Top library matches to the NIST 2017 MS library are reported for features with a minimum cosine similarity of 0.7. All annotated features were manually curated. Where possible, feature RT and mass spectrum were compared with an in-house library of reference metabolites that were prepared in the same manner and analyzed on the same instrument
"],"repository":["MetaboLights"],"study_status":["Public"],"ptm_modification":[""],"instrument_platform":["Gas Chromatography MS -"],"chromatography_protocol":["Samples were analyzed on an Agilent 8890-5977B GC-MSD equipped with a Pal3 autosampler that injected 1 μl onto a VF-5MS (30 m x 0.25 mm x 0.25 mm) column. The samples were injected with a split ratio of 15:1, helium flow rate of 1 ml/min and inlet temperature of 280 °C. The temperature was held for 2 min at 125 °C, raised at 3 °C/min to 150 °C, 5 °C/min to 225 °C, 15 °C/min to 310 °C and held for 3.3 min.
"],"publication":["A defined community of core gut microbiota members promotes cognitive performance in honey bees. 10.1073/ps.2608600123. PMID:42160337"],"submitter_affiliation":["University of Lausanne"],"submitter_name":["Andrew Quinn"],"organism_part":["Hindgut","solvent"],"technology_type":["mass spectrometry assay"],"disease":[""],"extraction_protocol":["Extraction was performed after addition of internal standards (ISTDs) for 2 h with a 1:1 methanol:acetonitrile solvent at -20 °C. Samples were again centrifuged, and the supernatant vacuum evaporated at ambient temperature. Metabolites were derivatized first with 20 mg/ml of methoxyamine hydrochloride in pyridine at 33 °C for 1.5 h, followed by sialylation with MSTFA for 2 h at 45 °C. Samples were kept in a queue for analysis at 15 °C for up to 24 h post derivatization
"],"organism":["blank","Apis mellifera carnica"],"full_dataset_link":["https://www.ebi.ac.uk/metabolights/MTBLS13943"],"author":["Andrew Quinn. University of Lausanne. Batiment Biophore, Lausanne, 1015, Switzerland. andrew.quinn@unil.ch.","Amelie Cabirol. Université Toulouse III - Paul Sabatier. amelie.cabirol@utoulouse.fr.","Philipp Engel. University of Lausanne. philipp.engel@unil.ch."],"data_transformation_protocol":["Data analysis of untargeted features was performed with derived mzml files (converted with msConvert in ProteoWizard) using MZmine 4.3 with the following Modules: Mass detection, Chromatogram builder, Local minimum feature resolver, GC-EI spectral deconvolution, GC aligner, Feature list row filter, Duplicate peak filter, and NIST MS Search. Analyte abundances of targeted metabolites previously acquired as pure analytical standards were calculated using the MassHunter Quantitative Analysis software (Agilent) with ions predefined in the SIM MS settings.
Combined peak areas from both targeted and untargeted analysis were analyzed with R Studio 2022.02.0. When identical metabolites were found in the scan and SIM modes, the data acquired in SIM mode was kept. Raw metabolite abundances were normalized to the internal standards. Low-quality samples and samples with an ISTD response < or > two SD from the batch mean were removed from the datasets. To assess differences in gut metabolic profiles across treatment groups, metabolite concentration data were standardized using z-score scaling and a permutational multivariate analysis of variance (PERMANOVA; “adonis2” function from the vegan package) using Euclidean distance and 999 permutations was performed. When a significant effect was detected, pairwise comparisons between treatment groups were performed (“pairwise.adonis”, pairwiseAdonis). P-values were adjusted for multiple comparisons using the Benjamini-Hochberg (BH) method. To quantify changes in metabolite abundance between treatment groups, we calculated the log2 fold-change values for each metabolite. Statistical significance of differences in normalized metabolite levels between groups was assessed using a Wilcoxon rank-sum test and corrected for multiple testing using the Benjamini-Hochberg method.
