Table of Contents

Cover

Title Page

List of Contributors

Preface

Abbreviations

Chapter 1: Characterization of Nanomaterials in Nanotoxicological Analyses

1.1 Introduction
1.2 Size and Morphology of NMs
1.3 Composition and Structure
1.4 Surface Properties
1.5 Interactions between NMs and Biological Environments
1.6 Conclusions
References

Chapter 2: Quantitative Analysis of Metal-Based Nanomaterials in Biological Samples Using ICP-MS

2.1 Introduction
2.2 ICP-MS: A Power Tool for Element Analysis
2.3 Single-Particle ICP-MS: Theory and Application
2.4 Analysis of Nanoparticles by ICP-MS Hyphenate Techniques
2.5 Conclusion and Outlook
References

Chapter 3: Stable Isotopic Tracing of Nanomaterials In Vivo

3.1 Introduction
3.2 Development of Stable Isotope Labeling in Nanotechnology
3.3 ¹³C-Labeled Carbon Nanomaterials
3.4 Metal Stable Isotope Labeled Nanoparticles
3.5 Summary and Outlook
References

Chapter 4: Radiolabeling of Nanoparticles

4.1 Introduction
4.2 Radiolabeling of Nanomaterials
4.3 Summary and Outlook
References

Chapter 5: New Methods for Nanotoxicity Analyses: Synchrotron-Radiation-Based Techniques

5.1 Introduction
5.2 Speciation Transformation of NMs in Biological System by SR-Based Techniques
5.3 SR-Based Analytical Techniques for Understanding Nano–Bio Interactions
5.4 Conclusion and Prospects
References

Chapter 6: Imaging Techniques in Nanotoxicology Research1)

6.1 Introduction
6.2 Imaging Techniques for In Vitro Visualization and Quantification of Nanomaterials
6.3 Distribution and Quantification of Nanomaterials In Vivo
6.4 Conclusions
References

Chapter 7: In Vivo Nanotoxicity Assays in Animal Models

7.1 Introduction
7.2 Laboratory Animal Models
7.3 Administration
7.4 Particokinetics
7.5 In Vivo Toxicity of Nanomaterials
7.6 Recommendations
References

Chapter 8: In Vitro Testing Methods for Nanomaterials

8.1 Introduction
8.2 Preparation of Nanoparticle Suspensions
8.3 Cell Viability Assays
8.4 Oxidative Stress Assay
8.5 Inflammatory Assay
8.6 Summary and Outlook
References

Chapter 9: Localizing the Cellular Uptake of Nanomaterials

9.1 Introduction
9.2 Mechanism of Cellular Uptake of Nanomaterials
9.3 Methods to Determine Cellular Nanoparticle Uptake In Vitro
9.4 Representative Cellular Uptake of Nanomaterials and Intracellular Location Determined with Different Methods
9.5 Summary and Outlook
References

Chapter 10: Methods and Techniques in Molecular Toxicology of Nanomaterials

10.1 Introduction
10.2 Gene Mutation Detection
10.3 Gene Expression Analysis
10.4 DNA Damage Detection
10.5 Chromosomal Aberration Analysis
10.6 Omics
10.7 Conclusions
References

Chapter 11: Analyses Methods for Nanoparticle Interaction with Biomacromolecules

11.1 Introduction
11.2 Biological Effects due to Nanoparticle–Biomolecule Interactions
11.3 Basic Methods to Understand NPs and Protein Interactions
11.4 Summary and Outlook
References

Chapter 12: “Omic” Techniques for Nanosafety

12.1 Introduction
12.2 Materials and Biological Models
12.3 Genomics Study for Nanosafety
12.4 Transcriptomics Study for the Biological Effects of ENMs
12.5 Proteomics Study for Nanosafety
12.6 Metabolomics Study for Nanosafety
12.7 Summary and Outlook
References

Chapter 13: Nanometallomics: New Approach on Analyzing Biological Effects of Metal-Related Nanomaterials1)

13.1 Introduction
13.2 Integrated Approaches on the ADME of Metal-Related Nanomaterials in Biological Systems
13.3 Interactions of Metal-Related Nanomaterials with Genes, Proteins, and Other Biomolecules
13.4 Conclusions
Acknowledgments
References

Chapter 14: Molecular Simulation Methods for Safety Analyses of Nanomaterials

14.1 Introduction
14.2 The Molecular Simulation Methods for Nanomaterials and Biological Systems
14.3 The Scientific Problems in Biological Effects of Nanomaterials Studied by Molecular Simulations
14.4 Summary and Outlook
Acknowledgments
References

Chapter 15: Ecotoxicity Analyses of Nanomaterials

15.1 Introduction
15.2 Transformation of ENMs in the Environment
15.3 Toxicity of ENMs in Terrestrial Ecosystem
15.4 Other Terrestrial Organisms
15.5 Aquatic Organisms
15.6 Challenges and Perspective
References

Index

End User License Agreement

List of Illustrations

Chapter 2: Quantitative Analysis of Metal-Based Nanomaterials in Biological Samples Using ICP-MS

