DOI: 10.5061/dryad.cfxpnvxb2
title: Data from: Rapid detection of subterranean fauna from passive sampling of groundwater eDNA

description: Groundwater is an essential source of freshwater that supports surface
 ecosystems as well as organisms adapted to living underground. The impacts
 of anthropogenic climate change, extraction, and pollution pose major
 threats to groundwater ecosystem health, prompting a need for efficient
 and reliable means to detect and monitor subterranean faunal communities.
 Conventional survey of subterranean fauna relies on the collection of
 organisms for morphological identification, which can be biased, labour
 intensive, and often indeterminate at lower taxonomic levels.
 Environmental DNA (eDNA)-based methods have been shown to dramatically
 improve on stygofaunal surveys, but currently rely on time-consuming
 active water filtration that limits the number of samples that can be
 processed. Passive eDNA sampling, which involves submersion of material
 (e.g. filter membrane, sponge, etc.) into the sampled environment for a
 fixed period, has previously shown promise as a viable alternative to
 active filtration in aquatic ecosystems and may be applicable to
 groundwater systems. Here, we compared groundwater eDNA collected from
 active pump filtered water samples to membranes submerged in water for 10
 min and 24 h, and haul-net samples morphologically identified, from bores
 at two geographically distinct locations in Western Australia. Our results
 show that while the relative abundance of eDNA in groundwater (measured
 through qPCR) is 100-800 times lower in passive samples, the diversity of
 species detected is comparable between passive and active eDNA collection.
 Additionally, standard metabarcoding assays (18S and COI) of passive eDNA
 samples detected most subterranean orders identified morphologically
 (12/17), and this proportion may be improved with increased sampling and
 application of DNA extraction methods that increase DNA yield. Our
 findings demonstrate that passive eDNA sample collection is a non-invasive
 survey method with the potential to improve the efficiency and level of
 replication of stygofaunal surveys but will benefit from further
 development.
description: Study sites The Pilbara is an ancient,
 geomorphologically stable region in northwest Western Australia that dates
 back 3.5 billion years (Buick et al., 1995). The climate is arid
 subtropical with hot, humid summers, and mild, dry winters. Rainfall is
 low and highly variable, most prevalent between November and April (summer
 wet season), and dependent on the passage of summer monsoon systems
 including cyclones. Our study was conducted at two
 sites. The first, Barrow Island, is a limestone island located
 approximately 60 km off the mainland Pilbara coast, of Western Australia
 (Moro and Lagdon, 2013). The primarily karstic geology of the island
 provides a habitat for a well-documented and diverse subterranean fauna
 assemblage (Humphreys et al., 2013). The groundwater on Barrow Island
 comprises an anchialine aquifer (Humphreys, 2001b); that is,
 physico-chemically stratified waters where a freshwater lens that
 originates from seasonal rainfall overlies seawater with a transitional
 zone in between. The brackish transitional zone, from marine to
 freshwater, is of comparable thickness to the freshwater layer, having
 been expanded due to tidal forces (Humphreys, 2001b; Pohlman, 2011).
 Access to the groundwater and <em>in situ </em>stygofauna
 sampling is typically conducted via bores that have been installed for
 specific operational or monitoring purposes. The bores are typically
 constructed of 50 or 100 mm diameter, Polyvinyl Chloride (PVC) casing that
 is slotted at discrete intervals depending on their purpose. Slots vary
 from 0.5 - 5 mm in width. Bores with larger slot sizes can have mesh
 across them to prevent debris from accumulating inside the bore. The depth
 of bores varies depending on their location on the island (bores at higher
 elevations are deeper in order to reach the water table) and the initial
 purpose of the bore. The second study site, Bungaroo
 Creek, is located approximately 162 km southeast of Barrow Island on
 mainland Australia and is an ephemeral tributary of the Robe River in the
 Pilbara. The groundwater associated with Bungaroo Creek, and the wider
 Robe River, is fresh with highly transmissive alluvial aquifer geology
 (Clark et al., 2021). The interstices of this geology form a habitable
 space for a significant subterranean faunal community in the area. Access
 to the groundwater, and stygofaunal communities, typically occurs through
 boreholes drilled for the purpose of water abstraction, groundwater level
 monitoring, physicochemical monitoring, and mineral exploration.
