“all that exists are atoms and the void…..”

Democritus of Abdera (ca. 470-ca. 380 BC)

Andre Nel M.B.,Ch.B, PhD

University of California Los Angeles, Santa Barbara, Davis, Riverside; Columbia University, NY; University of Texas, University of New Mexico, Lawrence Livermore National Laboratory, Lawrence Berkeley National Laboratory

University College Dublin, Nanyang Techonological University, Cardiff University Wales, Unversity of British Columbia, Universitat Rovira i Virgili, Foundation Institute for Materials Science

• Develop a library of reference NMs

• Understand the impacts of different classes of NMs on cells, organisms and ecological systems

• Develop a predictive model of toxicology and environmental impacts of NMs

• Develop a computerized expert system for risk ranking

• Develop guidelines and decision tools for safe design and use of NMs

Objectives of the UC CEIN

Hazard Identification

Exposure Assessment

Risk Characterization

Risk Management

Example of the traditional approach:

Chemical Industrial Toxicology

50,000 plus chemicals registered for

commercial use in the US

< 1,000 have undergone toxicity testing

Overwhelming of resources: each test

• $2-$4 million (for in vivo studies)

• > 3 years to complete

How do we approach the safety of a new technology

on a scale commensurate with its rate of expansion?

Do we do it the traditional way: one material at a time?

US National Academy of Science (NAS) Report (2007):

“Toxicity Testing in the 21st Century: A Vision and a

Strategy”

http://www.nap.edu/catalog.php?record_id=11970

Descriptive single material tox testing in animals is time

consuming and expensive

Transformative approach is required that can provide

broad coverage of panels of toxicants

Use a robust scientific basis to perform safety testing

Robust = array of predictive in vitro tests that utilize toxicity

pathways and mechanisms

High content or high throughput screening to facilitate

testing of large batches of materials

In vitro hazard needs to be predictive of in vivo

The Science at the Nano-bio interface

Nanoparticle

physicochemical

properties

Nanoparticle

Influence zone

Suspending

Media modulating

those properties

Nano-bio interface

Living matter

Characterization

Screening

Characteristics

defining cell uptake

and bioavailability

Oxidant injury

Lysosomal injury

Mitochondrial injury

Apoptosis

Membrane damage

DNA damage etc

Hydrophobicity

Charge

Protein coating

Size

Shape

Dispersability

Characteristics

defining

biocatalytic

activity

Material

Composition

Cellular binding

and uptake

In vitro assays that could be useful for high content or HTS

to build quantitative SAR’s for nanomaterials

100’s/year 1000’s/year 10,000’s/day 100,000’s/day

High Throughput Bacterial,Cellular or Molecular Screening

Immediate Relevance

High Throughput Screening and Data Mining based on

QSAR relationships that can be used to rank NM for

risk and priority in vivo testing

Prioritize in vivo testing

at increasing trophic levels

Cellular/tissue/systemic

NM libraries &

characterization

IRG #2IRG #3

Hi Thru put screening

Computerized expert system, multimediamodeling, risk ranking

Risk perception

Fate &

Transport

Molecular, cellular, &

organ injury

pathwaysOrganism, population,

community & ecosystem

toxicology

IRG #1

IRG #2

IRG #4

IRG #3IRG’s #5-7

Interdisciplinary Research Groups (IRGs)

Hoek, Zink, Kaner,

Wang, and Yaghi

(UCLA)

Stucky (UCSB)

Walker, Yan, and

Haddon (UCR)

Mädler (Bremen)

Boey, Loo, Jan, Yoong,

and Yang (NTU)

Somasundaran

(Columbia Univ)

Bertozzi (UCB/LBNL)

IRG 1: Nanomaterial Synthesis and Physicochemical

Characterization

IRG Leader: Eric M.V. Hoek (UCLA)

IRG participants:

Standard Reference Material library acquisition and

characterization

Preliminary SRMs:

• Oxides: TiO2, SiO2, CeO2, ZnO

• Carbonaceous: C60, CNTs, carbon black

• Metals: gold and silver NPs, quantum dots

Selection criteria:

• Large production volume of commercial analogs

• Expected applications leading to environmental exposure

Synthesis/acquisition:

• Commercial samples

• CEIN synthesized analogs

Combinatorial library designed to provide

the same material in different sizes,

shapes, roughness, aspect ratios, states

of dispersal, chemical composition etc

NPs Y Z

Surface charge

Hydrophilicity/phobicity

Biomolecules

Drug molecules

XNPs Y Z

Surface charge

Hydrophilicity/phobicity

Biomolecules

Drug molecules

X

Combinatorial Library

Automated Nanocrystal Synthesis

at The Molecular Foundry

IRGs 2: Interactions at Molecular, Cellular, Organ and

Systemic Levels

IRG 2 Team

Patricia Holden (UCSB)

Andre Nel (UCLA)

Gary Cherr (UCD)

Leonard Rome (UCLA)

Joshua Schimel (UCSB)

Roger Nisbet (UCSB)

Hunter Lenihan (UCSB)Klaine SJ et al Environmental Tox & Chemistry. 2008..

