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Environmental Measurements Methods

Does size matter? An experimental evaluation of the relative abundance and decay rates of aquatic eDNA. Jonas Bylemans, Elise M Furlan, Dianne M Gleeson, Christopher M Hardy, and Richard P Duncan Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b01071 • Publication Date (Web): 14 May 2018 Downloaded from http://pubs.acs.org on May 14, 2018

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Environmental Science & Technology

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Does size matter? An experimental evaluation of the

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relative abundance and decay rates of aquatic eDNA.

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Jonas Bylemans,*, †, ‡ Elise M. Furlan,†, ‡ Dianne M. Gleeson,†, ‡ Christopher M. Hardy,§, ‡

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Richard P. Duncan†

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†

Institute for Applied Ecology, University of Canberra, Canberra, ACT 2617, Australia

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‡

Invasive Animals CRC, University of Canberra, Canberra, ACT 2617, Australia

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§

CSIRO Land and Water, GPO Box 1700, Canberra, ACT 2601, Australia

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ACS Paragon Plus Environment

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KEYWORDS

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Environmental DNA, fish, eDNA target length, quantitative real-time PCR

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ABSTRACT

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Environmental DNA (eDNA) is increasingly used to monitor aquatic macro-fauna. Typically,

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short mitochondrial DNA fragments are targeted because these should be relatively more abundant

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in the environment as longer fragments will break into smaller fragments over time. However,

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longer fragments may permit more flexible primer design and increase taxonomic resolution for

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eDNA metabarcoding analyses, and recent studies have shown that long mitochondrial eDNA

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fragments can be extracted from environmental water samples. Nuclear eDNA fragments have

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also been proposed as targets but little is known about their persistence in the aquatic environment.

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Here we measure the abundance of mitochondrial eDNA fragments of different length, and short

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nuclear eDNA fragments, originating from captive fish in experimental tanks, and test whether

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longer mitochondrial and short nuclear fragments decay faster than short mitochondrial fragments

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following fish removal. We show that, when fish are present, shorter mitochondrial fragments are

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more abundant in water samples than both longer mitochondrial fragments and the short nuclear

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eDNA fragment. However, the rate of decay following fish removal was similar for all fragment

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types, suggesting that the differences in abundance resulted from differences in the rates at which

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different fragment types were produced rather than differences in their decay rates.

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ABSTRACT ART

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INTRODUCTION

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Environmental DNA (eDNA) extracted from environmental samples can be used to monitor the

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presence/absence of particular species and obtain biodiversity estimates.1–3 A key issue with using

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eDNA for monitoring purposes is that DNA in the environment can decay rapidly. Over time,

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longer DNA fragments break into smaller fragments causing the latter to be relatively more

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common in environmental samples.4–8 Mitochondrial DNA fragments are also likely to be more

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abundant in environmental samples than nuclear DNA fragments because mitochondrial DNA is

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present in higher copy numbers per cell and is believed to be less susceptible to environmental

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decay. Several studies have shown that recovery rates from environmental samples are lower for

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long relative to short fragments, and for nuclear relative to mitochondrial DNA fragments.4,6,9–11

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Consequently, most studies have used short mitochondrial DNA barcodes (i.e. typically between

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50 and 200 base pairs (bp)), particularly for ancient and highly degraded samples (e.g. ice cores,

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permafrost, fossil bones, faeces, etc.).4,9,12–16


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Environmental DNA from water samples is increasingly being used as a monitoring tool.17–19

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While the optimization of sampling, capturing and extraction protocols has received considerable

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attention, the relative abundance and decay of DNA fragments of different size and origin (i.e.

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mitochondrial versus nuclear) has not been formally evaluated.20–23 Within the water column, the

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relative abundance of different DNA fragments depends on both their rate of production and the

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rate at which fragments are removed from the water column (i.e. through decay, settling, advection

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and dispersion).24 While the source of eDNA is often unclear (e.g. from faeces, urine, mucous,

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etc.), the abundance of eDNA in the environment is known to be correlated with species’ biomass,

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ontogeny and metabolism, which are likely associated with differences in production rates.24–29 On

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the other hand, the decay of eDNA is known to be influenced by temperature, pH, UV-radiation

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and microbial activity.27,30–33 While DNA fragments can decay rapidly in some sample types, such

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as sediment and faecal samples,4,8,34 recent evidence suggests that the aquatic matrix preserves

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eDNA relatively well. For example, DNA fragments believed to be more susceptible to decay (i.e.