 Monitoring or water abstraction bores are typically cased using PVC with 1
 mm slots to allow water flow, while mineral exploration bores are
 generally uncased below ground level. Sample
 Collection and Processing Stygofaunal specimens and
 eDNA samples were collected from four bores in Bungaroo Creek (September
 2021) and four bores on Barrow Island (November 2021). Selected bores were
 known to be high in stygofauna diversity (taxon richness and abundance)
 (Humphreys et al., 2013). Whole specimens used to assess the baseline for
 morphological species diversity were collected using haul nets (similar to
 plankton nets – see Saccò et al., 2022b), which were 45 mm or 95 mm in
 diameter, depending on the internal diameter of the PVC casing. The
 haul-net sampling method incorporated six net hauls per bore, consistent
 with the Western Australian Environmental Protection Authority (EPA)
 (2021) technical guidance (EPA, 2021). Haul net samples were sorted and
 identified using a dissecting microscope and specimens of each morphotype
 were stored in glass vials in 100% ethanol and kept frozen at -20°C.
 Stygofaunal experts (authors NS and MTG) provided the morphological
 identifications. <em>eDNA Sample
 Collection</em> Water samples for active
 filtration were collected for eDNA analysis after hauling whole animal
 specimen samples used for morphological identification and reference DNA
 barcoding. Four 1-L water samples were collected from the upper 2 m of the
 water column using a sterile, 1 L plastic disposable bailer (groundwater
 samples-AFGW). Passive samples consisted of frames made of garden netting
 holding five 0.45 µm Supor polyethersulfone membranes 47 mm in diameter
 (Pall Corporation, Port Washington, USA). These were left in the bore,
 within the top 2 m, for either 10 min (PS10) or 24 h (PS24). All
 equipment, including haul nets, was sterilized between bores in 10% bleach
 for 10 min and rinsed in reverse osmosis (RO) water, and disposable gloves
 were used at each borehole to prevent contamination. Fresh bleach solution
 and RO water were used at each borehole for equipment that was not
 decontaminated in the lab ahead of time. Samples of the RO water used for
 rinsing equipment (i.e. field controls) were collected to assess sources
 of contamination. eDNA and haul net samples were kept
 on ice until they could be transferred to the refrigerator for storage at
 4°C at the end of the collecting day. Active filtered groundwater (AFGW)
 samples were filtered within 24 h of collection across 0.45 µm Supor
 polyethersulfone membranes (47 mm) using a peristaltic Pall Sentino
 Microbiology pump (Pall Corporation, Port Washington, USA). For samples
 with high turbidity, up to two membranes were used to increase the volume
 of water filtered. Filter membranes from the passive samples were removed
 from the sampling frames into individual sample bags. The samples were
 immediately frozen and stored at -20°C prior to, and on-ice during their
 transportation to, the Trace & Environmental DNA (TrEnD)
 Laboratory at Curtin University in Perth, Western Australia. All further
 processing was performed at this facility. eDNA
 Laboratory Processing DNA was extracted from filter
 membranes within one month of collection and filtering using a DNeasy
 Blood and Tissue Kit (Qiagen) with the following modifications: 540 µL of
 ATL lysis buffer and 60 µL of Proteinase K were used during the cell lysis
 phase and digested overnight at 56° C. A total of seven DNA extraction
 controls, containing the solutions and plastics supplied in the extraction
 kit, were used and processed alongside all eDNA samples in order to detect
 any laboratory or cross-contamination of samples. All eDNA extractions
 (post-lysis stage) were performed using an automated DNA extraction
 platform (QIAcube; Qiagen) with a customised eDNA protocol that elutes the
 DNA off of the silica membrane in 100 µL of elution buffer (10 mM Tris-Cl,
 0.5 mM EDTA; pH 9.0). DNA extracts were screened for
 quality and quantity of DNA using quantitative PCR (qPCR) with a neat and
 1/10 (18S) or neat and 1/5 dilution (COI) (Table 1) to determine the
 presence of inhibitors and the quantity of target template molecules
 present in each DNA extract (Murray et al., 2015). Each qPCR reaction for
 the 18S universal assay and the COI invertebrate assay was carried out
 with the same master mix with a total volume of 13 µL containing: 1X
 AmpliTaq Gold®PCR buffer (Life Technologies, Massachusetts, USA), 2 mmol/L
 MgCl2, 0.25 mM dNTPs, 0.4 µmol/L each of forward and reverse primers
 (Integrated DNA Technologies, Australia), 0.4 mg/mL BSA (Fisher Biotec,
 Australia), 0.3 µL of 5X SYBR® Green (Life Technologies), 1 U AmpliTaq
 Gold® DNA Polymerase (Life Technologies), 1 µL (18S) or 3 µL (COI) of
 genomic DNA template. The cycling conditions were initial denaturation at
 95°C for 5 min, followed by 50 cycles of 95°C for 30 s, annealing at
 51-52°C (depending on the assay) for 30 s, 72°C for 45 s, a melt curve
 stage of 95°C for 15 s, 60°C for 1 min, and 95°C for 15 s, and a final
 extension at 72° C for 10 min. All qPCR plates included a negative control
 and a positive control. For metabarcoding, each sample,
 including all controls, was assigned a unique combination of multiplex
 identifier (MID) tags for both assays. These MID tags were incorporated
 into fusion-tagged primers, and none of the primer-MID tag combinations
 had been used previously in the laboratory to prevent cross-contamination.
