Electronic Supplementary Material
Behavioural and physiological responses of birds to
environmentally relevant concentrations of an
antidepressant
Tom G. Bean, Alistair B. A. Boxall, Julie Lane, Stéphane Pietravalle, Katherine A.
Herborn and Kathryn E. Arnold
These supplementary materials contain extra information on the methods for drug prioritisation,
starling capture and husbandry, extraction of fluoxetine from the spiked invertebrate prey as a
quality control and extraction of fluoxetine from invertebrate samples taken from wastewater
treatment plants.
1)
Drug prioritisation
We conducted a desk based drug prioritisation study to identify priority pharmaceuticals for birds
foraging on Wastewater Treatment Plant (WWTP) trickling filters.
A) Background
The exposure of species to pharmaceuticals will differ according to their ecology and behaviour, for
example a hydrophobic pharmaceutical (e.g. the anti-obesity drug orlistat) is likely to sorb to sludge
and be removed during wastewater treatment and so is more likely to be ingested by birds feeding
on invertebrates from farmland spread with sludge than by birds feeding on river fish (1). Monitoring
data cannot be used in isolation to prioritise pharmaceuticals, because there is a relatively narrow
range of pharmaceuticals and matrices for which analytical detection methods are available (2). We
used the following framework to prioritise pharmaceuticals in the environment to which wild birds
foraging on trickling filter invertebrates are likely to be exposed.
Electronic Supplementary Material 1
Electronic Supplementary Material
B) Pharmaceutical Usage
Annual usage data for human pharmaceuticals can be obtained from Intercontinental Medical
Statistics (http://www.imshealth.com); however, the cost of obtaining this data is outside the
budget of many projects. Alternatively, prescription only usage can be reliably calculated from
certain national databases (e.g. the Prescription Cost Analysis for England (3, 4)). The amount of
each drug used is given in various units so the total annual mass of each drug used can be calculated.
Unfortunately, there do not seem to be equivalent databases for over the counter sales (OTC) or
veterinary medicines and those which are available appear to be unreliable or incomplete.
Prescription-only data will underestimate usage of pharmaceuticals that are also available OTC (e.g.
NSAIDs), thus OTC drugs are given special consideration in prioritisation calculations.
C) The Predicted Environmental Concentration (PEC)
For a human pharmaceutical excreted to wastewater, the Predicted environmental concentration
(PEC) is a function of the mass of a pharmaceutical used by a population over time and the
proportion of the drug excreted by patients unchanged in relation to how much the un-metabolised
drug is diluted in wastewater.
The PEC for a particular matrix can be obtained using Equation 1, assuming patient excretion is the
main source of pharmaceuticals in the environment (5).
Equation 1
PEC = A * WWTPRemoval
365*V*P*D
Where: A =
the mass of the pharmaceutical used by a population (mg yr-1)
WWTPRemoval =
the proportion removed by wastewater treatment processes
365 =
the number of days in a year
V=
the volume of wastewater per capita (L) per day
P=
the size of the population
D=
dilution factor in the environment (default of 10) (5)
We suggest that initially it may be safer to calculate PECs assuming a worst case scenario where
there is no metabolism because values quoted for the proportion excreted unchanged differ widely
between studies (e.g. for fluoxetine excretion rates range from ≤5% (6) to 30% (7). There is also the
Electronic Supplementary Material 2
Electronic Supplementary Material
added complication that some parent compounds can re-form in the environment but the extent to
which this occurs is poorly understood (8).
D) Bioconcentration/Bioaccumulation in Prey
Bioconcentration factors (BCF) and Bioaccumulation factors (BAF) for pharmaceuticals are reported
in the literature for a wide range of wildlife food types (e.g. invertebrates). Where these values are
not available, Quantitative structure–activity relationship (QSAR) models using software such as
EPIWIN (US Environment Protection Agency free software, downloaded from
http://www.epa.gov/oppt/exposure/pubs/episuitedl.htm ) can be used to estimate BCFs and BAFs
although the predicted values can often differ significantly from those obtained by uptake studies (9).
