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How reversible are the effects of silver nanoparticles on macrophages? A proteomic-instructed view

Bastien Dalzon a, Anaelle Torres a, Hélène Diemer b, Stéphane Ravanel c, Véronique Collin-Faure a, Karin Pernet-Gallay d, Pierre-Henri Jouneau e, Jacques Bourguignon c, Sarah Cianférani b, Marie Carrière f, Catherine Aude-Garcia§ a and Thierry Rabilloud *a
aChemistry and Biology of Metals, Univ. Grenoble Alpes, CNRS UMR5249, CEA, IRIG, CBM-ProMD, 17 Rue des Martyrs, F-38054 Grenoble Cedex 9, France. E-mail:; Tel: +33 438 783 212
bLaboratoire de Spectrométrie de Masse BioOrganique (LSMBO), Université de Strasbourg, CNRS, IPHC UMR 7178, 67000 Strasbourg, France
cUniv. Grenoble Alpes, INRA, CNRS UMR5168, CEA, IRIG, Laboratory of Plant Cellular Physiology, Grenoble, F-38000 France
dUniv. Grenoble Alpes, Inserm U1216 Grenoble Institut des Neurosciences, 38000 Grenoble, France
eUniv. Grenoble Alpes, Modelization and Exploration of Materials, CEA-DRF-IRIG-DEPHY-MEM-LEMMA, F-38000 Grenoble, France
fUniv. Grenoble-Alpes, CEA, CNRS UMR 5819, IRIG, SyMMES, Chimie Interface Biologie pour l'Environnement, la Santé et la Toxicologie (CIBEST), F-38054 Grenoble, France

Received 8th April 2019 , Accepted 21st July 2019

First published on 20th September 2019

Silver nanoparticles are known to strongly affect biological systems, and numerous toxicological studies have investigated their effects. Most of these studies examine the effects immediately following acute exposure. In this work, we have conducted further investigation by studying not only the acute, post-exposure response, but also the cellular response after a 72 hour-recovery-phase post exposure. As a biological model we have used macrophages, which are very important cells with respect to their role in the immune response to particulate materials. To investigate the response of macrophages to nanoparticles and their recovery post exposure, we have used a combination of proteomics and targeted experiments. These experiments provided evidence that the cellular reaction to nanoparticles, including the reaction during the recovery phase, is a very active process involving massive energy consumption. Pathways such as the oxidative stress response, central and lipid metabolism, protein production and quality control are strongly modulated during the cellular response to nanoparticles, and restoration of basic cellular homeostasis occurs during the recovery period. However, some specialized macrophage functions, such as lipopolysaccharide-induced cytokine and nitric oxide production, did not return to their basal levels even 72 hours post exposure, showing that some effects of silver nanoparticles persist even after exposure has ceased.

Environmental significance

Silver nanoparticles are known to have profound effects on living cells. Because of their widespread use, contamination is almost unavoidable. In this context, it is important not only to assess the immediate effects of silver nanoparticles on cells, but also how they recover after exposure. Using macrophages as the target cell type and a combination of proteomic and targeted experiments, we show here that the recovery phase is not just a “return to normal” condition. For example, some of the specialized macrophage functions are still not restored after this time, showing that subtle but sustained effects can occur after a single exposure. Although cell survival is not affected, such effects may impact the health status of living beings.

1. Introduction

Silver nanoparticles (AgNPs) are used as a biocide in a variety of consumer and medical products, because of the toxic effects that they have on microorganisms. However, as an unwanted side effect, AgNPs also show toxicity to mammalian cells. Thus, numerous toxicological studies have been conducted both in vitro in bacterial and eukaryotic model cell systems and in vivo in animal models, including at the microbiome level.1–3 Although some studies, especially those using animal models, have examined the effects of NPs after repeated, low-dose exposures,4–8 most of the cellular, toxicological studies have been conducted in an acute exposure mode, meaning that high doses have been used and exposure times have been short, spanning less than or equal to 24 hours. In these types of studies, toxicological endpoints are investigated at the end of the exposure period.9–16 In terms of exposure, the acute schemes relate most closely to accidental, acute exposures, while chronic schemes correspond highly to occupational exposures. It is of interest to study how biological systems recover after a single, high, non-lethal exposure. This is not a trivial question, as some mineral toxicants such as beryllium or crystalline silica show very prolonged effects, even after the exposure has ceased.17,18 This poor recovery has also been observed for silver nanomaterials such as silver nanowires19 and silver nanoparticles.20

Many toxicological studies have reported pro-inflammatory responses5,11,12,21 and/or immunological effects15,22 pointing to macrophages as a cell type of major interest in toxicological studies of AgNPs. This is in accordance with the important scavenging function of macrophages in many different tissues.

This work investigates the recovery of macrophages after a unique, acute, but subtoxic dose of AgNPs. Targeted experiments carried out primarily on macrophages showed that several functional effects (e.g. LPS-induced cytokine and NO production, mitochondrial transmembrane potential and phagocytosis) were altered immediately after exposure to AgNPs. However, these functions tended to return to normal after a 72 h recovery period.23 We therefore decided to get a broader view of cellular recovery using a proteomic approach.

Proteomic approaches have been used to study cellular responses to AgNPs in several models such as intestinal cells9,24,25 or liver cells.10 This allowed several important pathways modulated in response to acute exposures to AgNPs to be highlighted. These included mitochondrial proteins, pointing at potential mitochondrial dysfunction,9,10,24 and proteins involved in intermediate metabolism9,10,24 or in inflammatory responses.10 The latter findings reinforced the interest in studying macrophages, which are major players in inflammation. We therefore decided to use proteomics to study the cellular responses using a macrophage J774 cell line, directly after acute exposure and after a recovery period had lapsed. This model cell line was selected because, unlike human monocyte cell lines,26,27 mouse macrophage cell lines such as RAW264.7 and J774 do not need to be chemically differentiated into macrophages, a process that deeply alters cell physiology and causes some cell death. Furthermore, as opposed to primary macrophages derived from human blood, these mouse cell lines do not show extensive variability from one experiment to another. This explains why these cell lines are extensively used as models for testing of a wide variety of nanomaterials,28–31 including large scale projects.32–34

2. Experimental

Most experiments have been performed essentially as described in previous publications.35–37 Details are given here for the sake of the consistency of the paper. All biological experiments were carried out at least on three independent biological replicates.

2.1 Nanoparticles

PVP-coated silver nanoparticles were purchased from Sigma, directly as a concentrated suspension (catalog number #758329). Their characteristics have been published previously.23,38 These experiments confirmed the manufacturer's data and showed that the nanoparticles are spherical, with a diameter in the 50–110 nm range, and did not aggregate upon dilution in water or culture medium.

2.2 Cell culture

The mouse macrophage cell line J774 was obtained from the European Cell Culture Collection (Salisbury, UK). The cells were cultured in DMEM + 10% fetal bovine serum (FBS). For routine culture, cells were seeded in non-adherent flasks (e.g. suspension culture flasks from Greiner) at 200[thin space (1/6-em)]000 cells per ml and harvested 48 hours later, at 1[thin space (1/6-em)]000[thin space (1/6-em)]000 cells per ml. Cell viability was measured by a dye exclusion assay, either with eosin (1 mg ml−1)39 under a microscope or with propidium iodide (1 μg ml−1)40 in a flow cytometry mode.

For determination of the useful dose, cells were seeded at 500[thin space (1/6-em)]000 cells per ml. They were treated with nanoparticles on the following day and harvested after a further 24 hours in culture.

For treatment with nanoparticles, cells were seeded in classical cell culture flasks and left for 24 hours at 37 °C for cell adhesion and confluence. For the recovery condition, cells were treated with nanoparticles on the following day. After 24 hours of exposure, the cell culture medium was removed and replaced by fresh medium. For consistency reasons, this operation was also carried out on cells used for control and for acute exposure. Another medium culture change was carried out 36 hours after the initial medium change, i.e. mid-term of the 72 hour recovery period. Finally, acute exposure was carried out for the final 24 hours and the cells were used immediately afterwards.

2.3 Phagocytosis and particle internalization assay

The phagocytic activity was measured using fluorescent latex beads (1 μm diameter, green labelled, catalog number L4655 from Sigma). The beads were pre-incubated at a final concentration of 55 μg mL−1 for 30 minutes at 37 °C in PBS/FBS (v/v). Then, they were incubated with cells (5 μg mL−1) for 2 h 30 at 37 °C. Cells were harvested and washed with PBS. Cells were resuspended by vortexing with addition of 3/4 water volume and then 1/4 NaCl (35 mg mL−1) volume was added under vortexing in order to clean the cell surface of adsorbed particles. Cells were harvested in PBS with propidium iodide (1 μg mL−1). Viability and phagocytic activity were measured simultaneously by flow cytometry on a FacsCalibur instrument (Beckton Dickinson). The dead cells (propidium positive) were excluded from the analysis.

2.4 Mitochondrial transmembrane potential measurement

The mitochondrial transmembrane potential was assessed by rhodamine 123 uptake. Cells were incubated with rhodamine 123 (80 nM) for 30 minutes at 37 °C, 5% CO2 then rinsed twice in cold glucose (1 mg mL−1)–PBS (PBSG) and harvested in cold PBSG supplemented with propidium iodide (1 μg mL−1). The mitochondrial potential of the cells was analysed by flow cytometry on a FacsCalibur instrument (Beckton Dickinson). The dead cells (propidium positive) were excluded from the analysis. The low rhodamine concentration was used to avoid intramitochondrial fluorescence quenching that would result in a poor estimation of the mitochondrial potential.41

2.5 Enzyme assays

The enzymes were assayed according to published procedures (see below).

The cell extracts for enzyme assays were prepared by lysing the cells for 20 minutes at 0 °C in Hepes (20 mM, pH 7.5), MgCl2 (2 mM), KCl (50 mM), EGTA (1 mM), and tetradecyldimethylammonio propane sulfonate (SB 3-14) (0.15% (w/v)), followed by centrifugation at 15[thin space (1/6-em)]000g for 15 minutes to clear the extract. The protein concentration was determined by a dye-binding assay.42 The dehydrogenase or dehydrogenase-coupled activities were assayed at 500 nm using the phenazine methosulfate/iodonitrotetrazolium coupled assay.43 The enzyme assay buffer contained 25 mM Hepes, NaOH (pH 7.5), 5 mM magnesium acetate, 100 mM potassium nitrate and 1% Triton X-100. It also contained 30 μM phenazine methosulfate, 200 μM iodonitrotetrazolium chloride, 250 μM of the adequate cofactor (NAD or NADP) and 1–5 mM of the organic substrate, which was used to start the reaction. For phosphate-dependent enzymes such as glyceraldehyde dehydrogenase (GAPDH) and purine phosphorylase (PNPH), 50 mM potassium phosphate (pH 7.5) was added to the enzyme assay buffer. Triose phosphate isomerase was assayed with dihydroxyacetone phosphate and a glyceraldehyde dehydrogenase-coupled assay.44 Purine phosphorylase (PNPH) was assayed by a xanthine oxidase-coupled assay.45 Hexokinase was assayed by a glucose phosphate dehydrogenase (G6PDH)-coupled assay.46 Biliverdine reductase was assayed at 450 nm as described.47 Pyridoxal kinase was assayed directly at 388 nm.48 Enolase was assayed at 340 nm by a pyruvate kinase–lactate dehydrogenase-coupled assay.49

2.6 NADP/NADPH and glucose assays

The glucose concentration in conditioned media was determined by a hexokinase–G6PDH assay.50 Briefly, culture media collected at the end of the exposure period were centrifuged for 15 min at 15[thin space (1/6-em)]000g to pelletize the particulate material. The supernatant was collected, and diluted 100-fold in the dehydrogenase assay buffer described above, containing also 1 mM EGTA, 30 μM phenazine methosulfate, 200 μM iodonitrotetrazolium chloride, 10 IU ml−1 G6PDH and 7.5 IU ml−1 hexokinase. The reaction was started by the addition of ATP (1 mM final concentration) and the increase in absorbance at 500 nm read for 1 minute. The linear part of the absorbance curve was used to determine the reaction speed, which was proportional to the glucose concentration. Fresh culture media supplemented with 10% fetal calf serum, i.e. high glucose DMEM (4.5 g L−1 glucose), RPMI1640 (2 g L−1 glucose) and 199 medium (1 g L−1 glucose) were used as standards.

