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Protein biomarkers for in vitro testing of toxicology
André Schrattenholz1, Vukić Šoškić, Rainer Schöpf
1ProteoSys AG, Carl-Zeiss-Str.51, D-55129 Mainz, Germany. andre.schrattenholz@proteosys.com
Abstract:
The vision of the toxicology in the 21st century movement is to overcome the currently used animal tests and identify molecular pathways of toxicity, using human in vitro systems with the aim to provide the most relevant mechanistic information for human risk assessment. It is expected to translate key surrogate biomarkers to novel types of toxicity-related high throughput screening of the many thousands of compounds which need to be tested during development phases of the pharmaceutical industry and with regard to the REACH legislation in Europe. Systems biology, an emerging and increasingly popular field of research, appears to be the discipline of choice to integrate results from transcriptomics, proteomics, epigenomics and metabonomics technologies used to analyze samples from toxicological models. The challenges, however, with respect to data generation, statistical treatment, bioinformatic integration and interpretation or in silico modeling remain formidable. One of the main difficulties is the fact that the sheer number of molecular species is inflated enormously in the course of translation from genes to proteins due to post-translational modifications. Moreover, at the level of proteins, time scales of cellular reactions to toxic insults can be very fast, ranging from milliseconds to seconds. Linear dynamic ranges of concentration differences between conditions can also differ by several orders of magnitude. So, the search for protein biomarkers of toxicity requires sophisticated strategies for time-resolved quantitative differential approaches. The statistical principles, normalization of primary data and principal component and cluster analysis have been well developed for genomics/transcriptomics and partly for proteomics, but have not been widely adapted to technologies like metabonomics. Also, the integration of functional data, in particular data from mass spectrometry, with the aim of modeling pathways of toxicity for human risk assessment, is still at an infant stage.
Insights
The 21st-century toxicology aims to replace animal testing with human in vitro systems to identify toxicity pathways. This approach utilizes systems biology and omics technologies for improved human risk assessment and compound screening.
Area of Science:
- Toxicology and Systems Biology
- Biomarker Discovery
- Computational Toxicology
Background:
- The "toxicology in the 21st century" movement seeks to replace traditional animal testing with human in vitro methods.
- This shift aims to provide mechanistic insights for human risk assessment and high-throughput screening of chemical compounds, particularly relevant for pharmaceutical development and REACH legislation.
- Systems biology offers a framework to integrate multi-omics data (transcriptomics, proteomics, epigenomics, metabonomics) for toxicological studies.
Purpose of the Study:
- To explore the integration of systems biology approaches for toxicological research.
- To identify challenges and strategies for utilizing multi-omics data in toxicology.
- To advance the development of human-relevant in vitro toxicity testing and risk assessment.
Main Methods:
- Utilizing transcriptomics, proteomics, epigenomics, and metabonomics to analyze toxicological models.
- Applying systems biology principles for data integration and interpretation.
- Developing sophisticated strategies for time-resolved quantitative differential analysis of protein biomarkers.
Main Results:
- Significant challenges exist in data generation, statistical analysis, bioinformatic integration, and in silico modeling for multi-omics toxicological data.
- Post-translational modifications greatly increase molecular species complexity.
- Rapid cellular responses and wide dynamic ranges in protein concentrations necessitate advanced analytical techniques.
Conclusions:
- Integrating multi-omics data within a systems biology framework is crucial for advancing predictive toxicology.
- Further development is needed in statistical methods and data integration, especially for metabonomics and mass spectrometry-based functional data.
- The ultimate goal is to establish robust in vitro human systems for accurate toxicity pathway identification and risk assessment.
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