International Scholarly Research Notices

International Scholarly Research Notices / 2012 / Article

Research Article | Open Access

Volume 2012 |Article ID 454072 | https://doi.org/10.5402/2012/454072

S. Bancos, D.-H. Tsai, V. Hackley, J. L. Weaver, K. M. Tyner, "Evaluation of Viability and Proliferation Profiles on Macrophages Treated with Silica Nanoparticles In Vitro via Plate-Based, Flow Cytometry, and Coulter Counter Assays", International Scholarly Research Notices, vol. 2012, Article ID 454072, 11 pages, 2012. https://doi.org/10.5402/2012/454072

Evaluation of Viability and Proliferation Profiles on Macrophages Treated with Silica Nanoparticles In Vitro via Plate-Based, Flow Cytometry, and Coulter Counter Assays

Academic Editor: A. Hu
Received27 Jun 2012
Accepted26 Aug 2012
Published14 Nov 2012

Abstract

Nanoparticles (NPs) are known to interfere with many high-throughput cell viability and cell proliferation assays, which complicates the assessment of their potential toxic effects. The aim of this study was to compare viability and proliferation results for colloidal silica (SiO2 NP; 7 nm) in the RAW 264.7 mouse macrophage cell line using three different techniques: plate-based assays, flow cytometry analysis, and Coulter counter assays. Our data indicate that CellTiter-Blue, XTT, and CyQuant plate-based assays show increased values over control at low SiO2 NPs concentrations (0.001–0.01 g/L). SiO2 NPs show little-to-no interference with flow cytometry and Coulter counter assays, which not only were more reliable in determining cell viability and proliferation at low concentrations in vitro, but also identified changes in cell granularity and size that were not captured by the plate-based assays. At high SiO2 NP concentrations (1 g/L) all techniques indicated cytotoxicity. In conclusion, flow cytometry and Coulter counter identified new cellular features, and flow cytometry offered more flexibility in analyzing the viability and proliferation profile of SiO2 NP-treated RAW 264.7 cells.

1. Introduction

Nanoparticles (NPs) have been proposed as promising tools for therapy, drug delivery, imaging, and active pharmaceutical ingredients [15]. An early and crucial stage in drug development is toxicity testing. High throughput in vitro toxicity assays that are widely employed for small molecule drug screening include assays for cell membrane integrity, oxidative stress, apoptosis, proliferation, or metabolic activity [6]. These assays have also been used for NPs toxicity evaluation [710]. Although plate-based assays offer several advantages (e.g., fast, easy, and reproducible), accumulating data show that NP interference with plate-based assay substrates can lead to erroneous data and provide little correlation with in vivo studies [1114]. Some of NP properties that were reported to interfere with viability plate-based assays are surface charge, agglomeration/aggregation, hydrophobicity, and optical or magnetic properties [1517]. For example, it was reported that titanium dioxide NPs (TiO2 NP; various size and concentrations) bind lactate dehydrogenase (LDH, indicator of cell viability) and alter assay readout [18]; copper NPs (Cu NP, 40 nm) and silver NPs (Ag NP, 35 nm) inactivate LDH [19]; gold NPs (Au NP; 10 nm) can absorb and traffic amine-containing dyes inside cells resulting in false positive results for membrane permeability assays [11]; single-wall carbon nanotubes (SWCNTs) interact with and alter the readout of WST-1 (2-(4-iodophenyl)-3-(4-nitrophenyl)-5-(2,4-disulfophenyl)-2H-tetrazolium), Coomasie Blue, Alamar Blue, Neutral Red, MTT, and plate-based cytotoxicity assays [20].

The emerging consensus when using plate-based assays is that NP characterization and their characteristics, choice of cell lines and assays, and the use of appropriate controls are critical in obtaining reliable data [13, 21]. NP interference with viability assays, however, cannot be generalized for all type of NPs, and possible interactions between NPs and assay substrates should be identified for each NP separately. This is a challenging and labor-intensive task resulting in the current toxicology toolbox often being insufficient when applied to NPs. Therefore, it is crucial that alternative methods be developed to test NPs cytotoxicity in vitro. The determination of cell viability using cell dyes coupled with flow cytometry or microscopy techniques offer the advantage of evaluating cell viability on cell-by-cell basis and have been proposed as a method to overcome the plate-based assays interference issues [22].

SiO2 NPs are being proposed as new tools for imaging [2325] and drug and biologic delivery (e.g., nucleic acid-based reagents and siRNA) [2630]. SiO2 NPs may exist in many different forms, including different crystallinity, morphology, and pore structure, with each form exhibiting unique characteristics [3133]. Although several in vitro studies using SiO2 NPs have been performed to show either cytotoxicity [3436] or no effect on viability in vitro [34, 37, 38], there is limited information regarding SiO2 NPs interference with plate-based assays. For example, it is known that ViaLight substrate (fluorescent ATP) caused precipitation of 15 nm SiO2 NP resulting in a cloudy appearance of NP, but without ultimately affecting luminescence signal [22], and SiO2 NPs (15 nm) caused precipitation of LDH resulting in high absorbance values and false-positive results [22]; astrocytes treated with mesoporous silica NPs (SiO2 NP) show decreased MTT signal due to SiO2 NP-mediated formazan exocytosis as opposed to decreased viability [39].

In this study, we compared plate-based, flow cytometry, and Coulter counting assays for their ability to assess the effects of 7 nm colloidal SiO2 NPs on the RAW 264.7 macrophage cell line. The plate-based assays: CellTiter-Blue, XTT, LDH, and CyQuant were compared with flow cytometry (PI and Calcein AM staining) and Coulter counter assays. Our data show that results obtained by plate-based assays show increased values over control at low SiO2 NP concentrations. SiO2 NPs show little-to-no interference with flow cytometry and Coulter counter assays, which were not only more reliable in determining cell viability and proliferation in vitro, but also identified additional cellular changes that were not captured by the plate-based assays.

2. Methods

2.1. Reagents

SiO2 NPs (7 nm; Ludox, SM-30 colloidal silica) and bacterial lipopolysaccharide were purchased from Sigma. DMEM media was purchased from ATCC; FBS, Penicillin/Streptomycin, PBS, and trypsin were purchased from Invitrogen.

