Transcriptomic Dose-Response Analysis for Mode of Action and Risk Assessment

EPA Science Inventory

Microarray and RNA-seq technologies can play an important role in assessing the health risks associated with environmental exposures. The utility of gene expression data to predict hazard has been well documented. Early toxicogenomics studies used relatively high, single doses w...

Bisphenol A exposure leads to specific microRNA alterations in placental cells.

PubMed

Avissar-Whiting, Michele; Veiga, Keila R; Uhl, Kristen M; Maccani, Matthew A; Gagne, Luc A; Moen, Erika L; Marsit, Carmen J

2010-07-01

Exposure to bisphenol A (BPA) has been observed to alter developmental pathways and cell processes, at least in part, through epigenetic mechanisms. This study sought to investigate the effect of BPA on microRNAs (miRNAs) in human placental cells. miRNA microarray was performed following BPA treatment in three immortalized cytotrophoblast cell lines and the results validated using quantitative real-time PCR. For functional analysis, overexpression constructs were stably transfected into cells that were then assayed for changes in proliferation and response to toxicants. Microarray analysis revealed several miRNAs to be significantly altered in response to BPA treatment in two cell lines. Real-time PCR results confirmed that miR-146a was particularly strongly induced and its overexpression in cells led to slower proliferation as well as higher sensitivity to the DNA damaging agent, bleomycin. Overall, these results suggest that BPA can alter miRNA expression in placental cells, a potentially novel mode of BPA toxicity.

Bisphenol A Exposure Leads to Specific MicroRNA Alterations in Placental Cells

PubMed Central

Avissar-Whiting, Michele; Veiga, Keila; Uhl, Kristen; Maccani, Matthew; Gagne, Luc; Moen, Erika; Marsit, Carmen J.

2010-01-01

Exposure to bisphenol-A (BPA) has been observed to alter developmental pathways and cell processes, at least in part, through epigenetic mechanisms. This study sought to investigate the effect of BPA on microRNAs (miRNAs) in human placental cells. miRNA microarray was performed following BPA treatment in three immortalized cytotrophoblast cell lines and the results validated using quantitative real-time PCR. For functional analysis, overexpression constructs were stably transfected into cells that were then assayed for changes in proliferation and response to toxicants. Microarray analysis revealed several miRNAs to be significantly altered in response to BPA treatment in two cell lines. Real-time PCR results confirmed that miR-146a was particularly strongly induced and its overexpression in cells led to slower proliferation as well as higher sensitivity to the DNA damaging agent, bleomycin. Overall, these results suggest that BPA can alter miRNA expression in placental cells, a potentially novel mode of BPA toxicity. PMID:20417706

Exposure to the lampricide 3-trifluoromethyl-4-nitrophenol results in increased expression of carbohydrate transporters in S. cerevisiae

PubMed Central

Hinkle, Karen L.; Anderson, Chad C.; Forkey, Blake; Griffin, Jacob; Cone, Kelsey; Vitzthum, Carl; Olsen, Darlene

2016-01-01

The lampricide 3-trifluoromethyl-4-nitrophenol (TFM) is used to control sea lamprey (Petromyzon marinus) populations in freshwater lakes. While TFM can have sublethal and lethal effects, little is known about gene expression changes with TFM exposure. Microarray analysis was used to determine differential gene expression over 4 hours of exposure in S. cerevisiae. Among the most significantly up regulated genes were regulators of carbohydrate transport including HXT1, HXT3, HXT4, IMA5, MIG2, and YKR075C. PMID:26606276

Methods for transcriptomic analyses of the porcine host immune response: application to Salmonella infection using microarrays

USDA-ARS?s Scientific Manuscript database

Technological developments in both the collection and analysis of molecular genetic data over the past few years have provided new opportunities for an improved understanding of the global response to pathogen exposure. Such developments are particularly dramatic for scientists studying the pig, whe...

APPLICATION OF LASER CAPTURE MICRODISSECTION AND PROTEIN MICROARRAY TECHNOLOGIES IN THE MOLECULAR ANALYSIS OF AIRWAY INJURY FOLLOWING POLLUTION PARTICLE EXPOSURE

EPA Science Inventory

Understanding the mechanisms by which various types of air pollution particles (PM) mediate adverse health effects would provide biological plausibility to epidemiological associations of increased rates of morbidity and mortality. The majority of information regarding the means ...

The genomic transcriptional response of female fathead minnows (Pimephales promelas) to an acute exposure to the androgen, 17β-trenbolone

USGS Publications Warehouse

Dorts, Jennifer; Richter, Catherine A.; Wright-Osment, Maureen K.; Ellersieck, Mark R.; Carter, Barbara J.; Tillitt, Donald E.

2009-01-01

We investigated the genomic transcriptional response of female fathead minnows (Pimephales promelas) to an acute (4 days) exposure to 0.1 or 1.0 ??g/L of 17??-trenbolone (TB), the active metabolite of an anabolic androgenic steroid used as a growth promoter in cattle and a contaminant of concern in aquatic systems. Our objectives were to investigate the gene expression profile induced by TB, define biomarkers of exposure to TB, and increase our understanding of the mechanisms of adverse effects of TB on fish reproduction. In female gonad tissue, microarray analysis using a 22 K oligonucleotide microarray (EcoArray Inc., Gainesville, FL) showed 99 significantly upregulated genes and 741 significantly downregulated genes in response to 1 ??g TB/L. In particular, hydroxysteroid (17??) dehydrogenase 12a (hsd17b12a), zona pellucida glycoprotein 2.2 (zp2.2), and protein inhibitor of activated STAT, 2 (pias2) were all downregulated in gonad. Q-PCR measurements in a larger sample set were consistent with the microarray results in the direction and magnitude of these changes in gene expression. However, several novel potential biomarkers were verified by Q-PCR in the same samples, but could not be validated in independent samples. In liver, Q-PCR measurements showed a significant decrease in vitellogenin 1 (vtg1) mRNA expression. In brain, cytochrome P450, family 19, subfamily A, polypeptide 1b (cyp19a1b, previously known as aromatase B) transcript levels were significantly reduced following TB exposure. Our study provides a candidate gene involved in mediating the action of TB, hsd17b12a, and two potential biomarkers sensitive to acute TB exposure, hepatic vtg1 and brain cyp19a1b.

Microarray-based analysis of the lung recovery process after stainless-steel welding fume exposure in Sprague-Dawley rats.

PubMed

Oh, Jung-Hwa; Yang, Mi-jin; Yang, Young-Su; Park, Han-Jin; Heo, Sun Hee; Lee, Eun-Hee; Song, Chang-Woo; Yoon, Seokjoo

2009-02-01

Repeated exposure to welding fumes promotes a reversible increase in pulmonary disease risk, but the molecular mechanisms by which welding fumes induce lung injury and how the lung recovers from such insults are unclear. In the present study, pulmonary function and gene-expression profiles in the lung were analyzed by Affymetrix GeneChip microarray after 30 days of consecutive exposure to manual metal arc welding combined with stainless-steel (MMA-SS) welding fumes, and again after 30 days of recovery from MMA-SS fume exposure. In total, 577 genes were identified as being either up-regulated or down-regulated (over twofold changes, p < 0.05) in the lungs of low-dose or high-dose groups. Differentially expressed genes were classified based on a k-means clustering algorithm and biological functions and molecular networks were further analyzed using Ingenuity Pathways Analysis. Among the genes affected by exposure to or recovery from MMA-SS fumes, the transcriptional changes of 13 genes that were highly altered by treatment were confirmed by quantitative real-time PCR. Notably, Mmp12, Cd5l, Ccl7, Cxcl5, and Spp1 related to the immune response were up-regulated only in the exposure group, whereas Trem2, IgG-2a, Igh-1a, and Igh were persistently up-regulated in both the exposure and recovery groups. In addition, several genes that might play a role in the repair process of the lung were up-regulated exclusively in the recovery group. Collectively, these data may help elucidate the molecular mechanism of the recovery process of the lung after welding fume exposure.

Alteration of synaptic activity-regulating genes underlying functional improvement by long-term exposure to an enriched environment in the adult brain.

PubMed

Lee, Min-Young; Yu, Ji Hea; Kim, Ji Yeon; Seo, Jung Hwa; Park, Eun Sook; Kim, Chul Hoon; Kim, Hyongbum; Cho, Sung-Rae

2013-01-01

Housing animals in an enriched environment (EE) enhances behavioral function. However, the mechanism underlying this EE-mediated functional improvement and the resultant changes in gene expression have yet to be elucidated. We attempted to investigate the underlying mechanisms associated with long-term exposure to an EE by evaluating gene expression patterns. We housed 6-week-old CD-1 (ICR) mice in standard cages or an EE comprising a running wheel, novel objects, and social interaction for 2 months. Motor and cognitive performances were evaluated using the rotarod test and passive avoidance test, and gene expression profile was investigated in the cerebral hemispheres using microarray and gene set enrichment analysis (GSEA). In behavioral assessment, an EE significantly enhanced rotarod performance and short-term working memory. Microarray analysis revealed that genes associated with neuronal activity were significantly altered by an EE. GSEA showed that genes involved in synaptic transmission and postsynaptic signal transduction were globally upregulated, whereas those associated with reuptake by presynaptic neurotransmitter transporters were downregulated. In particular, both microarray and GSEA demonstrated that EE exposure increased opioid signaling, acetylcholine release cycle, and postsynaptic neurotransmitter receptors but decreased Na+ / Cl- -dependent neurotransmitter transporters, including dopamine transporter Slc6a3 in the brain. Western blotting confirmed that SLC6A3, DARPP32 (PPP1R1B), and P2RY12 were largely altered in a region-specific manner. An EE enhanced motor and cognitive function through the alteration of synaptic activity-regulating genes, improving the efficient use of neurotransmitters and synaptic plasticity by the upregulation of genes associated with postsynaptic receptor activity and downregulation of presynaptic reuptake by neurotransmitter transporters.

Correlation of gene expression and contaminat concentrations in wild largescale suckers: a field-based study

USGS Publications Warehouse

Christiansen, Helena E.; Mehinto, Alvine C.; Yu, Fahong; Perry, Russell W.; Denslow, Nancy D.; Maule, Alec G.; Mesa, Matthew G.

2014-01-01

Toxic compounds such as organochlorine pesticides (OCs), polychlorinated biphenyls (PCBs), and polybrominated diphenyl ether flame retardants (PBDEs) have been detected in fish, birds, and aquatic mammals that live in the Columbia River or use food resources from within the river. We developed a custom microarray for largescale suckers (Catostomus macrocheilus) and used it to investigate the molecular effects of contaminant exposure on wild fish in the Columbia River. Using Significance Analysis of Microarrays (SAM) we identified 72 probes representing 69 unique genes with expression patterns that correlated with hepatic tissue levels of OCs, PCBs, or PBDEs. These genes were involved in many biological processes previously shown to respond to contaminant exposure, including drug and lipid metabolism, apoptosis, cellular transport, oxidative stress, and cellular chaperone function. The relation between gene expression and contaminant concentration suggests that these genes may respond to environmental contaminant exposure and are promising candidates for further field and laboratory studies to develop biomarkers for monitoring exposure of wild fish to contaminant mixtures found in the Columbia River Basin. The array developed in this study could also be a useful tool for studies involving endangered sucker species and other sucker species used in contaminant research.

The effect of low-intensity pulsed ultrasound on wound healing using scratch assay in epithelial cells.

PubMed

Iwanabe, Yujiro; Masaki, Chihiro; Tamura, Akiko; Tsuka, Shintaro; Mukaibo, Taro; Kondo, Yusuke; Hosokawa, Ryuji

2016-10-01

Low-intensity pulsed ultrasound (LIPUS) is widely used in medical fields because it shortens the time required for biologic wound healing in fracture treatment. Also, in dental fields, LIPUS should be effectively employed for implant treatment. However, most of the relevant reports have been published on its effects on bone formation around implants, and the effects of LIPUS on soft tissue healing remain unclear. In the present study, we examined the effects of LIPUS on soft tissue healing using gingival epithelial cells. Gingival epithelial cells were cultured on a dish, followed by LIPUS exposure at a frequency of 3MHz for 15min. The cells were counted with a hemocytometer, and a scratch assay was conducted by measuring the closing area of the scratch wound using a microscope. Following LIPUS exposure, total RNA was collected for microarray analysis. In addition, real-time PCR was performed to examine the mRNA expression level of integrin α6β4. Furthermore, total protein was collected to examine the protein expression level of integrin α6β4 by western blotting. The cell count and scratch assay demonstrated that LIPUS exposure promoted cell proliferation and scratch-wound closure. Microarray analysis demonstrated the increased expression levels of adhesion-related genes, including integrin. Real-time PCR analysis demonstrated that LIPUS exposure significantly up-regulated the mRNA expression level of integrin α6β4. Western blotting showed intense staining of integrin α6β4. LIPUS exposure promotes wound closure in the scratch assay and up-regulates the expression level of integrin α6β4 as compared with the control. Copyright © 2016 Japan Prosthodontic Society. Published by Elsevier Ltd. All rights reserved.

Blood miRNAs as sensitive and specific biological indicators of environmental and occupational exposure to volatile organic compound (VOC).

PubMed

Song, Mi-Kyung; Ryu, Jae-Chun

2015-10-01

To date, there is still shortage of highly sensitive and specific minimally invasive biomarkers for assessment of environmental toxicants exposure. Because of the significance of microRNA (miRNA) in various diseases, circulating miRNAs in blood may be unique biomarkers for minimally invasive prediction of toxicants exposure. We identified and validated characteristic miRNA expression profiles of human whole blood in workers exposed to volatile organic compounds (VOCs) and compared the usefulness of miRNA indicator of VOCs with the effectiveness of the already used urinary biomarkers of occupational exposure. Using a microarray based approach we screened and detected deregulated miRNAs in their expression in workers exposed to VOCs (toluene [TOL], xylene [XYL] and ethylbenzene [EBZ]). Total 169 workers from four dockyards were enrolled in current study, and 50 subjects of them were used for miRNA microarray analysis. We identified 467 miRNAs for TOL, 211 miRNAs for XYL, and 695 miRNAs for XYL as characteristic discernible exposure indicator, which could discerned each VOC from the control group with higher accuracy, sensitivity, and specificity than urinary biomarkers. Current observations from this study point out that the altered levels of circulating miRNAs can be a reliable novel, minimally invasive biological indicator of occupational exposure to VOCs. Copyright © 2015 Elsevier GmbH. All rights reserved.

Gene expression profiling to identify the toxicities and potentially relevant human disease outcomes associated with environmental heavy metal exposure.

PubMed

Korashy, Hesham M; Attafi, Ibraheem M; Famulski, Konrad S; Bakheet, Saleh A; Hafez, Mohammed M; Alsaad, Abdulaziz M S; Al-Ghadeer, Abdul Rahman M

2017-02-01

Heavy metals are the most commonly encountered toxic substances that increase susceptibility to various diseases after prolonged exposure. We have previously shown that healthy volunteers living near a mining area had significant contamination with heavy metals associated with significant changes in the expression of some detoxifying genes, xenobiotic metabolizing enzymes, and DNA repair genes. However, alterations of most of the molecular target genes associated with diseases are still unknown. Thus, the aims of this study were to (a) evaluate the gene expression profile and (b) identify the toxicities and potentially relevant human disease outcomes associated with long-term human exposure to environmental heavy metals in mining area using microarray analysis. For this purpose, 40 healthy male volunteers who were residents of a heavy metal-polluted area (Mahd Al-Dhahab city, Saudi Arabia) and 20 healthy male volunteers who were residents of a non-heavy metal-polluted area were included in the study. Total RNA was isolated from whole blood using PAXgene Blood RNA tubes and then reversed transcribed and hybridized to the gene array using the Affymetrix U219 GeneChip. Microarray analysis showed about 2129 genes were identified and differentially altered, among which a shared set of 425 genes was differentially expressed in the heavy metal-exposed groups. Ingenuity pathway analysis revealed that the most altered gene-regulated diseases in heavy metal-exposed groups included hematological and developmental disorders and mostly renal and urological diseases. Quantitative real-time polymerase chain reaction closely matched the microarray data for some genes tested. Importantly, changes in gene-related diseases were attributed to alterations in the genes encoded for protein synthesis. Renal and urological diseases were the diseases that were most frequently associated with the heavy metal-exposed group. Therefore, there is a need for further studies to validate these genes, which could be used as early biomarkers to prevent renal injury. Copyright © 2016 Elsevier Ltd. All rights reserved.

Gene expression profiles in rainbow trout, Onchorynchus mykiss, exposed to a simple chemical mixture.

PubMed

Hook, Sharon E; Skillman, Ann D; Gopalan, Banu; Small, Jack A; Schultz, Irvin R

2008-03-01

Among proposed uses for microarrays in environmental toxiciology is the identification of key contributors to toxicity within a mixture. However, it remains uncertain whether the transcriptomic profiles resulting from exposure to a mixture have patterns of altered gene expression that contain identifiable contributions from each toxicant component. We exposed isogenic rainbow trout Onchorynchus mykiss, to sublethal levels of ethynylestradiol, 2,2,4,4-tetrabromodiphenyl ether, and chromium VI or to a mixture of all three toxicants Fluorescently labeled complementary DNA (cDNA) were generated and hybridized against a commercially available Salmonid array spotted with 16,000 cDNAs. Data were analyzed using analysis of variance (p<0.05) with a Benjamani-Hochberg multiple test correction (Genespring [Agilent] software package) to identify up and downregulated genes. Gene clustering patterns that can be used as "expression signatures" were determined using hierarchical cluster analysis. The gene ontology terms associated with significantly altered genes were also used to identify functional groups that were associated with toxicant exposure. Cross-ontological analytics approach was used to assign functional annotations to genes with "unknown" function. Our analysis indicates that transcriptomic profiles resulting from the mixture exposure resemble those of the individual contaminant exposures, but are not a simple additive list. However, patterns of altered genes representative of each component of the mixture are clearly discernible, and the functional classes of genes altered represent the individual components of the mixture. These findings indicate that the use of microarrays to identify transcriptomic profiles may aid in the identification of key stressors within a chemical mixture, ultimately improving environmental assessment.

Microarray-based bioinformatics analysis of the combined effects of SiNPs and PbAc on cardiovascular system in zebrafish.

PubMed

Hu, Hejing; Zhang, Yannan; Shi, Yanfeng; Feng, Lin; Duan, Junchao; Sun, Zhiwei

2017-10-01

With rapid development of nanotechnology and growing environmental pollution, the combined toxic effects of SiNPs and pollutants of heavy metals like lead have received global attentions. The aim of this study was to explore the cardiovascular effects of the co-exposure of SiNPs and lead acetate (PbAc) in zebrafish using microarray and bioinformatics analysis. Although there was no other obvious cardiovascular malformation except bleeding phenotype, bradycardia, angiogenesis inhibition and declined cardiac output in zebrafish co-exposed of SiNPs and PbAc at NOAEL level, significant changes were observed in mRNA and microRNA (miRNA) expression patterns. STC-GO analysis indicated that the co-exposure might have more toxic effects on cardiovascular system than that exposure alone. Key differentially expressed genes were discerned out based on the Dynamic-gene-network, including stxbp1a, ndfip2, celf4 and gsk3b. Furthermore, several miRNAs obtained from the miRNA-Gene-Network might play crucial roles in cardiovascular disease, such as dre-miR-93, dre-miR-34a, dre-miR-181c, dre-miR-7145, dre-miR-730, dre-miR-129-5p, dre-miR-19d, dre-miR-218b, dre-miR-221. Besides, the analysis of miRNA-pathway-network indicated that the zebrafish were stimulated by the co-exposure of SiNPs and PbAc, which might cause the disturbance of calcium homeostasis and endoplasmic reticulum stress. As a result, cardiac muscle contraction might be deteriorated. In general, our data provide abundant fundamental research clues to the combined toxicity of environmental pollutants and further in-depth verifications are needed. Copyright © 2017 Elsevier Ltd. All rights reserved.

Brain region-specific gene expression changes after chronic intermittent ethanol exposure and early withdrawal in C57BL/6J mice

PubMed Central

Melendez, Roberto I.; McGinty, Jacqueline F.; Kalivas, Peter W.; Becker, Howard C.

2014-01-01

Neuroadaptations that participate in the ontogeny of alcohol dependence are likely a result of altered gene expression in various brain regions. The present study investigated brain region-specific changes in the pattern and magnitude of gene expression immediately following chronic intermittent ethanol (CIE) exposure and 8 hours following final ethanol exposure [i.e. early withdrawal (EWD)]. High-density oligonucleotide microarrays (Affymetrix 430A 2.0, Affymetrix, Santa Clara, CA, USA) and bioinformatics analysis were used to characterize gene expression and function in the prefrontal cortex (PFC), hippocampus (HPC) and nucleus accumbens (NAc) of C57BL/6J mice (Jackson Laboratories, Bar Harbor, ME, USA). Gene expression levels were determined using gene chip robust multi-array average followed by statistical analysis of microarrays and validated by quantitative real-time reverse transcription polymerase chain reaction and Western blot analysis. Results indicated that immediately following CIE exposure, changes in gene expression were strikingly greater in the PFC (284 genes) compared with the HPC (16 genes) and NAc (32 genes). Bioinformatics analysis revealed that most of the transcriptionally responsive genes in the PFC were involved in Ras/MAPK signaling, notch signaling or ubiquitination. In contrast, during EWD, changes in gene expression were greatest in the HPC (139 genes) compared with the PFC (four genes) and NAc (eight genes). The most transcriptionally responsive genes in the HPC were involved in mRNA processing or actin dynamics. Of the few genes detected in the NAc, the most representatives were involved in circadian rhythms. Overall, these findings indicate that brain region-specific and time-dependent neuroadaptive alterations in gene expression play an integral role in the development of alcohol dependence and withdrawal. PMID:21812870

DNA microarrays and their use in dermatology.

PubMed

Mlakar, Vid; Glavac, Damjan

2007-03-01

Multiple different DNA microarray technologies are available on the market today. They can be used for studying either DNA or RNA with the purpose of identifying and explaining the role of genes involved in different processes. This paper reviews different DNA microarray platforms available for such studies and their usage in cases of malignant melanomas, psoriasis, and exposure of keratinocytes and melanocytes to UV illumination.

Phytoremediation potential of Arabidopsis with reference to acrylamide and microarray analysis of acrylamide-response genes.

PubMed

Gao, Jian-Jie; Peng, Ri-He; Zhu, Bo; Wang, Bo; Wang, Li-Juan; Xu, Jing; Sun, Miao; Yao, Quan-Hong

2015-10-01

Acrylamide (ACR) is a widely used industrial chemical. However, it is a dangerous compound because it showed neurotoxic effects in humans and act as reproductive toxicant and carcinogen in many animal species. In the environment, acrylamide has high soil mobility and may travel via groundwater. Phytoremediation is an effective method to remove the environmental pollutants, but the mechanism of plant response to acrylamide remains unknown. With the purpose of assessing remediation potentials of plants for acrylamide, we have examined acrylamide uptake by the model plant Arabidopsis grown on contaminated substrates with high performance liquid chromatography (HPLC) analysis. The result revealed that acrylamide could be absorbed and degraded by Arabidopsis. Further microarray analysis showed that 527 transcripts were up-regulated within 2-days under acrylamide exposure condition. We have found many potential acrylamide-induced genes playing a major role in plant metabolism and phytoremediation. Copyright © 2015 Elsevier Inc. All rights reserved.

Microarray Я US: a user-friendly graphical interface to Bioconductor tools that enables accurate microarray data analysis and expedites comprehensive functional analysis of microarray results.

PubMed

Dai, Yilin; Guo, Ling; Li, Meng; Chen, Yi-Bu

2012-06-08

Microarray data analysis presents a significant challenge to researchers who are unable to use the powerful Bioconductor and its numerous tools due to their lack of knowledge of R language. Among the few existing software programs that offer a graphic user interface to Bioconductor packages, none have implemented a comprehensive strategy to address the accuracy and reliability issue of microarray data analysis due to the well known probe design problems associated with many widely used microarray chips. There is also a lack of tools that would expedite the functional analysis of microarray results. We present Microarray Я US, an R-based graphical user interface that implements over a dozen popular Bioconductor packages to offer researchers a streamlined workflow for routine differential microarray expression data analysis without the need to learn R language. In order to enable a more accurate analysis and interpretation of microarray data, we incorporated the latest custom probe re-definition and re-annotation for Affymetrix and Illumina chips. A versatile microarray results output utility tool was also implemented for easy and fast generation of input files for over 20 of the most widely used functional analysis software programs. Coupled with a well-designed user interface, Microarray Я US leverages cutting edge Bioconductor packages for researchers with no knowledge in R language. It also enables a more reliable and accurate microarray data analysis and expedites downstream functional analysis of microarray results.

Persistently Elevated Somatic Mutation as a Biomarker for Clinically Relevant Exposures in GWI

DTIC Science & Technology

2017-10-01

radiation and/or chemicals. However, since some, but not...microarray data in breast cancer and acute myelogenous leukemia, for this analysis. Figure 1. Expression of NER genes in 10 GWI patients (red...undergoing genotoxic radio- and/or chemotherapy and victims of radiation accidents and A-bomb survivors. Perhaps because the published

Mobile-phone radiation-induced perturbation of gene-expression profiling, redox equilibrium and sporadic-apoptosis control in the ovary of Drosophila melanogaster

PubMed Central

Manta, Areti K.; Papadopoulou, Deppie; Polyzos, Alexander P.; Fragopoulou, Adamantia F.; Skouroliakou, Aikaterini S.; Thanos, Dimitris; Stravopodis, Dimitrios J.; Margaritis, Lukas H.

2017-01-01

ABSTRACT The daily use by people of wireless communication devices has increased exponentially in the last decade, begetting concerns regarding its potential health hazards. Drosophila melanogaster four days-old adult female flies were exposed for 30 min to radiation emitted by a commercial mobile phone at a SAR of 0.15 W/kg and a SAE of 270 J/kg. ROS levels and apoptotic follicles were assayed in parallel with a genome-wide microarrays analysis. ROS cellular contents were found to increase by 1.6-fold (x), immediately after the end of exposure, in follicles of pre-choriogenic stages (germarium - stage 10), while sporadically generated apoptotic follicles (germarium 2b and stages 7–9) presented with an averaged 2x upregulation in their sub-population mass, 4 h after fly's irradiation with mobile device. Microarray analysis revealed 168 genes being differentially expressed, 2 h post-exposure, in response to radiofrequency (RF) electromagnetic field-radiation exposure (≥1.25x, P < 0.05) and associated with multiple and critical biological processes, such as basic metabolism and cellular subroutines related to stress response and apoptotic death. Exposure of adult flies to mobile-phone radiation for 30 min has an immediate impact on ROS production in animal's ovary, which seems to cause a global, systemic and non-targeted transcriptional reprogramming of gene expression, 2 h post-exposure, being finally followed by induction of apoptosis 4 h after the end of exposure. Conclusively, this unique type of pulsed radiation, mainly being derived from daily used mobile phones, seems capable of mobilizing critical cytopathic mechanisms, and altering fundamental genetic programs and networks in D. melanogaster. PMID:27960592

Mobile-phone radiation-induced perturbation of gene-expression profiling, redox equilibrium and sporadic-apoptosis control in the ovary of Drosophila melanogaster.

PubMed

Manta, Areti K; Papadopoulou, Deppie; Polyzos, Alexander P; Fragopoulou, Adamantia F; Skouroliakou, Aikaterini S; Thanos, Dimitris; Stravopodis, Dimitrios J; Margaritis, Lukas H

2017-04-03

The daily use by people of wireless communication devices has increased exponentially in the last decade, begetting concerns regarding its potential health hazards. Drosophila melanogaster four days-old adult female flies were exposed for 30 min to radiation emitted by a commercial mobile phone at a SAR of 0.15 W/kg and a SAE of 270 J/kg. ROS levels and apoptotic follicles were assayed in parallel with a genome-wide microarrays analysis. ROS cellular contents were found to increase by 1.6-fold (x), immediately after the end of exposure, in follicles of pre-choriogenic stages (germarium - stage 10), while sporadically generated apoptotic follicles (germarium 2b and stages 7-9) presented with an averaged 2x upregulation in their sub-population mass, 4 h after fly's irradiation with mobile device. Microarray analysis revealed 168 genes being differentially expressed, 2 h post-exposure, in response to radiofrequency (RF) electromagnetic field-radiation exposure (≥1.25x, P < 0.05) and associated with multiple and critical biological processes, such as basic metabolism and cellular subroutines related to stress response and apoptotic death. Exposure of adult flies to mobile-phone radiation for 30 min has an immediate impact on ROS production in animal's ovary, which seems to cause a global, systemic and non-targeted transcriptional reprogramming of gene expression, 2 h post-exposure, being finally followed by induction of apoptosis 4 h after the end of exposure. Conclusively, this unique type of pulsed radiation, mainly being derived from daily used mobile phones, seems capable of mobilizing critical cytopathic mechanisms, and altering fundamental genetic programs and networks in D. melanogaster.

Molecular Analysis of Endocrine Disruption in Hornyhead Turbot at Wastewater Outfalls in Southern California Using a Second Generation Multi-Species Microarray

PubMed Central

Baker, Michael E.; Vidal-Dorsch, Doris E.; Ribecco, Cataldo; Sprague, L. James; Angert, Mila; Lekmine, Narimene; Ludka, Colleen; Martella, Andrea; Ricciardelli, Eugenia; Bay, Steven M.; Gully, Joseph R.; Kelley, Kevin M.; Schlenk, Daniel; Carnevali, Oliana; Šášik, Roman; Hardiman, Gary

2013-01-01

Sentinel fish hornyhead turbot ( Pleuronichthys verticalis ) captured near wastewater outfalls are used for monitoring exposure to industrial and agricultural chemicals of ~ 20 million people living in coastal Southern California. Although analyses of hormones in blood and organ morphology and histology are useful for assessing contaminant exposure, there is a need for quantitative and sensitive molecular measurements, since contaminants of emerging concern are known to produce subtle effects. We developed a second generation multi-species microarray with expanded content and sensitivity to investigate endocrine disruption in turbot captured near wastewater outfalls in San Diego, Orange County and Los Angeles California. Analysis of expression of genes involved in hormone [e.g., estrogen, androgen, thyroid] responses and xenobiotic metabolism in turbot livers was correlated with a series of phenotypic end points. Molecular analyses of turbot livers uncovered altered expression of vitellogenin and zona pellucida protein, indicating exposure to one or more estrogenic chemicals, as well as, alterations in cytochrome P450 (CYP) 1A, CYP3A and glutathione S-transferase-α indicating induction of the detoxification response. Molecular responses indicative of exposure to endocrine disruptors were observed in field-caught hornyhead turbot captured in Southern California demonstrating the utility of molecular methods for monitoring environmental chemicals in wastewater outfalls. Moreover, this approach can be adapted to monitor other sites for contaminants of emerging concern in other fish species for which there are few available gene sequences. PMID:24086568

Potential Adverse Effects of Prolonged Sevoflurane Exposure on Developing Monkey Brain: From Abnormal Lipid Metabolism to Neuronal Damage.

PubMed

Liu, Fang; Rainosek, Shuo W; Frisch-Daiello, Jessica L; Patterson, Tucker A; Paule, Merle G; Slikker, William; Wang, Cheng; Han, Xianlin

2015-10-01

Sevoflurane is a volatile anesthetic that has been widely used in general anesthesia, yet its safety in pediatric use is a public concern. This study sought to evaluate whether prolonged exposure of infant monkeys to a clinically relevant concentration of sevoflurane is associated with any adverse effects on the developing brain. Infant monkeys were exposed to 2.5% sevoflurane for 9 h, and frontal cortical tissues were harvested for DNA microarray, lipidomics, Luminex protein, and histological assays. DNA microarray analysis showed that sevoflurane exposure resulted in a broad identification of differentially expressed genes (DEGs) in the monkey brain. In general, these genes were associated with nervous system development, function, and neural cell viability. Notably, a number of DEGs were closely related to lipid metabolism. Lipidomic analysis demonstrated that critical lipid components, (eg, phosphatidylethanolamine, phosphatidylserine, and phosphatidylglycerol) were significantly downregulated by prolonged exposure of sevoflurane. Luminex protein analysis indicated abnormal levels of cytokines in sevoflurane-exposed brains. Consistently, Fluoro-Jade C staining revealed more degenerating neurons after sevoflurane exposure. These data demonstrate that a clinically relevant concentration of sevoflurane (2.5%) is capable of inducing and maintaining an effective surgical plane of anesthesia in the developing nonhuman primate and that a prolonged exposure of 9 h resulted in profound changes in gene expression, cytokine levels, lipid metabolism, and subsequently, neuronal damage. Generally, sevoflurane-induced neuronal damage was also associated with changes in lipid content, composition, or both; and specific lipid changes could provide insights into the molecular mechanism(s) underlying anesthetic-induced neurotoxicity and may be sensitive biomarkers for the early detection of anesthetic-induced neuronal damage. Published by Oxford University Press on behalf of the Society of Toxicology 2015. This work is written by a US Government employee and is in the public domain in the US.

Molecular insights into the progression of crystalline silica-induced pulmonary toxicity in rats.

PubMed

Sellamuthu, Rajendran; Umbright, Christina; Roberts, Jenny R; Cumpston, Amy; McKinney, Walter; Chen, Bean T; Frazer, David; Li, Shengqiao; Kashon, Michael; Joseph, Pius

2013-04-01

Identification of molecular target(s) and mechanism(s) of silica-induced pulmonary toxicity is important for the intervention and/or prevention of diseases associated with exposure to silica. Rats were exposed to crystalline silica by inhalation (15 mg m(-3), 6 h per day, 5 days) and global gene expression profile was determined in the lungs by microarray analysis at 1, 2, 4, 8 and 16 weeks following termination of silica exposure. The number of significantly differentially expressed genes (>1.5-fold change and <0.01 false discovery rate P-value) detected in the lungs during the post-exposure time intervals analyzed exhibited a steady increase in parallel with the progression of silica-induced pulmonary toxicity noticed in the rats. Quantitative real-time PCR analysis of a representative set of 10 genes confirmed the microarray findings. The number of biological functions, canonical pathways and molecular networks significantly affected by silica exposure, as identified by the bioinformatics analysis of the significantly differentially expressed genes detected during the post-exposure time intervals, also exhibited a steady increase similar to the silica-induced pulmonary toxicity. Genes involved in oxidative stress, inflammation, respiratory diseases, cancer, and tissue remodeling and fibrosis were significantly differentially expressed in the rat lungs; however, unresolved inflammation was the single most significant biological response to pulmonary exposure to silica. Excessive mucus production, as implicated by significant overexpression of the pendrin coding gene, SLC26A4, was identified as a potential novel mechanism for silica-induced pulmonary toxicity. Collectively, the findings of our study provided insights into the molecular mechanisms underlying the progression of crystalline silica-induced pulmonary toxicity in the rat. Published 2012. This article is a US Government work and is in the public domain in the USA. Published 2012. This article is a US Government work and is in the public domain in the USA.

Systematic Omics Analysis Review (SOAR) Tool to Support Risk Assessment

PubMed Central

McConnell, Emma R.; Bell, Shannon M.; Cote, Ila; Wang, Rong-Lin; Perkins, Edward J.; Garcia-Reyero, Natàlia; Gong, Ping; Burgoon, Lyle D.

2014-01-01

Environmental health risk assessors are challenged to understand and incorporate new data streams as the field of toxicology continues to adopt new molecular and systems biology technologies. Systematic screening reviews can help risk assessors and assessment teams determine which studies to consider for inclusion in a human health assessment. A tool for systematic reviews should be standardized and transparent in order to consistently determine which studies meet minimum quality criteria prior to performing in-depth analyses of the data. The Systematic Omics Analysis Review (SOAR) tool is focused on assisting risk assessment support teams in performing systematic reviews of transcriptomic studies. SOAR is a spreadsheet tool of 35 objective questions developed by domain experts, focused on transcriptomic microarray studies, and including four main topics: test system, test substance, experimental design, and microarray data. The tool will be used as a guide to identify studies that meet basic published quality criteria, such as those defined by the Minimum Information About a Microarray Experiment standard and the Toxicological Data Reliability Assessment Tool. Seven scientists were recruited to test the tool by using it to independently rate 15 published manuscripts that study chemical exposures with microarrays. Using their feedback, questions were weighted based on importance of the information and a suitability cutoff was set for each of the four topic sections. The final validation resulted in 100% agreement between the users on four separate manuscripts, showing that the SOAR tool may be used to facilitate the standardized and transparent screening of microarray literature for environmental human health risk assessment. PMID:25531884

Gene response profiles for Daphnia pulex exposed to the environmental stressor cadmium reveals novel crustacean metallothioneins.

PubMed

Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W

2007-12-21

Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences.

Gene response profiles for Daphnia pulex exposed to the environmental stressor cadmium reveals novel crustacean metallothioneins

PubMed Central

Shaw, Joseph R; Colbourne, John K; Davey, Jennifer C; Glaholt, Stephen P; Hampton, Thomas H; Chen, Celia Y; Folt, Carol L; Hamilton, Joshua W

2007-01-01

Background Genomic research tools such as microarrays are proving to be important resources to study the complex regulation of genes that respond to environmental perturbations. A first generation cDNA microarray was developed for the environmental indicator species Daphnia pulex, to identify genes whose regulation is modulated following exposure to the metal stressor cadmium. Our experiments revealed interesting changes in gene transcription that suggest their biological roles and their potentially toxicological features in responding to this important environmental contaminant. Results Our microarray identified genes reported in the literature to be regulated in response to cadmium exposure, suggested functional attributes for genes that share no sequence similarity to proteins in the public databases, and pointed to genes that are likely members of expanded gene families in the Daphnia genome. Genes identified on the microarray also were associated with cadmium induced phenotypes and population-level outcomes that we experimentally determined. A subset of genes regulated in response to cadmium exposure was independently validated using quantitative-realtime (Q-RT)-PCR. These microarray studies led to the discovery of three genes coding for the metal detoxication protein metallothionein (MT). The gene structures and predicted translated sequences of D. pulex MTs clearly place them in this gene family. Yet, they share little homology with previously characterized MTs. Conclusion The genomic information obtained from this study represents an important first step in characterizing microarray patterns that may be diagnostic to specific environmental contaminants and give insights into their toxicological mechanisms, while also providing a practical tool for evolutionary, ecological, and toxicological functional gene discovery studies. Advances in Daphnia genomics will enable the further development of this species as a model organism for the environmental sciences. PMID:18154678

APPLICATION OF CDNA MICROARRAY TO THE STUDY OF ARSENIC TOXICOLOGY AND CARCINOGENESIS

EPA Science Inventory

Arsenic (As) is a common environmental toxicant and known human carcinogen. Epidemiological studies link As exposure to various disorders and cancers. However, the molecular mechanisms for As toxicity and carcinogenicity are not completely known. The cDNA microarray, a high-th...

Microarray analysis of miRNA expression profiles following whole body irradiation in a mouse model.

PubMed

Aryankalayil, Molykutty J; Chopra, Sunita; Makinde, Adeola; Eke, Iris; Levin, Joel; Shankavaram, Uma; MacMillan, Laurel; Vanpouille-Box, Claire; Demaria, Sandra; Coleman, C Norman

2018-06-19

Accidental exposure to life-threatening radiation in a nuclear event is a major concern; there is an enormous need for identifying biomarkers for radiation biodosimetry to triage populations and treat critically exposed individuals. To identify dose-differentiating miRNA signatures from whole blood samples of whole body irradiated mice. Mice were whole body irradiated with X-rays (2 Gy-15 Gy); blood was collected at various time-points post-exposure; total RNA was isolated; miRNA microarrays were performed; miRNAs differentially expressed in irradiated vs. unirradiated controls were identified; feature extraction and classification models were applied to predict dose-differentiating miRNA signature. We observed a time and dose responsive alteration in the expression levels of miRNAs. Maximum number of miRNAs were altered at 24-h and 48-h time-points post-irradiation. A 23-miRNA signature was identified using feature selection algorithms and classifier models. An inverse correlation in the expression level changes of miR-17 members, and their targets were observed in whole body irradiated mice and non-human primates. Whole blood-based miRNA expression signatures might be used for predicting radiation exposures in a mass casualty nuclear incident.

Mining microarray datasets in nutrition: expression of the GPR120 (n-3 fatty acid receptor/sensor) gene is down-regulated in human adipocytes by macrophage secretions.

PubMed

Trayhurn, Paul; Denyer, Gareth

2012-01-01

Microarray datasets are a rich source of information in nutritional investigation. Targeted mining of microarray data following initial, non-biased bioinformatic analysis can provide key insight into specific genes and metabolic processes of interest. Microarrays from human adipocytes were examined to explore the effects of macrophage secretions on the expression of the G-protein-coupled receptor (GPR) genes that encode fatty acid receptors/sensors. Exposure of the adipocytes to macrophage-conditioned medium for 4 or 24 h had no effect on GPR40 and GPR43 expression, but there was a marked stimulation of GPR84 expression (receptor for medium-chain fatty acids), the mRNA level increasing 13·5-fold at 24 h relative to unconditioned medium. Importantly, expression of GPR120, which encodes an n-3 PUFA receptor/sensor, was strongly inhibited by the conditioned medium (15-fold decrease in mRNA at 24 h). Macrophage secretions have major effects on the expression of fatty acid receptor/sensor genes in human adipocytes, which may lead to an augmentation of the inflammatory response in adipose tissue in obesity.

Mining microarray datasets in nutrition: expression of the GPR120 (n-3 fatty acid receptor/sensor) gene is down-regulated in human adipocytes by macrophage secretions

PubMed Central

Trayhurn, Paul; Denyer, Gareth

2012-01-01

Microarray datasets are a rich source of information in nutritional investigation. Targeted mining of microarray data following initial, non-biased bioinformatic analysis can provide key insight into specific genes and metabolic processes of interest. Microarrays from human adipocytes were examined to explore the effects of macrophage secretions on the expression of the G-protein-coupled receptor (GPR) genes that encode fatty acid receptors/sensors. Exposure of the adipocytes to macrophage-conditioned medium for 4 or 24 h had no effect on GPR40 and GPR43 expression, but there was a marked stimulation of GPR84 expression (receptor for medium-chain fatty acids), the mRNA level increasing 13·5-fold at 24 h relative to unconditioned medium. Importantly, expression of GPR120, which encodes an n-3 PUFA receptor/sensor, was strongly inhibited by the conditioned medium (15-fold decrease in mRNA at 24 h). Macrophage secretions have major effects on the expression of fatty acid receptor/sensor genes in human adipocytes, which may lead to an augmentation of the inflammatory response in adipose tissue in obesity. PMID:25191551

Analysis of High-Throughput ELISA Microarray Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Amanda M.; Daly, Don S.; Zangar, Richard C.

Our research group develops analytical methods and software for the high-throughput analysis of quantitative enzyme-linked immunosorbent assay (ELISA) microarrays. ELISA microarrays differ from DNA microarrays in several fundamental aspects and most algorithms for analysis of DNA microarray data are not applicable to ELISA microarrays. In this review, we provide an overview of the steps involved in ELISA microarray data analysis and how the statistically sound algorithms we have developed provide an integrated software suite to address the needs of each data-processing step. The algorithms discussed are available in a set of open-source software tools (http://www.pnl.gov/statistics/ProMAT).

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

PubMed Central

Zhu, Yuerong; Zhu, Yuelin; Xu, Wei

2008-01-01

Background Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand. Results EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data. Conclusion EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from . PMID:18218103

Microarray-based analysis of gene expression in lycopersicon esculentum seedling roots in response to cadmium, chromium, mercury, and lead.

PubMed

Hou, Jing; Liu, Xinhui; Wang, Juan; Zhao, Shengnan; Cui, Baoshan

2015-02-03

The effects of heavy metals in agricultural soils have received special attention due to their potential for accumulation in crops, which can affect species at all trophic levels. Therefore, there is a critical need for reliable bioassays for assessing risk levels due to heavy metals in agricultural soil. In the present study, we used microarrays to investigate changes in gene expression of Lycopersicon esculentum in response to Cd-, Cr-, Hg-, or Pb-spiked soil. Exposure to (1)/10 median lethal concentrations (LC50) of Cd, Cr, Hg, or Pb for 7 days resulted in expression changes in 29 Cd-specific, 58 Cr-specific, 192 Hg-specific and 864 Pb-specific genes as determined by microarray analysis, whereas conventional morphological and physiological bioassays did not reveal any toxicant stresses. Hierarchical clustering analysis showed that the characteristic gene expression profiles induced by Cd, Cr, Hg, and Pb were distinct from not only the control but also one another. Furthermore, a total of three genes related to "ion transport" for Cd, 14 genes related to "external encapsulating structure organization", "reproductive developmental process", "lipid metabolic process" and "response to stimulus" for Cr, 11 genes related to "cellular metabolic process" and "cellular response to stimulus" for Hg, 78 genes related to 20 biological processes (e.g., DNA metabolic process, monosaccharide catabolic process, cell division) for Pb were identified and selected as their potential biomarkers. These findings demonstrated that microarray-based analysis of Lycopersicon esculentum was a sensitive tool for the early detection of potential toxicity of heavy metals in agricultural soil, as well as an effective tool for identifying the heavy metal-specific genes, which should be useful for assessing risk levels due to heavy metals in agricultural soil.

Chemiluminescence microarrays in analytical chemistry: a critical review.

PubMed

Seidel, Michael; Niessner, Reinhard

2014-09-01

Multi-analyte immunoassays on microarrays and on multiplex DNA microarrays have been described for quantitative analysis of small organic molecules (e.g., antibiotics, drugs of abuse, small molecule toxins), proteins (e.g., antibodies or protein toxins), and microorganisms, viruses, and eukaryotic cells. In analytical chemistry, multi-analyte detection by use of analytical microarrays has become an innovative research topic because of the possibility of generating several sets of quantitative data for different analyte classes in a short time. Chemiluminescence (CL) microarrays are powerful tools for rapid multiplex analysis of complex matrices. A wide range of applications for CL microarrays is described in the literature dealing with analytical microarrays. The motivation for this review is to summarize the current state of CL-based analytical microarrays. Combining analysis of different compound classes on CL microarrays reduces analysis time, cost of reagents, and use of laboratory space. Applications are discussed, with examples from food safety, water safety, environmental monitoring, diagnostics, forensics, toxicology, and biosecurity. The potential and limitations of research on multiplex analysis by use of CL microarrays are discussed in this review.

DEVELOPMENT OF MICROARRAYS AS A TOOL FOR DISCOVERING ENVIRONMENTAL EXPOSURE INDICATORS

EPA Science Inventory

Toxicogenomics includes research to identify differential gene expression in laboratory and field animals exposed to toxicants, and ultimately, to link the earliest indicators of exposure to adverse effects in organisms and populations. The USEPA National Exposure Research Labor...

Transcriptome analysis of the human T lymphocyte cell line Jurkat and human peripheral blood mononuclear cells exposed to deoxynivalenol (DON): New mechanistic insights

DOE Office of Scientific and Technical Information (OSTI.GOV)

Katika, Madhumohan R.; Department of Health Risk Analysis and Toxicology, Maastricht University; Netherlands Toxicogenomics Centre

Deoxynivalenol (DON) or vomitoxin is a commonly encountered type-B trichothecene mycotoxin, produced by Fusarium species predominantly found in cereals and grains. DON is known to exert toxic effects on the gastrointestinal, reproductive and neuroendocrine systems, and particularly on the immune system. Depending on dose and exposure time, it can either stimulate or suppress immune function. The main objective of this study was to obtain a deeper insight into DON-induced effects on lymphoid cells. For this, we exposed the human T-lymphocyte cell line Jurkat and human peripheral blood mononuclear cells (PBMCs) to various concentrations of DON for various times and examinedmore » gene expression changes by DNA microarray analysis. Jurkat cells were exposed to 0.25 and 0.5 μM DON for 3, 6 and 24 h. Biological interpretation of the microarray data indicated that DON affects various processes in these cells: It upregulates genes involved in ribosome structure and function, RNA/protein synthesis and processing, endoplasmic reticulum (ER) stress, calcium-mediated signaling, mitochondrial function, oxidative stress, the NFAT and NF-κB/TNF-α pathways, T cell activation and apoptosis. The effects of DON on the expression of genes involved in ER stress, NFAT activation and apoptosis were confirmed by qRT-PCR. Other biochemical experiments confirmed that DON activates calcium-dependent proteins such as calcineurin and M-calpain that are known to be involved in T cell activation and apoptosis. Induction of T cell activation was also confirmed by demonstrating that DON activates NFATC1 and induces its translocation from the cytoplasm to the nucleus. For the gene expression profiling of PBMCs, cells were exposed to 2 and 4 μM DON for 6 and 24 h. Comparison of the Jurkat microarray data with those obtained with PBMCs showed that most of the processes affected by DON in the Jurkat cell line were also affected in the PBMCs. -- Highlights: ► The human T cell line Jurkat and human PBMCs were exposed to DON. ► Whole-genome microarray experiments were performed. ► Microarray data indicates that DON affects ribosome and RNA/protein synthesis. ► DON treatment induces ER stress, calcium mediated signaling, NFAT and NF-κB. ► Exposure to DON induces T cell activation, oxidative stress and apoptosis.« less

Molecular pathway activation in cancer and tissue following space radiation exposure

NASA Astrophysics Data System (ADS)

Kovyrshina, Tatiana A.

Space radiation exposure is an important safety concern for astronauts, especially since one of the risks is carcinogenesis. This thesis explores the link between lung, colorectal, and breast cancer and iron particles and gamma radiation on a molecular level. We obtained DNA microarrays for each condition from the Gene Expression Omnibus (GEO), a public functional genomics data repository, cleaned up the data, and analysed overexpression and underexpression of pathway analysis. Our results show that pathways which participate in DNA replication appear to be overexpressed in cancer cells and cells exposed to ionizing radiation.

Protein expression profile changes in human fibroblasts induced by low dose energetic protons

NASA Astrophysics Data System (ADS)

Zhang, Ye; Clement, Jade Q.; Gridley, Daila S.; Rodhe, Larry H.; Wu, Honglu

2009-12-01

Extrapolation of known radiation risks to the risks from low dose and low dose-rate exposures of human population, especially prolonged exposures of astronauts in the space radiation environment, relies in part on the mechanistic understanding of radiation induced biological consequences at the molecular level. While some genomic data at the mRNA level are available for cells or animals exposed to radiation, the data at the protein level are still lacking. Here, we studied protein expression profile changes using Panorama antibody microarray chips that contain antibodies to 224 proteins (or their phosphorylated forms) involved in cell signaling that included mostly apoptosis, cytoskeleton, cell cycle and signal transduction. Normal human fibroblasts were cultured until fully confluent and then exposed to 2 cGy of 150 MeV protons at high-dose rate. The proteins were isolated at 2 or 6 h after exposure and labeled with Cy3 for the irradiated cells and with Cy5 for the control samples before loading onto the protein microarray chips. The intensities of the protein spots were analyzed using ScanAlyze software and normalized by the summed fluorescence intensities and the housekeeping proteins. The results showed that low dose protons altered the expression of more than 10% of the proteins listed in the microarray analysis in various protein functional groups. Cell cycle (24%) related proteins were induced by protons and most of them were regulators of G1/S-transition phase. Comparison of the overall protein expression profiles, cell cycle related proteins, cytoskeleton and signal transduction protein groups showed significantly more changes induced by protons compared with other protein functional groups.

cDNA microarray analysis of esophageal cancer: discoveries and prospects.

PubMed

Shimada, Yutaka; Sato, Fumiaki; Shimizu, Kazuharu; Tsujimoto, Gozoh; Tsukada, Kazuhiro

2009-07-01

Recent progress in molecular biology has revealed many genetic and epigenetic alterations that are involved in the development and progression of esophageal cancer. Microarray analysis has also revealed several genetic networks that are involved in esophageal cancer. However, clinical application of microarray techniques and use of microarray data have not yet occurred. In this review, we focus on the recent developments and problems with microarray analysis of esophageal cancer.

Importing MAGE-ML format microarray data into BioConductor.

PubMed

Durinck, Steffen; Allemeersch, Joke; Carey, Vincent J; Moreau, Yves; De Moor, Bart

2004-12-12

The microarray gene expression markup language (MAGE-ML) is a widely used XML (eXtensible Markup Language) standard for describing and exchanging information about microarray experiments. It can describe microarray designs, microarray experiment designs, gene expression data and data analysis results. We describe RMAGEML, a new Bioconductor package that provides a link between cDNA microarray data stored in MAGE-ML format and the Bioconductor framework for preprocessing, visualization and analysis of microarray experiments. http://www.bioconductor.org. Open Source.

Simulated Microgravity Regulates Gene Transcript Profiles of 2T3 Preosteoblasts: Comparison of the Random Positioning Machine and the Rotating Wall Vessel Bioreactor

NASA Technical Reports Server (NTRS)

Patel, Mamta J.; Liu, Wenbin; Sykes, Michelle C.; Ward, Nancy E.; Risin, Semyon A.; Risin, Diana; Hanjoong, Jo

2007-01-01

Microgravity of spaceflight induces bone loss due in part to decreased bone formation by osteoblasts. We have previously examined the microgravity-induced changes in gene expression profiles in 2T3 preosteoblasts using the Random Positioning Machine (RPM) to simulate microgravity conditions. Here, we hypothesized that exposure of preosteoblasts to an independent microgravity simulator, the Rotating Wall Vessel (RWV), induces similar changes in differentiation and gene transcript profiles, resulting in a more confined list of gravi-sensitive genes that may play a role in bone formation. In comparison to static 1g controls, exposure of 2T3 cells to RWV for 3 days inhibited alkaline phosphatase activity, a marker of differentiation, and downregulated 61 genes and upregulated 45 genes by more than two-fold as shown by microarray analysis. The microarray results were confirmed with real time PCR for downregulated genes osteomodulin, bone morphogenic protein 4 (BMP4), runx2, and parathyroid hormone receptor 1. Western blot analysis validated the expression of three downregulated genes, BMP4, peroxiredoxin IV, and osteoglycin, and one upregulated gene peroxiredoxin I. Comparison of the microarrays from the RPM and the RWV studies identified 14 gravi-sensitive genes that changed in the same direction in both systems. Further comparison of our results to a published database showing gene transcript profiles of mechanically loaded mouse tibiae revealed 16 genes upregulated by the loading that were shown to be downregulated by RWV and RPM. These mechanosensitive genes identified by the comparative studies may provide novel insights into understanding the mechanisms regulating bone formation and potential targets of countermeasure against decreased bone formation both in astronauts and in general patients with musculoskeletal disorders.

Modulation of Cholinergic Pathways and Inflammatory Mediators in Blast-Induced Traumatic Brain Injury

DTIC Science & Technology

2013-01-01

matic brain injury (TBI). Centrally acting acetylcholinesterase (AChE) inhibitors are also being considered as potential therapeutic candidates...repeated blast exposures [12]. AChE inhibitors are possible therapeutic candidates against Alzheimer’s disease and TBI [13–15]. In this study, we...esterase inhibitor , as described earlier [12,17–19]. Brain AChE activity was expressed as milliunits/mg protein. 2.3. Microarray analysis Various

Differential Gene Expression in Primary Human Skin Keratinocytes and Fibroblasts in Response to Ionizing Radiation

PubMed Central

Warters, Raymond L.; Packard, Ann T.; Kramer, Gwen F.; Gaffney, David K.; Moos, Philip J.

2009-01-01

Although skin is usually exposed during human exposures to ionizing radiation, there have been no thorough examinations of the transcriptional response of skin fibroblasts and keratinocytes to radiation. The transcriptional response of quiescent primary fibroblasts and keratinocytes exposed to from 10 cGy to 5 Gy and collected 4 h after treatment was examined. RNA was isolated and examined by microarray analysis for changes in the levels of gene expression. Exposure to ionizing radiation altered the expression of 279 genes across both cell types. Changes in RNA expression could be arranged into three main categories: (1) changes in keratinocytes but not in fibroblasts, (2) changes in fibroblasts but not in keratinocytes, and (3) changes in both. All of these changes were primarily of p53 target genes. Similar radiation-induced changes were induced in immortalized fibroblasts or keratinocytes. In separate experiments, protein was collected and analyzed by Western blotting for expression of proteins observed in microarray experiments to be overexpressed at the mRNA level. Both Q-PCR and Western blot analysis experiments validated these transcription changes. Our results are consistent with changes in the expression of p53 target genes as indicating the magnitude of cell responses to ionizing radiation. PMID:19580510

Biomarkers of acute respiratory allergen exposure: Screening for sensitization potential

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pucheu-Haston, Cherie M., E-mail: Pucheu-Haston.Cherie@epa.go; Copeland, Lisa B.; Vallanat, Beena

2010-04-15

Effective hazard screening will require the development of high-throughput or in vitro assays for the identification of potential sensitizers. The goal of this preliminary study was to identify potential biomarkers that differentiate the response to allergens vs non-allergens following an acute exposure in naive individuals. Female BALB/c mice received a single intratracheal aspiration exposure to Metarhizium anisopliae crude antigen (MACA) or bovine serum albumin (BSA) in Hank's Balanced Salt Solution (HBSS) or HBSS alone. Mice were terminated after 1, 3, 6, 12, 18 and 24 h. Bronchoalveolar lavage fluid (BALF) was evaluated to determine total and differential cellularity, total proteinmore » concentration and LDH activity. RNA was isolated from lung tissue for microarray analysis and qRT-PCR. MACA administration induced a rapid increase in BALF neutrophils, lymphocytes, eosinophils and total protein compared to BSA or HBSS. Microarray analysis demonstrated differential expression of genes involved in cytokine production, signaling, inflammatory cell recruitment, adhesion and activation in 3 and 12 h MACA-treated samples compared to BSA or HBSS. Further analyses allowed identification of approx 100 candidate biomarker genes. Eleven genes were selected for further assessment by qRT-PCR. Of these, 6 demonstrated persistently increased expression (Ccl17, Ccl22, Ccl7, Cxcl10, Cxcl2, Saa1), while C3ar1 increased from 6-24 h. In conclusion, a single respiratory exposure of mice to an allergenic mold extract induces an inflammatory response which is distinct in phenotype and gene transcription from the response to a control protein. Further validation of these biomarkers with additional allergens and irritants is needed. These biomarkers may facilitate improvements in screening methods.« less

The Longhorn Array Database (LAD): An Open-Source, MIAME compliant implementation of the Stanford Microarray Database (SMD)

PubMed Central

Killion, Patrick J; Sherlock, Gavin; Iyer, Vishwanath R

2003-01-01

Background The power of microarray analysis can be realized only if data is systematically archived and linked to biological annotations as well as analysis algorithms. Description The Longhorn Array Database (LAD) is a MIAME compliant microarray database that operates on PostgreSQL and Linux. It is a fully open source version of the Stanford Microarray Database (SMD), one of the largest microarray databases. LAD is available at Conclusions Our development of LAD provides a simple, free, open, reliable and proven solution for storage and analysis of two-color microarray data. PMID:12930545

Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization.

PubMed

Oikawa, Masahiro; Yoshiura, Koh-ichiro; Kondo, Hisayoshi; Miura, Shiro; Nagayasu, Takeshi; Nakashima, Masahiro

2011-12-07

It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A-bomb radiation may affect the increased amount of CNA as a hallmark of GIN and, subsequently, be associated with a higher histologic grade in breast cancer found in A-bomb survivors.

Significance of genomic instability in breast cancer in atomic bomb survivors: analysis of microarray-comparative genomic hybridization

PubMed Central

2011-01-01

Background It has been postulated that ionizing radiation induces breast cancers among atomic bomb (A-bomb) survivors. We have reported a higher incidence of HER2 and C-MYC oncogene amplification in breast cancers from A-bomb survivors. The purpose of this study was to clarify the effect of A-bomb radiation exposure on genomic instability (GIN), which is an important hallmark of carcinogenesis, in archival formalin-fixed paraffin-embedded (FFPE) tissues of breast cancer by using microarray-comparative genomic hybridization (aCGH). Methods Tumor DNA was extracted from FFPE tissues of invasive ductal cancers from 15 survivors who were exposed at 1.5 km or less from the hypocenter and 13 calendar year-matched non-exposed patients followed by aCGH analysis using a high-density oligonucleotide microarray. The total length of copy number aberrations (CNA) was used as an indicator of GIN, and correlation with clinicopathological factors were statistically tested. Results The mean of the derivative log ratio spread (DLRSpread), which estimates the noise by calculating the spread of log ratio differences between consecutive probes for all chromosomes, was 0.54 (range, 0.26 to 1.05). The concordance of results between aCGH and fluorescence in situ hybridization (FISH) for HER2 gene amplification was 88%. The incidence of HER2 amplification and histological grade was significantly higher in the A-bomb survivors than control group (P = 0.04, respectively). The total length of CNA tended to be larger in the A-bomb survivors (P = 0.15). Correlation analysis of CNA and clinicopathological factors revealed that DLRSpread was negatively correlated with that significantly (P = 0.034, r = -0.40). Multivariate analysis with covariance revealed that the exposure to A-bomb was a significant (P = 0.005) independent factor which was associated with larger total length of CNA of breast cancers. Conclusions Thus, archival FFPE tissues from A-bomb survivors are useful for genome-wide aCGH analysis. Our results suggested that A-bomb radiation may affect the increased amount of CNA as a hallmark of GIN and, subsequently, be associated with a higher histologic grade in breast cancer found in A-bomb survivors. PMID:22152285

Assessing mechanisms of toxicant response in the amphipod Melita plumulosa through transcriptomic profiling.

PubMed

Hook, Sharon E; Osborn, Hannah L; Spadaro, David A; Simpson, Stuart L

2014-01-01

This study describes the function of transcripts with altered abundance in the epibenthic amphipod, Melita plumulosa, following whole-sediment exposure to a series of common environmental contaminants. M. plumulosa were exposed for 48 h to sediments spiked and equilibrated with the following contaminants at concentrations predicted to cause sublethal effects to reproduction: porewater ammonia 30 mg L(-1); bifenthrin at 100 μg kg(-1); fipronil at 50 μg kg(-1); 0.6% diesel; 0.3% crude oil; 250 mg Cu kg(-1); 400 mg Ni kg(-1); and 400 mg Zn kg(-1). RNA was extracted and hybridized against a custom Agilent microarray developed for this species. Although the microarray represented a partial transcriptome and not all features on the array could be annotated, unique transcriptomic profiles were generated for each of the contaminant exposures. Hierarchical clustering grouped the expression profiles together by contaminant class, with copper and zinc, the petroleum products and nickel, and the pesticides each forming a distinct cluster. Many of the transcriptional changes observed were consistent with patterns previously described in other crustaceans. The changes in the transcriptome demonstrated that contaminant exposure caused changes in digestive function, growth and moulting, and the cytoskeleton following metal exposure, whereas exposure to petroleum products caused changes in carbohydrate metabolism, xenobiotic metabolism and hormone cycling. Functional analysis of these gene expression profiles can provide a better understanding of modes of toxic action and permits the prediction of mixture effects within contaminated ecosystems. Crown Copyright © 2013. Published by Elsevier B.V. All rights reserved.

ADAPTING MICROARRAY TECHNOLOGY FOR USE IN ECOTOXICOGENOMICS

EPA Science Inventory

Ecotoxicogenomics includes research to identify differential gene expression in laboratory and field animals exposed to toxicants, and ultimately, to link the earliest indicators of exposure to adverse effects in organisms and populations. The USEPA National Exposure Research La...

Exposure to Cobalt Causes Transcriptomic and Proteomic Changes in Two Rat Liver Derived Cell Lines

PubMed Central

Permenter, Matthew G.; Dennis, William E.; Sutto, Thomas E.; Jackson, David A.; Lewis, John A.; Stallings, Jonathan D.

2013-01-01

Cobalt is a transition group metal present in trace amounts in the human diet, but in larger doses it can be acutely toxic or cause adverse health effects in chronic exposures. Its use in many industrial processes and alloys worldwide presents opportunities for occupational exposures, including military personnel. While the toxic effects of cobalt have been widely studied, the exact mechanisms of toxicity remain unclear. In order to further elucidate these mechanisms and identify potential biomarkers of exposure or effect, we exposed two rat liver-derived cell lines, H4-II-E-C3 and MH1C1, to two concentrations of cobalt chloride. We examined changes in gene expression using DNA microarrays in both cell lines and examined changes in cytoplasmic protein abundance in MH1C1 cells using mass spectrometry. We chose to closely examine differentially expressed genes and proteins changing in abundance in both cell lines in order to remove cell line specific effects. We identified enriched pathways, networks, and biological functions using commercial bioinformatic tools and manual annotation. Many of the genes, proteins, and pathways modulated by exposure to cobalt appear to be due to an induction of a hypoxic-like response and oxidative stress. Genes that may be differentially expressed due to a hypoxic-like response are involved in Hif-1α signaling, glycolysis, gluconeogenesis, and other energy metabolism related processes. Gene expression changes linked to oxidative stress are also known to be involved in the NRF2-mediated response, protein degradation, and glutathione production. Using microarray and mass spectrometry analysis, we were able to identify modulated genes and proteins, further elucidate the mechanisms of toxicity of cobalt, and identify biomarkers of exposure and effect in vitro, thus providing targets for focused in vivo studies. PMID:24386269

The Microarray Revolution: Perspectives from Educators

ERIC Educational Resources Information Center

Brewster, Jay L.; Beason, K. Beth; Eckdahl, Todd T.; Evans, Irene M.

2004-01-01

In recent years, microarray analysis has become a key experimental tool, enabling the analysis of genome-wide patterns of gene expression. This review approaches the microarray revolution with a focus upon four topics: 1) the early development of this technology and its application to cancer diagnostics; 2) a primer of microarray research,…

Gene expression profiling of three different stressors in the water flea Daphnia magna.

PubMed

Jansen, Mieke; Vergauwen, Lucia; Vandenbrouck, Tine; Knapen, Dries; Dom, Nathalie; Spanier, Katina I; Cielen, Anke; De Meester, Luc

2013-07-01

Microarrays are an ideal tool to screen for differences in gene expression of thousands of genes simultaneously. However, often commercial arrays are not available. In this study, we performed microarray analyses to evaluate patterns of gene transcription following exposure to two natural and one anthropogenic stressor. cDNA microarrays compiled of three life stage specific and three stressor-specific EST libraries, yielding 1734 different EST sequences, were used. We exposed juveniles of the water flea Daphnia magna for 48, 96 and 144 h to three stressors known to exert strong selection in natural populations of this species i.e. a sublethal concentration of the pesticide carbaryl, infective spores of the endoparasite Pasteuria ramosa, and fish predation risk mimicked by exposure to fish kairomones. A total of 148 gene fragments were differentially expressed compared to the control. Based on a PCA, the exposure treatments were separated into two main groups based on the extent of the transcriptional response: a low and a high (144 h of fish or carbaryl exposure and 96 h of parasite exposure) stress group. Firstly, we observed a general stress-related transcriptional expression profile independent of the treatment characterized by repression of transcripts involved in transcription, translation, signal transduction and energy metabolism. Secondly, we observed treatment-specific responses including signs of migration to deeper water layers in response to fish predation, structural challenge of the cuticle in response to carbaryl exposure, and disturbance of the ATP production in parasite exposure. A third important conclusion is that transcription expression patterns exhibit stress-specific changes over time. Parasite exposure shows the most differentially expressed gene fragments after 96 h. The peak of differentially expressed transcripts came only after 144 h of fish exposure, while carbaryl exposure induced a more stable number of differently expressed gene fragments over time.

Gene expression analysis in rat lungs after intratracheal exposure to nanoparticles doped with cadmium

NASA Astrophysics Data System (ADS)

Coccini, Teresa; Fabbri, Marco; Roda, Elisa; Grazia Sacco, Maria; Manzo, Luigi; Gribaldo, Laura

2011-07-01

Silica nanoparticles (NPs) incorporating cadmium (Cd) have been developed for a range of potential application including drug delivery devices. Occupational Cd inhalation has been associated with emphysema, pulmonary fibrosis and lung tumours. Mechanistically, Cd can induce oxidative stress and mediate cell-signalling pathways that are involved in inflammation.This in vivo study aimed at investigating pulmonary molecular effects of NPs doped with Cd (NP-Cd, 1 mg/animal) compared to soluble CdCl2 (400 μg/animal), in Sprague Dawley rats treated intra-tracheally, 7 and 30 days after administration. NPs of silica containing Cd salt were prepared starting from commercial nano-size silica powder (HiSil™ T700 Degussa) with average pore size of 20 nm and surface area of 240 m2/g. Toxicogenomic analysis was performed by the DNA microarray technology (using Agilent Whole Rat Genome Microarray 4×44K) to evaluate changes in gene expression of the entire genome. These findings indicate that the whole genome analysis may represent a valuable approach to assess the whole spectrum of biological responses to cadmium containing nanomaterials.

Machine learning approaches to investigate the impact of PCBs on the transcriptome of the common bottlenose dolphin (Tursiops truncatus).

PubMed

Mancia, Annalaura; Ryan, James C; Van Dolah, Frances M; Kucklick, John R; Rowles, Teresa K; Wells, Randall S; Rosel, Patricia E; Hohn, Aleta A; Schwacke, Lori H

2014-09-01

As top-level predators, common bottlenose dolphins (Tursiops truncatus) are particularly sensitive to chemical and biological contaminants that accumulate and biomagnify in the marine food chain. This work investigates the potential use of microarray technology and gene expression profile analysis to screen common bottlenose dolphins for exposure to environmental contaminants through the immunological and/or endocrine perturbations associated with these agents. A dolphin microarray representing 24,418 unigene sequences was used to analyze blood samples collected from 47 dolphins during capture-release health assessments from five different US coastal locations (Beaufort, NC, Sarasota Bay, FL, Saint Joseph Bay, FL, Sapelo Island, GA and Brunswick, GA). Organohalogen contaminants including pesticides, polychlorinated biphenyl congeners (PCBs) and polybrominated diphenyl ether congeners were determined in blubber biopsy samples from the same animals. A subset of samples (n = 10, males; n = 8, females) with the highest and the lowest measured values of PCBs in their blubber was used as strata to determine the differential gene expression of the exposure extremes through machine learning classification algorithms. A set of genes associated primarily with nuclear and DNA stability, cell division and apoptosis regulation, intra- and extra-cellular traffic, and immune response activation was selected by the algorithm for identifying the two exposure extremes. In order to test the hypothesis that these gene expression patterns reflect PCB exposure, we next investigated the blood transcriptomes of the remaining dolphin samples using machine-learning approaches, including K-nn and Support Vector Machines classifiers. Using the derived gene sets, the algorithms worked very well (100% success rate) at classifying dolphins according to the contaminant load accumulated in their blubber. These results suggest that gene expression profile analysis may provide a valuable means to screen for indicators of chemical exposure. Copyright © 2014 Elsevier Ltd. All rights reserved.

EMAAS: An extensible grid-based Rich Internet Application for microarray data analysis and management

PubMed Central

Barton, G; Abbott, J; Chiba, N; Huang, DW; Huang, Y; Krznaric, M; Mack-Smith, J; Saleem, A; Sherman, BT; Tiwari, B; Tomlinson, C; Aitman, T; Darlington, J; Game, L; Sternberg, MJE; Butcher, SA

2008-01-01

Background Microarray experimentation requires the application of complex analysis methods as well as the use of non-trivial computer technologies to manage the resultant large data sets. This, together with the proliferation of tools and techniques for microarray data analysis, makes it very challenging for a laboratory scientist to keep up-to-date with the latest developments in this field. Our aim was to develop a distributed e-support system for microarray data analysis and management. Results EMAAS (Extensible MicroArray Analysis System) is a multi-user rich internet application (RIA) providing simple, robust access to up-to-date resources for microarray data storage and analysis, combined with integrated tools to optimise real time user support and training. The system leverages the power of distributed computing to perform microarray analyses, and provides seamless access to resources located at various remote facilities. The EMAAS framework allows users to import microarray data from several sources to an underlying database, to pre-process, quality assess and analyse the data, to perform functional analyses, and to track data analysis steps, all through a single easy to use web portal. This interface offers distance support to users both in the form of video tutorials and via live screen feeds using the web conferencing tool EVO. A number of analysis packages, including R-Bioconductor and Affymetrix Power Tools have been integrated on the server side and are available programmatically through the Postgres-PLR library or on grid compute clusters. Integrated distributed resources include the functional annotation tool DAVID, GeneCards and the microarray data repositories GEO, CELSIUS and MiMiR. EMAAS currently supports analysis of Affymetrix 3' and Exon expression arrays, and the system is extensible to cater for other microarray and transcriptomic platforms. Conclusion EMAAS enables users to track and perform microarray data management and analysis tasks through a single easy-to-use web application. The system architecture is flexible and scalable to allow new array types, analysis algorithms and tools to be added with relative ease and to cope with large increases in data volume. PMID:19032776

An Introduction to MAMA (Meta-Analysis of MicroArray data) System.

PubMed

Zhang, Zhe; Fenstermacher, David

2005-01-01

Analyzing microarray data across multiple experiments has been proven advantageous. To support this kind of analysis, we are developing a software system called MAMA (Meta-Analysis of MicroArray data). MAMA utilizes a client-server architecture with a relational database on the server-side for the storage of microarray datasets collected from various resources. The client-side is an application running on the end user's computer that allows the user to manipulate microarray data and analytical results locally. MAMA implementation will integrate several analytical methods, including meta-analysis within an open-source framework offering other developers the flexibility to plug in additional statistical algorithms.

MicroRNA regulatory networks reflective of polyhexamethylene guanidine phosphate-induced fibrosis in A549 human alveolar adenocarcinoma cells.

PubMed

Shin, Da Young; Jeong, Mi Ho; Bang, In Jae; Kim, Ha Ryong; Chung, Kyu Hyuck

2018-05-01

Polyhexamethylene guanidine phosphate (PHMG-phosphate), an active component of humidifier disinfectant, is suspected to be a major cause of pulmonary fibrosis. Fibrosis, induced by recurrent epithelial damage, is significantly affected by epigenetic regulation, including microRNAs (miRNAs). The aim of this study was to investigate the fibrogenic mechanisms of PHMG-phosphate through the profiling of miRNAs and their target genes. A549 cells were treated with 0.75 μg/mL PHMG-phosphate for 24 and 48 h and miRNA microarray expression analysis was conducted. The putative mRNA targets of the miRNAs were identified and subjected to Gene Ontology analysis. After exposure to PHMG-phosphate for 24 and 48 h, 46 and 33 miRNAs, respectively, showed a significant change in expression over 1.5-fold compared with the control. The integrated analysis of miRNA and mRNA microarray results revealed the putative targets that were prominently enriched were associated with the epithelial-mesenchymal transition (EMT), cell cycle changes, and apoptosis. The dose-dependent induction of EMT by PHMG-phosphate exposure was confirmed by western blot. We identified 13 putative EMT-related targets that may play a role in PHMG-phosphate-induced fibrosis according to the Comparative Toxicogenomic Database. Our findings contribute to the comprehension of the fibrogenic mechanism of PHMG-phosphate and will aid further study on PHMG-phosphate-induced toxicity. Copyright © 2018 Elsevier B.V. All rights reserved.

Arsenic exposure triggers a shift in microRNA expression.

PubMed

Sturchio, Elena; Colombo, Teresa; Boccia, Priscilla; Carucci, Nicoletta; Meconi, Claudia; Minoia, Claudio; Macino, Giuseppe

2014-02-15

Exposure to inorganic Arsenic (iAs) through drinking water is a major public health problem affecting most countries. iAs has been classified by the International Agency for Research on Cancer as Group 1: "Carcinogenic to humans". Although numerous studies have shown the related adverse effects of iAs, sensitive appropriate biomarkers for studies of environmental epidemiology are still required. The present work aims at investigate the role of microRNAs (miRNAs), powerful negative regulators of gene expression, playing a key role in many physiological and pathological cellular processes, in iAs exposure. To this end, we analyzed miRNA changes in expression profile triggered by iAs exposure in Jurkat cell line. We used microarray technology to profile the expression of miRNAs following 2 μmol/L sodium arsenite treatment at different time points. Moreover, we performed phenotypic analysis of iAs treated cells. Real Time Polymerase Chain Reaction (RT-PCR) was used to validate miRNA microarray data and to assay expression modulation of selected relevant mRNAs. Finally, bioinformatics techniques were applied to reconstruct iAs-relevant molecular pathways and miRNA regulatory networks from the expression data. We report miRNAs modulated after iAs treatment in Jurkat cells. In particular, we highlight 36 miRNAs exhibiting consistent dysregulation and particularly a panel of 8 miRNAs which we also validated by RT-PCR analysis. Computational analysis of lists of putative target genes for these 8 miRNAs points to an involvement in arsenic-response pathways, for a subset of them, that were analyzed by RT-PCR. Furthermore, iAs exposure reveals induction of cell cycle progression and the failure of apoptosis, supporting the idea of iAs carcinogenic activity. Our study provides a list of miRNAs whose expression levels are affected by iAs treatment, corroborating the importance of proceeding with the hunt for specific subset of miRNAs, which can serve as potential biomarkers of iAs effects with useful diagnostic value. Copyright © 2013 Elsevier B.V. All rights reserved.

Stannous Fluoride Effects on Gene Expression of Streptococcus mutans and Actinomyces viscosus.

PubMed

Shi, Y; Li, R; White, D J; Biesbrock, A R

2018-02-01

A genome-wide transcriptional analysis was performed to elucidate the bacterial cellular response of Streptococcus mutans and Actinomyces viscosus to NaF and SnF 2 . The minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) of SnF 2 were predetermined before microarray study. Gene expression profiling microarray experiments were carried out in the absence (control) and presence (experimental) of 10 ppm and 100 ppm Sn 2+ (in the form of SnF 2 ) and fluoride controls for 10-min exposures (4 biological replicates/treatment). These Sn 2+ levels and treatment time were chosen because they have been shown to slow bacterial growth of S. mutans (10 ppm) and A. viscosus (100 ppm) without affecting cell viability. All data generated by microarray experiments were analyzed with bioinformatics tools by applying the following criteria: 1) a q value should be ≤0.05, and 2) an absolute fold change in transcript level should be ≥1.5. Microarray results showed SnF 2 significantly inhibited several genes encoding enzymes of the galactose pathway upon a 10-min exposure versus a negative control: lacA and lacB (A and B subunits of the galactose-6-P isomerase), lacC (tagatose-6-P kinase), lacD (tagatose-1,6-bP adolase), galK (galactokinase), galT (galactose-1-phosphate uridylyltransferase), and galE (UDP-glucose 4-epimerase). A gene fruK encoding fructose-1-phosphate kinase in the fructose pathway was also significantly inhibited. Several genes encoding fructose/mannose-specific enzyme IIABC components in the phosphotransferase system (PTS) were also downregulated, as was ldh encoding lactate dehydrogenase, a key enzyme involved in lactic acid synthesis. SnF 2 downregulated the transcription of most key enzyme genes involved in the galactose pathway and also suppressed several key genes involved in the PTS, which transports sugars into the cell in the first step of glycolysis.

Investigating the epigenetic effects of a prototype smoke-derived carcinogen in human cells.

PubMed

Tommasi, Stella; Kim, Sang-in; Zhong, Xueyan; Wu, Xiwei; Pfeifer, Gerd P; Besaratinia, Ahmad

2010-05-12

Global loss of DNA methylation and locus/gene-specific gain of DNA methylation are two distinct hallmarks of carcinogenesis. Aberrant DNA methylation is implicated in smoking-related lung cancer. In this study, we have comprehensively investigated the modulation of DNA methylation consequent to chronic exposure to a prototype smoke-derived carcinogen, benzo[a]pyrene diol epoxide (B[a]PDE), in genomic regions of significance in lung cancer, in normal human cells. We have used a pulldown assay for enrichment of the CpG methylated fraction of cellular DNA combined with microarray platforms, followed by extensive validation through conventional bisulfite-based analysis. Here, we demonstrate strikingly similar patterns of DNA methylation in non-transformed B[a]PDE-treated cells vs control using high-throughput microarray-based DNA methylation profiling confirmed by conventional bisulfite-based DNA methylation analysis. The absence of aberrant DNA methylation in our model system within a timeframe that precedes cellular transformation suggests that following carcinogen exposure, other as yet unknown factors (secondary to carcinogen treatment) may help initiate global loss of DNA methylation and region-specific gain of DNA methylation, which can, in turn, contribute to lung cancer development. Unveiling the initiating events that cause aberrant DNA methylation in lung cancer has tremendous public health relevance, as it can help define future strategies for early detection and prevention of this highly lethal disease.

