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Competitive co-adsorption dynamics of viruses and dissolved organic matter to positively charged sorbent surfaces Antonius Armanious, Melanie Münch, Tamar Kohn, and Michael Sander Environ. Sci. Technol., Just Accepted Manuscript • DOI: 10.1021/acs.est.5b05726 • Publication Date (Web): 22 Feb 2016 Downloaded from http://pubs.acs.org on February 23, 2016

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Manuscript

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Competitive co-adsorption dynamics of viruses and dissolved organic

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matter to positively charged sorbent surfaces

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ANTONIUS ARMANIOUS1,2, MELANIE MÜNCH1, TAMAR KOHN2, MICHAEL SANDER1,*

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1: Institute of Biogeochemistry and Pollutant Dynamics (IBP)

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Department of Environmental Systems Science, ETH Zurich, Switzerland

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2: Laboratory of Environmental Chemistry, School of Architecture, Civil and

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Environmental Engineering (ENAC), École Polytechnique Fédérale de Lausanne

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(EPFL), Lausanne, Switzerland

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Submitted as manuscript to Environmental Science & Technology

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* Corresponding author:

Michael Sander

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email:

[email protected]

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Phone:

+41 (0)44 632-8314

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Fax:

+41 (0)44 633-1122

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Number of Figures:

3

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Number of Tables:

1

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Abstract

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Adsorption onto solid-water interfaces is a key process governing the fate and

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transport of waterborne viruses. While negatively charged viruses are known to

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extensively adsorb onto positively-charged adsorbent surfaces, virus adsorption in

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such systems in the presence of negatively charged dissolved organic matter (DOM)

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as co-adsorbate remains poorly studied and understood. This work provides a

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systematic assessment of the adsorption dynamics of negatively charged viruses (i.e.,

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bacteriophages MS2, fr, GA, and Qβ) and polystyrene nanospheres onto a positively

30

charged model sorbent surface in the presence of varying DOM concentrations. In all

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systems studied, DOM competitively suppressed the adsorption of the viruses and

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nanospheres onto the model surface. Electrostatic repulsion of the highly negatively

33

charged MS2, fr, and the nanospheres impaired their adsorption onto DOM adlayers

34

that formed during the co-adsorption process. In contrast, the effect of competition on

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overall adsorption was attenuated for less-negatively charged GA and Qβ because

36

these viruses also adsorbed onto DOM adlayer surfaces. Competition in MS2-DOM

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co-adsorbate systems were accurately described by a random sequential adsorption

38

model that explicitly accounts for unfolding of adsorbed DOM. Consistent findings

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for viruses and nanospheres suggest that the co-adsorbate effects described herein

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generally apply to systems containing negatively charged nanoparticles and DOM.

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Introduction

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Waterborne viruses cause a number of human diseases including meningitis,

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myocarditis, hepatitis, and gastroenteritis.1 A concise understanding of the fate and

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transport of these viruses is therefore critical for identifying, predicting, and possibly

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interrupting environmental transmission pathways of these viruses. In both natural

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and engineered systems, transport and infectivity of viruses are largely affected by

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their adsorption onto solid-water interfaces.2-10 This process thus has received

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considerable research attention. Adsorption has several energetic contributions

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including virus-surface electrostatic interactions,11-21 the hydrophobic effect,21-24 van

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der Waals interactions,11,12,14,25 and repulsive steric interactions.16,18,21,26 Electrostatics

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play a major role for adsorption onto charged sorbents and are attractive or repulsive

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if the viruses and the sorbents carry the opposite or the same net surface charges,

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respectively.11-21 A large number of waterborne viruses are net negatively charged at

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circumneutral pH27 and are therefore expected to strongly adsorb onto positively

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charged surfaces, including those of iron (oxyhydr-)oxides and aluminum

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oxides.11,14,19,20

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Virus adsorption onto sorbent surfaces in laboratory experiments is commonly

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investigated from solutions that contain only the virus and no other macromolecular

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co-adsorbates. While allowing to selectively studying virus-surface interactions, this

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experimental setup does not account for potential effects of co-adsorbates on virus