E) Predicted Wildlife Daily Dose
By multiplying the BCF or BAF by the PEC, the concentration in wildlife food can be estimated for any
pharmaceutical; the daily dose received by wildlife can be obtained by taking into account the mass
of the organism, the daily mass of prey eaten and the proportion of diet that comes from the
contaminated source. However, there is limited relevant information for most wild species on
foraging and behaviours that affect uptake from a contaminated source.
F) Using the Exposure Ratio to create an initial Prioritisation List
The predicted wildlife daily dose can be placed into context by calculating an exposure ratio
compared with the human defined daily dose. Exposure ratios for a range of drugs can be ranked
(highest to lowest) to provide an initial prioritisation list. Pharmaceuticals with an exposure ratio
greater than ≥0.07 (the approximate exposure ratio for diclofenac that was fatal to vultures (10)) be
selected for more detailed consideration.
G) Detailed Assessment of Physical, Chemical and Pharmacokinetic Properties
Next we conducted a literature review to assess the pharmacokinetic, physical and chemical
properties that affect uptake for the subset of pharmaceuticals highlighted by their exposure ratio.
The pharmaceuticals with the thirty highest risk characterisation ratios (Body weight corrected Bird
daily dose/ Body weight corrected human therapeutic dose) were selected for this detailed
assessment. We collected data on the proportion of the parent compound excreted unchanged and
whether the compound has conjugated metabolites (e.g. glucuronides or sulphates) as these
metabolites have potential to re-form the parent compound in the environment. We also collected a
Electronic Supplementary Material 3
Electronic Supplementary Material
measure of hydrophobicity (e.g. LogKow) and the BCF or BAF (see above). Ionisation (pKa) is relevant
too because uptake of highly ionised compounds at environmental pH (pH 7-8 for influent sewage,
personal measurement, unpublished data) for is likely to be lower than the BCF would suggest e.g.
see (11). A ‘qualitative filter’ of the data was made to identify which substances met the following
criteria so that the list could be refined:
1. Usage ≥ 10 tons year-1
2. Parent drug excretion ≥ 10%, or the range exceeds 10%
3. It has active metabolites’
4. Glucuronide or sulphate conjugates are excreted meaning there is the potential for the
parent compound reforming in the WWTP (12)
5. Meylan Log BCF (13) ≥ 2.7 which is equivalent to BCF >500 (which is the OSPAR DYNAMEC
definition of Bioaccumulative).
6. EPIWIN) prediction Log BCF ≥ 2.7 (US EPA EPIWIN software)
For pharmaceuticals meeting three or more of the above criteria, we did two additional checks.
1) We assessed how robust the source of the data was, favouring academic sources over web based
sources.
2) We looked up abiotic and bio-degradation rates
These final two stages minimised the chances that pharmaceuticals would be selected on the basis
of unreliable data and those that are readily degraded were excluded.
H) Priority pharmaceuticals for birds
The ten pharmaceuticals that were highlighted by the above qualitative assessment of the literature
included four antidepressants (fluoxetine, paroxetine, dosulepin and venlafaxine), two
antihistamines (cinnarizine and loratidine), two drugs used to treat hypertension (simvastatin and
verapamil), the antiobesity drug orlistat and the antiarrhythmic drug amiodarone. Antidepressants
had the greatest representation in our top ten and so we selected fluoxetine; which was the
antidepressant that met the largest number of the above criteria.
Electronic Supplementary Material 4
Electronic Supplementary Material
2)
Starling behaviour and physiology
A) Capture and Husbandry
Mist nets were put up about an hour and a half before dusk; all twenty-four birds were captured
over three nights. Each night, birds were removed from the net, placed in cloth bags and transported
for approximately one hour to a complex of Home Office Licensed outdoor aviaries. On the right leg
of each bird, a unique white numbered plastic leg ring (obtained from AC Hughes) and a green leg
ring, to which was attached a unique passive integrated transponder tag (PIT tag, 11.5 mm x 2.1 mm,
<0.1 g, Trovan Unique) was placed. On the left leg a unique combination of one or two coloured
rings was attached. This combination was also used to provide easy identification of treated birds.
The total mass of all leg rings was less than 1% of body weight.
Birds were placed into one of four outdoor aviaries referred to as Pen’s 4 (5 females), 5 (1 male and
5 females), 8 (6 males and 1 female) and 9 (5 males and 2 females). Three of the four pens were
mixed sex. In total there were twelve males (eight fluoxetine treated and four controls) and twelve
females (five fluoxetine treated and seven controls). Pens 8 and 9 and 4 and 5 were on opposite
sides of a central observation corridor and so were visually isolated.
