Toxic compounds in
saliva
Development and validation
of a microLC-QTOF
screening method
Master Thesis
Thijs Meijer
August 2015
University of Amsterdam
Chemistry – Analytical Sciences
MSc Chemistry
Analytical Sciences
Master Thesis
Toxic compounds in saliva
Development and validation of a
microLC-QTOF screening method
by
Thijs Meijer
August 2015
Supervisor:
Dr. W.Th. Kok
Daily Supervisor:
Drs. Ing. M.H. Blokland
ii
Abstract
Forensic veterinary toxicology is a growing field of interest. In The Netherlands only a veterinarian is
allowed to take blood samples. This is a problem, since veterinarians are not always available when an
acute intoxication takes place. Therefore, there is a need for toxicological analysis of alternative
matrices. Saliva can be an interesting and animal friendly alternative. It can be sampled relatively easy
without a veterinarian and it is a “mirror” of blood since it has comparable metabolism characteristics.
Acute intoxication of animals can take place by intake of all kinds of toxic compounds. Three main
compound groups were included in this study; pesticides, natural toxins and veterinary drugs. These
compounds can be toxic for animals due to accidentally intake during feeding or negligence of the owner
of the animal. They can also be administered on purpose like poisoning or overdosing.
The aim of this research project was to develop a multi-residue method for the analysis of
animal saliva using Liquid Chromatography – Mass Spectrometry (LC-MS). The development had to cover
the entire procedure; saliva sampling, samples pre-treatment, LC-MS analysis and data interpretation.
The method was validated according an in-house validation protocol based on official international
legislation. As model animal saliva, calf saliva has been used, because the availability of calf saliva for
this research was significantly higher compared to that of other animals.
A sampling method was developed with two types of sampling devices, one for small volume and
one for larger volume saliva sampling. The main reason for sample pre-treatment is to get rid of proteins
which are present in the saliva. To achieve this a protein precipitation method using acetonitrile was
developed and tested. A microLC-microfluidics-QTOF-MS method was developed for the identification of
the compounds in saliva. With the microLC-microfluidics technique a relatively high sensitivity can be
obtained using small sample injection volume and low flow rates. The microfluidics system consists of a
Waters IonKey system, which includes an analytical column in a chip device (iKey), using ESI as an
ionization technique. The IonKey source is placed in front of a QTOF MS. The acquisition method used is
a so called MSe method where a full scan and a fragmentation scan are acquired alternately. In this way
next to full scan data there is also fragmentation scan data available which can be used for more reliable
identification of the compounds.
A targeted library was developed using UNIFI, new MS software from Waters Corporation. The
library includes retention times, monoisotopic masses and if present fragment ions of the toxic
compounds which were included in the research project.
The developed method was validated according international legislation (2002/657/EC) to test
the characteristics of the method. For a screening method the limit of detection (CCß), selectivity and
ruggedness of the method and stability of the compounds and sample extracts needs to be validated.
The validation was performed on three days with 20 different blank saliva samples. The samples were
spikes at two levels, 0.1 and 1 mg/liter. These corresponds with the CCß levels of the validated
compounds. The validation results showed that with the method 203 compounds can be detected in
saliva with a CCß of 0.1 or 1 mg/l. The method was not selective for twelve compounds, interfering
peaks were found in the chromatograms. The method was rugged for two tested variations on the
sample pre-treatment and sample extracts were proven to be stable for one week in the freezer.
Within this research project a screening method for more than 200 toxic compounds was
successfully developed. The method consists of a sampling procedure, sample pre-treatment and
analyzing method using microLC-microfluidics-QTOF-MS. Additionally, the method was validated
according European legislation.
iii
Contents
Abstract .......................................................................................................................................... iii
Contents .......................................................................................................................................... iv
List of abbreviations ........................................................................................................................... v
1
Introduction .............................................................................................................................. 1
2
Background information .............................................................................................................. 4
3
2.1
Saliva ............................................................................................................................... 4
2.2
Transportation of toxic compounds in saliva ........................................................................... 5
2.3
Toxic compounds ................................................................................................................ 6
2.4
Liquid chromatography........................................................................................................ 6
2.5
Mass spectrometry ........................................................................................................... 10
2.6
Data handling .................................................................................................................. 11
2.7
Validation ........................................................................................................................ 12
Materials and Methods .............................................................................................................. 14
3.1
Materials ......................................................................................................................... 14
3.2
Methods .......................................................................................................................... 17
3.3 Validation .............................................................................................................................. 19
4
Results and discussion .............................................................................................................. 19
4.1
Sampling ......................................................................................................................... 21
4.2
Sample pre-treatment ....................................................................................................... 22
4.3
LC-MS analysis ................................................................................................................. 24
4.4
Validation ........................................................................................................................ 32
5
Conclusion .............................................................................................................................. 34
6
Recommendations and future perspectives .................................................................................. 35
7
References .............................................................................................................................. 36
Appendix I: Camera view of IonKey source interior .............................................................................. 37
Appendix II: TOF-MS calibration file ................................................................................................... 38
Appendix III: Compound list with RT and monoisotopic mass ................................................................ 39
Appendix III (continued): Compound list with RT and monoisotopic mass ............................................... 40
Appendix III (continued): Compound list with RT and monoisotopic mass ............................................... 41
Appendix IV: Processing method (partly) ............................................................................................ 42
Appendix V: Experimental scheme of validation day 3 .......................................................................... 43
Appendix VII: Validated compound with CCß values ............................................................................. 46
Appendix VII (continued): Validated compound with CCß values ............................................................ 50
Appendix VII (continued): Validated compound with CCß values ............................................................ 51
Appendix VII: Validated compound with CCß values ............................................................................. 46
Appendix VII (continued): Validated compound with CCß values ............................................................ 47
Appendix VII (continued): Validated compound with CCß values ............................................................ 48
Appendix VIII: Final sample pre-treatment method .............................................................................. 52
Appendix IX: Results of validation day 3 ............................................................................................. 53
iv
List of abbreviations
MeOH:
methanol
ACN:
acetonitrile
DMSO:
dimethyl sulfoxide
FA:
formic acid
LC:
liquid chromatography
MS:
mass spectrometry
TOF:
time of flight
UHPLC:
ultra high performance (pressure) liquid chromatography
IS:
internal standard
TIC:
total ion chromatogram
XIC:
extracted ion chromatogram
LOD:
limit of detection
LD50:
median lethal dose
GC:
gas chromatography
TLC:
thin layer chromatography
HPLC:
high pressure (performance) chromatography
SOP:
standard operating procedure
v
1
Introduction
Forensic veterinary toxicology is a growing field of interest. It is a discipline concerned with the study of
toxic substances or poisons in the veterinarian field. Reasons for this increased interest are growing
commercial interests of livestock and the way animal owners are committed to their animals nowadays
(1, 2). Chemical analyses of (biological) samples is an important aspect of veterinary toxicology for
which purpose blood or serum samples traditionally are the main matrices of investigation.
In The Netherlands only a veterinarian is allowed to take blood samples. This is a problem, since
veterinarians are not always available when an acute intoxication takes place. Therefore, there is a need
for toxicological analysis of alternative matrices. Matrices such as urine, hair, meat, organs, stomach
content and eyes are already used for the detection of forbidden or toxic substances (3) (see table 1).
However, all these matrices have disadvantages such as sampling time, contamination risk, the invasive
nature of the sampling procedure for the animal or an extensive sample pre-treatment procedure. Saliva
can be an interesting and animal friendly alternative to these matrices. It can be sampled relatively easy
without a veterinarian and it is a “mirror” of blood since it has comparable metabolism characteristics (4,
5). So, using saliva instead of blood makes it possible to undertake action in a more early state of the
intoxication, because no veterinarian is involved. It can be done relatively simple and sample pretreatment time can be relatively short.
Table 1: Matrices used for detection of toxic compounds.
Matrix
Collection procedure
Samples pre-treatment
Possible problems
Blood
Minimal
Small sample volume
Urine
Invasive; requires
veterinarian
Non-invasive
Extensive
Metabolism
Sweat
Non-invasive
Minimal
Small sample volume
Saliva
Non-invasive
Minimal
Hair
Non-invasive
Extensive
Small sample volume,
external contamination
External contamination
Acute intoxication can take place on purpose or by accident (1, 2, 6-9). For example, in the Netherlands
and some other countries in Europe intoxication of dogs is a well-known phenomenon (1). This can occur
accidentally by eating e.g. rodenticides or can occur deliberately by poisoning (10). Also whole groups of
animals can be intoxicated by the intake of feed which is contaminated with a toxic compound. This feed
is contaminated by plant toxins or mycotoxins present in the field or on the plants during harvesting of
the crops. An example of this is the intoxication of a flock of eight sheep by Pieris japonica in Belgium in
2005 (11). The sheep ate the leaves of the plant which were lying on the ground after trimming tasks in
a neighboring garden. The sheep showed marks of poisoning such as salivation and five of the eight
sheep died. Another recent example was the intoxication of a group of horses in The Netherlands (12).
Multiple horses got sick and one horse died. After analysis of the horses organs and the feed at the farm,
intoxication with colchicine was proven. Colchicine is a toxin which derives from the plant Colchicum
autumnale (autumn crocus, meadow saffron or naked lady). The toxin came into the feed of the horses
by mixing with the grass during harvesting.
1
Table 2 shows the number of reported cases of intoxication of animals from 2008 till 2013 in the
Netherlands. The majority of them are related to pets and then specific dogs and cats. As can be seen in
table 2, the total number of reported animal intoxications increased during the last years. This increase is
probably due to an increasing report rate by animal owners (9).
Table 2: Reported intoxications of animals in The Netherlands (9).
2008
2009
2010
2011
2012
2013
Dog
64%
63%
67%
68%
68%
70%
Cat
23%
20%
23%
23%
24%
24%
Horse
4%
2%
2%
1%
1%
1%
Rabbit
2%
2%
2%
2%
2%
2%
Cow
2%
7%
2%
3%
-
-
Sheep
1%
1%
1%
-
-
-
Goat
1%
1%
-
-
1%
-
Bird
1%
3%
1%
1%
1%
1%
Others
1%
1%
2%
2%
3%
2%
Total # of animals
2917
3928
3424
3879
4205
4479
The examples mentioned above were all cases where it took some time until the source of the
intoxication was discovered. The animals were already really sick or even died before appropriate action
was undertaken. A reason for this can be the need of assistance by a veterinarian to take blood samples
for investigation.
In human toxicology the use of saliva as a matrix for analytical investigations is already accepted for
many years (13, 14). Traditionally, saliva is mainly used for the analyses for illicit drugs such as cocaine
and amphetamine (15). Also hormonal research has been performed using saliva; for instance steroid
hormones (16). In the past decades a new type of analysis on the basis of saliva was introduced, namely
DNA analysis, which is used for identification purposes (17). Saliva therefore is a widely used matrix in
analytical human forensic toxicology.
The aim of this research project is to develop a multi-residue method for the analysis of animal saliva
using Liquid Chromatography – Mass Spectrometry (LC-MS). The development has to cover the entire
procedure, from saliva sampling on location, e.g. at the farm to MS data interpretation. The method has
to be able to deal with small amounts of sample material, because saliva sampling methods provide
relatively low volumes of sample material. Acute intoxications occur at concentrations in the order of the
median lethal dose (LD50). The LD50 is the dose of a compound where half the members of a tested
population die. The LD50 for the majority of toxic compounds is in the mg/l range. This means the limits
of Detection (LOD’s) of the compounds in the developed method don’t have to be in the μg/l (ppb)
range, but rather in the mg/l (ppm) range.
Compound classes of interest are plant toxins, mycotoxins, pesticides and veterinary drugs. Plant toxins
and mycotoxins can enter the body of an animal by direct consumption of the plant or fungus or, more
likely, by accidental mixing of toxic plants or fungi with other feed. Pesticides are the most likely
substances used for deliberate intoxication by mixing a pesticide with the animals feed or water.
Pesticide intoxication can also occur accidentally when animals eat for example rodenticides, which are
not stored in a correct way. Veterinary drugs can be a cause of intoxication when an overdose has been
2
administered. The goal for this this research project was to develop a method capable to analyze more
than 200 compounds of the classes mentioned before in samples of saliva in one LC-MS run. The method
will be validated according an in-house validation protocol based on official international legislation. To
our knowledge, no multi-class compound analytical toxicological screening method for veterinary saliva
has been developed so far. As model animal saliva, saliva of calves will be used, because the availability
of calf saliva for this research is significantly higher compared to that of other animals.
