Silica encapsulated DNA-based tracers for aquifer characterization

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Characterization of Natural and Affected Environments

Silica encapsulated DNA-based tracers for aquifer characterization Gediminas Mikutis, Claudia A. Deuber, Lucius Schmid, Anniina Kittilä, Nadine Lobsiger, Michela Puddu, Daphne Osk Asgeirsson, Robert N N. Grass, Martin O. Saar, and Wendelin J. Stark Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.8b03285 • Publication Date (Web): 02 Oct 2018 Downloaded from http://pubs.acs.org on October 7, 2018

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Environmental Science & Technology

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Silica encapsulated DNA-based tracers for aquifer

2

characterization

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Gediminas Mikutis,1 Claudia A. Deuber,2 Lucius Schmid,1 Anniina Kittilä,2 Nadine Lobsiger,1

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Michela Puddu,3 Daphne Asgeirsson,1 Robert N. Grass,1 Martin O. Saar,2 Wendelin J. Stark1*

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1

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Zurich, Vladimir-Prelog-Weg 1, 8093 Zurich, Switzerland

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2

8

Sonneggstrasse 5, 8092 Zurich, Switzerland

9

3

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Functional Materials Laboratory, Department of Chemistry and Applied Biosciences, ETH

Geothermal Energy and Geofluids Group, Department of Earth Sciences, ETH Zurich,

Haelixa AG, Otto-Stern-Weg 7, 8093 Zurich, Switzerland

* Corresponding author: [email protected]

11 12

KEYWORDS. DNA, tracer, colloid, column, groundwater, silica.

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ABSTRACT. Environmental tracing is a direct way to characterize aquifers, evaluate the solute

15

transfer parameter in underground reservoirs, and track contamination. By performing

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multitracer tests, and translating the tracer breakthrough times into tomographic maps, key

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parameters such as a reservoir’s effective porosity and permeability field may be obtained. DNA,

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with its modular design, allows the generation of a virtually unlimited number of distinguishable

ACS Paragon Plus Environment

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tracers. To overcome the insufficient DNA stability due to microbial activity, heat, and chemical

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stress, we present a method to encapsulated DNA into silica with control over the particle size.

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The reliability of DNA quantification is improved by the sample preservation with NaN3 and

22

particle redispersion strategies. In both sand column and unconsolidated aquifer experiments,

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DNA-based particle tracers exhibited slightly earlier and sharper breakthrough than the

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traditional solute tracer uranine. The reason behind this observation is the size exclusion effect,

25

whereby larger tracer particles are excluded from small pores, and are therefore transported with

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higher average velocity, which is pore size-dependent. Identical surface properties, and thus flow

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behavior, makes the new material an attractive tracer to characterize sandy groundwater

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reservoirs or to track multiple sources of contaminants with high spatial resolution.

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1. INTRODUCTION

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Aquifer tracer tests are a way to characterize the spread of both non-reactive (e.g. persistent

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organic pollutants, solvents) and reactive (e.g. biodegradable pharmaceuticals) solutes in

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groundwater. Information obtained from such tests can be used to determine solute and heat

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transport parameters (e.g. transport velocity, dispersivity)1 or information about aquifer structure

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(e.g. preferential flow paths).2-3 Some of the key characteristics of an ideal non-reactive tracer

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are absence of toxicity, simple quantification, low detection limit, and minimal interaction with

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the solid medium.4 Furthermore, in most cases multiple water flow paths, or streamlines, have to

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be traced (e.g. different origins of pollution, or when tracer tomography is performed), and in

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order to be able to compare the breakthrough curves (BTCs) of different tracers, their transport

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behavior in the fluid (e.g. water, oil) has to be understood. Only a limited number of

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distinguishable traditional solute tracers (e.g. salts, fluorescent dyes, fluorocarbons, radioactive

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isotopes, heat, etc) are available, thus limiting the number of distinct breakthrough curves that

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can be obtained from a single tracer experiment. This in turn limits the number of data points to

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be used for tracer tomography. Furthermore, even tracers of the same type (e.g. the fluorescent

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dyes uranine and sulforhodamine B) exhibit differences in their flow behaviors (e.g. retention

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time and mass recovery), making it even more difficult to compare breakthrough curves

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generated by different tracers.4-7

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To overcome the limited number of distinguishable tracers, DNA has been often proposed as a

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tracer of choice, because a virtually unlimited number of unique DNA sequences can be

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synthesized on demand.8 Using DNA allows for simultaneous tracing at multiple locations, or

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repeated tracer experiments without encountering background contamination (new DNA codes

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can be used in every experiment). Several studies showed the feasibility of using pure DNA


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sequences as tracers in hydrogeology: Sabir et al., for example, demonstrated that multiple DNA

