Olga Sambalova1,2, Kerstin Thorwarth1, Norbert Victor Heeb1, Davide Bleiner1, Yucheng Zhang1, Andreas Borgschulte1,2, Alexandra Kroll3. 1. Laboratory for Advanced Analytical Technologies, Coating Competence Center, and Electron Microscopy Centre, Empa, Ueberlandstrasse 129, 8600 Dübendorf, Switzerland. 2. Department of Chemistry, University Zürich, Winterthurerstrasse 190, 8057 Zürich, Switzerland. 3. Department of Environmental Toxicology, EAWAG, Ueberlandstrasse 133, 8600 Dübendorf, Switzerland.
Abstract
Biofilms causing medical conditions or interfering with technical applications can prove undesirably resistant to silver nanoparticle (AgNP)-based antimicrobial treatment, whereas beneficial biofilms may be adversely affected by the released silver nanoparticles. Isolated biofilm matrices can induce reduction of silver ions and stabilization of the formed nanosilver, thus altering the exposure conditions. We thus study the reduction of silver nitrate solution in model experiments under chemically defined conditions as well as in stream biofilms. Formed silver nanoparticles are characterized by state-of-the art methods. We find that isolated biopolymer fractions of biofilm organic matrix are capable of reducing ionic Ag, whereas other isolated fractions are not, meaning that biopolymer fractions contain both reducing agent and nucleation seed sites. In all of the investigated systems, we find that silver nanoparticle-biopolymer interface is dominated by carboxylate functional groups. This suggests that the mechanism of nanoparticle formation is of general nature. Moreover, we find that glucose concentration within the biofilm organic matrix correlates strongly with the nanoparticle formation rate. We propose a simple mechanistic explanation based on earlier literature and the experimental findings. The observed generality of the extracellular polymeric substance/AgNP system could be used to improve the understanding of impact of Ag+ on aqueous ecosystems, and consequently, to develop biofilm-specific medicines and bio-inspired water decontaminants.
Biofilms causing medical conditions or interfering with technical applications can prove undesirably resistant to silver nanoparticle (AgNP)-based antimicrobial treatment, whereas beneficial biofilms may be adversely affected by the released silver nanoparticles. Isolated biofilm matrices can induce reduction of silver ions and stabilization of the formed nanosilver, thus altering the exposure conditions. We thus study the reduction of silver nitrate solution in model experiments under chemically defined conditions as well as in stream biofilms. Formed silver nanoparticles are characterized by state-of-the art methods. We find that isolated biopolymer fractions of biofilm organic matrix are capable of reducing ionic Ag, whereas other isolated fractions are not, meaning that biopolymer fractions contain both reducing agent and nucleation seed sites. In all of the investigated systems, we find that silver nanoparticle-biopolymer interface is dominated by carboxylate functional groups. This suggests that the mechanism of nanoparticle formation is of general nature. Moreover, we find that glucoseconcentration within the biofilm organic matrix correlates strongly with the nanoparticle formation rate. We propose a simple mechanistic explanation based on earlier literature and the experimental findings. The observed generality of the extracellularpolymeric substance/AgNP system could be used to improve the understanding of impact of Ag+ on aqueous ecosystems, and consequently, to develop biofilm-specific medicines and bio-inspired water decontaminants.
Biofilms formed by
microorganisms are ubiquitous at natural and
anthropogenic surfaces. Biofilm-organized microorganisms can be detrimental
to the anthropogenic infrastructure (biofouling) in different health
conditions and medical applications due to superior mechanical properties,
making biofilms more resistant to removal than loosely associated
individuals.[1] Nonetheless, biofilms are
at the basis of technical applications (e.g., in wastewater treatment,
bioreactors/biofuel production[2]) and serve
essential ecosystem functions, e.g., in streams.[3,4] Stream
biofilms are primarily formed by bacteria and algae, with the specificcomposition being determined by environmentalconditions.[5] They contribute to oxygen production and nutrient
cycling, influence nearbed hydraulics, and serve as a habitat for
different life forms.[6,7] Silver ions have long been known
as potent bactericide with silver nanoparticles (AgNP) being increasingly
used as a source of Ag+ to avoid biofilm formation and
for long-term antibacterial activity. Toxic effects of Ag to microorganisms
have been reported extensively.[8] Ecologically
and technically relevant microorganisms have been assessed for their
sensitivity to Ag. For instance, in the algaeChlamydomonas
reinhardtii, carbonate-stabilized AgNP decrease growth
and photosynthetic activity more than Ag+.[9] In stream biofilms, AgNP exerts antimicrobial effects stronger
than or similar to Ag+.[10] The
integrity of biofilms is mediated by an extracellular organic matrix
containing extracellularpolymeric substances (EPS) like polysaccharides,
glycoproteins, low-molecular-weight acids (LMWA), and neutral/amphiphiliccompounds.[11,12] EPS act as the first line of