3
2
Background information
2.1
Saliva
Saliva is an important element in the digestion process of a lot of animals. Some species even use saliva
for nest building purposes (birds) and as a hunting tool where the saliva is venomous (vipers, cobras). In
mammals saliva has various functions (13). It works as a lubricant for the mouth and gullet to make sure
food passes easily. Furthermore, is helps moistening the food and creates a bolus which can be
swallowed more easily. Saliva contains the enzymes amylase and salivary lipase which can break down
respectively starch and fat in the food. Due to these enzymes the digestion already takes place in the
mouth of the animal. Saliva also acts as a buffer for the mouth area to protect for example teeth for
acidic conditions. Other functions where saliva plays a role are taste and microbial control. Figure 1
shows a scheme with the different functions of saliva in mammals.
Figure 1: Functions of saliva (from Lamy et al. (18)).
Saliva is produced in the salivary glands (13). Mammals have different glands in the mouth area where
they produce saliva (see figure 2). Therefore one can distinguish between gland specific saliva and whole
saliva. For certain purposes it can be useful to sample gland specific saliva when it is known that some
substances of interest are produced in a certain gland. However, most saliva purposes require whole
saliva. Whole saliva is a mixture of pure saliva from the salivary glands and other substances which occur
in the mouth area. These can be bronchial and nasal secretions, blood from oral wounds, bacteria,
viruses, fungi and food remains (19). The amount of saliva produced depends strongly on the animal.
Human salivary production is on average between 1 and 1.5 liter per day, for horses it is up to 40 liter
per day and for cows between 110 and 180 liter per day. Saliva production varies throughout the day
and depends on whether or not an animal is resting or eating and the nature of the diet (18). The high
rate of salivary production in cows can be explained by the fact that cows are ruminant animals. The pH
of saliva in mammals varies between 5.5 and 8.5, dependent of the species and moment of salivary
4
production. For example, the pH of saliva from a cow is around 8.2, because of high sodium bicarbonate
levels. The pH of saliva can be of high importance for the transportation of compounds between blood
and saliva, as is explained in more detail in chapter 2.2.
Figure 2: Schematic diagram of the salivary glands of four domestic mammals (from www.ucd.ie).
2.2
Transportation of toxic compounds in saliva
There are two ways in which toxic compounds can enter the saliva of an animal. The first one is direct
contamination of the saliva in the mouth area. This occurs when an animal is intoxicated orally, by eating
intoxicated products or when intoxicated products are administered. The second way of contamination is
by transport of compounds via the blood (5). Compounds enter the body orally or via intramuscular
administration, for example injection of a veterinary drug. After oral administration, uptake of the
compounds in the blood takes place in the digestion system. Primary organs where this uptake takes
place are liver, stomach and the intestinal canal. Via the blood, compounds can be transported to the
saliva. This transportation can occur in several ways and is dependent of the different chemical and
physiological properties of the toxic compound and the saliva (20). Lipid solubility, degree of ionization of
the compound in combination with the pH of the saliva and protein binding are the most important
properties.
Toxic compounds can enter the saliva via the lipid membrane by active or passive diffusion; active
diffusion via pores in a membrane or passive diffusion via a concentration gradient. The presence of the
5
majority of toxic compounds results from passive diffusion (21). To represent the concentration ratio
between saliva and plasma a so called S/P ratio is assigned. A ratio close to 1.0 means that the
concentration of the compound in saliva and plasma are almost the same. A low value of the S/P ratio
means the concentration in the plasma if higher than in the saliva, a high ratio means the concentration
in the saliva is higher than in plasma. When a compound has a low S/P ratio, the chance of detecting it in
saliva is not very high. Examples of toxic compounds with a relatively low S/P ratio are the pesticide
atrazine (S/P = 0.66)(22), digoxin (S/P = 0.53) and diazinon (S/P = 0.16) (21). With the low S/P ratio of
diazinon (0.16) there is still a significant concentration which can be found in saliva.
2.3
Toxic compounds
The compounds of interest in this study are compounds which have a toxicological effect on animals and
are available for intake by these animals. This intake can either be by the animal itself (eating, foraging)
or by administration due to human interference. Component groups of interest are pesticides, natural
toxins and veterinary drugs. Pesticides are used worldwide and on large scale to prevent vermin and
diseases in for example crops. Intake of pesticides by animals can be accidentally or on purpose. Animal
feed can be intoxicated with pesticides, animals may have access to pesticides which are not stored in a
correct way or used for other purposes such as mouse or rat poisoning. Additionally, animals can be
deliberately poisoned with pesticides in a conflict situating between persons (23). A well-known group of
toxic compounds in the animal toxicology are the natural toxins. These are toxins which are produced by
plants, fungi or animals. Some of these toxins are extremely toxic and are even used in the human crime
world for poisoning purposes. Incidents with animals occur when they eat these toxic plants or when
these plants or fungi are mixed in the animal feed. A third group of toxic compounds which are included
in this research work are veterinary drugs. Veterinary drugs can be dangerous for animals when they are
over dosed or when animals are extremely sensitive for the drug. Mostly intoxication by drugs is due to
accidental intake. Table 3 shows the toxic compound classes which caused intoxications of animals in The
Netherlands from 2008 till 2013 (9).
Table 3: Toxic compound classes which caused intoxications of animals in The Netherlands (9).
2008
2009
2010
2011
2012
2013
Pesticides
24%
19%
21%
20%
21%
18%
Human drugs
20%
19%
21%
22%
22%
23%
Plant, fungi and animal
toxins
Household chemicals
19%
14%
18%
20%
20%
21%
12%
11%
10%
14%
12%
11%
Food and drinks
7%
8%
10%
9%
10%
12%
Industrial products
4%
10%
3%
2%
3%
3%
Vet drugs
3%
5%
4%
5%
5%
5%
Others
11%
14%
13%
8%
7%
7%
2.4
Liquid chromatography
Chromatography is a technique which can separate different compounds in gas or liquid phase from each
other.
Gas
phase
chromatography
is
called
gas
chromatography
(GC),
where
liquid
phase
chromatography is called liquid chromatography (LC). Different types of GC and LC have been
developed, from simple techniques such as thin layer chromatography (TLC) to highly advanced
6
techniques such as ultra high performance liquid chromatography (UHPLC)(24). All chromatographic
techniques work with the same basic principle of separating compounds due to differences in molecular
characteristics in the mobile phase and the stationary phase in a chromatographic system. This
stationary phase can be for example paper, C18 particles or a coated capillary. The separation
characteristics can be for example molecular size, polarity or the ionization status of the molecule.
In this research a variant of high pressure (performance) liquid chromatography (HPLC) has been used.
HPLC is a separation techniques were compounds are separated on a column packed with stationary
phase particles. The sample is injected in the flow of a liquid (mobile phase) which is pumped under high
pressure through an analytical column. Due to the difference in affinity of the compound with the
stationary and the mobile phase, the compound will stay on the column or will be transported through
the column by the mobile phase. Because different compounds interact with the stationary and mobile
phases differently, a compound can be separated from matrix compounds or from other compounds of
interest. To achieve optimal separation different stationary phases and mobile phases can be used. The
mobile phase can be used in an isocratic or gradient flow. When using isocratic flow, one eluent is used
by using a single pump. This eluent can consist of multiple fluids in a fixed composition, e.g. 60% water
and 40% methanol. With a gradient flow a binary pump is used, so different eluents can be mixed to
create a variable eluent composition in time. Advantage of a gradient flow is that analysis time is
reduced and samples which cannot be separated with an isocratic flow can be separated better due to
the increase in eluent strength by changing the eluent composition. For example a gradient flow can start
with an eluent composition of 90% water and 10% methanol and can change to 100% B in for example
10 minutes time.
To achieve better separation (higher resolving power and peak capacity) smaller stationary phase
particle are needed (25). This can be explained using the Van Deemter curve, which shows the
correlation between the resolving power (Height Equivalent Theoretical Plate, HETP) of the column and
the mobile phase flow rate (26). The better the resolving power, the lower the value for HETP and at the
minimal HETP the flow rate is optimal. In UHPLC, using smaller particle sizes compared to HPLC, the part
of the curve on the right of the minimum is much lower (see figure 3). This means that higher mobile
phase flow rates can be used while retaining optimal resolving power. To achieve these higher flow rates
the LC systems need to be able to provide high pressures.
Figure 1: Van Deemter curves describing the dependence of the plate height (H) on the linear
velocity of the mobile phase (u) for stationary phases with different particle sizes (26).
7
Because sample volume, in combination with sensitivity, is important in this research project a
microUPCL has been used. With microUPLC the inner volumes of the LC tubing are smaller than with
conventional UPLC, so, to achieve the same amount of sensitivity, less sample volume is needed or with
the same sample volume a significant gain in sensitivity can be achieved. The gain in sensitivity resulting
from the use of a microUPLC column compared with a conventional UPLC column is shown by the
following relation:
Formula 1
where f is the gain in sensitivity, d1 and d2 are the diameters of the conventional UPLC and microUPLC
columns, respectively (27). This means in theory that reducing the column internal diameter form 2.1
mm to 150 μm, should result in an almost 200-fold gain in sensitivity. Also the flow rate is much lower
(1-5 μl/min), so a significant reduction of mobile phase can be achieved, which reduces costs and is
ecologically sustainable. A disadvantage of nano- and microUHPLC systems is the complexity of use.
Combining tubing or capillaries and nano- or micro columns to each other in the right way can be very
time consuming. Furthermore, because the flow rate is very low it is difficult to detect possible leakages.
Therefore, manufacturers try to come up with inventive techniques to avoid these problems. One of
these inventions is the chip based LC column system. In these systems the analytical column is build
inside a chip, so no manual connections have to be made. The system which has been used for this
research project uses the IonKey technology from Waters Corporation. The research was performed with
a test-version of the system, because RIKILT and Waters Corporation have an agreement for testing this
new technology (28).
By integrating a microLC column in a chip which can be slided into the source of the mass spectrometer,
leakages by connections are minimized. IonKey is a chip based microUPLC technique, which uses a so
called tile or iKey which has to be placed into a special designed electro spray ionization source (see
figure 4).
8
Figure 2: IonKey technology with the iKey inside the IonKey source.
The iKey consists of an inlet (from microLC pump or syringe pump) connected to the packed column or a
capillary. An iKey with a capillary can be used for infusion experiments, for example the calibration of the
mass spectrometer. The column can be packed with different stationary phase materials, all C18 based.
BEH (Ethylene Bridged Hybrid), CSH (Charged Surface Hybrid) and HSS (High Strength Silica), stationary
phases are available that can be used for different types of compounds depending on the application. At
the end of the column there is an electro spray ionization emitter. Because of the design of the iKey only
positive ionization mode is possible yet. Figure 5 shows a schematic overview of the iKey. The
electrospray ionization emitter works similar as a traditional electrospray ionization source.
Figure 3: iKey schematic view with the different inlets, the actual analytical chromatographic
column and the electrospray emitter (from www.waters.com).
When optimizing the working of the IonKey some parameters can be varied. These are the position of
the iKey, the capillary voltage, the capillary gas flow and the capillary temperature. The position of the
iKey can be altered in the x, y and z direction. Because of the low eluent flow it is important to accurately
9
set the position of the iKey. For this purpose a camera is installed on the source. With this camera
images of the sample flow and lock mass flow can be viewed, so the position of the iKey towards the
entrance of the mass spectrometer can be optimized. The capillary voltage, capillary gas flow and
temperature are important for an optimal evaporation and ionization of the sample flow. The settings for
these parameters are dependent on the sample flow. Generally the higher the flow, the higher the values
have to be. Appendix I shows a picture of a camera shot at the inside of the IonKey source.
2.5
Mass spectrometry
For screening purposes Time of Flight (TOF) mass spectrometry is an often used technique. A screening
method is a method where samples after analysis can be categorized as compliant (negative) or
potentially non-compliant (suspected). When a sample is compliant no compounds of interest are found
and the sample can be regarded as negative. When the sample is non-compliant one or more compounds
are detected in the sample. For screening methods this means the sample is suspected and an additional
confirmation analysis has to be performed to confirm the identity of the compound. Time of Flight mass
spectrometry is used to measure compound masses with a higher accuracy compared with for example
triple quadrupole mass spectrometers. Not the mass of an ion is measured, but the ratio between the
mass and charge of the ion (m/z). When the charge of the ion is singular, the exact mass is measured.