Investigating the Epigenetic Effects of a Prototype Smoke-Derived Carcinogen in Human Cells

PubMed Central

Tommasi, Stella; Kim, Sang-in; Zhong, Xueyan; Wu, Xiwei; Pfeifer, Gerd P.; Besaratinia, Ahmad

2010-01-01

Global loss of DNA methylation and locus/gene-specific gain of DNA methylation are two distinct hallmarks of carcinogenesis. Aberrant DNA methylation is implicated in smoking-related lung cancer. In this study, we have comprehensively investigated the modulation of DNA methylation consequent to chronic exposure to a prototype smoke-derived carcinogen, benzo[a]pyrene diol epoxide (B[a]PDE), in genomic regions of significance in lung cancer, in normal human cells. We have used a pulldown assay for enrichment of the CpG methylated fraction of cellular DNA combined with microarray platforms, followed by extensive validation through conventional bisulfite-based analysis. Here, we demonstrate strikingly similar patterns of DNA methylation in non-transformed B[a]PDE-treated cells vs control using high-throughput microarray-based DNA methylation profiling confirmed by conventional bisulfite-based DNA methylation analysis. The absence of aberrant DNA methylation in our model system within a timeframe that precedes cellular transformation suggests that following carcinogen exposure, other as yet unknown factors (secondary to carcinogen treatment) may help initiate global loss of DNA methylation and region-specific gain of DNA methylation, which can, in turn, contribute to lung cancer development. Unveiling the initiating events that cause aberrant DNA methylation in lung cancer has tremendous public health relevance, as it can help define future strategies for early detection and prevention of this highly lethal disease. PMID:20485678

Close-To-Practice Assessment Of Meat Freshness With Metal Oxide Sensor Microarray Electronic Nose

DOE Office of Scientific and Technical Information (OSTI.GOV)

Musatov, V. Yu.; Sysoev, V. V.; Sommer, M.

In this report we estimate the ability of KAMINA e-nose, based on a metal oxide sensor (MOS) microarray and Linear Discriminant Analysis (LDA) pattern recognition, to evaluate meat freshness. The received results show that, 1) one or two exposures of standard meat samples to the e-nose are enough for the instrument to recognize the fresh meat prepared by the same supplier with 100% probability; 2) the meat samples of two kinds, stored at 4 deg. C and 25 deg. C, are mutually recognized at early stages of decay with the help of the LDA model built independently under the e-nosemore » training to each kind of meat; 3) the 3-4 training cycles of exposure to meat from different suppliers are necessary for the e-nose to build a reliable LDA model accounting for the supplier factor. This study approves that the MOS e-nose is ready to be currently utilised in food industry for evaluation of product freshness. The e-nose performance is characterized by low training cost, a confident recognition power of various product decay conditions and easy adjustment to changing conditions.« less

Assessing differential expression in two-color microarrays: a resampling-based empirical Bayes approach.

PubMed

Li, Dongmei; Le Pape, Marc A; Parikh, Nisha I; Chen, Will X; Dye, Timothy D

2013-01-01

Microarrays are widely used for examining differential gene expression, identifying single nucleotide polymorphisms, and detecting methylation loci. Multiple testing methods in microarray data analysis aim at controlling both Type I and Type II error rates; however, real microarray data do not always fit their distribution assumptions. Smyth's ubiquitous parametric method, for example, inadequately accommodates violations of normality assumptions, resulting in inflated Type I error rates. The Significance Analysis of Microarrays, another widely used microarray data analysis method, is based on a permutation test and is robust to non-normally distributed data; however, the Significance Analysis of Microarrays method fold change criteria are problematic, and can critically alter the conclusion of a study, as a result of compositional changes of the control data set in the analysis. We propose a novel approach, combining resampling with empirical Bayes methods: the Resampling-based empirical Bayes Methods. This approach not only reduces false discovery rates for non-normally distributed microarray data, but it is also impervious to fold change threshold since no control data set selection is needed. Through simulation studies, sensitivities, specificities, total rejections, and false discovery rates are compared across the Smyth's parametric method, the Significance Analysis of Microarrays, and the Resampling-based empirical Bayes Methods. Differences in false discovery rates controls between each approach are illustrated through a preterm delivery methylation study. The results show that the Resampling-based empirical Bayes Methods offer significantly higher specificity and lower false discovery rates compared to Smyth's parametric method when data are not normally distributed. The Resampling-based empirical Bayes Methods also offers higher statistical power than the Significance Analysis of Microarrays method when the proportion of significantly differentially expressed genes is large for both normally and non-normally distributed data. Finally, the Resampling-based empirical Bayes Methods are generalizable to next generation sequencing RNA-seq data analysis.

Transfection microarray and the applications.

PubMed

Miyake, Masato; Yoshikawa, Tomohiro; Fujita, Satoshi; Miyake, Jun

2009-05-01

Microarray transfection has been extensively studied for high-throughput functional analysis of mammalian cells. However, control of efficiency and reproducibility are the critical issues for practical use. By using solid-phase transfection accelerators and nano-scaffold, we provide a highly efficient and reproducible microarray-transfection device, "transfection microarray". The device would be applied to the limited number of available primary cells and stem cells not only for large-scale functional analysis but also reporter-based time-lapse cellular event analysis.

Microarray technology for major chemical contaminants analysis in food: current status and prospects.

PubMed

Zhang, Zhaowei; Li, Peiwu; Hu, Xiaofeng; Zhang, Qi; Ding, Xiaoxia; Zhang, Wen

2012-01-01

Chemical contaminants in food have caused serious health issues in both humans and animals. Microarray technology is an advanced technique suitable for the analysis of chemical contaminates. In particular, immuno-microarray approach is one of the most promising methods for chemical contaminants analysis. The use of microarrays for the analysis of chemical contaminants is the subject of this review. Fabrication strategies and detection methods for chemical contaminants are discussed in detail. Application to the analysis of mycotoxins, biotoxins, pesticide residues, and pharmaceutical residues is also described. Finally, future challenges and opportunities are discussed.

Alteration of Gene Expression, DNA Methylation, and Histone Methylation in Free Radical Scavenging Networks in Adult Mouse Hippocampus following Fetal Alcohol Exposure.

PubMed

Chater-Diehl, Eric J; Laufer, Benjamin I; Castellani, Christina A; Alberry, Bonnie L; Singh, Shiva M

2016-01-01

The molecular basis of Fetal Alcohol Spectrum Disorders (FASD) is poorly understood; however, epigenetic and gene expression changes have been implicated. We have developed a mouse model of FASD characterized by learning and memory impairment and persistent gene expression changes. Epigenetic marks may maintain expression changes over a mouse's lifetime, an area few have explored. Here, mice were injected with saline or ethanol on postnatal days four and seven. At 70 days of age gene expression microarray, methylated DNA immunoprecipitation microarray, H3K4me3 and H3K27me3 chromatin immunoprecipitation microarray were performed. Following extensive pathway analysis of the affected genes, we identified the top affected gene expression pathway as "Free radical scavenging". We confirmed six of these changes by droplet digital PCR including the caspase Casp3 and Wnt transcription factor Tcf7l2. The top pathway for all methylation-affected genes was "Peroxisome biogenesis"; we confirmed differential DNA methylation in the Acca1 thiolase promoter. Altered methylation and gene expression in oxidative stress pathways in the adult hippocampus suggests a novel interface between epigenetic and oxidative stress mechanisms in FASD.

Prenatal metformin exposure in mice programs the metabolic phenotype of the offspring during a high fat diet at adulthood.

PubMed

Salomäki, Henriikka; Vähätalo, Laura H; Laurila, Kirsti; Jäppinen, Norma T; Penttinen, Anna-Maija; Ailanen, Liisa; Ilyasizadeh, Juan; Pesonen, Ullamari; Koulu, Markku

2013-01-01

The antidiabetic drug metformin is currently used prior and during pregnancy for polycystic ovary syndrome, as well as during gestational diabetes mellitus. We investigated the effects of prenatal metformin exposure on the metabolic phenotype of the offspring during adulthood in mice. Metformin (300 mg/kg) or vehicle was administered orally to dams on regular diet from the embryonic day E0.5 to E17.5. Gene expression profiles in liver and brain were analysed from 4-day old offspring by microarray. Body weight development and several metabolic parameters of offspring were monitored both during regular diet (RD-phase) and high fat diet (HFD-phase). At the end of the study, two doses of metformin or vehicle were given acutely to mice at the age of 20 weeks, and Insig-1 and GLUT4 mRNA expressions in liver and fat tissue were analysed using qRT-PCR. Metformin exposed fetuses were lighter at E18.5. There was no effect of metformin on the maternal body weight development or food intake. Metformin exposed offspring gained more body weight and mesenteric fat during the HFD-phase. The male offspring also had impaired glucose tolerance and elevated fasting glucose during the HFD-phase. Moreover, the expression of GLUT4 mRNA was down-regulated in epididymal fat in male offspring prenatally exposed to metformin. Based on the microarray and subsequent qRT-PCR analyses, the expression of Insig-1 was changed in the liver of neonatal mice exposed to metformin prenatally. Furthermore, metformin up-regulated the expression of Insig-1 later in development. Gene set enrichment analysis based on preliminary microarray data identified several differentially enriched pathways both in control and metformin exposed mice. The present study shows that prenatal metformin exposure causes long-term programming effects on the metabolic phenotype during high fat diet in mice. This should be taken into consideration when using metformin as a therapeutic agent during pregnancy.

DEVELOPMENT OF DNA MICROARRAYS FOR ECOLOGICAL EXPOSURE ASSESSMENT

EPA Science Inventory

EPA/ORD is moving forward with a computational toxicology initiative in FY 04 which aims to integrate genomics and computational methods to provide a mechanistic basis for prediction of exposure and effects of chemical stressors in the environment.

The goal of the presen...

Contributions to Statistical Problems Related to Microarray Data

ERIC Educational Resources Information Center

Hong, Feng

2009-01-01

Microarray is a high throughput technology to measure the gene expression. Analysis of microarray data brings many interesting and challenging problems. This thesis consists three studies related to microarray data. First, we propose a Bayesian model for microarray data and use Bayes Factors to identify differentially expressed genes. Second, we…

Microarray platform for omics analysis

NASA Astrophysics Data System (ADS)

Mecklenburg, Michael; Xie, Bin

2001-09-01

Microarray technology has revolutionized genetic analysis. However, limitations in genome analysis has lead to renewed interest in establishing 'omic' strategies. As we enter the post-genomic era, new microarray technologies are needed to address these new classes of 'omic' targets, such as proteins, as well as lipids and carbohydrates. We have developed a microarray platform that combines self- assembling monolayers with the biotin-streptavidin system to provide a robust, versatile immobilization scheme. A hydrophobic film is patterned on the surface creating an array of tension wells that eliminates evaporation effects thereby reducing the shear stress to which biomolecules are exposed to during immobilization. The streptavidin linker layer makes it possible to adapt and/or develop microarray based assays using virtually any class of biomolecules including: carbohydrates, peptides, antibodies, receptors, as well as them ore traditional DNA based arrays. Our microarray technology is designed to furnish seamless compatibility across the various 'omic' platforms by providing a common blueprint for fabricating and analyzing arrays. The prototype microarray uses a microscope slide footprint patterned with 2 by 96 flat wells. Data on the microarray platform will be presented.

Microarrays in brain research: the good, the bad and the ugly.

PubMed

Mirnics, K

2001-06-01

Making sense of microarray data is a complex process, in which the interpretation of findings will depend on the overall experimental design and judgement of the investigator performing the analysis. As a result, differences in tissue harvesting, microarray types, sample labelling and data analysis procedures make post hoc sharing of microarray data a great challenge. To ensure rapid and meaningful data exchange, we need to create some order out of the existing chaos. In these ground-breaking microarray standardization and data sharing efforts, NIH agencies should take a leading role

Sodium metavanadate exhibits carcinogenic tendencies in vitro in immortalized human bronchial epithelial cells.

PubMed

Passantino, Lisa; Muñoz, Alexandra B; Costa, Max

2013-10-01

Pentavalent vanadium compounds induce intracellular changes in vitro that are consistent with those of other carcinogenic substances. While there is no clear evidence that vanadium compounds cause cancer in humans, vanadium pentoxide causes lung cancer in rodents after long-term inhalation exposures and in turn IARC has categorized it as a group 2B possible human carcinogen. The goal of this study was to investigate the carcinogenicity of NaVO3 in the human immortalized bronchial epithelial cell line, Beas-2B. Cells were treated with 10 μM NaVO3 for 5 weeks, with or without recovery time, followed by gene expression microarray analysis. In a separate experiment, cells were exposed to 1-10 μM NaVO3 for 4 weeks and then grown in soft agar to test for anchorage-independent growth. A dose-dependent increase in the number of colonies was observed. In scratch tests, NaVO3-transformed clones could repair a wound faster than controls. In a gene expression microarray analysis of soft agar clones there were 2010 differentially expressed genes (DEG) (adjusted p-value ≤ 0.05) in NaVO3-transformed clones relative to control clones. DEG from this experiment were compared with the DEG of 5 week NaVO3 exposure with or without recovery, all with adjusted p-values < 0.05, and 469 genes were altered in the same direction for transformed clones, 5 week NaVO3-treated cells, and the recovered cells. The data from this study imply that chronic exposure to NaVO3 causes changes that are consistent with cellular transformation including anchorage-independent growth, enhanced migration ability, and gene expression changes that were likely epigenetically inherited.

Gene expression profiling of the effects of organic dust in lung epithelial and THP-1 cells reveals inductive effects on inflammatory and immune response genes

PubMed Central

Loose, David S.; Gottipati, Koteswara R.; Natarajan, Kartiga; Mitchell, Courtney T.

2016-01-01

The intensification and concentration of animal production operations expose workers to high levels of organic dusts in the work environment. Exposure to organic dusts is a risk factor for the development of acute and chronic respiratory symptoms and diseases. Lung epithelium plays important roles in the control of immune and inflammatory responses to environmental agents to maintain lung health. To better understand the effects of organic dust on lung inflammatory responses, we characterized the gene expression profiles of A549 alveolar and Beas2B bronchial epithelial and THP-1 monocytic cells influenced by exposure to poultry dust extract by DNA microarray analysis using Illumina Human HT-12 v4 Expression BeadChip. We found that A549 alveolar and Beas2B bronchial epithelial and THP-1 cells responded with unique changes in the gene expression profiles with regulation of genes encoding inflammatory cytokines, chemokines, and other inflammatory proteins being common to all the three cells. Significantly induced genes included IL-8, IL-6, IL-1β, ICAM-1, CCL2, CCL5, TLR4, and PTGS2. Validation by real-time qRT-PCR, ELISA, Western immunoblotting, and immunohistochemical staining of lung sections from mice exposed to dust extract validated DNA microarray results. Pathway analysis indicated that dust extract induced changes in gene expression influenced functions related to cellular growth and proliferation, cell death and survival, and cellular development. These data show that a broad range of inflammatory mediators produced in response to poultry dust exposure can modulate lung immune and inflammatory responses. This is the first report on organic dust induced changes in expression profiles in lung epithelial and THP-1 monocytic cells. PMID:26884459

HDBStat!: a platform-independent software suite for statistical analysis of high dimensional biology data.

PubMed

Trivedi, Prinal; Edwards, Jode W; Wang, Jelai; Gadbury, Gary L; Srinivasasainagendra, Vinodh; Zakharkin, Stanislav O; Kim, Kyoungmi; Mehta, Tapan; Brand, Jacob P L; Patki, Amit; Page, Grier P; Allison, David B

2005-04-06

Many efforts in microarray data analysis are focused on providing tools and methods for the qualitative analysis of microarray data. HDBStat! (High-Dimensional Biology-Statistics) is a software package designed for analysis of high dimensional biology data such as microarray data. It was initially developed for the analysis of microarray gene expression data, but it can also be used for some applications in proteomics and other aspects of genomics. HDBStat! provides statisticians and biologists a flexible and easy-to-use interface to analyze complex microarray data using a variety of methods for data preprocessing, quality control analysis and hypothesis testing. Results generated from data preprocessing methods, quality control analysis and hypothesis testing methods are output in the form of Excel CSV tables, graphs and an Html report summarizing data analysis. HDBStat! is a platform-independent software that is freely available to academic institutions and non-profit organizations. It can be downloaded from our website http://www.soph.uab.edu/ssg_content.asp?id=1164.

Meta-analysis of studies using suppression subtractive hybridization and microarrays to investigate the effects of environmental stress on gene transcription in oysters.

PubMed

Anderson, Kelli; Taylor, Daisy A; Thompson, Emma L; Melwani, Aroon R; Nair, Sham V; Raftos, David A

2015-01-01

Many microarray and suppression subtractive hybridization (SSH) studies have analyzed the effects of environmental stress on gene transcription in marine species. However, there have been no unifying analyses of these data to identify common stress response pathways. To address this shortfall, we conducted a meta-analysis of 14 studies that investigated the effects of different environmental stressors on gene expression in oysters. The stressors tested included chemical contamination, hypoxia and infection, as well as extremes of temperature, pH and turbidity. We found that the expression of over 400 genes in a range of oyster species changed significantly after exposure to environmental stress. A repeating pattern was evident in these transcriptional responses, regardless of the type of stress applied. Many of the genes that responded to environmental stress encoded proteins involved in translation and protein processing (including molecular chaperones), the mitochondrial electron transport chain, anti-oxidant activity and the cytoskeleton. In light of these findings, we put forward a consensus model of sub-cellular stress responses in oysters.

Alteration of estrogen-regulated gene expression in human cells induced by the agricultural and horticultural herbicide glyphosate.

PubMed

Hokanson, R; Fudge, R; Chowdhary, R; Busbee, D

2007-09-01

Gene expression is altered in mammalian cells (MCF-7 cells), by exposure to a variety of chemicals that mimic steroid hormones or interact with endocrine receptors or their co-factors. Among those populations chronically exposed to these endocrine disruptive chemicals are persons, and their families, who are employed in agriculture or horticulture, or who use agricultural/horticultural chemicals. Among the chemicals most commonly used, both commercially and in the home, is the herbicide glyphosate. Although glyphosate is commonly considered to be relatively non-toxic, we utilized in vitro DNA microarray analysis of this chemical to evaluate its capacity to alter the expression of a variety of genes in human cells. We selected a group of genes, determined by DNA microarray analysis to be dysregulated, and used quantitative real-time PCR to corroborate their altered states of expression. We discussed the reported function of those genes, with emphasis on altered physiological states that are capable of initiating adverse health effects that might be anticipated if gene expression were significantly altered in either adults or embryos exposed in utero.

Meta-Analysis of Studies Using Suppression Subtractive Hybridization and Microarrays to Investigate the Effects of Environmental Stress on Gene Transcription in Oysters

PubMed Central

Thompson, Emma L.; Melwani, Aroon R.; Nair, Sham V.; Raftos, David A.

2015-01-01

Many microarray and suppression subtractive hybridization (SSH) studies have analyzed the effects of environmental stress on gene transcription in marine species. However, there have been no unifying analyses of these data to identify common stress response pathways. To address this shortfall, we conducted a meta-analysis of 14 studies that investigated the effects of different environmental stressors on gene expression in oysters. The stressors tested included chemical contamination, hypoxia and infection, as well as extremes of temperature, pH and turbidity. We found that the expression of over 400 genes in a range of oyster species changed significantly after exposure to environmental stress. A repeating pattern was evident in these transcriptional responses, regardless of the type of stress applied. Many of the genes that responded to environmental stress encoded proteins involved in translation and protein processing (including molecular chaperones), the mitochondrial electron transport chain, anti-oxidant activity and the cytoskeleton. In light of these findings, we put forward a consensus model of sub-cellular stress responses in oysters. PMID:25768438

Differential gene expression associated with dietary methylmercury (MeHg) exposure in rainbow trout (Oncorhynchus mykiss) and zebrafish (Danio rerio)

PubMed Central

Liu, Qing; Basu, Niladri; Goetz, Giles; Jiang, Nan; Hutz, Reinhold J.; Tonellato, Peter J.; Carvan, Michael J.

2013-01-01

The objective of this study was to identify and evaluate conserved biomarkers that could be used in most species of teleost fish at most life-stages. We investigated the effects of sublethal methylmercury (MeHg) exposure on developing rainbow trout and zebrafish. Juvenile rainbow trout and young adult zebrafish were fed food with MeHg added at 0, 0.5, 5 and 50 ppm. Atomic absorption spectrometry was applied to measure whole body total Hg levels, and pathologic analysis was performed to identify MeHg-induced toxicity. Fish at six weeks were sampled from each group for microarray analysis using RNA from whole fish. MeHg-exposed trout and zebrafish did not show overt signs of toxicity or pathology, nor were significant differences seen in mortality, length, mass, or condition factor. The accumulation of MeHg in trout and zebrafish exhibited dose- and time-dependent patterns during six weeks, and zebrafish exhibited greater assimilation of total Hg than rainbow trout. The dysregulated genes in MeHg-treated fish have multiple functional annotations, such as iron ion homeostasis, glutathione transferase activity, regulation of muscle contraction, troponin I binding and calcium-dependent protein binding. Genes were selected as biomarker candidates based on their microarray data and their expression was evaluated by QPCR. Unfortunately, these genes are not good consistent biomarkers for both rainbow trout and zebrafish from QPCR evaluation using individual fish. Our conclusion is that biomarker analysis for aquatic toxicant assessment using fish needs to be based on tissue-, sex- and species-specific consideration. PMID:23529582

Impact of developmental lead exposure on splenic factors

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kasten-Jolly, Jane, E-mail: kjolly@wadsworth.or; Heo, Yong, E-mail: yheo@cu.ac.k; Lawrence, David A., E-mail: david.lawrence@wadsworth.or

2010-09-01

Lead (Pb) is known to alter the functions of numerous organ systems, including the hematopoietic and immune systems. Pb can induce anemia and can lower host resistance to bacterial and viral infections. The anemia is due to Pb's inhibition of hemoglobin synthesis and Pb's induction of membrane changes, leading to early erythrocyte senescence. Pb also increases B-cell activation/proliferation and skews T-cell help (Th) toward Th2 subset generation. The specific mechanisms for many of the Pb effects are, as yet, not completely understood. Therefore, we performed gene expression analysis, via microarray, on RNA from the spleens of developmentally Pb-exposed mice, inmore » order to gain further insight into these Pb effects. Splenic RNA microarray analysis indicated strong up-regulation of genes coding for proteolytic enzymes, lipases, amylase, and RNaseA. The data also showed that Pb affected the expression of many genes associated with innate immunity. Analysis of the microarray results via GeneSifter software indicated that Pb increased apoptosis, B-cell differentiation, and Th2 development. Direct up-regulation by Pb of expression of the gene encoding the heme-regulated inhibitor (HRI) suggested that Pb can decrease erythropoiesis by blocking globin mRNA translation. Pb's high elevation of digestive/catabolizing enzymes could generate immunogenic self peptides. With Pb's potential to induce new self-peptides and to enhance the expression of caspases, cytokines, and other immunomodulators, further evaluation of Pb's involvement in autoimmune phenomena, especially Th2-mediated autoantibody production, and alteration of organ system activities is warranted.« less

ArrayNinja: An Open Source Platform for Unified Planning and Analysis of Microarray Experiments.

PubMed

Dickson, B M; Cornett, E M; Ramjan, Z; Rothbart, S B

2016-01-01

Microarray-based proteomic platforms have emerged as valuable tools for studying various aspects of protein function, particularly in the field of chromatin biochemistry. Microarray technology itself is largely unrestricted in regard to printable material and platform design, and efficient multidimensional optimization of assay parameters requires fluidity in the design and analysis of custom print layouts. This motivates the need for streamlined software infrastructure that facilitates the combined planning and analysis of custom microarray experiments. To this end, we have developed ArrayNinja as a portable, open source, and interactive application that unifies the planning and visualization of microarray experiments and provides maximum flexibility to end users. Array experiments can be planned, stored to a private database, and merged with the imaged results for a level of data interaction and centralization that is not currently attainable with available microarray informatics tools. © 2016 Elsevier Inc. All rights reserved.

WebArray: an online platform for microarray data analysis

PubMed Central

Xia, Xiaoqin; McClelland, Michael; Wang, Yipeng

2005-01-01

Background Many cutting-edge microarray analysis tools and algorithms, including commonly used limma and affy packages in Bioconductor, need sophisticated knowledge of mathematics, statistics and computer skills for implementation. Commercially available software can provide a user-friendly interface at considerable cost. To facilitate the use of these tools for microarray data analysis on an open platform we developed an online microarray data analysis platform, WebArray, for bench biologists to utilize these tools to explore data from single/dual color microarray experiments. Results The currently implemented functions were based on limma and affy package from Bioconductor, the spacings LOESS histogram (SPLOSH) method, PCA-assisted normalization method and genome mapping method. WebArray incorporates these packages and provides a user-friendly interface for accessing a wide range of key functions of limma and others, such as spot quality weight, background correction, graphical plotting, normalization, linear modeling, empirical bayes statistical analysis, false discovery rate (FDR) estimation, chromosomal mapping for genome comparison. Conclusion WebArray offers a convenient platform for bench biologists to access several cutting-edge microarray data analysis tools. The website is freely available at . It runs on a Linux server with Apache and MySQL. PMID:16371165

Temporal patterns in the transcriptomic response of rainbow trout, Oncorhynchus mykiss, to crude oil.

PubMed

Hook, Sharon E; Lampi, Mark A; Febbo, Eric J; Ward, Jeff A; Parkerton, Thomas F

2010-09-01

Time is often not characterized as a variable in ecotoxicogenomic studies. In this study, temporal changes in gene expression were determined during exposure to crude oil and a subsequent recovery period. Juvenile rainbow trout, Oncorhynchus mykiss, were exposed for 96 h to the water accommodated fractions of 0.4, 2 or 10 mgl(-1) crude oil loadings. Following 96 h of exposure, fish were transferred to recovery tanks. Gill and liver samples were collected after 24 and 96 h of exposure, and after 96 h of recovery for RNA extraction and microarray analysis. Fluorescently labeled cDNA was hybridized against matched controls, using salmonid cDNA arrays. Each exposure scenario generated unique patterns of altered gene expression. More genes responded to crude oil in the gill than in the liver. In the gill, 1137 genes had altered expression at 24 h, 2003 genes had altered expression levels at 96 h of exposure, yet by 96 h of recovery, no genes were significantly altered in expression. In the liver at 10 mgl(-1), only five genes were changed at 24 h, yet 192 genes had altered expression after 96 h recovery. At 2 mgl(-1) in the liver, many genes had altered regulation at all three time points. The 0.4 mgl(-1) loading also showed 289 genes upregulated at 24 h after exposure. The Gene Ontology terms associated with altered expression in the liver suggested that the processes of protein synthesis, xenobiotic metabolism, and oxidoreductase activity were altered. The concentration-responsive expression profile of cytochrome P450 1A, a biomarker for oil exposure, did not predict the majority of gene expression profiles in any tissue or dose, since direct relationships with dose were not observed for most genes. While the genes and their associated functions agree with known modes of toxic action for crude oil, the gene lists obtained do not match our previously published work, presumably due to array analysis procedures. These results demonstrate that changes in gene expression with time and dose may be complicated, and should be characterized in controlled laboratory settings before attempts are made to interpret responses in field-collected organisms. Further, processes for analyzing microarray data need to be developed such that standardized gene lists are developed, or that analysis does not rely on lists of significantly altered genes before arrays can be further evaluated as a monitoring tool. Crown Copyright 2010. Published by Elsevier B.V. All rights reserved.

Alteration of gene expression by alcohol exposure at early neurulation.

PubMed

Zhou, Feng C; Zhao, Qianqian; Liu, Yunlong; Goodlett, Charles R; Liang, Tiebing; McClintick, Jeanette N; Edenberg, Howard J; Li, Lang

2011-02-21

We have previously demonstrated that alcohol exposure at early neurulation induces growth retardation, neural tube abnormalities, and alteration of DNA methylation. To explore the global gene expression changes which may underline these developmental defects, microarray analyses were performed in a whole embryo mouse culture model that allows control over alcohol and embryonic variables. Alcohol caused teratogenesis in brain, heart, forelimb, and optic vesicle; a subset of the embryos also showed cranial neural tube defects. In microarray analysis (accession number GSM9545), adopting hypothesis-driven Gene Set Enrichment Analysis (GSEA) informatics and intersection analysis of two independent experiments, we found that there was a collective reduction in expression of neural specification genes (neurogenin, Sox5, Bhlhe22), neural growth factor genes [Igf1, Efemp1, Klf10 (Tieg), and Edil3], and alteration of genes involved in cell growth, apoptosis, histone variants, eye and heart development. There was also a reduction of retinol binding protein 1 (Rbp1), and de novo expression of aldehyde dehydrogenase 1B1 (Aldh1B1). Remarkably, four key hematopoiesis genes (glycophorin A, adducin 2, beta-2 microglobulin, and ceruloplasmin) were absent after alcohol treatment, and histone variant genes were reduced. The down-regulation of the neurospecification and the neurotrophic genes were further confirmed by quantitative RT-PCR. Furthermore, the gene expression profile demonstrated distinct subgroups which corresponded with two distinct alcohol-related neural tube phenotypes: an open (ALC-NTO) and a closed neural tube (ALC-NTC). Further, the epidermal growth factor signaling pathway and histone variants were specifically altered in ALC-NTO, and a greater number of neurotrophic/growth factor genes were down-regulated in the ALC-NTO than in the ALC-NTC embryos. This study revealed a set of genes vulnerable to alcohol exposure and genes that were associated with neural tube defects during early neurulation.

Comparison of gene expression responses to hypoxia in viviparous (Xiphophorus) and oviparous (Oryzias) fishes using a medaka microarray.

PubMed

Boswell, Mikki G; Wells, Melissa C; Kirk, Lyndsey M; Ju, Zhenlin; Zhang, Ziping; Booth, Rachell E; Walter, Ronald B

2009-03-01

Gene expression profiling using DNA microarray technology is a useful tool for assessing gene transcript level responses after an organism is exposed to environmental stress. Herein, we detail results from studies using an 8 k medaka (Oryzias latipes) microarray to assess modulated gene expression patterns upon hypoxia exposure of the live-bearing aquaria fish, Xiphophorus maculatus. To assess the reproducibility and reliability of using the medaka array in cross-genus hybridization, a two-factor ANOVA analysis of gene expression was employed. The data show the tissue source of the RNA used for array hybridization contributed more to the observed response of modulated gene targets than did the species source of the RNA. In addition, hierarchical clustering via heat map analyses of groupings of tissues and species (Xiphophorus and medaka) suggests that hypoxia induced similar responses in the same tissues from these two diverse aquatic model organisms. Our Xiphophorus results indicate 206 brain, 37 liver, and 925 gill gene targets exhibit hypoxia induced expression changes. Analysis of the Xiphophorus data to determine those features exhibiting a significant (p<0.05)+/-3 fold change produced only two gene targets within brain tissue and 80 features within gill tissue. Of these 82 characterized features, 39 were identified via homology searching (cut-off E-value of 1 x 10(-5)) and placed into one or more biological process gene ontology groups. Among these 39 genes, metabolic energy changes and manipulation was the most affected biological pathway (13 genes).

Issues in the analysis of oligonucleotide tiling microarrays for transcript mapping

NASA Technical Reports Server (NTRS)

Royce, Thomas E.; Rozowsky, Joel S.; Bertone, Paul; Samanta, Manoj; Stolc, Viktor; Weissman, Sherman; Snyder, Michael; Gerstein, Mark

2005-01-01

Traditional microarrays use probes complementary to known genes to quantitate the differential gene expression between two or more conditions. Genomic tiling microarray experiments differ in that probes that span a genomic region at regular intervals are used to detect the presence or absence of transcription. This difference means the same sets of biases and the methods for addressing them are unlikely to be relevant to both types of experiment. We introduce the informatics challenges arising in the analysis of tiling microarray experiments as open problems to the scientific community and present initial approaches for the analysis of this nascent technology.

Effects of subchronic benzo(a)pyrene exposure on neurotransmitter receptor gene expression in the rat hippocampus related with spatial learning and memory change.

PubMed

Qiu, Chongying; Cheng, Shuqun; Xia, Yinyin; Peng, Bin; Tang, Qian; Tu, Baijie

2011-11-18

Exposure of laboratory rats to Benzo(a)pyrene (BaP), an environmental contaminant with its high lipophilicify which is widely dispersed in the environment and can easily cross the blood brain barrier presenting in the central nervous system, is associated with impaired learning and memory. The purpose of the research was to examine whether subchronic exposure to BaP affects spatial learning and memory, and how it alters normal gene expression in hippocampus, as well as selection of candidate genes involving neurotransmitter receptor attributed to learning and memory. Morris water maze (MWM) was used to evaluate behavioral differences between BaP-treated and vehicle-treated groups. To gain a better insight into the mechanism of BaP-induced neurotoxicity on learning and memory, we used whole genome oligo microarrays as well as Polymerase Chain Reaction (PCR) to assess the global impact of gene expression. Male Sprague-Dawley rats were intraperitoneally injected with 6.25mg/kg of BaP or vehicle for 14 weeks. The results from the Morris water maze (MWM) test showed that rats treated with BaP exhibited significantly higher mean latencies as compared to vehicle controls. BaP exposure significantly decreased the number of crossing the platform and the time spent in the target area. After the hippocampus was collected from each rat, total RNA was isolated. Microarray and PCR revealed that exposure to BaP affected mRNA expression of neurotransmitter receptors. The web tool DAVID was used to analyze the significantly enriched gene ontology (GO) and KEGG pathways in the differentially expressed genes. Analysis showed that the most significantly affected gene ontology category was behavior. Furthermore, the fourth highest significantly affected gene ontology category was learning and memory. KEGG molecular pathway analysis showed that "neuroactive ligand-receptor interaction" was affected by BaP with highest statistical significance, and 9 candidate neurotransmitter receptor genes involving learning and memory were selected out. Our results revealed a close link between behavioral changes and altered neurotransmitter receptor gene expression in BaP-treated rats. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

The Development of Protein Microarrays and Their Applications in DNA-Protein and Protein-Protein Interaction Analyses of Arabidopsis Transcription Factors

PubMed Central

Gong, Wei; He, Kun; Covington, Mike; Dinesh-Kumar, S. P.; Snyder, Michael; Harmer, Stacey L.; Zhu, Yu-Xian; Deng, Xing Wang

2009-01-01

We used our collection of Arabidopsis transcription factor (TF) ORFeome clones to construct protein microarrays containing as many as 802 TF proteins. These protein microarrays were used for both protein-DNA and protein-protein interaction analyses. For protein-DNA interaction studies, we examined AP2/ERF family TFs and their cognate cis-elements. By careful comparison of the DNA-binding specificity of 13 TFs on the protein microarray with previous non-microarray data, we showed that protein microarrays provide an efficient and high throughput tool for genome-wide analysis of TF-DNA interactions. This microarray protein-DNA interaction analysis allowed us to derive a comprehensive view of DNA-binding profiles of AP2/ERF family proteins in Arabidopsis. It also revealed four TFs that bound the EE (evening element) and had the expected phased gene expression under clock-regulation, thus providing a basis for further functional analysis of their roles in clock regulation of gene expression. We also developed procedures for detecting protein interactions using this TF protein microarray and discovered four novel partners that interact with HY5, which can be validated by yeast two-hybrid assays. Thus, plant TF protein microarrays offer an attractive high-throughput alternative to traditional techniques for TF functional characterization on a global scale. PMID:19802365

Karyotype versus microarray testing for genetic abnormalities after stillbirth.

PubMed

Reddy, Uma M; Page, Grier P; Saade, George R; Silver, Robert M; Thorsten, Vanessa R; Parker, Corette B; Pinar, Halit; Willinger, Marian; Stoll, Barbara J; Heim-Hall, Josefine; Varner, Michael W; Goldenberg, Robert L; Bukowski, Radek; Wapner, Ronald J; Drews-Botsch, Carolyn D; O'Brien, Barbara M; Dudley, Donald J; Levy, Brynn

2012-12-06

Genetic abnormalities have been associated with 6 to 13% of stillbirths, but the true prevalence may be higher. Unlike karyotype analysis, microarray analysis does not require live cells, and it detects small deletions and duplications called copy-number variants. The Stillbirth Collaborative Research Network conducted a population-based study of stillbirth in five geographic catchment areas. Standardized postmortem examinations and karyotype analyses were performed. A single-nucleotide polymorphism array was used to detect copy-number variants of at least 500 kb in placental or fetal tissue. Variants that were not identified in any of three databases of apparently unaffected persons were then classified into three groups: probably benign, clinical significance unknown, or pathogenic. We compared the results of karyotype and microarray analyses of samples obtained after delivery. In our analysis of samples from 532 stillbirths, microarray analysis yielded results more often than did karyotype analysis (87.4% vs. 70.5%, P<0.001) and provided better detection of genetic abnormalities (aneuploidy or pathogenic copy-number variants, 8.3% vs. 5.8%; P=0.007). Microarray analysis also identified more genetic abnormalities among 443 antepartum stillbirths (8.8% vs. 6.5%, P=0.02) and 67 stillbirths with congenital anomalies (29.9% vs. 19.4%, P=0.008). As compared with karyotype analysis, microarray analysis provided a relative increase in the diagnosis of genetic abnormalities of 41.9% in all stillbirths, 34.5% in antepartum stillbirths, and 53.8% in stillbirths with anomalies. Microarray analysis is more likely than karyotype analysis to provide a genetic diagnosis, primarily because of its success with nonviable tissue, and is especially valuable in analyses of stillbirths with congenital anomalies or in cases in which karyotype results cannot be obtained. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development.).

Emerging Use of Gene Expression Microarrays in Plant Physiology

DOE PAGES

Wullschleger, Stan D.; Difazio, Stephen P.

2003-01-01

Microarrays have become an important technology for the global analysis of gene expression in humans, animals, plants, and microbes. Implemented in the context of a well-designed experiment, cDNA and oligonucleotide arrays can provide highthroughput, simultaneous analysis of transcript abundance for hundreds, if not thousands, of genes. However, despite widespread acceptance, the use of microarrays as a tool to better understand processes of interest to the plant physiologist is still being explored. To help illustrate current uses of microarrays in the plant sciences, several case studies that we believe demonstrate the emerging application of gene expression arrays in plant physiology weremore » selected from among the many posters and presentations at the 2003 Plant and Animal Genome XI Conference. Based on this survey, microarrays are being used to assess gene expression in plants exposed to the experimental manipulation of air temperature, soil water content and aluminium concentration in the root zone. Analysis often includes characterizing transcript profiles for multiple post-treatment sampling periods and categorizing genes with common patterns of response using hierarchical clustering techniques. In addition, microarrays are also providing insights into developmental changes in gene expression associated with fibre and root elongation in cotton and maize, respectively. Technical and analytical limitations of microarrays are discussed and projects attempting to advance areas of microarray design and data analysis are highlighted. Finally, although much work remains, we conclude that microarrays are a valuable tool for the plant physiologist interested in the characterization and identification of individual genes and gene families with potential application in the fields of agriculture, horticulture and forestry.« less

Gene expression profiling in rat kidney after intratracheal exposure to cadmium-doped nanoparticles

NASA Astrophysics Data System (ADS)

Coccini, Teresa; Roda, Elisa; Fabbri, Marco; Sacco, Maria Grazia; Gribaldo, Laura; Manzo, Luigi

2012-08-01

While nephrotoxicity of cadmium is well documented, very limited information exists on renal effects of exposure to cadmium-containing nanomaterials. In this work, "omics" methodologies have been used to assess the action of cadmium-containing silica nanoparticles (Cd-SiNPs) in the kidney of Sprague-Dawley rats exposed intratracheally. Groups of animals received a single dose of Cd-SiNPs (1 mg/rat), CdCl2 (400 μg/rat) or 0.1 ml saline (control). Renal gene expression was evaluated 7 and 30 days post exposure by DNA microarray technology using the Agilent Whole Rat Genome Microarray 4x44K. Gene modulating effects were observed in kidney at both time periods after treatment with Cd-SiNPs. The number of differentially expressed genes being 139 and 153 at the post exposure days 7 and 30, respectively. Renal gene expression changes were also observed in the kidney of CdCl2-treated rats with a total of 253 and 70 probes modulated at 7 and 30 days, respectively. Analysis of renal gene expression profiles at day 7 indicated in both Cd-SiNP and CdCl2 groups downregulation of several cluster genes linked to immune function, oxidative stress, and inflammation processes. Differing from day 7, the majority of cluster gene categories modified by nanoparticles in kidney 30 days after dosing were genes implicated in cell regulation and apoptosis. Modest renal gene expression changes were observed at day 30 in rats treated with CdCl2. These results indicate that kidney may be a susceptible target for subtle long-lasting molecular alterations produced by cadmium nanoparticles locally instilled in the lung.

A genome-wide 20 K citrus microarray for gene expression analysis

PubMed Central

Martinez-Godoy, M Angeles; Mauri, Nuria; Juarez, Jose; Marques, M Carmen; Santiago, Julia; Forment, Javier; Gadea, Jose

2008-01-01

Background Understanding of genetic elements that contribute to key aspects of citrus biology will impact future improvements in this economically important crop. Global gene expression analysis demands microarray platforms with a high genome coverage. In the last years, genome-wide EST collections have been generated in citrus, opening the possibility to create new tools for functional genomics in this crop plant. Results We have designed and constructed a publicly available genome-wide cDNA microarray that include 21,081 putative unigenes of citrus. As a functional companion to the microarray, a web-browsable database [1] was created and populated with information about the unigenes represented in the microarray, including cDNA libraries, isolated clones, raw and processed nucleotide and protein sequences, and results of all the structural and functional annotation of the unigenes, like general description, BLAST hits, putative Arabidopsis orthologs, microsatellites, putative SNPs, GO classification and PFAM domains. We have performed a Gene Ontology comparison with the full set of Arabidopsis proteins to estimate the genome coverage of the microarray. We have also performed microarray hybridizations to check its usability. Conclusion This new cDNA microarray replaces the first 7K microarray generated two years ago and allows gene expression analysis at a more global scale. We have followed a rational design to minimize cross-hybridization while maintaining its utility for different citrus species. Furthermore, we also provide access to a website with full structural and functional annotation of the unigenes represented in the microarray, along with the ability to use this site to directly perform gene expression analysis using standard tools at different publicly available servers. Furthermore, we show how this microarray offers a good representation of the citrus genome and present the usefulness of this genomic tool for global studies in citrus by using it to catalogue genes expressed in citrus globular embryos. PMID:18598343

THE PATH FROM MOLECULAR INDICATORS OF EXPOSURE TO DESCRIBING DYNAMIC BIOLOGICAL SYSTEMS IN AN AQUATIC ORGANISM: MICROARRAYS AND THE FATHEAD MINNOW

EPA Science Inventory

The extent to which humans and wildlife are exposed to toxicants is an important focus of environmental research. This work has been directed toward the development of molecular indicators diagnostic for exposure to various stressors in freshwater fish. Research includes the di...

A Java-based tool for the design of classification microarrays.

PubMed

Meng, Da; Broschat, Shira L; Call, Douglas R

2008-08-04

Classification microarrays are used for purposes such as identifying strains of bacteria and determining genetic relationships to understand the epidemiology of an infectious disease. For these cases, mixed microarrays, which are composed of DNA from more than one organism, are more effective than conventional microarrays composed of DNA from a single organism. Selection of probes is a key factor in designing successful mixed microarrays because redundant sequences are inefficient and limited representation of diversity can restrict application of the microarray. We have developed a Java-based software tool, called PLASMID, for use in selecting the minimum set of probe sequences needed to classify different groups of plasmids or bacteria. The software program was successfully applied to several different sets of data. The utility of PLASMID was illustrated using existing mixed-plasmid microarray data as well as data from a virtual mixed-genome microarray constructed from different strains of Streptococcus. Moreover, use of data from expression microarray experiments demonstrated the generality of PLASMID. In this paper we describe a new software tool for selecting a set of probes for a classification microarray. While the tool was developed for the design of mixed microarrays-and mixed-plasmid microarrays in particular-it can also be used to design expression arrays. The user can choose from several clustering methods (including hierarchical, non-hierarchical, and a model-based genetic algorithm), several probe ranking methods, and several different display methods. A novel approach is used for probe redundancy reduction, and probe selection is accomplished via stepwise discriminant analysis. Data can be entered in different formats (including Excel and comma-delimited text), and dendrogram, heat map, and scatter plot images can be saved in several different formats (including jpeg and tiff). Weights generated using stepwise discriminant analysis can be stored for analysis of subsequent experimental data. Additionally, PLASMID can be used to construct virtual microarrays with genomes from public databases, which can then be used to identify an optimal set of probes.

Enhancing interdisciplinary mathematics and biology education: a microarray data analysis course bridging these disciplines.

PubMed

Tra, Yolande V; Evans, Irene M

2010-01-01

BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course.

Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

PubMed Central

Evans, Irene M.

2010-01-01

BIO2010 put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on microarray data analysis. We started using Genome Consortium for Active Teaching (GCAT) materials and Microarray Genome and Clustering Tool software and added R statistical software along with Bioconductor packages. In response to student feedback, one microarray data set was fully analyzed in class, starting from preprocessing to gene discovery to pathway analysis using the latter software. A class project was to conduct a similar analysis where students analyzed their own data or data from a published journal paper. This exercise showed the impact that filtering, preprocessing, and different normalization methods had on gene inclusion in the final data set. We conclude that this course achieved its goals to equip students with skills to analyze data from a microarray experiment. We offer our insight about collaborative teaching as well as how other faculty might design and implement a similar interdisciplinary course. PMID:20810954

Genomic analysis of Fusarium verticillioides.

PubMed

Brown, D W; Butchko, R A E; Proctor, R H

2008-09-01

Fusarium verticillioides (teleomorph Gibberella moniliformis) can be either an endophyte of maize, causing no visible disease, or a pathogen-causing disease of ears, stalks, roots and seedlings. At any stage, this fungus can synthesize fumonisins, a family of mycotoxins structurally similar to the sphingolipid sphinganine. Ingestion of fumonisin-contaminated maize has been associated with a number of animal diseases, including cancer in rodents, and exposure has been correlated with human oesophageal cancer in some regions of the world, and some evidence suggests that fumonisins are a risk factor for neural tube defects. A primary goal of the authors' laboratory is to eliminate fumonisin contamination of maize and maize products. Understanding how and why these toxins are made and the F. verticillioides-maize disease process will allow one to develop novel strategies to limit tissue destruction (rot) and fumonisin production. To meet this goal, genomic sequence data, expressed sequence tags (ESTs) and microarrays are being used to identify F. verticillioides genes involved in the biosynthesis of toxins and plant pathogenesis. This paper describes the current status of F. verticillioides genomic resources and three approaches being used to mine microarray data from a wild-type strain cultured in liquid fumonisin production medium for 12, 24, 48, 72, 96 and 120h. Taken together, these approaches demonstrate the power of microarray technology to provide information on different biological processes.

Chromosomal Microarray versus Karyotyping for Prenatal Diagnosis

PubMed Central

Wapner, Ronald J.; Martin, Christa Lese; Levy, Brynn; Ballif, Blake C.; Eng, Christine M.; Zachary, Julia M.; Savage, Melissa; Platt, Lawrence D.; Saltzman, Daniel; Grobman, William A.; Klugman, Susan; Scholl, Thomas; Simpson, Joe Leigh; McCall, Kimberly; Aggarwal, Vimla S.; Bunke, Brian; Nahum, Odelia; Patel, Ankita; Lamb, Allen N.; Thom, Elizabeth A.; Beaudet, Arthur L.; Ledbetter, David H.; Shaffer, Lisa G.; Jackson, Laird

2013-01-01

Background Chromosomal microarray analysis has emerged as a primary diagnostic tool for the evaluation of developmental delay and structural malformations in children. We aimed to evaluate the accuracy, efficacy, and incremental yield of chromosomal microarray analysis as compared with karyotyping for routine prenatal diagnosis. Methods Samples from women undergoing prenatal diagnosis at 29 centers were sent to a central karyotyping laboratory. Each sample was split in two; standard karyotyping was performed on one portion and the other was sent to one of four laboratories for chromosomal microarray. Results We enrolled a total of 4406 women. Indications for prenatal diagnosis were advanced maternal age (46.6%), abnormal result on Down’s syndrome screening (18.8%), structural anomalies on ultrasonography (25.2%), and other indications (9.4%). In 4340 (98.8%) of the fetal samples, microarray analysis was successful; 87.9% of samples could be used without tissue culture. Microarray analysis of the 4282 nonmosaic samples identified all the aneuploidies and unbalanced rearrangements identified on karyotyping but did not identify balanced translocations and fetal triploidy. In samples with a normal karyotype, microarray analysis revealed clinically relevant deletions or duplications in 6.0% with a structural anomaly and in 1.7% of those whose indications were advanced maternal age or positive screening results. Conclusions In the context of prenatal diagnostic testing, chromosomal microarray analysis identified additional, clinically significant cytogenetic information as compared with karyotyping and was equally efficacious in identifying aneuploidies and unbalanced rearrangements but did not identify balanced translocations and triploidies. (Funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development and others; ClinicalTrials.gov number, NCT01279733.) PMID:23215555

Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier.

PubMed

Kumar, Mukesh; Rath, Nitish Kumar; Rath, Santanu Kumar

2016-04-01

Microarray-based gene expression profiling has emerged as an efficient technique for classification, prognosis, diagnosis, and treatment of cancer. Frequent changes in the behavior of this disease generates an enormous volume of data. Microarray data satisfies both the veracity and velocity properties of big data, as it keeps changing with time. Therefore, the analysis of microarray datasets in a small amount of time is essential. They often contain a large amount of expression, but only a fraction of it comprises genes that are significantly expressed. The precise identification of genes of interest that are responsible for causing cancer are imperative in microarray data analysis. Most existing schemes employ a two-phase process such as feature selection/extraction followed by classification. In this paper, various statistical methods (tests) based on MapReduce are proposed for selecting relevant features. After feature selection, a MapReduce-based K-nearest neighbor (mrKNN) classifier is also employed to classify microarray data. These algorithms are successfully implemented in a Hadoop framework. A comparative analysis is done on these MapReduce-based models using microarray datasets of various dimensions. From the obtained results, it is observed that these models consume much less execution time than conventional models in processing big data. Copyright © 2016 Elsevier Inc. All rights reserved.

Effects of space flight exposure on cell growth, tumorigenicity and gene expression in cancer cells

NASA Astrophysics Data System (ADS)

Yang, Cheng; Li, Yuehui; Zhang, Zhijie; Luo, Chen; Tong, Yongqing; Zhou, Guohua; Xie, Pingli; Hu, Jinyue; Li, Guancheng

2008-12-01

It is well recognized that harsh outer space environment, consisting of microgravity and radiation, poses significant health risks for human cells. To investigate potential effects of the space environment exposure on cancer cells we examined the biological changes in Caski cells carried by the "Shen Zhou IV" spaceship. After exposure for 7 days in spaceflight, 1440 survival subclonal cell lines were established and 4 cell lines were screened. 44F10 and 17E3 were selected because of their increased cell proliferation and tumorigenesis, while 48A9 and 31F2 had slower cytological events. Experiments with cell proliferation assay, flow cytometry, soft agar assay, tumorigenesis assay and DNA microarray analysis have shown that selected cell lines presented multiple biological changes in cell morphology, cell growth, tumorigenicity and gene expression. These results suggest that space environment exposure can make significant biological impact on cancer cells and provide an entry point to find the immunological target of tumorigenesis.

Eye-Specific Gene Expression following Embryonic Ethanol Exposure in Zebrafish: Roles for Heat Shock Factor 1

PubMed Central

Kashyap, Bhavani; Pegorsch, Laurel; Frey, Ruth A.; Sun, Chi; Shelden, Eric A.; Stenkamp, Deborah L.

2014-01-01

The mechanisms through which ethanol exposure results in developmental defects remain unclear. We used the zebrafish model to elucidate eye-specific mechanisms that underlie ethanol-mediated microphthalmia (reduced eye size), through time-series microarray analysis of gene expression within eyes of embryos exposed to 1.5% ethanol. 62 genes were differentially expressed (DE) in ethanol-treated as compared to control eyes sampled during retinal neurogenesis (24-48 hours post-fertilization). The EDGE (extraction of differential gene expression) algorithm identified >3000 genes DE over developmental time in ethanol-exposed eyes as compared to controls. The DE lists included several genes indicating a mis-regulated cellular stress response due to ethanol exposure. Combined treatment with sub-threshold levels of ethanol and a morpholino targeting heat shock factor 1 mRNA resulted in microphthalmia, suggesting convergent molecular pathways. Thermal preconditioning partially prevented ethanol-mediated microphthalmia while maintaining Hsf-1 expression. These data suggest roles for reduced Hsf-1 in mediating microphthalmic effects of embryonic ethanol exposure. PMID:24355176

Inhalation toxicity of indoor air pollutants in Drosophila melanogaster using integrated transcriptomics and computational behavior analyses

NASA Astrophysics Data System (ADS)

Eom, Hyun-Jeong; Liu, Yuedan; Kwak, Gyu-Suk; Heo, Muyoung; Song, Kyung Seuk; Chung, Yun Doo; Chon, Tae-Soo; Choi, Jinhee

2017-06-01

We conducted an inhalation toxicity test on the alternative animal model, Drosophila melanogaster, to investigate potential hazards of indoor air pollution. The inhalation toxicity of toluene and formaldehyde was investigated using comprehensive transcriptomics and computational behavior analyses. The ingenuity pathway analysis (IPA) based on microarray data suggests the involvement of pathways related to immune response, stress response, and metabolism in formaldehyde and toluene exposure based on hub molecules. We conducted a toxicity test using mutants of the representative genes in these pathways to explore the toxicological consequences of alterations of these pathways. Furthermore, extensive computational behavior analysis showed that exposure to either toluene or formaldehyde reduced most of the behavioral parameters of both wild-type and mutants. Interestingly, behavioral alteration caused by toluene or formaldehyde exposure was most severe in the p38b mutant, suggesting that the defects in the p38 pathway underlie behavioral alteration. Overall, the results indicate that exposure to toluene and formaldehyde via inhalation causes severe toxicity in Drosophila, by inducing significant alterations in gene expression and behavior, suggesting that Drosophila can be used as a potential alternative model in inhalation toxicity screening.

Inhalation toxicity of indoor air pollutants in Drosophila melanogaster using integrated transcriptomics and computational behavior analyses

PubMed Central

Eom, Hyun-Jeong; Liu, Yuedan; Kwak, Gyu-Suk; Heo, Muyoung; Song, Kyung Seuk; Chung, Yun Doo; Chon, Tae-Soo; Choi, Jinhee

2017-01-01

We conducted an inhalation toxicity test on the alternative animal model, Drosophila melanogaster, to investigate potential hazards of indoor air pollution. The inhalation toxicity of toluene and formaldehyde was investigated using comprehensive transcriptomics and computational behavior analyses. The ingenuity pathway analysis (IPA) based on microarray data suggests the involvement of pathways related to immune response, stress response, and metabolism in formaldehyde and toluene exposure based on hub molecules. We conducted a toxicity test using mutants of the representative genes in these pathways to explore the toxicological consequences of alterations of these pathways. Furthermore, extensive computational behavior analysis showed that exposure to either toluene or formaldehyde reduced most of the behavioral parameters of both wild-type and mutants. Interestingly, behavioral alteration caused by toluene or formaldehyde exposure was most severe in the p38b mutant, suggesting that the defects in the p38 pathway underlie behavioral alteration. Overall, the results indicate that exposure to toluene and formaldehyde via inhalation causes severe toxicity in Drosophila, by inducing significant alterations in gene expression and behavior, suggesting that Drosophila can be used as a potential alternative model in inhalation toxicity screening. PMID:28621308

Gene-Expression Biomarkers for Application to High-Throughput Radiation Biodosimetry

DTIC Science & Technology

2005-01-01

nuclear disaster . Even with the delayed onset of symptoms, sometimes several days after exposure, gene-expression biomarkers can identify these exposed individuals very early after exposure, allowing for prompt medical intervention. This early assessment of a radiation dose after exposure would enhance the operational commander’s situational awareness of the radiation exposure status of deployed units and increase the prospect of reduced morbidity and mortality through early medical intervention. Candidate gene targets were selected from microarray studies of ex

Direct labeling of serum proteins by fluorescent dye for antibody microarray.

PubMed

Klimushina, M V; Gumanova, N G; Metelskaya, V A

2017-05-06

Analysis of serum proteome by antibody microarray is used to identify novel biomarkers and to study signaling pathways including protein phosphorylation and protein-protein interactions. Labeling of serum proteins is important for optimal performance of the antibody microarray. Proper choice of fluorescent label and optimal concentration of protein loaded on the microarray ensure good quality of imaging that can be reliably scanned and processed by the software. We have optimized direct serum protein labeling using fluorescent dye Arrayit Green 540 (Arrayit Corporation, USA) for antibody microarray. Optimized procedure produces high quality images that can be readily scanned and used for statistical analysis of protein composition of the serum. Copyright © 2017 Elsevier Inc. All rights reserved.

Modulation of Differentiation Processes in Murine Embryonic Stem Cells Exposed to Parabolic Flight-Induced Acute Hypergravity and Microgravity.

PubMed

Acharya, Aviseka; Brungs, Sonja; Henry, Margit; Rotshteyn, Tamara; Singh Yaduvanshi, Nirmala; Wegener, Lucia; Jentzsch, Simon; Hescheler, Jürgen; Hemmersbach, Ruth; Boeuf, Helene; Sachinidis, Agapios

2018-06-15

Embryonic developmental studies under microgravity conditions in space are very limited. To study the effects of short-term altered gravity on embryonic development processes, we exposed mouse embryonic stem cells (mESCs) to phases of hypergravity and microgravity and studied the differentiation potential of the cells using wide-genome microarray analysis. During the 64th European Space Agency's parabolic flight campaign, mESCs were exposed to 31 parabolas. Each parabola comprised phases lasting 22 s of hypergravity, microgravity, and a repeat of hypergravity. On different parabolas, RNA was isolated for microarray analysis. After exposure to 31 parabolas, mESCs (P31 mESCs) were further differentiated under normal gravity (1 g) conditions for 12 days, producing P31 12-day embryoid bodies (EBs). After analysis of the microarrays, the differentially expressed genes were analyzed using different bioinformatic tools to identify developmental and nondevelopmental biological processes affected by conditions on the parabolic flight experiment. Our results demonstrated that several genes belonging to GOs associated with cell cycle and proliferation were downregulated in undifferentiated mESCs exposed to gravity changes. However, several genes belonging to developmental processes, such as vasculature development, kidney development, skin development, and to the TGF-β signaling pathway, were upregulated. Interestingly, similar enriched and suppressed GOs were obtained in P31 12-day EBs compared with ground control 12-day EBs. Our results show that undifferentiated mESCs exposed to alternate hypergravity and microgravity phases expressed several genes associated with developmental/differentiation and cell cycle processes, suggesting a transition from the undifferentiated pluripotent to a more differentiated stage of mESCs.

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Amanda M.; Daly, Don S.; Willse, Alan R.

The Automated Microarray Image Analysis (AMIA) Toolbox for MATLAB is a flexible, open-source microarray image analysis tool that allows the user to customize analysis of sets of microarray images. This tool provides several methods of identifying and quantify spot statistics, as well as extensive diagnostic statistics and images to identify poor data quality or processing. The open nature of this software allows researchers to understand the algorithms used to provide intensity estimates and to modify them easily if desired.

Genome-wide expression analysis of human in vivo irritated epidermis: differential profiles induced by sodium lauryl sulfate and nonanoic acid.

PubMed

Clemmensen, Anders; Andersen, Klaus E; Clemmensen, Ole; Tan, Qihua; Petersen, Thomas K; Kruse, Torben A; Thomassen, Mads

2010-09-01

The pathogenesis of irritant contact dermatitis (ICD) is poorly understood, and genes participating in the epidermal response to chemical irritants are only partly known. It is commonly accepted that different irritants have different mechanisms of action in the development of ICD. To define the differential molecular events induced in the epidermis by different irritants, we collected sequential biopsies ((1/2), 4, and 24 hours after a single exposure and at day 11 after repeated exposure) from human volunteers exposed to either sodium lauryl sulfate (SLS) or nonanoic acid (NON). Gene expression analysis using high-density oligonucleotide microarrays (representing 47,000 transcripts) revealed essentially different pathway responses (1/2)hours after exposure: NON transiently induced the IL-6 pathway as well as a number of mitogen-activated signaling cascades including extracellular signal-regulated kinase and growth factor receptor signaling, whereas SLS transiently downregulated cellular energy metabolism pathways. Differential expression of the cyclooxygenase-2 and matrix metalloproteinase 3 transcripts was confirmed immunohistochemically. After cumulative exposure, 883 genes were differentially expressed, whereas we identified 23 suggested common biomarkers for ICD. In conclusion, we bring new insights into two hitherto less well-elucidated phases of skin irritancy: the very initial as well as the late phase after single and cumulative mild exposures, respectively.

ELISA-BASE: An Integrated Bioinformatics Tool for Analyzing and Tracking ELISA Microarray Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

White, Amanda M.; Collett, James L.; Seurynck-Servoss, Shannon L.

ELISA-BASE is an open-source database for capturing, organizing and analyzing protein enzyme-linked immunosorbent assay (ELISA) microarray data. ELISA-BASE is an extension of the BioArray Soft-ware Environment (BASE) database system, which was developed for DNA microarrays. In order to make BASE suitable for protein microarray experiments, we developed several plugins for importing and analyzing quantitative ELISA microarray data. Most notably, our Protein Microarray Analysis Tool (ProMAT) for processing quantita-tive ELISA data is now available as a plugin to the database.

Developmental effects of tobacco smoke exposure during human embryonic stem cell differentiation are mediated through the transforming growth factor-β superfamily member, Nodal

PubMed Central

Liszewski, Walter; Ritner, Carissa; Aurigui, Julian; Wong, Sharon S. Y.; Hussain, Naveed; Krueger, Winfried; Oncken, Cheryl; Bernstein, Harold S.

2012-01-01

While the pathologies associated with in utero smoke exposure are well established, their underlying molecular mechanisms are incompletely understood. We differentiated human embryonic stem cells in the presence of physiological concentrations of tobacco smoke and nicotine. Using post hoc microarray analysis, quantitative PCR, and immunoblot analysis, we demonstrated that tobacco smoke has lineage- and stage-specific effects on human embryonic stem cell differentiation, through both nicotine-dependent and -independent pathways. We show that three major stem cell pluripotency/differentiation pathways, Notch, canonical Wnt, and transforming growth factor-β, are affected by smoke exposure, and that Nodal signaling through SMAD2 is specifically impacted by effects on Lefty1, Nodal, and FoxH1. These events are associated with upregulation of microRNA-302a, a post-transcriptional silencer of Lefty1. The described studies provide insight into the mechanisms by which tobacco smoke influences fetal development at the cellular level, and identify specific transcriptional, post-transcriptional, and signaling pathways by which this likely occurs. PMID:22381624

A microarray analysis of sexual dimorphism of adipose tissues in high-fat-diet-induced obese mice

PubMed Central

Grove, KL; Fried, SK; Greenberg, AS; Xiao, XQ; Clegg, DJ

2013-01-01

Objective A sexual dimorphism exists in body fat distribution; females deposit relatively more fat in subcutaneous/inguinal depots whereas males deposit more fat in the intra-abdominal/gonadal depot. Our objective was to systematically document depot- and sex-related differences in the accumulation of adipose tissue and gene expression, comparing differentially expressed genes in diet-induced obese mice with mice maintained on a chow diet. Research Design and Methods We used a microarray approach to determine whether there are sexual dimorphisms in gene expression in age-matched male, female or ovariectomized female (OVX) C57/BL6 mice maintained on a high-fat (HF) diet. We then compared expression of validated genes between the sexes on a chow diet. Results After exposure to a high fat diet for 12 weeks, females gained less weight than males. The microarray analyses indicate in intra-abdominal/gonadal adipose tissue in females 1642 genes differ by at least twofold between the depots, whereas 706 genes differ in subcutaneous/inguinal adipose tissue when compared with males. Only 138 genes are commonly regulated in both sexes and adipose tissue depots. Inflammatory genes (cytokine–cytokine receptor interactions and acute-phase protein synthesis) are upregulated in males when compared with females, and there is a partial reversal after OVX, where OVX adipose tissue gene expression is more ′male-like′. This pattern is not observed in mice maintained on chow. Histology of male gonadal white adipose tissue (GWAT) shows more crown-like structures than females, indicative of inflammation and adipose tissue remodeling. In addition, genes related to insulin signaling and lipid synthesis are higher in females than males, regardless of dietary exposure. Conclusions These data suggest that male and female adipose tissue differ between the sexes regardless of diet. Moreover, HF diet exposure elicits a much greater inflammatory response in males when compared with females. This data set underscores the importance of analyzing depot-, sex- and steroid-dependent regulation of adipose tissue distribution and function. PMID:20157318

Transcriptome analysis in non-model species: a new method for the analysis of heterologous hybridization on microarrays

PubMed Central

2010-01-01

Background Recent developments in high-throughput methods of analyzing transcriptomic profiles are promising for many areas of biology, including ecophysiology. However, although commercial microarrays are available for most common laboratory models, transcriptome analysis in non-traditional model species still remains a challenge. Indeed, the signal resulting from heterologous hybridization is low and difficult to interpret because of the weak complementarity between probe and target sequences, especially when no microarray dedicated to a genetically close species is available. Results We show here that transcriptome analysis in a species genetically distant from laboratory models is made possible by using MAXRS, a new method of analyzing heterologous hybridization on microarrays. This method takes advantage of the design of several commercial microarrays, with different probes targeting the same transcript. To illustrate and test this method, we analyzed the transcriptome of king penguin pectoralis muscle hybridized to Affymetrix chicken microarrays, two organisms separated by an evolutionary distance of approximately 100 million years. The differential gene expression observed between different physiological situations computed by MAXRS was confirmed by real-time PCR on 10 genes out of 11 tested. Conclusions MAXRS appears to be an appropriate method for gene expression analysis under heterologous hybridization conditions. PMID:20509979

A Human Lectin Microarray for Sperm Surface Glycosylation Analysis *

PubMed Central

Sun, Yangyang; Cheng, Li; Gu, Yihua; Xin, Aijie; Wu, Bin; Zhou, Shumin; Guo, Shujuan; Liu, Yin; Diao, Hua; Shi, Huijuan; Wang, Guangyu; Tao, Sheng-ce

2016-01-01

Glycosylation is one of the most abundant and functionally important protein post-translational modifications. As such, technology for efficient glycosylation analysis is in high demand. Lectin microarrays are a powerful tool for such investigations and have been successfully applied for a variety of glycobiological studies. However, most of the current lectin microarrays are primarily constructed from plant lectins, which are not well suited for studies of human glycosylation because of the extreme complexity of human glycans. Herein, we constructed a human lectin microarray with 60 human lectin and lectin-like proteins. All of the lectins and lectin-like proteins were purified from yeast, and most showed binding to human glycans. To demonstrate the applicability of the human lectin microarray, human sperm were probed on the microarray and strong bindings were observed for several lectins, including galectin-1, 7, 8, GalNAc-T6, and ERGIC-53 (LMAN1). These bindings were validated by flow cytometry and fluorescence immunostaining. Further, mass spectrometry analysis showed that galectin-1 binds several membrane-associated proteins including heat shock protein 90. Finally, functional assays showed that binding of galectin-8 could significantly enhance the acrosome reaction within human sperms. To our knowledge, this is the first construction of a human lectin microarray, and we anticipate it will find wide use for a range of human or mammalian studies, alone or in combination with plant lectin microarrays. PMID:27364157

Differential expression of hepatic genes with embryonic exposure to an environmentally relevant PCB mixture in Japanese quail (Coturnix japonica).

PubMed

Bohannon, Meredith E; Porter, Tom E; Lavoie, Emma T; Ottinger, Mary Ann

2018-06-22

The upper Hudson River was contaminated with polychlorinated biphenyls (PCB) Aroclor mixtures from the 1940s until the late 1970s. Several well-established biomarkers, such as induction of hepatic cytochrome P450 monooxygenases, were used to measure exposure to PCBs and similar contaminants in birds. In the present study, Japanese quail eggs were injected with a PCB mixture based upon a congener profile found in spotted sandpiper eggs at the upper Hudson River and subsequently, RNA was extracted from hatchling liver tissue for hybridization to a customized chicken cDNA microarray. Nominal concentrations of the mixture used for microarray hybridization were 0, 6, 12, or 49 μg/g egg. Hepatic gene expression profiles were analyzed using cluster and pathway analyses. Results showed potentially useful biomarkers of both exposure and effect attributed to PCB mixture. Biorag and Ingenuity Pathway Analysis® analyses revealed differentially expressed genes including those involved in glycolysis, xenobiotic metabolism, replication, protein degradation, and tumor regulation. These genes included cytochrome P450 1A5 (CYP1A5), cytochrome b5 (CYB5), NADH-cytochrome b5 reductase, glutathione S-transferase (GSTA), fructose bisphosphate aldolase (ALDOB), glycogen phosphorylase, carbonic anhydrase, and DNA topoisomerase II. CYP1A5, CYB5, GSTA, and ALDOB were chosen for quantitative real-time polymerase chain reaction confirmation, as these genes exhibited a clear dose response on the array. Data demonstrated that an initial transcriptional profile associated with an environmentally relevant PCB mixture in Japanese quail occurred.

Construction of a robust microarray from a non-model species (largemouth bass) using pyrosequencing technology

PubMed Central

Garcia-Reyero, Natàlia; Griffitt, Robert J.; Liu, Li; Kroll, Kevin J.; Farmerie, William G.; Barber, David S.; Denslow, Nancy D.

2009-01-01

A novel custom microarray for largemouth bass (Micropterus salmoides) was designed with sequences obtained from a normalized cDNA library using the 454 Life Sciences GS-20 pyrosequencer. This approach yielded in excess of 58 million bases of high-quality sequence. The sequence information was combined with 2,616 reads obtained by traditional suppressive subtractive hybridizations to derive a total of 31,391 unique sequences. Annotation and coding sequences were predicted for these transcripts where possible. 16,350 annotated transcripts were selected as target sequences for the design of the custom largemouth bass oligonucleotide microarray. The microarray was validated by examining the transcriptomic response in male largemouth bass exposed to 17β-œstradiol. Transcriptomic responses were assessed in liver and gonad, and indicated gene expression profiles typical of exposure to œstradiol. The results demonstrate the potential to rapidly create the tools necessary to assess large scale transcriptional responses in non-model species, paving the way for expanded impact of toxicogenomics in ecotoxicology. PMID:19936325

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gentry, T.; Schadt, C.; Zhou, J.

Microarray technology has the unparalleled potential tosimultaneously determine the dynamics and/or activities of most, if notall, of the microbial populations in complex environments such as soilsand sediments. Researchers have developed several types of arrays thatcharacterize the microbial populations in these samples based on theirphylogenetic relatedness or functional genomic content. Several recentstudies have used these microarrays to investigate ecological issues;however, most have only analyzed a limited number of samples withrelatively few experiments utilizing the full high-throughput potentialof microarray analysis. This is due in part to the unique analyticalchallenges that these samples present with regard to sensitivity,specificity, quantitation, and data analysis. Thismore » review discussesspecific applications of microarrays to microbial ecology research alongwith some of the latest studies addressing the difficulties encounteredduring analysis of complex microbial communities within environmentalsamples. With continued development, microarray technology may ultimatelyachieve its potential for comprehensive, high-throughput characterizationof microbial populations in near real-time.« less

Fully automated analysis of multi-resolution four-channel micro-array genotyping data

NASA Astrophysics Data System (ADS)

Abbaspour, Mohsen; Abugharbieh, Rafeef; Podder, Mohua; Tebbutt, Scott J.

2006-03-01

We present a fully-automated and robust microarray image analysis system for handling multi-resolution images (down to 3-micron with sizes up to 80 MBs per channel). The system is developed to provide rapid and accurate data extraction for our recently developed microarray analysis and quality control tool (SNP Chart). Currently available commercial microarray image analysis applications are inefficient, due to the considerable user interaction typically required. Four-channel DNA microarray technology is a robust and accurate tool for determining genotypes of multiple genetic markers in individuals. It plays an important role in the state of the art trend where traditional medical treatments are to be replaced by personalized genetic medicine, i.e. individualized therapy based on the patient's genetic heritage. However, fast, robust, and precise image processing tools are required for the prospective practical use of microarray-based genetic testing for predicting disease susceptibilities and drug effects in clinical practice, which require a turn-around timeline compatible with clinical decision-making. In this paper we have developed a fully-automated image analysis platform for the rapid investigation of hundreds of genetic variations across multiple genes. Validation tests indicate very high accuracy levels for genotyping results. Our method achieves a significant reduction in analysis time, from several hours to just a few minutes, and is completely automated requiring no manual interaction or guidance.

Use of whole genome expression analysis in the toxicity screening of nanoparticles

DOE Office of Scientific and Technical Information (OSTI.GOV)

Fröhlich, Eleonore, E-mail: eleonore.froehlich@medunigraz.at; Meindl, Claudia; Wagner, Karin

2014-10-15

The use of nanoparticles (NPs) offers exciting new options in technical and medical applications provided they do not cause adverse cellular effects. Cellular effects of NPs depend on particle parameters and exposure conditions. In this study, whole genome expression arrays were employed to identify the influence of particle size, cytotoxicity, protein coating, and surface functionalization of polystyrene particles as model particles and for short carbon nanotubes (CNTs) as particles with potential interest in medical treatment. Another aim of the study was to find out whether screening by microarray would identify other or additional targets than commonly used cell-based assays formore » NP action. Whole genome expression analysis and assays for cell viability, interleukin secretion, oxidative stress, and apoptosis were employed. Similar to conventional assays, microarray data identified inflammation, oxidative stress, and apoptosis as affected by NP treatment. Application of lower particle doses and presence of protein decreased the total number of regulated genes but did not markedly influence the top regulated genes. Cellular effects of CNTs were small; only carboxyl-functionalized single-walled CNTs caused appreciable regulation of genes. It can be concluded that regulated functions correlated well with results in cell-based assays. Presence of protein mitigated cytotoxicity but did not cause a different pattern of regulated processes. - Highlights: • Regulated functions were screened using whole genome expression assays. • Polystyrene particles regulated more genes than short carbon nanotubes. • Protein coating of polystyrene particles did not change regulation pattern. • Functions regulated by microarray were confirmed by cell-based assay.« less

Toxicity evaluation of glyphosate agrochemical components using Japanese medaka (Oryzias latipes) and DNA microarray gene expression analysis.

PubMed

Uchida, Masaya; Takumi, Shota; Tachikawa, Keiko; Yamauchi, Ryoko; Goto, Yoshiyuki; Matsusaki, Hiromi; Nakamura, Hiroshi; Kagami, Yoshihiro; Kusano, Teruhiko; Arizono, Koji

2012-01-01

Using glyphosate agrochemical components, we investigated their acute toxicity to juvenile Japanese medaka (Oryzias latipes) as well as their toxic impact at gene expression level on the liver tissues of adult medaka using DNA microarray. In our acute toxicity test, juvenile medaka were exposed for 96 hr to each of the following glyphosate agrochemical components: 10~160 mg/l of glyphosate, 1.25~20 mg/l of fatty acid alkanolamide surfactant (DA), and 12~416 mg/l of a fully formulated glyphosate herbicide. As a result, LC(50) values of glyphosate, DA, and the glyphosate herbicide were > 160 mg/l, 8.5 mg/l, and 76.8 mg/l, respectively. On the other hand, adult male medaka fish were exposed to each of the glyphosate agrochemical components for 48 hr at the following concentrations: 16 mg/l of glyphosate, 0.5 mg/l of DA, and 16 mg/l-glyphosate/0.5 mg/l-DA mixture. Interestingly, DNA microarray analysis revealed that there were no significant gene expression changes in the medaka liver after exposure to glyphosate. Nevertheless, 78 and 138 genes were significantly induced by DA and the glyphosate/DA mixture, respectively. Furthermore, we identified five common genes that were affected by DA and glyphosate/DA mixture. These results suggested that glyphosate itself possessed very low toxicity as previously reported by some researchers at least to the small laboratory fish, and the major toxicity of the glyphosate agrochemical resided mainly in DA and perhaps in unintentionally generated byproduct(s) of glyphosate-DA mixture.

Upregulated expression of La ribonucleoprotein domain family member 6 and collagen type I gene following water-filtered broad-spectrum near-infrared irradiation in a 3-dimensional human epidermal tissue culture model as revealed by microarray analysis.

PubMed

Tanaka, Yohei; Nakayama, Jun

2018-05-01

Water-filtered broad-spectrum near-infrared irradiation can induce various biological effects, as our previous clinical, histological, and biochemical investigations have shown. However, few studies that examined the changes thus induced in gene expression. The aim was to investigate the changes in gene expression in a 3-dimensional reconstructed epidermal tissue culture exposed to water-filtered broad-spectrum near-infrared irradiation. DNA microarray and quantitative real-time polymerase chain reaction (PCR) analysis was used to assess gene expression levels in a 3-dimensional reconstructed epidermal model composed of normal human epidermal cells exposed to water-filtered broad-spectrum near-infrared irradiation. The water filter allowed 1000-1800 nm wavelengths and excluded 1400-1500 nm wavelengths, and cells were exposed to 5 or 10 rounds of near-infrared irradiation at 10 J/cm 2 . A DNA microarray with over 50 000 different probes showed 18 genes that were upregulated or downregulated by at least twofold after irradiation. Quantitative real-time PCR revealed that, relative to control cells, the gene encoding La ribonucleoprotein domain family member 6 (LARP6), which regulates collagen expression, was significantly and dose-dependently upregulated (P < 0.05) by water-filtered broad-spectrum near-infrared exposure. Gene encoding transcripts of collagen type I were significantly upregulated compared with controls (P < 0.05). This study demonstrates the ability of water-filtered broad-spectrum near-infrared irradiation to stimulate the production of type I collagen. © 2017 The Australasian College of Dermatologists.

Transcriptome profiling of the intoxication response of Tenebrio molitor larvae to Bacillus thuringiensis Cry3Aa protoxin.

PubMed

Oppert, Brenda; Dowd, Scot E; Bouffard, Pascal; Li, Lewyn; Conesa, Ana; Lorenzen, Marcé D; Toutges, Michelle; Marshall, Jeremy; Huestis, Diana L; Fabrick, Jeff; Oppert, Cris; Jurat-Fuentes, Juan Luis

2012-01-01

Bacillus thuringiensis (Bt) crystal (Cry) proteins are effective against a select number of insect pests, but improvements are needed to increase efficacy and decrease time to mortality for coleopteran pests. To gain insight into the Bt intoxication process in Coleoptera, we performed RNA-Seq on cDNA generated from the guts of Tenebrio molitor larvae that consumed either a control diet or a diet containing Cry3Aa protoxin. Approximately 134,090 and 124,287 sequence reads from the control and Cry3Aa-treated groups were assembled into 1,318 and 1,140 contigs, respectively. Enrichment analyses indicated that functions associated with mitochondrial respiration, signalling, maintenance of cell structure, membrane integrity, protein recycling/synthesis, and glycosyl hydrolases were significantly increased in Cry3Aa-treated larvae, whereas functions associated with many metabolic processes were reduced, especially glycolysis, tricarboxylic acid cycle, and fatty acid synthesis. Microarray analysis was used to evaluate temporal changes in gene expression after 6, 12 or 24 h of Cry3Aa exposure. Overall, microarray analysis indicated that transcripts related to allergens, chitin-binding proteins, glycosyl hydrolases, and tubulins were induced, and those related to immunity and metabolism were repressed in Cry3Aa-intoxicated larvae. The 24 h microarray data validated most of the RNA-Seq data. Of the three intoxication intervals, larvae demonstrated more differential expression of transcripts after 12 h exposure to Cry3Aa. Gene expression examined by three different methods in control vs. Cry3Aa-treated larvae at the 24 h time point indicated that transcripts encoding proteins with chitin-binding domain 3 were the most differentially expressed in Cry3Aa-intoxicated larvae. Overall, the data suggest that T. molitor larvae mount a complex response to Cry3Aa during the initial 24 h of intoxication. Data from this study represent the largest genetic sequence dataset for T. molitor to date. Furthermore, the methods in this study are useful for comparative analyses in organisms lacking a sequenced genome.