contact to Ag. Escherichia coli, bacteria
in activated sludge and marine diatoms showed an increase in EPS production
when exposed to AgNP.[13−15] EPS may fundamentally alter the exposure to bactericidal
Ag by reducing Ag+ to AgNP and stabilizing the latter within
its matrix, as shown with EPS from heterotrophic bacteria and stream
biofilms.[16−18] The mechanism of interaction of AgNP with EPS and
thus its potential specificity are unknown. We argue that knowledge
on this interaction is needed to better understand the potential adverse
environmental effects of Ag and develop targeted anti-biofilm compounds.Operando analysis of such interface reactions
in aqueous solutions is a great challenge. This is the result of the
thick layers of molecules that usually surround the atomically thin
interface. The probe beam must be capable of penetrating the surrounding
layers, i.e., without strong interaction with the material of this
layer, but still be sensitive enough to obtain information on the
interface. Furthermore, most surface science techniques require high
vacuum.[19] Optical spectroscopy can provide
information about the systems in an aqueous environment.[20,21] However, the challenge of confining the signal to the atomic interface
between covering layer and Ag surface remains. To overcome this challenge,
resonance methods are applicable, such as surface-enhanced Raman spectroscopy
(SERS). The Raman excitation from the molecules attached to the Ag
surface is greatly enhanced as the result of a stronger electric field
present directly at the NP surface, due to the resonant coupling of
the conduction band electrons to the incident laser light (surface
Plasmon resonance).[22,23] The enhancement is a local phenomenon
and decays drastically within a few angstroms into the bulk and the
medium.[22,24] SERS is thus a local probe of the molecules
in the direct vicinity of the AgNP surface.Our approach consisted
of characterization of AgNP formation in
the presence of a model polysaccharide and EPS extracted from natural
biofilms with and without the commonly bioavailable reducing agents
with UV–vis spectroscopy, dynamic light scattering (DLS), and
NP tracking analysis (NTA). Characterization of functional groups
interacting with AgNP was conducted using surface-enhanced Raman spectroscopy
(SERS). Also, the oxidation state of formed nanosilver was probed
with UV–vis spectroscopy, X-ray photoelectron spectroscopy
(XPS), and transition electron microscopy (TEM).
Results and Discussion
We develop a hypothesis of reaction mechanisms facilitating the
AgNP formation and subsequent stabilization within the EPS matrix
of stream biofilms (Scheme ) based on the earlier knowledge of aldehyde-facilitated reduction
of Ag+ and other transition metal ions,[26−30] as well as multifactorial AgNP/EPS system bulk and
interface analysis as described below. In general, chemically facilitated
formation of nanosilver from Ag salts requires a reducing agent and
a nucleation seed site.[31,32] Within the EPS matrix,
the role of the latter could be played by the largest constituent—polysaccharides,[33,34] whereas terminating sugars and saccharide monomers could act as
reducing agents.[35,36] Other biopolymers (BPs), such
as collagen,[37,38] chitosan,[33] and poly(vinylpyrrolidone) (PVP),[39] have previously been used as stabilizing agents for AgNPs. A range
of reducing agents have similarly been reported, e.g., sodium borohydride
(NaBH4),[40]N,N-dimethylformamaide,[41] and glucose.[35] Therefore, for the model
system, we concentrated on the EPS matrix components that could represent
the reducing agent and nucleation seed site system. The reaction under
investigation consists of AgNO3 in presence of one of the
following monosaccharides, which act as reducing agents: β-d-glucose (Glc), β-d-glucuronic acid (GlcA),
and N-acetyl-d-glucosamine (NAG), whereas
starch is used as the model seed site and stabilizing agent.[25]
Scheme 1
Simplified Reaction Mechanism of Ag+ Reduction with Glc
(A) Used as Reducing Agent[26,28−30] alongside the Reduction Potential of the Reaction[43,44] and Proposed Reaction Mechanisms with GlcA (B) and NAG (C) instead
of Glc, Explaining the Observed Relative Reaction Rates: Glc >
NAG
> GlcA
The latter triggers no NP formation.
Simplified Reaction Mechanism of Ag+ Reduction with Glc
(A) Used as Reducing Agent[26,28−30] alongside the Reduction Potential of the Reaction[43,44] and Proposed Reaction Mechanisms with GlcA (B) and NAG (C) instead
of Glc, Explaining the Observed Relative Reaction Rates: Glc >
NAG
> GlcA
The latter triggers no NP formation.In the absence of starch, no NP formation is
detected, signifying
that polysaccharidesare indispensable for NP formation. For spherical
Ag nanoparticles, the plasmon absorption is centered at around 400
nm,[42] which is in agreement with the obtained
UV–vis spectra (Figure A). In particular, the latter shows that Glc leads to fastest
growth rate of AgNPs, resulting also in larger NPs than if other reducing
sugarsare used. These results are supported by NTA and DLS (Table S4, SI). The second fastest NP formation
rate is observed with NAG, whereas GlcA deactivates the process of
Ag+ reduction and no AgNP formation is observed (Figure A).
