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Results for “Genomic profiling”

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PubMed2003

Advancing drug discovery through systems biology.

Pharmaceutical companies are facing an urgent need to both increase their lead compound and clinical candidate portfolios and satisfy market demands for continued innovation and revenue growth. Here, we outline an emerging approach that attempts to facilitate and alleviate many of the current drug discovery issues and problems. This is, in part, achieved through the systematic integration of technologies, which results in a superior output of data and information, thereby enhancing our understanding of biological function, chemico-biological interactions and, ultimately, drug discovery. Systems biology is one new discipline that is positioned to significantly impact this process.

Animals↗
PubMed2005

Finding the target after screening the phenotype.

Although most screening for new drug leads is being directed at known or emerging molecular targets, there has been a renaissance in screening based on changes in cell or organismal phenotypes. Phenotype-based screening is accompanied by the challenge of identifying the molecular target or targets bound by the drug leads and responsible for their pharmacological activity. A variety of technologies and approaches are being explored for target identification after phenotypic screening. Direct approaches employing affinity chromatography, expression cloning and protein microarrays analyze the compound bound to its target. Indirect approaches are based on comparison of the genome-wide activity profile of the compound with databases of the activity profiles of other compounds with known targets or activity profiles following specific genetic changes. This review will use case studies of target identification efforts and highlight the advantages and disadvantages of the various approaches to target identification after phenotypic screening.

Animals↗
PubMedDate not supplied

A dynamic approach to mapping coordinates between microplates and microarrays.

The retrieval of useful data from spotted microarray slides requires keeping track of which microplate wells and DNA sample corresponds to each spot on each array slide. Existing approaches are closely coupled with the type of arrayer in use and are computer operating-system-specific. To support the microarray researcher community at large who use different arrayers and computer platforms, increased flexibility, generality, and portability of these approaches are required. In this paper, we describe a general algorithm that correlates the well positions of DNA samples in each microplate to the positions of the spots on each array slide. Based on this algorithm, we have implemented a flexible and platform-independent program named MicroArray Convolutor (MAC) that provides a Web solution allowing the user to: (a) import a text file that identifies the DNA samples and their well locations, (b) select a transformation method that converts data in 96-well plate format into 384-well plate format, and (c) specify the output format of the array lists dependant on the configuration of the array platform as well as the downstream analysis software chosen for the array. MAC and its source code can be accessed via the following Web address: http://ymd.med.yale.edu/kei-cgi/kc_mac_dev8.pl.

Algorithms↗
PubMed2003

Prader-Willi syndrome transcripts are expressed in phenotypically significant regions of the developing mouse brain.

Prader-Willi syndrome (PWS) is a neurobehavioral disorder that is due to the loss of multiple, paternally-expressed, imprinted genes on human chromosome 15q11-q13. The candidate genes are conserved in mice and are located in an orthologous region on mouse 7C. Several mouse models in which one or more of the PWS candidate genes are silenced do not recapitulate the full PWS phenotype. We examined the expression patterns of the mouse orthologues of PWS candidate genes throughout the development of the brain regions most implicated in PWS, including the hypothalamus, pituitary, forebrain and hindbrain. Snrpn, Ipw and Ndn are widely expressed at high levels throughout the mouse brain, whereas Magel2, Mkrn3 and the snoRNA MBII-85 are preferentially expressed in specific brain regions. Magel2 is most specifically expressed in developing hypothalamus, the region of the brain implicated in PWS hyperphagia and obesity. Although Snrpn, Ipw and MBII-85 are putatively transcribed from the same promoter, the transcripts are differentially detected in neural tissues. The analysis of expression patterns of murine orthologues of human disease genes is valuable for identifying sites of gene expression that correlate with disease phenotype.

Animals↗
PubMed2005

MicroRNA: biological and computational perspective.