2.2. Determination of NP Concentration

SiO2 NPs were sterile filtered (0.22 μm Millex filter unit) after which thermogravimetric analysis (TGA) was performed as follows: 50 μL of SiO2 NPs were heated to 200°C (at a heating rate of 1°C/min) to remove the bound and unbound water, and the weight concentration was calculated based on starting SiO2 NPs volume. SiO2 NPs stock used for current experiments was between 380 g/L and 390 g/L. This stock concentration was used to prepare dilutions (freshly prepared for each experiment).

2.3. Endotoxin Test

To ensure that SiO2 NPs are free of Gram-negative bacterial endotoxin contamination, the Limulus amebocyte lysate (LAL) test was performed for all dilutions using LAL QCL-1000 (Lonza, MD, USA), PYROGENT Plus (Lonza, MD, UAS) and Pyrosate (Associates of Cape Code, Inc., MA, USA) kits following the instructions recommended by the manufacturers. All SiO2 NPs dilutions tested negative for endotoxin in all tests used.

LAL QCL-1000 identifies endotoxin contamination based on a colorimetric method (absorbance 405–410 nm). The kit requires that samples have a pH = 6–8. Because SiO2  NPs have a pH = 10.25–10.3, dilutions were performed in PBS (pH = 6.5). The final pH values of SiO2  NPs dilutions in PBS (pH = 6.5) were between pH = 6.2 (for 1 g/L SiO2 NPs) and pH = 6.4 (for 0.001 g/L SiO2  NPs). Endotoxin values were calculated using an endotoxin standard curve (from E. coli endotoxin O55:B5 with concentrations between 1 EU/mL and 0.015 EU/mL). Standard curve absorbance values were used to calculate the coefficient of correlation ( ), slope ( ), and intercept of mean Δ absorbance value ( ). The assay was validated using negative controls (LAL-free water and PBS pH = 6.5) and positive controls (SiO2  NPs dilutions spiked with 0.5 EU/mL endotoxin). Water and PBS tested negative for endotoxin whereas all positive controls were endotoxin positive. There was no inhibition noted with this assay.

LAL PYROGENT Plus kit determines gel clot formation in endotoxin-positive samples. SiO2  NPs were diluted in PBS pH = 6.5 (final concentrations: 1 g/L, 0.1 g/L, 0.01 g/L, and 0.001 g/L) and tested for gel clot formation as recommended by the manufacturer. Negative controls (LAL-free water and PBS) as well as positive controls (SiO2  NPs dilutions spiked with E. coli endotoxin 0.5 EU/mL) were included. SiO2  NPs dilutions tested negative for endotoxin. No interference was noted with the assay (all positive control samples formed gel clots). Kit sensitivity is reported as 0.125 EU/mL endotoxin, which was validated by E. coli endotoxin O55:B5 standard controls. Seven standard controls were prepared (1 EU/mL to 0.015 EU/mL), and the calculated sensitivity was 0.063 EU/mL (acceptable values are between 0.060 and 0.250 EU/mL).

Pyrosate LAL kit forms gel clots in endotoxin-contaminated samples but does not require pH adjustment. Serial SiO2  NPs dilutions (1 g/L; 0.1 g/L; 0.01 g/L and 0.001 g/L) were prepared in water (SiO2  NPs pH = 10.25–10.3). The assay was performed using negative controls (LAL-free water) and positive controls (ready-made endotoxin-spiked sample, provided by the manufacturer). All SiO2  NPs samples and the negative control were endotoxin free (no gel clot was formed) whereas all positive controls formed gel clots. Pyrosate kit sensitivity is reported as 0.25 EU/mL endotoxin.

2.4. NP Characterization

SiO2 NPs were analyzed by dynamic light scattering (DLS), transmission electron microscopy (TEM), and electrospray differential mobility analysis (ES-DMA). Zeta potential of SiO2 NPs (38-39 g/L in water) was performed on a Malvern Zetasizer instrument (Malvern Instruments, Worcestershire, UK) using disposable capillary cells. Zeta potential for each sample was measured three times at 37°C; each measurement contained 14 runs. The pH of SiO2  NPs in water is 10.3.

DLS was performed on a Malvern Zetasizer instrument (Malvern Instruments, Worcestershire, UK) using UV-disposable cuvettes for low volume (Brand, Germany). SiO2  NPs solutions were analyzed at 10-fold, 100-fold, and 1000-fold dilutions to probe for concentration-related effects (multiple scatters, agglomeration, and so forth). SiO2  NPs were measured by DLS in triplicate using water and cell culture media as dispersants. Measurements were performed at 25°C (for water dilutions) or 37°C (for media dilutions). Each measurement contained 11 runs (10 seconds duration/run) with 2-minute equilibration time at the beginning of the measurement. Refractive index (RI) and viscosity values were applied for water and media ( for media and 1.330 for water, resp., 0.790 cp viscosity for media and 0.6864 cp viscosity for water).

For TEM analysis an aliquot of SiO2  NPs was dropped onto a holey carbon-coated copper grid (quantifoil, EMS, PA USA) and allowed to air dry. Grids were analyzed on a JEOL 100 CX at 80 kV and 100 kX.

The ES-DMA system consists of an electrospray aerosol generator (ES, Model 3480, TSI Inc., MN, USA), a differential mobility analyzer (DMA, Model 3080n, TSI Inc.), and a condensation particle counter (Model 3776, TSI Inc.). Details of the ES-DMA experimental setup have been described in previous publications [40, 41]. To achieve sufficient resolution and accuracy, samples of colloidal silica were first diluted (105 fold) with 20 mmol/L ammonium aqueous solution, pH = 6.5. Argon gas was used as sheath flow and the ratio of sheath-to-aerosol flow rates was fixed at a value of 5. Data were collected with a scanning step size of 0.2 nm for 10 s.

2.5. Cell Culture Conditions

RAW 264.7 mouse macrophage-like cells were purchased from ATCC. All experiments were performed with cells passaged 5–15 times (batch received from ATCC was considered passage 1). Cells were cultured in DMEM media supplemented with FBS (10%) and Penicillin/Streptomycin (1%) at a density of 0.8 × 104 cells/cm2. This density was determined following vendor recommendation as well as a confirmation titration study (data not shown).