Figure 1
A: Representative UV–vis
spectra of AgNO3 in
the presence of starch, with one of the following reducing sugars:
Glc (black), NAG (red), GlcA (blue), and no sugar (pink). Samples
were taken after 2 h of reaction. The peaks at 412 and 424 nm are
characteristic of nanosilver surface plasmon resonance effect.[59] AgNP concentration contributes to the absorbance
intensity, whereas NPs’ core sizes refer to both the absorbance
intensity and the nanoparticle size.[59] Thus,
Glc resulted in a higher rate of nanoparticle formation than NAG,
whereas GlcA and no reducing sugar lead to no nanoparticle formation.
B: TEM image of AgNP embedded in the field EPS matrix. The nanosilver
atoms are distinguishable; however, the organic matrix atoms are nonidentifiable.
This image is representative for AgNPs imbedded in EPS matrix and
starch.
A: Representative UV–vis
spectra of AgNO3 in
the presence of starch, with one of the following reducing sugars:
Glc (black), NAG (red), GlcA (blue), and no sugar (pink). Samples
were taken after 2 h of reaction. The peaks at 412 and 424 nm are
characteristic of nanosilver surface plasmon resonance effect.[59] AgNPconcentration contributes to the absorbance
intensity, whereas NPs’ core sizes refer to both the absorbance
intensity and the nanoparticle size.[59] Thus,
Glc resulted in a higher rate of nanoparticle formation than NAG,
whereas GlcA and no reducing sugar lead to no nanoparticle formation.
B: TEM image of AgNP embedded in the field EPS matrix. The nanosilver
atoms are distinguishable; however, the organic matrix atoms are nonidentifiable.
This image is representative for AgNPs imbedded in EPS matrix and
starch.To develop a hypothesis of the
Ag+ reduction mechanism,
we consider our observations described further and the published mechanism
of aldehyde oxidation[26−30] (Scheme A). Glc
is a known reducing sugar and capable of reducing Ag+ to
Ag0 with the overall standard reduction potential of E0 = +0.75 V (vs SHE).[43,44] The simplified reaction mechanism is presented in Scheme A.[26−28] Briefly, anomericcarbon of the Glc is oxidized to form carboxylic acid, whereas Ag+ is reduced to Ag0, which is the first step of
a NP growth process.[45] The process then
involves nucleation of the new crystals and crystal growth via agglomeration
or monomer addition to form AgNP.[43] The
final step involves passivation of the capping agents. It is likely
that the Ag+ reduction step proceeds via radical formation[46] and, indeed, light is indispensable for AgNP
formation at the given reactant concentrations. However, for the sake
of simplicity, we ignore the multitude of intermediate steps, as further
experimental evidence would need to be provided to draw concrete conclusions.GlcA (Scheme B),
though structurally similar to Glc (Scheme A), has a carboxylic acid functional group
instead of a hydroxyl group on C6. We hypothesize that the absence
of AgNP formation may be due to the intramolecular reaction, which
results in a loss of the anomericcenter, and therefore the reducing
ability, of GlcA (Scheme B).NAG reduces Ag+, however, with hindered
reduction rates
compared to the reduction with Glc. This could be explained by an
intramolecular process (Scheme C) in which the doubly ringed compound is formed by the reaction
of amide functional group on C2 with the C1 of the sugar. However,
the formed complex bears a positive charge and therefore is prone
to opening, after which a redox reaction may follow, alike the intermolecular
reaction path with Glc (Scheme A).The reducing sugars used in the model experiments
are representative
of the saccharides commonly found in the extracellularpolymeric substance
(EPS) of benthic biofilms.[47,48] To establish the relevance
of the model to the environmental samples, in situ nanosilver formation facilitated by the EPS extracted from biofilms
colonized in river Chriesbach, Switzerland, and collected from 12
different field sites (Figure B; Table S1, SI) is examined. Three
replicas from each site are taken (noted later as A, B, and C). Liquid
chromatography–organiccarbon detection–organicnitrogen
detection (LC–OCD–OND) analysis identifies the similarity
of most biological replicas illustrating homogeneity along the stream
(Figures S1 and S2, Table S3, SI). In the presence of 3.5 mM AgNO3,
21 out of 36 EPS samples trigger the formation of AgNP within 12 days
(Table S5, SI).
Figure 3
A: Graph representing
dependence of AgNP formation reaction rate
on the concentration of glucose within the EPS matrix. Number refers
to collection site (B), whereas letters A–C denote three different
samples collected at each site. With the exception of samples 3A and
3C, a higher glucose concentration resulted in a higher rate of NP
formation. B: Map illustrating the 12 sampling sites (6 up- and 6
downstream from wastewater treatment plant; noted by numbers 1–12)
used for the collection of stream biofilms. Three samples per site
were collected (noted as A, B, and C).
