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RTI International
ERC/SRC center at University of Arizona May 31, 2012
Contemporary Issues in Nanotoxicology: Continuing to
Relate Material Properties to Biological Response
Christie Sayes, Ph.D.
Program Manager Nanotoxicology & Nanopharmacology
Center for Aerosol and Nanomaterials Engineering
RTI International
Engineering and Technology
ACKNOWLEDGMENTS
Support
Sayes Lab Department of Vet. Physiology & Pharmacology and the Department of Biomedical Engineering
o Michael Berg
o Amy Romoser
o Aishwarya Sooresh
o Allen Sho
o Peter “Alex” Smith
o David Figuero Center for Aerosols and Nanomaterials Engineering
o Spencer West
o Phil Durham
o Laura Haines
Texas A&M University RTI International
2
Engineering and Technology
NP
Advantages to Nanotechnology
Enhanced Drug
Solubility
Increased Drug
Specificity
Imaging
Applications
Diagnostics
Altered Optical
Properties
Increased
Insulating Ability
Improved
Electronic Efficacy
Bactericidal
Consumer Products Medicine & Research
But what are the risks? 3
Engineering and Technology
The most accepted toxicological
evaluation is an in vivo study. Because
tissues are composed of multiple cell
types, in vitro toxicology must use
multiple cell types in the study design.
Effects must be related to particle PCC
• Size
• Morphology
• Surface
Nanotoxicology is the study of the environmental and human health
effects of nanomaterials designed to improve our way of life.
3-step process to characterize nanotoxicity
1. Delivery
2. Chemical/biochemical reaction with target
3. Cellular dysfunction and resultant toxicities
What is Nanotoxicology?
4
Engineering and Technology
Themes in Nanotoxicology that Influence Other Fields
Approach: The scale of health using the hierarchical oxidative stress model
DIS
EA
SE
-FR
EE
DIS
EA
SE
D
no observable adverse effects
immunological response
no extended adverse effects
This approach fits well within RTI International
“turning knowledge into practice”
Level of Oxidative Stress Increasing
Increasing Particle Concentration
5
Engineering and Technology
0 5 10 15 20
0
1
2
3
4 media & UV
Time (min)
0
1
2
3
4 media & sonicate
0
1
2
3
4 media
RL
U (
x 1
0,0
00
)
0
1
2
3
4water
nano-TiO2 anatase
nano-TiO2 rutile
Structure Chemistry Toxicity
Toxicological evaluations require comprehensive material characterization including both
physical attributes and chemical surface reactivity.
Physical & chemical features of nanomaterials
6
Engineering and Technology
Nanoparticle Properties Relevant
To Nanotoxicology
1) Chemical composition
2) Size & size distribution
3) Surface area
4) Surface chemistry,
stability, REDOX
5) Crystallinity & purity
6) pH & ISP
SO3H
7
Engineering and Technology
Raw Materials Production
Product Manufacturing
Consumer Use
Product End of Life
A Life-Cycle Approach
Step 1: Material Characterization of Pristine Engineered Nanomaterial
Step 2: Formulate Nanocomposite or Other Nano-Enabled Bulk Material
Step 3: Simulate Wear-and-Tear or Weathering Conditions
Step 4: Measure Exposures
Step 5: Perform Focused Toxicity Testing
Step 6: Assess and Manage Risks
8
Engineering and Technology
CASE STUDY:
Importance of Material
Characterization
9
Engineering and Technology
Material Characterization
Berg & Sayes, Nanotoxicology, 2009
Effects of pH on a metal
oxide nanoparticle
10
Engineering and Technology
0
25
50
75
100
1hr 24hr 48hr
0
500
1000
1500
2000
2500
-80
-60
-40
-20
0
20
40
60
80
1 3 5 7 9 11 13
Zeta
po
ten
tia
l (m
V)
pH
model NP
control cells
Ce
llu
lar
via
bil
ity (
%)
Exposure time
0
25
50
75
100
1hr 24hr 48hr
0
500
1000
1500
2000
2500
3000
-80
-60
-40
-20
0
20
40
60
2 4 6 8 10
pH
TiO2
TiO2
Ce
llu
lar
via
bil
ity (
%)
Exposure time
0
25
50
75
100
1hr 24hr 48hr
0
500
1000
1500
2000
2500
3000
3500
-50
-30
-10
10
30
50
2 4 6 8 10
Siz
e (
nm
)
pH
Al2O3
Ce
llu
lar
via
bil
ity (
%)
Al2O3
Exposure time 11
Engineering and Technology
Gastric Acid Lysosomal
Fluid
Intestine &
Urine Blood
pH Level <2 4.5 5 7.4
Metal oxide
nanomaterial Zeta potential (mV) / Average agglomerate size (nm)
TiO2 +46/1573 +22/1860 +7/2390 -37/460
ZnO +50/360 +44/945 +16/1200 -3/1170
Al2O3 +45/561 +38/1750 +27/2400 -4/3050
CeO2 +32.6/1444 +26/2340 +20/2590 -6/2850
Fe2O3 +25.4/1800 -9/1740 -15/1700 -47/830
Can we predict how nanomaterials would behave in physiological compartments?
