Identification of mycotoxins and glyphosate in
human plasma
Bachelor thesis advanced level 15 hp Maine Area: Chemistry
Institution of Science and engineering, Örebro university Supervisor: Tuulia Hyötyläinen
Abstract
Type one diabetes (T1D) and islet autoimmunity (IA) in people with a genetically susceptibility for the diseases can be triggered by environmental factors. It is earlier showed that the diet can be one of the environmental factors as it has been indicated that a cereal rich diet can increase the risk of developing IA. In this study, we investigated blood plasma samples from a study done by L. Hakolas on children that have genetic risk of developing T1D and IA, with a focus on dietary contaminants originating from cereals. Mycotoxins often found on cereals could be one of the environmental factors triggering the development of the diseases. To see if this could be the case a method based on a liquid chromatography coupled with a quadrupole-time of flight (LC-QTOF) was developed for the analysis of mycotoxins and glyphosate; MS/MS mode was used after that to confirm the identity of the compounds. For sample preparation, protein precipitation of the plasma samples was applied. The method was optimized by analyzing 5 mycotoxin standards and a list of suspected compounds that could be found in the screening to make sure the method could separate all the compounds. Test plasma samples was also analyzed to determine the optimal plasma volume (100 µL) for extraction and injection volume (15µL). For the data preprocessing, MZmine software was used and could tentatively identify some of the mycotoxins based on accurate mass acquisition. After comparing the signal against the background noise, Ergotaminine, FB1, Gly and HT-2 and NIV were identified. As quality control three replicates of a pooled sample were analysed, using both positive and negative ionization modes. From the pooled sample mean, standard deviation (STD) and relative standard deviation (RSD) were calculated showing some variation among the plasma sample for some mycotoxins e.g., Gly. The results presented in this report show that some mycotoxins do occur in the blood plasma and that the amounts of the mycotoxins varied. However, how these mycotoxins can affect the progress of T1D and IA is still unknown and requires further studies.
Content
1. Theory ... 1
1.1 Introduction ... 1
1.1.1 Earlier diabetes study ... 1
1.1.2. Mycotoxin and Glyphosate ... 2
1.1.3 Analysis ... 2
1.2. Aim ... 4
2. Method and material ... 4
2.1. Method development ... 4
2.1.1. Materials ... 4
2.1.2. Mobile phase preparation ... 5
2.1.3. LC-QTOF run with standards ... 5
2.1.4. Test run with plasma samples ... 5
2.1.5. Test run with plasma samples after modification of the protein precipitation and addition of a filtration step ... 6
2.2. Sample run ... 6
2.2.1 LC-MS ... 6
2.2.2. MS/MS ... 6
3 Result and discussion ... 7
3.1 Result from standard run ... 7
3.2 Result from plasma sample run ... 9
3.2.1 Plasma volume ... 10
3.2.2 Injection volume ... 10
3.3. Result from sample run ... 12
3.3.1. Processed data from MZmine and identified components ... 12
3.3.2. Identified compounds ... 14
3.3.3 Hexanoic acid as an internal standard. ... 14
3.3.4 Quality control sample ... 15
4. Conclusions ... 16
5. References ... 16
Acknowledgment ... 18
1.
