代谢组学在量子点毒性研究中的应用进展及前景

量子点是由Ⅱ～Ⅵ或Ⅲ～Ⅴ族元素组成的半导体纳米微晶体。因其独特的光电学特性,例如荧光强度高和稳定性好,被广泛应用于生命科学领域,用于荧光探针、药学研究、医学成像和生物芯片等。但是,由于应用较广的量子点成分通常含有重金属,研究者普遍认为量子点具有一定的毒性,因而通过毒理学研究来评价量子点的生物安全性对于量子点的生物学应用至关重要。代谢组学是利用分析化学方法来研究一个代谢组中小分子代谢相关物质的含量,以及内外因素导致其变化规律的学科。目前,越来越多的研究者将代谢组学应用于量子点毒性研究中,利用其生物标志物的特异性,为量子点毒性研究提供了新的思路和技术。应用代谢组学不但提高了纳米毒理学研究的完善度,更可以准确地研究某些以前在量子点低剂量暴露后无法发现的生化反应。本文重点阐述了代谢组学在量子点毒性研究中的应用进展及发展前景,为以后相关的研究方向和研究内容提供有价值的参考。     

基于代谢组学指标的土壤亚致死剂量汞对蚯蚓的毒性研究

将赤子爱胜蚓(Eisenia fetida)暴露于亚致死剂量(1.0、5.0、25.0 mg·kg~(-1))汞污染土壤中4周,以蚯蚓个体(致死率、体重增长率)及小分子代谢物(代谢组)为指标研究其对汞的动态毒性响应,并采用最小二乘判别分析(OPLSA-DA)对暴露组及对照组的代谢物进行分类,进而识别潜在的标记物.结果表明,蚯蚓对汞的吸收尚未达到稳态,蚯蚓体内代谢物的响应依赖于暴露剂量及暴露时间.暴露1周时,蚯蚓体重略有增长但不显著;最低暴露剂量(1.0 mg·kg~(-1))导致蚯蚓体内亮氨酸、异亮氨酸、色氨酸、组氨酸、酪氨酸、5-氧脯氨酸、2-脱氧肌苷显著低于对照水平,柠檬酸、肌苷酸与腺苷在5.0、25.0 mg·kg~(-1)剂量下显著高于对照水平;暴露4周时,最高暴露剂量(25 mg·kg~(-1))显著抑制了蚯蚓的生长;汞添加组的蚯蚓体内谷氨酸、酪氨酸、马来酸、2-脱氧肌苷水平显著低于对照.上述代谢物对汞的动态变化表明它们可作为潜在生物标记物,用于诊断土壤汞污染.对代谢途径分析发现,1.0～25.0 mg·kg~(-1)汞即可破坏蚯蚓正常氨基酸代谢、三羧酸循环,扰乱能量代谢,对蚯蚓产生氧化损伤.本研究结果表明,相比个体水平的受试终点,代谢组学指标比个体水平指标能更敏感地响应较低剂量汞,是土壤汞污染生态毒性效应诊断的有效指标.另外,本研究结果可为土壤汞污染的风险评估及相关环境标准的修订提供大量基础数据.     

A new approach to graphical and numerical analysis of links between plant chemotaxonomy and secondary metabolism from HPLC data smoothed by a simplex mixture design

Summary. HPLC analysis of secondary metabolites represents an efficient tool for the studying of plant chemical diversity under different aspects: chemotaxonomy, metabolomics, adaptative responses to ecological factors, etc. Statistical analyses of HPLC databases, e.g. correlation analysis between HPLC peaks, can reliably provide information on the similarity/dissimilarity degrees between the chemical compounds. The similarities, corresponding to positive correlations, can be interpreted in terms of analogies between chemical structures, synchronic metabolisms or co-evolution of two compounds under certain environment conditions, etc. . In terms of metabolism, positive correlations can translate precursor-product relationships between compounds; negative correlations can be indicative of competitive processes between two compounds for a common precursor(s), enzyme(s) or substrate(s). Furthermore, the correlation analysis under a metabolic aspect can help to understand the biochemical origins of an observed polymorphism in a plant species. With the aim of showing this, we present a new approach based on a simplex mixture design, Scheffé matrix, which provides a correlation network making it possible to graphically visualise and to numerically model the metabolic trends between HPLC peaks. The principle of the approach consisted in mixing individual HPLC profiles representative of different phenotypes, then from a complete mixture set, a series of average profiles were calculated to provide a new database with a small variability. Several iterations of the mixture design provided a smoothed final database from which the relationships between the secondary metabolites were graphically and numerically analysed. These relationships were scale-dependent, namely either deterministic or systematic: the first consisted of a monotonic global trend covering the whole variation field of each metabolites’ pair; the second consisted of repetitive monotonic variations which gradually attenuated or intensified along a global trend. This new metabolomic approach was illustrated from 404 individual plants of Astragalus caprinus (Leguminoseae), belonging to four chemical phenotypes (chemotypes) on the basis of flavonoids analysed in their leaves. After smoothing, the relationships between flavonoids were numerically fitted using linear or polynomial models; therefore the co-response coefficients were easily interpreted in terms of metabolic affinities or competitions between flavonoids which would be responsible of the observed chemical polymorphism (the four chemotypes). The statistical validation of the approach was carried out by comparing Pearson correlations to Spearman correlations calculated from the smoothed and the crude HPLC database, respectively. Moreover, the signs of the smoothed relationships were finely supported by analogies and differences between the chemical structures of flavonoids, leading to fluent interpretation in relation to the pathway architecture.     

