Improvement of identification methods for honeybee specific Lactic Acid Bacteria; future approaches.

Lamei S, Hu YO, Olofsson TC, Andersson AF, Forsgren E, Vásquez A

PLoS ONE 12 (3) e0174614 [2017-03-27; online 2017-03-27]

Honeybees face many parasites and pathogens and consequently rely on a diverse set of individual and group-level defenses to prevent disease. The crop microbiota of Apis mellifera, composed of 13 Lactic Acid Bacterial (LAB) species within the genera Lactobacillus and Bifidobacterium, form a beneficial symbiotic relationship with each other and the honeybee to protect their niche and their host. Possibly playing a vital role in honeybee health, it is important that these honeybee specific Lactic Acid Bacterial (hbs-LAB) symbionts can be correctly identified, isolated and cultured, to further investigate their health promoting properties. We have previously reported successful identification to the strain level by culture-dependent methods and we recently sequenced and annotated the genomes of the 13 hbs-LAB. However, the hitherto applied techniques are unfortunately very time consuming, expensive and not ideal when analyzing a vast quantity of samples. In addition, other researchers have constantly failed to identify the 13 hbs-LAB from honeybee samples by using inadequate media and/or molecular techniques based on 16S rRNA gene sequencing with insufficient discriminatory power. The aim of this study was to develop better and more suitable methods for the identification and cultivation of hbs-LAB. We compared currently used bacterial cultivation media and could for the first time demonstrate a significant variation in the hbs-LAB basic requirements for optimal growth. We also present a new bacterial identification approach based on amplicon sequencing of a region of the 16S rRNA gene using the Illumina platform and an error correction software that can be used to successfully differentiate and rapidly identify the 13 hbs-LAB to the strain level.

Bioinformatics Support for Computational Resources [Service]

NGI Stockholm (Genomics Applications) [Service]

NGI Stockholm (Genomics Production) [Service]

National Genomics Infrastructure [Service]

PubMed 28346815

DOI 10.1371/journal.pone.0174614

Crossref 10.1371/journal.pone.0174614

pii: PONE-D-16-47026
pmc: PMC5367889