Development of a genotoxicity/carcinogenicity assessment method by DNA adductome analysis.

Safety evaluation is essential for the development of chemical substances. Since in vivo safety evaluation tests, such as carcinogenesis tests, require long-term observation using large numbers of experimental animals, it is necessary to develop alternative methods that can predict genotoxicity/carcinogenicity in the short term, taking into account the 3Rs (replacement, reduction, and refinement). We established a prediction model of the hepatotoxicity of chemicals using a DNA adductome, which is a comprehensive analysis of DNA adducts that may be used as an indicator of DNA damage in the liver. An adductome was generated with LC-high-resolution accurate mass spectrometer (HRAM) on liver of rats exposed to various chemicals for 24 h, based on two independent experimental protocols. The resulting adductome dataset obtained from each independent experiment (experiments 1 and 2) and integrated dataset were analyzed by linear discriminant analysis (LDA) and found to correctly classify the chemicals into the following four categories: non-genotoxic/non-hepatocarcinogens (-/-), genotoxic/non-hepatocarcinogens (+/-), non-genotoxic/hepatocarcinogens (-/+), and genotoxic/hepatocarcinogens (+/+), based on their genotoxicity/carcinogenicity properties. A prototype model for predicting the genotoxicity/carcinogenicity of the chemicals was established using machine learning methods (using random forest algorithm). When the prototype genotoxicity/carcinogenicity prediction model was used to make predictions for experiments 1 and 2 as well as the integrated dataset, the correct response rates were 89 % (genotoxicity), 94 % (carcinogenicity) and 87 % (genotoxicity/carcinogenicity) for experiment 1, 47 % (genotoxicity), 62 % (carcinogenicity) and 42 % (genotoxicity/carcinogenicity) for experiment 2, and 52 % (genotoxicity), 62 % (carcinogenicity), and 48 % (genotoxicity/carcinogenicity) for the integrated dataset. To improve the accuracy of the toxicity prediction model, the toxicity label was reconstructed as follows; Pattern 1: when +/+ and -/- chemicals were used from the toxicity labels +/+, +/-, -/+ and -/-; and Pattern 2: when +/+, +/-, and -/+ other than -/- were replaced with the label "Others". As a result, chemicals with only +/+ and -/- toxicity labels were used and the correct response rates were approximately 100 % for the measured data in experiment 1, 53 %-66 % for the data in experiment 2, and 59-73 % for the integrated data, all of which were 10 %-30 % higher compared with the data before the label change. In contrast, when the toxicity labels were replaced with -/- and "Others", they reached nearly 100 % in the measured data from experiment 1, 65 %-75 % in the data from experiment 2, and 70 %-78 % in the integrated data, all of which were 10 %-50 % higher compared with the data before the label change.

Genome Projector: zoomable genome map with multiple views.

BACKGROUND: Molecular biology data exist on diverse scales, from the level of molecules to -omics. At the same time, the data at each scale can be categorised into multiple layers, such as the genome, transcriptome, proteome, metabolome, and biochemical pathways. Due to the highly multi-layer and multi-dimensional nature of biological information, software interfaces for database browsing should provide an intuitive interface that allows for rapid migration across different views and scales. The Zoomable User Interface (ZUI) and tabbed browsing have proven successful for this purpose in other areas, especially to navigate the vast information in the World Wide Web. RESULTS: This paper presents Genome Projector, a Web-based gateway for genomics information with a zoomable user interface using Google Maps API, equipped with four seamlessly accessible and searchable views: a circular genome map, a traditional genome map, a biochemical pathways map, and a DNA walk map. The Web application for 320 bacterial genomes is available at http://www.g-language.org/GenomeProjector/. All data and software including the source code, documentations, and development API are freely available under the GNU General Public License. Zoomable maps can be easily created from any image file using the development API, and an online data mapping service for Genome Projector is also available at our Web site. CONCLUSION: Genome Projector is an intuitive Web application for browsing genomics information, implemented with a zoomable user interface and tabbed browsing utilising Google Maps API and Asynchronous JavaScript and XML (AJAX) technology.

Pathway projector: web-based zoomable pathway browser using KEGG atlas and Google Maps API.

BACKGROUND: Biochemical pathways provide an essential context for understanding comprehensive experimental data and the systematic workings of a cell. Therefore, the availability of online pathway browsers will facilitate post-genomic research, just as genome browsers have contributed to genomics. Many pathway maps have been provided online as part of public pathway databases. Most of these maps, however, function as the gateway interface to a specific database, and the comprehensiveness of their represented entities, data mapping capabilities, and user interfaces are not always sufficient for generic usage. METHODOLOGY/PRINCIPAL FINDINGS: We have identified five central requirements for a pathway browser: (1) availability of large integrated maps showing genes, enzymes, and metabolites; (2) comprehensive search features and data access; (3) data mapping for transcriptomic, proteomic, and metabolomic experiments, as well as the ability to edit and annotate pathway maps; (4) easy exchange of pathway data; and (5) intuitive user experience without the requirement for installation and regular maintenance. According to these requirements, we have evaluated existing pathway databases and tools and implemented a web-based pathway browser named Pathway Projector as a solution. CONCLUSIONS/SIGNIFICANCE: Pathway Projector provides integrated pathway maps that are based upon the KEGG Atlas, with the addition of nodes for genes and enzymes, and is implemented as a scalable, zoomable map utilizing the Google Maps API. Users can search pathway-related data using keywords, molecular weights, nucleotide sequences, and amino acid sequences, or as possible routes between compounds. In addition, experimental data from transcriptomic, proteomic, and metabolomic analyses can be readily mapped. Pathway Projector is freely available for academic users at (http://www.g-language.org/PathwayProjector/).