All birds were left to acclimatise for four weeks from the day that the final birds were brought into
captivity (24th October 2011). For the first two weeks of the acclimatisation period, Avipro®, a
veterinary probiotic combination of bacteria, enzymes, electrolytes and vitamins, was added to the
water hopper to help combat any infections brought in from the wild. When the birds were on
Avipro® the water bath was only available for one hour a day otherwise they did not drink from the
water hopper.
The day before baseline and end behavioural trials, a 500µL blood sample was collected using a 25
gauge needle and 1 mL syringe. Blood was transferred to a lithium heparin microtainer (BD, UK),
centrifuged at 2000 g for 3 minutes. Plasma was removed and placed into an Eppendorf tube and
stored on ice prior. Samples were stored at -20°C for analysis (not presented here).
B) Treatment
Treatment was started one pen at a time, and staggered over four weeks i.e. once each pen had
completed the baseline individual and group behaviour trials, treatment began for that pen. A
stratified sampling structure was used to allocate birds to their respective treatment groups to
ensure that the age structure and sexes of treatment groups were as balanced as possible.
Electronic Supplementary Material 5
Electronic Supplementary Material
In a pilot study injecting dye, we found that although freezing the worms for a short period of time
prevented worms from wriggling during an injection, frozen worms leaked more than fresh so we
used fresh worms.
C) Capture of birds from their home pens and hand feeding to administer spiked worms
Oral uptake of the treatment was carried out by catching each bird from its home aviary using a
large padded hand net and feeding it just one worm per day. Dosing took place five days a week so
that birds received their weekly dose over five days. Once birds were in the hand net, each was
placed into an individual bird bag and stored in a cage measuring 55cm x 75 cm x 30 cm until all birds
in all four pens had been caught (Taking approximately 20 minutes). Each bird was fed one wax
worm containing their appropriate treatment by placing the worm at the back of the throat with a
pair of tweezers. Birds were given the chance to swallow before massaging the neck if necessary to
ensure the worm was swallowed. Birds were then released immediately back into their appropriate
home aviary.
3)
Wax worm QA/QC
In order to confirm that the fluoxetine injected waxworms contained the expected concentration of
fluoxetine, we carried out a QA/QC study.
A) Sample preparation
The extraction and solid Phase Extraction (SPE) method was adapted from that presented by Chu
and Metcalfe (14) as follows. Whole wax worms 0.15-0.3g were extracted with 2 mL of methanol.
Samples were homogenised for approximately 10-30 seconds using an (Turax) homogeniser.
Samples were then diluted with 4mL of 0.05 M HCl in water which was added in 2 steps, after each
of which the sample was homogenised for a further 10-30 seconds. After homogenisation each
sample was then vortex mixed briefly, sonicated for 10 minutes and then centrifuged for 10 minutes
(4500 × g, 20°C). For muscle samples, it was necessary to pass samples through a 5µm PTFE filter
prior to the SPE.
MCX cartridges (Oasis 3cc, 60mg) were conditioned with 1mL of methanol and then equilibrated
with 1 mL of water. A 2.4 mL aliquot was taken for each sample and placed in a glass vial, samples
were loaded to the cartridge and then vials were rinsed with 0.6mL methanol. Cartridges were then
washed with 1 mL methanol followed by 1 mL of dichloromethane. Cartridges were eluted with 2.8
mL of 95% methanol 5% ammonium hydroxide (made from a 35% ammonium hydroxide solution)
into a glass vial containing 100uL of ‘keeper solution’ (9:1 Methanol:ethylacelate). Glass tubes were
transferred to a turbovap set at 45°C and blown to dryness under a steady flow of nitrogen (typically
Electronic Supplementary Material 6
Electronic Supplementary Material
5-10 psi), the keeper solution prevents the sample from sticking to the glass. To reconstitute the
samples, 0.5 mL of methanol was added first. Samples were vortex mixed for a few seconds and
then a further 0.5 mL of deionised water was added to make samples up to 1 mL. Each sample was
then pipetted into a 1 mL plastic syringe and passed through a 0.2µm PTFE filter into a total recovery
vial.
