DOI: 10.5061/dryad.v6wwpzh2r
title: Seasonal dynamics in the mammalian microbiome between disparate environments

description: Host-associated bacterial microbiomes can facilitate host acclimation to
 seasonal environmental change and are hypothesized to help hosts cope with
 recent anthropogenic environmental perturbations (e.g., landscape
 modification). However, it is unclear how recurrent and recent forms of
 environmental change interact to shape variation in the microbiome. The
 majority of wildlife microbiome research occurs within a single seasonal
 context. Meanwhile, the few studies of seasonal variation in the
 microbiome often restrict focus to a single environmental context. By
 sampling urban and exurban eastern grey squirrel populations in the
 spring, summer, autumn, and winter, we explored whether seasonal rhythms
 in the grey squirrel gut microbiome differed across environments using a
 16S amplicon sequencing approach. Differences in the microbiome between
 urban and exurban squirrels persisted across most of the year, which we
 hypothesize is linked to anthropogenic food consumption; but we also
 observed similarities in the urban and exurban grey squirrel microbiome
 during the autumn, which we attribute to engrained seed caching instincts
 in preparation for the winter. Host behaviour and diet selection may
 therefore be capable of maintaining similarities in microbiome structure
 between disparate environments. However, the depletion of an obligate host
 mucin glycan specialist (Akkermansia) during the winter in both urban and
 exurban squirrels was among the strongest differential abundance patterns
 we observed. In summary, urban grey squirrels showed different seasonal
 patterns in their microbiome than squirrels from exurban forests, however,
 in some instances host behaviour and physiological responses might be
 capable of maintaining similar microbiome responses across
 seasons. 
description: <em>Sampling Protocol</em> Adult
 eastern grey squirrels were trapped from 2016–2018 (Animal Utilization
 Protocol no. 3506, Wildlife Scientific Collectors Authorization no.
 1087323). The main campus of the University of Guelph (43°31052.3300 N,
 80°13036.8000 W, Guelph, Ontario, Canada) was used as our urban site,
 while the deciduous forests of the ‘rare Charitable Research Reserve’
 (43°22052.1700 N, 80°20052.4600 W, Cambridge, Ontario, Canada) served as
 our exurban site. Initial site selection involved qualitative assessments
 sites (e.g., prominence old growth forest versus human-built impervious
 surfaces, presence of refuse bins, human foot-traffic); however, post hoc 
 quantification of normalized difference vegetation index (NDVI) and
 normalized difference built-up index (NDBI) estimates (surrounding
 locations of sample collection) demonstrate clear differences in both the
 amount of vegetated area (NDVI<sub>exurban</sub> = 0.426 ±
 0.074; NDVI<sub>urban</sub> = 0.267 ± 0.081) and the footprint
 of human-built constructs (NDBI<sub>exurban</sub> = -0.311 ±
 0.024; NDBI<sub>exurban</sub> = -0.165 ± 0.108) between sites
 (Rimbach et al., 2022). Both study sites reside on the treaty lands and
 territory of the Neutral, Haudenosaunee, and the Anishinaabe
 peoples. Squirrels were captured using tomahawk Model
 102 traps (Tomahawk Live Trap Co., WI, USA). Traps were baited with either
 peanuts or oat and peanut butter balls and checked every hour from
 0600–1600. Following capture, squirrels were transferred to a cloth bag
 until fecal pellets could be collected (approximately 15 minutes). Sex and
 reproductive condition were recorded at the time of capture. Reproductive
 condition was coded as either reproductive female (lactating or in
 estrus), non-reproductive female, scrotal male, or non-scrotal male. All
 squirrels were provided with a unique pair of alpha-numeric ear tags for
 future recapture identification. Fecal pellets were stored on ice in the
 field until transfer to storage at -20 ºC. In total, we collected and
 sequenced fecal samples from 112 unique individuals, to avoid
 pseudo-replication at the individual-level. We collected a total of 64
 samples from urban squirrels
 (<em>n</em><sub>spring</sub>: 20,
 <em>n</em><sub>summer</sub>: 17,
 <em>n</em><sub>autumn</sub>: 10,
 <em>n</em><sub>winter</sub>: 17), 27 of which were