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adsorption. Arguably the most abundant and ubiquitous macromolecular co-adsorbate

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in natural and engineered systems is dissolved organic matter (DOM).28-31 DOM 3

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contains nanometer-sized ‘macromolecular’ constituents that are conceptualized both

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as supramolecular associations of smaller organic molecules32,33 and as longer-

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chained polyelectrolytes.34 DOM has a pH-dependent net negative charge reflecting

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the deprotonation of carboxylic and phenolic moieties in the DOM structure.35 As a

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consequence, DOM strongly adsorbs onto positively charged sorbent surfaces.36-40 It

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is thus reasonable to expect competitive adsorption between DOM and negatively

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charged viruses for these sorbent surfaces.

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Two scenarios are plausible for the effect of DOM as a co-adsorbate on virus

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adsorption. In the first, the viruses and DOM directly compete for positively charged

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adsorption sites and, at the same time, the virus does not adsorb onto DOM adlayers

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(i.e., DOM structures that form on the adsorbent surface during the co-adsorption

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process) due to unfavorable virus-DOM interactions. This scenario predicts

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competitive suppression of virus adsorption by DOM and, as a consequence,

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increasing virus transport and mobility. In the second scenario, the viruses and DOM

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still directly compete for adsorption sites but the virus experiences net attractive

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interactions with the DOM adlayers forming on the adsorbent surface. This scenario

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predicts that virus adsorption onto the DOM adlayers attenuates the effect of virus-

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DOM competitive adsorption. While indirect support for both scenarios can be found

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in the literature,3,41-43 a systematic study of virus-DOM competition on positively

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charged sorbents is missing from the literature. A fundamental understanding of

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competition is, however, required to accurately predict the fate and transport of

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waterborne viruses in DOM-containing systems.

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The objective of this work was to provide a systematic assessment of virus

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adsorption dynamics onto positively charged adsorbent surfaces in systems containing

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DOM as co-adsorbates. To this end, we systematically studied the adsorption of four

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bacteriophages (i.e., MS2, fr, GA and Qβ) onto positively charged amine-terminated

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self-assembled monolayers (SAM-NH3+) in the presence of varying concentrations of

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DOM (i.e., either Suwannee River humic acid (SRHA) or Suwannee River natural

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organic matter (SRNOM)). The four viruses were selected because they have

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spherical capsids with icosahedral symmetry and very similar diameters (Table 1) but

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different capsid surface charge and polarity characteristics. These viruses are

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considered surrogates for non-enveloped water-borne human viruses. MS2 and fr

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have comparatively high negative surface charges, resulting in strong electrostatic

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repulsion from DOM adlayers.21 Conversely, GA and Qβ carry smaller net negative

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charges and have net favorable interactions with DOM adlayers.21 These differences

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in virus-DOM adlayer interactions allow assessing the two scenarios outlined above.

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The SAM-NH3+ surface is chemically well defined and served as model for positively

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charged adsorbents in natural and engineered systems. Virus-DOM experiments were

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complemented by co-adsorbate experiments containing monodisperse, negatively

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charged polystyrene nanospheres (n-PS) and DOM to assess whether the results

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obtained with viruses universally apply to co-adsorbate systems containing negatively

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charged nanoparticles. All experiments were conducted under environmentally

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relevant solution chemistries (i.e., pH 6 and I= 10 mM). The effect of increasing I on

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co-adsorption dynamics was assessed in separate experiments. DOM concentrations

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covered a wide range of environmentally relevant values (0.25 and 50 µgDOM·mL-1). 5

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The virus/DOM and n-PS/DOM ratios were selected to result in different extents of

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competitive co-adsorption that were required to study this process on a mechanistic

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level. To obtain molecular level insights into the spatiotemporal dynamics of viruses

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and DOM on the sorbent surface, a random sequential adsorption (RSA) model was

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developed and used to simulate adsorption in the MS2-SRHA co-adsorbate system.