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long mitochondrial fragments and nuclear fragments) have been successfully extracted and

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amplified from water samples.35–38 One reason for these findings may be the fact that aquatic

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eDNA occurs mainly within whole organelles and/or cells, meaning it may be partly protected

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from environmental factors that could promote decay.39,40 However, a thorough evaluation of the

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relative abundance and decay rates of different eDNA fragments is needed as the ability to use

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non-standard fragments (i.e. longer mitochondrial fragments and nuclear fragments) could

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advance eDNA-based monitoring of aquatic biodiversity through more flexible primer design and

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increased taxonomic resolution of barcodes for whole community analyses (i.e. eDNA

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metabarcoding).


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Here we use replicate tanks stocked with three different densities of common goldfish (Carassius

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auratus) to quantify the relative abundance and decay rates of mitochondrial eDNA fragments of

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different size and a short nuclear eDNA fragment. We use these results to evaluate whether the

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differences in the relative abundances of the different fragments are caused by their susceptibility

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to environmental decay. Furthermore, using the eDNA degradation data and two different

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modelling approaches we aimed to gain a deeper understanding of the eDNA decay process in

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freshwater environments. Finally, we highlight the potential implications of our findings for

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advancing eDNA-based monitoring.

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MATERIALS AND METHODS

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Primer design and testing

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We designed primers to amplify different sized fragments (ca. 100, 300 and 500 bp) of the

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mitochondrial cytochrome c oxidase subunit I (COI) gene and a short (ca. 100 bp) fragment of the

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nuclear internal transcribed spacer (ITS) region of common goldfish. Target regions were selected

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based on high genetic variability between species and the presence of multiple copies within a

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cell.6,41,42 Fragment sizes for the mitochondrial DNA were chosen based on current size

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recommendations for eDNA studies (i.e. length of 50 to 200 bp) and the conditions currently

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preferred for High-Throughput Sequencing (HTS) platforms (i.e. 550 to 570 bp using 2 x 300 bp

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paired-end sequencing on the Illumina MiSeq allowing for a 50 to 30 bp overlap for sequence

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merging).3,43 The primer pairs were designed and tested both in silico and in vitro (Supporting

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Information). All primer pairs used for further analyses are given in Table 1. Hereafter, different

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DNA fragments will be referred to by the eDNA fragment ID’s in Table 1 which consist of the

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target region (COI or ITS) followed by the total length of the amplicon in brackets (i.e. COI


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(096bp), COI (285bp) and COI (515bp) for the short, medium and long mitochondrial fragments

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respectively and ITS (095bp) for the short nuclear fragment).

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Experimental protocol

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We sterilised all experimental and sampling equipment before use using a 10% bleach solution

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followed by thorough rinsing with UV-sterilized tap water. All tanks were set-up with a gravel

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substrate and a ca. 10 cm piece of PVC pipe for habitat enrichment. A constant airflow was

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provided to each tank through a cylindrical air stone (15 x 25 mm) and tanks were kept a constant

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temperature of 20 °C and a 12 h daylight cycle for the duration of the experiment. Goldfish (mean

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mass = 5.7 g, range = 3.3-9.5 g) purchased from a local pet shop were stocked individually in 10

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L, 30 L and 60 L tanks filled with UV-sterilized tap water to simulate high density (HD), medium

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density (MD) and low density (LD) conditions, respectively in three replicate treatments (n = 9

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tanks). A negative control tank (NCT), consisting of a 60 L tank without fish, was included to test

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for cross-contamination. Fish were fed half a cube of frozen artemia (ca. 1.4 g) every second day

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and no food was added to the NCT. Prior to stocking the tanks with fish, a 50 mL water sample

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was collected from each tank to test that they were initially free from goldfish DNA, with the time

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of this sample set to zero hours (0 h). Additional 50 mL water samples were collected at 2, 6, 24,

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72, 168 and 336 h after stocking. Immediately after collecting the 336 h sample, all fish were

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removed from the tanks and additional water samples were collected at 338, 342, 360, 408, 504,

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672 and 1008 h. Water volumes within tanks were kept constant by adding 50 mL of UV-sterilized

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tap water after each sample collection. Fin clips were collected from each fish after they were

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removed from the tanks. Genomic DNA was extracted from the fin clips and the COI and ITS

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target regions were amplified using PCR. Amplicons were sequenced for all (COI) or two (ITS)


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of the experimental animals to test for the presence of individual primer-template mismatches

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(Supporting Information).

