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Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
Exploring gut microbiota and its predicted functions in pulmonary tuberculosis: A multi-regional study using public
Tejaswini Baral1, Anwesh Maile2, Nagarajaram Hampapathalu Adimurthy2
1Department of Pharmacy Practice, Manipal College of Pharmaceutical Sciences, Manipal Academy of Higher Education, Manipal, Karnataka, India.
Background:
Pulmonary tuberculosis, caused by the bacillus Mycobacterium tuberculosis, remains a major global health challenge, particularly in developing countries. In this study, we analyzed publicly available 16S amplicon sequencing datasets from four geographical locations using a single workflow.
Methods:
We employed Quantitative Insights Into Microbial Ecology v.2 for microbial diversity analysis and Phylogenetic Investigation of Communities by Reconstruction of Unobserved States v.2 for functional pathway predictions of the gut microbiota in patients with PTB and antitubercular therapy.
Results:
Our analysis revealed statistically significant alpha diversity differences in West Africa with decreased microbial diversity in pulmonary tuberculosis patients after two months of antitubercular therapy. Additionally, there were no statistically significant differences observed in pairwise comparisons within the same location or in the aggregate beta diversity of the datasets. The predicted microbial metabolic pathways related to vitamin biosynthesis, amino acid synthesis, and energy production were depleted in pulmonary tuberculosis patients following antitubercular therapy.
Conclusions:
The observed alterations of gut microbial diversity and predicted functional profile underscores the influence of antitubercular therapy on gut health, suggesting that longer treatment durations may aggravate these alterations in gut microbial function. Moreover, geographical location exerts a more significant impact on microbial diversity than the disease state in a specific location, highlighting the potential for precision medicine to tailor interventions based on individual or regional microbiome characteristics.
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