Metabolomics as read-across tool: An example with 3-aminopropanol and 2-aminoethanol.

Read-across and grouping is one of the most commonly used alternative approaches for data gap filling in registrations submitted under the REACH Regulation as defined by the European Chemicals Agency (ECHA) in their 'Read-Across Assessment Framework' (RAAF, 2017). At the same time, the application of read-across is rejected by ECHA frequently due to various reasons. As a major reason hereof, applicants fail to reduce the level of 'remaining uncertainty' intrinsical to every read-across approach compared to testing a substance experimentally. Recently, the use of metabolomics to support read-across cases with biological information has been reported in a case study with phenoxy herbicides (Ravenzwaay et al., 2016). In the present case-study a 'weight-of-evidence' read-across approach from 2-aminoethanol (MEA = 'source') to 3-aminopropanol (3AP = 'target') with metabolomics as 'supporting evidence' reducing the remaining uncertainties is reported. We demonstrate the high structural similarity of the two analogous substances based on the available data and we report how metabolome data add confidence concerning mechanistic similarity in this read-across approach. Finally, the herein described read-across case supported by metabolomics is used to cover the data gaps in repeated dose and reproductive toxicity endpoint of 3AP via weight of evidence for the REACH-registration.

Metabolomics as read-across tool: A case study with phenoxy herbicides.

New technologies, such as metabolomics, can address chemical grouping and read across from a biological perspective. In a virtual case study, we selected MCPP as target substance and MCPA and 2,4-DP as source substances with the goal to waive a 90-day study with MCPP. In order to develop a convincing case to show how biological data can substantiate read across, we used metabolomics on blood samples from the 28-day studies to show the qualitative and quantitative similarity of the substances. The 28-day metabolome evaluation of source substances and the target substance indicate liver and kidneys as target organs. 2,4-DP was identified as the best source substance. Using the information of the 90-day 2,4-DP study, we predicted MCPP's toxicity profile at 2500 ppm: reduced food consumption and body weight gain, liver and kidney weight increases with clinical-pathology changes and a moderate red blood cell parameter reduction. NOEL prediction for MCPP was below that of 2,4-DP (<500 ppm), and similar to that of MCPA (≥150 ppm). Qualitatively, these predictions are comparable to the results of the real MCPP 90-day study in rats (reduced food consumption and body weight gain, weight increases and clinical-pathology changes in liver and kidneys, reduced red blood cells values). Quantitatively, the predicted NOAEL (150 ppm) is similar to the actual study (NOEL = 75 ppm, NOAEL ≤ 500 ppm). Thus, the 90-day rat toxicity study of MCPP could have been waived and substituted by the 90-day results of 2,4-DP by using metabolome data of 28 day studies.

The influence of the pH-value on the growth of Brevibacterium epidermidis in continuous culture.

Brevibacterium epidermidis is a major component of the bacterial flora of certain skin surface biotopes, characterized by a comparatively high pH-value. The presence of Brevibacterium epidermidis seems to be linked to the production of malodour. Skin surface pH has been found to be a major factor of bacterial growth on the skin. In order to find out if this might also apply to Brevibacterium epidermidis, this microorganism was grown in vitro in continuous culture using a chemostat. Specific growth rate and density of colony forming units were well correlated. While the organism grew readily from pH 5.5 to 8.5, this was not the case with a pH of 5.0. Thus pH-shifts induced by cosmetic procedures can only prevent unpleasant body odour due to abundant growth of bacteria if the pH-value is decreased to 5.0 or less.