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Effect-directed analysis (EDA) is increasingly used in environmental monitoring to detect and identify key toxicants. High-performance thin-layer chromatography (HPTLC) has proven to be a very suitable fractionation technique for this purpose. However, HPTLC is limited in its separation efficiency. Thus, separated fractions could still contain many different components and identification of the effective substances remains difficult. Therefore, in this study a workflow for selective EDA with two-dimensional HPTLC in combination with high-performance liquid chromatography-high-resolution mass spectrometry (HPLC-HRMS) was developed. The aim of the workflow was the stepwise reduction of the sample complexity in order to reduce the number of signals that could be responsible for the measured effects. As a consequence, the identification of effective substances should be facilitated. The acetylcholinesterase inhibition assay (AChE assay) for the detection of potential neurotoxic compounds was applied for biotesting. The transfer of effective zones from the first to the second dimension and also to the mass spectrometric measurement was enabled by extraction. A proof of concept was performed by spiking six acetylcholinesterase inhibiting substances into three different water matrices that were investigated with the developed workflow. The successful prioritization of all spiked compounds confirmed the efficiency of the workflow, regardless of the sample matrix. Biotesting of different water samples resulted in numerous potentially neurotoxic effects, which overlapped strongly in the first separation dimension. The higher peak capacity reached by two-dimensional HPTLC, on the other hand, resulted in discrete effective zones and enabled the identification of several compounds. For the substances lumichrome, a derivate of riboflavin and paraxanthine as well as for linear alkylbenzene sulfonates that were applied as anionic surfactants in detergents, the inhibiting effect to the AChE could be confirmed., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. The authors declare the following financial interests/personal relationships which may be considered as potential competing interests., (Copyright © 2020. Published by Elsevier B.V.)

There are thousands of organic trace substances in the environment that are not fully characterized, and evaluation of their relevance to the ecosystem is difficult. Effect-directed analysis (EDA) is a suitable tool to assess the effects of a substance via in-vitro bioassays, which can provide information about the relevance of the substance. High-performance thin-layer chromatography (HPTLC) has been shown to be a good method for fractionation. Environmental samples, however, often have high complexity, which is why the peak capacity of HPTLC is not sufficient. Therefore, this study focused on the development of selective two-dimensional (2D) HPTLC-EDA to increase the peak capacity and facilitate the identification of effective compounds. Thus, only effective zones were selected in the first dimension in terms of heart-cutting and were transferred to the second dimension through elution head-based extraction. Three 2D approaches were developed and validated. The best results in terms of peak capacity and orthogonality were achieved when the retardation factors of the first dimension were used to adjust the mobile phase (MP) for the second dimension. Applying the acetylcholinesterase (AChE) inhibition assay as an example EDA, analysis of spiked surface water by 2D HPTLC-EDA allowed zones with neurotoxic effects to responsible substances to be assigned. The 2D separation reduced the complexity of effective zones and thus facilitated the subsequent identification of effective compounds. Knowledge about a substancés effects enabled assessment of its relevance to the environment., (Copyright © 2017 Elsevier B.V. All rights reserved.)