Theory
1.1 Introduction
Diabetes is a disease that effect the metabolic system. It is a result of insulin secretion or the insulin action being defect and not working as it should be. The cases of diabetes can be categorized into two classes. Type 1 diabetes (T1D) and Type 2 diabetes (T2D). In patients having T1D the insulin secretion is lacking. Individuals can have a genetic risk of developing T1D. T2D is the result of the bodies resistant the insulin action and the insulin secretion not working fully. [1]
T1D can be considered to be a two-step disease. Individuals that express genetic risk of developing T1D will do so in two steps. First step is to develop the islet autoimmunity (IA). This is when the body starts to develop antibodies against insulin, insulinoma antigen-2, glutamic acid decarboxylase 65 and ZnT8 transporter. The risk of this stage developing to clinical onset of T1D is coupled with the number of antibodies present from the IA. [2]
From the first step the clinical onset of T1D is developed; however, an individual can be IA positive for a very long time, up to years before the T1D develops. It is suggested that in combination with the individual being genetic susceptible to IA and T1D a trigger in form of environmental factors are the activator that first develop IA and then allows it to progress to T1D. [2]
The fact that the genetic factors are not the only reason for development of T1D thus environmental factors (diet included) has a large impact and can provide an explanation for the increment in diabetes over the last decade. [2,3]
It has been suggested in earlier studies that the intake of different kinds of cereals enhance the risk of developing IA and T1D in infants caring the genetic risk for T1D. This indicates that the cereals possibly carry the environmental factor. The mechanism of these factors and exactly what environmental factors the cereal carries are is still unknown. [3]
1.1.1 Earlier diabetes study
Existing studies based on a cohort study of children with genetic susceptibility for T1D followed the children from birth to the age of 6 years old [3] . Under the time a food diary was established together with plasma samples that were taken to see if antibodies for insulin had developed indicating the progression of IA. The cohort study hypothesized if oats, wheat, rye, gluten-containing cereals, gluten and dietary fiber were consumed in high amounts would increase the risk of IA. For T1D, a high intake of oats, rye, gluten-containing cereals, gluten with avenin and dietary fiber indicated an increased risk of T1D; however after some adjustments and controls, none of the cereals indicated that they could give an increased risk of T1D. [3]
How the immune system is triggered and end up causing IA or T1D is still unclear. It is found that gluten in the roll as an antigen can modify gut microbiota which can lead to inflammation and thus trigger the start of IA. [4] It is also found that mycobiota and their toxins that are often found on cereals also can act as environmental factors that can lead to IA and T1D. For example, trichothecenes as t-2 toxin can disturb the intestine microbiota and thus creating an immune
response and alter the intestinal permeability and as gluten, then be the environmental factor that triggered the evolution of IA and T1D. [3,5]
1.1.2. Mycotoxin and Glyphosate
Molds can produce toxins that can give hazardous effects. The toxins produced by the molds are called mycotoxins. The production of the toxin from the mold is highly affected by the surroundings of the mold such as temperature and oxygen level. The molds and their toxins can often be found on organic material and vegetable. Deoxynivalenol (DON), deoxynivalenol 3-glucoside (DON-3G), T-2 toxin (T2) and zearalenone (ZEN) are the most common mycotoxins and can often be found on cereals; however, the levels of mycotoxins can vary from year to year depending on the temperature and weather conditions under the year. If consumed these toxins can cause negative health effects. [6]
Several weed killers have glyphosate, a phosphonic acid as the active ingredient and products containing the glyphosate can easily be bought for private and industrial farming. [7] It is shown in studies that glyphosate and weed killer containing the active ingredients can have a health hazardous effect by affecting the production of estrogen in mammals. [8] In literature a method for LC-MS was developed and it was shown that it could detect and identify glyphosate on cereal samples. [9]
1.1.3 Analysis
When analyzing serum from humans where the sample volume is often limited, a method that can analyze many components in one run is of importance. Quadrupole Time of Flight/Mass Spectrometry (QTOF/MS) has in last decade together with other high-resolution MS been used for screening of compounds for example organic contaminants. In literature the separation technique that has often been used together with the high-resolution MS has been gas chromatography (GC); however, these studies were done on fatty tissue where the compounds found often are non-polar. The compounds found in biological matrices as blood are often slightly polar to polar. A derivatization step is needed before the analysis when using the GC [10] in order to improve the performance of the chromatography and to improve the detection of the compounds. [11] With liquid chromatography (LC), derivatization is typically not needed. Progress in the development in the LC-QTOF/MS makes it a suitable method for screening of polar and slightly polar chemicals. A significant point to make is that the LC-QTOF/MS only need relatively low volumes of serum to produce a comprehensive profiling of chemical exposure. This is a crucial benefit when working with samples that have limited volume. [10]