MicroRNAs (miRNAs) are endogenously expressed non-coding RNAs of 20-24 nucleotides, which post-transcriptionally regulate gene expression in plants and animals. Recently it has been recognized that miRNAs comprise one of the abundant gene families in multicellular species, and their regulatory functions in various biological processes are widely spread. There has been a surge in the research activities in this field in the past few years. From the very beginning, computational methods have been utilized as indispensable tools, and many discoveries have been obtained through combination of experimental and computational approaches. In this review, both biological and computational aspects of miRNA will be discussed. A brief history of the discovery of miRNA and discussion of microarray applications in miRNA research are also included.

Animals↗
PubMed2026

Unlocking the Circulating Proteome: Toward Clinical Translation.

Blood-based proteomics is approaching a translational inflection point. Driven by advances in measurement technologies, rapid expansion of analytical capabilities, and growing adoption across research and medical communities, there is increasing demand for clinically actionable biomarkers. As the field transitions away from purely large-scale discovery-oriented studies toward more informed, targeted, application-driven analyses, the generation of proteomic data is no longer the bottleneck. Instead, the central challenge is to translate these measurements into robust, reproducible, and clinically meaningful insights. In this Review, we assess recent technological and methodological developments, evaluate persistent preanalytical and interpretative limitations, and outline the key steps required for clinical translation. We focus on three deeply interconnected dimensions: the capabilities and constraints of current measurement platforms, the role of computational and machine learning approaches in extracting biological and clinical signals, and the emergence of large-scale population studies that create new opportunities for validation and generalization. Finally, we discuss a forward-looking vision in which proteomics plays a central role in dynamic, multilayered omics frameworks, where integration with genomics, temporal profiling, and imaging can deepen our understanding of health, disease, and therapeutic response.

Humans↗
PubMed2003

Correlation of the structures of agricultural fungicides to gene expression in Saccharomyces cerevisiae upon exposure to toxic doses.

Correlations between the chemical structures of agricultural fungicides and mRNA expression levels following exposure of Saccharomyces cerevisiae to toxic doses of thiuram, zineb, maneb, TPN, and PCP were examined. Structurally, thiuram, zineb, and maneb are dithiocarbamate fungicides, whereas TPN and PCP are not. To characterize chemical toxicity, genes expression was classified according to the functional groups used by the MIPS database. However, no correlations between the classification scheme and chemical structures were found. Hierarchical clustering of gene expression profiles was performed to characterize the effects of the five chemicals. According to this analysis the similarity of gene expression profiles depended on the similarity of chemical structures. These results suggest that DNA microarray technology has potential for predicting the major chemicals which will cause environmental toxicity and will provide information on new biomonitoring methods.

Environmental Pollutants↗
PubMed2006

Toxicogenomic response of Staphylococcus aureus to peracetic acid.

Staphylococcus aureus is responsible for many incidents of hospital-acquired infection, which causes 90,000 deaths and dollars 4.5 billion loss a year in the United States. Despite a wide use of disinfectants such as peracetic acid in health care environments, we certainly need better understanding of the effects of antimicrobial application on target pathogens to avert infection outbreaks. Consequently, herein, we explored for the first time the toxicogenomic response of S. aureus to a sublethal concentration of peracetic acid (1 mM) by using microarray-based transcriptome analysis. In particular, we investigated the dynamics of global gene expression profiles during its cellular response, which involved initial growth inhibition (10 min) and subsequent partial recovery (20 min). Further, we compared transcriptome responses to peracetic acid between S. aureus and Pseudomonas aeruginosa. Our findings show that (i) the regulation of membrane transport genes was significantly altered, (ii) DNA repair and replication genes were selectively induced, and (iii) primary metabolism-related genes were differently repressed between the two growth states. Most intriguingly, we revealed that many virulence factor genes were induced upon the exposure, which proposes a possibilitythatthe pathogenesis of S. aureus may be stimulated in response to peracetic acid.

