Effects of estrogens and antiestrogens on gene expression of fathead minnow (Pimephales promelas) early life stages.

Endocrine disrupting chemicals (EDCs) are known to contaminate aquatic environments and alter the growth and reproduction of organisms. The objective of this study was to evaluate the sensitivity and utility of fathead minnow (Pimephales promelas) early life-stages as a model to measure effects of estrogenic and antiestrogenic EDCs on physiological and gene expression endpoints relative to growth and reproduction. Embryos (<24-h postfertilization, hpf) were exposed to a potent estrogen (17α-ethinyl estradiol, EE(2) , 2, 10, and 50 ng L(-1)); a weak estrogen (mycotoxin zearalenone, ZEAR, same concentrations as above); an antiestrogen (ZM 189, 154; 40, 250, and 1000 ng L(-1)); and to mixtures of EE(2) and ZM until swim-up stage (∼170 hpf). Exposure to all concentrations of ZEAR and to the lowest concentration of ZM resulted in increased body sizes, whereas high concentrations of EE(2) decreased body sizes. There was a significant increase in the frequency of abnormalities (mostly edema) in larvae exposed to all concentrations of EE(2), and high ZEAR, and EE(2) + ZM mixture groups. Expression of growth hormone was upregulated by most of the conditions tested. Exposure to 50 ng L(-1) ZEAR caused an induction of insulin-like growth factor 1, whereas exposure to 40 ng L(-1) ZM caused a downregulation of this gene. Expression of steroidogenic acute regulatory protein gene was significantly upregulated after exposure to all concentrations of EE(2) and luteinizing hormone expression increased significantly in response to all treatments tested. As expected, EE(2) induced vitellogenin expression; however, ZEAR also induced expression of this gene to similar levels compared to EE(2). Overall, exposure to EE(2) + ZM mixture resulted in a different expression pattern compared to single exposures. The results of this study suggest that an early life stage 7-day exposure is sufficient to recognize and evaluate effects of estrogenic compounds on gene expression in this fish model.

Characterization of ontogenetic changes in gene expression in the fathead minnow (Pimephales promelas).

Recently, researchers have begun looking at changes in gene expression in the fathead minnow (Pimephales promelas) after contaminant exposure as a way to develop biomarkers of exposure and effects. However, the bulk of this research has been conducted on adults, with few studies focusing on early life stages. Expression of selected genes important in growth, development, and reproduction in teleosts was quantified by quantitative polymerase chain reaction during different developmental time periods (from 0 to 28 d postfertilization [dpf]). Over the developmental period studied, there was a significant up-regulation of growth hormone mRNA and no significant changes in the expression of insulin-like growth factor 1. Thyroid hormone receptors A and B were detected in 4 dpf embryos and their expression stayed relatively constant. The variation in cytochrome P45019A mRNA expression was large during the first week of development, returning to 0 dpf expression levels thereafter. Estrogen receptor 2B was up-regulated during the first three weeks postfertilization, returning to prehatch values by 28 dpf. Expression of hydroxysteroid dehydrogenase 3B and steroidogenic acute regulatory protein increased after the third or fourth week postfertilization, respectively. Vitellogenin exhibited a large degree of variation within time points, especially after day 15, and a significant up-regulation for this gene was observed at 7 and 10 dpf. Knowledge of the normal changes in gene expression during embryo and larval development will allow for better experimental design and selection of suitable biomarkers when testing the potential toxicological effects of contaminants in this model fish species.

A molecular beacon DNA microarray system for rapid detection of E. coli O157:H7 that eliminates the risk of a false negative signal.

A DNA hybridization based optical detection platform for the detection of foodborne pathogens has been developed with virtually zero probability of the false negative signal. This portable, low-cost and real-time assaying detection platform utilizes the color changing molecular beacon as a probe for the optical detection of the target sequence. The computer-controlled detection platform exploits the target hybridization induced change of fluorescence color due to the Förster (fluorescence) resonance energy transfer (FRET) between a pair of spectrally shifted fluorophores conjugated to the opposite ends of a beacon (oligonucleotide probe). Unlike the traditional fluorophore-quencher beacon design, the presence of two fluorescence molecules allows to actively visualize both hybridized and unhybridized states of the beacon. This eliminates false negative signal detection characteristic for the fluorophore-quencher beacon where bleaching of the fluorophore or washout of a beacon is indistinguishable from the absence of the target DNA sequence. In perspective, the two-color design allows also to quantify the concentration of the target DNA in a sample down to < =1 ng/microl. The new design is suitable for simultaneous reliable detection of hundreds of DNA target sequences in one test run using a series of beacons immobilized on a single substrate in a spatial format.

An information technology emphasis in biomedical informatics education.

