Effects of silver nanoparticles on microbial growth dynamics

Authors


Correspondence

Michael Bunge, Institute of Applied Microbiology, Research Center for BioSystems, Land Use, and Nutrition (IFZ), Justus Liebig University of Giessen, Heinrich-Buff-Ring 26-32, 35392 Giessen, Germany. E-mail: michael.bunge@umwelt.uni-giessen.de

Abstract

Aims

Engineered metal nanoparticles are increasingly used in consumer products, in part as additives that exhibit advantageous antimicrobial properties. Conventional nanoparticle susceptibility testing is based largely on determination of nontemporal growth profiles such as measurements of inhibition zones in common agar diffusion tests, counting of colony-forming units, or endpoint or regular-interval growth determination via optical density measurements. For better evaluation of the dynamic effects from exposure to nanoparticles, a cultivation-based assay was established in a 96-well format and adapted for time-resolved testing of the effects of nanoparticles on micro-organisms.

Methods and Results

The modified assay allowed simultaneous cultivation and on-line analysis of microbial growth inhibition. The automated high-throughput assay combined continuous monitoring of microbial growth with the analysis of many replicates and was applied to Cupriavidus necator H16 test organisms to study the antimicrobial effects of spherical silver [Ag(0)] nanoparticles (primary particle size distribution D90 < 15 nm). Ag(0) concentrations above 80 μg ml−1 resulted in complete and irreversible inhibition of microbial growth, whereas extended lag phases and partial growth inhibition were observed at Ag(0) concentrations between 20 and 80 μg ml−1. Addition of Ag(0) nanoparticles at different growth stages led to either complete inhibition (addition of 40 μg ml−1 Ag(0) from 0 h to 6 h) or resulted in full recovery (40 μg ml−1 Ag(0) addition ≥9 h).

Conclusions

Contrary to the expected results, our data indicate growth stimulation of Cnecator at certain Ag(0) nanoparticle concentrations, as well as varying susceptibility to nanoparticles at different growth stages.

Significance and Impact of the Study

These results underscore the need for time-resolved analyses of microbial growth inhibition by Ag(0) nanoparticles. Due to the versatility of the technique, the assay will likely complement existing microbiological methods for cultivation and diagnostics of microbes, in addition to tests of other antimicrobial nanoparticles.

Introduction

The unique properties of metal nanoparticles allow them to have great potential in research and development and diverse applications in industrial products (Caruthers et al. 2007; Park 2007; Engel et al. 2008; Theron et al. 2008; Banerjee et al. 2011; Duncan 2011). The high surface-to-volume ratio of nanoscale materials is associated with a number of novel and desirable properties compared with the corresponding bulk materials. These properties include chemical, mechanical, electrical and optical characteristics such as light absorption and conductivity, as well as catalytic and biological activity (Park 2007; Nel et al. 2009). In particular, the vigorous antimicrobial properties of nanoscale metal and metal oxide particles such as Ag, TiO2 and ZnO have been the focus of industrial applications in biocidal coatings (e.g. filters for air and water treatment, clothes and other textiles, paints and varnishes, cosmetics and personal care products).

Silver, especially in its nanoscale form, has a strong toxicity towards a wide range of micro-organisms. Because of their large surface area, Ag(0) nanoparticles also release bioactive silver ions more effectively than bulk Ag(0). This biocidal property allows for the prevention and topical treatment of infectious diseases and also the production of antimicrobial, self-cleaning and self-disinfectant surfaces. Such applications of Ag(0) nanoparticles can be found in fillers and coatings in medical devices, implant and prosthetic materials and health care products (e.g. Schneider et al. 2008; Eby et al. 2009; Stevens et al. 2009; Lara et al. 2011; Taylor and Webster 2011; Zhao et al. 2011). Because the same biocidal effect can be achieved with relatively small input of raw materials, nanoparticles contribute to an efficient use of materials (Nel et al. 2006; Lok et al. 2007; Martinez-Castanon et al. 2008; Liu et al. 2010; Dal Lago et al. 2011).