2.6. CellTiter-Blue, XTT, LDH Release, and CyQuant Assays

All methods and assays used in the current communication are summarized in Table 1. RAW 264.7 cells were cultured as described above in 96-well flat bottom plates for 2 days (cells were ~80% confluent). Media was exchanged for fresh media with or without NPs and cells were cultured for 24 h after which CellTiter-Blue cell viability assay (Promega), CytoTox-one homogenous membrane integrity assay, in vitro toxicology assay kit XTT-based (Sigma) and CyQuant NF cell proliferation assay (Invitrogen) were applied according to the manufacturer’s instructions. In brief, substrates were either added directly to plates or added after the plates were centrifuged (400 g) and fresh media added to the wells. For CellTiter-Blue and XTT assays, substrates were added at 1 : 5 ratio; for LDH release a 1 : 1 ratio was used. Plates were incubated for 4 h at 37°C (CellTiter-Blue and XTT) or 10 min at RT (LDH release), after which fluorescence (excitation at 560 nm and emission at 590 nm for CellTiter-Blue and LDH release) or absorbance for XTT (450 nm) was measured using a plate reader (Molecular Devices, SpectraMax model). For CyQuant proliferation assays, media was removed, substrate was added, and plates were incubated at 37°C for 1 h; fluorescence was measured on a plate reader (excitation at 485 and emission at 530 nm). Viability or proliferation in experimental samples was calculated versus nontreated cells. LDH release was calculated versus maximum LDH release (Triton-X treated cells ±NP). All experiments were run three times in triplicates.


AssayReadoutInstrumentControls used

CellTiter-blue cell viability assay (Promega)Mitochondrial activityPlate reader Untreated; no cell control; pre- and postspike controls; positive control
In vitro toxicology assay kit XTT based (Sigma)Mitochondrial activity
CytoTox-one homegenouse membrane integrity assay (Promega)Membrane integrity
CyQuant NF cell proliferation assay (Invitrogen)Proliferation

PI (Invitrogen)Membrane integrityFlow cytometer Untreated; positive control
Calcein am stain (Invitrogen)Intracellular esterase activity
CFSE (Invitrogen)Proliferation/cell tracking

Coulter counterCell number and sizeCoulter counterUntreated; LPS control

For all plate-based assays, a “no cell” control and pre- and postspike controls were run in parallel. “No cell” controls were setup exactly as described for experimental samples but did not contain cells. Prespike samples were setup exactly as experimental samples but did not contain NPs. After the prespike values were recorded, SiO2 NPs were added and absorbance or fluorescence was immediately measured. These samples were defined as postspike controls.

2.7. Propidium Iodide (PI) and Calcein-AM Staining Coupled with Flow Cytometry

RAW 264.7 cells were cultured in 48-well plates for 2 days, after which cells were exposed to SiO2 NPs for 24 h. Supernatants were then collected, and cells were detached with trypsin and pooled with corresponding supernatants. Cells were washed in PBS, thoroughly resuspended by pipeting, and stained with PI (0.05 μg; 15 min, RT) or calcein green (50 nM; 30 min, RT). Flow analysis was performed on BD FacsAria III using FlowJo and Diva software, respectively. Viability was calculated versus nontreated cells.

2.8. Proliferation Assays Using Cell Trace CFSE Cell Proliferation Kit (Invitrogen)

RAW 264.7 cells were cultured in 48-well plates for 24 h at which point cells were stained with CFSE (carboxyfluorescein diacetate, succinimidyl ester; 5 μM). Fresh media was added, and cells were cultured for another 24 h at which time cells were exposed to media ±SiO2 NPs and incubated for additional 24 h. Supernatant and corresponding trypsin-treated cells were pooled, washed in PBS, and stained with PI. Cell data were collected on a BD FacsAria III, and data was analyzed using FlowJo software. Proliferation is represented in histograms.

2.9. Cell Size Measurements and Cell Counts Performed Using Coulter Counter

RAW 264.7 cells are adherent. In order to collect all cells for Coulter counter assays it was imperative to harvest all cells and to make sure that cells were uniformly dispersed (not always achievable with the plate-based trypsin method). Therefore, a cell suspension culture was utilized. In this case, cells were plated in Petri dishes containing Teflon inserts (to prevent cell adhesion) at 1 × 105 cells/mL culture media and were exposed to SiO2 NPs (0.005 g/L or 0.01 g/L). Dishes were kept on rotating platform (50 rpm) for 24 h after which cultures were thoroughly resuspended by pipeting. An aliquot was used to determine cell number and size using a Z2 Coulter particles counter and Size analyzer (Beckman Coulter, FL, USA). A 100-μm aperture was used, and cells between 6 μm and 35 μm were counted.

2.10. Digital Picture Acquisition

RAW 264.7 cells were cultured in 48-well plates for 2 days, after which cells were exposed to SiO2 NPs. At the end of the treatment digital pictures were taken using Scion VisiCapture Image Acquisition software (Scion Corporation, Frederick, MD, USA).

2.11. Statistical Analyses

Statistical analyses were performed using one-way ANOVA followed by Tukey’s multiple comparison test (to compare all groups) or two-way ANOVA followed by Bonferroni’s multiple comparison test (comparing SiO2 NP-treated samples to control).

3. Results

3.1. SiO2 NPs Characterization

SiO2 NP size was determined by TEM, ES-DMA, and DLS. Figure 1(a) shows that in dry state the primary size of SiO2 NP is ~10 nm. ES-DMA data (Figure 1(b)) shows that in solution phase the primary size is ~13 nm and that SiO2 NPs also form agglomerates (~18 nm). DLS measurements show that the size of a singlet SiO2 NP in water (Figure 1(c)) is ~7 nm, and agglomerates form with a size of ~50 nm, which is in agreement with both TEM and ES-DMA results. To evaluate their stability under experimental conditions, SiO2 NPs were diluted in culture media and DLS was performed after 30 min, 1 h, 3 h, or 24 h incubation at 37°C. Figure 1(d) shows that after 30 min, 1 h, or 3 h incubation in media SiO2 NPs exhibit an average size of ~30 nm (black lines). The DLS distribution of SiO2 NP in media is not attributable to culture media with FBS since a blank media containing FBS (10%) was also analyzed by DLS and showed a peak at ~10 nm and 50 nm (gray line). After 24 h incubation SiO2 NPs showed ~100 nm size (gray dotted line). Zeta potential was also measured, and the recorded values were −27 mV (measured immediately after dilution in water).

