Toxicology Centre
Untargeted strategy for identification of toxic
chemicals in OSPW
---- ROS activity and PPARγ agonistic activity in OSPW
Hui Peng, Jianxian Sun, Hattan A. AlHarbi, Steve Wiseman,
John P. Giesy
Nov 04, 2015
Toxicology Centre, University of Saskatchewan
Toxicology Centre
What is OSPW
 Oil Sands Process-Affected Water (OSPW) is produced during the surface
mining of oil sands in Alberta, The volume of OSPW is currently stored in
tailings is greater than 1 billion m3
PNAS, 2010, 951-952
Alberta Energy. Alberta Government. 2008.
http://www.energy .gov.ab.ca/OurBusiness/oilsands.asp
Toxicology Centre
OSPW: A Complex Mixture of Dissolved Organics
Three basic questions:
 What are chemical components?
 What is potential toxicity?
 What are causative chemicals?
Chemicals
• Ox +/• SOx +/• NOx +/-
Thousands of dissolved organic compounds
Toxicity
?






Acute toxicity;
Deformities;
Nuclear receptors;
Endocrine disruption;
Immune toxicity;
Oxidative stress
Toxicology Centre
Untargeted Strategy to Identify Causative Chemicals
Phenotype-based toxicity
(acute toxicity, ROS)
Unknown protein target
Effect-Directed Analysis (EDA)
Fractionation of
Active Fractions
Chemical
Analysis
Compare
Effects in
Bioassay
Identification of
Active Chemicals
Target-based toxicity
(Nuclear receptors…)
Known protein Target
Pull down system
Toxicology Centre
Case1: Oxidative stress (unknown protein target)
Oxidative stress is a general toxicity, which could be mediated by
multiple pathways, and no physically interacted protein could be
identified
Bioassay:
NRF2 Luciferase Reporter System
(High Throughput)
Untargeted Chemical Analysis:
HPLC Q-Exactive orbitrap
Toxicology Centre
1st dimension Fractionation
The highest oxidative stress response
was detected in F2 from HLB
cartridges
Toxicology Centre
Untargeted Mass Spec Analysis
positive
negative
Peaks
20000
Total peaks:
155892 in positive,
80830 in negative
15000
10000
5000
0
F1
ratio to max
1.5
F2
F3
F4
F5
 Greater than 10,000 peaks detected in 5
fractions
 Many peaks were specifically eluted in
F2, which may cause its greater potency.
 Potential causative chemicals were
narrowed in 1,000 chemicals from
10,000 compounds
F1
F2
F3
F4
F5
positive
1.0
negative
1.5
ratio to max
25000
0.5
F4
F1
F5
F2
F3
1.0
0.5
0.0
0.0
0
2000
4000
peak ID
6000
0
500
1000
1500
peak ID
2000
2500
Toxicology Centre
2nd dimension fractionation
60 HPLC fractions were
further conducted for
F2 from HLB cartridges
Toxicology Centre
2nd dimension fractionation
1.6
 EDA is useful to narrow down, but
difficult to exactly identify the
unknown causative chemicals
*
1.4
*
**
Fold Change
**
 Needs a lot of fractionation and
chemical analysis work.
1.2
*
* *
0.8
Ctrl
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
1.0
Our goal is to narrow down the list to <50, still working on…
Toxicology Centre
Case 2: PPARɣ Activation (known protein target)
 PPARs regulate intracellular lipid flux and adipocyte proliferation and
differentiation.
 PPARγ ligands might promote development of obesity.
 Activated by structurally diverse ligands
Toxicology Centre
PPARɣ Activation - Luciferase Reporter Gene Assay
Human PPAR-G
cell reporter system
PPAR response
80
60
rosiglitazone
40
20
0
0.1
1
10
100
1000
10000
Rosiglitazone (nM)
TE
Fractions
NAs
 Strong activity was
detected
 But NAs are not the
causative chemicals
Toxicology Centre
PPARγ mediated adipogenesis in 3T3-L1
The mouse embryonic fibroblast cell line 3T3-L1 is a favored model for
metabolism and obesity research, to confirm the downstream adipogenesis
effects of PPARγ ligands
Lipids accumulation and several PPARγ marker genes were up-regulated
Toxicology Centre
Ligand Identification: PPARɣ Pull-Down Assay
OSPW
Pull-down
Negative
control
Competitive
pull-down
His-PPARɣ
Putative ligands
Nonspecific binding
Rosiglitazone
Interfering compounds
Magnetic beads
intensity
 His-tag was used to make
the method more robust
 Competitive group is useful
to exclude non-specific
binding
mz
Toxicology Centre
Untargeted Mass Spec Analysis Using DIA Mode
…
Method 4
m/z 600-800
Retention time
m/z 200-400
Method 1
 Expand dynamic range
Retention time
…
Method 3
10 m/z precursor isolation window
m/z 800-1000
Full scan
 Collect MS2 information at the same
time.