TiO2 and Fe2O3 nanoparticles demonstrate strongly charged agglomerates at pH=7.4
Material Characterization
12
Engineering and Technology
CASE STUDY:
TOXICOLOGICAL EFFECTS
(AND MECHANISTIC ANALYSES)
OF SILICA NANOPARTICLES
13
Engineering and Technology
In vitro cellular systems will need to be further developed, standardized,
and validated (relative to in vivo effects) in order to provide useful
screening data on the relative toxicity of inhaled particles
Each particle should be tested on a case-by-case basis
Cannot assume that nanomaterials are the same as
their bulk counterpart
but also cannot assume that they are more toxic
Risk = Hazard Exposure
Most nanotoxicology studies include hazard
identification
only some include exposure assessment
14
Engineering and Technology
• Schematic diagram of the aerosol
nanoparticle reactor with
characterization instrumentation
• TEOS was pyrolyzed to generate SiO2
nanoparticles that are charged with an
aerosol neutralizer
• Characterized with a long or nano DMA,
and measured for particle concentration
with a condensation nucleus counter or
aerosol electrometer
Experimental Design
Exposure Groups
Group 1 (3 day exposure)
Sham (5 rats/group)
Particle-exposed (5 rats/group)
Targeted particle sizes = 35 nm
and 80 nm
Group 2 (1 day exposure)
Sham (5 rats/group)
Particle-exposed (5 rats/group)
Targeted particle sizes = 35 nm
and 80 nm
Inhalation
Post-exposure evaluation via
lung fluid and lung tissue
24 hr 1 wk 1 mo 2 mo
(lung fluid) (tissue)
Dose Metrics for Inhalation Studies
15
Engineering and Technology
Particle Physicochemical Characterization
Aerosol Concentrations and Sizing
of 37 nm Amorphous Silica Particles (1x Day 1)
0.00E+00
1.00E+06
2.00E+06
3.00E+06
4.00E+06
5.00E+06
6.00E+06
7.00E+06
1 10 100 1000
Size (nm)
Co
nc
en
tra
tio
n (
pa
rtic
les
/mL
)
initial concentration 7:00 am
animal exposure 7:15 am
animal exposure 8:20 am
animal exposure 9:20
animal exposure 10:40 am
animal exposure 11:45 am
Aerosol Concentrations and Sizing
of 71 nm Amorphous Silica Particles (3x Day 3)
0.0E+00
2.0E+06
4.0E+06
6.0E+06
8.0E+06
1.0E+07
1.2E+07
1.4E+07
1.6E+07
1.8E+07
1 10 100 1000
Size (nm)
Co
ncen
trati
on
(p
art
icle
s/m
L)
initial concentration 7:15 am
animal exposure 7:45 am
animal exposure 8:50 am
animal exposure 10:00 am
animal exposure 11:00 am
animal exposure 12:15 pm
Aerosol nanoparticle size distributions for SiO2 exposure in the inhalation chamber
as a function of exposure time demonstrating aerosol stability
