AQUA 2024

August 26 - 30, 2024

Copenhagen, Denmark

GENOME RESOURCE-BASED MULTI-OMICS APPROACH IN NON-MODEL AQUATIC ANIMALS FOR ENVIRONMENTAL HEALTH ASSESSMENT

Sang-Eun Nam1 , Somyeong Lee1 , Seong Duk Do1, Dae-Yeul Bae2, and Jae-Sung Rhee1,3,4,*

 

1 Department of Marine Science, College of Natural Sciences, Incheon National University, Incheon 22012,  Republic of Korea

2 Institute of Korea Eco-Network, Daejeon, 34028, South Korea

3 Research Institute of Basic Sciences, Incheon National University, Incheon 22012, South Korea

4 Yellow Sea Research Institute, Incheon 22012, Republic of Korea

 

*Correspondence: jsrhee@inu.ac.kr (J.-S. Rhee)

 



 In the field of aquatic ecotoxicology,  toxicity  assessment at molecular level through multi-omics approaches  has  been  primarily conducted in model organisms such as zebrafish and water fleas in laboratory rather than  on native species in real-world environments. In this study, we  aimed  to use a multi-omics platform  with non-model domestic species for health assessment by analyzing molecular  and biochemical responses. To facilitate omics applications , we  established  genome database for the swamp shrimp Neocaridina denticulata and the pale chub Zacco platypus.  For the  toxicity assessment of triclosan  (TCS)  as  an aquatic pollutant,  N. denticulata and Z. platypus  were  exposed to TCS for acute toxicity evaluation.  A range of TCS  concentrations below LC50 values  was determined to reduce mortality effects. We analyzed molecular and biochemical responses at the transcriptomic, proteomic, and metabolomic levels in response to TCS exposure. Finally, we integrated the three omics dataset such as transcriptome, proteome, and metabolome, obtained from the two species exposed to TCS. We found that glutathione metabolism was commonly changed in  both species in response to higher concentrations of TCS.  Furthermore,  N. denticulata  exhibited differential expression in carbohydrate metabolism such as glycolysis or starch metabolism, whereas Z . platypus showed significant changes in oxidative phosphorylation.  Through the integration of multi-omics datasets, we  identified several biomarkers with potential applications in health assessment and further validated their applicability in actual field environments.