When for example the charge of the ion is double, half the exact mass of the ion plus two protons is
measured. As the name already implicates, TOF uses the time an ion needs to travel a certain distance
through a flight tube to separate ions with different masses form each other (29). This TOF tube can
consist of one single tube or one or more so called reflectors. These reflectors ‘reflect’ the ions back into
the tube and in this way doubles or quadruples the path length and also corrects for thermal energy
differences in ions with the same mass to charge ratio (see figure 6). Due to the longer flight path the
accuracy and resolution will improve. For detection in a TOF instrument mainly a microchannel plate
detector or a secondary emission multiplier (SEM) is used. With TOF only full scan spectra can be
acquired, so no precursor selection and no fragmentation data can be obtained. When using a QTOF
system precursor selection and fragmentation is possible. A QTOF is a hybrid system where a quadrupole
is placed before the TOF tube (see figure 6). This quadrupole can be used for pre-cursor selection, so
specific ions can be selected and transferred to the TOF tube. Behind the quadrupole a fragmentation cell
is placed, so the selected pre-cursors can be fragmented and these fragments can be transferred to the
TOF tube. In this research measurements were done with a Waters Xevo QTOF. This instrument has a
method option called MSe, where alternating full scan and fragmentation scan spectra are acquired.
These spectra can be linked to each other based on scan time, so for every time point in the
chromatogram there will be a full scan spectrum and a fragmentation scan spectrum. This fragmentation
scan is an all ion fragmentation scan, so all ions which are passing the collision cell are fragmented. This
fragmentation is performed using a stepped collision energy, which means that during every
fragmentation scan different collision energies are applied on the ions. In this way ions which fragment
with lower energy as well as ions which fragment with higher energy will be fragmented.
The instrument has a Lock Mass correction device. This is an external syringe pump which introduces a
lock mass solution via a separate capillary into the ESI source. Via a baffle, a plate which switches
between sample and lock spray, every twenty seconds (or another interval which can be chosen by the
operator) the lock spray will be introduced. This lock spray solution consists of a compound with known
mass or masses. These masses are detected and the deviation between the exact mass and the
10
measured mass is calculated. Directly during the analysis or during data processing all the other
measured masses are corrected with this calculated deviation. In this way the instrument corrects for
small deviations in measured mass which is caused by for example temperature changes in the
environment. The capillary and baffle of the lock spray device can be seen in Appendix I.
Figure 4: Schematic view of a QTOF MS with from left to right the ionization source, quadrupole,
collision cell and a W mode reflectron TOF tube (from giga.ulg.ac.be).
The TOF MS has to be calibrated on a regular base, depending the standard practice of the company or
user. This calibration has to be performed to make sure the instrument is capable of performing
according to the specifications of the instrument or the company. A calibration solution is introduced into
the MS by infusion with an internal or external pump. This solution contains compounds with known
exact masses, which are present in a calibration table. The measured exact masses are compared with
the known exact masses and the deviation is calculated. This deviation has to fall within a pre-defined
criterion, for example < 2 mDa. When for all tested masses this criterion has been achieved the
calibration can be accepted and the TOF MS is calibrated and can be used for analysis.
2.6
Data handling
Mass spectrometry data is acquired using Waters Masslynx software. Further data processing was
performed using UNIFI. UNIFI is a new software package of Waters which is still in the development
phase. Masslynx has already an option to correct the measured mass with the help of the lock mass
when analyzing. When selecting this option the data has already been corrected before processing with
UNIFI. In UNIFI a targeted library has been build including exact masses and retention times of all
compounds included in the standard mixture. If known also common fragment masses of the compounds
are included in the method. The retention times were determined by injection of standard solutions
containing all compounds. When multiple peaks were present in the chromatogram, the MSe function of
the acquisition method was used to identify the correct peak using the product ions of the compound.
The retention time window used in the processing methods was 0.1 minute, which means the software
only looks at peaks 3 seconds before and 3 seconds after the entered retention time. Mass accuracy was
11
set at 25 mDa. This means the software only looks at masses which are in between 25 mDa of the
entered exact mass. Different adducts can be included in the method, for this study H+ and NH4+
adducts were included.
2.7
Validation
To test the performance of the developed method, the method has to be validated. This means that
different performance characteristics have to be determined. Validation of analytical methods has to be
performed according to national and international legislation. For different research fields, different
official validation documents were published. Since this research was performed within the RIKILT
Business unit Veterinary Drug Research, the validation was performed using EU Commission
Decision2002/657/CE (30). This document describes which characteristics should be determined for the
validation of an analytical method in the veterinary drug residue research field. The document
distinguishes between confirmatory and screening methods and between qualitative and quantitative
methods. Figure 7 shows the performance characteristics which should be determined when validating
one of the methods mentioned above.
Figure 5: Classification of analytical methods by the performance characteristics that have to be
determined according Commission Decision2002/657/CE (30).
Before starting the validation it has to be determined in which way the method has to be validated. The
method which has to be validated in this research project is a qualitative screening method. So according
to
the
table
the
following
characteristics
have
to
be
determined:
Detection
limit
(CCß),
selectivity/specificity and applicability/ruggedness/stability. These characteristics will be explained below.
Detection limit (CCß): The detection limit is the limit where with a certain certainty (ß) can be stated that
the found value is non-compliant (30). In this validation ß correspond with a certainty of 95%. This
means that a found concentration above this CCß limit can be stated as a suspect sample (31).
Selectivity/specificity: Selectivity or specificity says something about the statement how certain one is
that the compound found really is that compound. So the more certain one is that the compound found is
12
really that compound the more specific or selective the method is. LC-MS already is a selective
technique, because it measures retention times in combination with exact masses, which are specific for
a certain compound. To verify the selectivity blank saliva samples with and without addition of the
compounds will be analyzed. When no compounds are identified at the specific RT and mass of these
compounds in the saliva samples the method is selective for these compounds.
Ruggedness: The ruggedness (robustness) of the method says something about the capability of the
method to deal with certain changes in the method. To test this certain steps in the method which could
be critical are tested. When the results (number of identified peaks) of the ruggedness samples are
comparable with those of the control samples the method is robust for this step in the method.
Stability: The stability refers to the stability of the measured compounds in standard solutions and/or
final extracts. The stability of standard solutions is tested by comparing standards which have been
stored for a certain time in the refrigerator or freezer with standard which have been stored at -80°C.
The -80°C samples are assumed to be stable. After a certain storage time the standards are analyzed
and the results are compared. When the results are comparable (e.g. < 10% deviation in the measured
peak area) the compound is considered to be stable for the storage time and condition. Stability of
extracts is determined by storing sample extracts for a certain time (e.g. one week) in the refrigerator or
freezer before re-analyzing and compare the results with the original analysis. When the results are
comparable the extract are considered to be stable for the storage time and condition.
The way the above mentioned validation characteristics were determined is described in an in-house
validation plan. This plan is approved by the quality assurance officer before the validation can take
place.
13
3
Materials and Methods
In this chapter the materials used, chemicals and apparatus will be explained. The methods which have
been used for sample collection and sample pre-treatment are explained. Also the animals which have
been used for the collection of the saliva samples will be mentioned in this chapter.
3.1
Materials
Animals:
The saliva samples were collected from calves. For the preliminary sampling tests calves were used from
the dairy farm of Mts Meijer-Pelgrum in Lettele, The Netherlands, were samples were taken from calves
in the age of 4 weeks till 3 months. For the validation study samples were taken from the same farm
from calves in the ages of 2 till 3 months. These calves were fed milk, hay and maize during the day and
were able to drink water whole day. For the sampling tests and the validation study calves were samples
at Zodiac Carus. This is an animal research facility of Wageningen University and Research centre. The
animals were 2-4 months old and were fed hay and maize during the day and able to drink water whole
day. All animals were kept in spacious sheds, according the Dutch law on animal housing
(activiteitenbesluit en activiteitenregeling, Dutch Ministry of Infrastructure and Environment).
Chemicals:
Acetonitrile, methanol, formic acid and water were al ULC grade and were purchased from Actu-All
Chemicals (Oss, The Netherlands). DMSO, Sodium hydroxide and 2-propanol were purchased from
Sigma-Aldrich (Saint Louis, MO, USA).
Reagents:
Mobile
phase
A
(Water/Acetonitrile/Formic
acid
(99
/
1
/
0.1)
(V/V/V)),
Mobile
phase
B
(Acetonitrile/Water/Formic acid (99 / 1 / 0.1) (V/V/V)), Water / 2-propanol ((1 / 1) V/V)),
Leucine/Enkypheline (2000 μg/l), MS Leucine/Enkypheline Kit (Waters, 700002456)
Standard solution:
All standard solutions were made according in-house standard operating procedures. Standard mixtures
of the different compound groups were made in concentrations of 50 mg/liter. Table 5, 6 and 7 show the
compounds present in the standard mixtures. The three mixtures are combined in two Tox mixtures,
Total Tox mix 10 mg/l and Total Tox mix 1 mg/l. These two mixtures are being used for the additions in
the validation study. Furthermore there is an internal standard mixture where clenbuterol-d6 and
C-
13
caffeine (Caffeine-(3-methyl-13C)) are present in a concentration of 10 mg/l

Veterinary drug mixture 50 mg/l

Natural toxin mixture 50 mg/l

Pesticide mixture 50 mg/l

Total Tox mix 10 mg/l
14

Total Tox mix 1 mg/l

Internal standard mix 10 mg/l
Table 5: Toxins.
Component
Component
Component
Component
Abrine
Digitoxigenin
Lupanine
Rottlerin
Aconitine
Digitoxin
Lupinine
Santonin
Aflatoxin B1
Digoxin
Lycopsamine
Scopolamine
Aflatoxin B2
Echimidine
Monocrotaline
Senecionine
Aflatoxin G1
Emetine
Morphine
Senecionine-N-oxide
Aflatoxin G2
Ephedrine
Narceine
Seneciphylline
Ajmalicine
Erucifoline
Noscapine
Seneciphylline-N-oxide
Anisatine
Erucifoline-N-oxide
Ochratoxin A
Senkirkine
Aristolochia acid I
Genistein
Solanine alpha
Aristolochia acid II
Atropine
Geranyloxypsoralen 5(Bergamottin)
Grayanotoxin III
Ouabain (Strophanthin
G-)
Papaverine
Podophyllotoxin
Strychnine
13C-Caffeine
Heliotrine
Pulegone
Teucrin-A
Colchicine
Imperatorin
Rescinnamine
Convallatoxin
Jacobine
Reserpine
Tetrahydrocannabinol
(THC)
Tropine
Coumarin
Jacobine-N-oxide
Retorsine
Tubocurarine
Cucurbitacin I
Kavain
Retorsine-N-oxide
Umbelliferone
Cytisine
Lobeline
Ricinine
Vincamine
Component
Component
Component
Component
13C-Caffeine
diflubenzuron
isoproturon
propyzamide
2,4-D
diflufenican
isopyrazam
prosulfocarb
Abamectin
dimethenamid
Isoxaben
pymetrozine
Acephate
Dimethoate
isoxaflutole
pyraclostrobin
Acequinocyl
dimethomorph
kresoxim-methyl
pyridaben
Acetamiprid
dinoterb
Lenacil
pyridate
Aclonifen
Diuron
linuron
pyrimethanil
Aldicarb
DNOC
lufenuron
pyriproxyfen
ametoctradin
dodemorph
Malathion
pyroxsulfam
Amisulbrom
dodine
mandipropamid
quinmerac
Asulam
emamectin
MCPA
quinoclamine
Azadirachtin
epoxiconazole
MCPP
Quinoxyfen
azamethiphos
Ethirimol
mepanipyrim
quizalofop-ethyl
azoxystrobin
ethoprophos
mesosulfuron-methyl
rimsulfuron
Bendiocarb
etoxazole
mesotrione
silthiofam
Bentazone
famoxadone
metalaxyl
Simazine
Bifenazate
fenamidone
metamitron
spinosyn-A
Bifenthrin
Fenamiphos
metazachlor
spinosyn-D
Bixafen
fenhexamid
metconazole
spirodiclofen
Boscalid
fenoxaprop-ethyl
Methabenzthiazuron
spiromesifen
brodifacoum
fenoxycarb
Methamidophos
spirotetramat
Sparteine
Table 6: Pesticides.
15
bromadiolone
fenpropidin
methiocarb
Spiroxamine
Bromoxynil
Fenpropimorph
Methomyl
sulcotrione
Bupirimate
fipronil
methoxyfenozide
tebuconazole
Buprofezin
flonicamid
metolachlor
tebufenpyrad
Carbaryl
florasulam
Metoxuron
teflubenzuron
carbendazim
Fluazifop
metrafenone
tembotrione
carbetamide
fluazinam
metribuzin
tepraloxydim
Carbofuran
Flucycloxuron
metsulfuron-methyl
terbuthylazine
carfentrazone-ethyl
fludioxonil
Mevinphos
Terbutryn
Chlorantraniliprole
Flufenacet
Myclobutanil
Tetraconazole
Chlorbromuron
flufenoxuron
nicosulfuron
thiabendazole
Chloridazon
fluopicolide
Omethoate
thiacloprid
clodinafop-propargyl
fluoxastrobin
oxamyl
thiamethoxam
clofentezine
fluroxypyr
Oxydemeton-methyl
thiophanate-methyl
Clomazone
flutolanil
paclobutrazol
Tolylfluanid
Clopyralid
foramsulfuron
penconazole
topramezone
Clothianidin
fosthiazate
pencycuron
tri-allate
Cyazofamid
Haloxyfop
Phenmedipham
tribenuron-methyl
Cybutryne
Haloxyfop-p-methyl
picoxystrobin
triclopyr
Cymoxanil
hexythiazox
pinoxaden
trifloxystrobin
cyproconazole
imazalil
pirimicarb
triflumizole
Cyprodinil
imidacloprid
pirimiphos-methyl
Triflumuron
Cythioate
indoxacarb
prochloraz
triflusulfuron-methyl
desmedipham
iodosulfuron-methyl
Profenofos
Triforine
dichlofluanid
ioxynil
propamocarb
trinexapac-ethyl
difenoconazole
Iprovalicarb
propiconazole
tritosulfuron
Table 7: Veterinary drugs.
