Project Highlights:
· Develop an on-chip in vitro model of blood-brain barrier (BBB) for rapid and low-cost screening of the impacts of air pollutant particles on the brain;
· Screen a range of particle-based pollutants collected from previous projects in the UK and China, focussing on the total complexes and the extracted consistent to connect the continents to their individual effects;
· Build a model for prediction of the brain impacts of air pollution particle mixtures based on their physico-chemical characteristics and particle / co-pollutant ratios.
Overview:
Pollution is the great challenge of the Anthropocene epoch, contributing to 9 million premature deaths each year. Particles for a major constituent of air pollution are harmful to human and environmental health, with fine particles in the air resulting in a 4-6 month life expectancy reduction in the UK. Particles are also key vectors for pollutants, and indeed air pollution particles typically contain numerous organic and inorganic co-pollutants.
Ethical and animal welfare concerns are driving a move away from animal testing towards cellular-based in vitro testing of chemicals hazards, in line with the 3Rs principles of Replacement, Reduction and Refinement. We have successfully used a variety of human, animal and ecological cell models to assess the effects of different man-made hazards on human and environmental health. For example, we recently developed an in vitro transwell blood-brain barrier (BBB) model using human primary cells to mimic the in vivo BBB properties and functions, and have successfully applied it to test the transport of nanoscale particles across the barrier and their toxicity to neurons and brain tissue.
Building on this, the current project aims to develop a more realistic and sophisticated 3D in vitro BBB model using human primary cells, a BBB-on-a-chip, as an enabling technology to facilitate investigation of the human and environmental impacts of pollution, in support of the 3Rs and the implementation of New and Advanced Methodologies into regulation. UoB has a large collection of air pollution (particulate matter, PM) samples from urban, rural and remote (e.g., polar) regions in Beijing, Birmingham, and Thule (Greenland), and from specific sources (desert dust, road traffic and coal combustion) that will be utilised for this project. The composition, concentration and properties of the PM samples have been characterized. These particles, as received and following extraction of organic and inorganic constituents, will be screened for toxicity to, and passage across the in vitro BBB, in order to correlate cause and effect with PM pollutant composition. Using this unique dataset, a quantitative structure-activity model will be developed to support risk assessment and regulation.
Methodology:
The in vitro BBB model will be established by the PhD researcher following training in cell culture, and validation using a range of standardised tests will be performed. The transendothelial electrical resistance will be measured using an EVOM voltohmmeter. Protein expression of tight junction proteins will be examined using western blot and immunochemistry. The transport of known fluorescently-labelled compounds will be measured using microplate reader. TEM imaging will also be performed to confirm monolayer formation of the barrier. The panel of PM will be evaluated based on their chemical compositions and a sub-set selected for analysis of their toxicity to the barrier cells, and their transport across the barrier. The PM will then be washed to extract organic co-pollutants, and re-tested using the BBB model, using both the washed particles and the extracted co-pollutants to evaluate their impacts separately. Based on those datasets, a quantitative structure-activity model will be established.
Training and skills:
The student will be trained to handle cell culturing (including subculture, cryopreserve, defrosting of cells) different cells lines, barrier models and 3D cultures. Characterization of PM and extraction and chemical analysis skills will also be obtained. The student will also benefit from exposure to a number or experimental techniques at UoB including materials characterisation, biochemistry and molecular techniques, and will be trained in basic data handing and predictive modelling approaches.
Partners and collaboration:
Name of L1/L2 Partner: Environment Agency
Name of CASE: NovaMechanics, Cyprus
NovaMechanics Ltd is an R&D performing SME committed to the computer-aided design of new materials, small molecules and nanoparticles. NovaMechanics is focused on the development and implementation of in silico methods to guide decisions in the design and selection of promising candidates. Through the combination of industry-recognized expertise, state-of-the-art software and proprietary computing infrastructure, the company’s advanced in silico capabilities in molecular design and simulation provide the most effective path to molecular innovation. NovaMechanics will provide training in QSAR model development and provide access to INALOS and KNIME nodes.
Respiratory and Contact Infection Resilience of the Project:
The project is lab-based and will require extensive laboratory work. At UoB lab access was largely maintained throughout the pandemic with stringent controls to minimise risk of COVID-19 transmission. It seems likely that this access will be maintained in the event that more stringent COVID-19 regulations are re-enacted. As such, the project should be able to proceed under most likely conditions, if possibly in a more restricted, less interactive fashion than would be ideal.
Possible timeline:
Year 1: The student learn the cell culturing approaches and how to verify the establishment of a functioning BBB, and master a range of approaches such as fluorimetry, microscopy, biochemical assays etc.
Year 2: Screening of the PM Complexes, and the washed PM and extracted c-pollutants using the in vitro BBB, to understand the toxicity and transport / accumulation of the constituents versus the complex PM.
Year 3: Develop the predictive models based on the datasets and write up the publications
Applications should include:
• CENTA application form, downloadable from CENTA application
• CV with the names of at least two referees (preferably three and who can comment on your academic abilities)
• The application should please completed via: https://sits.bham.ac.uk/lpages/LES068.htm. Please select Apply Now in the PhD Geography and Environmental Science (CENTA) section. Please quote CENTA23_[B23] when completing the application form.
Further details:
Enquiries are very welcome, please contact Dr. Guo at [Email Address Removed], Prof. Lynch at [Email Address Removed] or Dr Thomas Matthews at [Email Address Removed].
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