SiO2 NPs were tested for endotoxin contamination by LAL assays, and SiO2 NPs tested negative as described in Material and Methods and as is represented in Table 2.


SiO2 NP dilutions Kit name Endotoxin sensitivity E. coli  
O55:B55 standards
Positive controls Negative controls Results Comments

1 g/L;
0.1 g/L;
0.01 g/L;
0.001 g/L
LAL QCL-1000A405 nm is linear between 1 EU/mL and 0.1 EU/mL From1 EU/mL to 0.015 EU/mL SiO2 NP dilutions spiked with E.  coli  endotoxin O55:B55 (0.5 EU/mL) LAL-free water and PBS SiO2 NPs are endotoxin-free colorimetric method; SiO2 NP diluted in PBS (pH = 6–8)

1 g/L;
0.1 g/L;
0.01 g/L;
0.001 g/L
PYROGENT Plus 0.125 EU/mL From1 EU/mL to 0.015 EU/mL SiO2 NP dilutions spiked with E.  coli  endotoxin O55:B55 (0.5 EU/mL) LAL-free water and PBS SiO2 NPs are endotoxin-free gel clot method; SiO2 NP diluted in PBS (pH = 6–8)

1 g/L;
0.1 g/L;
0.01 g/L;
0.001 g/L
Pyrosate 0.25 EU/mL N/A SiO2 NP dilutions spiked with endotoxin (provided by vendor) LAL-free water SiO2 NPs are endotoxin-free gel clot method; SiO2 NP diluted in water (pH = 10.25)

3.2. Evaluation of Viability Profiles of SiO2 NPs-Treated RAW264.7 Cells by Plate-Based and Flow Cytometry Assays

In order to determine the effect of SiO2 NPs on macrophage viability in vitro, the membrane permeability and mitochondrial activity of SiO2 NP-treated RAW 264.7 cells were determined by plate-based assays and flow cytometry. CellTiter-Blue is a fluorescent method that indicates mitochondrial activity based on the reduction of resazurin to resorufin in metabolically active cells. XTT substrate is reduced to formazan by mitochondrial dehydrogenase in viable cells and can be measured by absorbance. Lactate dehydrogenase (LDH) assay is a fluorometric method and measures LDH released by cells with damaged membrane into culture media. PI penetrates the leaky membrane of dead/dying cells, binds to their DNA, and it is widely used in membrane integrity and flow cytometry assays. Finally, calcein-AM is a cell-permeant dye that is converted in live cells by esterase activity to the fluorescent calcein green.

In order to detect possible interference with plate-based assays, two experimental setups were utilized. In the first setup, assay substrates were added to the experimental samples as recommended by vendors, and viability was calculated versus untreated samples (Figure 2(a)). In the alternative setup (Figure 2(b)) plates were first centrifuged, and media containing SiO2 NPs removed and replaced with fresh media to which substrates were added. In case of LDH release assays, where cell culture media is used as an endpoint, culture plates were centrifuged, and supernatant was transferred to new plates to which the assay substrate was added. Furthermore, background values obtained from the “no cell” controls were also subtracted (Figure 2(b)). For comparison, the flow cytometry data of PI and calcein green staining is included in both figures.

Figure 2(a) (assays performed as recommended by the vendors) shows that both CellTiter-Blue and XTT assays resulted in values over control at low SiO2 NPs concentrations, and in some cases the increase in viability endpoints is significantly above the control cells (CellTiter-Blue and XTT assays at 0.001 g/L or 0.01 g/L SiO2 NPs). However, LDH-release, PI and calcein AM staining showed a decrease in cell viability with significant changes at 0.1 g/L and 1 g/L SiO2 NPs. All assays showed significant decrease in cell viability endpoints at 1 g/L SiO2 NPs.

In Figure 2(b), where plates were centrifuged prior to substrate addition and background values were subtracted, values in CellTiter-Blue, XTT and LDH-release assays were reduced although significant decrease in cell viability compared to the control was still only detected at 1 g/L SiO2 NPs. Note that in Figure 2(a) LDH release reached ~62% at 0.1 g/L SiO2 NPs whereas in Figure 2(b) at the same concentration LDH-release value was ~22%. Flow cytometry assays (PI and calcein staining) were more sensitive in detecting altered cell activity, with change detected starting at 0.1 g/L.

In order to detect possible interference of SiO2 NPs with plate-based assays, a series of pre- and postspike controls were utilized for plate-based assays (as described in Material and Methods). No significant difference in measured values between pre and postspike samples was observed (see Supplementary material available online at http://dx.doi.org/10.5402/2012/454072).

3.3. Flow Cytometry and Visual Observations Identified Morphological Modifications in SiO2 NPs-Treated RAW 264.7 Cells In Vitro

While assessing the effect of SiO2 NPs on cell viability by flow cytometry, it was observed that SiO2 NP-treated RAW 264.7 cells show modification in their side scatter (SSC), which is a measure of relative cell granularity. In Figure 3(a) flow cytometry data are represented as plots. For visualization purposes and in order to quantify the changes in cell granularity each histogram is divided into quadrants (From Q1 to Q4). Quadrants coordinates were chosen based on cell distribution in no treatment samples so that the main population is found in one quadrant (Q4). Figure 3(a) shows that there was a wider distribution of cells on the SSC axis (indicative of increased relative granularity) in SiO2 NP- and LPS-treated cells versus control. Table 3 shows a quantitative analysis of cell distribution in each quadrant, and it illustrates that in SiO2 NP-treated cells ~28% exhibit increased granularity versus ~13% in no treatment cells. In LPS-treated cells ~42% of cells showed changes in SSC.


