Abstract:

Objective To investigate changes in respiratory microbial flora composition in pulmonary tuberculosis patients and healthy individuals. Methods Multiple Chinese and English databases were searched with keywords “tuberculosis” and “respiratory tract flora”. Publications between 2010 and 2019 were selected according to literature screening procedure and then included. All available next-generation sequencing data were collected, parameters unified, data pre-processed and then used for metagenomic analysis and statistical processing. Results Nine English literatures were included. Species analysis suggested that the top 10 most abundant bacterial groups in both tuberculosis group and healthy control group were: Firmicutes, OD1, Proteobacteria, Bacteroidetes, Actinobacteria, and Fusobacteria, Cyanobacteria. However, there were significant differences in the composition of respiratory bacterial flora between the two groups. α diversity analysis showed that the number of OTUs (286.60±22.82), Faith ‘s PD index (13.57±2.58), and Shannon index (7.17±0.24) observed in tuberculosis group were significantly higher than those of healthy control group (42.88±2.49, 6.52±0.22, 4.42±0.07, respectively), which was statistically significant (P=0.00016,0.00056,0.00016). Chao1 index of tuberculosis group was higher than healthy control group (266.50±92.71 vs. 38.44±2.86), without statistical significance (P>0.05). Six phyla were found to have different abundance in the two groups, 5 of which were clustered in healthy controls: Firmicutes, Proteobacteria, Bacteroidetes, Actinobacteria and Fusobacteria, the other one-OD1 clustered in tuberculosis group. F16 family, Gammaproteobacteria, Firmicutes phylum, Leuconostocaceae family and Bacilillaceae family were found to be tuberculosis-specific. Conclusion Compared with healthy people, there are significant changes in respiratory tract flora diversity and species composition in tuberculosis patients, with presence of unique flora.

Key words: Tuberculosis, pulmonary, Respiratory mucosa, Microbiology, Metagenome, Data interpretation, statistical