Statistical modelling based on structured surveys of Australian native possum excreta harbouring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans

  1. Koen Vandelannoote  Is a corresponding author
  2. Andrew H Buultjens
  3. Jessica L Porter
  4. Anita Velink
  5. John R Wallace
  6. Kim R Blasdell
  7. Michael Dunn
  8. Victoria Boyd
  9. Janet AM Fyfe
  10. Ee Laine Tay
  11. Paul DR Johnson
  12. Saras M Windecker
  13. Nick Golding
  14. Timothy P Stinear  Is a corresponding author
  1. University of Melbourne, Australia
  2. Millersville University, United States
  3. CSIRO Health and Biosecurity, Australia
  4. Victorian Infectious Diseases Reference Laboratory, Australia
  5. Department of Healt, Australia
  6. Austin Health, Australia
  7. Curtin University, Australia

Abstract

Background: Buruli ulcer (BU) is a neglected tropical disease caused by infection of subcutaneous tissue with Mycobacterium ulcerans. BU is commonly reported across rural regions of Central and West Africa but has been increasing dramatically in temperate southeast Australia around the major metropolitan city of Melbourne, with most disease transmission occurring in the summer months. Previous research has shown that Australian native possums are reservoirs of M. ulcerans and that they shed the bacteria in their fecal material (excreta). Field surveys show that locales where possums harbor M. ulcerans overlap with human cases of BU, raising the possibility of using possum excreta surveys to predict the risk of disease occurrence in humans.

Methods: We thus established a highly structured 12-month possum excreta surveillance program across an area of 350 km2 in the Mornington Peninsula area 70 km south of Melbourne, Australia. The primary objective of our study was to assess using statistical modelling if M. ulcerans surveillance of possum excreta provided useful information for predicting future human BU case locations.

Results: Over two sampling campaigns in summer and winter, we collected 2282 possum excreta specimens of which 11% were PCR positive for M. ulcerans-specific DNA. Using the spatial scanning statistical tool SaTScan, we observed non-random, co-correlated clustering of both M. ulcerans positive possum excreta and human BU cases. We next trained a statistical model with the Mornington Peninsula excreta survey data to predict the future likelihood of human BU cases occurring in the region. By observing where human BU cases subsequently occurred, we show that the excreta model performance was superior to a null model trained using the previous year's human BU case incidence data (AUC 0.66 vs 0.55). We then used data unseen by the excreta-informed model from a new survey of 661 possum excreta specimens in Geelong, a geographically separate BU endemic area to the southwest of Melbourne, to prospectively predict the location of human BU cases in that region. As for the Mornington Peninsula, the excreta-based BU prediction model outperformed the null model (AUC 0.75 vs 0.50) and pinpointed specific locations in Geelong where interventions could be deployed to interrupt disease spread.

Conclusions: This study highlights the One Health nature of BU by confirming a quantitative relationship between possum excreta shedding of M. ulcerans and humans developing BU. The excreta survey-informed modeling we have described will be a powerful tool for efficient targeting of public health responses to stop BU.

Funding: This research was supported by the National Health and Medical Research Council of Australia and the Victorian Government Department of Health (GNT1152807 and GNT1196396).

Data availability

The computer code and source data used in this study are available here: https://github.com/abuultjens/Possum_scat_survey_predict_human_BU.

Article and author information

Author details

  1. Koen Vandelannoote

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    For correspondence
    kvandelannoote@pasteur-kh.org
    Competing interests
    The authors declare that no competing interests exist.
  2. Andrew H Buultjens

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5984-1328
  3. Jessica L Porter

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  4. Anita Velink

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  5. John R Wallace

    Department of Biology, Millersville University, Millersville, United States
    Competing interests
    The authors declare that no competing interests exist.
  6. Kim R Blasdell

    CSIRO Health and Biosecurity, Geelong, Australia
    Competing interests
    The authors declare that no competing interests exist.
  7. Michael Dunn

    CSIRO Health and Biosecurity, Geelong, Australia
    Competing interests
    The authors declare that no competing interests exist.
  8. Victoria Boyd

    CSIRO Health and Biosecurity, Geelong, Australia
    Competing interests
    The authors declare that no competing interests exist.
  9. Janet AM Fyfe

    Doherty Institute for Infection and Immunity, Victorian Infectious Diseases Reference Laboratory, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
  10. Ee Laine Tay

    Health Protection branch, Department of Healt, Victoria, Australia
    Competing interests
    The authors declare that no competing interests exist.
  11. Paul DR Johnson

    North Eastern Public Health Unit, Austin Health, Heidelberg, Australia
    Competing interests
    The authors declare that no competing interests exist.
  12. Saras M Windecker

    School of Ecosystem and Forest Sciences, University of Melbourne, Melbourne, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-4870-8353
  13. Nick Golding