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Sample processing and qPCR analyses

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Processing and analyses of eDNA samples were performed in a trace DNA laboratory at the

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University of Canberra (Australia). This laboratory is spatially separated from other laboratories

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and is UV-radiated nightly to reduce the risk of contamination. Spatially separated room were used

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for eDNA extractions and PCR set-up with the latter having a positive air pressure.

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From each 50 ml water sample, eDNA was captured by filtering onto a glass fibre filter with a

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nominal pore size of 1.2 µm (MicroScience, Taren Point, Australia). While this approach may

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inherently bias the results due to a reduced likelihood of capturing free floating DNA, a 1.2 µm

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pore size is more suitable for field applications and would thus better reflect the accessible eDNA

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during field surveys. Negative equipment controls (NEC) were obtained for each sample by

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filtering 500 mL of UV-sterilized water through the sterilized equipment prior to filtering samples.

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Environmental DNA was extracted using the PowerWater DNA Extraction Kit (MoBio

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Laboratories, Carlsbad, USA) following manufacturing instructions (i.e. 100 µL of eDNA eluent).

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For each timepoint, one NEC was extracted to test for cross-contamination occurring during either

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the filtrations or DNA extraction phase. DNA extracts were transferred to 2 mL screw-cap tubes

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and stored at -20 °C for downstream analyses.

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Quantitative real-time PCR (qPCR) was used to determine eDNA concentrations. The absence

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of goldfish DNA from all negative control samples (i.e. water samples collected from the

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experimental tanks prior to introducing goldfish, water samples from the NCT and NEC’s) was

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confirmed by performing six qPCR replicates for the short COI and ITS fragments. For all

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experimental samples, six qPCR replicates were performed with each primer set. Due to the large


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number of qPCR analyses and the costs of probe-based qPCR assays, a SYBR® Green chemistry

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with previously published reaction conditions scaled down to a final reaction volume of 15 µL

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containing 1.5 µL of DNA extract was used.37 All qPCR reactions were set-up in a dedicated room

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within the trace DNA laboratory in 384-well plates using the epMotion® 5075 Liquid Handling

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Workstation (Eppendorf, Hamburg, Germany). Six non-template controls (NTC) and a standard

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curve, consisting of six qPCR replicates for each concentration (i.e. 3 x 101 to 3 x 106 molecules

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per reaction), were included on each plate. Synthetic gBlock® fragments (IDT, Coralville, USA)

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were used to construct standard curves. Synthetic fragments contained bp mismatches with the

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sequences of the experimental animals (Supporting Information) and Sangers sequencing of qPCR

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amplicons obtained from eDNA samples was used to evaluate potential cross-contamination (i.e.

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amplicon sequences should only match the sequences from the experimental animals).

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All qPCR analyses were performed using the Viia7 Real-Time PCR System (Applied

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Biosystems, Foster City, USA) under previously published cycling conditions.37 Amplification

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and melt curves were visually inspected and replicates were excluded from further analyses if the

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amplification curve did not show a clear exponential phase and/or the melt curve deviated from

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those obtained with genomic goldfish DNA (Supporting Information). Finally, for each fragment

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a subset of the PCR amplicons (ca. 10% of all samples showing a positive amplification) were

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purified using the MinElute PCR Purification Kit (Qiagen, Hilden, Germany) and Sanger

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sequenced at the ARCF Biomolecular Resource Facility (Australian National University) using an

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Applied Biosystems 3730xl DNA Analyzer (Thermo Fisher Scientific) following the

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manufacturer’s protocol.

