Current Projects

Fluorescent proteins are used in a wide range of both fundamental and translational research fields. Many of their applications rely on multiplexed detection of multiple fluorescent proteins. However, many proteins have broad emission spectra, therefore limiting the number of proteins that can be multiplexed before the spectra overlap and cannot be distinguished. The aim of this project is to develop a method to evolve fluorescent proteins to narrow their emission spectra and therefore increase the number that can be multiplexed. This will have a positive impact on multiple fields of research. In addition, the new proteins will likely have potential for commercial exploitation similar to previously developed fluorescent proteins.

During this pilot project, we aim to establish if and how fluorescent proteins with a narrowed emission spectra can be generated. Many previous studies have evolved fluorescent proteins to improve brightness, stability, excitation and emission peaks but none have ever altered the breadth of the emission spectrum.

This project will first determine whether this alteration is possible and second will characterise the nature of the mutations resulting in the desired fluorescence spectrum. We will generate sequencing data to profile the mutations that cause narrowing of emission spectra for a test case. These data will then be used in a seed corn project to predict mutations that will cause narrowing of the emission spectra of other fluorescent proteins

Amyotrophic Lateral Sclerosis (ALS) is a fatal neurodegenerative disease that involves death of motor neurons that are required for movement and breathing. So far there is no cure and most patients die within 3-5 years of diagnosis. The long term goal of my research is to identify key genes that are drivers of motor neuron death observed in ALS. If we can identify such genes, we can target them to improve motor neuron survival and enhance quality of life for the patient.

Gene expression within cells is controlled at multiple levels, namely 1) Transcriptional: Proteins called transcription factors (TFs) regulate how much of a gene is expressed into RNA, 2) Post-transcriptional: This is mediated by  RNA binding proteins (RBPs). RBPs control how much protein is made from the RNA, where the RNA gets localized and RNA splicing i.e. a process that allows different kinds of proteins to be made from the same RNA molecule. We will generate data that allows us to identify transcriptional and post-transcriptional regulation in ALS and healthy neurons.

This research aims to establish a metabolomic analysis pipeline using existing human samples obtained pre and post mitochondrially driven improvements in ageing muscle function. This will lay the foundations for future funding, which will generate comprehensive metabolomic networks of novel treatment strategies against the age-related loss of muscle mass (sarcopenia), using our biobank of ageing human muscle. This work will assist in mechanistic discovery by tackling the longer-term research question: what is the metabolomic biosignature of ageing per se and in response to antisarcopenic interventions (i.e. drug/ exercise)?

This project will generate metabolomic networks from human muscle and plasma samples obtained pre and post mitochondrially-driven improvements in ageing muscle function, via NAD+ precursor supplementation. These existing samples were collected alongside detailed functional and metabolic analysis, presenting an ideal opportunity to relate metabolomic signatures to physiological adaptations. As such, this project will achieve two key objectives: i) establish an internal metabolomic analysis pipeline for muscle and plasma samples and, ii) provide preliminary data for metabolomic and subsequent network-driven analysis to predict novel regulators of sarcopenia, which will lead to hypothesis generation for future studies of muscle ageing.

Extramyocellular adipose tissue (EMAT) accumulates within skeletal muscle with age. Concurrently, skeletal muscle mass declines. EMAT mechanically alters skeletal muscle function and adipose tissue inflammation promotes skeletal muscle loss. EMAT is now thought to develop from muscle-resident fibroadipogenic progenitors (FAP). The relationship between FAP and muscle cells has not been sufficiently detailed in humans. It is our ultimate aim to characterise this relationship and, using a combination of wet lab experiments and mathematical modelling, describe the accumulation of EMAT over the lifecourse.

We will:

1. Quantify skeletal muscle FAP and SC in lean (BMI < 25) young (18-30) and older (> 60 yr) individuals. The numbers of FAP and myogenic satellite cells (SC) associated with type I and type II muscle fibres will be measured.  
2. Establish the capability to isolate and culture FAP via magnetic-activated cell sorting.. We already have the ability to generate primary myogenic cultures.
3. We will established the capability to co-culture FAP and myogenic cells.