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Materials & Methods

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DOM samples and chemicals

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SRHA and SRNOM were obtained from the International Humic Substances

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Society (St. Paul, MN, USA) and were used as received. These materials are

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commonly used as models for DOM in aquatic systems. All chemicals were of

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analytical grade and used as received. A complete list is provided in the Supporting

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Information (SI).

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Viruses and nanospheres

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The bacteriophages MS2, fr, GA, and Qβ were propagated and purified as

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detailed in the SI. Suspensions of polystyrene nanospheres (n-PS; Fluoresbrite YO

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Carboxylate Microspheres, nominal diameter of 50 nm) were obtained from

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Polysciences, Inc. and used as received. Table 1 summarizes adsorption-relevant

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physicochemical properties of the viruses and n-PS.

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Table 1. Physicochemical properties of the viruses and polystyrene nanospheres (nPS) relevant to adsorption. Diameter [nm]

MS2

fr

GA

Qβ β

n-PS

28.8a

28.6a

28.8a

29.4a

30.6b

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3.9b/3.9c Isoelectric point (IEP) Surface charge [C·m-2]d -3.2·102 45.6e Hydrophobic score

3.5b/4.5c -2.5·102 230.4e

4.1b/5.0c -0.7·102 176.0e

4.3b/4.9c -1.3·102 592.8e

< 3.0b n.d. n.d.

130 131 132 133 134 135 136 137 138 139 140 141 142

Values taken from the Viperdb2 website (accessed May 2015).44 These values were calculated from the X-ray crystallographic structures of MS2 (2MS2)45, fr (1FRS)46, GA (1GAV)47, and Qβ (1QBE)48. b. The hydrodynamic diameter of n-PS and the isoelectric points (IEP) of viruses and n-PS were determined by dynamic light scattering and electrophoretic mobility measurements, respectively, all conducted at pH 6 and I = 10 mM (adjusted with NaCl). The experimental data for n-PS is provided in Figure S1 in the SI. The mean diameter of n-PS is reported here. c,d. Estimated from the calculated surface charges of the four viruses considering only the ionizable amino-acids and the C- and N-termini that are located on the outer surfaces of the virus capsids; the surface charges were calculated for a solution with pH 6.21 e. Estimated from the areas and numbers of apolar patches on the outer surfaces of the virus capsids and by applying a hydrophobic scoring system that increases exponentially with the area of each identified apolar patch.21,49 The physicochemical properties of MS2, fr, GA, and Qβ were taken from Armanious et al (2015).21 n.d.= not determined.

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Solutions

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a.

All solutions were prepared in MilliQ water (resistivity ≈ 18.2 MΩ·cm;

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Barnstead

NANOpure

Diamond)

and

buffered

to

pH

6

using

bis(2-

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hydroxyethyl)amino-tris(hydroxymethyl)-methane. The solution pH and ionic

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strength (I) were adjusted using 1 M HCl/NaOH and NaCl, respectively.

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SRHA and SRNOM stock solutions (500 µgDOM·mL-1) were prepared by

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dissolving the respective DOM in MilliQ water, followed by pH adjustment and

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sterile filtration, as detailed in the SI. Directly before the adsorption experiments,

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aliquots of the respective DOM stock solution were ten-fold diluted in pH 6 solutions

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to final DOM concentrations of 50 µgDOM·mL-1. These solutions were used to prepare

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experimental DOM solutions that contained either only DOM as single-adsorbate or

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DOM as co-adsorbate to either one of the viruses or n-PS. The tested DOM

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concentrations varied between 0.25 and 50 µgSRHA·mL-1.

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Solutions containing one of the viruses or n-PS were prepared by diluting virus

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and n-PS stock solutions into pH 6 solutions to final concentration of ≈5·1011

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virion·mL-1 and ≈1.5·1011 nanospheres·mL-1, respectively. Virus/DOM and n-

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PS/DOM co-adsorption experiments were started immediately after adding viruses or

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n-PS to DOM-containing solutions.

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Formation of positively charged model adsorbent surface

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Amine-terminated self-assembled monolayers (SAM-NH3+) were prepared on

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the surfaces of gold-coated sensors (QSX 301, Q-Sense AB) by placing them in 0.5–

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2.0 mM ethanolic cysteamine solutions at room temperature for at least eight hours.

