Lombardot Benoit, Oh Chun-Taek, Kwak Jihoon, Genovesio Auguste, Kang Myungjoo, Hansen Michael Adsett Edberg, Han Sung-Jun
Image Mining Group, Institut Pasteur Korea, Sampyeong-dong 696, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea.
Drug Biology Group, Institut Pasteur Korea, Sampyeong-dong 696, Bundang-gu, Seongnam-si, Gyeonggi-do, Korea.
PLoS One. 2015 Apr 1;10(4):e0121287. doi: 10.1371/journal.pone.0121287. eCollection 2015.
Genotoxicity testing is an important component of toxicity assessment. As illustrated by the European registration, evaluation, authorization, and restriction of chemicals (REACH) directive, it concerns all the chemicals used in industry. The commonly used in vivo mammalian tests appear to be ill adapted to tackle the large compound sets involved, due to throughput, cost, and ethical issues. The somatic mutation and recombination test (SMART) represents a more scalable alternative, since it uses Drosophila, which develops faster and requires less infrastructure. Despite these advantages, the manual scoring of the hairs on Drosophila wings required for the SMART limits its usage. To overcome this limitation, we have developed an automated SMART readout. It consists of automated imaging, followed by an image analysis pipeline that measures individual wing genotoxicity scores. Finally, we have developed a wing score-based dose-dependency approach that can provide genotoxicity profiles. We have validated our method using 6 compounds, obtaining profiles almost identical to those obtained from manual measures, even for low-genotoxicity compounds such as urethane. The automated SMART, with its faster and more reliable readout, fulfills the need for a high-throughput in vivo test. The flexible imaging strategy we describe and the analysis tools we provide should facilitate the optimization and dissemination of our methods.
遗传毒性测试是毒性评估的重要组成部分。正如欧洲化学品注册、评估、授权和限制(REACH)指令所表明的那样,它涉及工业中使用的所有化学品。由于通量、成本和伦理问题,常用的体内哺乳动物测试似乎不太适合处理所涉及的大量化合物集。体细胞突变和重组测试(SMART)是一种更具扩展性的替代方法,因为它使用果蝇,果蝇发育更快且所需基础设施更少。尽管有这些优点,但SMART所需的果蝇翅膀毛发的手动评分限制了其使用。为克服这一限制,我们开发了一种自动化的SMART读数方法。它包括自动成像,随后是一个图像分析流程,该流程可测量单个翅膀的遗传毒性评分。最后,我们开发了一种基于翅膀评分的剂量依赖性方法,该方法可以提供遗传毒性概况。我们使用6种化合物验证了我们的方法,即使对于低遗传毒性化合物如氨基甲酸乙酯,获得的概况也几乎与手动测量获得的概况相同。自动化的SMART具有更快、更可靠的读数,满足了高通量体内测试的需求。我们描述的灵活成像策略和提供的分析工具应有助于我们方法的优化和推广。