DNA traces the origin of honey by identifying plants, bacteria and fungi

The regional origin of a food product commonly affects its value. To this, DNA-based identification of tissue remains could offer fine resolution. For honey, this would allow the usage of not only pollen but all plant tissue, and also that of microbes in the product, for discerning the origin. Here we examined how plant, bacterial and fungal taxa identified by DNA metabarcoding and metagenomics differentiate between honey samples from three neighbouring countries. To establish how the taxonomic contents of honey reflect the country of origin, we used joint species distribution modelling. At the lowest taxonomic level by metabarcoding, with operational taxonomic units, the country of origin explained the majority of variation in the data (70–79%), with plant and fungal gene regions providing the clearest distinction between countries.figure2

Figure: Nonmetric multidimensional scaling (NMDS) plots for plant, bacterial and fungal OTU community similarities among samples originating from the three different countries. The ellipses confine 75% of the data points. Stress values for the different gene region analyses are given in Supplementary Table S4. The panels show the data from different gene regions: plants: (a) ITS2, (b) rbcLa, (c) trnL, bacteria: (d) 16Sa, (e) 16Sb, and fungi: (f) ITS. Samples from Estonia (ES) are shown in gray, from Finland (FI) in blue and from Sweden (SE) in light orange.

At the taxonomic level of genera, plants provided the most separation between countries with both metabarcoding and metagenomics. The DNA-based methods distinguish the countries more than the morphological pollen identification and the removal of pollen has only a minor effect on taxonomic recovery by DNA. As we find good resolution among honeys from regions with similar biota, DNA-based methods hold great promise for resolving honey origins among more different regions.

 

Wirta, H., Abrego, N., Miller, K. et al. DNA traces the origin of honey by identifying plants, bacteria and fungi. Sci Rep 11, 4798 (2021). https://doi.org/10.1038/s41598-021-84174-0

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