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Data from: Metabarcoding under Brine: Microbial ecology of five hyper-saline lakes at Rottnest Island (WA, Australia)

Cite this dataset

Saccò, Mattia et al. (2021). Data from: Metabarcoding under Brine: Microbial ecology of five hyper-saline lakes at Rottnest Island (WA, Australia) [Dataset]. Dryad.


Hypersaline ecosystems - aquatic environments where concentration of salt exceeds 35 g/L - host microbial communities which are highly specialized to cope with these extreme conditions. However, our knowledge on the taxonomic diversity and functional metabolisms characterising microbial communities in the water columns of hypersaline ecosystems is still limited, and this lack of knowledge may compromise the future preservation of these unique environments. DNA metabarcoding provides a reliable and affordable tool to investigate environmental dynamics of aquatic ecosystems, and its use in brine can be highly informative. Here, we make use of bacterial 16S metabarcoding techniques combined with hydrochemical analyses to investigate the microbial patterns (diversity and functions) from five hypersaline lakes located at Rottnest Island (WA). Our results indicate lake-driven microbial aquatic assemblages characterised by taxonomically and functionally moderately to extremely halophilic groups, with TDS (Total Dissolved Solids) and alkalinity amongst the most influential parameters driving the community assemblages. Overall, our findings suggest that DNA metabarcoding allows rapid but reliable ecological assessment of the hypersaline aquatic microbial communities at Rottnest Island. Further studies involving different hypersaline lakes across multiple seasons will help elucidate the full extent of the potential of this tool in brine.


Information extracted from the section '2.2.2. Genetic Investigations' from the source manuscript titled 'Metabarcoding under Brine: Microbial Ecology of Five Hyper-saline Lakes at Rottnest Island (WA, Australia)':

Water samples were used for bacterial 16S metabarcoding and microbial functional analysis. Five 1 litre water sample replicates (n=50) from the five lakes (Garden, Vincent, Serpentine, Herschel and Baghdad; Figure 1) were investigated. Water samples were filtered using two Sentino peristaltic microbiology pumps (Pall Life 126 Sciences, New York, USA), through 0.45 μm sterile membrane filters (Pall Life Sciences, New York, USA). All water filtering equipment was soaked for a minimum of 10 minutes in 10% sodium hypochlorite solution and treated with UV light prior to use and between sample replicates (n=5) for each SP. Immediately post-filtering, half of the filter membrane was used for DNA extraction, while the remaining half was frozen at -20°C.Water membranes, inclusive of laboratory controls, were extracted using DNeasy Blood and Tissue Kit (Qiagen; Venlo, Netherlands), with the following modifications to the manufacturer’s protocol.

For the DNA digest from water samples, both the ATL buffer (360 μL) and Proteinase K (40 μL) solutions were doubled to ensure that the samples were adequately exposed to the lysis solution to optimise DNA yield. The DNA digests were incubated (56°C) overnight in a rotating hybridisation oven. The digest was transferred into a clean tube and loaded into a QIAcube (Qiagen; Venlo, Netherlands) automated DNA extraction system for the remainder of the extraction process. The DNA was eluted off the silica column in 100 μL AE buffer.

The quality and quantity of DNA extracted from each sample was measured using quantitative PCR (qPCR), targeting the bacterial 16S gene. The PCR master mixes used to assess the quality and quantity of the DNA target of interest via qPCR (Applied Biosystems [ABI], USA) were carried out in 25 μL reaction volumes consisting of 2 mM MgCl2 (Fisher Biotec, Australia), 1 x PCR Gold Buffer (Fisher Biotec, Australia), 0.4 μM dNTPs (Astral Scientific, Australia), 0.1 mg bovine serum albumin (Fisher Biotec, Australia), 0.4 μM of each primer (Bact16S_515F and Bact16S_806R; [36,37]), 0.2 μL of AmpliTaq Gold (AmpliTaq Gold, ABI, USA) and 2 μL of template DNA (Neat, 1/10, 1/100 dilutions). The cycling conditions were: initial denaturation at 95°C for 5 minutes, followed by 40 cycles of 95°C for 30 seconds, 52°C for 30 seconds, 72°C for 30 seconds, and a final extension at 72°C for 10 minutes.

Extracts that successfully yielded DNA of sufficient quality, free of inhibition, as determined by the initial qPCR screen (detailed above), were assigned a unique 6-8bp multiplex identifier tag (MID-tag) with the bacterial 16S primer set. Independent MID-tag qPCRs for each sample were carried out in 25μL reactions containing 1 x PCR Gold Buffer, 2.5 mM MgCl2, 0.4 mg/mL BSA, 0.25 mM of each dNTP, 0.4 μM of each primer, 0.2μL AmpliTaq Gold and 2–4 μL of DNA as determined by the initial qPCR screen. The cycling conditions for qPCR using the MID-tag primer sets were as described above. MID-tag PCR amplicons were generated in duplicate for each sample and the bacterial 16S library was pooled in equimolar ratio post-PCR for DNA sequencing. The final library was size selected (160-600bp) using Pippin Prep (Sage Sciences, USA) to remove any MID-tag primer-dimer products that may have formed during amplification. The final library concentration was determined using a QuBitTM 4 Fluorometer (Thermofischer, Australia) and sequenced using a 500 cycle V2 kit on an Illumina MiSeq platform (Illumina, USA).

MID-tag bacterial 16S sequence reads obtained from the MiSeq were sorted (filtered) back to the water sample based on the MID-tags assigned to each DNA extract using Geneious v10.2.5 [38]. MID-tag and primer sequences were trimmed from the sequence reads allowing for no mismatch in length or base composition.


BHP Social Investment Fund, eDNA for Global Biodiversity (eDGES) programme

BHP Social Investment Fund, eDNA for Global Biodiversity (eDGES) programme