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Nianqing Xiao

Publications and source records attributed to Nianqing Xiao.

5 recordsLinked to original sources

Chemical effects in biological systems (CEBS) object model for toxicology data, SysTox-OM: design and application.

MOTIVATION: The CEBS data repository is being developed to promote a systems biology approach to understand the biological effects of environmental stressors. CEBS will house data from multiple gene expression platforms (transcriptomics), protein expression and protein-protein interaction (proteomics), and changes in low molecular weight metabolite levels (metabolomics) aligned by their detailed toxicological context. The system will accommodate extensive complex querying in a user-friendly manner. CEBS will store toxicological contexts including the study design details, treatment protocols, animal characteristics and conventional toxicological endpoints such as histopathology findings and clinical chemistry measures. All of these data types can be integrated in a seamless fashion to enable data query and analysis in a biologically meaningful manner. RESULTS: An object model, the SysBio-OM (Xirasagar et al., 2004) has been designed to facilitate the integration of microarray gene expression, proteomics and metabolomics data in the CEBS database system. We now report SysTox-OM as an open source systems toxicology model designed to integrate toxicological context into gene expression experiments. The SysTox-OM model is comprehensive and leverages other open source efforts, namely, the Standard for Exchange of Nonclinical Data (http://www.cdisc.org/models/send/v2/index.html) which is a data standard for capturing toxicological information for animal studies and Clinical Data Interchange Standards Consortium (http://www.cdisc.org/models/sdtm/index.html) that serves as a standard for the exchange of clinical data. Such standardization increases the accuracy of data mining, interpretation and exchange. The open source SysTox-OM model, which can be implemented on various software platforms, is presented here. AVAILABILITY: A universal modeling language (UML) depiction of the entire SysTox-OM is available at http://cebs.niehs.nih.gov and the Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http://cebs.niehs.nih.gov/cebsdownloads. Currently, the public toxicological data in CEBS can be queried via a web application based on the SysTox-OM at http://cebs.niehs.nih.gov CONTACT: xirasagars@saic.com SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Computational Biology↗

CEBS object model for systems biology data, SysBio-OM.

MOTIVATION: To promote a systems biology approach to understanding the biological effects of environmental stressors, the Chemical Effects in Biological Systems (CEBS) knowledge base is being developed to house data from multiple complex data streams in a systems friendly manner that will accommodate extensive querying from users. Unified data representation via a single object model will greatly aid in integrating data storage and management, and facilitate reuse of software to analyze and display data resulting from diverse differential expression or differential profile technologies. Data streams include, but are not limited to, gene expression analysis (transcriptomics), protein expression and protein-protein interaction analysis (proteomics) and changes in low molecular weight metabolite levels (metabolomics). RESULTS: To enable the integration of microarray gene expression, proteomics and metabolomics data in the CEBS system, we designed an object model, Systems Biology Object Model (SysBio-OM). The model is comprehensive and leverages other open source efforts, namely the MicroArray Gene Expression Object Model (MAGE-OM) and the Proteomics Experiment Data Repository (PEDRo) object model. SysBio-OM is designed by extending MAGE-OM to represent protein expression data elements (including those from PEDRo), protein-protein interaction and metabolomics data. SysBio-OM promotes the standardization of data representation and data quality by facilitating the capture of the minimum annotation required for an experiment. Such standardization refines the accuracy of data mining and interpretation. The open source SysBio-OM model, which can be implemented on varied computing platforms is presented here. AVAILABILITY: A universal modeling language depiction of the entire SysBio-OM is available at http://cebs.niehs.nih.gov/SysBioOM/. The Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http://cebs.niehs.nih.gov/cebsdownloads. The database and interface are being built to implement the model and will be available for public use at http://cebs.niehs.nih.gov.

Database Management Systems↗

Alterations in gene expression profiles during prostate cancer progression: functional correlations to tumorigenicity and down-regulation of selenoprotein-P in mouse and human tumors.