Component
Component
Component
Component
Chlortetracycline
Abamectine
Clencyclohexerol
Salmeterol
Demecloxycline
Doramectine
Clenpenterol
Terbutaline
Doxycycline
Emanmectine
Clenproperol
Tulobuterol
Oxytetracycline
Eprinomectine
Fenoterol
Zilpaterol
Tetracycline
Ivermectine
Isoxsuprine
Clenhexyl
Lasalocid
Moxidectine
Mabuterol
Ritodrine
Maduramycine
Broombuterol
Mapenterol
Metaproterenol
Monensin
Carbuterol
Procaterol
Hydroxymethylclenbuterol
Narasin
Cimaterol
Ractopamine
Bromchlorbuterol
Salinomycine
Cimbuterol
Reproterol
Semduramycine
Clenbuterol
Salbutamol
Apparatus:
Standard laboratory equipment was used for sample preparation and analysis. These consist of: Saliva
sampling devices (animal cotton rope, Salimetrics)(Swab, Henry Schein), Centrifugal tubes for saliva
sampling device (custom made), Centrifugal tubes for saliva sampling device (Salimetrics), Tubes 50 ml
(Greiner), Nitrile gloves (Medica), Tubes 1.5 ml (Eppendorf), Tube 12 ml with screw cap (Greiner), Vial
16
with screw cap, total recovery (Grace), Glass flasks, 250 ml (Scott), Pipettes of different types and
volumes, each calibrated according RIKILT SOP, Centrifuge (Eppendorf), Vortex (IKA).
LC-MS system consisting of: NanoAcquity UPLC (Waters Corporation), IonKey MS source (Waters
Corporation), iKey BEH C18 Separation Device, 130Å, 1.7μm, 150 μm x 50mm (Waters Corporation),
Xevo QTOF Mass spectrometer (Waters Corporation). Settings of the different systems can be found in
table 8 and 9.
Table 8: LC and IonKey settings.
Flow
3 μl/min
Gradient
See table 12
Injection volume
2 μl
Capillary Voltage
3.5 kV
Nanoflow gas
0.5 bar
iKey temperature
45°C
Sample tray temperature
8°C
Table 9: QTOF MS settings.
Source type
Electro spray ionization – positive mode
Mass range
50 – 1250 Da
Scan time
0.2 seconds
Cone voltage
20 kV
Source temperature
120°C
Cone gas flow
30 l/hour
MSe collision energy ramp
15 – 40 V
3.2
Methods
3.2.1
Sampling devices
Saliva sampling devices for human collection are commercially available on a large scale. Examples of
these are cotton buds (swabs) and spitting tubes of different companies. Devices for animal use on the
other hand are not so common. The reason for this is the fact that animal saliva is not used a lot as a
matrix of investigation. However, a few saliva sampling tools especially designed for animals are
commercially available. There is the animal cotton rope by Salimetrics and the pig cotton rope (Happy
Bite) designed by GD animal health in the Netherlands. Because these were the only animal sampling
devices found also human sampling devices were tested and used in this research. For the testing some
factors were important: ease of sampling, absorption capacity of the device and ease of saliva extraction
from the device. Most (human) saliva devices come with a manual where a short the sampling procedure
is explained. Important is to avoid contamination of the device, so gloves must be worn during sampling
(different for every animal) and the devices must be put directly after sampling in a storage tube. This
can be part of the sampling device (for some swabs) or this can be a separate tube. Another important
factor is the sampling time; the time the device stays in the mouth of the animal. For most devices it
was stated that the device should stay in the mouth for a time period of one minute.
17
Figure 8: Pictures of two sampling devices: swab (left) and cotton rope (right).
3.2.2
Salivary collection
Saliva collection has to be performed by one person when the calf can be fixed in the feeding fence or by
two persons when the calf cannot be fixed in a feeding fence. One person fixes the calf in a feeding fence
while the second person performs the actual sampling (figure 9). The mouth of the calf has to be held
open and the sampling device has to be placed in the mouth. The device has to be kept in the mouth for
a certain time before it can be taken out again. The device is transferred into a coded tube and stored in
a cooled environment until it is taken to the laboratory.
Figure 9: sampling of saliva from a calf. One person fixes the calf, the other performs the actual
sampling.
18
3.2.3
Sample pre-treatment
After sampling the samples have to be stored in a freezer (32) or an extraction step (extraction of the
saliva from the sampling device) has to be performed. The extraction of the saliva from the device is
done by centrifugation. Depending on the used device the centrifugation step can differ slightly. Using a
rope kind of device, the device has to be cut in pieces of 3-5 centimeters and put in a 50 ml centrifugal
tube with an centrifugal insert (filter). Using swab kind of devices, the actual swab has to be cut of the
stick and transferred to a 10 ml centrifugal tube with an centrifugal insert (filter). The tubes are
centrifuged for 10 minutes at 3200 g. The saliva which is at the bottom of the tubes is transferred to a
clean tube.
Before the saliva can be analyzed there has to be a sample pre-treatment procedure. The main reason
for this is to remove the proteins (precipitation) and feed and dirt particles which are present in the
saliva. Some different methods were testes:
1.
No protein precipitation.
2.
Protein precipitation using acetonitrile and methanol
3.
Filtration of the saliva to get rid of the proteins
4.
Combinations of 2 and 3
Results of the different pre-treatment methods can be found in chapter 4.2.
3.3 Validation
The validation has to be performed according an in-house validation protocol. This protocol is based on
EU legislation (see paragraph 2.7).
The validation is carried out during three days. Every day three times seven different blank saliva
samples are used for the experiments. One set of seven blank samples is only fortified with internal
standard mixture. These samples are used for the determination of the selectivity. The other two sets of
seven blank samples are fortified with standard mixtures of the toxic compounds at two different
concentrations. These concentrations are 100 microgram per liter and 1000 microgram per liter. These
samples are used for the identification of the compounds and the determination of CCß. At one of the
three days 6 additional samples (of one blank saliva sample) are analyzed for the determination of the
ruggedness. A scheme of the experiments of validation day 3 is shown in appendix V. In this study the
internal standards are add to the samples to verify if the sample pre-treatment went well. So if the
internal standards are not identified in the sample after data processing, there was something wrong
with the sample-pre-treatment in that sample.
19
Table 10 shows the scheme of the ruggedness test. Two steps are tested, shaking the sample during
protein precipitation and addition of DMSO. When the results (number of identified compounds) of the
ruggedness samples are the same as the control sample the method is robust for that step in the
method.
Table 10: Ruggedness of the method. Two varieties on the method were tested, shaking during
protein precipitation and DMSO addition.
SOP (A)
Variable (B)
Day 3
Level
(duplo)
0.5 mg/l
Criteria
According to SOP
According to SOP
Day 3
0.5 mg/l
Shake 30 sec vortex
Shake 10 sec vortex
95% Peak identification
Day 3
0.5 mg/l
5 microliter DMSO
No DMSO
95% Peak identification
The stability of the extracts is determined by storing the extracts of one of the validation days in the
freezer for one week. After this week they are re-analyzed using the same analyzing method. When the
results of the stability samples are comparable with the results of the original analysis, the samples are
considered to be stable for one week in the freezer.
20
4
Results and discussion
In this chapter the results will be presented and discussed. Sampling, sample pre-treatment, LC-MS
analysis and validation will be discussed in four different paragraphs.
4.1
Sampling
Different saliva sampling devices were tested within this project. A distinction can be made between
small volume and large volume devices. The small volume devices can be used for collecting volumes
less than 300 µl, the large volume devices can be used for volumes larger than 300 µl. The small volume
devices are the so called swabs, a stick with a cotton part on top. Different devices of different
manufacturers were tested and assessed for amount of saliva uptake, user friendliness and costs. Taken
these factors in account, the cotton swab of Henry Schein, (900-3156) is the most suitable small volume
device. This device consists of a wooden stick with cotton wool top. The saliva can be sampled and the
top of the stick can be broken of the rest of the stick and placed into a centrifugal device. The samples
should be prepared according paragraph 3.2.3 or placed in the freezer immediately.
Three large volume sampling devices were tested, all cotton ropes of different sizes. Table 11 shows the
different sample volumes which were collected with the different ropes.
Table 11: Saliva yield of the three different tested large volumes sampling devices.
Device
Sample #
Saliva (± µl)
Cotton rope
Custom rope
Children swab
1
2
3
1
2
1
2
3
3500
400
700
700
2000
1700
1000
3500
The so called ‘children swab’ showed good saliva yield, but is too small to put in an animals mouth
without the risk of swallowing. The custom made rope also showed good results concerning saliva yield.
The problem with this device is that it takes some time to manufacture it and the that cotton wool which
is used comes of the device, so the animal can swallow it. The most suitable large volume device, taken
into account the 3 factors mentioned above, is the animal cotton rope of Salimetrics. The saliva yield is
good (most samples > 250 μl), it can be held firmly by the sampler and the costs are relatively low.
Table 12 shows the saliva yield of the animal cotton rope sampled at three different days for nine
different calves.
Table 12: Saliva yield of the cotton rope device at three different sampling days (3,4 and 5) for nine
different calves (2-18, even numbers).
sample
3.2
3.4
3.6
3.8
3.10
3.12
3.14
3.16
3.18
saliva (± µl)
±650
±115
±1000
±450
±330
±330
±900
±1700
±620
sample
4.2
4.4
4.6
4.8
4.10
4.12
4.14
4.16
4.18
saliva (± µl)
±2350
±1200
±100
±250
±2250
±1050
±750
±700
±1950
sample
5.2
5.4
5.6
5.8
5.10
5.12
5.14
5.16
5.18
saliva (± µl)
±1250
±600
±500
±600
±1000
±250
±330
±800
±950
As can be seen in table 11 the variation of saliva yield of the different samples is large. This is due to the
different calves which were sampled. The saliva production during the day varies a lot, especially with
ruminating animals.
21
Figure 10: Saliva sampling from a calf with one of the tested swabs.
4.2
Sample pre-treatment
Different sample pre-treatment procedures for saliva clean up were tested:
1.
No protein precipitation, only dilution
2.
Protein precipitation using acetonitrile and methanol
3.
Filtration of the saliva to remove proteins
4.
Combinations of 2 and 3
The procedures were tested with saliva samples from calves (see paragraph 3.1). The samples were
fortified with a test mixture of 43 pre-selected compounds of the three compound classes. Recoveries
(identification and peak intensities) of the compounds were used to evaluate the procedures.
For the first option, the samples were injected directly on the LC-MS system after a 10-times dilution
with water. The LC-MS system gave an over-pressure error. The pressure on the IonKey exceeded the
maximum (10.000 psi). This was probably due to clogging of protein on the column with the increasing
percentage of organic solvent (acetonitrile) in the gradient. The column could not be used anymore, so
no further experiments without protein precipitation were performed.
For the second option, 100 microliter saliva was pipetted in an Eppendorf tube. 250 microliter of
methanol or acetonitrile was added and the tubes were shaken on a vortex for 30 seconds. Then the
tubes were centrifuged for 10 minutes at 14.000 g. After centrifugation, the supernatant was transferred
to a total recovery LC vial containing 5 microliter DMSO. The sample was evaporated to almost dry
(DMSO) at 40°C under a stream of nitrogen. 100 microliter water was added to the vial and shaken on a
vortex for 10 seconds. During analysis, no clogging of the IonKey occurred, so it seems there was
sufficient protein precipitation from the sample to prevent clogging. The results for acetonitrile and
22
methanol were similar, both solvents worked well. On the other hand, acetonitrile gave better
chromatographic results compared to methanol. The background noise in the chromatograms was
reduced using acetonitrile, so identification of the compounds was more straightforward. Figure 11 shows
two extracted ion chromatograms (XIC) of clenbuterol of the same saliva sample: the chromatogram at
the top after acetonitrile protein precipitation and the chromatogram at the bottom after methanol
protein precipitation. It can be seen that both the intensity of the clenbuterol peak and the signal to
noise ratio (S/N) is higher in the acetonitrile protein precipitation sample. This was the case with all of
the tested compounds in the test mixture.