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tracers can be detected in groundwater passing through fractured rocks and porous media at

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minute concentrations.3, 9-10 DNA detection is traditionally facilitated by quantitative polymerase

56

chain reaction (qPCR), which is a technique that first amplifies a specifically selected DNA

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sequence, and then a DNA sequence is detected using a DNA-binding fluorescent dye. The

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excellent limit of DNA detection was exploited by Foppen et al. when comparing synthetic DNA

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and a salt (NaCl) tracer in a stream, where DNA could be detected over a kilometer away.11 Even

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though concentrations as low as 10 attomolar (attomolar = 10-18 mol/L) could be detected, DNA

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recovery was found to be much lower than that of NaCl in long-distance experiments, possibly

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due to DNA adsorption, attachment, decay, and/or biological uptake processes in the stream.

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Controlled column experiments, comparing DNA and salt tracers (KCl), carried out by Aquilanti

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et al., showed that in a clean sand column, DNA behaves as a conservative tracer with very little

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adsorption and an almost pure advective flow (lower longitudinal dispersion than KCl).12 Most

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recently, Pang et al. showed that mere 36 µg of double stranded DNA (less stable single stranded

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DNA was used in previous studies) was sufficient to track groundwater over 37 meters down-

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gradient, still obtaining the signal 3 orders of magnitude above the limit of detection.13 However,

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as previously also reported by Sabir et al.,9 DNA had an earlier breakthrough than other solute

70

tracers, indicating that, depending on the length of the DNA sequence, it is transported through

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preferential flow paths. Therefore, the length of the DNA has to be accounted for if a direct

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comparison is needed. Their study also confirmed that the main disadvantage of using DNA as a

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tracer is its limited environmental stability: it degrades at low pH, when microbial activity is

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abundant,9 or at elevated temperature.14-16 In fact, free DNA was shown to have a half life of less


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than 10 h in the environment at 20° C.17-18 These factors make it difficult to use DNA tracer

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concentration profiles to quantify groundwater flow.

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One way to circumvent the differences in flow behavior and stability issues encountered is the

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encapsulation of DNA inside a protecting matrix. Such DNA encapsulation results in identical

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fluid transport behavior of all DNA sequences, while protecting the DNA from degradation. Just

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attaching DNA to the surface of silica and clay particles was shown to increase DNA stability

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under field conditions to some extent, but still kept DNA accessible to water.19 Sharma et al.

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developed a polylactic acid (PLA)-encapsulated DNA to trace surface waters for distances of up

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to 100 m.20 While tracing water flow in a glacier, it was shown that PLA-encapsulated DNA

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slightly outperforms non-encapsulated DNA tracers in terms of recovery.21 The disadvantage of

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PLA is its high degradation rate in various environments. Furthermore, authors did not report

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any stability performance data, especially towards chemical stresses, heat, and light.

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Encapsulation of DNA inside silica particles has been specifically developed to protect fragile

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DNA molecules from degradation due to physical (e.g. heat, light),14,

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nucleases, reactive oxygen species, bacterial activity, extreme pH)23 stresses. Silica-encapsulated

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DNA has found applications in long-term DNA24 and RNA25 storage, tracing products (e.g. oil,26

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milk,27 pesticides,28 polymers14) across their supply chain and to quantitatively trace sub-micron

92

size particles in municipal sewage throughout different processes in a wastewater treatment

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plant.29 The latter study quantified the fate of particulate matter, but did not provide insights into

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the transport behavior of these DNA-based tracer particles, which is required when using them as

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groundwater flow tracers. Horne and co-workers utilized these DNA-based as well as pure silica

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particles in sand columns,16, 30 Berea rock,31 and fractured medium,32 but no breakthrough curves


22

or chemical (e.g.

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or recovery was reported. The authors further reported the tracer loss, likely caused by the silica

98

dissolution at the applied operating temperatures.30

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In this paper, we report the use of stable, silicon oxide-encapsulated DNA tracers for

100

unconsolidated sand aquifer characterization. After describing the novel size-controlled tracer

101

production and characterization, we assess the interaction with sand and behavior in a two-phase

102

system. We also optimized the recovery and reproducibility to obtain tracer breakthrough curves

103

with the quality (in terms of recovery and measurement error) approaching that of conventional

104

tracers. To compare the DNA-based colloidal tracer to the traditional solute tracer uranine, we

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performed controlled sand column experiments using the encapsulated DNA tracers with various

106

tracer particle sizes, as well as both positive and negative surface charges. In order to validate the

107

use of the novel tracer in a more realistic scenario, we also compared the behavior of the DNA-

108

based particle tracer to fluorescent dyes in an unconsolidated aquifer.

