000 genes in the Blast Bank specimens of 99 adults with AML-related disorders: 83 individuals with AML and 16 patients in the RAEB stage of MDS. In contrast to the previous microarray analyses of BM MNCs of AML, unsupervised hierarchical clustering of the subjects based on the expression profile did not separate the patients into FAB subtype-matched subgroups. Comparison of gene expression profile between the long-time and short-time survivors has identified a small number of outcome-related genes. Supervised class prediction, based on these genes, with k-nearest neighbor method or Cox proportional hazard model both succeeded to clearly separate individuals into subgroups with statistically distinct prognoses. Our analysis may pave a way toward the expression profile-based novel stratification scheme for AML.

The intraclass correlation coefficient applied for evaluation of data correction, labeling methods, and rectal biopsy sampling in DNA microarray experiments

2003 ◽  
Vol 16 (1) ◽  
pp. 99-106 ◽  
Author(s):  
Linette Pellis ◽  
Nicole L. W. Franssen-van Hal ◽  
Jan Burema ◽  
Jaap Keijer
Keyword(s):  
Gene Expression ◽  
Correlation Coefficient ◽  
Intraclass Correlation Coefficient ◽  
Microarray Analysis ◽  
Dna Microarray ◽  
Microarray Data ◽  
Intraclass Correlation ◽  
Experimental Conditions ◽  
Data Correction ◽  
Dna Microarray Analysis

We show that the intraclass correlation coefficient (ICC) can be used as a relatively simple statistical measure to assess methodological and biological variation in DNA microarray analysis. The ICC is a measure that determines the reproducibility of a variable, which can easily be calculated from an ANOVA table. It is based on the assessment of both systematic deviation and random variation, and it facilitates comparison of multiple samples at once. We used the ICC first to optimize our microarray data normalization method and found that the use of median values instead of mean values improves data correction. Then the reproducibility of different labeling methods was evaluated, and labeling by indirect fluorescent dye incorporation appeared to be more reproducible than direct labeling. Finally, we determined optimal biopsy sampling by analyzing overall variation in gene expression. The variation in gene expression of rectal biopsies within persons decreased when two biopsies were taken instead of one, but it did not considerably improve when more than two biopsies were taken from one person, indicating that it is sufficient to use two biopsies per person for DNA microarray analysis under our experimental conditions. To optimize the accuracy of the microarray data, biopsies from at least six different persons should be used per group.

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