Knowledge transfer initiative between molecular biologists and environmental researchers and regulators

A Natural Environment Research Council (NERC) funded Knowledge Transfer (KT) workshop was held in the United Kingdom (UK) to identify the needs and opportunities in the application of molecular biology and ‘omics’ techniques to environmental monitoring and risk assessment. Attendees highlighted a lack of effective communication between end-users and researchers as well as difficulties with data interpretation as reasons behind the slow uptake of molecular biology and omics techniques. A number of promising areas in which new techniques could be implemented at a practical level in the very near future were identified, thereby raising the profile of these recent technologies and providing vital proof of concept work. Molecular taxonomy, bacterial source tracking and pre-screening of chemicals for potential toxicities were all viewed as areas in which omics and molecular techniques could have immediate value, with the aim of reducing cost, increasing efficiency and providing more comprehensive data of improved quality.     

Metabolic responses in zebrafish (Danio rerio) exposed to zinc and cadmium by nuclear magnetic resonance -based metabolomics

Heavy metals are common marine and soil pollutants that are mainly the result of industrial activity, and are a threat to the environment and human health. In this study, ¹H nuclear magnetic resonance (NMR)-based metabolomics was applied to adult Danio rerio to monitor the metabolic change as a response to ZnCl₂ and CdCl₂ exposure at different concentrations for 72?h. NMR spectroscopy was used to identify and quantify the metabolites extracted from D. rerio. The metabolite profiles of the control and heavy metal exposed group were classified by partial least squares – discriminant analysis (PLS-DA) analysis, and potential contaminant-specific biomarkers were suggested. For the ZnCl₂-exposed zebrafish, the levels of ATP, aspartate and NAD⁺ were increased, whereas the levels of formate, inosine, hypoxanthine and succinate decreased. In addition, the CdCl₂-exposed zebrafish showed an increase in the levels of ATP and formate and a decrease in the levels of glutamate, inosine and glutathione. Overall, Zn and Cd may lead to neurotoxicity, disturbances in the energy metabolism and oxidative stress. Our finding demonstrated that the application of NMR-based metabolomics might be useful for detecting the toxicity caused by sub-lethal concentrations of heavy metal contaminants in the environment.     

胚胎绒毛膜对微塑料颗粒与镉联合作用的影响

利用胚胎发育技术和代谢组学技术,以100nm（n-PS）和70~250μm（μ-PS）两种粒径的聚苯乙烯（Polystyrene,PS）颗粒为研究对象,从微塑料与胚胎绒毛膜相互作用这个角度,探讨了不同粒径微塑料颗粒和镉（Cd）对斑马鱼胚胎发育联合毒性的差异.结果表明,Cd单独暴露、及其与n-PS和μ-PS联合暴露中,胚胎绒毛膜上Cd的蓄积量分别为3.82,13.66,11.35mg/g,而这三个暴露组中Cd在胚胎体内的含量分别为0.24,0.16,0.20mg/g.n-PS更为显著地增加了Cd在胚胎绒毛膜上的蓄积、降低了Cd在胚胎中的含量（P<0.01）.但是μ-PS却更大程度地降低了Cd的胚胎发育毒性（P=0.006）.代谢组学的数据证实,由于PS颗粒对胚胎绒毛膜堵塞作用,纳米PS颗粒能够促进Cd作用下胚胎的氧化压力和细胞的能量需求.因此,胚胎绒毛膜在微塑料对水生生物早期发育的毒性研究中起着重要作用.本研究能够为微塑料在环境中的生物可利用性和效应研究提供一些新的思考方向.