To identify molecular changes that occur during prostate tumor progression, we have characterized a series of prostate cancer cell lines isolated at different stages of tumorigenesis from C3(1)/Tag transgenic mice. Cell lines derived from low- and high-grade prostatic intraepithelial neoplasia, invasive carcinoma, and a lung metastasis exhibited significant differences in cell growth, tumorigenicity, invasiveness, and angiogenesis. cDNA microarray analysis of 8700 features revealed correlations between the tumorigenicity of the C3(1)/Tag-Pr cells and changes in the expression levels of genes regulating cell growth, angiogenesis, and invasion. Many changes observed in transcriptional regulation in this in vitro system are similar to those reported for human prostate cancer, as well as other types of human tumors. This analysis of expression patterns has also identified novel genes that may be involved in mechanisms of prostate oncogenesis or serve as potential biomarkers or therapeutic targets for prostate cancer. Examples include the L1-cell adhesion molecule, metastasis-associated gene (MTA-2), Rab-25, tumor-associated signal transducer-2 (Trop-2), and Selenoprotein-P, a gene that binds selenium and prevents oxidative stress. Many genes identified in the Pr-cell line model have been shown to be altered in human prostate cancer. The comprehensive microarray data provides a rational basis for using this model system for studies where alterations of specific genes or pathways are of particular interest. Quantitative real-time reverse transcription-PCR for Selenoprotein-P demonstrated a similar down-regulation of the transcript of this gene in a subset of human prostate tumors, mouse tumors, and prostate carcinoma cell lines. This work demonstrates that expression profiling in animal models may lead to the identification of novel genes involved in human prostate cancer biology.

Animals↗

Initiating oncogenic event determines gene-expression patterns of human breast cancer models.

Molecular expression profiling of tumors initiated by transgenic overexpression of c-myc, c-neu, c-ha-ras, polyoma middle T antigen (PyMT) or simian virus 40 T/t antigen (T-ag) targeted to the mouse mammary gland have identified both common and oncogene-specific events associated with tumor formation and progression. The tumors shared great similarities in their gene-expression profiles as compared with the normal mammary gland with an induction of cell-cycle regulators, metabolic regulators, zinc finger proteins, and protein tyrosine phosphatases, along with the suppression of some protein tyrosine kinases. Selection and hierarchical clustering of the most variant genes, however, resulted in separating the mouse models into three groups with distinct oncogene-specific patterns of gene expression. Such an identification of targets specified by particular oncogenes may facilitate development of lesion-specific therapeutics and preclinical testing. Moreover, similarities in gene expression between human breast cancers and the mouse models have been identified, thus providing an important component for the validation of transgenic mammary cancer models.

Animals↗

ATP-dependent mobilization of the glucocorticoid receptor during chromatin remodeling.

Chromatin remodeling by the glucocorticoid receptor (GR) is associated with activation of transcription at the mouse mammary tumor virus (MMTV) promoter. We reconstituted this nucleoprotein transition with chromatin assembled on MMTV DNA. The remodeling event was ATP dependent and required either a nuclear extract from HeLa cells or purified human Swi/Snf. Through the use of a direct interaction assay (magnetic bead pull-down), we demonstrated recruitment of human Swi/Snf to MMTV chromatin by GR. Unexpectedly, we found that GR is actively displaced from the chromatin template during the remodeling process. ATP-dependent GR displacement was reversed by the addition of apyrase and was specific to chromatin templates. The disengagement reaction could also be induced with purified human Swi/Snf. Although GR apparently dissociated during chromatin remodeling by Swi/Snf, it participated in binding of the secondary transcription factor, nuclear factor 1. These results are paralleled by a recent discovery that the hormone-occupied receptor undergoes rapid exchange between chromatin and the nucleoplasmic compartment in living cells. Both the in vitro and in vivo results are consistent with a dynamic model (hit and run) in which GR first binds to chromatin after ligand activation, recruits a remodeling activity, facilitates transcription factor binding, and is simultaneously lost from the template.

Adenosine Triphosphate↗