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2. EXPERIMENTAL SECTION

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2.1.

Materials. Five distinct DNA sequences were used for encapsulation into silica-based

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particles. Random DNA sequences with lengths between 76 and 108 nucleotides (nt) were

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generated as follows: first, for each tracer, a random DNA sequence with a length of 10 000

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nt was generated, followed by suitable primer selection for sequences with defined lengths

115

using the Primer3 web tool (http://primer3.ut.ee/). The GC-content was selected to be

116

between 40-60%. Desalted single stranded DNA sequences were acquired from Microsynth

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AG (Balgach, CH). They were annealed in TE buffer (10 mM Tris, 1 mM EDTA, pH = 8.0)

118

and subsequently used without any purification. DNA and primer sequences are given in the


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supporting information (SI). SiO2 particles with narrow size distributions (133±4 nm; 365±20

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nm; 776±30 nm), used for DNA encapsulation, were purchased from microparticles GmbH

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(Berlin, DE). Alternatively, starting silica particles can be prepared as reported by Paunescu

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et al.23

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2.2.

DNA tracer production. Nanoparticles containing different DNA sequences were

124

prepared as illustrated in Figure 1A, according to a procedure adapted from Paunescu et al.33

125

First, silicon dioxide particles were functionalized with a quaternary amine that is capable of

126

non-covalently adsorbing DNA on the surface. To do so, 200 mg of particles, with required

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starting sizes (assuming ~20 nm size increase during encapsulation), were dispersed in

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isopropanol (50 g/L) and 40 µL of N-trimethoxysilylpropyl-N,N,N-trimethylammonium

129

chloride (TMAPS, 50% in methanol, ABCR) were added to achieve a positively charged

130

surface. The particles containing TMAPS, were shaken at 800 rpm at room temperature for

131

16 h, centrifuged for 10 min. at 12, 000 rpm and then washed with isopropanol and MilliQ

132

water. The particle surface potential changed from ca. -30 mV to between +30 and +45 mV

133

(measured by Zetasizer Nano as described in SI). To bind DNA onto the particle surface, 3.8

134

mL of functionalized particle suspension (50 mg/mL) were mixed with 40 mL of a ~100

135

µg/mL DNA solution in a falcon tube and shaken for 5 min. To confirm the non-covalent

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DNA attachment, the DNA concentration in the supernatant, after centrifuging the particles,

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was compared to the initial DNA concentration (measured by absorbance at 260 nm). After

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washing

139

poly(diallyldimethylammonium chloride) solution (PDADMAC, 20 wt% in H2O, MW

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200 000-350 000 g/mol, Sigma-Aldrich) were added to deposit the first layer of polymer onto

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the particles, containing DNA. After 20 min of shaking at 800 rpm at room temperature, the

the

DNA-bound

particles

once

with

water,


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mL

of

1

mg/mL

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particles were washed twice with MilliQ water and redispersed in 45 mL of 0.1 mg/mL

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poly(vinylpyrrolidone) solution (PVP, Mw ~ 10 000 g/mol, Sigma-Aldrich) and shaken at

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800 rpm for 20 min at room temperature, followed by a washing step with MilliQ water and

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another one with ethanol. Following this, a silica layer was grown in an acid-catalyzed Stöber

146

reaction (29 mL EtOH, 9 mL H2O, 2.75 mL tetraethoxysilane (TEOS, ≥99% Aldrich), 625

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µL of 10 M acetic acid). The reaction mixture was shaken (800 rpm) overnight. Next day,

148

particles were washed once with ethanol, once with MilliQ water, once with isopropanol, and

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finally redispersed in 20 mL isopropanol. The tracer characterization data is presented in

150

Figure 2.

151

2.3.

Tracer analysis. To quantify the amount of nanoparticles, the DNA threshold cycle Cq

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(qPCR output signal) had to be correlated to the particle concentration. Dilution curves of

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individual tracers were prepared in the concentration range between 100 mg/L (100 ppm) and

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1 ng/L (1 ppt) in the water obtained from the experimental site to ensure that the qPCR

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efficiency is identical between samples and the dilution curve. In all column and field

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experiments, samples of tracers to be injected were kept for analysis to exactly determine the

157

injected concentrations. Samples collected from these experiments were analyzed directly

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without any upconcentration (Figure 1B). Prior to qPCR analysis, DNA was released from

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silica particles by adding a buffered oxide etch solution (BOE, 0.23 g of NH4FHF (pure,

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Merck) and 0.19 g of NH4F (puriss, Sigma-Aldrich) in 10 ml water) to achieve a final BOE

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concentration of 1:100 (250 ppm F- ions). The dissolved DNA was directly used for qPCR

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reaction without any purification. qPCR was performed using SYBR Green-based master

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mixes on Roche LightCycler96 in triplicates. Widen field experiment samples were analyzed

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using 5 qPCR replicates. Detailed qPCR reaction setup and cycling parameters are provided


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in the supporting information. Threshold cycles obtained by qPCR were converted to the

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particle concentrations and plotted against time to obtain breakthrough curves.