X1_140513_SALTO_021
1: TOF MS ES+
277.087 0.0500Da
286
5.32
100
%
acetonitrile
5.88
10.15
4.64
0
1.00
2.00
X1_140513_SALTO_006
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
18.00
1: TOF MS ES+
277.087 0.0500Da
93
17.00
18.00
1: TOF MS ES+
TIC
8.57e3
5.33
100
methanol
%
5.29
8.68
5.86 6.22
4.674.85
1.27 1.67
0
1.00
2.00
X1_140513_SALTO_021
3.00
4.00
5.00
6.00
8.47
7.52 7.68
7.00
8.00
9.00
5.68
10.00
11.00
12.00
13.00
14.00
15.00
16.00
9.19
5.31
100
10.16
10.13 10.18
9.33 10.08
5.86
1.57
Figure 11:
XIC chromatograms of clenbuterol with acetonitrile (top) and methanol (bottom) protein
15.31
precipitation. Using acetonitrile gives
higher peak intensities 15.04
and
lower S/N ratios compared to
15.41
8.66
8.79
7.72 8.33
methanol.
15.66
6.01
4.28
7.00
7.95
%
4.75
1.36
0.03
1.78
2.62
3.35
15.99
4.02
9.41
9.79
17.32
10.64
0.69
17.99
18.65 18.91
14.89
11.43
0
1.00
2.00
X1_140513_SALTO_006
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
18.00
1: TOF MS ES+
TIC
100
For
the third option ultrafiltration was used. Ultrafiltration is a filtration technique9.53e3
where a sample is
1.58
1.36
1.28
filtered using centrifugal forces using special manufactured centrifugal filters. The idea is that large
6.20
7.99
1.13
%
molecules (proteins) and possible dirt particles stay on the filter. The filtrate then is processed further.
4.77
1.08
0.49
2.02
2.67 2.82
4.30
5.32 6.01
6.34
15.04
7.45 7.75
8.15
8.44
15.45
9.35
15.74
Different types of ultrafilters were tested containing different filtermembranes, all with a 3.000 Da
3.79
16.43
10.63
10.95 11.44
17.32
17.52
18.76 18.91
14.89
0
Time
membrane.
VWR
Centrifugal
Filter
PES
3K,
Millipore
Amicon
Centricon
YM 17.00
3K and
Millipore
Amicon Ultra
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
18.00
3K. The results looked promising, which means no clogging of the IonKey occurred and good recoveries
(number of detected compounds) of the compounds that were added to the saliva were obtained.
However, contrary to these good results in the first attempts, succeeding experiments still gave clogging
of the IonKey, which most likely means the proteins were not removed from the saliva samples
sufficiently. The most likely explanation for this observation is a variable protein concentration in the
samples. Using only ultrafiltration therefore is not a good option.
The fourth option tested was a combination of the techniques mentioned above. Combinations of protein
precipitation and filtration were used as well as combinations of dilution and filtration. These options
gave good results concerning protein precipitation, but there was no advantage compared to protein
precipitation with methanol or acetonitrile alone. Reduction of background noise did not improve and
there was no increase in identified compounds compared with protein precipitation with acetonitrile
alone. Figure 12 shows an example of clenbuterol in saliva with and without ultrafiltration. The saliva
sample without ultrafiltration (only precipitation with acetonitrile) has significantly higher intensity and a
23
higher signal to noise ratio. From this it can be concluded that using ultrafiltration causes loss in intensity
or even loss off compounds due to interaction with the filter membrane.
X1_140513_SALTO_023
1: TOF MS ES+
277.087 0.0500Da
599
5.37
100
%
acetonitrile without ultrafiltration
2.47 2.59
0.56 0.97 1.28
2.70
1.69
4.74
5.01
5.90
6.666.72 7.19
8.66
9.20
15.08 15.47
10.06
0
1.00
2.00
X1_140513_SALTO_008
3.00
4.00
5.00
3.09
3.08 3.11
100
6.00
7.00
8.00
9.00
10.00
3.05 3.13
9.749.80
%
2.97
9.68
9.64
9.58
5.24
3.20
5.44
2.92
1.71
2.82
13.00
14.00
15.00
16.00
17.00
18.00
1: TOF MS ES+
277.087 0.0500Da
205
acetonitrile with ultrafiltration
3.00 3.16
0.51
12.00
5.36
3.03
0.50 0.66 1.26
1.65
11.00
4.70
3.38
8.66
5.57 6.18 6.69
4.78
9.53
8.97
9.92
9.98
10.02
15.04
10.12
10.36
10.45
15.12
0
1.00
2.00
X1_140513_SALTO_023
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
10.06
100
18.00
1: TOF MS ES+
TIC
3.31e5
Figure 12: XIC chromatograms
of clenbuterol
with and without ultrafiltration in the sample pre6.13
9.35
5.86
treatment. Using ultrafiltration
gives lower10.33peak intensities and higher S/N ratios compared not
5.71
10.72 11.07
5.57
using ultrafiltration.
%
6.55 6.64 6.75
1.38 1.59
0.62
5.02 5.22
1.66
4.75
0
1.00
2.00
X1_140513_SALTO_008
3.00
4.00
15.12 15.47
11.51
12.01
4.35 4.47
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
18.00
1: TOF MS ES+
TIC
100
2.45e5
Summarizing
all the above it can be concluded that the optimal sample pre-treatment
method was
6.02
6.57 6.66
6.30
7.20
protein precipitation using acetonitrile. The full sample pre-treatment procedure is described in Appendix
5.74
5.59
%
IX.
10.27 10.46
5.03 5.24
1.51 1.61
10.63
0.60
4.79
8.18
8.47
4.41
9.53
11.19
14.89
3.11
0
Time
1.00
4.3
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
18.00
LC-MS analysis
LC:
Different eluent compositions were tested to achieve optimal chromatographic conditions. Because a
large number of different compounds will be introduced, it is necessary to have a good chromatographic
separation between all compounds. This will, however, mean that compromises have to made and some
peaks won’t be as sharp as for a dedicated single compound LC method. Eluents using water, methanol
an acetonitrile were tested. As additive, formic acid at a concentration of 0.1 % (v/v) was used. Figure
13 shows chromatograms of some veterinary drugs analyzed with an eluent consisting acetonitrile or
methanol. The peaks in the extracted ion chromatograms (XIC) with acetonitrile are sharper and the
intensities are higher compared to the use of methanol in the eluent. There is also significantly less noise
in the acetonitrile chromatograms. The recoveries of the compounds (identified peaks) were similar when
using acetonitrile or methanol. Based on these results an eluent composition consisting of water,
acetonitrile and formic acid was chosen for the final method.
24
X1_140422_SALTO_006
10.44
100
1: TOF MS ES+
416.3 0.0500Da
52
methanol
XIC salmeterol
%
10.40
10.38
10.92
12.54
12.86
13.09
14.09
14.40
14.66
0
1.00
X1_140422_SALTO_003
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
7.99
15.00
16.00
17.00
1: TOF MS ES+
416.3 0.0500Da
61
16.00
17.00
1: TOF MS ES+
277.09 0.0500Da
301
acetonitrile
XIC salmeterol
%
100
14.00
10.17
7.32
0
1.00
X1_140422_SALTO_006
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.52
10.00
11.00
12.00
13.00
6.70
100
14.00
15.00
methanol
XIC clenbuterol
%
6.68
6.38
0
1.00
X1_140422_SALTO_003
2.00
3.00
4.00
5.00
6.00
7.00
8.00
8.97
9.92
9.00
10.00
10.77
11.11
11.00
12.00
13.00
5.43
15.00
16.00
17.00
1: TOF MS ES+
277.09 0.0500Da
362
16.00
17.00
1: TOF MS ES+
TIC
2.40e4
acetonitrile
XIC clenbuterol
%
100
14.00
8.74
0
1.00
X1_140422_SALTO_006
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
10.71
100
10.77
9.93
%
0.03
11.11
10.63
6.71
7.63 8.01 8.08
7.16 7.30
6.58
8.97 9.19 9.76
8.47
11.53
12.65
12.84
15.00
methanol
TIC 15.05 15.17
14.95
12.90 13.67
14.07
15.80 16.35
2.69
0
1.00
X1_140422_SALTO_003
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
5.77
100
5.44
5.95
%
8.23
6.31
0.69
1.36 1.63
2.02
2.69
3.35
acetonitrile
TIC
7.47
4.98
6.596.91
4.18
8.02
8.79 9.16
17.00
1: TOF MS ES+
TIC
1.80e4
15.16 15.37 15.60
9.62 10.00 10.49
10.66
14.93
0
Time
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
Figure 13: TIC and XIC chromatograms of a saliva sample containing a mixture of toxic compounds.
Comparison of eluent with acetonitrile or methanol. Bottom chromatograms: TIC of acetonitrile and
methanol. Middle chromatograms: XIC of clenbuterol using acetonitrile and methanol. Top
chromatogram: XIC of salmeterol using acetonitrile and methanol.
The chromatography was performed using a gradient. Table 13 shows the gradient parameters. Solvent
A consists of 1% acetonitrile in water (v/v) containing 0.1% formic acid (v/v). Solvent B consists of 1%
water in acetonitrile (v/v) containing 0.1% formic acid (v/v).
Table 13: Gradient of the microUPLC system.
Minutes
Flow (μl/min)
%A
%B
0
3
99
1
1
3
99
1
4
3
60
40
10
3
0
100
10.5
3
99
1
15
3
99
1
25
Default flow rates on the microfluidics system go from 0.2 till 5 microliters per minute, depending on the
column which is used, the choice of solvents and the sample injection volume. In this study a flow rate of
3 microliter per minute was used.
The sample volume to be injected depends on different factors. First the amount of sample volume which
is available. When there is a small amount available one has to be aware of the fact that most injection
systems use more sample than the sample volume which is injected. Furthermore, usually one does not
want to finish the whole sample volume, so the injection volume has to be chosen in such a way that
there is enough sample left for a second injection. In this study a sample injection volume of 2 microliter
was used.
The repeatability of the iKey was tested by multiple injections of the same standard solution. Appendix VI
shows overlaid chromatograms of d6-clenbuterol of 7 saliva samples within one validation day. It can be
seen that the retention time and intensities of the peaks are similar, so the repeatability of the iKey is
good. Also the pressure profile (the pressure of the system during the injection cycle) gives an indication
of the stability and repeatability of the analytical column or in this case the iKey. Appendix VI shows the
pressure profile of all saliva samples of validation day 2 (n=21). The profiles are overlapping well, which
gives an indication of the correct functioning of the iKey. Also in Appendix VI a pressure profile can be
seen of three saliva samples injected on three different validation days. Also here the profiles are
overlapping well, which gives an indication of the correct functioning of the iKey over different days. The
variation between different iKeys was tested by injecting the same sample at two different iKey’s. Figure
14 shows a TIC and a XIC of clenbuterol in a saliva sample spiked with a mixture of veterinary drugs
injected on two different (used) iKey’s. It can be seen that the shape of the chromatogram (TIC) is very
different and also the retention time of clenbuterol is significantly different (0.5 minutes difference). This
experiment shows that one has to be critical when using multiple iKey’s, because chromatographic
characteristics (RT, peak shape) can be different between them. This can be caused by the same factors
compared to conventional LC columns; misuse of the iKey, type of eluent used on the iKey, type of
sample injected on the iKey or age of the iKey. It should be mentioned that when using two (new or
used) iKeys which are both in good shape the performance (RT, peak shape) is identical (no data shown,
but can be provided on request).
26
X1_140723_SALTO_004
1: TOF MS ES+
277.087 0.0500Da
2.72e3
5.31
100
iKey 2
XIC clenbuterol
%
5.39
5.43
0
1.00
2.00
X1_140723_SALTO_003
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
4.71
4.74
100
18.00
1: TOF MS ES+
277.087 0.0500Da
1.84e3
%
iKey 1
XIC clenbuterol
1.60
0
1.00
2.00
X1_140723_SALTO_004
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
5.95
100
18.00
1: TOF MS ES+
TIC
9.59e4
iKey 2
TIC
5.31
6.45
%
5.18
8.07
5.43
9.97
8.468.53
9.27
4.59
10.57
14.85
14.13
13.45
9.60
1.36
11.06
12.03 12.26
13.23
14.59
15.10
15.33
0
1.00
2.00
X1_140723_SALTO_003
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
5.35
100
4.71
1.59
5.27
iKey 1
TIC
5.78
14.89
%
18.00
1: TOF MS ES+
TIC
7.52e4
15.04
10.63
7.43
1.51
15.28
10.77
11.45
0
Time
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
18.00
Figure 14: Comparison of two different iKey’s. TIC and XIC of clenbuterol of a spiked saliva sample.