Control 0.01 g/LLPS (0.5 μg/mL)

Q13.9 ± 1.14 8.06 ± 2.14 5.6 ± 1.84
Q22.17 ± 2.050.85 ± 0.12 1.17 ± 0.20
Q312.56 ± 1.54 28.65 ± 1.9*42.15 ± 1.40*
Q483 ± 2.2262.7 ± 4.17*51.06 ± 3.25*

Morphological changes were observed by visual inspection of cell cultures. Figure 3(b) shows that SiO2 NPs-treated cells show increased cell size (black arrows) at 0.001 g/L and 0.01 g/L SiO2 NPs. Higher concentration (0.1 g/L) caused enlarged cells and also caused significant cell death (indicated by cell debris formation, black punctuated arrow). SiO2 NPs (1 g/L) killed most of the cells and precipitated in culture dishes (white arrow). Similarly to flow cytometry data LPS-treated cells appeared more granular than control samples; however, the morphology of LPS-treated cells differed from SiO2 NP-treated cells, as visible in Figure 3(b).

In order to obtain an exact cell size, Coulter counter measurements were performed. RAW 264.7 cells were cultured in the presence of SiO2 NPs (0.005 g/L or 0.01 g/L) or LPS in cell suspension for 24 h. As Figure 3(c) shows, ~85% of untreated cells exhibited sizes between 10–20 μm. LPS-treated cells showed similar cell size distribution to control cells. However, SiO2 NPs-treated cells showed a decrease in 10 and 20 μm cells but showed a significant increase in cells between 20 and 30 μm.

3.4. SiO2 NPs Determine Increased Proliferation (Plate-Based Assays) but Show Decreased Proliferation (Coulter Counter and Flow Cytometry Assays)

In order to determine if SiO2 NPs influence cell proliferation, SiO2 NP-treated RAW 264.7 cells were assayed for cell proliferation using 3 different methods: plate-based assays, Coulter counter, and flow cytometry. RAW 264.7 cells were exposed to SiO2 NPs (0.0025 g/L–0.009 g/L) for 24 h, and proliferation was determined by CyQuant 96 plate-based assay (measuring DNA content via fluorescence). Figure 4(a) shows that the plate-based assay shows increased values over control when treated with SiO2 NPs (0.0025 g/L). Pre- and postspike controls were also included, and controls did not indicate assay interference (data not shown).

Cells were also counted using Coulter counter assays, and 2 concentrations were used: 0.005 g/L and 0.01 g/L SiO2 NP. LPS was used as positive control. Figure 4(b) shows that SiO2 NPs cause a concentration-dependent decrease in RAW 264.7 cell numbers. There was ~30% decrease in cell number at 0.005 g/L and ~40% decrease at 0.01 g/L. However, based on PI data (Figure 2(b)) 0.01 g/L SiO2 NP causes ~20% decrease in viability. To make sure that the decrease in cell number is not partly due to decrease in viability, flow cytometry measurements using CFSE staining and PI staining were employed which allows analysis of live cell proliferation (by excluding dead, PI-positive cells). CFSE profiles (gated only on live cells) show a decreased proliferation in cells treated with LPS and SiO2 NPs (0.0025 g/L–0.01 g/L; Figure 4(c)). Although decrease in CFSE intensity occurred in LPS and SiO2 NP-treated samples, these changes were not statistically significant compared to control cells (based on mean fluorescence intensity values, data not shown).

4. Discussion

Plate-based assays are frequently performed for cytotoxicity evaluation, even though NP interference with this type of assay is rampant for many NP constructs. In order to account for NP interference, it is imperative to include controls in the experimental design. Controls can help detect, and in some cases account for, NP interference. Even when all the recommended controls are included, however, there are cases where NP interference detection and assay result interpretation is problematic [11, 42].

“No cell” controls are useful to detect NPs catalyzing assay substrates as well as to provide a background value for the NP solutions; however, the disadvantage of this type of control is that they do not contain cells and therefore NP characteristics (such as formation of protein corona and subsequent interaction with cells), and NP “stickiness” might be different in no-cell controls compared to treated samples. Prespike and postspike controls are recommended and widely used to determine quenching and other effects. However, the incubation time of NP with the substrate in postspiking controls is usually shorter (due to assay stability) and NP characteristics (agglomeration and protein corona) are therefore different, which might not allow complex substrate-NP interactions. In order to remove SiO2 NP and avoid possible interference with assay substrates, cell cultures were centrifuged, and SiO2 NP-containing media was replaced by fresh media at the end of treatments in Figure 2(b). In the case of CellTiter-Blue and XTT there was an increase value over control at low SiO2 NP concentrations. These values were decreased when plates were spun down and background values were subtracted. “No cell” controls as well as pre- and postspiked controls did not indicate any significant interference issues. It is possible, therefore, that the increased values over control at low SiO2 NPs concentrations could be due to increased mitochondrial activity.

Changes in mitochondrial activity are detected by MTT (3-(4, 5-dimethylthiazol-2-yl)-2, 5-diphenyltetrazolium bromide), XTT (2, 3-bis [2-methoxy-4-nitro-5-sulfophenyl]-2H-tetrazolium-5-carboxanilide), Alamar blue, resazurin (CellTiter-Blue), and ATP assays, to name only a few. Although, all the abovementioned assays are often termed “viability assays,” it is important to understand what the assays are actually measuring and caution should be taken when interpreting assay results. For example, increased values in CellTiter-Blue, XTT, MTT, or other assays might indicate NP assay interference but could also indicate increased mitochondrial activity. For example, the polyphenolic flavonoid genistein caused decreased cell number and cell-cycle arrest of human breast cancer cells but let to an increase in MTT values due to increased mitochondrial number and activity [43]. STI571 (Gleevec) caused apoptosis and decrease in cell number in human breast cells but showed increased MTT values due to STI571-mediated inhibition of Abl kinases required for formazan reduction [44]. Therefore, it is highly recommended that cytotoxicity evaluation should comprise of multiple tests and endpoints in order to determine the true effect of the NP on the cells. Current studies are underway to determine if our observed MTT increase is due to NP assay interference, or an actual increase in mitochondrial activity.