To identify the components
essential to AgNP formation, the EPS
samples are fractionated into biopolymers (BP), building blocks (BB)
of humic acids, low-molecular-weight acids (LMWA), and neutral/amphiphilic
(NA) compounds (Figure ), and each fraction is reacted separately with AgNO3.[12] It was found that the isolated biopolymer fraction
is capable of reducing ionic Ag, whereas other isolated fractions
are not, indicating that biopolymers within the EPS play a crucial
role in the reduction process and must contain both the nucleation
seed site, possibly relatively bulky polysaccharides, and the reducing
agent, possibly the terminating sugars of the polysaccharidechains.
Figure 2
Characteristic
LC–OCD–OND spectrum of EPS extracted
from field biofilm samples. Peaks represent different fractions of
EPS: biopolymers, building blocks of humic acids, low-molecular-weight
acids, and neutral compounds.[12]
Characteristic
LC–OCD–OND spectrum of EPS extracted
from field biofilm samples. Peaks represent different fractions of
EPS: biopolymers, building blocks of humic acids, low-molecular-weight
acids, and neutral compounds.[12]Based on the model study, we hypothesize that within
the biopolymer
fraction, Glccould be the driving reductant. Quantification of Glc
in the EPS samples results in measured concentrations of 1.572–151.5
μM (Table S5, SI), which are 2–4
orders of magnitude lower than the concentration used in the model
study (10.6 mM). However, a glucose assay indicates a clearcorrelation
between the NP formation rate and concentration of the glucose in
the EPS (Figure A; Table S5, SI). The other parameters, such as Cl– concentration
(Table S2, SI), do not seem to have a significant
effect. Ten EPS samples that trigger AgNP formation within 4 or 8
days contain detectable amounts of Glc, whereas nine samples with
AgNP formation after 12 days do not contain Glc above the detection
limit (0.156 μM) (Figure A; Table S5, SI). The highest detected
Glcconcentrations coincide with a reaction within 4 days (91.3 and
151.5 μM Glc). Exceptions are samples A and C taken from site
3, which trigger NP formation after 8 days but do not contain detectable
Glc. These stand out neither regarding EPS concentration of fractions
and protein nor regarding measured species composition (Table S3, SI). We conclude that Glc probably
is the main reducing agent in all of the AgNP-positive samples except
those taken from site 3, which probably contain other low-molecular-weight
reductants or reducing functional groups.A: Graph representing
dependence of AgNP formation reaction rate
on the concentration of glucose within the EPS matrix. Number refers
to collection site (B), whereas letters A–C denote three different
samples collected at each site. With the exception of samples 3A and
3C, a higher glucoseconcentration resulted in a higher rate of NP
formation. B: Map illustrating the 12 sampling sites (6 up- and 6
downstream from wastewater treatment plant; noted by numbers 1–12)
used for the collection of stream biofilms. Three samples per site
were collected (noted as A, B, and C).It is known that the specificity of the reducing and stabilizing
agents will affect the nanoparticle size, polydispersity, and surface
charge.[49,50] These parameters were taken into account
via the analysis by NTA, DLS, and TEM. The results show that the formed
NPs are in the size range of 60–200 nm (Table S4, SI) with the zeta-potential (ZP) values ranging
from −22 to −30 mV (Table S4, SI), though TEM imaging allows for the identification of smaller NPs
also (<10 nm; Figure S5C–E, SI). These results are in agreement with the previously reported systems.[46,51] However, although these factors are useful for describing variability
between the systems, they carry no information on the redox reaction
taking place at the AgNP–EPS interface. Therefore, there is
a need for surface-sensitive techniques to further understand the
systems on a molecular scale.Surface-enhanced Raman spectroscopy
(SERS) is a local probe of
the molecules in the direct vicinity of a AgNP surface.[52] The SERS spectra of starch/Glc/AgNPcomplex
(model system) and all of the field and colonized EPS/AgNPcomplexes
show two prominent peaks at 1361 and 1572 cm–1 (Figure ), which are not
present in the absence of AgNP. The degree of enhancement is especially
evident when considering the CH stretching peak of starch at 2911
cm–1, which is prominent in starch in the absence
of AgNP, but negligible compared to the peaks at 1361 and 1572 cm–1 (Figure ). The latter are assigned as the symmetric
and asymmetric stretching of the carboxylate functional groups, respectively.[36] The assignment is further confirmed against
the commercially available citrate and carbonateAgNP, which are known
to stabilize AgNP via carboxylate functional groups. The SERS spectra
of these complexes show the same two strong peaks at 1361 and 1572
cm–1 (Figure S4, SI).
The exclusive enhancement of the COO– vibrations
by the surface plasmons is in agreement with a binding of one or even
two oxygen atoms of a carboxylate group to Ag.[53] Thus, metallicAgNP is surrounded primarily by the carboxylate
functional groups of the EPS matrix. This was found to be true regardless
of the EPS fractional composition, which is analyzed by LC–OCD–OND
(Table S3, SI). It is well known that AgNPs
can be stabilized by the carboxylic acid groups of yeast[54] and other biomolecules.[50] However, the general selectivity of stabilizing groups observed
for all of the EPS may be surprising. The general presence of carboxylate
groups at the AgNP surface could be explained by considering the redox
process of NP formation, where the reducing sugar is oxidized to form
carboxylate functional groups, which then stabilize the NP.