Figure 2.1 ICP-MS-based hyphenated systems [29].
Figure 2.2 Conceptual diagram for the single-particle inductively coupled plasma–mass spectrometry (SP-ICP-MS) method. Samples containing dissolved metals will produce a constant stream of charged ions after passing through the plasma. The detector will then have a relatively constant intensity versus time signal for each dwell time. Conversely, a sample containing inorganic nanoparticles at a sufficiently low concentration will create a pulse of charged ions after passing through the plasma. Here, a resulting spike in intensity versus time will occur for dwell times that contained nanoparticulate metal [36].
Figure 2.3 DNA hybridization assay with AuNP probes by using SP-ICPMS. The first step was to functionalize citrate-protected AuNPs with two sets of single-stranded DNA, probe 1 and probe 2. Then DNA targets were hybridized with AuNP–probe 1 and AuNP–probe 2 in buffer solution. The solution of AuNP aggregates was introduced into the plasma torch by the nebulizer and then AuNPs underwent desolvation, particle vaporization, atomization, and ionization in the ICP zone at approximately 6000–7000 K. Finally, the frequency and intensity of the 197Au + pulse signals were recorded by the electron multiplier detector [50].
Figure 2.4 Mass cytometry allows single-cell atomic mass spectrometry of heavy elemental (>100 Da) reporters. Schematic of ICP-MS-based analysis of cellular markers. An affinity product (e.g., antibody) tagged with a specific element binds to the cellular epitope. The cell is introduced into the ICP by droplet nebulization. Each cell is atomized, ionized, overly abundant ions removed, and the elemental composition of remaining heavy elements (reporters) is determined. Signals corresponding to each elemental tag are then correlated with the presence of the respective marker and analyzed using conventional cytometry platforms [60].
Figure 2.5 Simultaneous identification and size characterization of ENMs in complex media by CE-ICP-MS. EOF = electro-osmotic flow [70].
Figure 2.6 Histogram showing the log-normal distribution of Au mass for the ablation of 70 cells. The two averages from single-cell analysis (the blue solid line) and cell digestion analysis (the red dot line) are 15 and 18 fg, respectively [75].

Chapter 3: Stable Isotopic Tracing of Nanomaterials In Vivo

Figure 3.1 Results of exposure of C₆₀ to ¹³C-enriched carbon vapor. (a) Positive ions generated from vaporization of a target comprised of amorphous ¹³C (99% atom ¹³C) target mixed with C₆₀ under the same conditions, with mass-scale expansion of C₆₀ illustrating the occurrence of atom exchange events. (b) C₆₂−C₇₀ mass region expanded to show growth of C₆₀ to larger fullerenes by successive ¹³C incorporation events.
Figure 3.2 Characterization of ¹³C-enriched C₆₀. (a) MS of ¹³C-enriched C₆₀; (b) MS of unlabeled C₆₀; (c) IR spectra; and (d) Raman spectra [29].
Figure 3.3 ¹³C NMR spectra of ¹³C-labeled C₆₀ fullerenols; SSB indicates sideband. (a) ¹H−¹³C CP spectra at contact times of 2 ms and (b) ¹³C MAS NMR spectrum of C₆₀ fullerenols [48].
Figure 3.4 Biodistribution of ¹³C−C₆₀ in mice after intravenous(i.v.) administration (n = 4) [29].
Figure 3.5 (a) The biodistributions of pristine SWNTs (¹³C-SWNT). (Reprinted with permission from [28], Copyright (2007) American Chemical Society.); (b) the PEGylated SWNTs (¹³C-SWNT). (Reprinted from the cited paper [27] with permission from Wiley.); (c) ¹³C-enriched carbon nanoparticles in mice at different time points postexposure via intravenous(i.v.) injection. (Reprinted with permission from [30], Copyright (2014) American Chemical Society.)
Figure 3.6 SWCNTs with different Raman colors and imaging. (a) Schematic SWNTs with three different isotope compositions (¹³C-SWNT, ¹²C/¹³C-SWNT, ¹²C-SWNT) conjugated with different targeting ligands and multicolor Raman imaging of live cells. (b) Solution-phase Raman spectra of the three SWNT conjugates under 785 nm laser excitation.
Figure 3.7 Raman spectra of the ¹²C 1-layer graphene (LG), ¹³C 1-LG, and ¹³C/12C 2-LG (¹³C is on top, ¹²C at bottom) samples.
Figure 3.8 Conceptual model. The exposure material is dispersed in artificial seawater (1), which results in the aggregation of the primary bulk and nano ZnO particles (2) and subsequent sedimentation (3). Dissolved aqueous ⁶⁸Zn is formed by dissolution of oxide precipitates or immediately after dispersion for ⁶⁸ZnCl₂ (4) and subsequently sorbed onto sediment particles (5). Corophium volutator feed on organic matter on the sediment surface or suspended particles by drawing this food into their U-shaped burrows. Uptake of the ⁶⁸Zn label from all forms of exposure material occurs via the dissolved state, directly from both the aqueous phase (6) and/or the intake of sediment with adsorbed Zn (7). The inset indicates food intake by C. volutator (8) and as the sediment and water pass through the alimentary canal, detoxification of Zn occurs through the formation of Zn-rich sphalerites in the hepatopancreas (9). The C. volutator are in a stage of metal accumulation for the duration of the exposure; therefore, defecation (10) does not include ⁶⁸Zn-rich sphalerites.

Chapter 4: Radiolabeling of Nanoparticles

Figure 4.1 Preparation of ¹²⁵I-SWNTols by chloramine-T method.
Figure 4.2 Autoradiographs of ceria NPs in cucumber leaves. (a) 7 nm ceria, third, fourth, fifth, and sixth leaves and (b) 25 nm ceria, first, fourth, and sixth leaves.