 Use a computational program to
construct the MS2 library for thousands
of compounds
Retention time
Toxicology Centre
Computation Program for Automatic
Data Analysis and MS2 Library Construction
PEAK DETECTION
Read DIA raw files
Detect peaks
Recovery low
abundant peaks
Retention correction
DIAread
LIBRARY ESTABLISHMENT
LIBpeaks
Build library peaks
MS2idt
Identify product ions
PEAKdet
PEAKrec
PREscore
Calculate scores
and formulae
OUTlist
Final library output
RETcor
Toxicology Centre
Positive control: MTX-DHFR
30
Ratio
20
MTX
10
0
0
500
1000
Peak ID
1500
2000
H2N N NH2
N N
N
N
H O
N OH
O
O OH
 MTX-DHFR is a widely used model to study protein-drug interaction
 MTX was specifically identified
Toxicology Centre
Profile of Compounds from Different Groups
Rosiglitazone (ug/L)
120
*
90
60
30
R
is
-P
PA
H
B
la
nk
0
 Rosiglitazone was clearly detected
 Multiple peaks were detected in each of the sample
Toxicology Centre
Compounds Detected as PPARɣ Ligands
Negative ion mode
Positive ion mode
 Only the compounds exhibited the highest peak abundance in group 2,
were considered to be potential ligands
 20 compounds in negative ion mode and 42 compounds in positive ion mode
were detected as potential PPARɣ ligands
Toxicology Centre
Predict the formula and compounds database
𝑚𝑚𝑧𝑧𝑟𝑟𝑟𝑟𝑟𝑟𝑟𝑟 − 𝑚𝑚𝑧𝑧𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡𝑡
𝑀𝑀𝑀𝑀1 = exp{−0.5 ×
𝛿𝛿
𝑅𝑅𝑇𝑇𝑎𝑎𝑎𝑎𝑎𝑎. − 𝑅𝑅𝑇𝑇𝑙𝑙𝑙𝑙𝑙𝑙.
𝐻𝐻𝐻𝐻𝐻𝐻𝐻𝐻 = exp{−0.5 ×
𝛿𝛿𝑅𝑅𝑅𝑅
∑ 𝑤𝑤𝐴𝐴𝑎𝑎𝑎𝑎𝑎𝑎 𝑤𝑤𝐴𝐴𝑙𝑙𝑙𝑙𝑙𝑙 2
𝑀𝑀𝑀𝑀2 =
∑ 𝑤𝑤𝐴𝐴𝑎𝑎𝑎𝑎𝑎𝑎2 ∑ 𝑤𝑤𝐴𝐴𝑙𝑙𝑙𝑙𝑙𝑙2
𝐴𝐴
⁄
𝑤𝑤 = 1 ( 1 +
�
∑ 𝐴𝐴 − 0.5
2
2
�
�
𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝒚𝒚𝑯𝑯𝑯𝑯𝑯𝑯𝑯𝑯 + 𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝒚𝒚𝑴𝑴𝑴𝑴𝟏𝟏 + 𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝒚𝒚𝑴𝑴𝑴𝑴𝟐𝟐
𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺𝑺 =
𝟑𝟑
 Accurately predict compound formula by combining MS1, isotopic peaks, MS2
fragment, and homologue information, which will be finished soon…
Toxicology Centre
Conclusions
Pull-down strategy
(known protein target)
ADV:
Effect-Directed Analysis
(unknown protein target)
Useful to identify unknown
ligands
Quantitative mass balance analysis
Compatible to multiple ligands
Easy for operation
Expand dynamic range
DISADV:
Time-effective
Need tagged-protein
Difficulty to identify unknown ligands
No mass balance information
Complicated by multiple ligands
High noisy
Time-consuming
Toxicology Centre
Acknowledgements
Toxicology Centre
Thank you!
