Integrated Analysis of Microbiome and Host Transcriptome Unveils Correlations Between Lung Microbiota and Host Immunity in Bronchoalveolar Lavage Fluid of Pneumocystis Pneumonia Patients

Objective: The lung microbiota of patients with pulmonary diseases is disrupted and impacts the immunity. The microbiological and immune landscape of the lungs in patients with pneumocystis pneumonia (PCP) remains poorly understood.

Methods: Multi-omics analysis and machine learning were performed on bronchoalveolar lavage fluid to explore interaction between the lung microbiota and host immunity in PCP. Then we constructed a diagnostic model using differential genes with LASSO regression and validated by qPCR. The immune infiltration analysis was performed to explore the landscape of lung immunity in patients with PCP.

Results: Patients with PCP showed a low alpha diversity of lung microbiota, accompanied by the elevated abundance of Firmicutes, and the differential expressed genes (DEGs) analysis displayed a downregulation of MAPK signaling. The MAPK10, TGFB1, and EFNA3 indicated a potential to predict PCP (AUC = 0.86). The lung immune landscape in PCP showed the lower levels of naïve CD4 T cells and activated dendritic cells. The correlation analysis of the MAPK signaling pathway-related DEGs and the differential microorganisms at the level of phylum showed that the Firmicutes was negatively correlated with these DEGs.

Conclusion: We profiled the characteristics of lung microbiota and immune landscape in PCP, which may contribute to elucidating the mechanism of PCP.