Chapter 5: New Methods for Nanotoxicity Analyses: Synchrotron-Radiation-Based Techniques

Figure 5.1 Example of SAXS diffractogram (experimental data on NM105 suspension sonicated at pH 2 as circles) illustrating the unified fit (solid red line) and its components, prevailing in each q-domain (dashed-dotted lines, see text for details). Insert of transmission electronic micrograph (credit P.-J. de Temmerman and J. Mast, CODA-CERVA) illustrating the gyration radius of primary particles (R_g1) and aggregates (R_g2) used in the model.
Figure 5.2 Stability regimes of BSA-Ag NPs in HNO₃ measured by absolute-intensity-calibrated USAXS. (a) In 50 mM HNO₃, BSA-Ag NPs slowly dissolve with almost no agglomeration, as evidenced by the relatively flat, low-q scattering curve, and optical clarity of the solution (inset). (b) In 250 mM HNO₃, BSA-Ag NPs simultaneously agglomerate and dissolve while the solution darkens. (c) In 500 mM HNO₃, the BSA coating completely destabilizes, causing rapid clustering of principal particles into agglomerates, as seen in the large scattering intensities at low-q values and the dark turbid suspension. In this case, “steady” dissolution proceeds as long as the particles are stirred; otherwise, they sediment, as detected by an exponential decay in the scattering intensity and by visual inspection.
Figure 5.3 River biofilm exposed to 1 mg/l Cu nanoparticles for 5 min. (a) Cu image difference map (I_931.3 eV–I₉₂₅ eV) (red) overlayed on the gray-scale of the biology image difference map (I_288.2 eV–I₂₈₀ eV). The white box indicates the area of the detailed study. Detailed study of a cyanobacterial cell. (b) Color-coded composite map of protein (red), lipid (green), and polysaccharides (blue). (c) Overlay of the Cu image difference map from a on the lipid and protein component maps from (b) (red = Cu nanoparticles, green = lipid, blue = protein).
Figure 5.4 STXM mapping of the electronic structure of graphene. STXM images and data of CVD grown SLG on Cu after wet etching in HNO₃ and transfer. (a) Transmission-mode data is converted to OD by I/I₀, where I₀ is measured in an empty scan region; summation of 0.3 eV energy steps is normalized to carbon at 320 eV. Corresponding white intensity describes the thickness and morphology of the graphene sheet. The scale bar is 1 µm and the total distance across the image is 4 µm. (b) Integrated C K-edge spectrum of entire image in (a). The electromagnetic field vector (E) and incident X-ray photon energy (hN) are at angle (Q). The angular difference between the pristine basal plane (blue P orbitals) and the asperity (red P orbitals) represents a degree of corrugation (F) of a rippled graphene sheet. (c) Isolated C K-edge spectra of each region displayed in (a), where spectra D and F displayed in the inset have the most prominent pre-edge features.
Figure 5.5 (A) Typical μ-XRF maps of P and Fe of macrophages unexposed or exposed to 50 µg/ml SWCNT for 24 h (a) and X-ray fluorescence spectra integrated exclusively over the scanned cells, normalized to the phosphorus signal (b). The inset represents zoomed areas around the positions of the Kα fluorescence peak of iron together with fits of its contribution (dashed lines) [34]. (B) X-ray microfluorescence spectra integrated over the whole murine macrophages exposed for 24 h to MWCNT suspensions at concentrations of 100 µg/ml [34]. (C) X-ray microfluorescence spectra integrated over the whole scanned area of murine macrophages exposed for 24 h to nonpurified SWCNT suspensions at 10 µg/ml [37].
Figure 5.6 The 3 D reconstructed tomography images of Hela cells. (a) Control cells and (b) cells after incubation with TiO₂ NPs for 6 h (red color indicates the TiO₂ NPs.
Figure 5.7 Cellular uptake, accumulation, and exocytosis of AgNPs. The spatial distribution of AgNPs in a single cell captured by SR-TXM. Smaller colored spots indicate particles or vesicles on the surface or inside the cells. Green, yellow, and red colors indicate increasing gradients of X-ray absorption intensity by vesicles or aggregated particles. The larger red particles in the square blue frames are gold particles used as a reference for data reconstruction processing. The color bar indicates the related contrast signals from X-ray absorption of silver inside cells.
Figure 5.8 Fe distribution in mouse olfactory bulb (A) and brain regions (B) tested by SR-XRF. (a) Control group and (b) Fe₂O₃-NP group. ON: olfactory nerve layer, Gl: glomerular layer, Epl: external plexiform layer, Ipl: internal plexiform layer, GrO: granule cell layer of olfactory bulb, Md: medullary layer, GrA: granule cell layer of accessory olfactory bulb, and AOE: anterior olfactory nucleus external part.
Figure 5.9 Two-dimensional elemental maps for Zn, Se, and Ca, Zn, Se overlay for D. magna exposed to red MUA-coated CDSe/ZnS QDs. Vertical columns correspond to Zn, Se, and an overlay of Ca, Zn, and Se, respectively. Horizontal rows correspond to 12 and 24-h exposure time points.
Figure 5.10 The biodistribution of nutritional elements in eggs after parental exposure to MNPs. Synchrotron-radiation-based microbeam X-ray fluorescence (SR-μ-XRF) mappings of Fe, Ca, Zn, and Cu in Drosophila eggs of the control and UN-, CA-, and APTS-MNP- (300 µg/g) treated groups.
Figure 5.11 In situ XAS analysis of intracellular Ti-rich regions. (a) μ-XRF image of a cross section of Caco-2 cells exposed for 24 h, on their apical pole, to 50 µg/ml of TiO₂-NPs. Phosphorus (P) distribution map is depicted in green and titanium (Ti) distribution map is depicted in red. The area pointed out with an arrow was further analyzed by XAS. (b) XAS spectra of reference Ti-acetate and TiO₂-anatase nanopowders (5, 12, and 25 nm) and of Ti-rich regions in Caco-2 cells exposed for 12 h (cells 12 h) or 24 h (cells 24 h) to 50 µg/ml of 12 nm-diameter anatase TiO₂-NPs. (c) Focus on the pre-edge region (4972–4985 eV) and its deconvolution using an arctangent function and four Gaussian peaks (A₁, A₂, A₃, B). Solid line: recorded data; dashed line: fit. Panels indicate A₂/A₃, which is the ratio of intensity of A₂ to intensity of A₃ [52].
Figure 5.12 In situ elemental analysis of the metabolization of QDs in C. elegans by XRF and XAS. (a) Scheme of XRF mapping of C. elegans; (b) mappings of an intact worm exposed to MEA-CdSe@ZnS for 24 h; and (c) in situ Se K edge microbeam X ray absorbance near-edge structure (μ-XANES) spectra of QDs within the digestive tract of C. elegans corresponded to points A, B, and C on XRF mappings. The beam size of μ-XRF mappings and μ-XAS spectra was 5 × 5 µm².
Figure 5.13 Comparison of the C K-edge, N K-edge, and O K-edge XANES spectra of SWCNTs, the pristine streptavidin protein, and SWCNTs treated in streptavidin protein solutions at different concentrations: 15, 200, and 1000 µg/ml.
Figure 5.14 Analysis for bio–nano interaction at molecular level. SRCD spectra of protein–Ag NP complex (red) and free protein (black) collected with a low volume capacity 10 cm path length cell. There is a decrease of 6 °C in the thermal unfolding of human serum albumin upon interaction with silver NPs.
Figure 5.15 Integrated synchrotron radiation analytical techniques for nanotoxicological studies.

