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

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Abstract

Identification of floral samples present in honey is important in order to determine the medicinal value, enhance the production of honey as well as to conserve the honey bees. Traditional approaches for studying pollen samples are based on microscopic observation which is laborious, time intensive and requires specialized palynological knowledge. Present study compares two composite honey metagenome collected from 20 samples in Mizoram, Northeast India using three gene loci- rbcL, matK and ITS2 that was sequenced using a next-generation sequencing (NGS) platform (Illumina Miseq). Furthermore, a classical palynology study for all 20 samples was carried out to evaluate the NGS approach. NGS based approach and pollen microscopic studies were able to detect the most abundant floral components of honey. We investigated the plants that were frequently used by honey bees by examining the results obtained from both the techniques. Microscopic examination of pollens detected plants with a broad taxonomic range covering 26 families. NGS based multigene approach revealed diverse plant species, which was higher than in any other previously reported techniques using a single locus. Frequently found herbaceous species were from the family Poaceae, Myrtaceae, Fabaceae and Asteraceae. The future NGS based approach using multi-loci target, with the help of an improved and robust plant database, can be a potential replacement technique for tedious microscopic studies to identify the polleniferous plants.

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Laha, R. C., De Mandal, S., Ralte, L., Ralte, L., Kumar, N. S., Gurusubramanian, G., … Kuravadi, N. A. (2017). Meta-barcoding in combination with palynological inference is a potent diagnostic marker for honey floral composition. AMB Express, 7(1). https://doi.org/10.1186/s13568-017-0429-7

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