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Data analyses

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Environmental DNA concentrations ([eDNA]) were expressed as copy numbers per mL of tank

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water and qPCR replicates that failed to amplify were assumed to have a concentration of zero

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copies per mL. Concentrations were calculated using eDNA copies per qPCR reaction (eDNA),

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the volume of template DNA used per qPCR reaction (1.5 x 10-3 mL) and the sample volume (50

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mL). A correction for the dilution effect, caused by adding UV-sterilized water to the experimental

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tanks, was included using the sample volume (50 mL) and the volume of the experimental tank

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expressed in mL (VT) (Equation 1). Nonetheless, eDNA measurements obtained after removing

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fish from the experimental tanks will be influenced by both eDNA decay and the dilution effect.

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As only small sample volumes were used, the dilution effect is unlikely to influence the overall

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eDNA decay trends observed.

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[𝑒𝐷𝑁𝐴] =

(𝑒𝐷𝑁𝐴 × (100 × 10−3 𝑚𝐿)) ((1.5 × 10−3 𝑚𝐿) × 50 𝑚𝐿)

×

(𝑉𝑇 −50 𝑚𝐿) 𝑉𝑇

(1)

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For further statistical analyses, eDNA concentrations were transformed using the natural logarithm

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(i.e. loge([eDNA] + 1)) and all analyses were conducted using R version 3.4.1 with the packages

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tidyverse and nlme.44–46 The data obtained for two experimental tanks was excluded from the final

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analyses as bp mismatches were observed between the primers and the template sequences for two

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experimental animals (see the “RESULTS AND DISCUSSION” section for a more detailed

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description).

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Inspection of the data prior to fish removal revealed that all eDNA fragments reached

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equilibrium concentrations after approximately 24 h (Supporting Information). We therefore

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estimated equilibrium eDNA concentrations using the data from 24 h until fish were removed (i.e.

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sampling time ≥ 24 h and sampling time ≤ 336 h). We fitted a linear mixed-effect model to the

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data with loge-transformed eDNA concentrations as the response variable. Fish density and


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fragment type were included as categorical fixed effects, and nested random effects were included

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to correct for pseudo-replication (i.e. individual samples nested within individual tanks). We

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estimated differences in eDNA equilibrium concentrations between density treatments and

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fragment types relative to a reference class set to zero (COI (096bp) in the HD treatment).

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The decay of aquatic eDNA has previously been modelled assuming a first-order exponential

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decay function.1,36,47 The concentration of a particular eDNA fragment at time (t), C(t), can thus

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be modelled using Equation 2 with C0 representing the equilibrium eDNA concentration prior to

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fish removal and k being the decay constant.

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𝐶(𝑡) = 𝐶0 × 𝑒 −𝑘𝑡

(2)

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While this first-order decay model may be a simplification of the true decay process, it allows us

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to quantify the decay constants for each fragment by density treatment combination, k, and to

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compare how decay constants vary under different conditions.31,40 Decay constants were estimated

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using the data obtained at least 6 hours after fish removal (i.e. sampling time ≥ 342 h). This was

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done to avoid a spike in eDNA concentrations immediately after fish removal in one tank, possibly

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caused by increased stress levels in the experimental animal and/or the resuspension of faecal

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matter. We also excluded sampling times for which all qPCR replicates failed to amplify, which

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implied that eDNA abundance had decayed below the detection limits (i.e. here assumed to be zero

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copies per mL). We estimated the parameters of the exponential decay model by fitting linear

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models using loge-transformed eDNA concentrations as the response variable. A linear mixed-

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effect model was used to evaluate the impact of fish density and fragment type on the decay

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constant. Sampling time was included as a continuous fixed effect along with categorical fixed

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effects for fish density and fragment type. Two-way interactions between sampling time and fish

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density, and sampling time and fragment type were also included (significant interactions imply


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differing slopes and hence differing values of the decay constant, k, for density and fragment type).

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A nested random effect was included to correct for pseudo-replication (i.e. individual samples

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nested within individual tanks). Differences in decay constants between density treatments and

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fragment types were estimated relative to a reference class set to zero (COI (096bp) in the HD

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treatment). To evaluate the fit of the exponential decay model we used separate linear models for

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each fragment by density treatment combination and calculated the Akaike Information Criterion

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(AIC).

