We have academic members of staff with associated PhD students and Postdoctoral Fellows directly associated with biosciences.
Recognised as internationally excellent* our current research teams support basic and applied research in the biosciences and across disciplinary boundaries, with a particular focus on the development of vibrant industrial collaborative research.
PhD title: Degraded and Degrading: Understanding Diagenetic Processes in Commingled Graves from Contexts of Mass Violence
Using animal models as human surrogates, the current project aims to examine early diagenesis presented within osseous tissue recovered from bodies interred within commingled graves of variable size and conditions over periods of 6 months to 2 years. Utilizing X-ray Fluorescence (XRF) Spectroscopy to examine intra- and inter-skeletal variation of inorganic elemental composition; Next Generation Sequencing (NGS) to observe microbial community variation; and microscopic analysis of bioerosion to document the degree of bioerosion present within each sample (Oxford Histological Index); results should provide insight into the progression of diagenesis within commingled and mass graves - dependent upon the state and position of the interred cadaver(s) - and potential alternative methods to isolate and re-association commingled remains for victim identification.
PhD title: The Development Of Mass Spectrometry Based Diagnostics
The project is built on already growing impact of mass spectrometry in clinical diagnostics. Mass spectrometry approaches are already used in the diagnosis of metabolic disorders, tissue imaging, drug abuse/compliance and biomarker discovery. This research will utilise the development of smaller, cheaper more robust mass spectrometry instrumentation to provide clinically relevant information in an accurate and timely manner. Working in conjunction with health care professionals the project will initially involve the development, testing and evaluation of a number of mass spectrometry based screens including for smoking, diabetes, alcohol abuse, compliance with given medication and use of prohibited substances. The aim is to provide a comprehensive, easily administered panel of tests. The wider use of mass spectrometry as a more sophisticated clinical tool for the diagnosis of genetic conditions such as hemoglobinopathies, to inform cancer diagnosis and to monitor diseases of pregnancy will also be explored.
PhD title: Metabolomic inference and community structure analysis of Bifidobacteria strains on the gut of preterm infants at risk of necrotising enterocolitis
This research aims to investigate the gut microbiome of preterm infants. An infant is designated preterm when born before 37 weeks gestational age (GA). The research also explores the mechanisms of probiotics on the gut microbiome in infants at risk of Necrotising Enterocolitis (NEC). NEC is a severe gut infection prevalent in the preterm infant population, causing 21% of all deaths in infants under 32 weeks GA, with morbidity rates of up to 40%. The probiotics used in this study contained Bifidobacteria spp. and Lactobacillus acidophilus. B. infantis utilises several small Human Milk Oligosaccharides (HMOs) as a carbon source and increases acetate levels, potentially protecting against enteropathogens by improving gut barrier function. Bifidobacteria spp. and L. acidophilus have an immunoregulatory role by attenuating IL6 and IL8 which are linked to the NEC inflammatory response HMO utilisation.
The research objectives are to compare the bacterial community found in preterm infants’ stool samples and the short chain fatty acid signature in corresponding breast milk samples. The methods used to elucidate this include: Next Generation sequencing, UPLC-MS analysis and data analysis using metabolomic inference packages in R.
PhD title: Multidisciplinary approaches to the investigation of preservation processes at the Roman Site of Vindolanda, Northumberland, UK
Vegetable tanned leather can remain relatively stable when buried in wet soil, but normally degrades as water and chemicals from the surrounding soil leach into and break down its collagen structure. Nevertheless, large numbers of leather artefacts have been excavated at several wet archaeological sites, such as Roman Vindolanda in Northumberland. The preservation at Vindolanda has been attributed to a variety of agents, such as high tannin concentrations or anaerobic conditions in the soil. The ability to quickly and non-destructively characterise the protein preservation of archaeological leather and the process by which it has been preserved will be investigated in this project.
As such, an analysis will be carried out on experimentally buried modern leather, as well as leather samples from known soil contexts at Vindolanda. To test their accuracy, results form non-destructive approaches such as Scanning Electron Microscopy (SEM), portable X-Ray Fluorescence (pXRF) and Fourier Transform Infrared (FTIR) spectroscopy will be compared to quantitative ones. The quantitative approaches will be Ultra High-Performance Liquid Chromatography (UPLC) and tandem Mass Spectrometry with Quadrupole and Time of Flight detectors (UPLC-Q-TOF). This will be done to decipher what non-destructive approaches are likely to be the most useful predictors for protein preservation in archaeological leather. Further, whether a relationship can be established between this preservation and the associated soil conditions. This project will further our understanding of protein breakdown mechanisms in archaeological soil contexts and aid archaeological conservators when deciding the most appropriate measures to take towards artefact stabilisation or further scientific analysis.