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2.4.

Sand column experiments. We first tested the transport behavior of the new DNA-based

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tracer particles in four column experiments, where three unique DNA tracers with different

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particle sizes (negatively-charged) and one positively-charged tracer flowed through a sand

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column. Uranine (Sigma Aldrich, Buchs, CH) as a solute dye tracer was used in each

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experiment for two reasons: (i) to compare the transport behavior between colloidal DNA

172

tracer and a dye tracer and (ii) to be able to compare the four column experiments to each

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other by normalizing the transport data to those of uranine in each experiment.

174

Sand for these column experiments was obtained by collecting a sediment mixture in

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Schaffhausen, Switzerland, which was then wet-sieved to remove silt and clay to obtain a

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fairly uniform sand size distribution of 0.20–0.63 mm. A plexiglass column (29.6 cm long,

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and with 6.3 cm inner diameter) was packed by loading highly permeable filter stones at the

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top and bottom to prevent sand from blocking the tubing and to ensure a radial distribution of

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the tracer at the inlet. Dry sand was then filled in the column followed by flushing with CO2

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before filling with deionized water at 21±2° C. The bulk density of the sand column was 1.62

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g/cm3, resulting in a porosity of 0.39 and a total pore volume of 325.4 mL. As the injection

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loop volume (2.94 mL = 0.009 pore volumes) is small, compared to the total pore volume,

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the injection is approximated as a pulse injection (Dirac Delta function).

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The three first tracer tests were performed one after another with a break of two hours in

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between to rinse any residual material left, and a final test with positively charged particles

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was performed the following morning after keeping the steady state in the column overnight.


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A standard tracer mixture (V = 2.94 mL) contained 0.1 ppm (0.0001 g/L) uranine and 25

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ppm (0.025 g/L) colloidal DNA tracer. Even though DNA-based particle tracers can be

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detected down to 1 ppt (10-9 mg/mL), we chose to use higher concentrations in the column

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experiments to make sure that the BTCs result in high-resolution signals. After pulse

191

injection, the column and all tubing were covered to prevent the light-sensitive uranine dye

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from degrading. DNA-based particle tracers do not degrade on this timescale.22 Water

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samples with a volume of ~2 mL were taken at intervals of 20-60 s, with higher frequencies

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at the expected peak arrival time, and lower frequencies at the beginning (before

195

breakthrough) and the end of the experiment. With a flow rate of ~9 mL/min, one sample

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could be filled in ~15 seconds, resembling a close-to-instantaneous sampling point in time.

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Each of the collected samples was then split into two parts: 200 µL were used for qPCR

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quantification of DNA as described above, and the rest was kept for uranine fluorescence

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measurements using a luminescence spectrometer (Perkin Elmer LS 50 B).

200

2.5.

Subsurface flow experiments. We applied the DNA-based colloidal tracers to assess the

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hydraulic conductivity of an unconsolidated aquifer in Widen, Felben-Wellhausen,

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Switzerland, which is a flat meadow next to the Thur river (the field map is provided in SI).

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The field site is well characterized and contains the following horizontal layers (from the

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surface): (i) 10 cm humus and organic material; (ii) 2-3 m well sorted silty sand with some

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clay (flood sediments), and (iii) 7 m thick layer of sandy gravel with some fine materials,

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well-graded and well-rounded components.34-36 The site is equipped with over 20 wells of

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varying diameters, 4 of which are multi-chamber wells allowing for injection and sampling at

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different depths. Since the natural hydraulic head gradient at the site at the time of the

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experiment was not compatible with the multi-chamber well positioning, a forced hydraulic


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head gradient was established using water pumps. A hydraulic dipole tracer test was

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conducted by pumping water into one well and out of another well (the field structure is

212

presented in section 3.5). Between these wells, multi-chamber tracer injection and production

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wells were located 3 meters apart, enabling tracer injection and production at multiple

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depths. We injected 1 liter water solutions containing 200 mg DNA-based particle tracers

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(W-1 is Channel 3, and two other tracers with unique DNA but the same characteristics in

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Channel 1 and 5; not presented here) and variable amounts of dyes (1 g uranine in Channel 1;

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4 g sulforhodamine B in Channel 3; 20 g Na-naphthionate in Channel 5) into the

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multichannel injection well (MC1). 5 mg of a randomly generated free DNA (GM03) were

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also added to Channel 3. Water samples with a volume of ~60 mL were subsequently

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collected in Channels 1-5 of the multichannel Production Well MC3, 3 meters away, for 5

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hours. The samples were then split into two parts: 1 mL was analyzed by qPCR as described

222

above and the rest by luminescence spectrometry.