Anti-Infective Agents↗
PubMed2003

Discovery of an inhibitor of a transcription factor using small molecule microarrays and diversity-oriented synthesis.

Small molecule microarrays were screened to identify a small molecule ligand for Hap3p, a subunit of the yeast Hap2/3/4/5p transcription factor complex. The compound, named haptamide A, was determined to have a KD of 5.03 muM for binding to Hap3p using surface plasmon resonance analysis. Haptamide A also inhibited activation of a GDH1-lacZ reporter gene in a dose-dependent fashion. To explore structure-activity relationships, 11 derivatives of haptamide A were prepared using the same synthetic route that was developed for the original library synthesis. Analysis of dissociation constants and IC50 values for the reporter gene assay revealed a more potent inhibitor, haptamide B, with a KD of 330 nM. Whole-genome transcriptional profiling was used to compare effects of haptamide B with a hap3Delta yeast strain. Treatment with haptamide B, like the deletion mutant, reduced lactate-induced transcription of several genes from wild-type levels. Profiling the genetic "knockout" and the chemical genetic "knockdown" led to the identification of several genes that are regulated by Hap3p under nonfermentative conditions. These results demonstrate that a small molecule discovered using the small molecule microarray binding assay can permeate yeast cells and reach its target transcription factor protein in cells.

Amides↗
PubMedDate not supplied

Gene expression profiling after irradiation: clues to understanding acute and persistent responses?

Ionizing radiation (IR) is an ever-present hazard to humans primarily due to its mutagenic, carcinogenic, and cell killing ability. In addition to causing DNA damage, irradiation initiates a plethora of signal transduction cascades responsible for maintaining cellular homeostasis and promoting interactions with neighboring cells. Large-scale changes in gene expression have also been found after irradiation, and microarrays have helped discern these subsequent transcriptional alterations. While some studies have focused on low dose-rate experiments, others have analyzed the gene expression response of IR compared to other DNA damaging agents. Very few genes have been found to be consistently up-regulated by IR, but that set includes GADD45, CDKN1A, and genes associated with the nucleotide excision repair pathway. Overall, the immediate transcriptional responses to IR have implications for DNA repair, cell cycle arrest, growth control, and cell signaling. Additionally, there is a substantial p53-independent component to the transcriptional profile that could be exploited to increase the effectiveness of radiotherapy. Initial characterizations of the persistent responses to IR yielded a completely different profile than observed immediately after exposure. This profile is ephemeral, shifting even over the course of one set of experiments. Microarray analysis of radiation responses has also been applied to clinical response to radiotherapy, identifying genes linked to radio-sensitivity and resistance in B-cell chronic lymphoid leukemia and cervical cancer. Overall, these large-scale gene expression studies have added to the understanding of the complicated biological responses to IR, and when combined with other data sets will yield a complete picture of the short and long-term consequences of radiation.

Animals↗
PubMed2002

Dissecting glucose signalling with diversity-oriented synthesis and small-molecule microarrays.

Small molecules that alter protein function provide a means to modulate biological networks with temporal resolution. Here we demonstrate a potentially general and scalable method of identifying such molecules by application to a particular protein, Ure2p, which represses the transcription factors Gln3p and Nil1p. By probing a high-density microarray of small molecules generated by diversity-oriented synthesis with fluorescently labelled Ure2p, we performed 3,780 protein-binding assays in parallel and identified several compounds that bind Ure2p. One compound, which we call uretupamine, specifically activates a glucose-sensitive transcriptional pathway downstream of Ure2p. Whole-genome transcription profiling and chemical epistasis demonstrate the remarkable Ure2p specificity of uretupamine and its ability to modulate the glucose-sensitive subset of genes downstream of Ure2p. These results demonstrate that diversity-oriented synthesis and small-molecule microarrays can be used to identify small molecules that bind to a protein of interest, and that these small molecules can regulate specific functions of the protein.

Dioxanes↗