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Randomized Controlled Trial
. 2023 Jun 15;11(3):e0206622.
doi: 10.1128/spectrum.02066-22. Epub 2023 Apr 24.

Azithromycin Exposure Induces Transient Microbial Composition Shifts and Decreases the Airway Microbiota Resilience from Outdoor PM2.5 Stress in Healthy Adults: a Randomized, Double-Blind, Placebo-Controlled Trial

Affiliations
Randomized Controlled Trial

Azithromycin Exposure Induces Transient Microbial Composition Shifts and Decreases the Airway Microbiota Resilience from Outdoor PM2.5 Stress in Healthy Adults: a Randomized, Double-Blind, Placebo-Controlled Trial

Sisi Du et al. Microbiol Spectr. .

Abstract

Inappropriate antibiotic prescriptions are common for patients with upper respiratory tract infections (URTIs). Few data exist regarding the effects of antibiotic administration on airway microbiota among healthy adults. We conducted a randomized, double-blind, placebo-controlled trial to characterize the airway microbiota longitudinally in healthy adults using 16S rRNA gene sequencing and quantification. Both the induced sputum and oral wash samples were collected over a 60-day period following a 3-day intervention with 500 mg azithromycin or placebo. Environmental information, including air quality data (particulate matter [PM2.5] and PM10, air quality index [AQI] values), were also collected during the study. A total of 48 healthy volunteers were enrolled and randomly assigned into two groups. Azithromycin did not alter bacterial load but significantly reduced species richness and Shannon index. Azithromycin exposure resulted in a decrease in the detection rate and relative abundance of different genera belonging to Veillonellaceae, Leptotrichia, Fusobacterium, Neisseria, and Haemophilus. In contrast, the relative abundance of taxa belonging to Streptococcus increased immediately after azithromycin intervention. The shifts in the diversity of the microbiology composition took between 14 and 60 days to recover, depending on the measure used: either UniFrac phylogenetic distance or α-diversity. Outdoor environmental perturbations, especially the high concentration of PM2.5, contributed to novel variability in microbial community composition of the azithromycin group at D30 (30 days after baseline). The network analysis found that azithromycin altered the microbial interactions within airway microbiota. The influence was still obvious at D14 when the relative abundance of most taxa had returned to the baseline level. Compared to the sputum microbiota, oral cavity microbiota had a different pattern of change over time. The induced sputum microbial data can represent the airway microbiota composition in healthy adults. Azithromycin may have transient effects in the airway microbiota of healthy adults and decrease the airway microbiota resilience against outdoor environmental stress. The influence of azithromycin on microbial interactions is noteworthy, although the airway microbiota has returned to a near-baseline level. IMPORTANCE The influence of antibiotic administration on the airway microbiota of healthy adults remains unknown. This study is a randomized, double-blind, placebo-controlled trial aiming to investigate the microbial shifts in airways after exposure to azithromycin among heathy adults. We find that azithromycin changes the airway microbial community composition of healthy adults and decreases the airway microbiota resilience against outdoor environmental stress. This study depicts the longitudinal recovery trajectory of airway microbiota after the antibiotic perturbation and may provide reference for appropriate antibiotic prescription.

Keywords: PM2.5; airway microbiota; azithromycin; biodiversity; healthy volunteers; network; stability.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

FIG 1
FIG 1
Overview of the study design and sample collection. The healthy volunteers (n = 48) enrolled in this study were stratified by gender and randomly assigned to either the azithromycin or the placebo group (1:1). Either 500 mg azithromycin or 500 mg starch contained in identical opaque white capsules was administered once daily (QD) for 3 days. The sputum samples were collected the day before the drug administration (D0), the day after the treatment course is completed (D4), and at 14 (D14), 30 (D30), and 60 days (D60) postdosing. Then 16S rRNA gene sequencing was applied to the induced sputum samples and negative-control samples. The bacterial DNA of sputum samples was quantified using a QX200 Droplet Digital PCR system. The microbial ecology analysis is performed on the data produced from the study later.
FIG 2
FIG 2
Sputum bacterial DNA quantification using droplet digital PCR of the 16S rRNA gene. There was no significant difference in sputum bacterial DNA load across different time points in either the azithromycin group (A) or the placebo group (B) (Wilcoxon signed-rank test, Bonferroni adjusted P values [q] > 0.05 for all). The boxplots represent the bacterial DNA load for the subjects (center line, mean; box limits, ±standard deviation; whisker limits, maximum/minimum). The points are connected across time points by gray lines.
FIG 3
FIG 3
Airway microbial diversity and community composition changes in the azithromycin group. (A, B) The boxplots represent the diversity measures for the subjects (center line, mean; box limits, ±standard deviation; whisker limits, maximum/minimum). (A) Species richness. (B) Shannon index. The points are connected across time points by gray lines. (C, E) Principal coordinate analysis (PCoA) plots based on unweighted UniFrac distance (C) and weighted UniFrac distance (E). The ellipses represent the 68% confidence interval for each time point. (D) The boxplots in dark yellow showed that the extent of compositional changes between paired samples in the azithromycin (AZM) group during the study time (D0 versus D4, D0 versus D14, and D0 versus D30) were significantly different compared to the degree of variation over time observed for paired samples in the placebo (PLA) group (two-sided Wilcoxon rank sum test, q < 0.05), but the compositional changes between D0 and D60 did not differ from the placebo group. (F) The significant difference between paired samples in the azithromycin group was observed only at D4 compared to the shift for paired samples in the placebo group (two-sided Wilcoxon rank sum test, q = 0.0075), but the compositional changes between D0 and D14, between D0 and D30, and between D0 and D60 did not differ from the placebo group (center line, mean; box limits, ±standard deviation; whisker limits, maximum/minimum).
FIG 4
FIG 4
Microbial taxonomic variation after azithromycin administration during 60-day follow-up. The blue boxes mean the detection rate of zero-radius operational taxonomic units (ZOTUs) across the five time points. The detection rate describes the proportion of individual ZOTU appearing in the subjects. The red boxes mean the mean relative abundance of ZOTUs across the five time points. The relative abundance describes the mean percentage of the individual ZOTU in the whole subjects. *, P value ≥ 0.05: there is not a significant difference in the relative abundance of the species at D14 compared to D0; P value < 0.05: there is a significant difference in the relative abundance of the species at D14 compared to D0.
FIG 5
FIG 5
The network analysis in the azithromycin group. (A) Networks of co-occurring ZOTUs in airway microbiota for time points D0, D4, D14, D30, and D60. Nodes are colored by ZOTU genera, with size proportional to mean relative abundance and edge width proportional to confidence score. (B) The number of shared edges between network D0 and time points D4, D14, D30, and D60. (C) The closeness centralization of shared nodes between network D0 and time points D4, D14, D30, and D60.

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