Chapter 6: Imaging Techniques in Nanotoxicology Research1)

Figure 6.1 Imaging techniques for cellular visualization of nanomaterials. (a,b) SEM [5]; (c,d) ESEM [6]; (e) EELS [7]; (f,g) STEM [8]; (h) TEM [9]; (i) EDX [10]; (j,k) PIXE [11]; (l) STXM; (m,n) μ-XRF[12]; (o) SIMS [13]; (p) LA-ICP-MS [14]; (q,r) confocal [15]; (s) multiphoton luminescence [16]; (t) dark-field microscopy [9]; and (u–y) AFM [[6, 17]].
Figure 6.2 Atomic force microscopy of silica NPs and carbon nanohorns in macrophages and red blood cells. (a) Schematic of the experimental set-up; (b) AFM image of macrophages exposed to SWCNH; (c) phase image of macrophages; (d) phase image of erythrocytes; (e) phase images of buried silica NPs in macrophages at different spatial resolution; and (f) influence of the driving frequencies on resulting force curves and phase images [17].
Figure 6.3 Commonly used imaging techniques arranged according to their spatial resolutions and sensitivities.

Chapter 7: In Vivo Nanotoxicity Assays in Animal Models

Figure 7.1 Schematic representation of zebrafish life cycle and embryonic development.
Figure 7.2 Automatic zebrafish manipulation and imaging platform.
Figure 7.3 (a) Schematic representation of C. elegans life cycle and (b) anatomy of an adult hermaphrodite.
Figure 7.4 Schematic representation of Drosophila life cycle.
Figure 7.5 Uptake and translocation routes of NMs.
Figure 7.6 Exposure chamber (breathing zone) for whole-body exposure (a) and nose-only exposure (b).
Figure 7.7 Schematic representation of inhalation exposure system for manufactured nanomaterials. Vertical view (a) and perspective view (b).
Figure 7.8 Diagram of the nebulizer NM delivery system.
Figure 7.9 Skin layers.
Figure 7.10 Predicted fractional deposition of inhaled particles in the nasopharyngeal, tracheobronchial, and alveolar regions of the human respiratory tract during nasal breathing [62].
Figure 7.11 Schematic representation of human and mouse placentae.