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Details on the formation and verification of proper SAM formation are provided in

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the SI.

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Adsorption experiments

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All adsorption experiments were conducted using a quartz crystal microbalance

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with dissipation monitoring (QCM-D) equipped with four flow-through cells (Q-

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Sense E4 system; Q-Sense AB). QCM-D monitors the changes in resonance

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frequencies (∆fn) and energy dissipation values (∆Dn) of the fundamental oscillation

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(n = 1) and several overtones (n = 3–13) of a piezo-quartz crystal that is embedded

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into each sensor upon adsorption to and desorption from the sensor surface. The

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measured frequency changes can be converted to changes in adsorbed mass using the

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Sauerbrey equation (Equation 1):

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∆ = − ×

∆

Eq. 1



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where ∆ [ng·cm-2] is the areal mass density of the wet adlayer on the sensor

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and C (= 17.7 [ng·cm-2·Hz-1]) is a sensor-specific proportionality constant. The

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Sauerbrey equation was applicable in this study because the formed adlayers were

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weakly dissipative, as evidenced from overlaying ∆fn/n traces for the different

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overtones and ∆Dn·(∆fn/n)-1 2000 ng·cm-2 in the absence of SRHA to approximately 400

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ng·cm-2 at 2.50 µgSRHA·mL-1 (Figures 2a,b). The observed effects of SRHA on

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overall adsorption were fully consistent with competitive adsorption between the

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viruses and SRHA for SAM-NH3+ surfaces and, at the same time, repulsion of MS2

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and fr from formed SRHA adlayers: the sharp transitions from initially fast to

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plateauing adsorption suggests that at the times when the transitions occurred the

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SAM-NH3+ surfaces had become jammed by the viruses and SRHA, thereby

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preventing additional adsorption. Some systems showed pronounced maxima in the

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adsorbed masses during the transitions, suggesting that a fraction of the adsorbed

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viruses were competitively displaced from the SAM-NH3+ surfaces by SRHA and,

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hence, that some of the viruses were weakly adsorbed. Weaker adsorption may have

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resulted from incomplete contact between the virus capsid and the SAM-NH3+

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surfaces (e.g., due to partial blocking by SRHA) or to orientations of the adsorbed

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viruses that resulted in a larger number of hydrophilic loops between the capsids and

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the SAM-NH3+ surfaces and hence steric repulsion.16,21

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The effects of SRHA on the adsorption profiles of GA and Qβ were distinctly

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different from the effects for MS2 and fr (Figures 2c,d). First, for a given SRHA

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concentration, the transitions from initial phases with high adsorption rates to the

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subsequent phases of lower adsorption rates were much more gradual and occurred at

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much larger adsorbed masses in the GA and Qβ than in the MS2 and fr co-adsorbate

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systems. Adsorption in the GA and Qβ co-adsorbate systems also leveled off at much

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larger final adsorbed masses. The observed effects are consistent with net attractive

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interactions of GA and Qβ with SRHA adlayers: while directly competing with

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SRHA for the SAM-NH3+ surface, Qβ and GA also adsorbed onto the surface of

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SRHA patches that formed on the SAM-NH3+ surface during the co-adsorption

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process. Adsorption onto SRHA adlayer patches is directly supported by the good

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agreements between the final adsorbed masses in the co-adsorbate systems with the

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highest SRHA concentration and in the systems in which GA and Qβ were adsorbed

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onto SRHA adlayers pre-adsorbed onto the SAM-NH3+ surfaces (Figure 1d and open

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symbols in Figure 2c,d). We note that adsorption of the viruses onto SRHA adlayers

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in the co-adsorbate systems was also apparent from changes in the viscoelastic

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properties of the adlayers, as detailed in the SI (Figure S2). The more pronounced

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decrease in final adsorbed masses of GA than Qβ with increasing SRHA

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concentrations (Figures 2c,d) is consistent with the lower affinity of GA than Qβ to

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the SRHA adlayer surfaces (Figure 1d).