Figure 4
SERS spectra
of starch (cyan) and AgNP stabilized by citrate (red),
field EPS (blue), starch/Glc (black), and colonized EPS (green) systems.
The starch peak at 2911 cm–1 (assigned as CH stretching
vibrations) can be used as a reference: in the presence of AgNP (starch/Glc)
system, the intensity of otherwise prominent CH peak is negligible
compared to highly amplified signals at 1362 and 1573 cm–1 (assigned as COO– stretching vibrations).[36] The amplification of the signal is due to the
SERS effect, signifying close proximity of the COO– functional groups to the AgNP surface. The prominent amplification
of the COO– groups is also observed in AgNP stabilized
by citrate (known to be stabilized by COO–; used
as reference), as well as colonized and field EPS. This suggests that
EPS supports the formed NP primarily by COO– functional
groups.
SERS spectra
of starch (cyan) and AgNP stabilized by citrate (red),
field EPS (blue), starch/Glc (black), and colonized EPS (green) systems.
The starch peak at 2911 cm–1 (assigned as CH stretching
vibrations) can be used as a reference: in the presence of AgNP (starch/Glc)
system, the intensity of otherwise prominent CH peak is negligible
compared to highly amplified signals at 1362 and 1573 cm–1 (assigned as COO– stretching vibrations).[36] The amplification of the signal is due to the
SERS effect, signifying close proximity of the COO– functional groups to the AgNP surface. The prominent amplification
of the COO– groups is also observed in AgNP stabilized
by citrate (known to be stabilized by COO–; used
as reference), as well as colonized and field EPS. This suggests that
EPS supports the formed NP primarily by COO– functional
groups.The EPS/AgNP as well as model
samples has the characteristic yellow
color from plasmon absorbance, which is indicative of nonoxidized
silver surface.[46,51] However, it is well known that
AgNPs in aqueous environment are unstable due to agglomeration and
surface oxidation of the particles.[36,55,56] To further characterize the Ag surface and especially
probe the oxidation state of the silver, we utilize the X-ray photoelectron
spectroscopy (XPS) (Figure ) and electron diffraction (Figure S5B, SI). The XPS spectrum allows identification of Ag, C, O, N,
Na, and Ca atoms present in the EPS/AgNP samples (Figure ). The Ag 3d5/2 peak
at 368 eV is characteristic of nonoxidized Ag.[57] However, due to the broadness of the peak, no definite
conclusion can be drawn and the peak may consist of multiple overlapping
peaks.[57] In addition, electron diffraction
identifies Ag(111) and Ag(002) facets, which are characteristic of
nonoxidized Ag (Figure S5B, SI). Yet, both
methods cannot exclude the existence of an oxidized silver surface,
which is likely under these conditions. However, this does not undermine
the SERS effect. It has been observed that intentionally oxidized
Ag enhances the SERS effect compared to metallic Ag, which is explained
by a stronger binding of the exciting molecules to an activated, i.e.,
oxidized, surface.[58]
Figure 5
Representative X-ray
photoelectron spectroscopy spectrum of AgNP
embedded in the EPS matrix extracted from field biofilm samples after
sputtering. The inset shows the enlargement of the Ag 3d region. The
pristine sample is depicted in red, whereas the sputtered is shown
in black. The peak at 368 eV is characteristic of metallic Ag, though
the spectrum does not exclude the possibility of oxide layer on the
surface, as the peak at 386 eV may consist of multiple overlapping
signals.[57] Apart from Ag, the elements
that are clearly identified by XPS are Na, C, O, and N.
Representative X-ray
photoelectron spectroscopy spectrum of AgNP
embedded in the EPS matrix extracted from field biofilm samples after
sputtering. The inset shows the enlargement of the Ag 3d region. The
pristine sample is depicted in red, whereas the sputtered is shown
in black. The peak at 368 eV is characteristic of metallic Ag, though
the spectrum does not exclude the possibility of oxide layer on the
surface, as the peak at 386 eV may consist of multiple overlapping
signals.[57] Apart from Ag, the elements
that are clearly identified by XPS are Na, C, O, and N.The EPS/AgNP system is also studied by Fourier
transform infrared
(FTIR) (Figure S6, SI). Among others, the
carboxylate peaks are clearly visible on the obtained spectra; however,
the EPS without AgNPs also displays carboxylate peaks (1395 and 1653
cm–1), and no conclusive information on the interface
can be drawn from the method.
Conclusions
We studied the redox
reaction of Ag nanoparticle formation and
stabilization within EPS matrices extracted from benthic biofilms.
