Bacterial diversity in Buruli ulcer skin lesions: Challenges in the clinical microbiome analysis of a skin disease

Abstract

Background: Buruli ulcer (BU) is an infectious disease caused by Mycobacterium ulcerans and considered the third most prevalent mycobacterial disease in humans. Secondary bacterial infections in open BU lesions are the main cause of pain, delayed healing and systemic illness, resulting in prolonged hospital stay. Thus, understanding the diversity of bacteria, termed the microbiome, in these open lesions is important for proper treatment. However, adequately studying the human microbiome in a clinical setting can prove difficult when investigating a neglected tropical skin disease due to its rarity and the setting.

Methodology/principal findings: Using 16S rRNA sequencing, we determined the microbial composition of 5 BU lesions, 3 non-BU lesions and 3 healthy skin samples. Although no significant differences in diversity were found between BU and non-BU lesions, the former were characterized by an increase of Bacteroidetes compared to the non-BU wounds and the BU lesions also contained significantly more obligate anaerobes. With this molecular-based study, we were also able to detect bacteria that were missed by culture-based methods in previous BU studies.

Conclusions/significance: Our study suggests that BU may lead to changes in the skin bacterial community within the lesions. However, in order to determine if such changes hold true across all BU cases and are either a cause or consequence of a specific wound environment, further microbiome studies are necessary. Such skin microbiome analysis requires large sample sizes and lesions from the same body site in many patients, both of which can be difficult for a rare disease. Our study proposes a pipeline for such studies and highlights several drawbacks that must be considered if microbiome analysis is to be utilized for neglected tropical diseases.

Fig 1. α-diversity calculations for BU (n = 6; 5 patients), non-BU (n = 3; 3 patients), and healthy (n = 3; 3 patients) samples.

Whiskers in the boxplot represent minimum and maximum α-diversity values within the three groups. Significant differences were only seen between BU and healthy samples: (A) p = 0.027; (B) p = 0.009; (C) p = 0.036; non-parametric two sample t-test via Monte-Carlo permutation with Bonferroni multiple test correction.

Fig 2. PCoA plot representing the distances between samples, expressed by the Bray-Curtis metric.

Each point represents a different sample, while the colored circles, triangles, and squares represent BU, non-BU, and Healthy, respectively.

Fig 3. Phylum taxonomy level classifications.

Bar plot showing the relative proportions of the phyla within all the samples.

Fig 4. Oxygen tolerance within the three groups: Whiskers in the boxplot represent minimum and maximum values within the three groups.

The BU lesions were almost entirely dominated by obligate anaerobes, which was significantly different from the healthy samples (p = 0.0325; Welch’s t-test with Benjamini-Hochberg FDR multiple test correction). The Non-BU group showed an increase in facultative anaerobic bacteria.