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The changes in the adsorption profiles in the n-PS-SRHA co-adsorbate

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systems with increasing SRHA concentrations were comparable to those measured for 19

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MS2 and fr, consistent with direct competition of n-PS and SRHA for the SAM-NH3+

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surfaces without adsorption of n-PS onto the SRHA adlayer patches formed during

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co-adsorption. The similar co-adsorbate effects of SRHA on MS2/fr and n-PS

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adsorption strongly suggest that the co-adsorbate dynamics described herein broadly

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apply to negatively charged nanoparticles of both natural and anthropogenic origin.

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The broader applicability of the results was further supported by two sets of

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complementary experiments in which MS2 was co-adsorbed with (i) SRNOM, a

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second DOM, under the same solution conditions and (ii) SRHA at a higher ionic

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strength of I= 250 mM. As shown in Figures S3 and S4 in the SI, the effects of DOM

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on the adsorption profiles in the MS2-SRNOM systems and the MS2-SRHA systems

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at elevated I were similar to those described above in the MS2-SRHA system. Slightly

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higher final adsorbed masses in the MS2-SRHA co-adsorbate systems at I= 250 mM

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than 10 mM likely resulted from attenuation of virus-virus and virus-DOM

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electrostatic repulsion at the higher I and, as a consequence, higher surface jamming

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limits as well as slightly increased MS2 adsorption onto the SRHA adlayers. These

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results are in agreement with the slightly increased MS2 adsorption onto the SRHA

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adlayers in single-adsorbate experiments (Figure S4b).21 While not explicitly studied

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here, the competitive suppression of DOM on virus adsorption are generally expected

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to increase with increasing solution pH due to increasing net negative surface charges

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of the DOM adlayers and the viruses and hence increased virus-DOM electrostatic

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repulsion.21

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Competitive adsorption of negatively charged nanoparticles and DOM on

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positively charged sorbent surfaces also occurs in systems in which the adsorbates are

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sequentially adsorbed. To illustrate this, we pre-adsorbed different amounts of SRHA

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onto SAM-NH3+ surfaces, followed by rinsing and subsequent delivery of MS2 or n-

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PS containing solutions to the sensors. As expected, the final masses at which

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adsorption of MS2 and n-PS plateaued decreased with increasing SRHA pre-

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adsorption (Figures S5 and S6, SI).

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Modeling of competitive adsorption dynamics in MS2-SRHA co-adsorbate

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systems. In a first simplistic modeling approach, we linearly combined the single-

425

adsorbate MS2 and SRHA adsorption profiles to estimate the times at which the

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jamming limits for both adsorbates on the SAM-NH3+ surfaces were attained in the

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MS2-SRHA co-adsorbate systems. Based on the assumptions that the final adsorbed

428

masses in the co-adsorbate systems were dominated by MS2, we used the estimated

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times and the single-adsorbate MS2 adsorption profiles to estimate final adsorbed

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masses of MS2 in the co-adsorbate systems (Figure S7). This modeling approach

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resulted in overall good agreement between the predicted and experimental final

432

adsorbed masses in the co-adsorbate systems with the lower two SRHA

433

concentrations (i.e., 0.25 and 0.50 µgSRHA·mL-1) but underestimated the final adsorbed

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masses in the co-adsorbate systems with the highest SRHA concentration (i.e., 2.50

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µgSRHA·mL-1) (Figure S7). A more rigorous modeling approach was thus needed to

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predict competition dynamics in all co-adsorbate systems.

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In a second step, we developed a model based on random sequential

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adsorption (RSA) of a binary mixture of co-adsorbing spheres to obtain a concise

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picture of the spatiotemporal dynamics of SRHA and MS2 arrangements on the SAM-

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NH3+ surfaces in the co-adsorbate systems. MS2 was modeled as a rigid ‘sphere’ with

441

a diameter of d  = 28.8 nm (Table 1; Figure 3a). The model had two input

442

variables for MS2: the circular footprint area of each MS2 virion on the sorbent

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surface, parameterized by the footprint diameter, d 

444

located below adsorbed virion and defines the area over which the virion interacts

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with the SAM-NH3+ surface) and the maximum number of SRHA assemblies,

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 N  , that may be pre-adsorbed on the SAM-NH3+ surface in the footprint area of

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a virion without impairing its adsorption (Figure 3a). We varied d 

448

 and 10 nm and N  between 0 and 2.



