DOI: 10.5061/dryad.qz612jmrj
title: Raw reads and metadata for 16S and 12S sequencing for microbiome and dietary analysis of Tasmanian devils

description: The gut microbiome is an important component of host health and function
 and is influenced by internal and external factors such as host phylogeny,
 age, diet, and environment. Monitoring the gut microbiome has become an
 increasingly important management tool for wild populations of threatened
 species. The Tasmanian devil (Sarcophilus harrisii) is the largest extant
 carnivorous marsupial from the island state of Tasmania, Australia. Devils
 are currently endangered due to devil facial tumour disease. Previous
 assessments have shown differences between captive and wild devil gut
 microbiomes and changes during translocations. However, wild gut
 microbiome variability across Tasmania and the drivers of these
 differences are not well understood. We conducted a range-wide assessment
 of gut microbiomes at ten locations across Tasmania, via 16S rRNA
 sequencing, and tested the influence of diet (12S sequencing), location,
 sex, and cohort. We show that the five most abundant phylum and genera
 were consistent across all ten locations. Location, cohort, and sex
 impacted bacterial richness, but location did not impact diversity. While
 there were differences in diet across the state, there was no strong
 evidence of differences between juveniles and adults, nor between males
 and females. Contrary to our hypothesis, diet only explained a small
 amount of variation seen in microbial communities. We suspect that other
 variables, such as environmental factors and immune system development may
 have a stronger influence on gut microbiome variability. Adjustments to
 dietary supplementation is not necessary when preparing devils for
 translocation to different sites. Future research should prioritize
 collecting environmental samples for microbial analysis and integrating
 metabolomics to elucidate functional differences associated with Tasmanian
 devil gut microbiome variability.  
description: DNA from faecal material was extracted in a dedicated clean
 laboratory within a biosafety cabinet following the QIAmp PowerFecal Pro
 Kit (Qiagen) using 250 mg of fecal material from the center of each scat.
 A core subsample was taken from each fecal sample to ensure an even view
 of the bacterial community. Contamination was reduced by decontaminating
 the workspace and tools using 70% ethanol and bleach between each sample.
 Negative controls were used during each extraction batch to detect
 contaminants. DNA quantity and quality were checked using a Nanodrop
 (Thermo Fisher Scientific). The DNA extractions from the faecal samples
 had a 260/280nm ratio of approximately ~1.8, indicating “pure DNA”. To
 confirm the successful isolation of bacterial DNA, PCR amplification to
 target the V3-V4 region using 341F and 806R primers was performed on a
 random subset of samples from each batch, with banding confirmed through
 gel electrophoresis following Chong et al. 2019. PCR steps included (1)
 initial denaturation at 95 °C for 1 minute, (2) 35 cycles of denaturation
 at 95 °C for 15 s, (3) annealing at 55 °C for 15 s, (4) extension at 72 °C
 for 15 s, and (5) final extension at 72 °C for 1 minute. 20 uL of each of
 the resulting amplicon products were loaded into 96-well fully skirted PCR
 plates with a final concentration of 5-10 ng/uL and sent for 16S V3-V4
 amplicon library preparation and Illumina MiSeq v3 2 × 300 base-pair
 sequencing. In addition, amplicon products of the 12S
 V5 region targeting vertebrate species for all samples were produced to
 capture a broad range of prey species, including a blocking
 oligonucleotide primer (“12Sv5DevilB”) to reduce Tasmanian devil host DNA
 amplification. Successful DNA amplification was confirmed for all samples
 using gel electrophoresis (1% agarose at 90 voltage for 35 minutes).
 Amplicon products were sent with Illumina overhangs for Indexing PCR and
 Library preparation using Illumina MiSeq v2 sequencing platform.