 from males (<em>n</em><sub>scrotal</sub> = 21;
 <em>n</em><sub>non-scrotal </sub>= 6) and 37 were
 from females (<em>n</em><sub>reproductive</sub> =
 7; <em>n</em><sub>non-reproductive </sub>= 30). At
 our exurban site, we collected a total of 48 samples
 (<em>n</em><sub>spring</sub>: 15,
 <em>n</em><sub>summer</sub>: 20,
 <em>n</em><sub>autumn</sub>: 5,
 <em>n</em><sub>winter</sub>: 8), 27 of which were
 from males (<em>n</em><sub>scrotal</sub> = 22;
 <em>n</em><sub>non-scrotal </sub>= 5) and 21 were
 from females (<em>n</em><sub>reproductive</sub> =
 3; <em>n</em><sub>non-reproductive </sub>=
 18).<strong> </strong> <em>Sequencing
 and Bioinformatics</em> We extracted DNA from 0.2
 g of feces using QIAamp DNA Stool Mini Kits (Qiagen, Hilden Germany). The
 v4 region of the 16S rRNA gene was amplified in triplicate (primers, 515F:
 5’-GTGYCAGCMGCCGCGGTAA-3’; 806R: 5’-GGACTACNVGGGTWTCTAAT-3’) at
 MetaGenomBio Inc. (Waterloo, Canada; Walters et al., 2015). Triplicate PCR
 products were pooled and sequenced to a depth of 30,000 reads/sample on an
 Illumina MiSeq platform (v2 chemistry). Briefly, we merged paired-end
 reads and performed quality filtering using a standardized mothur pipeline
 (Kozich et al., 2013). Paired-end reads were clustered to operational
 taxonomic units (OTUs) based on a 97% 16S rRNA gene sequence similarity
 using the OptiClust algorithm (Westcott & Schloss, 2017). 
 Taxonomy was assigned to representative v4 sequences using the SILVA v138
 reference database (Yilmaz et al., 2014). Only OTUs which were present at
 a relative abundance of 0.001 in at least a single sample were retained
 for analysis to remove singletons and potential sequencing errors. OTU
 counts were rarefied to the lowest read-count in the dataset (3326 reads)
 prior to all analyses. References
 Rimbach, R., Grant, A., Gupte, P. R., Newman, A., Stothart, M.
 R., & Pontzer, H. (2022). Comfortably numb? Regional differences
 in the relationship between indices of urbanization and a stress indicator
 in eastern gray squirrels. <em>Urban Naturalist</em>,
 <em>9</em>(54), 1–15. http://www.eaglehill.us/urna.
 Kozich, J. J., Westcott, S. L., Baxter, N. T., Highlander, S. K.,
 & Schloss, P. D. (2013). Development of a dual-index sequencing
 strategy and curation pipeline for analyzing amplicon sequence data on the
 miseq illumina sequencing platform. <em>Applied and Environmental
 Microbiology</em>, <em>79</em>(17), 5112–5120.
 https://doi.org/10.1128/AEM.01043-13 Walters, W., Hyde,
 E. R., Berg-lyons, D., Ackermann, G., Humphrey, G., Parada, A., Gilbert,
 J. a, & Jansson, J. K. (2015). Improved bacterial 16S rRNA gene
 (V4 and V4-5) and fungal internal transcribed spacer marker gene primers
 for microbial community surveys. <em>mSystems</em>,
 <em>1</em>(1), 1–10. https://doi.org/10.1128/mSystems.00009-15.Editor Westcott, S. L., & Schloss, P. D. (2017). OptiClust, an improved method for assigning amplicon-based sequence data to operational taxonomic units. <em>mSphere</em>, <em>2</em>(2), 1–11. https://doi.org/10.1128/mspheredirect.00073-17 Yilmaz, P., Parfrey, L. W., Yarza, P., Gerken, J., Pruesse, E., Quast, C., Schweer, T., Peplies, J., Ludwig, W., & Glöckner, F. O. (2014). The SILVA and ‘‘All-species Living Tree Project (LTP)’’ taxonomic frameworks. Nucleic Acid Research, 42, 643–648. https://doi.org/10.1093/nar/gkt1209
description: # Seasonal dynamics in the mammalian microbiome between disparate
 environments This README was generated on 2023-11-03 by Mason Stothart
 GENERAL INFORMATION 1. Title of Dataset: Grey squirrel feces 16S rRNA gene
 amplicon Meta-Data and R script 2. Author Information A. Principal
 Investigator Contact Information Name: Amy E.M. Newman Institution:
 University of Guelph Address: 474-570 Gordon St, Guelph, ON N1G 1Y2 Email:
 [newman01@uoguelph.ca](mailto:newman01@uoguelph.ca) B. Associate or
 Co-investigator Contact Information Name: Mason Stothart Institution:
 University of Calgary Address: 3280 Hospital Drive NW Calgary Email:
 [mason.stothart1@ucalgary.ca](mailto:mason.stothart1@ucalgary.ca) 3. Date
 of data collection (single date, range, approximate date): 2016-05-01 -
 2018-03-01 4. Geographic location of data collection : Guelph Ontario,
 Canada & rare Charitable Research Reserve Cambridge, Canada 5.