The NADP–NADPH concentration was determined using an adapted alkaline extraction buffer.51 Briefly, at the end of the exposure period, cells were collected by scraping, rinsed twice in PBS and pelleted. The packed cell pellet (PCP) volume was estimated, and the cells were lysed in 10 PCP volumes of 10 mM CAPS, 1 mM EGTA and 2 mM MgCl2 for 10 minutes on ice with occasional vortexing. The suspension was centrifuged (10[thin space (1/6-em)]000g, 5 minutes, 4 °C), the viscous cell pellet discarded and the supernatant collected and split into two aliquots. The first aliquot was neutralized on ice by adding 0.1 volume of 1 M tricine. This aliquot contained both the oxidized and reduced forms of the pyridine nucleotides, and was also used to determine the protein concentration by a dye-binding assay.42

The other aliquot was heated at 60 °C for 30 minutes in a thermostated water bath to destroy the oxidized forms of the pyridine nucleotides.51 It was then cooled on ice, neutralized by adding 0.1 volume of 1 M tricine, and centrifuged for 10 minutes at 10[thin space (1/6-em)]000g at 4 °C to eliminate any particulate material.

The NADP–NADPH concentration was then determined by using an enzyme cycling assay and standard NADP solutions.52

2.7 NO production and cytokine production

The cells were grown to confluence in a 6-well plate and pre-treated with nanoparticles as described above. For the final 18 hours of culture, half of the wells were treated with 100 ng ml−1 LPS (from salmonella, purchased from Sigma), and arginine monohydrochloride was added to all the wells (5 mM final concentration) to give a high concentration of the substrate for nitric oxide synthase. After 18 hours of incubation, the cell culture medium was recovered and centrifuged at 10[thin space (1/6-em)]000g for 10 minutes to remove cells and debris, and the nitrite concentration in the supernatants was read at 540 nm after addition of an equal volume of Griess reagent and incubation at room temperature for 30 minutes.

For cytokine production, a commercial kit (BD Cytometric Bead Array, catalog number 552364 from BD Biosciences) was used.

2.8 F-actin staining

The experiments were performed essentially as previously described.53 The cells were recovered at the mid-term medium change (see above) and cultured on coverslips placed in 6-well plates. For the acute exposure condition, the cells were exposed to silver nanoparticles for 24 h at 37 °C. At the end of the exposure time, the cells were washed twice for 5 min at 4 °C in PBS and fixed in 4% paraformaldehyde for 30 min at room temperature. After two washes (5 min/4 °C in PBS), they were permeabilized in 0.1% Triton X100 for 5 min at room temperature. After two more washes in PBS, 500 nM Phalloidin-Atto 550 (Sigma) was added to the cells and left for 20 min at room temperature in the dark. Coverslip-attached cells were washed, placed on microscope slides (Thermo Scientific) using a Vectashield mounting medium containing DAPI (Eurobio) and imaged using a Zeiss LSM 800 confocal microscope. The images were processed using ImageJ software.

2.9 Silver assay by ICP-MS

For measuring the Ag-NP uptake and release in cells, 2 mL cell cultures in 6-well plates were used, with the exposure scheme described above in section 2.2. At the end of the exposure period, the culture medium was removed and saved and the cell layer was gently rinsed twice with culture medium without serum.

The cells were then lysed by scraping in 2 ml of lysis buffer (50 mM Hepes (pH 7.5), 4 mM magnesium acetate, 200 mM sorbitol, and 0.1% (w/v) tetradecyldimethylammonio propane sulfonate (SB 3-14)). The lysate was pipetted into a microtube and incubated for 20 minutes on ice to complete cell lysis. For determination of soluble silver, aliquots of the culture media and of the cell lysates were centrifuged for 45 minutes at 16[thin space (1/6-em)]000g, and the upper half of the supernatant was collected.

The samples were mineralized by the addition of one volume of suprapure 65% HNO3 and incubation on a rotating wheel at room temperature for 18 h.

Mineralized samples were diluted in 0.5% (v/v) HNO3 and analysed using an iCAP RQ quadrupole mass instrument (Thermo Fisher Scientific GmbH, Germany) equipped with an ASX-560 auto-sampler (Teledyne CETAC Technologies, Omaha, USA). The instrument was used with a MicroMist U-Series glass concentric nebulizer, a quartz spray chamber cooled at 3 °C, a Qnova quartz torch, a nickel sample cone, and a nickel skimmer cone equipped with a high-sensitivity insert. 24Mg, 25Mg, 107Ag and 109Ag concentrations were determined using standard curves and corrected using an internal standard solution of 103Rh added online. Data integration was done using the Qtegra software (version 2.8.2944.115). The results were normalized using the Mg concentration (4 mM in the cellular extracts and 0.82 mM in culture medium). To take into account the cellular concentration effects, the protein concentration of the extracts was determined by a dye-binding assay.42

2.10 Proteomics

The 2D gel-based proteomic experiments were essentially carried out as previously described,35 at least on independent biological triplicates. However, detailed materials and methods are provided for the sake of paper consistency.
2.10.1 Sample preparation. The cells were collected by scraping and then washed three times in PBS. The cells were then washed once in TSE buffer (10 mM Tris-HCl (pH 7.5), 0.25 M sucrose, and 1 mM EDTA), and the volume of the cell pellet was estimated. The pellet was resuspended in its own volume of TSE buffer. Then 4 volumes (respective to the cell suspension just prepared) of concentrated lysis buffer (8.75 M urea, 2.5 M thiourea, 5% w/v CHAPS, 6.25 mM TCEP-HCl, 20 mM spermine base, and 20 mM spermine tetrahydrochloride) were added and the solution was left to extract at room temperature for 1 hour. The nucleic acids were then pelleted by centrifugation (270[thin space (1/6-em)]000g at room temperature for 1 h), and the protein concentration in the supernatant was determined by a dye-binding assay.42 Carrier ampholytes (Pharmalytes, pH 3–10) were added to a final concentration of 0.4% (w/v), and the samples were kept frozen at −20 °C until use.
2.10.2 Isoelectric focusing. Home-made 160 mm long 4–8 linear pH gradient gels54 were cast according to published procedures.55 Four mm-wide strips were cut and rehydrated overnight with the sample, diluted to a final volume of 0.6 ml of the rehydration solution (7 M urea, 2 M thiourea, 4% CHAPS, 0.4% carrier ampholytes (Pharmalytes 3–10) and 100 mM dithiodiethanol).56

The strips were then placed in a Multiphor plate (GE Healthcare), and IEF was carried out with the following electrical parameters: 100 V for 1 hour, then 300 V for 3 hours, then 1000 V for 1 hour, then 3400 V up to 60–70 kVh. After IEF, the gels were equilibrated for 20 minutes in 125 mM Tris, 100 mM HCl, 2.5% SDS, 30% glycerol and 6 M urea.57 They were then transferred on top of the SDS gels and sealed in place with 1% agarose dissolved in 125 mM Tris, 100 mM HCl, 0.4% SDS and 0.005% (w/v) bromophenol blue.

2.10.3 SDS electrophoresis and protein detection. Ten percent gels (160 × 200 × 1.5 mm) were used for protein separation. The Tris taurine buffer system58 was used and operated at an ionic strength of 0.1 and a pH of 7.9. The final gel composition is thus 180 mM Tris, 100 mM HCl, 10% (w/v) acrylamide, and 0.27% bisacrylamide. The upper electrode buffer is 50 mM Tris, 200 mM taurine, and 0.1% SDS. The lower electrode buffer is 50 mM Tris, 200 mM glycine, and 0.1% SDS. The gels were run at 25 V for 1 hour, then 12.5 W was applied per gel until the dye front reached the bottom of the gel. Detection was carried out by tetrathionate silver staining59 .
2.10.4 Image analysis and global analysis of the spot abundance data. The gels were scanned after silver staining on a flatbed scanner (Epson perfection V750), using 16 bit grayscale image acquisition. The gel images were then analyzed using the Delta 2D software (v 3.6). The spots that were never expressed above 100 ppm of the total spots were first filtered out. Then, significantly-varying spots were selected on the basis of their Student's T-test p-value between the treated and the control groups. Spots showing a p-value lower than 0.05 were selected. This strategy is used to avoid the use of arbitrary thresholds, which can result in discarding statistically-valid relevant changes and including non-valid changes.60 The false positive concern was taken into account using several approaches such as the Benjamini Hochberg approach,61 the sequential goodness of fit approach62 and the sequential Fisher test approach.63 Furthermore, we checked that all the spots that we found through the T-test also had a p < 0.05 in a non-parametric Mann–Whitney U-test.

For the global analysis of the spot abundance data, we used directly the spot abundance data as provided by the gel analysis software. The software directly normalizes each spot abundance by the sum of all spot abundances detected on the gel. These relative abundance data were used directly for global analysis using the PAST software suite64 without any transformation. No limitation in the number of principal components was implemented in the principal component analysis.

2.10.5 Mass spectrometry. The spots selected for identification were excised from silver-stained gels and destained with ferricyanide/thiosulfate on the same day as silver staining in order to improve the efficiency of the identification process.65,66 In-gel digestion was performed with an automated protein digestion system, MassPrep Station (Waters, Milford, USA). The gel plugs were washed twice with 50 μL of 25 mM ammonium hydrogen carbonate (NH4HCO3) and 50 μL of acetonitrile. The cysteine residues were reduced by 50 μL of 10 mM dithiothreitol at 57 °C and alkylated by 50 μL of 55 mM iodoacetamide. After dehydration with acetonitrile, the proteins were cleaved in the gel with 10 μL of 12.5 ng μL−1 modified porcine trypsin (Promega, Madison, WI, USA) in 25 mM NH4HCO3. The digestion was performed overnight at room temperature. The generated peptides were extracted with 30 μL of 60% acetonitrile in 0.1% formic acid. Acetonitrile was evaporated under vacuum before nanoLC-MS/MS analysis.

NanoLC-MS/MS analysis was performed using a nanoACQUITY Ultra-Performance-LC (Waters Corporation, Milford, USA) coupled to a Synapt™ High Definition Mass Spectrometer™ (Waters Corporation, Milford, USA), or to a TripleTOF 5600 (Sciex, Ontario, Canada).

