Sputum Microbiota in Coal Workers Diagnosed with Pneumoconiosis as Revealed by 16S rRNA Gene Sequencing

Research progress on the pathogenesis and prediction of pneumoconiosis among coal miners

Pneumoconiosis is the most common occupational disease among coal miners, which is a lung disease caused by long-term inhalation of coal dust and retention in the lungs. The early stage of this disease is highly insidious, and pulmonary fibrosis may occur in the middle and late stages, leading to an increase in patient pain index and mortality rate. Currently, there is a lack of effective treatment methods. The pathogenesis of pneumoconiosis is complex and has many influencing factors. Although the characteristics of coal dust have been considered the main cause of different mechanisms of pneumoconiosis, the effects of coal dust composition, particle size and shape, and coal dust concentration on the pathogenesis of pneumoconiosis have not been systematically elucidated. Meanwhile, considering the irreversibility of pneumoconiosis progression, early prediction for pneumoconiosis patients is particularly important. However, there is no early prediction standard for pneumoconiosis among coal miners. This review summarizes the relevant research on the pathogenesis and prediction of pneumoconiosis in coal miners in recent years. Firstly, the pathogenesis of coal worker pneumoconiosis and silicosis was discussed, and the impact of coal dust characteristics on pneumoconiosis was analyzed. Then, the early diagnostic methods for pneumoconiosis have been systematically introduced, with a focus on image collaborative computer-aided diagnosis analysis and biomarker detection. Finally, the challenge of early screening technology for miners with pneumoconiosis was proposed.

Lung microbiome: new insights into the pathogenesis of respiratory diseases

The lungs were long thought to be sterile until technical advances uncovered the presence of the lung microbial community. The microbiome of healthy lungs is mainly derived from the upper respiratory tract (URT) microbiome but also has its own characteristic flora. The selection mechanisms in the lung, including clearance by coughing, pulmonary macrophages, the oscillation of respiratory cilia, and bacterial inhibition by alveolar surfactant, keep the microbiome transient and mobile, which is different from the microbiome in other organs. The pulmonary bacteriome has been intensively studied recently, but relatively little research has focused on the mycobiome and virome. This up-to-date review retrospectively summarizes the lung microbiome's history, composition, and function. We focus on the interaction of the lung microbiome with the oropharynx and gut microbiome and emphasize the role it plays in the innate and adaptive immune responses. More importantly, we focus on multiple respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), fibrosis, bronchiectasis, and pneumonia. The impact of the lung microbiome on coronavirus disease 2019 (COVID-19) and lung cancer has also been comprehensively studied. Furthermore, by summarizing the therapeutic potential of the lung microbiome in lung diseases and examining the shortcomings of the field, we propose an outlook of the direction of lung microbiome research.

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

Background

Pneumoconiosis 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.

Methods

We 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.

Results

Among 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.

Conclusions

Overall, 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.

Microbiota and mycobiota in bronchoalveolar lavage fluid of silicosis patients

BACKGROUND

The contribution of bronchoalveolar lavage fluid (BALF) microbiota and mycobiota to silicosis has recently been noticed. However, many confounding factors can influence the accuracy of BALF microbiota and mycobiota studies, resulting in inconsistencies in the published results. In this cross-sectional study, we systematically investigated the effects of "sampling in different rounds of BALF" on its microbiota and mycobiota. We further explored the relationship between silicosis fatigue and the microbiota and mycobiota.

METHODS

After obtaining approval from the ethics board, we collected 100 BALF samples from 10 patients with silicosis. Demographic data, clinical information, and blood test results were also collected from each patient. The characteristics of the microbiota and mycobiota were defined using next-generation sequencing. However, no non-silicosis referent group was examined, which was a major limitation of this study.

RESULTS

Our analysis indicated that subsampling from different rounds of BALF did not affect the alpha- and beta-diversities of microbial and fungal communities when the centrifuged BALF sediment was sufficient for DNA extraction. In contrast, fatigue status significantly influenced the beta-diversity of microbes and fungi (Principal Coordinates Analysis, P = 0.001; P = 0.002). The abundance of Vibrio alone could distinguish silicosis patients with fatigue from those without fatigue (area under the curve = 0.938, 95% confidence interval [CI] 0.870-1.000). Significant correlations were found between Vibrio and haemoglobin levels (P < 0.001, ρ = -0.64).

CONCLUSIONS

Sampling in different rounds of BALF showed minimal effect on BALF microbial and fungal diversities; the first round of BALF collection was recommended for microbial and fungal analyses for convenience. In addition, Vibrio may be a potential biomarker for silicosis fatigue screening.