PhD title: The Placental Microbiota in Chorioamnionitis
Chorioamnionitis is inflammation of the fetal compartment of the placental membranes, consisting of the amnion and chorion. Chorioamnionitis impacts 35% of preterm births, with links to adverse maternal and neonatal outcomes. The microbiome and bacterial load levels related to inflammatory markers and histological staging of chorioamnionitis are unknown.
The aim of this project is to determine if there is a distinct fetal membrane microbiome and bacterial load associated with chorioamnionitis. Findings aim to increase current knowledge of histological chorioamnionitis.
Frozen amnion and chorion from preterm spontaneous labour with histological chorioamnionitis were analysed alongside preterm and term labour without chorioamnionitis.16S rRNA gene targeted Next Generation Sequencing aimed to determine microbial communities of genomic DNA extracted from fetal membranes. qPCR aimed to assess bacterial load comparison between subgroups, plus correlation analysis when combined with inflammatory data.
Finding so far indicate that greater bacterial load is present in histological chorioamnionitis. Bacterial load is linked to severity and staging of the condition and the expression of five specific inflammatory genes.
Further research investigating the five inflammatory factors as potential biomarkers to histological chorioamnionitis requires attention, plus, identifying the location and spatial distribution of bacterium on the placental membranes via Raman Microscopy, and understand the inflammatory response to bacterial components via cell culture stimulation.
PhD title: Studying the effects of Inclusion Bodies on Escherichia coli viability
The overarching aim of this research is to discover the changes in gene expression as inclusion bodies (IBs) are formed.
The project initially builds on a novel protein engineering approach designed with the use of an aggregating tag to enhance, and potentially better control inclusion IB formation in Escherichia coli.
The study investigates the effects of IB formation on cell viability and explores the molecular control of inclusion body formation during recombinant protein expression using RT-qPCR and RNAseq to analyse the change in mRNA expression of recombinant proteins, alongside monitoring gene expression of the whole transcriptome, particularly focusing on markers of cell division, cell stress and chaperones.
The study further aims to compare differences in IBs formed in the cytosol to those in the periplasmic space. In collaboration with an industrial partner the project aims to give the bioprocessing industry the required control of stable aggregate formation.
PhD title: Utilization of enhanced shape selective information obtained from a cyclic ion mobility-enabled -mass spectrometer for the characterisation of complex mixtures
Many industrial formulations are made up of mixtures of separate components each of which can exhibit structural complexity. They may be composed of many similar products including those of the similar molecular weight, which cannot be readily separated by separation science approaches. Carbon number variation and ethylene or propylene oxide distributions add to the complexity. The properties of these formulations are dependent on the chemical structure and relative concentration of formulation components. Components of identical molecular mass in polysorbate, and other formulations have been separated by ion mobility and then fragmented for additional characterization. The rapidity and level of structural detail provided by these experiments offers a significant opportunity to develop practical screening methods for complex formulations. This requires the calculation of energy minimized three-dimensional structures and the prediction from that structure of the experimental cross section.
In this work we have used a robust approach using nitrogen based calibration standards for the estimation of cross sections and the use of Avogadro and Gaussian09 for the generation of minimized structures. The trajectory method (TM) incorporated into the MOBCAL program, which incorporates charged-induced dipole interactions, has been used to predict the experimental cross sections. Where available the predicted values have been compared with published data. A range of model structures and industrially relevant formulation mixtures have been experimentally measured - and good agreement has been obtained with predicted values. The Q-cIM-oaToF mass spectrometer used in these investigations has provided a number of experimental improvements including an improved mobility resolution of Ω/∆Ω of 65 for single pass operation, higher TOF analyser resolution and an enhanced dynamic range.
PhD title: An integrated experimental modelling and machine learning framework for poly-omic characterisation of ovarian cancer
Ovarian cancer is currently the most deadly gynaecological malignancy at advanced age in developed countries. Early detection is still the main determinant of treatment and survival. In this context, the development of effective tools for the identification of reliable and precise biomarkers is thus urgently required. However, it has now become evident from many studies that cancer is a complex, multi-factorial and heterogeneous disease that should be investigated with multi-scale and multi-omics approaches, including genome-scale metabolic models.