The nanoLC system was composed of an ACQUITY UPLC® CSH130 C18 column (250 mm × 75 μm with a 1.7 μm particle size, Waters Corporation, Milford, USA) and a symmetry C18 precolumn (20 mm × 180 μm with a 5 μm particle size, Waters Corporation, Milford, USA). The solvent system consisted of 0.1% formic acid in water (solvent A) and 0.1% formic acid in acetonitrile (solvent B). 4 μL of the sample were loaded into the enrichment column over 3 min at 5 μL min−1 with 99% of solvent A and 1% of solvent B. Elution of the peptides was performed at a flow rate of 300 nL min−1 with a 8–35% linear gradient of solvent B in 9 minutes.

The Synapt™ High Definition Mass Spectrometer™ (Waters Corporation, Milford, USA) was equipped with a Z-spray ion source and a lock mass system. The system was fully controlled by MassLynx 4.1 SCN639 (Waters Corporation, Milford, USA). The capillary voltage was set at 2.8 kV and the cone voltage at 35 V. Mass calibration of the TOF was achieved using fragment ions from Glu-fibrino-peptide B in the [50;2000] m/z range. Online correction of this calibration was performed with Glu-fibrino-peptide B as the lock-mass. The ion (M + 2H)2+ at m/z 785.8426 was used to calibrate MS data and the fragment ion (M + H)+ at m/z 684.3469 was used to calibrate MS/MS data during the analysis.

For tandem MS experiments, the system was operated with automatic switching between the MS (0.5 s per scan in the m/z range [150;1700]) and MS/MS mode (0.5 s per scan in the m/z range [50;2000]). The two most abundant peptides (intensity threshold 20 counts per s), preferably doubly and triply charged ions, were selected in each MS spectrum for further isolation and CID fragmentation using a collision energy profile. Fragmentation was performed using argon as the collision gas.

Mass data collected during analysis were processed and converted into .pkl files using ProteinLynx Global Server 2.3 (Waters Corporation, Milford, USA). Normal background subtraction was used for both MS and MS/MS with a 5% threshold and polynomial correction of order 5. Smoothing was performed on MS/MS spectra (Savitzky–Golay, 2 iterations, window of 3 channels). Deisotoping was applied for MS (medium deisotoping) and for MS/MS (fast deisotoping).

The TripleTOF 5600 (Sciex, Ontario, Canada) was operated in positive mode, with the following settings: ion spray voltage floating (ISVF) 2300 V, curtain gas (CUR) 10, interface heater temperature (IHT) 150, ion source gas 1 (GS1) 2, declustering potential (DP) 80 V. The information-dependent acquisition (IDA) mode was used with Top 10 MS/MS scans. The MS scan had an accumulation time of 250 ms in the m/z [400;1250] range and the MS/MS scans 100 ms in the m/z [150;1800] range in high sensitivity mode. Switching criteria were set to ions with a charge state of 2–4 and an abundance threshold of more than 500 counts; the exclusion time was set at 4 s. The IDA rolling collision energy script was used for automatically adapting the CE. Mass calibration of the analyser was achieved using peptides from digested BSA. The complete system was fully controlled by AnalystTF 1.7 (Sciex). Raw data collected were processed and converted with MSDataConverter in the .mgf peak list format.

For protein identification, the MS/MS data were interpreted using a local Mascot server with the MASCOT 2.4.1 algorithm (Matrix Science, London, UK) against UniProtKB/SwissProt (version 2016_01, 550[thin space (1/6-em)]299 sequences). The research was carried out in all species. Spectra were searched with a mass tolerance of 15 ppm for MS and 0.05 Da for MS/MS data, allowing a maximum of one trypsin missed cleavage. Carbamidomethylation of cysteine residues and oxidation of methionine residues were specified as variable modifications. Protein identifications were validated with at least two peptides with a Mascot ion score above 30.

2.11 Electron microscopy

J774 macrophage cells were grown on coverslips and treated with AgNPs as described above. Cells were allowed to recover for 72 hours before being fixed with 2.5% glutaraldehyde in 0.1 M cacodylate buffer (pH 7.4) for 2 hours at room temperature. Cells were then washed with buffer, post fixed with 1% osmium tetroxide in the same buffer for 1 hour at 4°, and washed with water. Cells were then dehydrated through a series of graded alcohol (30–60–90–100–100–100%) and infiltrated with a mix of 1/1 epon/alcohol (100%) for 1 hour before several baths of fresh epon (Fluka) for 3 hours. Finally, a capsule full of epon was placed on the surface of the cells and the resin was allowed to polymerise for 72 h at 60 °C. The polymerised bloc was then detached from the coverslip with HF (48%) over 1 hour. Ultrathin sections of the cell monolayer were cut with an ultramicrotome (Leica). For transmission electron microscopy (TEM) observation, the sections were post-stained with 5% uranyl acetate and 0.4% lead citrate and observed with a transmission electron microscope at 80 kV (JEOL 1200EX). Images were acquired with a digital camera at magnification ranging from 15k to 50k (Veleta, Olympus). For scanning transmission electron microscopy observation (STEM) and energy dispersive spectroscopic analysis (EDS), the sections were not post-stained. They were coated with a thin layer of carbon and observed and analyzed with an OSIRIS microscope (TECNAI) operating at 200 kV.

3. Results

3.1 Silver accumulation upon treatment with silver nanoparticles and after recovery

First, the effect of silver nanoparticles and soluble silver on cell viability was assayed, and the results are shown in Fig. 1. For all the subsequent experiments, a dose of 20 μg ml−1 was selected, corresponding to the lethal dose 20% (LD20). This dose ensures strong effects on cells while keeping cellular mortality at an acceptable level for subsequent experiments. We also checked the presence of nanoparticles in cells by electron microscopy. Control cells did not show any electron-dense materials (Fig. 2A and B), while cells exposed to Ag nanoparticles acutely showed some electron-dense particles located in large membrane compartments called macropinosomes (Fig. 2C and D). After the recovery period, these electron dense particles were still observed in the macropinosomes (Fig. 2E and F). Energy dispersive spectroscopic analysis of these electron-dense features confirmed that they contained Ag (Fig. 2G–I).
image file: c9en00408d-f1.tif
Fig. 1 Dose response curve to silver nanoparticles and ionic silver. Cell viability was measured by dye exclusion. The cells were exposed to silver nanoparticles (panel A) or silver lactate (panel B) for 24 hours before measurement of cell viability (n = 3).

image file: c9en00408d-f2.tif
Fig. 2 Ag distribution in macrophages. Control cells (A and B) or cells exposed to Ag nanoparticles (C–G) were imaged by transmission electron microscopy (A–F) or scanning transmission electron microscopy (G). Panels A and B: control cells; panels C and D: cells acutely exposed to Ag nanoparticles; panels E and F: recovering cells. A, C and E: High contrast images; B, D and F: low contrast images highlighting the presence of electron-dense materials, which are probably Ag nanoparticles or debris of Ag nanoparticles (*). Panel G is a HAADF image of a multilamellar body containing electron-dense materials. H and I: Chemical element distribution of the area of G delimited by the white square, analyzed by energy dispersive spectroscopy. Panel H shows the Ag distribution and panel I shows the EDS spectra of area1 (an intracellular region containing some Ag) and area2 (an intracellular region that does not contain any Ag) of H.

Silver accumulation in cells was measured by ICP-MS. The results are summarized in Table 1. They showed a strong accumulation of silver in cells at the end of the 24 hour exposure followed by a moderate loss of total silver. The cells were able to cycle once during the 72 h recovery period, as shown by the increase in the protein amount in the extracts, which resulted in a further reduction of the cellular silver content. A moderate but detectable silver excretion was also evidenced. It should be also noted that the protein concentration is used in toxicology as an indicator for cell number,67,68

Table 1 Measurements of silver concentrations
Unexposed Exposed to 20 μg ml−1 AgNPs 72 h recovery after exposure to AgNPs
a This value contains both the soluble silver that is actively excreted by cells during the exposure and the soluble silver that arises from nanoparticle dissolution directly in the culture medium. b Defined as soluble silver in medium/total silver (i.e. silver in medium + silver in cells).
Protein concentration in the cell extract (mg ml−1) 0.352 ± 0.02 0.322 ± 0.02 0.657 ± 0.04
Total silver concentration in the cell extract (μg l−1) 0 9794 ± 1159 8258 ± 1536
Soluble silver concentration in the cell extract (μg l−1) 0 39.86 ± 11.83 47.57 ± 3.11
Soluble silver concentration in culture medium (μg l−1) 457 ± 64a 142 ± 4
Normalized silver content (ng Ag mg−1 protein) 0 30[thin space (1/6-em)]608 ± 5055 12[thin space (1/6-em)]530 ± 1984
Soluble silver fraction in cells 0 0.0041 ± 0.0014 0.0059 ± 0.001
Fraction of silver excretedb 0 ND 0.017 ± 0.003

3.2 Global analysis of the proteomic results

From the total protein expression data obtained from the gel analysis software, a subset of variable proteins (p < 0.25 in either the acute vs. control or the recovery vs. control comparisons) was extracted. This allowed the noise brought by proteins that do not show a consistent variation in the biological phenomena under investigation to be decreased. This subset was then tested using the PAST statistical suite.64 As a first test, a hierarchical clustering was performed, and the results are shown in Fig. 3A. Clustering clearly separates the control group from the two silver-treated ones, but gives no information regarding which silver treatment condition is closer to the control. Principal component analysis gave a more valuable indication, as shown in Fig. 3B. The recovery group appeared to be in an intermediate position between the control and acute groups along component one, which carries most of the variance. This is an expected position in a “return to normal” model during the recovery phase. However, the recovery group separated from both the control and the acute groups in component 2. This suggested that the three conditions were fairly different from each other. This was further confirmed by analysis of similarities (ANOSIM), which gave the following results for the p-values of the pairwise comparisons:
image file: c9en00408d-f3.tif
Fig. 3 Global analysis of proteomic data. Global data analysis was performed on the proteomic data to derive the relationships between the various samples used. Panel A: Hierarchical clustering. The Euclidean distance similarity index and Ward's algorithm were used for this analysis. C1–C4: Control (non-exposed) cells. A1–A4: Acutely exposed cells (24 hours). R1–R4: Recovering cells (72 hours post-exposure). Panel B: Principal component analysis. A representation displaying the first two principal components is shown. The PCA yielded 11 components, of which the first two, represented in the figure, explained 70% of the total variance (axis 1 – 54%, axis 2 – 16%). Component 3 explained 7.5% of the variance, component 4 explained 6%, and the remaining components explained less than 4% of the variance each. Samples labelled as in panel A.

p = 0.031 for the acute vs. control comparison

p = 0.032 for the recovery vs. control comparison

p = 0.027 for the acute vs. recovery comparison
These figures suggest that the recovery phase was a very active state, which did not represent just an intermediate state between the control and the acute stage, i.e. immediately after exposure to silver nanoparticles. To further investigate this aspect, we extracted the intensity values for the spots that were significantly altered (p < 0.05) between the control group and at least one of the silver-treated groups. In order to cope with the multiple testing issue, we used several approaches such as the Benjamini Hochberg approach,61 the sequential goodness of fit approach62 and the sequential Fisher test approach.63 All the selected spots showed a very low q-value for the condition for which they were variable compared to the control (Table S1).