Transcriptome Profiling of the Intoxication Response of Tenebrio molitor Larvae to Bacillus thuringiensis Cry3Aa Protoxin

PubMed Central

Oppert, Brenda; Dowd, Scot E.; Bouffard, Pascal; Li, Lewyn; Conesa, Ana; Lorenzen, Marcé D.; Toutges, Michelle; Marshall, Jeremy; Huestis, Diana L.; Fabrick, Jeff; Oppert, Cris; Jurat-Fuentes, Juan Luis

2012-01-01

Bacillus thuringiensis (Bt) crystal (Cry) proteins are effective against a select number of insect pests, but improvements are needed to increase efficacy and decrease time to mortality for coleopteran pests. To gain insight into the Bt intoxication process in Coleoptera, we performed RNA-Seq on cDNA generated from the guts of Tenebrio molitor larvae that consumed either a control diet or a diet containing Cry3Aa protoxin. Approximately 134,090 and 124,287 sequence reads from the control and Cry3Aa-treated groups were assembled into 1,318 and 1,140 contigs, respectively. Enrichment analyses indicated that functions associated with mitochondrial respiration, signalling, maintenance of cell structure, membrane integrity, protein recycling/synthesis, and glycosyl hydrolases were significantly increased in Cry3Aa-treated larvae, whereas functions associated with many metabolic processes were reduced, especially glycolysis, tricarboxylic acid cycle, and fatty acid synthesis. Microarray analysis was used to evaluate temporal changes in gene expression after 6, 12 or 24 h of Cry3Aa exposure. Overall, microarray analysis indicated that transcripts related to allergens, chitin-binding proteins, glycosyl hydrolases, and tubulins were induced, and those related to immunity and metabolism were repressed in Cry3Aa-intoxicated larvae. The 24 h microarray data validated most of the RNA-Seq data. Of the three intoxication intervals, larvae demonstrated more differential expression of transcripts after 12 h exposure to Cry3Aa. Gene expression examined by three different methods in control vs. Cry3Aa-treated larvae at the 24 h time point indicated that transcripts encoding proteins with chitin-binding domain 3 were the most differentially expressed in Cry3Aa-intoxicated larvae. Overall, the data suggest that T. molitor larvae mount a complex response to Cry3Aa during the initial 24 h of intoxication. Data from this study represent the largest genetic sequence dataset for T. molitor to date. Furthermore, the methods in this study are useful for comparative analyses in organisms lacking a sequenced genome. PMID:22558093

The Use of Signal-Transduction and Metabolic Pathways to Predict Human Disease Targets from Electric and Magnetic Fields Using in vitro Data in Human Cell Lines

PubMed Central

Parham, Fred; Portier, Christopher J.; Chang, Xiaoqing; Mevissen, Meike

2016-01-01

Using in vitro data in human cell lines, several research groups have investigated changes in gene expression in cellular systems following exposure to extremely low frequency (ELF) and radiofrequency (RF) electromagnetic fields (EMF). For ELF EMF, we obtained five studies with complete microarray data and three studies with only lists of significantly altered genes. Likewise, for RF EMF, we obtained 13 complete microarray datasets and 5 limited datasets. Plausible linkages between exposure to ELF and RF EMF and human diseases were identified using a three-step process: (a) linking genes associated with classes of human diseases to molecular pathways, (b) linking pathways to ELF and RF EMF microarray data, and (c) identifying associations between human disease and EMF exposures where the pathways are significantly similar. A total of 60 pathways were associated with human diseases, mostly focused on basic cellular functions like JAK–STAT signaling or metabolic functions like xenobiotic metabolism by cytochrome P450 enzymes. ELF EMF datasets were sporadically linked to human diseases, but no clear pattern emerged. Individual datasets showed some linkage to cancer, chemical dependency, metabolic disorders, and neurological disorders. RF EMF datasets were not strongly linked to any disorders but strongly linked to changes in several pathways. Based on these analyses, the most promising area for further research would be to focus on EMF and neurological function and disorders. PMID:27656641

PRACTICAL STRATEGIES FOR PROCESSING AND ANALYZING SPOTTED OLIGONUCLEOTIDE MICROARRAY DATA

EPA Science Inventory

Thoughtful data analysis is as important as experimental design, biological sample quality, and appropriate experimental procedures for making microarrays a useful supplement to traditional toxicology. In the present study, spotted oligonucleotide microarrays were used to profile...

Suppression of Radiation-Induced Testicular Germ Cell Apoptosis by 2,5-Hexanedione Pretreatment. III. Candidate Gene Analysis Identifies a Role for Fas in the Attenuation of X-ray–Induced Apoptosis

PubMed Central

Campion, Sarah N.; Sandrof, Moses A.; Yamasaki, Hideki; Boekelheide, Kim

2010-01-01

Germ cell apoptosis directly induced by x-radiation (x-ray) exposure is stage specific, with a higher incidence in stage II/III seminiferous tubules. A priming exposure to the Sertoli cell toxicant 2,5-hexanedione (HD) results in a marked reduction in x-ray–induced germ cell apoptosis in these affected stages. Because of the stage specificity of these responses, examination of associated gene expression in whole testis tissue has clear limitations. Laser capture microdissection (LCM) of specific cell populations in the testis is a valuable technique for investigating the responses of different cell types following toxicant exposure. LCM coupled with quantitative real-time PCR was performed to examine the expression of apoptosis-related genes at both early (3 h) and later (12 h) time points after x-ray exposure, with or without the priming exposure to HD. The mRNAs examined include Fas, FasL, caspase 3, bcl-2, p53, PUMA, and AEN, which were identified either by literature searches or microarray analysis. Group 1 seminiferous tubules (stages I–VI) exhibited the greatest changes in gene expression. Further analysis of this stage group (SG) revealed that Fas induction by x-ray is significantly attenuated by HD co-exposure. Selecting only for germ cells from seminiferous tubules of the most sensitive SG has provided further insight into the mechanisms involved in the co-exposure response. It is hypothesized that following co-exposure, germ cells adapt to the lack of Sertoli cell support by reducing the Fas response to normal FasL signals. These findings provide a better understanding and appreciation of the tissue complexity and technical difficulties associated with examining gene expression in the testis. PMID:20616204

GeneXplorer: an interactive web application for microarray data visualization and analysis.

PubMed

Rees, Christian A; Demeter, Janos; Matese, John C; Botstein, David; Sherlock, Gavin

2004-10-01

When publishing large-scale microarray datasets, it is of great value to create supplemental websites where either the full data, or selected subsets corresponding to figures within the paper, can be browsed. We set out to create a CGI application containing many of the features of some of the existing standalone software for the visualization of clustered microarray data. We present GeneXplorer, a web application for interactive microarray data visualization and analysis in a web environment. GeneXplorer allows users to browse a microarray dataset in an intuitive fashion. It provides simple access to microarray data over the Internet and uses only HTML and JavaScript to display graphic and annotation information. It provides radar and zoom views of the data, allows display of the nearest neighbors to a gene expression vector based on their Pearson correlations and provides the ability to search gene annotation fields. The software is released under the permissive MIT Open Source license, and the complete documentation and the entire source code are freely available for download from CPAN http://search.cpan.org/dist/Microarray-GeneXplorer/.

Hepatic gene expression in rainbow trout (Oncorhynchus mykiss) exposed to different hydrocarbon mixtures.

PubMed

Hook, Sharon E; Lampi, Mark A; Febbo, Eric J; Ward, Jeff A; Parkerton, Thomas F

2010-09-01

Traditional biomarkers for hydrocarbon exposure are not induced by all petroleum substances. The objective of this study was to determine if exposure to a crude oil and different refined oils would generate a common hydrocarbon-specific response in gene expression profiles that could be used as generic biomarkers of hydrocarbon exposure. Juvenile rainbow trout (Oncorhynchus mykiss) were exposed to the water accommodated fraction (WAF) of either kerosene, gas oil, heavy fuel oil, or crude oil for 96 h. Tissue was collected for RNA extraction and microarray analysis. Exposure to each WAF resulted in a different list of differentially regulated genes, with few genes in common across treatments. Exposure to crude oil WAF changed the expression of genes including cytochrome P4501A (CYP1A) and glutathione-S-transferase (GST) with known roles in detoxification pathways. These gene expression profiles were compared to others from previous experiments that used a diverse suite of toxicants. Clustering algorithms successfully identified gene expression profiles resulting from hydrocarbon exposure. These preliminary analyses highlight the difficulties of using single genes as diagnostic of petroleum hydrocarbon exposures. Further work is needed to determine if multivariate transcriptomic-based biomarkers may be a more effective tool than single gene studies for exposure monitoring of different oils. Copyright 2010 SETAC.

Nanotechnology: moving from microarrays toward nanoarrays.

PubMed

Chen, Hua; Li, Jun

2007-01-01

Microarrays are important tools for high-throughput analysis of biomolecules. The use of microarrays for parallel screening of nucleic acid and protein profiles has become an industry standard. A few limitations of microarrays are the requirement for relatively large sample volumes and elongated incubation time, as well as the limit of detection. In addition, traditional microarrays make use of bulky instrumentation for the detection, and sample amplification and labeling are quite laborious, which increase analysis cost and delays the time for obtaining results. These problems limit microarray techniques from point-of-care and field applications. One strategy for overcoming these problems is to develop nanoarrays, particularly electronics-based nanoarrays. With further miniaturization, higher sensitivity, and simplified sample preparation, nanoarrays could potentially be employed for biomolecular analysis in personal healthcare and monitoring of trace pathogens. In this chapter, it is intended to introduce the concept and advantage of nanotechnology and then describe current methods and protocols for novel nanoarrays in three aspects: (1) label-free nucleic acids analysis using nanoarrays, (2) nanoarrays for protein detection by conventional optical fluorescence microscopy as well as by novel label-free methods such as atomic force microscopy, and (3) nanoarray for enzymatic-based assay. These nanoarrays will have significant applications in drug discovery, medical diagnosis, genetic testing, environmental monitoring, and food safety inspection.

Long-term trihexyphenidyl exposure alters neuroimmune response and inflammation in aging rat: relevance to age and Alzheimer's disease.

PubMed

Huang, Yuqi; Zhao, Zhe; Wei, Xiaoli; Zheng, Yong; Yu, Jianqiang; Zheng, Jianquan; Wang, Liyun

2016-07-01

Clinical studies have shown an association between long-term anticholinergic (AC) drug exposure and Alzheimer's disease (AD) pathogenesis, which has been primarily investigated in Parkinson's disease (PD). However, long-term AC exposure as a risk factor for developing neurodegenerative disorders and the exact mechanisms and potential for disease progression remain unclear. Here, we have addressed the issue using trihexyphenidyl (THP), a commonly used AC drug in PD patients, to determine if THP can accelerate AD-like neurodegenerative progression and study potential mechanisms involved. Male Sprague-Dawley rats (SD) were intraperitoneally injected with THP (0.3 and 1.0 mg/kg) or normal saline (NS) for 7 months. Alterations in cognitive and behavioral performance were assessed using the Morris water maze (MWM) and open field tests. After behavior tests, whole genome oligo microarrays, quantitative real-time reverse transcription-polymerase chain reaction (qRT-PCR), immunohistochemistry, and immunofluorescence-confocal were used to investigate the global mechanisms underlying THP-induced neuropathology with aging. Compared with NS controls, the MWM test results showed that THP-treated rats exhibited significantly extended mean latencies during the initial 3 months of testing; however, this behavioral deficit was restored between the fourth and sixth month of MWM testing. The same tendencies were confirmed by MWM probe and open field tests. Gene microarray analysis identified 68 (47 %) upregulated and 176 (53 %) downregulated genes in the "THP-aging" vs. "NS-aging" group. The most significant populations of genes downregulated by THP were the immune response-, antigen processing and presentation-, and major histocompatibility complex (MHC)-related genes, as validated by qRT-PCR. The decreased expression of MHC class I in THP-treated aging brains was confirmed by confocal analysis. Notably, long-term THP treatment primed hippocampal and cortical microglia to undergo an inflammatory phenotypic switch, causing microgliosis and microglia activation, which were positively accompanied by pathological misfolded tau lesions. Our findings suggest that immune response and neuroinflammation represent a pivotal mechanism in THP-induced AD-like neuropathology processes with long-term exposure to AC drugs.

Global gene expression and Ingenuity biological functions analysis on PCBs 153 and 138 induced human PBMC in vitro reveals differential mode(s) of action in developing toxicities.

PubMed

Ghosh, Somiranjan; Zang, Shizhu; Mitra, Partha S; Ghimbovschi, Svetlana; Hoffman, Eric P; Dutta, Sisir K

2011-07-01

Several reports have indicated that low level of polychlorinated biphenyl (PCB) exposure can adversely affect a multitude of physiological disorders and diseases in in vitro, in vivo, and as reported in epidemiological studies. This investigation is focused on the possible contribution of two most prevalent PCB congeners in vitro in developing toxicities. We used PCBs 138 and 153 at the human equivalence level as model agents to test their specificity in developing toxicities. We chose a global approach using oligonucleotide microarray technology to investigate modulated gene expression for biological effects, upon exposure of PCBs, followed by Ingenuity Pathway Analysis (IPA), to understand the underlying consequence in developing disease and disorders. We performed in vitro studies with human peripheral blood mononuclear cells (PBMC), where PBMC cells were exposed to respective PCBs for 48 h. Overall, our observation on gene expression indicated that PCB produces a unique signature affecting different pathways, specific for each congener. While analyzing these data through IPA, the prominent and interesting disease and disorders were neurological disease, cancer, cardiovascular disease, respiratory disease, as well as endocrine system disorders, genetic disorders, and reproductive system disease. They showed strong resemblances with in vitro, in vivo, and in the epidemiological studies. A distinct difference was observed in renal and urological diseases, organisimal injury and abnormalities, dental disease, ophthalmic disease, and psychological disorders, which are only revealed by PCB 138 exposure, but not in PCB 153. The present study emphasizes the challenges of global gene expression in vitro and was correlated with the results of exposed human population. The microarray results give a molecular mechanistic insight and functional effects, following PCB exposure. The extent of changes in genes related to several possible mode(s) of action highlights the changes in cellular functions and signaling pathways that play major roles. In addition to understanding the pathways related to mode of action for chemicals, these data could lead to the identification of genomic signatures that could be used for screening of chemicals for their potential to cause disease and developmental disorders. Copyright © 2011 Elsevier Ltd. All rights reserved.

A meta-data based method for DNA microarray imputation.

PubMed

Jörnsten, Rebecka; Ouyang, Ming; Wang, Hui-Yu

2007-03-29

DNA microarray experiments are conducted in logical sets, such as time course profiling after a treatment is applied to the samples, or comparisons of the samples under two or more conditions. Due to cost and design constraints of spotted cDNA microarray experiments, each logical set commonly includes only a small number of replicates per condition. Despite the vast improvement of the microarray technology in recent years, missing values are prevalent. Intuitively, imputation of missing values is best done using many replicates within the same logical set. In practice, there are few replicates and thus reliable imputation within logical sets is difficult. However, it is in the case of few replicates that the presence of missing values, and how they are imputed, can have the most profound impact on the outcome of downstream analyses (e.g. significance analysis and clustering). This study explores the feasibility of imputation across logical sets, using the vast amount of publicly available microarray data to improve imputation reliability in the small sample size setting. We download all cDNA microarray data of Saccharomyces cerevisiae, Arabidopsis thaliana, and Caenorhabditis elegans from the Stanford Microarray Database. Through cross-validation and simulation, we find that, for all three species, our proposed imputation using data from public databases is far superior to imputation within a logical set, sometimes to an astonishing degree. Furthermore, the imputation root mean square error for significant genes is generally a lot less than that of non-significant ones. Since downstream analysis of significant genes, such as clustering and network analysis, can be very sensitive to small perturbations of estimated gene effects, it is highly recommended that researchers apply reliable data imputation prior to further analysis. Our method can also be applied to cDNA microarray experiments from other species, provided good reference data are available.

BABAR: an R package to simplify the normalisation of common reference design microarray-based transcriptomic datasets

PubMed Central

2010-01-01

Background The development of DNA microarrays has facilitated the generation of hundreds of thousands of transcriptomic datasets. The use of a common reference microarray design allows existing transcriptomic data to be readily compared and re-analysed in the light of new data, and the combination of this design with large datasets is ideal for 'systems'-level analyses. One issue is that these datasets are typically collected over many years and may be heterogeneous in nature, containing different microarray file formats and gene array layouts, dye-swaps, and showing varying scales of log2- ratios of expression between microarrays. Excellent software exists for the normalisation and analysis of microarray data but many data have yet to be analysed as existing methods struggle with heterogeneous datasets; options include normalising microarrays on an individual or experimental group basis. Our solution was to develop the Batch Anti-Banana Algorithm in R (BABAR) algorithm and software package which uses cyclic loess to normalise across the complete dataset. We have already used BABAR to analyse the function of Salmonella genes involved in the process of infection of mammalian cells. Results The only input required by BABAR is unprocessed GenePix or BlueFuse microarray data files. BABAR provides a combination of 'within' and 'between' microarray normalisation steps and diagnostic boxplots. When applied to a real heterogeneous dataset, BABAR normalised the dataset to produce a comparable scaling between the microarrays, with the microarray data in excellent agreement with RT-PCR analysis. When applied to a real non-heterogeneous dataset and a simulated dataset, BABAR's performance in identifying differentially expressed genes showed some benefits over standard techniques. Conclusions BABAR is an easy-to-use software tool, simplifying the simultaneous normalisation of heterogeneous two-colour common reference design cDNA microarray-based transcriptomic datasets. We show BABAR transforms real and simulated datasets to allow for the correct interpretation of these data, and is the ideal tool to facilitate the identification of differentially expressed genes or network inference analysis from transcriptomic datasets. PMID:20128918

Global transcriptional responses of Bacillus subtilis to xenocoumacin 1.

PubMed

Zhou, T; Zeng, H; Qiu, D; Yang, X; Wang, B; Chen, M; Guo, L; Wang, S

2011-09-01

To determine the global transcriptional response of Bacillus subtilis to an antimicrobial agent, xenocoumacin 1 (Xcn1). Subinhibitory concentration of Xcn1 applied to B. subtilis was measured according to Hutter's method for determining optimal concentrations. cDNA microarray technology was used to study the global transcriptional response of B. subtilis to Xcn1. Real-time RT-PCR was employed to verify alterations in the transcript levels of six genes. The subinhibitory concentration was determined to be 1 μg ml(-1). The microarray data demonstrated that Xcn1 treatment of B. subtilis led to more than a 2.0-fold up-regulation of 480 genes and more than a 2.0-fold down-regulation of 479 genes (q ≤ 0.05). The transcriptional responses of B. subtilis to Xcn1 were determined, and several processes were affected by Xcn1. Additionally, cluster analysis of gene expression profiles after treatment with Xcn1 or 37 previously studied antibiotics indicated that Xcn1 has similar mechanisms of action to protein synthesis inhibitors. These microarray data showed alterations of gene expression in B. subtilis after exposure to Xcn1. From the results, we identified various processes affected by Xcn1. This study provides a whole-genome perspective to elucidate the action of Xcn1 as a potential antimicrobial agent. © 2011 The Authors. Journal of Applied Microbiology © 2011 The Society for Applied Microbiology.

Temporal effects in porcine skin following bromine vapor exposure.

PubMed

Price, Jennifer A; Rogers, James V; Wendling, Morgan Q S; Plahovinsak, Jennifer L; Perry, Mark R; Reid, Frances M; Kiser, Robyn C; Graham, John S

2011-09-01

Bromine is an industrial chemical that causes severe cutaneous burns. When selecting or developing effective treatments for bromine burns, it is important to understand the molecular mechanisms of tissue damage and wound healing. This study investigated the effect of cutaneous bromine vapor exposure on gene expression using a weanling swine burn model by microarray analysis. Ventral abdominal sites were exposed to a mean calculated bromine vapor concentration of 0.51 g/L for 7 or 17 min. At 6 h, 48 h, and 7 days post-exposure, total RNA from skin samples was isolated, processed, and analyzed with Affymetrix GeneChip® Porcine Genome Arrays (N = 3 per experimental group). Differences in gene expression were observed with respect to exposure duration and sampling time. Ingenuity Pathways Analysis (IPA) revealed four common biological functions (cancer, cellular movement, cell-to-cell signaling and interaction, and tissue development) among the top ten functions of each experimental group, while canonical pathway analysis revealed 9 genes (ARG2, CCR1, HMOX1, ATF2, IL-8, TIMP1, ESR1, HSPAIL, and SELE) that were commonly shared among four significantly altered signaling pathways. Among these, the transcripts encoding HMOX1 and ESR1 were identified using IPA as common potential therapeutic targets for Phase II/III clinical trial or FDA-approved drugs. The present study describes the transcriptional responses to cutaneous bromine vapor exposure identifying molecular networks and genes that could serve as targets for developing therapeutics for bromine-induced skin injury.

Preferential epigenetic programming of estrogen response after in utero xenoestrogen (bisphenol-A) exposure

PubMed Central

Jorgensen, Elisa M.; Alderman, Myles H.; Taylor, Hugh S.

2016-01-01

Bisphenol-A (BPA) is an environmentally ubiquitous estrogen-like endocrine-disrupting compound. Exposure to BPA in utero has been linked to female reproductive disorders, including endometrial hyperplasia and breast cancer. Estrogens are an etiological factor in many of these conditions. We sought to determine whether in utero exposure to BPA altered the global CpG methylation pattern of the uterine genome, subsequent gene expression, and estrogen response. Pregnant mice were exposed to an environmentally relevant dose of BPA or DMSO control. Uterine DNA and RNA were examined by using methylated DNA immunoprecipitation methylation microarray, expression microarray, and quantitative PCR. In utero BPA exposure altered the global CpG methylation profile of the uterine genome and subsequent gene expression. The effect on gene expression was not apparent until sexual maturation, which suggested that estrogen response was the primary alteration. Indeed, prenatal BPA exposure preferentially altered adult estrogen-responsive gene expression. Changes in estrogen response were accompanied by altered methylation that preferentially affected estrogen receptor-α (ERα)–binding genes. The majority of genes that demonstrated both altered expression and ERα binding had decreased methylation. BPA selectively altered the normal developmental programming of estrogen-responsive genes via modification of the genes that bind ERα. Gene–environment interactions driven by early life xenoestrogen exposure likely contributes to increased risk of estrogen-related disease in adults.—Jorgensen, E. M., Alderman, M. H., III, Taylor, H. S. Preferential epigenetic programming of estrogen response after in utero xenoestrogen (bisphenol-A) exposure. PMID:27312807

Stanniocalcin 2 is an estrogen-responsive gene coexpressed with the estrogen receptor in human breast cancer.

PubMed

Bouras, Toula; Southey, Melissa C; Chang, Andy C; Reddel, Roger R; Willhite, Dorian; Glynne, Richard; Henderson, Michael A; Armes, Jane E; Venter, Deon J

2002-03-01

Differences in gene expression are likely to explain the phenotypic variation between hormone-responsive and hormone-unresponsive breast cancers. In this study, DNA microarray analysis of approximately 10,000 known genes and 25,000 expressed sequence tag clusters was performed to identify genes induced by estrogen and repressed by the pure antiestrogen ICI 182 780 in vitro that correlated with estrogen receptor (ER) expression in primary breast carcinomas in vivo. Stanniocalcin (STC) 2 was identified as one of the genes that fulfilled these criteria. DNA microarray hybridization showed a 3-fold induction of STC2 mRNA expression in MCF-7 cells in < or = 3 h of estrogen exposure and a 3-fold repression in the presence of antiestrogen (one-way ANOVA, P < 0.0005). In 13 ER-positive and 12 ER-negative breast carcinomas, the microarray-derived mRNA levels observed for STC2 correlated with tumor ER mRNA (Pearson's correlation, r = 0.85; P < 0.0001) and ER protein status (Spearman's rank correlation, r = 0.73; P < 0.0001). The expression profile of STC2 was further confirmed by in situ hybridization and immunohistochemistry on a larger cohort of 236 unselected breast carcinomas using tissue microarrays. STC2 mRNA and protein expression were found to be associated with tumor ER status (Fisher's exact test, P < 0.005). The related gene, STC1, was also examined and shown to be associated with ER status in breast carcinomas (Fisher's exact test, P < 0.05). This study demonstrates the feasibility of using global gene expression data derived from an in vitro model to pinpoint novel estrogen-responsive genes of potential clinical relevance.

A RNA-Seq Analysis of the Rat Supraoptic Nucleus Transcriptome: Effects of Salt Loading on Gene Expression

PubMed Central

Salinas, Yasmmyn D.; Shi, YiJun; Greenwood, Michael; Hoe, See Ziau; Murphy, David; Gainer, Harold

2015-01-01

Magnocellular neurons (MCNs) in the hypothalamo-neurohypophysial system (HNS) are highly specialized to release large amounts of arginine vasopressin (Avp) or oxytocin (Oxt) into the blood stream and play critical roles in the regulation of body fluid homeostasis. The MCNs are osmosensory neurons and are excited by exposure to hypertonic solutions and inhibited by hypotonic solutions. The MCNs respond to systemic hypertonic and hypotonic stimulation with large changes in the expression of their Avp and Oxt genes, and microarray studies have shown that these osmotic perturbations also cause large changes in global gene expression in the HNS. In this paper, we examine gene expression in the rat supraoptic nucleus (SON) under normosmotic and chronic salt-loading SL) conditions by the first time using “new-generation”, RNA sequencing (RNA-Seq) methods. We reliably detect 9,709 genes as present in the SON by RNA-Seq, and 552 of these genes were changed in expression as a result of chronic SL. These genes reflect diverse functions, and 42 of these are involved in either transcriptional or translational processes. In addition, we compare the SON transcriptomes resolved by RNA-Seq methods with the SON transcriptomes determined by Affymetrix microarray methods in rats under the same osmotic conditions, and find that there are 6,466 genes present in the SON that are represented in both data sets, although 1,040 of the expressed genes were found only in the microarray data, and 2,762 of the expressed genes are selectively found in the RNA-Seq data and not the microarray data. These data provide the research community a comprehensive view of the transcriptome in the SON under normosmotic conditions and the changes in specific gene expression evoked by salt loading. PMID:25897513

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

PubMed Central

Ryan, Natalia; Chorley, Brian; Tice, Raymond R.; Judson, Richard; Corton, J. Christopher

2016-01-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including “very weak” agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. PMID:26865669

The efficacy of microarray screening for autosomal recessive retinitis pigmentosa in routine clinical practice

PubMed Central

van Huet, Ramon A. C.; Pierrache, Laurence H.M.; Meester-Smoor, Magda A.; Klaver, Caroline C.W.; van den Born, L. Ingeborgh; Hoyng, Carel B.; de Wijs, Ilse J.; Collin, Rob W. J.; Hoefsloot, Lies H.

2015-01-01

Purpose To determine the efficacy of multiple versions of a commercially available arrayed primer extension (APEX) microarray chip for autosomal recessive retinitis pigmentosa (arRP). Methods We included 250 probands suspected of arRP who were genetically analyzed with the APEX microarray between January 2008 and November 2013. The mode of inheritance had to be autosomal recessive according to the pedigree (including isolated cases). If the microarray identified a heterozygous mutation, we performed Sanger sequencing of exons and exon–intron boundaries of that specific gene. The efficacy of this microarray chip with the additional Sanger sequencing approach was determined by the percentage of patients that received a molecular diagnosis. We also collected data from genetic tests other than the APEX analysis for arRP to provide a detailed description of the molecular diagnoses in our study cohort. Results The APEX microarray chip for arRP identified the molecular diagnosis in 21 (8.5%) of the patients in our cohort. Additional Sanger sequencing yielded a second mutation in 17 patients (6.8%), thereby establishing the molecular diagnosis. In total, 38 patients (15.2%) received a molecular diagnosis after analysis using the microarray and additional Sanger sequencing approach. Further genetic analyses after a negative result of the arRP microarray (n = 107) resulted in a molecular diagnosis of arRP (n = 23), autosomal dominant RP (n = 5), X-linked RP (n = 2), and choroideremia (n = 1). Conclusions The efficacy of the commercially available APEX microarray chips for arRP appears to be low, most likely caused by the limitations of this technique and the genetic and allelic heterogeneity of RP. Diagnostic yields up to 40% have been reported for next-generation sequencing (NGS) techniques that, as expected, thereby outperform targeted APEX analysis. PMID:25999674

Principles of gene microarray data analysis.

PubMed

Mocellin, Simone; Rossi, Carlo Riccardo

2007-01-01

The development of several gene expression profiling methods, such as comparative genomic hybridization (CGH), differential display, serial analysis of gene expression (SAGE), and gene microarray, together with the sequencing of the human genome, has provided an opportunity to monitor and investigate the complex cascade of molecular events leading to tumor development and progression. The availability of such large amounts of information has shifted the attention of scientists towards a nonreductionist approach to biological phenomena. High throughput technologies can be used to follow changing patterns of gene expression over time. Among them, gene microarray has become prominent because it is easier to use, does not require large-scale DNA sequencing, and allows for the parallel quantification of thousands of genes from multiple samples. Gene microarray technology is rapidly spreading worldwide and has the potential to drastically change the therapeutic approach to patients affected with tumor. Therefore, it is of paramount importance for both researchers and clinicians to know the principles underlying the analysis of the huge amount of data generated with microarray technology.

16S rRNA gene-based phylogenetic microarray for simultaneous identification of members of the genus Burkholderia.

PubMed

Schönmann, Susan; Loy, Alexander; Wimmersberger, Céline; Sobek, Jens; Aquino, Catharine; Vandamme, Peter; Frey, Beat; Rehrauer, Hubert; Eberl, Leo

2009-04-01

For cultivation-independent and highly parallel analysis of members of the genus Burkholderia, an oligonucleotide microarray (phylochip) consisting of 131 hierarchically nested 16S rRNA gene-targeted oligonucleotide probes was developed. A novel primer pair was designed for selective amplification of a 1.3 kb 16S rRNA gene fragment of Burkholderia species prior to microarray analysis. The diagnostic performance of the microarray for identification and differentiation of Burkholderia species was tested with 44 reference strains of the genera Burkholderia, Pandoraea, Ralstonia and Limnobacter. Hybridization patterns based on presence/absence of probe signals were interpreted semi-automatically using the novel likelihood-based strategy of the web-tool Phylo- Detect. Eighty-eight per cent of the reference strains were correctly identified at the species level. The evaluated microarray was applied to investigate shifts in the Burkholderia community structure in acidic forest soil upon addition of cadmium, a condition that selected for Burkholderia species. The microarray results were in agreement with those obtained from phylogenetic analysis of Burkholderia 16S rRNA gene sequences recovered from the same cadmiumcontaminated soil, demonstrating the value of the Burkholderia phylochip for determinative and environmental studies.

Support vector machine and principal component analysis for microarray data classification

NASA Astrophysics Data System (ADS)

Astuti, Widi; Adiwijaya

2018-03-01

Cancer is a leading cause of death worldwide although a significant proportion of it can be cured if it is detected early. In recent decades, technology called microarray takes an important role in the diagnosis of cancer. By using data mining technique, microarray data classification can be performed to improve the accuracy of cancer diagnosis compared to traditional techniques. The characteristic of microarray data is small sample but it has huge dimension. Since that, there is a challenge for researcher to provide solutions for microarray data classification with high performance in both accuracy and running time. This research proposed the usage of Principal Component Analysis (PCA) as a dimension reduction method along with Support Vector Method (SVM) optimized by kernel functions as a classifier for microarray data classification. The proposed scheme was applied on seven data sets using 5-fold cross validation and then evaluation and analysis conducted on term of both accuracy and running time. The result showed that the scheme can obtained 100% accuracy for Ovarian and Lung Cancer data when Linear and Cubic kernel functions are used. In term of running time, PCA greatly reduced the running time for every data sets.

Experimental Approaches to Microarray Analysis of Tumor Samples

ERIC Educational Resources Information Center

Furge, Laura Lowe; Winter, Michael B.; Meyers, Jacob I.; Furge, Kyle A.

2008-01-01

Comprehensive measurement of gene expression using high-density nucleic acid arrays (i.e. microarrays) has become an important tool for investigating the molecular differences in clinical and research samples. Consequently, inclusion of discussion in biochemistry, molecular biology, or other appropriate courses of microarray technologies has…

Multiplex cDNA quantification method that facilitates the standardization of gene expression data

PubMed Central

Gotoh, Osamu; Murakami, Yasufumi; Suyama, Akira

2011-01-01

Microarray-based gene expression measurement is one of the major methods for transcriptome analysis. However, current microarray data are substantially affected by microarray platforms and RNA references because of the microarray method can provide merely the relative amounts of gene expression levels. Therefore, valid comparisons of the microarray data require standardized platforms, internal and/or external controls and complicated normalizations. These requirements impose limitations on the extensive comparison of gene expression data. Here, we report an effective approach to removing the unfavorable limitations by measuring the absolute amounts of gene expression levels on common DNA microarrays. We have developed a multiplex cDNA quantification method called GEP-DEAN (Gene expression profiling by DCN-encoding-based analysis). The method was validated by using chemically synthesized DNA strands of known quantities and cDNA samples prepared from mouse liver, demonstrating that the absolute amounts of cDNA strands were successfully measured with a sensitivity of 18 zmol in a highly multiplexed manner in 7 h. PMID:21415008

Spot detection and image segmentation in DNA microarray data.

PubMed

Qin, Li; Rueda, Luis; Ali, Adnan; Ngom, Alioune

2005-01-01

Following the invention of microarrays in 1994, the development and applications of this technology have grown exponentially. The numerous applications of microarray technology include clinical diagnosis and treatment, drug design and discovery, tumour detection, and environmental health research. One of the key issues in the experimental approaches utilising microarrays is to extract quantitative information from the spots, which represent genes in a given experiment. For this process, the initial stages are important and they influence future steps in the analysis. Identifying the spots and separating the background from the foreground is a fundamental problem in DNA microarray data analysis. In this review, we present an overview of state-of-the-art methods for microarray image segmentation. We discuss the foundations of the circle-shaped approach, adaptive shape segmentation, histogram-based methods and the recently introduced clustering-based techniques. We analytically show that clustering-based techniques are equivalent to the one-dimensional, standard k-means clustering algorithm that utilises the Euclidean distance.

Split-plot microarray experiments: issues of design, power and sample size.

PubMed

Tsai, Pi-Wen; Lee, Mei-Ling Ting

2005-01-01

This article focuses on microarray experiments with two or more factors in which treatment combinations of the factors corresponding to the samples paired together onto arrays are not completely random. A main effect of one (or more) factor(s) is confounded with arrays (the experimental blocks). This is called a split-plot microarray experiment. We utilise an analysis of variance (ANOVA) model to assess differentially expressed genes for between-array and within-array comparisons that are generic under a split-plot microarray experiment. Instead of standard t- or F-test statistics that rely on mean square errors of the ANOVA model, we use a robust method, referred to as 'a pooled percentile estimator', to identify genes that are differentially expressed across different treatment conditions. We illustrate the design and analysis of split-plot microarray experiments based on a case application described by Jin et al. A brief discussion of power and sample size for split-plot microarray experiments is also presented.

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni

PubMed Central

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-01-01

Background Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. Results We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1, cytoplasmic intermediate filament (IF) protein and transcription enzymes such as elongation factor 1α and EF-2. Conclusion Production of the first cDNA microarray for profiling gene expression in B. glabrata provides a foundation for expanding our understanding of pathways and genes involved in the snail internal defence system (IDS). We demonstrate resistant strain-specific expression of genes potentially associated with the snail IDS, ranging from signalling and inflammation responses through to lysis of proteinacous products (encapsulated sporocysts or phagocytosed parasite components) and processing/degradation of these targeted products by ubiquitination. PMID:19114004

Biomphalaria glabrata transcriptome: cDNA microarray profiling identifies resistant- and susceptible-specific gene expression in haemocytes from snail strains exposed to Schistosoma mansoni.

PubMed

Lockyer, Anne E; Spinks, Jenny; Kane, Richard A; Hoffmann, Karl F; Fitzpatrick, Jennifer M; Rollinson, David; Noble, Leslie R; Jones, Catherine S

2008-12-29

Biomphalaria glabrata is an intermediate snail host for Schistosoma mansoni, one of the important schistosomes infecting man. B. glabrata/S. mansoni provides a useful model system for investigating the intimate interactions between host and parasite. Examining differential gene expression between S. mansoni-exposed schistosome-resistant and susceptible snail lines will identify genes and pathways that may be involved in snail defences. We have developed a 2053 element cDNA microarray for B. glabrata containing clones from ORESTES (Open Reading frame ESTs) libraries, suppression subtractive hybridization (SSH) libraries and clones identified in previous expression studies. Snail haemocyte RNA, extracted from parasite-challenged resistant and susceptible snails, 2 to 24 h post-exposure to S. mansoni, was hybridized to the custom made cDNA microarray and 98 differentially expressed genes or gene clusters were identified, 94 resistant-associated and 4 susceptible-associated. Quantitative PCR analysis verified the cDNA microarray results for representative transcripts. Differentially expressed genes were annotated and clustered using gene ontology (GO) terminology and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway analysis. 61% of the identified differentially expressed genes have no known function including the 4 susceptible strain-specific transcripts. Resistant strain-specific expression of genes implicated in innate immunity of invertebrates was identified, including hydrolytic enzymes such as cathepsin L, a cysteine proteinase involved in lysis of phagocytosed particles; metabolic enzymes such as ornithine decarboxylase, the rate-limiting enzyme in the production of polyamines, important in inflammation and infection processes, as well as scavenging damaging free radicals produced during production of reactive oxygen species; stress response genes such as HSP70; proteins involved in signalling, such as importin 7 and copine 1, cytoplasmic intermediate filament (IF) protein and transcription enzymes such as elongation factor 1alpha and EF-2. Production of the first cDNA microarray for profiling gene expression in B. glabrata provides a foundation for expanding our understanding of pathways and genes involved in the snail internal defence system (IDS). We demonstrate resistant strain-specific expression of genes potentially associated with the snail IDS, ranging from signalling and inflammation responses through to lysis of proteinacous products (encapsulated sporocysts or phagocytosed parasite components) and processing/degradation of these targeted products by ubiquitination.

Fetal exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin induces expression of the chemokine genes Cxcl4 and Cxcl7 in the perinatal mouse brain.

PubMed

Mitsui, Tetsuo; Taniguchi, Naofumi; Kawasaki, Nobuchika; Kagami, Yoshihiro; Arita, Jun

2011-04-01

Fetal exposure to dioxins affects brain development and influences behaviors in human and laboratory animals. However, the cellular target and mechanisms of the neurotoxic action of dioxins are largely unknown. To investigate the molecular basis for the neurotoxicity of dioxins, pregnant C57BL/6 mice were exposed to 5 µg kg(-1) body weight of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) by a single gavage on gestational day 12.5 (GD 12.5), and gene expression of the whole fetal brain at GD 18.5 was profiled by DNA microarray analysis. The analysis revealed that the expression of two chemokine genes, Cxcl4 and Cxcl7, was up-regulated by TCDD exposure. Real-time PCR analysis verified that they were up-regulated by TCDD in both male and female brains, while the mRNA levels of a majority of other chemokines and their receptor genes were not affected. The up-regulation was TCDD dose-dependent and peaked at GD 15.5-18.5. In situ hybridization analysis showed that the Cxcl4 mRNA expression was localized in part of the surface of cerebral cortex and that the level was increased by TCDD treatment. These results suggest that Cxcl4 and Cxcl7 play a role in the development of neurobehavioral alterations that are triggered by in utero TCDD exposure and later surface in adults. Copyright © 2011 John Wiley & Sons, Ltd.

Environmental exposure to BDE47 is associated with increased diabetes prevalence: Evidence from community-based case-control studies and an animal experiment

NASA Astrophysics Data System (ADS)

Zhang, Zhan; Li, Shushu; Liu, Lu; Wang, Li; Xiao, Xue; Sun, Zhenzhen; Wang, Xichen; Wang, Chao; Wang, Meilin; Li, Lei; Xu, Qiujin; Gao, Weimin; Wang, Shou-Lin

2016-06-01

Brominated flame retardants exposure has been associated with increasing trends of diabetes and metabolic disease. Thus, the purpose of this study was to provide evidence of polybrominated diphenyl ethers (PBDEs) exposure in relation to diabetes prevalence and to reveal the potential underlying mechanism in epidemiological and animal studies. All the participants received a questionnaire, health examination, and the detection of 7 PBDE congeners in serum in two independent community-based studies from 2011 to 2012 in China. Male rats were exposed to 2,2’4,4’-tetrabromodiphenyl ether (BDE47) for 8 weeks to explore its effects on glucose homeostasis and potential mechanisms using high-throughput genomic analysis. Among the 7 congeners, BDE47 showed significant high detection rate and concentration in cases in Study I and Study II. Every tertile of BDE47 exposure significantly increased the risk of diabetes prevalence in Study I (Ptrend = 0.001) and Study II (Ptrend < 0.001). Additionally, BDE47 treatments induced hyperglycemia in rats. Furthermore, gene microarray analysis showed that diabetes pathway and three gene ontology terms involved in glucose transport were enriched. The results indicated that environmental exposure to BDE47 was associated with increased diabetes prevalence. However, further prospective and mechanistic studies are needed to the causation of diabetes in relation to BDE47.

Detection of cryptic pathogenic copy number variations and constitutional loss of heterozygosity using high resolution SNP microarray analysis in 117 patients referred for cytogenetic analysis and impact on clinical practice.

PubMed

Bruno, D L; Ganesamoorthy, D; Schoumans, J; Bankier, A; Coman, D; Delatycki, M; Gardner, R J M; Hunter, M; James, P A; Kannu, P; McGillivray, G; Pachter, N; Peters, H; Rieubland, C; Savarirayan, R; Scheffer, I E; Sheffield, L; Tan, T; White, S M; Yeung, A; Bowman, Z; Ngo, C; Choy, K W; Cacheux, V; Wong, L; Amor, D J; Slater, H R

2009-02-01

Microarray genome analysis is realising its promise for improving detection of genetic abnormalities in individuals with mental retardation and congenital abnormality. Copy number variations (CNVs) are now readily detectable using a variety of platforms and a major challenge is the distinction of pathogenic from ubiquitous, benign polymorphic CNVs. The aim of this study was to investigate replacement of time consuming, locus specific testing for specific microdeletion and microduplication syndromes with microarray analysis, which theoretically should detect all known syndromes with CNV aetiologies as well as new ones. Genome wide copy number analysis was performed on 117 patients using Affymetrix 250K microarrays. 434 CNVs (195 losses and 239 gains) were found, including 18 pathogenic CNVs and 9 identified as "potentially pathogenic". Almost all pathogenic CNVs were larger than 500 kb, significantly larger than the median size of all CNVs detected. Segmental regions of loss of heterozygosity larger than 5 Mb were found in 5 patients. Genome microarray analysis has improved diagnostic success in this group of patients. Several examples of recently discovered "new syndromes" were found suggesting they are more common than previously suspected and collectively are likely to be a major cause of mental retardation. The findings have several implications for clinical practice. The study revealed the potential to make genetic diagnoses that were not evident in the clinical presentation, with implications for pretest counselling and the consent process. The importance of contributing novel CNVs to high quality databases for genotype-phenotype analysis and review of guidelines for selection of individuals for microarray analysis is emphasised.

Transcriptional response of mysid crustacean, Americamysis bahia, is affected by subchronic exposure to nonylphenol.

PubMed

Uchida, Masaya; Hirano, Masashi; Ishibashi, Hiroshi; Kobayashi, Jun; Kagami, Yoshihiro; Koyanagi, Akiko; Kusano, Teruhiko; Koga, Minoru; Arizono, Koji

2016-11-01

Nonylphenol (NP) has been classified as an endocrine-disrupting chemical. In this study, we conducted mysid DNA microarray analysis with which has 2240 oligo DNA probes to observe differential gene expressions in mysid crustacean (Americamysis bahia) exposed to 1, 3, 10 and 30 μg/l of NP for 14 days. As a result, we found 31, 27, 39 and 68 genes were differentially expressed in the respective concentrations. Among these genes, the expressions of five particular genes were regulated in a similar manner at all concentrations of the NP exposure. So, we focused on one gene encoding cuticle protein, and another encoding cuticular protein analogous to peritrophins 1-H precursor. These genes were down-regulated by NP exposure in a dose-dependent manner, and it suggested that they were related in a reduction of the number of molting in mysids. Thus, they might become useful molecular biomarker candidates to evaluate molting inhibition in mysids. Copyright © 2016 Elsevier Inc. All rights reserved.

Cell cycle arrest and gene expression profiling of testis in mice exposed to fluoride.

PubMed

Su, Kai; Sun, Zilong; Niu, Ruiyan; Lei, Ying; Cheng, Jing; Wang, Jundong

2017-05-01

Exposure to fluoride results in low reproductive capacity; however, the mechanism underlying the impact of fluoride on male productive system still remains obscure. To assess the potential toxicity in testis of mice administrated with fluoride, global genome microarray and real-time PCR were performed to detect and identify the altered transcriptions. The results revealed that 763 differentially expressed genes were identified, including 330 up-regulated and 433 down-regulated genes, which were involved in spermatogenesis, apoptosis, DNA damage, DNA replication, and cell differentiation. Twelve differential expressed genes were selected to confirm the microarray results using real-time PCR, and the result kept the same tendency with that of microarray. Furthermore, compared with the control group, more apoptotic spermatogenic cells were observed in the fluoride group, and the spermatogonium were markedly increased in S phase and decreased in G2/M phase by fluoride. Our findings suggested global genome microarray provides an insight into the reproductive toxicity induced by fluoride, and several important biological clues for further investigations. © 2016 Wiley Periodicals, Inc. Environ Toxicol 32: 1558-1565, 2017. © 2016 Wiley Periodicals, Inc.

microRNA-183 is Essential for Hair Cell Regeneration after Neomycin Injury in Zebrafish.

PubMed

Kim, Chang Woo; Han, Ji Hyuk; Wu, Ling; Choi, Jae Young

2018-01-01

microRNAs (miRNAs) are non-coding RNAs composed of 20 to 22 nucleotides that regulate development and differentiation in various organs by silencing specific RNAs and regulating gene expression. In the present study, we show that the microRNA (miR)-183 cluster is upregulated during hair cell regeneration and that its inhibition reduces hair cell regeneration following neomycin-induced ototoxicity in zebrafish. miRNA expression patterns after neomycin exposure were analyzed using microarray chips. Quantitative polymerase chain reaction was performed to validate miR-183 cluster expression patterns following neomycin exposure (500 μM for 2 h). After injection of an antisense morpholino (MO) to miR-183 (MO-183) immediately after fertilization, hair cell regeneration after neomycin exposure in neuromast cells was evaluated by fluorescent staining (YO-PRO1). The MO-183 effect also was assessed in transgenic zebrafish larvae expressing green fluorescent protein (GFP) in inner ear hair cells. Microarray analysis clearly showed that the miR-183 cluster (miR-96, miR-182, and miR-183) was upregulated after neomycin treatment. We also confirmed upregulated expression of the miR-183 cluster during hair cell regeneration after neomycin-induced ototoxicity. miR-183 inhibition using MO-183 reduced hair cell regeneration in both wild-type and GFP transgenic zebrafish larvae. Our work demonstrates that the miR-183 cluster is essential for the regeneration of hair cells following ototoxic injury in zebrafish larvae. Therefore, regulation of the miR-183 cluster can be a novel target for stimulation of hair cell regeneration. © Copyright: Yonsei University College of Medicine 2018

Gene transcription patterns and energy reserves in Daphnia magna show no nanoparticle specific toxicity when exposed to ZnO and CuO nanoparticles.

PubMed

Adam, Nathalie; Vergauwen, Lucia; Blust, Ronny; Knapen, Dries

2015-04-01

There is still a lot of contradiction on whether metal ions are solely responsible for the observed toxicity of ZnO and CuO nanoparticles to aquatic species. While most experiments have studied nanoparticle effects at organismal levels (e.g. mortality, reproduction), effects at lower levels of biological organization may clarify the role of metal ions, nanoparticles and nanoparticle aggregates. In this study, the effect of ZnO and CuO nanoparticles was tested at two lower levels: energy reserves and gene transcription and compared with zinc and copper salts. Daphnia magna was exposed during 96h to 10% immobilization concentrations of all chemicals, after which daphnids were sampled for determination of glycogen, lipid and protein concentration and for a differential gene transcription analysis using microarray. The dissolved, nanoparticle and aggregated fraction in the medium was characterized. The results showed that ZnO nanoparticles had largely dissolved directly after addition to the test medium. The CuO nanoparticles mostly formed aggregates, while only a small fraction dissolved. The exposure to zinc (both nano and metal salt) had no effect on the available energy reserves. However, in the copper exposure, the glycogen, lipid and protein concentration in the exposed daphnids was lower than in the unexposed ones. When comparing the nanoparticle (ZnO or CuO) exposed daphnids to the metal salt (zinc or copper salt) exposed daphnids, the microarray results showed no significantly differentially transcribed gene fragments. The results indicate that under the current exposure conditions the toxicity of ZnO and CuO nanoparticles to D. magna is solely caused by toxic metal ions. Copyright © 2015 Elsevier Inc. All rights reserved.

In vitro expression of hard metal dust (WC-Co) - responsive genes in human peripheral blood mononucleated cells

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lombaert, Nooemi; Lison, Dominique; Van Hummelen, Paul

Hard metals consist of tungsten carbide (WC) and metallic cobalt (Co) particles and are important industrial materials produced for their extreme hardness and high wear resistance properties. While occupational exposure to metallic Co alone is apparently not associated with an increased risk of cancer, the WC-Co particle mixture was shown to be carcinogenic in exposed workers. The in vitro mutagenic/apoptogenic potential of WC-Co in human peripheral blood mononucleated cells was previously demonstrated by us. This study aimed at obtaining a broader view of the pathways responsible for WC-Co induced carcinogenicity, and in particular genotoxicity and apoptosis. We analyzed the profilemore » of gene expression induced in vitro by WC-Co versus control (24 h treatment) in human PBMC and monocytes using microarrays. The most significantly up-regulated pathways for WC-Co treated PBMC were apoptosis and stress/defense response; the most down-regulated was immune response. For WC-Co treated monocytes the most significantly up- and down-regulated pathways were nucleosome/chromatin assembly and immune response respectively. Quantitative RT-PCR data for a selection of the most strongly modulated genes (HMOX1, HSPA1A, HSPA1L, BNIP3, BNIP3L, ADORA2B, MT3, PLA2G7, TNFAIP6), and some additionally chosen apoptosis related genes (BCL2, BAX, FAS, FASL, TNF{alpha}), confirmed the microarray data after WC-Co exposure and demonstrated limited differences between the Co-containing compounds. Overall, this study provides the first analysis of gene expression induced by the WC-Co mixture showing a large profile of gene modulation and giving a preliminary indication for a hypoxia mimicking environment induced by WC-Co exposure.« less

Testing an aflatoxin B1 gene signature in rat archival tissues.

PubMed

Merrick, B Alex; Auerbach, Scott S; Stockton, Patricia S; Foley, Julie F; Malarkey, David E; Sills, Robert C; Irwin, Richard D; Tice, Raymond R

2012-05-21

Archival tissues from laboratory studies represent a unique opportunity to explore the relationship between genomic changes and agent-induced disease. In this study, we evaluated the applicability of qPCR for detecting genomic changes in formalin-fixed, paraffin-embedded (FFPE) tissues by determining if a subset of 14 genes from a 90-gene signature derived from microarray data and associated with eventual tumor development could be detected in archival liver, kidney, and lung of rats exposed to aflatoxin B1 (AFB1) for 90 days in feed at 1 ppm. These tissues originated from the same rats used in the microarray study. The 14 genes evaluated were Adam8, Cdh13, Ddit4l, Mybl2, Akr7a3, Akr7a2, Fhit, Wwox, Abcb1b, Abcc3, Cxcl1, Gsta5, Grin2c, and the C8orf46 homologue. The qPCR FFPE liver results were compared to the original liver microarray data and to qPCR results using RNA from fresh frozen liver. Archival liver paraffin blocks yielded 30 to 50 μg of degraded RNA that ranged in size from 0.1 to 4 kB. qPCR results from FFPE and fresh frozen liver samples were positively correlated (p ≤ 0.05) by regression analysis and showed good agreement in direction and proportion of change with microarray data for 11 of 14 genes. All 14 transcripts could be amplified from FFPE kidney RNA except the glutamate receptor gene Grin2c; however, only Abcb1b was significantly upregulated from control. Abundant constitutive transcripts, S18 and β-actin, could be amplified from lung FFPE samples, but the narrow RNA size range (25-500 bp length) prevented consistent detection of target transcripts. Overall, a discrete gene signature derived from prior transcript profiling and representing cell cycle progression, DNA damage response, and xenosensor and detoxication pathways was successfully applied to archival liver and kidney by qPCR and indicated that gene expression changes in response to subchronic AFB1 exposure occurred predominantly in the liver, the primary target for AFB1-induced tumors. We conclude that an evaluation of gene signatures in archival tissues can be an important toxicological tool for evaluating critical molecular events associated with chemical exposures.

MALDI-TOF mass spectrometry for quantitative gene expression analysis of acid responses in Staphylococcus aureus.

PubMed

Rode, Tone Mari; Berget, Ingunn; Langsrud, Solveig; Møretrø, Trond; Holck, Askild

2009-07-01

Microorganisms are constantly exposed to new and altered growth conditions, and respond by changing gene expression patterns. Several methods for studying gene expression exist. During the last decade, the analysis of microarrays has been one of the most common approaches applied for large scale gene expression studies. A relatively new method for gene expression analysis is MassARRAY, which combines real competitive-PCR and MALDI-TOF (matrix-assisted laser desorption/ionization time-of-flight) mass spectrometry. In contrast to microarray methods, MassARRAY technology is suitable for analysing a larger number of samples, though for a smaller set of genes. In this study we compare the results from MassARRAY with microarrays on gene expression responses of Staphylococcus aureus exposed to acid stress at pH 4.5. RNA isolated from the same stress experiments was analysed using both the MassARRAY and the microarray methods. The MassARRAY and microarray methods showed good correlation. Both MassARRAY and microarray estimated somewhat lower fold changes compared with quantitative real-time PCR (qRT-PCR). The results confirmed the up-regulation of the urease genes in acidic environments, and also indicated the importance of metal ion regulation. This study shows that the MassARRAY technology is suitable for gene expression analysis in prokaryotes, and has advantages when a set of genes is being analysed for an organism exposed to many different environmental conditions.

Microarray analysis of potential genes in the pathogenesis of recurrent oral ulcer.

PubMed

Han, Jingying; He, Zhiwei; Li, Kun; Hou, Lu

2015-01-01

Recurrent oral ulcer seriously threatens patients' daily life and health. This study investigated potential genes and pathways that participate in the pathogenesis of recurrent oral ulcer by high throughput bioinformatic analysis. RT-PCR and Western blot were applied to further verify screened interleukins effect. Recurrent oral ulcer related genes were collected from websites and papers, and further found out from Human Genome 280 6.0 microarray data. Each pathway of recurrent oral ulcer related genes were got through chip hybridization. RT-PCR was applied to test four recurrent oral ulcer related genes to verify the microarray data. Data transformation, scatter plot, clustering analysis, and expression pattern analysis were used to analyze recurrent oral ulcer related gene expression changes. Recurrent oral ulcer gene microarray was successfully established. Microarray showed that 551 genes involved in recurrent oral ulcer activity and 196 genes were recurrent oral ulcer related genes. Of them, 76 genes up-regulated, 62 genes down-regulated, and 58 genes up-/down-regulated. Total expression level up-regulated 752 times (60%) and down-regulated 485 times (40%). IL-2 plays an important role in the occurrence, development and recurrence of recurrent oral ulcer on the mRNA and protein levels. Gene microarray can be used to analyze potential genes and pathways in recurrent oral ulcer. IL-2 may be involved in the pathogenesis of recurrent oral ulcer.

A preliminary result of three-dimensional microarray technology to gene analysis with endoscopic ultrasound-guided fine-needle aspiration specimens and pancreatic juices

PubMed Central

2010-01-01

Background Analysis of gene expression and gene mutation may add information to be different from ordinary pathological tissue diagnosis. Since samples obtained endoscopically are very small, it is desired that more sensitive technology is developed for gene analysis. We investigated whether gene expression and gene mutation analysis by newly developed ultra-sensitive three-dimensional (3D) microarray is possible using small amount samples from endoscopic ultrasound-guided fine-needle aspiration (EUS-FNA) specimens and pancreatic juices. Methods Small amount samples from 17 EUS-FNA specimens and 16 pancreatic juices were obtained. After nucleic acid extraction, the samples were amplified with labeling and analyzed by the 3D microarray. Results The analyzable rate with the microarray was 46% (6/13) in EUS-FNA specimens of RNAlater® storage, and RNA degradations were observed in all the samples of frozen storage. In pancreatic juices, the analyzable rate was 67% (4/6) in frozen storage samples and 20% (2/10) in RNAlater® storage. EUS-FNA specimens were classified into cancer and non-cancer by gene expression analysis and K-ras codon 12 mutations were also detected using the 3D microarray. Conclusions Gene analysis from small amount samples obtained endoscopically was possible by newly developed 3D microarray technology. High quality RNA from EUS-FNA samples were obtained and remained in good condition only using RNA stabilizer. In contrast, high quality RNA from pancreatic juice samples were obtained only in frozen storage without RNA stabilizer. PMID:20416107

MAAMD: a workflow to standardize meta-analyses and comparison of affymetrix microarray data

PubMed Central

2014-01-01

Background Mandatory deposit of raw microarray data files for public access, prior to study publication, provides significant opportunities to conduct new bioinformatics analyses within and across multiple datasets. Analysis of raw microarray data files (e.g. Affymetrix CEL files) can be time consuming, complex, and requires fundamental computational and bioinformatics skills. The development of analytical workflows to automate these tasks simplifies the processing of, improves the efficiency of, and serves to standardize multiple and sequential analyses. Once installed, workflows facilitate the tedious steps required to run rapid intra- and inter-dataset comparisons. Results We developed a workflow to facilitate and standardize Meta-Analysis of Affymetrix Microarray Data analysis (MAAMD) in Kepler. Two freely available stand-alone software tools, R and AltAnalyze were embedded in MAAMD. The inputs of MAAMD are user-editable csv files, which contain sample information and parameters describing the locations of input files and required tools. MAAMD was tested by analyzing 4 different GEO datasets from mice and drosophila. MAAMD automates data downloading, data organization, data quality control assesment, differential gene expression analysis, clustering analysis, pathway visualization, gene-set enrichment analysis, and cross-species orthologous-gene comparisons. MAAMD was utilized to identify gene orthologues responding to hypoxia or hyperoxia in both mice and drosophila. The entire set of analyses for 4 datasets (34 total microarrays) finished in ~ one hour. Conclusions MAAMD saves time, minimizes the required computer skills, and offers a standardized procedure for users to analyze microarray datasets and make new intra- and inter-dataset comparisons. PMID:24621103

Gene Expression Browser: Large-Scale and Cross-Experiment Microarray Data Management, Search & Visualization

USDA-ARS?s Scientific Manuscript database

The amount of microarray gene expression data in public repositories has been increasing exponentially for the last couple of decades. High-throughput microarray data integration and analysis has become a critical step in exploring the large amount of expression data for biological discovery. Howeve...

Molecular and physiological responses to titanium dioxide ...

EPA Pesticide Factsheets

- Changes in tissue transcriptomes and productivity of Arabidopsis thaliana were investigated during exposure of plants to two widely-used engineered metal oxide nanoparticles, titanium dioxide (nano-titanium) and cerium dioxide (nano-cerium). Microarray analyses confirmed that exposure to either nanoparticle altered the transcriptomes of rosette leaves and roots, with comparatively larger numbers of differentially expressed genes (DEGs) found under nano-titania exposure. Nano-titania induced more DEGs in rosette leaves, whereas roots had more DEGs under nano-ceria exposure. MapMan analyses indicated that while nano-titania up-regulated overall and secondary metabolism in both tissues, metabolic processes under nano-ceria remained mostly unchanged. Gene enrichment analysis indicated that both nanoparticles mainly enriched ontology groups such as responses to stress (abiotic and biotic), and defense responses (pathogens), and responses to endogenous stimuli (hormones). Nano-titania specifically induced genes associated with photosynthesis, whereas nano-ceria induced expression of genes related to activating transcription factors, most notably those belonging to the ethylene responsive element binding protein family. Interestingly, there were also increased numbers of rosette leaves and plant biomass under nano-ceria exposure, but not under nano-titania. Other transcriptomic responses did not clearly relate to responses observed at the organism level. This may b

Parallel, confocal, and complete spectrum imager for fluorescent detection of high-density microarray

NASA Astrophysics Data System (ADS)

Bogdanov, Valery L.; Boyce-Jacino, Michael

1999-05-01

Confined arrays of biochemical probes deposited on a solid support surface (analytical microarray or 'chip') provide an opportunity to analysis multiple reactions simultaneously. Microarrays are increasingly used in genetics, medicine and environment scanning as research and analytical instruments. A power of microarray technology comes from its parallelism which grows with array miniaturization, minimization of reagent volume per reaction site and reaction multiplexing. An optical detector of microarray signals should combine high sensitivity, spatial and spectral resolution. Additionally, low-cost and a high processing rate are needed to transfer microarray technology into biomedical practice. We designed an imager that provides confocal and complete spectrum detection of entire fluorescently-labeled microarray in parallel. Imager uses microlens array, non-slit spectral decomposer, and high- sensitive detector (cooled CCD). Two imaging channels provide a simultaneous detection of localization, integrated and spectral intensities for each reaction site in microarray. A dimensional matching between microarray and imager's optics eliminates all in moving parts in instrumentation, enabling highly informative, fast and low-cost microarray detection. We report theory of confocal hyperspectral imaging with microlenses array and experimental data for implementation of developed imager to detect fluorescently labeled microarray with a density approximately 103 sites per cm2.

Transcriptional responses to complex mixtures - A review

EPA Science Inventory

Exposure of people to hazardous compounds is primarily through complex environmental mixtures, those that occur through media such as air, soil, water, food, cigarette smoke, and combustion emissions. Microarray technology offers the ability to query the entire genome after expos...

Altered gene expression in the brain and ovaries of zebrafish (Danio rerio) exposed to the aromatase inhibitor fadrozole: microarray analysis and hypothesis generation.

PubMed

Villeneuve, L; Wang, Rong-Lin; Bencic, David C; Biales, Adam D; Martinović, Dalma; Lazorchak, James M; Toth, Gregory; Ankley, Gerald T

2009-08-01

As part of a research effort examining system-wide responses of the hypothalamic-pituitary-gonadal (HPG) axis in fish to endocrine-active chemicals (EACs) with different modes of action, zebrafish (Danio rerio) were exposed to 25 or 100 microg/L of the aromatase inhibitor fadrozole for 24, 48, or 96 h. Global transcriptional response in brain and ovarian tissue of fish exposed to 25 microg/L of fadrozole was compared to that in control fish using a commercially available, 22,000-gene oligonucleotide microarray. Transcripts altered in brain were functionally linked to differentiation, development, DNA replication, and cell cycle. Additionally, multiple genes associated with the one-carbon pool by folate pathway (KEGG 00670) were significantly up-regulated. Transcripts altered in ovary were functionally linked to cell-cell adhesion, extracellular matrix, vasculogenesis, and development. Promoter motif analysis identified GATA-binding factor 2, Ikaros 2, alcohol dehydrogenase gene regulator 1, myoblast-determining factor, and several heat shock factors as being associated with coexpressed gene clusters that were differentially expressed following exposure to fadrozole. Based on the transcriptional changes observed, it was hypothesized that fadrozole elicits neurodegenerative stress in brain tissue and that fish cope with this stress through proliferation of radial glial cells. Additionally, it was hypothesized that changes of gene expression in the ovary of fadrozole-exposed zebrafish reflect disruption of oocyte maturation and ovulation because of impaired vitellogenesis. These hypotheses and others derived from the microarray results provide a foundation for future studies aimed at understanding responses of the HPG axis to EACs and other chemical stressors.

Multiplexed Analysis of Serum Breast and Ovarian Cancer Markers by Means of Suspension Bead-quantum Dot Microarrays

NASA Astrophysics Data System (ADS)

Brazhnik, Kristina; Sokolova, Zinaida; Baryshnikova, Maria; Bilan, Regina; Nabiev, Igor; Sukhanova, Alyona

Multiplexed analysis of cancer markers is crucial for early tumor diagnosis and screening. We have designed lab-on-a-bead microarray for quantitative detection of three breast cancer markers in human serum. Quantum dots were used as bead-bound fluorescent tags for identifying each marker by means of flow cytometry. Antigen-specific beads reliably detected CA 15-3, CEA, and CA 125 in serum samples, providing clear discrimination between the samples with respect to the antigen levels. The novel microarray is advantageous over the routine single-analyte ones due to the simultaneous detection of various markers. Therefore the developed microarray is a promising tool for serum tumor marker profiling.

Effects of crude oil exposure and elevated temperature on the liver transcriptome of polar cod (Boreogadus saida).

PubMed

Andersen, Øivind; Frantzen, Marianne; Rosland, Marte; Timmerhaus, Gerrit; Skugor, Adrijana; Krasnov, Aleksei

2015-08-01

Petroleum-related activities in the Arctic have raised concerns about the adverse effects of potential oil spill on the environment and living organisms. Polar cod plays a key role in the Arctic marine ecosystem and is an important species for monitoring oil pollution in this region. We examined potential interactions of oil pollution and global warming by analysing liver transcriptome changes in polar cod exposed to crude oil at elevated temperature. Adult males and females were kept at high (11°C) or normal (4°C) temperature for 5 days before exposure to mechanically dispersed crude oil for 2 days followed by recovery in clean sea water for 11 days at the two temperatures. Genome-wide microarray analysis of liver samples revealed numerous differentially expressed genes induced by uptake of oil as confirmed by increased levels of bile polycyclic aromatic hydrocarbon (PAH) metabolites. The hepatic response included genes playing important roles in xenobiotic detoxification and closely related biochemical processes, but also of importance for protein stress response, cell repair and immunity. Though magnitude of transcriptome responses was similar at both temperatures, the upregulated expression of cyp1a1 and several chaperone genes was much stronger at 11°C. Most gene expression changes returned to basal levels after recovery. The microarray results were validated by qPCR measurement of eleven selected genes representing both known and novel biomarkers to assess exposure to anthropogenic threats on polar cod. Strong upregulation of the gene encoding fibroblast growth factor 7 is proposed to protect the liver of polar fish with aglomerular kidneys from the toxic effect of accumulated biliary compounds. The highly altered liver transcriptome patterns after acute oil exposure and recovery suggests rapid responses in polar cod to oil pollutants and the ability to cope with toxicity in relatively short time. Copyright © 2015 Elsevier B.V. All rights reserved.

Methoxychlor affects multiple hormone signaling pathways in the largemouth bass (Micropterus salmoides) liver

PubMed Central

Martyniuk, Christopher J.; Spade, Daniel J.; Blum, Jason L.; Kroll, Kevin J.; Denslow, Nancy D.

2011-01-01

Methoxychlor (MXC) is an organochlorine pesticide that has been shown to have estrogenic activity by activating estrogen receptors and inducing vitellogenin production in male fish. Previous studies report that exposure to MXC induces changes in mRNA abundance of reproductive genes in the liver and testes of largemouth bass (Micropterus salmoides). The objective of the present study was to better characterize the mode of action of MXC by measuring the global transcriptomic response in the male largemouth liver using an oligonucleotide microarray. Microarray analysis identified highly significant changes in the expression of 37 transcripts (p<0.001) (20 induced and 17 decreased) in the liver after MXC injection and a total of 900 expression changes (p<0.05) in transcripts with high homology to known genes. Largemouth bass estrogen receptor alpha (esr1) and androgen receptor (ar) were among the transcripts that were increased in the liver after MXC treatment. Functional enrichment analysis identified the molecular functions of steroid binding and androgen receptor activity as well as steroid hormone receptor activity as being significantly over-represented gene ontology terms. Pathway analysis identified c-fos signaling as being putatively affected through both estrogen and androgen signaling. This study provides evidence that MXC elicits transcriptional effects through the estrogen receptor as well as androgen receptor-mediated pathways in the liver. PMID:21276474

Construction of a cDNA microarray derived from the ascidian Ciona intestinalis.

PubMed

Azumi, Kaoru; Takahashi, Hiroki; Miki, Yasufumi; Fujie, Manabu; Usami, Takeshi; Ishikawa, Hisayoshi; Kitayama, Atsusi; Satou, Yutaka; Ueno, Naoto; Satoh, Nori

2003-10-01

A cDNA microarray was constructed from a basal chordate, the ascidian Ciona intestinalis. The draft genome of Ciona has been read and inferred to contain approximately 16,000 protein-coding genes, and cDNAs for transcripts of 13,464 genes have been characterized and compiled as the "Ciona intestinalis Gene Collection Release I". In the present study, we constructed a cDNA microarray of these 13,464 Ciona genes. A preliminary experiment with Cy3- and Cy5-labeled probes showed extensive differential gene expression between fertilized eggs and larvae. In addition, there was a good correlation between results obtained by the present microarray analysis and those from previous EST analyses. This first microarray of a large collection of Ciona intestinalis cDNA clones should facilitate the analysis of global gene expression and gene networks during the embryogenesis of basal chordates.

Implementation of GenePattern within the Stanford Microarray Database.

PubMed

Hubble, Jeremy; Demeter, Janos; Jin, Heng; Mao, Maria; Nitzberg, Michael; Reddy, T B K; Wymore, Farrell; Zachariah, Zachariah K; Sherlock, Gavin; Ball, Catherine A

2009-01-01

Hundreds of researchers across the world use the Stanford Microarray Database (SMD; http://smd.stanford.edu/) to store, annotate, view, analyze and share microarray data. In addition to providing registered users at Stanford access to their own data, SMD also provides access to public data, and tools with which to analyze those data, to any public user anywhere in the world. Previously, the addition of new microarray data analysis tools to SMD has been limited by available engineering resources, and in addition, the existing suite of tools did not provide a simple way to design, execute and share analysis pipelines, or to document such pipelines for the purposes of publication. To address this, we have incorporated the GenePattern software package directly into SMD, providing access to many new analysis tools, as well as a plug-in architecture that allows users to directly integrate and share additional tools through SMD. In this article, we describe our implementation of the GenePattern microarray analysis software package into the SMD code base. This extension is available with the SMD source code that is fully and freely available to others under an Open Source license, enabling other groups to create a local installation of SMD with an enriched data analysis capability.

Identification of a transcriptional signature for the wound healing continuum

PubMed Central

Peake, Matthew A; Caley, Mathew; Giles, Peter J; Wall, Ivan; Enoch, Stuart; Davies, Lindsay C; Kipling, David; Thomas, David W; Stephens, Phil

2014-01-01

There is a spectrum/continuum of adult human wound healing outcomes ranging from the enhanced (nearly scarless) healing observed in oral mucosa to scarring within skin and the nonhealing of chronic skin wounds. Central to these outcomes is the role of the fibroblast. Global gene expression profiling utilizing microarrays is starting to give insight into the role of such cells during the healing process, but no studies to date have produced a gene signature for this wound healing continuum. Microarray analysis of adult oral mucosal fibroblast (OMF), normal skin fibroblast (NF), and chronic wound fibroblast (CWF) at 0 and 6 hours post-serum stimulation was performed. Genes whose expression increases following serum exposure in the order OMF < NF < CWF are candidates for a negative/impaired healing phenotype (the dysfunctional healing group), whereas genes with the converse pattern are potentially associated with a positive/preferential healing phenotype (the enhanced healing group). Sixty-six genes in the enhanced healing group and 38 genes in the dysfunctional healing group were identified. Overrepresentation analysis revealed pathways directly and indirectly associated with wound healing and aging and additional categories associated with differentiation, development, and morphogenesis. Knowledge of this wound healing continuum gene signature may in turn assist in the therapeutic assessment/treatment of a patient's wounds. PMID:24844339

Increased expression of protein kinase A inhibitor alpha (PKI-alpha) and decreased PKA-regulated genes in chronic intermittent alcohol exposure.

PubMed

Repunte-Canonigo, Vez; Lutjens, Robert; van der Stap, Lena D; Sanna, Pietro Paolo

2007-03-23

Intermittent models of alcohol exposure that mimic human patterns of alcohol consumption produce profound physiological and biochemical changes and induce rapid increases in alcohol self-administration. We used high-density oligonucleotide microarrays to investigate gene expression changes during chronic intermittent alcohol exposure in three brain regions that receive mesocorticolimbic dopaminergic projections and that are believed to be involved in alcohol's reinforcing actions: the medial prefrontal cortex, the nucleus accumbens and the amygdala. An independent replication of the experiment was used for RT-PCR validation of the microarray results. The protein kinase A inhibitor alpha (PKI-alpha, Pkia), a member of the endogenous PKI family implicated in reducing nuclear PKA activity, was found to be increased in all three regions tested. Conversely, we observed a downregulation of the expression of several PKA-regulated transcripts in one or more of the brain regions studied, including the activity and neurotransmitter-regulated early gene (Ania) - 1, -3, -7, -8, the transcription factors Egr1 and NGFI-B (Nr4a1) and the neuropeptide NPY. Reduced expression of PKA-regulated genes in mesocorticolimbic projection areas may have motivational significance in the rapid increase in alcohol self-administration induced by intermittent alcohol exposure.

Genome-scale cluster analysis of replicated microarrays using shrinkage correlation coefficient.

PubMed

Yao, Jianchao; Chang, Chunqi; Salmi, Mari L; Hung, Yeung Sam; Loraine, Ann; Roux, Stanley J

2008-06-18

Currently, clustering with some form of correlation coefficient as the gene similarity metric has become a popular method for profiling genomic data. The Pearson correlation coefficient and the standard deviation (SD)-weighted correlation coefficient are the two most widely-used correlations as the similarity metrics in clustering microarray data. However, these two correlations are not optimal for analyzing replicated microarray data generated by most laboratories. An effective correlation coefficient is needed to provide statistically sufficient analysis of replicated microarray data. In this study, we describe a novel correlation coefficient, shrinkage correlation coefficient (SCC), that fully exploits the similarity between the replicated microarray experimental samples. The methodology considers both the number of replicates and the variance within each experimental group in clustering expression data, and provides a robust statistical estimation of the error of replicated microarray data. The value of SCC is revealed by its comparison with two other correlation coefficients that are currently the most widely-used (Pearson correlation coefficient and SD-weighted correlation coefficient) using statistical measures on both synthetic expression data as well as real gene expression data from Saccharomyces cerevisiae. Two leading clustering methods, hierarchical and k-means clustering were applied for the comparison. The comparison indicated that using SCC achieves better clustering performance. Applying SCC-based hierarchical clustering to the replicated microarray data obtained from germinating spores of the fern Ceratopteris richardii, we discovered two clusters of genes with shared expression patterns during spore germination. Functional analysis suggested that some of the genetic mechanisms that control germination in such diverse plant lineages as mosses and angiosperms are also conserved among ferns. This study shows that SCC is an alternative to the Pearson correlation coefficient and the SD-weighted correlation coefficient, and is particularly useful for clustering replicated microarray data. This computational approach should be generally useful for proteomic data or other high-throughput analysis methodology.

Fabrication of Carbohydrate Microarrays by Boronate Formation.

PubMed

Adak, Avijit K; Lin, Ting-Wei; Li, Ben-Yuan; Lin, Chun-Cheng

2017-01-01

The interactions between soluble carbohydrates and/or surface displayed glycans and protein receptors are essential to many biological processes and cellular recognition events. Carbohydrate microarrays provide opportunities for high-throughput quantitative analysis of carbohydrate-protein interactions. Over the past decade, various techniques have been implemented for immobilizing glycans on solid surfaces in a microarray format. Herein, we describe a detailed protocol for fabricating carbohydrate microarrays that capitalizes on the intrinsic reactivity of boronic acid toward carbohydrates to form stable boronate diesters. A large variety of unprotected carbohydrates ranging in structure from simple disaccharides and trisaccharides to considerably more complex human milk and blood group (oligo)saccharides have been covalently immobilized in a single step on glass slides, which were derivatized with high-affinity boronic acid ligands. The immobilized ligands in these microarrays maintain the receptor-binding activities including those of lectins and antibodies according to the structures of their pendant carbohydrates for rapid analysis of a number of carbohydrate-recognition events within 30 h. This method facilitates the direct construction of otherwise difficult to obtain carbohydrate microarrays from underivatized glycans.

The Glycan Microarray Story from Construction to Applications.

PubMed

Hyun, Ji Young; Pai, Jaeyoung; Shin, Injae

2017-04-18

Not only are glycan-mediated binding processes in cells and organisms essential for a wide range of physiological processes, but they are also implicated in various pathological processes. As a result, elucidation of glycan-associated biomolecular interactions and their consequences is of great importance in basic biological research and biomedical applications. In 2002, we and others were the first to utilize glycan microarrays in efforts aimed at the rapid analysis of glycan-associated recognition events. Because they contain a number of glycans immobilized in a dense and orderly manner on a solid surface, glycan microarrays enable multiple parallel analyses of glycan-protein binding events while utilizing only small amounts of glycan samples. Therefore, this microarray technology has become a leading edge tool in studies aimed at elucidating roles played by glycans and glycan binding proteins in biological systems. In this Account, we summarize our efforts on the construction of glycan microarrays and their applications in studies of glycan-associated interactions. Immobilization strategies of functionalized and unmodified glycans on derivatized glass surfaces are described. Although others have developed immobilization techniques, our efforts have focused on improving the efficiencies and operational simplicity of microarray construction. The microarray-based technology has been most extensively used for rapid analysis of the glycan binding properties of proteins. In addition, glycan microarrays have been employed to determine glycan-protein interactions quantitatively, detect pathogens, and rapidly assess substrate specificities of carbohydrate-processing enzymes. More recently, the microarrays have been employed to identify functional glycans that elicit cell surface lectin-mediated cellular responses. Owing to these efforts, it is now possible to use glycan microarrays to expand the understanding of roles played by glycans and glycan binding proteins in biological systems.

EDGE3: A web-based solution for management and analysis of Agilent two color microarray experiments

PubMed Central

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-01-01

Background The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE3 was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. Results EDGE3 has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE3 is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Conclusion Here, we present EDGE3, an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE3 provides a means for managing RNA samples and arrays during the hybridization process. EDGE3 is freely available for download at . PMID:19732451

EDGE(3): a web-based solution for management and analysis of Agilent two color microarray experiments.

PubMed

Vollrath, Aaron L; Smith, Adam A; Craven, Mark; Bradfield, Christopher A

2009-09-04

The ability to generate transcriptional data on the scale of entire genomes has been a boon both in the improvement of biological understanding and in the amount of data generated. The latter, the amount of data generated, has implications when it comes to effective storage, analysis and sharing of these data. A number of software tools have been developed to store, analyze, and share microarray data. However, a majority of these tools do not offer all of these features nor do they specifically target the commonly used two color Agilent DNA microarray platform. Thus, the motivating factor for the development of EDGE(3) was to incorporate the storage, analysis and sharing of microarray data in a manner that would provide a means for research groups to collaborate on Agilent-based microarray experiments without a large investment in software-related expenditures or extensive training of end-users. EDGE(3) has been developed with two major functions in mind. The first function is to provide a workflow process for the generation of microarray data by a research laboratory or a microarray facility. The second is to store, analyze, and share microarray data in a manner that doesn't require complicated software. To satisfy the first function, EDGE3 has been developed as a means to establish a well defined experimental workflow and information system for microarray generation. To satisfy the second function, the software application utilized as the user interface of EDGE(3) is a web browser. Within the web browser, a user is able to access the entire functionality, including, but not limited to, the ability to perform a number of bioinformatics based analyses, collaborate between research groups through a user-based security model, and access to the raw data files and quality control files generated by the software used to extract the signals from an array image. Here, we present EDGE(3), an open-source, web-based application that allows for the storage, analysis, and controlled sharing of transcription-based microarray data generated on the Agilent DNA platform. In addition, EDGE(3) provides a means for managing RNA samples and arrays during the hybridization process. EDGE(3) is freely available for download at http://edge.oncology.wisc.edu/.

MAPPI-DAT: data management and analysis for protein-protein interaction data from the high-throughput MAPPIT cell microarray platform.

PubMed

Gupta, Surya; De Puysseleyr, Veronic; Van der Heyden, José; Maddelein, Davy; Lemmens, Irma; Lievens, Sam; Degroeve, Sven; Tavernier, Jan; Martens, Lennart

2017-05-01

Protein-protein interaction (PPI) studies have dramatically expanded our knowledge about cellular behaviour and development in different conditions. A multitude of high-throughput PPI techniques have been developed to achieve proteome-scale coverage for PPI studies, including the microarray based Mammalian Protein-Protein Interaction Trap (MAPPIT) system. Because such high-throughput techniques typically report thousands of interactions, managing and analysing the large amounts of acquired data is a challenge. We have therefore built the MAPPIT cell microArray Protein Protein Interaction-Data management & Analysis Tool (MAPPI-DAT) as an automated data management and analysis tool for MAPPIT cell microarray experiments. MAPPI-DAT stores the experimental data and metadata in a systematic and structured way, automates data analysis and interpretation, and enables the meta-analysis of MAPPIT cell microarray data across all stored experiments. MAPPI-DAT is developed in Python, using R for data analysis and MySQL as data management system. MAPPI-DAT is cross-platform and can be ran on Microsoft Windows, Linux and OS X/macOS. The source code and a Microsoft Windows executable are freely available under the permissive Apache2 open source license at https://github.com/compomics/MAPPI-DAT. jan.tavernier@vib-ugent.be or lennart.martens@vib-ugent.be. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press.

