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

考虑到当地和全球环境变化的空前速度，以及对生物系统日益增加的压力，对复杂生物反应的理解从未如此迫切。胚胎对环境变化极为敏感，在空间、功能和时间表型变化方面表现出令人难以置信的多样性和动态性。因此，他们提出了一个独特的系统，推动了我们如何衡量复杂的生物反应的界限，以应对日益复杂和人为影响的自然世界。我的FLF的头四年支持开发全新的技术和方法，用于测量海洋和淡水中生命最初阶段的环境敏感性。该奖学金支持将研究从传统的手动表型方法转移到测量发育中动物最动态的生物学，并转向测量整个生物体生物反应的综合、数据丰富和可扩展的方法。我将利用我的FLF的三年延期，大致与我最初的奖学金一致，通过以下方式推动创新的影响：I)在发育生物体中建立预测表型组学的能力，使生物反应能够通过基于先前发育表型的深度学习训练的时间序列模型进行预测。这将与预测敏感性、人为选择晚年的特定结果以及在实验中实现动态反馈循环以评估不同环境驱动因素的时间特异性效应具有广泛的相关性。ii)在实验室和现场仪器之间创建数字孪生，以实现实验室现场条件的动态环境同步，以评估现场模拟环境事件的实时生物影响。iii)将胚胎基因组学仪器和研究方法的用户基础扩展到不同的研究领域、大洲和部门。与本地用户组和开源硬件社区合作，我们将扩展这些方法的适用性，以应对不同利益相关者的挑战。建立一个全球用户社区将支持在全球范围内并行进行的环境敏感性实验，但也将使人们能够协同努力，通过时间间隔生物成像记录生物早期生命的可见生理多样性。制作出来的视频将保存在第一个开发生物体的开源资源库中，这对两位研究人员来说都是无价的，而且在全球环境变化的背景下，它也可以作为一种资源，照亮隐藏的生物发展世界。

Advances in understanding complex biological responses have never been so urgent given the unprecedented rates of local and global environmental change, and the increasing pressures on biological systems. Embryos are extremely sensitive to environmental change and exhibit incredible diversity and dynamism in spatial, functional and temporal phenotypic change. They therefore present a unique system for pushing the boundaries of how we measure complex biological responses to an increasingly complex and anthropogenically impacted natural world. The first four years of my FLF supported the development of entirely new technologies and approaches for measuring environmental sensitivity during the earliest stages of life, in marine and freshwaters. The Fellowship supported moving research away from traditional manual phenotypic approaches to measuring the biology of developing animals at their most dynamic, and moving towards integrative, data-rich and scalable methods of measuring whole-organismal biological responses. I will use a three year extension to my FLF, broadly in line with my initial Fellowship, to drive impact from the innovation to date by: i) Establishing the capability for predictive phenomics in developing organisms, to enable biological responses to be predicted via timeseries models trained using deep learning on the basis of the previous developmental phenotype. This will have broad relevance for predicting sensitivity, artificially selecting for particular outcomes in later life and enabling dynamic feedback loops within experiments to assess the time-specific effects of different environmental drivers. ii) Creating digital twinning between laboratory and field instruments to enable dynamic environmental synchronisation of field conditions in the laboratory to assess the real-time biological impacts of simulated environmental events in the field. iii) Extending the user base of the EmbryoPhenomics instrumentation and research approaches to different research areas, continents and sectors. Working with local user groups and the open-source hardware community we will extend the applicability of these approaches to the challenges of different stakeholders. Establishing a global community of users will support environmental sensitivity experiments being run in parallel globally, but will also enable a concerted effort to document the visible physiological diversity of organisms during their early life, via timelapse bioimaging. The resulting video will be maintained in the first open-source repository of developing organisms and will be invaluable to both researchers, but also as a resource for shining a light on the hidden world of biological development, within the context of global environmental change.