We then divided this dataset of 239 spots into lists (Table S2). The first list, labelled as “returning spots”, contained the spots for which the amplitude of the change in abundance between the recovery and control stages is lower than the amplitude of the change in abundance between the acute exposure and control stages. 135 spots belonged to this list. It was then divided into subsets. The first subset contained “fast returning spots”. It was defined as spots for which the quantitative change in the acute vs. control comparison shows an amplitude at least twice that in the recover vs. control comparison (i.e. more than 50% convergence). 44 spots belonged to this subset. The other subset of this list contained the 91 “slow returning spots”, for which the return-to-normal trend was lower than 50% in the 72 hour recovery period.

The other list, labelled as “diverging spots”, contained the 104 spots for which the amplitude of the change in abundance between the recovery and control stages is higher than the amplitude of the change in abundance between the acute exposure and control stages. This list was also divided into subsets. The “fast diverging spots” subset was defined as the spots for which the quantitative change in the recover vs. control comparison was at least 1.5 higher than the quantitative change in the acute vs. control comparison (i.e. more than 50% divergence). 53 spots belonged to this subset. The other subset of this list contained the 51 “slow diverging spots”, for which the diverging trend was lower than 50% in the 72 hour recovery period.

3.3 Detailed analysis of the proteomic results

In order to gain more precise insights, we investigated which proteins were significantly altered (p < 0.05) between the control group and at least one of the silver-treated groups. The list of modulated proteins is given in Table 2 and the corresponding 2D gel images are shown in Fig. 4. As 2D gels separate protein forms, a variation in a spot does not necessarily mean that the whole amount of the protein is modulated. In fact, a single protein can be represented by various 2D gel spots, which do not necessarily all change upon the treatment with nanoparticles. To alleviate this problem, we systematically identified by mass spectrometry not only the modulated spots, but also the neighboring spots to check for such isoform issues. The quantitative results have been integrated in Table 2 and the mass spectrometry identification parameters are detailed in Table S3. The results for some classes (apoptosis, cell fate and energy metabolism) are also shown in gel images in Fig. 4, and the results for the other classes are shown in Fig. S1–S5. For global analysis of the modulated proteins, we used the DAVID annotation tool,69,70 available at, and the results are shown in Tables S4 and S5. The results showed that some functional classes such as energy metabolism, cytoskeleton especially actin cytoskeleton, protein folding and quality control (especially the ubiquitin/proteasome pathway), nucleotide and nucleic acid metabolism, cell signaling, oxidative stress response and detoxification proteins are strongly represented among the modulated proteins. This prompted us to carry out validation experiments on some of these proteins or pathways.
Table 2 Differentially-expressed proteins identified in the proteomic screen
Spot number Protein name Accession number Ratio acute/ctrl T test acute vs. ctrl Ratio recov/ctrl T test recov vs. ctrl
∑: sum of the different spots identified for the same protein.
A1 Casp3 P70677 0.59 0.04 1.00 0.99
A2 Efhd2 Q9D8Y 1.24 0.02 1.18 0.23
C1 Actin P60710 1.51 <0.01 1.67 0.01
C2a Actn4/1 P57780 1.45 0.04 1.18 0.16
C2b Actn4/2 P57780 1.43 0.04 1.38 0.01
C2c Actn4/3 P57780 1.25 0.33 1.17 0.03
C2d Actn4/4 P57780 1.44 0.20 1.28 0.05
C2S ∑ Actn4 P57780 1.36 0.16 1.23 0.02
C3a Arp2/1 P61161 0.90 0.06 0.76 <0.01
C3b Arp2/2 P61161 1.10 0.41 0.94 0.63
C3c Arp2/3 P61161 1.19 0.04 1.32 <0.01
C3S ∑ Arp2 P61161 1.15 0.07 1.14 0.06
C4a Arpc2/1 Q9CVB6 0.57 0.03 0.52 0.02
C4b Arpc2/2 Q9CVB6 0.76 0.04 0.78 0.06
C4c Arpc2/3 Q9CVB6 0.91 0.51 1.12 0.41
C4S ∑Arpc2 Q9CVB6 0.80 0.11 0.90 0.39
C5a Arpc5/1 Q9CPW4 0.59 0.03 0.25 0.01
C5b Arpc5/2 Q9CPW4 1.06 0.51 0.99 0.90
C5S ∑ Arpc5 Q9CPW4 0.88 0.30 0.71 0.04
C6a Capg/1 P24452 0.81 0.01 1.00 0.97
C6b Capg/2 P24452 1.16 0.15 1.04 0.58
C6S ∑ capg P24452 0.35 0.39 0.35 0.39
C7 Capza2 P47754 1.30 0.01 1.28 0.01
C8a Capzb/1 P47757 1.07 0.37 1.20 0.06
C8b Capzb/2 P47757 0.80 0.02 1.01 0.95
C8S ∑ capzb P47757 0.98 0.60 1.13 0.14
C9a Cof/1 P18760 0.67 0.05 0.60 0.03
C9b Cof/2 P18760 1.49 0.01 1.26 0.10
C9c Cof/3 P18760 0.74 <0.01 0.73 <0.01
C9S ∑ Cof P18760 0.86 0.02 0.79 <0.01
C10a Dyncli2/1 O88487 1.21 0.49 2.20 <0.01
C10b Dyncli2/2 O88487 1.43 0.26 1.69 0.04
C10S ∑ dyncli2 O88487 1.36 0.30 1.84 0.01
C11a Gelsolin/1 P13020 1.16 0.44 0.94 0.71
C11b Gelsolin/2 P13020 1.16 0.36 1.00 0.97
C11c Gelsolin/3 P13020 1.39 0.16 1.27 0.26
C11d Gelsolin/4 P13020 1.57 0.05 1.32 0.13
C11S ∑ gelsolin P13020 1.33 0.15 1.15 0.39
C12 Gmfg Q9ERL7 0.54 <0.01 0.66 <0.01
C13 Lasp1 Q61792 0.41 <0.01 0.38 <0.01
C14 Ml12b Q3THE2 0.92 0.51 0.81 0.01
C15a Moesin/1 P26041 0.94 0.75 0.86 0.41
C15b Moesin/2 P26041 0.90 0.53 0.78 0.08
C15c Moesin/3 P26041 1.22 0.17 0.89 0.13
C15d Moesin/4 P26041 1.18 0.07 1.09 0.10
C15e Moesin/5 P26041 1.52 0.03 1.24 0.04
C15S ∑ Moesin P26041 1.20 0.08 1.01 0.91
C16 Mtap Q9CQ65 1.04 0.83 1.30 0.02
C17 RhoA Q9QUI0 0.59 <0.01 0.76 0.02
C18a Rhogdi1/1 Q99PT1 0.71 <0.01 0.67 <0.01
C18b Rhogdi1/2 Q99PT1 1.16 0.13 1.11 0.08
C18S ∑ RhoGdi1 Q99PT1 0.99 0.85 0.95 0.28
C19a Rhogdi2/1 Q61599 0.64 <0.01 0.54 <0.01
C19b Rhogdi2/2 Q61599 1.00 0.99 0.95 0.17
C19S ∑ rhogdi2 Q61599 0.87 0.02 0.80 <0.01
C20a Stmn/1 P54227 0.84 0.19 0.70 0.01
C20b Stmn/2 P54227 0.60 0.02 0.53 0.01
C20c Stmn/3 P54227 0.88 0.14 0.76 0.01
C20S ∑ Stmn P54227 0.83 0.05 0.71 0.01
C21a Sw70/1 Q6A028 1.63 0.02 1.50 0.20
C21b Sw70/2 Q6A028 2.02 0.02 1.76 0.08