DEB Modeling

Organismal

-NM

+NMPopulation

Growth /

Respiration

Time

Population

Responses

Cellular

IRG2: Interactions at Molecular, Cellular, Organ and

Systemic Levels

relates state of the environment to rates of growth,

reproduction/division, respiration + other fluxes

v-ATPase

Dissolution in suspending medium

Particle environment

(vacuum, gas, water)

pH 4.0-5.5

Lysosome

Cell

Particles and ions

crossing the cell membrane

MeOx - NP

Me2x+ - ion

Bio-molecule

Proton

Lysosome

Additional

cellular effects

Xia et al ACS Nano. 2008. Online

Nel et al. Nature Materials. Accepted

Particle Dissolution and release of toxic Metal ions

Particle-mediated Oxygen Radical production

Q Q.-

H2O2

OH.

Redox cycling

and catalytic

chemistry

Semiconductor

properties

Excited state

Electron-donor

active groups

O2

O2.-

e-

O2.- O2

e-

Electron hole

pairsOH

.

UV

e-

h+

O2

O2.-

H2O

Fe++

Fenton chemistry

Ambient UFP

Metal NP

Carbon NT

TiO2

Fullerene

Metal oxide

TiO2

Dissolution

Release of

ions

ZnO

Redox cycling

organics

Nel et al. Science, 311, 622-627, 2006

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v-ATPase

CFTR

Cationic

polymer

H2O

H2O

EnzymeEndosome

Lysosome

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+ Cationic toxicity and the

Proton Sponge Hypothesis

Nel et al. Nature Materials. Accepted

IRG 5: High Throughput Screening, Data Mining, and

Quantitative Structure-Activity Relationships for NM

Properties and Nanotoxicity

Group Leader: Ken Bradley (UCLA)

Participants:

Damoiseaux

Nel

Hoek

Keller

Cherr

Establish HTS

methodologies

Perform HTS

Data Mining &

QSAR profiling

+

Nano

Materials

Luminescence

Fluorescence

microscopy

Fluorescence

Spectroscopy

UV/Vis

spectroscopy

Cells

Bacteria

Yeasts

Organisms

Mitochondrial damage, ROS

generation, stress response,

cellular apoptosis

• Genotoxicity: Mutatox

• Cellular viability: Microtox

• ATP levels: ATPlite

• Luminescent reporter genes

• Fluorescent Reporter Genes (GFP)

• Mitochondrial damage (Mitotox)

• ROS generation

• Cellular apoptosis

• NADP (Mitoscan)

• Growth/viability/proliferation

via culture optical density

Epithelial

Endothelial

Macrophage

Kidney

Liver

Neuronal

etc

Tier 1Phase 2 anti-ox enzymesHO-1GSH

ROS Tier 1 Tier 2 Tier 3

Particle 1

Particle 2

Particle 3

Particle 4

Particle 5

Particle 6

Nel, Wiesner et al. Nano Letters. 2006

Tier 3MitochondriaMMPATPROS[Ca2+]m

Cell deathcaspase activationPI uptakeMTS assay

[Ca2+]i

SignalingJNKNF-kB

Tier 2InflammationcytokineschemokinesAbiotic

Biotic

In vitro comparison of Nanoparticle toxicity based on

the hierarchical oxidative stress paradigm

Focus: Quantifying effects of NMs on the

structure and function of food webs,

bioaccumulation and biomagnification, and

ecosystem-level processes

IRG3: Organismal, Population, Community, and

Ecosystem Ecotoxicology

IRG 3 Team

Hunter Lenihan (UCSB)

Joshua Schimel (UCSB)

Gary Cherr (UCD)

Roger Nisbet (UCSB)

Bradley Cardinale (UCSB)

Jorge Gardea-Torresday (UTEP)

Terrestrial Freshwater Marine

Benthic

algae

Invertebrate

grazers

Predatory

fish

Predatory

invertebrate

Invertebrate

filter-feeders

Planktonic

algae

Bacteria

Protozoa

Micro

arthropods

IRG3: Three model ecological systems

IRG 4: Fate & Transport

IRG Leader: Arturo Keller (UCSB)