The extremely high reactivity of metal nanoparticles is associated both with known and unknown toxic effects, including those against micro-organisms (Klaine et al. 2008; Nel et al. 2009; Marambio-Jones and Hoek 2010). A prerequisite for understanding the cellular mechanisms of the antimicrobial effects is to monitor the susceptibility of micro-organisms to biocidal metal nanoparticles. Such metal nanoparticles interact with microbial cells through multiple biochemical pathways, for instance, via the production of reactive oxygen species (ROS) (e.g. Klaine et al. 2008; Marambio-Jones and Hoek 2010). ROS can damage cell structures and can ultimately cause cell death (Neal 2008; Su et al. 2009). The surface-to-volume ratio increases with decreasing particle size. Thus, there is also an inverse relationship between particle size and the number of surface-oriented groups covering the particles, which is important for defining the chemical and biological properties of the nanoparticles, including generation of ROS (Nel et al. 2006; Carlson et al. 2008; Choi and Hu 2008; Neal 2008). Furthermore, the biocidal effect of most metal nanoparticles depends on their stability and resistance to agglomeration and aggregation. These properties are associated with increased release of metal ions from the larger surface area, resulting in a longer time for interaction between the nanoparticles and bacteria, and thus, a more potent antimicrobial activity (Jiang et al. 2009; Bae et al. 2010; Jin et al. 2010). However, the reactivity and biocidal properties between different metals differ greatly.

Several main mechanisms underlie the biocidal properties of silver against micro-organisms. First, Ag(0) nanoparticles attach to the cell surface, alter the physical and chemical properties of the cell membranes and the cell wall and disturb important functions such as permeability, osmoregulation, electron transport and respiration (Sondi and Salopek-Sondi 2004; Nel et al. 2009; Su et al. 2009; Marambio-Jones and Hoek 2010). Second, Ag(0) nanoparticles can cause further damage to bacterial cells by permeating the cell, where they interact with DNA, proteins and other phosphorus- and sulfur-containing cell constituents (AshaRani et al. 2009; Nel et al. 2009; Marambio-Jones and Hoek 2010). Third, Ag(0) nanoparticles release silver ions, generating an amplified biocidal effect, which is size- and dose-dependent (Lok et al. 2007; Liu et al. 2010; Marambio-Jones and Hoek 2010).

Conventional agar diffusion tests, serial dilutions and counting of colony-forming units or endpoint growth determination via turbidity measurements of the cell density are commonly used for evaluating the effects of nanoparticles on microbial biota, regardless of whether these are desired effects (e.g. against pathogens) or adverse effects on beneficial micro-organisms. By using these standard cultivation-dependent techniques for endpoint growth determination or inspection at regular time intervals, many studies have confirmed the effective biocidal activity of Ag(0)- and other metal nanoparticles against micro-organisms (e.g. Kim et al. 2007; Fernandez et al. 2008; Martinez-Castanon et al. 2008; Ruparelia et al. 2008; Egger et al. 2009; Fabrega et al. 2009; Jain et al. 2009; Travan et al. 2009; Li et al. 2010; Liu et al. 2010; Amato et al. 2011; Gottesman et al. 2011; Huang et al. 2011; Lalueza et al. 2011; Guzman et al. 2012; Oei et al. 2012).

On the other hand, researchers have demonstrated a delayed release of nanoparticle Ag(0) from processed materials (Wijnhoven et al. 2009; Benn et al. 2010), as well as successive formation of silver ions on the surface of Ag(0) nanoparticles (Lok et al. 2007; Damm and Münstedt 2008; Wijnhoven et al. 2009; Liu and Hurt 2010; Liu et al. 2010). Furthermore, nanoparticle transport, biosorption, toxicity and formation of microbial metal resistance are also subject to temporal effects and will thus largely affect microbial growth dynamics (Nies 2003; Nel et al. 2006, 2009; Harrison et al. 2007). Therefore, existing methods of acquiring growth profiles based on endpoint measurements or on analyses at discrete time points are of limited applicability for studying the entire range of dynamic effects of nanoparticle exposure on micro-organisms and the time-dependent expression of cellular response mechanisms.