 This dataset contains the raw reads for both 16S and 12S
 sequencing and the corresponding metadata. Samples have been anonymised
 due to being a threatened species.
description: # Raw reads and metadata for 16S and 12S sequencing for microbiome and
 dietary analysis of Tasmanian devils This dataset was generated to assess
 the gut microbiome and diet of Tasmanian devils (*Sarcophilus harrisii*)
 across 10 locations in Tasmania, Australia. We used high-throughput
 sequencing to target two amplicon regions: * The **bacterial 16S rRNA gene
 (V3–V4 region)** to characterize gut microbiota. * The **vertebrate
 mitochondrial 12S rRNA gene** to detect vertebrate dietary DNA. The
 dataset includes raw sequencing reads (FASTQ files) and associated sample
 metadata. ## Descriptions The dataset includes paired-end FASTQ files from
 amplicon sequencing of Tasmanian devil fecal samples, generated to
 characterize both gut microbiota (16S rRNA gene) and dietary composition
 (12S mitochondrial gene). Files are demultiplexed and anonymised due to
 threatened species status. There are a total of 856 FASTQ files: * **428
 files for 16S sequencing** (214 samples × forward and reverse reads;
 folder `Microbiome_(16S)_fastq.zip`) * **428 files for 12S sequencing**
 (214 samples × forward and reverse reads; folder `Diet_(12S)_fastq.zip`)
 Each sample has two associated files: one forward read (R1) and one
 reverse read (R2). File names follow the convention:
 \[Gene]_[LocationCode][SampleCode]_S[RunNumber]_L001_R[ReadDirection]_001.fastq.gz Where: * `[Gene]` is either `16S` (microbiome) or `12S` (diet) * `[LocationCode]` is a 2–3 letter abbreviation for the sampling location: * `BRO` = Bronte * `FEN` = Fentonbury * `BUC` = Buckland * `GRA` = Granville * `KEM` = Kempton * `MI` = Maria Island * `NNP` = Narawntapu * `SH` = Stony Head * `WOO` = Woolnorth * `WU` = wukalina * `[SampleCode]` is a numeric identifier for the sample at that location * `S[RunNumber]` is a sequencing run/sample ID * `L001` is the Illumina lane number * `R1`/`R2` indicate forward/reverse reads ### Metadata File Description The dataset includes a metadata file (`sample_metadata_anonymousIDs.csv`) that provides contextual information for each fecal sample included in the sequencing dataset. Each row corresponds to a single sample, and columns contain the following variables: * **SampleID** – Unique identifier for each sample, which corresponds to the FASTQ filenames. * **Sex** – Biological sex of the individual devil. * **Age** – Age of the individual at the time of sampling. * **DFT_Score** – Scoring system indicating Devil Facial Tumor (DFT) status. * **DFT** – Indicates presence or absence of Devil Facial Tumor. * **Location** – Full name of the sampling location (e.g., `Woolnorth`, `Fentonbury`, etc.), matching the location codes in FASTQ filenames. * **Sample_Date** – Date the fecal sample was collected, in `MM_DD_YYYY` format. * **Extraction_Date** – Date the DNA was extracted from the sample, in `MM_DD_YYYY` format. * **ng_uL** – DNA concentration (nanograms per microliter) after extraction. * **Negative_Control** – Indicates which negative control was processed alongside the sample. * **Cohort** – Age cohort classification (`Juvenile` or `Adult`), used for broad biological grouping. ## Sharing/Access information All data are provided directly through this Dryad submission. ## Code/Software R (version 4.2.2) was used for all primary analyses. The workflow is documented in the script `DevilGM.R`, provided with this dataset. Some preprocessing and phylogenetic tree generation steps were completed using QIIME2 and shell commands. The script includes: * Amplicon sequence processing and quality filtering using `dada2` * Taxonomic assignment with the SILVA reference database (16S) and BLASTN against NCBI mitochondrial genomes (12S) * Contaminant filtering using negative controls with `decontam` * Integration of QIIME2-generated phylogenetic trees into R using `phyloseq` * Diversity analyses (alpha and beta), ordination, and differential abundance testing using `DESeq2` * Metadata integration and taxonomic table formatting for downstream analysis Annotations are provided throughout the script for reproducibility and clarity.