We present the evidence that both reducing agent and nucleation seed
site, possibly polysaccharides,[31] are found
within the biopolymer fraction of EPS. Moreover, there is a clearcorrelation between the glucoseconcentration within the EPS and the
Ag nanoparticle formation rate, as determined by UV–vis, NTA,
and DLS. This suggests that glucose is a crucial reducing agent within
the EPS. Another commonly bioavailable sugar, N-acetyl
glucosamine (NAG), could also play a role in the redox process, whereas
glucuronic acid showed no evidence of nanoparticle formation, as demonstrated
by a model study with starch as the stabilizing polysaccharide. From
an environmental perspective, we conclude that the resulting exposure
of microorganisms to AgNP depends on the chemical and structural composition
of the EPS. The interface of the formed NPs was characterized by SERS,
and the presence of carboxylate functional groups at the NP surface
was found to be perpetual for all of the EPS/AgNP systems. The generality
of the interaction and the applicability of SERS method for interface
analysis of AgNP in a complex biological environment is thus demonstrated.
Based on these findings as well as earlier literature,[26−30] we present a hypothesis for plausible redox mechanism of EPS-facilitated
reduction of ionic silver. The mechanism is based on the oxidation
of aldehyde groups at the anomericcarbon of reducing sugar monomers
to carboxylic acid groups. The latter then stabilize the surface of
the formed Ag0, which could explain the apparently omnipresent
carboxylate functionalization of Ag surface in the EPS/AgNP mixture.The observed generality of the EPS/AgNP system could be used to
improve the understanding of specific responses of microorganisms
to Ag based on their EPS composition, and consequently, to develop
biofilm-specific medicines and bio-inspired water decontaminants.
Thus, this study suggests that Ag ions can be used to eliminate harmful
bacteria, if the EPS-mediated NP formation and stabilization via carboxylic
acid groups is disrupted. This method would be making use of bactericidal
properties of Ag ions, which are, however, harmless to mammaliancells.
The same effect could also be industrially applicable for, e.g., removing
biofilm formation on ship hulls or inside the water pipes. On the
other hand, Ag ions can be efficiently trapped in the artificial or
biological polymer matrix with a high number of carboxylic acid terminated
surface functional groups. This could be useful in, e.g., wastewater
treatment for achieving minimum environmental disturbance of the aquatic
ecosystems.
Materials and Methods
Chemicals
All of the chemicals were
purchased from
Sigma-Aldrich if not stated specifically below. Nanopure water (18.1
MΩ·cm, Milli-Q) was used as a solvent.Silver nanoparticles
with a nominal primary particle size of 25 nm were produced by wet
precipitation from AgNO3 in the presence of carbonate or
citric acid by NanoSys GmbH (Wolfhalden, Switzerland) as an aqueous
suspension with a nominal concentration of 1 g/L (9.27 mM) Ag. The
original suspension was kept in the dark.All of the nanoparticles
were formed under irradiated conditions
(light spectrum mimicking the sunlight spectrum). In the absence of
light, no nanoparticle formation was observed on the chosen timeframe
at the given concentrations. Blank experiments without the EPS yield
no nanosilver, as well as not all of the EPS samples will trigger
a nanoparticle formation, suggesting that the chemical composition
of the EPS is of crucial importance for nanoparticle formation and
stabilization.
Synthesis of EPS Stabilized Ag Nanoparticles
All of
the silver nanoparticles were formed in situ in the UV–vis
exposure system by the EPS extracted from periphyton. The UV–vis
exposure system was constructed with a thermostat (Lauda RC6 RC),
control stirrer module (H & P Labortechnik Variomag Telemodul
40-S), and a set of lamps (Philips Master TL5 HO 54W/865 SLV/40).
The conditions used for nanoparticle synthesis were as follows: temperature
20 °C, stirring 200 rpm, and light irradiation matching sunlight
spectrum.
Silver Film Preparation
The samples were prepared using
unbalanced direct current magnetron sputter deposition from an elemental
Ag target with a purity of 5N in a UHV system at room temperature.
The deposition chamber used is an ATC 1500 F sputtering system from
AJA international Inc. (North Scituate, MA). The base pressure before
deposition was <5 × 10–7 Pa; during deposition,
the pressure was kept at 5.4 Pa using a constant Ar flow of 16 sccm.
Silver was sputtered at a power density of 5.0 W/cm2. Before
deposition, the samples were cleaned using a radio frequency bias
on the substrate of −250 V in flowing Ar (15 sccm) at a pressure
of 0.5 Pa. The samples were grown to a thickness of 200 nm, as determined
using a Bruker Dektak XT surface profilometer equipped with a diamond
stylus.
Colonization of Stream Biofilms on Artificial Substrates and
Sampling of Biofilms
Biofilms were colonized on glass microscope
slides (38 × 26 mm2, Thermo Scientific) which were
placed vertically in river Chriesbach for 21 days (Dübendorf,
Switzerland, 47°24′16.8″N, 8°36′41.0″E).
For the extraction of extracellularpolymeric substances, the biofilms
were scraped off the glass slides with a clean glass slide into 1
mL/slide NaHCO3 (2 mM, pH 7.6) in a glass beaker. The extracellularpolymeric substances were extracted on the same day (see below).
