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秀丽隐杆线虫和寄生线虫的自动化、高通量运动分析:在寻找新型驱虫药中的应用

Automated, high-throughput, motility analysis in Caenorhabditis elegans and parasitic nematodes: Applications in the search for new anthelmintics.

作者信息

Buckingham Steven D, Partridge Frederick A, Sattelle David B

机构信息

Wolfson Institute for Biomedical Research, Division of Medicine, University College London, Cruciform Building, Gower Street, London WC1E 6BT, United Kingdom.

出版信息

Int J Parasitol Drugs Drug Resist. 2014 Oct 30;4(3):226-32. doi: 10.1016/j.ijpddr.2014.10.004. eCollection 2014 Dec.

DOI:10.1016/j.ijpddr.2014.10.004
PMID:25516833
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC4266775/
Abstract

The scale of the damage worldwide to human health, animal health and agricultural crops resulting from parasitic nematodes, together with the paucity of treatments and the threat of developing resistance to the limited set of widely-deployed chemical tools, underlines the urgent need to develop novel drugs and chemicals to control nematode parasites. Robust chemical screens which can be automated are a key part of that discovery process. Hitherto, the successful automation of nematode behaviours has been a bottleneck in the chemical discovery process. As the measurement of nematode motility can provide a direct scalar readout of the activity of the neuromuscular system and an indirect measure of the health of the animal, this omission is acute. Motility offers a useful assay for high-throughput, phenotypic drug/chemical screening and several recent developments have helped realise, at least in part, the potential of nematode-based drug screening. Here we review the challenges encountered in automating nematode motility and some important developments in the application of machine vision, statistical imaging and tracking approaches which enable the automated characterisation of nematode movement. Such developments facilitate automated screening for new drugs and chemicals aimed at controlling human and animal nematode parasites (anthelmintics) and plant nematode parasites (nematicides).

摘要

寄生线虫对全球人类健康、动物健康和农作物造成的损害规模,加上治疗方法的匮乏以及对有限的广泛使用的化学药物产生抗药性的威胁,凸显了开发新型药物和化学物质以控制线虫寄生虫的迫切需求。能够自动化的强大化学筛选是该发现过程的关键部分。迄今为止,线虫行为的成功自动化一直是化学发现过程中的一个瓶颈。由于线虫运动能力的测量可以直接标量读出神经肌肉系统的活动,并间接衡量动物的健康状况,这一疏漏非常严重。运动能力为高通量、表型药物/化学筛选提供了一种有用的检测方法,最近的一些进展至少部分地实现了基于线虫的药物筛选的潜力。在这里,我们回顾了线虫运动自动化过程中遇到的挑战,以及机器视觉、统计成像和跟踪方法应用中的一些重要进展,这些方法能够对线虫运动进行自动表征。这些进展有助于自动筛选旨在控制人类和动物线虫寄生虫(驱虫药)以及植物线虫寄生虫(杀线虫剂)的新型药物和化学物质。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8808/4266775/d6f7bee7a4b2/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8808/4266775/22277e29912d/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8808/4266775/35dd8ce81fbd/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8808/4266775/d6f7bee7a4b2/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8808/4266775/22277e29912d/fx1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8808/4266775/35dd8ce81fbd/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/8808/4266775/d6f7bee7a4b2/gr2.jpg

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