Similar to mitochondrial assays, cell proliferation should be evaluated by complementary methods. For example, in this study Coulter counter measurement was the most sensitive technique in determining a significant decrease in cell number in SiO2 NP-treated cells versus control. On the other hand, the plate-based CyQuant assay showed an increase of cell proliferation (at 0.0025 g/L), with no other significant change noted. CFSE only showed a trend of decreased proliferation (complementing the Coulter counter assay).

Protocol modifications can influence assay outcomes therefore any adjustments when performing plate-based assays should be recorded and reported. Changes such as plate centrifugation and supernatant transfer as well as background subtraction lead to decreased values in CellTiter-Blue, XTT, and LDH-release assays. For example, LDH-release showed significant decrease in membrane integrity at 0.1 g/L SiO2 NP, but when the plates were centrifuged the only significant decrease in membrane integrity occurred at 1 g/L. It is possible that similar to TiO2 NP [18], SiO2 NPs bind LDH, and SiO2 NP-LDH complexes were removed after plate centrifugation (in Figure 2(b)). Both PI and LDH release are indicators of membrane integrity; therefore, it was expected that LDH release will correlate with PI staining results. However, this was the case only in Figure 2(a) but not in Figure 2(b). Therefore, when complementary assays result in contradictory data, they should be confirmed by a third technique or assay.

Although sample preparation for PI staining and flow cytometry measurements are more time consuming, viability determination by flow cytometry proved to be more sensitive and reliable for SiO2 NP. It has been demonstrated that when PI staining is performed in plate-based assays, it can bind to NPs and be transported inside the cells resulting in false-negative results [11]. However in case of flow cytometry PI staining is performed after media containing NP is removed, the cells are harvested from the plate and washed several times, all of which reduces the possibility of false-negative results through that particular mechanism. However, when preparing the samples for flow cytometry assay, especially in the case of adherent cells, cells should be carefully harvested, making sure that certain subpopulations are not lost or damaged during sample preparation (due to centrifugation or incomplete trypsin digestion), and cells are thoroughly processed to single-cell suspension. These considerations are applicable for Coulter counter assays as well. Therefore in the present study adherent and cell suspension cultures were used for flow cytometry and Coulter counter measurements.

Once NPs are phagocytosed, they can change cells’ granularity. This feature was captured in flow cytometry analysis where SiO2 NPs-treated RAW 264.7 cells showed changes in granularity. Therefore, modification in SSC can serve as a good indicator of NP incorporation (Figure 4(a)) or cell activation (as seen in case of LPS treatment; Figure 4(a)). Cell populations exhibiting changes in SSC can be identified and selectively sorted (using a cell sorter) if highly purified cell populations are required.

Even in cases when NP interference with plate-based or other absorbance or fluorescent-based assays is not detected, it is highly recommended that NPs are well characterized, controls (no cell controls, pre- and postspike, positive controls) are included, and results are confirmed by a battery of assays and techniques. By using a combination of plate-base assays, flow cytometry, Coulter counter assays and microscopy analysis we showed that concentrations of 0.001 g/L–0.01 g/L colloidal SiO2 NPs (7 nm) do not cause cytotoxicity in RAW 264.7 cells but determine an increase in granularity and cell size and a decrease in cell number at 24 h.

We conclude that (1) although we could not detect common causes of SiO2 NPs interference with plate-based assays at low SiO2 NP concentrations, plate-based assays and flow cytometry assays do not correlate; (2) flow cytometry staining was more sensitive in detecting decreased cell viability; (3) Coulter counter assay detected decreased proliferation and changes in cell size; (4) a panel of different techniques is required in order to determine and validate in vitro studies.

Disclosure

The findings and conclusions in this paper have not been formally disseminated by the Food and Drug Administration and should not be construed to represent any agency determination or policy. The mention of commercial products, their sources, or their use in connection with material reported herein is not to be construed as either an actual or implied endorsement of such products by the Department of Health and Human Services or by the National Institute of Standards and Technology.

Conflict of Interests

The authors do not have any conflict of interests.

Acknowledgments

The authors acknowledge the Office of Science and Engineering Laboratories, FDA, for the use of their TEM and TGA. This project was supported in part by an appointment to the Research Participation Program at the Center for Drug Evaluation and Research administered by the Oak Ridge Institute for Science and Education through an interagency agreement between the U.S. Department of Energy and the U.S. Food and Drug Administration.

Supplementary Materials

Supplemental Data: Pre- and postspike controls for CellTiter-Blue, XTT and LDH-release assays.