Field Sampling of Stream Biofilms
The samples were
taken on November 5 and 6, 2015, from six rivers in the Swiss Plateau
upstream and downstream communal wastewater treatment plants (sites
1–12, Table S1 of SI, Figure B). Three stones of similar
size from similar microenvironments in the river bed were selected
at each sampling site. The biofilms were brushed off the stones with
tooth brushes into 15 mL of stream water, which was sampled at the
site and filtered through two layers of paper towel. The stones were
washed with another 15 mL of filtered stream water. The extraction
of extracellularpolymeric substances was performed on the same day
(see below).
Water Analytics
At each field sampling
site, spot measures
of physical parameters were taken roughly at the same distance above
ground as the surfaces of the stones sampled. The water temperature
was measured with a DIEHL frigoton thermometer and flow velocity with
a Schiltknecht MiniAir2 Micro anemometer (flow accuracy 1.0% fs, 3.0%
rdg).Waterchemistry of the grab samples (500 mL) taken from
each sampling site and of the extracted EPS (see below) was determined
as follows: Na+, K+, Ca2+, Mg2+, NO32–, SO42–, and Cl– content was quantified
by ion chromatography (Metrohm 761 Compact IC, with chemical suppression
for NO32–, SO42–, and Cl–), with a 8 mM HNO3/1.197 mM
dipicolinic acid solution as the mobile phase and a Metrosep C 6 –
250/4.0 separation column (Metrohm, Na+, K+,
Ca2+, and Mg2+) or a Metrosep A Supp 5 100/4
mm column (Metrohm, NO32–, SO42–, and Cl–) as the stationary
phase. PO43– was quantified colorimetrically
(Varian Cary 50 Bio Spectrophotometer) based on the formation of molybdenum
blue. Silica was determined colorimetrically based on the reduction
of siliciomolybdate to silicomolybdous acid in the presence of ascorbic
acid using the Autoanalyzer AA3, Bran + Luebbe (Contrec). TOC and
DOC were measured with a shimadzu TOC-L CSH system. LOQ were 2.5 mg/L
Na+, 1 mg/L K+, 5 mg/L Ca2+, 2.5
mg/L Mg2+, 0.5 mg/L NO32–,
5 mg/L SO42–, 0.5 mg/L Cl–, 1 mg/L H4SiO4, and 0.5 mg/L OC.Metalconcentrations were determined by inductively coupled plasma
mass spectrometry (ICP-MS) after microwave digestion. 0.5 mL of each
sample was digested with 4 mL of 65% HNO3 and 0.5 mL of
30% H2O2 in a microwave digestion unit (MLS
ultraClave 4; 10 min at 180 °C/100 bar, 14 min at 210 °C/100
bar) and diluted 1:100 with nanopure water (18.1 MΩ·cm,
Milli-Q). One sample per run contained only HNO3 and H2O2 to determine the background concentration of
target metals.The target metalconcentrations were measured
by HR-ICP-MS (Element
2 High Resolution Sector Field ICP-MS; Thermo Finnigan). The instrument
was calibrated with a multielement mass standard (Merck, 1113550100).
The calibration curve for data analysis was made with the calibration
standard Merck IV in the concentration range 0–20 μg/L.
A reference with a concentration within the calibration range was
measured every 10 samples, the calibration samples were measured every
40 samples.
Extraction, Characterization, and Fractionation
of Extracellular
Polymeric Substances (EPS) from Periphyton
The extraction
procedure was performed as described previously.[5,9,25] The biomass was resuspended by gentle pipetting
and sonication in a water bath (45 kHz, 60 W, VWR UltrasonicCleaner)
for 30 s. Fine sediment and larger biomass was allowed to settle for
∼1 min, the supernatant was removed and centrifuged at 1880g for 10 min. Biomass was resuspended a second time in 2
mL/slide fresh solution and treated as described above. All of the
supernatants were sequentially filtered (1 μm glass fiber [VWR],
0.45 μm polypropylene [PALL], and 0.22 μm PES [Millipore]
filters). The filters were washed with nanopure water (18.1 MΩ·cm,
Milli-Q) before use. EPS extracts were stored in glass bottles at
4 °C (0.02% (w/v) NaN3). All of the extraction steps
were performed on ice, and the water bath for ultrasound treatment
was at room temperature.Organiccarbon and nitrogen size distribution
was measured by size-exclusion chromatography–organiccarbon
detection–organicnitrogen detection (LC–OCD–OND)
as described previously.[5,9] The samples were diluted
with nanopure water (18.1 MΩ·cm, Milli-Q) right before
they were measured. A size exclusion column (250 × 20 mm2, Toyopearl TSK HW-50S) was used to separate the EPS compounds.
The mobile phase was phosphate buffer (24 mM, pH 6.6), and the acidification
solution was phosphoric acid (60 mM, pH 1.2). The detection limit
was 10 μg/L for both OC and ON. The software FIFFIKUS was used
to quantify the total organiccarbon (TOC), dissolved (DOC), and chromatographable
DOCcompounds (cDOC). The chromatograms obtained from LC–OCD–OND
were integrated to determine the amount of biopolymers (BP, high Mr polysaccharides, and proteins), building blocks
of humic substances (BB), low Mr acids
(LMWA), and amphiphilic/neutral compounds (NA, alcohols, aldehydes,
amino acids, and ketones).To separate the fractions BP, BB,
LMWA, and NA, a Bio-Rad 2110
fractionator coupled to the LC–OCD–OND system was employed.