    Spatial Ecology and Epidemiology Group, Curtin University, Bentley, Australia
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-8916-5570
  14. Timothy P Stinear

    Department of Microbiology and Immunology, University of Melbourne, Melbourne, Australia
    For correspondence
    tstinear@unimelb.edu.au
    Competing interests
    The authors declare that no competing interests exist.
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0003-0150-123X

Funding

National Health and Medical Research Council (GNT1152807)

  • Timothy P Stinear

National Health and Medical Research Council (GNT1196396)

  • Timothy P Stinear

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Ethics

Human subjects: Ethical approval for the use in this study of de-identified human BU case location, aggregated at mesh block level, was obtained from the Victorian Government Department of Health Human Ethics Committee under HREC/54166/DHHS-2019-179235(v3), "Spatial risk map of Buruli ulcer infection in Victoria".

Copyright

© 2023, Vandelannoote et al.

This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.

Metrics

  • 1,298
    views
  • 139
    downloads
  • 15
    citations

Views, downloads and citations are aggregated across all versions of this paper published by eLife.

Download links

A two-part list of links to download the article, or parts of the article, in various formats.

Downloads (link to download the article as PDF)

Open citations (links to open the citations from this article in various online reference manager services)

Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)

  1. Koen Vandelannoote
  2. Andrew H Buultjens
  3. Jessica L Porter
  4. Anita Velink
  5. John R Wallace
  6. Kim R Blasdell
  7. Michael Dunn
  8. Victoria Boyd
  9. Janet AM Fyfe
  10. Ee Laine Tay
  11. Paul DR Johnson
  12. Saras M Windecker
  13. Nick Golding
  14. Timothy P Stinear
(2023)
Statistical modelling based on structured surveys of Australian native possum excreta harbouring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans
eLife 12:e84983.
https://doi.org/10.7554/eLife.84983

Share this article

https://doi.org/10.7554/eLife.84983

Further reading

    1. Epidemiology and Global Health
    2. Genetics and Genomics
    Tianyu Zhao, Hui Li ... Li Chen
    Research Article

    Alzheimer’s disease (AD) is a complex degenerative disease of the central nervous system, and elucidating its pathogenesis remains challenging. In this study, we used the inverse-variance weighted (IVW) model as the major analysis method to perform hypothesis-free Mendelian randomization (MR) analysis on the data from MRC IEU OpenGWAS (18,097 exposure traits and 16 AD outcome traits), and conducted sensitivity analysis with six models, to assess the robustness of the IVW results, to identify various classes of risk or protective factors for AD, early-onset AD, and late-onset AD. We generated 400,274 data entries in total, among which the major analysis method of the IVW model consists of 73,129 records with 4840 exposure traits, which fall into 10 categories: Disease, Medical laboratory science, Imaging, Anthropometric, Treatment, Molecular trait, Gut microbiota, Past history, Family history, and Lifestyle trait. More importantly, a freely accessed online platform called MRAD (https://gwasmrad.com/mrad/) has been developed using the Shiny package with MR analysis results. Additionally, novel potential AD therapeutic targets (CD33, TBCA, VPS29, GNAI3, PSME1) are identified, among which CD33 was positively associated with the main outcome traits of AD, as well as with both EOAD and LOAD. TBCA and VPS29 were negatively associated with the main outcome traits of AD, as well as with both EOAD and LOAD. GNAI3 and PSME1 were negatively associated with the main outcome traits of AD, as well as with LOAD, but had no significant causal association with EOAD. The findings of our research advance our understanding of the etiology of AD.

    1. Epidemiology and Global Health
    Xiaoning Wang, Jinxiang Zhao ... Dong Liu
    Research Article

    Artificially sweetened beverages containing noncaloric monosaccharides were suggested as healthier alternatives to sugar-sweetened beverages. Nevertheless, the potential detrimental effects of these noncaloric monosaccharides on blood vessel function remain inadequately understood. We have established a zebrafish model that exhibits significant excessive angiogenesis induced by high glucose, resembling the hyperangiogenic characteristics observed in proliferative diabetic retinopathy (PDR). Utilizing this model, we observed that glucose and noncaloric monosaccharides could induce excessive formation of blood vessels, especially intersegmental vessels (ISVs). The excessively branched vessels were observed to be formed by ectopic activation of quiescent endothelial cells (ECs) into tip cells. Single-cell transcriptomic sequencing analysis of the ECs in the embryos exposed to high glucose revealed an augmented ratio of capillary ECs, proliferating ECs, and a series of upregulated proangiogenic genes. Further analysis and experiments validated that reduced foxo1a mediated the excessive angiogenesis induced by monosaccharides via upregulating the expression of marcksl1a. This study has provided new evidence showing the negative effects of noncaloric monosaccharides on the vascular system and the underlying mechanisms.