Progress towards an OECD reporting framework for transcriptomics and metabolomics in regulatory toxicology.

Omics methodologies are widely used in toxicological research to understand modes and mechanisms of toxicity. Increasingly, these methodologies are being applied to questions of regulatory interest such as molecular point-of-departure derivation and chemical grouping/read-across. Despite its value, widespread regulatory acceptance of omics data has not yet occurred. Barriers to the routine application of omics data in regulatory decision making have been: 1) lack of transparency for data processing methods used to convert raw data into an interpretable list of observations; and 2) lack of standardization in reporting to ensure that omics data, associated metadata and the methodologies used to generate results are available for review by stakeholders, including regulators. Thus, in 2017, the Organisation for Economic Co-operation and Development (OECD) Extended Advisory Group on Molecular Screening and Toxicogenomics (EAGMST) launched a project to develop guidance for the reporting of omics data aimed at fostering further regulatory use. Here, we report on the ongoing development of the first formal reporting framework describing the processing and analysis of both transcriptomic and metabolomic data for regulatory toxicology. We introduce the modular structure, content, harmonization and strategy for trialling this reporting framework prior to its publication by the OECD.

Identification of major loci and genomic regions controlling acid and volatile content in tomato fruit: implications for flavor improvement.

Plant metabolites are important to world food security due to their roles in crop yield and nutritional quality. Here we report the metabolic profile of 300 tomato accessions (Solanum lycopersicum and related wild species) by quantifying 60 primary and secondary metabolites, including volatile organic compounds, over a period of 2 yr. Metabolite content and genetic inheritance of metabolites varied broadly, both within and between different genetic groups. Using genotype information gained from 10 000 single nucleotide polymorphism markers, we performed a metabolite genome-wide association mapping (GWAS) study. We identified 79 associations influencing 13 primary and 19 secondary metabolites with large effects at high resolution. Four genome regions were detected, highlighting clusters of associations controlling the variation of several metabolites. Local linkage disequilibrium analysis and allele mining identified possible candidate genes which may modulate the content of metabolites that are of significant importance for human diet and fruit consumption. We precisely characterized two associations involved in fruit acidity and phenylpropanoid volatile production. Taken together, this study reveals complex and distinct metabolite regulation in tomato subspecies and demonstrates that GWAS is a powerful tool for gene-metabolite annotation and identification, pathways elucidation, and further crop improvement.

Predictive liver lipid biomarker signature of Acetyl-coenzyme A carboxylase inhibitor related developmental toxicity in non-pregnant female Han Wistar rats - Lipidomics biomarker discovery and validation.

INTRODUCTION: Acetyl-coenzyme A carboxylase (ACCase) inhibition is an attractive herbicide target. However, issues with fetal developmental toxicity identified at the late stages of the development process can halt progression of previously promising candidates. OBJECTIVES: To select and verify predictive lipid biomarkers of ACCase inhibition activity in vivo using liver samples obtained from early stage 7 day repeat dose studies in non-pregnant female Han Wistar rats that could be translated to developmental toxicity endpoints discovered during late-stage studies to provide an early screening tool. METHODS: Liver samples from eight rat repeat dose studies, exposed to six ACCase inhibitors from three different chemistries and one alternative mode of action (MoA) that also perturbs lipid biochemistry, were analysed using liquid chromatography - high resolution accurate mass - mass spectrometry. Multivariate and univariate data analysis methods were used for biomarker discovery and validation. RESULTS: A biomarker signature consisting of sixteen lipids biomarkers were selected. Verification of the signature as indicative of ACCase inhibition was established by demonstrating consistent perturbations in the biomarkers using two different ACCase inhibitor chemistries and the lack thereof with an alternate MoA. The fold change profile pattern was predictive of which test substance doses would or would not cause developmental toxicity. CONCLUSION: A strategy for selecting and verifying a robust signature of lipid biomarkers for predicting a toxicological end point has been described and demonstrated. Differences in lipidomic profiles correlated with developmental toxicity suggesting that indicators of a molecular initiation event resulting in pup developmental toxicity can be predicted from short term, toxicity studies conducted in non-pregnant adult female Han Wistar rats.

The Impact of Disturbed Soil Structure on the Degradation of 2 Fungicides Under Constant and Variable Moisture.

Degradation of agrochemicals in soil is frequently faster under field conditions than in laboratory studies. Field studies are carried out on relatively undisturbed soil, whereas laboratory studies typically use sieved soil, which can have a significant impact on the physical and microbial nature of the soil and may contribute to differences in degradation between laboratory and field studies. A laboratory study was therefore conducted to determine the importance of soil structure and variable soil moisture on the degradation of 2 fungicides (azoxystrobin and paclobutrazol) that show significant differences between laboratory and field degradation rates in regulatory studies. Degradation rates were measured in undisturbed cores of a sandy clay loam soil (under constant or variable moisture contents) and in sieved soil. For azoxystrobin, degradation rates under all conditions were similar (median degradation time [DegT50] 34-37 d). However, for paclobutrazol, degradation was significantly faster in undisturbed cores (DegT50 255 d in sieved soil and 63 d in undisturbed cores). Varying the moisture content did not further enhance degradation of either fungicide. Further examination into the impact of soil structure on paclobutrazol degradation, comparing undisturbed and sieved/repacked cores, revealed that the impact of sieving could not be mitigated by repacking the soil to a realistic bulk density. Examination of fungal and bacterial community structure using automated ribosomal spacer analysis showed significant initial differences between sieved/repacked and intact soil cores, although such differences were reduced at the end of the study (70 d). The present study demonstrates that disruption of soil structure significantly impacts microbial community structure, and for some compounds this may explain the differences between laboratory and field degradation rates. Environ Toxicol Chem 2021;40:2715-2725. © 2021 SETAC.