Toxicology Centre
Proposed ant- and agonistic PPARg activity of OSPW
Toxicology Centre
Antiadipogenesis effect was mediated by wnt
Toxicology Centre
His-tag pull down system
H
C
CH2
CH2
CH2
N
N
N
N
O
O
O
Imidazole
N
Ni
O
H
N
O
N
120
N
N
NH
N
His3
O
*
90
60
30
0
R
H
N
C
is
-P
PA
H
C
H
H
N
la
nk
C
B
H
C
HN
O
Rosiglitazone (ug/L)
O
His tag-system:
1. His tag is small
2. His large library
3. His-tag antibody
4. Using imidazole not methanol to elute protein
Toxicology Centre
Validation in 3T3-L1 Cell Line
The mouse embryonic fibroblast cell line 3T3-L1 is a favored model for
metabolism and obesity research, because the cells can be chemically
induced to differentiate into adipocytes.
Induce for 2 days
Exposure for 8 days
10 ug/ml insulin
1 uM DEX
0.5 mM MIX
10 ug/ml insulin
OSPW
Red Oil O staining of lipids
Toxicology Centre
Validation of Data Processing
NL: 1.16E6
100
60
Computation:
rt: 2.42 min
Intensity: 4.28E4
80
60
40
40
20
20
18.76
2
4
6
8 10 12 14 16 18 20 22 24
Time (min)
positive
25000
Total peaks:
155892 in positive,
80830 in negative
negative
20000
0 0
2
4
6
8
1.5
15000
10000
ratio to max
0 0
1.0
10 12 14 16 18 20 22 24
Time (min)
100%Hex
20%DCM
50%DCM
100%DCM
100%MeOH
0.5
5000
0.0
eO
H
LB
_M
0%
DC
M
M
10
_5
0%
DC
M
DC
0%
_2
00
%
He
x
0
_1
Peaks
NL: 4.28E4
2.03
Relative Abundance
Relative Abundance
Computation:
rt: 22.51 min
Intensity: 1.16E6
80
100
22.53
0
2000
4000
peak ID
6000
Toxicology Centre
Keap 1-NRF2
Under normal conditions, Nrf2 is constantly ubiquitinated through Keap1 and degraded in
the proteasome. Following Exposure to electrophiles or oxidative stress, Keap1 is inactivated.
Stabilized Nrf2 accumulates in the nucleus and activates many cytoprotective genes.
Yoichiro et al., 2012. Frontiers in Oncology
Toxicology Centre
Case 1: Oxidative Stress (no protein target)
Water Research, 2012, 6359-6368
Comparative Biochemistry and Physiology, 2013, 227-235
 Oxidative stress is the production and
accumulation of free radicals.
 Induction of oxidative stress in fathead minnow
by OSPW have been reported
 There are multiple pathways to induce ROS
with no certain protein targets.
Toxicology Centre
1st Dimension Fractionation
OSPW
HLB
HLB
100% Hex
Hex/DCM
(5:1)
Hex/DCM
(1:1)
100% DCM
100% MeOH
F1
F2
F3
F4
F5
Polarity
 Dissolved organic phase of was separated into 5 fractions based on
polarity by use of HLB columns.
 Total extract created by pooling of samples.
Toxicology Centre
in vivo:
Medaka larvae
Lipid Hydroperoxide (LPO)
3
**
Fold-change
Gene Expression
2
**
1
0
Ctrl
tBHQ
0.250.5
0.250.5
0.250.5
F1
F2
F5
 Oxidative stress related
genes were induced in
F2 group;
 F2 exposure significant
increased concentrations
of LPO
Toxicology Centre
Wnt-pathway
Toxicology Centre
PPARG-Wnt pathway
Toxicology Centre
Peak Detection and Match
NL: 1.16E6
Computation:
rt: 22.51 min
Intensity: 1.16E6
80
60
100
22.53
Relative Abundance
Relative Abundance
100
40
20
18.76
0 0
2
4
6
8 10 12 14 16 18 20 22 24
Time (min)
NL: 4.28E4
2.03
Computation:
rt: 2.42 min
Intensity: 4.28E4
80
60
40
20
0 0
2
4
6
8
10 12 14 16 18 20 22 24
Time (min)
Intensity cutoff: 1E4
positive
25000
negative
Peaks
20000
Total peaks:
155892 in positive,
80830 in negative
15000
10000
5000
0
F1
F2
F3
F4
F5
 Greater than 10,000 peaks detected in 5
fractions
 Rank order of peak abundance
 F1 > F3 > F4 > F2 > F5