Shape of the chromatogram (TIC) as well as retention time of clenbuterol (XIC) are different
between the iKey’s.
MS:
Before every MS analysis the correct working of the lock-spray have to be tested. This can be done
manually by switching the lock spray to the MS inlet. When a convenient signal (user specified) is
produced regarding intensity and stability, the lock spray is working in a correct way. Figure 15 shows a
lock spray spectrum using a Leucine and Enkypheline mixture of 2000 μg/l. The masses with a star are
the lock spray masses which should be detected.
27
20; blank saliva (T) + 1 ppm
X1_141222_SALTO_val day 3_024 18 (5.676)
*
397
100
3: TOF MS ES+
3.68e3
*
556
%
*
425
594
*
278
557
!
279
398
85
59
86
120
136 163 177
426
205
336
221
79 90
!;103
0
50
100
137
150
199
262
!
280
234 261
317
250
300
200
331 337
595
538
481
375 393
399
373
350
400
510
558
443
596
511
!
493
465
512
450
500
!
!
616 636 658 692 698 714 749 778 792 810
550
600
650
700
750
800
865 872
850
906
900
910
!
!
!
!
937 958
996
986
950
m/z
1000
Figure 15: Lock spray spectrum of Leucine/Enkypheline mixture. The masses with a star are the
lock spray masses which should be detected.
Also before every MS analysis the MS should be calibrated (see 2.5). An example of a calibration file is
shown in Appendix II.
In UNIFI a targeted data processing method was build containing all compounds which are present in the
standard mixtures (see chapter 3.1). The compound characteristics that were included in the library were
retention time, monoisotopic mass and (if known) the fragment masses. The retention times of the
compounds were determined by manually evaluation of the peaks in chromatograms for analyzed
standard solutions containing some groups of compounds. The final compound list including retention
times and monoisotopic masses can be found in appendix III (only validated compounds, see chapter
4.4). The compounds together with the retention times and monoisotopic masses were imported in a
targeted processing method in UNIFI (see paragraph 2.6). Part of the processing method is included in
appendix IV. Figure 16 to 18 show the results for a saliva sample fortified with 0.1 mg/l clenbuterol.
Figure 16 shows the extracted ion chromatogram where clenbuterol can be found at retention time 5.12.
In figure 17 a part of a low energy and a high energy spectrum of this clenbuterol peak can be seen. The
peaks of clenbuterol, with experimental mass 277.07869 Da and its chlorine isotope peak 279.08188
(clenbuterol contains two chlorine atoms), are significantly higher in the low energy spectrum compared
to the high energy spectrum. This is explained by the fact that with high energy part of the precursor ion
is fragmented. Figure 18 shows the full spectra (high and low energy), where the fragment masses are
identified. Figures 19 and 20 show a comparable chromatogram and high and low energy spectra for the
toxin atropine in fortified saliva sample (0.1 mg/l). Also here the fragment ions are identified. In this way
all compounds are identified based on the retention time, monoisotopic mass and fragment ions (if
present in the method). If the deviation in retention time and the monoisotopic mass are within the set
criteria (RT 0.1 minute and mass <25mDa, see paragraph 2.6) the compounds are identified. When
there are also identified fragment ions, the identification is even more reliable.
28
Figure 16: Chromatogram of clenbuterol in saliva (saliva sample fortified with 0.1 mg/l
clenbuterol).
Figure 17: Part of the spectrum of [M+H]+ ion of clenbuterol (277.0787). Top: low energy scan.
Bottom: high energy scan. The low energy scan shows high intensities of the peaks, the high energy
scan low intensities.
29
Figure 18: Full spectrum of precursor and product ions of clenbuterol (277.0787). Top: low energy
scan. Bottom: high energy scan. The low energy scan only shows the [M+H]+ ion of clenbuterol, the
high energy scan shows the fragment ions of clenbuterol.
30
Figure 19: Chromatogram of atropine in saliva (saliva sample fortified with 0.1 mg/l atropine).
Figure 20: Full spectrum of precursor and product ions of Atropine (290.17504). Top: low energy
scan. Bottom: high energy scan. The low energy scan only shows the [M+H]+ ion of atropine, the
high energy scan shows the fragment ions of atropine.
31
4.4
Validation
Sample pre-treatment of the validation samples was performed according the method described in
Appendix IX after all sample pre-treatment and LC-MS parameters were optimized. The validation itself
was performed according an in-house validation protocol which is described in paragraph 2.7 and 3.3.
This means that the validation was performed during 3 days with 20 different saliva samples. The
acquisition data was processed using the processing method in UNIFI. Compounds are considered to be
identified when UNIFI identifies a peak in a chromatogram and when this is visually confirmed as an
actual peak by the reviewer. This means that a peak has to fulfill the criteria of retention time and mass
deviation (see paragraph 2.6) and an additional check is performed.
After data processing of validation day 1 it became clear the data was not suitable for further evaluation.
Something went wrong in the LC-MS analysis causing retention time shifts of the chromatographic peaks.
Due to this the samples of validation day 1 were analyzed again after being stored in the freezer for 1
week (see also stability of the samples extracts). After data reviewing it became clear that the reanalyzed data of validation day 1 could be used for the validation. Appendix X shows 2 examples of
processed validation data of validation day 3. It can be seen that both compounds (trifloxystrobin and
clenbuterol) were identified in all spiked saliva samples (n=7). Trifloxystrobin was unidentified in all
blank saliva samples (selectivity samples) and in three of the 7 blank saliva samples clenbuterol was
identified. Nevertheless, with a visual check clenbuterol could be considered as unidentified in these
three samples, because the intensities of the peaks were to low (the integrated peak was not a real
chromatographic peak). To prevent the software to generate false positive samples (falsely identified
peaks) a peak intensity detection threshold could be included in the method. This was not done in this
validation to prevent false negative (falsely unidentified peaks) samples to occur.
CCß is the concentration value for which in 95% of the fortified samples the compound is identified. In
this validation study 21 blank saliva samples were used. One sample (sample G, validation day 1) was
considered to be an outlier, because the retention times of most compounds were not stable and did not
pass the requirements. Probably something went wrong in the LC-MS analysis, which caused this
problem. For every compound 19 of the 20 saliva samples have to give a positive identification at the
validation level. Because 20 screen positive control samples have been used in this validation, the CCß is
set to the target concentration (See, Guidelines for the validation of screening methods for residues of
veterinary medicines,(33)). Appendix VII shows the number of identifications per sample at the two
concentration levels. When no or less than 19 identification at 1 mg/l were found while at 0.1 mg/l 19 or
20 identifications were found this is due to an overloading problem of the TOF MS. Because the detector
was overloaded the mass assignment was not accurate anymore. When this was the case the CCß of the
compound was set to 0.1 mg/l. The table in Appendix VIII gives the CCß values (0.1 mg/l or 1 mg/l) for
the identified compounds, which are in total 202 compounds. Compounds which did not succeed these
requirements (so less than 19 identifications) were considered to be non-validated compound and were
left out the results of this validation study. These were not included in in the table in Appendix VII and
VIII. These were in total 94 compounds which corresponds with 31% of the total compounds in the tox
mixes. One of the reasons some compounds were not identified lies in the problem that the more polar
compounds were not retained well on the iKey. This has to do with the characteristics of the iKey. A
solution to avoid this problem can be the use of a trapping column in front of the iKey.
32
For the selectivity the same 21 saliva samples were analyzed and processed with the same method as
the fortified samples. Also in this case the outlier sample was left out. When a well-defined peak was
detected at the retention time of a compound in one of the samples the method could be considered as
not selective for this compound. For twelve compounds peaks were found (identified after automatic data
processing and manual check) in the blank samples. This means the analysis is not selective for these
compounds. The non-selective compounds can be found in table 14, between brackets are the number of
samples were the compound was identified in the blank saliva samples (n=20). For all other compounds
no peaks were founds in the blank samples, so the analysis is selective for these compounds.
Table 14: Non-selective compounds from the validation experiments. Between brackets the number
of samples (out of 20) which show no interfering peaks.
Toxins
#
Veterinary drugs
#
Pesticides
#
coumarin
(8/20)
broomchloorbuterol
(13/20)
carbetamide
(13/20)
digitoxigenin
(10/20)
carbuterol
(15/20)
disulfoton-sulfone
(18/20)
santonin
(13/20)
ractopamine
(9/20)
fenbuconazole
(16/20)
pirimicarb
(14/20)
tebufenozide
(13/20)
trinexapac-ethyl
(8/20)
The ruggedness was performed according table 5, chapter 2.7 for all validated compounds. For all
ruggedness samples all compounds were identified. This means the method is robust for the tested
variations in the method for the validated compounds. From this it can be concluded that the addition of
DMSO to prevent the compounds from not re-dissolving after evaporating has no added value. In case of
a continuation of the project or an additional validation this should be taken into account.
To determine the stability of the sample extracts the samples of validation day 1 were stored in the
freezer for one week and analyzed again. Because the initial analysis of validation day 1 failed, the
results of the stability test (samples of day 1 stored in the freezer for 1 week and re-analyzed) were used
as a full validation day (validation day 1). Because of this it can be stated that the identified compounds
mentioned in appendix VII are stable for one week in the freezer. The stability of the standard solutions
has not been tested in this validation, because information on these stabilities was already obtained in
other studies performed at RIKILT. Data on this is available in multiple RIKILT SOP’s.
33
5
Conclusion
A complete method for the toxicological screening of bovine saliva was successfully developed and
validated as part of this research project. This method includes a saliva sampling method, sample pretreatment, LC-MS analysis and data processing.
A saliva sampling method was developed. Sampling can be performed using two different sampling
devices depending on the amount of saliva needed. For amounts lower than 300 μl a swab has to be
used while for amounts higher than 300 μl a cotton rope has to be used. After sampling the saliva has to
be extracted from the devices or the devices have to be stored in the freezer as soon as possible.
The main reason for sample pre-treatment is to get rid of proteins which are present in the saliva. To
achieve this a protein precipitation method using acetonitrile was developed and tested.
Three main compound groups were included in the study, namely pesticides, natural toxins and
veterinary drugs. These compounds can be toxic for animals due to accidentally intake during feeding or
negligence of the owner of the animal. They can also be administered on purpose like poisoning or
overdosing.
A microLC-microfluidics-TOF-MS method was developed for the identification of the compounds in saliva.
Compared to conventional LC, with microLC a relatively low flow is used, 3 μl/min. An injection volume of
2 μl has been used. The microfluidics system consists of a Waters IonKey system, which includes an
analytical column in a chip device (iKey), using ESI as an ionization technique. The IonKey source is
placed in front of a QTOF. The acquisition method used is a so called MSe method were a full scan and a
fragmentation scan are acquired alternately. In this way next to full scan data there is also fragmentation
scan data available which can be used for more reliable identification of the compounds.
A targeted library was developed using UNIFI software. The library was constructed using experimental
obtained data using standard solutions containing pesticides, natural toxins and veterinary drugs. The
library includes retention times, monoisotopic masses and if present fragment ions.
The developed method was validated according 2002/657/EC to test the characteristics of the method.
For a screening method the limit of detection (CCß), selectivity and ruggedness of the method and
stability of the compounds and sample extracts needs to be validated. The validation was performed on
three days with 20 different blank saliva samples. The samples were spikes at two levels, 0.1 and 1
mg/liter. These corresponds with the CCß levels of the validated compounds. The validation results show
that with the method 203 compounds can be detected in saliva with a CCß of 0.1 or 1 mg/l (appendix
VIII). The method was not selective for twelve compounds, interfering peaks were found in the
chromatograms. The method was rugged for the tested variations on the sample pre-treatment and
sample extracts are stable for one week in the freezer.
Summarizing, within this research project a screening method for more than 200 toxic compounds was
successfully developed. The method consists of a sampling procedure, sample pre-treatment and
analyzing method using microLC-microfluidics-TOF-MS. Additionally, the method was validated according
European legislation.
34
6
Recommendations and future perspectives
Additional to the conclusion of this thesis some recommendation and future perspectives can be made. In
this study only bovine saliva was validated. It would be useful to perform an additional validation with
saliva from other animals as well. For example horses and dogs will be of great interest because owners
of these animals have the tendency of being concerned about their animal, so most forensic saliva
samples will be coming from these animals.
Also instead of saliva, serum could be validated additionally. As already mentioned in this thesis, serum
is a common matrix in forensic science, but not always easy to sample.
In addition to the compounds which are validated in this study, it would be useful to extend the number
of compounds. This can be done by adding new compound groups, such as human drugs, illicit drugs or
cleaning agents.