Typical aerosol exposure run on day 1
for the d50 = 37 nm particle generation
experiment
Typical aerosol exposure run on day 3
for the d50 = 83 nm particle exposure
experiment
37 nm 83 nm
16
Engineering and Technology
Inflammatory Response Dead Cells
Pulmonary Effects
Lung lavage fluid percent polymorphed neutrophil
(%PMN) values
Lung lavage fluid lactate dehydrogenase (LDH) values
0
100
200
300
400
500
24 Hour
1 Week
1 Month
0
100
200
300
400
500
Sham 1X Exp 1X Sham 3X Exp 3X
37 nm SiO2
83 nm SiO2
0%
25%
50%
75%
100%
0%
25%
50%
75%
100%
Sham 1X Exp 1X Sham 3X Exp 3X
37 nm SiO2
83 nm SiO2
17
Engineering and Technology
sham (unexposed) animals animals exposed to
83 nm aerosolized silica
nanoparticles
AD
TB
AD
TB
AD
Lung pathology after 2 month exposure
animals exposed to
37 nm aerosolized silica
nanoparticles
AD
TB
Exposed Sham
Catalase Activity
(mU • mL-1 • mg protein-1) 34.35 ± 0.2 31.63 ± 0.01
Total Glutathione
(mM/10k cells) 2.34 ± 0.19 1.69 ± 0.14
Pulmonary Effects
18
Engineering and Technology
Lung Tissue of Rat Exposed to Positive Control Particle after 1 week
19
Engineering and Technology
0
100
200
300
0.01 0.1 100 0.01:4 0.1:4 100:4 0.01:4 0.1:4 100:4 0.01:4 0.1:4 100:4
Control Fe2O3 Fe2O3:ECB Fe2O3:ECB + AA Fe2O3:ox-ECB
RF
U
Nanomaterial dose (mg/L)
*
*
* *
2011
Berg and Sayes, CRT (2010)
Oxidative Stress is a Theme in Nanotoxicology
20
Engineering and Technology
Differential Cellular Uptake Mechanisms
21
Engineering and Technology
Tier 1
Normal
Tier 2
Antioxidant Defense
Tier 3
Inflammation
The Role of In Vitro Toxicology in Nanotoxicology
Due to the enormous range of nanomaterial-types, coupled with the infinite variety of surface
coatings, in vitro toxicology will play a major role in hazard identification
Hierarchical Oxidative Stress Model
But, are we considering if the effects are reversible? 22
Engineering and Technology
Characteristics of A549 and MeT-5A Cells
A549 Cell Line
• Isolated through explant culture of
lung carcinomatous tissue
• Considered a type II lung epithelial cell
epithelial (surfactant producing)
• Reported to have high levels of
antioxidant enzymes
MeT-5A Cell Line
• Isolated from pleural fluids obtained
from non-cancerous individuals
• Transfected with a plasmid containing
SV40
• Normal cell precursor to mesothelioma
Berg JM, Figueroa DE, Romoser AA, Sayes CM. (2012)
Toxicology In Vitro, submitted.
Cu/Zn SOD
Mn SOD
A549 MeT-5A
Catalase
GAPDH
23
Engineering and Technology
Silica at the Nanoscale: How safe is it?