C21S ∑ Sw70 Q6A028 1.77 0.01 1.60 0.14
C22 Tbcb Q9D1E6 1.31 0.03 1.11 0.45
C23a Tctp/1 P63028 0.60 <0.01 0.54 <0.01
C23b Tctp/2 P63028 0.84 0.03 0.85 0.05
C23S ∑ Tctp P63028 0.84 0.03 0.72 <0.01
C24a Twf1/1 Q91YR1 0.58 <0.01 0.93 0.39
C24b Twf1/2 Q91YR1 0.25 0.01 0.86 0.52
C24S ∑ Twf1 Q91YR1 0.40 <0.01 0.89 0.47
C25 Twf2 Q9Z0P5 0.70 0.01 0.60 0.01
C26 Vime P20152 1.54 0.05 1.35 0.04
C27a Vinculin/1 Q64727 1.28 0.25 1.24 0.11
C27b Vinculin/2 Q64727 1.32 0.07 1.16 0.24
C27c Vinculin/3 Q64727 1.63 0.01 1.12 0.28
C27S ∑ Vinculin Q64727 1.39 0.07 1.18 0.16
D1 Cbx1 P83917 0.91 0.27 0.72 <0.01
D2a Ddb1/1 Q3U1J4 1.74 0.04 1.40 0.16
D2b Ddb1/2 Q3U1J4 0.93 0.65 0.78 0.21
D2S ∑ Ddb1 Q3U1J4 1.31 0.14 1.07 0.73
D3 Nt5c Q9JM14 1.18 0.08 1.39 0.03
D4a Pcna/1 P17918 0.57 <0.01 0.57 <0.01
D4b Pcna/2 P17918 0.82 0.02 0.80 0.03
D4c Pcna/3 P17918 1.00 0.92 0.98 0.73
D4S ∑ Pcna P17918 0.84 <0.01 0.82 0.02
D5 Ruvb2 Q9WTM5 1.46 0.06 1.42 0.04
E1a 6pgd/1 Q9DCD0 0.88 0.05 0.95 0.42
E1b 6pgd/2 Q9DCD0 1.05 0.32 1.01 0.90
E1S ∑ 6pgd Q9DCD0 0.98 0.45 0.99 0.82
E2a Aacs/1 Q9D2R0 1.79 0.11 1.39 0.52
E2b Aacs/2 Q9D2R0 3.12 0.01 2.56 <0.01
E2S ∑ Aacs Q9D2R0 2.17 0.01 1.73 0.16
E3 Acadl P51174 1.13 0.14 1.27 0.01
E4a Eno1a/1 P17182 0.99 0.96 0.89 0.28
E4b Eno1a/2 P17182 1.10 0.50 0.89 0.42
E4c Eno1a/3 P17182 1.18 0.10 1.21 0.10
E4d Eno1a/4 P17182 1.50 <0.01 1.42 <0.01
E4S ∑ Eno1A P17182 1.26 0.02 1.19 0.06
E5 GalK Q9R0N0 1.45 <0.01 1.50 0.03
E6 Gapdh P16858 0.56 <0.01 0.60 <0.01
E7 Gpd1L Q3ULJ0 2.27 <0.01 1.42 0.14
E8a Hxk3/1 Q3TRM8 1.91 0.02 1.80 0.03
E8b Hxk3/2 Q3TRM8 1.23 0.04 1.22 0.09
E8c Hxk3/3 Q3TRM8 1.52 0.02 1.52 0.02
E8S ∑ Hxk3 Q3TRM8 1.51 0.01 1.49 0.01
E9 Idhc O88844 1.24 0.02 1.19 <0.01
E10a Ldha/1 P06151 0.79 0.02 0.86 0.06
E10b Ldha/2 P06151 0.97 0.81 0.89 0.40
E10S ∑ Ldha P06151 0.89 0.26 0.88 0.21
E11a Mdhc/1 P14152 0.47 0.02 0.72 0.11
E11b Mdhc/2 P14152 0.83 0.01 0.84 0.01
E11c Mdhc/3 P14152 1.38 0.02 1.40 <0.01
E11S ∑ Mdhc P14152 1.01 0.91 1.05 0.20
E12 Pckgm Q8BH04 1.30 0.20 0.61 0.01
E13 Pfkap Q9WUA3 0.84 0.01 0.86 0.01
E14 Pfkl P12382 1.83 0.01 1.62 0.03
E15a Pgls/1 Q9CQ60 0.78 0.02 0.97 0.75
E15b Pgls/2 Q9CQ60 1.11 0.16 1.22 0.01
E16 Pgp Q8CHP8 1.37 0.02 1.60 0.05
E17a Taldo1 Q93092 0.80 0.02 0.66 <0.01
E17b Taldo/2 Q93092 1.17 0.12 1.18 0.08
E17c Taldo/3 Q93092 1.24 0.02 1.23 <0.01
E17d Taldo/4 Q93092 0.81 0.06 0.79 0.02
E17e Taldo/5 Q93092 1.22 0.06 1.36 0.02
E17S ∑ Taldo Q93092 1.08 0.16 1.09 0.06
E18a Tpis/1 P17751 0.74 0.01 0.82 0.04
E18b Tpis/2 P17751 1.04 0.61 1.20 0.09
E18c Tpis/3 P17751 1.45 0.04 1.43 0.05
E18S ∑ Tpis P17751 1.09 0.29 1.16 0.17
F1 Cdk4 P30285 0.69 <0.01 0.71 <0.01
F2 Cdk6 Q64261 0.71 0.04 0.77 0.02
F3a Ndrg1/1 Q62433 1.32 0.09 1.52 0.04
F3b Ndrg1/2 Q62433 1.38 0.01 1.33 0.02
F3S ∑ ndrg1 Q62433 1.34 0.02 1.44 0.03
F4 Pa2 g4 P50580 1.50 <0.01 1.31 0.01
F5a Vma5a/1 Q99KC8 1.60 0.06 0.99 0.97
F5b Vma5a/2 Q99KC8 1.31 0.11 1.19 0.10
F5c Vma5a/3 Q99KC8 1.84 <0.01 1.59 0.02
F5S ∑ Vma5a Q99KC8 1.54 0.02 1.25 0.12
G1 GalE Q8R059 0.50 0.03 1.09 0.50
G2 Gnpda1 O88958 0.47 <0.01 0.63 0.01
G3 Gt25c Q8K297 1.53 0.01 1.48 0.01
G4 Mlec Q6ZQI3 1.49 0.02 1.79 <0.01
G5a Naga/1 Q8JZV7 1.19 0.07 1.19 0.06
G5b Naga/2 Q8JZV7 1.05 0.56 1.18 0.08
G5S ∑ Naga Q8JZV7 1.12 0.16 1.19 0.06
H1 Adh5 P28474 0.72 0.09 0.74 0.11
H2a Aldr/1 P45376 0.57 0.01 0.66 0.01
H2b Aldr/2 P45376 0.84 0.09 0.73 0.04
H2c Aldr/3 P45376 1.18 0.04 1.25 0.01
H2S ∑ Aldr P45376 0.85 0.02 0.89 0.10
H3 Aldr2 P47738 1.16 0.08 1.23 <0.01
H4a Bvra/1 Q9CY64 0.54 0.02 0.62 0.03
H4b Bvra/2 Q9CY64 1.23 0.08 1.30 0.06
H4S ∑ Bvra Q9CY64 0.98 0.81 1.06 0.54
H5 Bvrb Q923D2 1.45 0.01 0.96 0.77
H6 Ca13 Q9D6N1 0.62 0.01 0.83 0.11
H7a Esd/1 Q9R0P3 0.56 <0.01 0.64 0.01
H7b Esd/2 Q9R0P3 0.78 <0.01 0.92 0.15
H7S ∑ Esd Q9R0P3 0.73 <0.01 0.86 0.02
H8 Frih P09528 0.61 0.01 0.67 0.02
H9 Gclm O09172 1.32 0.01 0.98 0.86
H10 Hmox2 O70252 1.53 <0.01 1.03 0.69
H11a Lgul/1 Q9CPU0 0.80 0.04 0.77 0.05
H11b Lgul/2 Q9CPU0 1.10 0.24 1.10 0.16
H11S ∑ Lgul Q9CPU0 1.00 0.99 1.00 0.96
L1 Anxa1 P10107 0.78 0.02 1.11 0.06
L2a Anxa2/1 P07356 0.79 0.01 0.60 <0.01
L2b Anxa2/2 P07356 0.44 <0.01 0.56 <0.01
L2S ∑ Anxa2 P07356 0.67 <0.01 0.59 <0.01
L3 Anxa3 O35639 1.34 0.01 1.30 0.02
L4 Anxa4 P97429 1.30 0.01 1.33 <0.01
L5a Anxa5/1 P48036 0.88 0.02 0.81 <0.01
L5b Anxa5/2 P48036 1.09 0.34 1.07 0.37
L5S ∑ Anxa5 P48036 0.95 0.35 0.90 0.08
L6 Anxa6 P14824 1.54 0.02 1.80 <0.01
L7 Anxa7 Q07076 1.14 0.44 1.57 0.02
L8 Idi1 P58044 1.40 0.02 1.34 0.01
L9 Lypla2 Q9WTL7 1.07 0.28 1.22 0.02
L10 Mbd3 Q9Z2D8 1.52 0.02 1.77 <0.01
L11 Pipna P53810 1.22 0.11 1.32 0.01
L12 Ppt1 O88531 1.24 0.14 1.34 0.03
M1a Clic4/1 Q9QYB1 0.90 0.12 0.95 0.58
M1b Clic4/2 Q9QYB1 1.27 0.02 1.27 0.04
M1S ∑ Clic4 Q9QYB1 1.12 0.04 1.14 0.01
M2 Clybl Q8R4N0 1.80 0.03 1.41 0.19
M3 Gatm Q9D964 0.68 0.01 0.54 0.01
M4 Hmgcl P38060 0.61 <0.01 0.76 0.07
M5 Nduv2 Q9D6J6 1.24 0.01 1.49 0.05
M6 Oat P29758 1.30 0.05 1.50 0.01
M7 Odba P50136 1.54 0.02 1.28 0.12
M8 Phb P67778 1.12 0.16 1.18 0.05
M9 Tmem11 Q8BK08 1.78 0.04 1.46 0.41
M10 Vdac2 Q60930 0.63 0.02 0.72 0.05
M11a Atpb ac P56480 1.23 0.16 1.41 0.03
M11b Atpb bas P56480 1.60 0.04 1.58 <0.01
M11S ∑Atpb P56480 1.41 0.06 1.49 <0.01
M12 Clpp O88696 1.28 0.33 1.84 0.02
M13a Trap1/1 Q9CQN1 1.74 0.02 1.32 0.13
M13b Trap1/2 Q9CQN1 1.21 0.25 0.92 0.64
M13S ∑Trap1 Q9CQN1 1.47 0.03 1.11 0.51
N1a Aprt/1 P08030 0.52 <0.01 0.72 <0.01
N1b Aprt/2 P08030 1.06 0.43 1.08 0.39
N1S ∑ Aprt P08030 0.92 0.19 0.99 0.85
N2 Bpnt1 Q9Z0S1 1.77 0.02 1.87 0.01
N3 Guaa Q3THK7 1.42 0.02 1.12 0.25
N4 Hint1 P70349 1.46 0.30 0.64 0.02
N5 Ndka P15532 0.42 0.03 0.75 0.22
N6 Paps1 Q60967 5.54 0.04 2.44 0.01
N7a Pnph/1 P23492 0.83 0.12 0.72 0.05
N7b Pnph/2 P23492 1.25 0.02 1.22 0.08
N7S ∑ Pnph P23492 1.08 0.17 1.02 0.76
N8a Prps1/1 Q9D7G0 0.69 0.01 0.92 0.48
N8b Prps1/2 Q9D7G0 0.57 <0.01 0.77 0.16
N8c Prps1/3 Q9D7G0 0.52 0.01 0.83 0.21
N8S ∑ Prps1 Q9D7G0 0.60 <0.01 0.83 0.14
N9a Pur4/1 Q5SUR0 1.71 0.14 1.27 0.07
N9b Pur4/2 Q5SUR0 2.53 0.01 2.01 0.01
N9c Pur4/3 Q5SUR0 1.15 0.53 1.25 0.22
N9S ∑ Pur4 Q5SUR0 1.65 0.07 1.43 0.01