"],"study_factor":["Hive","Organism part","Colonization"],"submitter_email":["andrew.quinn@unil.ch"],"sample_collection_protocol":["Microbiota-deprived honey bees were obtained from 7 colonies of Apis mellifera carnica maintained on the campus of the University of Lausanne during the spring and summer seasons of 2023. Briefly, dark-eyed pupae were gently extracted from their wax cell and placed into sterilized plastic boxes in an incubator (35°C, 75% humidity) for three days. A sterility check was performed for each box, by culturing one bee gut homogenate (in 1mL sterile 1X PBS) on three growth media (Supplementary Table 1). Any box showing signs of contamination 24 hours later was discarded. On day 3 post pupae extraction, hatched adult bees were randomly assigned to one of the following gnotobiotic groups: microbiota-deprived (MD), colonized by the defined bacterial community BeeCom, or by the BeeCom depleted from single members. Each experimental replicate used pupae from a single hive. Bacterial strains used for the colonization were obtained from existing glycerol stocks stored at -80°C. Colonization stocks were prepared by culturing each strain under its optimal culturing conditions, restreaking once, washing in 1X PBS, diluting to OD600 = 1 and storing in 20% glycerol at -80°C until further use. To mimic intra-genus diversity, we included several strains per genus, one per species. Colonized bees were obtained by feeding MD bees 5µL of a solution containing the colonization stocks diluted ten times in a 1:1 mixture of 1X PBS and 50% sucrose solution (w/v). The colonization stock used for the MD group consisted of 20% glycerol in 1X PBS. The BeeCom and drop-out communities contained all strains in equal proportions.
Colonized bees were housed in cages of 10-19 individuals depending on the mortality encountered during the generation of MD bees. For a given replicate, all treatment groups contained the same number of individuals. The experiment weas9 times. Bees had unlimited access to 50% sucrose solution (w/v) and to sterilized pollen. Cages were kept at 30°C with 70% humidity for seven days. On the last evening, bees were transferred to clean cages for a 12-hours overnight fasting and behavioral analysis.
Subsequently, bees were anesthetized with CO2 gas and placed on ice. Hindguts were removed with sterilized tweezers and immediately homogenized with 750µL of deionized water, zirconia beads (0.1 mm dia. Zirconia/Silica beads; Carl Roth) and glass beads in a Fast- Prep24 5G homogenizer (MP Biomedicals) at 6 m/s for 45 s. Homogenized bee gut extracts were centrifuged at 4000 g-1 for 20 min at 4 °C and frozen at -70 °C until extraction.
"],"omics_type":["Metabolomics"],"study_design":["Agilent 5977B GC/MSD","blank","gas chromatography-mass spectrometry","Hindgut","untargeted analysis","solvent blank","Brain-Gut Axis","untargeted metabolite profiling","experimental sample","Apis mellifera","solvent","learning and/or memory behavior phenotype","Apis mellifera carnica","Agilent 8890 GC"],"curator_keywords":["Agilent 5977B GC/MSD","blank","gas chromatography-mass spectrometry","Hindgut","untargeted analysis","solvent blank","Brain-Gut Axis","untargeted metabolite profiling","experimental sample","Apis mellifera","solvent","learning and/or memory behavior phenotype","Agilent 8890 GC","Apis mellifera carnica"],"mass_spectrometry_protocol":["The Agilent 5977B MSD was run in SIM/Scan mode with ~3 ions selected for each targeted metabolite and a scan from 50-600 Da. Source and quadrupole temperatures were set at 230 C and 150 C respectively. EI source voltage was set at 70 eV.