Micrometer crystalline SiO2 is a Class II IARC
probable carcinogen often associated with
respiratory diseases such as:
• Silicosis
• Fibrosis
Endpoints in toxicological studies involving
SiO2 are often dependent upon particle
surface characteristics
Micrometer amorphous SiO2 is under GRAS
classification and often used as a negative
control in toxicological studies
Since SiO2 particle toxicity has often been reported as a function of surface
parameters, and since nanoparticles exhibit high surface area to mass ratios, it
is necessary to reevaluate the safety of SiO2 particles at the nanoscale
SEM: Nanoscale Amorphous SiO2
24
Engineering and Technology
250 nm
5 µm
Transmission Electron Micrograph
Scanning Electron Micrograph
Energy Dispersive X-ray Spectroscopy
Silica Nanoparticle Characterization
25
Engineering and Technology
Concentration of H2O2 (µM)
Differential Response to Oxidative Stress
MTT Assay Live:Dead Cell Counts
0
20
40
60
80
100
120
50 100 250 500 800 1500 2000
0
20
40
60
80
100
120
140
5 50 100 250 500 800 1000 1500 2000
*
* * * *
*
*
*
* * * *
Cell
Via
bili
ty (
% o
f C
ontr
ol)
Concentration of H2O2 (µM)
* * * *
* * *
*
0
20
40
60
80
100
120
0.01 0.1 1 10 25 50 75 100
Concentration of 30 nm SiO2 (µg/mL) Concentration of 30 nm SiO2 (µg/mL)
* * *
0
20
40
60
80
100
120
140
0.01 0.1 1 10 25 50 75 100
* * *
* * *
p<0.05 A549
MeT-5A
26
Engineering and Technology
Ub
sMaf
Cytosol
Nucleus
ROS
Nrf-2 P
P P
ARE
↑CAT ↑other antioxidants
Ke
ap
1
Nrf-2 P
P
P
Kinase
Signaling
Cascade(s)
SiO2
SiO2
Nrf-2
Cul3
Rbx1 E2
Ub
Ub
HS
HS
Keap1
S S
NF-E2 Related Factor (Nrf2)
• Critical regulator of
intracellular
antioxidants and
phase II
detoxification
enzymes.
• May be induced by:
• Electophilic
Stress
• Kinase Signaling
Pathways
• Activation of Nrf2
can be cyto-
protective at low
levels of ROS
The Good The Bad • Elevated Nrf2 is a major
obstacle to the
successful treatment of
many cancers
The Ugly We hypothesize that SiO2
nanomaterials, which has
been shown to produce
ROS, may activate the
Nrf2 signaling pathway.
This induction might lead
to the induction of many
phase II genes which can
have implications in both
resistance against cell
death and carcinogenesis
27
Engineering and Technology
Ub
sMaf
Cytosol
Nucleus
ROS
Nrf-2 P
P P
ARE
↑CAT ↑other antioxidants
Kea
p1
Nrf-2 P
P
P
Kinase
Signaling
Cascade(s)
SiO2
SiO2
Nrf-2
Cul3
Rbx1 E2
Ub
Ub
HS
HS
Keap1
S S
SiO2 exposed epithelial cells values given in hours
Cont. 0.5 2 4 8 12 24 48 1
NRF2
GAPDH
SiO2 exposed mesothelial cells Cont. 0.5 2 4 8 12 24 48 1
NRF2
GAPDH
Nrf2 Stabilization
28
Engineering and Technology
Nrf2 Cytoplasmic Stabilization & Nuclear Translocation
Unexposed Control tBHQ (50 mM) SiO2 (75 µg/mL)
ep
ith
elia
l m
eso
the
lial
Scale bar = 10 mm
Cytoplasmic stabilization & nuclear translocation of NRF-2 (GREEN) was evident following
treatment with tBHQ or SiO2 nanoparticles for 24 hrs in both cell lines
29
Engineering and Technology
CASE STUDY:
MIXTURES NANOTOXICOLOGY –
ITS HARDLY EVER JUST ONE
30
Engineering and Technology
Exposure to Nanoparticle Mixtures
Reported Exposure to Nanoparticle Mixtures
Reference
Manganese from nearby welding during Li4Ti5O12 handling Peters, 2009
Iron and nickel as catalysts in carbon nanotube synthesis Maynard, 2004
Silicon & asbestos from insulation during CNTsynthesis Han, 2008
Combustion-derived particles from forklifts, heaters, & traffic Kuhlbusch, 2006 & 2010
Therefore, nanoparticle exposures are often mixtures of
combustion derived
carbonaceous particles and transition metals 31
Engineering and Technology
Nanoparticles Representative of Mixtures
Carbonaceous Particle
• Engineered Carbon Black
• Used as a surrogate for elemental
carbon in particulate matter
• Extensively used in airborne
toxicological studies
Fe2O3
ECB
Transition Metal
• Iron oxide (Fe2O3)
• Represent transition metal oxides in
particulate matter
• Water insoluble particle, but soluble in
acidic pH
32
Engineering and Technology
Guo and Sayes, P&FT, 2009
Aim
Determine if Co-exposures to
Fe2O3 and ECB results in additive
or synergistic cytotoxicological
effects
Conclusion
“Co-exposure to carbon black and
Fe2O3 particles can cause
oxidative stress that is
significantly greater than the
additive effects of exposures to
either particle type alone.”
