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Using “Omics” and Integrated Multi-Omics Approaches to Guide Probiotic Selection to Mitigate Chytridiomycosis and Other Emerging Infectious Diseases
Frontiers in Microbiology (2016)
  • Eria A Rebollar, James Madison University
  • Rachael E Antwis, North-West University (South Africa)
  • Matthew H Becker, National Zoological Park
  • Lisa K Belden, Virginia Tech
  • Molly C Bletz, Technische Universität Braunschweig
  • Robert M Brucker, Harvard University
  • Xavier A Harrison, Zoological Society of London
  • Myra C Hughey, Virginia Tech
  • Jordan G Kueneman, University of Colorado, Boulder
  • Andrew H Loudon, University of British Columbia
  • Valerie McKenzie, University of Colorado, Boulder
  • Daniel Medina, Virginia Tech
  • Kevin P. C. Minbiole, Villanova University
  • Louise A Rollins-Smith, Vanderbilt University
  • Jenifer B Walke, Virginia Tech
  • Sophie Weiss, University of Colorado, Boulder
  • Douglas C Woodhams, University of Massachusetts Boston
  • Reid N Harris, James Madison University
Abstract
Emerging infectious diseases in wildlife are responsible for massive population declines. In amphibians, chytridiomycosis caused by Batrachochytrium dendrobatidis, Bd, has severely affected many amphibian populations and species around the world. One promising management strategy is probiotic bioaugmentation of antifungal bacteria on amphibian skin. In vivo experimental trials using bioaugmentation strategies have had mixed results, and therefore a more informed strategy is needed to select successful probiotic candidates. Metagenomic, transcriptomic, and metabolomic methods, colloquially called “omics,” are approaches that can better inform probiotic selection and optimize selection protocols. The integration of multiple omic data using bioinformatic and statistical tools and in silico models that link bacterial community structure with bacterial defensive function can allow the identification of species involved in pathogen inhibition. We recommend using 16S rRNA gene amplicon sequencing and methods such as indicator species analysis, the Kolmogorov–Smirnov Measure, and co-occurrence networks to identify bacteria that are associated with pathogen resistance in field surveys and experimental trials. In addition to 16S amplicon sequencing, we recommend approaches that give insight into symbiont function such as shotgun metagenomics, metatranscriptomics, or metabolomics to maximize the probability of finding effective probiotic candidates, which can then be isolated in culture and tested in persistence and clinical trials. An effective mitigation strategy to ameliorate chytridiomycosis and other emerging infectious diseases is necessary; the advancement of omic methods and the integration of multiple omic data provide a promising avenue toward conservation of imperiled species.
Disciplines
Publication Date
February, 2016
Citation Information
Eria A Rebollar, Rachael E Antwis, Matthew H Becker, Lisa K Belden, et al.. "Using “Omics” and Integrated Multi-Omics Approaches to Guide Probiotic Selection to Mitigate Chytridiomycosis and Other Emerging Infectious Diseases" Frontiers in Microbiology (2016)
Available at: http://works.bepress.com/jmu-cgems/5/