Author: Leung, Kar Long
Title: The use of multiple biomarkers in marine pollution monitoring: a case study in Victoria Harbour, Hong Kong
Advisors: Fang, James (ABCT)
Degree: M.Phil.
Year: 2022
Subject: Marine pollution -- Measurement
Environmental monitoring
Biochemical markers
Water quality management
Hong Kong Polytechnic University -- Dissertations
Department: Department of Applied Biology and Chemical Technology
Pages: xiii, 60 pages : color illustrations, map
Language: English
Abstract: The rapid growth of human population, industrialisation and urbanisation in coastal areas have resulted in different extents of marine pollution worldwide. For instance, heavy metals and persistent organic pollutants (POPs) are chemical pollutants that have received great attention owing to their persistency and bioaccumulation nature. In the case of Hong Kong waters, the presence of heavy metals such as cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb) and zinc (Zn), and POPs such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs) and organochlorine pesticides (OCPs), have been reported since the 1980s. Chemical analyses and monitoring of heavy metals and POPs are routinely carried out in seawater and sediments in Hong Kong and elsewhere, but it should be noted that such results of environmental concentrations do not provide any information about bioavailability of these pollutants. To address this concern, the biomonitoring approach has been proposed, in which one could select a model animal and analyse the bioaccumulated level of a target pollutant to indicate its bioavailable fraction. A range of cellular biomarkers have also been developed to indicate the biological responses of the model animal to the target pollutant. This information of biological impact is essential for the ecological risk assessment of the pollutant. However, pollutants usually occur as a mixture in the environment, and it remains a challenge on how to select the optimal combination of biomarkers for pollution monitoring in this cocktail situation.
Victoria Harbour, Hong Kong, was investigated here as a case study to tackle this challenge by identifying the optimal subset of biomarkers in the green-lipped mussel Perna viridis that can explain the maximal variability of mixed pollutants using multivariate statistical techniques. We adopted a transplantation approach in the fieldwork, where all mussels were collected from a reference site and redeployed at the same site and four other polluted sites within Victoria Harbour. There were two rounds of mussel transplantation that lasted five weeks each in the dry season and wet season of 2019 (5 sites × 2 seasons). Mussels were then retrieved and processed (n = 10 per site, each n pooled from 10 mussels), from which haemolymph was freshly extracted to assess lysosomal destabilisation (LysD) and micronucleus frequency (MN), while hepatopancreas was used to determine seven other biomarkers, namely superoxide dismutase (SOD), catalase (CAT), glutathione (GSH), acetylcholinesterase (AChE), lipid peroxidation (LPx), the nucleic acid ratio of RNA to DNA (R:D) and the total energy reserve (Et). The remaining soft tissue was used to analyse Cd, Cr, Cu, Pb, Zn and 16 forms of low-molecular-weight (LMW) and high-molecular-weight (HMW) PAHs, as well as 28 congeners of PCBs and 21 types of OCPs, following established methods. Since PCBs and OCPs were not detectable in all samples, seven variables of detected pollutants (Cd, Cr, Cu, Pb, Zn, LMW PAHs and HMW PAHs) and nine variables of biomarkers in P. viridis (SOD, CAT, GSH, AChE, LysD, MN, LPx, R:D and Et) obtained from five sites in two seasons were analysed with the multivariate statistical software PRIMER 7.
Significantly the lowest levels of Cu, LMW PAHs and HMW PAHs were found in P. viridis at the reference site regardless of the season. The reference-site mussels also showed the lowest concentrations of Cd and Zn in the dry season and Cr in the wet season, but relatively high levels of Pb. The results of principal component analysis (PCA) identified LMW PAHs and HMW PAHs as two key variables to drive the reference-site samples to cluster away from the within-harbour samples, based on PC1 and PC2 (cumulative variation: 58-62%). This spatial clustering was more pronounced in the dry season than wet season, as revealed by the results of non-metric multi-dimensional scaling (nMDS; 2D stress: 0.16-0.19) and the similarity profile analysis (SIMPROF; p < 0.05). As for the biomarkers, P. viridis at the reference site showed significantly the highest levels of SOD and AChE and lowest extents of LysD, MN and Et in the dry season, but the highest values of CAT, AChE and R:D and lowest levels of GSH and LysD in the wet season, compared to the within-harbour sites. The results of PCA, using PC1 and PC2, revealed that the different biological responses of mussels between the reference site and within-harbour sites were mainly due to CAT, LysD and MN in the dry season, and GSH and LysD in the wet season (cumulative variation: 49-50%). The similarity and dissimilarity among samples based on the nine variables of biomarkers were elucidated using nMDS (2D stress: 0.19) and SIMPROF (p < 0.05), in which most of the reference-site samples formed their own cluster regardless of the season.
To link these biological changes to the tissue burden of heavy metals and PAHs in P. viridis, the routine for linking of biota to environment (BIOENV) was employed to derive the single best biomarker that provided the highest correlation with the similarity matrix of pollutants per season, where LysD and R:D were identified in the dry season (ρ = 0.20) and wet season (ρ = 0.14), respectively (p < 0.001). Moreover, the optimal subset predictors for the pollutants were derived to be LysD, R:D, GSH and AChE in the dry season (ρ = 0.33), and LysD, R:D, CAT and Et in the wet season (ρ = 0.25; p < 0.01). Based on these BIOENV results, LysD and R:D appeared to be the two most responsive biomarkers to the cocktail situation of heavy metals and PAHs, among the nine tested biomarkers in P. viridis. LysD is a cytohistological biomarker of effect, which quantifies the swelling or bursting of lysosomes induced by sequestration and overload of xenobiotics. R:D is a biomarker of growth at the molecular level, of which a higher value indicates a greater growth potential, given that the quantity of DNA is relatively stable but that of RNA increases along with protein synthesis. In conclusion, we recommend LysD and R:D in P. viridis to be two core biomarkers for marine pollution montoring in Hong Kong waters, and our findings are applicable to other Indo-Pacific areas where P. viridis is abundant. The non-specific nature of LysD and R:D makes them suitable as a screening tool to pinpoint the pollution hotspots, which can then be assessed with other more specific biomarkers and sophisticated chemical analyses to characterise the pollutants and their biological impacts.
Rights: All rights reserved
Access: open access

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