Pathway Analysis Hints Towards Beneficial Effects of Long-Term Vibration on Human Chondrocytes.

PubMed

Lützenberg, Ronald; Solano, Kendrick; Buken, Christoph; Sahana, Jayashree; Riwaldt, Stefan; Kopp, Sascha; Krüger, Marcus; Schulz, Herbert; Saar, Kathrin; Huebner, Norbert; Hemmersbach, Ruth; Bauer, Johann; Infanger, Manfred; Grimm, Daniela; Wehland, Markus

2018-06-27

Spaceflight negatively influences the function of cartilage tissue in vivo. In vitro human chondrocytes exhibit an altered gene expression of inflammation markers after a two-hour exposure to vibration. Little is known about the impact of long-term vibration on chondrocytes. Human cartilage cells were exposed for up to 24 h (VIB) on a specialised vibration platform (Vibraplex) simulating the vibration profile which occurs during parabolic flights and compared to static control conditions (CON). Afterwards, they were investigated by phase-contrast microscopy, rhodamine phalloidin staining, microarray analysis, qPCR and western blot analysis. Morphological investigations revealed no changes between CON and VIB chondrocytes. F-Actin staining showed no alterations of the cytoskeleton in VIB compared with CON cells. DAPI and TUNEL staining did not identify apoptotic cells. ICAM-1 was elevated and vimentin, beta-tubulin and osteopontin proteins were significantly reduced in VIB compared to CON cells. qPCR of cytoskeletal genes, ITGB1, SOX3, SOX5, SOX9 did not reveal differential regulations. Microarray analysis detected 13 differentially expressed genes, mostly indicating unspecific stimulations. Pathway analyses demonstrated interactions of PSMD4 and CNOT7 with ICAM. Long-term vibration did not damage human chondrocytes in vitro. The reduction of osteopontin protein and the down-regulation of PSMD4 and TBX15 gene expression suggest that in vitro long-term vibration might even positively influence cultured chondrocytes. © 2018 The Author(s). Published by S. Karger AG, Basel.

TOXICOGENOMIC ANALYSIS INCORPORATING OPERON-TRANSCRIPTIONAL COUPLING AND TOXICANT CONCENTRATRION-EXPRESSION RESPONSE: Analysis of MX-Treated Salmonella

EPA Science Inventory

What is the study? This study is the first to use microarray analysis in the Ames strains of Salmonella. The microarray chips were custom-designed for this study and are not commercially available, and we evaluated the well-studied drinking water mutagen, MX. Because much inform...

MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

EPA Science Inventory

MICROARRAY ANALYSIS OF DICHLOROACETIC ACID-INDUCED CHANGES IN GENE EXPRESSION

Dichloroacetic acid (DCA) is a major by-product of water disinfection by chlorination. Several studies have demonstrated the hepatocarcinogenicity of DCA in rodents when administered in dri...

Robust gene selection methods using weighting schemes for microarray data analysis.

PubMed

Kang, Suyeon; Song, Jongwoo

2017-09-02

A common task in microarray data analysis is to identify informative genes that are differentially expressed between two different states. Owing to the high-dimensional nature of microarray data, identification of significant genes has been essential in analyzing the data. However, the performances of many gene selection techniques are highly dependent on the experimental conditions, such as the presence of measurement error or a limited number of sample replicates. We have proposed new filter-based gene selection techniques, by applying a simple modification to significance analysis of microarrays (SAM). To prove the effectiveness of the proposed method, we considered a series of synthetic datasets with different noise levels and sample sizes along with two real datasets. The following findings were made. First, our proposed methods outperform conventional methods for all simulation set-ups. In particular, our methods are much better when the given data are noisy and sample size is small. They showed relatively robust performance regardless of noise level and sample size, whereas the performance of SAM became significantly worse as the noise level became high or sample size decreased. When sufficient sample replicates were available, SAM and our methods showed similar performance. Finally, our proposed methods are competitive with traditional methods in classification tasks for microarrays. The results of simulation study and real data analysis have demonstrated that our proposed methods are effective for detecting significant genes and classification tasks, especially when the given data are noisy or have few sample replicates. By employing weighting schemes, we can obtain robust and reliable results for microarray data analysis.

The application of DNA microarrays in gene expression analysis.

PubMed

van Hal, N L; Vorst, O; van Houwelingen, A M; Kok, E J; Peijnenburg, A; Aharoni, A; van Tunen, A J; Keijer, J

2000-03-31

DNA microarray technology is a new and powerful technology that will substantially increase the speed of molecular biological research. This paper gives a survey of DNA microarray technology and its use in gene expression studies. The technical aspects and their potential improvements are discussed. These comprise array manufacturing and design, array hybridisation, scanning, and data handling. Furthermore, it is discussed how DNA microarrays can be applied in the working fields of: safety, functionality and health of food and gene discovery and pathway engineering in plants.

Implementation of mutual information and bayes theorem for classification microarray data

NASA Astrophysics Data System (ADS)

Dwifebri Purbolaksono, Mahendra; Widiastuti, Kurnia C.; Syahrul Mubarok, Mohamad; Adiwijaya; Aminy Ma’ruf, Firda

2018-03-01

Microarray Technology is one of technology which able to read the structure of gen. The analysis is important for this technology. It is for deciding which attribute is more important than the others. Microarray technology is able to get cancer information to diagnose a person’s gen. Preparation of microarray data is a huge problem and takes a long time. That is because microarray data contains high number of insignificant and irrelevant attributes. So, it needs a method to reduce the dimension of microarray data without eliminating important information in every attribute. This research uses Mutual Information to reduce dimension. System is built with Machine Learning approach specifically Bayes Theorem. This theorem uses a statistical and probability approach. By combining both methods, it will be powerful for Microarray Data Classification. The experiment results show that system is good to classify Microarray data with highest F1-score using Bayesian Network by 91.06%, and Naïve Bayes by 88.85%.

Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB.

PubMed

Chatziioannou, Aristotelis; Moulos, Panagiotis; Kolisis, Fragiskos N

2009-10-27

The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods. We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime. Gene ARMADA provides a highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.

Microarray data mining using Bioconductor packages.

PubMed

Nie, Haisheng; Neerincx, Pieter B T; van der Poel, Jan; Ferrari, Francesco; Bicciato, Silvio; Leunissen, Jack A M; Groenen, Martien A M

2009-07-16

This paper describes the results of a Gene Ontology (GO) term enrichment analysis of chicken microarray data using the Bioconductor packages. By checking the enriched GO terms in three contrasts, MM8-PM8, MM8-MA8, and MM8-MM24, of the provided microarray data during this workshop, this analysis aimed to investigate the host reactions in chickens occurring shortly after a secondary challenge with either a homologous or heterologous species of Eimeria. The results of GO enrichment analysis using GO terms annotated to chicken genes and GO terms annotated to chicken-human orthologous genes were also compared. Furthermore, a locally adaptive statistical procedure (LAP) was performed to test differentially expressed chromosomal regions, rather than individual genes, in the chicken genome after Eimeria challenge. GO enrichment analysis identified significant (raw p-value < 0.05) GO terms for all three contrasts included in the analysis. Some of the GO terms linked to, generally, primary immune responses or secondary immune responses indicating the GO enrichment analysis is a useful approach to analyze microarray data. The comparisons of GO enrichment results using chicken gene information and chicken-human orthologous gene information showed more refined GO terms related to immune responses when using chicken-human orthologous gene information, this suggests that using chicken-human orthologous gene information has higher power to detect significant GO terms with more refined functionality. Furthermore, three chromosome regions were identified to be significantly up-regulated in contrast MM8-PM8 (q-value < 0.01). Overall, this paper describes a practical approach to analyze microarray data in farm animals where the genome information is still incomplete. For farm animals, such as chicken, with currently limited gene annotation, borrowing gene annotation information from orthologous genes in well-annotated species, such as human, will help improve the pathway analysis results substantially. Furthermore, LAP analysis approach is a relatively new and very useful way to be applied in microarray analysis.

Polyadenylation state microarray (PASTA) analysis.

PubMed

Beilharz, Traude H; Preiss, Thomas

2011-01-01

Nearly all eukaryotic mRNAs terminate in a poly(A) tail that serves important roles in mRNA utilization. In the cytoplasm, the poly(A) tail promotes both mRNA stability and translation, and these functions are frequently regulated through changes in tail length. To identify the scope of poly(A) tail length control in a transcriptome, we developed the polyadenylation state microarray (PASTA) method. It involves the purification of mRNA based on poly(A) tail length using thermal elution from poly(U) sepharose, followed by microarray analysis of the resulting fractions. In this chapter we detail our PASTA approach and describe some methods for bulk and mRNA-specific poly(A) tail length measurements of use to monitor the procedure and independently verify the microarray data.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sobinoff, A.P.; Pye, V.; Nixon, B.

Benzo(a)pyrene (BaP) is an ovotoxic constituent of cigarette smoke associated with pre-mature ovarian failure and decreased rates of conception in IVF patients. Although the overall effect of BaP on female fertility has been documented, the exact molecular mechanisms behind its ovotoxicity remain elusive. In this study we examined the effects of BaP exposure on the ovarian transcriptome, and observed the effects of in vivo exposure on oocyte dysfunction. Microarray analysis of BaP cultured neonatal ovaries revealed a complex mechanism of ovotoxicity involving a small cohort of genes associated with follicular growth, cell cycle progression, and cell death. Histomorphological and immunohistochemicalmore » analysis supported these results, with BaP exposure causing increased primordial follicle activation and developing follicle atresia in vitro and in vivo. Functional analysis of oocytes obtained from adult Swiss mice treated neonatally revealed significantly increased levels of mitochondrial ROS/lipid peroxidation, and severely reduced sperm-egg binding and fusion in both low (1.5 mg/kg/daily) and high (3 mg/kg/daily) dose treatments. Our results reveal a complex mechanism of BaP induced ovotoxicity involving developing follicle atresia and accelerated primordial follicle activation, and suggest short term neonatal BaP exposure causes mitochondrial leakage resulting in reduced oolemma fluidity and impaired fertilisation in adulthood. This study highlights BaP as a key compound which may be partially responsible for the documented effects of cigarette smoke on follicular development and sub-fertility. -- Highlights: ► BaP exposure up-regulates canonical pathways linked with follicular growth/atresia. ► BaP causes primordial follicle activation and developing follicle atresia. ► BaP causes oocyte mitochondrial ROS and lipid peroxidation, impairing fertilisation. ► Short term neonatal BaP exposure compromises adult oocyte quality.« less

The Use of Atomic Force Microscopy for 3D Analysis of Nucleic Acid Hybridization on Microarrays.

PubMed

Dubrovin, E V; Presnova, G V; Rubtsova, M Yu; Egorov, A M; Grigorenko, V G; Yaminsky, I V

2015-01-01

Oligonucleotide microarrays are considered today to be one of the most efficient methods of gene diagnostics. The capability of atomic force microscopy (AFM) to characterize the three-dimensional morphology of single molecules on a surface allows one to use it as an effective tool for the 3D analysis of a microarray for the detection of nucleic acids. The high resolution of AFM offers ways to decrease the detection threshold of target DNA and increase the signal-to-noise ratio. In this work, we suggest an approach to the evaluation of the results of hybridization of gold nanoparticle-labeled nucleic acids on silicon microarrays based on an AFM analysis of the surface both in air and in liquid which takes into account of their three-dimensional structure. We suggest a quantitative measure of the hybridization results which is based on the fraction of the surface area occupied by the nanoparticles.

The Utility of Chromosomal Microarray Analysis in Developmental and Behavioral Pediatrics

ERIC Educational Resources Information Center

Beaudet, Arthur L.

2013-01-01

Chromosomal microarray analysis (CMA) has emerged as a powerful new tool to identify genomic abnormalities associated with a wide range of developmental disabilities including congenital malformations, cognitive impairment, and behavioral abnormalities. CMA includes array comparative genomic hybridization (CGH) and single nucleotide polymorphism…

Evaluation of chronic lymphocytic leukemia by oligonucleotide-based microarray analysis uncovers novel aberrations not detected by FISH or cytogenetic analysis

PubMed Central

2011-01-01

Background Cytogenetic evaluation is a key component of the diagnosis and prognosis of chronic lymphocytic leukemia (CLL). We performed oligonucleotide-based comparative genomic hybridization microarray analysis on 34 samples with CLL and known abnormal karyotypes previously determined by cytogenetics and/or fluorescence in situ hybridization (FISH). Results Using a custom designed microarray that targets >1800 genes involved in hematologic disease and other malignancies, we identified additional cryptic aberrations and novel findings in 59% of cases. These included gains and losses of genes associated with cell cycle regulation, apoptosis and susceptibility loci on 3p21.31, 5q35.2q35.3, 10q23.31q23.33, 11q22.3, and 22q11.23. Conclusions Our results show that microarray analysis will detect known aberrations, including microscopic and cryptic alterations. In addition, novel genomic changes will be uncovered that may become important prognostic predictors or treatment targets for CLL in the future. PMID:22087757

Effects of developmental lead exposure on the hippocampal methylome: Influences of sex and timing and level of exposure.

PubMed

Singh, G; Singh, V; Wang, Zi-Xuan; Voisin, G; Lefebvre, F; Navenot, J-M; Evans, B; Verma, M; Anderson, D W; Schneider, J S

2018-06-15

Developmental lead (Pb) exposure results in persistent cognitive/behavioral impairments as well as an elevated risk for developing a variety of diseases in later life. Environmental exposures during development can result in a variety of epigenetic changes, including alterations in DNA methylation, that can influence gene expression patterns and affect the function and development of the nervous system. The present promoter-based methylation microarray profiling study explored the extent to which developmental Pb exposure may modify the methylome of a brain region, hippocampus, known to be sensitive to the effects of Pb exposure. Male and female Long Evans rats were exposed to 0 ppm, 150 ppm, 375 ppm, or 750 ppm Pb through perinatal exposures (gestation through lactation), early postnatal exposures (birth through weaning), or long-term postnatal exposures (birth through postnatal day 55). Results showed a significant contribution of sex to the hippocampal methylome and effects of Pb exposure level, with non-linear dose response effects on methylation. Surprisingly, the developmental period of exposure contributed only a small amount of variance to the overall data and gene ontology (GO) analysis revealed the largest number of overrepresented GO terms in the groups with the lowest level of exposure. The highest number of significant differentially methylated regions was found in females exposed to Pb at the lowest exposure level. Our data reinforce the significant effect that low level Pb exposure may have on gene-specific DNA methylation patterns in brain and that this occurs in a sex-dependent manner. Copyright © 2018 Elsevier B.V. All rights reserved.

Analysis of microRNA and gene expression profiling in triazole fungicide-treated HepG2 cell line.

PubMed

An, Yu Ri; Kim, Seung Jun; Oh, Moon-Ju; Kim, Hyun-Mi; Shim, Il-Seob; Kim, Pil-Je; Choi, Kyunghee; Hwang, Seung Yong

2013-01-07

MicroRNA (miRNA) plays an important role in various diseases and in cellular and molecular responses to toxicants. In the present study, we investigated differential expression of miRNAs in response to three triazole fungicides (myclobutanil, propiconazole, and triadimefon). The human hepatoma cell line (HepG2) was treated with the above triazoles for 3 h or 48 h. miRNA-based microarray experiments were carried out using the Agilent human miRNA v13 array. At early exposure (3h), six miRNAs were differentially expressed and at late exposure (48 h), three miRNAs were significantly expressed. Overall, this study provides an array of potential biomarkers for the above triazole fungicides. Furthermore, these miRNAs induced by triazoles could be the foundation for the development of a miRNA-based toxic biomarker library that can predict environmental toxicity. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Microarray analysis of toxicogenomic effects of Ortho-phenylphenol in Staphylococcus aureus

PubMed Central

Jang, Hyeung-Jin; Nde, Chantal; Toghrol, Freshteh; Bentley, William E

2008-01-01

Background Staphylococcus aureus (S. aureus), is responsible for many infectious diseases, ranging from benign skin infections to life-threatening endocarditis and toxic shock syndrome. Ortho-phenylphenol (OPP) is an antimicrobial agent and an active ingredient of EPA-registered disinfectants with wide human exposure in various agricultural, hospital and veterinary disinfectant products. Despite many uses, an understanding of a cellular response to OPP and it's mechanism of action, targeted genes, and the connectivity between targeted genes and the rest of cell metabolism remains obscure. Results Herein, we performed a genome-wide transcriptome analysis of the cellular responses of S. aureus when exposed to 0.82 mM of OPP for 20 and 60 min. Our data indicated that OPP downregulated the biosynthesis of many amino acids, which are required for protein synthesis. In particular, the genes encoding the enzymes of the diaminopimelate (DAP) pathway which results in lysine biosynthesis were significantly downregualted. Intriguingly, we revealed that the transcription of genes encoding ribosomal proteins was upregulated by OPP and at the same time, the genes encoding iron acquisition and transport were downregulated. The genes encoding virulence factors were upregulated and genes encoding phospholipids were downregulated upon 20 min exposure to OPP. Conclusion By using microarray analysis that enables us to simultaneously and globally examine the complete transcriptome during cellular responses, we have revealed novel information regarding the mode of action of OPP on Staphylococcus: OPP inhibits anabolism of many amino acids and highly downregulates the genes that encode the enzymes involved in the DAP pathway. Lysine and DAP are essential for building up the peptidoglycan cell wall. It was concluded that the mode of action of OPP is similar to the mechanism of action of some antibiotics. The discovery of this phenomenon provides useful information that will benefit further antimicrobial research on S. aureus. PMID:18793396

A CROSS-SPECIES APPROACH TO USING GENOMICS TOOLS IN AQUATIC TOXICOLOGY

EPA Science Inventory

Microarray technology has proven to be a useful tool for analyzing the transcriptome of various organisms representing conditions such as disease states, developmental stages, and responses to chemical exposure. Most commercially available arrays are limited to organisms that ha...

Molecular and physiological responses to titanium dioxide and cerium oxide nanoparticles in Arabidopsis

EPA Science Inventory

- Changes in tissue transcriptomes and productivity of Arabidopsis thaliana were investigated during exposure of plants to two widely-used engineered metal oxide nanoparticles, titanium dioxide (nano-titanium) and cerium dioxide (nano-cerium). Microarray analyses confirmed that e...

Interim report on updated microarray probes for the LLNL Burkholderia pseudomallei SNP array

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gardner, S; Jaing, C

2012-03-27

The overall goal of this project is to forensically characterize 100 unknown Burkholderia isolates in the US-Australia collaboration. We will identify genome-wide single nucleotide polymorphisms (SNPs) from B. pseudomallei and near neighbor species including B. mallei, B. thailandensis and B. oklahomensis. We will design microarray probes to detect these SNP markers and analyze 100 Burkholderia genomic DNAs extracted from environmental, clinical and near neighbor isolates from Australian collaborators on the Burkholderia SNP microarray. We will analyze the microarray genotyping results to characterize the genetic diversity of these new isolates and triage the samples for whole genome sequencing. In this interimmore » report, we described the SNP analysis and the microarray probe design for the Burkholderia SNP microarray.« less

Generalized Correlation Coefficient for Non-Parametric Analysis of Microarray Time-Course Data.

PubMed

Tan, Qihua; Thomassen, Mads; Burton, Mark; Mose, Kristian Fredløv; Andersen, Klaus Ejner; Hjelmborg, Jacob; Kruse, Torben

2017-06-06

Modeling complex time-course patterns is a challenging issue in microarray study due to complex gene expression patterns in response to the time-course experiment. We introduce the generalized correlation coefficient and propose a combinatory approach for detecting, testing and clustering the heterogeneous time-course gene expression patterns. Application of the method identified nonlinear time-course patterns in high agreement with parametric analysis. We conclude that the non-parametric nature in the generalized correlation analysis could be an useful and efficient tool for analyzing microarray time-course data and for exploring the complex relationships in the omics data for studying their association with disease and health.

MGDB: crossing the marker genes of a user microarray with a database of public-microarrays marker genes.

PubMed

Huerta, Mario; Munyi, Marc; Expósito, David; Querol, Enric; Cedano, Juan

2014-06-15

The microarrays performed by scientific teams grow exponentially. These microarray data could be useful for researchers around the world, but unfortunately they are underused. To fully exploit these data, it is necessary (i) to extract these data from a repository of the high-throughput gene expression data like Gene Expression Omnibus (GEO) and (ii) to make the data from different microarrays comparable with tools easy to use for scientists. We have developed these two solutions in our server, implementing a database of microarray marker genes (Marker Genes Data Base). This database contains the marker genes of all GEO microarray datasets and it is updated monthly with the new microarrays from GEO. Thus, researchers can see whether the marker genes of their microarray are marker genes in other microarrays in the database, expanding the analysis of their microarray to the rest of the public microarrays. This solution helps not only to corroborate the conclusions regarding a researcher's microarray but also to identify the phenotype of different subsets of individuals under investigation, to frame the results with microarray experiments from other species, pathologies or tissues, to search for drugs that promote the transition between the studied phenotypes, to detect undesirable side effects of the treatment applied, etc. Thus, the researcher can quickly add relevant information to his/her studies from all of the previous analyses performed in other studies as long as they have been deposited in public repositories. Marker-gene database tool: http://ibb.uab.es/mgdb © The Author 2014. Published by Oxford University Press.

Repeated Exposure to Neurotoxic Levels of Chlorpyriphos Alters Hippocampal Expression of Neurotrophins and Neuropeptides

DTIC Science & Technology

2016-01-13

Institute for Science and Engineering, Oak Ridge, TN 37831, United States bUnited States Army Center for Environmental Health Research (USACEHR...online 13 January 2016 Keywords: Chlorpyrifos Cholinesterase inhibition Gene expression Microarray miRNA Organophosphorus pesticide A B S T R A C T...Chlorpyrifos (CPF), an organophosphorus pesticide (OP), is one of the most widely used pesticides in the world. Subchronic exposures to CPF that do not

Transcriptome analysis of salinity stress responses in common wheat using a 22k oligo-DNA microarray.

PubMed

Kawaura, Kanako; Mochida, Keiichi; Yamazaki, Yukiko; Ogihara, Yasunari

2006-04-01

In this study, we constructed a 22k wheat oligo-DNA microarray. A total of 148,676 expressed sequence tags of common wheat were collected from the database of the Wheat Genomics Consortium of Japan. These were grouped into 34,064 contigs, which were then used to design an oligonucleotide DNA microarray. Following a multistep selection of the sense strand, 21,939 60-mer oligo-DNA probes were selected for attachment on the microarray slide. This 22k oligo-DNA microarray was used to examine the transcriptional response of wheat to salt stress. More than 95% of the probes gave reproducible hybridization signals when targeted with RNAs extracted from salt-treated wheat shoots and roots. With the microarray, we identified 1,811 genes whose expressions changed more than 2-fold in response to salt. These included genes known to mediate response to salt, as well as unknown genes, and they were classified into 12 major groups by hierarchical clustering. These gene expression patterns were also confirmed by real-time reverse transcription-PCR. Many of the genes with unknown function were clustered together with genes known to be involved in response to salt stress. Thus, analysis of gene expression patterns combined with gene ontology should help identify the function of the unknown genes. Also, functional analysis of these wheat genes should provide new insight into the response to salt stress. Finally, these results indicate that the 22k oligo-DNA microarray is a reliable method for monitoring global gene expression patterns in wheat.

Identifying molecular features for prostate cancer with Gleason 7 based on microarray gene expression profiles.

PubMed

Bălăcescu, Loredana; Bălăcescu, O; Crişan, N; Fetica, B; Petruţ, B; Bungărdean, Cătălina; Rus, Meda; Tudoran, Oana; Meurice, G; Irimie, Al; Dragoş, N; Berindan-Neagoe, Ioana

2011-01-01

Prostate cancer represents the first leading cause of cancer among western male population, with different clinical behavior ranging from indolent to metastatic disease. Although many molecules and deregulated pathways are known, the molecular mechanisms involved in the development of prostate cancer are not fully understood. The aim of this study was to explore the molecular variation underlying the prostate cancer, based on microarray analysis and bioinformatics approaches. Normal and prostate cancer tissues were collected by macrodissection from prostatectomy pieces. All prostate cancer specimens used in our study were Gleason score 7. Gene expression microarray (Agilent Technologies) was used for Whole Human Genome evaluation. The bioinformatics and functional analysis were based on Limma and Ingenuity software. The microarray analysis identified 1119 differentially expressed genes between prostate cancer and normal prostate, which were up- or down-regulated at least 2-fold. P-values were adjusted for multiple testing using Benjamini-Hochberg method with a false discovery rate of 0.01. These genes were analyzed with Ingenuity Pathway Analysis software and were established 23 genetic networks. Our microarray results provide new information regarding the molecular networks in prostate cancer stratified as Gleason 7. These data highlighted gene expression profiles for better understanding of prostate cancer progression.

Global view of the mechanisms of improved learning and memory capability in mice with music-exposure by microarray.

PubMed

Meng, Bo; Zhu, Shujia; Li, Shijia; Zeng, Qingwen; Mei, Bing

2009-08-28

Music has been proved beneficial to improve learning and memory in many species including human in previous research work. Although some genes have been identified to contribute to the mechanisms, it is believed that the effect of music is manifold, behind which must concern a complex regulation network. To further understand the mechanisms, we exposed the mice to classical music for one month. The subsequent behavioral experiments showed improvement of spatial learning capability and elevation of fear-motivated memory in the mice with music-exposure as compared to the naïve mice. Meanwhile, we applied the microarray to compare the gene expression profiles of the hippocampus and cortex between the mice with music-exposure and the naïve mice. The results showed approximately 454 genes in cortex (200 genes up-regulated and 254 genes down-regulated) and 437 genes in hippocampus (256 genes up-regulated and 181 genes down-regulated) were significantly affected in music-exposing mice, which mainly involved in ion channel activity and/or synaptic transmission, cytoskeleton, development, transcription, hormone activity. Our work may provide some hints for better understanding the effects of music on learning and memory.

Porous Silicon Antibody Microarrays for Quantitative Analysis: Measurement of Free and Total PSA in Clinical Plasma Samples

PubMed Central

Tojo, Axel; Malm, Johan; Marko-Varga, György; Lilja, Hans; Laurell, Thomas

2014-01-01

The antibody microarrays have become widespread, but their use for quantitative analyses in clinical samples has not yet been established. We investigated an immunoassay based on nanoporous silicon antibody microarrays for quantification of total prostate-specific-antigen (PSA) in 80 clinical plasma samples, and provide quantitative data from a duplex microarray assay that simultaneously quantifies free and total PSA in plasma. To further develop the assay the porous silicon chips was placed into a standard 96-well microtiter plate for higher throughput analysis. The samples analyzed by this quantitative microarray were 80 plasma samples obtained from men undergoing clinical PSA testing (dynamic range: 0.14-44ng/ml, LOD: 0.14ng/ml). The second dataset, measuring free PSA (dynamic range: 0.40-74.9ng/ml, LOD: 0.47ng/ml) and total PSA (dynamic range: 0.87-295ng/ml, LOD: 0.76ng/ml), was also obtained from the clinical routine. The reference for the quantification was a commercially available assay, the ProStatus PSA Free/Total DELFIA. In an analysis of 80 plasma samples the microarray platform performs well across the range of total PSA levels. This assay might have the potential to substitute for the large-scale microtiter plate format in diagnostic applications. The duplex assay paves the way for a future quantitative multiplex assay, which analyses several prostate cancer biomarkers simultaneously. PMID:22921878

Systematic evaluation of RNA quality, microarray data reliability and pathway analysis in fresh, fresh frozen and formalin-fixed paraffin-embedded tissue samples.

PubMed

Wimmer, Isabella; Tröscher, Anna R; Brunner, Florian; Rubino, Stephen J; Bien, Christian G; Weiner, Howard L; Lassmann, Hans; Bauer, Jan

2018-04-20

Formalin-fixed paraffin-embedded (FFPE) tissues are valuable resources commonly used in pathology. However, formalin fixation modifies nucleic acids challenging the isolation of high-quality RNA for genetic profiling. Here, we assessed feasibility and reliability of microarray studies analysing transcriptome data from fresh, fresh-frozen (FF) and FFPE tissues. We show that reproducible microarray data can be generated from only 2 ng FFPE-derived RNA. For RNA quality assessment, fragment size distribution (DV200) and qPCR proved most suitable. During RNA isolation, extending tissue lysis time to 10 hours reduced high-molecular-weight species, while additional incubation at 70 °C markedly increased RNA yields. Since FF- and FFPE-derived microarrays constitute different data entities, we used indirect measures to investigate gene signal variation and relative gene expression. Whole-genome analyses revealed high concordance rates, while reviewing on single-genes basis showed higher data variation in FFPE than FF arrays. Using an experimental model, gene set enrichment analysis (GSEA) of FFPE-derived microarrays and fresh tissue-derived RNA-Seq datasets yielded similarly affected pathways confirming the applicability of FFPE tissue in global gene expression analysis. Our study provides a workflow comprising RNA isolation, quality assessment and microarray profiling using minimal RNA input, thus enabling hypothesis-generating pathway analyses from limited amounts of precious, pathologically significant FFPE tissues.

Comparative analysis of the transcriptome responses of zebrafish embryos after exposure to low concentrations of cadmium, cobalt and copper.

PubMed

Sonnack, Laura; Klawonn, Thorsten; Kriehuber, Ralf; Hollert, Henner; Schäfers, Christoph; Fenske, Martina

2018-03-01

Metal toxicity is a global environmental challenge. Fish are particularly prone to metal exposure, which can be lethal or cause sublethal physiological impairments. The objective of this study was to investigate how adverse effects of chronic exposure to non-toxic levels of essential and non-essential metals in early life stage zebrafish may be explained by changes in the transcriptome. We therefore studied the effects of three different metals at low concentrations in zebrafish embryos by transcriptomics analysis. The study design compared exposure effects caused by different metals at different developmental stages (pre-hatch and post-hatch). Wild-type embryos were exposed to solutions of low concentrations of copper (CuSO 4 ), cadmium (CdCl 2 ) and cobalt (CoSO 4 ) until 96h post-fertilization (hpf) and microarray experiments were carried out to determine transcriptome profiles at 48 and 96hpf. We found that the toxic metal cadmium affected the expression of more genes at 96hpf than 48hpf. The opposite effect was observed for the essential metals cobalt and copper, which also showed enrichment of different GO terms. Genes involved in neuromast and motor neuron development were significantly enriched, agreeing with our previous results showing motor neuron and neuromast damage in the embryos. Our data provide evidence that the response of the transcriptome of fish embryos to metal exposure differs for essential and non-essential metals. Copyright © 2017 Elsevier Inc. All rights reserved.

Analysis of genomic responses in a rat lung model treated with a humidifier sterilizer containing polyhexamethyleneguanidine phosphate.

PubMed

Kim, Min-Seok; Jeong, Seok Won; Choi, Seong-Jin; Han, Jin-Young; Kim, Sung-Hwan; Yoon, Seokjoo; Oh, Jung-Hwa; Lee, Kyuhong

2017-02-15

The antimicrobial biocide polyhexamethyleneguanidine (PHMG) phosphate is the main ingredient in the commercially available humidifier disinfectant. PHMG phosphate-based humidifier disinfectants can cause pulmonary fibrosis and induce inflammatory and fibrotic responses both in vivo and in vitro. However, toxicological mechanisms including genomic alterations induced by inhalation exposure to PHMG phosphate have not been elucidated. Therefore, this study evaluated the toxicological effects of the PHMG phosphate-containing humidifier disinfectant. We used DNA microarray to identify global gene expression changes in rats treated with PHMG phosphate-containing humidifier disinfectant for 4 weeks and 10 weeks. Functional significance of differentially expressed genes (DEGs) was estimated by gene ontology (GO) analysis. Four weeks post-exposure, 320 and 392 DEGs were identified in female and male rats, respectively (>2-fold, p<0.05). Ten weeks post-exposure, 1290 and 995 DEGs were identified in females and males, respectively. Of these, 119 and 556 genes overlapped between females and males at 4 weeks and 10 weeks, respectively, post-PHMG phosphate exposure. In addition, 21 genes were upregulated and 4 genes were downregulated in response to PHMG phosphate in a time-dependent manner. Thus, we predict that changes in genomic responses could be a significant molecular mechanism underlying PHMG phosphate toxicity. Further studies are required to determine the detailed mechanism of PHMG phosphate-induced pulmonary toxicity. Copyright © 2016. Published by Elsevier B.V.

Comparative study of joint analysis of microarray gene expression data in survival prediction and risk assessment of breast cancer patients

PubMed Central

2016-01-01

Abstract Microarray gene expression data sets are jointly analyzed to increase statistical power. They could either be merged together or analyzed by meta-analysis. For a given ensemble of data sets, it cannot be foreseen which of these paradigms, merging or meta-analysis, works better. In this article, three joint analysis methods, Z -score normalization, ComBat and the inverse normal method (meta-analysis) were selected for survival prognosis and risk assessment of breast cancer patients. The methods were applied to eight microarray gene expression data sets, totaling 1324 patients with two clinical endpoints, overall survival and relapse-free survival. The performance derived from the joint analysis methods was evaluated using Cox regression for survival analysis and independent validation used as bias estimation. Overall, Z -score normalization had a better performance than ComBat and meta-analysis. Higher Area Under the Receiver Operating Characteristic curve and hazard ratio were also obtained when independent validation was used as bias estimation. With a lower time and memory complexity, Z -score normalization is a simple method for joint analysis of microarray gene expression data sets. The derived findings suggest further assessment of this method in future survival prediction and cancer classification applications. PMID:26504096

Derivation of Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Teleost Reproductive Axis.

EPA Science Inventory

Oligonucleotide microarrays are a powerful tool for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-based analyses to detect diffe...

Circular RNA expression profiles in hippocampus from mice with perinatal glyphosate exposure.

PubMed

Yu, Ning; Tong, Yun; Zhang, Danni; Zhao, Shanshan; Fan, Xinli; Wu, Lihui; Ji, Hua

2018-07-02

Glyphosate is the active ingredient in numerous herbicide formulations. The roles of glyphosate in embryo-toxicity and neurotoxicity have been reported in human and animal models. Recently, several studies have reported evidence linking neurodevelopmental disorders (NDDs) with gestational glyphosate exposure. However, the role of glyphosate in neuronal development is still not fully understood. Our previous study found that perinatal glyphosate exposure resulted in differential microRNA expression in the prefrontal cortex of mouse offspring. However, the mechanism of glyphosate-induced neurotoxicity in the developing brain is still not fully understood. Considering the pivotal role of Circular RNAs (circRNAs) in the regulation of gene expression, a circRNA microarray method was used in this study to investigate circRNA expression changes in the hippocampus of mice with perinatal glyphosate exposure. The circRNA microarrays revealed that 663 circRNAs were significantly altered in the perinatal glyphosate exposure group compared with the control group. Among them, 330 were significantly upregulated, and the other 333 were downregulated. Furthermore, the relative expression levels of mmu-circRNA-014015, mmu-circRNA-28128 and mmu-circRNA-29837 were verified using quantitative real-time polymerase chain reaction (qRT-PCR). Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses demonstrated that stress-associated steroid metabolism pathways, such as aldosterone synthesis and secretion pathways, may be involved in the neurotoxicity of glyphosate. These results showed that circRNAs are aberrantly expressed in the hippocampus of mice with perinatal glyphosate exposure and play potential roles in glyphosate-induced neurotoxicity. Copyright © 2018 Elsevier Inc. All rights reserved.

A probabilistic framework for microarray data analysis: fundamental probability models and statistical inference.

PubMed

Ogunnaike, Babatunde A; Gelmi, Claudio A; Edwards, Jeremy S

2010-05-21

Gene expression studies generate large quantities of data with the defining characteristic that the number of genes (whose expression profiles are to be determined) exceed the number of available replicates by several orders of magnitude. Standard spot-by-spot analysis still seeks to extract useful information for each gene on the basis of the number of available replicates, and thus plays to the weakness of microarrays. On the other hand, because of the data volume, treating the entire data set as an ensemble, and developing theoretical distributions for these ensembles provides a framework that plays instead to the strength of microarrays. We present theoretical results that under reasonable assumptions, the distribution of microarray intensities follows the Gamma model, with the biological interpretations of the model parameters emerging naturally. We subsequently establish that for each microarray data set, the fractional intensities can be represented as a mixture of Beta densities, and develop a procedure for using these results to draw statistical inference regarding differential gene expression. We illustrate the results with experimental data from gene expression studies on Deinococcus radiodurans following DNA damage using cDNA microarrays. Copyright (c) 2010 Elsevier Ltd. All rights reserved.

Microarray-based screening of heat shock protein inhibitors.

PubMed

Schax, Emilia; Walter, Johanna-Gabriela; Märzhäuser, Helene; Stahl, Frank; Scheper, Thomas; Agard, David A; Eichner, Simone; Kirschning, Andreas; Zeilinger, Carsten

2014-06-20

Based on the importance of heat shock proteins (HSPs) in diseases such as cancer, Alzheimer's disease or malaria, inhibitors of these chaperons are needed. Today's state-of-the-art techniques to identify HSP inhibitors are performed in microplate format, requiring large amounts of proteins and potential inhibitors. In contrast, we have developed a miniaturized protein microarray-based assay to identify novel inhibitors, allowing analysis with 300 pmol of protein. The assay is based on competitive binding of fluorescence-labeled ATP and potential inhibitors to the ATP-binding site of HSP. Therefore, the developed microarray enables the parallel analysis of different ATP-binding proteins on a single microarray. We have demonstrated the possibility of multiplexing by immobilizing full-length human HSP90α and HtpG of Helicobacter pylori on microarrays. Fluorescence-labeled ATP was competed by novel geldanamycin/reblastatin derivatives with IC50 values in the range of 0.5 nM to 4 μM and Z(*)-factors between 0.60 and 0.96. Our results demonstrate the potential of a target-oriented multiplexed protein microarray to identify novel inhibitors for different members of the HSP90 family. Copyright © 2014 Elsevier B.V. All rights reserved.

Rapid Detection of Rare Deleterious Variants by Next Generation Sequencing with Optional Microarray SNP Genotype Data

PubMed Central

Watson, Christopher M.; Crinnion, Laura A.; Gurgel‐Gianetti, Juliana; Harrison, Sally M.; Daly, Catherine; Antanavicuite, Agne; Lascelles, Carolina; Markham, Alexander F.; Pena, Sergio D. J.; Bonthron, David T.

2015-01-01

ABSTRACT Autozygosity mapping is a powerful technique for the identification of rare, autosomal recessive, disease‐causing genes. The ease with which this category of disease gene can be identified has greatly increased through the availability of genome‐wide SNP genotyping microarrays and subsequently of exome sequencing. Although these methods have simplified the generation of experimental data, its analysis, particularly when disparate data types must be integrated, remains time consuming. Moreover, the huge volume of sequence variant data generated from next generation sequencing experiments opens up the possibility of using these data instead of microarray genotype data to identify disease loci. To allow these two types of data to be used in an integrated fashion, we have developed AgileVCFMapper, a program that performs both the mapping of disease loci by SNP genotyping and the analysis of potentially deleterious variants using exome sequence variant data, in a single step. This method does not require microarray SNP genotype data, although analysis with a combination of microarray and exome genotype data enables more precise delineation of disease loci, due to superior marker density and distribution. PMID:26037133

Automatic Identification and Quantification of Extra-Well Fluorescence in Microarray Images.

PubMed

Rivera, Robert; Wang, Jie; Yu, Xiaobo; Demirkan, Gokhan; Hopper, Marika; Bian, Xiaofang; Tahsin, Tasnia; Magee, D Mitchell; Qiu, Ji; LaBaer, Joshua; Wallstrom, Garrick

2017-11-03

In recent studies involving NAPPA microarrays, extra-well fluorescence is used as a key measure for identifying disease biomarkers because there is evidence to support that it is better correlated with strong antibody responses than statistical analysis involving intraspot intensity. Because this feature is not well quantified by traditional image analysis software, identification and quantification of extra-well fluorescence is performed manually, which is both time-consuming and highly susceptible to variation between raters. A system that could automate this task efficiently and effectively would greatly improve the process of data acquisition in microarray studies, thereby accelerating the discovery of disease biomarkers. In this study, we experimented with different machine learning methods, as well as novel heuristics, for identifying spots exhibiting extra-well fluorescence (rings) in microarray images and assigning each ring a grade of 1-5 based on its intensity and morphology. The sensitivity of our final system for identifying rings was found to be 72% at 99% specificity and 98% at 92% specificity. Our system performs this task significantly faster than a human, while maintaining high performance, and therefore represents a valuable tool for microarray image analysis.

Thermodynamically optimal whole-genome tiling microarray design and validation.

PubMed

Cho, Hyejin; Chou, Hui-Hsien

2016-06-13

Microarray is an efficient apparatus to interrogate the whole transcriptome of species. Microarray can be designed according to annotated gene sets, but the resulted microarrays cannot be used to identify novel transcripts and this design method is not applicable to unannotated species. Alternatively, a whole-genome tiling microarray can be designed using only genomic sequences without gene annotations, and it can be used to detect novel RNA transcripts as well as known genes. The difficulty with tiling microarray design lies in the tradeoff between probe-specificity and coverage of the genome. Sequence comparison methods based on BLAST or similar software are commonly employed in microarray design, but they cannot precisely determine the subtle thermodynamic competition between probe targets and partially matched probe nontargets during hybridizations. Using the whole-genome thermodynamic analysis software PICKY to design tiling microarrays, we can achieve maximum whole-genome coverage allowable under the thermodynamic constraints of each target genome. The resulted tiling microarrays are thermodynamically optimal in the sense that all selected probes share the same melting temperature separation range between their targets and closest nontargets, and no additional probes can be added without violating the specificity of the microarray to the target genome. This new design method was used to create two whole-genome tiling microarrays for Escherichia coli MG1655 and Agrobacterium tumefaciens C58 and the experiment results validated the design.

PageMan: an interactive ontology tool to generate, display, and annotate overview graphs for profiling experiments.

PubMed

Usadel, Björn; Nagel, Axel; Steinhauser, Dirk; Gibon, Yves; Bläsing, Oliver E; Redestig, Henning; Sreenivasulu, Nese; Krall, Leonard; Hannah, Matthew A; Poree, Fabien; Fernie, Alisdair R; Stitt, Mark

2006-12-18

Microarray technology has become a widely accepted and standardized tool in biology. The first microarray data analysis programs were developed to support pair-wise comparison. However, as microarray experiments have become more routine, large scale experiments have become more common, which investigate multiple time points or sets of mutants or transgenics. To extract biological information from such high-throughput expression data, it is necessary to develop efficient analytical platforms, which combine manually curated gene ontologies with efficient visualization and navigation tools. Currently, most tools focus on a few limited biological aspects, rather than offering a holistic, integrated analysis. Here we introduce PageMan, a multiplatform, user-friendly, and stand-alone software tool that annotates, investigates, and condenses high-throughput microarray data in the context of functional ontologies. It includes a GUI tool to transform different ontologies into a suitable format, enabling the user to compare and choose between different ontologies. It is equipped with several statistical modules for data analysis, including over-representation analysis and Wilcoxon statistical testing. Results are exported in a graphical format for direct use, or for further editing in graphics programs.PageMan provides a fast overview of single treatments, allows genome-level responses to be compared across several microarray experiments covering, for example, stress responses at multiple time points. This aids in searching for trait-specific changes in pathways using mutants or transgenics, analyzing development time-courses, and comparison between species. In a case study, we analyze the results of publicly available microarrays of multiple cold stress experiments using PageMan, and compare the results to a previously published meta-analysis.PageMan offers a complete user's guide, a web-based over-representation analysis as well as a tutorial, and is freely available at http://mapman.mpimp-golm.mpg.de/pageman/. PageMan allows multiple microarray experiments to be efficiently condensed into a single page graphical display. The flexible interface allows data to be quickly and easily visualized, facilitating comparisons within experiments and to published experiments, thus enabling researchers to gain a rapid overview of the biological responses in the experiments.

Identification of candidate genes in osteoporosis by integrated microarray analysis.

PubMed

Li, J J; Wang, B Q; Fei, Q; Yang, Y; Li, D

2016-12-01

In order to screen the altered gene expression profile in peripheral blood mononuclear cells of patients with osteoporosis, we performed an integrated analysis of the online microarray studies of osteoporosis. We searched the Gene Expression Omnibus (GEO) database for microarray studies of peripheral blood mononuclear cells in patients with osteoporosis. Subsequently, we integrated gene expression data sets from multiple microarray studies to obtain differentially expressed genes (DEGs) between patients with osteoporosis and normal controls. Gene function analysis was performed to uncover the functions of identified DEGs. A total of three microarray studies were selected for integrated analysis. In all, 1125 genes were found to be significantly differentially expressed between osteoporosis patients and normal controls, with 373 upregulated and 752 downregulated genes. Positive regulation of the cellular amino metabolic process (gene ontology (GO): 0033240, false discovery rate (FDR) = 1.00E + 00) was significantly enriched under the GO category for biological processes, while for molecular functions, flavin adenine dinucleotide binding (GO: 0050660, FDR = 3.66E-01) and androgen receptor binding (GO: 0050681, FDR = 6.35E-01) were significantly enriched. DEGs were enriched in many osteoporosis-related signalling pathways, including those of mitogen-activated protein kinase (MAPK) and calcium. Protein-protein interaction (PPI) network analysis showed that the significant hub proteins contained ubiquitin specific peptidase 9, X-linked (Degree = 99), ubiquitin specific peptidase 19 (Degree = 57) and ubiquitin conjugating enzyme E2 B (Degree = 57). Analysis of gene function of identified differentially expressed genes may expand our understanding of fundamental mechanisms leading to osteoporosis. Moreover, significantly enriched pathways, such as MAPK and calcium, may involve in osteoporosis through osteoblastic differentiation and bone formation.Cite this article: J. J. Li, B. Q. Wang, Q. Fei, Y. Yang, D. Li. Identification of candidate genes in osteoporosis by integrated microarray analysis. Bone Joint Res 2016;5:594-601. DOI: 10.1302/2046-3758.512.BJR-2016-0073.R1. © 2016 Fei et al.

Dose-specific transcriptional responses in thyroid tissue in mice after (131)I administration.

PubMed

Rudqvist, Nils; Schüler, Emil; Parris, Toshima Z; Langen, Britta; Helou, Khalil; Forssell-Aronsson, Eva

2015-03-01

In the present investigation, microarray analysis was used to monitor transcriptional activity in thyroids in mice 24 h after (131)I exposure. The aims of this study were to 1) assess the transcriptional patterns associated with (131)I exposure in normal mouse thyroid tissue and 2) propose biomarkers for (131)I exposure of the thyroid. Adult BALB/c nude mice were i.v. injected with 13, 130 or 260 kBq of (131)I and killed 24h after injection (absorbed dose to thyroid: 0.85, 8.5, or 17 Gy). Mock-treated mice were used as controls. Total RNA was extracted from thyroids and processed using the Illumina platform. In total, 497, 546, and 90 transcripts were regulated (fold change ≥1.5) in the thyroid after 0.85, 8.5, and 17 Gy, respectively. These were involved in several biological functions, e.g. oxygen access, inflammation and immune response, and apoptosis/anti-apoptosis. Approximately 50% of the involved transcripts at each absorbed dose level were dose-specific, and 18 transcripts were commonly detected at all absorbed dose levels. The Agpat9, Plau, Prf1, and S100a8 gene expression displayed a monotone decrease in regulation with absorbed dose, and further studies need to be performed to evaluate if they may be useful as dose-related biomarkers for 131I exposure. Distinct and substantial differences in gene expression and affected biological functions were detected at the different absorbed dose levels. The transcriptional profiles were specific for the different absorbed dose levels. We propose that the Agpat9, Plau, Prf1, and S100a8 genes might be novel potential absorbed dose-related biomarkers to (131)I exposure of thyroid. During the recent years, genomic techniques have been developed; however, they have not been fully utilized in nuclear medicine and radiation biology. We have used RNA microarrays to investigate genome-wide transcriptional regulations in thyroid tissue in mice after low, intermediate, and high absorbed doses from (131)I exposure in vivo. Using this approach, we have identified novel biological responses and potential absorbed dose-related biomarkers to (131)I exposure. Our research shows the importance of embracing technological advances and multi-disciplinary collaboration in order to apply them in radiation therapy, nuclear medicine, and radiation biology. This work may contribute with new knowledge of potential normal tissue effects or complications that may occur after exposure to ionizing radiation in diagnostic and therapeutic nuclear medicine, and due to radioactive fallout or accident with radionuclide spread. Copyright © 2014 Elsevier Inc. All rights reserved.

Workflows for microarray data processing in the Kepler environment.

PubMed

Stropp, Thomas; McPhillips, Timothy; Ludäscher, Bertram; Bieda, Mark

2012-05-17

Microarray data analysis has been the subject of extensive and ongoing pipeline development due to its complexity, the availability of several options at each analysis step, and the development of new analysis demands, including integration with new data sources. Bioinformatics pipelines are usually custom built for different applications, making them typically difficult to modify, extend and repurpose. Scientific workflow systems are intended to address these issues by providing general-purpose frameworks in which to develop and execute such pipelines. The Kepler workflow environment is a well-established system under continual development that is employed in several areas of scientific research. Kepler provides a flexible graphical interface, featuring clear display of parameter values, for design and modification of workflows. It has capabilities for developing novel computational components in the R, Python, and Java programming languages, all of which are widely used for bioinformatics algorithm development, along with capabilities for invoking external applications and using web services. We developed a series of fully functional bioinformatics pipelines addressing common tasks in microarray processing in the Kepler workflow environment. These pipelines consist of a set of tools for GFF file processing of NimbleGen chromatin immunoprecipitation on microarray (ChIP-chip) datasets and more comprehensive workflows for Affymetrix gene expression microarray bioinformatics and basic primer design for PCR experiments, which are often used to validate microarray results. Although functional in themselves, these workflows can be easily customized, extended, or repurposed to match the needs of specific projects and are designed to be a toolkit and starting point for specific applications. These workflows illustrate a workflow programming paradigm focusing on local resources (programs and data) and therefore are close to traditional shell scripting or R/BioConductor scripting approaches to pipeline design. Finally, we suggest that microarray data processing task workflows may provide a basis for future example-based comparison of different workflow systems. We provide a set of tools and complete workflows for microarray data analysis in the Kepler environment, which has the advantages of offering graphical, clear display of conceptual steps and parameters and the ability to easily integrate other resources such as remote data and web services.

Chronic Ethanol Exposure Produces Time- and Brain Region-Dependent Changes in Gene Coexpression Networks

PubMed Central

Osterndorff-Kahanek, Elizabeth A.; Becker, Howard C.; Lopez, Marcelo F.; Farris, Sean P.; Tiwari, Gayatri R.; Nunez, Yury O.; Harris, R. Adron; Mayfield, R. Dayne

2015-01-01

Repeated ethanol exposure and withdrawal in mice increases voluntary drinking and represents an animal model of physical dependence. We examined time- and brain region-dependent changes in gene coexpression networks in amygdala (AMY), nucleus accumbens (NAC), prefrontal cortex (PFC), and liver after four weekly cycles of chronic intermittent ethanol (CIE) vapor exposure in C57BL/6J mice. Microarrays were used to compare gene expression profiles at 0-, 8-, and 120-hours following the last ethanol exposure. Each brain region exhibited a large number of differentially expressed genes (2,000-3,000) at the 0- and 8-hour time points, but fewer changes were detected at the 120-hour time point (400-600). Within each region, there was little gene overlap across time (~20%). All brain regions were significantly enriched with differentially expressed immune-related genes at the 8-hour time point. Weighted gene correlation network analysis identified modules that were highly enriched with differentially expressed genes at the 0- and 8-hour time points with virtually no enrichment at 120 hours. Modules enriched for both ethanol-responsive and cell-specific genes were identified in each brain region. These results indicate that chronic alcohol exposure causes global ‘rewiring‘ of coexpression systems involving glial and immune signaling as well as neuronal genes. PMID:25803291

Cells exposed to nanosecond electrical pulses exhibit biomarkers of mechanical stress

NASA Astrophysics Data System (ADS)

Roth, Caleb C.; Barnes, Ronald A.; Ibey, Bennett L.; Beier, Hope T.; Moen, Erick K.; Glickman, Randolph D.

2015-03-01

Exposure of cells to very short (<1 μs) electric pulses in the megavolt/meter range have been shown to cause disruption of the plasma membrane. This disruption is often characterized by the formation of numerous small pores (<2 nm in diameter) in the plasma membrane that last for several minutes, allowing the flow of ions into the cell. These small pores are called nanopores and the resulting damage to the plasma membrane is referred to as nanoporation. Nanosecond electrical pulse (nsEP) exposure can impart many different stressors on a cell, including electrical, electro-chemical, and mechanical stress. Thus, nsEP exposure is not a "clean" insult, making determination of the mechanism of nanoporation quite difficult. We hypothesize that nsEP exposure creates acoustic shock waves capable of causing nanoporation. Microarray analysis of primary adult human dermal fibroblasts (HDFa) exposed to nsEP, indicated several genes associated with mechanical stress were selectively upregulated 4 h post exposure. The idea that nanoporation is caused by external mechanical force from acoustic shock waves has, to our knowledge, not been investigated. This work will critically challenge the existing paradigm that nanoporation is caused solely by an electric-field driven event and could provide the basis for a plausible explanation for electroporation.

Tobacco use induces anti-apoptotic, proliferative patterns of gene expression in circulating leukocytes of Caucasian males

PubMed Central

Charles, Peter C; Alder, Brian D; Hilliard, Eleanor G; Schisler, Jonathan C; Lineberger, Robert E; Parker, Joel S; Mapara, Sabeen; Wu, Samuel S; Portbury, Andrea; Patterson, Cam; Stouffer, George A

2008-01-01

Background Strong epidemiologic evidence correlates tobacco use with a variety of serious adverse health effects, but the biological mechanisms that produce these effects remain elusive. Results We analyzed gene transcription data to identify expression spectra related to tobacco use in circulating leukocytes of 67 Caucasian male subjects. Levels of cotinine, a nicotine metabolite, were used as a surrogate marker for tobacco exposure. Significance Analysis of Microarray and Gene Set Analysis identified 109 genes in 16 gene sets whose transcription levels were differentially regulated by nicotine exposure. We subsequently analyzed this gene set by hyperclustering, a technique that allows the data to be clustered by both expression ratio and gene annotation (e.g. Gene Ontologies). Conclusion Our results demonstrate that tobacco use affects transcription of groups of genes that are involved in proliferation and apoptosis in circulating leukocytes. These transcriptional effects include a repertoire of transcriptional changes likely to increase the incidence of neoplasia through an altered expression of genes associated with transcription and signaling, interferon responses and repression of apoptotic pathways. PMID:18710571

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays

PubMed Central

Goodman, Corey W.; Major, Heather J.; Walls, William D.; Sheffield, Val C.; Casavant, Thomas L.; Darbro, Benjamin W.

2016-01-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. PMID:25595567

Manganese-Induced Neurotoxicity and Alterations in Gene Expression in Human Neuroblastoma SH-SY5Y Cells.

PubMed

Gandhi, Deepa; Sivanesan, Saravanadevi; Kannan, Krishnamurthi

2018-06-01

Manganese (Mn) is an essential trace element required for many physiological functions including proper biochemical and cellular functioning of the central nervous system (CNS). However, exposure to excess level of Mn through occupational settings or from environmental sources has been associated with neurotoxicity. The cellular and molecular mechanism of Mn-induced neurotoxicity remains unclear. In the current study, we investigated the effects of 30-day exposure to a sub-lethal concentration of Mn (100 μM) in human neuroblastoma cells (SH-SY5Y) using transcriptomic approach. Microarray analysis revealed differential expression of 1057 transcripts in Mn-exposed SH-SY5Y cells as compared to control cells. Gene functional annotation cluster analysis exhibited that the differentially expressed genes were associated with several biological pathways. Specifically, genes involved in neuronal pathways including neuron differentiation and development, regulation of neurogenesis, synaptic transmission, and neuronal cell death (apoptosis) were found to be significantly altered. KEGG pathway analysis showed upregulation of p53 signaling pathways and neuroactive ligand-receptor interaction pathways, and downregulation of neurotrophin signaling pathway. On the basis of the gene expression profile, possible molecular mechanisms underlying Mn-induced neuronal toxicity were predicted.

Transcriptional responses associated with sulfur mustard and thermal burns in porcine skin.

PubMed

Rogers, James V; McDougal, James N; Price, Jennifer A; Reid, Frances M; Graham, John S

2008-01-01

In military and civilian environments, serious cutaneous damage can result from thermal burns or exposure to the blistering agent sulfur mustard [bis (2-chloroethyl) sulfide; HD]. Similar therapies have historically been used to treat cutaneous thermal and HD injuries; however, the underlying molecular mechanisms of tissue damage and wound healing may differ between the types of burns. Using microarray analysis, this study assessed the transcriptional responses to cutaneous HD and thermal injury at 48 hours post-exposure to identify molecular networks and genes associated with each type of skin injury. Ventral abdominal sites on each of 4 weanling swine were exposed to 400 mul of undiluted HD or a heated brass rod (70 degrees C) for 8 minutes and 45-60 seconds, respectively. At 48 hours post-exposure, total RNA was isolated from excised skin samples and hybridized to Affymetrix GeneChip Porcine Genome Arrays (containing 20,201 genes). Both HD and thermal exposure promoted significant transcriptional changes where 290 and 267 transcripts were increased and 197 and 707 transcripts were decreased with HD and thermal exposure, respectively. HD- and thermal-injured skin expressed 149 increased and 148 decreased common transcripts. Comparison of the 10 most significantly changed biological functions for HD and thermal exposures identified 7 overlapping functional groups. Canonical pathways analysis revealed 15 separate signaling pathways containing transcripts associated with both HD and thermal exposure. Within these pathways, 5 transcripts (CXCR4, FGFR2, HMOX1, IL1R1, and TLR4) were identified as known targets for existing phase II/III clinical trial or Food and Drug Administration (FDA)-approved drugs. This study is the first to directly assess transcriptional changes in porcine skin subjected to HD or thermal injury over the same time period.

Identification of Gender-specific Transcripts by Microarray in Gonad Tissue of Larval and Juvenile Xenopus tropicalis

EPA Science Inventory

Amphibian model species Xenopus tropicalis is currently being utilized by EPA in the development of a standardized in vivo reproductive toxicity assay. Perturbations to the hypothalamic-pituitary-gonadal axis from exposure to endocrine disrupting compounds during larval develop...

MICROARRAY DATA ANALYSIS USING MULTIPLE STATISTICAL MODELS

EPA Science Inventory

Microarray Data Analysis Using Multiple Statistical Models

Wenjun Bao1, Judith E. Schmid1, Amber K. Goetz1, Ming Ouyang2, William J. Welsh2,Andrew I. Brooks3,4, ChiYi Chu3,Mitsunori Ogihara3,4, Yinhe Cheng5, David J. Dix1. 1National Health and Environmental Effects Researc...

Parents' Perceptions of the Usefulness of Chromosomal Microarray Analysis for Children with Autism Spectrum Disorders

ERIC Educational Resources Information Center

Reiff, Marian; Giarelli, Ellen; Bernhardt, Barbara A.; Easley, Ebony; Spinner, Nancy B.; Sankar, Pamela L.; Mulchandani, Surabhi

2015-01-01

Clinical guidelines recommend chromosomal microarray analysis (CMA) for all children with autism spectrum disorders (ASDs). We explored the test's perceived usefulness among parents of children with ASD who had undergone CMA, and received a result categorized as pathogenic, variant of uncertain significance, or negative. Fifty-seven parents…

A Graphical Systems Model and Tissue-specific Functional Gene Sets to Aid Transcriptomic Analysis of Chemical Impacts on the Female Teleost Reproductive Axis

EPA Science Inventory

Oligonucleotide microarrays and other ‘omics’ approaches are powerful tools for unsupervised analysis of chemical impacts on biological systems. However, the lack of well annotated biological pathways for many aquatic organisms, including fish, and the poor power of microarray-b...

CGO: utilizing and integrating gene expression microarray data in clinical research and data management.

PubMed

Bumm, Klaus; Zheng, Mingzhong; Bailey, Clyde; Zhan, Fenghuang; Chiriva-Internati, M; Eddlemon, Paul; Terry, Julian; Barlogie, Bart; Shaughnessy, John D

2002-02-01

Clinical GeneOrganizer (CGO) is a novel windows-based archiving, organization and data mining software for the integration of gene expression profiling in clinical medicine. The program implements various user-friendly tools and extracts data for further statistical analysis. This software was written for Affymetrix GeneChip *.txt files, but can also be used for any other microarray-derived data. The MS-SQL server version acts as a data mart and links microarray data with clinical parameters of any other existing database and therefore represents a valuable tool for combining gene expression analysis and clinical disease characteristics.

cluML: A markup language for clustering and cluster validity assessment of microarray data.

PubMed

Bolshakova, Nadia; Cunningham, Pádraig

2005-01-01

cluML is a new markup language for microarray data clustering and cluster validity assessment. The XML-based format has been designed to address some of the limitations observed in traditional formats, such as inability to store multiple clustering (including biclustering) and validation results within a dataset. cluML is an effective tool to support biomedical knowledge representation in gene expression data analysis. Although cluML was developed for DNA microarray analysis applications, it can be effectively used for the representation of clustering and for the validation of other biomedical and physical data that has no limitations.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium.

PubMed

Ryan, Natalia; Chorley, Brian; Tice, Raymond R; Judson, Richard; Corton, J Christopher

2016-05-01

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells. Published by Oxford University Press on behalf of the Society of Toxicology 2016. This work is written by US Government employees and is in the public domain in the US.

Analysis of developmental gene conservation in the Actinomycetales using DNA/DNA microarray comparisons.

PubMed

Kirby, Ralph; Herron, Paul; Hoskisson, Paul

2011-02-01

Based on available genome sequences, Actinomycetales show significant gene synteny across a wide range of species and genera. In addition, many genera show varying degrees of complex morphological development. Using the presence of gene synteny as a basis, it is clear that an analysis of gene conservation across the Streptomyces and various other Actinomycetales will provide information on both the importance of genes and gene clusters and the evolution of morphogenesis in these bacteria. Genome sequencing, although becoming cheaper, is still relatively expensive for comparing large numbers of strains. Thus, a heterologous DNA/DNA microarray hybridization dataset based on a Streptomyces coelicolor microarray allows a cheaper and greater depth of analysis of gene conservation. This study, using both bioinformatical and microarray approaches, was able to classify genes previously identified as involved in morphogenesis in Streptomyces into various subgroups in terms of conservation across species and genera. This will allow the targeting of genes for further study based on their importance at the species level and at higher evolutionary levels.

Cross species analysis of microarray expression data

PubMed Central

Lu, Yong; Huggins, Peter; Bar-Joseph, Ziv

2009-01-01

Motivation: Many biological systems operate in a similar manner across a large number of species or conditions. Cross-species analysis of sequence and interaction data is often applied to determine the function of new genes. In contrast to these static measurements, microarrays measure the dynamic, condition-specific response of complex biological systems. The recent exponential growth in microarray expression datasets allows researchers to combine expression experiments from multiple species to identify genes that are not only conserved in sequence but also operated in a similar way in the different species studied. Results: In this review we discuss the computational and technical challenges associated with these studies, the approaches that have been developed to address these challenges and the advantages of cross-species analysis of microarray data. We show how successful application of these methods lead to insights that cannot be obtained when analyzing data from a single species. We also highlight current open problems and discuss possible ways to address them. Contact: zivbj@cs.cmu.edu PMID:19357096

Separation and Analysis of Adherent and Non-Adherent Cancer Cells Using a Single-Cell Microarray Chip.

PubMed

Yamamura, Shohei; Yamada, Eriko; Kimura, Fukiko; Miyajima, Kumiko; Shigeto, Hajime

2017-10-21

A new single-cell microarray chip was designed and developed to separate and analyze single adherent and non-adherent cancer cells. The single-cell microarray chip is made of polystyrene with over 60,000 microchambers of 10 different size patterns (31-40 µm upper diameter, 11-20 µm lower diameter). A drop of suspension of adherent carcinoma (NCI-H1650) and non-adherent leukocyte (CCRF-CEM) cells was placed onto the chip, and single-cell occupancy of NCI-H1650 and CCRF-CEM was determined to be 79% and 84%, respectively. This was achieved by controlling the chip design and surface treatment. Analysis of protein expression in single NCI-H1650 and CCRF-CEM cells was performed on the single-cell microarray chip by multi-antibody staining. Additionally, with this system, we retrieved positive single cells from the microchambers by a micromanipulator. Thus, this system demonstrates the potential for easy and accurate separation and analysis of various types of single cells.

Transcriptomic Analysis of Ciguatoxin-Induced Changes in Gene Expression in Primary Cultures of Mice Cortical Neurons.

PubMed

Rubiolo, Juan Andrés; Vale, Carmen; Boente-Juncal, Andrea; Hirama, Masahiro; Yamashita, Shuji; Camiña, Mercedes; Vieytes, Mercedes R; Botana, Luis M

2018-05-10

Ciguatoxins are polyether marine toxins that act as sodium channel activators. These toxins cause ciguatera, one of the most widespread nonbacterial forms of food poisoning, which presents several symptoms in humans including long-term neurological alterations. Earlier work has shown that both acute and chronic exposure of primary cortical neurons to synthetic ciguatoxin CTX3C have profound impacts on neuronal function. Thus, the present work aimed to identify relevant neuronal genes and metabolic pathways that could be altered by ciguatoxin exposure. To study the effect of ciguatoxins in primary neurons in culture, we performed a transcriptomic analysis using whole mouse genome microarrays, for primary cortical neurons exposed during 6, 24, or 72 h in culture to CTX3C. Here, we have shown that the effects of the toxin on gene expression differ with the exposure time. The results presented here have identified several relevant genes and pathways related to the effect of ciguatoxins on neurons and may assist in future research or even treatment of ciguatera. Moreover, we demonstrated that the effects of the toxin on gene expression were exclusively consequential of its action as a voltage-gated sodium channel activator, since all the effects of CTX3C were avoided by preincubation of the neurons with the sodium channel blocker tetrodotoxin.

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarrays. 22-24 January 2001, Zurich, Switzerland.

PubMed

Jain, K K

2001-02-01

Cambridge Healthtech Institute's Third Annual Conference on Lab-on-a-Chip and Microarray technology covered the latest advances in this technology and applications in life sciences. Highlights of the meetings are reported briefly with emphasis on applications in genomics, drug discovery and molecular diagnostics. There was an emphasis on microfluidics because of the wide applications in laboratory and drug discovery. The lab-on-a-chip provides the facilities of a complete laboratory in a hand-held miniature device. Several microarray systems have been used for hybridisation and detection techniques. Oligonucleotide scanning arrays provide a versatile tool for the analysis of nucleic acid interactions and provide a platform for improving the array-based methods for investigation of antisense therapeutics. A method for analysing combinatorial DNA arrays using oligonucleotide-modified gold nanoparticle probes and a conventional scanner has considerable potential in molecular diagnostics. Various applications of microarray technology for high-throughput screening in drug discovery and single nucleotide polymorphisms (SNP) analysis were discussed. Protein chips have important applications in proteomics. With the considerable amount of data generated by the different technologies using microarrays, it is obvious that the reading of the information and its interpretation and management through the use of bioinformatics is essential. Various techniques for data analysis were presented. Biochip and microarray technology has an essential role to play in the evolving trends in healthcare, which integrate diagnosis with prevention/treatment and emphasise personalised medicines.

Differential gene expression detection and sample classification using penalized linear regression models.

PubMed

Wu, Baolin

2006-02-15

Differential gene expression detection and sample classification using microarray data have received much research interest recently. Owing to the large number of genes p and small number of samples n (p > n), microarray data analysis poses big challenges for statistical analysis. An obvious problem owing to the 'large p small n' is over-fitting. Just by chance, we are likely to find some non-differentially expressed genes that can classify the samples very well. The idea of shrinkage is to regularize the model parameters to reduce the effects of noise and produce reliable inferences. Shrinkage has been successfully applied in the microarray data analysis. The SAM statistics proposed by Tusher et al. and the 'nearest shrunken centroid' proposed by Tibshirani et al. are ad hoc shrinkage methods. Both methods are simple, intuitive and prove to be useful in empirical studies. Recently Wu proposed the penalized t/F-statistics with shrinkage by formally using the (1) penalized linear regression models for two-class microarray data, showing good performance. In this paper we systematically discussed the use of penalized regression models for analyzing microarray data. We generalize the two-class penalized t/F-statistics proposed by Wu to multi-class microarray data. We formally derive the ad hoc shrunken centroid used by Tibshirani et al. using the (1) penalized regression models. And we show that the penalized linear regression models provide a rigorous and unified statistical framework for sample classification and differential gene expression detection.

Best practices for hybridization design in two-colour microarray analysis.

PubMed

Knapen, Dries; Vergauwen, Lucia; Laukens, Kris; Blust, Ronny

2009-07-01

Two-colour microarrays are a popular platform of choice in gene expression studies. Because two different samples are hybridized on a single microarray, and several microarrays are usually needed in a given experiment, there are many possible ways to combine samples on different microarrays. The actual combination employed is commonly referred to as the 'hybridization design'. Different types of hybridization designs have been developed, all aimed at optimizing the experimental setup for the detection of differentially expressed genes while coping with technical noise. Here, we first provide an overview of the different classes of hybridization designs, discussing their advantages and limitations, and then we illustrate the current trends in the use of different hybridization design types in contemporary research.

Carcinogens induce loss of the primary cilium in human renal proximal tubular epithelial cells independently of effects on the cell cycle

PubMed Central

Radford, Robert; Slattery, Craig; Jennings, Paul; Blacque, Oliver; Pfaller, Walter; Gmuender, Hans; Van Delft, Joost; Ryan, Michael P.

2012-01-01

The primary cilium is an immotile sensory and signaling organelle found on the majority of mammalian cell types. Of the multitude of roles that the primary cilium performs, perhaps some of the most important include maintenance of differentiation, quiescence, and cellular polarity. Given that the progression of cancer requires disruption of all of these processes, we have investigated the effects of several carcinogens on the primary cilium of the RPTEC/TERT1 human proximal tubular epithelial cell line. Using both scanning electron microscopy and immunofluorescent labeling of the ciliary markers acetylated tubulin and Arl13b, we confirmed that RPTEC/TERT1 cells express primary cilium upon reaching confluence. Treatment with the carcinogens ochratoxin A (OTA) and potassium bromate (KBrO3) caused a significant reduction in the number of ciliated cells, while exposure to nifedipine, a noncarcinogenic renal toxin, had no effect on primary cilium expression. Flow cytometric analysis of the effects of all three compounds on the cell cycle revealed that only KBrO3 resulted in an increase in the proportion of cells entering the cell cycle. Microarray analysis revealed dysregulation of multiple pathways affecting ciliogenesis and ciliary maintenance following OTA and KBrO3 exposure, which were unaffected by nifedipine exposure. The primary cilium represents a unique physical checkpoint with relevance to carcinogenesis. We have shown that the renal carcinogens OTA and KBrO3 cause significant deciliation in a model of the proximal tubule. With KBrO3, this was followed by reentry into the cell cycle; however, deciliation was not found to be associated with reentry into the cell cycle following OTA exposure. Transcriptomic analysis identified dysregulation of Wnt signaling and ciliary trafficking in response to OTA and KBrO3 exposure. PMID:22262483

Improvement of experimental testing and network training conditions with genome-wide microarrays for more accurate predictions of drug gene targets

PubMed Central

2014-01-01

Background Genome-wide microarrays have been useful for predicting chemical-genetic interactions at the gene level. However, interpreting genome-wide microarray results can be overwhelming due to the vast output of gene expression data combined with off-target transcriptional responses many times induced by a drug treatment. This study demonstrates how experimental and computational methods can interact with each other, to arrive at more accurate predictions of drug-induced perturbations. We present a two-stage strategy that links microarray experimental testing and network training conditions to predict gene perturbations for a drug with a known mechanism of action in a well-studied organism. Results S. cerevisiae cells were treated with the antifungal, fluconazole, and expression profiling was conducted under different biological conditions using Affymetrix genome-wide microarrays. Transcripts were filtered with a formal network-based method, sparse simultaneous equation models and Lasso regression (SSEM-Lasso), under different network training conditions. Gene expression results were evaluated using both gene set and single gene target analyses, and the drug’s transcriptional effects were narrowed first by pathway and then by individual genes. Variables included: (i) Testing conditions – exposure time and concentration and (ii) Network training conditions – training compendium modifications. Two analyses of SSEM-Lasso output – gene set and single gene – were conducted to gain a better understanding of how SSEM-Lasso predicts perturbation targets. Conclusions This study demonstrates that genome-wide microarrays can be optimized using a two-stage strategy for a more in-depth understanding of how a cell manifests biological reactions to a drug treatment at the transcription level. Additionally, a more detailed understanding of how the statistical model, SSEM-Lasso, propagates perturbations through a network of gene regulatory interactions is achieved. PMID:24444313

Changes in trophoblasts gene expression in response to perchlorate exposition.

PubMed

la Peña Sol, De; Isela, Santiago-Roque; Zendy, Olivo-Vidal; Mónica, Navarro-Meza; Irene, Xochihua-Rosas; Omar, Arroyo-Helguera

2018-04-17

Contaminated water with chlorates is a public health problem associated with iodine deficiency. Epidemiological evidence shows that iodine deficiency is a risk factor for preeclampsia (PE). In this study we use human BeWo trophoblast cells exposed to perchlorate (KClO 4 ) and changes in gene expression were analyzed by microarrays, quantitative RT-PCR (qRT-PCR) and immunoblot. The microarray analysis identified 48 transcripts up-regulated and 112 down-regulated in comparison with non-exposed trophoblast. The qRT-PCR analysis confirmed changes in GAS7, PKP2, Emilin, Dynatic 3, protocadherins 11, 15, gamma A12, EGFR, SAFB1, ACE2, ANXA2, Apoliprotein E, SREBF1, and C/EBP-β. KClO 4 exposition decreased the mRNA and protein of C/EBP-β and GPX4. Also, we observed a nuclear translocation of HIF1α protein, and increase in both Snail and ACE2 protein by immunoblot. These effects were accompanied by an increases in ROS and nitric oxide. In conclusion, our results show that exposure to KClO 4 alters genes involved in migration, adhesion, differentiation, and correlate with the increase of oxidative stress and nitric oxide production in trophoblast cells. It is possible that iodine deficiency is associated with these processes. However, further studies are required to corroborate the role of iodine in trophoblast cells. Copyright © 2018 Elsevier Ltd. All rights reserved.

[Diagnosis of a case with Williams-Beuren syndrome with nephrocalcinosis using chromosome microarray analysis].

PubMed

Jin, S J; Liu, M; Long, W J; Luo, X P

2016-12-02

Objective: To explore the clinical phenotypes and the genetic cause for a boy with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders. Method: Routine G-banding and chromosome microarray analysis were applied to a child with unexplained growth retardation, nephrocalcinosis, auditory anomalies and multi-organ/system developmental disorders treated in the Department of Pediatrics of Tongji Hospital Affiliated to Tongji Medical College of Huazhong University of Science and Technology in September 2015 and his parents to conduct the chromosomal karyotype analysis and the whole genome scanning. Deleted genes were searched in the Decipher and NCBI databases, and their relationships with the clinical phenotypes were analyzed. Result: A six-month-old boy was refered to us because of unexplained growth retardation and feeding intolerance.The affected child presented with abnormal manifestation such as special face, umbilical hernia, growth retardation, hypothyroidism, congenital heart disease, right ear sensorineural deafness, hypercalcemia and nephrocalcinosis. The child's karyotype was 46, XY, 16qh + , and his parents' karyotypes were normal. Chromosome microarray analysis revealed a 1 436 kb deletion on the 7q11.23(72701098_74136633) region of the child. This region included 23 protein-coding genes, which were reported to be corresponding to Williams-Beuren syndrome and its certain clinical phenotypes. His parents' results of chromosome microarray analysis were normal. Conclusion: A boy with characteristic manifestation of Williams-Beuren syndrome and rare nephrocalcinosis was diagnosed using chromosome microarray analysis. The deletion on the 7q11.23 might be related to the clinical phenotypes of Williams-Beuren syndrome, yet further studies are needed.

AFM 4.0: a toolbox for DNA microarray analysis

PubMed Central

Breitkreutz, Bobby-Joe; Jorgensen, Paul; Breitkreutz, Ashton; Tyers, Mike

2001-01-01

We have developed a series of programs, collectively packaged as Array File Maker 4.0 (AFM), that manipulate and manage DNA microarray data. AFM 4.0 is simple to use, applicable to any organism or microarray, and operates within the familiar confines of Microsoft Excel. Given a database of expression ratios, AFM 4.0 generates input files for clustering, helps prepare colored figures and Venn diagrams, and can uncover aneuploidy in yeast microarray data. AFM 4.0 should be especially useful to laboratories that do not have access to specialized commercial or in-house software. PMID:11532221

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gao, Xiugong, E-mail: xiugong.gao@fda.hhs.gov; Sprando, Robert L.; Yourick, Jeffrey J.

Developmental toxicity testing has traditionally relied on animal models which are costly, time consuming, and require the sacrifice of large numbers of animals. In addition, there are significant disparities between human beings and animals in their responses to chemicals. Thalidomide is a species-specific developmental toxicant that causes severe limb malformations in humans but not in mice. Here, we used microarrays to study transcriptomic changes induced by thalidomide in an in vitro model based on differentiation of mouse embryonic stem cells (mESCs). C57BL/6 mESCs were allowed to differentiate spontaneously and RNA was collected at 24, 48, and 72 h after exposuremore » to 0.25 mM thalidomide. Global gene expression analysis using microarrays revealed hundreds of differentially expressed genes upon thalidomide exposure that were enriched in gene ontology (GO) terms and canonical pathways associated with embryonic development and differentiation. In addition, many genes were found to be involved in small GTPases-mediated signal transduction, heart development, and inflammatory responses, which coincide with clinical evidences and may represent critical embryotoxicities of thalidomide. These results demonstrate that transcriptomics in combination with mouse embryonic stem cell differentiation is a promising alternative model for developmental toxicity assessment. - Highlights: • Studied genomic changes in mouse embryonic stem cells upon thalidomide exposure • Identified gene expression changes that may represent thalidomide embryotoxicity • The toxicogenomic changes coincide well with known thalidomide clinical outcomes. • The mouse embryonic stem cell model is suitable for developmental toxicity testing. • The model has the potential for high-throughput screening of a multitude of compounds.« less

Mitochondrial damage and cytoskeleton reorganization in human dermal fibroblasts exposed to artificial visible light similar to screen-emitted light.

PubMed

Rascalou, Adeline; Lamartine, Jérôme; Poydenot, Pauline; Demarne, Frédéric; Bechetoille, Nicolas

2018-05-05

Artificial visible light is everywhere in modern life. Social communication confronts us with screens of all kinds, and their use is on the rise. We are therefore increasingly exposed to artificial visible light, the effects of which on skin are poorly known. The purpose of this study was to model the artificial visible light emitted by electronic devices and assess its effect on normal human fibroblasts. The spectral irradiance emitted by electronic devices was optically measured and equipment was developed to accurately reproduce such artificial visible light. Effects on normal human fibroblasts were analyzed on human genome microarray-based gene expression analysis. At cellular level, visualization and image analysis were performed on the mitochondrial network and F-actin cytoskeleton. Cell proliferation, ATP release and type I procollagen secretion were also measured. We developed a device consisting of 36 LEDs simultaneously emitting blue, green and red light at distinct wavelengths (450 nm, 525 nm and 625 nm) with narrow spectra and equivalent radiant power for the three colors. A dose of 99 J/cm 2 artificial visible light was selected so as not to induce cell mortality following exposure. Microarray analysis revealed 2984 light-modulated transcripts. Functional annotation of light-responsive genes revealed several enriched functions including, amongst others, the "mitochondria" and "integrin signaling" categories. Selected results were confirmed by real-time quantitative PCR, analyzing 24 genes representing these two categories. Analysis of micro-patterned culture plates showed marked fragmentation of the mitochondrial network and disorganization of the F-actin cytoskeleton following exposure. Functionally, there was considerable impairment of cell growth and spread, ATP release and type I procollagen secretion in exposed fibroblasts. Artificial visible light induces drastic molecular and cellular changes in normal human fibroblasts. This may impede normal cellular functions and contribute to premature skin aging. The present results extend our knowledge of the effects of the low-energy wavelengths that are increasingly used to treat skin disorders. Copyright © 2018 Japanese Society for Investigative Dermatology. Published by Elsevier B.V. All rights reserved.

Fully Automated Complementary DNA Microarray Segmentation using a Novel Fuzzy-based Algorithm.

