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

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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.