[SIM Parameters]
Group 1 Group ID : ISTDs
Resolution : 1
Group Start Time : 2.4
Number of Ions : 5
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 117.00,20 ) ( 144.10,20 ) ( 158.10,20 )
( 159.10,15 ) ( 191.00,15 )
Group 2 Group ID : 4-Aminobutyrate
Resolution : 1
Group Start Time : 7
Number of Ions : 2
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 174.10,50 ) ( 304.10,25 )
Group 3 Group ID : Anth_Glu_Tart
Resolution : 1
Group Start Time : 13
Number of Ions : 6
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 246.10,25 ) ( 266.10,25 ) ( 281.00,15 )
( 292.10,25 ) ( 348.10,15 ) ( 423.10,15 )
Group 4 Group ID : 3-OH_Anth_2_Vanil_Glnl
Resolution : 1
Group Start Time : 16.5
Number of Ions : 6
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 156.00,20 ) ( 164.00,15 ) ( 192.10,50 )
( 245.10,15 ) ( 267.00,20 ) ( 312.00,15 )
Group 5 Group ID : 3-Hydroxyanthranilic Acid_3
Resolution : 1
Group Start Time : 18
Number of Ions : 3
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 192.10,15 ) ( 354.10,50 ) ( 355.10,15 )
Group 6 Group ID : 3-Indoleacetic acid_1
Resolution : 1
Group Start Time : 20
Number of Ions : 3
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 130.00,50 ) ( 232.10,15 ) ( 247.10,15 )
Group 7 Group ID : 3-Indoleacetic acid_2
Resolution : 1
Group Start Time : 21
Number of Ions : 3
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 202.10,50 ) ( 203.10,15 ) ( 319.10,15 )
Group 8 Group ID : Kynurenate_3IPA
Resolution : 1
Group Start Time : 23
Number of Ions : 4
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 202.10,50 ) ( 231.10,15 ) ( 304.10,20 )
( 318.10,50 )
Group 9 Group ID : 3IA_Kynurenine2
Resolution : 1
Group Start Time : 24
Number of Ions : 5
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 130.00,50 ) ( 192.10,50 ) ( 202.10,50 )
( 203.10,15 ) ( 352.10,15 )
Group 10 Group ID : Kynurenine_3-Tryptophan_1
Resolution : 1
Group Start Time : 25.55
Number of Ions : 6
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 130.00,15 ) ( 192.10,50 ) ( 202.10,50 )
( 218.10,50 ) ( 347.10,15 ) ( 424.20,15 )
Group 11 Group ID : Tryptamine-Tryptophan_3
Resolution : 1
Group Start Time : 25.92
Number of Ions : 6
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 174.10,50 ) ( 175.10,15 ) ( 202.10,50 )
( 289.10,15 ) ( 291.10,15 ) ( 361.20,15 )
Group 12 Group ID : 3-Hydroxykynurenine
Resolution : 1
Group Start Time : 27
Number of Ions : 3
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 208.00,25 ) ( 323.10,15 ) ( 440.20,25 )
Group 13 Group ID : Indoleacrylic acid
Resolution : 1
Group Start Time : 27.9
Number of Ions : 3
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 242.10,15 ) ( 316.10,15 ) ( 331.10,50 )
Group 14 Group ID : 5-Hydroxytryptophan
Resolution : 1
Group Start Time : 28.1
Number of Ions : 7
Ions
Dwell In Group :( Mass, Dwell) ( Mass, Dwell) ( Mass, Dwell)
( 174.10,50 ) ( 175.10,15 ) ( 218.10,50 )
( 219.10,15 ) ( 290.10,50 ) ( 291.10,15 )
( 436.20,15 )
Gut microbiota across animals have been shown to influence host cognition and behavior. However, it remains unclear whether these cognitive effects are driven by specific bacterial species or arise from community-level interactions. Here, we leveraged the honey bee (Apis mellifera) as a model system, which harbors a simple and well-characterized gut microbiota that is experimentally tractable and has been previously shown to impact host cognition. We established a defined bacterial community - composed of core members of the honey bee gut microbiota. Gnotobiotic bee experiments with the full community, communities missing individual members, or individual members showed that only the full community enhanced honey bees’ performances in odour discrimination learning and short-term memory compared to microbiota-deprived bees. Metabolomic analyses identified several metabolites associated with learning success that mapped to pathways modulated by microbial colonization, including tryptophan metabolism, nucleoside metabolism, and lysine degradation. However, many of these metabolites were not altered by removing individual members from the community. This suggest that microbiota-mediated improvements in cognition are emergent properties of the community as a whole, rather than the result of individual metabolites or specific bacterial taxa acting alone. Our findings support a systems-level view of the microbiome, suggesting that understanding and manipulating host development, particularly in relation to brain function, should prioritize microbial community function (e.g., metabolic pathways) over taxonomic composition alone.
","dates":{"publication":"2026-05-21","submission":"2026-02-27"},"accession":"MTBLS13943","cross_references":{"pubmed":["42160337"]}}