Genome-wide transcript profiling was used to monitor signal transduction during yeast pheromone response. Genetic manipulations allowed analysis of changes in gene expression underlying pheromone signaling, cell cycle control, and polarized morphogenesis. A two-dimensional hierarchical clustered matrix, covering 383 of the most highly regulated genes, was constructed from 46 diverse experimental conditions. Diagnostic subsets of coexpressed genes reflected signaling activity, cross talk, and overlap of multiple mitogen-activated protein kinase (MAPK) pathways. Analysis of the profiles specified by two different MAPKs-Fus3p and Kss1p-revealed functional overlap of the filamentous growth and mating responses. Global transcript analysis reflects biological responses associated with the activation and perturbation of signal transduction pathways.
We describe a flexible system for gene expression profiling using arrays of tens of thousands of oligonucleotides synthesized in situ by an ink-jet printing method employing standard phosphoramidite chemistry. We have characterized the dependence of hybridization specificity and sensitivity on parameters including oligonucleotide length, hybridization stringency, sequence identity, sample abundance, and sample preparation method. We find that 60-mer oligonucleotides reliably detect transcript ratios at one copy per cell in complex biological samples, and that ink-jet arrays are compatible with several different sample amplification and labeling techniques. Furthermore, results using only a single carefully selected oligonucleotide per gene correlate closely with those obtained using complementary DNA (cDNA) arrays. Most of the genes for which measurements differ are members of gene families that can only be distinguished by oligonucleotides. Because different oligonucleotide sequences can be specified for each array, we anticipate that ink-jet oligonucleotide array technology will be useful in a wide variety of DNA microarray applications.
Ischemic brain and peripheral white blood cells release cytokines, chemokines and other molecules that activate the peripheral white blood cells after stroke. To assess gene expression in these peripheral white blood cells, whole blood was examined using oligonucleotide microarrays in 15 patients at 2.4 ± 0.5, 5 and 24 h after onset of ischemic stroke and compared with control blood samples. The 2.4 h blood samples were drawn before patients were treated either with tissue-type plasminogen activator (tPA) alone or with tPA plus Eptifibatide (the Combination approach to Lysis utilizing Eptifibatide And Recombinant tPA trial). Most genes induced in whole blood at 2 to 3 h were also induced at 5 and 24 h. Separate studies showed that the genes induced at 2 to 24 h after stroke were expressed mainly by polymorphonuclear leukocytes and to a lesser degree by monocytes. These genes included: matrix metalloproteinase 9; S100 calcium-binding proteins P, A12 and A9; coagulation factor V; arginase I; carbonic anhydrase IV; lymphocyte antigen 96 (cluster of differentiation (CD)96); monocarboxylic acid transporter (6); ets-2 (erythroblastosis virus E26 oncogene homolog 2); homeobox gene Hox 1.11; cytoskeleton-associated protein 4; N-formylpeptide receptor; ribonuclease-2; N-acetylneuraminate pyruvate lyase; BCL6; glycogen phosphorylase. The fold change of these genes varied from 1.6 to 6.8 and these 18 genes correctly classified 10/15 patients at 2.4 h, 13/15 patients at 5h and 15/15 patients at 24 h after stroke. These data provide insights into the inflammatory responses after stroke in humans, and should be helpful in diagnosis, understanding etiology and pathogenesis, and guiding acute treatment and development of new treatments for stroke.
Modern methods that use systematic, quantitative and unbiased approaches are making it possible to discover proteins altered by a disease. To identify proteins that might be differentially expressed in autism, serum proteins from blood were subjected to trypsin digestion followed by liquid chromatography-electrospray ionization-mass spectrometry (LC-ESI-MS) on time-of-flight (TOF) instruments to identify differentially expressed peptides. Children with autism 4-6 years of age (n = 69) were compared to typically developing children (n = 35) with similar age and gender distributions. A total of 6348 peptide components were quantified. Of these, five peptide components corresponding to four known proteins had an effect size > 0.99 with a P < 0.05 and a Mascot identification score of 30 or greater for autism compared to controls. The four proteins were: Apolipoprotein (apo) B-100, Complement Factor H Related Protein (FHR1), Complement C1q and Fibronectin 1 (FN1). In addition, apo B-100 and apo A-IV were higher in children with high compared to low functioning autism. Apos are involved in the transport of lipids, cholesterol and vitamin E. The complement system is involved in the lysis and removal of infectious organisms in blood, and may be involved in cellular apoptosis in brain. Despite limitations of the study, including the low fold changes and variable detection rates for the peptide components, the data support possible differences of circulating proteins in autism, and should help stimulate the continued search for causes and treatments of autism by examining peripheral blood.
The objective of this study was to identify gene expression differences in blood differences in children with autism (AU) and autism spectrum disorder (ASD) compared to general population controls. Transcriptional profiles were compared with age- and gender-matched, typically developing children from the general population (GP). The AU group was subdivided based on a history of developmental regression (A-R) or a history of early onset (A-E without regression). Total RNA from blood was processed on human Affymetrix microarrays. Thirty-five children with AU (17 with early onset autism and 18 with autism with regression) and 14 ASD children (who did not meet criteria for AU) were compared to 12 GP children. Unpaired t tests (corrected for multiple comparisons with a false discovery rate of 0.05) detected a number of genes that were regulated more than 1.5-fold for AU versus GP (n=55 genes), for A-E versus GP (n=140 genes), for A-R versus GP (n=20 genes), and for A-R versus A-E (n=494 genes). No genes were significantly regulated for ASD versus GP. There were 11 genes shared between the comparisons of all autism subgroups to GP (AU, A-E, and A-R versus GP) and these genes were all expressed in natural killer cells and many belonged to the KEGG natural killer cytotoxicity pathway (p=0.02). A subset of these genes (n=7) was tested with qRT-PCR and all genes were found to be differentially expressed (p<0.05). We conclude that the gene expression data support emerging evidence for abnormalities in peripheral blood leukocytes in autism that could represent a genetic and/or environmental predisposition to the disorder.
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