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The effect of training set on the classification of honey bee gut microbiota using the Naive Bayesian Classifier.

ABSTRACT: BACKGROUND: Microbial ecologists now routinely utilize next-generation sequencing methods to assess microbial diversity in the environment. One tool heavily utilized by many groups is the Naïve Bayesian Classifier developed by the Ribosomal Database Project (RDP-NBC). However, the consistency and confidence of classifications provided by the RDP-NBC is dependent on the training set utilized. RESULTS: We explored the stability of classification of honey bee gut microbiota sequences by the RDP-NBC utilizing three publically available ribosomal RNA sequence databases as training sets: ARB-SILVA, Greengenes and RDP. We found that the inclusion of previously published, high-quality, full-length sequences from 16S rRNA clone libraries improved the precision in classification of novel bee-associated sequences. Specifically, by including bee-specific 16S rRNA gene sequences a larger fraction of sequences were classified at a higher confidence by the RDP-NBC (based on bootstrap scores). CONCLUSIONS: Results from the analysis of these bee-associated sequences have ramifications for other environments represented by few sequences in the public databases or few bacterial isolates. We conclude that for the exploration of relatively novel habitats, the inclusion of high-quality, full-length 16S rRNA gene sequences allows for a more confident taxonomic classification.

SUBMITTER: Newton IL

PROVIDER: S-EPMC3520854 | biostudies-literature | 2012

REPOSITORIES: biostudies-literature

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The effect of training set on the classification of honey bee gut microbiota using the Naïve Bayesian Classifier.

Newton Irene L G IL Roeselers Guus G

BMC microbiology 20120926

<h4>Background</h4>Microbial ecologists now routinely utilize next-generation sequencing methods to assess microbial diversity in the environment. One tool heavily utilized by many groups is the Naïve Bayesian Classifier developed by the Ribosomal Database Project (RDP-NBC). However, the consistency and confidence of classifications provided by the RDP-NBC is dependent on the training set utilized.<h4>Results</h4>We explored the stability of classification of honey bee gut microbiota sequences b ...[more]

PMID: 23013113

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Project description:Background Honey bee gut microbiota transmitted via social interactions are beneficial to the host health. Although the microbial community is relatively stable, individual variations and high strain-level diversity have been detected across honey bees. Although the bee gut microbiota structure is influenced by environmental factors, the heritability of the gut members and the contribution of the host genetics remains elusive. Considering bees within a colony are not readily genetically identical due to the polyandry of the queen, we hypothesize that the microbiota structure can be shaped by host genetics. Results We used shotgun metagenomics to simultaneously profile the microbiota and host genotypes of bees from hives of four different subspecies. Gut composition is more distant between genetically different bees at both phylotype- and “sequence-discrete population” levels. We then performed a successive passaging experiment within colonies of hybrid bees generated by artificial insemination, which revealed that the microbial composition dramatically shifts across batches of bees during the social transmission. Specifically, different strains from the phylotype of Snodgrassella alvi are preferentially selected by genetically varied hosts, and strains from different hosts show a remarkably biased distribution of single-nucleotide polymorphism in the Type IV pili loci. Genome-wide association analysis identified that the relative abundance of a cluster of Bifidobacterium strains is associated with the host glutamate receptor gene specifically expressed in the bee brain. Finally, mono-colonization of Bifidobacterium with a specific polysaccharide utilization locus impacts the alternative splicing of the gluR-B gene, which is associated with an increased GABA level in the brain. Conclusions Our results indicated that host genetics influence the bee gut composition and suggest a gut-brain connection implicated in the gut bacterial strain preference. Honey bees have been used extensively as a model organism for social behaviors, genetics, and the gut microbiome. Further identification of host genetic function as a shaping force of microbial structure will advance our understanding of the host-microbe interactions. Video abstract Supplementary Information The online version contains supplementary material available at 10.1186/s40168-021-01174-y.

Dataset Information

The effect of training set on the classification of honey bee gut microbiota using the Naive Bayesian Classifier.

Publications

The effect of training set on the classification of honey bee gut microbiota using the Naïve Bayesian Classifier.

Similar Datasets

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