Bombus Microbiome Diversity and Pathogen Prevelence in the State of Maine


Meeting Abstract

P2-197  Saturday, Jan. 5 15:30 – 17:30  Bombus Microbiome Diversity and Pathogen Prevelence in the State of Maine YOUNG, MG*; MCMAHON, TW; ANGELINI, DR; Colby College; Colby College; Colby College mgyoun21@colby.edu

Bumblebees are critical, native pollinators, contributing to both local ecosystems and agriculture throughout North America. Similar to the honeybee, many Bombus species have faced decline over recent years due to multifaceted causes that work in conjunction to overwhelm the natural defenses of bees (Goulson et al. 2008; 2015). Currently, Maine’s endemic populations are threatened by the use of agrochemicals, climate change, and various diseases and parasites. Through ecological genomic research, we have investigated both the range and diversity of the Maine bumblebee species and looked for correlations between microbiome composition and anthropogenic and environmental factors. This has been accomplished through 16s and 18s sequencing of field samples collected across the diverse biomes of the state during the summers of 2017 and 2018. Analysis of species distribution suggests that many of the coastal islands act as refuges for threatened bees due to their geographic isolation from the mainland. With our data, we have assessed the prevalence of known pathogens, such as Crithidia, Nosema, and Apicystis. Previous research indicates that bumblebees forage within a maximum range of 5 km (Goulson 2010; Stubbs & Drummond 2001; Dibble et al. 2017). We tested the hypothesis that islands outside of this daily foraging range are geographically isolated from the spread of both pathogenic and benign microbes by comparing island and mainland samples with differential abundance analysis of observed OTUs and the use of various diversity metrics. Taking into account both the microbiotic and metadata profile collected on each sample, we used statistical analysis to further examine for predictors of microbiome health and other correlations within our data.

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