Genome-scale metabolic models (GSMMs) have succeeded in recapitulating and predicting mechanistic behaviours of several cells - ranging from microbial to algae and human- and model predictions have been validated experimentally in breast cancer, confirming the high predictive capability of GSMMs. The aim of this research is to integrate advanced computational biology, specially GSMMs and artificial intelligence tools with patient molecular data to produce novel clinically convenient insights of ovarian cancer. The integrated tool will help us to identify biomarkers for improved and early detection of ovarian cancer.
For the study, tissue, urine and blood samples will be collected from the different stages of ovarian cancer patients from the James Cook University Hospital. Proteomic and metabolomics data will be generated through LC-MS-MS experiments and processed using state-of-the-art software namely Progenesis LC-MS and Progenesis QI. To integrate experimentally-generated multi-omics data within the most recent genome-scale reconstruction of the human metabolism, and will design and develop a deep learning pipeline to analyse GSMMs generated large-scale data about ovarian tumour and normal cells.
PhD title: Synthesis and characterisation of catalysts for clean and sustainable fuel synthesis
Our natural resources are depleting at a very fast rate and there is an urgent need to find alternative sources of fuel. Hydrogen is one of the clean and sustainable fuels and possibly the answer to future energy demands.My research area is in the field of Artificial Photosynthesis, focused on the development of catalysts that biomimics the process of natural photosynthesis. I aim to synthesize catalysts that are capable of producing hydrogen and oxygen from water and sunlight. These catalysts are coordination complexes based on abundant and inexpensive metals such as cobalt and nickel (e.g. using cobaloximes or Dubois-type catalysts), and are combined with organic polymers that are capable of harvesting sunlight. They will be characterised using NMR, IR, MS, UV-VIS and elemental analysis to name a few. These catalysts would then be immobilised onto organic polymers, and these polymers would be deposited onto transparent conductive electrodes (e.g. FTO or ITO).
PhD title: Application of geometric morphometric analysis to the process of the identification of weapon class in trauma analysis.
Geometric morphometric analysis (GMM) quantifies shape employing landmarks to record morphological points. Thus can detect subtle changes within shape. The aim of this project is to test the applicability of geometric morphometrics (GMM) to the analysis of trauma sustained to the human body, in particular the skeleton, within a forensic context. The primary objective is to employ GMM to trauma, specifically sharp force trauma, sustained to both the soft tissue and to the skeleton, to identify weapon class.
PhD title: Investigation of Protein and Dye Degradation of Wool in Soil Environment
Most of the woollen archaeological textiles excavated and displayed in museums are characterised by poor state of conservation due to exposure to various environmental factors like site of burial which includes composition of soil, temperature, pH, oxygen, metal content and various microorganisms (bacteria and fungi) and other factors like dye used and techniques used for dyeing (e.g. mordants). Archaeological textiles are able to tell us about the social, chronological and cultural aspects of societies in the past and thus preservation of these textiles is important. For assisting with the preservation of archaeological textiles, it is important to understand biodegradation of fibres and dyes used at biomolecular level. This information will help the conservators to choose appropriate measures in conservation of archaeological textiles.
The current study aims to investigate the protein and dye degradation of wool in burial environment. Shetland wool dyed using Birch dye will be exposed to various burial conditions using microcosm for 2, 4, 6 and 8 months. After burial, wool will undergo various substantial analysis like SEM for visual degradation observations, SEM-EDX and XRF for elemental analysis of dyed wool, LC-MS/MS for studying protein degradation of wool and HPLC-PDA for dye component analysis. Results of these visual, spectroscopic and chromatographic analysis will be evaluated and compared to understand the protein preservation of archaeological textiles which will also contribute towards growing literature in archaeological protein degradation.
PhD title: Visualising Vindolanda: Bioimaging from macro to micro
This research investigates potential ways to enhance the visualisation of Vindolanda and other archaeological investigations, from the macroscopic scale down to the microscopic scale. Vindolanda is a Roman World Heritage site at Hadrian’s Wall, known for the excellent levels of preservation of delicate artefacts.
The macroscopic component involves 3D terrestrial scanning of the excavations, followed by 3D surface scanning of recovered artefacts. These include a series of bovine crania used in target practice.
The microscopic component involves the use of pXRF for determining the inorganic elements in the burial environment. This shows the chemical composition associated with the excellent preservation and different contextual layers. This data is then processed into heat maps that contribute toward the interpretation and visualisation of the excavations, such as by demonstrating the internal and external areas of archaeological dwellings.
