Electronic Supplementary Material
Earthworm metabolomic responses after exposure to aged PCB contaminated soils
Melissa Whitfield Åslund†, Myrna J. Simpson†*, André J. Simpson†, Barbara A. Zeeb‡, and Allison Rutter§,
†
Department of Physical and Environmental Sciences, University of Toronto, 1265 Military Trail Toronto,
Ontario, Canada M1C 1A4
‡
Department of Chemistry and Chemical Engineering, Royal Military College of Canada, Kingston, Ontario,
Canada
§
School of Environmental Studies, Queen’s University, Kingston, Ontario, Canada
*Corresponding author, Phone: +1 416-287-7234, Fax: +1 416 287-7279, Email: myrna.simpson@utoronto.ca
S1. Analysis of soil PCB concentrations
PCBs present in soil samples were extracted and quantified using procedures adapted from EPA Methods
3540C and 8082A (EPA 1996; EPA 2007). Prior to analysis, approximately 10 g (wet weight) was sub-sampled
from each soil for the determination of percent dry weight (EPA 1996). A separate subsample (10 g wet weight)
was collected from each soil, accurately weighed, mixed with 10 g sodium sulfate (Na2SO4; min 99.5% purity,
Fisher Scientific), and spiked with decachlorobiphenyl (DCBP, min 99.2% purity, Sigma Aldrich) as a
surrogate standard. Soil samples were extracted in a soxhlet apparatus for 4 hours at 4-6 cycles per hour in 250
mL of dichloromethane (DCM, Pesticide grade, Fisher Scientific). Following extraction, sample extracts were
concentrated by rotoevaporation, the solvent exchanged for hexane, and then extracts were applied to a Florisil
column (1000 mg/ 6 mL, Fisher Scientific) for cleanup. Analysis of extracts for total Aroclors was then
performed using an Agilent 6890 Plus gas chromatograph equipped with a micro-63 Ni electron capture
detector (GC/μECD), a SPB™-1 fused silica capillary column (30 m, 0.25 mm ID x 0.25 μm film thickness) and
HPChem station software. The carrier gas was helium, at a flow rate of 1.6 mL·min-1. Nitrogen was used as the
makeup gas for the electron capture detector (ECD). Detection limits were 0.1 mg·kg-1. All values were
reported as mg·kg-1 dry weight. Total soil PCB concentrations were corrected for extraction efficiency using the
surrogate standard percent recovery and calculated on a dry weight basis by comparison to observed soil percent
dry weight (EPA 1996).
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For every nine samples extracted and subsequently processed, one analytical blank (Ottawa sand), one
control sample (a blank sample spiked with a known amount of either Aroclor 1254 or 1260), and one analytical
duplicate were also extracted and processed. None of the analytical blanks contained any PCBs at
concentrations above detection limits (0.1 μg·g-1) and all control samples were between 70 to 130% of the
expected value. Relative standard deviations between the samples and their analytical duplicate were below
30% for all results.
S2: Soil water holding capacity (WHC)
Water holding capacity (WHC) was determined after Parent (Parent and Caron 1993). Water was mixed
into approximately 10 g of soil until a slurry was formed and allowed to settle for one hour. The slurry was
added to a glass funnel lined with filter paper (Whatman, Grade 1) which was then covered with aluminum foil
and allowed to drain into a beaker for 24 hours. The mass of the soil at maximum water holding capacity (gwhc)
was recorded. Samples were then dried for 24 hours at 105°C and the mass of dry soil (gdry) also recorded. Soil
WHC was determined gravimetrically by dividing the mass of water in the soil at WHC by the mass of ovendry soil, i.e. WHC = (gwhc – gdry)/ gdry.
S3: Soil pH
To measure soil pH, 50 mL of deionized water was added to 10 g of air-dried soil (1:5 soil to water
ratio), shaken for 30 minutes on an orbital shaker and allowed to settle for one hour. The pH of the supernatant
was then measured using an Accumet basic AB15 pH meter (Fisher Scientific).
S4: Permutation testing
The significance of each PLS model was estimated through response permutation testing (Alam et al.
2010; Eriksson et al. 2006). In this method, the X table (the quotient normalized NMR spectra) remained fixed,
and the order of the Y vector was randomly permuted 400 times. Each time, a new PLS model was fitted and
Q2Y calculated, providing a reference distribution of the Q2Y statistic. Confidence in the validity of the PLS
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model is increased if the PLS models built using the permuted dataset consistently give lower Q2Y values than
the original model (Eriksson et al. 2006).
S5: Cross-validated predictions of y-variables and histograms of Q2Y values from 400-fold permutation
tests
Tables S1- S4 present the cross-validated predictions and permuted Q2Y values for the PLS models presented in
Tables 2a and 2b in the main text. For each PLS model, two figures are presented:
Cross-validated predictions: Average predictions of y-values ( ŷi ) given spectra i by the PLS model
derived during the leave one out cross-validation procedure with spectra i omitted for PLS models with
optimized number of components (See Tables 2a, 2b). The solid line indicates a linear regression between
the actual and predicted values. Error bars represent the standard error of the mean. In PLS models which
include the unspiked artificial control treatment, the mean predicted values for this treatment are indicated
with an unfilled marker (∆).
Histograms of permuted Q2Y values: Histogram of PLS regression Q2Y values for cross-validated PLS
models with optimized number of components (See Tables 2a, 2b) Distribution was constructed using 400
permutations of the Y table. The Q2Y observed in the optimized model using the unpermuted Y table is
also indicated.