 Information about funding sources that supported the collection of the
 data: This work was funded through Natural Sciences and Engineering
 Research Council of Canada (NSERC) and University of Guelph funds to
 A.E.M., a American Society of Mammalogists grant-in-aid of research to
 M.R.S., a rare Charitable Research Reserve ‘Ages Foundation Fellowship’ to
 M.R.S.; M.R.S. was supported by an Ontario Graduate Scholarship and NSERC
 CGS-M while completing this research. SHARING/ACCESS INFORMATION 1.
 Licenses/restrictions placed on the data: N/A 2. Links to publications
 that cite or use the data: N/A 3. Links to other publicly accessible
 locations of the data: N/A 4. Links/relationships to ancillary data sets:
 5. Was data derived from another source? yes/no A. If yes, list source(s):
 No 6. Recommended citation for this dataset: TBD DATA & FILE OVERVIEW
 File List: * grey-squirrel_microbiome_metadata_2023-09-25.csv *
 grey-squirrel_16S-OTU-tree.phylip.tre * EcoEvo_Stothart-et-al_2023-09-25.R
 * Eco-Evo_Grey-Squirrel_Seasonal-Microbiome.biom Relationship between
 files, if important: Files correspond to sample meta-data, phylogenetic
 tree constructed from 16S rRNA gene amplicon sequencing data, R script
 used for data analysis, and raw 16S rRNA gene amplicon .biom table
 containing operational taxonomic unit (OTU) taxonomy and counts across
 samples. Additional related data collected that was not included in the
 current data package: N/A Are there multiple versions of the dataset?
 yes/no A. If yes, name of file(s) that was updated: No METHODOLOGICAL
 INFORMATION Description of methods used for collection/generation of data:
 N/A Methods for processing the data: 16S rRNA gene amplicon sequencing and
 bioinformatics We extracted DNA from 0.2 g of feces using QIAamp DNA Stool
 Mini Kits (Qiagen, Hilden Germany). The v4 region of the 16S rRNA gene was
 amplified in triplicate (primers, 515F: 5’-GTGYCAGCMGCCGCGGTAA-3’; 806R:
 5’-GGACTACNVGGGTWTCTAAT-3’) at MetaGenomBio Inc. (Waterloo, Canada;
 Walters et al., 2015). Triplicate PCR products were pooled and sequenced
 to a depth of 30,000 reads/sample on an Illumina MiSeq platform (v2
 chemistry). Briefly, we merged paired-end reads and performed quality
 filtering using a standardized mothur pipeline (Kozich et al., 2013).
 Paired-end reads were clustered to operational taxonomic units (OTUs)
 based on a 97% 16S rRNA gene sequence similarity using the OptiClust
 algorithm (Westcott & Schloss, 2017).  Taxonomy was assigned to
 representative v4 sequences using the SILVA v138 reference database
 (Yilmaz et al., 2014). Only OTUs which were present at a relative
 abundance of 0.001 in at least a single sample were retained for analysis
 to remove singletons and potential sequencing errors. OTU counts were
 rarefied to the lowest read-count in the dataset (3326 reads) prior to all
 analyses. References Kozich, J. J., Westcott, S. L., Baxter, N. T.,
 Highlander, S. K., & Schloss, P. D. (2013). Development of a
 dual-index sequencing strategy and curation pipeline for analyzing
 amplicon sequence data on the miseq illumina sequencing platform. *Applied
 and Environmental Microbiology*, *79*(17), 5112–5120.