 Fusion PCRs were done in duplicate (18S) or quadruplicate (COI) to
 minimize PCR stochasticity. Additional PCR replication was employed for
 the COI assay because of the higher cycle threshold (CT-the cycle number
 at which amplification is detectable) values indicating a low initial copy
 number of eDNA for that assay. The PCR mixes were prepared in a dedicated
 ultra-clean room before DNA was added. The PCRs were performed with the
 same conditions as the standard qPCRs described above, except the total
 volume of PCR was doubled to 25 µL and the DNA template was increased to
 2-10 µL depending on sample performance in qPCR. Samples were then pooled
 into approximately equimolar concentrations to produce a PCR amplicon
 library that was size-selected to remove any primer-dimer that may have
 accumulated during fusion PCR. Size selection was performed (250-600-bp
 for 18S, 200-500 bp for COI) using a PippinPrep 2% ethidium bromide
 cassette (Sage Science, Beverly, MA, U.S.A). Libraries were cleaned using
 a QIAquick PCR Purification Kit (Qiagen, Germany) and quantified using
 Qubit Fluorometric Quantitation (Thermo Fisher Scientific). Sequencing was
 performed on the Illumina MiSeq platform as per manufacturer's
 instructions using 500-cycle paired-end V2 for the 18S assay, and
 300-cycle single-end V2 for the COI assay. Table 1: PCR
 Primers used for amplification and sequencing of groundwater eDNA
 samples 
 <strong>PCR assay</strong> 
 <strong>Target Taxa</strong>
 <strong>Primer
 name</strong> 
 <strong>Oligonucleotide sequence
 (5’-3’)</strong> 
 <strong>Target length (bp)</strong>
 <strong>Annealing temperature
 (°C)</strong> 
 <strong>Reference</strong> 
 18S 
 Eukaryotes 
 18S_1F 
 GCCAGTAGTCATATGCTTGTCT 
 ~340–420   
 52 (Pochon et al.,
 2013) 
 18S_400R 
 GCCTGCTGCCTTCCTT 
 COI 
 Invertebrates 
 fwhF2 
 GGDACWGGWTGAACWGTWTAYCCHCC 
 ~205 51
 (Vamos et al., 2017) 
 fwh2Rn 
 GTRATWGCHCCDGCTARWACWGG 
 
 Bioinformatics DNA sequences were processed
 using eDNAFlow, an automated bioinformatics workflow designed for the
 analysis of eDNA metabarcoding data (Mousavi-Derazmahalleh et al., 2021).
 This pipeline uses AdaptorRemoval (Schubert et al., 2016) and FASTQC
 (Andrews, 2010) to quality filter and demultiplex sequences using
 ‘obitools’ (Boyer et al., 2016). The minimum Phred quality score was set
 at 20, with a minimum alignment of 12 for the paired-end reads (18S only),
 a minimum length of 100 bp, and a maximum of 2 primer mismatches allowed,
 but no mismatches allowed in the MID-tag sequences. The 18S demultiplexed
 sequences were then denoised using USEARCH <em>unoise3</em>
 (Edgar, 2016) to create Zero-radius operational taxonomic units (ZOTUs)
 with a minimum abundance of 8 reads which is the recommended default for
 the <em>unoise3 </em>command. Because the COI region is so
 variable (more so than 18S), sequences were clustered using USEARCH
 <em>cluster_otus</em> into OTUs with 97% sequence similarity.