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References
Alam TM, Alam MK, Neerathilingam M, Volk DE, Sarkar S, Shakeel Ansari GA, Luxon BA (2010) 1H NMR
metabonomic study of rat response to tri-phenyl phosphate and tri-butyl phosphate exposure. Metabolomics
6:386-394
Eriksson L, Johansson E, Kettaneh-Wold N, Trygg J, Wikström C, Wold S (2006) Multi- and Megavariate Data
Analysis Part I Basic Principles and Applications. Umetrics, Umeå , Sweden
Parent LE, Caron J (1993) Physical Properties of Organic Soils. In: Carter MR (ed) Soil sampling and methods
of analysis. Lewis Publishers, Boca Raton, Florida, pp 450-451
United States Environmental Protection Agency (EPA) (2007) Method 8082A Polychlorinated Biphenyls by
Gas Chromatography. In: Test Methods for Evaluating Solid Waste, Physical/Chemical Methods. National
Technical Information Service (NTIS), U.S. Department of Commerce, Springfield, VA
United States Environmental Protection Agency (EPA) (1996) Method 3540C Soxhlet Extraction. In: Test
Methods for Evaluating Solid Waste, Physical/Chemical Methods. National Technical Information Service
(NTIS), U.S. Department of Commerce, Springfield, VA
4
Table S1: Cross-validated predictions and permutation histograms for PLS models constructed using
earthworm metabolic data collected after two days of exposure, with the artificial soil treatment included
Artificial soil treatment Length of
Y-variable Cross-validated predictions Histograms of permuted Q2Y
included?
exposure
values
Yes
2 days
[PCB]
Predicted y-value
300
250
200
Observed
Q2Y
150
100
50
0
0
100
200
Actual y-value
300
Yes
2 days
pH
Predicted y-value
8.0
7.8
Observed
Q2Y
7.6
7.4
7.4
7.6
7.8
Actual y-value
8
Yes
2 days
Total soil C
Predicted y-value
5
4
Observed
Q2Y
3
2
2
3
4
Actual y-value
5
Yes
2 days
Inorganic C
Predicted y-value
4
Observed
Q2Y
3
2
1
0
0
1
2
3
Actual y-value
4
Yes
2 days
Organic C
Predicted y-value
4
3
2
Observed
Q2Y
1
0
0
5
1
2
3
Actual y-value
4
Table S2: Cross-validated predictions and permutation histograms for PLS models constructed using
earthworm metabolic data collected after 14 days of exposure, with the artificial soil treatment included
Artificial soil treatment Length of
Fig. 2 Histograms of permuted
Y-variable Fig. 1 Cross-validated
included?
exposure
Q2Y values
predictions
Yes
14 days
[PCB]
Predicted y-value
300
250
200
Observed
Q2Y
150
100
50
0
0
100
200
Actual y-value
300
Yes
14 days
pH
Predicted y-value
8.0
7.8
Observed
Q2Y
7.6
7.4
7.4
7.6
7.8
Actual y-value
8
Yes
14 days
Total soil C
Predicted y-value
5
4
Observed
Q2Y
3
2
2
3
4
Actual y-value
5
Yes
14 days
Inorganic C
Predicted y-value
4
3
Observed
Q2Y
2
1
0
0
1
2
3
Actual y-value
4
Yes
14 days
Organic C
Predicted y-value
4
3
Observed
Q2Y
2
1
0
0
6
1
2
3
Actual y-value
4
Table S3: Cross-validated predictions and permutation histograms for PLS models constructed using
earthworm metabolic data collected after two days of exposure, with the artificial soil treatment excluded
Artificial soil treatment Length of
Fig. 2 Histograms of permuted
Y-variable Fig. 1 Cross-validated
included?
exposure
Q2Y values
predictions
No
2 days
[PCB]
Predicted y-value
300
250
Observed
Q2Y
200
150
100
50
0
0
100
200
Actual y-value
300
No
2 days
pH
Predicted y-value
8.0
Observed
Q2Y
7.8
7.6
7.4
7.6
7.7
7.8
Actual y-value
7.9
No
2 days
Total soil C
Predicted y-value
5
4
Observed
Q2Y
3
2
2
3
4
Actual y-value
5
No
2 days
Inorganic C
Predicted y-value
4
3
Observed
Q2Y
2
1
0
0
1
2
3
Actual y-value
4
No
2 days
Organic C
Predicted y-value
2
Observed
Q2Y
1
0
0
7
1
Actual y-value
2
Table S4: Cross-validated predictions and permutation histograms for PLS models constructed using
earthworm metabolic data collected after 14 days of exposure, with the artificial soil treatment excluded
Artificial soil treatment Length of
Fig. 2 Histograms of permuted
Y-variable Fig. 1 Cross-validated
included?
exposure
Q2Y values
predictions
No
14
[PCB]
Predicted y-value
300
250
200
Observed
Q2Y
150
100
50
0
0
100
200
Actual y-value
300
8.0
14
pH
Predicted y-value
No
Observed
Q2Y
7.8
7.6
7.4
7.6
7.7
7.8
Actual y-value
7.9
No
14
Total soil C
Predicted y-value
5
4
Observed
Q2Y
3
2
2
3
4
Actual y-value
5
No
14
Inorganic C
Predicted y-value
4
3
Observed
Q2Y
2
1
0
0
1
2
3
Actual y-value
4
No
14
Organic C
Predicted y-value
2
Observed
Q2Y
1
0
0
8
1
Actual y-value
2
Figure S1:
Fig. S1 Sample 500 MHz 1H NMR spectrum of E. fetida tissue extract collected and processed using methods
described in the primary text.
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