Air pollution exposure is linked to diseases spanning multiple physiological systems. However, environmental stress is overwhelmingly associated with several lung diseases. Since the chemical composition of air pollutants varies widely across geographical locations, research on how specific components in pollutant mixtures contribute to cellular dysfunction is needed. In this work, we utilized microscopy-based morphological profiling as a tool to assess the cellular susceptibility to pollutants. Through our analysis, we established morphological profiles of formaldehyde-exposed cells that showed dose-dependent shifts in cell shape profiles correlating with overall cell health. As a real-world proof-of-concept validation, we evaluated the differences in particulate matter (PM) composition across multiple geographical areas, including both urban and suburban communities in Austin, Texas, USA. Data from this real-world study was used to inform a multicombinatorial study involving metals, selenium (Se) and manganese (Mn), which were differentially abundant across PM collection sites. As proof of concept to demonstrate the potential of establishing low-cost, high-throughput combinatorial screening of the biological effects of these metals, we incorporated microfluidic technology to simultaneously generate variable two-component metal mixtures in a multiwell plate format that enabled microscopy-based morphological screening as a proxy for toxicity. Combinatorial analysis of Se and Mn showed dynamic cell responses across a range of concentrations. Interestingly, exposure mixtures containing both Se and Mn yielded healthier cellular phenotypes relative to Se exposure as a single component. These results demonstrate the development of a high-throughput pipeline to detect dynamic biological responses to common air pollutants. Leveraging multiple technologies, we demonstrate the feasibility of a cost-effective approach that can serve as a starting point to inform focused screenings and studies of air pollutant mixtures that affect health outcomes.
Quiñones-Díaz et al. (Wed,) studied this question.
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