B) HPLC analysis of wax worm extracts
Wax worm extracts were analysed by HPLC with fluorescence (230nm, 305nm). We used a gradient
mobile phase (1 mL min-1) which ran from 10-90% aqueous (0.1% H3PO4) with the remaining
percentage made up of HPLC methanol. All solvent used was HPLC fluorescence grade (Fisher,
Loughborough UK). We used a C-18 column (Kinetex 5µm C18 150x4.6mm, Phenomenex,
Macclesfield UK). Run time was 23 minutes per sample with the fluoxetine peak typically coming off
at 11.7-11.8 minutes.
C) Results
The mean concentration per wax worm was 1.58 µg/worm, N = 8, Percentage Relative Standard
Deviation (%RSD )= 13. The fluoxetine concentration and percentage recovery from wax worms is
also presented in the results section of the main paper
4)
Fluoxetine concentration in Earthworms from Wastewater
treatment plants
In order to confirm that the estimated concentration of fluoxetine in invertebrates living on WWTPs
was environmentally relevant, we analysed the concentrations of fluoxetine in earthwoms collected
from four WWTPs.
A) Sample collection
Earthworms, (Eisenia fetida) were collected from the top 10 cm of the trickling filter beds of four
wastewater trickling plants in Northern England in November 2013. Samples were stored in solvent
rinsed glass jars and placed on ice during transportation to the laboratory. In the laboratory, sludge
and biofilm were washed away using deionised water. Worms were stored at -20°C until extraction
and analysis.
B) Sample preparation
Samples were brought up to room temperature; chopped using a knife and board which had been
solvent rinsed and mixed to create an homogenous sample. Triplicate 0.3g samples were weighed
Electronic Supplementary Material 7
Electronic Supplementary Material
out into centrifuge tubes. Ten nanograms of fluoxetine internal standard (d-5) was spiked in and
samples were extracted with 5mL of 7:3 Acetonitrile:water following the method of Carter et al. (15).
C) Analysis using LC MS/MS
Samples were analysed using the Applied Biosystems/MDS Sciex API 3000 triple quadrupole in
positive ion mode for LC-MS/MS analyses. MRM transitions were Fluoxetine: 310.2>147.9, CV/CE=13
and Fluoxetine-d5: 315.2>153.2, CV/CE=13. For the Liquid Chromatography we used a Dionex
Acclaim® RSLC C18 Polar Advantage II column (2.2 µm 120A 2.1x100mm). A ramp gradient method
was used consisting of A: H2O 0.1% formic acid, B:Acetonitrile 0.1% formic acid was used at a flow
rate of 200 µL min-1with a total run time of 9 mins. The gradient was as follows 1 min 15% B, 1.5mins,
40% B, 5.5mins 45% B, 5.6mins 95% B, 7mins 95% B, 7.2mins 15% B, 9mins 15% B. Retention times
were 5.5mins for both analyte and internal standard.
D) Results
The percentage recovery of the extraction method was 111.3%. Mean (n=3) fluoxetine
concentrations and standard errors were WWTP site 1= 6.9 ng g-1 ±4.3, WWTP site 2= 35.5 ng g-1 ±3.4,
WWTP site 3= 26.9 ng g-1 ±9.6 and WWTP site 4=35.4 ng g-1 ±9.5.
E) Discussion
Our predicted daily dose of 0.92 µg day-1 was based on birds consuming 23.5 g day-1 of invertebrates
on a wet weight basis which have accumulated fluoxetine from the biofilm/sludge using a BCF of 133.
The BCF was experimentally defined by Carter et al. prior to this study (unpublished data, 2011).
More recently Carter et al. (15) have published work on a larger experiment which suggest the BCF is
in the range of 25.4-35.8. In terms of the accuracy of our predicted dose, the concentrations we
found in earthworms are at worst the same order of magnitude as our predicted dose and at best
within 0.09 µg day-1 of our dose assuming feeding rates are as we predicted.
Electronic Supplementary Material 8
Electronic Supplementary Material
Table S1: Effects of treatment and day on behaviour, CORT and mass measured pre-treatment
(baseline). Wald statistics from repeated measures GEE compared to a χ2 distribution with 1 degree
of freedom. The χ2 value along with P> χ are reported for each of the explanatory variables.