This study comprises the design and application of growth tests for a reliable and time-resolved assessment of the antimicrobial properties of Ag(0) nanoparticles on microbial growth in comparison with the respective bulk material. The automated assay in 96-well microtitre plates allows simultaneous cultivation and online monitoring of microbial growth and combines high temporal resolution with the analysis of many replicate cultures.

Materials and methods

Micro-organisms and culture conditions for growth

Cupriavidus necator H16 (DSM 428, syn. Ralstonia eutropha) was obtained from the German Collection of Micro-organisms and Cell Cultures (DSMZ) and was grown according to the instructions by DSMZ, either in nutrient broth or on nutrient agar (DSMZ medium number 1) or in DSMZ medium number 81 (mineral medium for chemilithotrophic growth, H-3; www.dsmz.de). Culture bottles and Erlenmeyer flasks containing the media were autoclaved for 30 min at 122°C and subsequently stored at 4°C. All manipulations, including addition of supplementary media ingredients and inoculations of precultures (16 h), were performed by using sterile microbiological techniques. For cultures in Erlenmeyer flasks (25°C, agitation at 120 rev min−1), 1-ml samples were withdrawn at predetermined time intervals, and samples were used for routine determination of the optical density (OD660nm), total cell numbers over the incubation time and colony-forming units on growth plates using 1·5% (w/v) agar. Typically, two sampling bottles remained uninoculated and served as sterile controls.

Frozen cultures for preservation were prepared by mixing equal amounts of pregrown cultures and 20% sterile glycerol (Carl Roth, Karlsruhe, Germany), and 2-ml aliquots were stored at −80°C.

Cultivation and growth analysis of C. necator in microtitre plates

Cultivation of Cnecator H16 in microtitre plates was performed using sterile 96-well suspension culture plates (polystyrene microplates, flat bottom, art. 655161; Greiner bio-one, Frickenhausen, Germany) and closed with sterile standard-profile lids without condensation rings (polystyrene lids, art. 656161). Precultures (40 ml, 16 h at 25°C, agitation at 100  rev min−1) grown in 100-ml Erlenmeyer flasks were harvested, resuspended in fresh medium (10% v/v) and mixed with Ag(0) nanoparticles (AgPure W10, primary size distribution D90 < 15 nm, ras materials, Regensburg, Germany) which were added from 1 mg ml−1 or 5 mg ml−1 Ag(0) stock solutions, resulting in a final Ag(0) concentration of 10–100 μg ml−1. Aliquots of 250 μl of the desired master suspension (Ag(0) concentrations 0 to 100 μg ml−1) were transferred into the appropriate wells using multichannel pipettes. The stability of nanoparticle suspensions in medium was monitored by light and electron microscopy (data not shown), as well as by nanoparticle tracking analysis (NTA). Spectrophotometer wavelength scans (450–1000 nm) for Ag(0) nanoparticles were carried out at a concentration of 1 mg ml−1 Ag(0) (AgPure W10).

Cell cultivation and growth analysis were performed using a Tecan infinite M200 multimode microplate reader equipped with monochromator optics. Microplates were incubated at 25°C, under orbital shaking conditions of 3-mm shaking amplitude and 15-s shaking cycles, and conditioned for 30 min for temperature equilibration before measurements were started. Measurement was performed each 15 min using the multiple-reads-per-well mode (filled-circle alignment, nine reads per well, border 1000 μm). In general, eight replicate cultures were analysed for growth at each Ag(0) concentration, along with another eight replicates per Ag(0) concentration as sterile media controls. The latter background readings were also measured at each sampling time, and all readings were normalized appropriately. Growth analysis of Cnecator in the presence of Ag(0) nanoparticles was performed along with controls without Ag(0) to obtain reference growth curves.

