Developing an integrative approach to phenomics for industrial, biomedical and environmental applications

用于分子水平现象的高通量和自动化测量的组学技术使生物学的所有领域都取得了重大进展。这种还原论的方法来理解生物学是富有成效的，但它们的能力有限，无法理解复杂的、多维度的综合实体，我们简单地称之为表型。一种描述和量化表型的突破性新方法是表型组学-在生物体范围内获取高维数据。由于表型组的信息含量和复杂性使基因组相形见绌，表型组学的挑战相当大。然而，在医学和植物科学中发展表型组学方法的重大进展正在证明其改变我们对生物现象的解释和理解的潜力。该奖学金将推动新一代水生胚胎表型组学技术的发展，并验证其在解决一些最紧迫的生物医学，环境和工业问题和挑战方面的应用。水生胚胎体积小，灵敏度高，时间，空间和功能变化率高，使表型组学的优良模型。我的奖学金将得到EmbryoPhenomics（EP）的支持，这是我在过去八年中开发的一项尖端技术，能够以前所未有的时间，空间和功能分辨率对数百种不同水生胚胎的表型进行全自动同时高通量筛选（Tills et al 2018 PLoS Biology，16：e30000074）。EP由两种协同技术组成：定制高通量生物成像硬件（HEIF资助）和自动化分析软件（NERC资助）。EP平台通过全自动采集和分析数百万张图像，同时对数百个发育中的水生胚胎进行分析，克服了研究生物体生命史最具活力时期的挑战，并已被证明在测量不同物种对长期和短期暴露于环境驱动因素的致死和亚致死生物反应方面非常有效。我将更广泛地使用人工智能（AI）和机器学习来训练模型：（i）从水生胚胎的视频中识别和量化表型性状;以及（ii）整合（i）中产生的每个胚胎的数千个性状，以识别功能组合表型信号。目前，EP的硬件部件是定制部件和定制高端消费部件，成本高，创新障碍大。这个奖学金将支持我开发LabEP和FieldEP -两个变革性的和可访问的表型组学技术。LabEP将是现有EP技术的优化版本，具有增强的功能和较低的成本;开发定制的3D打印部件，用于同时高通量筛选数千个胚胎的微流体培养设备以及强大的AI模型，这些模型将被验证用于药物化合物筛选和生态毒理学。FieldEP将是一个长期的现场部署相机系统，将使用定制训练的AI模型与环境传感器协同作用，自动量化原位生物反应。FieldEP将被验证用于量化普利茅斯海洋环境中混合和波动的环境驱动因素的表型反应，普利茅斯是英国第一个拟议的海洋公园，南极洲的后勤挑战环境。该奖学金将支持我通过创新实验室（高通量）和现场（混合和波动的环境驱动因素）的新兴技术实现的尖端方法，并将其应用于生物学中一些最紧迫的挑战，来开发表型组学的综合方法。

Omics technologies for high-throughput and automated measurement of phenomena at the molecular level have enabled significant advances in all areas of biology. Such reductionist approaches to understanding biology have been productive, but they are limited in their capacity to provide understanding of the complex, multidimensional integrated entity we refer to simply to as the phenotype. A ground-breaking new approach to describing and quantifying the phenotype is phenomics - the acquisition of high-dimensional data on an organism-wide scale. The challenge of phenomics is considerable due to the information content and complexity of the phenome dwarfing that of the genome. Yet significant advances in the development of phenomics approaches in medicine and plant science are demonstrating its potential to transform our interpretation and understanding of biological phenomena. This fellowship will drive the development of a new generation of technologies for phenomics in aquatic embryos and validate their application for addressing some of the most pressing biomedical, environmental and industrial questions and challenges. The small size, high sensitivity and high rates of temporal, spatial and functional change make aquatic embryos excellent models for phenomics. My fellowship will be underpinned by EmbryoPhenomics (EP), a cutting-edge technology that I have developed over the past eight years that enables the fully automated simultaneous high-throughput screening of the phenome of hundreds of different aquatic embryos with unprecedented temporal, spatial and functional resolution (Tills et al 2018 PLoS Biology, 16: e30000074). EP consists of two synergistic technologies: custom high-throughput bioimaging hardware (HEIF funded) and automated analytical software (NERC funded). The EP platform surmounts the challenge of studying the most dynamic period of an organism's life history via the fully automated acquisition and analysis of millions of images, of hundreds of developing aquatic embryos simultaneously and it has proven highly effective at the measurement of lethal and sublethal biological responses to long- and short-term exposures to environmental drivers in different species.With EP as a foundation, I will use artificial intelligence (AI), and machine learning more broadly, to train models for: (i) the identification and quantification of phenotypic traits from video of aquatic embryos; and (ii) the integration of the thousands of traits for each embryo produced in (i) to identify functional combinatorial phenomic signals. Currently the hardware components of EP are bespoke parts and custom high-end consumer parts, with a high cost and barrier to innovation. This fellowship will support me in developing LabEP and FieldEP - two transformative and accessible technologies for phenomics. LabEP will be an optimised version of the existing EP technology with enhanced functionality and a lower cost drawing on; the development of custom 3D printed parts, microfluidic culture devices for high-throughput screening of thousands of embryos simultaneously and powerful AI models that will be validated for both pharmaceutical compound screening and ecotoxicology. FieldEP will be a long-term field-deployable camera system that will automatically quantify biological responses in situ using custom trained AI models in synergy with environmental sensors. FieldEP will be validated for quantifying phenomic responses to mixed and fluctuating environmental drivers in marine environments in both Plymouth, the UK's first proposed marine park, and the logistically challenging environment of Antarctica. This fellowship will support me in developing an integrative approach to phenomics via the innovation of cutting-edge approaches enabled by emerging technologies for the laboratory (high-throughput) and field (mixed and fluctuating environmental drivers) and their application to some of the most pressing challenges in biology.