PubMed

Saberkari, Hamidreza; Bahrami, Sheyda; Shamsi, Mousa; Amoshahy, Mohammad Javad; Ghavifekr, Habib Badri; Sedaaghi, Mohammad Hossein

2015-01-01

DNA microarray is a powerful approach to study simultaneously, the expression of 1000 of genes in a single experiment. The average value of the fluorescent intensity could be calculated in a microarray experiment. The calculated intensity values are very close in amount to the levels of expression of a particular gene. However, determining the appropriate position of every spot in microarray images is a main challenge, which leads to the accurate classification of normal and abnormal (cancer) cells. In this paper, first a preprocessing approach is performed to eliminate the noise and artifacts available in microarray cells using the nonlinear anisotropic diffusion filtering method. Then, the coordinate center of each spot is positioned utilizing the mathematical morphology operations. Finally, the position of each spot is exactly determined through applying a novel hybrid model based on the principle component analysis and the spatial fuzzy c-means clustering (SFCM) algorithm. Using a Gaussian kernel in SFCM algorithm will lead to improving the quality in complementary DNA microarray segmentation. The performance of the proposed algorithm has been evaluated on the real microarray images, which is available in Stanford Microarray Databases. Results illustrate that the accuracy of microarray cells segmentation in the proposed algorithm reaches to 100% and 98% for noiseless/noisy cells, respectively.

APPLICATION OF CDNA MICROARRAY TECHNOLOGY TO IN VITRO TOXICOLOGY AND THE SELECTION OF GENES FOR A REAL TIME RT-PCR-BASED SCREEN FOR OXIDATIVE STRESS IN HEP-G2 CELLS

EPA Science Inventory

Large-scale analysis of gene expression using cDNA microarrays promises the
rapid detection of the mode of toxicity for drugs and other chemicals. cDNA
microarrays were used to examine chemically-induced alterations of gene
expression in HepG2 cells exposed to oxidative ...

Where statistics and molecular microarray experiments biology meet.

PubMed

Kelmansky, Diana M

2013-01-01

This review chapter presents a statistical point of view to microarray experiments with the purpose of understanding the apparent contradictions that often appear in relation to their results. We give a brief introduction of molecular biology for nonspecialists. We describe microarray experiments from their construction and the biological principles the experiments rely on, to data acquisition and analysis. The role of epidemiological approaches and sample size considerations are also discussed.

Self-directed student research through analysis of microarray datasets: a computer-based functional genomics practical class for masters-level students.

PubMed

Grenville-Briggs, Laura J; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate active learning through experience of current research methods in bioinformatics and functional genomics. They seek to closely mimic a realistic research environment, and require the students first to propose research hypotheses, then test those hypotheses using specific sections of the microarray dataset. The complexity of the microarray data provides students with the freedom to propose their own unique hypotheses, tested using appropriate sections of the microarray data. This research latitude was highly regarded by students and is a strength of this practical. In addition, the focus on DNA damage by radiation and mutagenic chemicals allows them to place their results in a human medical context, and successfully sparks broad interest in the subject material. In evaluation, 79% of students scored the practical workshops on a five-point scale as 4 or 5 (totally effective) for student learning. More broadly, the general use of microarray data as a "student research playground" is also discussed. Copyright © 2011 Wiley Periodicals, Inc.

Phenotypic and genomic responses to titanium dioxide and cerium oxide nanoparticles in Arabidopsis germinants

EPA Science Inventory

The effects of exposure to two nanoparticles (NPs) -titanium dioxide (nano-titania) and cerium oxide (nano-ceria) at 500 mg NPs L-1 on gene expression and growth in Arabidopsis thaliana germinants were studied using microarrays and phenotype studies. After 12 days post treatment,...

Identification and handling of artifactual gene expression profiles emerging in microarray hybridization experiments

PubMed Central

Brodsky, Leonid; Leontovich, Andrei; Shtutman, Michael; Feinstein, Elena

2004-01-01

Mathematical methods of analysis of microarray hybridizations deal with gene expression profiles as elementary units. However, some of these profiles do not reflect a biologically relevant transcriptional response, but rather stem from technical artifacts. Here, we describe two technically independent but rationally interconnected methods for identification of such artifactual profiles. Our diagnostics are based on detection of deviations from uniformity, which is assumed as the main underlying principle of microarray design. Method 1 is based on detection of non-uniformity of microarray distribution of printed genes that are clustered based on the similarity of their expression profiles. Method 2 is based on evaluation of the presence of gene-specific microarray spots within the slides’ areas characterized by an abnormal concentration of low/high differential expression values, which we define as ‘patterns of differentials’. Applying two novel algorithms, for nested clustering (method 1) and for pattern detection (method 2), we can make a dual estimation of the profile’s quality for almost every printed gene. Genes with artifactual profiles detected by method 1 may then be removed from further analysis. Suspicious differential expression values detected by method 2 may be either removed or weighted according to the probabilities of patterns that cover them, thus diminishing their input in any further data analysis. PMID:14999086

Novel calibration tools and validation concepts for microarray-based platforms used in molecular diagnostics and food safety control.

PubMed

Brunner, C; Hoffmann, K; Thiele, T; Schedler, U; Jehle, H; Resch-Genger, U

2015-04-01

Commercial platforms consisting of ready-to-use microarrays printed with target-specific DNA probes, a microarray scanner, and software for data analysis are available for different applications in medical diagnostics and food analysis, detecting, e.g., viral and bacteriological DNA sequences. The transfer of these tools from basic research to routine analysis, their broad acceptance in regulated areas, and their use in medical practice requires suitable calibration tools for regular control of instrument performance in addition to internal assay controls. Here, we present the development of a novel assay-adapted calibration slide for a commercialized DNA-based assay platform, consisting of precisely arranged fluorescent areas of various intensities obtained by incorporating different concentrations of a "green" dye and a "red" dye in a polymer matrix. These dyes present "Cy3" and "Cy5" analogues with improved photostability, chosen based upon their spectroscopic properties closely matching those of common labels for the green and red channel of microarray scanners. This simple tool allows to efficiently and regularly assess and control the performance of the microarray scanner provided with the biochip platform and to compare different scanners. It will be eventually used as fluorescence intensity scale for referencing of assays results and to enhance the overall comparability of diagnostic tests.

Analysis of host response to bacterial infection using error model based gene expression microarray experiments

PubMed Central

Stekel, Dov J.; Sarti, Donatella; Trevino, Victor; Zhang, Lihong; Salmon, Mike; Buckley, Chris D.; Stevens, Mark; Pallen, Mark J.; Penn, Charles; Falciani, Francesco

2005-01-01

A key step in the analysis of microarray data is the selection of genes that are differentially expressed. Ideally, such experiments should be properly replicated in order to infer both technical and biological variability, and the data should be subjected to rigorous hypothesis tests to identify the differentially expressed genes. However, in microarray experiments involving the analysis of very large numbers of biological samples, replication is not always practical. Therefore, there is a need for a method to select differentially expressed genes in a rational way from insufficiently replicated data. In this paper, we describe a simple method that uses bootstrapping to generate an error model from a replicated pilot study that can be used to identify differentially expressed genes in subsequent large-scale studies on the same platform, but in which there may be no replicated arrays. The method builds a stratified error model that includes array-to-array variability, feature-to-feature variability and the dependence of error on signal intensity. We apply this model to the characterization of the host response in a model of bacterial infection of human intestinal epithelial cells. We demonstrate the effectiveness of error model based microarray experiments and propose this as a general strategy for a microarray-based screening of large collections of biological samples. PMID:15800204

AccuTyping: new algorithms for automated analysis of data from high-throughput genotyping with oligonucleotide microarrays

PubMed Central

Hu, Guohong; Wang, Hui-Yun; Greenawalt, Danielle M.; Azaro, Marco A.; Luo, Minjie; Tereshchenko, Irina V.; Cui, Xiangfeng; Yang, Qifeng; Gao, Richeng; Shen, Li; Li, Honghua

2006-01-01

Microarray-based analysis of single nucleotide polymorphisms (SNPs) has many applications in large-scale genetic studies. To minimize the influence of experimental variation, microarray data usually need to be processed in different aspects including background subtraction, normalization and low-signal filtering before genotype determination. Although many algorithms are sophisticated for these purposes, biases are still present. In the present paper, new algorithms for SNP microarray data analysis and the software, AccuTyping, developed based on these algorithms are described. The algorithms take advantage of a large number of SNPs included in each assay, and the fact that the top and bottom 20% of SNPs can be safely treated as homozygous after sorting based on their ratios between the signal intensities. These SNPs are then used as controls for color channel normalization and background subtraction. Genotype calls are made based on the logarithms of signal intensity ratios using two cutoff values, which were determined after training the program with a dataset of ∼160 000 genotypes and validated by non-microarray methods. AccuTyping was used to determine >300 000 genotypes of DNA and sperm samples. The accuracy was shown to be >99%. AccuTyping can be downloaded from . PMID:16982644

The statistics of identifying differentially expressed genes in Expresso and TM4: a comparison

PubMed Central

Sioson, Allan A; Mane, Shrinivasrao P; Li, Pinghua; Sha, Wei; Heath, Lenwood S; Bohnert, Hans J; Grene, Ruth

2006-01-01

Background Analysis of DNA microarray data takes as input spot intensity measurements from scanner software and returns differential expression of genes between two conditions, together with a statistical significance assessment. This process typically consists of two steps: data normalization and identification of differentially expressed genes through statistical analysis. The Expresso microarray experiment management system implements these steps with a two-stage, log-linear ANOVA mixed model technique, tailored to individual experimental designs. The complement of tools in TM4, on the other hand, is based on a number of preset design choices that limit its flexibility. In the TM4 microarray analysis suite, normalization, filter, and analysis methods form an analysis pipeline. TM4 computes integrated intensity values (IIV) from the average intensities and spot pixel counts returned by the scanner software as input to its normalization steps. By contrast, Expresso can use either IIV data or median intensity values (MIV). Here, we compare Expresso and TM4 analysis of two experiments and assess the results against qRT-PCR data. Results The Expresso analysis using MIV data consistently identifies more genes as differentially expressed, when compared to Expresso analysis with IIV data. The typical TM4 normalization and filtering pipeline corrects systematic intensity-specific bias on a per microarray basis. Subsequent statistical analysis with Expresso or a TM4 t-test can effectively identify differentially expressed genes. The best agreement with qRT-PCR data is obtained through the use of Expresso analysis and MIV data. Conclusion The results of this research are of practical value to biologists who analyze microarray data sets. The TM4 normalization and filtering pipeline corrects microarray-specific systematic bias and complements the normalization stage in Expresso analysis. The results of Expresso using MIV data have the best agreement with qRT-PCR results. In one experiment, MIV is a better choice than IIV as input to data normalization and statistical analysis methods, as it yields as greater number of statistically significant differentially expressed genes; TM4 does not support the choice of MIV input data. Overall, the more flexible and extensive statistical models of Expresso achieve more accurate analytical results, when judged by the yardstick of qRT-PCR data, in the context of an experimental design of modest complexity. PMID:16626497

Diagnostic Yield of Chromosomal Microarray Analysis in an Autism Primary Care Practice: Which Guidelines to Implement?

ERIC Educational Resources Information Center

McGrew, Susan G.; Peters, Brittany R.; Crittendon, Julie A.; Veenstra-VanderWeele, Jeremy

2012-01-01

Genetic testing is recommended for patients with ASD; however specific recommendations vary by specialty. American Academy of Pediatrics and American Academy of Neurology guidelines recommend G-banded karyotype and Fragile X DNA. The American College of Medical Genetics recommends Chromosomal Microarray Analysis (CMA). We determined the yield of…

Self-Directed Student Research through Analysis of Microarray Datasets: A Computer-Based Functional Genomics Practical Class for Masters-Level Students

ERIC Educational Resources Information Center

Grenville-Briggs, Laura J.; Stansfield, Ian

2011-01-01

This report describes a linked series of Masters-level computer practical workshops. They comprise an advanced functional genomics investigation, based upon analysis of a microarray dataset probing yeast DNA damage responses. The workshops require the students to analyse highly complex transcriptomics datasets, and were designed to stimulate…

CNV-ROC: A cost effective, computer-aided analytical performance evaluator of chromosomal microarrays.

PubMed

Goodman, Corey W; Major, Heather J; Walls, William D; Sheffield, Val C; Casavant, Thomas L; Darbro, Benjamin W

2015-04-01

Chromosomal microarrays (CMAs) are routinely used in both research and clinical laboratories; yet, little attention has been given to the estimation of genome-wide true and false negatives during the assessment of these assays and how such information could be used to calibrate various algorithmic metrics to improve performance. Low-throughput, locus-specific methods such as fluorescence in situ hybridization (FISH), quantitative PCR (qPCR), or multiplex ligation-dependent probe amplification (MLPA) preclude rigorous calibration of various metrics used by copy number variant (CNV) detection algorithms. To aid this task, we have established a comparative methodology, CNV-ROC, which is capable of performing a high throughput, low cost, analysis of CMAs that takes into consideration genome-wide true and false negatives. CNV-ROC uses a higher resolution microarray to confirm calls from a lower resolution microarray and provides for a true measure of genome-wide performance metrics at the resolution offered by microarray testing. CNV-ROC also provides for a very precise comparison of CNV calls between two microarray platforms without the need to establish an arbitrary degree of overlap. Comparison of CNVs across microarrays is done on a per-probe basis and receiver operator characteristic (ROC) analysis is used to calibrate algorithmic metrics, such as log2 ratio threshold, to enhance CNV calling performance. CNV-ROC addresses a critical and consistently overlooked aspect of analytical assessments of genome-wide techniques like CMAs which is the measurement and use of genome-wide true and false negative data for the calculation of performance metrics and comparison of CNV profiles between different microarray experiments. Copyright © 2015 Elsevier Inc. All rights reserved.

Fabrication of antibody microarrays by light-induced covalent and oriented immobilization.

PubMed

Adak, Avijit K; Li, Ben-Yuan; Huang, Li-De; Lin, Ting-Wei; Chang, Tsung-Che; Hwang, Kuo Chu; Lin, Chun-Cheng

2014-07-09

Antibody microarrays have important applications for the sensitive detection of biologically important target molecules and as biosensors for clinical applications. Microarrays produced by oriented immobilization of antibodies generally have higher antigen-binding capacities than those in which antibodies are immobilized with random orientations. Here, we present a UV photo-cross-linking approach that utilizes boronic acid to achieve oriented immobilization of an antibody on a surface while retaining the antigen-binding activity of the immobilized antibody. A photoactive boronic acid probe was designed and synthesized in which boronic acid provided good affinity and specificity for the recognition of glycan chains on the Fc region of the antibody, enabling covalent tethering to the antibody upon exposure to UV light. Once irradiated with optimal UV exposure (16 mW/cm(2)), significant antibody immobilization on a boronic acid-presenting surface with maximal antigen detection sensitivity in a single step was achieved, thus obviating the necessity of prior antibody modifications. The developed approach is highly modular, as demonstrated by its implementation in sensitive sandwich immunoassays for the protein analytes Ricinus communis agglutinin 120, human prostate-specific antigen, and interleukin-6 with limits of detection of 7.4, 29, and 16 pM, respectively. Furthermore, the present system enabled the detection of multiple analytes in samples without any noticeable cross-reactivities. Antibody coupling via the use of boronic acid and UV light represents a practical, oriented immobilization method with significant implications for the construction of a large array of immunosensors for diagnostic applications.

Parallel human genome analysis: microarray-based expression monitoring of 1000 genes.

PubMed Central

Schena, M; Shalon, D; Heller, R; Chai, A; Brown, P O; Davis, R W

1996-01-01

Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm2 DNA "chips" were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay. Array elements that displayed differential expression patterns under given experimental conditions were characterized by sequencing. The identification of known and novel heat shock and phorbol ester-regulated genes in human T cells demonstrates the sensitivity of the assay. Parallel gene analysis with microarrays provides a rapid and efficient method for large-scale human gene discovery. Images Fig. 1 Fig. 2 Fig. 3 PMID:8855227

Microarray Data Processing Techniques for Genome-Scale Network Inference from Large Public Repositories.

PubMed

Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas

2016-09-19

Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data.

PubMed

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R; Del Río-Navarro, Blanca E; Mendoza-Vargas, Alfredo; Sánchez, Filiberto; Ochoa-Leyva, Adrian

2017-01-01

In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6-10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments.

Chipster: user-friendly analysis software for microarray and other high-throughput data.

PubMed

Kallio, M Aleksi; Tuimala, Jarno T; Hupponen, Taavi; Klemelä, Petri; Gentile, Massimiliano; Scheinin, Ilari; Koski, Mikko; Käki, Janne; Korpelainen, Eija I

2011-10-14

The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available.

Chipster: user-friendly analysis software for microarray and other high-throughput data

PubMed Central

2011-01-01

Background The growth of high-throughput technologies such as microarrays and next generation sequencing has been accompanied by active research in data analysis methodology, producing new analysis methods at a rapid pace. While most of the newly developed methods are freely available, their use requires substantial computational skills. In order to enable non-programming biologists to benefit from the method development in a timely manner, we have created the Chipster software. Results Chipster (http://chipster.csc.fi/) brings a powerful collection of data analysis methods within the reach of bioscientists via its intuitive graphical user interface. Users can analyze and integrate different data types such as gene expression, miRNA and aCGH. The analysis functionality is complemented with rich interactive visualizations, allowing users to select datapoints and create new gene lists based on these selections. Importantly, users can save the performed analysis steps as reusable, automatic workflows, which can also be shared with other users. Being a versatile and easily extendable platform, Chipster can be used for microarray, proteomics and sequencing data. In this article we describe its comprehensive collection of analysis and visualization tools for microarray data using three case studies. Conclusions Chipster is a user-friendly analysis software for high-throughput data. Its intuitive graphical user interface enables biologists to access a powerful collection of data analysis and integration tools, and to visualize data interactively. Users can collaborate by sharing analysis sessions and workflows. Chipster is open source, and the server installation package is freely available. PMID:21999641

Functional Genomic Analysis of the Impact of Camelina (Camelina sativa) Meal on Atlantic Salmon (Salmo salar) Distal Intestine Gene Expression and Physiology.

PubMed

Brown, Tyler D; Hori, Tiago S; Xue, Xi; Ye, Chang Lin; Anderson, Derek M; Rise, Matthew L

2016-06-01

The inclusion of plant meals in diets of farmed Atlantic salmon can elicit inflammatory responses in the distal intestine (DI). For the present work, fish were fed a standard fish meal (FM) diet or a diet with partial replacement of FM with solvent-extracted camelina meal (CM) (8, 16, or 24 % CM inclusion) during a 16-week feeding trial. A significant decrease in growth performance was seen in fish fed all CM inclusion diets (Hixson et al. in Aquacult Nutr 22:615-630, 2016). A 4x44K oligonucleotide microarray experiment was carried out and significance analysis of microarrays (SAM) and rank products (RP) methods were used to identify differentially expressed genes between the DIs of fish fed the 24 % CM diet and those fed the FM diet. Twelve features representing six known transcripts and two unknowns were identified as CM responsive by both SAM and RP. The six known transcripts (including thioredoxin and ependymin), in addition to tgfb, mmp13, and GILT, were studied using qPCR with RNA templates from all four experimental diet groups. All six microarray-identified genes were confirmed to be CM responsive, as was tgfb and mmp13. Histopathological analyses identified signs of inflammation in the DI of salmon fed CM-containing diets, including lamina propria and sub-epithelial mucosa thickening, infiltration of eosinophilic granule cells, increased goblet cells and decreased enterocyte vacuolization. All of these were significantly altered in 24 % CM compared to all other diets, with the latter two also altered in 16 % CM compared with 8 % CM and control diet groups. Significant correlation was seen between histological parameters as well as between five of the qPCR analyzed genes and histological parameters. These molecular biomarkers of inflammation arising from long-term dietary CM exposure will be useful in the development of CM-containing diets that do not have deleterious effects on salmon growth or physiology.

A database for the analysis of immunity genes in Drosophila: PADMA database.

PubMed

Lee, Mark J; Mondal, Ariful; Small, Chiyedza; Paddibhatla, Indira; Kawaguchi, Akira; Govind, Shubha

2011-01-01

While microarray experiments generate voluminous data, discerning trends that support an existing or alternative paradigm is challenging. To synergize hypothesis building and testing, we designed the Pathogen Associated Drosophila MicroArray (PADMA) database for easy retrieval and comparison of microarray results from immunity-related experiments (www.padmadatabase.org). PADMA also allows biologists to upload their microarray-results and compare it with datasets housed within PADMA. We tested PADMA using a preliminary dataset from Ganaspis xanthopoda-infected fly larvae, and uncovered unexpected trends in gene expression, reshaping our hypothesis. Thus, the PADMA database will be a useful resource to fly researchers to evaluate, revise, and refine hypotheses.

Enhancing Interdisciplinary Mathematics and Biology Education: A Microarray Data Analysis Course Bridging These Disciplines

ERIC Educational Resources Information Center

Tra, Yolande V.; Evans, Irene M.

2010-01-01

"BIO2010" put forth the goal of improving the mathematical educational background of biology students. The analysis and interpretation of microarray high-dimensional data can be very challenging and is best done by a statistician and a biologist working and teaching in a collaborative manner. We set up such a collaboration and designed a course on…

Diagnostic Yield of Chromosomal Microarray Analysis in a Cohort of Patients with Autism Spectrum Disorders from a Highly Consanguineous Population

ERIC Educational Resources Information Center

Al-Mamari, Watfa; Al-Saegh, Abeer; Al-Kindy, Adila; Bruwer, Zandre; Al-Murshedi, Fathiya; Al-Thihli, Khalid

2015-01-01

Autism Spectrum Disorders are a complicated group of disorders characterized with heterogeneous genetic etiologies. The genetic investigations for this group of disorders have expanded considerably over the past decade. In our study we designed a tired approach and studied the diagnostic yield of chromosomal microarray analysis on patients…

Immunological Targeting of Tumor Initiating Prostate Cancer Cells

DTIC Science & Technology

2014-10-01

clinically using well-accepted immuno-competent animal models. 2) Keywords: Prostate Cancer, Lymphocyte, Vaccine, Antibody 3) Overall Project Summary...castrate animals . Task 1: Identify and verify antigenic targets from CAstrate Resistant Luminal Epithelial Cells (CRLEC) (months 1-16... animals per group will be processed to derive sufficient RNA for microarray analysis; the experiment will be repeated x 3. Microarray analysis will

MiMiR – an integrated platform for microarray data sharing, mining and analysis

PubMed Central

Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

2008-01-01

Background Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. Results A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. Conclusion The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies. PMID:18801157

MiMiR--an integrated platform for microarray data sharing, mining and analysis.

PubMed

Tomlinson, Chris; Thimma, Manjula; Alexandrakis, Stelios; Castillo, Tito; Dennis, Jayne L; Brooks, Anthony; Bradley, Thomas; Turnbull, Carly; Blaveri, Ekaterini; Barton, Geraint; Chiba, Norie; Maratou, Klio; Soutter, Pat; Aitman, Tim; Game, Laurence

2008-09-18

Despite considerable efforts within the microarray community for standardising data format, content and description, microarray technologies present major challenges in managing, sharing, analysing and re-using the large amount of data generated locally or internationally. Additionally, it is recognised that inconsistent and low quality experimental annotation in public data repositories significantly compromises the re-use of microarray data for meta-analysis. MiMiR, the Microarray data Mining Resource was designed to tackle some of these limitations and challenges. Here we present new software components and enhancements to the original infrastructure that increase accessibility, utility and opportunities for large scale mining of experimental and clinical data. A user friendly Online Annotation Tool allows researchers to submit detailed experimental information via the web at the time of data generation rather than at the time of publication. This ensures the easy access and high accuracy of meta-data collected. Experiments are programmatically built in the MiMiR database from the submitted information and details are systematically curated and further annotated by a team of trained annotators using a new Curation and Annotation Tool. Clinical information can be annotated and coded with a clinical Data Mapping Tool within an appropriate ethical framework. Users can visualise experimental annotation, assess data quality, download and share data via a web-based experiment browser called MiMiR Online. All requests to access data in MiMiR are routed through a sophisticated middleware security layer thereby allowing secure data access and sharing amongst MiMiR registered users prior to publication. Data in MiMiR can be mined and analysed using the integrated EMAAS open source analysis web portal or via export of data and meta-data into Rosetta Resolver data analysis package. The new MiMiR suite of software enables systematic and effective capture of extensive experimental and clinical information with the highest MIAME score, and secure data sharing prior to publication. MiMiR currently contains more than 150 experiments corresponding to over 3000 hybridisations and supports the Microarray Centre's large microarray user community and two international consortia. The MiMiR flexible and scalable hardware and software architecture enables secure warehousing of thousands of datasets, including clinical studies, from microarray and potentially other -omics technologies.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Andersen, G.L.; He, Z.; DeSantis, T.Z.

Microarrays have proven to be a useful and high-throughput method to provide targeted DNA sequence information for up to many thousands of specific genetic regions in a single test. A microarray consists of multiple DNA oligonucleotide probes that, under high stringency conditions, hybridize only to specific complementary nucleic acid sequences (targets). A fluorescent signal indicates the presence and, in many cases, the abundance of genetic regions of interest. In this chapter we will look at how microarrays are used in microbial ecology, especially with the recent increase in microbial community DNA sequence data. Of particular interest to microbial ecologists, phylogeneticmore » microarrays are used for the analysis of phylotypes in a community and functional gene arrays are used for the analysis of functional genes, and, by inference, phylotypes in environmental samples. A phylogenetic microarray that has been developed by the Andersen laboratory, the PhyloChip, will be discussed as an example of a microarray that targets the known diversity within the 16S rRNA gene to determine microbial community composition. Using multiple, confirmatory probes to increase the confidence of detection and a mismatch probe for every perfect match probe to minimize the effect of cross-hybridization by non-target regions, the PhyloChip is able to simultaneously identify any of thousands of taxa present in an environmental sample. The PhyloChip is shown to reveal greater diversity within a community than rRNA gene sequencing due to the placement of the entire gene product on the microarray compared with the analysis of up to thousands of individual molecules by traditional sequencing methods. A functional gene array that has been developed by the Zhou laboratory, the GeoChip, will be discussed as an example of a microarray that dynamically identifies functional activities of multiple members within a community. The recent version of GeoChip contains more than 24,000 50mer oligonucleotide probes and covers more than 10,000 gene sequences in 150 gene categories involved in carbon, nitrogen, sulfur, and phosphorus cycling, metal resistance and reduction, and organic contaminant degradation. GeoChip can be used as a generic tool for microbial community analysis, and also link microbial community structure to ecosystem functioning. Examples of the application of both arrays in different environmental samples will be described in the two subsequent sections.« less

Evaluation of a low density DNA microarray for small B-cell non-Hodgkin lymphoma differential diagnosis.

PubMed

Gillet, Jean-Pierre; Molina, Thierry Jo; Jamart, Jacques; Gaulard, Philippe; Leroy, Karen; Briere, Josette; Theate, Ivan; Thieblemont, Catherine; Bosly, Andre; Herin, Michel; Hamels, Jacques; Remacle, Jose

2009-03-01

Lymphomas are classified according to the World Health Organisation (WHO) classification which defines subtypes on the basis of clinical, morphological, immunophenotypic, molecular and cytogenetic criteria. Differential diagnosis of the subtypes is sometimes difficult, especially for small B-cell lymphoma (SBCL). Standardisation of molecular genetic assays using multiple gene expression analysis by microarrays could be a useful complement to the current diagnosis. The aim of the present study was to develop a low density DNA microarray for the analysis of 107 genes associated with B-cell non-Hodgkin lymphoma and to evaluate its performance in the diagnosis of SBCL. A predictive tool based on Fisher discriminant analysis using a training set of 40 patients including four different subtypes (follicular lymphoma n = 15, mantle cell lymphoma n = 7, B-cell chronic lymphocytic leukemia n = 6 and splenic marginal zone lymphoma n = 12) was designed. A short additional preliminary analysis to gauge the accuracy of this signature was then performed on an external set of nine patients. Using this model, eight of nine of those samples were classified successfully. This pilot study demonstrates that such a microarray tool may be a promising diagnostic approach for small B-cell non-Hodgkin lymphoma.

MAGMA: analysis of two-channel microarrays made easy.

PubMed

Rehrauer, Hubert; Zoller, Stefan; Schlapbach, Ralph

2007-07-01

The web application MAGMA provides a simple and intuitive interface to identify differentially expressed genes from two-channel microarray data. While the underlying algorithms are not superior to those of similar web applications, MAGMA is particularly user friendly and can be used without prior training. The user interface guides the novice user through the most typical microarray analysis workflow consisting of data upload, annotation, normalization and statistical analysis. It automatically generates R-scripts that document MAGMA's entire data processing steps, thereby allowing the user to regenerate all results in his local R installation. The implementation of MAGMA follows the model-view-controller design pattern that strictly separates the R-based statistical data processing, the web-representation and the application logic. This modular design makes the application flexible and easily extendible by experts in one of the fields: statistical microarray analysis, web design or software development. State-of-the-art Java Server Faces technology was used to generate the web interface and to perform user input processing. MAGMA's object-oriented modular framework makes it easily extendible and applicable to other fields and demonstrates that modern Java technology is also suitable for rather small and concise academic projects. MAGMA is freely available at www.magma-fgcz.uzh.ch.

Tomato Expression Database (TED): a suite of data presentation and analysis tools

PubMed Central

Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James

2006-01-01

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150 000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at . PMID:16381976

Tomato Expression Database (TED): a suite of data presentation and analysis tools.

PubMed

Fei, Zhangjun; Tang, Xuemei; Alba, Rob; Giovannoni, James

2006-01-01

The Tomato Expression Database (TED) includes three integrated components. The Tomato Microarray Data Warehouse serves as a central repository for raw gene expression data derived from the public tomato cDNA microarray. In addition to expression data, TED stores experimental design and array information in compliance with the MIAME guidelines and provides web interfaces for researchers to retrieve data for their own analysis and use. The Tomato Microarray Expression Database contains normalized and processed microarray data for ten time points with nine pair-wise comparisons during fruit development and ripening in a normal tomato variety and nearly isogenic single gene mutants impacting fruit development and ripening. Finally, the Tomato Digital Expression Database contains raw and normalized digital expression (EST abundance) data derived from analysis of the complete public tomato EST collection containing >150,000 ESTs derived from 27 different non-normalized EST libraries. This last component also includes tools for the comparison of tomato and Arabidopsis digital expression data. A set of query interfaces and analysis, and visualization tools have been developed and incorporated into TED, which aid users in identifying and deciphering biologically important information from our datasets. TED can be accessed at http://ted.bti.cornell.edu.

Olfactory Transcriptional Analysis of Salmon Exposed to Mixtures of Chlorpyrifos and Malathion Reveal Novel Molecular Pathways of Neurobehavioral Injury

PubMed Central

Wang, Lu; Espinoza, Herbert M.; MacDonald, James W.; Bammler, Theo K.; Williams, Chase R.; Yeh, Andrew; Louie, Ke’ale W.; Marcinek, David J.; Gallagher, Evan P.

2016-01-01

Pacific salmon exposed to sublethal concentrations of organophosphate pesticides (OP) have impaired olfactory function that can lead to loss of behaviors that are essential for survival. These exposures often involve mixtures and can occur at levels below those which inhibit acetylcholinesterase (AChE). In this study, juvenile Coho salmon were exposed for 24 h to either 0.1, 0.5, or 2.5 ppb chlorpyrifos (CPF), 2, 10, or 50 ppb malathion (MAL), or binary mixtures of 0.1 CPF:2 ppb MAL, 0.5 CPF:10 ppb MAL, or 2.5 CPF:10 ppb MAL to mimic single and binary environmental exposures. Microarray analysis of olfactory rosettes from pesticide-exposed salmon revealed differentially expressed genes involved in nervous system function and signaling, aryl hydrocarbon receptor signaling, xenobiotic metabolism, and mitochondrial dysfunction. Coho exposed to OP mixtures exhibited a more pronounced loss in detection of a predatory olfactory cue relative to those exposed to single compounds, whereas respirometry experiments demonstrated that exposure to OPs, individually and in mixtures, reduced maximum respiratory capacity of olfactory rosette mitochondria. The observed molecular, biochemical, and behavioral effects occurred largely in the absence of effects on brain AChE. In summary, our results provide new insights associated with the sublethal neurotoxic effects of OP mixtures relevant to environmental exposures involving molecular and cellular pathways of injury to the salmon olfactory system that underlie neurobehavioral injury. PMID:26494550

Development and application of a microarray meter tool to optimize microarray experiments

PubMed Central

Rouse, Richard JD; Field, Katrine; Lapira, Jennifer; Lee, Allen; Wick, Ivan; Eckhardt, Colleen; Bhasker, C Ramana; Soverchia, Laura; Hardiman, Gary

2008-01-01

Background Successful microarray experimentation requires a complex interplay between the slide chemistry, the printing pins, the nucleic acid probes and targets, and the hybridization milieu. Optimization of these parameters and a careful evaluation of emerging slide chemistries are a prerequisite to any large scale array fabrication effort. We have developed a 'microarray meter' tool which assesses the inherent variations associated with microarray measurement prior to embarking on large scale projects. Findings The microarray meter consists of nucleic acid targets (reference and dynamic range control) and probe components. Different plate designs containing identical probe material were formulated to accommodate different robotic and pin designs. We examined the variability in probe quality and quantity (as judged by the amount of DNA printed and remaining post-hybridization) using three robots equipped with capillary printing pins. Discussion The generation of microarray data with minimal variation requires consistent quality control of the (DNA microarray) manufacturing and experimental processes. Spot reproducibility is a measure primarily of the variations associated with printing. The microarray meter assesses array quality by measuring the DNA content for every feature. It provides a post-hybridization analysis of array quality by scoring probe performance using three metrics, a) a measure of variability in the signal intensities, b) a measure of the signal dynamic range and c) a measure of variability of the spot morphologies. PMID:18710498

Assessing the impact of Benzo[a]pyrene on Marine Mussels: Application of a novel targeted low density microarray complementing classical biomarker responses

PubMed Central

Sforzini, Susanna; Arlt, Volker M.; Barranger, Audrey; Dallas, Lorna J.; Oliveri, Caterina; Aminot, Yann; Pacchioni, Beniamina; Millino, Caterina; Lanfranchi, Gerolamo; Readman, James W.; Moore, Michael N.; Viarengo, Aldo; Jha, Awadhesh N.

2017-01-01

Despite the increasing use of mussels in environmental monitoring and ecotoxicological studies, their genomes and gene functions have not been thoroughly explored. Several cDNA microarrays were recently proposed for Mytilus spp., but putatively identified partial transcripts have rendered the generation of robust transcriptional responses difficult in terms of pathway identification. We developed a new low density oligonucleotide microarray with 465 probes covering the same number of genes. Target genes were selected to cover most of the well-known biological processes in the stress response documented over the last decade in bivalve species at the cellular and tissue levels. Our new ‘STressREsponse Microarray’ (STREM) platform consists of eight sub-arrays with three replicates for each target in each sub-array. To assess the potential use of the new array, we tested the effect of the ubiquitous environmental pollutant benzo[a]pyrene (B[a]P) at 5, 50, and 100 μg/L on two target tissues, the gills and digestive gland, of Mytilus galloprovincialis exposed invivo for three days. Bioaccumulation of B[a]P was also determined demonstrating exposure in both tissues. In addition to the well-known effects of B[a]P on DNA metabolism and oxidative stress, the new array data provided clues about the implication of other biological processes, such as cytoskeleton, immune response, adhesion to substrate, and mitochondrial activities. Transcriptional data were confirmed using qRT-PCR. We further investigated cellular functions and possible alterations related to biological processes highlighted by the microarray data using oxidative stress biomarkers (Lipofuscin content) and the assessment of genotoxicity. DNA damage, as measured by the alkaline comet assay, increased as a function of dose.DNA adducts measurements using 32P-postlabeling method also showed the presence of bulky DNA adducts (i.e. dG-N2-BPDE). Lipofiscin content increased significantly in B[a]P exposed mussels. Immunohistochemical analysis of tubulin and actin showed changes in cytoskeleton organisation. Our results adopting an integrated approach confirmed that the combination of newly developed transcriptomic approcah, classical biomarkers along with chemical analysis of water and tissue samples should be considered for environmental bioimonitoring and ecotoxicological studies to obtain holistic information to assess the impact of contaminants on the biota. PMID:28651000

High-throughput DNA microarray detection of pathogenic bacteria in shallow well groundwater in the Kathmandu Valley, Nepal.

PubMed

Inoue, Daisuke; Hinoura, Takuji; Suzuki, Noriko; Pang, Junqin; Malla, Rabin; Shrestha, Sadhana; Chapagain, Saroj Kumar; Matsuzawa, Hiroaki; Nakamura, Takashi; Tanaka, Yasuhiro; Ike, Michihiko; Nishida, Kei; Sei, Kazunari

2015-01-01

Because of heavy dependence on groundwater for drinking water and other domestic use, microbial contamination of groundwater is a serious problem in the Kathmandu Valley, Nepal. This study investigated comprehensively the occurrence of pathogenic bacteria in shallow well groundwater in the Kathmandu Valley by applying DNA microarray analysis targeting 941 pathogenic bacterial species/groups. Water quality measurements found significant coliform (fecal) contamination in 10 of the 11 investigated groundwater samples and significant nitrogen contamination in some samples. The results of DNA microarray analysis revealed the presence of 1-37 pathogen species/groups, including 1-27 biosafety level 2 ones, in 9 of the 11 groundwater samples. While the detected pathogens included several feces- and animal-related ones, those belonging to Legionella and Arthrobacter, which were considered not to be directly associated with feces, were detected prevalently. This study could provide a rough picture of overall pathogenic bacterial contamination in the Kathmandu Valley, and demonstrated the usefulness of DNA microarray analysis as a comprehensive screening tool of a wide variety of pathogenic bacteria.

Microarray Analysis of Long Noncoding RNAs in Female Diabetic Peripheral Neuropathy Patients.

PubMed

Luo, Lin; Ji, Lin-Dan; Cai, Jiang-Jia; Feng, Mei; Zhou, Mi; Hu, Su-Pei; Xu, Jin; Zhou, Wen-Hua

2018-01-01

Diabetic peripheral neuropathy (DPN) is the most common complication of diabetes mellitus (DM). Because of its controversial pathogenesis, DPN is still not diagnosed or managed properly in most patients. In this study, human lncRNA microarrays were used to identify the differentially expressed lncRNAs in DM and DPN patients, and some of the discovered lncRNAs were further validated in additional 78 samples by quantitative realtime PCR (qRT-PCR). The microarray analysis identified 446 and 1327 differentially expressed lncRNAs in DM and DPN, respectively. The KEGG pathway analysis further revealed that the differentially expressed lncRNA-coexpressed mRNAs between DPN and DM groups were significantly enriched in the MAPK signaling pathway. The lncRNA/mRNA coexpression network indicated that BDNF and TRAF2 correlated with 6 lncRNAs. The qRT-PCR confirmed the initial microarray results. These findings demonstrated that the interplay between lncRNAs and mRNA may be involved in the pathogenesis of DPN, especially the neurotrophin-MAPK signaling pathway, thus providing relevant information for future studies. © 2018 The Author(s). Published by S. Karger AG, Basel.

MASQOT: a method for cDNA microarray spot quality control

PubMed Central

Bylesjö, Max; Eriksson, Daniel; Sjödin, Andreas; Sjöström, Michael; Jansson, Stefan; Antti, Henrik; Trygg, Johan

2005-01-01

Background cDNA microarray technology has emerged as a major player in the parallel detection of biomolecules, but still suffers from fundamental technical problems. Identifying and removing unreliable data is crucial to prevent the risk of receiving illusive analysis results. Visual assessment of spot quality is still a common procedure, despite the time-consuming work of manually inspecting spots in the range of hundreds of thousands or more. Results A novel methodology for cDNA microarray spot quality control is outlined. Multivariate discriminant analysis was used to assess spot quality based on existing and novel descriptors. The presented methodology displays high reproducibility and was found superior in identifying unreliable data compared to other evaluated methodologies. Conclusion The proposed methodology for cDNA microarray spot quality control generates non-discrete values of spot quality which can be utilized as weights in subsequent analysis procedures as well as to discard spots of undesired quality using the suggested threshold values. The MASQOT approach provides a consistent assessment of spot quality and can be considered an alternative to the labor-intensive manual quality assessment process. PMID:16223442

Upregulated epidermal growth factor receptor expression following near-infrared irradiation simulating solar radiation in a three-dimensional reconstructed human corneal epithelial tissue culture model.

PubMed

Tanaka, Yohei; Nakayama, Jun

2016-01-01

Humans are increasingly exposed to near-infrared (NIR) radiation from both natural (eg, solar) and artificial (eg, electrical appliances) sources. Although the biological effects of sun and ultraviolet (UV) exposure have been extensively investigated, the biological effect of NIR radiation is still unclear. We previously reported that NIR as well as UV induces photoaging and standard UV-blocking materials, such as sunglasses, do not sufficiently block NIR. The objective of this study was to investigate changes in gene expression in three-dimensional reconstructed corneal epithelial tissue culture exposed to broad-spectrum NIR irradiation to simulate solar NIR radiation that reaches human tissues. DNA microarray and quantitative real-time polymerase chain reaction analysis were used to assess gene expression levels in a three-dimensional reconstructed corneal epithelial model composed of normal human corneal epithelial cells exposed to water-filtered broad-spectrum NIR irradiation with a contact cooling (20°C). The water-filter allowed 1,000-1,800 nm wavelengths and excluded 1,400-1,500 nm wavelengths. A DNA microarray with >62,000 different probes showed 25 and 150 genes that were up- or downregulated by at least fourfold and twofold, respectively, after NIR irradiation. In particular, epidermal growth factor receptor (EGFR) was upregulated by 19.4-fold relative to control cells. Quantitative real-time polymerase chain reaction analysis revealed that two variants of EGFR in human corneal epithelial tissue were also significantly upregulated after five rounds of 10 J/cm(2) irradiation (P<0.05). We found that NIR irradiation induced the upregulated expression of EGFR in human corneal cells. Since over half of the solar energy reaching the Earth is in the NIR region, which cannot be adequately blocked by eyewear and thus can induce eye damage with intensive or long-term exposure, protection from both UV and NIR radiation may prevent changes in gene expression and in turn eye damage.

Clinical application of chromosomal microarray analysis for the prenatal diagnosis of chromosomal abnormalities and copy number variations in fetuses with congenital heart disease.

PubMed

Xia, Yu; Yang, Yongchao; Huang, Shufang; Wu, Yueheng; Li, Ping; Zhuang, Jian

2018-03-24

This study aimed to determine chromosomal abnormalities and copy number variations (CNVs) in fetuses with congenital heart disease (CHD) by chromosomal microarray analysis (CMA). One hundred and ten cases with CHD detected by prenatal echocardiography were enrolled in the study; 27 cases were simple CHDs, and 83 were complex CHDs. Chromosomal microarray analysis was performed on the Affymetrix CytoScan HD platform. All annotated CNVs were validated by quantitative PCR. Chromosomal microarray analysis identified 6 cases with chromosomal abnormalities, including 2 cases with trisomy 21, 2 cases with trisomy 18, 1 case with trisomy 13, and 1 unusual case of mosaic trisomy 21. Pathogenic CNVs were detected in 15.5% (17/110) of the fetuses with CHDs, including 13 cases with CHD-associated CNVs. We further identified 10 genes as likely novel CHD candidate genes through gene functional enrichment analysis. We also found that pathogenic CMA results impacted the rate of pregnancy termination. This study shows that CMA is particularly effective for identifying chromosomal abnormalities and CNVs in fetuses with CHDs as well as having an effect on obstetrical outcomes. The elucidation of the genetic basis of CHDs will continue to expand our understanding of the etiology of CHDs. © 2018 John Wiley & Sons, Ltd.

An evaluation of tyramide signal amplification and archived fixed and frozen tissue in microarray gene expression analysis

PubMed Central

Karsten, Stanislav L.; Van Deerlin, Vivianna M. D.; Sabatti, Chiara; Gill, Lisa H.; Geschwind, Daniel H.

2002-01-01

Archival formalin-fixed, paraffin-embedded and ethanol-fixed tissues represent a potentially invaluable resource for gene expression analysis, as they are the most widely available material for studies of human disease. Little data are available evaluating whether RNA obtained from fixed (archival) tissues could produce reliable and reproducible microarray expression data. Here we compare the use of RNA isolated from human archival tissues fixed in ethanol and formalin to frozen tissue in cDNA microarray experiments. Since an additional factor that can limit the utility of archival tissue is the often small quantities available, we also evaluate the use of the tyramide signal amplification method (TSA), which allows the use of small amounts of RNA. Detailed analysis indicates that TSA provides a consistent and reproducible signal amplification method for cDNA microarray analysis, across both arrays and the genes tested. Analysis of this method also highlights the importance of performing non-linear channel normalization and dye switching. Furthermore, archived, fixed specimens can perform well, but not surprisingly, produce more variable results than frozen tissues. Consistent results are more easily obtainable using ethanol-fixed tissues, whereas formalin-fixed tissue does not typically provide a useful substrate for cDNA synthesis and labeling. PMID:11788730

MIGS-GPU: Microarray Image Gridding and Segmentation on the GPU.

PubMed

Katsigiannis, Stamos; Zacharia, Eleni; Maroulis, Dimitris

2017-05-01

Complementary DNA (cDNA) microarray is a powerful tool for simultaneously studying the expression level of thousands of genes. Nevertheless, the analysis of microarray images remains an arduous and challenging task due to the poor quality of the images that often suffer from noise, artifacts, and uneven background. In this study, the MIGS-GPU [Microarray Image Gridding and Segmentation on Graphics Processing Unit (GPU)] software for gridding and segmenting microarray images is presented. MIGS-GPU's computations are performed on the GPU by means of the compute unified device architecture (CUDA) in order to achieve fast performance and increase the utilization of available system resources. Evaluation on both real and synthetic cDNA microarray images showed that MIGS-GPU provides better performance than state-of-the-art alternatives, while the proposed GPU implementation achieves significantly lower computational times compared to the respective CPU approaches. Consequently, MIGS-GPU can be an advantageous and useful tool for biomedical laboratories, offering a user-friendly interface that requires minimum input in order to run.

The MicroArray Quality Control (MAQC) project shows inter- and intraplatform reproducibility of gene expression measurements

PubMed Central

2012-01-01

Over the last decade, the introduction of microarray technology has had a profound impact on gene expression research. The publication of studies with dissimilar or altogether contradictory results, obtained using different microarray platforms to analyze identical RNA samples, has raised concerns about the reliability of this technology. The MicroArray Quality Control (MAQC) project was initiated to address these concerns, as well as other performance and data analysis issues. Expression data on four titration pools from two distinct reference RNA samples were generated at multiple test sites using a variety of microarray-based and alternative technology platforms. Here we describe the experimental design and probe mapping efforts behind the MAQC project. We show intraplatform consistency across test sites as well as a high level of interplatform concordance in terms of genes identified as differentially expressed. This study provides a resource that represents an important first step toward establishing a framework for the use of microarrays in clinical and regulatory settings. PMID:16964229

Women's experiences receiving abnormal prenatal chromosomal microarray testing results.

PubMed

Bernhardt, Barbara A; Soucier, Danielle; Hanson, Karen; Savage, Melissa S; Jackson, Laird; Wapner, Ronald J

2013-02-01

Genomic microarrays can detect copy-number variants not detectable by conventional cytogenetics. This technology is diffusing rapidly into prenatal settings even though the clinical implications of many copy-number variants are currently unknown. We conducted a qualitative pilot study to explore the experiences of women receiving abnormal results from prenatal microarray testing performed in a research setting. Participants were a subset of women participating in a multicenter prospective study "Prenatal Cytogenetic Diagnosis by Array-based Copy Number Analysis." Telephone interviews were conducted with 23 women receiving abnormal prenatal microarray results. We found that five key elements dominated the experiences of women who had received abnormal prenatal microarray results: an offer too good to pass up, blindsided by the results, uncertainty and unquantifiable risks, need for support, and toxic knowledge. As prenatal microarray testing is increasingly used, uncertain findings will be common, resulting in greater need for careful pre- and posttest counseling, and more education of and resources for providers so they can adequately support the women who are undergoing testing.

Fuzzy support vector machine: an efficient rule-based classification technique for microarrays.

PubMed

Hajiloo, Mohsen; Rabiee, Hamid R; Anooshahpour, Mahdi

2013-01-01

The abundance of gene expression microarray data has led to the development of machine learning algorithms applicable for tackling disease diagnosis, disease prognosis, and treatment selection problems. However, these algorithms often produce classifiers with weaknesses in terms of accuracy, robustness, and interpretability. This paper introduces fuzzy support vector machine which is a learning algorithm based on combination of fuzzy classifiers and kernel machines for microarray classification. Experimental results on public leukemia, prostate, and colon cancer datasets show that fuzzy support vector machine applied in combination with filter or wrapper feature selection methods develops a robust model with higher accuracy than the conventional microarray classification models such as support vector machine, artificial neural network, decision trees, k nearest neighbors, and diagonal linear discriminant analysis. Furthermore, the interpretable rule-base inferred from fuzzy support vector machine helps extracting biological knowledge from microarray data. Fuzzy support vector machine as a new classification model with high generalization power, robustness, and good interpretability seems to be a promising tool for gene expression microarray classification.

Microarray Meta-Analysis Identifies Acute Lung Injury Biomarkers in Donor Lungs That Predict Development of Primary Graft Failure in Recipients

PubMed Central

Haitsma, Jack J.; Furmli, Suleiman; Masoom, Hussain; Liu, Mingyao; Imai, Yumiko; Slutsky, Arthur S.; Beyene, Joseph; Greenwood, Celia M. T.; dos Santos, Claudia

2012-01-01

Objectives To perform a meta-analysis of gene expression microarray data from animal studies of lung injury, and to identify an injury-specific gene expression signature capable of predicting the development of lung injury in humans. Methods We performed a microarray meta-analysis using 77 microarray chips across six platforms, two species and different animal lung injury models exposed to lung injury with or/and without mechanical ventilation. Individual gene chips were classified and grouped based on the strategy used to induce lung injury. Effect size (change in gene expression) was calculated between non-injurious and injurious conditions comparing two main strategies to pool chips: (1) one-hit and (2) two-hit lung injury models. A random effects model was used to integrate individual effect sizes calculated from each experiment. Classification models were built using the gene expression signatures generated by the meta-analysis to predict the development of lung injury in human lung transplant recipients. Results Two injury-specific lists of differentially expressed genes generated from our meta-analysis of lung injury models were validated using external data sets and prospective data from animal models of ventilator-induced lung injury (VILI). Pathway analysis of gene sets revealed that both new and previously implicated VILI-related pathways are enriched with differentially regulated genes. Classification model based on gene expression signatures identified in animal models of lung injury predicted development of primary graft failure (PGF) in lung transplant recipients with larger than 80% accuracy based upon injury profiles from transplant donors. We also found that better classifier performance can be achieved by using meta-analysis to identify differentially-expressed genes than using single study-based differential analysis. Conclusion Taken together, our data suggests that microarray analysis of gene expression data allows for the detection of “injury" gene predictors that can classify lung injury samples and identify patients at risk for clinically relevant lung injury complications. PMID:23071521

Addressable droplet microarrays for single cell protein analysis.

PubMed

Salehi-Reyhani, Ali; Burgin, Edward; Ces, Oscar; Willison, Keith R; Klug, David R

2014-11-07

Addressable droplet microarrays are potentially attractive as a way to achieve miniaturised, reduced volume, high sensitivity analyses without the need to fabricate microfluidic devices or small volume chambers. We report a practical method for producing oil-encapsulated addressable droplet microarrays which can be used for such analyses. To demonstrate their utility, we undertake a series of single cell analyses, to determine the variation in copy number of p53 proteins in cells of a human cancer cell line.

Recurrent pregnancy loss evaluation combined with 24-chromosome microarray of miscarriage tissue provides a probable or definite cause of pregnancy loss in over 90% of patients.

PubMed

Popescu, F; Jaslow, C R; Kutteh, W H

2018-04-01

Will the addition of 24-chromosome microarray analysis on miscarriage tissue combined with the standard American Society for Reproductive Medicine (ASRM) evaluation for recurrent miscarriage explain most losses? Over 90% of patients with recurrent pregnancy loss (RPL) will have a probable or definitive cause identified when combining genetic testing on miscarriage tissue with the standard ASRM evaluation for recurrent miscarriage. RPL is estimated to occur in 2-4% of reproductive age couples. A probable cause can be identified in approximately 50% of patients after an ASRM recommended workup including an evaluation for parental chromosomal abnormalities, congenital and acquired uterine anomalies, endocrine imbalances and autoimmune factors including antiphospholipid syndrome. Single-center, prospective cohort study that included 100 patients seen in a private RPL clinic from 2014 to 2017. All 100 women had two or more pregnancy losses, a complete evaluation for RPL as defined by the ASRM, and miscarriage tissue evaluated by 24-chromosome microarray analysis after their second or subsequent miscarriage. Frequencies of abnormal results for evidence-based diagnostic tests considered definite or probable causes of RPL (karyotyping for parental chromosomal abnormalities, and 24-chromosome microarray evaluation for products of conception (POC); pelvic sonohysterography, hysterosalpingogram, or hysteroscopy for uterine anomalies; immunological tests for lupus anticoagulant and anticardiolipin antibodies; and blood tests for thyroid stimulating hormone (TSH), prolactin and hemoglobin A1c) were evaluated. We excluded cases where there was maternal cell contamination of the miscarriage tissue or if the ASRM evaluation was incomplete. A cost analysis for the evaluation of RPL was conducted to determine whether a proposed procedure of 24-chromome microarray evaluation followed by an ASRM RPL workup (for those RPL patients who had a normal 24-chromosome microarray evaluation) was more cost-efficient than conducting ASRM RPL workups on RPL patients followed by 24-chromosome microarray analysis (for those RPL patients who had a normal RPL workup). A definite or probable cause of pregnancy loss was identified in the vast majority (95/100; 95%) of RPL patients when a 24-chromosome pair microarray evaluation of POC testing is combined with the standard ASRM RPL workup evaluation at the time of the second or subsequent loss. The ASRM RPL workup identified an abnormality and a probable explanation for pregnancy loss in only 45/100 or 45% of all patients. A definite abnormality was identified in 67/100 patients or 67% when initial testing was performed using 24-chromosome microarray analyses on the miscarriage tissue. Only 5/100 (5%) patients, who had a euploid loss and a normal ASRM RPL workup, had a pregnancy loss without a probable or definitive cause identified. All other losses were explained by an abnormal 24-chromosome microarray analysis of the miscarriage tissue, an abnormal finding of the RPL workup, or a combination of both. Results from the cost analysis indicated that an initial approach of using a 24-chromosome microarray analysis on miscarriage tissue resulted in a 50% savings in cost to the health care system and to the patient. This is a single-center study on a small group of well-characterized women with RPL. There was an incomplete follow-up on subsequent pregnancy outcomes after evaluation, however this should not affect our principal results. The maternal age of patients varied from 26 to 45 years old. More aneuploid pregnancy losses would be expected in older women, particularly over the age of 35 years old. Evaluation of POC using 24-chromosome microarray analysis adds significantly to the ASRM recommended evaluation of RPL. Genetic evaluation on miscarriage tissue obtained at the time of the second and subsequent pregnancy losses should be offered to all couples with two or more consecutive pregnancy losses. The combination of a genetic evaluation on miscarriage tissue with an evidence-based evaluation for RPL will identify a probable or definitive cause in over 90% of miscarriages. No funding was received for this study and there are no conflicts of interest to declare. Not applicable.

A Platform for Combined DNA and Protein Microarrays Based on Total Internal Reflection Fluorescence

PubMed Central

Asanov, Alexander; Zepeda, Angélica; Vaca, Luis

2012-01-01

We have developed a novel microarray technology based on total internal reflection fluorescence (TIRF) in combination with DNA and protein bioassays immobilized at the TIRF surface. Unlike conventional microarrays that exhibit reduced signal-to-background ratio, require several stages of incubation, rinsing and stringency control, and measure only end-point results, our TIRF microarray technology provides several orders of magnitude better signal-to-background ratio, performs analysis rapidly in one step, and measures the entire course of association and dissociation kinetics between target DNA and protein molecules and the bioassays. In many practical cases detection of only DNA or protein markers alone does not provide the necessary accuracy for diagnosing a disease or detecting a pathogen. Here we describe TIRF microarrays that detect DNA and protein markers simultaneously, which reduces the probabilities of false responses. Supersensitive and multiplexed TIRF DNA and protein microarray technology may provide a platform for accurate diagnosis or enhanced research studies. Our TIRF microarray system can be mounted on upright or inverted microscopes or interfaced directly with CCD cameras equipped with a single objective, facilitating the development of portable devices. As proof-of-concept we applied TIRF microarrays for detecting molecular markers from Bacillus anthracis, the pathogen responsible for anthrax. PMID:22438738

Validation of MIMGO: a method to identify differentially expressed GO terms in a microarray dataset

PubMed Central

2012-01-01

Background We previously proposed an algorithm for the identification of GO terms that commonly annotate genes whose expression is upregulated or downregulated in some microarray data compared with in other microarray data. We call these “differentially expressed GO terms” and have named the algorithm “matrix-assisted identification method of differentially expressed GO terms” (MIMGO). MIMGO can also identify microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. However, MIMGO has not yet been validated on a real microarray dataset using all available GO terms. Findings We combined Gene Set Enrichment Analysis (GSEA) with MIMGO to identify differentially expressed GO terms in a yeast cell cycle microarray dataset. GSEA followed by MIMGO (GSEA + MIMGO) correctly identified (p < 0.05) microarray data in which genes annotated to differentially expressed GO terms are upregulated. We found that GSEA + MIMGO was slightly less effective than, or comparable to, GSEA (Pearson), a method that uses Pearson’s correlation as a metric, at detecting true differentially expressed GO terms. However, unlike other methods including GSEA (Pearson), GSEA + MIMGO can comprehensively identify the microarray data in which genes annotated with a differentially expressed GO term are upregulated or downregulated. Conclusions MIMGO is a reliable method to identify differentially expressed GO terms comprehensively. PMID:23232071

The use of open source bioinformatics tools to dissect transcriptomic data.

PubMed

Nitsche, Benjamin M; Ram, Arthur F J; Meyer, Vera

2012-01-01

Microarrays are a valuable technology to study fungal physiology on a transcriptomic level. Various microarray platforms are available comprising both single and two channel arrays. Despite different technologies, preprocessing of microarray data generally includes quality control, background correction, normalization, and summarization of probe level data. Subsequently, depending on the experimental design, diverse statistical analysis can be performed, including the identification of differentially expressed genes and the construction of gene coexpression networks.We describe how Bioconductor, a collection of open source and open development packages for the statistical programming language R, can be used for dissecting microarray data. We provide fundamental details that facilitate the process of getting started with R and Bioconductor. Using two publicly available microarray datasets from Aspergillus niger, we give detailed protocols on how to identify differentially expressed genes and how to construct gene coexpression networks.

Short-term exposure of Arabidopsis cell culures to hyper-G: Short-term changes in transcription regulation expression

NASA Astrophysics Data System (ADS)

Babbick, Maren; Hampp, Rudiger

2005-08-01

Callus cultures of Arabidopsis thaliana (cv. Columbia) were used to screen for early changes in gene expression in response to altered gravitational fields. In a recent microarray study we found hyper- g dependent changes in gene expression which indicated the involvement of WRKY genes [Martzivanou M. and Hampp R., Physiol. Plant., 118, 221-231,2003]. WRKY genes code for a family of plant-specific regulators of gene expression. In this study we report on the exposure of Arabidopsis callus cultures to 8g for up to 30 min. Quantitative analysis by real time RT-PCR of the amount of transcripts of WRKYs 3, 6, 22, 46, 65 and 70 showed individual changes in expression. As far as their function is known, these WRKY proteins are mainly involved in stress responses. As most alterations in transcript amount occurred within 10 min of treatment, such genes can be used for the investigation of microgravity-related effects on gene expression under sounding rocket conditions (TEXUS, MAXUS).

Integrated Microfluidic Devices for Automated Microarray-Based Gene Expression and Genotyping Analysis

NASA Astrophysics Data System (ADS)

Liu, Robin H.; Lodes, Mike; Fuji, H. Sho; Danley, David; McShea, Andrew

Microarray assays typically involve multistage sample processing and fluidic handling, which are generally labor-intensive and time-consuming. Automation of these processes would improve robustness, reduce run-to-run and operator-to-operator variation, and reduce costs. In this chapter, a fully integrated and self-contained microfluidic biochip device that has been developed to automate the fluidic handling steps for microarray-based gene expression or genotyping analysis is presented. The device consists of a semiconductor-based CustomArray® chip with 12,000 features and a microfluidic cartridge. The CustomArray was manufactured using a semiconductor-based in situ synthesis technology. The micro-fluidic cartridge consists of microfluidic pumps, mixers, valves, fluid channels, and reagent storage chambers. Microarray hybridization and subsequent fluidic handling and reactions (including a number of washing and labeling steps) were performed in this fully automated and miniature device before fluorescent image scanning of the microarray chip. Electrochemical micropumps were integrated in the cartridge to provide pumping of liquid solutions. A micromixing technique based on gas bubbling generated by electrochemical micropumps was developed. Low-cost check valves were implemented in the cartridge to prevent cross-talk of the stored reagents. Gene expression study of the human leukemia cell line (K562) and genotyping detection and sequencing of influenza A subtypes have been demonstrated using this integrated biochip platform. For gene expression assays, the microfluidic CustomArray device detected sample RNAs with a concentration as low as 0.375 pM. Detection was quantitative over more than three orders of magnitude. Experiment also showed that chip-to-chip variability was low indicating that the integrated microfluidic devices eliminate manual fluidic handling steps that can be a significant source of variability in genomic analysis. The genotyping results showed that the device identified influenza A hemagglutinin and neuraminidase subtypes and sequenced portions of both genes, demonstrating the potential of integrated microfluidic and microarray technology for multiple virus detection. The device provides a cost-effective solution to eliminate labor-intensive and time-consuming fluidic handling steps and allows microarray-based DNA analysis in a rapid and automated fashion.

CLUSFAVOR 5.0: hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles

PubMed Central

Peterson, Leif E

2002-01-01

CLUSFAVOR (CLUSter and Factor Analysis with Varimax Orthogonal Rotation) 5.0 is a Windows-based computer program for hierarchical cluster and principal-component analysis of microarray-based transcriptional profiles. CLUSFAVOR 5.0 standardizes input data; sorts data according to gene-specific coefficient of variation, standard deviation, average and total expression, and Shannon entropy; performs hierarchical cluster analysis using nearest-neighbor, unweighted pair-group method using arithmetic averages (UPGMA), or furthest-neighbor joining methods, and Euclidean, correlation, or jack-knife distances; and performs principal-component analysis. PMID:12184816

Parallel characterization of anaerobic toluene- and ethylbenzene-degrading microbial consortia by PCR-denaturing gradient gel electrophoresis, RNA-DNA membrane hybridization, and DNA microarray technology

NASA Technical Reports Server (NTRS)

Koizumi, Yoshikazu; Kelly, John J.; Nakagawa, Tatsunori; Urakawa, Hidetoshi; El-Fantroussi, Said; Al-Muzaini, Saleh; Fukui, Manabu; Urushigawa, Yoshikuni; Stahl, David A.

2002-01-01

A mesophilic toluene-degrading consortium (TDC) and an ethylbenzene-degrading consortium (EDC) were established under sulfate-reducing conditions. These consortia were first characterized by denaturing gradient gel electrophoresis (DGGE) fingerprinting of PCR-amplified 16S rRNA gene fragments, followed by sequencing. The sequences of the major bands (T-1 and E-2) belonging to TDC and EDC, respectively, were affiliated with the family Desulfobacteriaceae. Another major band from EDC (E-1) was related to an uncultured non-sulfate-reducing soil bacterium. Oligonucleotide probes specific for the 16S rRNAs of target organisms corresponding to T-1, E-1, and E-2 were designed, and hybridization conditions were optimized for two analytical formats, membrane and DNA microarray hybridization. Both formats were used to characterize the TDC and EDC, and the results of both were consistent with DGGE analysis. In order to assess the utility of the microarray format for analysis of environmental samples, oil-contaminated sediments from the coast of Kuwait were analyzed. The DNA microarray successfully detected bacterial nucleic acids from these samples, but probes targeting specific groups of sulfate-reducing bacteria did not give positive signals. The results of this study demonstrate the limitations and the potential utility of DNA microarrays for microbial community analysis.

Parallel Characterization of Anaerobic Toluene- and Ethylbenzene-Degrading Microbial Consortia by PCR-Denaturing Gradient Gel Electrophoresis, RNA-DNA Membrane Hybridization, and DNA Microarray Technology

PubMed Central

Koizumi, Yoshikazu; Kelly, John J.; Nakagawa, Tatsunori; Urakawa, Hidetoshi; El-Fantroussi, Saïd; Al-Muzaini, Saleh; Fukui, Manabu; Urushigawa, Yoshikuni; Stahl, David A.

2002-01-01

A mesophilic toluene-degrading consortium (TDC) and an ethylbenzene-degrading consortium (EDC) were established under sulfate-reducing conditions. These consortia were first characterized by denaturing gradient gel electrophoresis (DGGE) fingerprinting of PCR-amplified 16S rRNA gene fragments, followed by sequencing. The sequences of the major bands (T-1 and E-2) belonging to TDC and EDC, respectively, were affiliated with the family Desulfobacteriaceae. Another major band from EDC (E-1) was related to an uncultured non-sulfate-reducing soil bacterium. Oligonucleotide probes specific for the 16S rRNAs of target organisms corresponding to T-1, E-1, and E-2 were designed, and hybridization conditions were optimized for two analytical formats, membrane and DNA microarray hybridization. Both formats were used to characterize the TDC and EDC, and the results of both were consistent with DGGE analysis. In order to assess the utility of the microarray format for analysis of environmental samples, oil-contaminated sediments from the coast of Kuwait were analyzed. The DNA microarray successfully detected bacterial nucleic acids from these samples, but probes targeting specific groups of sulfate-reducing bacteria did not give positive signals. The results of this study demonstrate the limitations and the potential utility of DNA microarrays for microbial community analysis. PMID:12088997

Ontology-based, Tissue MicroArray oriented, image centered tissue bank

PubMed Central

Viti, Federica; Merelli, Ivan; Caprera, Andrea; Lazzari, Barbara; Stella, Alessandra; Milanesi, Luciano

2008-01-01

Background Tissue MicroArray technique is becoming increasingly important in pathology for the validation of experimental data from transcriptomic analysis. This approach produces many images which need to be properly managed, if possible with an infrastructure able to support tissue sharing between institutes. Moreover, the available frameworks oriented to Tissue MicroArray provide good storage for clinical patient, sample treatment and block construction information, but their utility is limited by the lack of data integration with biomolecular information. Results In this work we propose a Tissue MicroArray web oriented system to support researchers in managing bio-samples and, through the use of ontologies, enables tissue sharing aimed at the design of Tissue MicroArray experiments and results evaluation. Indeed, our system provides ontological description both for pre-analysis tissue images and for post-process analysis image results, which is crucial for information exchange. Moreover, working on well-defined terms it is then possible to query web resources for literature articles to integrate both pathology and bioinformatics data. Conclusions Using this system, users associate an ontology-based description to each image uploaded into the database and also integrate results with the ontological description of biosequences identified in every tissue. Moreover, it is possible to integrate the ontological description provided by the user with a full compliant gene ontology definition, enabling statistical studies about correlation between the analyzed pathology and the most commonly related biological processes. PMID:18460177

HIF-1 and SKN-1 coordinate the transcriptional response to hydrogen sulfide in Caenorhabditis elegans.

PubMed

Miller, Dana L; Budde, Mark W; Roth, Mark B

2011-01-01

Hydrogen sulfide (H₂S) has dramatic physiological effects on animals that are associated with improved survival. C. elegans grown in H₂S are long-lived and thermotolerant. To identify mechanisms by which adaptation to H₂S effects physiological functions, we have measured transcriptional responses to H₂S exposure. Using microarray analysis we observe rapid changes in the abundance of specific mRNAs. The number and magnitude of transcriptional changes increased with the duration of H₂S exposure. Functional annotation suggests that genes associated with protein homeostasis are upregulated upon prolonged exposure to H₂S. Previous work has shown that the hypoxia-inducible transcription factor, HIF-1, is required for survival in H₂S. In fact, we show that hif-1 is required for most, if not all, early transcriptional changes in H₂S. Moreover, our data demonstrate that SKN-1, the C. elegans homologue of NRF2, also contributes to H₂S-dependent changes in transcription. We show that these results are functionally important, as skn-1 is essential to survive exposure to H₂S. Our results suggest a model in which HIF-1 and SKN-1 coordinate a broad transcriptional response to H₂S that culminates in a global reorganization of protein homeostasis networks.

Reverse transcription loop-mediated isothermal amplification (RT-LAMP), a light for mammalian transcript analysis in low-input laboratories.

PubMed

Pandey, Mamta; Singh, Dheer; Onteru, Suneel K

2018-06-01

Transcript analysis is usually performed by costly, time-consuming, and expertise intensive methods, like real time-PCR, microarray, etc. However, they are not much feasible in low-input laboratories. Therefore, we implemented the reverse transcription loop-mediated isothermal amplification (RT-LAMP) as a means of mammalian transcript analysis. Particularly, RT-LAMP was developed for buffalo aromatase cytochrome P450 (CYP19) transcript, to study its expression in 3D-cultured buffalo granulosa cells, which were exposed to lipopolysaccharide (LPS). The CYP19-RT-LAMP assay rapidly identified the LPS-induced downregulation of the CYP19 gene within 30 min at 63°C in a water bath. The assay was visualized via unaided eye by observing the change in turbidity and fluorescence, which were decreased by increasing the LPS exposure time to granulosa cells. Overall, the developed CYP19-RT-LAMP assay provided a hope on the application of RT-LAMP for mammalian transcript analysis in low-input laboratories. © 2017 Wiley Periodicals, Inc.

Comparison of gene expression microarray data with count-based RNA measurements informs microarray interpretation.

PubMed

Richard, Arianne C; Lyons, Paul A; Peters, James E; Biasci, Daniele; Flint, Shaun M; Lee, James C; McKinney, Eoin F; Siegel, Richard M; Smith, Kenneth G C

2014-08-04

Although numerous investigations have compared gene expression microarray platforms, preprocessing methods and batch correction algorithms using constructed spike-in or dilution datasets, there remains a paucity of studies examining the properties of microarray data using diverse biological samples. Most microarray experiments seek to identify subtle differences between samples with variable background noise, a scenario poorly represented by constructed datasets. Thus, microarray users lack important information regarding the complexities introduced in real-world experimental settings. The recent development of a multiplexed, digital technology for nucleic acid measurement enables counting of individual RNA molecules without amplification and, for the first time, permits such a study. Using a set of human leukocyte subset RNA samples, we compared previously acquired microarray expression values with RNA molecule counts determined by the nCounter Analysis System (NanoString Technologies) in selected genes. We found that gene measurements across samples correlated well between the two platforms, particularly for high-variance genes, while genes deemed unexpressed by the nCounter generally had both low expression and low variance on the microarray. Confirming previous findings from spike-in and dilution datasets, this "gold-standard" comparison demonstrated signal compression that varied dramatically by expression level and, to a lesser extent, by dataset. Most importantly, examination of three different cell types revealed that noise levels differed across tissues. Microarray measurements generally correlate with relative RNA molecule counts within optimal ranges but suffer from expression-dependent accuracy bias and precision that varies across datasets. We urge microarray users to consider expression-level effects in signal interpretation and to evaluate noise properties in each dataset independently.

Genome Expression Pathway Analysis Tool – Analysis and visualization of microarray gene expression data under genomic, proteomic and metabolic context

PubMed Central

Weniger, Markus; Engelmann, Julia C; Schultz, Jörg

2007-01-01

Background Regulation of gene expression is relevant to many areas of biology and medicine, in the study of treatments, diseases, and developmental stages. Microarrays can be used to measure the expression level of thousands of mRNAs at the same time, allowing insight into or comparison of different cellular conditions. The data derived out of microarray experiments is highly dimensional and often noisy, and interpretation of the results can get intricate. Although programs for the statistical analysis of microarray data exist, most of them lack an integration of analysis results and biological interpretation. Results We have developed GEPAT, Genome Expression Pathway Analysis Tool, offering an analysis of gene expression data under genomic, proteomic and metabolic context. We provide an integration of statistical methods for data import and data analysis together with a biological interpretation for subsets of probes or single probes on the chip. GEPAT imports various types of oligonucleotide and cDNA array data formats. Different normalization methods can be applied to the data, afterwards data annotation is performed. After import, GEPAT offers various statistical data analysis methods, as hierarchical, k-means and PCA clustering, a linear model based t-test or chromosomal profile comparison. The results of the analysis can be interpreted by enrichment of biological terms, pathway analysis or interaction networks. Different biological databases are included, to give various information for each probe on the chip. GEPAT offers no linear work flow, but allows the usage of any subset of probes and samples as a start for a new data analysis. GEPAT relies on established data analysis packages, offers a modular approach for an easy extension, and can be run on a computer grid to allow a large number of users. It is freely available under the LGPL open source license for academic and commercial users at . Conclusion GEPAT is a modular, scalable and professional-grade software integrating analysis and interpretation of microarray gene expression data. An installation available for academic users can be found at . PMID:17543125

Development of DNA Microarrays for Metabolic Pathway and Bioprocess Monitoring

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gregory Stephanopoulos

Transcriptional profiling experiments utilizing DNA microarrays to study the intracellular accumulation of PHB in Synechocystis has proved difficult in large part because strains that show significant differences in PHB which would justify global analysis of gene expression have not been isolated.

Gene Expression Changes in the Olfactory Bulb of Mice Induced by Exposure to Diesel Exhaust Are Dependent on Animal Rearing Environment

PubMed Central

Yokota, Satoshi; Hori, Hiroshi; Umezawa, Masakazu; Kubota, Natsuko; Niki, Rikio; Yanagita, Shinya; Takeda, Ken

2013-01-01

There is an emerging concern that particulate air pollution increases the risk of cranial nerve disease onset. Small nanoparticles, mainly derived from diesel exhaust particles reach the olfactory bulb by their nasal depositions. It has been reported that diesel exhaust inhalation causes inflammation of the olfactory bulb and other brain regions. However, these toxicological studies have not evaluated animal rearing environment. We hypothesized that rearing environment can change mice phenotypes and thus might alter toxicological study results. In this study, we exposed mice to diesel exhaust inhalation at 90 µg/m3, 8 hours/day, for 28 consecutive days after rearing in a standard cage or environmental enrichment conditions. Microarray analysis found that expression levels of 112 genes were changed by diesel exhaust inhalation. Functional analysis using Gene Ontology revealed that the dysregulated genes were involved in inflammation and immune response. This result was supported by pathway analysis. Quantitative RT-PCR analysis confirmed 10 genes. Interestingly, background gene expression of the olfactory bulb of mice reared in a standard cage environment was changed by diesel exhaust inhalation, whereas there was no significant effect of diesel exhaust exposure on gene expression levels of mice reared with environmental enrichment. The results indicate for the first time that the effect of diesel exhaust exposure on gene expression of the olfactory bulb was influenced by rearing environment. Rearing environment, such as environmental enrichment, may be an important contributive factor to causation in evaluating still undefined toxic environmental substances such as diesel exhaust. PMID:23940539

Microbiome Analysis of Stool Samples from African Americans with Colon Polyps

PubMed Central

Brim, Hassan; Yooseph, Shibu; Zoetendal, Erwin G.; Lee, Edward; Torralbo, Manolito; Laiyemo, Adeyinka O.; Shokrani, Babak; Nelson, Karen; Ashktorab, Hassan

2013-01-01

Background Colonic polyps are common tumors occurring in ~50% of Western populations with ~10% risk of malignant progression. Dietary agents have been considered the primary environmental exposure to promote colorectal cancer (CRC) development. However, the colonic mucosa is permanently in contact with the microbiota and its metabolic products including toxins that also have the potential to trigger oncogenic transformation. Aim To analyze fecal DNA for microbiota composition and functional potential in African Americans with pre-neoplastic lesions. Materials & Methods We analyzed the bacterial composition of stool samples from 6 healthy individuals and 6 patients with colon polyps using 16S ribosomal RNA-based phylogenetic microarray; the Human intestinal Tract Chip (HITChip) and 16S rRNA gene barcoded 454 pyrosequencing. The functional potential was determined by sequence-based metagenomics using 454 pyrosequencing. Results Fecal microbiota profiling of samples from the healthy and polyp patients using both a phylogenetic microarraying (HITChip) and barcoded 454 pyrosequencing generated similar results. A distinction between both sets of samples was only obtained when the analysis was performed at the sub-genus level. Most of the species leading to the dissociation were from the Bacteroides group. The metagenomic analysis did not reveal major differences in bacterial gene prevalence/abundances between the two groups even when the analysis and comparisons were restricted to available Bacteroides genomes. Conclusion This study reveals that at the pre-neoplastic stages, there is a trend showing microbiota changes between healthy and colon polyp patients at the sub-genus level. These differences were not reflected at the genome/functions levels. Bacteria and associated functions within the Bacteroides group need to be further analyzed and dissected to pinpoint potential actors in the early colon oncogenic transformation in a large sample size. PMID:24376500

Dissection of the cis-2-decenoic acid signaling network in Pseudomonas aeruginosa using microarray technique

PubMed Central

Rahmani-Badi, Azadeh; Sepehr, Shayesteh; Fallahi, Hossein; Heidari-Keshel, Saeed

2015-01-01

Many bacterial pathogens use quorum-sensing (QS) signaling to regulate the expression of factors contributing to virulence and persistence. Bacteria produce signals of different chemical classes. The signal molecule, known as diffusible signal factor (DSF), is a cis-unsaturated fatty acid that was first described in the plant pathogen Xanthomonas campestris. Previous works have shown that human pathogen, Pseudomonas aeruginosa, also synthesizes a structurally related molecule, characterized as cis-2-decenoic acid (C10: Δ2, CDA) that induces biofilm dispersal by multiple types of bacteria. Furthermore, CDA has been shown to be involved in inter-kingdom signaling that modulates fungal behavior. Therefore, an understanding of its signaling mechanism could suggest strategies for interference, with consequences for disease control. To identify the components of CDA signaling pathway in this pathogen, a comparative transcritpome analysis was conducted, in the presence and absence of CDA. A protein-protein interaction (PPI) network for differentially expressed (DE) genes with known function was then constructed by STRING and Cytoscape. In addition, the effects of CDA in combination with antimicrobial agents on the biofilm surface area and bacteria viability were evaluated using fluorescence microscopy and digital image analysis. Microarray analysis identified 666 differentially expressed genes in the presence of CDA and gene ontology (GO) analysis revealed that in P. aeruginosa, CDA mediates dispersion of biofilms through signaling pathways, including enhanced motility, metabolic activity, virulence as well as persistence at different temperatures. PPI data suggested that a cluster of five genes (PA4978, PA4979, PA4980, PA4982, PA4983) is involved in the CDA synthesis and perception. Combined treatments using both CDA and antimicrobial agents showed that following exposure of the biofilms to CDA, remaining cells on the surface were easily removed and killed by antimicrobials. PMID:25972860

Gene expression profiling in gill tissues of White spot syndrome virus infected black tiger shrimp Penaeus monodon by DNA microarray.

PubMed

Shekhar, M S; Gomathi, A; Gopikrishna, G; Ponniah, A G

2015-06-01

White spot syndrome virus (WSSV) continues to be the most devastating viral pathogen infecting penaeid shrimp the world over. The genome of WSSV has been deciphered and characterized from three geographical isolates and significant progress has been made in developing various molecular diagnostic methods to detect the virus. However, the information on host immune gene response to WSSV pathogenesis is limited. Microarray analysis was carried out as an approach to analyse the gene expression in black tiger shrimp Penaeus monodon in response to WSSV infection. Gill tissues collected from the WSSV infected shrimp at 6, 24, 48 h and moribund stage were analysed for differential gene expression. Shrimp cDNAs of 40,059 unique sequences were considered for designing the microarray chip. The Cy3-labeled cRNA derived from healthy and WSSV-infected shrimp was subjected to hybridization with all the DNA spots in the microarray which revealed 8,633 and 11,147 as up- and down-regulated genes respectively at different time intervals post infection. The altered expression of these numerous genes represented diverse functions such as immune response, osmoregulation, apoptosis, nucleic acid binding, energy and metabolism, signal transduction, stress response and molting. The changes in gene expression profiles observed by microarray analysis provides molecular insights and framework of genes which are up- and down-regulated at different time intervals during WSSV infection in shrimp. The microarray data was validated by Real Time analysis of four differentially expressed genes involved in apoptosis (translationally controlled tumor protein, inhibitor of apoptosis protein, ubiquitin conjugated enzyme E2 and caspase) for gene expression levels. The role of apoptosis related genes in WSSV infected shrimp is discussed herein.