Endpoint
Treatment
χ2
P
Day
χ2
P
Interaction
χ2
P
Exploration
0.032
0.86
1.02
0.31
1.70
0.19
Activity
2.14
0.14
0.39
0.53
0.80
0.37
Boldness
0.57
0.45
3.39
0.066
1.60
0.21
Corticosterone
metabolites
Body Mass
1.11
0.29
3.37
0.067
0.80
0.37
2.20
0.14
78.13
<0.01
0.13
0.72
References
1.
Monteiro SC, Boxall ABA. Occurrence and Fate of Human Pharmaceuticals in the
Environment. Reviews of Environmental Contamination and Toxicology, Vol 202. 2010;202:53-154.
2.
Roos V, Gunnarsson L, Fick J, Larsson D, Ruden C. Prioritising pharmaceuticals for
environmental risk assessment: Towards adequate and feasible first-tier selection. Science of the
Total Environment. 2012;421:102-10.
3.
NHS. Prescription Cost Analysis England 2009 Prescription items dispensed in the community
in England and listed alphabetically within chemical entity by therapeutic class. 2010. Available from:
http://www.ic.nhs.uk/statistics-and-data-collections/primary-care/prescriptions/prescription-costanalysis-england--2009.
4.
Service NH. Prescription Cost Analysis England 2012. Health and Social Care Information
Centre; 2013.
5.
Williams RT. Human Health Pharmaceuticals in the Enivironment- an introduction. In:
Williams RT, editor. Human Pharmaceuticals: assessing the impacts an aquatic ecosystems.
Pensacola: Setac Press; 2005.
6.
Jjemba PK. Excretion and ecotoxicity of pharmaceutical and personal care products in the
environment. Ecotoxicology and Environmental Safety. 2006;63(1):113-30.
7.
Nentwig G. Effects of pharmaceuticals on aquatic invertebrates. Part II: The antidepressant
drug fluoxetine. Archives of Environmental Contamination and Toxicology. 2007;52(2):163-70.
8.
Domenech X, Ribera M, Peral J. Assessment of Pharmaceuticals Fate in a Model Environment.
Water Air and Soil Pollution. 2011;218(1-4):413-22.
9.
Qin H, Chen J, Wang Y, Wang B, Li X, Li F, et al. Development and assessment of quantitative
structure-activity relationship models for bioconcentration factors of organic pollutants. Chinese
Science Bulletin. 2009;54(4):628-34.
10.
Swan GE, Cuthbert R, Quevedo M, Green RE, Pain DJ, Bartels P, et al. Toxicity of diclofenac to
Gyps vultures. Biology Letters. 2006;2:279-82.
11.
Nakamura Y, Yamamoto H, Sekizawa J, Kondo T, Hirai N, Tatarazako N. The effects of pH on
fluoxetine in Japanese medaka (Oryzias latipes): Acute toxicity in fish larvae and bioaccumulation in
juvenile fish. Chemosphere. 2008;70(5):865-73.
12.
Andersen H, Grist H, Sorensen B, Ternes TA. Fate of estrogens in a municipal sewage
treatment plant. Environmental Science and Technology. 2003;37:4021-6.
Electronic Supplementary Material 9
Electronic Supplementary Material
13.
Meylan WM, Howard PH, Boethling RS, Aronson D, Printup H, Gouchie S. Improved method
for estimating bioconcentration/bioaccumulation factor from octanol/water partition coefficient.
Environmental Toxicology and Chemistry. 1999;18(4):664-72.
14.
Chu S, Metcalfe CD. Analysis of paroxetine, fluoxetine and norfluoxetine in fish tissues using
pressurized liquid extraction, mixed mode solid phase extraction cleanup and liquid
chromatography-tandem mass spectrometry. Journal of Chromatography A. 2007;1163(1-2):112-8.
15.
Carter LJ, Harris E, Williams M, Ryan JJ, Kookana RS, Boxall ABA. Fate and Uptake of
Pharmaceuticals in Soil-Plant Systems. Journal of Agricultural and Food Chemistry. 2014;62(4):816-25.
Electronic Supplementary Material 10