Chapter 9: Localizing the Cellular Uptake of Nanomaterials

Figure 9.1 Known pathways of cellular uptake of NPs.
Figure 9.2 The schematic of the spinning disk laser scanning confocal microscopy live-cell imaging system for temporal resolution cell imaging and cellular NP trajectories analysis (left part of picture was afforded by PerkinElmer Inc.). Live cells using a spinning disk laser confocal scanning microscope equipped with a cultivation chamber fitted with a temp control and CO₂-control device. The cellular NPs trajectories were analyzed by professional imaging software Volocity. The circles in the live-cell image of fluorescent dots (right bottom) represent the areas from which the trajectories were generated in the right upper image.
Figure 9.3 Confocal microscopic images show the subcellular localization of FITC-C₆₀(C(COOH)₂)₂ mainly in the lysosome. (a). FITC-C₆₀(C(COOH)₂)₂ (green fluorescence) were uptake by HeLa cells. (b). Punctate co-localization of FITC-C₆₀(C(COOH)₂)₂ with Lyso Tracker Red. (c). C₆₀(C(COOH)₂)₂ nanoparticles are not located in mitochondria. Bar: 10 μm.
Figure 9.4 Confocal microscopy study of the localization of PS NPs and tubulin in HeLa cells at different phases of mitosis. (a) Colocalization of COOH-PS NPs (green) with tubulin (CY-3-microtubulin antibody, red) after incubation for 24 h in fixed cells. (b) Colocalization of NH2-PS NPs (orange) with tubulin (TubulinTracker Green, Oregon Green 488 Taxol, bis-acetate) in live cells. The nuclei were stained with Hoechst 33342 (blue). Scale bar: 10 µm.
Figure 9.5 Uptake pathways and quantitative process of internalization and removal of Au NRs in A549, 16HBE, and MSC cells by ICP-MS after treated with Au NRs. (a, c) The process of cellular internalization and exclusion of Au NRs, respectively. (b) Uptake pathways for Au NRs in two types of cells using specific endocytosis inhibitors.

Chapter 10: Methods and Techniques in Molecular Toxicology of Nanomaterials

Figure 10.1 Schematic of widely applied techniques in molecular toxicology of nanomaterials.
Figure 10.2 (a) Ames test procedure of plate incorporation assay method. (b–d) TEM microphotographs of Salmonella typhimurium TA98 showing: (b) control cell, (c) internalization of ZnO NPs, and (d) internalization of TiO₂ NPs [80].
Figure 10.3 (a) The procedure of one-step and two-step RT-PCR. (b) Changes of genes expression from real-time RT-PCR analysis at 24 and 48 h Au NP treatment [116].
Figure 10.4 (a) Effects of Nano-Co (Co NPs) or Nano-TiO₂ (TiO₂ NPs) exposure on DNA double-strand breaks (DSBs) in A549 cells. (Reprinted with permission from [137], Copyright (2012), American Chemical Society.) (b) Immunofluorescence images of γ-H2AX after treatment with TiO₂ NPs. (c) Comparison of generation of γ-H2AX after treatment with TiO₂ NPs in different size detected by western blotting [138].
Figure 10.5 (a) Ag NP treated IMR-90 cells show acentric and centric fragments. (b) Arrow indicates acentric fragments. (c) Untreated cancer cells with no aberrations. (d) Ag NP treated U251 cells. White arrow points to a dicentric chromosome. (e) Acentric fragments. (f) Centric fragments. Red arrow points to a chromosome fragment [151]. (g) Fluorescence in situ Hybridization (FISH) analysis of control and Au NP treated MRC-5 lung fibroblasts (1 nM concentration and 72 h) [116]. (Copyright © 2011 Elsevier Ltd.) (h) The various possible fates of cultured cytokinesis-blocked cells following exposure to cytotoxic/genotoxic agents [152].

