Analysis of single-cell microbial mass spectra profiles from single-particle aerosol mass spectrometry

Single-particle aerosol mass spectrometry is a practical method for studying microbial aerosols. However, the related mass spectral characteristics of single-cell microorganisms have not yet been studied systematically; hence, further investigations are necessary.

Different microbial cells were grown and directly aerosolized in the laboratory. These aerosols were then drawn into a single-particle mass spectrometer platform, and single-cell mass spectra profiles were obtained in real-time. The biological characteristics, ion variation trends, and microbial types were analyzed with either laser pulse energy or laser fluence.

The single-particle mass spectra contained prominent peaks that could be attributed to the presence of biological matter, such as organic phosphate and nitrogen, amino acids, and spore-associated calcium complexes. Limited types of average mass spectral patterns were present, and a significant correlation was found between the ion intensity trend (presence and absence of peaks) and laser ionization energy (expressed by the total positive ion intensity). Although a single spectral data point does not contain all the peaks of the average spectrum, it covers most of the characteristic peaks and could be identified using a machine learning algorithm. After the analysis of single-particle mass spectra, we found that using multi-group features (e.g., peak intensity ratio of m/z +47 and +41, peak intensity ratio of ⁵⁹ N(CH₃ )₃ ⁺ and ⁷⁴ N(CH₃ )₄ ⁺ , and 12 peak variables) led to an identification accuracy of approximately 92.4% with the random forest algorithm.

The results indicate that single-cell mass spectral profiles can be used to distinguish microbial aerosols and further illustrate their origin in a laboratory setting.