The effects of bulk Ag(0) (Ag(0) flakes, purity ≥99·9%, particle size 10 μm, Sigma-Aldrich) were determined by culturing cells under identical growth conditions to the nanoparticles. The Ag(0) flakes were diluted to 10 and 50 μg ml−1 and compared with Ag(0)-nanoparticle-mediated growth inhibition.

Characterization of Ag(0) nanoparticles by nanoparticle tracking analysis

The particle size distribution of suspended nanoparticles was measured for up to 72 h using nanoparticle tracking analysis (NTA). NTA was performed on a NanoSight LM14 device (NanoSight Ltd, Amesbury, UK) equipped with a 532-nm laser (50 mW) and NTA software (ver. 2·2) for capture and analysis of data. Dilutions of 1 : 100 were prepared in three replicates using autoclaved (30 min at 122°C) and sterile-filtered deionized water (sterile 0·2-μm pore size membrane filters, cellulose acetate, Whatman; Pure Lab Plus, ELGA LabWater). One ml was injected into the sample chamber using sterile syringes and sterile-filtered deionized H2O served as a particle-free control. Between analyses, the sample chamber was cleaned by rinsing with sterile-filtered deionized water, and then, fresh water samples were analysed to exclude cross-contamination. All measurements were performed at 25°C for 90 s, and sample videos were taken at a speed of 30 frames per second.

Data analysis

The maximum specific growth rate, the duration of lag phase and the maximum final OD values were determined during 85 h of growth in the presence or absence of Ag(0) nanoparticles. For calculations, the normalized mean OD660nm values from cultures with 0, 20, 40 and 60 μg ml−1 Ag(0) nanoparticles were used at each of the 340 time points, respectively. The maximum specific growth rate was determined for each interval during the exponential growth phase, considering OD660nm values between 0·2 and 0·75 (OD660nm = 0·2 to 0·6 for 60 μg ml−1) and according to μ = (lnx1−lnx2)/t1t2, where, μ is the growth rate, x1 is the OD660nm at time t1 and x2 is the OD660nm at time t2 (h). Average growth rates for larger intervals (1 h) were calculated from the data for growth rates at 15-min intervals. Maximum final OD660nm values were determined from the mean values (eight replicates each) between 81 h and the end of the cultivation, whereas the duration of the lag phase was read when the OD660nm had reached ≥0·2.

Results

Experimental design

For development of an automated method for simultaneous cell culturing and monitoring of microbial growth in the presence of Ag(0) nanoparticles, a multifunctional monochromator-based instrument was used, providing continuous absorbance measurements in the range of 230–1000 nm (1-nm increment). In addition to the simultaneous analysis of a large number of replicates, it offers the possibility of parallel cultivation and growth analysis in a microplate format with a high temporal resolution. Furthermore, the monochromator-based instrument enables adjustment of the optical measurement settings in the presence of dispersed metal nanoparticles. Metal nanoparticles frequently exhibit strong background signals (Fig. 1, insert), which impair absorbance measurements due to nanoparticle-specific and concentration-dependent properties (e.g. type of metal/metal oxide and size distribution).

Figure 1.

Comparison of absorption spectra from samples with (i) 1 mg ml−1 Ag(0) nanoparticles (AgNPs) in medium and in the presence of cell suspensions of Cupriavidus necator H16, (ii) 1 mg ml−1 Ag(0) nanoparticles in sterile medium controls and (iii) test cell suspensions without Ag(0) nanoparticles. The monochromator-based detection permitted adjustment of the optical measurement settings to obtain optimal absorbance signal-to-noise ratios for different types of nanoparticles. Absorbance scans show mean values of eight replicates at 1-nm incremental wavelengths from 450 to 1000 nm. Error bars indicating standard deviations are presented only for selected wavelengths. Insert: background signals of metal nanoparticle suspensions: example of a 96-well microplate with Ag(0) nanoparticles at 0, 50 and 100 μg ml−1. (image) Cells + Growth Medium + 1 mg ml−1 AgNPs; (image) Growth Medium + 1 mg ml−1 AgNPs; (image) Cells + Growth Medium w/o AgNPs.