Chapter 11: Analyses Methods for Nanoparticle Interaction with Biomacromolecules

Figure 11.1 Surface hydrophobicity of Au NPs influencing the adsorption of serum proteins that determines the cellular uptake of NPs. (a) SDS-PAGE of serum proteins adsorbed on Au NPs. The lanes labeled with NP 4, NP 3, NP 2, and NP 1 correspond to the proteins adsorbed to the corresponding Au NPs that are incubated with 50% FBS for 6 h. The hydrophobicity index is shown as LogP square values, representing the hydrophobicity of the head groups. The values for four NPs are 0.63, 1.8, 2.9, and 3.65, respectively. (b) Uptake of four Au NPs inside HeLa cells within culture media containing three kinds of serum proteins (BSA, IgG, and Tf). The contents of three proteins are 25 mg/ml (BSA), 5 mg/ml (IgG), and 2 mg/ml (Tf). The protein mixture refers to a medium containing a mixture of all three proteins used at the same concentrations. (c) The relationship between Au NP surface hydrophobicity (LogP square values) and the amount of cellular uptake. HeLa cells that were exposed to Au NPs in the media supplemented with 10% FBS.
Figure 11.2 PEG backfilling preventing nonspecific adsorption of serum proteins on NPs that improves binding specificity of NPs to targeted cells. (a) Scheme of the backfilling strategy for mPEG docking with different chain lengths on OPSS-PEG-Herceptin-AF647-modifed Au NPs. (b) The specific binding efficiency of Herceptin-conjugated Au NPs to cells in media containing human serum. Two kinds of cells have high-level (SKBR3) or low-level (MCF7) expression of Herceptin-associated receptor, ErbB2-receptor. IF shows fluorescence intensity, and cell count means normalized cell number included in all events counted. Red and blue lines represent cells treated with or without competitive Herceptin molecules, respectively. (c) The binding specificity of NPs to targeted cells is dependent on serum-protein adsorption and the chain length of PEG for backfilling.
Figure 11.3 Superoxide-scavenging abilities in the CeO₂ NPs (nanoceria). (a) The antioxidant role of CeO₂ NPs mixed with the lysates of human bronchial epithelial cells, (b) the SOD mimetic activity of the CeO₂ NPs after the mixing of CuZn-SOD (final concentration of 1 U/ml) with CeO₂ NPs (0.033 nM) within 24 h, and (c) SOD mimetic activity for CeO₂ NPs. Effect of SOD/CeO₂ NPs on superoxide anions from KO₂ was determined by ESR measurement.
Figure 11.4 The characterization of protein corona on NPs in different physiological media. (a) Mean dynamic sizes of 50 μM FBS-coated Au NRs determined by DLS when incubated in PBS (pH at 7.2) and in artificial lysosomal fluid (ALF, pH at 4.5) during 60 min, respectively. (b) The visible and NIR absorption spectra of Au NRs before and after incubation with 10% fetal bovine serum (FBS) in PBS (Phosphate buffer solution) at different time intervals at 37 °C. (Reprinted with permission from [38]. Copyright © 2011 American Chemical Society.) (c) Zeta potentials of Au NRs dispersed in aqueous solution after being incubated with medium with (w/) or without (w/o) serum at 37 °C for 1 or 30 min and centrifuged. The inset shows reducing band intensity in SDS-PAGE for serum proteins recognized as serum albumin mainly in the supernatant separated from Au NRs and serum mixture after 2 h incubation. CTRL (control) represents the serum proteins without incubation with Au NRs [77].
Figure 11.5 The application of SAXS into the study of nano–protein interactions. SAXS data (scattering intensity I(q) versus length of scattering vector q) for, respectively, 1.0 mg/ml SC (open triangles) and 1.2 mg/ml SM particles (the silica NPs) and 1.0 mg/ml SC (closed triangles). The line is the sum of the SC and the SM scattering. (b) SAXS data for, respectively, 1.0 mg/ml BSA (open squares) and 1.2 mg/ml SM particles and 1.0 mg/ml BSA (closed squares). The line is the sum of the BSA and the SM scattering. Insets in both graphs show the residuals between the scattering intensities from the samples with SM + protein and the sum of the SM and protein scattering.
Figure 11.6 The binding of BSA protein to the surface of Au NRs and its influence on cytotoxicity. (a) TEM images of BSA-adsorbed Au NRs. (b) The interfaces for BSA (plane S) via disulfides (yellow) to bind the Au (111) surface of Au NRs. (c) Various sulfur species in reference samples: Au−S, R−S (cysteine, thiol, Met), and R−S−S−R′ (cystine), shown as normalized S K-edge XANES spectra. (d) Chemical species of sulfur in cysteine, Met, and cystine after incubation with Au NRs. (e) Elemental mappings of Au, S, and Ca using μ-XRF to analyze internalized FBS/Au NRs in cells at different time intervals. The insets are cell images under a bright field. (f) LDH release from cells exposed to Au NRs and FBS-coated Au NRs for 24 h, which indicated the changed permeation of cell membrane after treatment. (g) Cytotoxicity was evaluated by alive–dead assay for cells exposed to CTAB/Au NRs and FBS/Au NRs after exposure for 12 and 24 h.

Chapter 12: “Omic” Techniques for Nanosafety

Figure 12.1 Major dose–response profiles for gene expression changes induced by 10 and 500 nm amorphous silica particles. Heat map profiles for the three major dose–response patterns of gene expression (2 h) identified by supervised hierarchical clustering are shown in (a–c). The centroid plots in (d–f) represent the corresponding overall average patterns of expression at three different doses of each particle for pattern a (d), pattern b (e), and pattern c (f).
Figure 12.2 Comparison of network analysis between GO and rGO by Pathway Studio.
Figure 12.3 Gene/protein expression profiles of biomarkers indicate difference of DNA damage repair pathways upon exposure to four types of ENMs ((a) TiO₂-NPs, 50 µg/ml, (b) carbon black (CB), 5, 50 µg/ml for human cells), (c) single-walled carbon nanotube (SWCNT, 8 µg/ml for E. coli, 10 µg/ml/l for yeast and human cells), and (d) purified fullerene (C60, 50 µg/ml) across three species. The mean natural log of induction factor (ln I) indicates the magnitude of altered gene/protein expression (represented by a green-black-red color scale at bottom). Red spectrum colors indicate upregulation, green spectrum colors indicate downregulation. Values beyond ±2 are shown as ±2). X-axis bottom: for E. coli and yeast: testing time in minutes, the first data point shown is at 20 min after exposure due to data smoothing with moving average of every five data points; for human cells: testing time in hours. Y-axis left: clusters of genes/proteins by DNA damage repair pathways. Y-axis right for each species [43].
Figure 12.4 Transcriptomic analysis of gene regulation by SPIONPs. (a) Hierarchical clustering of significantly effected (compared to time matched controls) transcripts shows a higher preponderance of downregulation (green) by SPIONP exposures. Upregulation (red) was more prominent during earlier time points where the most highly induced mRNAs encoded inflammatory cytokines. (b) Highest ranking biological processes associated with transcripts upregulated by in vivo exposure to SPIO NPs. Cellular processes associated with inflammation and clearance of foreign bodies (cytokine production, cell migration, chemotaxis) were significantly up-regulated [24].
Figure 12.5 (a) Cartoon representation of the possible exchange/interaction scenarios at the bio–nano interface at the cellular level. (b) Schematic drawing of the structure of NP–protein complexes in plasma: the “core” nanoparticle is surrounded by the protein corona composed of an outer weakly interacting layer of protein (left, full red arrows) rapidly exchanging with a collection of free proteins and a “hard” slowly exchanging corona of proteins (right). Diagram is not to scale in representing the proportions of the different objects.
Figure 12.6 Bioinformatic classification of identified corona proteins according to their functions. Employing bioinformatics tools, proteins identified in the respective SiNPs corona were classified according to biological processes of the blood system (a). The relative percentages of the proteins compared to crude plasma are shown. A significant enrichment of plasma proteins involved in complement activation (b), lipoproteins (c), coagulation (d) as well as proteins grouped as “tissue leakage” (g) was evident in the corona. Although immunoglobulins (e), acute-phase response proteins (f), and serum albumin (h) were present in high amounts in the plasma, these proteins displayed a lower affinity for the SiNPs.
Figure 12.7 Protein coronas and their composition are established rapidly. (a) SDS-PAGE was used to visualize nanoparticle-bound plasma proteins. Molecular mass and time points are indicated. (b) Corona quantification (protein (fg) per particle at the indicated time points. Continuously increased protein binding was observed for AmSil30 and also, slightly, for nPsNPs, whereas pPsNPs showed decreased binding over time. Values are mean + s.d. from two independent experiments. (c,d) Classification of corona proteins identified on nine different nanoparticles by LC-MS according to their calculated molecular mass (c) or isoelectric point (d). Relative percentages are shown. (e) Plasma exposure time modulates protein abundance (averaged molecule number per nanoparticle) on the indicated silica nanoparticles. Compared with SiNP30, proteins bound to the larger SiNP140 in higher copy numbers. Relative numbers of proteins present at the indicated copy numbers per indicated nanoparticle are shown. (f) Dendrogram illustrating sample similarities between protein binding profiles, which shows that they are correctly kinetically classified and that significant changes in the corona composition occurred at early rather than at late exposure time periods.
Figure 12.8 Representative PCA score plots (PC1 versus PC2) derived from the ¹H NMR data of body fluid samples (plasma and urine) and tissue samples (extracted from brain, kidney, liver, lung, and spleen) from the corresponding groups of rats: C, control group; L, low-dose group; H, high-dose group; 0, 0 h post-dose; 6, 6 h post-dose; 24, 24 h post-dose; 48, 48 h post-dose [29].

