Logit-log evaluation of planar yeast estrogen screens

Progress, applications, and challenges in high-throughput effect-directed analysis for toxicity driver identification - is it time for HT-EDA?

The rapid increase in the production and global use of chemicals and their mixtures has raised concerns about their potential impact on human and environmental health. With advances in analytical techniques, in particular, high-resolution mass spectrometry (HRMS), thousands of compounds and transformation products with potential adverse effects can now be detected in environmental samples. However, identifying and prioritizing the toxicity drivers among these compounds remain a significant challenge. Effect-directed analysis (EDA) emerged as an important tool to address this challenge, combining biotesting, sample fractionation, and chemical analysis to unravel toxicity drivers in complex mixtures. Traditional EDA workflows are labor-intensive and time-consuming, hindering large-scale applications. The concept of high-throughput (HT) EDA has recently gained traction as a means of accelerating these workflows. Key features of HT-EDA include the combination of microfractionation and downscaled bioassays, automation of sample preparation and biotesting, and efficient data processing workflows supported by novel computational tools. In addition to microplate-based fractionation, high-performance thin-layer chromatography (HPTLC) offers an interesting alternative to HPLC in HT-EDA. This review provides an updated perspective on the state-of-the-art in HT-EDA, and novel methods/tools that can be incorporated into HT-EDA workflows. It also discusses recent studies on HT-EDA, HT bioassays, and computational prioritization tools, along with considerations regarding HPTLC. By identifying current gaps in HT-EDA and proposing new approaches to overcome them, this review aims to bring HT-EDA a step closer to monitoring applications.

Non-target estrogenic screening of 60 pesticides, six plant protection products, and tomato, grape, and wine samples by planar chromatography combined with the planar yeast estrogen screen bioassay

For non-target residue analysis of xenoestrogens in food, sophisticated chromatographic-mass spectrometric techniques lack in biological effect detection. Various in vitro assays providing sum values encounter problems when opposing signals are present in a complex sample. Due to physicochemical signal reduction, cytotoxic or antagonistic effect responses, the resulting sum value is falsified. Instead, the demonstrated non-target estrogenic screening with an integrated planar chromatographic separation differentiated opposing signals, detected and prioritized important estrogenic compounds, and directly assigned tentatively the responsible compounds. Sixty pesticides were investigated, ten of which showed estrogenic effects. Exemplarily, half-maximal effective concentrations and 17β-estradiol equivalents were determined. Estrogenic pesticide responses were confirmed in six tested plant protection products. In food, such as tomato, grape, and wine, several compounds with an estrogenic effect were detected. It showed that rinsing with water was not sufficient to remove selected residues and illustrated that, though not usually performed for tomatoes, peeling would be more appropriate. Though not in the focus, reaction or breakdown products that are estrogenic were detected, underlining the great potential of non-target planar chromatographic bioassay screening for food safety and food control.

Planar chromatography - Current practice and future prospects

Planar chromatography, in the form of thin-layer or high-performance thin-layer chromatography (TLC, HPTLC), continues to provide a robust and widely used separation technique. It is unrivaled as a simple and rapid qualitative method for mixture analysis, or for finding bioactive components in mixtures. The format of TLC/HPTLC also provides a unique method for preserving the separation, enabling further investigation of components of interest (including quantification/structure determination) separated in both time and space from the original analysis. The current practice of planar chromatography and areas of development of the technology are reviewed and promising future directions in the use of TLC/HPTLC are outlined.

Estrogenic activity of food contact materials-evaluation of 20 chemicals using a yeast estrogen screen on HPTLC or 96-well plates

Food contact materials (FCM) may contain complex mixtures of estrogenic chemicals. A yeast estrogen screen performed on high performance thin-layer chromatography plates (planar-YES, P-YES) is promising for analysis of such mixtures, as it could allow for better elucidation of effects compared with established methods in microtiter plates. However, the P-YES has not been directly compared with established methods. We compared the performance of a microtiter plate YES (lyticase-YES, L-YES) to P-YES on silica gel HPTLC plates using 17β-estradiol (E2), 20 chemicals representative of migrants from plastic FCM, and three migrates of coated metal food cans. Effective doses (ED10, ED50) and estradiol equivalencies were calculated for each chemical. Thirteen chemicals had calculable EDs in the L-YES or P-YES, with average EDs 13-fold (range 0.63-36) more potent in P-YES than in the L-YES. Normalized to E2, the median estrogenicity was within 1.5-fold (0.43-8.8) between the assays. Therefore, P-YES was as or more sensitive than L-YES but potencies relative to E2 were comparable between assays. With chromatography, the P-YES detected estrogenicity in coated metal cans, effects that were unmeasurable in L-YES. With the sample preparation methods used in this study, both YES assays are sufficiently sensitive to detect bisphenol A below the specific migration limit for plastic packaging (0.05 mg/kg food). This study demonstrates that P-YES outperforms L-YES because it is more sensitive, provides comparable estradiol equivalents, and circumvents confounding mixture effects. The P-YES will be useful for routine monitoring of FCM and toxicant identification in problematic materials. Graphical abstract.

Combination of yeast-based in vitro screens with high-performance thin-layer chromatography as a novel tool for the detection of hormonal and dioxin-like compounds

The combination of classic in vitro bioassays with high-performance thin-layer chromatography (HPTLC) is a promising technique to directly link chemical analysis of contaminants to their potential adverse biological effects. With respect to endocrine disruption, much work is focused on estrogenicity. While a direct combination of HPTLC and the yeast estrogen screen is already developed, it is well accepted that further endocrine effects are relevant for monitoring environmental wellbeing. Here we show that non-estrogenic specific biological endpoints, (partly) related to the endocrine system, can also be addressed by combining respective yeast reporter gene assays with HPTLC to support effect-directed analysis (EDA). These are: androgenicity (YAS), thyroidogenicity (YTS), dioxin-like effects (YDS), effects on the vitamin D (YVS) and the retinoic acid receptor (YRaS). A proof of principle is demonstrated within this study by the characterization of dose-dependent responses to different model compounds for the respective receptors with and without chromatographic development of the HPTLC-plate. Limits of quantification (LOQ) for several model compounds were determined, e.g. 37 pg for testosterone (p-YAS), 0.476 ng for β-naphthoflavone (p-YDS) and 1.02 ng for calcipotriol hydrate (p-YVS) with chromatographic development. The LOQ for p-YTS and p-YRaS were 10.16 pg for 3,3',5-triiodothyroacetic acid (p-YTS) and 0.41 pg for tamibarotene (p-YRaS), without chromatographic separation. Furthermore, we challenged the developed methodology using environmental samples, demonstrating an elimination efficiency of androgenic activity from municipal wastewater by a wastewater treatment plant between 99.4 and 100%. We anticipate our methodology to substantially broaden the spectrum of specific endpoints combined with HPTLC for an efficient and robust screening of environmental samples to guide a subsequent in-depth EDA.