N10 Pur9 Q9CWJ9 1.16 0.27 1.23 0.01
N11 Nt5c3b Q3UFY7 1.55 <0.01 1.64 0.01
O1 Prx1ox P35700 0.58 0.02 0.70 0.04
O2a Prx3/1 P20108 0.93 0.69 1.13 0.08
O2b Prx3/2 P20108 1.23 0.06 1.32 0.01
O2S ∑ Prx3 P20108 1.16 0.22 1.27 0.01
O3 Prx4 O08807 0.75 0.06 0.56 0.01
O4a Prx6/1 O08709 0.56 0.02 0.45 0.01
O4b Prx6/2 O08709 1.05 0.64 0.97 0.76
O4S ∑ Prx6 O08709 0.96 0.63 0.87 0.23
P1 Aars Q8BGQ7 1.65 0.01 1.18 0.20
P2a Eef2/1 P58252 0.77 0.02 0.63 <0.01
P2b Eef2/2 P58252 1.06 0.41 0.96 0.39
P2c Eef2/3 P58252 0.84 0.07 0.90 0.20
P2d Eef2/4 P58252 0.99 0.88 0.98 0.61
P2e Eef2/5 P58252 1.39 0.01 1.29 0.01
P2S ∑ Eef2 P58252 1.02 0.72 0.97 0.43
P3 If3g Q9Z1D1 0.77 0.31 0.56 0.03
P4a If5a/1 P63242 0.54 <0.01 0.62 <0.01
P4d If5a/2 P63242 1.07 0.26 1.03 0.58
P4S ∑ If5a P63242 0.86 0.04 0.87 0.04
P5 If4a1 P60843 1.55 0.01 1.51 0.01
P6 If4a3 Q91VC3 1.27 0.05 1.09 0.28
P7 Rla0 P14869 1.28 0.07 1.33 0.04
P8 Rs4y1 P62702 0.50 0.04 0.62 0.07
P9a Sars/1 P26638 1.42 0.03 1.05 0.59
P9b Sars/2 P26638 1.52 0.04 1.10 0.42
P9S ∑ Sars P26638 1.48 0.02 1.08 0.46
Q1a Dpp3/1 Q99KK7 1.28 0.22 1.75 <0.01
Q1b Dpp3/2 Q99KK7 1.55 0.04 1.84 <0.01
Q1S ∑ Dpp3 Q99KK7 1.40 0.09 1.79 <0.01
Q2a Hsp74/1 Q61316 0.77 0.22 0.77 0.23
Q2b Hsp74/2 Q61316 1.33 0.08 1.18 0.23
Q2c Hsp74/3 Q61316 1.31 0.09 1.14 0.29
Q2d Hsp74/4 Q61316 1.26 0.15 1.31 <0.01
Q2S ∑ Hsp74 Q61316 1.07 0.58 1.03 0.80
Q3a Hyou1/1 Q9JKR6 1.18 0.25 0.83 0.20
Q3b Hyou1/2 Q9JKR6 1.38 0.01 1.18 0.03
Q3c Hyou1/3 Q9JKR6 1.35 0.01 1.21 0.05
Q3d Hyou1/4 Q9JKR6 0.80 0.23 0.79 0.11
Q3S ∑ Hyou1 Q9JKR6 1.04 0.67 0.93 0.27
Q4 Lxn P70202 0.98 0.80 1.26 <0.01
Q5 Pfd2 O70591 0.72 0.01 0.70 0.01
Q6a Ppce/1 Q9QUR6 1.40 0.15 1.78 0.01
Q6b Ppce/2 Q9QUR6 1.58 0.04 1.66 0.01
Q6S ∑ Ppce Q9QUR6 1.50 0.07 1.71 0.01
Q7a Ppia/1 P17742 0.68 0.11 0.57 0.05
Q7b Ppia/2 P17742 0.80 0.21 0.79 0.21
Q7c Ppia/3 P17742 0.81 0.09 0.99 0.97
Q7S ∑ Ppia P17742 0.78 0.09 0.83 0.21
Q8a Spb6/1 Q60854 1.66 0.02 1.49 0.01
Q8b Spb6/2 Q60854 1.43 0.01 1.42 0.01
Q8S ∑ Spb6 Q60854 1.57 0.01 1.46 <0.01
Q9 Stip1 Q60864 1.72 <0.01 0.94 0.67
Q10 Tcpa P11983 1.55 0.02 1.09 0.55
R1a Btf3/1 Q64152 0.56 0.01 0.50 0.01
R1b Btf3/2 Q64152 0.76 0.05 0.76 0.05
R1S ∑ Btf3 Q64152 0.66 0.02 0.64 0.01
R2 Dcps Q9DAR7 1.30 <0.01 1.20 0.02
R3 Ddx39a Q8VDW0 1.64 0.03 1.31 0.02
R4 Ddx39b Q9Z1N5 1.59 0.03 1.35 0.11
R5 Mgn P61327 0.96 0.60 0.56 0.01
R6a Sf3b2/1 Q3UJB0 1.03 0.91 0.87 0.49
R6b Sf3b2/2 Q3UJB0 1.16 0.44 1.32 <0.01
R6c Sf3b2/3 Q3UJB0 1.26 0.38 1.80 <0.01
R6S ∑ Sf3b2 Q3UJB0 1.13 0.54 1.27 0.03
R7 ExoS4 Q921I9 0.88 0.42 0.51 0.02
R8 ExoS6 Q8BTW3 1.50 0.02 1.53 0.01
S1a 14-3-3 gam/1 P61982 0.85 0.28 0.67 0.02
S1b 14-3-3 gam/2 P61982 0.83 0.06 0.91 0.24
S1S ∑ 14-3-3 gam P61982 0.84 0.10 0.82 0.07
S2 14-3-3 th P68254 1.31 0.01 1.19 0.04
S3 Cab39 Q06138 0.70 0.03 0.62 <0.01
S4 Fam49b Q921M7 1.47 0.02 1.59 0.05
S5 Gbb1 P62874 1.17 0.03 1.18 0.03
S6a Gnai2/1 P08752 1.33 0.06 1.42 0.05
S6b Gnai2/2 P08752 1.51 <0.01 1.67 0.01
S6S ∑ Gnai2 P08752 1.45 0.01 1.59 0.02
S7 Gnb2L1 P68040 0.89 0.02 0.81 <0.01
S8 Grb2 Q60631 1.06 0.83 1.46 0.02
S9 Igbp1 Q61249 1.36 0.06 1.36 0.04
S10 In35 Q9D8C4 1.25 0.04 1.21 0.14
S11 Inpp P49442 2.46 0.01 1.76 0.17
S12 Ppp1ca P62137 1.17 0.07 1.27 0.02
S13a Ppp1r7/1 Q3UM45 0.30 0.02 0.38 0.04
S13b Ppp1r7/2 Q3UM45 0.67 0.02 0.73 0.08
S13c Ppp1r7/3 Q3UM45 0.90 0.51 0.94 0.72
S13S ∑ Ppp1r7 Q3UM45 0.61 0.03 0.68 0.06
S14 Ppp6 O00743 1.48 0.03 1.04 0.82
S15a Snd1/1 Q78PY7 0.65 0.03 0.66 0.04
S15b Snd1/2 Q78PY7 0.59 0.02 0.50 0.01
S15c Snd1/3 Q78PY7 0.89 0.34 0.78 0.18
S15d Snd1/4 Q78PY7 1.11 0.34 0.91 0.47
S15S ∑ Snd1 Q78PY7 0.79 <0.01 0.70 0.01
U1 Chip Q9WUD1 0.59 <0.01 0.73 0.11
U2 Csn4 O88544 1.34 0.03 1.37 0.03
U3a Prs8/1 P62196 0.60 <0.01 0.65 <0.01
U3b Prs8/2 P62196 0.85 0.04 0.85 0.22
U3S ∑ Prs8 P62196 0.31 0.33 0.32 0.34
U4a Psa2/1 P49722 0.58 <0.01 0.58 <0.01
U4b Psa2/2 P49722 1.15 0.12 1.28 0.07
U4S ∑ Psa2 P49722 0.86 0.04 0.92 0.36
U5a Psa5/1 Q9Z2U1 0.80 0.01 0.84 0.11
U5b Psa5/2 Q9Z2U1 0.92 0.33 0.99 0.83
U5S ∑ Psa5 Q9Z2U1 0.86 0.07 0.92 0.22
U6 Psb10 O35955 0.73 0.12 0.43 0.02
U7a Psb2/1 Q9R1P3 0.67 0.02 0.76 0.14
U7b Psb2/2 Q9R1P3 0.90 0.36 1.01 0.91
U7S ∑ Psb2 Q9R1P3 0.82 0.09 0.92 0.50
U8 Psb3 mod Q9R1P1 0.47 0.01 0.65 <0.01
U9a Psb4/1 P99026 0.74 0.05 0.69 0.03
U9b Psb4/2 P99026 0.98 0.71 0.94 0.25
U9S ∑ Psb4 P99026 0.90 0.05 0.86 0.01
U10 Psmd14 O35593 1.03 0.61 1.32 <0.01
U11a Psmd2/1 Q8VDM4 0.82 0.22 1.12 0.24
U11b Psmd2/2 Q8VDM4 1.10 0.11 1.09 0.02
U11c Psmd2/3 Q8VDM4 1.39 0.02 1.13 0.17
U11S ∑ Psmd2 Q8VDM4 1.03 0.70 1.12 0.12
U12 Psmd7 P26516 0.68 0.03 0.68 0.02
U13 Psme1 P97371 1.40 <0.01 1.40 <0.01
U14a Psme2/1 P97372 1.00 0.98 0.71 <0.01
U14b Psme2/2 P97372 1.22 <0.01 1.07 0.34
U14S ∑ Psme2 P97372 1.15 <0.01 0.96 0.50
U15 Ubl7 Q91W67 0.41 0.02 0.88 0.55
V1 Asna1 O54984 1.29 0.09 1.46 <0.01
V2 Chm2a Q9DB34 0.83 <0.01 0.92 0.09
V3 CopE O89079 1.35 0.01 1.41 0.07
V4 Emc2 Q9CRD2 0.56 0.01 0.84 0.07
V5 Erp29 P57759 0.78 0.12 0.68 0.05
V6 Mss4 Q91X96 0.52 0.04 0.64 0.10
V7 Nsf1c Q9CZ44 1.55 0.01 1.51 0.01
V8 Pef1 Q8BFY6 0.64 0.05 0.50 0.02
V9 Snaa Q9DB05 1.53 <0.01 1.99 0.05
V10 Snap23 O09044 0.53 0.02 0.34 0.01
V11 Stxb2 Q64324 2.07 <0.01 1.30 0.09
V12a Tera/1 Q01853 1.31 0.13 1.18 0.16
V12b Tera/2 Q01853 1.49 0.02 1.06 0.38
V12c Tera/3 Q01853 1.39 0.02 1.29 0.04
V12d Tera/4 Q01853 1.48 0.10 1.35 <0.01
V12S ∑ Tera Q01853 1.43 0.02 1.25 0.01
V13 Tpd52 Q62393 1.42 0.04 1.31 0.10
V14 Vat1 Q62465 1.48 0.01 1.22 0.15
V15 Vps29 Q9QZ88 1.30 0.05 1.29 0.08
V16a Vps35/1 Q9EQH3 2.44 0.16 2.33 <0.01
V16b Vps35/2 Q9EQH3 1.80 0.17 2.03 0.01
V16c Vps35/3 Q9EQH3 1.53 0.33 2.25 <0.01
V16S ∑ Vps35 Q9EQH3 1.79 0.18 2.20 <0.01
V17 Vta1 Q9CR26 2.84 0.01 2.97 0.02
X1 Pdxk Q8K183 1.29 <0.01 1.45 0.02
X2 Spee Q64674 1.55 0.02 1.43 0.07
X3 Sps1 Q8BH69 1.49 0.02 1.95 0.01
X4a Ran/1 P62827| 0.83 0.04 0.87 0.12
X4b Ran/2 P62827| 1.18 0.08 1.11 0.17
X4S ∑ Ran P62827| 1.03 0.62 1.00 0.98
Y1 CatD P18242 1.38 0.01 1.48 <0.01
Y2 CatZ Q9WUU7 1.79 0.04 1.08 0.85
Y3 Ncf4 P97369 1.15 0.02 1.19 0.01