Chapter 14: Molecular Simulation Methods for Safety Analyses of Nanomaterials

Figure 14.1 Four molecular simulation methods as classical molecular dynamics, first-principles, QM/MM, and reactive molecular dynamics in simulation scale–modeling scale coordinate.
Figure 14.2 Characteristic snapshots of the simulation interaction process of Gd@C₈₂(OH)₂₂ binding to MMP-9 [28].
Figure 14.3 Interactions between BFG, Ig, Tf, BSA, and SWCNTs. (a,b) AFM images of proteins after incubation with SWCNTs for 10 min and 5 h. (c) Molecular modeling illustrations for proteins binding to SWCNTs after incubation d,e Locations and the interaction details of the most preferred binding sites on proteins for SWCNTs [41].
Figure 14.4 (a) RMSD of the backbone of the whole four-triplex bundle with reference to the initial conformation in Tetramer-0 (black), and Tetramer-Gd (red) systems. (b) Initial conformation of the four collagen triplexes [50].
Figure 14.5 The electric details during the transitions [83].

Chapter 15: Ecotoxicity Analyses of Nanomaterials

Figure 15.1 Pathway and transformation of nanomaterials in the environment.
Figure 15.2 Interactions between E. coli and CeO₂ NPs: in NS (a) and in PBS (b).
Figure 15.3 (a,e) TEM images of root cells and (b,f) Ce maps of rectangle area in (a) and (e) obtained by a ratio of 886 and 888 eV images. Color bar values are estimated from Ce absorption coefficients and X-ray absorption measurements (in g/cm²). The calculated surface densities are respectively between 1.1 × 10⁻⁵ to 6.4 × 10⁻⁵ and 2.4 × 10⁻⁶ to 2.8 × 10⁻⁵ g/cm²; (c,g) color-coded maps of Ce components in (b) and (f) derived from an STXM Ce M edge stack analysis. The order of Ce contents is as follows: green > red > yellow; blue color represents the non-Ce regions; panels (d) and (h) are respectively the XAFS spectra extracted from the image sequences of (c) and (g). The black line spectra above belong to the standard compounds and the colored spectra below belong to the root samples. The vertical red dotted lines indicate the characteristic peaks of CePO₄ and the dash lines indicate the characteristic peaks of CeO₂ NPs.

List of Tables

Chapter 3: Stable Isotopic Tracing of Nanomaterials In Vivo

Table 3.1 Stable-isotope-labeled nanomaterials and their structure and nanobiological effects
Table 3.2 Natural Zn isotope abundances and isotopic enrichment and approximate cost of commercially available enriched Zn isotopes [88]

Chapter 4: Radiolabeling of Nanoparticles

Table 4.1 SuiTable isotopes for radiotracer research
Table 4.2 An overview of radiolabeling of iron oxide NPs for multimodal imaging

Chapter 7: In Vivo Nanotoxicity Assays in Animal Models

Table 7.1 Main features of animal models widely used in nanotoxicology

Chapter 8: In Vitro Testing Methods for Nanomaterials

Table 8.1 In vitro methods and in nanotoxicology studies

Chapter 12: “Omic” Techniques for Nanosafety

Table 12.1 KEGG pathway analysis of gene expression data from Daphnia magna exposed to Ag NWs identified the enrichments of different biological pathways.^a

