Shifts in the Midgut/Pyloric Microbiota Composition within a Honey Bee Apiary throughout a Season

Abstract

Honey bees (Apis mellifera) are prominent crop pollinators and are, thus, important for effective food production. The honey bee gut microbiota is mainly host specific, with only a few species being shared with other insects. It currently remains unclear how environmental/dietary conditions affect the microbiota within a honey bee population over time. Therefore, the aim of the present study was to characterize the composition of the midgut/pyloric microbiota of a honey bee apiary throughout a season. The rationale for investigating the midgut/pyloric microbiota is its dynamic nature. Monthly sampling of a demographic homogenous population of bees was performed between May and October, with concordant recording of the honey bee diet. Mixed Sanger-and Illumina 16S rRNA gene sequencing in combination with a quantitative PCR analysis were used to determine the bacterial composition. A marked increase in α-diversity was detected between May and June. Furthermore, we found that four distinct phylotypes belonging to the Proteobacteria dominated the microbiota, and these displayed major shifts throughout the season. Gilliamella apicola dominated the composition early on, and Snodgrassella alvi began to dominate when the other bacteria declined to an absolute low in October. In vitro co-culturing revealed that G. apicola suppressed S. alvi. No shift was detected in the composition of the microbiota under stable environment/dietary conditions between November and February. Therefore, environmental/dietary changes may trigger the shifts observed in the honey bee midgut/pyloric microbiota throughout a season.

Honey bee gut microbial communities are robust to the fungicide Pristine® consumed in pollen

“…Diversity was not impacted by the treatment in either experiment. There were notable differences between experiments that might have been due to differences in pollen consumption between high and low doses of Pristine® (experiment 2) (DeGrandi-Hoffman et al 2015) or environmental and dietary factors that can affect the gut microbiome in honey bees and other organisms (Ludvigsen et al 2015).…”

“…We fed the bees polyfloral mixes of pollen that were collected during the year when the experiment was conducted, so the species composition probably differed. There is evidence that bee bread communities (Anderson et al 2014) and midgut/pyloric (Ludvigsen et al 2015) bacterial communities fluctuate with pollen source and season. Gut bacterial communities also can differ among colonies (Hroncova et al 2015).…”

“…This diversity can change with age (Anderson et al 2015), season (Hroncova et al 2015;Ludvigsen et al 2015), and nutrition (Ludvigsen et al 2015;Saraiva et al 2015). In this study, we used high-throughput sequencing to examine the effects of feeding pollen with added Pristine® on the composition and diversity of microbial communities in the gut of nurse bees (i.e., worker bees that care for brood).…”

Microorganisms in Honey

“…New methodologies have made it possible to access information about the differences in the profile of this microbiota in different apiculture sources [118][119][120][121], species [53,122] and genetic diversity [116] of honeybees, development stages [53,68,117,[122][123][124][125][126], nutrition [116,127], location inside the gut [49,53,68] and digestive system [120], ontogenetic stage and geographic location [118,122,125], environmental conditions [128], health control [129], and individual [116,125].…”

“…This access has been carried out mainly by sequencing the coding region of the 16S subunit of the bacterial ribosome [53,121,130], both from genomic DNA from microorganisms growing on selective media as Man-Rogosa-Sharpe agar, Sabouraud dextrose agar, and Candida agar [117,120,131,132], such as process-independent culture as specific PCR [68], denaturing gradient gel electrophoresis [124,125], mixed and deep 16S sequencing [49,128], pyrosequencing [53,116,121], and clone library [115,118,120,122]. While culturedependent methods are ideal for quantification of microorganisms and phenotypic testing, culture-independent methods generally have greater coverage in relation to the amount of different species accessed and are ideal for fingerprinting studies, and the identification of these species may be performed by real-time PCR analysis [49,68,125,128].…”