223 224

3.

RESULTS AND DISCUSSION

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3.1.

DNA tracer production and characterization

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Encapsulation of DNA for environmental tracing is achieved as illustrated in Figure 1A: short

227

( 8 (experimental

309

details are provided in SI). Although this experiment confirms that particles prefer water over oil,

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their possible accumulation at oil/water interface (Pickering emulsion) is yet to be studied.40-42

311 312

3.3. Recovery optimization and biofilm growth prevention

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Since DNA is first exponentially amplified, and its quantification is based on the fluorescence of

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an intercalating dye after every DNA amplification cycle, the window of the DNA particle tracer

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concentrations that can be detected spreads over roughly 10 orders of magnitude (typically


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roughly between 10-10 g/L (=0.1 ppt) and 1 g/L (=1000 ppm). The downside of the logarithmic

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detection scale is its effect on the precision during sample quantification. For instance, an error

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of 0.2 Cq units on a linear scale would seem acceptable in a range of 40 Cq units for qPCR.

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However, when converted to absolute concentration, an error of 0.2 cycles results in an absolute

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concentration ambiguity of ±15% (=20.2). Errors with such magnitude may make the

321

breakthrough curves appear less smooth. We nevertheless found that the measurement errors can

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be minimized, producing good quality BTCs, by ensuring that the particles are equally

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distributed within the whole volume of samples ahead of analysis by vortexing or mixing the

324

sample, automated sample handling and that a sufficient number of replicates are analyzed (read-

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out optimization results are given in the SI). To confirm that every DNA-based tracer can be

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detected using qPCR without interference of other DNA sequences, we quantified each of the

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five different DNAs in the presence of other tracers to prove that each tracer could be detected

328

selectively down to 1 ppt. We also found that DNA-based tracers do not interact with up to 500

329

ppb of uranine and up to 50 ppm of sulforhodamine B. We furthermore characterized the qPCR

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salt tolerance – DNA could be detected in solutions containing up to 100 mM of NaCl without

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any inhibition. If, however, the dye or salt concentration is higher than expected, DNA-based

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particle tracers can be extracted by sample centrifugation and redispersion in water. Furthermore,

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this method allows upconcentrating samples to increase the limit of detection. Details of the

334

interference experiments are given in the SI.

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Although encapsulated DNA-based tracers can be stored for months in pure water or organic

336

solvents without significant degradation, we observed that the DNA signal in the samples

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obtained from the Widen field site decays very sharply, especially when the air temperature is

338

high (Figure 3). This is likely due to microbial activity inside the sample bottles, resulting in


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biofilm growth that engulfs silica particles in the period between samples are collected and the

340

analysis is performed. In fact, biofilms do not only engulf nanoparticles during growth, but also

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work as sticky “sponges,” to the surface of which nanoparticles get attached.43 Attempts to

342

retrieve the particles from biofilms formed inside sample bottles by mechanical biofilm

343

degradation (vortexing, ultrasound), chemical stresses, or autoclaving44 gave inconclusive results

344

(see Section 9 of the SI for more details).

345

Preventing the microbial activity from the beginning proved to be a more successful approach

346

(Figure 3). While tracer concentration remained stable in deionized water for extended periods of

347

time, irrespective of temperature, the amount of tracer recovered heavily depended on

348

temperature when environmental water samples were investigated. If the water sample was

349

frozen, the tracer concentration did not change. However, even when keeping samples in a

350

fridge, the recoverable concentration decreased considerably within days. The effect was even

351

stronger at room temperature and above, where microbial growth becomes more favorable. If the

352

tracer analysis is not done within hours of sample collection, freezing samples allows

353

quantitative DNA recovery after thawing the sample, irrespective of storage time. Since freezing

354

or at least refrigeration of the samples might not be possible in every setting, we looked into

355

methods to prevent either biofilm formation (e.g. adding d-amino acids45) or microbial activity in

356

general (adding sodium azide46-47). The addition of d-tyrosine did not improve the recovery. In

357

contrast, sodium azide, especially at higher concentrations, proved to be effective in preserving

358

the DNA-based tracers for extended periods of time, resulting in a recovery loss of only 1 qPCR

359

cycle after storing the samples at room temperature for a week.


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Figure 3. Relative tracer recovery after storing samples from the Widen field site for 7 days at

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given temperatures measured (i) without any additives (control); (ii) with sodium azide; (iii) with

363

d-tyrosine. Error bars represent standard deviations of experimental triplicates. Detailed

364

experimental procedure is provided in section 9 of the SI.