These pilot data will inform wet lab experiments and mathematical modelling that will form part of a future research proposal

The long-term aim of the research is to discover novel pathways in depression through non-neuronal brain cells called astrocytes.  Post-mortem and pre-clinical studies show decreased astrocyte density and expression of astrocyte-specific genes in depression. However, mechanisms underlying these changes and their contribution to depression aetiology are unknown. The current project aims to identify common molecular pathways in astrocytes activated by antidepressant treatment and by two common triggers of depression, stress and inflammation. This will allow us to identify astrocytic genes dysregulated in depression and their potential involvement in response to antidepressant treatment.
 
This project will enable us to analyse changes in astrocytic gene expression following the treatment with antidepressant fluoxetine. We have already obtained total mRNA from primary astrocytes treated with fluoxetine. We will launch the analysis of publicly available transcriptomic data of astrocytes challenged by inflammation or chronic stress (Simard 2017;Liddelow 2017;Birck 2016;Pantazanos 2017;Zhang 2016). Taken together, we will generate: RNA-Seq data from the mRNA samples, and Analysis pipelines produced using publicly available RNA-seq data.

The long-term research question here is to determine which facets of measurable behaviour during simple object interaction tasks distinguish children with developmental coordination disorder (DCD) from typically-developing children. Identification of the hand/eye kinemtatic and/or fingertip force signatures is the first step to identifying a multivariate behavioural biomarker which could support an objective differential diagnosis in young children and guide the development of new rehabilitation strategies.

This research follows on from a completed project examining high-resolution data on hand kinematics, object kinematics, eye-gaze position, and fingertip force data from a sample of 120 children with and without DCD. The unique dataset was collected to examine sensorimotor prediction, as indexed by discrete metrics derived from the dataset utlizing <1% of the total data collected on each trial (4 seconds per trial at 120-500Hz, depending on the equipment). This research will facilitate the creation of new derived variables from this existing, underutilised, resource in order to create a candidate set of variables aimed at identifying DCD.

This project will develop a computational workflow to gain new insights into immunometabolism.

During infection the host cellular metabolism shifts in order to support the anti-infectious programs. Most research focuses on one single type of -omics data to investigate these phenomena. There are significant advantages to taking a multi-omics integrative approach, which provides a more comprehensive view of complex responses. Given the complexity of integrative datasets there is a need for new tools which can extract biological insights and inform future research.

Our collaborator developed a triple-omics protocol (metabolomic, proteomic and lipidomic)¹. In this proposal, we aim to develop statistical and mathematical approaches in the context of a relevant human health problem: the metabolic remodelling of immune cells in response to a deadly infectious disease.

A key step in macrophage activation is production of high amounts of the metabolite itaconate². Itaconate’s wider role in cellular metabolism is still largely unknown. Multi-omics analysis will pinpoint the molecular alterations caused by itaconate that contribute to macrophage activation. We will use this biological problem to develop new modelling pipelines/tools for analysing multi-omics biology.

We will generate a multi-omics dataset reflecting the concerted changes occurring in macrophages upon infection. Wild-type (Wt) and itaconate-null (Irg1-null) macrophages will be infected with the pathogenic yeast Cryptococcus neoformans³, using non-infected macrophages as controls (4 experimental groups in technical quadriplicates). Metabolites, lipids, and proteins will be quantified from every sample.

The bacteria that are normally found on the skin vary between different parts of the body and are known to vary at different stages of life and between the sexes. The Human Microbiome Project revealed the microbiomes of major body sites but the microbiome of the shoulder (both surface as well as subcutaneous) is not known. Understanding the shoulder microbiome is the fundamental first step in defining what may be a cause of postoperative infections in patient undergoing shoulder surgery.

This research will allow collection and storage of the samples in preparation for analysis and application for the future funding and has been agreed with the Royal Devon and Exeter Tissue bank (RDETB) for support with sample collection and storage.