The challenge of the LC-QTOF/MS method is that it is limited to the identification of chemicals that exist in databases and that the limit of detection (LOD) is higher for the untargeted LC-QTOF/MS then for the targeted LC-MS/MS analysis, it is shown that the LC-MS/MS had a sensitivity 4-40 times higher than the LC-QTOF/MS when 6 standards was analysed in a validation run in found literature. Although the MS/MS has a higher sensitivity the LC-QTOF/MS still detects the environmental organic acids (EOAs) in biological samples. In literature 282 of the 693 EOAs in the database was found in the biological samples indicating that the higher LOD for LC-QTOF/MS does not hinder the detection of these compounds. The LC-QTOF/MS is a method that would therefore work to screen for which mycotoxins are present. However, to have a higher sensitivity for the compounds more optimization would be needed to be done or to use another instrument like the MS/MS. [10]
Majority of the published methods for the analysis of mycotoxins are based on targeted analyses with LC combined with triple quadrupole MS, using LC-MS/MS. It has been shown that with some clean up procedure the recovery is relatively high for components like ZEN, DON, DON-3G and T2 [12] it has also been tested that glyphosate can be extracted with similar methods and analysed with the LC-MS/MS technique. [13] In the MS/MS procedure, the mass of the specific analyte is isolated, then the selected masses are fragmented and then the mass of the fragments from the original molecule are measured. By doing so the fragment will be the indicator of that the original molecule was correctly identified. [11]
The QTOF-MS using the MS/MS mode can be used for both targeted and suspect screening approach. A targeted approach often uses three quadrupoles, in this case the third quadruple is fixed at a m/z and by doing so the selectivity is increased, also 100% of the duty cycle is assigned the chosen m/z. [14] Because of that the m/z need to be absolutely fixed on the m/z it is searching for this technique only preselected compounds can be detected. [15] The suspected screening approach uses a list that is done beforehand with suspected compounds within a m/z tolerance span. The need for a standard is not required, thus the chromatogram is checked for the exact mass from the list. The identification of suspected compounds is verified by the fragmentation and later, identification can be confirmed by use of authentic standards, if available. Instrument that is often used for the suspected screening approach is QTOF/MS and the Orbitrap-MS [15]. Because of the amount of mycotoxins that could be found in plasma and the restricted volume of sample available the suspected screening approach would be the best option.
Glyphosate is a very polar compound, that is water soluble and insoluble in non polar organic solvents. [16] Some mycotoxins are on the other hand semi polar, meaning partially polar. To analyze these compounds in the sample run puts requirements on the developed method to be able to separate all the compounds within a resendable retention time. LC, is a method that can separate both polar and semi polar compounds however the difficulty lies in doing it on one run. Polar compounds typically require hydrophilic interaction liquid chromatography (HILC) while semi polar compounds require reversed phase liquid chromatography (RPLC). [17] A mixed mode column that could work in both RPLC and HILC mode could be a good solution thus it gives the advantage of both the modes. [18]
When working with blood samples a problem for the LC part of the method can arise. The plasma contains proteins and phospholipids, and these can contaminate the equipment by clotting. Often when working with biological matrixes as plasma SPE can be used to clean up the samples, this method is used in multiple studies and then provides both better accuracy, reproducibility and detection thus the coeluting compounds are removed. SPE cleanup has proven to be able to clean up both fish matrix that contain different fat content [19] as well as for matrixes as chicken plasma.[20] However, in a case where glyphosate were to be analyzed SPE for phospholipid removal is not a very good method as the SPE step will remove the phosphate containing compounds, by doing so the glyphosate is lost. [21] Therefore, protein precipitation (PPT) is a more suitable clean-up method for biological fluids (bio-fluid). This is a method that removes the protein by adding a water miscible organic solvent as methanol (MeOH) or Acetonitrile (ACN). This will cause the hydration layer on proteins to be destroyed and thus causing the repulsive force between the proteins to reduce, this will in turn lower the solubility of the proteins in the bio-fluid. ACN as the solvent in the PPT is a more effective solvent when precipitating proteins and the precipitants will be larger and thus not have as large pressure on the filtration of the precipitation. [22]
1.2. Aim
The aim with this thesis is to develop a method for a qualitative analysis of mycotoxins and glyphoshate in plasma samples. This was done by testing different mobile phases for the chromatographic separation, as well as test different injection volumes and extraction volumes of plasma samples to find the settings that would enable the separation and detection of multiple mycotoxins and glyphosate. Another purpose with this report is to identify which mycotoxins and glyphosate can be found in blood plasma sample from children that is at a genetic risk of T1D to further on maybe see if these could be the environmental factors taken in with the food that increase the progress of IA showed in earlier studies.