(the footprint is centrally



between 4

449

SRHA assemblies were modeled based on two conceptual approaches (Figure

450

3a). The first approach assumed spherical SRHA assemblies in solution that

451

maintained their shape upon adsorption onto the SAM-NH3+ surfaces (i.e., the SRHA

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! spheres are ‘rigid’ and have the same diameters in solution as on the surface; d 

453

!" = d  ). While also assuming spherical SRHA assemblies in solution, the second

454

approach assumed that the assemblies partially unfolded on the SAM-NH3+ surfaces

455

! !" upon adsorption (i.e., d  ≠ d  ). The final thicknesses of SRHA adlayers

456

were 1 nm for both approaches corresponding to the experimentally determined

457

SRHA adlayer thickness at pH 6 and I= 10 mM, as detailed in the SI. For the first

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! !" approach, this meant that d  = d  = 1 nm. For the second approach,

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! d  = 2.7 nm was estimated from experimentally measured thicknesses of

460

SRHA adlayers formed on the SAM-NH3+ surfaces in separate experiments run under

461

conditions that disfavor SRHA unfolding (i.e., high I of 500 mM and high SRHA

462

concentration). The SRHA spheres were assumed to unfold on the sorbent while

463

conserving their volumes into disc-shaped circular assemblies with diameters of

464

!" d  = 3.6 nm and heights of 1 nm (Figure 3a). While the second approach makes

465

several assumptions, SRHA unfolding is supported experimentally by systematic

466

changes in single-adsorbate SRHA adsorption profiles as a function of solution I and

467

SRHA concentrations, as detailed in the SI (Figure S8). Sorbent-inducted unfolding

468

is generally well-established for polyelectrolytes and proteins on sorbent surfaces.52-57

469

We note that the two approaches to model SRHA did not only differ in the footprint

470

area of adsorbed SRHA assembly, but also in the estimated number of SRHA

471

assemblies that adsorbed per MS2 virion onto the SAM-NH3+ surface, as detailed

472

below.

473

In the model calculations, a single adsorption attempt of a MS2 sphere was

474

alternated with a defined number of adsorption attempts of SRHA spheres. The ratios

475

of attempts of MS2 to SRHA spheres for the different co-adsorbate systems were

476

estimated from the initial adsorption rates in the MS2 and SRHA single-adsorbate

477

systems using a solvation model proposed by Bingen et al (2008; Figure S9)58, as

478

detailed in the SI. Allowing for SRHA unfolding on the SAM-NH3+ surfaces largely

479

decreased the total number of SRHA spheres that co-adsorbed per MS2 virion. For 23

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example, the MS2:SRHA number ratios at the lowest experimental SRHA

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! concentration of 0.25 µgSRHA·mL-1 decreased from 1:1000 to 1:55 for d  = 1.0

482

and 2.7 nm, respectively. The positions at which individual spheres approached the

483

sorbent surface were randomly generated over a square area with side lengths of 1000

484

nm. For simplicity, we assumed purely vertical approach trajectories of the spheres to

485

the surface with no lateral movement. Adsorption attempts were unsuccessful if pre-

486

adsorbed molecules blocked the sorbent surface in the footprint area of an

487

approaching sphere (i.e., either SRHA or MS2 for approaching SRHA spheres or

488

 SRHA, at numbers larger than N  , or MS2 for approaching MS2).