The absorption of Ag(0) nanoparticle suspensions in the presence or absence of test organisms was determined at wavelengths from 450 to 1000 nm. Absorbance scans of 1 mg ml−1 Ag(0) nanoparticles in medium in the presence of test cell suspensions (Cnecator H16) and of 1 mg ml−1 Ag(0) nanoparticles in sterile medium controls showed decreasing values at wavelengths of > 500 nm and reached an OD < 1 at 650 nm and of 625 nm, respectively (Fig. 1). Cell suspensions with the same cell density but without Ag(0) nanoparticles served as controls and revealed a decreasing trend, from OD = 1·01 (450 nm) to OD = 0·57 (1000 nm) (Fig. 1). Based on the high variability of OD values in samples with Ag(0) nanoparticles at <520 nm and the high background signals between 520 nm and 650 nm, the wavelength was set to 660nm to allow reliable and comparable data acquisition during subsequent analyses. Besides this optimization of signal-to-noise ratios, subsequent analyses included parallel measurements of sterile uninoculated controls at identical Ag(0) concentrations used for normalization of test samples.

The NTA technique allows visualization of individual nanoparticles in solution, including monitoring and analysis of their Brownian motion, from which the particle size distribution can be obtained. In a typical NTA measurement, a liquid sample containing nanoparticles at a concentration in the range of 107–10ml−1 is introduced into a sample chamber through which a laser beam is passed. The scattered light from particles within the path of the beam is observed as a measure of their positions via a microscope with an attached CCD camera. The motion of the particles in the field of view (approx. 100 × 100 μm) is recorded, and the resulting video is then analysed. The NTA software helps to identify and track individual nanoparticles moving under Brownian motion. Results are displayed as a particle diameter distribution, calculated from the measured diffusion coefficient together with the temperature and viscosity of the dispersant in which the nanoparticles are suspended. The time-resolved NTA analysis of Ag(0) nanoparticles in liquid growth media revealed only slight systematic changes in particle size distribution over time. An increase in the average particle size was found, however, even after 72 h of cultivation; the majority of the particles or agglomerates had sizes below 70 nm (Fig. 2). Hence, formation of larger aggregates could be excluded, thus ensuring ‘nano-effects’ throughout growth analysis.

Figure 2.

Time course of particle size distributions measured by nanoparticle tracking analysis. Characterization at time point zero was performed both in sterile deionized water and in liquid growth media. (image) T0 h AgNPs in H2O; (image) T0 h AgNPs in media; (image) T24 h AgNPs in media; (image) T48 h AgNPs in media; (image) T72 h AgNPs in media.

Evaluation of the cultivation-based assay: Concentration-dependent nanoparticle inhibition of microbial growth

The established technique of simultaneous cultivation and growth monitoring in microplates was extended to inhibition experiments with Cnecator test organisms in the presence of different concentrations of Ag(0) nanoparticles.

Experiments were run over 85 h with a time resolution of 15 min resulting in 340 time points for each measurement (Fig. 3). Growth experiments with inoculated Cnecator cells at each Ag(0) nanoparticle concentration (0, 20, 40, 60 and 80 μg ml−1) were performed using eight replicate cultures (2720 single data points from each Ag(0) concentration with the bacteria). Parallel runs of uninoculated controls at each concentration (2720 single data points from each Ag(0) nanoparticle concentration without bacteria) were also included; thus, the graphs presented in Fig. 3 display the results of 27 200 single data points.

Figure 3.

Growth of Cupriavidus necator H16 in the presence of Ag(0) nanoparticles. Whereas the duration of lag phases was a measure for partial growth inhibition, neither final OD values nor maximum slope of the growth curves correlated with Ag(0) concentration and the corresponding repression. Each growth curve represents means of eight replicates at each of 340 time points over 85 h of growth. Using a time resolution of 15 min, each curve conveys 2720 single measurements for a total of 27 200 single data points for the graph. For visual clarity, standard deviations (error bars) are only presented for selected time points. (image) Cnecator, 80 µg ml−1 AgNPs; (image) Cnecator, 60 µg ml−1 AgNPs; (image) Cnecator, 40 µg ml−1 AgNPs; (image) Cnecator, 20 µg ml−1 AgNPs; (image) Cnecator, w/o AgNPs.