33
Engineering and Technology
Chemically Active Groups on
ECB Surface Gives Rise to
Surface Redox Capabilities
H2Q(s) + 2Fe3+
(aq) ------> Q(s) + 2Fe2+(aq) + 2H+
Fenton Reaction:
Fe2+ + H2O2 → Fe3+ + OH· + OH-
Hypothesis: Oxidative stress formed in a co-exposure of
Fe2O3 and ECB can be eliminated by surface oxidation of
ECB (termed: ox-ECB).
Oxidation Decreases Reductive Capacity
34
Engineering and Technology
XPS gives quantitative data on
elemental composition and chemistry on the particle surface
ECB (%) Ox-ECB (%)
%C [C/ C+O] 89.88 88.53
%O [O/ C+O] 10.12 11.47
O:C 0.1126 0.1295
Ratio of Q(s):H2Q(s) was found to be circa 5000 times greater in ox-ECB than in ECB.
The O:C ratio in ox-ECB is 15% greater than in ECB. This may not seem like a large
increase, but edge carbons comprise about 20% of the total carbon content for 50 nm
amorphous carbon particles.
H2Q(s) + 2Fe3+(aq) ------> Q(s) + 2Fe2+
(aq) + 2H+
Surface Chemistry Analysis with XPS
35
Engineering and Technology
N
VV
Fe2O3
ECB
Fe2O3
ECB
V
V
V
ox-ECB
N
Fe2O3
Fe2O3 + ECB
2 mm 1 mm 0.5 mm
Fe2O3 + ECB Fe2O3 + ox-ECB
Intracellular Nanoparticle Incorporation
36
Engineering and Technology
1. A majority of the Fe2O3 is internalized into the cells after 24 hours
2. Uptake of Fe2O3 is not altered following ECB co-exposure
Intracellular Nanoparticle Incorporation
37
Engineering and Technology
Nanoparticle Agglomerates in Cellular Vesicles
STEM-HAADF micrograph
of internalized Fe2O3
nanoparticle agglomerates
Lysosomal Trafficking
• Nanoparticles accumulate in
lysosomes
• pH ≤ 5.2 (pKa Lysotracker Red)
• May alter dynamic nanoparticle
properties
• May solubilize water insoluble
particles
Fe2O3 Exposed
2μm
Control ECB Ox-ECB
Fe2O3
1 hr
3 hr
24 hr
Intracellular Trafficking of Nanoparticles
38
Engineering and Technology
Oxidant Production
• Significant increases seen
in Fe2O3 and ECB co-
exposure groups
• Oxidant production
eliminated by addition of
L-ascorbic acid
• ox-ECB and Fe2O3 did not
differ from control groups
• Effects greater at 25
hours than at 2.5 hours
Statistically significant to control population; P<0.05
39
Engineering and Technology
Nanomaterial physicochemical
features Induced toxicological effects Mathematical techniques
Cross-validation More
fundamental
More
complicated Immediate Systemic
Regression
Analysis Classification
Primary particle
size
Zeta potential (as
a measure of
surface charge)
Cell viability Metabolism Linear
Linear
Discriminant
Analysis
Inter-lab
comparisons
Shape Agglomerate size Tissue
damage
Distribution &
accumulation Non-linear
k-Nearest
Neighbor Beta-testers
Chemical
composition
Adsorption of
surrounding
matrix
Cytokine
production Inflammation
Machine
learning
Support Vector
Machines
Additional
physicochemical
data
Specific surface
area
Reductive
capacity
Membrane
damage
Immune
response
Causal
relationships
Decision Trees
or Neural
Networks
Additional
toxicology data
THREE KEY AREAS OF GROWTH:
Mathematical/Computational-Based Predictive Models
Alternative Toxicity Testing
Characterization of Real-World Exposure Scenarios
Where Do We Go From Here?
40