Literature DB >> 33637887

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

Helena Wirta1, Nerea Abrego2,3, Kirsten Miller4,5, Tomas Roslin2,4, Eero Vesterinen4,6.   

Abstract

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. 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.

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Year:  2021        PMID: 33637887      PMCID: PMC7910293          DOI: 10.1038/s41598-021-84174-0

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  50 in total

1.  Automated DNA extraction from pollen in honey.

Authors:  Patrick Guertler; Adelina Eicheldinger; Paul Muschler; Ottmar Goerlich; Ulrich Busch
Journal:  Food Chem       Date:  2013-11-01       Impact factor: 7.514

2.  Error filtering, pair assembly and error correction for next-generation sequencing reads.

Authors:  Robert C Edgar; Henrik Flyvbjerg
Journal:  Bioinformatics       Date:  2015-07-02       Impact factor: 6.937

Review 3.  Microorganisms in honey.

Authors:  J A Snowdon; D O Cliver
Journal:  Int J Food Microbiol       Date:  1996-08       Impact factor: 5.277

4.  Two major medicinal honeys have different mechanisms of bactericidal activity.

Authors:  Paulus H S Kwakman; Anje A Te Velde; Leonie de Boer; Christina M J E Vandenbroucke-Grauls; Sebastian A J Zaat
Journal:  PLoS One       Date:  2011-03-04       Impact factor: 3.240

5.  Distinctive gut microbiota of honey bees assessed using deep sampling from individual worker bees.

Authors:  Nancy A Moran; Allison K Hansen; J Elijah Powell; Zakee L Sabree
Journal:  PLoS One       Date:  2012-04-27       Impact factor: 3.240

6.  Quality control and preprocessing of metagenomic datasets.

Authors:  Robert Schmieder; Robert Edwards
Journal:  Bioinformatics       Date:  2011-01-28       Impact factor: 6.937

7.  Microbial ecology of the hive and pollination landscape: bacterial associates from floral nectar, the alimentary tract and stored food of honey bees (Apis mellifera).

Authors:  Kirk E Anderson; Timothy H Sheehan; Brendon M Mott; Patrick Maes; Lucy Snyder; Melissa R Schwan; Alexander Walton; Beryl M Jones; Vanessa Corby-Harris
Journal:  PLoS One       Date:  2013-12-17       Impact factor: 3.240

8.  Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition.

Authors:  Rama Chandra Laha; Surajit De Mandal; Lalhmanghai Ralte; Laldinfeli Ralte; Nachimuthu Senthil Kumar; Guruswami Gurusubramanian; Ramalingam Satishkumar; Raja Mugasimangalam; Nagesh Aswathnarayana Kuravadi
Journal:  AMB Express       Date:  2017-06-24       Impact factor: 3.298

9.  PEAR: a fast and accurate Illumina Paired-End reAd mergeR.

Authors:  Jiajie Zhang; Kassian Kobert; Tomáš Flouri; Alexandros Stamatakis
Journal:  Bioinformatics       Date:  2013-10-18       Impact factor: 6.937

10.  Trimmomatic: a flexible trimmer for Illumina sequence data.

Authors:  Anthony M Bolger; Marc Lohse; Bjoern Usadel
Journal:  Bioinformatics       Date:  2014-04-01       Impact factor: 6.937

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  2 in total

1.  A detailed workflow to develop QIIME2-formatted reference databases for taxonomic analysis of DNA metabarcoding data.

Authors:  Benjamin Dubois; Frédéric Debode; Louis Hautier; Julie Hulin; Gilles San Martin; Alain Delvaux; Eric Janssen; Dominique Mingeot
Journal:  BMC Genom Data       Date:  2022-07-08

2.  Reconstructing the ecosystem context of a species: Honey-borne DNA reveals the roles of the honeybee.

Authors:  Helena Kristiina Wirta; Mohammad Bahram; Kirsten Miller; Tomas Roslin; Eero Vesterinen
Journal:  PLoS One       Date:  2022-07-13       Impact factor: 3.752

  2 in total

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