Another way of extending the amount of compounds is to improve the analysis method. With the used
iKey it is not possible to analyze in the negative electrospray ionization mode. When the manufacturer
develops a system where this is possible also compounds could be measured which have to be analyzed
in negative ionization mode.
To test the analytical system used, microfluidics systems of other manufacturers could be used.
In the method development and validation it was found that more polar compounds could not be
separated with the iKey, they eluted in the death volume of the column. This can be (partly) solved by
using a trap column in front of the iKey.
35
7
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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.
36
Appendix I: Camera view of IonKey source interior
Baffle in ESI position
Baffle in Lock spray position
37
Appendix II: TOF-MS calibration file
38
Appendix III: Compound list with RT and monoisotopic mass
Toxins
Aconitine
Aflatoxin B1
Aflatoxin B2
Aflatoxin G1
Ajmalicine
Aristolochia Acid II
Atropine
Colchicine
Convallatoxin
Coumarin
Digitoxigenin
Digoxin
Erucifoline-N-Oxide
Genistein
Heliotrine
Imperatorin
Jacobine
Kavain
Lobeline
Narceine
Noscapine
Ochratoxin A
Ouabain (Strophanthin G-)
Papaverine
Podophyllotoxin
Rescinnamine
Reserpine
Retorsine
Santonin
Senecionine
Senecionine-N-Oxide
Seneciphylline
Senkirkine
Solanine Alpha
Umbelliferone
Vincamine
RT
7.53
6.94
6.65
661
5.98
6.61
4.60
6.59
6.39
5.49
7.77
7.40
5.41
8.98
4.46
8.98
5.10
8.09
6.59
6.15
6.00
8.88
4.98
5.92
9.46
8.08
7.88
5.12
7.08
5.01
5.12
4.55
5.38
6.80
4.70
5.70
Mass
Veterinary drugs
645.3149
Broombuterol
312.0634
Broomchloorbuterol
314.0790
Carbuterol
328.0583
Cimaterol
352.1787
Clenbuterol
311.0430
Clencyclohexerol
289.1678
Clenpenterol
399.1682
Clenproperol
550.2778
Demecloxycline
146.0368
Doxycycline
374.2457
Emamectin
780.4296
Eprinomectine
365.1475 Hydroxymethylclenbuterol
270.0528
Isoxsuprine
313.1889
Mabuterol
270.0892
Mapenterol
351.1682
Monensin
230.0943
Moxidectine
337.2042
Oxytetracycline
445.1737
Ractopamine
413.1475
Salbutamol
403.0823
Salmeterol
584.2833
Tetracycline
339.1471
Tulobuterol
414.1315
634.2890
608.2734
351.1682
246.1256
335.1733
351.1682
333.1576
365.1838
867.4980
162.0317
354.1943
RT
5.31
5.36
1.60
1.59
5.12
4.05
5.75
4.58
5.07
6.00
9.58
10.64
4.47
5.69
5.75
6.25
11.36
11.23
4.60
4.88
1.65
7.90
4.81
5.15
Mass
363.9786
320.0291
267.1583
219.1372
276.0796
318.0902
290.0953
262.0640
464.0986
444.1533
885.5238
913.5188
292.0745
301.1678
310.1060
324.1216
670.4292
639.3771
460.1482
301.1678
239.1521
415.2723
444.1533
227.1077
39
Appendix III (continued): Compound list with RT and monoisotopic mass
Pesticides
Acetamiprid
Aclonifen
Aldicarb Sulfon
Aldicarb Sulfoxide
Ametoctradin
Atrazine
Azadirachtin
Azoxystrobin
Benzoylprop-Ethyl
Bitertanol
Bixafen
Bupirimate
Buprofezin
Carbaryl
Carbetamide
Carbofuran
Carfentrazone-Ethyl
Chlorantraniliprole
Chlorbromuron
Chloridazon
Chlorpyrifos
Clomazone
Clothianidin
Cyazofamid
Cybutryne
Cyproconazole I
Cyproconazole II
Cyprodinil
Cythioate
Diazinon
Dichlorvos
Difenoconazole I
Difenoconazole II
Diflufenican
Dimethenamid
Dimethoate
RT
5.53
8.92
7.22
7.70
8.72
7.37
9.26
8.88
9.90
9.33
9,49
8.30
9.06
7.33
6.33
7.03
9.60
8.36
8.66
5.04
10.61
8.17
4.89
9.60
7.65
8.63
8.63
7.81
6.95
9.77
6.65
9.72
9.72
10.17
8.61
5.09
Mass
222.0672
264.0302
222.0674
206.0725
275.2110
215.0938
720.2629
403.1168
365.0585
337.1790
413.0310
316.1569
305.1562
201.0790
236.1161
221.1052
411.0364
480.9708
291.9614
221.0356
348.9263
239.0713
249.0087
324.0448
253.1361
291.1138
291.1138
225.1266
296.9895
304.1010
219.9459
405.0647
405.0647
394.0741
275.0747
228.9996
Pesticides
Dimethomorph I
Dimethomorph II
Dimoxystrobin
Disulfoton
Disulfoton-Sulfone
Diuron
Dodemorph
Ethirimol
Ethoprophos
Etoxazole
Fenamidone
Fenamiphos
Fenbuconazole
Fenhexamid
Fenobucarb
Fenpropimorph
Flamprop-Isopropyl
Flamprop-Methyl
Florasulam
Fluazifop
Fluazifop-P-Butyl
Flufenacet
Fluopicolide
Fluoxastrobin
Flusilazole
Flutolanil
Flutriafol
Foramsulfuron
Fosthiazate
Haloxyfop
Haloxyfop-P-Methyl
Hexaconazole
Imazalil
Imidacloprid
Iprodione
Iprovalicarb
RT
8.47
8.61
9.37
6.10
8.33
7.67
7.81
5.20
8.91
10.01
8.87
8.91
9.25
9.01
8.47
8.09
9.87
9.15
7.15
9.50
10.58
9.34
9.06
9.41
9.20
9.28
7.71
7.07
7.55
10.11
10.17
9.25
7.20
5.14
8.94
8.83
Mass
387.1237
387.1237
326.1630
274.0285
306.0183
232.0170
281.2719
209.1528
242.0564
359.1697
311.1092
303.1058
336.1142
301.0636
207.1259
303.2562
363.1037
335.0724
359.0300
327.0718
383.1344
363.0665
381.9654
458.0793
315.1003
323.1133
301.1027
452.1114
283.0466
361.0329
375.0485
313.0749
296.0483
255.0523
329.0334
320.2100
40
Appendix III (continued): Compound list with RT and monoisotopic mass
Pesticides
Isoprocarb
Isoproturon
Isopyrazam
Isoxaben
Kresoxim-Methyl
Lenacil
Linuron
Mandipropamid
Mecoprop
Mepanipyrim
Mepronil
Mesosulfuron-Methyl
Metalaxyl
Metamitron
Metazachlor
Metconazole
Methidathion
Methoxyfenozide
Metolachlor
Metoxuron
Metrafenone
Metribuzin
Mevinphos
Myclobutanil
Nicosulfuron
Ouabain (Strophanthin G-)
Oxadixyl
Parathion
Penconazole
Pencycuron
Picoxystrobin
Pirimicarb
Pirimiphos-Methyl
Podophyllotoxin
Prochloraz
Profenofos
RT
8.02
7.71
10.01
9.13
9.62
7.04
8.50
9.06
6.46
8.87
9.10
7.95
7.82
4.70
8.02
9.32
8.40
9.16
9.18
6.22
10.15
6.48
5.24
8.89
6.75
4.98
6.73
9.72
9.21
10.00
9.73
5.13
9.56
9.46
8.66
10.16
Mass
193.1103
206.1419
359.1809
332.1736
313.1314
234.1368
248.0119
411.1237
214.0397
223.1109
269.1416
503.0781
279.1471
202.0855
277.0982
319.1451
301.9619
368.2100
283.1339
228.0666
408.0572
214.0888
224.0450
288.1142
410.1009
584.2833
278.1267
291.0330
283.0643
328.1342
367.1031
238.1430
305.0963
414.1315
375.0308
371.9351
Pesticides
Propiconazole I
Propiconazole II
Propoxur
Propyzamide
Prosulfocarb
Pyraclostrobin
Pyroxsulfam
Quinmerac
Quinoclamine
Quinoxyfen
Quizalofop-Ethyl
Silthiofam
Simazine
Spinosyn-A
Spiroxamine I
Spiroxamine II
Sulcotrione
Tebuconazole
Tebufenozide
Tebufenpyrad
Terbucarb
Terbuthylazine
Terbutryn
Tetraconazole
Thiacloprid
Thiophanate-Methyl
Topramezone
Triazophos
Triazoxide
Tricyclazole
Trifloxystrobin
Trinexapac-Ethyl
Triticonazole
Tritosulfuron
Vamidothion
Zoxamide
RT
9.39
9.39
6.94
8.85
9.18
9.90
7.34
7.22
6.41
10.06
10.24
9.45
6.42
9.04
8.10
8.10
7.30
9.12
9.55
10.26
10.06
8.44
7.41
9.13
6.09
6.96
6.60
9.25
5.88
5.75
10.31
7.95
8.69
9.70
5.26
9.78
Mass
341.0698
341.0698
209.1052
255.0218
251.1344
387.0986
434.0620
221.0244
207.0087
306.9967
372.0877
267.1113
201.0781
731.4608
297.2668
297.2668
328.0172
307.1451
352.2151
333.1608
277.2042
229.1094
241.1361
371.0215
252.0236
342.0456
363.0889
313.0650
247.0261
189.0361
408.1297
252.0998
317.1295
445.0279
287.0415
335.0247
41
Appendix IV: Processing method (partly)
42
Appendix V: Experimental scheme of validation day 3
sample
#
1
2
3
4
5
6
7
sample description
blank saliva (O)
blank saliva (P)
blank saliva (Q)
blank saliva (R)
blank saliva (S)
blank saliva (T)
blank saliva (U)
volume
µl
100
100
100
100
100
100
100
VL
mg/l
0
0
0
0
0
0
0
spike solution (ng/µl)
1
10
8
9
10
11
12
13
14
blank saliva (O) + 0.1 ppm
blank saliva (P) + 0.1 ppm
blank saliva (Q) + 0.1 ppm
blank saliva (R) + 0.1 ppm
blank saliva (S) + 0.1 ppm
blank saliva (T) + 0.1 ppm
blank saliva (U) + 0.1 ppm
100
100
100
100
100
100
100
0.1
0.1
0.1
0.1
0.1
0.1
0.1
15
16
17
18
19
20
21
blank saliva (O) + 1 ppm
blank saliva (P) + 1 ppm
blank saliva (Q) + 1 ppm
blank saliva (R) + 1 ppm
blank saliva (S) + 1 ppm
blank saliva (T) + 1 ppm
blank saliva (U) + 1 ppm
100
100
100
100
100
100
100
1
1
1
1
1
1
1
10
10
10
10
10
10
10
5
5
5
5
5
5
5
22
23
24
25
26
27
Robustness 1
Robustness 2
Robustness 3
Robustness 4
Robustness 5
Robustness 6
100
100
100
100
100
100
1
1
1
1
1
1
10
10
10
10
10
10
5
5
5
5
5
5
28
29
30
chem
chem + IS
chem + IS + 1 ppm
10
5
5
10
10
10
10
10
10
10
IS
13C-Caf/clen-d6 (10 ng/µl)
5
5
5
5
5
5
5
5
5
5
5
5
5
5
43
Appendix VI: iKey repeatability
Figure 6: Overlaid pressure profiles of 21 saliva samples within one day (validation day 2)
Figure 7: Overlaid chromatogram (IS, clenbuterol-d6) of 7 saliva samples within one day (validation
day 2)
44
Appendix VI (continued): iKey repeatability
1; blank saliva (O)
X1_141222_SALTO_val day 3_003
4800.000
1.12
nBSM System Pressure
Range: 2785
6.23
15.39
4600.000
4400.000
4200.000
4000.000
3800.000
3600.000
3400.000
3200.000
3000.000
2800.000
psi
2600.000
2400.000
2200.000
2000.000
1800.000
1600.000
1400.000
1200.000
1000.000
800.000
600.000
400.000
200.000
0.000
Time
1.00
2.00
3.00
4.00
5.00
6.00
7.00
8.00
9.00
10.00
11.00
12.00
13.00
14.00
15.00
16.00
17.00
18.00
Figure 8: Overlaid pressure profiles of 3 saliva samples between days (validation day 1, 2 and 3)
45
Appendix VII: Validated compounds with detection results
Number of samples in which the compound was identified (out of 20 validation samples). *: less
than 19 or no identifications
Toxins
Aconitine
Aflatoxin B1
Aflatoxin B2
Aflatoxin G1
Ajmalicine
Aristolochia Acid II
Atropine
Colchicine
Convallatoxin
Coumarin
Digitoxigenin
Digoxin
Erucifoline-N-Oxide
Genistein
Heliotrine
