Abstract
BackgroundThe specific interactions of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), and the lung microbiota in infection are entirely unexplored. Studies in cancer and other infectious diseases suggest that there are important exchanges occurring between host and microbiota that influence the immunological landscape. This can result in alterations in immune regulation and inflammation both locally and systemically. To assess whether Mtb infection modifies the lung microbiome, and identify changes in microbial abundance and diversity as a function of pulmonary inflammation, we compared infected and uninfected lung lobe washes collected serially from 26 macaques by bronchoalveolar lavage over the course of infection.ResultsWe found that Mtb induced an initial increase in lung microbial diversity at 1 month post infection that normalized by 5 months of infection across all macaques. Several core genera showed global shifts from baseline and throughout infection. Moreover, we identified several specific taxa normally associated with the oral microbiome that increased in relative abundance in the lung following Mtb infection, including SR1, Aggregatibacter, Leptotrichia, Prevotella, and Campylobacter. On an individual macaque level, we found significant heterogeneity in both the magnitude and duration of change within the lung microbial community that was unrelated to lung inflammation and lobe involvement as seen by positron emission tomography/computed tomography (PET/CT) imaging. By comparing microbial interaction networks pre- and post-infection using the predictive algorithm SPIEC-EASI, we observe that extra connections are gained by Actinomycetales, the order containing Mtb, in spite of an overall reduction in the number of interactions of the whole community post-infection, implicating Mtb-driven ecological reorganization within the lung.ConclusionsThis study is the first to probe the dynamic interplay between Mtb and host microbiota longitudinally and in the macaque lung. Our findings suggest that Mtb can alter the microbial landscape of infected lung lobes and that these interactions induce dysbiosis that can disrupt oral-airway boundaries, shift overall lung diversity, and modulate specific microbial relationships. We also provide evidence that this effect is heterogeneous across different macaques. Overall, however, the changes to the airway microbiota after Mtb infection were surprisingly modest, despite a range of Mtb-induced pulmonary inflammation in this cohort of macaques.
Highlights
The specific interactions of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), and the lung microbiota in infection are entirely unexplored
Our findings suggest that Mtb can alter the microbial landscape of infected lung lobes and that these interactions induce dysbiosis that can disrupt oral-airway boundaries, shift overall lung diversity, and modulate specific microbial relationships
When we performed a Wilcoxon test, we observed a small but significant change post-infection compared to the baseline, with an initial overall increase in Beta-diversity at 1 month followed by a decline in Beta-diversity at months 4 and 5 (Fig. 1), indicating that microbial communities of the samples are becoming more similar at these later time points
Summary
The specific interactions of Mycobacterium tuberculosis (Mtb), the causative agent of tuberculosis (TB), and the lung microbiota in infection are entirely unexplored. Studies in cancer and other infectious diseases suggest that there are important exchanges occurring between host and microbiota that influence the immunological landscape. This can result in alterations in immune regulation and inflammation both locally and systemically. In the context of infectious disease, studies have shown that the microbiome has important influences on the immunological landscape by altering immune regulation, inflammation, and pathogen colonization [2, 7,8,9]. The precise mechanisms driving the variability in human Mtb infection outcome are poorly understood but may include the earliest interactions between pathogen and the local lung microbiota [21]
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