Fractions were taken between retention times of 30–45 min (BP),
45–49 min (BB), 49–57 min (LMWA), and 57–80 min
(NA).
Nanoparticle Tracking Analysis (NTA)
Nanoparticle tracking
analysis (NTA, NanoSight LM10 equipped with a LM14 temperature controller
(NanoSight Ltd.)) was used to determine a number-based particle size
distribution. Each sample was directly measured three times for 60
s. All of the NTA videos were analyzed with the same settings in batch
processing mode. Analyses that resulted in less than 200 tracked particles
were not used. Videos were analyzed using the NanoSight NTA 2.3 Analytical
Software (NanoSight Ltd.). Settings were as follows: background extract:
on; brightness: 0; gain: 1; blur size: 9 × 9; detection threshold
type: single; detection threshold: 15; min track lenth: 10; min expected
size: auto; temperature: 23 °C; and viscosity: 0.9326.
Dynamic
Light Scattering (DLS) and Zeta-Potential (ZP)
Dynamic light
scattering (DLS) and zeta-potential (ZP) were measured
with a Malvern Instruments Nano ZS in polystyrenecuvettes. Each sample
was measured at the temperature of 25 °C three times and the
autocorrelation function was analyzed using the cumulant analysis
algorithm resulting in a mean size (z-average) and
a standard deviation (polydispersity index). The DLS measurements
performed on aqueous suspension containing EPS did not indicate any
particles.
UV–vis Absorption Spectra
UV–vis light
absorption (190–900 nm) was recorded with a CARY 100 UV–vis
spectrophotometer (Agilent Technologies) in microquartz cuvettes.
AgNP show size- and surface-specific surface plasmon resonance, which
results in a specific UV–vis absorption spectrum. The spectra
were recorded in a solution with an optical path length of 10 mm.
Surface-Enhanced Raman Spectroscopy (SERS)
Raman spectra
were recorded with a Bruker SENTERRA Raman microscope with 532 nm
20 mW laser and 10× objective lens. Each sample was measured
on glass slides for 180 s.
Fourier Transform Infrared Spectroscopy (FTIR)
Infrared
spectra were measured in solid state with a Cary 600 Series ATR-FTIR
Spectrometer (Agilent Technologies). The average of 32 measurements
was taken.
Transmission Electron Microscopy (TEM)
Transmission
electron microscopy (TEM) samples were prepared by casting one drop
of the solution directly onto copper grids (TedPella, product number:
11824) with the carbon lacey network covered with a ∼3 nm thin
carbon film. High-resolution TEM (HR-TEM) and selected area electron
diffraction (SAED) were performed on a JEOL 2200FS microscope operated
at 200 kV. Typically, 0.5 s exposure time was used for recording the
HR-TEM images. No morphological change in the particles caused by
the electron beam was observed during imaging and diffraction. An
analysis of the images and diffraction patterns was performed using
a DigitalMicrograph.
X-ray Photoelectron Spectroscopy (XPS)
The samples
were characterized by X-ray photoelectron spectroscopy (XPS) using
a Quantum 2000 (Physical Electronics Inc.) instrument under ultrahigh
vacuum (<5 × 10–7 Pa). Monochromatic Al
Kα X-rays with a photon energy hν = 1486.7
eV were used, and the data were recorded at an analyzer pass energy
of 23.50 eV and a step size of 0.1 eV (for the detailed spectra) and
a pass energy of 58.70 eV and a step size of 0.5 eV for the survey.
Argon ions and electron neutralizers were used to compensate for surface
charging.The data were collected with (∼2 nm removed) and without
sputter-cleaning to eliminate contaminations. The XPS background spectrum
was checked with a CasaXPS software and found to be linear for the
region of interest (365–375 eV).
Glucose Assay
Glucoseconcentration of extracted EPS
samples was determined with a High Sensitivity Glucose Assay Kit (Sigma-Aldrich,
MAK181) according to the procedure described by the manufacturer.
In the presence of glucose, a fluorometric product is formed proportional
to the glucoseconcentration. Of each sample, 1 and 10 μL were
reacted in duplicate with the reaction mix in a final volume of 100
μL in 96-well plates. Fluorescence was measured with a Tecan
plate reader (excitation: 535 nm, emission: 587 nm). Standard deviation
of blanks was 0.0518 pmol/μL, detection limit was thus in the
range of 0.156 pmol/μL. Spiking extracted EPS with glucose showed
no interference with the assay above the detection limit.
Authors: E I Alarcon; B Vulesevic; A Argawal; A Ross; P Bejjani; J Podrebarac; R Ravichandran; J Phopase; E J Suuronen; M Griffith Journal: Nanoscale Date: 2016-03-28 Impact factor: 7.790
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