Periodic Reporting for period 1 - TOXIFATE (Future Toxicology: Better predicting Toxicant-induced cell fate.)
Reporting period: 2020-10-01 to 2022-09-30
Current global prosperity and modern health care rely upon the safe use of chemicals in industry, agriculture, and medicine. This prosperity is entirely dependent upon robust toxicology that identifies toxic chemicals so harm human health or the environment. The use of in vitro and computational approaches to predict chemical toxicity is revolutionizing toxicology right now. This revolution will have scientific, societal and ethical impact as it aims to improve toxicity assessment while reducing costs, increasing the number of chemicals that can be assessed and reducing animal use. A recent breakthrough was that computational approaches can sometimes outperform animal testing in predicting human toxicity, demonstrating the promise of this approach. However, our understanding of chemical-induced changes in cell and molecular biology is still rudimentary and we don’t have sufficient data to complete the revolution. The TOXIFATE project is contributing to the revolution by multi-disciplinary training in in vitro toxicology and computational approaches and generating a new and large dataset that will improve the prediction of muscle toxicity.
TOXIFATE is:
1) Generating new datasets that show the quantitative relationships between cell stress and cell death responses using new in vitro biosensor assays.
2) Providing multi-disciplinary training of EU toxicologists in innovative in vitro and in silico technologies.
3) Contributing to society by improving chemical safety by providing new ways to quickly, ethically, and economically identify chemical hazards.
TOXIFATE is:
1) Generating new datasets that show the quantitative relationships between cell stress and cell death responses using new in vitro biosensor assays.
2) Providing multi-disciplinary training of EU toxicologists in innovative in vitro and in silico technologies.
3) Contributing to society by improving chemical safety by providing new ways to quickly, ethically, and economically identify chemical hazards.
In the first half of the project (01/10/2020–30/09/2022), TOXIFATE Doctoral Fellows (DFs) completed training in the methodology of TEMPO-Seq transcriptomics and bioinformatics provided by Bioclavis (UK) and began large data analysis and cheminformatics training provided by ProtoQSAR (Spain). The DFs also received training in toxicology, including toxicity assays, advanced cell culture methods, automated high-throughput and high-content screening, and live cell imaging.
The DFs tested thirty myotoxic chemicals at different concentrations on mouse C2C12 myoblasts and myotubes. The chemical’s effects were assessed by Cell Painting Assays and live-cell imaging to visualize changes in cell morphology and changes in cellular organelles. The resulting data were composed of single-cell phenotypic data including morphological measurements, intensity, symmetry, and texture properties. The DFs also generated transcriptomic data describing toxicant-induced changes in gene expression using TEMO-SEQ, a rapid and cost-effective technology suited to economically assessing transcriptomic changes in a large number of samples. Finally the project has generated a proteomic data set describing early events in myoblast differentiation. The resulting datasets (terabytes) describing the toxicant-induced responses in cell morphology and gene expression are now being used to build a models for myotoxicity prediction.
The DFs tested thirty myotoxic chemicals at different concentrations on mouse C2C12 myoblasts and myotubes. The chemical’s effects were assessed by Cell Painting Assays and live-cell imaging to visualize changes in cell morphology and changes in cellular organelles. The resulting data were composed of single-cell phenotypic data including morphological measurements, intensity, symmetry, and texture properties. The DFs also generated transcriptomic data describing toxicant-induced changes in gene expression using TEMO-SEQ, a rapid and cost-effective technology suited to economically assessing transcriptomic changes in a large number of samples. Finally the project has generated a proteomic data set describing early events in myoblast differentiation. The resulting datasets (terabytes) describing the toxicant-induced responses in cell morphology and gene expression are now being used to build a models for myotoxicity prediction.
1. First high-content screening data set of myoblasts and myotubes treated with muscle toxicants.
2. First transcriptomics data set of myoblasts and myotubes treated with muscle toxicants.
3. First proteomic data set comparing dying and differentiating muscle cells.
4. First identification of caspase substrates specifically cleaved in differentiating muscle cells.
5. First isolation of myoblasts committed to a specific cell fate.
Advance over the state-of-the-art expected to the end of the project:
The research advances made by TOXIFATE will impact improve the identification of toxicants using in vitro and silico approaches, reducing the dependence on animal testing, increasing the speed of toxicity testing and reducing the cost of testing. These advances will be implemented through TOXIFATE data that enables the production of new software that allows the in silico prediction of muscle toxicity. The project necessarily involves research into muscle stem cell cells involved in tissue repair and regeneration, and how these stem cells make life and death decisions. The proteomic dataset has relevance beyond toxicology; muscular dystrophies and muscle cancers (rhabdomyosarcomas) are diseases that are linked to defects in muscle repair and regeneration. Thus, the discoveries of TOXIFATE have the potential to identify new therapeutic strategies for these diseases.
2. First transcriptomics data set of myoblasts and myotubes treated with muscle toxicants.
3. First proteomic data set comparing dying and differentiating muscle cells.
4. First identification of caspase substrates specifically cleaved in differentiating muscle cells.
5. First isolation of myoblasts committed to a specific cell fate.
Advance over the state-of-the-art expected to the end of the project:
The research advances made by TOXIFATE will impact improve the identification of toxicants using in vitro and silico approaches, reducing the dependence on animal testing, increasing the speed of toxicity testing and reducing the cost of testing. These advances will be implemented through TOXIFATE data that enables the production of new software that allows the in silico prediction of muscle toxicity. The project necessarily involves research into muscle stem cell cells involved in tissue repair and regeneration, and how these stem cells make life and death decisions. The proteomic dataset has relevance beyond toxicology; muscular dystrophies and muscle cancers (rhabdomyosarcomas) are diseases that are linked to defects in muscle repair and regeneration. Thus, the discoveries of TOXIFATE have the potential to identify new therapeutic strategies for these diseases.