2025-B13 Exploring How Environmental Pollutants Cross the Brain’s DefenCe

Project highlights

Innovate with a cutting-edge in vitro ‘Brain-on-a-Chip’ model to explore how air pollutants impact brain health.

Analyze a unique collection of air pollution particles from the UK and China to understand their individual and combined effects on the brain.

Develop predictive models to assess how different types of air pollution influence brain function

Overview

Pollution is one of the greatest challenges of our time, contributing to millions of premature deaths globally each year. Airborne particles, a major component of air pollution, are not only harmful themselves but also act as carriers for various toxic substances, significantly impacting human health and the environment. Fine particulate matter, in particular, has been linked to respiratory and cardiovascular diseases, and recent studies suggest that these particles can even affect the brain. This project offers a unique opportunity to explore how these particles penetrate the blood-brain barrier (BBB) and influence brain health using an innovative ‘Brain-on-a-Chip’ model.

Traditional methods of studying these impacts often rely on animal testing, which raises ethical concerns and has limitations in predicting human responses. In line with the 3Rs principles of Replacement, Reduction, and Refinement, this project aims to develop a cutting-edge, 3D in vitro BBB model using human primary cells. By creating this sophisticated ‘Brain-on-a-Chip’, we aim to transform the way we assess the neurotoxicity of pollutants, offering a rapid, low-cost, and human-relevant alternative to traditional animal models.

The project also leverages an extensive collection of air pollution samples gathered from diverse environments, including urban and rural areas in the UK and China, as well as remote regions like Greenland. These samples, collected from various sources such as road traffic, industrial emissions, and natural dust, have been extensively characterized in terms of their chemical composition and physical properties. Using our BBB model, we will screen these particles to understand their toxicity and ability to cross the BBB, correlating their effects with their chemical make-up and pollutant content.

By integrating these experimental results with advanced data analysis and predictive modelling, we aim to build a quantitative structure-activity model that can forecast the potential neurotoxic effects of different air pollutant mixtures. This research not only contributes to our understanding of the health impacts of air pollution but also supports the development of safer regulatory policies and innovative strategies for pollution management, paving the way for healthier and more sustainable environments.

Figure 1: Air pollution and brain health.

CENTA Flagship

This is a CENTA Flagship Project

Host

University of Birmingham

Theme

Climate and Environmental Sustainability

Supervisors

Project investigator

Dr Zhiling Guo, University of Birmingham, ([email protected])

Co-investigators

Prof Iseult Lynch, University of Birmingham, ([email protected])
Prof Zongbo Shi, University of Birmingham, ([email protected])
Dr Fatima Nasser

How to apply

Each host has a slightly different application process.
Find out how to apply for this studentship.
All applications must include the CENTA application form.
Choose your application route

Methodology

The methodology involves a multi-step approach integrating experimental and computational techniques. First, a Brain-on-a-chip model will be constructed using human brain cells to replicate the physiological environment of the human blood brain barrier. The model will be validated by assessing its barrier integrity, permeability, and functional markers.

Air pollution samples from diverse environments will then be introduced to the BBB model. The impact of different particulate matter types on BBB integrity and function will be evaluated using assays for trans-endothelial electrical resistance, permeability to fluorescent markers, and inflammatory responses. High-resolution microscopy and biochemical analyses will be used to track particle translocation and cellular uptake.

Finally, experimental data will be integrated with chemical and physical properties of particles using machine learning algorithms to develop a quantitative structure-activity relationship (QSAR) model. This model will predict neurotoxic potential based on pollutant characteristics, facilitating risk assessment and regulatory decision-making.

Training and skills

DRs will be awarded CENTA Training Credits (CTCs) for participation in CENTA-provided and ‘free choice’ external training. One CTC can be earned per 3 hours training, and DRs must accrue 100 CTCs across the three and a half years of their PhD.

Students involved in this project will gain extensive training in advanced cell culture techniques, including the development and maintenance of complex 3D in vitro models such as the Blood-Brain Barrier (BBB) on-a-chip. They will acquire skills in state-of-the-art analytical methods, including high-resolution microscopy, biochemical assays, and trans-endothelial electrical resistance (TEER) measurements to evaluate barrier integrity. Additionally, students will gain proficiency in handling and characterizing air pollution samples, data analysis, and machine learning techniques for predictive modeling. This comprehensive skill set will prepare them for careers in environmental health, toxicology, and advanced in vitro model development.

Partners and collaboration

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.

Further details

 For any enquiries related to this project please contact Dr. Guo at [email protected], Prof. Lynch at [email protected], Prof. Shi at [email protected], or Dr Thomas Matthews at [email protected].

 To apply to this project: 

You must include a CENTA studentship application form, downloadable from: CENTA Studentship Application Form 2025.

You must include a CV with the names of at least two referees (preferably three) who can comment on your academic abilities.

Please submit your application and complete the host institution application process via: https://sits.bham.ac.uk/lpages/LES068.htm.   Please select the PhD Geography and Environmental Science (CENTA) 2025/26 Apply Now button. The CENTA Studentship Application Form 2025 and CV can be uploaded to the Application Information section of the online form.  Please quote CENTA 2025-B13  when completing the application form.

 Applications must be submitted by 23:59 GMT on Wednesday 8th January 2025.  

Possible timeline

Year 1

Model Development and Validation

Months 1-3: Establishment of 3D in vitro BBB model using human primary cells.

Months 4-6: Validation of the model’s barrier integrity and functional markers.

Months 7-12: Optimization of model conditions and validation with control substances.

Year 2

Experimental Screening

Months 13-15: Collection and preparation of air pollution samples.

Months 16-20: Exposure studies using the BBB model to assess particle translocation and toxicity.

Months 21-24: Data analysis of BBB permeability, inflammation, and cellular responses.

Year 3

Data Integration and Modeling

Months 25-28: Integration of experimental data with pollutant properties.

Months 29-32: Development of QSAR model to predict neurotoxicity.

Months 33-36: Model validation, refinement, and dissemination of results through publications and conferences.