In the absence of Ag(0) nanoparticles, Cnecator showed rapid growth and reached optical density values of up to OD660nm = 0·9 in the course of cultivation. No lag phase was observed. The stationary phase was reached after approximately 36 h. Cultures of Cnecator containing 80 μg ml−1 Ag(0) did not show bacterial growth within 85 h. Growth curves at concentrations of 20, 40 and 60 μg ml−1 exhibited extended lag phases with increasing concentrations, resulting in a maximum duration of 30 h for cultures with 60 μg ml−1 Ag(0) (Figs 3 and 4c). Maximum slopes of the growth curves during the exponential phase of cultures with 20 or 40 μg ml−1 were considerably higher than those of the controls without added Ag(0) (Figs 3 and 4b). Furthermore, despite of the delayed onset of growth, the addition of 20 μg ml−1 or 40 μg ml−1 Ag(0) led, at least transiently, to higher OD values (Fig. 3). In contrast, growth in Cnecator cultures in the presence of 60 μg ml−1 Ag(0) resulted in a shallower growth curve slope and lower OD660nm values than the samples with 20 μg ml−1 and 40 μg ml−1 Ag(0) (Figs 3, 4a,b). This suggests that neither the maximum specific growth rate nor the maximum final OD values will serve as meaningful predictors for the effects of nanoparticles on microbial growth in this concentration range.

Figure 4.

Dose-dependent effect of Ag(0) nanoparticles on selected growth parameters of Cnecator H16 in the range of 0–60 μg ml−1 Ag(0). (a) final OD660nm values, (b) maximum specific growth rates (c) duration of lag phases.

Growth-phase-dependent sensitivity of Cnecator H16 to Ag(0) nanoparticles

To investigate whether the physiological state of the cells influenced sensitivity to Ag(0), the nanoparticles were added during different growth phases of Cnecator cultures (Fig. 5a). The addition of 40 μg ml−1 Ag(0) nanoparticles at the beginning of the cultivation resulted in complete inhibition, as no growth was observed in the respective wells. The controls without Ag(0) nanoparticles showed steady growth to OD660nm = 0·9 during the same time period. The initial growth of cultures to which Ag(0) nanoparticles were added after 24 or 48 h proceeded identically to those of the untreated controls (Fig. 5a). However, Ag(0) nanoparticle addition to these cultures was followed by a pronounced decline of the OD, but both cultures with delayed Ag(0) nanoparticle addition recovered their growth (Fig. 5a). Although the final OD values of the controls were not obtained in the cultures with delayed Ag(0) exposure, after the regeneration phase, they showed a more rapid increase in cell density during particular growth periods.

Figure 5.

Cupriavidus necator H16 with Ag(0) nanoparticle addition at different growth stages. Ag(0) nanoparticle addition was conducted at the same concentration (40 μg ml−1) but (a) after 0, 24 and 48 h; and (b) after 0, 3, 6, 9 and 12 h. Each curve shows mean values of eight replicate cultivations, all analysed with a 15-min time resolution at 482 (a) and 146 (b) time points, respectively. Standard deviations are only shown for data points every 6 h. (a) (image) C. necator w/o AgNPs; (image) C. necator, 40 µg ml−1 AgNPs after 48 h; (image) C. necator, 40 µg ml−1 AgNPs after 24 h; (image) C. necator, 40 µg ml−1 AgNPs after 0 h. (b) (image) C. necator w/o AgNPs; (image) C. necator, 40 µg ml−1 AgNPs after 12 h; (image) C. necator, 40 µg ml−1 AgNPs after 9 h; (image) C. necator, 40 µg ml−1 AgNPs after 6h; (image) C. necator, 40 µg ml−1 AgNPs after 3 h; (image) C. necator, 40 µg ml−1 AgNPs after 0 h

Because the addition of nanoparticles at time zero resulted in complete and irreversible growth inhibition and treatment with the same Ag(0) concentration 12 h later allowed full recovery, the experiment was repeated by monitoring growth after Ag(0) had been added within the first 12 h of incubation, at 0, 3, 6, 9 and 12 h (Fig. 5b).