 The OTU sequences were then queried against a custom barcode reference
 library for stygofauna (Guzik et al. <em>in prep</em>),
 specimens barcoded for this project (See Supplementary Information), and
 GenBank (NCBI) using blastn with the following parameters (-outfmt
 "5" -perc_identity 95 -qcov_hsp_perc 95 -max_target_seqs 10).
 Search parameters were more relaxed for the COI assay (-perc_identity 85)
 initial screening to maximise the number of taxonomic identifications for
 OTUs in this incredibly variable region, but the final taxonomic
 assignment for both assays was performed using a simple lowest common
 ancestor algorithm on MEGAN (Huson et al., 2007) with a minimum score of
 450 for 18S and 275 for COI based on the lengths of the amplicons. Niches
 (i.e. stygofaunal, troglofaunal, non-subterranean taxon groups) were
 assigned to all metazoan taxa identified from OTUs after van der Heyde et
 al. (2023). This allowed us to parse stygofaunal and troglofaunal taxa
 from non-subterranean taxa.
description: # Data from: Rapid detection of subterranean fauna from passive sampling
 of groundwater eDNA 1. Author contact:
 [mieke.vanderheyde@curtin.edu.au](mailto:mieke.vanderheyde@curtin.edu.au)
 2. Date of data collection (single date, range, approximate date): 2021 3.
 Geographic location of data collection: Pilbara, Western Australia,
 Australia ## SHARING/ACCESS INFORMATION 1. Licenses/restrictions placed on
 the data: CC0 2. Recommended citation for this dataset: van der Heyde,
 Mieke et al. (2024). Data from: Rapid detection of subterranean fauna from
 passive sampling of groundwater eDNA [Dataset]. Dryad.
 [https://doi.org/10.5061/dryad.cfxpnvxb2](https://doi.org/10.5061/dryad.cfxpnvxb2) ## DATA & FILE OVERVIEW #### File List: A) Passive_COI.fasta B) Passive_18S.fasta C) Passive_COI_otus.fasta D) Passive_18S_zotus.fasta E) Passive_COI_taxonomy_OtuTable.xlsx F) Passive_18S_taxonomy_zotuTable.xlsx G) Passive_sample_metadata_dryad.xlsx H) README.md ## Description of the data and file structure The two gene regions sequenced are 18S and COI. The files "Passive_COI.fasta" and "Passive_18S.fasta" contain the demultiplexed sequences processed using eDNAFlow ([https://github.com/mahsa-mousavi/eDNAFlow](https://github.com/mahsa-mousavi/eDNAFlow)). The file "Passive_18S_zotus.fasta" contains the sequences Zero radius operational taxonomic units (ZOTU) that result from denoising the 18S sequences generated through metabarcoding. Similarly, the "Passive_COI_otus.fasta" contains the OTU sequences for the COI sequences, except they are clustered at 97% because the COI region is more variable than 18S. The "Passive_COI_taxonomy_OtuTable.xlsx" and the "Passive_18S_taxonomy_zotuTable.xlsx" contain the OTU tables and assigned taxonomy for the respective metabarcoding assays. The first nine columns contain information about the OTUs including the OTU ID and taxonomic information separated by Kingdom, Phylum, Order, Family, and Taxon. Taxon indicates the lowest taxonomic identification assigned, which could be species, genus, family, or higher order level. * Niche was assigned for the metazoan taxa differentiating between SY-stygofauna, PoSY-potential stygofauna, TF-troglofauna, PoTF-potential troglofauna, and Not-not subterranean. * The "stygofauna" column identifies whether the taxa is stygofauna "stygo", troglofauna "trog" or not subterranean at all "Not" * The "subfauna" column divides the taxa between subterranean fauna and potential subterranean fauna "subfauna", and non-subterranean fauna taxa "Not" * The remaining columns in these files indicate the sample as the column header and the number of sequence reads of each OTU was detected from that sample. The "Passive_sample_metadata_dryad.xlsx" file contains the metadata for the samples including the date they were collected (Date_collected), the date they were filtered or processed (Date_filtered), the Location (Barrow Island or Bungaroo Creek), The Site (bore identification), the volume of sample filtered (mL), the longitude and latitude in decimal degrees and the sample type. The Sample type was coded as follows: * GW-filtered groundwater sample * PS10-passive sample submerged for 10 minutes * PS24-passive sample submerged for 24 hours * CONTROL-field controls collected during sampling * LAB CONTROL-extraction controls from the lab * GW DEEP-deeper water samples that were also filtered (not included in further analysis) * Missing data are coded as NA