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List of Contributors

Xueling Chang
Institute of High Energy Physics

CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety

Chinese Academy of Sciences
Beijing 100049
China

Chunying Chen
CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety National Center for Nanoscience and Technology
Beijing 100190
China

Weiyue Feng
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Yuxi Gao
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects ofNanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Zhanjun Gu
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Xiao He
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Chenchen Li
Shanghai University
Institute of Nanochemistry and Nanobiology
Shanghai 200444
China

Wei Li
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

and

Wuhan Institute of Virology Chinese Academy of Sciences
Wuhan 430071
China

Yu-Feng Li
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Xueying Liu
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Yuhui Ma
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Bing Wang
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Liming Wang
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Meng Wang
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Yanli Wang
Shanghai University
Institute of Nanochemistry and Nanobiology
Shanghai 200444
China

Liang Yan
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Peng Zhang
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Zhiyong Zhang
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Feng Zhao
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Jiating Zhao
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Lina Zhao
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Yuliang Zhao
Institute of High Energy Physics CAS Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety Chinese Academy of Sciences
Beijing 100049
China

Preface

After more than 30 years of basic and applied research, nanotechnology is coming to play a big role in almost all of our lives, ranging from industry, food, and agriculture to biomedicine, and so on. Nanomaterials are known as the most important bases of nanotechnology and possess more novel and unique physicochemical properties than bulk materials. So, the impacts of their unpredictable behaviors on human health and the environment undoubtedly cause public concern. The understanding of the safety and potential hazards of engineered nanomaterials (ENMs), that is, nanotoxicity, has witnessed an explosion in the past decade and become one of key issues in nanotechnology, in particularly, the sustainable development of nanotechnology.

The study of toxicology of nanomaterials, unlike the classic one for those ordinary chemical compounds, should be approached by many ways, as multiparameters associated with the size, shape, chemical composition, crystalline structure, aspect ratio, surface property (chemical modification, surface charge, surface area, biological/chemical activity, etc.), agglomeration, concentration, and so on, likely combine to contribute to the overall toxicity. To obtain the whole picture, the advanced methods with integrated techniques for quantitatively monitoring the biological responses with material-specific or exposure-route-specific are needed. Moreover, it is expected that some new techniques, such as synchrotron-radiation-based analytical techniques, high-throughput “omic” techniques, in situ, and in vivo image techniques, as well as computational biology are involved for the exploration of exposure, early effect, differentially sensitive targets, and molecular mechanisms of ENMs in biological systems and, furthermore, trigger revolutionary research to understand the complex reactions of nanomaterials occurring at a nano–bio interface of biological or environmental systems.

Toxicology of Nanomaterials focuses on topics describing the current tools and methods that have been developed to study nanomaterial effects on biological and environmental systems, including the following: Characterization of Nanomaterials in Nanotoxicological Analyses (Ma Yuhui); Quantitative Analysis of Metal-Based Nanomaterials in Biological Samples Using inductively coupled plasma–mass spectrometry (ICP-MS) (Wang Meng); Stable Isotopic Tracing of Nanomaterials In Vivo (Chang Xueling, Zhao Yuliang); Radiolabeling of Nanoparticles (Zhang Zhiyong); New Methods for Nanotoxicity Analyses: Synchrotron-Radiation-Based Techniques (Wang Bing, Feng Weiyue); Imaging Techniques in Nanotoxicology Research (Yan Liang, Li Yufeng, Gu Zhanjun); In Vivo Nanotoxicity Assays in Animal Models (He Xiao); In Vitro Testing Methods for Nanomaterials (Zhao Feng, Liu Xueying); Localizing cellular uptake of nanomaterials (Li wei); Methods and Techniques in Molecular Toxicology of Nanomaterials (Wang Yanli, Li Chenchen, Chen Chunying); Analyses Methods for Nanoparticle Interaction with Biomacromolecules (Wang Liming, Chen Chunying); Omics Techniques in Nanosafety (Feng Weiyue); Nanometallomics: New Approach on Analyzing Biological Effects of Metal-Related Nanomaterials (Li Yufeng, Zhao Jiating, Gao Yuxi, Chen Chunying); Molecular Simulation Methods for safety Analyses of Nanomaterials (Zhao Lina): Ecotoxicity Analyses of Nanomaterials (Zhang Peng). Excepting Yanli Wang, all the other authors are from Chinese Academy of Sciences Key Laboratory for Biomedical Effects of Nanomaterials and Nanosafety. Please note that the book is not possible to describe detailed principles of all the aforementioned analyses methods, but describes how to apply these methods in the study of nanotoxicology.

The outcomes from more than 10 years of nanosafety research have shown that the interactions between nanomaterials and cells, animals, humans, or the environment are remarkably complex. Thus, this book also intends to give the state-of-art information on multidisciplinary techniques from biology, chemistry, and physics that enables the study of nanotoxicology. The book is designed to benefit researchers who plan to investigate nanotoxicology, nanomedicines, nanobiotechnology, and biomedical nanomaterials, nanochemistry, nanobioanalytical sciences, and so on, in particularly, to understand how the physical, chemical, and other properties of nanomaterials influence their biological/environmental behaviors and interactions and thus determine the ultimate impacts on health and the environment, and to design/synthesize/manufacture safer nanomaterials in various applications.

Beijing June, 2016

Yuliang Zhao, Zhiyong Zhang, and Weiyue Feng