Development of a multiple-biomarker approach using the green-lipped mussel Perna viridis for marine pollution monitoring: a case study in Victoria Harbour, Hong Kong

Ryan Kar-Long Leung; Ling Jin; Hang-Kin Kong; Chen Su; Xingchao Ren; Xiaoshou Liu; Youji Wang; Menghong Hu; Kevin Wing Hin Kwok; Rudolf Shiu Sun Wu; Apple Pui-Yi Chui; James Kar-Hei Fang

doi:10.1016/j.marpolbul.2024.116684

Development of a multiple-biomarker approach using the green-lipped mussel Perna viridis for marine pollution monitoring: a case study in Victoria Harbour, Hong Kong

Mar Pollut Bull. 2024 Sep:206:116684. doi: 10.1016/j.marpolbul.2024.116684. Epub 2024 Jul 30.

Authors

Affiliations

¹ Department of Applied Biology and Chemical Technology, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China.
² Department of Civil and Environmental Engineering, and Department of Health Technology and Informatics, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China; State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China; Research Institute for Future Food, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China; Research Institute for Sustainable Urban Development, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China.
³ Research Institute for Future Food, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China; Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China.
⁴ Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China.
⁵ College of Marine Life Sciences and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ocean University of China, Qingdao 266003, China.
⁶ International Research Center for Marine Biosciences at Shanghai Ocean University, Ministry of Science and Technology, Shanghai 201306, China.
⁷ Research Institute for Future Food, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China; Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China; Research Institute for Land and Space, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China.
⁸ State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China; Department of Science and Environmental Studies, The Education University of Hong Kong, Tai Po, Hong Kong SAR, China.
⁹ State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China; Simon F.S. Li Marine Science Laboratory, School of Life Sciences, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China. Electronic address: applepychui@cuhk.edu.hk.
¹⁰ State Key Laboratory of Marine Pollution, City University of Hong Kong, Kowloon Tong, Hong Kong SAR, China; Research Institute for Future Food, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China; Research Institute for Sustainable Urban Development, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China; Department of Food Science and Nutrition, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China; Research Institute for Land and Space, The Hong Kong Polytechnic University, Hung Hom, Hong Kong SAR, China. Electronic address: james.fang@polyu.edu.hk.

PMID: 39083912
DOI: 10.1016/j.marpolbul.2024.116684

Abstract

Pollutants often exist as mixtures in environmental settings, creating a challenge in selecting the most effective combination of biomarkers for routine monitoring. This study was conducted seasonally in Victoria Harbour, Hong Kong, to compare the responses of nine biomarkers in the green-lipped mussel Perna viridis with respect to its tissue levels of persistent organic pollutants and heavy metals. Multivariate statistical techniques were utilised to determine the single best predictor and optimal subset of biomarkers in P. viridis for each of the four scenarios: representing overall biomarker responses in the dry season, and wet season, as well as correlating tissue levels of mixed pollutants in the dry season, and wet season. Our findings recommend lysosomal destabilisation, and the nucleic acid ratio of RNA to DNA, as the core biomarkers in P. viridis for marine pollution monitoring. The non-specificity of these biomarkers allows effective identification of pollution hotspots and guides further detailed assessment.

Keywords: Biomonitoring; Heavy metals; Lysosomal destabilisation; PAHs; RNA:DNA.

MeSH terms

Animals
Biomarkers* / analysis
Environmental Monitoring* / methods
Hong Kong
Metals, Heavy / analysis
Perna*
Seasons
Water Pollutants, Chemical* / analysis

Substances

Water Pollutants, Chemical
Biomarkers
Metals, Heavy