New statistical and computational tools for optimization of planarian behavioral chemical screens

用于优化涡虫行为化学筛选的新统计和计算工具

基本信息

批准号：
10658688
负责人：
Eva-Maria Schoetz Collins
金额：
$ 13.95万
依托单位：
SWARTHMORE COLLEGE
依托单位国家：
美国
项目类别：
财政年份：
2023
资助国家：
美国
起止时间：
2023-06-15 至 2025-05-31
项目状态：
未结题

来源：
https://reporter.nih.gov/project-details/10658688
关键词：
Acceleration Accidents Acute Adult Algorithms Anatomy Animal Testing Anxiety Bayesian Method Bayesian Modeling Behavior Behavior monitoring Behavioral Benchmarking Bioinformatics Biological Assay Categories Chemical Exposure Chemicals Classification Code Communities Complex Computer Analysis Computer Vision Systems Contracts Data Development Dugesia (turbellarian)Embryo Entropy Esthesia Evaluation Event Fresh Water Goals Health Human In Vitro Information Theory Invertebrates Letters Libraries Locomotion Machine Learning Measurement Measures Methodology Methods Modeling Molecular Morphology Muscle National Toxicology Program Natural regeneration Nematoda Nerve Regeneration Nervous System Neurophysiology - biologic function Neurotoxins Organism Organophosphorus Compounds Phenotype Planarians Population Rapid screening Research Resolution Scheme Sensitivity and Specificity Severities Shapes Spasm Speed Strategic Planning System Terrorism Testing Therapeutic Time Toxic effect Toxicology United States National Institutes of Health Whole Organism Work Xenobiotics Zebrafish adverse outcome asexual chemical safety complex data computerized tools cost cost effective data library design developmental neurotoxicity high throughput screening improved interoperability mass casualty neural neural circuit neurodevelopment neuronal circuitry neurotoxicity neurotoxicology novel therapeutics prevent response safety assessment screening tool treatment strategy tv watching

项目摘要

Objectives. There is an urgent need to develop high-throughput screening (HTS) non-animal models to replace, refine, and/or reduce (“3Rs”) vertebrate toxicology testing. The development of HTS models is especially challenging for neurotoxicity (NT) and developmental neurotoxicity (DNT) where the functional relevancy of adverse outcomes needs to be assessed on the whole organism level. The overarching goal of this research is to develop a non-animal organismal HTS methodology to identify NT and DNT. The specific objective is to determine whether using state-of-the-art computational approaches will increase sensitivity and specificity of planarian HTS to identify NT and DNT using the verified National Toxicology Program 87-compound library (NTP87). As a partner in the NTP Neurotoxicology Screening Strategies Initiative, we previously screened the NTP87 library consisting of known and suspected developmental neurotoxicants in the asexual freshwater planarian Dugesia japonica using 9 readouts. Using this library, we demonstrated that planarian HTS can identify known (developmental-) neurotoxicants and adds complementary value to screens in developing zebrafish. Planarians are invertebrates of intermediate neural and anatomical complexity compared to nematodes and zebrafish and have tractable, evolutionarily conserved neuronal circuits. Planarians uniquely allow for direct comparison of xenobiotic effects on the adult and developing nervous systems. For asexual D. japonica, which reproduce via fission, neuroregeneration is the sole method of neurodevelopment and shares conserved key events with vertebrate neurodevelopment. These features and our previous work demonstrate the value of planarian HTS for first-tier screening of potential neurotoxicants. We hypothesize that we can augment sensitivity and specificity of this non-animal model by re-analyzing our NTP87 data using state-of-the- art machine learning and statistical tools. Experimental approach. In Aim 1, we will re-analyze the raw data using 18 new behavioral and 10 new morphological readouts using computer vision and machine learning. Thus, in total we assay 37 readouts evaluated at 5 concentrations, in intact and regenerating organisms. In Aim 2, we will re-analyze potency including all 37 readouts using a benchmark concentration approach with empirically determined, endpoint- specific benchmark responses. This analysis will overcome the intrinsic limitations associated with lowest- observed-effect levels that was previously applied. In Aim 3, we will use a Bayesian statistical model originally developed for zebrafish embryo screens to obtain a holistic toxicity summary score and evaluate the relative importance of the different readouts for the predictive capabilities of the planarian system. Expected results. By combining non-animal organismal behavioral HTS with state-of-the-art analytical approaches, this project will bolster the development of a non-animal organismal HTS methodology that can be integrated with predictive bioinformatics to meet the urgent need to fill the DNT data gap.

目标迫切需要开发高通量筛选（HTS）非动物模型来替代，改进和/或减少（“3R”）脊椎动物毒理学测试 HTS 模型的开发尤其重要。神经毒性（NT）和发育神经毒性（DNT）具有挑战性，其中功能相关性需要在整个有机体水平上评估不良后果这项研究的总体目标。是开发一种非动物生物HTS方法来鉴定NT和DNT，具体目标是。确定使用最先进的计算方法是否会提高敏感性和特异性涡虫 HTS 使用经过验证的国家毒理学计划 87 种化合物库来识别 NT 和 DNT (NTP87) 作为 NTP 神经毒理学筛选策略计划的合作伙伴，我们之前筛选了 NTP87 文库由无性淡水中已知和可疑的发育神经毒物组成使用 9 个读数的涡虫 Dugesia japonica 使用该库，我们证明涡虫 HTS 可以识别。已知的（发育）神经毒物，并为发育中的斑马鱼筛选增加补充价值。与线虫相比，涡虫是具有中等神经和解剖复杂性的无脊椎动物斑马鱼具有易于处理、进化上保守的神经回路，独特地允许直接进行。对于无性D. japonica，异生素对成虫发育和神经系统的影响的比较。通过裂变繁殖，神经再生是神经发育的唯一方法，并共享保守的密钥这些特征和我们之前的工作证明了脊椎动物神经发育的价值。我们发现涡虫 HTS 用于潜在神经毒物的一级筛查。通过使用最新的 NTP87 数据重新分析该非动物模型的敏感性和特异性艺术机器学习和统计工具。在目标 1 中，我们将使用 18 个新行为和 10 个新行为重新分析原始数据。使用计算机视觉和机器学习进行形态学读数因此，我们总共检测了 37 个读数。在完整和再生生物体中以 5 种浓度进行评估在目标 2 中，我们将重新分析效力。包括使用基准浓度方法的所有 37 个读数，并根据经验确定终点 - 该分析将克服与最低相关的内在限制。在目标 3 中，我们最初将使用贝叶斯统计模型。为斑马鱼胚胎筛选而开发，以获得整体毒性总结评分并评估相对不同读数对于涡虫系统预测能力的重要性。通过将非动物生物行为 HTS 与最先进的分析相结合，获得预期结果。方法，该项目将促进非动物生物 HTS 方法的开发，该方法可以与预测生物信息学相结合，满足填补DNT数据空白的迫切需要。