由光電埤塘吳郭魚與模式青鱂魚評估鎵與銦對魚體之暴露風險及毒性潛勢指標

Abstract

光電埤塘（Photovoltaic pond）為政府近年推行漁電共生政策，廣泛於漁業養殖用地鋪設太陽能光電板之建設，鎵與銦則為光電板重要材料的成分。本研究透過生物累積與毒性潛勢分析探討光電埤塘中養殖吳郭魚暴露於鎵與銦的風險。吾人於桃園縣大觀地區兩處光電埤塘，石厝埤（ST）與大埔埤（DP），及一處未設有光電板之觀光埤塘桃園 3-5 圳（REF）採集水樣、底泥及吳郭魚（Oreochromis niloticus）樣品，進行鎵、銦與六種重金屬（鉛、鉻、鋅、銅、鎳、鎘）之濃度分析，以及魚樣肝臟之次世代定序差異基因表達分析（Next Generation Sequencing-Differential GeneExpression, NGS-DGE）。結果顯示，相較於參考點，兩處光電埤塘的水體皆能檢測出微量鎵濃度（0.21-1.02 µg/L）；即便水體中未檢出銦，三處埤塘之底泥皆可測得鎵（3.91~7.57 mg/kg）與銦（<0.030mg/kg）。兩處光電埤塘採集之魚體內部器官，包括性腺、肝、腦與肉，皆測得相較於參考點魚樣較高的鎵含量，其中光電埤塘二的吳郭魚性腺中鎵之生物濃縮係數（Bioconcentration Factor，BCF）可達 3267 L/kg。銦於魚體內部器官之分布相對較低（12.35~317.20 µg/kg）。水體其他重金屬物種如鉛、鉻於性腺之 BCF 可高達 19315 L/kg。由 NGS-DGE 之途徑豐度分析（Pathwayenrichment analysis）指出，兩處光電埤塘採集之魚樣相較於參考點有 25 個途徑受到顯著影響，其中以甘油脂代謝（Glycerolipid metabolism）、固醇類生合成（Steroid biosynthesis）、PPAR 傳訊途徑(Peroxisome proliferators-activated receptor signaling pathway, PPAR pathway)等脂肪酸代謝相關途徑最為明顯。吾人挑選與這些途徑最高度相關的差異基因設計引子進行定量聚合酶連鎖反應（Quantitative polymerase chain reaction, qPCR）驗證，結果顯示調控葡萄糖激酶之 gck 、蘋果酸酶的 me1、乙醯乙醯輔酶 A 之 aacs 與二未命名基因最能反應鎵對吳郭魚的差異效應，具高潛力做評估光電板對生態影響之生物指標。

Gallium (Ga) and indium (In) are technology-critical elements (TCEs) commonly used in the manufacturing of electronic products as essential materials of semiconductorselectro-optics, photovoltaic panels and etc. In the recent decades, the rise in the consumer markets for electronic devices has led to the drastic escalation in Ga and In production. Although increasing occurrences of Ga and In through anthropogenic activities were recognized as emerging contaminants and regulated in discharge of wastewaters of related industries in certain countries, these two TCEs are still reported with environmental concentrations below the legislated standards their sub-lethal toxic effects under environmentally relevant concentrations are less studied. At which their risks of exposure and toxicity remain undetermined with inadequate in-situ case studies and biomarkers. Originally used for aquaculture practice, Photovoltaic ponds installing with photovoltaic panels to produce electricity happened to be befitting sites for in-situ Ga and In risk assessments. Two photovoltaic ponds, ShihTsuo (ST) and DaPu (DP) in Taoyuan city of Taiwan, were selected to study possible exposure routes of Ga and In through aquaculture practice leading to potential risks of environmental toxicity and human health hazard, as compared to a referencepond (REF). With cultured tilapias (Oreochromis sp.) being the major biological indicators of these selected ponds, the objectives of this study include (1) to evaluate exposure risks of Ga and In towards tilapias, (2) to investigate toxic responses of tilapias by exploring biomarkers with RNA sequencing (RNAseq) and (3) to validate molecular biomarkers from tilapias using laboratory medakas fish (Oryzias latipes). In result, ST pond presented the highest concentrations of Ga in pond water (1.02 µg/L), fish gonad (2835.8 µg/kg) and liver (66.1 µg/kg) among all comparisons, while DP pond reached higher bioconcentration factor (3267 L/kg, gonadal BCF) for its lower Ga concentration in water (0.21 µg/L). The presence of In in gonads (81.7-121.5 µg/kg) and livers (17.4-31.9 µg/kg) from photovoltaic ponds were higher than REF (2.2 and 13.5 µg/kg, respectively), despite non-detectable in water samples among all sites (<0.04 µg/L). Neither Ga nor In exceeded current regulated water standards (0.01 mg/L), while their exposure were proven to be reflected by the more sensitive bioindicator, thus concluding possible risks of Ga and In towards cultivated tilapias. Hence, 25 bio-molecular pathways were identified to be potentially affected by Ga and In from the results of Next Generation SequencingDifferential Gene Expression (NGS-DGE) on tilapias following pathway enrichment analysis. In which the most significantly disturbed pathways were all lipid related, such as Glycerolipid metabolism, steroid biosynthesis and Peroxisome proliferators-activated receptor (PPAR) signaling pathways. Differentially expressed genes (DEGs) were then filtered from these pathways and further validated with quantitative polymerase chain reaction (qPCR) in Ga-exposed medakas. Overall resulting in five DEGs, gck, me1, aacs, ENSONIG27834 and ENSONIG13592, to be the most suitable biomarkers for Ga exposure and potential in situ biomonitoring indicators for future risk assessments on photovoltaic ponds.