Bioaerosols are of great health and environmental concern. Current techniques for their characterization are generally designed to detect individual species or oppositely unspecific molecular tracers. Metaproteomics on the other hand features the possibility to cover a broad range of taxonomies in a single analysis. This work presents a successful application of metaproteomics to characterize the biological fraction of airborne particulate matter (PM). A bottom-up proteomic strategy was employed, including protein extraction by ultrasonication in aqueous buffer, in-solution tryptic digestion, and nanoflow liquid chromatography-high-resolution mass spectrometry analysis. Extraction parameters were optimized to enhance proteins' recovery. The method was validated on Escherichia coli extracts before its application on ambient PM₁₀ samples collected over 12 weeks in Strasbourg, France. A total of 1,087 peptides were detected across all samples, with a weekly average of 223 ± 104 peptides corresponding to 111 ± 40 proteins. Peptides from species belonging to animals, plants, fungi, bacteria, and archaea kingdoms were inventoried. Many of them proved to be very relevant, as they were related to human allergens and pathogens, plant pathogens, or ecological indicators. In this work, the major benefits of metaproteomics, yet rather unexploited, as well as its pitfalls and challenges for a broader application in atmospheric chemistry, are discussed.