Understanding colour retention in red chilli pepper fruit using a metabolite profiling approach.

Carotenoids are the pigments responsible for conferring the characteristic deep red colour to chilli pepper. The post-harvest retention of this colour is a key trait that governs the price of the produce. Determining colour retention and the associated underlying biochemical mechanisms are important issues that require investigation. In this present study, the ability of image analysis to determine colour change in ground chilli fruit was evaluated. This method enabled differentiation of extreme retention phenotypes whilst also reducing the duration of storage required to make accurate determinations. The analysis of volatiles indicated different levels of lipid and carotenoid derived volatiles in lines with different retention properties. Metabolite profiling of intermediary metabolism supported these findings, with increased levels of unsaturated fatty acids present in lines with low retention properties. Collectively, these data have led us to propose that in chilli fruit lipid peroxidation is one of the progenitors of carotenoid degradation.

High throughput quantitative volatile profiling of melons with silicone rod extraction - thermal desorption - GC-MS for plant breeding line selection.

Volatile compounds determine the aroma of fruits, giving their unique flavor characteristics. The aim of many plant breeding projects is to improve the consumers' flavor experience when eating fresh produce. Large scale breeding trials produce thousands of samples which need volatile profiling amongst other phenotypes. Despite this interest, current methods have limitations: sampling unsuitable for field conditions, high cost and the inherent issue of highly variable data, which can hinder interpretation. We introduced a simple and robust sampling methodology based on silicone rod extraction, thermal desorption gas chromatography - mass spectrometry (GC-MS) to address these issues. We used differentiated calibration standards to generate quantitative data for metabolites of varying abundance. The method was used to profile 327 melons with high sensitivity (0.05-10 ng/mL, compound dependent), good reproducibility (7%) and differentiate melon varieties based on their volatile profile. The data were then used for line selection for a desired flavor profile.

Determination of phenols and chlorophenols as trimethylsilyl derivatives using gas chromatography-mass spectrometry.

A rapid and simple method is described for the simultaneous determination of 6 phenols (phenol, o-, m-, p-cresol, catechol and resorcinol) and 19 chlorophenols (all mono-, di-, tri-, and tetrachlorophenol isomers and pentachlorophenol) present in aqueous samples. The method is based on derivatization with trimethylsilyl-N,N-dimethylcarbamate (TMSDMC). In contrast to other derivatization agents, TMSDMC instantaneously reacts with the phenolic compounds at room temperature and no further sample processing is necessary prior to instrumental analysis. The determination of the derivatives was performed by capillary gas chromatography-mass spectrometry (GC-MS). The stability of the most instable trimethylsilyl derivative (pentachlorophenol) was studied using different excess levels of the derivatization reagent. The derivatization method was tested on spiked water samples preconcentrated by solid phase extraction on Isolute ENV+ cartridge. The overall method gave detection limits of 0.01-0.25 microg/L for all compounds and < 0.05 microg/L for 17 of them.

Metabolic differences in ripening of Solanum lycopersicum 'Ailsa Craig' and three monogenic mutants.

Application of mass spectrometry enables the detection of metabolic differences between groups of related organisms. Differences in the metabolic fingerprints of wild-type Solanum lycopersicum and three monogenic mutants, ripening inhibitor (rin), non-ripening (nor) and Colourless non-ripening (Cnr), of tomato are captured with regard to ripening behaviour. A high-resolution tandem mass spectrometry system coupled to liquid chromatography produced a time series of the ripening behaviour at discrete intervals with a focus on changes post-anthesis. Internal standards and quality controls were used to ensure system stability. The raw data of the samples and reference compounds including study protocols have been deposited in the open metabolomics database MetaboLights via the metadata annotation tool Isatab to enable efficient re-use of the datasets, such as in metabolomics cross-study comparisons or data fusion exercises.

Target list building for volatile metabolite profiling of fruit.

Fruit flavour is the combination of numerous biochemicals: sugars for sweetness, acids for sourness and volatile metabolites for aroma. The objective of this study was to establish a method to develop a target list of statistically relevant compounds for the characterization of melon from non-targeted data, while preserving the profile information. Five different varieties were sampled (sampling 12 biological replicates from 12 plants) using dynamic headspace extraction, then analysed by gas chromatography-mass spectrometry in full scan mode. Using Metalign and SIMCA-P software the raw data was spectrally aligned and then subjected to principal component analysis (PCA). The principal component analysis plot showed good separation of the five varieties based on their full scan GC-MS profile. Mass spectral data points responsible for the differences between varieties were highlighted by further statistical analysis. The mass spectra were then reconstructed and the corresponding chemicals identified using library search or reference standards were available to create a new target component list. To validate the new target list, the initial data set was re-processed using the targeted approach and the results subjected again to principal component analysis. The two representations showed excellent agreement on the separation of the five varieties. The new target list obtained from this study can be applied to differentiate and characterize the volatile profile of melon varieties using a list of statistically significant compounds.