Using novel phenomics technology for environmental sensitivity prediction in marine invertebrates

Primary supervisor: Professor Simon Rundle (University of Plymouth)

Secondary supervisor: Dr Oliver Tills (University of Plymouth)

Additional supervisors:

Dr Michal Mackiewicz, (University of East Anglia). Email:

Professor John Spicer (University of Plymouth)

Scientific background

This PhD will apply a new, cutting-edge technology, EmbryoPhenomics, to develop novel tools for predicting environmental sensitivity in marine invertebrates.  

The accurate prediction of how organisms will respond to global change represents a significant scientific challenge but is essential for developing policy decisions and mitigation strategies. 

Phenomics is a new, technology-enabled approach that uses the high-throughput acquisition of high-dimensional data of the observable phenotype (i.e. morphology, physiology and behaviour) to measure biological responses more robustly and provide a more holistic understanding of the mechanisms underpinning sensitivity.  

EmbryoPhenomics uses bio-imaging and advanced image analysis to measure the sensitivity of early developmental stages in aquatic species with different life history strategies and will be used to produce novel, sub-lethal phenomic end points that can be used as predictive tools.

Research methodology

The student will work within the new EmbryoPhenomics facility at the University of Plymouth. 

They will design and carry out experiments assessing the response of marine invertebrates (molluscs and crustaceans; encapsulated and planktonic developers) to current and predicted levels of environmental stressors (temperature, salinity and oxygen) in isolation and in combination; there will also be the opportunity to compare responses under static and fluctuating conditions. 

They will apply this unique capability for high-throughput phenomics in embryos and identify lethal and sub-lethal responses, including traits and ‘proxy traits’ that are key ‘end points’ of environmental stress.


The student will benefit from a truly, interdisciplinary training in practical and Computational Biology, all within an environmental context. 

As well as learning how to use the EmbryoPhenomics platform, i.e. bio-imaging and data acquisition, image analysis and interpretation, they will receive training in Computational Biology (Python, and advanced R) and handling large data sets, developmental ecophysiology, and the use of large-scale experiments for addressing questions in environmental biology.  

Person specification

Candidates should have a minimum of a 2.1 Bachelor degree in a Biological Sciences subject or Environmental Science with some element of biology. They should also have a good level of numeracy and be willing to learn the computational skills associated with this PhD.


This PhD will use new, cutting-edge technology developed for phenomics in aquatic invertebrates to produce end points for gauging biological sensitivity to environmental stress. 

New technologies can offer powerful approaches for assessing biological responses to environmental change and help to inform the consequences of environmental impacts and potential solutions (1). 

Although molecular –omics are now widely applied in Biology the same technology-enabled understanding of whole-organism responses through what has been termed phenomics (2) are only now emerging. 

Such phenomic approaches generate high-dimensional data of the observable characteristics in a comparable way to the ‘large data’ approaches applied in other fields, but they have been restricted mostly to the disciplines of plant and cell biology, and medical science (3,4,5).

EmbryoPhenomics is an automated, bio-imaging platform for high-throughput phenotyping the development of early life stages of aquatic organisms (6). 

It offers the opportunity to measure the environmental sensitivity of large numbers of individual organisms in a high-throughput manner, drawing on data describing embryonic development with unprecedented spatial, functional and temporal resolution. 

Given the highly dynamic nature of early development, this period can have heightened sensitivity to environmental change (4), but is largely ignored in predictions of species’ sensitivity. 

This project will apply the EmbryoPhenomics platform to quantifying developmental-stage-specific lethal- and sub-lethal sensitivities. 

This approach has been successfully trialled with a freshwater mollusc and marine crustacean exposed to thermal and osmotic stress, producing measures for >450 embryos (6). 

The time-series datasets produced for each embryo by EmbryoPhenomics are extensive and have high-dimensionality, incorporating measures for growth, movement, physiological performance and machine vision proxy-trait parameters indicative of embryo health. 

This project will capitalise on the unique datasets produced at the EmbryoPhenomics facility and the inter-disciplinary supervisory team to develop unique analytical approaches to interrogate these data in order to support research that addresses how aquatic organisms will respond in the face of environmental change during arguably their most critical life history stage.

Aims and objectives

The overall aim of this studentship will be to develop and apply phenomic approaches to understand the sensitivity of early life stages of aquatic organisms to forecasted levels of environmental change. 

It will extend the application of the EmbryoPhenomics technology to different species of marine invertebrate by: i) carrying out high-throughput trials to assess lethal and sub-lethal sensitivity of different developmental stages to mixtures of environmental stress; ii) developing machine learning and analytical approaches for identifying key phenomic responses to individual and combined environmental stressors; and iii) building n-dimensional environmental sensitivity models for predicting developmental-stage-specific organismal responses to environmental stress.

Research excellence

This project draws on EmbryoPhenomics, a new technology built by the Plymouth team (Rundle, Tills, Spicer) using NERC Innovation and HEIF funding. 

Hence, the student will work alongside a research team who are at the forefront of the use of phenomics in marine and freshwater ecophysiology and in investigating the impact of multiple stressors (hypoxia, ocean acidification and thermal stress) in marine ecosystems. 

The computational expertise of Dr Mackiewicz at UEA adds a critical, interdisciplinary dimension to the project and he will support the student in the development of novel computational approaches to maximise the explanatory power of the phenomic datasets produced during the student’s laboratory trials.

Training and personal development

The student will be trained in general eco-physiological skills including animal collection and maintenance, laboratory experimentation (including the effect of multiple stressors), experimental design and data analysis. 

They will also receive specific training in the use of OpenVim the bio-imaging system developed to produce high-resolution time-lapse videos of developing embryos and EmbryoCV the Python-based software, which extracts phenomic data from these videos. 

This training will be provided in the new EmbryoPhenomics facility at the University of Plymouth and will be re-informed by the attendance of DTP training courses in Advanced image analysis for environmental science (run by the Plymouth team) and Python modelling and applications in environmental sciences. Dr Mackiewicz will provide training in pattern recognition analysis.


(1) Ge, Y. & Wang, D.Z. et al. (2013) Environmental OMICS: current status and future directions. Journal of Integrated OMICS 3: 75-87.

(2) Houle, D et al. (2010) Phenomics: the next challenge. Nature Review Genetics 11: 855-866.

(3) Pound, M.P. et al. (2017). AutoRoot: Open-source software employing a novel image analysis approach to support fully-automated plant phenotyping. Plant Methods 13:12

(4) Alexandrov, V. et al. (2016). Large-scale phenome analysis defines a behavioural signature for Huntingdon’s disease genotype in mice. Nature Biotechnology 34:845–851

(5) Styles, E.B. et al (2016) Exploring Quantitative Yeast Phenomics with Single-Cell Analysis of DNA Damage Foci. Cell Systems 28:264-277.

(6) Tills, O et al (in revision) A high-throughput and open-source approach for to embryo phenomics. PlosBiology


This project has been shortlisted for funding by the ARIES NERC Doctoral Training Partnership. Undertaking a PhD with ARIES will involve attendance at training events.

ARIES is committed to equality & diversity, and inclusion of students of any and all backgrounds. All ARIES Universities have Athena Swan Bronze status as a minimum.  

Applicants from quantitative disciplines who may have limited environmental science experience may be considered for an additional three-month stipend to take appropriate advanced-level courses.

Usually, only UK and EU nationals who have been resident in the UK for three years are eligible for a stipend. Shortlisted applicants will be interviewed on 26/27 February 2019.

For further information please see or contact us at