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Detection of Environmental Pollution based on Behavioral Time-series Data from Danio rerio Tracking Experiments

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Behavior is what ultimately connects an organism to its environment. It integrates internal stimuli of the organism triggered by physiological and biochemical processes and stimuli from the environment. Behavioral disturbances can affect organisms, populations, and entire food webs in unpredictable ways. Changes in natural behaviors, can have direct or indirect effects of great significance. These changes can lead to impaired individual fitness, impaired population dynamics, or impaired community structures, thus promoting ecosystem disturbances. For this reason, behavior-based bioassays have high evidential value in detecting environmentally relevant toxins.

Danio rerio (zebrafish) is a well-established model organism in ecotoxicology and in neurotoxicity research and its nervous system is similar to that of mammals in many important aspects. Zebrafish larvae are widely used for neurotoxicity and drug efficacy studies and are also used to evaluate neurotoxicological effects of contaminants. One of the most important behavioral traits is the distinct locomotor response to a light stimulus, which can be quantified using the Light/Dark Transition Test (LDTT aka PMR).

In this project researchers from the Computational Ecotoxicology group at the Institute for Environmental Research (COPE), RWTH Aachen University develop an algorithm for the standardized and automatized statistical analysis of data from the LDTT/PMR with Danio rerio larvae using methods from multivariate statistics, machine learning and AI. The algorithm is intended to enable direct, automated analysis of LDTT/PMR data and the detection of behavioral, environmental toxicological effects directly from the raw data of the most common analytical systems. This is an important step towards using the test as a screening tool in various different application areas, such as consumer protection and neurotoxicological environmental research. In order to successfully establish the newly developed evaluation approaches in the practice of test application, it is necessary to develop a tool with an easily understandable interface to the raw data, which can be used by experimental biologists without explicit programming knowledge. The workflow should be easy to use and well documented so that the interpretation of results becomes as simple as possible.

With better statistics and efficient, streamlined data analysis, not only more sensitive analysis in the LDTT/PMR is possible, but also the advanced study of neurotoxic modes of action of chemicals and the application of the test to detect environmental toxicological effects based on detailed behavioral patterns. Given the large number of substances that remain to be tested for neurotoxic effects further development of the LDTT/PMR toward an automated but cost-effective high-throughput system makes this reaserch even more urgent. The developed algorithm will benefit different research areas, as it can be easily adapted to other test species, other bioanalytical systems, and different application areas (including drug discovery).


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Sep. 2023: Jaqueline Lange finishes her Master thesis called “Non-linear dynamics in behavior of Danio rerio larvae in the light-dark transition test”


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Oral presentations:



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Photo: Richard Ottermanns
Dr. rer. nat. Dipl.-Ing. Richard Ottermanns, main PI in the project, COPE work group leader at the Institute for Environmental Research, Contact-link
Photo: Katja Schröder
MSc Katja Schöder, Co-PI in the project, PhD-Thesis (ongoing): Development of sensitive statistics for chemobehavioral profiling with zebrafish light/dark transition test data, MSc-Thesis (2021): Application, advancement and automation of an existing algorithm for analysis of behavioural toxicity evaluated by the light/dark transition test with Danio rerio, Contact-link
Photo: Jaqueline Lange
BSc Jaqueline Lange, Co-investigator in the project, MSc-Thesis (ongoing): Non-linear dynamics in behavior of Danio rerio larvae in the light-dark transition test, Contact-link
Photo: Luca Frings
BSc Luca Frings, Co-investigator in the project, MSc-Thesis (ongoing): Sensitivity analysis of an autocorrelation model for behavior time-series derived from the light/dark transition test with Danio rerio embryos to evaluate the biological relevance of the model parameters, Contact-link


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This project is supported by the following partners:


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Herausgegeben im Auftrag des Rektors der Rheinisch-Westfälischen Technischen Hochschule (RWTH) Aachen.

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Inhaltliche Verantwortlichkeit

Ansprechpartner: Dr. Richard Ottermanns

Telefon: +49 241 80 26688

E-Mail: ottermanns(at)bio5(dot)rwth-aachen(dot)de

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Telefon: +49 241 80 26688

E-Mail: ottermanns(at)bio5(dot)rwth-aachen(dot)de

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