2. Method and material
2.1. Method development
The method was developed in multiple steps, first analytical standards were analyzed to ensure the suitability of this method for the targeted compounds. After that optimal volumes of plasma samples and injection volumes were evaluated on test plasma sample. This were done to determine a volume that would give a satisfactory signal without overloading the instrument or require too high volume of the sample. Last the method was used for the real plasma samples. 2.1.1. Materials
All the method development and material used as can be found below. Standards
Zearaleine (ZEN)100 ppm Deoxynivalenol (DON) 25 ppm
Deoxynivalenol 3- glucoside (DON-3G) 50 ppm T-2 toxin 1000 ppm
Glyphosate 400 ppm (Gly) Polar metabolites 10 ppm
Short chain fatty acids (SCFA) 20 ppm PFAS mixture 200 ppb
Bile acids 100ppb (BA) HT-2 500 ppm
Isobutyric acid 1000 ppm
Ammonium acetate, >99.0%,CAS. # 631-61-8 from Sigma Aldrich Formic acid, CAS. # 64-18-6 from Fisher Chemical
Acetonitrile, grade LC/MS, Purity 99.99%, CAS. # 75-05-8 from Fisher Chemical.
2-propanol , grade LC/MS, >99.9% purity, CAS. # 67-63-0 from Honeywell Methanol, grade LC/MS, >99.9% purity CAS. #67-56-1 from Fisher Chemical Water, grade LC/MS, CAS. # 7732-18-5 Fisher Chemical
Nitrogen-gas, 99.999% Filter 13 mm 0.2 µm GHP
Plasma samples from L. Hakolas study [3] Eppendorf tubes
LC-vials
LC instrument, 1290 Infinity II from Agilent Technologies 6545 Q-TOF LC/MS from Agilent Technologies
Atlantis Premier BEH C18 AX 1.7 µm, VanGuard FIT 2.1x100 mm column 1/pk
2.1.2. Mobile phase preparation
Two mobile phases were prepared, one with organic solvent and one with water.
The mobile phase A where prepared so that it would be 0.5 mM ammonium acetate, 0.1 % formic acid in water. It was also controlled to have a pH around 3. B were prepared so that it would contain 0.5 mM ammonium acetate, 0.1% formic acid in 2-propanol (IPA) mixed with a solution of 0.5 mM ammonium acetate, 0.1 % formic acid in ACN. Mobile phase B was put into ultrasonic bath for 20 min to assist in the solving of the ammonium acetate in the ACN and IPA. The IPA and ACN mix were mixed 50/50 and made up the mobile phase B. The mobile phase flow for the analysis was set to 0.4 mL/min.
2.1.3. LC-QTOF run with standards
To ensure that the method could identify the targeted compounds and to find out the retention times (RT) for the compounds in the new column a run with standard was performed. During this run the column had a temperature set at 50 °C. The standard for mycotoxins that were analyzed were, ZEN, DON, DON-3G, T-2 toxin and Gly. In addition to the mycotoxins, polar metabolites, SCFA, a mix of PFAS and BA were also analysed to see if the method could detect all the compounds. The sample preparation method was based on method reported in literature for the mycotoxins [20]. During the development of this method the extraction efficiencies were not determined.
A mixture of the mycotoxins (ZEN, DON, DON-3G and T-2 toxin) was prepared with the concentration 5ppm and the total volume of 100 µL, the mycotoxins were solved in MeOH to obtain the desired volume. Also, a solution of glyphosate with the concentration 10 ppm diluted with MeOH: H2O (1:1) was analyzed to ensure that the glyphosate was dissolved in the solvent and could be analyzed. PFAS and BA mix had a very low concentration (0.2 ppm and 1 ppm respectively) and thus the mix where directly injected to the LC. The polar metabolites and the SCFA were made to a concentration of 5 ppm and were diluted to the concentration with the solvent MeOH.
During the laboratory work the standard for HT-2 toxin arrived, this standard was also analyzed after the rest of the standards to ensure that the method could detect HT-2 toxin. The standard was diluted to 5ppm with MeOH:H2O (1:1) solvent and had an injection volume of 1 µL. The method used in the LC-QTOF were an injection volume of 1.0 µL for the mycotoxins, glyphosate standards, polar metabolites and the SCFA samples. For the PFAS and BA mix an injection volume om 20 µL were used.