Unprecedented growth in the interdisciplinary domain of biomedical informatics reflects the recent advancements in genomic sequence availability, high-content biotechnology screening systems, as well as the expectations of computational biology to command a leading role in drug discovery and disease characterization. These forces have moved much of life sciences research almost completely into the computational domain. Importantly, educational training in biomedical informatics has been limited to students enrolled in the life sciences curricula, yet much of the skills needed to succeed in biomedical informatics involve or augment training in information technology curricula. This manuscript describes the methods and rationale for training students enrolled in information technology curricula in the field of biomedical informatics, which augments the existing information technology curriculum and provides training on specific subjects in Biomedical Informatics not emphasized in bioinformatics courses offered in life science programs, and does not require prerequisite courses in the life sciences.

Induction of the transferrin receptor gene by benzo[a]pyrene in breast cancer MCF-7 cells: potential as a biomarker of PAH exposure.

Polycyclic aromatic hydrocarbons (PAHs) are widespread environmental DNA-damaging agents regarded as risk factors for human disease, including lung and breast cancer. The biotransformation of PAHs to carcinogenic metabolites is mediated by the aromatic hydrocarbon receptor (AhR), which activates transcription at xenobiotic responsive elements (XREs = 5'-GCGTG-3') found in the promoter regions of genes encoding for detoxifying enzymes, including CYP1A1 and CYP1B1. In this study, we wished to identify novel biomarkers that may be useful in monitoring critical carcinogenic events of the breast induced by PAHs. Using a GeneMAP CancerArray, we analyzed in breast cancer MCF-7 cells the temporal effects of the AhR agonist benzo[a]pyrene (B[a]P), which is a prototype PAH and known environmental carcinogen. Genes upregulated at least threefold by B[a]P and containing potential XREs within their promoter regions included CYP1A1, CYP1B1, paired box gene 3 (PAX3), cortactin (CTTN/EMS1), beta-2-microglobulin (B2M), and transferrin receptor (TfR). The stimulatory effects of B[a]P on expression of these genes were abrogated by cotreatment with the AhR antagonist flavonoid, alpha-napthoflavone (ANF). The TfR gene was selected for further analysis as its promoter region contains two potential XREs and its expression has been shown to be increased in breast cancer cells. Accumulation of TfR mRNA in B[a]P-treated cells was confirmed by quantitative real time PCR. Transient transfection studies indicated that the transcriptional activity of the TfR promoter was stimulated by B[a]P, whereas ANF counteracted this induction. These results indicate that the TfR gene may be a potential biomarker of PAH exposure.

3rd International Symposium on Early Toxicity Screening. 11 December 2002, Philadelphia, Pennsylvania, USA.

The 3rd International Symposium on Early Toxicity Screening: Early ADME-Tox Screening Approaches included presentations by primarily non-academic scientists, including biotechnology companies, pharmaceutical scientists and contract research service leaders. A central theme heard throughout the presentations involved the fundamental objectives of and obstacles to ADME and toxicity testing during drug development. In summary, successful preclinical drug safety assessment involves understanding a model's limited ability to mimic the human drug response, increasing the model's ability to mimic the human drug response, and adopting new strategies that model better human drug responses, while simultaneously conducting safety assessment more quickly, more thoroughly and more cost effectively.

Construction of a drug safety assurance information system based on clinical genotyping.

To capitalize on the vast potential of patient genetic information to aid in assuring drug safety, a substantial effort is needed in both the training of healthcare professionals and the operational enablement of clinical environments. Our research aims to satisfy these needs through the development of a drug safety assurance information system (GeneScription) based on clinical genotyping that utilizes patient-specific genetic information to predict and prevent adverse drug responses. In this paper, we present the motivations for this work, the algorithms at the heart of GeneScription, and a discussion of our system and its uses. We also describe our efforts to validate GeneScription through its evaluation by practicing pharmacists and pharmacy professors and its repeated use in training pharmacists. The positive assessment of the GeneScription software tool by these domain experts provides strong validation of the importance, accuracy, and effectiveness of GeneScription.

Pharmacogenomics training using an instructional software system.

OBJECTIVES: To implement an elective course in pharmacogenomics designed to teach pharmacy students about the fundamentals of pharmacogenomics and the anticipated changes it will bring to the profession. DESIGN: The 8 sessions of the course covered the basics of pharmacogenomics, genomic biotechnology, implementation of pharmacogenetics in pharmacy, information security and privacy, ethical issues related to the use of genomic data, pharmacoepidemiology, and use and promotion of GeneScription, a software program designed to mimic the professional pharmacy environment. ASSESSMENT: Student grades were based on completion of a patient education pamphlet, a 2-page paper on pharmacogenomics, and precourse and postcourse survey instruments. In the postcourse survey, all students strongly agreed that genomic data could be used to determine the optimal dose of a drug and genomic data for metabolizing enzymes could be stored in a safe place. Students also were more willing to submit deoxyribonucleic acid (DNA) data for genetic profiling and better understood how DNA analysis is performed after completing the course. CONCLUSIONS: An elective course in pharmacogenomics equipped pharmacy students with the basic knowledge necessary to make clinical decisions based on pharmacogenomic data and to teach other healthcare professionals and patients about pharmacogenomics. For personalized medicine to become a reality, all pharmacists and pharmacy students must learn this knowledge and these skills.

Development and evaluation of a PCR and mass spectroscopy (PCR-MS)-based method for quantitative, type-specific detection of human papillomavirus.