Reuse of imputed data in microarray analysis increases imputation efficiency

PubMed Central

Kim, Ki-Yeol; Kim, Byoung-Jin; Yi, Gwan-Su

2004-01-01

Background The imputation of missing values is necessary for the efficient use of DNA microarray data, because many clustering algorithms and some statistical analysis require a complete data set. A few imputation methods for DNA microarray data have been introduced, but the efficiency of the methods was low and the validity of imputed values in these methods had not been fully checked. Results We developed a new cluster-based imputation method called sequential K-nearest neighbor (SKNN) method. This imputes the missing values sequentially from the gene having least missing values, and uses the imputed values for the later imputation. Although it uses the imputed values, the efficiency of this new method is greatly improved in its accuracy and computational complexity over the conventional KNN-based method and other methods based on maximum likelihood estimation. The performance of SKNN was in particular higher than other imputation methods for the data with high missing rates and large number of experiments. Application of Expectation Maximization (EM) to the SKNN method improved the accuracy, but increased computational time proportional to the number of iterations. The Multiple Imputation (MI) method, which is well known but not applied previously to microarray data, showed a similarly high accuracy as the SKNN method, with slightly higher dependency on the types of data sets. Conclusions Sequential reuse of imputed data in KNN-based imputation greatly increases the efficiency of imputation. The SKNN method should be practically useful to save the data of some microarray experiments which have high amounts of missing entries. The SKNN method generates reliable imputed values which can be used for further cluster-based analysis of microarray data. PMID:15504240

Detection of clonal evolution in hematopoietic malignancies by combining comparative genomic hybridization and single nucleotide polymorphism arrays.

PubMed

Hartmann, Luise; Stephenson, Christine F; Verkamp, Stephanie R; Johnson, Krystal R; Burnworth, Bettina; Hammock, Kelle; Brodersen, Lisa Eidenschink; de Baca, Monica E; Wells, Denise A; Loken, Michael R; Zehentner, Barbara K

2014-12-01

Array comparative genomic hybridization (aCGH) has become a powerful tool for analyzing hematopoietic neoplasms and identifying genome-wide copy number changes in a single assay. aCGH also has superior resolution compared with fluorescence in situ hybridization (FISH) or conventional cytogenetics. Integration of single nucleotide polymorphism (SNP) probes with microarray analysis allows additional identification of acquired uniparental disomy, a copy neutral aberration with known potential to contribute to tumor pathogenesis. However, a limitation of microarray analysis has been the inability to detect clonal heterogeneity in a sample. This study comprised 16 samples (acute myeloid leukemia, myelodysplastic syndrome, chronic lymphocytic leukemia, plasma cell neoplasm) with complex cytogenetic features and evidence of clonal evolution. We used an integrated manual peak reassignment approach combining analysis of aCGH and SNP microarray data for characterization of subclonal abnormalities. We compared array findings with results obtained from conventional cytogenetic and FISH studies. Clonal heterogeneity was detected in 13 of 16 samples by microarray on the basis of log2 values. Use of the manual peak reassignment analysis approach improved resolution of the sample's clonal composition and genetic heterogeneity in 10 of 13 (77%) patients. Moreover, in 3 patients, clonal disease progression was revealed by array analysis that was not evident by cytogenetic or FISH studies. Genetic abnormalities originating from separate clonal subpopulations can be identified and further characterized by combining aCGH and SNP hybridization results from 1 integrated microarray chip by use of the manual peak reassignment technique. Its clinical utility in comparison to conventional cytogenetic or FISH studies is demonstrated. © 2014 American Association for Clinical Chemistry.

Transcriptomic Analysis of Ciguatoxin-Induced Changes in Gene Expression in Primary Cultures of Mice Cortical Neurons

PubMed Central

Rubiolo, Juan Andrés; Boente-Juncal, Andrea; Hirama, Masahiro; Yamashita, Shuji; Camiña, Mercedes; Vieytes, Mercedes R.

2018-01-01

Ciguatoxins are polyether marine toxins that act as sodium channel activators. These toxins cause ciguatera, one of the most widespread nonbacterial forms of food poisoning, which presents several symptoms in humans including long-term neurological alterations. Earlier work has shown that both acute and chronic exposure of primary cortical neurons to synthetic ciguatoxin CTX3C have profound impacts on neuronal function. Thus, the present work aimed to identify relevant neuronal genes and metabolic pathways that could be altered by ciguatoxin exposure. To study the effect of ciguatoxins in primary neurons in culture, we performed a transcriptomic analysis using whole mouse genome microarrays, for primary cortical neurons exposed during 6, 24, or 72 h in culture to CTX3C. Here, we have shown that the effects of the toxin on gene expression differ with the exposure time. The results presented here have identified several relevant genes and pathways related to the effect of ciguatoxins on neurons and may assist in future research or even treatment of ciguatera. Moreover, we demonstrated that the effects of the toxin on gene expression were exclusively consequential of its action as a voltage-gated sodium channel activator, since all the effects of CTX3C were avoided by preincubation of the neurons with the sodium channel blocker tetrodotoxin. PMID:29748486

Oxidative stress and reduced responsiveness of challenged circulating leukocytes following pulmonary instillation of metal-rich particulate matter in rats

PubMed Central

2014-01-01

Welding fume is an exposure that consists of a mixture of metal-rich particulate matter with gases (ozone, carbon monoxide) and/or vapors (VOCs). Data suggests that welders are immune compromised. Given the inability of pulmonary leukocytes to properly respond to a secondary infection in animal models, the question arose whether the dysfunction persisted systemically. Our aim was to evaluate the circulating leukocyte population in terms of cellular activation, presence of oxidative stress, and functionality after a secondary challenge, following welding fume exposure. Rats were intratracheally instilled (ITI) with PBS or 2 mg of welding fume collected from a stainless steel weld. Rats were sacrificed 4 and 24 h post-exposure and whole blood was collected. Whole blood was used for cellular differential counts, RNA isolation with subsequent microarray and Ingenuity Pathway Analysis, and secondary stimulation with LPS utilizing TruCulture technology. In addition, mononuclear cells were isolated 24 h post-exposure to measure oxidative stress by flow cytometry and confocal microscopy. Welding fume exposure had rapid effects on the circulating leukocyte population as identified by relative mRNA expression changes. Instillation of welding fume reduced inflammatory protein production of circulating leukocytes when challenged with the secondary stimulus LPS. The effects were not related to transcription, but were observed in conjunction with oxidative stress. These findings support previous studies of an inadequate pulmonary immune response following a metal-rich exposure and extend those findings showing leukocyte dysfunction occurs systemically. PMID:25123171

Oxidative stress and reduced responsiveness of challenged circulating leukocytes following pulmonary instillation of metal-rich particulate matter in rats.

PubMed

Erdely, Aaron; Antonini, James M; Young, Shih-Houng; Kashon, Michael L; Gu, Ja K; Hulderman, Tracy; Salmen, Rebecca; Meighan, Terence; Roberts, Jenny R; Zeidler-Erdely, Patti C

2014-08-15

Welding fume is an exposure that consists of a mixture of metal-rich particulate matter with gases (ozone, carbon monoxide) and/or vapors (VOCs). Data suggests that welders are immune compromised. Given the inability of pulmonary leukocytes to properly respond to a secondary infection in animal models, the question arose whether the dysfunction persisted systemically. Our aim was to evaluate the circulating leukocyte population in terms of cellular activation, presence of oxidative stress, and functionality after a secondary challenge, following welding fume exposure. Rats were intratracheally instilled (ITI) with PBS or 2 mg of welding fume collected from a stainless steel weld. Rats were sacrificed 4 and 24 h post-exposure and whole blood was collected. Whole blood was used for cellular differential counts, RNA isolation with subsequent microarray and Ingenuity Pathway Analysis, and secondary stimulation with LPS utilizing TruCulture technology. In addition, mononuclear cells were isolated 24 h post-exposure to measure oxidative stress by flow cytometry and confocal microscopy. Welding fume exposure had rapid effects on the circulating leukocyte population as identified by relative mRNA expression changes. Instillation of welding fume reduced inflammatory protein production of circulating leukocytes when challenged with the secondary stimulus LPS. The effects were not related to transcription, but were observed in conjunction with oxidative stress. These findings support previous studies of an inadequate pulmonary immune response following a metal-rich exposure and extend those findings showing leukocyte dysfunction occurs systemically.

Analysis and modelling of septic shock microarray data using Singular Value Decomposition.

PubMed

Allanki, Srinivas; Dixit, Madhulika; Thangaraj, Paul; Sinha, Nandan Kumar

2017-06-01

Being a high throughput technique, enormous amounts of microarray data has been generated and there arises a need for more efficient techniques of analysis, in terms of speed and accuracy. Finding the differentially expressed genes based on just fold change and p-value might not extract all the vital biological signals that occur at a lower gene expression level. Besides this, numerous mathematical models have been generated to predict the clinical outcome from microarray data, while very few, if not none, aim at predicting the vital genes that are important in a disease progression. Such models help a basic researcher narrow down and concentrate on a promising set of genes which leads to the discovery of gene-based therapies. In this article, as a first objective, we have used the lesser known and used Singular Value Decomposition (SVD) technique to build a microarray data analysis tool that works with gene expression patterns and intrinsic structure of the data in an unsupervised manner. We have re-analysed a microarray data over the clinical course of Septic shock from Cazalis et al. (2014) and have shown that our proposed analysis provides additional information compared to the conventional method. As a second objective, we developed a novel mathematical model that predicts a set of vital genes in the disease progression that works by generating samples in the continuum between health and disease, using a simple normal-distribution-based random number generator. We also verify that most of the predicted genes are indeed related to septic shock. Copyright © 2017 Elsevier Inc. All rights reserved.

Biomarkers of the Hedgehog/Smoothened pathway in healthy volunteers

PubMed Central

Kadam, Sunil K; Patel, Bharvin K R; Jones, Emma; Nguyen, Tuan S; Verma, Lalit K; Landschulz, Katherine T; Stepaniants, Sergey; Li, Bin; Brandt, John T; Brail, Leslie H

2012-01-01

The Hedgehog (Hh) pathway is involved in oncogenic transformation and tumor maintenance. The primary objective of this study was to select surrogate tissue to measure messenger ribonucleic acid (mRNA) levels of Hh pathway genes for measurement of pharmacodynamic effect. Expression of Hh pathway specific genes was measured by quantitative real time polymerase chain reaction (qRT-PCR) and global gene expression using Affymetrix U133 microarrays. Correlations were made between the expression of specific genes determined by qRT-PCR and normalized microarray data. Gene ontology analysis using microarray data for a broader set of Hh pathway genes was performed to identify additional Hh pathway-related markers in the surrogate tissue. RNA extracted from blood, hair follicle, and skin obtained from healthy subjects was analyzed by qRT-PCR for 31 genes, whereas 8 samples were analyzed for a 7-gene subset. Twelve sample sets, each with ≤500 ng total RNA derived from hair, skin, and blood, were analyzed using Affymetrix U133 microarrays. Transcripts for several Hh pathway genes were undetectable in blood using qRT-PCR. Skin was the most desirable matrix, followed by hair follicle. Whether processed by robust multiarray average or microarray suite 5 (MAS5), expression patterns of individual samples showed co-clustered signals; both normalization methods were equally effective for unsupervised analysis. The MAS5- normalized probe sets appeared better suited for supervised analysis. This work provides the basis for selection of a surrogate tissue and an expression analysis-based approach to evaluate pathway-related genes as markers of pharmacodynamic effect with novel inhibitors of the Hh pathway. PMID:22611475

A novel approach for human whole transcriptome analysis based on absolute gene expression of microarray data

PubMed Central

Bikel, Shirley; Jacobo-Albavera, Leonor; Sánchez-Muñoz, Fausto; Cornejo-Granados, Fernanda; Canizales-Quinteros, Samuel; Soberón, Xavier; Sotelo-Mundo, Rogerio R.; del Río-Navarro, Blanca E.; Mendoza-Vargas, Alfredo; Sánchez, Filiberto

2017-01-01

Background In spite of the emergence of RNA sequencing (RNA-seq), microarrays remain in widespread use for gene expression analysis in the clinic. There are over 767,000 RNA microarrays from human samples in public repositories, which are an invaluable resource for biomedical research and personalized medicine. The absolute gene expression analysis allows the transcriptome profiling of all expressed genes under a specific biological condition without the need of a reference sample. However, the background fluorescence represents a challenge to determine the absolute gene expression in microarrays. Given that the Y chromosome is absent in female subjects, we used it as a new approach for absolute gene expression analysis in which the fluorescence of the Y chromosome genes of female subjects was used as the background fluorescence for all the probes in the microarray. This fluorescence was used to establish an absolute gene expression threshold, allowing the differentiation between expressed and non-expressed genes in microarrays. Methods We extracted the RNA from 16 children leukocyte samples (nine males and seven females, ages 6–10 years). An Affymetrix Gene Chip Human Gene 1.0 ST Array was carried out for each sample and the fluorescence of 124 genes of the Y chromosome was used to calculate the absolute gene expression threshold. After that, several expressed and non-expressed genes according to our absolute gene expression threshold were compared against the expression obtained using real-time quantitative polymerase chain reaction (RT-qPCR). Results From the 124 genes of the Y chromosome, three genes (DDX3Y, TXLNG2P and EIF1AY) that displayed significant differences between sexes were used to calculate the absolute gene expression threshold. Using this threshold, we selected 13 expressed and non-expressed genes and confirmed their expression level by RT-qPCR. Then, we selected the top 5% most expressed genes and found that several KEGG pathways were significantly enriched. Interestingly, these pathways were related to the typical functions of leukocytes cells, such as antigen processing and presentation and natural killer cell mediated cytotoxicity. We also applied this method to obtain the absolute gene expression threshold in already published microarray data of liver cells, where the top 5% expressed genes showed an enrichment of typical KEGG pathways for liver cells. Our results suggest that the three selected genes of the Y chromosome can be used to calculate an absolute gene expression threshold, allowing a transcriptome profiling of microarray data without the need of an additional reference experiment. Discussion Our approach based on the establishment of a threshold for absolute gene expression analysis will allow a new way to analyze thousands of microarrays from public databases. This allows the study of different human diseases without the need of having additional samples for relative expression experiments. PMID:29230367

DigOut: viewing differential expression genes as outliers.

PubMed

Yu, Hui; Tu, Kang; Xie, Lu; Li, Yuan-Yuan

2010-12-01

With regards to well-replicated two-conditional microarray datasets, the selection of differentially expressed (DE) genes is a well-studied computational topic, but for multi-conditional microarray datasets with limited or no replication, the same task is not properly addressed by previous studies. This paper adopts multivariate outlier analysis to analyze replication-lacking multi-conditional microarray datasets, finding that it performs significantly better than the widely used limit fold change (LFC) model in a simulated comparative experiment. Compared with the LFC model, the multivariate outlier analysis also demonstrates improved stability against sample variations in a series of manipulated real expression datasets. The reanalysis of a real non-replicated multi-conditional expression dataset series leads to satisfactory results. In conclusion, a multivariate outlier analysis algorithm, like DigOut, is particularly useful for selecting DE genes from non-replicated multi-conditional gene expression dataset.

A comparative study of RNA-Seq and microarray data analysis on the two examples of rectal-cancer patients and Burkitt Lymphoma cells.

PubMed

Wolff, Alexander; Bayerlová, Michaela; Gaedcke, Jochen; Kube, Dieter; Beißbarth, Tim

2018-01-01

Pipeline comparisons for gene expression data are highly valuable for applied real data analyses, as they enable the selection of suitable analysis strategies for the dataset at hand. Such pipelines for RNA-Seq data should include mapping of reads, counting and differential gene expression analysis or preprocessing, normalization and differential gene expression in case of microarray analysis, in order to give a global insight into pipeline performances. Four commonly used RNA-Seq pipelines (STAR/HTSeq-Count/edgeR, STAR/RSEM/edgeR, Sailfish/edgeR, TopHat2/Cufflinks/CuffDiff)) were investigated on multiple levels (alignment and counting) and cross-compared with the microarray counterpart on the level of gene expression and gene ontology enrichment. For these comparisons we generated two matched microarray and RNA-Seq datasets: Burkitt Lymphoma cell line data and rectal cancer patient data. The overall mapping rate of STAR was 98.98% for the cell line dataset and 98.49% for the patient dataset. Tophat's overall mapping rate was 97.02% and 96.73%, respectively, while Sailfish had only an overall mapping rate of 84.81% and 54.44%. The correlation of gene expression in microarray and RNA-Seq data was moderately worse for the patient dataset (ρ = 0.67-0.69) than for the cell line dataset (ρ = 0.87-0.88). An exception were the correlation results of Cufflinks, which were substantially lower (ρ = 0.21-0.29 and 0.34-0.53). For both datasets we identified very low numbers of differentially expressed genes using the microarray platform. For RNA-Seq we checked the agreement of differentially expressed genes identified in the different pipelines and of GO-term enrichment results. In conclusion the combination of STAR aligner with HTSeq-Count followed by STAR aligner with RSEM and Sailfish generated differentially expressed genes best suited for the dataset at hand and in agreement with most of the other transcriptomics pipelines.

'Systems toxicology' approach identifies coordinated metabolic responses to copper in a terrestrial non-model invertebrate, the earthworm Lumbricus rubellus.

PubMed

Bundy, Jacob G; Sidhu, Jasmin K; Rana, Faisal; Spurgeon, David J; Svendsen, Claus; Wren, Jodie F; Stürzenbaum, Stephen R; Morgan, A John; Kille, Peter

2008-06-03

New methods are needed for research into non-model organisms, to monitor the effects of toxic disruption at both the molecular and functional organism level. We exposed earthworms (Lumbricus rubellus Hoffmeister) to sub-lethal levels of copper (10-480 mg/kg soil) for 70 days as a real-world situation, and monitored both molecular (cDNA transcript microarrays and nuclear magnetic resonance-based metabolic profiling: metabolomics) and ecological/functional endpoints (reproduction rate and weight change, which have direct relevance to population-level impacts). Both of the molecular endpoints, metabolomics and transcriptomics, were highly sensitive, with clear copper-induced differences even at levels below those that caused a reduction in reproductive parameters. The microarray and metabolomic data provided evidence that the copper exposure led to a disruption of energy metabolism: transcripts of enzymes from oxidative phosphorylation were significantly over-represented, and increases in transcripts of carbohydrate metabolising enzymes (maltase-glucoamylase, mannosidase) had corresponding decreases in small-molecule metabolites (glucose, mannose). Treating both enzymes and metabolites as functional cohorts led to clear inferences about changes in energetic metabolism (carbohydrate use and oxidative phosphorylation), which would not have been possible by taking a 'biomarker' approach to data analysis. Multiple post-genomic techniques can be combined to provide mechanistic information about the toxic effects of chemical contaminants, even for non-model organisms with few additional mechanistic toxicological data. With 70-day no-observed-effect and lowest-observed-effect concentrations (NOEC and LOEC) of 10 and 40 mg kg-1 for metabolomic and microarray profiles, copper is shown to interfere with energy metabolism in an important soil organism at an ecologically and functionally relevant level.

Microarray gene-expression study in fibroblast and lymphoblastoid cell lines from antipsychotic-naïve first-episode schizophrenia patients.

PubMed

Gassó, Patricia; Mas, Sergi; Rodríguez, Natalia; Boloc, Daniel; García-Cerro, Susana; Bernardo, Miquel; Lafuente, Amalia; Parellada, Eduard

2017-12-01

Schizophrenia (SZ) is a chronic psychiatric disorder whose onset of symptoms occurs in late adolescence and early adulthood. The etiology is complex and involves important gene-environment interactions. Microarray gene-expression studies on SZ have identified alterations in several biological processes. The heterogeneity in the results can be attributed to the use of different sample types and other important confounding factors including age, illness chronicity and antipsychotic exposure. The aim of the present microarray study was to analyze, for the first time to our knowledge, differences in gene expression profiles in 18 fibroblast (FCLs) and 14 lymphoblastoid cell lines (LCLs) from antipsychotic-naïve first-episode schizophrenia (FES) patients and healthy controls. We used an analytical approach based on protein-protein interaction network construction and functional annotation analysis to identify the biological processes that are altered in SZ. Significant differences in the expression of 32 genes were found when LCLs were assessed. The network and gene set enrichment approach revealed the involvement of similar biological processes in FCLs and LCLs, including apoptosis and related biological terms such as cell cycle, autophagy, cytoskeleton organization and response to stress and stimulus. Metabolism and other processes, including signal transduction, kinase activity and phosphorylation, were also identified. These results were replicated in two independent cohorts using the same analytical approach. This provides more evidence for altered apoptotic processes in antipsychotic-naïve FES patients and other important biological functions such as cytoskeleton organization and metabolism. The convergent results obtained in both peripheral cell models support their usefulness for transcriptome studies on SZ. Copyright © 2017 Elsevier Ltd. All rights reserved.

Differential transcriptomic responses of Biomphalaria glabrata (Gastropoda, Mollusca) to bacteria and metazoan parasites, Schistosoma mansoni and Echinostoma paraensei (Digenea, Platyhelminthes)

PubMed Central

Adema, Coen M; Hanington, Patrick C.; Lun, Cheng-Man; Rosenberg, George H.; Aragon, Anthony D; Stout, Barbara A; Richard, Mara L. Lennard; Gross, Paul S.; Loker, Eric S

2009-01-01

A 70-mer oligonucleotide-based microarray (1152 features) that emphasizes stress and immune responses factors was constructed to study transcriptomic responses of the snail Biomphalaria glabrata to different immune challenges. In addition to sequences with relevant putative ID and Gene Ontology (GO) annotation, the array features non-immune factors and unknown B. glabrata ESTs for functional gene discovery. The transcription profiles of B. glabrata (3 biological replicates, each a pool of 5 snails) were recorded at 12 hours post wounding, exposure to Gram negative or Gram positive bacteria (Escherichia coli and Micrococcus luteus, respectively), or infection with compatible trematode parasites (S. mansoni or E. paraensei, 20 miracidia/snail), relative to controls, using universal reference RNA. The data were subjected to Significance Analysis for Microarrays (SAM), with a false positive rate (FPR) ≤10%. Wounding yielded a modest differential expression profile (27 up/21 down) with affected features mostly dissimilar from other treatments. Partially overlapping, yet distinct expression profiles were recorded from snails challenged with E. coli (83 up/20 down) or M. luteus (120 up/42 down), mostly showing up-regulation of defense and stress-related features. Significantly altered expression of selected immune features indicates that B. glabrata detects and responds differently to compatible trematodes. Echinostoma paraensei infection was associated mostly with down regulation of many (immune-) transcripts (42 up/68 down), whereas S. mansoni exposure yielded a preponderance of up-regulated features (140 up/23 down), with only few known immune genes affected. These observations may reflect the divergent strategies developed by trematodes during their evolution as specialized pathogens of snails to negate host defense responses. Clearly, the immune defenses of B. glabrata distinguish and respond differently to various immune challenges. PMID:19962194

Dose-effect of ionizing radiation-induced PIG3 gene expression alteration in human lymphoblastoid AHH-1 cells and human peripheral blood lymphocytes.

PubMed

Liu, Qing-Jie; Zhang, De-Qin; Zhang, Qing-Zhao; Feng, Jiang-Bin; Lu, Xue; Wang, Xin-Ru; Li, Kun-Peng; Chen, De-Qing; Mu, Xiao-Feng; Li, Shuang; Gao, Ling

2015-01-01

To identify new ionizing radiation (IR)-sensitive genes and observe the dose-effect of gene expression alteration (GEA) induced by IR. Microarray was used to screen the differentially expressed genes in human lymphoblastoid cells (AHH-1) using three doses of (60)Co γ-rays (0.5-8 Gy at 1 Gy/min). Given that p53-inducible gene 3 (PIG3) was consistently upregulated, the GEA of PIG3 in AHH-1 cells and human peripheral blood lymphocytes (HPBL) induced by γ-rays (1 Gy/min) was measured at messenger RNA (mRNA) and protein levels. The GEA of PIG3 in AHH-1 cells exposed to neutron radiation (californium-252, 0.073 Gy/min) was also quantified. PIG3 was one of the seven differentially expressed genes found in the microarray analysis. The PIG3 mRNA and protein levels in AHH-1 cells were significantly increased from 1-10 Gy of γ-rays 8-72 h or 8-168 h after exposure, respectively. The enhancement was also observed in AHH-1 cells from 0.4-1.6 Gy of neutrons 48 h post-irradiation. The PIG3 mRNA levels (mRNA copy numbers) in HPBL were significantly increased from 1-8 Gy of γ-rays within 4-24 h post-irradiation, but the highest increase in signal-to-noise responsiveness is approximately two-fold, which was less than that of AHH-1 (approximately 20-fold). IR can upregulate the PIG3 gene expression in AHH-1 and HPBL in the early phase after exposure; however, the IR induced expression levels of PIG3 are greater in AHH-1 than HPBL.

Prediction of regulatory gene pairs using dynamic time warping and gene ontology.

PubMed

Yang, Andy C; Hsu, Hui-Huang; Lu, Ming-Da; Tseng, Vincent S; Shih, Timothy K

2014-01-01

Selecting informative genes is the most important task for data analysis on microarray gene expression data. In this work, we aim at identifying regulatory gene pairs from microarray gene expression data. However, microarray data often contain multiple missing expression values. Missing value imputation is thus needed before further processing for regulatory gene pairs becomes possible. We develop a novel approach to first impute missing values in microarray time series data by combining k-Nearest Neighbour (KNN), Dynamic Time Warping (DTW) and Gene Ontology (GO). After missing values are imputed, we then perform gene regulation prediction based on our proposed DTW-GO distance measurement of gene pairs. Experimental results show that our approach is more accurate when compared with existing missing value imputation methods on real microarray data sets. Furthermore, our approach can also discover more regulatory gene pairs that are known in the literature than other methods.

Temperature Gradient Effect on Gas Discrimination Power of a Metal-Oxide Thin-Film Sensor Microarray

PubMed Central

Sysoev, Victor V.; Kiselev, Ilya; Frietsch, Markus; Goschnick, Joachim

2004-01-01

The paper presents results concerning the effect of spatial inhomogeneous operating temperature on the gas discrimination power of a gas-sensor microarray, with the latter based on a thin SnO2 film employed in the KAMINA electronic nose. Three different temperature distributions over the substrate are discussed: a nearly homogeneous one and two temperature gradients, equal to approx. 3.3 °C/mm and 6.7 °C/mm, applied across the sensor elements (segments) of the array. The gas discrimination power of the microarray is judged by using the Mahalanobis distance in the LDA (Linear Discrimination Analysis) coordinate system between the data clusters obtained by the response of the microarray to four target vapors: ethanol, acetone, propanol and ammonia. It is shown that the application of a temperature gradient increases the gas discrimination power of the microarray by up to 35 %.

Chondrocyte channel transcriptomics

PubMed Central

Lewis, Rebecca; May, Hannah; Mobasheri, Ali; Barrett-Jolley, Richard

2013-01-01

To date, a range of ion channels have been identified in chondrocytes using a number of different techniques, predominantly electrophysiological and/or biomolecular; each of these has its advantages and disadvantages. Here we aim to compare and contrast the data available from biophysical and microarray experiments. This letter analyses recent transcriptomics datasets from chondrocytes, accessible from the European Bioinformatics Institute (EBI). We discuss whether such bioinformatic analysis of microarray datasets can potentially accelerate identification and discovery of ion channels in chondrocytes. The ion channels which appear most frequently across these microarray datasets are discussed, along with their possible functions. We discuss whether functional or protein data exist which support the microarray data. A microarray experiment comparing gene expression in osteoarthritis and healthy cartilage is also discussed and we verify the differential expression of 2 of these genes, namely the genes encoding large calcium-activated potassium (BK) and aquaporin channels. PMID:23995703

Histological and Transcriptomic Changes in Male Zebrafish Testes Due to Early Life Exposure to Low Level 2,3,7,8-Tetrachlorodibenzo-p-Dioxin.

PubMed

Baker, Bridget B; Yee, Jeremiah S; Meyer, Danielle N; Yang, Doris; Baker, Tracie R

2016-10-01

We have shown that zebrafish (Danio rerio) are an excellent model for evaluating the link between early life stage exposure to environmental chemicals and disease in adulthood and subsequent unexposed generations. Previously, we used this model to identify transgenerational effects of dioxin (2,3,7,8-tetrachlorodibenzo-p-dioxin [TCDD]) on skeletal development, sex ratio, and reproductive capacity. Transgenerational inheritance of TCDD toxicity, notably decreased reproductive capacity, appears to be mediated through the male germ line. Thus, we examine testicular tissue for structural and gene expression changes using histology, microarray, and quantitative reverse transcription polymerase chain reaction (qRT-PCR). Histological analysis revealed decreased spermatozoa with concurrent increase in spermatogonia, and decreased germinal epithelium thickness in TCDD-exposed males compared with controls. We also identified altered expression of genes associated with testis development, steroidogenesis, spermatogenesis, hormone metabolism, and xenobiotic response. Altered genes are in pathways involving lipid metabolism, molecular transport, small molecule biochemistry, cell morphology, and metabolism of vitamins and minerals. These data will inform future investigations to elucidate the mechanism of adult-onset and transgenerational infertility due to TCDD exposure in zebrafish.

Transcriptome Profiling of In-Vivo Produced Bovine Pre-implantation Embryos Using Two-color Microarray Platform.

PubMed

Salehi, Reza; Tsoi, Stephen C M; Colazo, Marcos G; Ambrose, Divakar J; Robert, Claude; Dyck, Michael K

2017-01-30

Early embryonic loss is a large contributor to infertility in cattle. Moreover, bovine becomes an interesting model to study human preimplantation embryo development due to their similar developmental process. Although genetic factors are known to affect early embryonic development, the discovery of such factors has been a serious challenge. Microarray technology allows quantitative measurement and gene expression profiling of transcript levels on a genome-wide basis. One of the main decisions that have to be made when planning a microarray experiment is whether to use a one- or two-color approach. Two-color design increases technical replication, minimizes variability, improves sensitivity and accuracy as well as allows having loop designs, defining the common reference samples. Although microarray is a powerful biological tool, there are potential pitfalls that can attenuate its power. Hence, in this technical paper we demonstrate an optimized protocol for RNA extraction, amplification, labeling, hybridization of the labeled amplified RNA to the array, array scanning and data analysis using the two-color analysis strategy.

Clustering gene expression data based on predicted differential effects of GV interaction.

PubMed

Pan, Hai-Yan; Zhu, Jun; Han, Dan-Fu

2005-02-01

Microarray has become a popular biotechnology in biological and medical research. However, systematic and stochastic variabilities in microarray data are expected and unavoidable, resulting in the problem that the raw measurements have inherent "noise" within microarray experiments. Currently, logarithmic ratios are usually analyzed by various clustering methods directly, which may introduce bias interpretation in identifying groups of genes or samples. In this paper, a statistical method based on mixed model approaches was proposed for microarray data cluster analysis. The underlying rationale of this method is to partition the observed total gene expression level into various variations caused by different factors using an ANOVA model, and to predict the differential effects of GV (gene by variety) interaction using the adjusted unbiased prediction (AUP) method. The predicted GV interaction effects can then be used as the inputs of cluster analysis. We illustrated the application of our method with a gene expression dataset and elucidated the utility of our approach using an external validation.

Cell cycle pathway dysregulation in human keratinocytes during chronic exposure to low arsenite.

PubMed

Al-Eryani, Laila; Waigel, Sabine; Jala, Venkatakrishna; Jenkins, Samantha F; States, J Christopher

2017-09-15

Arsenic is naturally prevalent in the earth's crust and widely distributed in air and water. Chronic low arsenic exposure is associated with several cancers in vivo, including skin cancer, and with transformation in vitro of cell lines including immortalized human keratinocytes (HaCaT). Arsenic also is associated with cell cycle dysregulation at different exposure levels in multiple cell lines. In this work, we analyzed gene expression in HaCaT cells to gain an understanding of gene expression changes contributing to transformation at an early time point. HaCaT cells were exposed to 0 or 100nM NaAsO 2 for 7weeks. Total RNA was purified and analyzed by microarray hybridization. Differential expression with fold change≥|1.5| and p-value≤0.05 was determined using Partek Genomic Suite™ and pathway and network analyses using MetaCore™ software (FDR≤0.05). Cell cycle analysis was performed using flow cytometry. 644 mRNAs were differentially expressed. Cell cycle/cell cycle regulation pathways predominated in the list of dysregulated pathways. Genes involved in replication origin licensing were enriched in the network. Cell cycle assay analysis showed an increase in G2/M compartment in arsenite-exposed cells. Arsenite exposure induced differential gene expression indicating dysregulation of cell cycle control, which was confirmed by cell cycle analysis. The results suggest that cell cycle dysregulation is an early event in transformation manifested in cells unable to transit G2/M efficiently. Further study at later time points will reveal additional changes in gene expression related to transformation processes. Copyright © 2017 Elsevier Inc. All rights reserved.

Global gene expression associated with hepatocarcinogenesis in adult male mice induced by in utero arsenic exposure.

PubMed

Liu, Jie; Xie, Yaxiong; Ducharme, Danica M K; Shen, Jun; Diwan, Bhalchandra A; Merrick, B Alex; Grissom, Sherry F; Tucker, Charles J; Paules, Richard S; Tennant, Raymond; Waalkes, Michael P

2006-03-01

Our previous work has shown that exposure to inorganic arsenic in utero produces hepatocellular carcinoma (HCC) in adult male mice. To explore further the molecular mechanisms of transplacental arsenic hepatocarcinogenesis, we conducted a second arsenic transplacental carcinogenesis study and used a genomewide microarray to profile arsenic-induced aberrant gene expression more extensively. Briefly, pregnant C3H mice were given drinking water containing 85 ppm arsenic as sodium arsenite or unaltered water from days 8 to 18 of gestation. The incidence of HCC in adult male offspring was increased 4-fold and tumor multiplicity 3-fold after transplacental arsenic exposure. Samples of normal liver and liver tumors were taken at autopsy for genomic analysis. Arsenic exposure in utero resulted in significant alterations (p < 0.001) in the expression of 2,010 genes in arsenic-exposed liver samples and in the expression of 2,540 genes in arsenic-induced HCC. Ingenuity Pathway Analysis revealed that significant alterations in gene expression occurred in a number of biological networks, and Myc plays a critical role in one of the primary networks. Real-time reverse transcriptase-polymerase chain reaction and Western blot analysis of selected genes/proteins showed > 90% concordance. Arsenic-altered gene expression included activation of oncogenes and HCC biomarkers, and increased expression of cell proliferation-related genes, stress proteins, and insulin-like growth factors and genes involved in cell-cell communications. Liver feminization was evidenced by increased expression of estrogen-linked genes and altered expression of genes that encode gender-related metabolic enzymes. These novel findings are in agreement with the biology and histology of arsenic-induced HCC, thereby indicating that multiple genetic events are associated with transplacental arsenic hepatocarcinogenesis.

GenePublisher: Automated analysis of DNA microarray data.

PubMed

Knudsen, Steen; Workman, Christopher; Sicheritz-Ponten, Thomas; Friis, Carsten

2003-07-01

GenePublisher, a system for automatic analysis of data from DNA microarray experiments, has been implemented with a web interface at http://www.cbs.dtu.dk/services/GenePublisher. Raw data are uploaded to the server together with a specification of the data. The server performs normalization, statistical analysis and visualization of the data. The results are run against databases of signal transduction pathways, metabolic pathways and promoter sequences in order to extract more information. The results of the entire analysis are summarized in report form and returned to the user.

Single-Nucleotide Polymorphism-Microarray Ploidy Analysis of Paraffin-Embedded Products of Conception in Recurrent Pregnancy Loss Evaluations.

PubMed

Maslow, Bat-Sheva L; Budinetz, Tara; Sueldo, Carolina; Anspach, Erica; Engmann, Lawrence; Benadiva, Claudio; Nulsen, John C

2015-07-01

To compare the analysis of chromosome number from paraffin-embedded products of conception using single-nucleotide polymorphism (SNP) microarray with the recommended screening for the evaluation of couples presenting with recurrent pregnancy loss who do not have previous fetal cytogenetic data. We performed a retrospective cohort study including all women who presented for a new evaluation of recurrent pregnancy loss over a 2-year period (January 1, 2012, to December 31, 2013). All participants had at least two documented first-trimester losses and both the recommended screening tests and SNP microarray performed on at least one paraffin-embedded products of conception sample. Single-nucleotide polymorphism microarray identifies all 24 chromosomes (22 autosomes, X, and Y). Forty-two women with a total of 178 losses were included in the study. Paraffin-embedded products of conception from 62 losses were sent for SNP microarray. Single-nucleotide polymorphism microarray successfully diagnosed fetal chromosome number in 71% (44/62) of samples, of which 43% (19/44) were euploid and 57% (25/44) were noneuploid. Seven of 42 (17%) participants had abnormalities on recurrent pregnancy loss screening. The per-person detection rate for a cause of pregnancy loss was significantly higher in the SNP microarray (0.50; 95% confidence interval [CI] 0.36-0.64) compared with recurrent pregnancy loss evaluation (0.17; 95% CI 0.08-0.31) (P=.002). Participants with one or more euploid loss identified on paraffin-embedded products of conception were significantly more likely to have an abnormality on recurrent pregnancy loss screening than those with only noneuploid results (P=.028). The significance remained when controlling for age, number of losses, number of samples, and total pregnancies. These results suggest that SNP microarray testing of paraffin-embedded products of conception is a valuable tool for the evaluation of recurrent pregnancy loss in patients without prior fetal cytogenetic results. Recommended recurrent pregnancy loss screening was unnecessary in almost half the patients in our study. II.

eSensor: an electrochemical detection-based DNA microarray technology enabling sample-to-answer molecular diagnostics

NASA Astrophysics Data System (ADS)

Liu, Robin H.; Longiaru, Mathew

2009-05-01

DNA microarrays are becoming a widespread tool used in life science and drug screening due to its many benefits of miniaturization and integration. Microarrays permit a highly multiplexed DNA analysis. Recently, the development of new detection methods and simplified methodologies has rapidly expanded the use of microarray technologies from predominantly gene expression analysis into the arena of diagnostics. Osmetech's eSensor® is an electrochemical detection platform based on a low-to- medium density DNA hybridization array on a cost-effective printed circuit board substrate. eSensor® has been cleared by FDA for Warfarin sensitivity test and Cystic Fibrosis Carrier Detection. Other genetic-based diagnostic and infectious disease detection tests are under development. The eSensor® platform eliminates the need for an expensive laser-based optical system and fluorescent reagents. It allows one to perform hybridization and detection in a single and small instrument without any fluidic processing and handling. Furthermore, the eSensor® platform is readily adaptable to on-chip sample-to-answer genetic analyses using microfluidics technology. The eSensor® platform provides a cost-effective solution to direct sample-to-answer genetic analysis, and thus have a potential impact in the fields of point-of-care genetic analysis, environmental testing, and biological warfare agent detection.

Towards the integration, annotation and association of historical microarray experiments with RNA-seq.

PubMed

Chavan, Shweta S; Bauer, Michael A; Peterson, Erich A; Heuck, Christoph J; Johann, Donald J

2013-01-01

Transcriptome analysis by microarrays has produced important advances in biomedicine. For instance in multiple myeloma (MM), microarray approaches led to the development of an effective disease subtyping via cluster assignment, and a 70 gene risk score. Both enabled an improved molecular understanding of MM, and have provided prognostic information for the purposes of clinical management. Many researchers are now transitioning to Next Generation Sequencing (NGS) approaches and RNA-seq in particular, due to its discovery-based nature, improved sensitivity, and dynamic range. Additionally, RNA-seq allows for the analysis of gene isoforms, splice variants, and novel gene fusions. Given the voluminous amounts of historical microarray data, there is now a need to associate and integrate microarray and RNA-seq data via advanced bioinformatic approaches. Custom software was developed following a model-view-controller (MVC) approach to integrate Affymetrix probe set-IDs, and gene annotation information from a variety of sources. The tool/approach employs an assortment of strategies to integrate, cross reference, and associate microarray and RNA-seq datasets. Output from a variety of transcriptome reconstruction and quantitation tools (e.g., Cufflinks) can be directly integrated, and/or associated with Affymetrix probe set data, as well as necessary gene identifiers and/or symbols from a diversity of sources. Strategies are employed to maximize the annotation and cross referencing process. Custom gene sets (e.g., MM 70 risk score (GEP-70)) can be specified, and the tool can be directly assimilated into an RNA-seq pipeline. A novel bioinformatic approach to aid in the facilitation of both annotation and association of historic microarray data, in conjunction with richer RNA-seq data, is now assisting with the study of MM cancer biology.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards.

PubMed

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Laegreid, Astrid

2007-10-18

The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish.

Optimization of cDNA microarrays procedures using criteria that do not rely on external standards

PubMed Central

Bruland, Torunn; Anderssen, Endre; Doseth, Berit; Bergum, Hallgeir; Beisvag, Vidar; Lægreid, Astrid

2007-01-01

Background The measurement of gene expression using microarray technology is a complicated process in which a large number of factors can be varied. Due to the lack of standard calibration samples such as are used in traditional chemical analysis it may be a problem to evaluate whether changes done to the microarray procedure actually improve the identification of truly differentially expressed genes. The purpose of the present work is to report the optimization of several steps in the microarray process both in laboratory practices and in data processing using criteria that do not rely on external standards. Results We performed a cDNA microarry experiment including RNA from samples with high expected differential gene expression termed "high contrasts" (rat cell lines AR42J and NRK52E) compared to self-self hybridization, and optimized a pipeline to maximize the number of genes found to be differentially expressed in the "high contrasts" RNA samples by estimating the false discovery rate (FDR) using a null distribution obtained from the self-self experiment. The proposed high-contrast versus self-self method (HCSSM) requires only four microarrays per evaluation. The effects of blocking reagent dose, filtering, and background corrections methodologies were investigated. In our experiments a dose of 250 ng LNA (locked nucleic acid) dT blocker, no background correction and weight based filtering gave the largest number of differentially expressed genes. The choice of background correction method had a stronger impact on the estimated number of differentially expressed genes than the choice of filtering method. Cross platform microarray (Illumina) analysis was used to validate that the increase in the number of differentially expressed genes found by HCSSM was real. Conclusion The results show that HCSSM can be a useful and simple approach to optimize microarray procedures without including external standards. Our optimizing method is highly applicable to both long oligo-probe microarrays which have become commonly used for well characterized organisms such as man, mouse and rat, as well as to cDNA microarrays which are still of importance for organisms with incomplete genome sequence information such as many bacteria, plants and fish. PMID:17949480

Epigenetic Vestiges of Early Developmental Adversity: Childhood Stress Exposure and DNA Methylation in Adolescence

ERIC Educational Resources Information Center

Essex, Marilyn J.; Boyce, W. Thomas; Hertzman, Clyde; Lam, Lucia L.; Armstrong, Jeffrey M.; Neumann, Sarah M. A.; Kobor, Michael S.

2013-01-01

Fifteen-year-old adolescents (N = 109) in a longitudinal study of child development were recruited to examine differences in DNA methylation in relation to parent reports of adversity during the adolescents' infancy and preschool periods. Microarray technology applied to 28,000 cytosine-guanine dinucleotide sites within DNA derived from buccal…

Analysis of transcriptional responses in the mouse dorsal striatum following acute 3,4-methylenedioxymethamphetamine (ecstasy): identification of extracellular signal-regulated kinase-controlled genes

PubMed Central

Salzmann, Julie; Canestrelli, Corinne; Noble, Florence; Marie-Claire, Cynthia

2006-01-01

3,4-methylenedioxymethamphetamine (MDMA, ecstasy), a widely used recreational drug with psychoactive properties, induces both serotonin (5-HT) and dopamine (DA) release in the brain. However, little is known about its intracellular effects. We previously showed that MDMA rewarding effects in mice were dependent upon ERK activation and that dorsal striatum was a critical region for mediating ERK-dependent Egr1 MDMA-induced transcription. Here, we extend these findings by showing that MDMA is indeed able to activate ERK within this structure. To identify genes regulated by acute MDMA in the mice dorsal striatum, and selectively controlled by this kinase, we performed microarray experiments by using a selective inhibitor of ERK activation, SL327. Of the ~24,000 genes from the microarray, 27 showed altered expression after exposure to MDMA, and among these, 59% were partially or totally inhibited by SL327 pretreatment. Our results showed that the genes regulated by MDMA encode proteins that belong to transcription factors family, signalling pathways (phosphatases, cytoskeleton regulation), and synaptic functions. These early changes, and especially those controlled by ERK activation might play significant roles in the expression of many of the behaviours that occur following MDMA taking. PMID:16289835

6.0 K microarray reveals differential transcriptomic responses in the dinoflagellate Prorocentrum minimum exposed to polychlorinated biphenyl (PCB).

PubMed

Wang, Hui; Guo, Ruoyu; Ki, Jang-Seu

2018-03-01

Endocrine disrupting chemicals (EDCs) have toxic effects on algae; however, their molecular genomic responses have not been sufficiently elucidated. Here, we evaluated genome-scaled responses of the dinoflagellate alga Prorocentrum minimum exposed to an EDC, polychlorinated biphenyl (PCB), using a 6.0 K microarray. Based on two-fold change cut-off, we identified that 609 genes (∼10.2%) responded to the PCB treatment. KEGG pathway analysis showed that differentially expressed genes (DEGs) were related to ribosomes, biosynthesis of amino acids, spliceosomes, and cellular processes. Many DEGs were involved in cell cycle progression, apoptosis, signal transduction, ion binding, and cellular transportation. In contrast, only a few genes related to photosynthesis and oxidative stress were expressed in response to PCB exposure. This was supported by that fact that there were no obvious changes in the photosynthetic efficiency and reactive oxygen species (ROS) production. These results suggest that PCB might not cause chloroplast and oxidative damage, but could lead to cell cycle arrest and apoptosis. In addition, various signal transduction and transport pathways might be disrupted in the cells, which could further contribute to cell death. These results expand the genomic understanding of the effects of EDCs on this dinoflagellate protist. Copyright © 2017 Elsevier Ltd. All rights reserved.

ArraySolver: an algorithm for colour-coded graphical display and Wilcoxon signed-rank statistics for comparing microarray gene expression data.

PubMed

Khan, Haseeb Ahmad

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann-Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n < or = 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform.

ArraySolver: An Algorithm for Colour-Coded Graphical Display and Wilcoxon Signed-Rank Statistics for Comparing Microarray Gene Expression Data

PubMed Central

2004-01-01

The massive surge in the production of microarray data poses a great challenge for proper analysis and interpretation. In recent years numerous computational tools have been developed to extract meaningful interpretation of microarray gene expression data. However, a convenient tool for two-groups comparison of microarray data is still lacking and users have to rely on commercial statistical packages that might be costly and require special skills, in addition to extra time and effort for transferring data from one platform to other. Various statistical methods, including the t-test, analysis of variance, Pearson test and Mann–Whitney U test, have been reported for comparing microarray data, whereas the utilization of the Wilcoxon signed-rank test, which is an appropriate test for two-groups comparison of gene expression data, has largely been neglected in microarray studies. The aim of this investigation was to build an integrated tool, ArraySolver, for colour-coded graphical display and comparison of gene expression data using the Wilcoxon signed-rank test. The results of software validation showed similar outputs with ArraySolver and SPSS for large datasets. Whereas the former program appeared to be more accurate for 25 or fewer pairs (n ≤ 25), suggesting its potential application in analysing molecular signatures that usually contain small numbers of genes. The main advantages of ArraySolver are easy data selection, convenient report format, accurate statistics and the familiar Excel platform. PMID:18629036

RECOVERING FILTER-BASED MICROARRAY DATA FOR PATHWAYS ANALYSIS USING A MULTIPOINT ALIGNMENT STRATEGY

EPA Science Inventory

The use of commercial microarrays are rapidly becoming the method of choice for profiling gene expression and assessing various disease states. Research Genetics has provided a series of well defined biological and software tools to the research community for these analyses. Th...

Microarray-mediated transcriptome analysis of the tributyltin (TBT)-resistant bacterium Pseudomonas aeruginosa 25W in the presence of TBT.

PubMed

Dubey, Santosh K; Tokashiki, Tsutomu; Suzuki, Satoru

2006-04-01

The tributyltin (TBT)-resistant bacterium, Pseudomonas aeruginosa 25W, which was isolated in seawater from the Arabian Sea, was subjected to transcriptome analysis in the presence of high concentrations of TBT. Only slight effects were observed at TBT concentration of 50 microM, but exposure to 500 microM resulted in the upregulation of 6 genes and the downregulation of 75. Among the 75 downregulated genes, 53% (40 out of 75) were of hypothetical function, followed by 14 transcriptional regulation- and translation-associated genes. The results of this study indicated that although the 25W strain was highly resistant to TBT, high concentrations of TBT result in toxic effect on the transcriptional and translational levels. The target genes likely belong to a specific category of transcription- and translation-associated genes rather than to other gene categories.

Tumor Cell Gene Expression Changes Following Short-term In vivo Exposure to Single Agent Chemotherapeutics are Related to Survival in Multiple Myeloma

PubMed Central

Burington, Bart; Barlogie, Bart; Zhan, Fenghuang; Crowley, John; Shaughnessy, John D.

2013-01-01

Changes in global gene expression patterns in tumor cells following in vivo therapy may vary by treatment and provide added or synergistic prognostic power over pretherapy gene expression profiles (GEP). This molecular readout of drug-cell interaction may also point to mechanisms of action/resistance. In newly diagnosed patients with multiple myeloma (MM), microarray data were obtained on tumor cells prior to and 48 hours after in vivo treatment using dexamethasone (n = 45) or thalidomide (n = 42); in the case of relapsed MM, microarray data were obtained prior to (n = 36) and after (n = 19) lenalidomide administration. Dexamethasone and thalidomide induced both common and unique GEP changes in tumor cells. Combined baseline and 48-hour changes in GEP in a subset of genes, many related to oxidative stress and cytoskeletal dynamics, were predictive of outcome in newly diagnosed MM patients receiving tandem transplants. Thalidomide-altered genes also changed following lenalidomide exposure and predicted event-free and overall survival in relapsed patients receiving lenalidomide as a single agent. Combined with baseline molecular features, changes in GEP following short-term single-agent exposure may help guide treatment decisions for patients with MM. Genes whose drug-altered expression were found to be related to survival may point to molecular switches related to response and/or resistance to different classes of drugs. PMID:18676754

Estimating gene function with least squares nonnegative matrix factorization.

PubMed

Wang, Guoli; Ochs, Michael F

2007-01-01

Nonnegative matrix factorization is a machine learning algorithm that has extracted information from data in a number of fields, including imaging and spectral analysis, text mining, and microarray data analysis. One limitation with the method for linking genes through microarray data in order to estimate gene function is the high variance observed in transcription levels between different genes. Least squares nonnegative matrix factorization uses estimates of the uncertainties on the mRNA levels for each gene in each condition, to guide the algorithm to a local minimum in normalized chi2, rather than a Euclidean distance or divergence between the reconstructed data and the data itself. Herein, application of this method to microarray data is demonstrated in order to predict gene function.

Microarray expression technology: from start to finish.

PubMed

Elvidge, Gareth

2006-01-01

The recent introduction of new microarray expression technologies and the further development of established platforms ensure that the researcher is presented with a range of options for performing an experiment. Whilst this has opened up the possibilities for future applications, such as exon-specific arrays, increased sample throughput and 'chromatin immunoprecipitation (ChIP) on chip' experiments, the initial decision processes and experiment planning are made more difficult. This review will give an overview of the various technologies that are available to perform a microarray expression experiment, from the initial planning stages through to the final data analysis. Both practical aspects and data analysis options will be considered. The relative advantages and disadvantages will be discussed with insights provided for future directions of the technology.

Single molecule fluorescence microscopy for ultra-sensitive RNA expression profiling

NASA Astrophysics Data System (ADS)

Hesse, Jan; Jacak, Jaroslaw; Regl, Gerhard; Eichberger, Thomas; Aberger, Fritz; Schlapak, Robert; Howorka, Stefan; Muresan, Leila; Frischauf, Anna-Maria; Schütz, Gerhard J.

2007-02-01

We developed a microarray analysis platform for ultra-sensitive RNA expression profiling of minute samples. It utilizes a novel scanning system for single molecule fluorescence detection on cm2 size samples in combination with specialized biochips, optimized for low autofluorescence and weak unspecific adsorption. 20 μg total RNA was extracted from 10 6 cells of a human keratinocyte cell line (HaCaT) and reversely transcribed in the presence of Alexa647-aha-dUTP. 1% of the resulting labeled cDNA was used for complex hybridization to a custom-made oligonucleotide microarray representing a set of 125 different genes. For low abundant genes, individual cDNA molecules hybridized to the microarray spots could be resolved. Single cDNA molecules hybridized to the chip surface appeared as diffraction limited features in the fluorescence images. The à trous wavelet method was utilized for localization and counting of the separated cDNA signals. Subsequently, the degree of labeling of the localized cDNA molecules was determined by brightness analysis for the different genes. Variations by factors up to 6 were found, which in conventional microarray analysis would result in a misrepresentation of the relative abundance of mRNAs.

Dual-color Proteomic Profiling of Complex Samples with a Microarray of 810 Cancer-related Antibodies*

PubMed Central

Schröder, Christoph; Jacob, Anette; Tonack, Sarah; Radon, Tomasz P.; Sill, Martin; Zucknick, Manuela; Rüffer, Sven; Costello, Eithne; Neoptolemos, John P.; Crnogorac-Jurcevic, Tatjana; Bauer, Andrea; Fellenberg, Kurt; Hoheisel, Jörg D.

2010-01-01

Antibody microarrays have the potential to enable comprehensive proteomic analysis of small amounts of sample material. Here, protocols are presented for the production, quality assessment, and reproducible application of antibody microarrays in a two-color mode with an array of 1,800 features, representing 810 antibodies that were directed at 741 cancer-related proteins. In addition to measures of array quality, we implemented indicators for the accuracy and significance of dual-color detection. Dual-color measurements outperform a single-color approach concerning assay reproducibility and discriminative power. In the analysis of serum samples, depletion of high-abundance proteins did not improve technical assay quality. On the contrary, depletion introduced a strong bias in protein representation. In an initial study, we demonstrated the applicability of the protocols to proteins derived from urine samples. We identified differences between urine samples from pancreatic cancer patients and healthy subjects and between sexes. This study demonstrates that biomedically relevant data can be produced. As demonstrated by the thorough quality analysis, the dual-color antibody array approach proved to be competitive with other proteomic techniques and comparable in performance to transcriptional microarray analyses. PMID:20164060

Estimating differential expression from multiple indicators

PubMed Central

Ilmjärv, Sten; Hundahl, Christian Ansgar; Reimets, Riin; Niitsoo, Margus; Kolde, Raivo; Vilo, Jaak; Vasar, Eero; Luuk, Hendrik

2014-01-01

Regardless of the advent of high-throughput sequencing, microarrays remain central in current biomedical research. Conventional microarray analysis pipelines apply data reduction before the estimation of differential expression, which is likely to render the estimates susceptible to noise from signal summarization and reduce statistical power. We present a probe-level framework, which capitalizes on the high number of concurrent measurements to provide more robust differential expression estimates. The framework naturally extends to various experimental designs and target categories (e.g. transcripts, genes, genomic regions) as well as small sample sizes. Benchmarking in relation to popular microarray and RNA-sequencing data-analysis pipelines indicated high and stable performance on the Microarray Quality Control dataset and in a cell-culture model of hypoxia. Experimental-data-exhibiting long-range epigenetic silencing of gene expression was used to demonstrate the efficacy of detecting differential expression of genomic regions, a level of analysis not embraced by conventional workflows. Finally, we designed and conducted an experiment to identify hypothermia-responsive genes in terms of monotonic time-response. As a novel insight, hypothermia-dependent up-regulation of multiple genes of two major antioxidant pathways was identified and verified by quantitative real-time PCR. PMID:24586062

The effect of column purification on cDNA indirect labelling for microarrays

PubMed Central

Molas, M Lia; Kiss, John Z

2007-01-01

Background The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. Results We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Conclusion Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays. PMID:17597522

The effect of column purification on cDNA indirect labelling for microarrays.

PubMed

Molas, M Lia; Kiss, John Z

2007-06-27

The success of the microarray reproducibility is dependent upon the performance of standardized procedures. Since the introduction of microarray technology for the analysis of global gene expression, reproducibility of results among different laboratories has been a major problem. Two of the main contributors to this variability are the use of different microarray platforms and different laboratory practices. In this paper, we address the latter question in terms of how variation in one of the steps of a labelling procedure affects the cDNA product prior to microarray hybridization. We used a standard procedure to label cDNA for microarray hybridization and employed different types of column chromatography for cDNA purification. After purifying labelled cDNA, we used the Agilent 2100 Bioanalyzer and agarose gel electrophoresis to assess the quality of the labelled cDNA before its hybridization onto a microarray platform. There were major differences in the cDNA profile (i.e. cDNA fragment lengths and abundance) as a result of using four different columns for purification. In addition, different columns have different efficiencies to remove rRNA contamination. This study indicates that the appropriate column to use in this type of protocol has to be experimentally determined. Finally, we present new evidence establishing the importance of testing the method of purification used during an indirect labelling procedure. Our results confirm the importance of assessing the quality of the sample in the labelling procedure prior to hybridization onto a microarray platform. Standardization of column purification systems to be used in labelling procedures will improve the reproducibility of microarray results among different laboratories. In addition, implementation of a quality control check point of the labelled samples prior to microarray hybridization will prevent hybridizing a poor quality sample to expensive micorarrays.

Methylmercury-induced changes in gene transcription associated with neuroendocrine disruption in largemouth bass (Micropterus salmoides)

PubMed Central

Annis, Mandy L.; Brumbaugh, William G.; Chasar, Lia C.; Denslow, Nancy D.; Tillitt, Donald E.

2014-01-01

Methyl-mercury (MeHg) is a potent neuroendocrine disruptor that impairs reproductive processes in fish. The objectives of this study were to (1) characterize transcriptomic changes induced by MeHg exposure in the female largemouth bass (LMB) hypothalamus under controlled laboratory conditions, (2) investigate the health and reproductive impacts of MeHg exposure on male and female largemouth bass (LMB) in the natural environment, and (3) identify MeHg-associated gene expression patterns in whole brain of female LMB from MeHg-contaminated habitats. The laboratory experiment was a single injection of 2.5 μg MeHg/g body weight for 96 h exposure. The field survey compared river systems in Florida, USA with comparably lower concentrations of MeHg (Wekiva, Santa Fe, and St. Johns Rivers) in fish and one river system with LMB that contained elevated concentrations of MeHg (St. Marys River). Microarray analysis was used to quantify transcriptomic responses to MeHg exposure. Although fish at the high-MeHg site did not show overt health or reproductive impairment, there were MeHg-responsive genes and pathways identified in the laboratory study that were also altered in fish from the high-MeHg site relative to fish at the low-MeHg sites. Gene network analysis suggested that MeHg regulated the expression targets of neuropeptide receptor and steroid signaling, as well as structural components of the cell. Disease-associated gene networks related to MeHg exposure, based upon expression data, included cerebellum ataxia, movement disorders, and hypercalcemia. Gene responses in the CNS are consistent with the documented neurotoxicological and neuroendocrine disrupting effects of MeHg in vertebrates. PMID:24694518

Methylmercury-induced changes in gene transcription associated with neuroendocrine disruption in largemouth bass (Micropterus salmoides).

PubMed

Richter, Catherine A; Martyniuk, Christopher J; Annis, Mandy L; Brumbaugh, William G; Chasar, Lia C; Denslow, Nancy D; Tillitt, Donald E

2014-07-01

Methyl-mercury (MeHg) is a potent neuroendocrine disruptor that impairs reproductive processes in fish. The objectives of this study were to (1) characterize transcriptomic changes induced by MeHg exposure in the female largemouth bass (LMB) hypothalamus under controlled laboratory conditions, (2) investigate the health and reproductive impacts of MeHg exposure on male and female largemouth bass (LMB) in the natural environment, and (3) identify MeHg-associated gene expression patterns in whole brain of female LMB from MeHg-contaminated habitats. The laboratory experiment was a single injection of 2.5 μg MeHg/g body weight for 96 h exposure. The field survey compared river systems in Florida, USA with comparably lower concentrations of MeHg (Wekiva, Santa Fe, and St. Johns Rivers) in fish and one river system with LMB that contained elevated concentrations of MeHg (St. Marys River). Microarray analysis was used to quantify transcriptomic responses to MeHg exposure. Although fish at the high-MeHg site did not show overt health or reproductive impairment, there were MeHg-responsive genes and pathways identified in the laboratory study that were also altered in fish from the high-MeHg site relative to fish at the low-MeHg sites. Gene network analysis suggested that MeHg regulated the expression targets of neuropeptide receptor and steroid signaling, as well as structural components of the cell. Disease-associated gene networks related to MeHg exposure, based upon expression data, included cerebellum ataxia, movement disorders, and hypercalcemia. Gene responses in the CNS are consistent with the documented neurotoxicological and neuroendocrine disrupting effects of MeHg in vertebrates. Published by Elsevier Inc.

Methylmercury-induced changes in gene transcription associated with neuroendocrine disruption in largemouth bass (Micropterus salmoides)

USGS Publications Warehouse

Richter, Catherine A.; Martyniuk, Christopher J.; Annis, Mandy L.; Brumbaugh, William G.; Chasar, Lia C.; Denslow, Nancy D.; Tillitt, Donald E.

2014-01-01

Methyl-mercury (MeHg) is a potent neuroendocrine disruptor that impairs reproductive processes in fish. The objectives of this study were to (1) characterize transcriptomic changes induced by MeHg exposure in the female largemouth bass (LMB) hypothalamus under controlled laboratory conditions, (2) investigate the health and reproductive impacts of MeHg exposure on male and female largemouth bass (LMB) in the natural environment, and (3) identify MeHg-associated gene expression patterns in whole brain of female LMB from MeHg-contaminated habitats. The laboratory experiment was a single injection of 2.5 μg MeHg/g body weight for 96 h exposure. The field survey compared river systems in Florida, USA with comparably lower concentrations of MeHg (Wekiva, Santa Fe, and St. Johns Rivers) in fish and one river system with LMB that contained elevated concentrations of MeHg (St. Marys River). Microarray analysis was used to quantify transcriptomic responses to MeHg exposure. Although fish at the high-MeHg site did not show overt health or reproductive impairment, there were MeHg-responsive genes and pathways identified in the laboratory study that were also altered in fish from the high-MeHg site relative to fish at the low-MeHg sites. Gene network analysis suggested that MeHg regulated the expression targets of neuropeptide receptor and steroid signaling, as well as structural components of the cell. Disease-associated gene networks related to MeHg exposure, based upon expression data, included cerebellum ataxia, movement disorders, and hypercalcemia. Gene responses in the CNS are consistent with the documented neurotoxicological and neuroendocrine disrupting effects of MeHg in vertebrates.

Functional interaction analysis of GM1-related carbohydrates and Vibrio cholerae toxins using carbohydrate microarray.

PubMed

Kim, Chang Sup; Seo, Jeong Hyun; Cha, Hyung Joon

2012-08-07

The development of analytical tools is important for understanding the infection mechanisms of pathogenic bacteria or viruses. In the present work, a functional carbohydrate microarray combined with a fluorescence immunoassay was developed to analyze the interactions of Vibrio cholerae toxin (ctx) proteins and GM1-related carbohydrates. Ctx proteins were loaded onto the surface-immobilized GM1 pentasaccharide and six related carbohydrates, and their binding affinities were detected immunologically. The analysis of the ctx-carbohydrate interactions revealed that the intrinsic selectivity of ctx was GM1 pentasaccharide ≫ GM2 tetrasaccharide > asialo GM1 tetrasaccharide ≥ GM3trisaccharide, indicating that a two-finger grip formation and the terminal monosaccharides play important roles in the ctx-GM1 interaction. In addition, whole cholera toxin (ctxAB(5)) had a stricter substrate specificity and a stronger binding affinity than only the cholera toxin B subunit (ctxB). On the basis of the quantitative analysis, the carbohydrate microarray showed the sensitivity of detection of the ctxAB(5)-GM1 interaction with a limit-of-detection (LOD) of 2 ng mL(-1) (23 pM), which is comparable to other reported high sensitivity assay tools. In addition, the carbohydrate microarray successfully detected the actual toxin directly secreted from V. cholerae, without showing cross-reactivity to other bacteria. Collectively, these results demonstrate that the functional carbohydrate microarray is suitable for analyzing toxin protein-carbohydrate interactions and can be applied as a biosensor for toxin detection.

Bacterial identification and subtyping using DNA microarray and DNA sequencing.

PubMed

Al-Khaldi, Sufian F; Mossoba, Magdi M; Allard, Marc M; Lienau, E Kurt; Brown, Eric D

2012-01-01

The era of fast and accurate discovery of biological sequence motifs in prokaryotic and eukaryotic cells is here. The co-evolution of direct genome sequencing and DNA microarray strategies not only will identify, isotype, and serotype pathogenic bacteria, but also it will aid in the discovery of new gene functions by detecting gene expressions in different diseases and environmental conditions. Microarray bacterial identification has made great advances in working with pure and mixed bacterial samples. The technological advances have moved beyond bacterial gene expression to include bacterial identification and isotyping. Application of new tools such as mid-infrared chemical imaging improves detection of hybridization in DNA microarrays. The research in this field is promising and future work will reveal the potential of infrared technology in bacterial identification. On the other hand, DNA sequencing by using 454 pyrosequencing is so cost effective that the promise of $1,000 per bacterial genome sequence is becoming a reality. Pyrosequencing technology is a simple to use technique that can produce accurate and quantitative analysis of DNA sequences with a great speed. The deposition of massive amounts of bacterial genomic information in databanks is creating fingerprint phylogenetic analysis that will ultimately replace several technologies such as Pulsed Field Gel Electrophoresis. In this chapter, we will review (1) the use of DNA microarray using fluorescence and infrared imaging detection for identification of pathogenic bacteria, and (2) use of pyrosequencing in DNA cluster analysis to fingerprint bacterial phylogenetic trees.

Archetypal analysis of diverse Pseudomonas aeruginosa transcriptomes reveals adaptation in cystic fibrosis airways

PubMed Central

2013-01-01

Background Analysis of global gene expression by DNA microarrays is widely used in experimental molecular biology. However, the complexity of such high-dimensional data sets makes it difficult to fully understand the underlying biological features present in the data. The aim of this study is to introduce a method for DNA microarray analysis that provides an intuitive interpretation of data through dimension reduction and pattern recognition. We present the first “Archetypal Analysis” of global gene expression. The analysis is based on microarray data from five integrated studies of Pseudomonas aeruginosa isolated from the airways of cystic fibrosis patients. Results Our analysis clustered samples into distinct groups with comprehensible characteristics since the archetypes representing the individual groups are closely related to samples present in the data set. Significant changes in gene expression between different groups identified adaptive changes of the bacteria residing in the cystic fibrosis lung. The analysis suggests a similar gene expression pattern between isolates with a high mutation rate (hypermutators) despite accumulation of different mutations for these isolates. This suggests positive selection in the cystic fibrosis lung environment, and changes in gene expression for these isolates are therefore most likely related to adaptation of the bacteria. Conclusions Archetypal analysis succeeded in identifying adaptive changes of P. aeruginosa. The combination of clustering and matrix factorization made it possible to reveal minor similarities among different groups of data, which other analytical methods failed to identify. We suggest that this analysis could be used to supplement current methods used to analyze DNA microarray data. PMID:24059747

Gene features selection for three-class disease classification via multiple orthogonal partial least square discriminant analysis and S-plot using microarray data.

PubMed

Yang, Mingxing; Li, Xiumin; Li, Zhibin; Ou, Zhimin; Liu, Ming; Liu, Suhuan; Li, Xuejun; Yang, Shuyu

2013-01-01

DNA microarray analysis is characterized by obtaining a large number of gene variables from a small number of observations. Cluster analysis is widely used to analyze DNA microarray data to make classification and diagnosis of disease. Because there are so many irrelevant and insignificant genes in a dataset, a feature selection approach must be employed in data analysis. The performance of cluster analysis of this high-throughput data depends on whether the feature selection approach chooses the most relevant genes associated with disease classes. Here we proposed a new method using multiple Orthogonal Partial Least Squares-Discriminant Analysis (mOPLS-DA) models and S-plots to select the most relevant genes to conduct three-class disease classification and prediction. We tested our method using Golub's leukemia microarray data. For three classes with subtypes, we proposed hierarchical orthogonal partial least squares-discriminant analysis (OPLS-DA) models and S-plots to select features for two main classes and their subtypes. For three classes in parallel, we employed three OPLS-DA models and S-plots to choose marker genes for each class. The power of feature selection to classify and predict three-class disease was evaluated using cluster analysis. Further, the general performance of our method was tested using four public datasets and compared with those of four other feature selection methods. The results revealed that our method effectively selected the most relevant features for disease classification and prediction, and its performance was better than that of the other methods.

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships

PubMed Central

2010-01-01

Background The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. Results In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. Conclusion High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data. PMID:20122245

Knowledge-based analysis of microarrays for the discovery of transcriptional regulation relationships.

PubMed

Seok, Junhee; Kaushal, Amit; Davis, Ronald W; Xiao, Wenzhong

2010-01-18

The large amount of high-throughput genomic data has facilitated the discovery of the regulatory relationships between transcription factors and their target genes. While early methods for discovery of transcriptional regulation relationships from microarray data often focused on the high-throughput experimental data alone, more recent approaches have explored the integration of external knowledge bases of gene interactions. In this work, we develop an algorithm that provides improved performance in the prediction of transcriptional regulatory relationships by supplementing the analysis of microarray data with a new method of integrating information from an existing knowledge base. Using a well-known dataset of yeast microarrays and the Yeast Proteome Database, a comprehensive collection of known information of yeast genes, we show that knowledge-based predictions demonstrate better sensitivity and specificity in inferring new transcriptional interactions than predictions from microarray data alone. We also show that comprehensive, direct and high-quality knowledge bases provide better prediction performance. Comparison of our results with ChIP-chip data and growth fitness data suggests that our predicted genome-wide regulatory pairs in yeast are reasonable candidates for follow-up biological verification. High quality, comprehensive, and direct knowledge bases, when combined with appropriate bioinformatic algorithms, can significantly improve the discovery of gene regulatory relationships from high throughput gene expression data.

Evaluation of high throughput gene expression platforms using a genomic biomarker signature for prediction of skin sensitization.

PubMed

Forreryd, Andy; Johansson, Henrik; Albrekt, Ann-Sofie; Lindstedt, Malin

2014-05-16

Allergic contact dermatitis (ACD) develops upon exposure to certain chemical compounds termed skin sensitizers. To reduce the occurrence of skin sensitizers, chemicals are regularly screened for their capacity to induce sensitization. The recently developed Genomic Allergen Rapid Detection (GARD) assay is an in vitro alternative to animal testing for identification of skin sensitizers, classifying chemicals by evaluating transcriptional levels of a genomic biomarker signature. During assay development and biomarker identification, genome-wide expression analysis was applied using microarrays covering approximately 30,000 transcripts. However, the microarray platform suffers from drawbacks in terms of low sample throughput, high cost per sample and time consuming protocols and is a limiting factor for adaption of GARD into a routine assay for screening of potential sensitizers. With the purpose to simplify assay procedures, improve technical parameters and increase sample throughput, we assessed the performance of three high throughput gene expression platforms--nCounter®, BioMark HD™ and OpenArray®--and correlated their performance metrics against our previously generated microarray data. We measured the levels of 30 transcripts from the GARD biomarker signature across 48 samples. Detection sensitivity, reproducibility, correlations and overall structure of gene expression measurements were compared across platforms. Gene expression data from all of the evaluated platforms could be used to classify most of the sensitizers from non-sensitizers in the GARD assay. Results also showed high data quality and acceptable reproducibility for all platforms but only medium to poor correlations of expression measurements across platforms. In addition, evaluated platforms were superior to the microarray platform in terms of cost efficiency, simplicity of protocols and sample throughput. We evaluated the performance of three non-array based platforms using a limited set of transcripts from the GARD biomarker signature. We demonstrated that it was possible to achieve acceptable discriminatory power in terms of separation between sensitizers and non-sensitizers in the GARD assay while reducing assay costs, simplify assay procedures and increase sample throughput by using an alternative platform, providing a first step towards the goal to prepare GARD for formal validation and adaption of the assay for industrial screening of potential sensitizers.

Discovery of genes implicated in whirling disease infection and resistance in rainbow trout using genome-wide expression profiling

PubMed Central

Baerwald, Melinda R; Welsh, Amy B; Hedrick, Ronald P; May, Bernie

2008-01-01

Background Whirling disease, caused by the pathogen Myxobolus cerebralis, afflicts several salmonid species. Rainbow trout are particularly susceptible and may suffer high mortality rates. The disease is persistent and spreading in hatcheries and natural waters of several countries, including the U.S.A., and the economic losses attributed to whirling disease are substantial. In this study, genome-wide expression profiling using cDNA microarrays was conducted for resistant Hofer and susceptible Trout Lodge rainbow trout strains following pathogen exposure with the primary objective of identifying specific genes implicated in whirling disease resistance. Results Several genes were significantly up-regulated in skin following pathogen exposure for both the resistant and susceptible rainbow trout strains. For both strains, response to infection appears to be linked with the interferon system. Expression profiles for three genes identified with microarrays were confirmed with qRT-PCR. Ubiquitin-like protein 1 was up-regulated over 100 fold and interferon regulating factor 1 was up-regulated over 15 fold following pathogen exposure for both strains. Expression of metallothionein B, which has known roles in inflammation and immune response, was up-regulated over 5 fold in the resistant Hofer strain but was unchanged in the susceptible Trout Lodge strain following pathogen exposure. Conclusion The present study has provided an initial view into the genetic basis underlying immune response and resistance of rainbow trout to the whirling disease parasite. The identified genes have allowed us to gain insight into the molecular mechanisms implicated in salmonid immune response and resistance to whirling disease infection. PMID:18218127

Gene expression profiling of whole blood: Comparison of target preparation methods for accurate and reproducible microarray analysis

PubMed Central

Vartanian, Kristina; Slottke, Rachel; Johnstone, Timothy; Casale, Amanda; Planck, Stephen R; Choi, Dongseok; Smith, Justine R; Rosenbaum, James T; Harrington, Christina A

2009-01-01

Background Peripheral blood is an accessible and informative source of transcriptomal information for many human disease and pharmacogenomic studies. While there can be significant advantages to analyzing RNA isolated from whole blood, particularly in clinical studies, the preparation of samples for microarray analysis is complicated by the need to minimize artifacts associated with highly abundant globin RNA transcripts. The impact of globin RNA transcripts on expression profiling data can potentially be reduced by using RNA preparation and labeling methods that remove or block globin RNA during the microarray assay. We compared four different methods for preparing microarray hybridization targets from human whole blood collected in PAXGene tubes. Three of the methods utilized the Affymetrix one-cycle cDNA synthesis/in vitro transcription protocol but varied treatment of input RNA as follows: i. no treatment; ii. treatment with GLOBINclear; or iii. treatment with globin PNA oligos. In the fourth method cDNA targets were prepared with the Ovation amplification and labeling system. Results We find that microarray targets generated with labeling methods that reduce globin mRNA levels or minimize the impact of globin transcripts during hybridization detect more transcripts in the microarray assay compared with the standard Affymetrix method. Comparison of microarray results with quantitative PCR analysis of a panel of genes from the NF-kappa B pathway shows good correlation of transcript measurements produced with all four target preparation methods, although method-specific differences in overall correlation were observed. The impact of freezing blood collected in PAXGene tubes on data reproducibility was also examined. Expression profiles show little or no difference when RNA is extracted from either fresh or frozen blood samples. Conclusion RNA preparation and labeling methods designed to reduce the impact of globin mRNA transcripts can significantly improve the sensitivity of the DNA microarray expression profiling assay for whole blood samples. While blockage of globin transcripts during first strand cDNA synthesis with globin PNAs resulted in the best overall performance in this study, we conclude that selection of a protocol for expression profiling studies in blood should depend on several factors, including implementation requirements of the method and study design. RNA isolated from either freshly collected or frozen blood samples stored in PAXGene tubes can be used without altering gene expression profiles. PMID:19123946

APPLICATION OF DNA MICROARRAYS TO REPRODUCTIVE TOXICOLOGY AND THE DEVELOPMENT OF A TESTIS ARRAY

EPA Science Inventory

With the advent of sequence information for entire mammalian genomes, it is now possible to analyze gene expression and gene polymorphisms on a genomic scale. The primary tool for analysis of gene expression is the DNA microarray. We have used commercially available cDNA micro...

Microarrays for Undergraduate Classes

ERIC Educational Resources Information Center

Hancock, Dale; Nguyen, Lisa L.; Denyer, Gareth S.; Johnston, Jill M.

2006-01-01

A microarray experiment is presented that, in six laboratory sessions, takes undergraduate students from the tissue sample right through to data analysis. The model chosen, the murine erythroleukemia cell line, can be easily cultured in sufficient quantities for class use. Large changes in gene expression can be induced in these cells by…

BIOMONITORING THE TOXICOGENOMIC RESPONSE TO ENDOCRINE DISRUPTING CHEMICALS IN HUMANS, LABORATORY SPECIES AND WILDLIFE

EPA Science Inventory

With the advent of sequence information for entire eukaryotic genomes, it is now possible to analyze gene expression on a genomic scale. The primary tool for genomic analysis of gene expression is the gene microarray. We have used commercially available and custom cDNA microarray...

CLOFIBRATE-INDUCED GENE EXPRESSION CHANGES IN RAT LIVER: A CROSS-LABORATORY ANALYSIS USING MEMBRANE CDNA ARRAYS

EPA Science Inventory

Microarrays have the potential to significantly impact our ability to identify toxic hazards by the identification of mechanistically-relevant markers of toxicity. To be useful for risk assessment however, microarray data must be challenged to determine its reliability and inter...

Comparative analysis of microarray data in Arabidopsis transcriptome during compatible interactions with plant viruses

USDA-ARS?s Scientific Manuscript database

To analyze transcriptome response to virus infection, we have assembled currently available microarray data on changes in gene expression levels in compatible Arabidopsis-virus interactions. We used the mean r (Pearson’s correlation coefficient) for neighboring pairs to estimate pairwise local simil...

Gene expression profile of blood cells for the prediction of delayed cerebral ischemia after intracranial aneurysm rupture: a pilot study in humans.

PubMed

Baumann, Antoine; Devaux, Yvan; Audibert, Gérard; Zhang, Lu; Bracard, Serge; Colnat-Coulbois, Sophie; Klein, Olivier; Zannad, Faiez; Charpentier, Claire; Longrois, Dan; Mertes, Paul-Michel

2013-01-01

Delayed cerebral ischemia (DCI) is a potentially devastating complication after intracranial aneurysm rupture and its mechanisms remain poorly elucidated. Early identification of the patients prone to developing DCI after rupture may represent a major breakthrough in its prevention and treatment. The single gene approach of DCI has demonstrated interest in humans. We hypothesized that whole genome expression profile of blood cells may be useful for better comprehension and prediction of aneurysmal DCI. Over a 35-month period, 218 patients with aneurysm rupture were included in this study. DCI was defined as the occurrence of a new delayed neurological deficit occurring within 2 weeks after aneurysm rupture with evidence of ischemia either on perfusion-diffusion MRI, CT angiography or CT perfusion imaging, or with cerebral angiography. DCI patients were matched against controls based on 4 out of 5 criteria (age, sex, Fisher grade, aneurysm location and smoking status). Genome-wide expression analysis of blood cells obtained at admission was performed by microarrays. Transcriptomic analysis was performed using long oligonucleotide microarrays representing 25,000 genes. Quantitative PCR: 1 µg of total RNA extracted was reverse-transcribed, and the resulting cDNA was diluted 10-fold before performing quantitative PCR. Microarray data were first analyzed by 'Significance Analysis of Microarrays' software which includes the Benjamini correction for multiple testing. In a second step, microarray data fold change was compared using a two-tailed, paired t test. Analysis of receiver-operating characteristic (ROC) curves and the area under the ROC curves were used for prediction analysis. Logistic regression models were used to investigate the additive value of multiple biomarkers. A total of 16 patients demonstrated DCI. Significance Analysis of Microarrays software failed to retrieve significant genes, most probably because of the heterogeneity of the patients included in the microarray experiments and the small size of the DCI population sample. Standard two-tailed paired t test and C-statistic revealed significant associations between gene expression and the occurrence of DCI: in particular, the expression of neuroregulin 1 was 1.6-fold upregulated in patients with DCI (p = 0.01) and predicted DCI with an area under the ROC curve of 0.96. Logistic regression analyses revealed a significant association between neuroregulin 1 and DCI (odds ratio 1.46, 95% confidence interval 1.02-2.09, p = 0.02). This pilot study suggests that blood cells may be a reservoir of prognostic biomarkers of DCI in patients with intracranial aneurysm rupture. Despite an evident lack of power, this study elicited neuroregulin 1, a vasoreactivity-, inflammation- and angiogenesis-related gene, as a possible candidate predictor of DCI. Larger cohort studies are needed but genome-wide microarray-based studies are promising research tools for the understanding of DCI after intracranial aneurysm rupture. © 2013 S. Karger AG, Basel.