365 366

3.4.

367

Since particulate matter are vectors that accelerate the transport of many sorbing contaminants

368

(e.g. pathogens, heavy metals, etc.) in groundwater aquifers and soils, it is crucial to understand

369

the transport and deposition rates of such colloids.39 To characterize the colloidal tracer

370

breakthrough curves (BTCs) under controlled conditions in porous media, we set up a column

371

experiment (Figure 4A), where we injected DNA-based tracers with different particle sizes and

372

surface charges to investigate the influence of particle size and charge on BTCs. To be able to

373

compare the BTCs to those of solute tracers, the solute dye tracer uranine was also injected in

374

each experiment. In total, four different DNA particle tracers were tested. Besides the standard

375

159 nm sized DNA particles (W-1), two larger particle sizes, 410 nm (W-2) and 848 nm (W-3),

376

were assessed. To understand how the surface charge affects the tracer breakthrough and

Porous sand column tracer characterization


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recovery, positively charged particles with a diameter of 150 nm (W-4) were compared to the

378

standard 150 nm negatively charged tracer. The BTCs of differently sized particles, in

379

comparison to uranine, are presented in Figure 4B-D. The curves are fitted using one-

380

dimensional advection-dispersion transport equation for saturated steady-state flow model48 to

381

describe the solute and the particulate DNA-based tracer transport in a porous column:

382

(1)

383

where the concentration c dependence on the relative pore volume VPR is a function of the total

384

pore volume VPT, the column cross-sectional area A and length L, its effective porosity φe, its

385

longitudinal dispersivity αL, the specific fluid discharge qfR, and the relative colloid deposition

386

rate coefficient KDR (see SI for the model derivation). Fitting was done using Levenberg–

387

Marquardt algorithm.

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Figure 4. Sand column experiment setup and results. A) A pulse of tracers with differently sized

391

DNA particles (always in comparison with the solute dye tracer uranine) was passed through a

392

vertical sand column at a constant flow rate and then analyzed by qPCR and fluorescence

393

analysis. B-D) Breakthrough curves of DNA-based tracers with increasing sizes in comparison to

394

uranine as a control solute dye tracer. The symbols indicate experimental data, whereas solid

395

lines represent an analytic solution.

396 397

The transport parameters obtained from fitting breakthrough datapoints for both uranine and

398

DNA tracers (Figure 4B-D) are summarized in Table 2. Colloidal DNA-based tracers showed

399

earlier breakthroughs in comparison to the solute tracer uranine. Increasing the colloid size also

400

led to a sequential increase in the average particle travel velocity, and therefore earlier arrival

401

time (Figure 5). The reason for higher travel velocity is the size exclusion effect, where larger

402

colloids are excluded from small pores (the principle also applied in size exclusion

403

chromatography). In fact, several earlier studies confirmed that colloids are typically transported


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faster than solute chemicals and, thus, arrive earlier.48-51 Sirivithayapakorn and Keller also found

405

that the smallest pores, that particulate matter can pass through, are roughly 50% wider than the

406

diameter of a particle.51 Therefore, unlike solutes, that enter channels with a diameter below 10

407

nm, particles are preferentially transported through significantly larger pores (>200 nm). The

408

effective porosity that larger particles experience is therefore smaller than that of small particles

409

or of a solute dye tracer. Therefore, although tracers of different sizes cannot be directly

410

compared, injecting particles with different sizes at the same location may provide information

411

about the reservoir pore size distribution (see the variation of effective porosities).

412 413

Table 2. Transport parameters (pore volumes of the peak arrival, average velocity ut, colloid

414

deposition rate coefficient KD, effective porosity φe, and longitudinal dispersivity αL) obtained

415

from fitting the data (equation 1) from the three tracer tests with different DNA particles, every

416

time in combination with uranine for direct comparison. Qm corresponds to the water flow rate

417

throughout the experiment. Test no. Qm [mL/min] Tracer 1

9.18

2

8.99

3

9.16

peak VP

ut [cm/min] KD [min-1]

φe [%]

αL [cm]

uranine

1.02

0.75

0.015

39.9

0.038

W-1 (159 nm)

0.98

0.78

0.008

38.5

0.060

uranine

1.03

0.73

0.018

40.3

0.038

W-2 (410 nm)

0.96

0.78

0.019

37.6

0.049

uranine

1.01

0.76

0.018

39.5

0.037

W-3 (848 nm)

0.93

0.82

0.034

36.4

0.050

418 419

The recovery of the smallest DNA-based tracer (85.9% for W-1) was higher than that of uranine

420

(67.4%), however, it decreased with increasing particle size (56.3% for W-2; 39.3% for W-3).