  1. Supplementary Data

References

  1. M. Chidambaram, R. Manavalan, and K. Kathiresan, “Nanotherapeutics to overcome conventional cancer chemotherapy limitations,” Journal of Pharmacy and Pharmaceutical Sciences, vol. 14, no. 1, pp. 67–77, 2011. View at: Google Scholar
  2. R. Sinha, G. J. Kim, S. Nie, and D. M. Shin, “Nanotechnology in cancer therapeutics: bioconjugated nanoparticles for drug delivery,” Molecular Cancer Therapeutics, vol. 5, no. 8, pp. 1909–1917, 2006. View at: Publisher Site | Google Scholar
  3. E. Blanco, A. Hsiao, A. P. Mann, M. G. Landry, F. Meric-Bernstam, and M. Ferrari, “Nanomedicine in cancer therapy: innovative trends and prospects,” Cancer Science, vol. 102, no. 7, pp. 1247–1252, 2011. View at: Publisher Site | Google Scholar
  4. W. L. Monsky, D. S. Vien, and D. P. Link, “Nanotechnology development and utilization: a primer for diagnostic and interventional radiologists,” Radiographics, vol. 31, no. 5, pp. 1449–1462, 2011. View at: Publisher Site | Google Scholar
  5. S. Katteboinaa, V. S. R. Chandrasekhar P, and S. Balaji, “Drug nanocrystals: a novel formulation approach for poorly soluble drugs,” International Journal of PharmTech Research, vol. 1, no. 3, pp. 682–694, 2009. View at: Google Scholar
  6. J. M. McKim, “Building a tiered approach to in vitro predictive toxicity screening: a focus on assays with in vivo relevance,” Combinatorial Chemistry and High Throughput Screening, vol. 13, no. 2, pp. 188–206, 2010. View at: Publisher Site | Google Scholar
  7. R. Damoiseaux, S. George, M. Li et al., “No time to lose—high throughput screening to assess nanomaterial safety,” Nanoscale, vol. 3, no. 4, pp. 1345–1360, 2011. View at: Publisher Site | Google Scholar
  8. S. Y. Shaw, E. C. Westly, M. J. Pittet, A. Subramanian, S. L. Schreiber, and R. Weissleder, “Perturbational profiling of nanomaterial biologic activity,” Proceedings of the National Academy of Sciences of the United States of America, vol. 105, no. 21, pp. 7387–7392, 2008. View at: Publisher Site | Google Scholar
  9. A. Kroll, C. Dierker, C. Rommel et al., “Cytotoxicity screening of 23 engineered nanomaterials using a test matrix of ten cell lines and three different assays,” Particle and Fibre Toxicology, vol. 23, article 9, 2011. View at: Publisher Site | Google Scholar
  10. S. George, T. Xia, R. Rallo et al., “Use of a high-throughput screening approach coupled with in vivo zebrafish embryo screening to develop hazard ranking for engineered nanomaterials,” ACS Nano, vol. 5, no. 3, pp. 1805–1817, 2011. View at: Publisher Site | Google Scholar
  11. A. M. Keene, R. J. Allaway, N. Sadrieh, and K. M. Tyner, “Gold nanoparticle trafficking of typically excluded compounds across the cell membrane in JB6 Cl 41-5a cells causes assay interference,” Nanotoxicology, vol. 5, no. 4, pp. 469–478, 2011. View at: Publisher Site | Google Scholar
  12. B. Kong, J. H. Seog, L. M. Graham, and S. B. Lee, “Experimental considerations on the cytotoxicity of nanoparticles,” Nanomedicine, vol. 6, no. 5, pp. 929–941, 2011. View at: Publisher Site | Google Scholar
  13. G. J. Oostingh, E. Casals, P. Italiani et al., “Problems and challenges in the development and validation of human cell-based assays to determine nanoparticle-induced immunomodulatory effects,” Particle and Fibre Toxicology, vol. 8, article 8, 2011. View at: Publisher Site | Google Scholar
  14. D. B. Warheit, C. M. Sayes, and K. L. Reed, “Nanoscale and fine zinc oxide particles: can in vitro assays accurately forecast lung hazards following inhalation exposures?” Environmental Science and Technology, vol. 43, no. 20, pp. 7939–7945, 2009. View at: Publisher Site | Google Scholar
  15. C. Hoskins, L. Wang, W. P. Cheng, and A. Cuschieri, “Dilemmas in the reliable estimation of the in-vitro cell viability in magnetic nanoparticle engineering: which tests and what protocols?” Nanoscale Research Letters, vol. 7, Article ID 77, pp. 1–22, 2012. View at: Publisher Site | Google Scholar
  16. W. Wohlleben, S. N. Kolle, L.-C. Hasenkamp et al., “Artifacts by marker enzyme adsorption on nanomaterials in cytotoxicity assays with tissue cultures,” Journal of Physics, vol. 304, no. 1, Article ID 012061, 2011. View at: Publisher Site | Google Scholar
  17. A. Kroll, M. H. Pillukat, D. Hahn, and J. Schnekenburger, “Current in vitro methods in nanoparticle risk assessment: limitations and challenges,” European Journal of Pharmaceutics and Biopharmaceutics, vol. 72, no. 2, pp. 370–377, 2009. View at: Publisher Site | Google Scholar
  18. M. S. K. Zaqout, T. Sumizawa, H. Igisu, D. Wilson, T. Myojo, and S. Ueno, “Binding of titanium dioxide nanoparticles to lactate dehydrogenase,” Environmental Health and Preventive Medicine, vol. 17, no. 4, pp. 341–345, 2012. View at: Publisher Site | Google Scholar
  19. X. Han, R. Gelein, N. Corson et al., “Validation of an LDH assay for assessing nanoparticle toxicity,” Toxicology, vol. 287, no. 1–3, pp. 99–104, 2011. View at: Publisher Site | Google Scholar
  20. A. Casey, E. Herzog, M. Davoren, F. M. Lyng, H. J. Byrne, and G. Chambers, “Spectroscopic analysis confirms the interactions between single walled carbon nanotubes and various dyes commonly used to assess cytotoxicity,” Carbon, vol. 45, no. 7, pp. 1425–1432, 2007. View at: Publisher Site | Google Scholar
  21. A. Dhawan and V. Sharma, “Toxicity assessment of nanomaterials: methods and challenges,” Analytical and Bioanalytical Chemistry, vol. 398, no. 2, pp. 589–605, 2010. View at: Publisher Site | Google Scholar
  22. B. Wahl, N. Daum, H. L. Ohrem, and C. M. Lehr, “Novel luminescence assay offers new possibilities for the risk assessment of silica nanoparticles,” Nanotoxicology, vol. 2, no. 4, pp. 243–251, 2008. View at: Publisher Site | Google Scholar
  23. S. Santra, “Fluorescent silica nanoparticles for cancer imaging,” Methods in Molecular Biology, vol. 624, pp. 151–162, 2010. View at: Publisher Site | Google Scholar
