Uncovering the cytotoxic effects of air pollution with multi-modal imaging of in vitro respiratory models.
Zeinab Al-RekabiCamilla DondiNilofar FaruquiNazia S SiddiquiLinda ElowssonJenny RisslerMonica KåredalIan MudwayAnna-Karin Larsson-CallerfeltMichael ShawPublished in: Royal Society open science (2023)
Annually, an estimated seven million deaths are linked to exposure to airborne pollutants. Despite extensive epidemiological evidence supporting clear associations between poor air quality and a range of short- and long-term health effects, there are considerable gaps in our understanding of the specific mechanisms by which pollutant exposure induces adverse biological responses at the cellular and tissue levels. The development of more complex, predictive, in vitro respiratory models, including two- and three-dimensional cell cultures, spheroids, organoids and tissue cultures, along with more realistic aerosol exposure systems, offers new opportunities to investigate the cytotoxic effects of airborne particulates under controlled laboratory conditions. Parallel advances in high-resolution microscopy have resulted in a range of in vitro imaging tools capable of visualizing and analysing biological systems across unprecedented scales of length, time and complexity. This article considers state-of-the-art in vitro respiratory models and aerosol exposure systems and how they can be interrogated using high-resolution microscopy techniques to investigate cell-pollutant interactions, from the uptake and trafficking of particles to structural and functional modification of subcellular organelles and cells. These data can provide a mechanistic basis from which to advance our understanding of the health effects of airborne particulate pollution and develop improved mitigation measures.
Keyphrases
- high resolution
- particulate matter
- air pollution
- heavy metals
- single cell
- high speed
- cell therapy
- mass spectrometry
- healthcare
- climate change
- induced apoptosis
- public health
- risk assessment
- tandem mass spectrometry
- mesenchymal stem cells
- single molecule
- oxidative stress
- cell cycle arrest
- fluorescence imaging
- big data
- optical coherence tomography
- deep learning
- chronic obstructive pulmonary disease
- water soluble
- machine learning
- social media
- artificial intelligence
- high throughput
- mental health
- liquid chromatography
- drinking water
- drug induced