Knowledge of the central role of high-risk human papillomavirus (HPV) in cervical carcinogenesis, coupled with an emerging need to monitor the efficacy of newly introduced HPV vaccines, warrant development and evaluation of type-specific, quantitative HPV detection methods. In the present study, a prototype PCR and mass spectroscopy (PCR-MS)-based method to detect and quantitate 13 high-risk HPV types is compared to the Hybrid Capture 2 High-Risk HPV DNA test (HC2; Digene Corp., Gaithersburg, MD) in 199 cervical scraping samples and to DNA sequencing in 77 cervical tumor samples. High-risk HPV types were detected in 76/77 (98.7%) cervical tumor samples by PCR-MS. Degenerate and type-specific sequencing confirmed the types detected by PCR-MS. In 199 cervical scraping samples, all 13 HPV types were detected by PCR-MS. Eighteen (14.5%) of 124 cervical scraping samples that were positive for high-risk HPV by HC2 were negative by PCR-MS. In all these cases, degenerate DNA sequencing failed to detect any of the 13 high-risk HPV types. Nearly half (46.7%) of the 75 cervical scraping samples that were negative for high-risk HPV by the HC2 assay were positive by PCR-MS. Type-specific sequencing in a subset of these samples confirmed the HPV type detected by PCR-MS. Quantitative PCR-MS results demonstrated that 11/75 (14.7%) samples contained as much HPV copies/cell as HC2-positive samples. These findings suggest that this prototype PCR-MS assay performs at least as well as HC2 for HPV detection, while offering the additional, unique advantages of type-specific identification and quantitation. Further validation work is underway to define clinically meaningful HPV detection thresholds and to evaluate the potential clinical application of future generations of the PCR-MS assay.

Drug safety assurance through clinical genotyping: near-term considerations for a system-wide implementation of personalized medicine.

The rationale and overall system-wide behavior of a clinical genotyping information system (both DNA analysis and data management) requires a near-term, scalable approach, which is emerging in the focused implementation of pharmacogenomics and drug safety assurance. The challenges to implementing a successful clinical genotyping system are described, as are how the benefits of a focused, near-term system for drug safety assessment and assurance overcome the logistical and operational challenges that perpetually hinder the development of a societal-scale clinical genotyping system. This rationale is based on the premise that a focused application domain for clinical genotyping, specifically drug safety assurance, provides a transition paradigm for both professionals and consumers of healthcare, thereby facilitating the movement of genotyping from bench to bedside and paving the way for the adoption of prognostic and diagnostic applications in clinical genomics.

Interactive analysis of systems biology molecular expression data.

BACKGROUND: Systems biology aims to understand biological systems on a comprehensive scale, such that the components that make up the whole are connected to one another and work through dependent interactions. Molecular correlations and comparative studies of molecular expression are crucial to establishing interdependent connections in systems biology. The existing software packages provide limited data mining capability. The user must first generate visualization data with a preferred data mining algorithm and then upload the resulting data into the visualization package for graphic visualization of molecular relations. RESULTS: Presented is a novel interactive visual data mining application, SysNet that provides an interactive environment for the analysis of high data volume molecular expression information of most any type from biological systems. It integrates interactive graphic visualization and statistical data mining into a single package. SysNet interactively presents intermolecular correlation information with circular and heatmap layouts. It is also applicable to comparative analysis of molecular expression data, such as time course data. CONCLUSION: The SysNet program has been utilized to analyze elemental profile changes in response to an increasing concentration of iron (Fe) in growth media (an ionomics dataset). This study case demonstrates that the SysNet software is an effective platform for interactive analysis of molecular expression information in systems biology.

Technical issues in DNA microarray production and utilization: impact on clinical research.

The adoption and utilization of genomic technologies in healthcare requires that many issues surrounding the integrity of these assay platforms, as well as their overall impact on human health, be definitive. Many concerns common to DNA microarray production must be addressed to exploit the high-content screening capabilities of this assay platform for both genotyping and gene expression profiling in the clinic. Equally important to the success of genomic technology in healthcare is the development of a supporting information system that offers impact at both the personal and population level, and facilitates the adoption, use and, ultimately, impact of genomic information in therapeutic decision support.

Aligning experimental design with bioinformatics analysis to meet discovery research objectives.

The utility of genomic technology and bioinformatic analytical support to provide new and needed insight into the molecular basis of disease, development, and diversity continues to grow as more research model systems and populations are investigated. Yet deriving results that meet a specific set of research objectives requires aligning or coordinating the design of the experiment, the laboratory techniques, and the data analysis. The following paragraphs describe several important interdependent factors that need to be considered to generate high quality data from the microarray platform. These factors include aligning oligonucleotide probe design with the sample labeling strategy if oligonucleotide probes are employed, recognizing that compromises are inherent in different sample procurement methods, normalizing 2-color microarray raw data, and distinguishing the difference between gene clustering and sample clustering. These factors do not represent an exhaustive list of technical variables in microarray-based research, but this list highlights those variables that span both experimental execution and data analysis.