better cell models to improve in vitro/in vivo correlation...
TRANSCRIPT
24/03/2017
Theme IV/Project 5
Better cell models to improve in
vitro/in vivo correlation in air pollution
toxicology
Ian Mudway
Background
Theme IV/Project 5 – Improved in vitro systems for evaluating and comparing
toxicity of air pollutants
The purpose of this project is to apply the in vitro cell culture and exposure systems
developed under project 4 for use in the toxicological assessment of nanomaterials to
investigate the toxicity of components of ambient air pollution.
Deliverables and milestones
•Milestone 1 – Develop programme of experimental work including identification of
appropriate systems and pollutants in consultation with consortium and other experts and
criteria governing the choice of materials on which to focus. (16/17)
•Milestone 2 – Commence experimental studies. (17/18)
Theme II: project 4 (David Phillips (King’s), Ian Jarvis (King’s) Volker Arlt
(King’s)); Martin Leonard (PHE)
Theme III: project 1 (Ken Raj (PHE))
Theme IV: project 4/5 (Terry Tetley (Imperial) and Rachel Smith (PHE))
Models
Theme II: project 4 Theme III: project 1 Theme IV: project 4
HCAEC
A549
BEAS2b/HBEC3kt
MDM
hAEC
EpiAirway (MatTek)
TT1 cell line
Primary bronchial
epithelial cells
Primary Type II cells (AT2)
Primary alv. Macrophages
SmallAir (Epithelix)
Dendritic cells Co-culture
BEAS2b + MDM
Co-culture
SRM2975 (diesel); SRM1648a (urban dust)
Co-culture
AT2 + TT1
MDM
MDDC
Primary MC
Primary DCs
Lymphocytes
Epithelial cells
HPRU members
Co-culture
MDDC/DC + CD4/CD8
Collaborators
Airway nerves
Airway/alveolar explants
Environmental samples: PM10, PM2.5, PM2.5-10, PM0.1
What is a good cell model? Physiological relevance
• Immortalised cell lines
• Primary cells
• Commercial cell lines
• Differentiated primary cells
• Explants
What is a good cell model? C
oh
ere
nc
e
In vitro – In vivo
correlation
• Co-culture
• Air-Liquid interface
• Submerged culture
• Respiratory tract lining fluid
• Interstitium
• Oxygen (13 vs. 21%)
• Tissue culture artefacts
Th
rou
gh
pu
t
Challenges
• Identifying the toxic components/characteristics of PM.
• Identifying source-specific toxicity.
• Disentangling the contribution of highly correlated
pollutants to adverse cellular responses: PM2.5 and NO2.
• Understanding the mechanisms leading to the systemic
effects of air pollutants.
• Identifying/validating source specific epigenetic and
metabolomics signatures in urban populations.
• Linking acute effects in vitro with long-term effects in
vivo.
Model specification
Strategy
Co-culture
Relevant ‘new’ reference materials
Known & contrasting clinical
responses
Standardisation
• Petrodiesel
• Biodiesel
– RME
– HVO
– Soy
– Pine
– Algae
• Biomass (wood)
• Contemporary PM
Impinger fluid and filter collection.
Extensive physical and chemical
characterisation
Chamber studies: Diesel Salvi SS, et al., (1999) AJCCRM
Salvi SS, et al., (2000) AJCCRM
Nordenhäll C et al., (2001) Eur Respir J
Stenfors N, et al., (2004) Eur Res J
Mudway IS et al., (2004) Arch Biochem Biophys
Pourarzar J et al., (2005) Am J Physiol
Behndig AF et al., (2006) Eur Res J
Sehlstedt M et al., (2010) Inhal Tox
Behndig AF et al. (2010) Thorax
Löndahl J et al., (2012) Part Fibre Toxicol
Muala A et al., (2014) Environ Health
Chamber studies:
Diesel
Neutrophils after air
Neutrophils after DE
NFkB
AhR
CYP1A1
Chamber studies:
Wood smoke
3 hour exposure
Bronchoscopy 24 hours post exposure
• Particle number concentration: 1-
2.5 × 105 part/cm3.
• The particle number size
distribution was bimodal with one
peak at 60-70 nm and one peak at
150-200 nm.
Exposure Conditions
Muala A et al. Part Fibre Toxicol. 2015 ;12:33
Chamber studies:
Wood smoke
The extra-cellular conundrum #1
The extra-cellular conundrum #2 Oxidant gases: ozone and nitrogen dioxide
Future Plans
• Samples to be provided from Umea
• Composition to be determined at FOI Sweden
and KCL
• Distribution of PM samples to interested groups
for parallel investigations
• Generation of pilot data
• Group meeting to review data and discuss joint
applications