Imperatorin
Jacobine
Kavain
Lobeline
Narceine
Noscapine
Ochratoxin A
Ouabain (Strophanthin G-)
Papaverine
Podophyllotoxin
Rescinnamine
Reserpine
Retorsine
Santonin
Senecionine
Senecionine-N-Oxide
Seneciphylline
Senkirkine
Solanine Alpha
Umbelliferone
Vincamine
0.1 mg/l
19/20
*
20/20
*
20/20
*
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
19/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
*
20/20
1 mg/l
*
20/20
20/20
19/20
20/20
20/20
19/20
18/20
20/20
20/20
20/20
20/20
20/20
20/20
*
20/20
20/20
20/20
19/20
*
19/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
17/20
20/20
*
20/20
20/20
20/20
Veterinary drugs
Broombuterol
Broomchloorbuterol
Carbuterol
Cimaterol
Clenbuterol
Clencyclohexerol
Clenpenterol
Clenproperol
Demecloxycline
Doxycycline
Emamectin
Eprinomectine
Hydroxymethylclenbuterol
Isoxsuprine
Mabuterol
Mapenterol
Monensin
Moxidectine
Oxytetracycline
Ractopamine
Salbutamol
Salmeterol
Tetracycline
Tulobuterol
0.1 mg/l
*
20/20
20/20
19/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
19/20
20/20
20/20
20/20
20/20
*
20/20
20/20
20/20
*
20/20
20/20
20/20
1 mg/l
20/20
20/20
18/20
20/20
*
20/20
20/20
20/20
20/20
20/20
18/20
19/20
*
20/20
15/20
20/20
20/20
20/20
20/20
20/20
19/20
20/20
20/20
20/20
46
Appendix VII (continued): Validated compound with CCß values
Number of samples in which the compound was identified (out of 20 validation samples). *: less
than 19 or no identifications
Pesticides
Acetamiprid
Aclonifen
Aldicarb Sulfon
Aldicarb Sulfoxide
Ametoctradin
Atrazine
Azadirachtin
Azoxystrobin
Benzoylprop-Ethyl
Bitertanol
Bixafen
Bupirimate
Buprofezin
Carbaryl
Carbetamide
Carbofuran
Carfentrazone-Ethyl
Chlorantraniliprole
Chlorbromuron
Chloridazon
Chlorpyrifos
Clomazone
Clothianidin
Cyazofamid
Cybutryne
Cyproconazole I
Cyproconazole II
Cyprodinil
Cythioate
Diazinon
Dichlorvos
Difenoconazole I
Difenoconazole II
Diflufenican
Dimethenamid
Dimethoate
0.1 mg/l
20/20
20/20
*
*
20/20
20/20
*
20/20
20/20
19/20
20/20
20/20
20/20
*
20/20
20/20
*
20/20
20/20
20/20
*
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
19/20
20/20
20/20
16/20
20/20
20/20
1 mg/l
20/20
20/20
20/20
20/20
20/20
20/20
20/20
19/20
20/20
20/20
20/20
13/20
20/20
19/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
13/20
20/20
20/20
20/20
20/20
18/20
20/20
20/20
20/20
20/20
20/20
20/20
Pesticides
Dimethomorph I
Dimethomorph II
Dimoxystrobin
Disulfoton
Disulfoton-Sulfone
Diuron
Dodemorph
Ethirimol
Ethoprophos
Etoxazole
Fenamidone
Fenamiphos
Fenbuconazole
Fenhexamid
Fenobucarb
Fenpropimorph
Flamprop-Isopropyl
Flamprop-Methyl
Florasulam
Fluazifop
Fluazifop-P-Butyl
Flufenacet
Fluopicolide
Fluoxastrobin
Flusilazole
Flutolanil
Flutriafol
Foramsulfuron
Fosthiazate
Haloxyfop
Haloxyfop-P-Methyl
Hexaconazole
Imazalil
Imidacloprid
Iprodione
Iprovalicarb
0.1 mg/l
20/20
20/20
20/20
20/20
18/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
19/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
19/20
19/20
20/20
20/20
20/20
20/20
20/20
1 mg/l
20/20
20/20
20/20
20/20
19/20
20/20
20/20
20/20
20/20
20/20
15/20
20/20
20/20
20/20
20/20
19/20
20/20
19/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
17/20
20/20
20/20
19/20
20/20
13/20
20/20
20/20
20/20
*
47
Appendix VII (continued): Validated compound with CCß values
Number of samples in which the compound was identified (out of 20 validation samples). *: less
than 19 or no identifications
Pesticides
Isoprocarb
Isoproturon
Is opyrazam
Isoxaben
Kresoxim-Methyl
Lenacil
Linuron
Mandipropamid
Mecoprop
Mepanipyrim
Mepronil
Mesosulfuron-Methyl
Metalaxyl
Metamitron
Metazachlor
Metconazole
Methidathion
Methoxyfenozide
Metolachlor
Metoxuron
Metrafenone
Metribuzin
Mevinphos
Myclobutanil
Nicosulfuron
Ouabain (Strophanthin G-)
Oxadixyl
Parathion
Penconazole
Pencycuron
Picoxystrobin
Pirimicarb
Pirimiphos-Methyl
Podophyllotoxin
Prochloraz
Profenofos
0.1 mg/l
20/20
20/20
20/20
20/20
*
20/20
20/20
20/20
19/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
*
1 mg/l
20/20
*
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
*
20/20
20/20
18/20
20/20
20/20
20/20
20/20
19/20
*
20/20
20/20
20/20
20/20
20/20
20/20
14/20
20/20
20/20
*
*
20/20
20/20
20/20
Pesticides
Propiconazole I
Propiconazole II
Propoxur
Propyzamide
Prosulfocarb
Pyraclostrobin
Pyroxsulfam
Quinmerac
Quinoclamine
Quinoxyfen
Quizalofop-Ethyl
Silthiofam
Simazine
Spinosyn-A
Spiroxamine I
Spiroxamine II
Sulcotrione
Tebuconazole
Tebufenozide
Tebufenpyrad
Terbucarb
Terbuthylazine
Terbutryn
Tetraconazole
Thiacloprid
Thiophanate-Methyl
Topramezone
Triazophos
Triazoxide
Tricyclazole
Trifloxystrobin
Trinexapac-Ethyl
Triticonazole
Tritosulfuron
Vamidothion
Zoxamide
0.1 mg/l
20/20
20/20
19/20
20/20
*
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
19/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
20/20
19/20
19/20
20/20
20/20
20/20
20/20
*
20/20
19/20
20/20
20/20
1 mg/l
20/20
20/20
20/20
20/20
20/20
20/20
20/20
18/20
20/20
20/20
20/20
20/20
20/20
18/20
20/20
20/20
20/20
*
20/20
20/20
20/20
20/20
17/20
20/20
20/20
20/20
19/20
16/20
17/20
20/20
20/20
20/20
*
19/20
20/20
20/20
48
Appendix VIII: Validated compound with CCß values
Toxins
Aconitine
Aflatoxin B1
Aflatoxin B2
Aflatoxin G1
Ajmalicine
Aristolochia Acid II
Atropine
Colchicine
Convallatoxin
Coumarin
Digitoxigenin
Digoxin
Erucifoline-N-Oxide
Genistein
Heliotrine
Imperatorin
Jacobine
Kavain
Lobeline
Narceine
Noscapine
Ochratoxin A
Ouabain (Strophanthin G-)
Papaverine
Podophyllotoxin
Rescinnamine
Reserpine
Retorsine
Santonin
Senecionine
Senecionine-N-Oxide
Seneciphylline
Senkirkine
Solanine Alpha
Umbelliferone
Vincamine
0.1 mg/l
x
1 mg/l
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Veterinary drugs
Broombuterol
Broomchloorbuterol
Carbuterol
Cimaterol
Clenbuterol
Clencyclohexerol
Clenpenterol
Clenproperol
Demecloxycline
Doxycycline
Emamectin
Eprinomectine
Hydroxymethylclenbuterol
Isoxsuprine
Mabuterol
Mapenterol
Monensin
Moxidectine
Oxytetracycline
Ractopamine
Salbutamol
Salmeterol
Tetracycline
Tulobuterol
0.1 mg/l
1 mg/l
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
49
Appendix VIII (continued): Validated compound with CCß values
Pesticides
Acetamiprid
Aclonifen
Aldicarb Sulfon
Aldicarb Sulfoxide
Ametoctradin
Atrazine
Azadirachtin
Azoxystrobin
Benzoylprop-Ethyl
Bitertanol
Bixafen
Bupirimate
Buprofezin
Carbaryl
Carbetamide
Carbofuran
Carfentrazone-Ethyl
Chlorantraniliprole
Chlorbromuron
Chloridazon
Chlorpyrifos
Clomazone
Clothianidin
Cyazofamid
Cybutryne
Cyproconazole I
Cyproconazole II
Cyprodinil
Cythioate
Diazinon
Dichlorvos
Difenoconazole I
Difenoconazole II
Diflufenican
Dimethenamid
Dimethoate
0.1 mg/l
x
x
1 mg/l
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Pesticides
Dimethomorph I
Dimethomorph II
Dimoxystrobin
Disulfoton
Disulfoton-Sulfone
Diuron
Dodemorph
Ethirimol
Ethoprophos
Etoxazole
Fenamidone
Fenamiphos
Fenbuconazole
Fenhexamid
Fenobucarb
Fenpropimorph
Flamprop-Isopropyl
Flamprop-Methyl
Florasulam
Fluazifop
Fluazifop-P-Butyl
Flufenacet
Fluopicolide
Fluoxastrobin
Flusilazole
Flutolanil
Flutriafol
Foramsulfuron
Fosthiazate
Haloxyfop
Haloxyfop-P-Methyl
Hexaconazole
Imazalil
Imidacloprid
Iprodione
Iprovalicarb
0.1 mg/l
x
x
x
x
1 mg/l
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
50
Appendix VIII (continued): Validated compound with CCß values
Pesticides
Isoprocarb
Isoproturon
Isopyrazam
Isoxaben
Kresoxim-Methyl
Lenacil
Linuron
Mandipropamid
Mecoprop
Mepanipyrim
Mepronil
Mesosulfuron-Methyl
Metalaxyl
Metamitron
Metazachlor
Metconazole
Methidathion
Methoxyfenozide
Metolachlor
Metoxuron
Metrafenone
Metribuzin
Mevinphos
Myclobutanil
Nicosulfuron
Ouabain (Strophanthin G-)
Oxadixyl
Parathion
Penconazole
Pencycuron
Picoxystrobin
Pirimicarb
Pirimiphos-Methyl
Podophyllotoxin
Prochloraz
Profenofos
0.1 mg/l
x
x
x
x
1 mg/l
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
Pesticides
Propiconazole I
Propiconazole II
Propoxur
Propyzamide
Prosulfocarb
Pyraclostrobin
Pyroxsulfam
Quinmerac
Quinoclamine
Quinoxyfen
Quizalofop-Ethyl
Silthiofam
Simazine
Spinosyn-A
Spiroxamine I
Spiroxamine II
Sulcotrione
Tebuconazole
Tebufenozide
Tebufenpyrad
Terbucarb
Terbuthylazine
Terbutryn
Tetraconazole
Thiacloprid
Thiophanate-Methyl
Topramezone
Triazophos
Triazoxide
Tricyclazole
Trifloxystrobin
Trinexapac-Ethyl
Triticonazole
Tritosulfuron
Vamidothion
Zoxamide
0.1 mg/l
x
x
x
x
1 mg/l
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
x
51
Appendix IX: Final sample pre-treatment method
100 µl saliva in a 1.5 ml Eppendorf Tube
Control samples
Tox mix 1 mg/l
(µl)
Tox mix 10 mg/l
(µl)
Internal standard mix 10 mg/l
(µl)
-
-
5
10
-
5
-
10
5
Control sample 0 mg/l
Control sample 0.1 mg/l
Control sample 1 mg/l
Add 5 µl IS to the samples
Add 250 µl acetonitrile to the samples
Shake thoroughly with a vortex for 30 seconds
Centrifuge 10 minutes at 10 000 g
Transfer the supernatant into a 1.5 ml total recovery LC-MS vial
Add 5 µl DMSO
Evaporate the sample under a nitrogen gas flow at 40°C
Reconstitute with 100 µl water and cap the vial. Vortex thoroughly for 30 seconds and place in
an ultrasonic bath for 1 minute.
52
Appendix X: Results of validation day 3
53