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The assumption that the eDNA decay process can be summarized into a single decay constant

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may not apply if some fragments were more prone to decay than others (e.g. fragments present

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within cells versus free floating DNA). This would result in the decay constant decreasing over

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time as fragments prone to rapid decay (i.e. having a higher decay constant) were removed first

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from the population, leaving behind fragments with lower decay constants. To test if the eDNA

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decay constant varied over time for each treatment by fragment combination, we fitted a Weibull

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decay model to the data (Equation 3). The Weibull parameter (β) in this model allows for the decay

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constant to vary with time, with values of β less than one indicating a decreasing decay constant

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and values larger than one indicating an increasing decay constant over time. When β equals one

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the model reduces to the first-order exponential decay function.

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𝐶(𝑡) = 𝐶0 × 𝑒 (−𝑘 × 𝑡

𝛽)

(3)

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We estimated parameters for the Weibull model for each fragment by density treatment

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combination as above (i.e. using the data obtained at least 6 hours after fish removal and sampling

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times for which all replicates tested negative for eDNA excluded). We used the AIC to evaluate

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the fit of the model for each treatment by fragment combination and compared AIC values from


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the Weibull model with those obtained from the first-order exponential decay model to assess

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which model best described the data.

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RESULTS AND DISCUSSION

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Primer design and testing

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All primer pairs successfully passed the in silico and in vitro evaluation. The performance of the

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different primer pairs was evaluated based on the standard curves included in the qPCR analyses.

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The results show that the amplification efficiency decreases with increasing amplicon length and

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that the efficiency of the primers targeting the ITS (096bp) fragment is lower compared to those

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for the COI (095bp) fragment (Table 1). Nonetheless, this will not affect the validity of the eDNA

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quantifications as both standard curve samples and experimental samples will be amplified with a

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comparable efficiency.48

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The COI barcode sequences (660bp in length) from the experimental animals revealed that two

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mitochondrial haplotypes were present. Two out of the nine sequences had a 98% match with C.

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auratus voucher specimens, which were used as a basis for primer development. This genetic

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variation in the mitochondrial genome resulted in a reduced or failed amplification in two of the

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experimental tanks when using the goldfish specific COI primers. The data obtained from these

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replicate tanks was thus excluded from further analysis (i.e. removal of one LD and one HD

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replicate tank). In contrast, identical sequences were obtained for the ITS regions of two

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experimental animals with different COI haplotypes and these were used as a basis for primer

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development (Supporting Information). Primers targeting the ITS (096bp) fragment showed

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consistent amplification in all replicate tanks. While this suggests that the ITS region can be a

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valuable target for the development of primers specific to species with a high mitochondrial


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genetic variability (e.g. goldfish), the relative abundance and the decay rate of the ITS (096bp)

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fragment also needs to be considered.

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Effect of fragment size

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Equilibrium concentrations of mitochondrial eDNA fragments decreased with decreasing fish

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density, which is consistent with previously published results.28,29 The model estimates of the mean

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eDNA concentrations in the MD and LD treatments were on average 0.43 and 0.16 times that of

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the HD treatment, respectively (Figure 1). The 95% confidence intervals around the model

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estimates revealed a significant decrease in equilibrium concentrations for longer mitochondrial

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fragments, which is consistent with the prevailing view that shorter mitochondrial DNA fragments

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are more abundant in environmental samples (Figure 1).4–6 The mean estimates for the equilibrium

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concentrations of the COI (285bp) and COI (515bp) fragments were 0.76 and 0.31 times that of

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the COI (096bp) fragment, respectively. In contrast, a previous study by Deagle et al.4 revealed

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that a 327 bp sea lion DNA fragment is on average 0.099 (± 0.057) less abundant than a 91 bp

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fragment in sea lion faecal samples. Furthermore, a study by Dell’Anno et al.34 found that

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degradation rates for extracellular DNA in marine sediments were 7-100 times higher than those

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observed in the water column, and Deiner et al.38 recently showed that even complete

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mitochondrial genomes can be extracted and amplified from aquatic eDNA samples.

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Consequently, the aquatic matrix seems to preserve longer DNA fragment relatively well.