As in the previous experiment, controls without Ag(0) showed rapid and immediate growth without a pronounced lag phase. Cultures with Ag(0) nanoparticle addition at time zero did not grow, nor did cultures with Ag(0) added after 3 h and 6 h, respectively (Fig. 5a,b). Although cultures that received Ag(0) nanoparticles after 9 or 12 h also showed rapid decrease in OD, these cultures were fully recovered. After a regeneration phase of up to 12 h, these cultures restarted rapid growth, with maximum specific growth rates which exceeded those of the control by a factor of five (Fig. 5b). Furthermore, although the cultures contained antimicrobial Ag(0) nanoparticles which transiently led to a lower OD and disruption of growth, they eventually reached even higher OD values than the Ag(0)-free control already after 27 h.

For testing the effectiveness of Ag(0) nanoparticles and validating risk assessment protocols, it is crucial to distinguish between antimicrobial effects that are based on nanoscale-related properties and those due to general metal toxicity. Comparison of growth in the presence of identical concentrations of nanoscale Ag(0) (primary size distribution D90 <15 nm) and bulk Ag(0) (Ag(0) flakes, particle size 10 μm) revealed distinct differences at a concentration of 50 μg ml−1 Ag(0) (Fig. 6). Whereas nanoscale Ag(0) treatment resulted in clear growth inhibition of Cnecator test organisms, bulk Ag(0) exhibited effects comparable with those seen with the addition of 10 μg ml−1 nanosized Ag(0) (Fig. 6). Nevertheless, compared with the controls without Ag(0), the addition of bulk Ag(0) had a significant effect on the growth of Cnecator.

Figure 6.

Comparison of antimicrobial effects of nanoscale vs bulk Ag(0) on the growth of Cupriavidus necator. Each curve represents the time course of mean values of four replicate cultures which were analysed every 15 min. Error bars correspond to standard deviations and are shown for data points approximately every 6 h. Data for uninoculated controls are also shown. (image) Sterile control; (image) C. necator 10 µg ml−1 AgNPs; (image) C. necator 50 µg ml−1 AgNPs; (image) C. necator 50 µg ml−1 bulk Ag.

Discussion

Nanotechnology approaches using engineered nanoparticles with biocidal properties (e.g. Ag, Zn, Cu, Ce and Ni) offer novel applications, including control of unwanted microbial colonization on diverse surfaces and prevention of biofouling, improved waste-water treatment and drinking water purification and the prophylaxis and topical treatment of infectious diseases. In contrast, the extensive use of engineered nanoparticles with antimicrobial properties and their increased release into the environment have raised major concerns due to potential (eco)toxicological effects and inappropriate testing methods. At present, there are virtually no applicable standard methodologies for evaluating the effects of exposure of microbial biota to nanoparticles, regardless of whether these are favourable effects (e.g. against pathogens) or adverse impacts in the environment.

Commonly used techniques, such as agar diffusion tests, are often inhibited by nanoparticle agglomeration or aggregation and lowered nanoparticle transport due to interactions with media components or the solidified agar matrix (Gallant-Behm et al. 2005; Dhawan et al. 2009; Jin et al. 2010; Römer et al. 2011). As a result of nanoparticle re-aggregation, these tests usually provide inconclusive results or can underestimate nanoparticle toxicity (Jiang et al. 2009; Liu et al. 2009; Bae et al. 2010; Römer et al. 2011). Conventional growth experiments in liquid media in culture bottles are highly laborious and require regular sampling and offline measurements. Therefore, such testing is frequently restricted to a small number of replicates, limited to endpoint growth determination or analysis at discrete time points. Such growth analyses may not cover details of the entire course of cultivation and are of low temporal resolution and will not recognize shifted or long-term effects. Hence, they are inadequate for tracking the finer temporal changes of microbial growth affected by nanoparticles, which may, however, convey important information for a sound evaluation of nanoparticle-mediated effects.