image file: c9en00408d-f4.tif
Fig. 4 Proteomic analysis of total cell extracts by 2D electrophoresis. Total cell extracts of RAW274.7 cells were separated by two-dimensional gel electrophoresis. The first dimension covered a 4–8 pH range and the second dimension a 15–200 kDa range. Total cellular proteins (150 μg) were loaded on the first dimension gel. A: Gel obtained from control cells. B: Gel obtained from cells treated for 24 hours with 20 μg ml−1 silver nanoparticles. C: Gel obtained from cells treated for 24 hours with 20 μg ml−1 silver nanoparticles and left to recover for 72 hours. Only the proteins involved in apoptosis (A), energy metabolism (E) and control of cell fate and proliferation (F) are shown in this figure.

3.4 Enzymatic activities

For some of the modulated proteins, we first checked whether their enzyme activities (Table 3), i.e. the relevant parameter in terms of cell physiology, followed or not the trends observed via proteomics. There is no obvious inference between the two parameters, as the activity may be modulated by PTM and thus correlate with one or several spots, or with the sum of the spots representing the same protein. One good example is represented by malate dehydrogenase, which is known to be up-regulated by acetylation.71 In our case, the activity correlated with the amount of the acidic, modified spots and not with the total amount of the protein. For other activities, e.g. lactate dehydrogenase, triose phosphate isomerase and purine phosphorylase, the activity correlated with the total protein amount and not with a single spot. For several other enzymes such as enolase, hexokinase, pyridoxal kinase and isocitrate dehydrogenase, we detected an increase of the protein amount by proteomics and a stable or decreased enzyme activity.
Table 3 Enzyme activities
Enzyme Control Acute Recov Ctrl + silver ion
All the activities are expressed in nmol substrate converted per min per mg total protein. Statistical significance of the results in the Student T test: *p < 0.05. ND: not determined. Abbreviations: LDH: lactate dehydrogenase; MDH: malate dehydrogenase; TPIS: triose phosphate isomerase; BVR: biliverdine reductase; PDXK: pyridoxal kinase; GAPDH: glyceraldehyde phosphate dehydrogenase; 6PGDH: 6-phosphogluconate dehydrogenase; PNPH: purine nucleoside phosphorylase; HXK: hexokinase; ENO: enolase; IDHC: NADPH-dependent isocitrate dehydrogenase.
LDH 74.4 ± 2.75 68.9 ± 1.14* 73.8 ± 4.13 ND
MDH 37.4 ± 0.95 31.3 ± 2.85* 31.7 ± 2.36* ND
TPIS 70.7 ± 8.75 76.6 ± 5.58 76.3 ± 7.80 ND
BVR 0.67 ± 0.04 0.53 ± 0.1* 0.79 ± 0.06* ND
PDXK 7.4 ± 0.95 5.9 ± 0.6* 7.5 ± 0.68* ND
GAPDH 157.12 ± 14.5 144.25 ± 9.77 157.44 ± 5.91 ND
6PGDH 30.69 ± 3.17 39.37 ± 4.92* 38.75 ± 1.24* ND
PNPH 8.97 ± 1.17 9.12 ± 1.6 9.06 ± 0.77 ND
HXK 23.4 ± 3.04 16.3 ± 4* 23.3 ± 2.45 (1 μM) 14.2 ± 2.93
ENO 214.5 ± 13.6 166.4 ± 28.1* 184 ± 41 (10 μM) 167 ± 12.4
IDHC 16.37 ± 1.48 17.62 ± 2.79 23.75 ± 2.97** (5 μM) 8.06 ± 1.09

3.5 Mitochondrial potential and glucose consumption

Several mitochondrial proteins appeared modulated upon exposure of macrophages to silver nanoparticles, among which are a few subunits of the respiratory complexes (NDUV2 and ATPB), some components of the mitochondrial protein quality control (TRAP1 and CLPP) and an antioxidant protein (PRX3). As this may suggest perturbations in the mitochondrial functions, we investigated the mitochondrial transmembrane potential. The results, shown in Fig. 5, indicated that all viable cells accumulated rhodamine 123 and thus had a strong mitochondrial transmembrane potential. However, the amount of accumulated rhodamine 123 and thus the level of the mitochondrial transmembrane potential were lower for the acute condition and went back to normal after 72 hours of recovery. As a lower transmembrane potential is indicative of a less efficient oxidative phosphorylation chain, we investigated the global metabolism under the three experimental conditions.
image file: c9en00408d-f5.tif
Fig. 5 Mitochondrial transmembrane potential analysis. The rhodamine 123 accumulation method was used. Panel A: Proportion of rhodamine123-positive cells in the viable cell population. Panel B: Mean rhodamine 123 fluorescence (in the viable cell population only). Symbols indicate the statistical significance (Student's T-test): *: p < 0.05. ctrl: Non exposed cells. acute: Cells exposed for 24 hours to silver nanoparticles (20 μg ml−1). recov: Recovering cells (72 hours post exposure to silver nanoparticles). Symbols indicate the statistical significance (Student's T-test): *: p < 0.05.

We thus measured the glucose consumption during the last 36 hours of the experiments by measuring the remaining glucose in the culture medium at the end of the experiment. The initial medium contained 4.1 g of glucose per liter due to the dilution brought by the addition of fetal serum to obtain the complete medium. In the untreated, control cells, 1.8 ± 0.2 g of glucose per liter remained in the culture medium after 36 hours of culture. In contrast, 1 ± 0.05 g of glucose and 0.9 ± 0.04 g of glucose remained in the medium for the acute and recovery conditions, respectively. These differences were statistically significant (Mann Whitney U test, p < 0.05).

The increased glucose consumption in the acute exposure condition could be correlated with the less efficient mitochondria via a Warburg effect. However, this correlation did not hold for the recovery condition, in which the mitochondria appear as efficient as those of the control cells. This may suggest that the silver expulsion process that takes place during the recovery period consumes a lot of energy.

3.6 Glutathione levels

One of the proteins that is induced after acute exposure to silver nanoparticles is GCLM, i.e. the regulatory subunit of the enzyme involved in the first step of glutathione biosynthesis, which is the limiting step of the pathway.72 We thus investigated the levels of free glutathione, as studies on primary macrophages had shown that treatment with silver nanoparticles decreased the levels of free glutathione.23 This result may be due to the formation of silver–glutathione complexes.73 We thus measured by flow cytometry the proportion of cells with high levels of reduced glutathione, and the level of glutathione in this population. The results, shown in Fig. 6, indicated that the glutathione level is only 70% of the normal one just after the exposure to silver nanoparticles, and is 85% of the normal after 3 days of recovery. Thus, here again, the increase in GCLM amount can be interpreted as a cellular mechanism to compensate for the decrease of free glutathione caused by silver.
image file: c9en00408d-f6.tif
Fig. 6 Free glutathione levels. The chlorobimane (mCB) conjugation method was used. Panel A: Proportion of GSH-positive cells in the viable cell population. Panel B: Mean GSH-mCB conjugate fluorescence (in the viable cell population only). Symbols indicate the statistical significance (Student's T-test): ***: p < 0.001. ctrl: Non exposed cells. acute: Cells exposed for 24 hours to silver nanoparticles (20 μg ml−1). recov: Recovering cells (72 hours post exposure to silver nanoparticles).

3.7 Actin cytoskeleton and phagocytosis

Cytoskeletal proteins, especially proteins implicated in the actin cytoskeleton dynamics, were among the most important classes emerging from the proteomic screen. Of note, many of these proteins have activities that are modulated by phosphorylation, such as cofilin74,75 or Rho-GDIs.76,77 As the regulation patterns that emerged from the proteomic screen for these proteins were very complex, with some spots modulated while others were constant, we directly examined the consequences on the actin cytoskeleton. The results, shown in Fig. 7, indicated a strong vesicularization of the cells during the recovery period.
image file: c9en00408d-f7.tif
Fig. 7 Confocal imaging of the F-actin cytoskeleton. Only one confocal plane inside the cells is shown (going through the cell nucleus). A: Unexposed cells. B: Acutely-exposed cells. C: Recovering cells. Silver-treated cells show an important vesicularization, compatible with the presence of nanoparticles within the cell phagosomes.

Phagocytosis is one of the specialized functions of the macrophages that is highly dependent on the actin cytoskeleton. We thus tested the phagocytic activity of the cells. The results, shown in Fig. 8, indicated that the proportion of phagocytic cells does not change upon treatment with silver nanoparticles. However, the number of internalized particles per cell, as described by the mean fluorescence, slightly decreased immediately after exposure to nanoparticles and went back to quasi-normal values after 72 hours of recovery.

image file: c9en00408d-f8.tif
Fig. 8 Phagocytosis. The phagocytic capacity was assessed by fluorescent latex bead internalization. Panel A: Proportion of positive cells in the viable cell population. Panel B: Mean cellular fluorescence (in the viable cell population only). ctrl: Non exposed cells. acute: Cells exposed for 24 hours to silver nanoparticles (20 μg ml−1). recov: Recovering cells (72 hours post exposure to silver nanoparticles).

3.8 NO and cytokine production, redox balance

Production of nitric oxide and pro-inflammatory cytokines such as IL-6 and TNF upon stimulation is another specialized function of macrophages. We thus investigated their production after treatment of macrophages with silver nanoparticles under two schemes: either after treatment with nanoparticles only, or after treatment with nanoparticles and lipopolysaccharide (LPS) for the last 24 hours of culture. The first scheme investigated the intrinsic pro-inflammatory action of the nanoparticles, while the second one investigated the interference of nanoparticles with a standard pro-inflammatory response induced by a bacterial stimulus. The results, shown in Fig. 9, indicated that silver nanoparticles have a weak but significant intrinsic pro-inflammatory effect, as detected from NO and TNF production, which returned to normal values after the recovery period. The situation was however very different for the combined nanoparticle–LPS treatment. In this case, the acute exposure condition did not differ significantly from the control cells (exposed to LPS only), while the cytokine and NO production were significantly lower after the recovery period. As the NO production is NADPH-dependent, we investigated the NADP–NADPH levels after treatment with nanoparticles. The results, shown in Table 4, indicated that both the total NADP + NADPH and NADPH levels were similar for the three conditions tested.
image file: c9en00408d-f9.tif
Fig. 9 NO and cytokine production. NO, TNF-alpha and IL-6 production were measured under the different cell culture conditions, with and without further exposure to LPS. ctrl: Non exposed cells. acute: cells exposed for 24 hours to silver nanoparticles (20 μg ml−1). recov: Recovering cells (72 hours post exposure to silver nanoparticles). Symbols indicate the statistical significance (Student's T-test): *: p < 0.05 ; **: p < 0.01 ; ***: p < 0.001. A and B: NO production, without (panel A) and with (panel B) exposure to LPS. C and D: TNF-alpha production, without (panel C) and with (panel D) exposure to LPS. E: IL-6 production with exposure to LPS. IL-6 is undetectable under the three culture conditions tested when the cells are not exposed to LPS.
Table 4 NADP(H) concentrations in cells
Ctrl Acute Recov
All the concentrations are expressed in nmol nucleotide per mg total protein.
NADPH 1.87 ± 0.12 1.88 ± 0.03 1.85 ± 0.01
NADP + NADPH 2.5 ± 0.09 2.33 ± 0.04 2.62 ± 0.06
NADPH/(NADP + NADPH) 0.75 ± 0.07 0.81 ± 0.02 0.71 ± 0.02

4. Discussion

Silver nanoparticles are usually produced through a wet route and need to be stabilized as soon as prepared to avoid irreversible aggregation. Stabilization of AGNPs is usually achieved through interaction with complex ions such as citrate, or by polymers such as polyethylene glycol or polyvinylpyrrolidone (PVP). As such, PVP-coated silver nanoparticles are industrial products used in several applications including as antibacterial compounds,78 conductive inks,79–81 and sensors,82 and in electromechanics.83 In the course of their use, nanoparticles can be aerosolized. In this case they can contaminate living organisms without being modified. In the specific case of inhalation contamination, the nanoparticles reach the alveolae where there will be internalized by the lung macrophages, which is the reason why we made the choice to use this cell type in this study. Regarding other environmental dispersion routes, PVP-coated silver nanoparticles have been shown to be the most resistant in freshwater environments,84 and thus recommended for ecotoxicological testing.84 The PVP-coated silver nanoparticles, therefore, appear to be relevant for assessing the toxicity of silver nanoparticles.

Most of the toxicological studies on nanoparticles use an acute exposure scheme; they expose cells to a high, but non-lethal dose. Such a scheme does not represent chronic daily exposure under, for example, occupational conditions, but may represent the dose following an accidental exposure. To fully evaluate the toxicity of AgNPs, it is therefore important to know not only the acute effects post exposure, but also how cells recover from such exposures to high dosages of AgNPs. To accomplish this, a ternary comparison must be made between cells before and immediately after treatment and also between cells at the end of a recovery period. In this experimental frame, the acute exposure point is not the primary focus of attention. We therefore decided not to investigate in detail the role of silver ions in the acute response, based on the fact that the rather large silver nanoparticles used in this study dissolve to a very low extent,23 producing free silver ion concentrations that are far below the LD20 observed for silver ions. Furthermore, this aspect has been investigated in numerous studies (e.g. in ref. 8, 15, 59 and 85) and the general outcome of these studies is that the mechanisms observed for silver nanoparticles cannot be explained by silver ions, at least for large nanoparticles.15

In this frame, the proteomic approach is of interest because it can be used to explore not only a few parameters, as targeted approaches do, but also can be used to investigate a few hundred parameters at the same time, i.e. the abundances of the various proteins analyzed in a proteomic screen. In this respect, the use of a 2D gel-based proteomic approach may appear as a medium scale approach, compared to deep shotgun proteomic approaches. However, compared to shotgun proteomics, 2D gels have the unique ability to separate protein forms, without the requirement that they appear as a single product. With growing recognition of the importance of post-translational modifications, the ability to do this is biologically relevant. Indeed, we have shown both in this study and in previous ones53,86 that some enzyme activities correlate with a single protein form and not with the sum of all the protein forms, showing the relevance of this parameter.

