Characterizing temporal variability and repeatability of dose-dependent functional genomics approach for evaluating...

Area of Science:

• Toxicogenomics
• Functional Genomics
• Chemical Safety Assessment

Background:

• Dose-dependent functional genomics identifies molecular initiating events (MIE) and points of departure (POD) for chemical toxification.
• Experimental design factors like dose, replicates, and time influence POD variability and repeatability.

Purpose of the Study:

• To evaluate POD profiles and MIE variability under triclosan (TCS) exposure using a dose-dependent functional genomics approach.
• To determine the optimal experimental design for POD and MIE identification in toxicological studies.
• To identify biomarkers for TCS exposure.

Main Methods:

• Utilized a dose-dependent functional genomics approach in Saccharomyces cerevisiae.
• Subsampled a full dataset (9 concentrations, 6 replicates) 484 times to simulate various experimental designs (4 dose groups, 5 replicate numbers).
• Analyzed POD profiles and identified MIE at multiple time points (9h, 24h, 48h).

Main Results:

• The optimal experimental design involved a wide dose range with narrow spacing at high concentrations (Dose C) and three replicates.
• POD variability was robust across designs, primarily influenced by dose range/interval rather than replicate number.
• The glycerophospholipid metabolism pathway was identified as the MIE for TCS toxification across all time points.
• 13 key mutant strains involved in TCS toxification MIE were identified as potential biomarkers.

Conclusions:

• The dose-dependent functional genomics approach is repeatable and effective for MIE identification.
• Experimental design, particularly dose range and spacing, significantly impacts POD, while replicate number has less influence.
• Identified MIE and biomarkers provide insights into TCS toxicity mechanisms and aid future study design.