  24. P. Couleaud, D. Bechet, R. Vanderesse et al., “Functionalized silica-based nanoparticles for photodynamic therapy,” Nanomedicine, vol. 6, no. 6, pp. 995–1009, 2011. View at: Publisher Site | Google Scholar
  25. A. Burns, H. Ow, and U. Wiesner, “Fluorescent core-shell silica nanoparticles: towards “lab on a particle” architectures for nanobiotechnology,” Chemical Society Reviews, vol. 35, no. 11, pp. 1028–1042, 2006. View at: Publisher Site | Google Scholar
  26. J. Lu, M. Liong, Z. Li, J. I. Zink, and F. Tamanoi, “Biocompatibility, biodistribution, and drug-delivery efficiency of mesoporous silica nanoparticles for cancer therapy in animals,” Small, vol. 6, no. 16, pp. 1794–1805, 2010. View at: Publisher Site | Google Scholar
  27. C. Hom, J. Lu, and F. Tamanoi, “Silica nanoparticles as a delivery system for nucleic acid-based reagents,” Journal of Materials Chemistry, vol. 19, no. 35, pp. 6308–6316, 2009. View at: Publisher Site | Google Scholar
  28. C. Hom, J. Lu, M. Liong et al., “Mesoporous silica nanoparticles facilitate delivery of siRNA to shutdown signaling pathways in mammalian cells,” Small, vol. 6, no. 11, pp. 1185–1190, 2010. View at: Publisher Site | Google Scholar
  29. I. I. Slowing, J. L. Vivero-Escoto, C. W. Wu, and V. S. Y. Lin, “Mesoporous silica nanoparticles as controlled release drug delivery and gene transfection carriers,” Advanced Drug Delivery Reviews, vol. 60, no. 11, pp. 1278–1288, 2008. View at: Publisher Site | Google Scholar
  30. J. M. Rosenholm, V. Mamaeva, C. Sahlgren, and M. Lindén, “Nanoparticles in targeted cancer therapy: mesoporous silica nanoparticles entering preclinical development stage,” Nanomedicine, vol. 7, no. 1, pp. 111–120, 2012. View at: Publisher Site | Google Scholar
  31. D. Napierska, L. C. J. Thomassen, D. Lison, J. A. Martens, and P. H. Hoet, “The nanosilica hazard: another variable entity,” Particle and Fibre Toxicology, vol. 7, article 39, 2010. View at: Publisher Site | Google Scholar
  32. T. Aubert, F. Grasset, S. Mornet et al., “Functional silica nanoparticles synthesized by water-in-oil microemulsion processes,” Journal of Colloid and Interface Science, vol. 341, no. 2, pp. 201–208, 2010. View at: Publisher Site | Google Scholar
  33. Y. L. Zhao, Z. Li, S. Kabehie, Y. Y. Botros, J. F. Stoddart, and J. I. Zink, “pH-operated nanopistons on the surfaces of mesoporous silica nanoparticles,” Journal of the American Chemical Society, vol. 132, no. 37, pp. 13016–13025, 2010. View at: Publisher Site | Google Scholar
  34. C. Uboldi, G. Giudetti, F. Broggi, D. Gilliland, J. Ponti, and F. Rossi, “Amorphous silica nanoparticles do not induce cytotoxicity, cell transformation or genotoxicity in Balb/3T3 mouse fibroblasts,” Mutation Research, vol. 745, no. 1-2, pp. 11–20, 2012. View at: Publisher Site | Google Scholar
  35. B. M. Mohamed, N. K. Verma, A. Prina-Mello et al., “Activation of stress-related signalling pathway in human cells upon SiO2 nanoparticles exposure as an early indicator of cytotoxicity,” Journal of Nanobiotechnology, vol. 9, article 29, 2011. View at: Publisher Site | Google Scholar
  36. M. J. Akhtar, M. Ahamed, S. Kumar et al., “Nanotoxicity of pure silica mediated through oxidant generation rather than glutathione depletion in human lung epithelial cells,” Toxicology, vol. 276, no. 2, pp. 95–102, 2010. View at: Publisher Site | Google Scholar
  37. H. J. Eom and J. Choi, “SiO2 nanoparticles induced cytotoxicity by oxidative stress in human bronchial epithelial cell, beas-2B,” Environmental Health and Toxicology, vol. 26, article e2011013, 2011. View at: Google Scholar
  38. T. Yu, A. Malugin, and H. Ghandehari, “Impact of silica nanoparticle design on cellular toxicity and hemolytic activity,” ACS Nano, vol. 5, no. 7, pp. 5717–5728, 2011. View at: Publisher Site | Google Scholar
  39. M. Fisichella, H. Dabboue, S. Bhattacharyya et al., “Mesoporous silica nanoparticles enhance MTT formazan exocytosis in HeLa cells and astrocytes,” Toxicology in Vitro, vol. 23, no. 4, pp. 697–703, 2009. View at: Publisher Site | Google Scholar
  40. D. H. Tsai, R. A. Zangmeister, L. F. Pease, M. J. Tarlov, and M. R. Zachariah, “Gas-phase ion-mobility characterization of SAM-functionalized Au nanoparticles,” Langmuir, vol. 24, no. 16, pp. 8483–8490, 2008. View at: Publisher Site | Google Scholar
  41. D. H. Tsai, L. F. Pease, R. A. Zangmeister, M. J. Tarlov, and M. R. Zachariah, “Aggregation kinetics of colloidal particles measured by gas-phase differential mobility analysis,” Langmuir, vol. 25, no. 1, pp. 140–146, 2009. View at: Publisher Site | Google Scholar
  42. N. A. Monteiro-Riviere, A. O. Inman, and L. W. Zhang, “Limitations and relative utility of screening assays to assess engineered nanoparticle toxicity in a human cell line,” Toxicology and Applied Pharmacology, vol. 234, no. 2, pp. 222–235, 2009. View at: Publisher Site | Google Scholar
  43. M. C. Pagliacci, F. Spinozzi, G. Migliorati et al., “Genistein inhibits tumour cell growth in vitro but enhances mitochondrial reduction of tetrazolium salts: a further pitfall in the use of the MTT assay for evaluating cell growth and survival,” European Journal of Cancer A, vol. 29, no. 11, pp. 1573–1577, 1993. View at: Google Scholar
  44. J. T. Sims and R. Plattner, “MTT assays cannot be utilized to study the effects of STI571/Gleevec on the viability of solid tumor cell lines,” Cancer Chemotherapy and Pharmacology, vol. 64, no. 3, pp. 629–633, 2009. View at: Publisher Site | Google Scholar

Copyright © 2012 S. Bancos et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


More related articles

 PDF Download Citation Citation
 Download other formatsMore
 Order printed copiesOrder
Views8810
Downloads1634
Citations

Related articles

We are committed to sharing findings related to COVID-19 as quickly as possible. We will be providing unlimited waivers of publication charges for accepted research articles as well as case reports and case series related to COVID-19. Review articles are excluded from this waiver policy. Sign up here as a reviewer to help fast-track new submissions.