Selection of Reliable Biomarkers from PCR Array Analyses Using Relative Distance Computational Model: Methodology and Proof-of-Concept Study

It is increasingly evident about the difficulty to monitor chemical exposure through biomarkers as almost all the biomarkers so far proposed are not specific for any individual chemical. In this proof-of-concept study, adult male zebrafish (Danio rerio) were exposed to 5 or 25 µg/L 17β-estradiol (E2), 100 µg/L lindane, 5 nM 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) or 15 mg/L arsenic for 96 h, and the expression profiles of 59 genes involved in 7 pathways plus 2 well characterized biomarker genes, vtg1 (vitellogenin1) and cyp1a1 (cytochrome P450 1A1), were examined. Relative distance (RD) computational model was developed to screen favorable genes and generate appropriate gene sets for the differentiation of chemicals/concentrations selected. Our results demonstrated that the known biomarker genes were not always good candidates for the differentiation of pair of chemicals/concentrations, and other genes had higher potentials in some cases. Furthermore, the differentiation of 5 chemicals/concentrations examined were attainable using expression data of various gene sets, and the best combination was the set consisting of 50 genes; however, as few as two genes (e.g. vtg1 and hspa5 [heat shock protein 5]) were sufficient to differentiate the five chemical/concentration groups in the present test. These observations suggest that multi-parameter arrays should be more reliable for biomonitoring of chemical exposure than traditional biomarkers, and the RD computational model provides an effective tool for the selection of parameters and generation of parameter sets.越来越多的证据表明，通过生物标志物监测化学暴露存在较大难度，因为迄今为止提出的几乎所有生物标志物都无法针对某一种特定化学物质实现特异性识别。本概念验证研究中，将成年雄性斑马鱼（Danio rerio）暴露于5或25 µg/L的17β-雌二醇（17β-estradiol, E2）、100 µg/L林丹（lindane）、5 nM 2,3,7,8-四氯二苯并对二噁英（2,3,7,8-tetrachlorodibenzo-p-dioxin, TCDD）或15 mg/L砷中96小时，随后检测了7条通路相关的59个基因，以及2个已得到充分表征的生物标志物基因vtg1（卵黄蛋白原1，vitellogenin1）和cyp1a1（细胞色素P450 1A1，cytochrome P450 1A1）的表达谱。本研究开发了相对距离（Relative Distance, RD）计算模型，用于筛选适宜基因并生成合适的基因集，以区分所选化学物质/浓度组别。研究结果显示，已知的生物标志物基因并非总能作为区分特定化学物质/浓度对的优质候选基因，在部分场景中其他基因具备更高的区分潜力。此外，借助不同基因集的表达数据即可实现对本次检测的5种化学物质/浓度组别的区分，最优基因集包含50个基因；但仅需2个基因（例如vtg1与hspa5[热休克蛋白5，heat shock protein 5]）便可足够区分本次实验中的5个化学物质/浓度组别。上述观测结果表明，多参数阵列用于化学暴露的生物监测，相比传统生物标志物具备更高的可靠性；而RD计算模型可为参数筛选与参数集生成提供一种高效工具。