Application of mNGS in the study of pulmonary microbiome in pneumoconiosis complicated with pulmonary infection patients and exploration of potential biomarkers

Abstract

BackgroundPneumoconiosis patients have a high prevalence of pulmonary infections, which can complicate diagnosis and treatment. And there is no comprehensive study of the microbiome of patients with pneumoconiosis. The application of metagenomic next-generation sequencing (mNGS) fills the gap to some extent by analyzing the lung microbiota of pneumoconiosis population while achieving accurate diagnosis.MethodsWe retrospectively analyzed 44 patients with suspected pneumoconiosis complicated with pulmonary infection between Jan 2020 and Nov 2022. Bronchoalveolar lavage fluid (BALF) specimens from 44 patients were collected and tested using the mNGS technology.ResultsAmong the lung microbiome of pneumoconiosis patients with complicated pulmonary infection (P group), the most frequently detected bacteria and fungi at the genus level were Streptococcus and Aspergillus, at the species level were Streptococcus pneumoniae and Aspergillus flavus, respectively, and the most frequently detected DNA virus was Human gammaherpesvirus 4. There was no significant difference in α diversity between the P group and the non-pneumoconiosis patients complicated with pulmonary infection group (Non-P group) in pulmonary flora, while P< 0.01 for β diversity analysis, and the differential species between the two groups were Mycobacterium colombiense and Fusobacterium nucleatum. In addition, we monitored a high distribution of Malassezia and Pneumocystis in the P group, while herpes virus was detected in the majority of samples.ConclusionsOverall, we not only revealed a comprehensive lung microbiome profile of pneumoconiosis patients, but also compared the differences between their microbiome and that of non-pneumoconiosis complicated with pulmonary infection patients. This provides a good basis for a better understanding of the relationship between pneumoconiosis and microorganisms, and for the search of potential biomarkers.

Optimizing treatment administration strategies using negative mNGS results in corticosteroid-sensitive diffuse parenchymal lung diseases

“…utilize mNGS to uncover the relationship between lung microbiota and lung diseases in patients with pneumoconiosis and pulmonary infection, implying that lung microbiota could be biomarkers in lung diseases. 15 CRP and PCT could exclude the infection probabilities in critical ill patients but the predictive performance was vulnerable to the impact of antibiotic utility. 30 Compared to CRP or PCT, microbiota would serve as better biomarkers for assessing therapeutic efficacy and monitoring disease progression in lung diseases, as they are less influenced by prior antibiotic exposure.…”

“…Medical modification could be dependent on these results. 14 Moreover, compared to 16S rRNA, mNGS furnishes a broader spectrum of information about the background microbiota, 15 which may be associated with the manifestations of the disease.…”