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Environmental DNA decay constants estimated from the first-order exponential decay models

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ranged from 0.11 to 0.77 day-1, which are towards the lower end of previously published records

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(i.e. 0.05 to 17.9 day-1).19,26,27,30,31 This could be a consequence of the UV-sterilized tap water used

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in the experimental tanks, which is likely to reduce the influence of microbial organisms on the

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decay process. However, similar decay constants have been obtained by Thomsen et al.19 (i.e. 0.32


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and 0.70 day-1) when using natural seawater and by Strickler et al.31 (i.e. 0.05-0.34 day-1) when

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using tap water inoculated with micro-organisms. More importantly, we expected to find higher

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decay constants for longer fragments if DNA fragmentation (i.e. events such as strand breaks that

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prevent DNA replication during PCR) is a random process and a major cause of eDNA decay.4,9

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However, given the strongly overlapping confidence intervals around the estimates of the decay

274

constants we can conclude that there is no clear evidence that larger eDNA fragments have higher

275

decay constants (Figure 2). In contrast to our findings, a recent study did report a significantly

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higher decay constant for a 719 bp fragment relative to a 127 bp fragment.36 The smaller

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differences in length between fragments in our study may partly explain why we did not observe

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an effect. Alternatively, the short decay time used by Jo et al.36 (i.e. up to 48 hours after fish

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removal) may have resulted in an over-estimation of decay constant given that we found that decay

280

rates can be high initially but decrease over time (see “Comparison of eDNA decay models”

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section). Nevertheless, the absence of a clear length dependent decay constant in our study

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provides evidence that DNA fragmentation may not be the rate determining step in the decay

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process of aquatic eDNA. In the current study, the rate of decay may be more strongly affected by

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the time taken to break down phospholipid bilayers as aquatic eDNA is mainly present in

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mitochondria or whole cells and the methods used here will primarily capture this eDNA

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fraction.39,40

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Equilibrium concentrations of aquatic eDNA are a function of both eDNA production and decay

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rates. As decay rates did not vary consistently by fragment length, our results imply that the

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differences in equilibrium concentrations were caused primarily by differences in the production

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rates of eDNA fragments of different length. Intestinal cells present in faecal matter are an

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important source of aquatic eDNA.25,49 Given that DNA in faeces is often fragmented, some


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proportion of the eDNA released by animals may already be fragmented.4 Therefore, the eDNA

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released into the water column through fish excrements might explain why production rates differ

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for fragments of different length. This inherent fragmentation of eDNA released by aquatic

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organisms will need to be considered in future studies aimed at evaluating the relative contribution

296

of DNA fragmentation on the overall decay process.

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Effect of fragment origin

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A comparison of the relative abundance of nuclear and mitochondrial eDNA fragments of similar

299

size reveals that nuclear eDNA appears less abundant than the mitochondrial fragment. The

300

estimates of the equilibrium eDNA concentrations showed that the ITS (095bp) fragment was 0.29

301

times less abundant than the COI (096bp) fragment (Figure 1). While some previous studies have

302

shown that nuclear eDNA may be equally or even more abundant than mitochondrial fragments,

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species-specific differences in the number of ribosomal operons are well known.37,41,49,50

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Counter to our expectations, the first-order decay constant estimated from the nuclear data was

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lower for the ITS (095bp) fragment than the COI (096bp) fragment (Figure 2). When considering

306

the absolute estimates for the decay constant for each fragment by treatment combination, we only

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find a significant difference between the ITS (095bp) and COI (096bp) decay constants in the HD

308

treatment (Supporting Information). Within the HD treatment, the build-up of fish excrements is

309

likely to influence both the pH and microbial activity, which in turn can increase the decay

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constant.30,31 While we did observe increased decay constants for the mitochondrial fragments in

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the HD treatments, no significant increase was observed for the ITS (095bp) fragment

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(Supplementary Information). Consequently, the impact of environmental conditions on the decay

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process may differ depending on the origin of the DNA fragment.


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Comparison of eDNA decay models

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Modelling of aquatic eDNA has commonly assumed an exponential rate of decay.19,30,31 However

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we found that a Weibull decay model with a decay constant that decreases over time better

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describes the eDNA decay process. The mean estimate of log(β) was less than zero (implying β

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