Using omics and integrated multi-omics approaches to guide probiotic selection to mitigate chytridiomycosis and other emerging infectious diseases
| Autor: | Molly C. Bletz, Jenifer B. Walke, Daniel Medina, Lisa K. Belden, Reid N. Harris, Louise A. Rollins-Smith, Valerie J. McKenzie, Myra C. Hughey, Eria A. Rebollar, Robert M. Brucker, Rachael E. Antwis, Xavier A. Harrison, Jordan G. Kueneman, Andrew H. Loudon, Kevin P. C. Minbiole, Matthew H. Becker, Sophie Weiss, Douglas C. Woodhams |
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| Přispěvatelé: | Biological Sciences |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
0301 basic medicine
Microbiology (medical) In silico 030106 microbiology Population lcsh:QR1-502 Review Biology Microbiology lcsh:Microbiology Amphibians transcriptomics 03 medical and health sciences Metabolomics Chytridiomycosis education Selection (genetic algorithm) education.field_of_study metatranscriptomics business.industry Emerging diseases Probiotics Omics 3. Good health Biotechnology 030104 developmental biology Metagenomics Identification (biology) business |
| Zdroj: | Frontiers in Microbiology, Vol 7 (2016) Frontiers in Microbiology |
| ISSN: | 1664-302X |
| DOI: | 10.3389/fmicb.2016.00068/full |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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