Suppr超能文献

生态毒性测试中的高通量筛选范式:新出现的前景与当前挑战。

High-throughput screening paradigms in ecotoxicity testing: Emerging prospects and ongoing challenges.

作者信息

Wlodkowic Donald, Jansen Marcus

机构信息

The Neurotox Lab, School of Science, RMIT University, Melbourne, VIC, 3083, Australia.

LemnaTec GmbH, Nerscheider Weg 170, 52076, Aachen, Germany.

出版信息

Chemosphere. 2022 Nov;307(Pt 2):135929. doi: 10.1016/j.chemosphere.2022.135929. Epub 2022 Aug 6.

Abstract

The rapidly increasing number of new production chemicals coupled with stringent implementation of global chemical management programs necessities a paradigm shift towards boarder uses of low-cost and high-throughput ecotoxicity testing strategies as well as deeper understanding of cellular and sub-cellular mechanisms of ecotoxicity that can be used in effective risk assessment. The latter will require automated acquisition of biological data, new capabilities for big data analysis as well as computational simulations capable of translating new data into in vivo relevance. However, very few efforts have been so far devoted into the development of automated bioanalytical systems in ecotoxicology. This is in stark contrast to standardized and high-throughput chemical screening and prioritization routines found in modern drug discovery pipelines. As a result, the high-throughput and high-content data acquisition in ecotoxicology is still in its infancy with limited examples focused on cell-free and cell-based assays. In this work we outline recent developments and emerging prospects of high-throughput bioanalytical approaches in ecotoxicology that reach beyond in vitro biotests. We discuss future importance of automated quantitative data acquisition for cell-free, cell-based as well as developments in phytotoxicity and in vivo biotests utilizing small aquatic model organisms. We also discuss recent innovations such as organs-on-a-chip technologies and existing challenges for emerging high-throughput ecotoxicity testing strategies. Lastly, we provide seminal examples of the small number of successful high-throughput implementations that have been employed in prioritization of chemicals and accelerated environmental risk assessment.

摘要

新生产化学品的数量迅速增加,再加上全球化学品管理计划的严格实施,有必要实现范式转变,转向更广泛地使用低成本和高通量生态毒性测试策略,并更深入地了解可用于有效风险评估的生态毒性细胞和亚细胞机制。后者将需要自动获取生物数据、大数据分析的新能力以及能够将新数据转化为体内相关性的计算模拟。然而,到目前为止,在生态毒理学中致力于开发自动化生物分析系统的工作很少。这与现代药物发现流程中标准化和高通量的化学筛选及优先级排序程序形成鲜明对比。因此,生态毒理学中的高通量和高内涵数据采集仍处于起步阶段,只有有限的例子侧重于无细胞和基于细胞的检测。在这项工作中,我们概述了生态毒理学中高通量生物分析方法的最新进展和新兴前景,这些方法超越了体外生物测试。我们讨论了自动定量数据采集对于无细胞、基于细胞的检测以及利用小型水生模式生物进行植物毒性和体内生物测试的未来重要性。我们还讨论了诸如芯片器官技术等最新创新以及新兴高通量生态毒性测试策略面临的现有挑战。最后,我们提供了少数成功的高通量实施方案的开创性例子,这些方案已用于化学品优先级排序和加速环境风险评估。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验