Geographical inference of dust from typical Chinese cities based on metagenomic shotgun sequencing.

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<0.001). Additionally, 127 biomarkers are identified using linear discriminant analysis effect size (LEfSe) to distinguish between the cities. Each city harbors a distinct microbial community, with unique species and relatively abundant taxa that contribute to its differentiated microbial profile. All samples are randomly split into training and testing sets in a 7:3 ratio. Five machine learning models including SourceTracker, FEAST, LightGBM, Random Forest and Support Vector Machine are applied to 51 randomly sample data and achieve average accuracies of 88.89%, 92.16%, 98.04%, 99.35% and 69.28%, respectively. These results constitute a microbial genetic map of four cities in China that highlights distinct microbial taxonomic signatures and provides an approach for city-scale source tracking of dust samples.

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