Real-time volatilomics reveals microbiota and pathogen fingerprints in the honey bee
Fido, M.; Moriano-Gutierrez, S.; Lan, J.; Pirat, A.; Zufferey, L.; Cappio Barazzone, E.; Zenobi, R.; Engel, P.; Slack, E.
Show abstract
Understanding the complex relationship between gut microbiota and their hosts often relies on invasive sampling techniques. Honey bees provide a tractable model for host-microbe studies. Here we establish single-bee volatilomics using secondary electrospray ionization (SESI-HRMS) to examine volatile organic compounds released to the air around an individual live honey bee. Specifically, we focused on primary gut microbiota metabolites present in gnotobiotic bees. Our findings reveal distinct volatilome profiles in honey bees that depend on their gut bacterial colonization state. We cross-validated our findings using an established metabolomics technique, LC-HRMS, to compare and contrast the metabolites detectable with each mass spectrometry-based method. Finally, we assessed the ability of SESI-HRMS to detect colonization with the bee pathogen S. marcescens. By comparing the volatile signature of this bacterium grown in liquid culture with that of infected honey bee headspace, we identified overlapping compounds, including butane-2,3-diol, that were absent in uninfected bees. SESI-HRMS volatilomics, paired with LC-HRMS, therefore has potential to identify non-invasive biomarkers of bee microbiome composition and infection at the level of individual insects. These biomarkers represent practical targets for the development of simple, field-ready diagnostic tools for monitoring pollinator health.
Matching journals
The top 8 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Rapid Screening of COVID-19 Disease Directly from Clinical Nasopharyngeal Swabs using the MasSpec Pen Technology 94%
- UCL-MetIsoLib: A Public High-Resolution Tandem Mass Spectrometry Library for HILIC-Based Isomer-Resolved Profiling of Glycolysis, Central Carbon Metabolism, and Beyond in Urine, Plasma, Tissues, Cells, and Patient-Derived Organoids 93%
- MS-CleanR: A feature-filtering approach to improve annotation rate in untargeted LC-MS based metabolomics 93%
Similar papers in this journal
- Critical Assessment of MetaProteome Investigation 2 (CAMPI-2): Multi-laboratory assessment of sample processing methods to stabilize fecal microbiome for functional analysis 93%
- RapidAIM: A culture- and metaproteomics-based Rapid Assay of Individual Microbiome responses to drugs 91%
- Fetal programming by the parental microbiome of offspring behavior, and DNA methylation and gene expression within the hippocampus 91%
Similar papers in this journal
- Rapid detection of Staphylococcus aureus and Streptococcus pneumoniae by real-time analysis of volatile metabolites 93%
- Shotgun lipidomics and mass spectrometry imaging unveil diversity and dynamics in lipid composition in Gammarus fossarum 91%
- Spatial proteomics reveals subcellular reorganization in human keratinocytes exposed to UVA light 91%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.