4.7 Article

Bee foraging preferences, microbiota and pathogens revealed by direct shotgun metagenomics of honey

期刊

MOLECULAR ECOLOGY RESOURCES
卷 22, 期 7, 页码 2506-2523

出版社

WILEY
DOI: 10.1111/1755-0998.13626

关键词

biomonitoring; gut microbiome; honeybee; plant foraging; shotgun sequencing; Varroa

资金

  1. Marie Skodowska-Curie Individual Fellowship [798082]
  2. Fondation Sante research grant
  3. Greek Ministry of Rural Development and Food grant (programme for production and marketing of beekeeping)
  4. Operational Program Competitiveness, Entrepreneurship and Innovation, NSRF 2014-2020 [MIS 5002562]
  5. European Union (European Regional Development Fund)
  6. Marie Curie Actions (MSCA) [798082] Funding Source: Marie Curie Actions (MSCA)

向作者/读者索取更多资源

Honeybees play a crucial role in providing essential ecosystem services, but they are facing pressures from human activities and the environment. Honey, as a valuable biomonitoring tool, can be used to assess the ecological niche of honeybees. This study compared different classifiers and optimized DNA extraction methods to explore the relationships between honeybees and other species, as well as the impact of honey on bee microbiota. The results demonstrate that this approach can comprehensively describe honeybee ecological niches and has the potential to assess bee health on a large scale.
Honeybees (Apis mellifera) continue to succumb to human and environmental pressures despite their crucial role in providing essential ecosystem services. Owing to their foraging and honey production activities, honeybees form complex relationships with species across all domains, such as plants, viruses, bacteria and other hive pests, making honey a valuable biomonitoring tool for assessing their ecological niche. Thus, the application of honey shotgun metagenomics (SM) has paved the way for a detailed description of the species honeybees interact with. Nevertheless, SM bioinformatics tools and DNA extraction methods rely on resources not necessarily optimized for honey. In this study, we compared five widely used taxonomic classifiers using simulated species communities commonly found in honey. We found that Kraken 2 with a threshold of 0.5 performs best in assessing species distribution. We also optimized a simple NaOH-based honey DNA extraction methodology (Direct-SM), which profiled species seasonal variability similarly to an established column-based DNA extraction approach (SM). Both approaches produce results consistent with melissopalinology analysis describing the botanical landscape surrounding the apiary. Interestingly, we detected a strong stability of the bacteria constituting the core and noncore gut microbiome across seasons, pointing to the potential utility of honey for noninvasive assessment of bee microbiota. Finally, the Direct-SM approach to detect Varroa correlates well with the biomonitoring of mite infestation observed in hives. These observations suggest that Direct-SM methodology has the potential to comprehensively describe honeybee ecological niches and can be tested as a building block for large-scale studies to assess bee health in the field.

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