Label-free Raman spectroscopic imaging enables high-content molecular phenotyping of respiratory diseases from bronchoalveolar lavage fluid.

BACKGROUND: Conventional BALF analysis is limited by time-consuming labeling, poor multiplexing, and lack of spatial resolution-constraints that Raman imaging can overcome through label-free, multiplexed molecular mapping. However, its clinical application to BALF remains unexplored. We aimed to address this gap by establishing a Raman imaging platform for simultaneous biomarker detection across respiratory diseases. METHODS: Fresh BALF samples were collected from patients diagnosed with Mycoplasma pneumoniae pneumonia (n = 6), lobar pneumonia (n = 6), asthma (n = 6), and asthmatic bronchitis (n = 6), along with healthy controls (n = 6), following standard protocols. An automated Raman imaging method was then developed to identify biomarkers in BALF using confocal Raman microscopy. RESULTS: Our method enables the simultaneous Raman spectroscopy imaging of nine biomarkers in BALF samples across different respiratory diseases, including glycogen, hyaluronic acid, four specific proteins, and three lipid types. An entire saturated lipid droplet in the BALF of·asthmatic bronchitis was observed and reconstructed. Based on the reconstructed Raman images of biomarkers, we achieved rapid and stain-free differentiation of Mycoplasma pneumoniae pneumonia, lobar pneumonia, asthma, and asthmatic bronchitis. Our method can complete Raman data acquisition and Raman imaging reconstruction within 10 minutes. CONCLUSIONS: Raman images highlighted the unique distribution characteristics of various biomarkers, serving as a novel and rapid method for BALF testing and respiratory diseases diagnosis.