Profiling In Situ Microbial Community Structure with an Amplification Microarray

PubMed Central

Knickerbocker, Christopher; Bryant, Lexi; Golova, Julia; Wiles, Cory; Williams, Kenneth H.; Peacock, Aaron D.; Long, Philip E.

2013-01-01

The objectives of this study were to unify amplification, labeling, and microarray hybridization chemistries within a single, closed microfluidic chamber (an amplification microarray) and verify technology performance on a series of groundwater samples from an in situ field experiment designed to compare U(VI) mobility under conditions of various alkalinities (as HCO3−) during stimulated microbial activity accompanying acetate amendment. Analytical limits of detection were between 2 and 200 cell equivalents of purified DNA. Amplification microarray signatures were well correlated with 16S rRNA-targeted quantitative PCR results and hybridization microarray signatures. The succession of the microbial community was evident with and consistent between the two microarray platforms. Amplification microarray analysis of acetate-treated groundwater showed elevated levels of iron-reducing bacteria (Flexibacter, Geobacter, Rhodoferax, and Shewanella) relative to the average background profile, as expected. Identical molecular signatures were evident in the transect treated with acetate plus NaHCO3, but at much lower signal intensities and with a much more rapid decline (to nondetection). Azoarcus, Thaurea, and Methylobacterium were responsive in the acetate-only transect but not in the presence of bicarbonate. Observed differences in microbial community composition or response to bicarbonate amendment likely had an effect on measured rates of U reduction, with higher rates probable in the part of the field experiment that was amended with bicarbonate. The simplification in microarray-based work flow is a significant technological advance toward entirely closed-amplicon microarray-based tests and is generally extensible to any number of environmental monitoring applications. PMID:23160129

Bioinformatic tools for inferring functional information from plant microarray data: tools for the first steps.

PubMed

Page, Grier P; Coulibaly, Issa

2008-01-01

Microarrays are a very powerful tool for quantifying the amount of RNA in samples; however, their ability to query essentially every gene in a genome, which can number in the tens of thousands, presents analytical and interpretative problems. As a result, a variety of software and web-based tools have been developed to help with these issues. This article highlights and reviews some of the tools for the first steps in the analysis of a microarray study. We have tried for a balance between free and commercial systems. We have organized the tools by topics including image processing tools (Section 2), power analysis tools (Section 3), image analysis tools (Section 4), database tools (Section 5), databases of functional information (Section 6), annotation tools (Section 7), statistical and data mining tools (Section 8), and dissemination tools (Section 9).

Bioinformatics and Microarray Data Analysis on the Cloud.

PubMed

Calabrese, Barbara; Cannataro, Mario

2016-01-01

High-throughput platforms such as microarray, mass spectrometry, and next-generation sequencing are producing an increasing volume of omics data that needs large data storage and computing power. Cloud computing offers massive scalable computing and storage, data sharing, on-demand anytime and anywhere access to resources and applications, and thus, it may represent the key technology for facing those issues. In fact, in the recent years it has been adopted for the deployment of different bioinformatics solutions and services both in academia and in the industry. Although this, cloud computing presents several issues regarding the security and privacy of data, that are particularly important when analyzing patients data, such as in personalized medicine. This chapter reviews main academic and industrial cloud-based bioinformatics solutions; with a special focus on microarray data analysis solutions and underlines main issues and problems related to the use of such platforms for the storage and analysis of patients data.

Identification of differentially expressed genes and false discovery rate in microarray studies.

PubMed

Gusnanto, Arief; Calza, Stefano; Pawitan, Yudi

2007-04-01

To highlight the development in microarray data analysis for the identification of differentially expressed genes, particularly via control of false discovery rate. The emergence of high-throughput technology such as microarrays raises two fundamental statistical issues: multiplicity and sensitivity. We focus on the biological problem of identifying differentially expressed genes. First, multiplicity arises due to testing tens of thousands of hypotheses, rendering the standard P value meaningless. Second, known optimal single-test procedures such as the t-test perform poorly in the context of highly multiple tests. The standard approach of dealing with multiplicity is too conservative in the microarray context. The false discovery rate concept is fast becoming the key statistical assessment tool replacing the P value. We review the false discovery rate approach and argue that it is more sensible for microarray data. We also discuss some methods to take into account additional information from the microarrays to improve the false discovery rate. There is growing consensus on how to analyse microarray data using the false discovery rate framework in place of the classical P value. Further research is needed on the preprocessing of the raw data, such as the normalization step and filtering, and on finding the most sensitive test procedure.

An evaluation of two-channel ChIP-on-chip and DNA methylation microarray normalization strategies

PubMed Central

2012-01-01

Background The combination of chromatin immunoprecipitation with two-channel microarray technology enables genome-wide mapping of binding sites of DNA-interacting proteins (ChIP-on-chip) or sites with methylated CpG di-nucleotides (DNA methylation microarray). These powerful tools are the gateway to understanding gene transcription regulation. Since the goals of such studies, the sample preparation procedures, the microarray content and study design are all different from transcriptomics microarrays, the data pre-processing strategies traditionally applied to transcriptomics microarrays may not be appropriate. Particularly, the main challenge of the normalization of "regulation microarrays" is (i) to make the data of individual microarrays quantitatively comparable and (ii) to keep the signals of the enriched probes, representing DNA sequences from the precipitate, as distinguishable as possible from the signals of the un-enriched probes, representing DNA sequences largely absent from the precipitate. Results We compare several widely used normalization approaches (VSN, LOWESS, quantile, T-quantile, Tukey's biweight scaling, Peng's method) applied to a selection of regulation microarray datasets, ranging from DNA methylation to transcription factor binding and histone modification studies. Through comparison of the data distributions of control probes and gene promoter probes before and after normalization, and assessment of the power to identify known enriched genomic regions after normalization, we demonstrate that there are clear differences in performance between normalization procedures. Conclusion T-quantile normalization applied separately on the channels and Tukey's biweight scaling outperform other methods in terms of the conservation of enriched and un-enriched signal separation, as well as in identification of genomic regions known to be enriched. T-quantile normalization is preferable as it additionally improves comparability between microarrays. In contrast, popular normalization approaches like quantile, LOWESS, Peng's method and VSN normalization alter the data distributions of regulation microarrays to such an extent that using these approaches will impact the reliability of the downstream analysis substantially. PMID:22276688

Advantages of RNA-seq compared to RNA microarrays for transcriptome profiling of anterior cruciate ligament tears.

PubMed

Rai, Muhammad Farooq; Tycksen, Eric D; Sandell, Linda J; Brophy, Robert H

2018-01-01

Microarrays and RNA-seq are at the forefront of high throughput transcriptome analyses. Since these methodologies are based on different principles, there are concerns about the concordance of data between the two techniques. The concordance of RNA-seq and microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed in clinically derived ligament tissues. To demonstrate the concordance between RNA-seq and microarrays and to assess potential benefits of RNA-seq over microarrays, we assessed differences in transcript expression in anterior cruciate ligament (ACL) tissues based on time-from-injury. ACL remnants were collected from patients with an ACL tear at the time of ACL reconstruction. RNA prepared from torn ACL remnants was subjected to Agilent microarrays (N = 24) and RNA-seq (N = 8). The correlation of biological replicates in RNA-seq and microarrays data was similar (0.98 vs. 0.97), demonstrating that each platform has high internal reproducibility. Correlations between the RNA-seq data and the individual microarrays were low, but correlations between the RNA-seq values and the geometric mean of the microarrays values were moderate. The cross-platform concordance for differentially expressed transcripts or enriched pathways was linearly correlated (r = 0.64). RNA-Seq was superior in detecting low abundance transcripts and differentiating biologically critical isoforms. Additional independent validation of transcript expression was undertaken using microfluidic PCR for selected genes. PCR data showed 100% concordance (in expression pattern) with RNA-seq and microarrays data. These findings demonstrate that RNA-seq has advantages over microarrays for transcriptome profiling of ligament tissues when available and affordable. Furthermore, these findings are likely transferable to other musculoskeletal tissues where tissue collection is challenging and cells are in low abundance. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:484-497, 2018. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc.

A model of binding on DNA microarrays: understanding the combined effect of probe synthesis failure, cross-hybridization, DNA fragmentation and other experimental details of affymetrix arrays

PubMed Central

2012-01-01

Background DNA microarrays are used both for research and for diagnostics. In research, Affymetrix arrays are commonly used for genome wide association studies, resequencing, and for gene expression analysis. These arrays provide large amounts of data. This data is analyzed using statistical methods that quite often discard a large portion of the information. Most of the information that is lost comes from probes that systematically fail across chips and from batch effects. The aim of this study was to develop a comprehensive model for hybridization that predicts probe intensities for Affymetrix arrays and that could provide a basis for improved microarray analysis and probe development. The first part of the model calculates probe binding affinities to all the possible targets in the hybridization solution using the Langmuir isotherm. In the second part of the model we integrate details that are specific to each experiment and contribute to the differences between hybridization in solution and on the microarray. These details include fragmentation, wash stringency, temperature, salt concentration, and scanner settings. Furthermore, the model fits probe synthesis efficiency and target concentration parameters directly to the data. All the parameters used in the model have a well-established physical origin. Results For the 302 chips that were analyzed the mean correlation between expected and observed probe intensities was 0.701 with a range of 0.88 to 0.55. All available chips were included in the analysis regardless of the data quality. Our results show that batch effects arise from differences in probe synthesis, scanner settings, wash strength, and target fragmentation. We also show that probe synthesis efficiencies for different nucleotides are not uniform. Conclusions To date this is the most complete model for binding on microarrays. This is the first model that includes both probe synthesis efficiency and hybridization kinetics/cross-hybridization. These two factors are sequence dependent and have a large impact on probe intensity. The results presented here provide novel insight into the effect of probe synthesis errors on Affymetrix microarrays; furthermore, the algorithms developed in this work provide useful tools for the analysis of cross-hybridization, probe synthesis efficiency, fragmentation, wash stringency, temperature, and salt concentration on microarray intensities. PMID:23270536

Sex-Specific Associations between Particulate Matter Exposure and Gene Expression in Independent Discovery and Validation Cohorts of Middle-Aged Men and Women.

PubMed

Vrijens, Karen; Winckelmans, Ellen; Tsamou, Maria; Baeyens, Willy; De Boever, Patrick; Jennen, Danyel; de Kok, Theo M; Den Hond, Elly; Lefebvre, Wouter; Plusquin, Michelle; Reynders, Hans; Schoeters, Greet; Van Larebeke, Nicolas; Vanpoucke, Charlotte; Kleinjans, Jos; Nawrot, Tim S

2017-04-01

Particulate matter (PM) exposure leads to premature death, mainly due to respiratory and cardiovascular diseases. Identification of transcriptomic biomarkers of air pollution exposure and effect in a healthy adult population. Microarray analyses were performed in 98 healthy volunteers (48 men, 50 women). The expression of eight sex-specific candidate biomarker genes (significantly associated with PM 10 in the discovery cohort and with a reported link to air pollution-related disease) was measured with qPCR in an independent validation cohort (75 men, 94 women). Pathway analysis was performed using Gene Set Enrichment Analysis. Average daily PM 2.5 and PM 10 exposures over 2-years were estimated for each participant's residential address using spatiotemporal interpolation in combination with a dispersion model. Average long-term PM 10 was 25.9 (± 5.4) and 23.7 (± 2.3) μg/m 3 in the discovery and validation cohorts, respectively. In discovery analysis, associations between PM 10 and the expression of individual genes differed by sex. In the validation cohort, long-term PM 10 was associated with the expression of DNAJB5 and EAPP in men and ARHGAP4 ( p = 0.053) in women. AKAP6 and LIMK1 were significantly associated with PM 10 in women, although associations differed in direction between the discovery and validation cohorts. Expression of the eight candidate genes in the discovery cohort differentiated between validation cohort participants with high versus low PM 10 exposure (area under the receiver operating curve = 0.92; 95% CI: 0.85, 1.00; p = 0.0002 in men, 0.86; 95% CI: 0.76, 0.96; p = 0.004 in women). Expression of the sex-specific candidate genes identified in the discovery population predicted PM 10 exposure in an independent cohort of adults from the same area. Confirmation in other populations may further support this as a new approach for exposure assessment, and may contribute to the discovery of molecular mechanisms for PM-induced health effects.

Importance of the efficiency of double-stranded DNA formation in cDNA synthesis for the imprecision of microarray expression analysis.

PubMed

Thormar, Hans G; Gudmundsson, Bjarki; Eiriksdottir, Freyja; Kil, Siyoen; Gunnarsson, Gudmundur H; Magnusson, Magnus Karl; Hsu, Jason C; Jonsson, Jon J

2013-04-01

The causes of imprecision in microarray expression analysis are poorly understood, limiting the use of this technology in molecular diagnostics. Two-dimensional strandness-dependent electrophoresis (2D-SDE) separates nucleic acid molecules on the basis of length and strandness, i.e., double-stranded DNA (dsDNA), single-stranded DNA (ssDNA), and RNA·DNA hybrids. We used 2D-SDE to measure the efficiency of cDNA synthesis and its importance for the imprecision of an in vitro transcription-based microarray expression analysis. The relative amount of double-stranded cDNA formed in replicate experiments that used the same RNA sample template was highly variable, ranging between 0% and 72% of the total DNA. Microarray experiments showed an inverse relationship between the difference between sample pairs in probe variance and the relative amount of dsDNA. Approximately 15% of probes showed between-sample variation (P < 0.05) when the dsDNA percentage was between 12% and 35%. In contrast, only 3% of probes showed between-sample variation when the dsDNA percentage was 69% and 72%. Replication experiments of the 35% dsDNA and 72% dsDNA samples were used to separate sample variation from probe replication variation. The estimated SD of the sample-to-sample variation and of the probe replicates was lower in 72% dsDNA samples than in 35% dsDNA samples. Variation in the relative amount of double-stranded cDNA synthesized can be an important component of the imprecision in T7 RNA polymerase-based microarray expression analysis. © 2013 American Association for Clinical Chemistry

Quantitative Proteomic and Microarray Analysis of the Archaeon Methanosarcina Acetivorans Grown with Acetate Versus Methanol*

PubMed Central

Li, Lingyun; Li, Qingbo; Rohlin, Lars; Kim, UnMi; Salmon, Kirsty; Rejtar, Tomas; Gunsalus, Robert P.; Karger, Barry L.; Ferry, James G.

2008-01-01

Summary Methanosarcina acetivorans strain C2A is an acetate- and methanol-utilizing methane-producing organism for which the genome, the largest yet sequenced among the Archaea, reveals extensive physiological diversity. LC linear ion trap-FTICR mass spectrometry was employed to analyze acetate- vs. methanol-grown cells metabolically labeled with 14N vs. 15N, respectively, to obtain quantitative protein abundance ratios. DNA microarray analyses of acetate- vs. methanol-grown cells was also performed to determine gene expression ratios. The combined approaches were highly complementary, extending the physiological understanding of growth and methanogenesis. Of the 1081 proteins detected, 255 were ≥ 3-fold differentially abundant. DNA microarray analysis revealed 410 genes that were ≥ 2.5-fold differentially expressed of 1972 genes with detected expression. The ratios of differentially abundant proteins were in good agreement with expression ratios of the encoding genes. Taken together, the results suggest several novel roles for electron transport components specific to acetate-grown cells, including two flavodoxins each specific for growth on acetate or methanol. Protein abundance ratios indicated that duplicate CO dehydrogenase/acetyl-CoA complexes function in the conversion of acetate to methane. Surprisingly, the protein abundance and gene expression ratios indicated a general stress response in acetate- vs. methanol-grown cells that included enzymes specific for polyphosphate accumulation and oxidative stress. The microarray analysis identified transcripts of several genes encoding regulatory proteins with identity to the PhoU, MarR, GlnK, and TetR families commonly found in the Bacteria domain. An analysis of neighboring genes suggested roles in controlling phosphate metabolism (PhoU), ammonia assimilation (GlnK), and molybdopterin cofactor biosynthesis (TetR). Finally, the proteomic and microarray results suggested roles for two-component regulatory systems specific for each growth substrate. PMID:17269732

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma

PubMed Central

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-01-01

Objective This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Methods Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Results Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification (P=0.009) or deletion (P=0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly (P=1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Conclusion Chromosomal CNVs may contribute to their transcript expression in cervical cancer. PMID:29312578

BioconductorBuntu: a Linux distribution that implements a web-based DNA microarray analysis server.

PubMed

Geeleher, Paul; Morris, Dermot; Hinde, John P; Golden, Aaron

2009-06-01

BioconductorBuntu is a custom distribution of Ubuntu Linux that automatically installs a server-side microarray processing environment, providing a user-friendly web-based GUI to many of the tools developed by the Bioconductor Project, accessible locally or across a network. System installation is via booting off a CD image or by using a Debian package provided to upgrade an existing Ubuntu installation. In its current version, several microarray analysis pipelines are supported including oligonucleotide, dual-or single-dye experiments, including post-processing with Gene Set Enrichment Analysis. BioconductorBuntu is designed to be extensible, by server-side integration of further relevant Bioconductor modules as required, facilitated by its straightforward underlying Python-based infrastructure. BioconductorBuntu offers an ideal environment for the development of processing procedures to facilitate the analysis of next-generation sequencing datasets. BioconductorBuntu is available for download under a creative commons license along with additional documentation and a tutorial from (http://bioinf.nuigalway.ie).

A benchmark for statistical microarray data analysis that preserves actual biological and technical variance.

PubMed

De Hertogh, Benoît; De Meulder, Bertrand; Berger, Fabrice; Pierre, Michael; Bareke, Eric; Gaigneaux, Anthoula; Depiereux, Eric

2010-01-11

Recent reanalysis of spike-in datasets underscored the need for new and more accurate benchmark datasets for statistical microarray analysis. We present here a fresh method using biologically-relevant data to evaluate the performance of statistical methods. Our novel method ranks the probesets from a dataset composed of publicly-available biological microarray data and extracts subset matrices with precise information/noise ratios. Our method can be used to determine the capability of different methods to better estimate variance for a given number of replicates. The mean-variance and mean-fold change relationships of the matrices revealed a closer approximation of biological reality. Performance analysis refined the results from benchmarks published previously.We show that the Shrinkage t test (close to Limma) was the best of the methods tested, except when two replicates were examined, where the Regularized t test and the Window t test performed slightly better. The R scripts used for the analysis are available at http://urbm-cluster.urbm.fundp.ac.be/~bdemeulder/.

Integrated analysis of chromosome copy number variation and gene expression in cervical carcinoma.

PubMed

Yan, Deng; Yi, Song; Chiu, Wang Chi; Qin, Liu Gui; Kin, Wong Hoi; Kwok Hung, Chung Tony; Linxiao, Han; Wai, Choy Kwong; Yi, Sui; Tao, Yang; Tao, Tang

2017-12-12

This study was conducted to explore chromosomal copy number variations (CNV) and transcript expression and to examine pathways in cervical pathogenesis using genome-wide high resolution microarrays. Genome-wide chromosomal CNVs were investigated in 6 cervical cancer cell lines by Human Genome CGH Microarray Kit (4x44K). Gene expression profiles in cervical cancer cell lines, primary cervical carcinoma and normal cervical epithelium tissues were also studied using the Whole Human Genome Microarray Kit (4x44K). Fifty common chromosomal CNVs were identified in the cervical cancer cell lines. Correlation analysis revealed that gene up-regulation or down-regulation is significantly correlated with genomic amplification ( P =0.009) or deletion ( P =0.006) events. Expression profiles were identified through cluster analysis. Gene annotation analysis pinpointed cell cycle pathways was significantly ( P =1.15E-08) affected in cervical cancer. Common CNVs were associated with cervical cancer. Chromosomal CNVs may contribute to their transcript expression in cervical cancer.

Identifying novel glioma associated pathways based on systems biology level meta-analysis.

PubMed

Hu, Yangfan; Li, Jinquan; Yan, Wenying; Chen, Jiajia; Li, Yin; Hu, Guang; Shen, Bairong

2013-01-01

With recent advances in microarray technology, including genomics, proteomics, and metabolomics, it brings a great challenge for integrating this "-omics" data to analysis complex disease. Glioma is an extremely aggressive and lethal form of brain tumor, and thus the study of the molecule mechanism underlying glioma remains very important. To date, most studies focus on detecting the differentially expressed genes in glioma. However, the meta-analysis for pathway analysis based on multiple microarray datasets has not been systematically pursued. In this study, we therefore developed a systems biology based approach by integrating three types of omics data to identify common pathways in glioma. Firstly, the meta-analysis has been performed to study the overlapping of signatures at different levels based on the microarray gene expression data of glioma. Among these gene expression datasets, 12 pathways were found in GeneGO database that shared by four stages. Then, microRNA expression profiles and ChIP-seq data were integrated for the further pathway enrichment analysis. As a result, we suggest 5 of these pathways could be served as putative pathways in glioma. Among them, the pathway of TGF-beta-dependent induction of EMT via SMAD is of particular importance. Our results demonstrate that the meta-analysis based on systems biology level provide a more useful approach to study the molecule mechanism of complex disease. The integration of different types of omics data, including gene expression microarrays, microRNA and ChIP-seq data, suggest some common pathways correlated with glioma. These findings will offer useful potential candidates for targeted therapeutic intervention of glioma.

Prenatal exposure to escitalopram and/or stress in rats produces limited effects on endocrine, behavioral, or gene expression measures in adult male rats

PubMed Central

Bourke, Chase H.; Stowe, Zachary N.; Neigh, Gretchen N.; Olson, Darin E.; Owens, Michael J.

2013-01-01

Stress and/or antidepressants during pregnancy have been implicated in a wide range of long-term effects in the offspring. We investigated the long-term effects of prenatal stress and/or clinically relevant antidepressant exposure on male adult offspring in a model of the pharmacotherapy of maternal depression. Female Sprague-Dawley rats were implanted with osmotic minipumps that delivered clinically relevant exposure to the antidepressant escitalopram throughout gestation. Subsequently, pregnant females were exposed on gestational days 10–20 to a chronic unpredictable mild stress paradigm. The male offspring were analyzed in adulthood. Baseline physiological measurements were largely unaltered by prenatal manipulations. Behavioral characterization of the male offspring, with or without pre-exposure to an acute stressor, did not reveal any group differences. Prenatal stress exposure resulted in a faster return towards baseline following the peak response to an acute restraint stressor, but not an airpuff startle stressor, in adulthood. Microarray analysis of the hippocampus and hypothalamus comparing all treatment groups revealed no significantly-altered transcripts. Real time PCR of the hippocampus confirmed that several transcripts in the CRFergic, serotonergic, and neural plasticity pathways were unaffected by prenatal exposures. This stress model of maternal depression and its treatment indicate that escitalopram use and/or stress during pregnancy produced no alterations in our measures of male adult behavior or the transcriptome, however prenatal stress exposure resulted in some evidence for increased glucocorticoid negative feedback following an acute restraint stress. Study design should be carefully considered before implications for human health are ascribed to prenatal exposure to stress or antidepressant medication. PMID:23906943

GDF-15 gene expression alterations in human lymphoblastoid cells and peripheral blood lymphocytes following exposure to ionizing radiation

PubMed Central

Li, Shuang; Zhang, Qing-Zhao; Zhang, De-Qin; Feng, Jiang-Bin; Luo, Qun; Lu, Xue; Wang, Xin-Ru; Li, Kun-Peng; Chen, De-Qing; Mu, Xiao-Feng; Gao, Ling; Liu, Qing-Jie

2017-01-01

The identification of rapid, sensitive and high-throughput biomarkers is imperative in order to identify individuals harmed by radiation accidents, and accurately evaluate the absorbed doses of radiation. DNA microarrays have previously been used to evaluate the alterations in growth/differentiation factor 15 (GDF15) gene expression in AHH-1 human lymphoblastoid cells, following exposure to γ-rays. The present study aimed to characterize the relationship between the dose of ionizing radiation and the produced effects in GDF-15 gene expression in AHH-1 cells and human peripheral blood lymphocytes (HPBLs). GDF-15 mRNA and protein expression levels following exposure to γ-rays and neutron radiation were assessed by reverse transcription-quantitative polymerase chain reaction and western blot analysis in AHH-1 cells. In addition, alterations in GDF-15 gene expression in HPBLs following ex vivo irradiation were evaluated. The present results demonstrated that GDF-15 mRNA and protein expression levels in AHH-1 cells were significantly upregulated following exposure to γ-ray doses ranging between 1 and 10 Gy, regardless of the dose rate. A total of 48 h following exposure to neutron radiation, a dose-response relationship was identified in AHH-1 cells at γ-ray doses between 0.4 and 1.6 Gy. GDF-15 mRNA levels in HPBLs were significantly upregulated following exposure to γ-ray doses between 1 and 8 Gy, within 4–48 h following irradiation. These results suggested that significant time- and dose-dependent alterations in GDF-15 mRNA and protein expression occur in AHH-1 cells and HPBLs in the early phases following exposure to ionizing radiation. In conclusion, alterations in GDF-15 gene expression may have potential as a biomarker to evaluate radiation exposure. PMID:28440431

Potential physiological effects of pharmaceutical compounds in Atlantic salmon (Salmo salar) implied by transcriptomic analysis.

PubMed

Hampel, Miriam; Alonso, Esteban; Aparicio, Irene; Bron, James E; Santos, Juan Luis; Taggart, John B; Leaver, Michael J

2010-05-01

Pharmaceuticals are emerging pollutants widely used in everyday urban activities which can be detected in surface, ground, and drinking waters. Their presence is derived from consumption of medicines, disposal of expired medications, release of treated and untreated urban effluents, and from the pharmaceutical industry. Their growing use has become an alarming environmental problem which potentially will become dangerous in the future. However, there is still a lack of knowledge about long-term effects in non-target organisms as well as for human health. Toxicity testing has indicated a relatively low acute toxicity to fish species, but no information is available on possible sublethal effects. This study provides data on the physiological pathways involved in the exposure of Atlantic salmon as representative test species to three pharmaceutical compounds found in ground, surface, and drinking waters based on the evaluation of the xenobiotic-induced impairment resulting in the activation and silencing of specific genes. Individuals of Atlantic salmon (Salmo salar) parr were exposed during 5 days to environmentally relevant concentrations of three representative pharmaceutical compounds with high consumption rates: the analgesic acetaminophen (54.77+/-34.67 microg L(-1)), the anticonvulsant carbamazepine (7.85+/-0.13 microg L(-1)), and the beta-blocker atenolol (11.08+/-7.98 microg L(-1)). Five immature males were selected for transcriptome analysis in brain tissues by means of a 17k salmon cDNA microarray. For this purpose, mRNA was isolated and reverse-transcribed into cDNA which was labeled with fluorescent dyes and hybridized against a common pool to the arrays. Lists of significantly up- and down-regulated candidate genes were submitted to KEGG (Kyoto Encyclopedia of Genes and Genomes) in order to analyze for induced pathways and to evaluate the usefulness of this method in cases of not completely annotated test organisms. Exposure during 5 days to environmentally relevant concentrations of the selected pharmaceutical compounds acetaminophen, carbamazepine, and atenolol produced differences in the expression of 659, 700, and 480 candidate genes, respectively. KEGG annotation numbers (KO annotations) were obtained for between 26.57% and 33.33% of these differently expressed genes per treatment in comparison to non-exposure conditions. Pathways that showed to be induced did not always follow previously reported targets or metabolic routes for the employed treatments; however, several other pathways have been found (four or more features) to be significantly induced. Energy-related pathways have been altered under exposure in all the selected treatments, indicating a possible energy budget leakage due to additional processes resulting from the exposure to environmental contaminants. Observed induction of pathways may indicate additional processes involved in the mode of action of the selected pharmaceuticals which may not have been detected with conventional methods like quantitative PCR in which only suspected features are analyzed punctually for effects. The employment of novel high-throughput screening techniques in combination with global pathway analysis methods, even if the organism is not completely annotated, allows the examination of a much broader range of candidates for potential effects of exposure at the gene level. The continuously growing number of annotations of representative species relevant for environmental quality testing is facilitating pathway analysis processes for not completely annotated organisms. KEGG has shown to be a useful tool for the analysis of induced pathways from data generated by microarray techniques with the selected pharmaceutical contaminants acetaminophen, carbamazepine, and atenolol, but further studies have to be carried out in order to determine if a similar expression pattern in terms of fold change quantity and pathways is observed after long-term exposure. Together with the information obtained in this study, it will then be possible to evaluate the potential risk that the continuous release of these compounds may have on the environment and ecosystem functioning.

High-Throughput Quantification of SH2 Domain-Phosphopeptide Interactions with Cellulose-Peptide Conjugate Microarrays.

PubMed

Engelmann, Brett W

2017-01-01

The Src Homology 2 (SH2) domain family primarily recognizes phosphorylated tyrosine (pY) containing peptide motifs. The relative affinity preferences among competing SH2 domains for phosphopeptide ligands define "specificity space," and underpins many functional pY mediated interactions within signaling networks. The degree of promiscuity exhibited and the dynamic range of affinities supported by individual domains or phosphopeptides is best resolved by a carefully executed and controlled quantitative high-throughput experiment. Here, I describe the fabrication and application of a cellulose-peptide conjugate microarray (CPCMA) platform to the quantitative analysis of SH2 domain specificity space. Included herein are instructions for optimal experimental design with special attention paid to common sources of systematic error, phosphopeptide SPOT synthesis, microarray fabrication, analyte titrations, data capture, and analysis.

Microbial Diagnostic Microarrays for the Detection and Typing of Food- and Water-Borne (Bacterial) Pathogens

PubMed Central

Kostić, Tanja; Sessitsch, Angela

2011-01-01

Reliable and sensitive pathogen detection in clinical and environmental (including food and water) samples is of greatest importance for public health. Standard microbiological methods have several limitations and improved alternatives are needed. Most important requirements for reliable analysis include: (i) specificity; (ii) sensitivity; (iii) multiplexing potential; (iv) robustness; (v) speed; (vi) automation potential; and (vii) low cost. Microarray technology can, through its very nature, fulfill many of these requirements directly and the remaining challenges have been tackled. In this review, we attempt to compare performance characteristics of the microbial diagnostic microarrays developed for the detection and typing of food and water pathogens, and discuss limitations, points still to be addressed and issues specific for the analysis of food, water and environmental samples. PMID:27605332

The pathogenesis shared between abdominal aortic aneurysms and intracranial aneurysms: a microarray analysis.

PubMed

Wang, Wen; Li, Hao; Zhao, Zheng; Wang, Haoyuan; Zhang, Dong; Zhang, Yan; Lan, Qing; Wang, Jiangfei; Cao, Yong; Zhao, Jizong

2018-04-01

Abdominal aortic aneurysms (AAAs) and intracranial saccular aneurysms (IAs) are the most common types of aneurysms. This study was to investigate the common pathogenesis shared between these two kinds of aneurysms. We collected 12 IAs samples and 12 control arteries from the Beijing Tiantan Hospital and performed microarray analysis. In addition, we utilized the microarray datasets of IAs and AAAs from the Gene Expression Omnibus (GEO), in combination with our microarray results, to generate messenger RNA expression profiles for both AAAs and IAs in our study. Functional exploration and protein-protein interaction (PPI) analysis were performed. A total of 727 common genes were differentially expressed (404 was upregulated; 323 was downregulated) for both AAAs and IAs. The GO and pathway analyses showed that the common dysregulated genes were mainly enriched in vascular smooth muscle contraction, muscle contraction, immune response, defense response, cell activation, IL-6 signaling and chemokine signaling pathways, etc. The further protein-protein analysis identified 35 hub nodes, including TNF, IL6, MAPK13, and CCL5. These hub node genes were enriched in inflammatory response, positive regulation of IL-6 production, chemokine signaling pathway, and T/B cell receptor signaling pathway. Our study will gain new insight into the molecular mechanisms for the pathogenesis of both types of aneurysms and provide new therapeutic targets for the patients harboring AAAs and IAs.

Cloud-scale genomic signals processing classification analysis for gene expression microarray data.

PubMed

Harvey, Benjamin; Soo-Yeon Ji

2014-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring inference though analysis of DNA/mRNA sequence data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological inference by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale classification analysis of microarray data using Wavelet thresholding in a Cloud environment to identify significantly expressed features. This paper proposes a novel methodology that uses Wavelet based Denoising to initialize a threshold for determination of significantly expressed genes for classification. Additionally, this research was implemented and encompassed within cloud-based distributed processing environment. The utilization of Cloud computing and Wavelet thresholding was used for the classification 14 tumor classes from the Global Cancer Map (GCM). The results proved to be more accurate than using a predefined p-value for differential expression classification. This novel methodology analyzed Wavelet based threshold features of gene expression in a Cloud environment, furthermore classifying the expression of samples by analyzing gene patterns, which inform us of biological processes. Moreover, enabling researchers to face the present and forthcoming challenges that may arise in the analysis of data in functional genomics of large microarray datasets.

[Differentially expressed genes of cell signal transduction associated with benzene poisoning by cDNA microarray].

PubMed

Wang, Hong; Bi, Yongyi; Tao, Ning; Wang, Chunhong

2005-08-01

To detect the differential expression of cell signal transduction genes associated with benzene poisoning, and to explore the pathogenic mechanisms of blood system damage induced by benzene. Peripheral white blood cell gene expression profile of 7 benzene poisoning patients, including one aplastic anemia, was determined by cDNA microarray. Seven chips from normal workers were served as controls. Cluster analysis of gene expression profile was performed. Among the 4265 target genes, 176 genes associated with cell signal transduction were differentially expressed. 35 up-regulated genes including PTPRC, STAT4, IFITM1 etc were found in at least 6 pieces of microarray; 45 down-regulated genes including ARHB, PPP3CB, CDC37 etc were found in at least 5 pieces of microarray. cDNA microarray technology is an effective technique for screening the differentially expressed genes of cell signal transduction. Disorder in cell signal transduction may play certain role in the pathogenic mechanism of benzene poisoning.

A study of metaheuristic algorithms for high dimensional feature selection on microarray data

NASA Astrophysics Data System (ADS)

Dankolo, Muhammad Nasiru; Radzi, Nor Haizan Mohamed; Sallehuddin, Roselina; Mustaffa, Noorfa Haszlinna

2017-11-01

Microarray systems enable experts to examine gene profile at molecular level using machine learning algorithms. It increases the potentials of classification and diagnosis of many diseases at gene expression level. Though, numerous difficulties may affect the efficiency of machine learning algorithms which includes vast number of genes features comprised in the original data. Many of these features may be unrelated to the intended analysis. Therefore, feature selection is necessary to be performed in the data pre-processing. Many feature selection algorithms are developed and applied on microarray which including the metaheuristic optimization algorithms. This paper discusses the application of the metaheuristics algorithms for feature selection in microarray dataset. This study reveals that, the algorithms have yield an interesting result with limited resources thereby saving computational expenses of machine learning algorithms.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jenny, Matthew J.; Department of Biological Sciences, University of Alabama, Tuscaloosa, AL 35487; Aluru, Neelakanteswar

Although many drugs and environmental chemicals are teratogenic, the mechanisms by which most toxicants disrupt embryonic development are not well understood. MicroRNAs, single-stranded RNA molecules of ∼ 22 nt that regulate protein expression by inhibiting mRNA translation and promoting mRNA sequestration or degradation, are important regulators of a variety of cellular processes including embryonic development and cellular differentiation. Recent studies have demonstrated that exposure to xenobiotics can alter microRNA expression and contribute to the mechanisms by which environmental chemicals disrupt embryonic development. In this study we tested the hypothesis that developmental exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), a well-known teratogen, alters microRNAmore » expression during zebrafish development. We exposed zebrafish embryos to DMSO (0.1%) or TCDD (5 nM) for 1 h at 30 hours post fertilization (hpf) and measured microRNA expression using several methods at 36 and 60 hpf. TCDD caused strong induction of CYP1A at 36 hpf (62-fold) and 60 hpf (135-fold) as determined by real-time RT-PCR, verifying the effectiveness of the exposure. MicroRNA expression profiles were determined using microarrays (Agilent and Exiqon), next-generation sequencing (SOLiD), and real-time RT-PCR. The two microarray platforms yielded results that were similar but not identical; both showed significant changes in expression of miR-451, 23a, 23b, 24 and 27e at 60 hpf. Multiple analyses were performed on the SOLiD sequences yielding a total of 16 microRNAs as differentially expressed by TCDD in zebrafish embryos. However, miR-27e was the only microRNA to be identified as differentially expressed by all three methods (both microarrays, SOLiD sequencing, and real-time RT-PCR). These results suggest that TCDD exposure causes modest changes in expression of microRNAs, including some (miR-451, 23a, 23b, 24 and 27e) that are critical for hematopoiesis and cardiovascular development. -- Highlights: ► Zebrafish embryos were exposed to TCDD at two different developmental timepoints. ► Compared different methods in detecting global changes in microRNA expression. ► TCDD caused significant changes in microRNA expression in zebrafish embryos. ► Differentially expressed microRNAs have roles related to TCDD-induced phenotypes.« less

Transcriptome signatures of p,p´-DDE-induced liver damage in Mus spretus mice.

PubMed

Morales-Prieto, Noelia; Ruiz-Laguna, Julia; Sheehan, David; Abril, Nieves

2018-07-01

The use of DDT (1,1,1-trichloro-2,2-bis(p-chlorophenyl) ethane) in some countries, although regulated, is contributing to an increased worldwide risk of exposure to this organochlorine pesticide or its derivative p,p'-DDE [1,1-dichloro-2,2-bis(p-chlorophenyl) ethylene]. Many studies have associated p,p'-DDE exposure to type 2 diabetes, obesity and alterations of the reproductive system, but their molecular mechanisms of toxicity remain poorly understood. We have addressed this issue by using commercial microarrays based on probes for the entire Mus musculus genome to determine the hepatic transcriptional signatures of p,p'-DDE in the phylogenetically close mouse species Mus spretus. High-stringency hybridization conditions and analysis assured reliable results, which were also verified, in part, by qRT-PCR, immunoblotting and/or enzymatic activity. Our data linked 198 deregulated genes to mitochondrial dysfunction and perturbations of central signaling pathways (kinases, lipids, and retinoic acid) leading to enhanced lipogenesis and aerobic glycolysis, inflammation, cell proliferation and testosterone catabolism and excretion. Alterations of transcript levels of genes encoding enzymes involved in testosterone catabolism and excretion would explain the relationships established between p,p´-DDE exposure and reproductive disorders, obesity and diabetes. Further studies will help to fully understand the molecular basis of p,p´-DDE molecular toxicity in liver and reproductive organs, to identify effective exposure biomarkers and perhaps to design efficient p,p'-DDE exposure counteractive strategies. Copyright © 2018 Elsevier Ltd. All rights reserved.

Transcriptional profiling of primary endometrial epithelial cells following acute HIV-1 exposure reveals gene signatures related to innate immunity.

PubMed

Zahoor, Muhammad Atif; Woods, Matthew William; Dizzell, Sara; Nazli, Aisha; Mueller, Kristen M; Nguyen, Philip V; Verschoor, Chris P; Kaushic, Charu

2018-04-01

Genital epithelial cells (GECs) line the mucosal surface of the female genital tract (FGT) and are the first cells that interface with both commensal microbiota and sexually transmitted pathogens. Despite the protective barrier formed by GECs, the FGT is a major site of HIV-1 infection. This highlights the importance of studying the interaction of HIV-1 and GECs. Using microarray analysis, we characterized the transcriptional profile of primary endometrial GECs grown in the presence or absence of physiological levels of E2 (10 -9  mol/L) or P4 (10 -7  mol/L) following acute exposure to HIV-1 for 6 hours. Acute exposure of primary endometrial GECs to HIV-1 resulted in the expression of genes related to inflammation, plasminogen activation, adhesion and diapedesis and interferon response. Interestingly, exposure to HIV-1 in the presence of E2 and P4 resulted in differential transcriptional profiles, suggesting that the response of primary endometrial GECs to HIV-1 exposure is modulated by female sex hormones. The gene expression signature of endometrial GECs indicates that the response of these cells may be key to determining host susceptibility to HIV-1 and that sex hormones modulate these interactions. This study allows us to explore possible mechanisms that explain the hormone-mediated fluctuation of HIV-1 susceptibility in women. © 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Genome-wide identification of WRKY family genes and their response to cold stress in Vitis vinifera

PubMed Central

2014-01-01

Background WRKY transcription factors are one of the largest families of transcriptional regulators in plants. WRKY genes are not only found to play significant roles in biotic and abiotic stress response, but also regulate growth and development. Grapevine (Vitis vinifera) production is largely limited by stressful climate conditions such as cold stress and the role of WRKY genes in the survival of grapevine under these conditions remains unknown. Results We identified a total of 59 VvWRKYs from the V. vinifera genome, belonging to four subgroups according to conserved WRKY domains and zinc-finger structure. The majority of VvWRKYs were expressed in more than one tissue among the 7 tissues examined which included young leaves, mature leaves, tendril, stem apex, root, young fruits and ripe fruits. Publicly available microarray data suggested that a subset of VvWRKYs was activated in response to diverse stresses. Quantitative real-time PCR (qRT-PCR) results demonstrated that the expression levels of 36 VvWRKYs are changed following cold exposure. Comparative analysis was performed on data from publicly available microarray experiments, previous global transcriptome analysis studies, and qRT-PCR. We identified 15 VvWRKYs in at least two of these databases which may relate to cold stress. Among them, the transcription of three genes can be induced by exogenous ABA application, suggesting that they can be involved in an ABA-dependent signaling pathway in response to cold stress. Conclusions We identified 59 VvWRKYs from the V. vinifera genome and 15 of them showed cold stress-induced expression patterns. These genes represented candidate genes for future functional analysis of VvWRKYs involved in the low temperature-related signal pathways in grape. PMID:24755338

Subchronic effects of valproic acid on gene expression profiles for lipid metabolism in mouse liver

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lee, Min-Ho; Kim, Mingoo; Lee, Byung-Hoon

2008-02-01

Valproic acid (VPA) is used clinically to treat epilepsy, however it induces hepatotoxicity such as microvesicular steatosis. Acute hepatotoxicity of VPA has been well documented by biochemical studies and microarray analysis, but little is known about the chronic effects of VPA in the liver. In the present investigation, we profiled gene expression patterns in the mouse liver after subchronic treatment with VPA. VPA was administered orally at a dose of 100 mg/kg/day or 500 mg/kg/day to ICR mice, and the livers were obtained after 1, 2, or 4 weeks. The activities of serum liver enzymes did not change, whereas triglyceridemore » concentration increased significantly. Microarray analysis revealed that 1325 genes of a set of 32,996 individual genes were VPA responsive when examined by two-way ANOVA (P < 0.05) and fold change (> 1.5). Consistent with our previous results obtained using an acute VPA exposure model (Lee et al., Toxicol Appl Pharmacol. 220:45-59, 2007), the most significantly over-represented biological terms for these genes included lipid, fatty acid, and steroid metabolism. Biological pathway analysis suggests that the genes responsible for increased biosynthesis of cholesterol and triglyceride, and for decreased fatty acid {beta}-oxidation contribute to the abnormalities in lipid metabolism induced by subchronic VPA treatment. A comparison of the VPA-responsive genes in the acute and subchronic models extracted 15 commonly altered genes, such as Cyp4a14 and Adpn, which may have predictive power to distinguish the mode of action of hepatotoxicants. Our data provide a better understanding of the molecular mechanisms of VPA-induced hepatotoxicity and useful information to predict steatogenic hepatotoxicity.« less

Selection of higher order regression models in the analysis of multi-factorial transcription data.

PubMed

Prazeres da Costa, Olivia; Hoffman, Arthur; Rey, Johannes W; Mansmann, Ulrich; Buch, Thorsten; Tresch, Achim

2014-01-01

Many studies examine gene expression data that has been obtained under the influence of multiple factors, such as genetic background, environmental conditions, or exposure to diseases. The interplay of multiple factors may lead to effect modification and confounding. Higher order linear regression models can account for these effects. We present a new methodology for linear model selection and apply it to microarray data of bone marrow-derived macrophages. This experiment investigates the influence of three variable factors: the genetic background of the mice from which the macrophages were obtained, Yersinia enterocolitica infection (two strains, and a mock control), and treatment/non-treatment with interferon-γ. We set up four different linear regression models in a hierarchical order. We introduce the eruption plot as a new practical tool for model selection complementary to global testing. It visually compares the size and significance of effect estimates between two nested models. Using this methodology we were able to select the most appropriate model by keeping only relevant factors showing additional explanatory power. Application to experimental data allowed us to qualify the interaction of factors as either neutral (no interaction), alleviating (co-occurring effects are weaker than expected from the single effects), or aggravating (stronger than expected). We find a biologically meaningful gene cluster of putative C2TA target genes that appear to be co-regulated with MHC class II genes. We introduced the eruption plot as a tool for visual model comparison to identify relevant higher order interactions in the analysis of expression data obtained under the influence of multiple factors. We conclude that model selection in higher order linear regression models should generally be performed for the analysis of multi-factorial microarray data.

microRNA-206 in Rat Medial Prefrontal Cortex Regulates BDNF Expression and Alcohol Drinking

PubMed Central

Barbier, Estelle; Flanigan, Meghan; Solomon, Matthew; Pincus, Alexandra; Pilling, Andrew; Sun, Hui; Schank, Jesse R.; King, Courtney; Heilig, Markus

2014-01-01

Escalation of voluntary alcohol consumption is a hallmark of alcoholism, but its neural substrates remain unknown. In rats, escalation occurs following prolonged exposure to cycles of alcohol intoxication, and is associated with persistent, wide-ranging changes in gene expression within the medial prefrontal cortex (mPFC). Here, we examined whether induction of microRNA (miR) 206 in mPFC contributes to escalated alcohol consumption. Following up on a microarray screen, quantitative real-time reverse transcription PCR (qPCR) confirmed that a history of dependence results in persistent (>3weeks) up-regulation of miR-206 expression in the mPFC, but not in the ventral tegmental area, amygdala, or nucleus accumbens. Viral-mediated overexpression of miR-206 in the mPFC of nondependent rats reproduced the escalation of alcohol self-administration seen following a history of dependence and significantly inhibited BDNF expression. Bioinformatic analysis identified three conserved target sites for miR-206 in the 3′-UTR of the rat BDNF transcript. Accordingly, BDNF was downregulated in post-dependent rats on microarray analysis, and this was confirmed by qPCR. In vitro, BDNF expression was repressed by miR-206 but not miR-9 in a 3′-UTR reporter assay, confirming BDNF as a functional target of miR-206. Mutation analysis showed that repression was dependent on the presence of all three miR-206 target sites in the BDNF 3′-UTR. Inhibition of miR-206 expression in differentiated rat cortical primary neurons significantly increased secreted levels of BDNF. In conclusion, recruitment of miR-206 in the mPFC contributes to escalated alcohol consumption following a history of dependence, with BDNF as a possible mediator of its action. PMID:24672003

Decreased Fibronectin Production Significantly Contributes to Dysregulated Repair of Asthmatic Epithelium

PubMed Central

Kicic, Anthony; Hallstrand, Teal S.; Sutanto, Erika N.; Stevens, Paul T.; Kobor, Michael S.; Taplin, Christopher; Paré, Peter D.; Beyer, Richard P.; Stick, Stephen M.; Knight, Darryl A.

2010-01-01

Rationale: Damage to airway epithelium is followed by deposition of extracellular matrix (ECM) and migration of adjacent epithelial cells. We have shown that epithelial cells from children with asthma fail to heal a wound in vitro. Objectives: To determine whether dysregulated ECM production by the epithelium plays a role in aberrant repair in asthma. Methods: Airway epithelial cells (AEC) from children with asthma (n = 36), healthy atopic control subjects (n = 23), and healthy nonatopic control subjects (n = 53) were investigated by microarray, gene expression and silencing, transcript regulation analysis, and ability to close mechanical wounds. Measurements and Main Results: Time to repair a mechanical wound in vitro by AEC from healthy and atopic children was not significantly different and both were faster than AEC from children with asthma. Microarray analysis revealed differential expression of multiple gene sets associated with repair and remodeling in asthmatic AEC. Fibronectin (FN) was the only ECM component whose expression was significantly lower in asthmatic AEC. Expression differences were verified by quantitative polymerase chain reaction and ELISA, and reduced FN expression persisted in asthmatic cells over passage. Silencing of FN expression in nonasthmatic AEC inhibited wound repair, whereas addition of FN to asthmatic AEC restored reparative capacity. Asthmatic AEC failed to synthesize FN in response to wounding or cytokine/growth factor stimulation. Exposure to 5′, 2′deoxyazacytidine had no effect on FN expression and subsequent analysis of the FN promoter did not show evidence of DNA methylation. Conclusions: These data show that the reduced capacity of asthmatic epithelial cells to secrete FN is an important contributor to the dysregulated AEC repair observed in these cells. PMID:20110557

microRNA-206 in rat medial prefrontal cortex regulates BDNF expression and alcohol drinking.

PubMed

Tapocik, Jenica D; Barbier, Estelle; Flanigan, Meghan; Solomon, Matthew; Pincus, Alexandra; Pilling, Andrew; Sun, Hui; Schank, Jesse R; King, Courtney; Heilig, Markus

2014-03-26

Escalation of voluntary alcohol consumption is a hallmark of alcoholism, but its neural substrates remain unknown. In rats, escalation occurs following prolonged exposure to cycles of alcohol intoxication, and is associated with persistent, wide-ranging changes in gene expression within the medial prefrontal cortex (mPFC). Here, we examined whether induction of microRNA (miR) 206 in mPFC contributes to escalated alcohol consumption. Following up on a microarray screen, quantitative real-time reverse transcription PCR (qPCR) confirmed that a history of dependence results in persistent (>3weeks) up-regulation of miR-206 expression in the mPFC, but not in the ventral tegmental area, amygdala, or nucleus accumbens. Viral-mediated overexpression of miR-206 in the mPFC of nondependent rats reproduced the escalation of alcohol self-administration seen following a history of dependence and significantly inhibited BDNF expression. Bioinformatic analysis identified three conserved target sites for miR-206 in the 3'-UTR of the rat BDNF transcript. Accordingly, BDNF was downregulated in post-dependent rats on microarray analysis, and this was confirmed by qPCR. In vitro, BDNF expression was repressed by miR-206 but not miR-9 in a 3'-UTR reporter assay, confirming BDNF as a functional target of miR-206. Mutation analysis showed that repression was dependent on the presence of all three miR-206 target sites in the BDNF 3'-UTR. Inhibition of miR-206 expression in differentiated rat cortical primary neurons significantly increased secreted levels of BDNF. In conclusion, recruitment of miR-206 in the mPFC contributes to escalated alcohol consumption following a history of dependence, with BDNF as a possible mediator of its action.

Microarray analysis identified Puccinia striiformis f. sp. tritici genes involved in infection and sporulation.

USDA-ARS?s Scientific Manuscript database

Puccinia striiformis f. sp. tritici (Pst) causes stripe rust, one of the most important diseases of wheat worldwide. To identify Pst genes involved in infection and sporulation, a custom oligonucleotide Genechip was made using sequences of 442 genes selected from Pst cDNA libraries. Microarray analy...

Clear cell papillary renal cell carcinoma: a chromosomal microarray analysis of two cases using a novel Molecular Inversion Probe (MIP) technology.

PubMed

Alexiev, Borislav A; Zou, Ying S

2014-12-01

Chromosomal microarray analysis using novel Molecular Inversion Probe (MIP) technology demonstrated 2,570 kb copy neutral LOH of 10q11.22 in two clear cell papillary renal cell carcinomas. In addition, one of the tumors had a big 29,784 kb deletion of 13q11-q14.2. There were two variants of unknown significance, a 2,509 kb gain of Xp22.33 and a 257 kb homozygous deletion of 8p11.22. The somatic mutation panel containing 74 mutations in nine genes did not reveal any mutations. Besides identification of submicroscopic duplications or deletions, SNP microarrays can reveal abnormal allelic imbalances including LOH and copy neutral LOH, which cannot be recognized by chromosome, FISH, and non-SNP microarray arrays. To the best of our knowledge, this is the first study demonstrating copy neutral LOH of 10q11.22 in clear cell papillary renal cell carcinomas using the new MIP SNP OncoScan FFPE Assay Kit on formalin-fixed paraffin-embedded tumor samples. Copyright © 2014 Elsevier GmbH. All rights reserved.

A Unique Procedure to Identify Cell Surface Markers Through a Spherical Self-Organizing Map Applied to DNA Microarray Analysis.

PubMed

Sugii, Yuh; Kasai, Tomonari; Ikeda, Masashi; Vaidyanath, Arun; Kumon, Kazuki; Mizutani, Akifumi; Seno, Akimasa; Tokutaka, Heizo; Kudoh, Takayuki; Seno, Masaharu

2016-01-01

To identify cell-specific markers, we designed a DNA microarray platform with oligonucleotide probes for human membrane-anchored proteins. Human glioma cell lines were analyzed using microarray and compared with normal and fetal brain tissues. For the microarray analysis, we employed a spherical self-organizing map, which is a clustering method suitable for the conversion of multidimensional data into two-dimensional data and displays the relationship on a spherical surface. Based on the gene expression profile, the cell surface characteristics were successfully mirrored onto the spherical surface, thereby distinguishing normal brain tissue from the disease model based on the strength of gene expression. The clustered glioma-specific genes were further analyzed by polymerase chain reaction procedure and immunocytochemical staining of glioma cells. Our platform and the following procedure were successfully demonstrated to categorize the genes coding for cell surface proteins that are specific to glioma cells. Our assessment demonstrates that a spherical self-organizing map is a valuable tool for distinguishing cell surface markers and can be employed in marker discovery studies for the treatment of cancer.

Systematic analysis of microarray datasets to identify Parkinson's disease‑associated pathways and genes.

PubMed

Feng, Yinling; Wang, Xuefeng

2017-03-01

In order to investigate commonly disturbed genes and pathways in various brain regions of patients with Parkinson's disease (PD), microarray datasets from previous studies were collected and systematically analyzed. Different normalization methods were applied to microarray datasets from different platforms. A strategy combining gene co‑expression networks and clinical information was adopted, using weighted gene co‑expression network analysis (WGCNA) to screen for commonly disturbed genes in different brain regions of patients with PD. Functional enrichment analysis of commonly disturbed genes was performed using the Database for Annotation, Visualization, and Integrated Discovery (DAVID). Co‑pathway relationships were identified with Pearson's correlation coefficient tests and a hypergeometric distribution‑based test. Common genes in pathway pairs were selected out and regarded as risk genes. A total of 17 microarray datasets from 7 platforms were retained for further analysis. Five gene coexpression modules were identified, containing 9,745, 736, 233, 101 and 93 genes, respectively. One module was significantly correlated with PD samples and thus the 736 genes it contained were considered to be candidate PD‑associated genes. Functional enrichment analysis demonstrated that these genes were implicated in oxidative phosphorylation and PD. A total of 44 pathway pairs and 52 risk genes were revealed, and a risk gene pathway relationship network was constructed. Eight modules were identified and were revealed to be associated with PD, cancers and metabolism. A number of disturbed pathways and risk genes were unveiled in PD, and these findings may help advance understanding of PD pathogenesis.

Interactions of a pesticide/heavy metal mixture in marine bivalves: a transcriptomic assessment

PubMed Central

2011-01-01

Background Mixtures of chemicals present in aquatic environments may elicit toxicity due to additive or synergistic effects among the constituents or, vice versa, the adverse outcome may be reduced by antagonistic interactions. Deviations from additivity should be explained either by the perturbations of toxicokinetic parameters and/or chemical toxicodynamics. We addressed this important question in marine mussels exposed subchronically to a binary mixture made of two wide-spread pollutants: the heavy metal nickel and the organic phosphorus pesticide Chlorpyrifos. To this aim, we carried out in tissues of Mytius galloprovincialis (Lam) a systems approach based on the evaluation and integration of different disciplines, i.e. high throughput gene expression profiling, functional genomics, stress biomakers and toxicokinetics. Results Cellular and tissue biomarkers, viz. digestive gland lysosomal membrane stability, lysosomal/cytosol volume ratio, neutral lipid content and gill acetylcholinesterase activity were, in general, altered by either the exposure to nickel and Chlorpyrifos. However, their joint action rendered (i) an overall decrease of the stress syndrome level, as evaluated through an expert system integrating biomarkers and (ii) statistically significant antagonistic deviations from the reference model systems to predict mixture toxicity. While toxicokinetic modeling did not explain mixture interactions, gene expression profiling and further Gene Ontology-based functional genomics analysis provided clues that the decrement of toxicity may arise from the development of specific toxicodynamics. Multivariate statistics of microarray data (238 genes in total, representing about 14% of the whole microarray catalogue) showed two separate patterns for the single chemicals: the one belonging to the heavy metal -135 differentially expressed genes (DEGs) was characterized by the modulation of transcript levels involved in nucleic acid metabolism, cell proliferation and lipid metabolic processes. Chlorpyrifos exposure (43 DEGs) yielded a molecular signature which was biased towards carbohydrate catabolism (indeed, chitin metabolism) and developmental processes. The exposure to the mixture (103 DEGs) elicited a composite complex profile which encompassed the core properties of the pesticide but also a relevant set of unique features. Finally, the relative mRNA abundance of twelve genes was followed by Q-PCR to either confirm or complement microarray data. These results, in general, were compatible with those from arrays and indeed confirmed the association of the relative abundance of two GM-2 ganglioside activator genes in the development of the hyperlipidosis syndrome observed in digestive gland lysosomes of single chemical exposed mussels. Conclusion The transcriptomic assessment fitted with biological data to indicate the occurrence of different toxicodynamic events and, in general, a decrease of toxicity, driven by the mitigation or even abolition of lysosomal responses. Furthermore, our results emphasized the importance of the application of mechanistic approaches and the power of systems assessment to study toxicological responses in ecologically relevant organisms. PMID:21496282

Interactions of a pesticide/heavy metal mixture in marine bivalves: a transcriptomic assessment.

PubMed

Dondero, Francesco; Banni, Mohamed; Negri, Alessandro; Boatti, Lara; Dagnino, Alessandro; Viarengo, Aldo

2011-04-16

Mixtures of chemicals present in aquatic environments may elicit toxicity due to additive or synergistic effects among the constituents or, vice versa, the adverse outcome may be reduced by antagonistic interactions. Deviations from additivity should be explained either by the perturbations of toxicokinetic parameters and/or chemical toxicodynamics. We addressed this important question in marine mussels exposed subchronically to a binary mixture made of two wide-spread pollutants: the heavy metal nickel and the organic phosphorus pesticide Chlorpyrifos. To this aim, we carried out in tissues of Mytius galloprovincialis (Lam) a systems approach based on the evaluation and integration of different disciplines, i.e. high throughput gene expression profiling, functional genomics, stress biomakers and toxicokinetics. Cellular and tissue biomarkers, viz. digestive gland lysosomal membrane stability, lysosomal/cytosol volume ratio, neutral lipid content and gill acetylcholinesterase activity were, in general, altered by either the exposure to nickel and Chlorpyrifos. However, their joint action rendered (i) an overall decrease of the stress syndrome level, as evaluated through an expert system integrating biomarkers and (ii) statistically significant antagonistic deviations from the reference model systems to predict mixture toxicity. While toxicokinetic modeling did not explain mixture interactions, gene expression profiling and further Gene Ontology-based functional genomics analysis provided clues that the decrement of toxicity may arise from the development of specific toxicodynamics. Multivariate statistics of microarray data (238 genes in total, representing about 14% of the whole microarray catalogue) showed two separate patterns for the single chemicals: the one belonging to the heavy metal -135 differentially expressed genes (DEGs) was characterized by the modulation of transcript levels involved in nucleic acid metabolism, cell proliferation and lipid metabolic processes. Chlorpyrifos exposure (43 DEGs) yielded a molecular signature which was biased towards carbohydrate catabolism (indeed, chitin metabolism) and developmental processes. The exposure to the mixture (103 DEGs) elicited a composite complex profile which encompassed the core properties of the pesticide but also a relevant set of unique features. Finally, the relative mRNA abundance of twelve genes was followed by Q-PCR to either confirm or complement microarray data. These results, in general, were compatible with those from arrays and indeed confirmed the association of the relative abundance of two GM-2 ganglioside activator genes in the development of the hyperlipidosis syndrome observed in digestive gland lysosomes of single chemical exposed mussels. The transcriptomic assessment fitted with biological data to indicate the occurrence of different toxicodynamic events and, in general, a decrease of toxicity, driven by the mitigation or even abolition of lysosomal responses. Furthermore, our results emphasized the importance of the application of mechanistic approaches and the power of systems assessment to study toxicological responses in ecologically relevant organisms.

Neonicotinoid Insecticides Alter the Gene Expression Profile of Neuron-Enriched Cultures from Neonatal Rat Cerebellum

PubMed Central

Kimura-Kuroda, Junko; Nishito, Yasumasa; Yanagisawa, Hiroko; Kuroda, Yoichiro; Komuta, Yukari; Kawano, Hitoshi; Hayashi, Masaharu

2016-01-01

Neonicotinoids are considered safe because of their low affinities to mammalian nicotinic acetylcholine receptors (nAChRs) relative to insect nAChRs. However, because of importance of nAChRs in mammalian brain development, there remains a need to establish the safety of chronic neonicotinoid exposures with regards to children’s health. Here we examined the effects of long-term (14 days) and low dose (1 μM) exposure of neuron-enriched cultures from neonatal rat cerebellum to nicotine and two neonicotinoids: acetamiprid and imidacloprid. Immunocytochemistry revealed no differences in the number or morphology of immature neurons or glial cells in any group versus untreated control cultures. However, a slight disturbance in Purkinje cell dendritic arborization was observed in the exposed cultures. Next we performed transcriptome analysis on total RNAs using microarrays, and identified significant differential expression (p < 0.05, q < 0.05, ≥1.5 fold) between control cultures versus nicotine-, acetamiprid-, or imidacloprid-exposed cultures in 34, 48, and 67 genes, respectively. Common to all exposed groups were nine genes essential for neurodevelopment, suggesting that chronic neonicotinoid exposure alters the transcriptome of the developing mammalian brain in a similar way to nicotine exposure. Our results highlight the need for further careful investigations into the effects of neonicotinoids in the developing mammalian brain. PMID:27782041

Transient and permanent changes in DNA methylation patterns in inorganic arsenic-mediated epithelial-to-mesenchymal transition

PubMed Central

Eckstein, Meredith; Rea, Matthew; Fondufe-Mittendorf, Yvonne N.

2017-01-01

Chronic low dose inorganic arsenic exposure causes cells to take on an epithelial-to-mesenchymal phenotype, which is a crucial process in carcinogenesis. Inorganic arsenic is not a mutagen and thus epigenetic alterations have been implicated in this process. Indeed, during the epithelial-to-mesenchymal transition, morphologic changes to cells correlate with changes in chromatin structure and gene expression, ultimately driving this process. However, studies on the effects of inorganic arsenic exposure/withdrawal on the epithelial-to-mesenchymal transition and the impact of epigenetic alterations in this process are limited. In this study we used high-resolution microarray analysis to measure the changes in DNA methylation in cells undergoing inorganic arsenic-induced epithelial-to-mesenchymal transition, and on the reversal of this process, after removal of the inorganic arsenic exposure. We found that cells exposed to chronic, low-dose inorganic arsenic exposure showed 30,530 sites were differentially methylated, and with inorganic arsenic withdrawal several differential methylated sites were reversed, albeit not completely. Furthermore, these changes in DNA methylation mainly correlated with changes in gene expression at most sites tested but not at all. This study suggests that DNA methylation changes on gene expression are not clear-cut and provide a platform to begin to uncover the relationship between DNA methylation and gene expression, specifically within the context of inorganic arsenic treatment. PMID:28336213

Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline

PubMed Central

Rahmatallah, Yasir; Emmert-Streib, Frank

2016-01-01

Transcriptome sequencing (RNA-seq) is gradually replacing microarrays for high-throughput studies of gene expression. The main challenge of analyzing microarray data is not in finding differentially expressed genes, but in gaining insights into the biological processes underlying phenotypic differences. To interpret experimental results from microarrays, gene set analysis (GSA) has become the method of choice, in particular because it incorporates pre-existing biological knowledge (in a form of functionally related gene sets) into the analysis. Here we provide a brief review of several statistically different GSA approaches (competitive and self-contained) that can be adapted from microarrays practice as well as those specifically designed for RNA-seq. We evaluate their performance (in terms of Type I error rate, power, robustness to the sample size and heterogeneity, as well as the sensitivity to different types of selection biases) on simulated and real RNA-seq data. Not surprisingly, the performance of various GSA approaches depends only on the statistical hypothesis they test and does not depend on whether the test was developed for microarrays or RNA-seq data. Interestingly, we found that competitive methods have lower power as well as robustness to the samples heterogeneity than self-contained methods, leading to poor results reproducibility. We also found that the power of unsupervised competitive methods depends on the balance between up- and down-regulated genes in tested gene sets. These properties of competitive methods have been overlooked before. Our evaluation provides a concise guideline for selecting GSA approaches, best performing under particular experimental settings in the context of RNA-seq. PMID:26342128

Comparison of RNA-seq and microarray-based models for clinical endpoint prediction.

PubMed

Zhang, Wenqian; Yu, Ying; Hertwig, Falk; Thierry-Mieg, Jean; Zhang, Wenwei; Thierry-Mieg, Danielle; Wang, Jian; Furlanello, Cesare; Devanarayan, Viswanath; Cheng, Jie; Deng, Youping; Hero, Barbara; Hong, Huixiao; Jia, Meiwen; Li, Li; Lin, Simon M; Nikolsky, Yuri; Oberthuer, André; Qing, Tao; Su, Zhenqiang; Volland, Ruth; Wang, Charles; Wang, May D; Ai, Junmei; Albanese, Davide; Asgharzadeh, Shahab; Avigad, Smadar; Bao, Wenjun; Bessarabova, Marina; Brilliant, Murray H; Brors, Benedikt; Chierici, Marco; Chu, Tzu-Ming; Zhang, Jibin; Grundy, Richard G; He, Min Max; Hebbring, Scott; Kaufman, Howard L; Lababidi, Samir; Lancashire, Lee J; Li, Yan; Lu, Xin X; Luo, Heng; Ma, Xiwen; Ning, Baitang; Noguera, Rosa; Peifer, Martin; Phan, John H; Roels, Frederik; Rosswog, Carolina; Shao, Susan; Shen, Jie; Theissen, Jessica; Tonini, Gian Paolo; Vandesompele, Jo; Wu, Po-Yen; Xiao, Wenzhong; Xu, Joshua; Xu, Weihong; Xuan, Jiekun; Yang, Yong; Ye, Zhan; Dong, Zirui; Zhang, Ke K; Yin, Ye; Zhao, Chen; Zheng, Yuanting; Wolfinger, Russell D; Shi, Tieliu; Malkas, Linda H; Berthold, Frank; Wang, Jun; Tong, Weida; Shi, Leming; Peng, Zhiyu; Fischer, Matthias

2015-06-25

Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based applications beyond the limitations of microarrays, we sought to systematically evaluate the performance of RNA-seq-based and microarray-based classifiers in this MAQC-III/SEQC study for clinical endpoint prediction using neuroblastoma as a model. We generate gene expression profiles from 498 primary neuroblastomas using both RNA-seq and 44 k microarrays. Characterization of the neuroblastoma transcriptome by RNA-seq reveals that more than 48,000 genes and 200,000 transcripts are being expressed in this malignancy. We also find that RNA-seq provides much more detailed information on specific transcript expression patterns in clinico-genetic neuroblastoma subgroups than microarrays. To systematically compare the power of RNA-seq and microarray-based models in predicting clinical endpoints, we divide the cohort randomly into training and validation sets and develop 360 predictive models on six clinical endpoints of varying predictability. Evaluation of factors potentially affecting model performances reveals that prediction accuracies are most strongly influenced by the nature of the clinical endpoint, whereas technological platforms (RNA-seq vs. microarrays), RNA-seq data analysis pipelines, and feature levels (gene vs. transcript vs. exon-junction level) do not significantly affect performances of the models. We demonstrate that RNA-seq outperforms microarrays in determining the transcriptomic characteristics of cancer, while RNA-seq and microarray-based models perform similarly in clinical endpoint prediction. Our findings may be valuable to guide future studies on the development of gene expression-based predictive models and their implementation in clinical practice.

Dynamics of 17alpha-ethynylestradiol exposure in rainbow trout (Oncorhynchus mykiss): absorption, tissue distribution, and hepatic gene expression pattern.

PubMed

Skillman, Ann D; Nagler, James J; Hook, Sharon E; Small, Jack A; Schultz, Irvin R

2006-11-01

17alpha-Ethynylestradiol (EE2) is a synthetic estrogen identified in sewage effluents. To understand better the absorption kinetics of EE2 and the induction of vitellogenin (VTG) and estrogen receptor alpha (ERalpha) mRNA, we subjected male rainbow trout (Onchorynchus mykiss) to continuous water exposures of 125 ng/L of EE2 for up to 61 d. Trout were either repetitively sampled for blood plasma or serially killed at selected time intervals. Vitellogenin, ERalpha mRNA, and EE2 were measured using enzyme-linked immunosorbent assay and using quantitative polymerase chain reaction and gas chromatography-mass spectrometry, respectively. In separate experiments, trout were exposed to EE2 for 7 d, and hepatic gene expression was assessed using a low- and high-density cDNA microarray. The EE2 was rapidly absorbed by the trout, with an apparent equilibrium at 16 h in plasma and liver. The ERalpha mRNA levels also increased rapidly, reaching near-peak levels by 48 h. In contrast, plasma levels of VTG continuously increased for 19 d. After 61 d, tissues with the highest levels of VTG were the liver, kidney, and testes. Microarray-based gene expression studies provided unexpected results. In some cases, known estrogen-responsive genes (e.g., ERalpha) were unresponsive, whereas many of the genes that have no apparent link to estrogen function or EE2 toxicity were significantly altered in expression. Of the two microarray approaches tested in the present study, the high-density array appeared to be superior because of the improved quality of the hybridization signal and the robustness of the response in terms of the number of genes identified as being EE2 responsive.

DYNAMICS OF 17α-ETHYNYLESTRADIOL EXPOSURE IN RAINBOW TROUT (ONCORHYNCHUS MYKISS): ABSORPTION, TISSUE DISTRIBUTION, AND HEPATIC GENE EXPRESSION PATTERN

PubMed Central

Skillman, Ann D.; Nagler, James J.; Hook, Sharon E.; Small, Jack A.; Schultz, Irvin R.

2008-01-01

17α-Ethynylestradiol (EE2) is a synthetic estrogen identified in sewage effluents. To understand better the absorption kinetics of EE2 and the induction of vitellogenin (VTG) and estrogen receptor α (ERα) mRNA, we subjected male rainbow trout (Onchorynchus mykiss) to continuous water exposures of 125 ng/L of EE2 for up to 61 d. Trout were either repetitively sampled for blood plasma or serially killed at selected time intervals. Vitellogenin, ERα mRNA, and EE2 were measured using enzyme-linked immunosorbent assay and using quantitative polymerase chain reaction and gas chromatography–mass spectrometry, respectively. In separate experiments, trout were exposed to EE2 for 7 d, and hepatic gene expression was assessed using a low- and high-density cDNA microarray. The EE2 was rapidly absorbed by the trout, with an apparent equilibrium at 16 h in plasma and liver. The ERα mRNA levels also increased rapidly, reaching near-peak levels by 48 h. In contrast, plasma levels of VTG continuously increased for 19 d. After 61 d, tissues with the highest levels of VTG were the liver, kidney, and testes. Microarray-based gene expression studies provided unexpected results. In some cases, known estrogen-responsive genes (e.g., ERα) were unresponsive, whereas many of the genes that have no apparent link to estrogen function or EE2 toxicity were significantly altered in expression. Of the two microarray approaches tested in the present study, the high-density array appeared to be superior because of the improved quality of the hybridization signal and the robustness of the response in terms of the number of genes identified as being EE2 responsive. PMID:17089724

A comprehensive sensitivity analysis of microarray breast cancer classification under feature variability

PubMed Central

2009-01-01

Background Large discrepancies in signature composition and outcome concordance have been observed between different microarray breast cancer expression profiling studies. This is often ascribed to differences in array platform as well as biological variability. We conjecture that other reasons for the observed discrepancies are the measurement error associated with each feature and the choice of preprocessing method. Microarray data are known to be subject to technical variation and the confidence intervals around individual point estimates of expression levels can be wide. Furthermore, the estimated expression values also vary depending on the selected preprocessing scheme. In microarray breast cancer classification studies, however, these two forms of feature variability are almost always ignored and hence their exact role is unclear. Results We have performed a comprehensive sensitivity analysis of microarray breast cancer classification under the two types of feature variability mentioned above. We used data from six state of the art preprocessing methods, using a compendium consisting of eight diferent datasets, involving 1131 hybridizations, containing data from both one and two-color array technology. For a wide range of classifiers, we performed a joint study on performance, concordance and stability. In the stability analysis we explicitly tested classifiers for their noise tolerance by using perturbed expression profiles that are based on uncertainty information directly related to the preprocessing methods. Our results indicate that signature composition is strongly influenced by feature variability, even if the array platform and the stratification of patient samples are identical. In addition, we show that there is often a high level of discordance between individual class assignments for signatures constructed on data coming from different preprocessing schemes, even if the actual signature composition is identical. Conclusion Feature variability can have a strong impact on breast cancer signature composition, as well as the classification of individual patient samples. We therefore strongly recommend that feature variability is considered in analyzing data from microarray breast cancer expression profiling experiments. PMID:19941644

Mutation analysis of 272 Spanish families affected by autosomal recessive retinitis pigmentosa using a genotyping microarray.

PubMed

Ávila-Fernández, Almudena; Cantalapiedra, Diego; Aller, Elena; Vallespín, Elena; Aguirre-Lambán, Jana; Blanco-Kelly, Fiona; Corton, M; Riveiro-Álvarez, Rosa; Allikmets, Rando; Trujillo-Tiebas, María José; Millán, José M; Cremers, Frans P M; Ayuso, Carmen

2010-12-03

Retinitis pigmentosa (RP) is a genetically heterogeneous disorder characterized by progressive loss of vision. The aim of this study was to identify the causative mutations in 272 Spanish families using a genotyping microarray. 272 unrelated Spanish families, 107 with autosomal recessive RP (arRP) and 165 with sporadic RP (sRP), were studied using the APEX genotyping microarray. The families were also classified by clinical criteria: 86 juveniles and 186 typical RP families. Haplotype and sequence analysis were performed to identify the second mutated allele. At least one-gene variant was found in 14% and 16% of the juvenile and typical RP groups respectively. Further study identified four new mutations, providing both causative changes in 11% of the families. Retinol Dehydrogenase 12 (RDH12) was the most frequently mutated gene in the juvenile RP group, and Usher Syndrome 2A (USH2A) and Ceramide Kinase-Like (CERKL) were the most frequently mutated genes in the typical RP group. The only variant found in CERKL was p.Arg257Stop, the most frequent mutation. The genotyping microarray combined with segregation and sequence analysis allowed us to identify the causative mutations in 11% of the families. Due to the low number of characterized families, this approach should be used in tandem with other techniques.

Curation of microarray oligonucleotides and corresponding ESTs/cDNAs used for gene expression analysis in zebra finches.

PubMed

Lovell, Peter V; Huizinga, Nicole A; Getachew, Abel; Mees, Brianna; Friedrich, Samantha R; Wirthlin, Morgan; Mello, Claudio V

2018-05-18

Zebra finches are a major model organism for investigating mechanisms of vocal learning, a trait that enables spoken language in humans. The development of cDNA collections with expressed sequence tags (ESTs) and microarrays has allowed for extensive molecular characterizations of circuitry underlying vocal learning and production. However, poor database curation can lead to errors in transcriptome and bioinformatics analyses, limiting the impact of these resources. Here we used genomic alignments and synteny analysis for orthology verification to curate and reannotate ~ 35% of the oligonucleotides and corresponding ESTs/cDNAs that make-up Agilent microarrays for gene expression analysis in finches. We found that: (1) 5475 out of 43,084 oligos (a) failed to align to the zebra finch genome, (b) aligned to multiple loci, or (c) aligned to Chr_un only, and thus need to be flagged until a better genome assembly is available, or (d) reflect cloning artifacts; (2) Out of 9635 valid oligos examined further, 3120 were incorrectly named, including 1533 with no known orthologs; and (3) 2635 oligos required name update. The resulting curated dataset provides a reference for correcting gene identification errors in previous finch microarrays studies, and avoiding such errors in future studies.

A Model-Based Joint Identification of Differentially Expressed Genes and Phenotype-Associated Genes

PubMed Central

Seo, Minseok; Shin, Su-kyung; Kwon, Eun-Young; Kim, Sung-Eun; Bae, Yun-Jung; Lee, Seungyeoun; Sung, Mi-Kyung; Choi, Myung-Sook; Park, Taesung

2016-01-01

Over the last decade, many analytical methods and tools have been developed for microarray data. The detection of differentially expressed genes (DEGs) among different treatment groups is often a primary purpose of microarray data analysis. In addition, association studies investigating the relationship between genes and a phenotype of interest such as survival time are also popular in microarray data analysis. Phenotype association analysis provides a list of phenotype-associated genes (PAGs). However, it is sometimes necessary to identify genes that are both DEGs and PAGs. We consider the joint identification of DEGs and PAGs in microarray data analyses. The first approach we used was a naïve approach that detects DEGs and PAGs separately and then identifies the genes in an intersection of the list of PAGs and DEGs. The second approach we considered was a hierarchical approach that detects DEGs first and then chooses PAGs from among the DEGs or vice versa. In this study, we propose a new model-based approach for the joint identification of DEGs and PAGs. Unlike the previous two-step approaches, the proposed method identifies genes simultaneously that are DEGs and PAGs. This method uses standard regression models but adopts different null hypothesis from ordinary regression models, which allows us to perform joint identification in one-step. The proposed model-based methods were evaluated using experimental data and simulation studies. The proposed methods were used to analyze a microarray experiment in which the main interest lies in detecting genes that are both DEGs and PAGs, where DEGs are identified between two diet groups and PAGs are associated with four phenotypes reflecting the expression of leptin, adiponectin, insulin-like growth factor 1, and insulin. Model-based approaches provided a larger number of genes, which are both DEGs and PAGs, than other methods. Simulation studies showed that they have more power than other methods. Through analysis of data from experimental microarrays and simulation studies, the proposed model-based approach was shown to provide a more powerful result than the naïve approach and the hierarchical approach. Since our approach is model-based, it is very flexible and can easily handle different types of covariates. PMID:26964035

Microarray applications to understand the impact of exposure to environmental contaminants in wild dolphins (Tursiops truncatus).

PubMed

Mancia, Annalaura; Abelli, Luigi; Kucklick, John R; Rowles, Teresa K; Wells, Randall S; Balmer, Brian C; Hohn, Aleta A; Baatz, John E; Ryan, James C

2015-02-01

It is increasingly common to monitor the marine environment and establish geographic trends of environmental contamination by measuring contaminant levels in animals from higher trophic levels. The health of an ecosystem is largely reflected in the health of its inhabitants. As an apex predator, the common bottlenose dolphin (Tursiops truncatus) can reflect the health of near shore marine ecosystems, and reflect coastal threats that pose risk to human health, such as legacy contaminants or marine toxins, e.g. polychlorinated biphenyls (PCBs) and brevetoxins. Major advances in the understanding of dolphin biology and the unique adaptations of these animals in response to the marine environment are being made as a result of the development of cell-lines for use in in vitro experiments, the production of monoclonal antibodies to recognize dolphin proteins, the development of dolphin DNA microarrays to measure global gene expression and the sequencing of the dolphin genome. These advances may play a central role in understanding the complex and specialized biology of the dolphin with regard to how this species responds to an array of environmental insults. This work presents the creation, characterization and application of a new molecular tool to better understand the complex and unique biology of the common bottlenose dolphin and its response to environmental stress and infection. A dolphin oligo microarray representing 24,418 unigene sequences was developed and used to analyze blood samples collected from 69 dolphins during capture-release health assessments at five geographic locations (Beaufort, NC, Sarasota Bay, FL, Saint Joseph Bay, FL, Sapelo Island, GA and Brunswick, GA). The microarray was validated and tested for its ability to: 1) distinguish male from female dolphins; 2) differentiate dolphins inhabiting different geographic locations (Atlantic coasts vs the Gulf of Mexico); and 3) study in detail dolphins resident in one site, the Georgia coast, known to be heavily contaminated by Aroclor 1268, an uncommon polychlorinated (PCB) mixture. The microarray was able to distinguish dolphins by sex, geographic location, and corroborate previously published health irregularities for the Georgia dolphins. Genes involved in xenobiotic metabolism, development/differentiation and oncogenic pathways were found to be differentially expressed in GA dolphins. The report bridges the advancements in dolphin genome sequencing to the first step towards providing a cost-effective means to screen for indicators of chemical toxin exposure as well as disease status in top level predators. Copyright © 2014 Elsevier B.V. All rights reserved.