421

Consequently, the colloidal deposition rate increased roughly linearly from 0.008 min-1 for


22

Page 23 of 36


422

159 nm particles to 0.034 min-1 for 848 nm ones (Figure 5). In fact, several other researchers also

423

found that the total recovery (irrespective of breakthrough time) of particles is the highest in the

424

particle size range between 100-200 nm,52-53 because it is dependent on several factors such as

425

particle diffusion and gravitational sedimentation. It is therefore advantageous to use the colloids

426

smaller than 200 nm in field tracer tests to optimize recovery. Zhuang et al. also suggested that

427

colloidal transport and retention can be influenced by other parameters such as grain sizes and

428

properties, solution chemistry, as well as particle surface charge.53 In our experiments, all

429

particles had an identical surface and shape, and the effect of particle charge (ζ = -45.1 mV vs

430

+22.8 mV) did not affect tracer breakthrough times or tracer recovery in sand (Figure S6). In

431

other media, surface charge may have a significant influence on the tracer recovery.54

432

433 434

Figure 5. Tracer breakthrough time in a sand column experiment dependence on its diameter

435

(left axis, filled squares), where increasing the tracer size results in an earlier tracer concentration

436

peak arrival. Uranine is assumed to be 5 nm in diameter. The dotted line corresponds to

437

exponential fitting of the data. Deposition rate dependence based on the particles size is

438

displayed as empty triangles (right axis).


23


Page 24 of 36

439

Colloidal tracer longitudinal dispersivity is higher than observed for uranine, and increases even

440

more for particles with a diameter of 848 nm. Although it has been reported also previously that

441

dispersivity increases with increasing particle size,55 it may also be a result of the particle size

442

distribution, and further research is needed.56

443

The difference between the colloidal tracer and solutes average velocities (4-8% in this

444

experiment, depending on size) is large in comparison to the variation between the retention of

445

solute tracers from the same class (e.g. uranine vs sulforhodamine B).57 Although Kong et al.58

446

show that it does not significantly influence the result of tomographic inversion, depending on

447

the intended use of the tracing experiment data, the different tracer flow parameters may not be

448

appropriate to ignore. This is especially true if the particles used in the tracer operations are

449

significantly larger than the pore diameter of pores accessible to solutes. Therefore, in order to be

450

able to interpret the colloidal tracer breakthrough data and to compare it to the breakthrough

451

curves generated by solute tracers, it may have to be corrected using control experiments in a

452

comparable environment. On the other hand, the difference in the transport parameters may be

453

seen as an opportunity to generate additional data about the reservoir: the unique effective

454

porosities quantified using tracers with different diameters injected in the same location could be

455

correlated to the reservoir’s pore size distribution. However, further research on the relationship

456

between the size exclusion effect and the pore size distribution is needed to make quantitative

457

statements.

458


24

Page 25 of 36

459


3.5.

Groundwater flow characterization

460

To compare the tracer behavior in a real unconsolidated aquifer, we performed a field test at the

461

Widen field site (Felben-Wellhausen, Switzerland). After establishing the hydraulic gradient by

462

pumping water in P11, and withdrawing from P13, unique colloidal DNA, free DNA, and

463

fluorescent tracers were injected at three different depths in Injection Well MC1, and sampled at

464

five intervals in a down-gradient Sampling Well MC3, 3 meters apart from the Injection Well

465

MC1 as shown in Figure 6A.

466 467

Figure 6. A comparison of solute and colloid tracer transport behavior in an unconsolidated

468

aquifer. A) Vertical cross section of the experimental setup at the Widen field site, where tracers

469

are injected at three depths in Well MC1, and sampled 3 meters down the forced hydraulic head

470

gradient at five depths (or channels) in Well MC3. B) Breakthrough curves of DNA Tracer W-1

471

(GM2) and dye tracer suforhodamine B in Channel 4 (B) and in Channel 5 (C) of the Sampling

472

Well MC3. Neither tracer was detected in other channels. The data points were fitted (solid lines)

473

using an extreme-peak distribution function. Since clear signals for both solute and DNA-based

474

tracers were detected only in the two lower channels (4 and 5), the BTCs of only these two

475

channels are presented.


25


Page 26 of 36

476

Since clear signals for both solute and DNA-based particle tracers were detected only in the two

477

lower channels (4 and 5), the BTCs of only these two channels are presented in Figure 6B-C.