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489 490 491 492 493 494 495 496 497 498

Figure 3. Predictions of surface adsorption dynamics in the co-adsorbate systems containing MS2 and Suwannee River humic acid (SRHA) using a random sequential adsorption (RSA) model for a binary mixture of spheres. (a) Model input parameters for RSA model. MS2 virions were modeled as spheres with a fixed diameter, d  . Simulations were run for different diameters of the circular footprint areas of MS2  virions on the sorbent surface, d  , and for different maximum numbers of #$$%&'( SRHA assemblies, N  , that were allowed in the circular footprint area between adsorbed virions and the adsorbent surface. Two diameters of adsorbed SRHA, !" d  , were used as input parameters for the calculations, representing two 25

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conceptual models in which SRHA assemblies either maintained their solution conformation in adsorbed states or unfolded on the surface upon adsorption. (b) Snapshots of the spatial arrangements of MS2 and SRHA on the adsorbent surfaces at the ends of selected simulation runs. The simulations were run with the specified input parameters for a total of 1000 loops (snapshots I & II) and 10000 loops (snapshots III) of sequential one MS2 and 1000 (snapshots I & II) or 55 (snapshots III) SRHA adsorption attempts. (c) Changes in the simulated fractional coverages of  #$$%&'( MS2, θ  , on the adsorbent surface as a function of d  and N  and for !" the two conceptual models assuming conformational stability (i.e., d  = 1.0 nm) !" and unfolding (i.e., d  = 3.6 nm) of SRHA on the adsorbent surface. The shaded colored bar corresponds to the experimentally estimated θ  for the simulated coadsorbate system with a concentration of SRHA of 0.25 µgSRHA·mL-1. (d) Changes in  the simulated θ  values on the adsorbent surface as a function of d  for the conceptual model assuming unfolding of SRHA on the adsorbent surface (i.e., !" d  = 3.6 nm) and for the three experimental SRHA concentrations (i.e., 0.25, 0.5, and 2.5 µgSRHA·mL-1). The corresponding experimental θ  values are shown as colored shaded bars. Good agreement between simulated and experimental  θ  values was obtained for *  of ≈ 7 to 8 nm, at all tested SRHA concentrations.

518

Figure 3b shows three snapshots I to III of a 200*200 nm area of the sorbent

499 500 501 502 503 504 505 506 507 508 509 510 511 512 513 514 515



519

surfaces at the end of selected simulations that were run with d 

520

for the lowest experimental SRHA concentration of 0.25 µgSRHA·mL-1. Snapshots I

521

!"  and II were run with d  = 1.0 nm (i.e., no SRHA unfolding). Increasing N 

522

from 0 (snapshot I) to 2 (snapshot II) increased the predicted fractional surface

523

coverages by MS2 from θ  = 0.010 to 0.031. This increase mirrors expectations of

524

decreasing SRHA-MS2 competition as the number of pre-adsorbed SRHA assemblies

525

allowed within the footprint area of adsorbing virions increases. Snapshot III was

526

!" simulated with d  = 3.6 nm (i.e., unfolding of SRHA on the sorbent) and

527

 N  = 0. The predicted θ  values were almost tenfold higher than for snapshot

528

I (i.e., θ  values of 0.094 and 0.010, respectively), reflecting decreased competition

529

in the simulations in which SRHA unfolded due to the smaller number of SRHA 26

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530

spheres that were delivered to the sorbent surface per virion. Consistently, SRHA

531

unfolding also resulted in a much lower number of adsorbed SRHA assemblies in

532

snapshot III as compared to snapshots I and II.

533



The effect of d 

on predicted θ  values is shown in Figure 3c for

534

!" simulations run with d  = 1.0 nm (no SRHA unfolding; open symbols) and 3.6

535

nm (with SRHA unfolding; closed symbols). These simulations were run for the

536

lowest tested SRHA concentration of 0.25 µgSRHA·mL-1. The shaded bar at θ  =

537

0.115±0.005 corresponds to the measured θ  value determined in the respective co-

538

adsorbate experiment, as detailed in the SI. Simulated θ  values decreased with

539

increasing d 

540

increasing footprint areas on the sorbent surface required for MS2 adsorption.

