A review on recent taxonomic updates of gut bacteria associated with social bees, with a curated genomic reference database.
Chengfeng YangJiawei HuQinzhi SuZijing ZhangYating DuJieni WangHuihui SunBenfeng HanJunbo TangLizhen GuoHu LiWanzhi CaiHao ZhengXin ZhouXue ZhangPublished in: Insect science (2024)
Honeybees and bumblebees play a crucial role as essential pollinators. The special gut microbiome of social bees is a key factor in determining the overall fitness and health of the host. Although bees harbor relatively simple microbial communities at the genus level, recent studies have unveiled significant genetic divergence and variations in gene content within each bacterial genus. However, a comprehensive and refined genomics-based taxonomic database specific to social bee gut microbiomes remains lacking. Here, we first provided an overview of the current knowledge on the distribution and function of social bee gut bacteria, as well as the factors that influence the gut population dynamics. We then consolidated all available genomes of the gut bacteria of social bees and refined the species-level taxonomy, by constructing a maximum-likelihood core genome phylogeny and calculating genome-wide pairwise average nucleotide identity. On the basis of the refined species taxonomy, we constructed a curated genomic reference database, named the bee gut microbe genome sequence database (BGM-GDb). To evaluate the species-profiling performance of the curated BGM-GDb, we retrieved a series of bee gut metagenomic data and inferred the species-level composition using metagenomic intra-species diversity analysis system (MIDAS), and then compared the results with those obtained from a prebuilt MIDAS database. We found that compared with the default database, the BGM-GDb excelled in aligned read counts and bacterial richness. Overall, this high-resolution and precise genomic reference database will facilitate research in understanding the gut community structure of social bees.
Keyphrases
- healthcare
- genome wide
- mental health
- adverse drug
- copy number
- high resolution
- dna methylation
- public health
- emergency department
- physical activity
- single cell
- deep learning
- machine learning
- body composition
- risk assessment
- big data
- wastewater treatment
- functional connectivity
- climate change
- mass spectrometry
- amino acid
- data analysis
- tandem mass spectrometry