 [https://doi.org/10.1128/AEM.01043-13](https://doi.org/10.1128/AEM.01043-13) Walters, W., Hyde, E. R., Berg-lyons, D., Ackermann, G., Humphrey, G., Parada, A., Gilbert, J. a, & Jansson, J. K. (2015). Improved bacterial 16S rRNA gene (V4 and V4-5) and fungal internal transcribed spacer marker gene primers for microbial community surveys. *mSystems*, *1*(1), 1–10. [https://doi.org/10.1128/mSystems.00009-15.Editor](https://doi.org/10.1128/mSystems.00009-15.Editor) Westcott, S. L., & Schloss, P. D. (2017). OptiClust, an improved method for assigning amplicon-based sequence data to operational taxonomic units. *mSphere*, *2*(2), 1–11. [https://doi.org/10.1128/mspheredirect.00073-17](https://doi.org/10.1128/mspheredirect.00073-17) Yilmaz, P., Parfrey, L. W., Yarza, P., Gerken, J., Pruesse, E., Quast, C., Schweer, T., Peplies, J., Ludwig, W., & Glöckner, F. O. (2014). The SILVA and ‘‘All-species Living Tree Project (LTP)’’ taxonomic frameworks. Nucleic Acid Research, 42, 643–648. [https://doi.org/10.1093/nar/gkt1209](https://doi.org/10.1093/nar/gkt1209) Instrument- or software-specific information needed to interpret the data: R v4.2.1, R packages: ape (v-5.6-2), phyloseq (v-1.40.0, genefilter (v-1.78.0), vegan (v-2.6-2), microbiome (v-1.18.0), ANCOMBC (v-1.6.2), ALDEx2 (v-1.26.0), breakaway (v-4.8.4) Standards and calibration information, if appropriate: N/A Environmental/experimental conditions: Wild Describe any quality-assurance procedures performed on the data: Validated against sequencing negative controls People involved with sample collection, processing, analysis and/or submission: Mason Stothart, Hayley Spina, Michelle Hotchkiss, Winnie Ko, and Amy Newman DATA-SPECIFIC INFORMATION FOR: grey-squirrel_microbiome_metadata_2023-09-25.csv 1. Number of variables: 12 2. Number of cases/rows: 118 3. Variable List: | Variable | Description | | ----------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | sample\_names | unique ID corresponding to fecal samples and sequence fasta files. | | year | year of sample collection | | month | month of sample collection | | day | day of month of sample collection | | season | Season of sample collection (Fall, Winter, Spring, Summer) | | fecal\_ID | Sample ID with year indicator | | left\_tag | squirrel left ear tag alphanumeric code | | right\_tag | squirrel right ear tag alphanumeric code | | environment | environment in which focal animal was captured | | mass | mass of squirrel in grams | | sex | sex of squirrel (male = M, female = F) | | reproductive\_condition | reproductive condition of squirrel at time of capture (R = female in estrus, NR = female in non-reproductive condition, SCR = male with external testes, NSCR = male with no external testes) | EcoEvo_Stothart-et-al_2023-09-25.R Description: An R file containing scripts used to process and analyze data contained within the Grey-squirrel_microbiome_metadata_2023-09-25.csv, grey-squirrel_16S-OTU-tree.phylip.tre, and Eco-Evo_Grey-Squirrel_Seasonal-Microbiome.biom data files. This includes commands for importing microbiome data into a 'phyloseq' format, alpha diversity analyses using the 'breakaway' package, tests of beta diversity using PERMANOVA tests, and differential abundance tests using the packages ANCOMBC and ALDEx2. R version 4.2.1 Loaded R packages: ape (v-5.6-2), phyloseq (v-1.40.0, genefilter (v-1.78.0), vegan (v-2.6-2), microbiome (v-1.18.0), ANCOMBC (v-1.6.2), ALDEx2 (v-1.26.0), breakaway (v-4.8.4) Missing data codes: N/A Specialized formats or other abbreviations used: N/A