541

!" Simulations with d  = 1.0 nm resulted in much smaller predicted than

542

experimental θ  values, even at the lowest d 

543

 N  from 0 to 2 increased the predicted θ  values, they remained smaller than

544

the experimental θ  values. Conversely, the experimental θ  values were

545

!" predicted with d  = 3.7 nm and with reasonable input parameters of d 

546

 7.0 nm and N  = 0. In fact, the experimental θ  values at all three SRHA

547

concentrations (shaded bars in Figure 3d) were accurately predicted by simulations

548

!" with d  = 3.7 nm, d 

549

agreement between predicted and experimental θ  at all SRHA concentrations with

550

a single set of MS2 and SRHA footprint parameters suggests that the main processes



, reflecting increasing competition between MS2 and SRHA with



of 4 nm. While increasing





=

 between ≈ 7 and 8 nm and N  = 0. The good

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551

and dynamics of MS2-SRHA competition were accurately captured. While the

552

simulations results strongly support unfolding of SRHA upon adsorption as a key

553

process, it is important to note that other factors that are not explicitly accounted for

554

in the developed model could also affect competition dynamics. These factors include

555

the poly-dispersity of SRHA and lateral movement of the MS2 and SRHA above and

556

on the sorbent surface during the adsorption process.

557

Implications

558

This work provides direct evidence for and a mechanistic understanding of

559

competitive adsorption between negatively charged viruses and DOM onto positively

560

charged sorbent surface by combined experimental and modeling approaches.

561

Positively-charged sorbents are present both in natural systems (i.e., the surfaces of

562

iron (oxyhydr-)oxide and aluminum oxides in soils, sediments and lakes) and in

563

engineered systems (i.e., filter materials, ceramics and membranes). Based on the

564

results obtained herein, we predict that viruses that experience net repulsive

565

interactions with DOM adlayers will show largely decreased adsorption and removal

566

from solution and, thus, increased mobility in such systems in the presence of DOM

567

as co-adsorbate. These effects are expected to increase with decreasing virus/DOM

568

ratios and are thus expected to occur in most natural systems with much higher DOM

569

than virus concentrations. Conversely, we predict that the effects of competition by

570

DOM on adsorption are attenuated for viruses that experience net attractive

571

interactions with DOM adlayers and thus adsorb onto DOM adlayer surfaces that

572

form during the co-adsorption process. Predictions of virus fate and transport in

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573

systems with positively charged sorbents and DOM thus require a detailed

574

understanding of the energetics of virus-DOM interactions.

575

The RSA model developed herein accurately predicted competition in the

576

MS2-SRHA co-adsorbate systems. The modeling results suggest that unfolding of

577

DOM upon adsorption needs to be accounted for to accurately predict virus-DOM

578

surface competition. We postulate that unfolding dynamics are generally important in

579

systems that contain structurally unstable polyelectrolytes. Future studies may extend

580

on the work presented herein by experimental investigations on DOM unfolding and

581

by increasing the complexity of the proposed model, for instance by explicitly

582

accounting for DOM polydispersity and DOM unfolding dynamics, by parameterizing

583

virus-DOM interactions, and by allowing for lateral movement of the adsorbates

584

before and after adsorption.

585

Based on coherent results from co-adsorbate systems containing negatively

586

charged nanospheres and DOM, we postulate that the competitive effects described

587

herein universally apply to systems containing negatively charged nanoparticles and

588

DOM as co-adsorbates on positively charged sorbents. The nanoparticles may be both

589

natural (e.g., enzymes and proteins) and anthropogenic (e.g., quantum dots, metallic

590

nanoparticles, fullerenes, and carbon nanotubes). From a methodological perspective,

591

this work demonstrates the capabilities of in situ surface techniques to directly assess

592

competition dynamics in such systems at the molecular level.

593

Supporting Information

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594

Additional information and data on the preparation of solutions, virus

595

purification, tailoring of sensors, measuring electrophoretic mobilities and the

596

hydrodynamic diameter of n-PS, single-adsorbate and co-adsorbate experiments of

597

viruses and n-PS, and modeling of competitive adsorption of MS2/SRHA co-

598

adsorbate system. This material is available free of charge via the Internet at

599

http://pubs.acs.org/.

600

Acknowledgments We thank the Swiss National Science Foundation, SINERGIA Project

601 602

CRSI22_127568, for funding.

603

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