Data and code from: Pervasive and dynamic gut dysbiosis in wild bumble bees
Data files
Sep 03, 2026 version files 8.93 MB
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3.2kmradius_S2_NDVI_2020-01-01_2025-01-01.csv
5.22 KB
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advsearch_bacdive_2025-05-14_ALL_TOP_GENERA_filt_empty_rows.csv
92.54 KB
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Combined_VOMITS_16S_data_analysis_Rcode_Resubmission.R
92.46 KB
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Combined_VOMITS_metadata_121925.txt
38.72 KB
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MAG_ID_tax_type.csv
296 B
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pathofact_intermed.csv
98.18 KB
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PRISM_Daily_1981_2010.csv
535.77 KB
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PRISM_Daily_2021_2024.csv
86.55 KB
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README.md
5.78 KB
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seqtab_wTax_mctoolsr.txt
7.97 MB
Abstract
Stressors can shift the microbiome into an altered, “dysbiotic” state that reduces host fitness. While well-studied in humans and laboratory models, the prevalence, predictability, and drivers of dysbiosis in wildlife remain unclear. We addressed these questions by monitoring gut microbiomes of wild bumble bees in Southern California, focusing on Bombus vosnesenskii, a major pollinator in western North America. More than a third of all B. vosnesenskii bees exhibited dysbiosis, when defined as a > 50 % replacement of host-specialized core bacteria by environmental bacteria. This replacement covaried with increased alpha and beta diversity, an enrichment of oxygen-tolerant taxa, and pathogen infection—all common hallmarks of dysbiosis in other hosts. Other co-occurring Bombus, including two at-risk species, also exhibited dysbiosis. In B. vosnesenskii, dysbiosis was not correlated with certain stressors, such as heat or resource limitation, although other, unmeasured stressors cannot be ruled out. We next examined how dysbiosis varied over two years of sampling. In the first year, dysbiosis emerged only late in the season, when bumble bee colonies normally reproduce and then senesce. Two years later, following an intervening year with historic rainfall and elevated resources, dysbiosis was entrenched throughout the season. These findings show that dysbiosis is both pervasive and highly dynamic in wild bumble bees. The dynamics coincide with host life cycle transitions and environmental change, but the underlying causality remains uncertain. Given that dysbiosis may harm host health, we argue that long-term microbiome monitoring should be considered both for bumble bees and for other wildlife of conservation concern.
Dataset DOI: 10.5061/dryad.1jwstqkb8
Description of the data and file structure
Bumble bees were collected in the field and subject to microsatellite genotyping, 16S rRNA gene sequencing, quantitative PCR, and shotgun metagenomics (on a subset of 16 individuals). Additionally, food plant identity, pollen content in the gut, body size (wing cell length), and wing wear were recorded. See the Materials and Methods section of the paper for more detail.
Files and variables
File: 3.2kmradius_S2_NDVI_2020-01-01_2025-01-01.csv
Description: NDVI values (from satellite imagery) for a 3.2 km-radius area around the field site where bees were collected.
Variables
- date: Date
- ndvi: Normalized Difference Vegetation Index
File: advsearch_bacdive_2025-05-14_ALL_TOP_GENERA_filt_empty_rows.csv
Description: Records in the BacDive database for the oxygen tolerance category of species of cultured bacteria belonging to genera that were abundant in wild bumble bees.
Variables
- genus: Genus of bacterium
- species: Species of bacterium
- oxygen_tolerance: Oxygen tolerance category as defined by BacDive
File: MAG_ID_tax_type.csv
Description: Summary information for bacterial metagenome-assembled genomes (MAGs).
Variables
- MAG: Unique identifier to distinguish MAGs
- MAG_genus: Genus of the MAG
- MAG_type: Whether a given genus is classified as Core or Environmental for the purposes of data analysis (see paper for information on this classification).
File: Combined_VOMITS_16S_data_analysis_Rcode_Resubmission.R
Description: R code for data analysis and visualization.
File: Combined_VOMITS_metadata_121925.txt
Description: Information about bee samples collected in this study. "NA" cells refer to one of two types of missing data. In the case of rows corresponding to negative or positive control samples (where variable "Sample_Type" is something other than "Gut"), "NA" is inserted for columns that are not applicable because they only pertain to bee samples. In the case of rows corresponding to bee gut samples ("Sample_Type" = "Gut"), "NA" is inserted when the sample lacks data for a particular column. For example, genotyping failed for some bees and so for those, the variable "Colony" = "NA". Wing and pollen grain data were not recorded for Bombus species besides B. vosnesenskii, so those samples have "NA" values for related variables: "WingCellSize1_mm", "WingCellSize2_mm", "WingWearScore1", "WingWearScore2", "PollenGrainsPerGut". The time of collection ("Time") and/or plant identity ("PlantCollectedFrom" and "PlantFamily" variables) is also missing for a couple samples.
Variables
- LibraryID: unique identifier for each sequence library
- SampleID: unique identifier for each individual bee sample
- Year: Year
- Month: Month
- Day: Day
- Time: Time of day
- CollectionDate: Date in Year-Month-Day format
- Sample_Type: type of sample
- Colony: Unique colony identifier, obtained from microsatellite analysis
- Caste: Equivalent to sex; whether bee individuals were male or female (within female, workers or gynes)
- BombusSpecies: Bumble bee species to which sample belongs
- PlantCollectedFrom: The plant genus from which the bee was collected while foraging
- PlantFamily: Family taxonomic classification of "PlantCollectedFrom" variable
- WingCellSize1_mm: Length of the wing cell of the left wing in mm
- WingCellSize2_mm: Length of the wing cell of the right wing in mm
- WingWearScore1: Degree of wing wear for left wing
- WingWearScore2: Degree of wing wear for right wing
- PollenGrainsPerGut: Number of pollen grains counted in gut homogenate
- qPCRrun: Unique identifier for each qPCR assay
- qPCRMeanConc: The raw copy number value obtained from qPCR
- GutNotes: qualitative notes about gut appearance, recorded during dissection
- BeeNotes: qualitative notes about bee appearance/behavior, recorded during field collection
File: PRISM_Daily_2021_2024.csv
Description: Weather (temperature and precipitation data) for the field site, obtained from Google Earth Engine, for the duration of the study period
Variables
- date: Date
- day: Day
- tmax: Max daily temperature
- tmean: Mean daily temperature
- prcp: Precipitation in mm
File: PRISM_Daily_1981_2010.csv
Description: Weather (temperature and precipitation data) for the field site, obtained from Google Earth Engine, for a 30-year historical period
Variables
- date: Date
- day: Day
- tmax: Max daily temperature
- tmean: Mean daily temperature
- prcp: Precipitation in mm
File: pathofact_intermed.csv
Description: All genes identified by PathoFact for each MAG, and their respective category (antimicrobial resistance, toxin, or virulence factor).
Variables
- MAG: Unique MAG identifier (see MAG_ID_tax_type.csv file)
- GeneType: category of gene from PathoFact analysis
File: seqtab_wTax_mctoolsr.txt
Description: The amplicon sequence variant table (also known as an OTU table) for the 16S rRNA gene sequence data. This table is formatted for analysis with the mctoolsr package.
Variables
- ASV_ID: unique identifier code for each amplicon sequence variant
- taxonomy: taxonomic classification derived from the SILVA database for each ASV
- All other columns have the library ID as the header (see "LibraryID" variable in the "Combined_VOMITS_metadata_121925.txt" file) and numeric values represent sequence counts for each ASV
Code/software
R version 4.5.0 was used to run the code (available in the file "Combined_VOMITS_16S_data_analysis_Rcode_Resubmission.R").