Analysis of Protein-DNA Interaction by Chromatin Immunoprecipitation and DNA Tiling Microarray (ChIP-on-chip).

PubMed

Gao, Hui; Zhao, Chunyan

2018-01-01

Chromatin immunoprecipitation (ChIP) has become the most effective and widely used tool to study the interactions between specific proteins or modified forms of proteins and a genomic DNA region. Combined with genome-wide profiling technologies, such as microarray hybridization (ChIP-on-chip) or massively parallel sequencing (ChIP-seq), ChIP could provide a genome-wide mapping of in vivo protein-DNA interactions in various organisms. Here, we describe a protocol of ChIP-on-chip that uses tiling microarray to obtain a genome-wide profiling of ChIPed DNA.

Cloud-Scale Genomic Signals Processing for Robust Large-Scale Cancer Genomic Microarray Data Analysis.

PubMed

Harvey, Benjamin Simeon; Ji, Soo-Yeon

2017-01-01

As microarray data available to scientists continues to increase in size and complexity, it has become overwhelmingly important to find multiple ways to bring forth oncological inference to the bioinformatics community through the analysis of large-scale cancer genomic (LSCG) DNA and mRNA microarray data that is useful to scientists. Though there have been many attempts to elucidate the issue of bringing forth biological interpretation by means of wavelet preprocessing and classification, there has not been a research effort that focuses on a cloud-scale distributed parallel (CSDP) separable 1-D wavelet decomposition technique for denoising through differential expression thresholding and classification of LSCG microarray data. This research presents a novel methodology that utilizes a CSDP separable 1-D method for wavelet-based transformation in order to initialize a threshold which will retain significantly expressed genes through the denoising process for robust classification of cancer patients. Additionally, the overall study was implemented and encompassed within CSDP environment. The utilization of cloud computing and wavelet-based thresholding for denoising was used for the classification of samples within the Global Cancer Map, Cancer Cell Line Encyclopedia, and The Cancer Genome Atlas. The results proved that separable 1-D parallel distributed wavelet denoising in the cloud and differential expression thresholding increased the computational performance and enabled the generation of higher quality LSCG microarray datasets, which led to more accurate classification results.

A hybrid approach to device integration on a genetic analysis platform

NASA Astrophysics Data System (ADS)

Brennan, Des; Jary, Dorothee; Kurg, Ants; Berik, Evgeny; Justice, John; Aherne, Margaret; Macek, Milan; Galvin, Paul

2012-10-01

Point-of-care (POC) systems require significant component integration to implement biochemical protocols associated with molecular diagnostic assays. Hybrid platforms where discrete components are combined in a single platform are a suitable approach to integration, where combining multiple device fabrication steps on a single substrate is not possible due to incompatible or costly fabrication steps. We integrate three devices each with a specific system functionality: (i) a silicon electro-wetting-on-dielectric (EWOD) device to move and mix sample and reagent droplets in an oil phase, (ii) a polymer microfluidic chip containing channels and reservoirs and (iii) an aqueous phase glass microarray for fluorescence microarray hybridization detection. The EWOD device offers the possibility of fully integrating on-chip sample preparation using nanolitre sample and reagent volumes. A key challenge is sample transfer from the oil phase EWOD device to the aqueous phase microarray for hybridization detection. The EWOD device, waveguide performance and functionality are maintained during the integration process. An on-chip biochemical protocol for arrayed primer extension (APEX) was implemented for single nucleotide polymorphism (SNiP) analysis. The prepared sample is aspirated from the EWOD oil phase to the aqueous phase microarray for hybridization. A bench-top instrumentation system was also developed around the integrated platform to drive the EWOD electrodes, implement APEX sample heating and image the microarray after hybridization.

Exposure to Nickel, Chromium, or Cadmium Causes Distinct Changes in the Gene Expression Patterns of a Rat Liver Derived Cell Line

PubMed Central

Permenter, Matthew G.; Lewis, John A.; Jackson, David A.

2011-01-01

Many heavy metals, including nickel (Ni), cadmium (Cd), and chromium (Cr) are toxic industrial chemicals with an exposure risk in both occupational and environmental settings that may cause harmful outcomes. While these substances are known to produce adverse health effects leading to disease or health problems, the detailed mechanisms remain unclear. To elucidate the processes involved in the toxicity of nickel, cadmium, and chromium at the molecular level and to perform a comparative analysis, H4-II-E-C3 rat liver-derived cell lines were treated with soluble salts of each metal using concentrations derived from viability assays, and gene expression patterns were determined with DNA microarrays. We identified both common and unique biological responses to exposure to the three metals. Nickel, cadmium, chromium all induced oxidative stress with both similar and unique genes and pathways responding to this stress. Although all three metals are known to be genotoxic, evidence for DNA damage in our study only exists in response to chromium. Nickel induced a hypoxic response as well as inducing genes involved in chromatin structure, perhaps by replacing iron in key proteins. Cadmium distinctly perturbed genes related to endoplasmic reticulum stress and invoked the unfolded protein response leading to apoptosis. With these studies, we have completed the first gene expression comparative analysis of nickel, cadmium, and chromium in H4-II-E-C3 cells. PMID:22110744

Global gene expression analysis of early response to chemotherapy treatment in ovarian cancer spheroids.

PubMed

L'Espérance, Sylvain; Bachvarova, Magdalena; Tetu, Bernard; Mes-Masson, Anne-Marie; Bachvarov, Dimcho

2008-02-26

Chemotherapy (CT) resistance in ovarian cancer (OC) is broad and encompasses diverse unrelated drugs, suggesting more than one mechanism of resistance. To better understand the molecular mechanisms controlling the immediate response of OC cells to CT exposure, we have performed gene expression profiling in spheroid cultures derived from six OC cell lines (OVCAR3, SKOV3, TOV-112, TOV-21, OV-90 and TOV-155), following treatment with 10,0 microM cisplatin, 2,5 microM paclitaxel or 5,0 microM topotecan for 72 hours. Exposure of OC spheroids to these CT drugs resulted in differential expression of genes associated with cell growth and proliferation, cellular assembly and organization, cell death, cell cycle control and cell signaling. Genes, functionally involved in DNA repair, DNA replication and cell cycle arrest were mostly overexpressed, while genes implicated in metabolism (especially lipid metabolism), signal transduction, immune and inflammatory response, transport, transcription regulation and protein biosynthesis, were commonly suppressed following all treatments. Cisplatin and topotecan treatments triggered similar alterations in gene and pathway expression patterns, while paclitaxel action was mainly associated with induction of genes and pathways linked to cellular assembly and organization (including numerous tubulin genes), cell death and protein synthesis. The microarray data were further confirmed by pathway and network analyses. Most alterations in gene expression were directly related to mechanisms of the cytotoxics actions in OC spheroids. However, the induction of genes linked to mechanisms of DNA replication and repair in cisplatin- and topotecan-treated OC spheroids could be associated with immediate adaptive response to treatment. Similarly, overexpression of different tubulin genes upon exposure to paclitaxel could represent an early compensatory effect to this drug action. Finally, multicellular growth conditions that are known to alter gene expression (including cell adhesion and cytoskeleton organization), could substantially contribute in reducing the initial effectiveness of CT drugs in OC spheroids. Results described in this study underscore the potential of the microarray technology for unraveling the complex mechanisms of CT drugs actions in OC spheroids and early cellular response to treatment.

Diagnosis of Zika Virus Infection by Peptide Array and Enzyme-Linked Immunosorbent Assay.

PubMed

Mishra, Nischay; Caciula, Adrian; Price, Adam; Thakkar, Riddhi; Ng, James; Chauhan, Lokendra V; Jain, Komal; Che, Xiaoyu; Espinosa, Diego A; Montoya Cruz, Magelda; Balmaseda, Angel; Sullivan, Eric H; Patel, Jigar J; Jarman, Richard G; Rakeman, Jennifer L; Egan, Christina T; Reusken, Chantal B E M; Koopmans, Marion P G; Harris, Eva; Tokarz, Rafal; Briese, Thomas; Lipkin, W Ian

2018-03-06

Zika virus (ZIKV) is implicated in fetal stillbirth, microcephaly, intracranial calcifications, and ocular anomalies following vertical transmission from infected mothers. In adults, infection may trigger autoimmune inflammatory polyneuropathy. Transmission most commonly follows the bite of infected Aedes mosquitoes but may also occur through sexual intercourse or receipt of blood products. Definitive diagnosis through detection of viral RNA is possible in serum or plasma within 10 days of disease onset, in whole blood within 3 weeks of onset, and in semen for up to 3 months. Serological diagnosis is nonetheless critical because few patients have access to molecular diagnostics during the acute phase of infection and infection may be associated with only mild or inapparent disease that does not prompt molecular testing. Serological diagnosis is confounded by cross-reactivity of immune sera with other flaviviruses endemic in the areas where ZIKV has recently emerged. Accordingly, we built a high-density microarray comprising nonredundant 12-mer peptides that tile, with one-residue overlap, the proteomes of Zika, dengue, yellow fever, West Nile, Ilheus, Oropouche, and chikungunya viruses. Serological analysis enabled discovery of a ZIKV NS2B 20-residue peptide that had high sensitivity (96.0%) and specificity (95.9%) versus natural infection with or vaccination against dengue, chikungunya, yellow fever, West Nile, tick-borne encephalitis, or Japanese encephalitis virus in a microarray assay and an enzyme-linked immunosorbent assay (ELISA) of early-convalescent-phase sera (2 to 3 weeks after onset of symptomatic infection). IMPORTANCE The emergence of Zika virus (ZIKV) as a teratogen is a profound challenge to global public health. Molecular diagnosis of infection is straightforward during the 3-week period when patients are viremic. However, serological diagnosis thereafter of historical exposure has been confounded by cross-reactivity. Using high-density peptide arrays that tile the proteomes of a selection of flaviviruses to identify a ZIKV-specific peptide, we established two assays that enable sensitive and specific diagnosis of exposure to ZIKV. These assays may be useful in guiding clinical management of mothers at risk for potential exposure to ZIKV and enable insights into the epidemiology of ZIKV infections.

Performance of automated scoring of ER, PR, HER2, CK5/6 and EGFR in breast cancer tissue microarrays in the Breast Cancer Association Consortium

PubMed Central

Howat, William J; Blows, Fiona M; Provenzano, Elena; Brook, Mark N; Morris, Lorna; Gazinska, Patrycja; Johnson, Nicola; McDuffus, Leigh‐Anne; Miller, Jodi; Sawyer, Elinor J; Pinder, Sarah; van Deurzen, Carolien H M; Jones, Louise; Sironen, Reijo; Visscher, Daniel; Caldas, Carlos; Daley, Frances; Coulson, Penny; Broeks, Annegien; Sanders, Joyce; Wesseling, Jelle; Nevanlinna, Heli; Fagerholm, Rainer; Blomqvist, Carl; Heikkilä, Päivi; Ali, H Raza; Dawson, Sarah‐Jane; Figueroa, Jonine; Lissowska, Jolanta; Brinton, Louise; Mannermaa, Arto; Kataja, Vesa; Kosma, Veli‐Matti; Cox, Angela; Brock, Ian W; Cross, Simon S; Reed, Malcolm W; Couch, Fergus J; Olson, Janet E; Devillee, Peter; Mesker, Wilma E; Seyaneve, Caroline M; Hollestelle, Antoinette; Benitez, Javier; Perez, Jose Ignacio Arias; Menéndez, Primitiva; Bolla, Manjeet K; Easton, Douglas F; Schmidt, Marjanka K; Pharoah, Paul D; Sherman, Mark E

2014-01-01

Abstract Breast cancer risk factors and clinical outcomes vary by tumour marker expression. However, individual studies often lack the power required to assess these relationships, and large‐scale analyses are limited by the need for high throughput, standardized scoring methods. To address these limitations, we assessed whether automated image analysis of immunohistochemically stained tissue microarrays can permit rapid, standardized scoring of tumour markers from multiple studies. Tissue microarray sections prepared in nine studies containing 20 263 cores from 8267 breast cancers stained for two nuclear (oestrogen receptor, progesterone receptor), two membranous (human epidermal growth factor receptor 2 and epidermal growth factor receptor) and one cytoplasmic (cytokeratin 5/6) marker were scanned as digital images. Automated algorithms were used to score markers in tumour cells using the Ariol system. We compared automated scores against visual reads, and their associations with breast cancer survival. Approximately 65–70% of tissue microarray cores were satisfactory for scoring. Among satisfactory cores, agreement between dichotomous automated and visual scores was highest for oestrogen receptor (Kappa = 0.76), followed by human epidermal growth factor receptor 2 (Kappa = 0.69) and progesterone receptor (Kappa = 0.67). Automated quantitative scores for these markers were associated with hazard ratios for breast cancer mortality in a dose‐response manner. Considering visual scores of epidermal growth factor receptor or cytokeratin 5/6 as the reference, automated scoring achieved excellent negative predictive value (96–98%), but yielded many false positives (positive predictive value = 30–32%). For all markers, we observed substantial heterogeneity in automated scoring performance across tissue microarrays. Automated analysis is a potentially useful tool for large‐scale, quantitative scoring of immunohistochemically stained tissue microarrays available in consortia. However, continued optimization, rigorous marker‐specific quality control measures and standardization of tissue microarray designs, staining and scoring protocols is needed to enhance results. PMID:27499890

Dose-response relationships in gene expression profiles in rainbow trout, Oncorhyncus mykiss, exposed to ethynylestradiol.

PubMed

Hook, Sharon E; Skillman, Ann D; Small, Jack A; Schultz, Irvin R

2006-07-01

Determining how gene expression profiles change with toxicant dose will improve the utility of arrays in identifying biomarkers and modes of toxic action. Isogenic rainbow trout, Oncorhyncus mykiss,were exposed to 10, 50 or 100 ng/L ethynylestradiol (a xeno-estrogen) for 7 days. Following exposure hepatic RNA was extracted. Fluorescently labeled cDNA were generated and hybridized against a commercially available Atlantic Salmon/Trout array (GRASP project, University of Victoria) spotted with 16,000 cDNAs. Transcript expression in treated vs control fish was analyzed via Genespring (Silicon Genetics) to identify genes with altered expression, as well as to determine gene clustering patterns that can be used as "expression signatures". Array results were confirmed via qRT PCR. Our analysis indicates that gene expression profiles varied somewhat with dose. Established biomarkers of exposure to estrogenic chemicals, such as vitellogenin, vitelline envelope proteins, and the estrogen receptor alpha, were induced at every dose. Other genes were dose specific, suggesting that different doses induce distinct physiological responses. These findings demonstrate that cDNA microarrays could be used to identify both toxicant class and relative dose.

In situ oligonucleotide synthesis on poly(dimethylsiloxane): a flexible substrate for microarray fabrication

PubMed Central

Moorcroft, Matthew J.; Meuleman, Wouter R. A.; Latham, Steven G.; Nicholls, Thomas J.; Egeland, Ryan D.; Southern, Edwin M.

2005-01-01

In this paper, we demonstrate in situ synthesis of oligonucleotide probes on poly(dimethylsiloxane) (PDMS) microchannels through use of conventional phosphoramidite chemistry. PDMS polymer was moulded into a series of microchannels using standard soft lithography (micro-moulding), with dimensions <100 μm. The surface of the PDMS was derivatized by exposure to ultraviolet/ozone followed by vapour phase deposition of glycidoxypropyltrimethoxysilane and reaction with poly(ethylene glycol) spacer, resulting in a reactive surface for oligonucleotide coupling. High, reproducible yields were achieved for both 6mer and 21mer probes as assessed by hybridization to fluorescent oligonucleotides. Oligonucleotide surface density was comparable with that obtained on glass substrates. These results suggest PDMS as a stable and flexible alternative to glass as a suitable substrate in the fabrication and synthesis of DNA microarrays. PMID:15870385

Diet-induced obesity reprograms the inflammatory response of the murine lung to inhaled endotoxin

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tilton, Susan C., E-mail: susan.tilton@pnnl.gov; Waters, Katrina M.; Karin, Norman J.

The co-occurrence of environmental factors is common in complex human diseases and, as such, understanding the molecular responses involved is essential to determine risk and susceptibility to disease. We have investigated the key biological pathways that define susceptibility for pulmonary infection during obesity in diet-induced obese (DIO) and regular weight (RW) C57BL/6 mice exposed to inhaled lipopolysaccharide (LPS). LPS induced a strong inflammatory response in all mice as indicated by elevated cell counts of macrophages and neutrophils and levels of proinflammatory cytokines (MDC, MIP-1γ, IL-12, RANTES) in the bronchoalveolar lavage fluid. Additionally, DIO mice exhibited 50% greater macrophage cell counts,more » but decreased levels of the cytokines, IL-6, TARC, TNF-α, and VEGF relative to RW mice. Microarray analysis of lung tissue showed over half of the LPS-induced expression in DIO mice consisted of genes unique for obese mice, suggesting that obesity reprograms how the lung responds to subsequent insult. In particular, we found that obese animals exposed to LPS have gene signatures showing increased inflammatory and oxidative stress response and decreased antioxidant capacity compared with RW. Because signaling pathways for these responses can be common to various sources of environmentally induced lung damage, we further identified biomarkers that are indicative of specific toxicant exposure by comparing gene signatures after LPS exposure to those from a parallel study with cigarette smoke. These data show obesity may increase sensitivity to further insult and that co-occurrence of environmental stressors result in complex biosignatures that are not predicted from analysis of individual exposures. - Highlights: ► Obesity modulates inflammatory markers in BAL fluid after LPS exposure. ► Obese animals have a unique transcriptional signature in lung after LPS exposure. ► Obesity elevates inflammatory stress and reduces antioxidant capacity in the lung. ► Toxicant-specific biomarkers predict exposure independent of systemic inflammation.« less

Circular RNA profiles in mouse lung tissue induced by radon.

PubMed

Pei, Weiwei; Tao, Lijing; Zhang, Leshuai W; Zhang, Shuyu; Cao, Jianping; Jiao, Yang; Tong, Jian; Nie, Jihua

2017-04-07

Radon is a known human lung carcinogen, whose underlying carcinogenic mechanism remains unclear. Recently, circular RNA (circRNA), a class of endogenous non-protein coding RNAs that contain a circular loop, was found to exhibit multiple biological effects. In this study, circRNA profiles in mouse lung tissues between control and radon exposure were analyzed. Six mice were exposed to radon at concentration of 100,000 Bq/m 3 , 12 h/d, for up to cumulative doses of 60 working level months (WLM). H&E staining and immunohistochemistry of caspase-3 were used to detect the damages in lung tissue. The lung tissue of control and exposed group were selected for circRNA microarray study. The circRNA/microRNA interaction was analyzed by starBase prediction software. 5 highest expressing circRNAs were selected by real-time PCR to validate the consistency in mouse lung tissue exposed to radon. Inflammatory reaction was found in mouse lung tissue exposed to radon, and caspase-3 expression was significantly increased. Microarray screening revealed 107 up-regulated and 83 down-regulated circRNAs, among which top 30 circRNAs with the highest fold changes were chosen for further analysis, with 5 microRNAs binding sites listed for each circRNA. Consistency of the top 5 circRNAs with the highest expressions were confirmed in mice exposed with 60WLM of radon. Mouse lung tissue was severely injured when exposed to radon through pathological diagnosis and immunohistochemical analysis. A series of differentially expressed circRNAs demonstrated that they may play an important role in pulmonary toxicity induced by radon.

Automatic image analysis and spot classification for detection of pathogenic Escherichia coli on glass slide DNA microarrays

USDA-ARS?s Scientific Manuscript database

A computer algorithm was created to inspect scanned images from DNA microarray slides developed to rapidly detect and genotype E. Coli O157 virulent strains. The algorithm computes centroid locations for signal and background pixels in RGB space and defines a plane perpendicular to the line connect...

Microarray as a First Genetic Test in Global Developmental Delay: A Cost-Effectiveness Analysis

ERIC Educational Resources Information Center

Trakadis, Yannis; Shevell, Michael

2011-01-01

Aim: Microarray technology has a significantly higher clinical yield than karyotyping in individuals with global developmental delay (GDD). Despite this, it has not yet been routinely implemented as a screening test owing to the perception that this approach is more expensive. We aimed to evaluate the effect that replacing karyotype with…

Assessing probe-specific dye and slide biases in two-color microarray data

USDA-ARS?s Scientific Manuscript database

A primary reason for using two-color microarrays is that the use of two samples labeled with different dyes on the same slide and that bind to probes on the same spot is supposed to adjust for many factors that introduce noise and errors into the analysis. Most users assume that any differences bet...

Exploratory Visual Analysis of Statistical Results from Microarray Experiments Comparing High and Low Grade Glioma

PubMed Central

Reif, David M.; Israel, Mark A.; Moore, Jason H.

2007-01-01

The biological interpretation of gene expression microarray results is a daunting challenge. For complex diseases such as cancer, wherein the body of published research is extensive, the incorporation of expert knowledge provides a useful analytical framework. We have previously developed the Exploratory Visual Analysis (EVA) software for exploring data analysis results in the context of annotation information about each gene, as well as biologically relevant groups of genes. We present EVA as a flexible combination of statistics and biological annotation that provides a straightforward visual interface for the interpretation of microarray analyses of gene expression in the most commonly occuring class of brain tumors, glioma. We demonstrate the utility of EVA for the biological interpretation of statistical results by analyzing publicly available gene expression profiles of two important glial tumors. The results of a statistical comparison between 21 malignant, high-grade glioblastoma multiforme (GBM) tumors and 19 indolent, low-grade pilocytic astrocytomas were analyzed using EVA. By using EVA to examine the results of a relatively simple statistical analysis, we were able to identify tumor class-specific gene expression patterns having both statistical and biological significance. Our interactive analysis highlighted the potential importance of genes involved in cell cycle progression, proliferation, signaling, adhesion, migration, motility, and structure, as well as candidate gene loci on a region of Chromosome 7 that has been implicated in glioma. Because EVA does not require statistical or computational expertise and has the flexibility to accommodate any type of statistical analysis, we anticipate EVA will prove a useful addition to the repertoire of computational methods used for microarray data analysis. EVA is available at no charge to academic users and can be found at http://www.epistasis.org. PMID:19390666

Autoregressive-model-based missing value estimation for DNA microarray time series data.

PubMed

Choong, Miew Keen; Charbit, Maurice; Yan, Hong

2009-01-01

Missing value estimation is important in DNA microarray data analysis. A number of algorithms have been developed to solve this problem, but they have several limitations. Most existing algorithms are not able to deal with the situation where a particular time point (column) of the data is missing entirely. In this paper, we present an autoregressive-model-based missing value estimation method (ARLSimpute) that takes into account the dynamic property of microarray temporal data and the local similarity structures in the data. ARLSimpute is especially effective for the situation where a particular time point contains many missing values or where the entire time point is missing. Experiment results suggest that our proposed algorithm is an accurate missing value estimator in comparison with other imputation methods on simulated as well as real microarray time series datasets.

Linking mechanistic and behavioral responses to sublethal esfenvalerate exposure in the endangered delta smelt; Hypomesus transpacificus (Fam. Osmeridae)

PubMed Central

2009-01-01

Background The delta smelt (Hypomesus transpacificus) is a pelagic fish species listed as endangered under both the USA Federal and Californian State Endangered Species Acts and considered an indicator of ecosystem health in its habitat range, which is limited to the Sacramento-San Joaquin estuary in California, USA. Anthropogenic contaminants are one of multiple stressors affecting this system, and among them, current-use insecticides are of major concern. Interrogative tools are required to successfully monitor effects of contaminants on the delta smelt, and to research potential causes of population decline in this species. We have created a microarray to investigate genome-wide effects of potentially causative stressors, and applied this tool to assess effects of the pyrethroid insecticide esfenvalerate on larval delta smelt. Selected genes were further investigated as molecular biomarkers using quantitative PCR analyses. Results Exposure to esfenvalerate affected swimming behavior of larval delta smelt at concentrations as low as 0.0625 μg.L-1, and significant differences in expression were measured in genes involved in neuromuscular activity. Alterations in the expression of genes associated with immune responses, along with apoptosis, redox, osmotic stress, detoxification, and growth and development appear to have been invoked by esfenvalerate exposure. Swimming impairment correlated significantly with expression of aspartoacylase (ASPA), an enzyme involved in brain cell function and associated with numerous human diseases. Selected genes were investigated for their use as molecular biomarkers, and strong links were determined between measured downregulation in ASPA and observed behavioral responses in fish exposed to environmentally relevant pyrethroid concentrations. Conclusions The results of this study show that microarray technology is a useful approach in screening for, and generation of molecular biomarkers in endangered, non-model organisms, identifying specific genes that can be directly linked with sublethal toxicological endpoints; such as changes in expression levels of neuromuscular genes resulting in measurable swimming impairments. The developed microarrays were successfully applied on larval fish exposed to esfenvalerate, a known contaminant of the Sacramento-San Joaquin estuary, and has permitted the identification of specific biomarkers which could provide insight into the factors contributing to delta smelt population decline. PMID:20003521

Gene Expression Profile Analysis as a Prognostic Indicator of Normal Tissue Response to Simulated Space Radiations

NASA Technical Reports Server (NTRS)

Story, Michael; Stivers, David N.

2004-01-01

This project was funded as a pilot project to determine the feasibility of using gene expression profiles to characterize the response of human cells to exposure to particulate radiations such as those encountered in the spaceflight environment. We proposed to use microarray technology to examine the gene expression patterns of a bank of well-characterized human fibroblast cell cultures. These fibroblast cultures were derived from breast or head and neck cancer patients who exhibited normal, minimal, or severe normal tissue reactions following low LET radiation exposure via radiotherapy. Furthermore, determination of SF2 values from fibroblasts cultured from these individuals were predictive of risk for severe late reactions. We hypothesized that by determining the expression of thousands of genes we could identify gene expression patterns that reflect how normal tissues respond to high Z and energy (HZE) particles, that is, that there are molecular signatures for HZE exposures. We also hypothesized that individuals who are intrinsically radiosensitive may elicit a unique response. Because this was funded as a pilot project we focused our initial studies on logistics and appropriate experimental design, and then to test our hypothesis that there is a unique molecular response to specific particles, in this case C and Fe, for primary human skin fibroblasts.

Genetic background modulates lncRNA-coordinated tissue response to low dose ionizing radiation

DOE PAGES

Tang, Jonathan; Huang, Yurong; Nguyen, David H.; ...

2015-02-04

Long noncoding RNAs (lncRNAs) are emerging as key regulators of diverse cell functions and processes. However, the relevance of lncRNAs in the cell and tissue response to ionizing radiation has not yet been characterized. Here we used microarray profiling to determine lncRNA and mRNA expression in mammary glands of BALB/c and SPRET/EiJ mice after low-dose ionizing radiation (LDIR) exposure. We found that unirradiated mammary tissues of these strains differed significantly in baseline expressions of 290 lncRNAs. LDIR exposure (10 cGy) induced a significant change in the expression of many lncRNAs. The vast majority of lncRNAs identified to be differentially expressed aftermore » LDIR in either BALB/c or SPRET/EiJ had a significantly correlated expression pattern with at least one LDIR responsive mRNA. Functional analysis revealed that the response to LDIR in BALB/c mice is highly dynamic with enrichment for genes involved in tissue injury, inflammatory responses, and mammary gland development at 2, 4, and 8 weeks after LDIR, respectively. Our study demonstrates that genetic background strongly influences the expression of lncRNAs and their response to radiation and that lncRNAs may coordinate the tissue response to LDIR exposure via regulation of coding mRNAs.« less

Chronic Exposure to Carbon Nanotubes Induces Invasion of Human Mesothelial Cells through Matrix Metalloproteinase-2

PubMed Central

Lohcharoenkal, Warangkana; Wang, Liying; Stueckle, Todd A.; Dinu, Cerasela Zoica; Castranova, Vincent; Liu, Yuxin; Rojanasakul, Yon

2013-01-01

Malignant mesothelioma is one of the most aggressive forms of cancer known. Recent studies have shown that carbon nanotubes (CNTs) are biopersistent and induce mesothelioma in animals, but the underlying mechanisms are not known. Here, we investigate the effect of long-term exposure to high aspect ratio CNTs on the aggressive behaviors of human pleural mesothelial cells, the primary cellular target of human lung mesothelioma. We show that chronic exposure (4 months) to single- and multi-walled CNTs induced proliferation, migration and invasion of the cells similar to that observed in asbestos-exposed cells. An upregulation of several key genes known to be important in cell invasion, notably matrix metalloproteinase-2 (MMP-2), was observed in the exposed mesothelial cells as determined by real-time PCR. Western blot and enzyme activity assays confirmed the increased expression and activity of MMP-2. Whole genome microarray analysis further indicated the importance of MMP-2 in the invasion gene signaling network of the exposed cells. Knockdown of MMP-2 in CNT and asbestos-exposed cells by shRNA-mediated gene silencing effectively inhibited the aggressive phenotypes. This study demonstrates CNT-induced cell invasion and indicates the role of MMP-2 in the process. PMID:23924264

Genetic background modulates lncRNA-coordinated tissue response to low dose ionizing radiation

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tang, Jonathan; Huang, Yurong; Nguyen, David H.

Long noncoding RNAs (lncRNAs) are emerging as key regulators of diverse cell functions and processes. However, the relevance of lncRNAs in the cell and tissue response to ionizing radiation has not yet been characterized. Here we used microarray profiling to determine lncRNA and mRNA expression in mammary glands of BALB/c and SPRET/EiJ mice after low-dose ionizing radiation (LDIR) exposure. We found that unirradiated mammary tissues of these strains differed significantly in baseline expressions of 290 lncRNAs. LDIR exposure (10 cGy) induced a significant change in the expression of many lncRNAs. The vast majority of lncRNAs identified to be differentially expressed aftermore » LDIR in either BALB/c or SPRET/EiJ had a significantly correlated expression pattern with at least one LDIR responsive mRNA. Functional analysis revealed that the response to LDIR in BALB/c mice is highly dynamic with enrichment for genes involved in tissue injury, inflammatory responses, and mammary gland development at 2, 4, and 8 weeks after LDIR, respectively. Our study demonstrates that genetic background strongly influences the expression of lncRNAs and their response to radiation and that lncRNAs may coordinate the tissue response to LDIR exposure via regulation of coding mRNAs.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Poulsen, Sarah S., E-mail: spo@nrcwe.dk; Department of Science, Systems and Models, Roskilde University, DK-4000 Roskilde; Saber, Anne T., E-mail: ats@nrcwe.dk

Multi-walled carbon nanotubes (MWCNTs) are an inhomogeneous group of nanomaterials that vary in lengths, shapes and types of metal contamination, which makes hazard evaluation difficult. Here we present a toxicogenomic analysis of female C57BL/6 mouse lungs following a single intratracheal instillation of 0, 18, 54 or 162 μg/mouse of a small, curled (CNT{sub Small}, 0.8 ± 0.1 μm in length) or large, thick MWCNT (CNT{sub Large}, 4 ± 0.4 μm in length). The two MWCNTs were extensively characterized by SEM and TEM imaging, thermogravimetric analysis, and Brunauer–Emmett–Teller surface area analysis. Lung tissues were harvested 24 h, 3 days and 28more » days post-exposure. DNA microarrays were used to analyze gene expression, in parallel with analysis of bronchoalveolar lavage fluid, lung histology, DNA damage (comet assay) and the presence of reactive oxygen species (dichlorodihydrofluorescein assay), to profile and characterize related pulmonary endpoints. Overall changes in global transcription following exposure to CNT{sub Small} or CNT{sub Large} were similar. Both MWCNTs elicited strong acute phase and inflammatory responses that peaked at day 3, persisted up to 28 days, and were characterized by increased cellular influx in bronchoalveolar lavage fluid, interstitial pneumonia and gene expression changes. However, CNT{sub Large} elicited an earlier onset of inflammation and DNA damage, and induced more fibrosis and a unique fibrotic gene expression signature at day 28, compared to CNT{sub Small}. The results indicate that the extent of change at the molecular level during early response phases following an acute exposure is greater in mice exposed to CNT{sub Large}, which may eventually lead to the different responses observed at day 28. - Highlights: • We evaluate the toxicogenomic response in mice following MWCNT instillation. • Two MWCNTs of different properties were examined and thoroughly characterized. • MWCNT exposure leads to increased pulmonary inflammation and acute phase response. • The thick and straight MWCNT induced transcriptional and histological pulmonary fibrotic changes. • This was not observed following exposure to the thinner and curled MWCNT.« less

THE GOOD, THE BAD, AND THE TOXIC: APPROACHING HORMESIS IN DAPHNIA MAGNA EXPOSED TO AN ENERGETIC COMPOUND

PubMed Central

Stanley, Jacob K.; Perkins, Edward J.; Habib, Tanwir; Sims, Jerre G.; Chappell, Pornsawan; Escalon, B. Lynn; Wilbanks, Mitchell; Garcia-Reyero, Natàlia

2014-01-01

A hormetic response is characterized by an opposite effect in small and large doses of chemical exposure, often resulting in seemingly beneficial effects at low doses. Here, we examined the potential mechanisms underlying the hormetic response of Daphnia magna to the energetic trinitrotoluene (TNT). Daphnia magna were exposed to TNT for 21 days and a significant increase in adult length and number of neonates was identified at low concentrations (0.002 – 0.22 mg/L TNT) while toxic effects were identified at high concentrations (0.97 mg/L TNT and above). Microarray analysis of D. magna exposed to 0.004, 0.12, and 1.85 mg/L TNT identified effects on lipid metabolism as a potential mechanism underlying hormetic effects. Lipidomic analysis of exposed D. magna supported the hypothesis that TNT exposure affected lipid and fatty acid metabolism, showing that hormetic effects could be related to changes in polyunsaturated fatty acids known to be involved in Daphnia growth and reproduction. Our results show that Daphnia exposed to low levels of TNT presented hormetic growth and reproduction enhancement while higher TNT concentrations had an opposite effect. Our results also show how a systems approach can help elucidate potential mechanisms of action and adverse outcomes. PMID:23898970

mTOR Activation by PI3K/Akt and ERK Signaling in Short ELF-EMF Exposed Human Keratinocytes

PubMed Central

Patruno, Antonia; Pesce, Mirko; Grilli, Alfredo; Speranza, Lorenza; Franceschelli, Sara; De Lutiis, Maria Anna; Vianale, Giovina; Costantini, Erica; Amerio, Paolo; Muraro, Raffaella; Felaco, Mario; Reale, Marcella

2015-01-01

Several reports suggest that ELF-EMF exposures interact with biological processes including promotion of cell proliferation. However, the molecular mechanisms by which ELF-EMF controls cell growth are not completely understood. The present study aimed to investigate the effect of ELF-EMF on keratinocytes proliferation and molecular mechanisms involved. Effect of ELF-EMF (50 Hz, 1 mT) on HaCaT cell cycle and cells growth and viability was monitored by FACS analysis and BrdU assay. Gene expression profile by microarray and qRT-PCR validation was performed in HaCaT cells exposed or not to ELF-EMF. mTOR, Akt and MAPKs expressions were evaluated by Western blot analysis. In HaCaT cells, short ELF-EMF exposure modulates distinct patterns of gene expression involved in cell proliferation and in the cell cycle. mTOR activation resulted the main molecular target of ELF-EMF on HaCaT cells. Our data showed the increase of the canonical pathway of mTOR regulation (PI3K/Akt) and activation of ERK signaling pathways. Our results indicate that ELF-EMF selectively modulated the expression of multiple genes related to pivotal biological processes and functions that play a key role in physio-pathological mechanisms such as wound healing. PMID:26431550

A microarray-based genotyping and genetic mapping approach for highly heterozygous outcrossing species enables localization of a large fraction of the unassembled Populus trichocarpa genome sequence.

PubMed

Drost, Derek R; Novaes, Evandro; Boaventura-Novaes, Carolina; Benedict, Catherine I; Brown, Ryan S; Yin, Tongming; Tuskan, Gerald A; Kirst, Matias

2009-06-01

Microarrays have demonstrated significant power for genome-wide analyses of gene expression, and recently have also revolutionized the genetic analysis of segregating populations by genotyping thousands of loci in a single assay. Although microarray-based genotyping approaches have been successfully applied in yeast and several inbred plant species, their power has not been proven in an outcrossing species with extensive genetic diversity. Here we have developed methods for high-throughput microarray-based genotyping in such species using a pseudo-backcross progeny of 154 individuals of Populus trichocarpa and P. deltoides analyzed with long-oligonucleotide in situ-synthesized microarray probes. Our analysis resulted in high-confidence genotypes for 719 single-feature polymorphism (SFP) and 1014 gene expression marker (GEM) candidates. Using these genotypes and an established microsatellite (SSR) framework map, we produced a high-density genetic map comprising over 600 SFPs, GEMs and SSRs. The abundance of gene-based markers allowed us to localize over 35 million base pairs of previously unplaced whole-genome shotgun (WGS) scaffold sequence to putative locations in the genome of P. trichocarpa. A high proportion of sampled scaffolds could be verified for their placement with independently mapped SSRs, demonstrating the previously un-utilized power that high-density genotyping can provide in the context of map-based WGS sequence reassembly. Our results provide a substantial contribution to the continued improvement of the Populus genome assembly, while demonstrating the feasibility of microarray-based genotyping in a highly heterozygous population. The strategies presented are applicable to genetic mapping efforts in all plant species with similarly high levels of genetic diversity.

Cruella: developing a scalable tissue microarray data management system.

PubMed

Cowan, James D; Rimm, David L; Tuck, David P

2006-06-01

Compared with DNA microarray technology, relatively little information is available concerning the special requirements, design influences, and implementation strategies of data systems for tissue microarray technology. These issues include the requirement to accommodate new and different data elements for each new project as well as the need to interact with pre-existing models for clinical, biological, and specimen-related data. To design and implement a flexible, scalable tissue microarray data storage and management system that could accommodate information regarding different disease types and different clinical investigators, and different clinical investigation questions, all of which could potentially contribute unforeseen data types that require dynamic integration with existing data. The unpredictability of the data elements combined with the novelty of automated analysis algorithms and controlled vocabulary standards in this area require flexible designs and practical decisions. Our design includes a custom Java-based persistence layer to mediate and facilitate interaction with an object-relational database model and a novel database schema. User interaction is provided through a Java Servlet-based Web interface. Cruella has become an indispensable resource and is used by dozens of researchers every day. The system stores millions of experimental values covering more than 300 biological markers and more than 30 disease types. The experimental data are merged with clinical data that has been aggregated from multiple sources and is available to the researchers for management, analysis, and export. Cruella addresses many of the special considerations for managing tissue microarray experimental data and the associated clinical information. A metadata-driven approach provides a practical solution to many of the unique issues inherent in tissue microarray research, and allows relatively straightforward interoperability with and accommodation of new data models.

Evaluation of the skin irritation using a DNA microarray on a reconstructed human epidermal model.

PubMed

Niwa, Makoto; Nagai, Kanji; Oike, Hideaki; Kobori, Masuko

2009-02-01

To avoid the need to use animals to test the skin irritancy potential of chemicals and cosmetics, it is important to establish an in vitro method based on the reconstructed human epidermal model. To evaluate skin irritancy efficiently and sensitively, we determined the gene expression induced by a topically-applied mild irritant sodium dodecyl sulfate (SDS) in a reconstructed human epidermal model LabCyte EPI-MODEL (LabCyte) using a DNA microarray carrying genes that were related to inflammation, immunity, stress and housekeeping. The expression and secretion of IL-1alpha in reconstructed human epidermal culture is known to be induced by irritation. We detected the induction of IL-1alpha expression and its secretion into the cell culture medium by treatment with 0.075% SDS for 18 h in LabCyte culture using DNA microarray, quantitative reverse-transcription polymerase chain reaction (RT-PCR) and ELISA. DNA microarray analysis indicated that the expression of 10 of the 205 genes carried on the DNA microarray was significantly induced in a LabCyte culture by 0.05% or 0.075% SDS irritation for 18 h. RT-PCR analysis confirmed that SDS treatment significantly induced the expressions of interleukin-1 receptor antagonist (IL-1RN), FOS-like antigen 1 (FOSL1), heat shock 70 kDa protein 1A (HSPA1) and myeloid differentiation primary response gene (88) (MYD88), as well as the known marker genes for irritation IL-1beta and IL-8 in a LabCyte culture. Our results showed that a DNA microarray is a useful tool for efficiently evaluating mild skin irritation using a reconstructed human epidermal model.

Development and experimental validation of a 20K Atlantic cod (Gadus morhua) oligonucleotide microarray based on a collection of over 150,000 ESTs.

PubMed

Booman, Marije; Borza, Tudor; Feng, Charles Y; Hori, Tiago S; Higgins, Brent; Culf, Adrian; Léger, Daniel; Chute, Ian C; Belkaid, Anissa; Rise, Marlies; Gamperl, A Kurt; Hubert, Sophie; Kimball, Jennifer; Ouellette, Rodney J; Johnson, Stewart C; Bowman, Sharen; Rise, Matthew L

2011-08-01

The collapse of Atlantic cod (Gadus morhua) wild populations strongly impacted the Atlantic cod fishery and led to the development of cod aquaculture. In order to improve aquaculture and broodstock quality, we need to gain knowledge of genes and pathways involved in Atlantic cod responses to pathogens and other stressors. The Atlantic Cod Genomics and Broodstock Development Project has generated over 150,000 expressed sequence tags from 42 cDNA libraries representing various tissues, developmental stages, and stimuli. We used this resource to develop an Atlantic cod oligonucleotide microarray containing 20,000 unique probes. Selection of sequences from the full range of cDNA libraries enables application of the microarray for a broad spectrum of Atlantic cod functional genomics studies. We included sequences that were highly abundant in suppression subtractive hybridization (SSH) libraries, which were enriched for transcripts responsive to pathogens or other stressors. These sequences represent genes that potentially play an important role in stress and/or immune responses, making the microarray particularly useful for studies of Atlantic cod gene expression responses to immune stimuli and other stressors. To demonstrate its value, we used the microarray to analyze the Atlantic cod spleen response to stimulation with formalin-killed, atypical Aeromonas salmonicida, resulting in a gene expression profile that indicates a strong innate immune response. These results were further validated by quantitative PCR analysis and comparison to results from previous analysis of an SSH library. This study shows that the Atlantic cod 20K oligonucleotide microarray is a valuable new tool for Atlantic cod functional genomics research.

Interim Report on SNP analysis and forensic microarray probe design for South American hemorrhagic fever viruses, tick-borne encephalitis virus, henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever viruses, Rift Valley fever

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jaing, C; Gardner, S

The goal of this project is to develop forensic genotyping assays for select agent viruses, enhancing the current capabilities for the viral bioforensics and law enforcement community. We used a multipronged approach combining bioinformatics analysis, PCR-enriched samples, microarrays and TaqMan assays to develop high resolution and cost effective genotyping methods for strain level forensic discrimination of viruses. We have leveraged substantial experience and efficiency gained through year 1 on software development, SNP discovery, TaqMan signature design and phylogenetic signature mapping to scale up the development of forensics signatures in year 2. In this report, we have summarized the whole genomemore » wide SNP analysis and microarray probe design for forensics characterization of South American hemorrhagic fever viruses, tick-borne encephalitis viruses and henipaviruses, Old World Arenaviruses, filoviruses, Crimean-Congo hemorrhagic fever virus, Rift Valley fever virus and Japanese encephalitis virus.« less

Upregulated epidermal growth factor receptor expression following near-infrared irradiation simulating solar radiation in a three-dimensional reconstructed human corneal epithelial tissue culture model

PubMed Central

Tanaka, Yohei; Nakayama, Jun

2016-01-01

Background and objective Humans are increasingly exposed to near-infrared (NIR) radiation from both natural (eg, solar) and artificial (eg, electrical appliances) sources. Although the biological effects of sun and ultraviolet (UV) exposure have been extensively investigated, the biological effect of NIR radiation is still unclear. We previously reported that NIR as well as UV induces photoaging and standard UV-blocking materials, such as sunglasses, do not sufficiently block NIR. The objective of this study was to investigate changes in gene expression in three-dimensional reconstructed corneal epithelial tissue culture exposed to broad-spectrum NIR irradiation to simulate solar NIR radiation that reaches human tissues. Materials and methods DNA microarray and quantitative real-time polymerase chain reaction analysis were used to assess gene expression levels in a three-dimensional reconstructed corneal epithelial model composed of normal human corneal epithelial cells exposed to water-filtered broad-spectrum NIR irradiation with a contact cooling (20°C). The water-filter allowed 1,000–1,800 nm wavelengths and excluded 1,400–1,500 nm wavelengths. Results A DNA microarray with >62,000 different probes showed 25 and 150 genes that were up- or downregulated by at least fourfold and twofold, respectively, after NIR irradiation. In particular, epidermal growth factor receptor (EGFR) was upregulated by 19.4-fold relative to control cells. Quantitative real-time polymerase chain reaction analysis revealed that two variants of EGFR in human corneal epithelial tissue were also significantly upregulated after five rounds of 10 J/cm2 irradiation (P<0.05). Conclusion We found that NIR irradiation induced the upregulated expression of EGFR in human corneal cells. Since over half of the solar energy reaching the Earth is in the NIR region, which cannot be adequately blocked by eyewear and thus can induce eye damage with intensive or long-term exposure, protection from both UV and NIR radiation may prevent changes in gene expression and in turn eye damage. PMID:27536083

Coral-zooxanthellae meta-transcriptomics reveals integrated response to pollutant stress.

PubMed

Gust, Kurt A; Najar, Fares Z; Habib, Tanwir; Lotufo, Guilherme R; Piggot, Alan M; Fouke, Bruce W; Laird, Jennifer G; Wilbanks, Mitchell S; Rawat, Arun; Indest, Karl J; Roe, Bruce A; Perkins, Edward J

2014-07-12

Corals represent symbiotic meta-organisms that require harmonization among the coral animal, photosynthetic zooxanthellae and associated microbes to survive environmental stresses. We investigated integrated-responses among coral and zooxanthellae in the scleractinian coral Acropora formosa in response to an emerging marine pollutant, the munitions constituent, 1,3,5-trinitro-1,3,5 triazine (RDX; 5 day exposures to 0 (control), 0.5, 0.9, 1.8, 3.7, and 7.2 mg/L, measured in seawater). RDX accumulated readily in coral soft tissues with bioconcentration factors ranging from 1.1 to 1.5. Next-generation sequencing of a normalized meta-transcriptomic library developed for the eukaryotic components of the A. formosa coral holobiont was leveraged to conduct microarray-based global transcript expression analysis of integrated coral/zooxanthellae responses to the RDX exposure. Total differentially expressed transcripts (DET) increased with increasing RDX exposure concentrations as did the proportion of zooxanthellae DET relative to the coral animal. Transcriptional responses in the coral demonstrated higher sensitivity to RDX compared to zooxanthellae where increased expression of gene transcripts coding xenobiotic detoxification mechanisms (i.e. cytochrome P450 and UDP glucuronosyltransferase 2 family) were initiated at the lowest exposure concentration. Increased expression of these detoxification mechanisms was sustained at higher RDX concentrations as well as production of a physical barrier to exposure through a 40% increase in mucocyte density at the maximum RDX exposure. At and above the 1.8 mg/L exposure concentration, DET coding for genes involved in central energy metabolism, including photosynthesis, glycolysis and electron-transport functions, were decreased in zooxanthellae although preliminary data indicated that zooxanthellae densities were not affected. In contrast, significantly increased transcript expression for genes involved in cellular energy production including glycolysis and electron-transport pathways was observed in the coral animal. Transcriptional network analysis for central energy metabolism demonstrated highly correlated responses to RDX among the coral animal and zooxanthellae indicative of potential compensatory responses to lost photosynthetic potential within the holobiont. These observations underscore the potential for complex integrated responses to RDX exposure among species comprising the coral holobiont and highlight the need to understand holobiont-species interactions to accurately assess pollutant impacts.

The global response of Nostoc punctiforme ATCC 29133 to UVA stress, assessed in a temporal DNA microarray study.

PubMed

Soule, Tanya; Gao, Qunjie; Stout, Valerie; Garcia-Pichel, Ferran

2013-01-01

Cyanobacteria in nature are exposed not only to the visible spectrum of sunlight but also to its harmful ultraviolet components (UVA and UVB). We used Nostoc punctiforme ATCC 29133 as a model to study the UVA response by analyzing global gene expression patterns using genomic microarrays. UVA exposure resulted in the statistically detectable differential expression of 573 genes of the 6903 that were probed, compared with that of the control cultures. Of those genes, 473 were up-regulated, while only 100 were down-regulated. Many of the down-regulated genes were involved in photosynthetic pigment biosynthesis, indicating a significant shift in this metabolism. As expected, we detected the up-regulation of genes encoding antioxidant enzymes and the sunscreen, scytonemin. However, a majority of the up-regulated genes, 47%, were unassignable bioinformatically to known functional categories, suggesting that the UVA stress response is not well understood. Interestingly, the most dramatic up-regulation involved several contiguous genes of unassigned metabolism on plasmid A. This is the first global UVA stress response analysis of any phototrophic microorganism and the differential expression of 8% of the genes of the Nostoc genome indicates that adaptation to UVA in Nostoc has been an evolutionary force of significance. © 2012 Wiley Periodicals, Inc. Photochemistry and Photobiology © 2012 The American Society of Photobiology.

Honey bee aggression supports a link between gene regulation and behavioral evolution.

PubMed

Alaux, Cédric; Sinha, Saurabh; Hasadsri, Linda; Hunt, Greg J; Guzmán-Novoa, Ernesto; DeGrandi-Hoffman, Gloria; Uribe-Rubio, José Luis; Southey, Bruce R; Rodriguez-Zas, Sandra; Robinson, Gene E

2009-09-08

A prominent theory states that animal phenotypes arise by evolutionary changes in gene regulation, but the extent to which this theory holds true for behavioral evolution is not known. Because "nature and nurture" are now understood to involve hereditary and environmental influences on gene expression, we studied whether environmental influences on a behavioral phenotype, i.e., aggression, could have evolved into inherited differences via changes in gene expression. Here, with microarray analysis of honey bees, we show that aggression-related genes with inherited patterns of brain expression are also environmentally regulated. There were expression differences in the brain for hundreds of genes between the highly aggressive Africanized honey bee compared with European honey bee (EHB) subspecies. Similar results were obtained for EHB in response to exposure to alarm pheromone (which provokes aggression) and when comparing old and young bees (aggressive tendencies increase with age). There was significant overlap of the gene lists generated from these three microarray experiments. Moreover, there was statistical enrichment of several of the same cis regulatory motifs in promoters of genes on all three gene lists. Aggression shows a remarkably robust brain molecular signature regardless of whether it occurs because of inherited, age-related, or environmental (social) factors. It appears that one element in the evolution of different degrees of aggressive behavior in honey bees involved changes in regulation of genes that mediate the response to alarm pheromone.

Whole-genome transcriptional analysis of heavy metal stresses inCaulobacter crescentus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hu, Ping; Brodie, Eoin L.; Suzuki, Yohey

2005-09-21

The bacterium Caulobacter crescentus and related stalkbacterial species are known for their distinctive ability to live in lownutrient environments, a characteristic of most heavy metal contaminatedsites. Caulobacter crescentus is a model organism for studying cell cycleregulation with well developed genetics. We have identified the pathwaysresponding to heavy metal toxicity in C. crescentus to provide insightsfor possible application of Caulobacter to environmental restoration. Weexposed C. crescentus cells to four heavy metals (chromium, cadmium,selenium and uranium) and analyzed genome wide transcriptional activitiespost exposure using a Affymetrix GeneChip microarray. C. crescentusshowed surprisingly high tolerance to uranium, a possible mechanism forwhich may be formationmore » of extracellular calcium-uranium-phosphateprecipitates. The principal response to these metals was protectionagainst oxidative stress (up-regulation of manganese-dependent superoxidedismutase, sodA). Glutathione S-transferase, thioredoxin, glutaredoxinsand DNA repair enzymes responded most strongly to cadmium and chromate.The cadmium and chromium stress response also focused on reducing theintracellular metal concentration, with multiple efflux pumps employed toremove cadmium while a sulfate transporter was down-regulated to reducenon-specific uptake of chromium. Membrane proteins were also up-regulatedin response to most of the metals tested. A two-component signaltransduction system involved in the uranium response was identified.Several differentially regulated transcripts from regions previously notknown to encode proteins were identified, demonstrating the advantage ofevaluating the transcriptome using whole genome microarrays.« less

Multi-membership gene regulation in pathway based microarray analysis

PubMed Central

2011-01-01

Background Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. Results We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. Conclusions We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes. PMID:21939531

Multi-membership gene regulation in pathway based microarray analysis.

PubMed

Pavlidis, Stelios P; Payne, Annette M; Swift, Stephen M

2011-09-22

Gene expression analysis has been intensively researched for more than a decade. Recently, there has been elevated interest in the integration of microarray data analysis with other types of biological knowledge in a holistic analytical approach. We propose a methodology that can be facilitated for pathway based microarray data analysis, based on the observation that a substantial proportion of genes present in biochemical pathway databases are members of a number of distinct pathways. Our methodology aims towards establishing the state of individual pathways, by identifying those truly affected by the experimental conditions based on the behaviour of such genes. For that purpose it considers all the pathways in which a gene participates and the general census of gene expression per pathway. We utilise hill climbing, simulated annealing and a genetic algorithm to analyse the consistency of the produced results, through the application of fuzzy adjusted rand indexes and hamming distance. All algorithms produce highly consistent genes to pathways allocations, revealing the contribution of genes to pathway functionality, in agreement with current pathway state visualisation techniques, with the simulated annealing search proving slightly superior in terms of efficiency. We show that the expression values of genes, which are members of a number of biochemical pathways or modules, are the net effect of the contribution of each gene to these biochemical processes. We show that by manipulating the pathway and module contribution of such genes to follow underlying trends we can interpret microarray results centred on the behaviour of these genes.

Quantitative comparison of microarray experiments with published leukemia related gene expression signatures.

PubMed

Klein, Hans-Ulrich; Ruckert, Christian; Kohlmann, Alexander; Bullinger, Lars; Thiede, Christian; Haferlach, Torsten; Dugas, Martin

2009-12-15

Multiple gene expression signatures derived from microarray experiments have been published in the field of leukemia research. A comparison of these signatures with results from new experiments is useful for verification as well as for interpretation of the results obtained. Currently, the percentage of overlapping genes is frequently used to compare published gene signatures against a signature derived from a new experiment. However, it has been shown that the percentage of overlapping genes is of limited use for comparing two experiments due to the variability of gene signatures caused by different array platforms or assay-specific influencing parameters. Here, we present a robust approach for a systematic and quantitative comparison of published gene expression signatures with an exemplary query dataset. A database storing 138 leukemia-related published gene signatures was designed. Each gene signature was manually annotated with terms according to a leukemia-specific taxonomy. Two analysis steps are implemented to compare a new microarray dataset with the results from previous experiments stored and curated in the database. First, the global test method is applied to assess gene signatures and to constitute a ranking among them. In a subsequent analysis step, the focus is shifted from single gene signatures to chromosomal aberrations or molecular mutations as modeled in the taxonomy. Potentially interesting disease characteristics are detected based on the ranking of gene signatures associated with these aberrations stored in the database. Two example analyses are presented. An implementation of the approach is freely available as web-based application. The presented approach helps researchers to systematically integrate the knowledge derived from numerous microarray experiments into the analysis of a new dataset. By means of example leukemia datasets we demonstrate that this approach detects related experiments as well as related molecular mutations and may help to interpret new microarray data.

ValWorkBench: an open source Java library for cluster validation, with applications to microarray data analysis.

PubMed

Giancarlo, R; Scaturro, D; Utro, F

2015-02-01

The prediction of the number of clusters in a dataset, in particular microarrays, is a fundamental task in biological data analysis, usually performed via validation measures. Unfortunately, it has received very little attention and in fact there is a growing need for software tools/libraries dedicated to it. Here we present ValWorkBench, a software library consisting of eleven well known validation measures, together with novel heuristic approximations for some of them. The main objective of this paper is to provide the interested researcher with the full software documentation of an open source cluster validation platform having the main features of being easily extendible in a homogeneous way and of offering software components that can be readily re-used. Consequently, the focus of the presentation is on the architecture of the library, since it provides an essential map that can be used to access the full software documentation, which is available at the supplementary material website [1]. The mentioned main features of ValWorkBench are also discussed and exemplified, with emphasis on software abstraction design and re-usability. A comparison with existing cluster validation software libraries, mainly in terms of the mentioned features, is also offered. It suggests that ValWorkBench is a much needed contribution to the microarray software development/algorithm engineering community. For completeness, it is important to mention that previous accurate algorithmic experimental analysis of the relative merits of each of the implemented measures [19,23,25], carried out specifically on microarray data, gives useful insights on the effectiveness of ValWorkBench for cluster validation to researchers in the microarray community interested in its use for the mentioned task. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Microarray analysis of the rat lacrimal gland following the loss of parasympathetic control of secretion

PubMed Central

Nguyen, Doan H.; Toshida, Hiroshi; Schurr, Jill; Beuerman, Roger W.

2010-01-01

Previous studies showed that loss of muscarinic parasympathetic input to the lacrimal gland (LG) leads to a dramatic reduction in tear secretion and profound changes to LG structure. In this study, we used DNA microarrays to examine the regulation of the gene expression of the genes for secretory function and organization of the LG. Long-Evans rats anesthetized with a mixture of ketamine/xylazine (80:10 mg/kg) underwent unilateral sectioning of the greater superficial petrosal nerve, the input to the pterygopalatine ganglion. After 7 days, tear secretion was measured, the animals were killed, and structural changes in the LG were examined by light microscopy. Total RNA from control and experimental LGs (n = 5) was used for DNA microarray analysis employing the U34A GeneChip. Three statistical algorithms (detection, change call, and signal log ratio) were used to determine differential gene expression using the Microarray Suite (5.0) and Data Mining Tools (3.0). Tear secretion was significantly reduced and corneal ulcers developed in all experimental eyes. Light microscopy showed breakdown of the acinar structure of the LG. DNA microarray analysis showed downregulation of genes associated with the endoplasmic reticulum and Golgi, including genes involved in protein folding and processing. Conversely, transcripts for cytoskeleton and extracellular matrix components, inflammation, and apoptosis were upregulated. The number of significantly upregulated genes (116) was substantially greater than the number of downregulated genes (49). Removal of the main secretory input to the rat LG resulted in clinical symptoms associated with severe dry eye. Components of the secretory pathway were negatively affected, and the increase in cell proliferation and inflammation may lead to loss of organization in the parasympathectomized lacrimal gland. PMID:15084711

Identification of novel and known oocyte-specific genes using complementary DNA subtraction and microarray analysis in three different species.

PubMed

Vallée, Maud; Gravel, Catherine; Palin, Marie-France; Reghenas, Hélène; Stothard, Paul; Wishart, David S; Sirard, Marc-André

2005-07-01

The main objective of the present study was to identify novel oocyte-specific genes in three different species: bovine, mouse, and Xenopus laevis. To achieve this goal, two powerful technologies were combined: a polymerase chain reaction (PCR)-based cDNA subtraction, and cDNA microarrays. Three subtractive libraries consisting of 3456 clones were established and enriched for oocyte-specific transcripts. Sequencing analysis of the positive insert-containing clones resulted in the following classification: 53% of the clones corresponded to known cDNAs, 26% were classified as uncharacterized cDNAs, and a final 9% were classified as novel sequences. All these clones were used for cDNA microarray preparation. Results from these microarray analyses revealed that in addition to already known oocyte-specific genes, such as GDF9, BMP15, and ZP, known genes with unknown function in the oocyte were identified, such as a MLF1-interacting protein (MLF1IP), B-cell translocation gene 4 (BTG4), and phosphotyrosine-binding protein (xPTB). Furthermore, 15 novel oocyte-specific genes were validated by reverse transcription-PCR to confirm their preferential expression in the oocyte compared to somatic tissues. The results obtained in the present study confirmed that microarray analysis is a robust technique to identify true positives from the suppressive subtractive hybridization experiment. Furthermore, obtaining oocyte-specific genes from three species simultaneously allowed us to look at important genes that are conserved across species. Further characterization of these novel oocyte-specific genes will lead to a better understanding of the molecular mechanisms related to the unique functions found in the oocyte.

Glycome Diagnosis of Human Induced Pluripotent Stem Cells Using Lectin Microarray*

PubMed Central

Tateno, Hiroaki; Toyota, Masashi; Saito, Shigeru; Onuma, Yasuko; Ito, Yuzuru; Hiemori, Keiko; Fukumura, Mihoko; Matsushima, Asako; Nakanishi, Mio; Ohnuma, Kiyoshi; Akutsu, Hidenori; Umezawa, Akihiro; Horimoto, Katsuhisa; Hirabayashi, Jun; Asashima, Makoto

2011-01-01

Induced pluripotent stem cells (iPSCs) can now be produced from various somatic cell (SC) lines by ectopic expression of the four transcription factors. Although the procedure has been demonstrated to induce global change in gene and microRNA expressions and even epigenetic modification, it remains largely unknown how this transcription factor-induced reprogramming affects the total glycan repertoire expressed on the cells. Here we performed a comprehensive glycan analysis using 114 types of human iPSCs generated from five different SCs and compared their glycomes with those of human embryonic stem cells (ESCs; nine cell types) using a high density lectin microarray. In unsupervised cluster analysis of the results obtained by lectin microarray, both undifferentiated iPSCs and ESCs were clustered as one large group. However, they were clearly separated from the group of differentiated SCs, whereas all of the four SCs had apparently distinct glycome profiles from one another, demonstrating that SCs with originally distinct glycan profiles have acquired those similar to ESCs upon induction of pluripotency. Thirty-eight lectins discriminating between SCs and iPSCs/ESCs were statistically selected, and characteristic features of the pluripotent state were then obtained at the level of the cellular glycome. The expression profiles of relevant glycosyltransferase genes agreed well with the results obtained by lectin microarray. Among the 38 lectins, rBC2LCN was found to detect only undifferentiated iPSCs/ESCs and not differentiated SCs. Hence, the high density lectin microarray has proved to be valid for not only comprehensive analysis of glycans but also diagnosis of stem cells under the concept of the cellular glycome. PMID:21471226

Microarray analysis of gene expression profiles in ripening pineapple fruits.

PubMed

Koia, Jonni H; Moyle, Richard L; Botella, Jose R

2012-12-18

Pineapple (Ananas comosus) is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC) analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study extends our knowledge of the molecular basis of pineapple fruit ripening and non-climacteric fruit ripening in general.

Microarray analysis of gene expression profiles in ripening pineapple fruits

PubMed Central

2012-01-01

Background Pineapple (Ananas comosus) is a tropical fruit crop of significant commercial importance. Although the physiological changes that occur during pineapple fruit development have been well characterized, little is known about the molecular events that occur during the fruit ripening process. Understanding the molecular basis of pineapple fruit ripening will aid the development of new varieties via molecular breeding or genetic modification. In this study we developed a 9277 element pineapple microarray and used it to profile gene expression changes that occur during pineapple fruit ripening. Results Microarray analyses identified 271 unique cDNAs differentially expressed at least 1.5-fold between the mature green and mature yellow stages of pineapple fruit ripening. Among these 271 sequences, 184 share significant homology with genes encoding proteins of known function, 53 share homology with genes encoding proteins of unknown function and 34 share no significant homology with any database accession. Of the 237 pineapple sequences with homologs, 160 were up-regulated and 77 were down-regulated during pineapple fruit ripening. DAVID Functional Annotation Cluster (FAC) analysis of all 237 sequences with homologs revealed confident enrichment scores for redox activity, organic acid metabolism, metalloenzyme activity, glycolysis, vitamin C biosynthesis, antioxidant activity and cysteine peptidase activity, indicating the functional significance and importance of these processes and pathways during pineapple fruit development. Quantitative real-time PCR analysis validated the microarray expression results for nine out of ten genes tested. Conclusions This is the first report of a microarray based gene expression study undertaken in pineapple. Our bioinformatic analyses of the transcript profiles have identified a number of genes, processes and pathways with putative involvement in the pineapple fruit ripening process. This study extends our knowledge of the molecular basis of pineapple fruit ripening and non-climacteric fruit ripening in general. PMID:23245313

Structurally distinct polycyclic aromatic hydrocarbons induce differential transcriptional responses in developing zebrafish

PubMed Central

Goodale, Britton C.; Tilton, Susan C.; Wilson, Glenn; Corvi, Margaret M.; Janszen, Derek B.; Anderson, Kim A.; Waters, Katrina M.; Tanguay, Robert L.

2014-01-01

Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous in the environment as components of fossil fuels and by-products of combustion. These multi-ring chemicals differentially activate the Aryl Hydrocarbon Receptor (AHR) in a structurally dependent manner, and induce toxicity via both AHR-dependent and-independent mechanisms. PAH exposure is known to induce developmental malformations in zebrafish embryos, and recent studies have shown cardiac toxicity induced by compounds with low AHR affinity. Unraveling the potentially diverse molecular mechanisms of PAH toxicity is essential for understanding the hazard posed by complex PAH mixtures present in the environment. We analyzed transcriptional responses to PAH exposure in zebrafish embryos exposed to benz(a)anthracene (BAA), dibenzothiophene (DBT) and pyrene (PYR) at concentrations that induced developmental malformations by 120 hours post-fertilization (hpf). Whole genome microarray analysis of mRNA expression at 24 and 48 hpf identified genes that were differentially regulated over time and in response to the three PAH structures. PAH body burdens were analyzed at both time points using GC-MS, and demonstrated differences in PAH uptake into the embryos. This was important for discerning dose-related differences from those that represented unique molecular mechanisms. While BAA misregulated the least number of transcripts, it caused strong induction of cyp1a and other genes known to be downstream of the AHR, which were not induced by the other two PAHs. Analysis of functional roles of misregulated genes and their predicted regulatory transcription factors also distinguished the BAA response from regulatory networks disrupted by DBT and PYR exposure. These results indicate that systems approaches can be used to classify the toxicity of PAHs based on the networks perturbed following exposure, and may provide a path for unraveling the toxicity of complex PAH mixtures. PMID:23656968

Controlling false-negative errors in microarray differential expression analysis: a PRIM approach.

PubMed

Cole, Steve W; Galic, Zoran; Zack, Jerome A

2003-09-22

Theoretical considerations suggest that current microarray screening algorithms may fail to detect many true differences in gene expression (Type II analytic errors). We assessed 'false negative' error rates in differential expression analyses by conventional linear statistical models (e.g. t-test), microarray-adapted variants (e.g. SAM, Cyber-T), and a novel strategy based on hold-out cross-validation. The latter approach employs the machine-learning algorithm Patient Rule Induction Method (PRIM) to infer minimum thresholds for reliable change in gene expression from Boolean conjunctions of fold-induction and raw fluorescence measurements. Monte Carlo analyses based on four empirical data sets show that conventional statistical models and their microarray-adapted variants overlook more than 50% of genes showing significant up-regulation. Conjoint PRIM prediction rules recover approximately twice as many differentially expressed transcripts while maintaining strong control over false-positive (Type I) errors. As a result, experimental replication rates increase and total analytic error rates decline. RT-PCR studies confirm that gene inductions detected by PRIM but overlooked by other methods represent true changes in mRNA levels. PRIM-based conjoint inference rules thus represent an improved strategy for high-sensitivity screening of DNA microarrays. Freestanding JAVA application at http://microarray.crump.ucla.edu/focus

Strategies for comparing gene expression profiles from different microarray platforms: application to a case-control experiment.

PubMed

Severgnini, Marco; Bicciato, Silvio; Mangano, Eleonora; Scarlatti, Francesca; Mezzelani, Alessandra; Mattioli, Michela; Ghidoni, Riccardo; Peano, Clelia; Bonnal, Raoul; Viti, Federica; Milanesi, Luciano; De Bellis, Gianluca; Battaglia, Cristina

2006-06-01

Meta-analysis of microarray data is increasingly important, considering both the availability of multiple platforms using disparate technologies and the accumulation in public repositories of data sets from different laboratories. We addressed the issue of comparing gene expression profiles from two microarray platforms by devising a standardized investigative strategy. We tested this procedure by studying MDA-MB-231 cells, which undergo apoptosis on treatment with resveratrol. Gene expression profiles were obtained using high-density, short-oligonucleotide, single-color microarray platforms: GeneChip (Affymetrix) and CodeLink (Amersham). Interplatform analyses were carried out on 8414 common transcripts represented on both platforms, as identified by LocusLink ID, representing 70.8% and 88.6% of annotated GeneChip and CodeLink features, respectively. We identified 105 differentially expressed genes (DEGs) on CodeLink and 42 DEGs on GeneChip. Among them, only 9 DEGs were commonly identified by both platforms. Multiple analyses (BLAST alignment of probes with target sequences, gene ontology, literature mining, and quantitative real-time PCR) permitted us to investigate the factors contributing to the generation of platform-dependent results in single-color microarray experiments. An effective approach to cross-platform comparison involves microarrays of similar technologies, samples prepared by identical methods, and a standardized battery of bioinformatic and statistical analyses.

Development and Comparison of Two Assay Formats for Parallel Detection of Four Biothreat Pathogens by Using Suspension Microarrays

PubMed Central

Janse, Ingmar; Bok, Jasper M.; Hamidjaja, Raditijo A.; Hodemaekers, Hennie M.; van Rotterdam, Bart J.

2012-01-01

Microarrays provide a powerful analytical tool for the simultaneous detection of multiple pathogens. We developed diagnostic suspension microarrays for sensitive and specific detection of the biothreat pathogens Bacillus anthracis, Yersinia pestis, Francisella tularensis and Coxiella burnetii. Two assay chemistries for amplification and labeling were developed, one method using direct hybridization and the other using target-specific primer extension, combined with hybridization to universal arrays. Asymmetric PCR products for both assay chemistries were produced by using a multiplex asymmetric PCR amplifying 16 DNA signatures (16-plex). The performances of both assay chemistries were compared and their advantages and disadvantages are discussed. The developed microarrays detected multiple signature sequences and an internal control which made it possible to confidently identify the targeted pathogens and assess their virulence potential. The microarrays were highly specific and detected various strains of the targeted pathogens. Detection limits for the different pathogen signatures were similar or slightly higher compared to real-time PCR. Probit analysis showed that even a few genomic copies could be detected with 95% confidence. The microarrays detected DNA from different pathogens mixed in different ratios and from spiked or naturally contaminated samples. The assays that were developed have a potential for application in surveillance and diagnostics. PMID:22355407

Microarray platform affords improved product analysis in mammalian cell growth studies

PubMed Central

Li, Lingyun; Migliore, Nicole; Schaefer, Eugene; Sharfstein, Susan T.; Dordick, Jonathan S.; Linhardt, Robert J.

2014-01-01

High throughput (HT) platforms serve as cost-efficient and rapid screening method for evaluating the effect of cell culture conditions and screening of chemicals. The aim of the current study was to develop a high-throughput cell-based microarray platform to assess the effect of culture conditions on Chinese hamster ovary (CHO) cells. Specifically, growth, transgene expression and metabolism of a GS/MSX CHO cell line, which produces a therapeutic monoclonal antibody, was examined using microarray system in conjunction with conventional shake flask platform in a non-proprietary medium. The microarray system consists of 60 nl spots of cells encapsulated in alginate and separated in groups via an 8-well chamber system attached to the chip. Results show the non-proprietary medium developed allows cell growth, production and normal glycosylation of recombinant antibody and metabolism of the recombinant CHO cells in both the microarray and shake flask platforms. In addition, 10.3 mM glutamate addition to the defined base media results in lactate metabolism shift in the recombinant GS/MSX CHO cells in the shake flask platform. Ultimately, the results demonstrate that the high-throughput microarray platform has the potential to be utilized for evaluating the impact of media additives on cellular processes, such as, cell growth, metabolism and productivity. PMID:24227746

Development and comparison of two assay formats for parallel detection of four biothreat pathogens by using suspension microarrays.

PubMed

Janse, Ingmar; Bok, Jasper M; Hamidjaja, Raditijo A; Hodemaekers, Hennie M; van Rotterdam, Bart J

2012-01-01

Microarrays provide a powerful analytical tool for the simultaneous detection of multiple pathogens. We developed diagnostic suspension microarrays for sensitive and specific detection of the biothreat pathogens Bacillus anthracis, Yersinia pestis, Francisella tularensis and Coxiella burnetii. Two assay chemistries for amplification and labeling were developed, one method using direct hybridization and the other using target-specific primer extension, combined with hybridization to universal arrays. Asymmetric PCR products for both assay chemistries were produced by using a multiplex asymmetric PCR amplifying 16 DNA signatures (16-plex). The performances of both assay chemistries were compared and their advantages and disadvantages are discussed. The developed microarrays detected multiple signature sequences and an internal control which made it possible to confidently identify the targeted pathogens and assess their virulence potential. The microarrays were highly specific and detected various strains of the targeted pathogens. Detection limits for the different pathogen signatures were similar or slightly higher compared to real-time PCR. Probit analysis showed that even a few genomic copies could be detected with 95% confidence. The microarrays detected DNA from different pathogens mixed in different ratios and from spiked or naturally contaminated samples. The assays that were developed have a potential for application in surveillance and diagnostics.

Assessment of data processing to improve reliability of microarray experiments using genomic DNA reference.

PubMed

Yang, Yunfeng; Zhu, Mengxia; Wu, Liyou; Zhou, Jizhong

2008-09-16

Using genomic DNA as common reference in microarray experiments has recently been tested by different laboratories. Conflicting results have been reported with regard to the reliability of microarray results using this method. To explain it, we hypothesize that data processing is a critical element that impacts the data quality. Microarray experiments were performed in a gamma-proteobacterium Shewanella oneidensis. Pair-wise comparison of three experimental conditions was obtained either with two labeled cDNA samples co-hybridized to the same array, or by employing Shewanella genomic DNA as a standard reference. Various data processing techniques were exploited to reduce the amount of inconsistency between both methods and the results were assessed. We discovered that data quality was significantly improved by imposing the constraint of minimal number of replicates, logarithmic transformation and random error analyses. These findings demonstrate that data processing significantly influences data quality, which provides an explanation for the conflicting evaluation in the literature. This work could serve as a guideline for microarray data analysis using genomic DNA as a standard reference.

Employing image processing techniques for cancer detection using microarray images.

PubMed

Dehghan Khalilabad, Nastaran; Hassanpour, Hamid

2017-02-01

Microarray technology is a powerful genomic tool for simultaneously studying and analyzing the behavior of thousands of genes. The analysis of images obtained from this technology plays a critical role in the detection and treatment of diseases. The aim of the current study is to develop an automated system for analyzing data from microarray images in order to detect cancerous cases. The proposed system consists of three main phases, namely image processing, data mining, and the detection of the disease. The image processing phase performs operations such as refining image rotation, gridding (locating genes) and extracting raw data from images the data mining includes normalizing the extracted data and selecting the more effective genes. Finally, via the extracted data, cancerous cell is recognized. To evaluate the performance of the proposed system, microarray database is employed which includes Breast cancer, Myeloid Leukemia and Lymphomas from the Stanford Microarray Database. The results indicate that the proposed system is able to identify the type of cancer from the data set with an accuracy of 95.45%, 94.11%, and 100%, respectively. Copyright © 2017 Elsevier Ltd. All rights reserved.

Improved microarray methods for profiling the yeast knockout strain collection

PubMed Central

Yuan, Daniel S.; Pan, Xuewen; Ooi, Siew Loon; Peyser, Brian D.; Spencer, Forrest A.; Irizarry, Rafael A.; Boeke, Jef D.

2005-01-01

A remarkable feature of the Yeast Knockout strain collection is the presence of two unique 20mer TAG sequences in almost every strain. In principle, the relative abundances of strains in a complex mixture can be profiled swiftly and quantitatively by amplifying these sequences and hybridizing them to microarrays, but TAG microarrays have not been widely used. Here, we introduce a TAG microarray design with sophisticated controls and describe a robust method for hybridizing high concentrations of dye-labeled TAGs in single-stranded form. We also highlight the importance of avoiding PCR contamination and provide procedures for detection and eradication. Validation experiments using these methods yielded false positive (FP) and false negative (FN) rates for individual TAG detection of 3–6% and 15–18%, respectively. Analysis demonstrated that cross-hybridization was the chief source of FPs, while TAG amplification defects were the main cause of FNs. The materials, protocols, data and associated software described here comprise a suite of experimental resources that should facilitate the use of TAG microarrays for a wide variety of genetic screens. PMID:15994458

An efficient method to identify differentially expressed genes in microarray experiments

PubMed Central

Qin, Huaizhen; Feng, Tao; Harding, Scott A.; Tsai, Chung-Jui; Zhang, Shuanglin

2013-01-01

Motivation Microarray experiments typically analyze thousands to tens of thousands of genes from small numbers of biological replicates. The fact that genes are normally expressed in functionally relevant patterns suggests that gene-expression data can be stratified and clustered into relatively homogenous groups. Cluster-wise dimensionality reduction should make it feasible to improve screening power while minimizing information loss. Results We propose a powerful and computationally simple method for finding differentially expressed genes in small microarray experiments. The method incorporates a novel stratification-based tight clustering algorithm, principal component analysis and information pooling. Comprehensive simulations show that our method is substantially more powerful than the popular SAM and eBayes approaches. We applied the method to three real microarray datasets: one from a Populus nitrogen stress experiment with 3 biological replicates; and two from public microarray datasets of human cancers with 10 to 40 biological replicates. In all three analyses, our method proved more robust than the popular alternatives for identification of differentially expressed genes. Availability The C++ code to implement the proposed method is available upon request for academic use. PMID:18453554

Clustering approaches to identifying gene expression patterns from DNA microarray data.

PubMed

Do, Jin Hwan; Choi, Dong-Kug

2008-04-30

The analysis of microarray data is essential for large amounts of gene expression data. In this review we focus on clustering techniques. The biological rationale for this approach is the fact that many co-expressed genes are co-regulated, and identifying co-expressed genes could aid in functional annotation of novel genes, de novo identification of transcription factor binding sites and elucidation of complex biological pathways. Co-expressed genes are usually identified in microarray experiments by clustering techniques. There are many such methods, and the results obtained even for the same datasets may vary considerably depending on the algorithms and metrics for dissimilarity measures used, as well as on user-selectable parameters such as desired number of clusters and initial values. Therefore, biologists who want to interpret microarray data should be aware of the weakness and strengths of the clustering methods used. In this review, we survey the basic principles of clustering of DNA microarray data from crisp clustering algorithms such as hierarchical clustering, K-means and self-organizing maps, to complex clustering algorithms like fuzzy clustering.

Specific Discrimination of Three Pathogenic Salmonella enterica subsp. enterica Serotypes by carB-Based Oligonucleotide Microarray

PubMed Central

Shin, Hwa Hui; Hwang, Byeong Hee; Seo, Jeong Hyun

2014-01-01

It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes. PMID:24185846

Specific discrimination of three pathogenic Salmonella enterica subsp. enterica serotypes by carB-based oligonucleotide microarray.

PubMed

Shin, Hwa Hui; Hwang, Byeong Hee; Seo, Jeong Hyun; Cha, Hyung Joon

2014-01-01

It is important to rapidly and selectively detect and analyze pathogenic Salmonella enterica subsp. enterica in contaminated food to reduce the morbidity and mortality of Salmonella infection and to guarantee food safety. In the present work, we developed an oligonucleotide microarray containing duplicate specific capture probes based on the carB gene, which encodes the carbamoyl phosphate synthetase large subunit, as a competent biomarker evaluated by genetic analysis to selectively and efficiently detect and discriminate three S. enterica subsp. enterica serotypes: Choleraesuis, Enteritidis, and Typhimurium. Using the developed microarray system, three serotype targets were successfully analyzed in a range as low as 1.6 to 3.1 nM and were specifically discriminated from each other without nonspecific signals. In addition, the constructed microarray did not have cross-reactivity with other common pathogenic bacteria and even enabled the clear discrimination of the target Salmonella serotype from a bacterial mixture. Therefore, these results demonstrated that our novel carB-based oligonucleotide microarray can be used as an effective and specific detection system for S. enterica subsp. enterica serotypes.