, Volume 14, Issue 2, pp 329–341 | Cite as

Ecology and Feeding Habits Drive Infection of Water Bugs with Mycobacterium ulcerans

  • Solange Meyin A. EbongEmail author
  • Gabriel E. García-Peña
  • Dominique Pluot-Sigwalt
  • Laurent Marsollier
  • Philippe Le Gall
  • Sara Eyangoh
  • Jean-François Guégan
Original Contribution


Mycobacterium ulcerans (MU), the causative agent of Buruli ulcer, is present in a wide spectrum of environments, including terrestrial and aquatic ecosystems in tropical regions. The most promising studies on the epidemiological risk of this disease suggest that some ecological settings may favor infection of animals with MU including human. A species’ needs and impacts on resources and the environment, i.e., its ecological niche, may influence its susceptibility to be infected by this microbial form. For example, some Naucoridae may dive in fresh waters to prey upon infected animals and thus may get infected with MU. However, these studies have rarely considered that inference on the ecological settings favoring infection and transmission may be confounded because host carrier sister species have similar ecological niches, and potentially the same host–microbe interactions. Hence, a relationship between the ecological niche of Naucoridae and its infection with MU may be due to a symbiotic relationship between the host and the pathogen, rather than its ecological niche. To account for this confounding effect, we investigated the relationships between surrogates of the ecological niche of water bug species and their susceptibility to MU, by performing phylogenetic comparative analyses on a large dataset of 11 families of water bugs collected in 10 different sites across Cameroon, central Africa. Our results indicate that MU circulates and infects a couple of host taxa, i.e., Belostomatidae, Naucoridae, living both in the aquatic vegetation and as predators inside the trophic network and sister species of water bugs have indeed similar host–microbe interactions with MU.


Hemiptera Mycobacterium ulcerans Buruli ulcer disease ecology 



We thank the staff at the Département Systématique et Evolution at Museum National d’Histoire Naturelle Paris, France notably Eric Guilbert and Laurent Fauve who introduced SMàE to morphological taxonomy techniques and assisted her a lot in the bibliographic research on Afro-tropical water bugs. The Collaboration with Professor Myriam Harry allowed us to obtain the sequences of aquatic bugs that were used in this study, and we present our gratitude.

Supplementary material

10393_2017_1228_MOESM1_ESM.pdf (327 kb)
Supplementary Figure 1. Distributions of the posterior estimates of the transition rates (q) of the correlated models of evolution. Prior distribution was assumed exponential (1.5 e−1.5x ). (PDF 326 kb)
10393_2017_1228_MOESM2_ESM.pdf (361 kb)
Supplementary Fig. 2. Models correlation between the ecological traits and susceptibility to Mycobacterium ulcerans (MU). Results found by the maximum likelihood procedure were corroborated by the Bayesian approach of BayesTraits. The harmonic mean was used as surrogate of the marginal likelihood to compare the fit of two models: one suggesting the correlated model of evolution of an ecological trait and susceptibility to MU and other model suggesting the independent evolution of these two traits (red). Statistical inference was assessed by the log Bayes Factor (log BF) = 2(log H correlated model − log H independent model). These estimates suggest positive evidence for the correlation (logBF > 2) between susceptibility to MU and the ecological traits: macropredator (logBF = 7.2), living in aquatic vegetation (log BF = 7.0) and living at the bottom of the water column (log BF = 2.8). (PDF 360 kb)
10393_2017_1228_MOESM3_ESM.pdf (37 kb)
Supplementary Table 1. Evolution models of nucleotide sequences. Analysis was performed using JModelTest. The likelihood scores were calculated with PhyML for 88 candidate models and number of substation schemes equal to 11. Akaike’s test allowed to select the best model (GTR + I+G) with following settings: Partition = 012345, negative log likelihood (-InL) = 12489.6675, number of estimated parameters (K) = 356, P-inv = 0.0000, Gamma shape = 0.2310 (PDF 37 kb)
10393_2017_1228_MOESM4_ESM.doc (28 kb)
Supplementary file 1: Script used for sunning the models on Bayes traits (DOC 28 kb)
10393_2017_1228_MOESM5_ESM.nex (6 kb)
Supplementary file 2: Nexus file V.nex (NEX 6 kb)


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Copyright information

© International Association for Ecology and Health 2017

Authors and Affiliations

  • Solange Meyin A. Ebong
    • 1
    • 2
    • 3
    Email author
  • Gabriel E. García-Peña
    • 1
    • 4
  • Dominique Pluot-Sigwalt
    • 5
  • Laurent Marsollier
    • 6
  • Philippe Le Gall
    • 7
  • Sara Eyangoh
    • 2
  • Jean-François Guégan
    • 1
  1. 1.UMR MIVEGEC IRD, CNRS, Université de MontpellierCentre IRD de MontpellierMontpellier CedexFrance
  2. 2.Service de MycobactériologieCentre Pasteur du CamerounYaoundéCameroon
  3. 3.Laboratoire de Parasitologie et Ecologie, Faculté des SciencesUniversité de Yaoundé IYaoundéCameroon
  4. 4.Centre de Synthèse et d’Analyse sur la Biodiversité (CESAB)Aix-en-Provence Cedex 3France
  5. 5.Département Systématique et Evolution, UMR7205 CNRS/MNHNMuseum National d’Histoire NaturelleParisFrance
  6. 6.Inserm Avenir ATOMycA CRCNA Inserm U892 & CNRS U6299Université et CHU d’AngersAngersFrance
  7. 7.UMR EGCE IRD, CNRS et Université Paris-Sud OrsayCentre CNRS de Gif-sur-YvetteGif-sur-Yvette CedexFrance

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