First, we performed a global analysis of the proteomic results. Both the principal component analysis and the analysis of similarity (ANOSIM) indicated that the recovery state was not just an intermediate state between the unexposed cells and the acutely-exposed cells. If this were the case, the recovery state should not have been separated from the other two states as it is in the principal component analysis. This is further confirmed by ANOSIM. The fact that all the p-values in the binary comparison are low and rather similar shows that the three states are significantly different from each other. If the recovery stage was just between the other two stages, at least one of the p-values between the recovery stage and one of the other two stages should be much higher than the p-value between the control and the acute stage. As this is not the case, we can reject the hypothesis that the recovery phase is only an intermediate between the control and acutely-treated stages.

We then performed a more detailed analysis of the proteomic results. The first important challenge was to determine to what extent the changes observed through proteomics are specific to silver nanoparticles and which are due to the simple presence of a PVP-coated nanoparticle. We have addressed this question in previously published studies.35,53 In these studies, we showed that PVP-coated zirconium oxide nanoparticles induced minimal changes at the proteomic level. This ruled out the possibility that the changes that we observe in the present study could be due either to the internalization process per se or are due to the effect of the addition of PVP.

As a further step, we compared our results obtained immediately after exposure to those published in the literature.9,10,24 It should be noted that this comparison is challenging because these other studies did not use the same cell type as was used here (although two of them use human intestinal cell lines, however different ones9,24) or the same silver nanoparticles. Citrate-coated silver nanoparticles were used in one study,24 while the other two used surfactant-coated nanoparticles,9,10 and in this study PVP-coated nanoparticles were used. These differences are very likely to explain the wide differences observed between the studies in which proteins were differentially modulated by treatment, with a minimal overlap between the results. Despite this general trend, several convergences could be observed between our study and those previously published. For example, increases in the abundances of Ran, Moesin, RuvB2, EfhD2, Pfkl, Anxa3, Tcpa and Tbcb were observed both in our study and the one published by Verano-Braga et al.24

However, proteomics is prone to multiple testing issues, so that the results obtained by proteomics must be verified by independent, targeted experiments. To accomplish this, we analyzed enzyme activities. Our enzyme activity results were consistent with observations made about changes at the proteomic level. However, a few discrepancies occurred, which were always of the same type: increases in the protein level by proteomics, corresponding to stable or decreased activities. We could, however, show that these enzyme activities are very sensitive to the silver ion, which was released within cells during their exposure to silver nanoparticles. Thus, the increase in protein levels can be seen in such cases as a cellular mechanism to compensate for the decrease of activity brought by silver.

We then carried out indirect validation studies, for example on the free glutathione levels, which were decreased immediately after exposure, a phenomenon that was previously observed for copper nanopartlcles.35 We also tested phagocytosis, which is an important function of macrophages and is important for clearing bacteria. For this assay we used micron-sized fluorescent beads, which functioned as bacterial mimics. This allowed us to investigate whether nanoparticle-treated cells were still able to clear bacteria. The proteomic screen suggested that phagocytosis might be altered after treatment with silver nanoparticles, which was confirmed in our assay testing the ability of the cell to clear bacteria. These results were previously observed for primary macrophages.23

The key question asked in this study, however, does not revolve around the acute response to silver nanoparticles, but instead asks to what extent and by which means do cells recover after such an exposure. In a simple model for recovery, protein changes should exhibit trends that return to normal, i.e. the amplitude of the change in abundance between the recovery and control stages should be lower than the amplitude of the change in abundance between the acute exposure and control stages. Out of the 239 spots that are highlighted in the proteomic screen, 135 (56%) show such a trend. This means that 104 (44%) show a stronger response at the recovery phase than immediately after exposure. With such a split trend, it is interesting to evaluate the results of targeted experiments during the recovery phase.

Interestingly, this split trend was also apparent in the results of targeted experiments. General metabolic processes seem to return to normal (mitochondrial potential, glutathione levels, and most enzymatic activities), as well as phagocytosis and basal NO production (without LPS stimulation). Oppositely, the LPS-induced activities (e.g. NO, IL-6 and TNF production) worsen during the recovery phase, as well as the isocitrate dehydrogenase activity, and the glucose consumption, which stays much higher at both the recovery and acute exposure phases than in unexposed cells.

It was the necessary to check in detail how proteomic changes correlate with observed functional changes. For example, for mitochondrial proteins, the proteomic screen detects an increase in the beta subunit of ATP synthase (ATPB) and an increase in one subunit of respiratory complex I (NDUV2) upon cell exposure to silver nanoparticles. At the same time the mitochondrial transmembrane potential decreases slightly, showing that this increase in mitochondrial proteins could be an attempt to restore normal energy production in cells. Upon recovery, one of the ATPB spots slightly decreases compared to the value immediately after exposure, while the other spot further increases. The NDUV2 spot is also enhanced. However, even the ATPB spot that decreased is still significantly more abundant at this stage of recovery than in control cells. This shows that the cellular situation is still not back to normal, as can be expected from the still high intracellular silver content, and that restoring the metabolic activity of a cell is an active process requiring an upregulation of several proteins.

Opposite to the delayed return to control values, GCLM, for example, shows an increase just after exposure. When the glutathione demand is high and the free glutathione levels are low, there is a return to control values at the end of the recovery period, at which point free glutathione levels are close to normal again.

In contrast to this simple case, the regulation of the actin cytoskeleton is much more complex. Many of the proteins interacting with actin and regulating its dynamics are regulated by phosphorylation. This holds true for cofilin,74 actinin 4,87 vinculin,88 swap70,89 arpc5,90 gelsolin91 and Arp2.92 While this further demonstrates the interest of taking into account modified protein forms, there are no obvious rules to predict which modified spot(s) is (are) effector(s) on the actin cytoskeleton. For example, the effector spot for cofilin is the median spot.93 Consistent with what has been described in the literature, we observe mostly modulations on acidic, modified forms of the above-cited proteins.

In line with the sustained changes in the actin cytoskeleton observed even at the recovery stage, we observe sustained changes in these modified spots, as exemplified by spots 2 of actinin 4 and cofilin, and spots 1 for Arp2 and Arpc5. It must be recalled, however, that such changes are not induced by the particle internalization process per se, as they were not observed for cells treated with the non-toxic zirconium oxide nanoparticles.53 They are also not induced by every toxic nanoparticle, as they were observed neither with zinc oxide53 nor with copper oxide, except for arpc5 which also decreased in response to treatment with copper oxide.37

Overall, the proteomic results suggest that the recovery process is a slow process. To evaluate this aspect, we determined the number of spots that showed a fast recovery. This category was defined as spots for which the quantitative change in the acute vs. control comparison showed an amplitude at least twice that in the recovery vs. control comparison. Only 44 spots were identified that fell in this category (including GCLM).

A striking result of our study was the observation that some changes in protein levels that were not immediately significant after exposure became significant at the end of the 72 h recovery phase. Such changes were observed both in targeted experiments (e.g. for the LPS-dependent responses) and in the proteomic screen. 51 spots showed such an expression profile, i.e. 21% of the total variable spots.

Functionally speaking, the results obtained when evaluating LPS-induced activities contrast with those previously described on primary macrophages,23 in which the cytokine and TNF productions also tended to return to normal values during the recovery phase. This discrepancy may have several origins. One such cause for the discrepancy could be differences in the persistence of silver between differing experimental conditions. In the experiments on primary macrophages, measurements of silver by PIXE showed a strong decrease (50%) in cellular silver content upon recovery, without any cellular multiplication (primary macrophages are post-mitotic in vitro). In the current experiments using the J774 cell line, the total silver content decreased by only 15%, and the decrease in cellular silver content is due mostly to cell division. The simple fact that the cells are able to divide shows that the silver concentration present in the cells is not toxic and explains also why, generally, the cellular parameter tends to return to normal levels. The remaining silver concentration may, however, may be high enough to inhibit specialized macrophage functions that depend on cell signaling, such as LPS-dependent activities.

In this context, it is tempting to dismiss the results obtained on the cell lines and favor those obtained using primary cells. The situation may, however, not be so simple. First, primary macrophages in vitro survive for only a few days once differentiated, while resident macrophages, such as those used in experiments using cell lines, have a very long lifespan,94,95 Furthermore, the condition in which the results between cell lines and primary macrophages diverge corresponds to an acute exposure to silver nanoparticles followed by a massive exposure to bacteria (mimicked by exposure to LPS), i.e. conditions that have not been tested in vivo. Therefore, we are currently unable to determine which system best represents the in vivo situation.

5. Conclusions

Overall, our results obtained both by targeted measurements and by proteomic experiments involving hundreds of proteins show that recovery after an acute exposure to silver nanoparticles is a very active process that involves a massive energy consumption, 50% higher than normal. This process leads to the quasi restoration of cellular homeostasis within 72 hours post exposure, as confirmed by targeted experiments testing the activity of enzymes, on mitochondrial function and on phagocytosis. Proteomic experiments also show, however, that this restoration of cellular homeostasis involves changes in the levels of many proteins, of which many are sustained, or even amplified, at the end of the 72 hour recovery period studied. The persistence of proteomic changes might be linked with the persistence of intracellular silver during the recovery period, which may require a long-lasting cellular adaptation process. Some other specialized macrophage functions, such as LPS-induced cytokine or nitric oxide production, did not return to normal within the 72 hour recovery period.

Author contributions

AT performed the phagocytosis, rhodamine uptake and glutathione assay experiments. BD performed the cytokine assays and confocal microscopy experiments. HD, SC, VSF and TR performed the proteomic experiments. TR performed in addition the enzymatic, NADP(H) and glucose assays. SR and JB performed the ICP-MS experiments. MC, KPG and PHJ performed the electron microscopy experiments.


This work was funded by ANSES (Agence Nationale de Sécurité Alimentaire, Environementale et du Travail) (PNREST 2011/25, Innimmunotox project) and by the CEA toxicology program (Nanostress grant). It is a contribution to the Labex Serenade (no. ANR-11-LABX-0064) funded by the “Investissements d'Avenir” French Government program of the French National Research Agency (ANR) through the A*MIDEX project (no. ANR-11-IDEX-0001-02). STEM-EDS analyses were conducted with the TEM OSIRIS, Nano-Safety Platform, CEA-Grenoble, operated by P. H. Jouneau. This project was managed by Agence National de la Recherche (ANR), program ‘Investissements d'Avenir’, reference ANR-10-EQPX-39.

Conflicts of interest

There are no conflicts of interest to declare.


We thank Anne Bertrand and the electron microscopy facility of the Grenoble Institute of Neurosciences for the preparation of the samples and her kind help during the acquisition of the electron microscopy images.


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Electronic supplementary information (ESI) available. See DOI: 10.1039/c9en00408d
These authors contributed equally to this work.
§ Deceased: Nov. 21st, 2018. This paper is dedicated to her memory.

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