478

Injecting 1 liter of tracer mixture, containing 0.2 g DNA-based particle tracer (2 mg DNA

479

content), 5 mg free (non-encapsulated) DNA tracer, and 4 g sulforhodamine B, allowed detecting

480

the DNA-based particle tracer diluted over 8 orders of magnitude. At the time of the tracer

481

breakthrough in Channel 4, the DNA particle tracer showed a dilution of over 2000 times

482

compared to the initial concentration. The dilution of the dye tracer was roughly 50% higher than

483

that of DNA colloids, indicating that the small solute tracer diffuses through narrower pore-space

484

openings into a larger total volume. In Channel 5, the dilution of both tracers was more than 6

485

orders of magnitude. Thus, only a minor fraction of the fluid travelled this way. No tracer was

486

detected in Channels 1-3 of MC3 (Figure 6). Free, non-encapsulated DNA tracer was not

487

detected in any of the analyzed samples at all. As in sand column experiments, DNA-tracer

488

breakthrough peaks were observed earlier than the breakthrough of the solute dye tracer. Earlier

489

and sharper BTCs suggest that the DNA particle tracer disperses into fewer flow paths compared

490

to dye tracers and, thus, travels preferentially through wider flow paths that exhibit on average

491

faster fluid flow velocities. This theory is also confirmed by a more pronounced tailing of the

492

dye tracer in the BTCs (Figure 6B-C), as the solute dye tracer is slowly released, over longer

493

periods of time, from the narrow pores. The breakthrough curves of both the DNA-based and the

494

solute dye tracer are otherwise very similar. However, care has to be taken when choosing a

495

tracer and interpreting breakthrough curves: large particles depict to the flow of large

496

contaminants (e.g. virus), whereas solute tracers provide a better description of solute transport.

497

If tracers with multiple sizes are compared in the same experiment, their BTCs have to be

498

corrected for the size exclusion effect. Tomographic inversion algorithms of such BTCs, using


26

Page 27 of 36


499

unique but identically behaving (= same diameter, shape, and surface charge) DNA tracers in

500

two-dimensional or three-dimensional setups, enable generating hydraulic conductivity (i.e.

501

permeability) maps of the geologic formation or reservoir.58 Alternatively, a large number of

502

unique DNA tracers could serve as a basic environmental engineering tool to track the transport

503

and fate of various species across long distances.

504

In summary, we presented DNA-based particles as novel groundwater tracers with a virtually

505

unlimited number of possible unique “fingerprints”. In contrast to non-encapsulated DNA-based

506

tracers, colloidal DNA tracers were stable in groundwater, also at elevated temperatures, and low

507

pH. This makes such tracers attractive for use in both surface and underground tracing

508

operations, where many differently tagged tracers with ideally identical transport behaviors need

509

to be employed. The capacity to control the encapsulate size and surface properties ensures that

510

every tracer, irrespective of its DNA sequence, interacts with stationary and mobile phases in

511

identical ways and thus simplifies tracer analysis (e.g., breakthrough curves, tomographic

512

inversions). A method to preserve DNA upon sample collection in the presence of microbial

513

activity presented herein enables quantitative DNA tracer analysis over a longer period of time.

514

Through sand column and an unconsolidated aquifer experiments we showed that the particle

515

tracer is transported faster than solute dye tracer and that larger particles travel faster than

516

smaller ones or dye tracers. The reason for this observation is that particles (compared to a

517

solute) only access larger pores or fractures of reservoir formations, where larger average fluid

518

flow velocities prevail. Although the ability to control particle size and improved tracer analysis

519

enabled quantitative tracer use in sand-based aquifers, in order to apply the tracer to the oil and

520

geothermal industry, the particle interaction with other rocks, sediments (e.g. clay), and high salt

521

concentrations is yet to be explored.


27


Page 28 of 36

522

ASSOCIATED CONTENT

523

Supporting Information. Additional tracer characterization, transport equation derivation,

524

compatibility and recovery assessment, and field data is available in the Supporting Information.

525

This material is available free of charge via the Internet at http://pubs.acs.org.”

526 527

AUTHOR INFORMATION

528

Corresponding Author

529

*Wendelin J. Stark

530

Institute for Chemical and Bioengineering, ETH Zürich

531

Vladimir-Prelog-Weg 1, 8093 Zürich (Switzerland)

532

E-mail: [email protected]

533 534

Author Contributions

535

The manuscript was written through contributions of all authors. All authors have given approval

536

to the final version of the manuscript.

537

Notes

538

Competing financial interests: G. Mikutis, R. N. Grass, M. Puddu, and W. J. Stark declare

539

financial interest in the form of technology commercialization through Haelixa AG, of which

540

they are shareholders.

541


28

Page 29 of 36


542

ACKNOWLEDGMENT

543

Financial support was provided by ETH Zurich, Switzerland. The Werner Siemens Foundation is

544

further thanked by Martin Saar for its support of the Geothermal Energy and Geofluids Chair at

545

ETH Zurich.

546 547

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Silica encapsulated DNA-based tracers for aquifer characterization

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