Participants

P Somasundaran (Columbia U)

S Walker (UCR)

E Hoek (UCLA)

A Keller (UCSB)

Develop methods for sampling and analyzing NP in aqueous media

Develop relationships between NP characteristics and fate & transport parameters:

• NM interactions with different types of water in the absence or presence of NOM

• Transport phenomena

• Effect of NM on biogeochemical reactions

IRG 4 Objectives

Detecting nanomaterials in the environment

Develop protocols for quantitative measurement of NMs

in aqueous samples

Separation

• Gravitational FFF (Field-Flow Fractionation)

• Ultracentrifuge FFF

• Split FFF

• HPLC

• Ultracentrifuge w/o FFF

Detecting nanomaterials in the environment

Analysis of nano-scale fractions

• Dynamic Light Scattering (size distribution)

• AA or ICP-MS (chemical composition)

• X-ray spectromicroscopy (chemical composition)

• Spectroscopic analysis (using IRG 1 signals)

• C-14 labeled particles (to test protocol)

IRG 6: Integrated Data Management, Integrated Multimedia

Modeling and Computerized Expert System for Risk Ranking

and NM Safe Design

IRG 6 Team

Yoram Cohen (UCLA)

Ken Bradley (UCLA)

E. M.V Hoek (UCLA)

Barbara H. Harthorn (UCSB)

NCEAS Ecoinformatics (UCSB)

Arturo Keller (UCSB)

Francesc Giralt (URV)

Robert Rallo (URV)

Computerized Expert System

Machine Learning/

Pattern Recognition/

Fuzzy ARTMAP Classification/

Cognitive NN

Multimedia Analysis

AIR

Water

Soil

QSARs

In vivo

toxicity

Nanoparticle structural & physicochemical information

• Environmental Impact

• Exposure

• Risk Evaluation

• Scoring

• Ranking

• QRA

Cell, organism, HTS

Fate&

transport

1. Size, shape, aspect ratio

2. Hydrophobicity

3. Surface area, roughness & porosity

4. Solubility-release of toxic species

5. Surface species, contaminants,

adsorption during synthesis/history

6. Capacity to produce ROS

7. Structure/composition

8. Surface charge

9. Dispersion/aggregation

Zn++

O2 / H2OROS

1

2

3

3

4

5

6

78

9

e-

Zn++

Toxicological properties

that could be modified

to improve safety

Nel et al. Nature Materials. Accepted

Expert system for Nanomaterial Safe design

IRG 7: Environmental Risk Perception and Risk Communication

IRG 7 Team

Barbara H. Harthorn (UCSB)

Terre Satterfield (UBC)

William Freudenburg (UCSB)

Nick Pidgeon (Cardiff)

Paul Slovic (DR)

Robin Gregory (DR)

Objectives of IRG 7

• Develop comprehensive program to identify factors driving emerging public perceptions of risks to the environment regarding NMs and their enabled products.

Quantify Risk Perception Factors

• Develop models of emergent knowledge about nanotechnology risks, identifying key potentials for stigmatization or attenuation

Behavioral Implications

• Identify risk scoring factors to account for risk concerns and risk perception

• Develop scoring factors

Develop scoring methodology

• Work with science journalists to develop socially sustainable environmental risk communication

Risk Communication

• Focus research on cases of water filtration, soil/food production, nano energy and air quality, and climate change

Study Cases

Education and OutreachGroup Leader: Hilary Godwin (UCLA)

Program Objectives

Train a diverse cohort of new scientists who are broadly

trained to handle complex issues related to nanomaterials

in the environment

Train researchers to use appropriate safeguards when

handling or disposing of nanomaterials

Build a cohesive network of stakeholders with interests at

the interface of nanoscience and the environment

Accurately communicate to the public the implications of

nanotechnology in the environment

Core Program Components

Course on Nanotechnology and the Environment

Capstone course on Nanotoxicology

Training Course on Safe Handling of NMs

Annual International Meetings

Journalist–Scientist Communication Program

Disasters of the First Industrial Revolution

Mesoporous Nanoparticles for delivery of guess molecules,

imageging and targeting

Stimuli

• Light

• pH

• Enzymatic

• Temp

• Redox

Thread

Motorized

Bifunctional

valve

Targeting

epitope Stopper

Luminescent

Probe,

gadolinium

Drug

Paramagnetic

FeO

Liong et al. ACS Nano. 2008

FeO nanocrystal

Anticancer drug

Phosphonate coating

Targeting ligand

Multifunctional Silica Mesoporous Nanoparticles

designed for targeted delivery and imaging