Factors that influence microbial growth dynamics include the delayed release of Ag(0) from processed materials and the successive generation of silver ions, cell sorption and interaction of Ag(0) nanoparticles with cellular components, the manifestation of toxic effects and the formation of cellular stress response mechanisms (Nel et al. 2006, 2009; Lok et al. 2007; Damm and Münstedt 2008; Wijnhoven et al. 2009; Benn et al. 2010; Liu and Hurt 2010; Liu et al. 2010). Expression of a diverse array of metal resistance strategies evolved by the bacteria to encounter heavy metal toxicity comprises reduction or modification of the heavy metals to less toxic species, chelation, sequestration, reduced uptake, efflux mechanisms and increased expression of the cellular repair machinery (Nies 2003; Harrison et al. 2007).

In this study, we established a 96-well-based assay that was adapted for time-resolved testing of the dynamic effects of Ag(0) nanoparticles on micro-organisms. This method allowed simultaneous cultivation and online analysis of microbial growth. The automated high-throughput assay, which combined monitoring of microbial growth rates at high temporal resolution with analysis of many replicates, was applied to Cnecator test organisms to test the antimicrobial effects of the nanoparticles. Concentrations above 80 μg ml−1 Ag(0) nanoparticles revealed complete and irreversible growth inhibition, whereas Ag(0) concentrations of ≥20 μg ml−1 resulted in partial repression of bacterial growth and correlated with extended lag phases. However, reduced optical density in the plateau phase was only partly related to Ag(0) concentration and the corresponding growth inhibition (Fig. 4a). The maximum slope of the growth curves during the exponential phase was also not a measure of growth inhibition in the concentration range studied (Fig. 4b). Even more intriguing, compared with the Ag(0)-free controls, treatment with Ag(0) nanoparticles resulted in higher maximum growth rates after the extended lag phases at all concentrations tested between 20 and 60 μg ml−1 (Fig. 4b). This was similar to the effects induced by a delayed addition of Ag(0) nanoparticles, which caused a weaker inhibition with increasing time of nanoparticle treatment, indicating that the susceptibility of the micro-organisms to Ag(0) nanoparticles is growth-stage dependent.

Contrary to our expectations, in cultures that received Ag(0) nanoparticles at ≥9 h of growth, a reversible growth inhibition could be compensated for by higher growth rates until the end of the experiment (Fig. 5). These observations support the assumption that during particular growth phases micro-organisms might experience partial growth stimulation under moderate stress conditions in comparison with cultures without Ag(0) treatment. This aspect should be taken into account when treating unwanted micro-organisms, such as pathogens and food contaminants, with antimicrobial metal nanoparticles. It also suggests that for a comprehensive evaluation of nanoparticle toxicity against micro-organisms, the common use of nontemporal growth profiles or endpoint growth measurements is questionable, and full analysis will require monitoring of complex growth dynamics.

Nanoparticle-specific background signals frequently interfere with turbidity measurements in microbiological tests used for optimizing nanoparticle formulations or for risk assessment. An important prerequisite for testing metal nanoparticle suspensions with high background was the ability of the monochromator-based detection system to permit one-nm resolved measurements for the optical density. This allowed validated adjustment of the analytical settings for data acquisition and improved signal-to-noise ratios resulting in highly reproducible data, even from a large number of separate cultures in different microtitre plate wells. The high performance of the technique is associated with its ability to be easily implemented in routine lab applications. In addition to other established methods for kinetic analyses, such as isothermal microcalorimetry, it will permit a comprehensive and profound growth-dependent assessment of inhibiting agents, specifically for the elucidation of the effects by Ag(0) nanoparticles.

Acknowledgements

We greatly appreciate assistance by Rita Geissler-Plaum and technical support by Martin Arnemann. We thank Marcella (Marcy) Card for her valuable comments on the manuscript.

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