The eluent gradient program for the mobile phases A and B was as follows: minute 0-4 the A phase were 100% and B phase 0%. From minute 4-10 A phase changed to 0% and phase B changed to 100%. Minute 10-20 was kept at 100% B. The washing step between the samples were set at 7 minutes and also under that the time the mobile phases were changed back to 100% A. The mycotoxin mixture was run in both negative and positive mode, however the other standards were only run in negative mode.
2.1.4. Test run with plasma samples
The plasma samples were thawed on ice and after that clean up by a protein precipitation. The plasma was vortexed and placed in 4 different Eppendorf tubes with the volume of 30, 50, 70 and 100 µL plasma sample respectively. Three times the plasma volume of ACN with 0.1% formic acid was added.
The samples and the ACN with 0.1% formic acid were vortexed for 1 min and then left for 30 min. The Eppendorf tubes was then centrifuged for three min with the relative centrifugal force (RCF) set at 9000. From the centrifuged tubes all the supernatant except 20 µL was taken and transferred to a LC-vial. The supernatant was evaporated with nitrogen-gas until dryness. The targets were resolved in 60 µL MeOH: H2O (1:1) after the evaporation. The vials were vortexed and then put on to the LC-QTOF with the injection volume set to 5 µL and 15 µL for testing the injection volume in both positive mode and negative mode.
2.1.5. Test run with plasma samples after modification of the protein precipitation and addition of a filtration step
Plasma sample was thawed in ice and 100 µL of the plasma was transferred to an Eppendorf tube, six times the plasma volume of ACN with 0.1 % formic acid was added to the tube This was changed from the previous run. The tube was vortexed and left to stand for 30 min to allow for the protein precipitating to befall. All the liquid from the Eppendorf tubes after the protein precipitation was filtered thru a 13 mm 0.2 µm GHP filter syringe into a LC-vial also this filtration was added from the previous run thus the filtration should give a cleaner extract and thus, a better chromatographic results. The liquid in the LC-vial was evaporated in a nitrogen gas evaporator until dryness. 60 µL in MeOH:H2O (1:1) was added to resolve the analytes. The LC-vials with the samples was then put into the LC. The settings for the LC-run was an injection volume of 15 µL in both negative and positive mode. The time schedule was the same as for the standard run.
2.2. Sample run 2.2.1 LC-MS
The plasma sample that were to be analyzed followed the procedure that was seen to give the best result in the method development and therefore, the parameters and procedure found in section 2.1.5 was used. In this method development the best method was considered to be the one giving a good intensity on the signal without using too much of the meaning having a LOD that was sufficient. The actual LODs were not determined for this method. The shape of the peaks should also not show a large band broadening. Other factors that can be considered then deciding that is the best method could be the sample through-put, i.e. the total analysis time as well as repeatability, the environmental impact factor.
The only change that was made are that from every sample after the protein precipitation and filtration to new LC-vials 5 µL was taken and placed in an Eppendorf tube. Also, to every sample 600 µL of hexanoic acid in the concentration of 0.2 ppm was added as an internal standard.
After the filtration 5 µL was taken from the 30 sample and collected in an Eppendorf tube to make up a pooled sample. The tube with the pooled sample was divided to 3 replicates with 500 µL in each. All samples were analyzed with the LC/Q-TOF method.
All the samples came from the L. Hakolas study and the order of the sample was randomized before the experiment started.
2.2.2. MS/MS
To identify the compounds a MS/MS was performed. A collision cell at 40eV was used to fragment the compounds and thereafter the fragment was detected. The 40 eV were chosen thus it has chosen to be a sufficient energy to fragment the compounds to the product ions that can
be used to identify the compounds. The parameters were based on methods published in literature [23]
Out of the three pooled sample two of them were merge and analyzed again, this time also with the MS/MS settings. This was done in both negative and positive mode and with the injection volume of 15 µL.
The list for the compound, weight, RT and timespan used for the MS/MS can be found in the appendix table 1.1. The settings for the ESI and MS-TOF can be found in table 1.
Table 1. settings for the Dual AJS ESI both in seg and expt, and settings for the MS TOF (expt)
Dual AJS ESI (seg)
Gas Temp 193 °C
Drying Gas 10 l/min
Nebulizer 21 psi
Sheath Gas Temp 379 °C Sheath Gas flow 11 l/min Dual AJS ESI (Expt)
VCap 3643 V Nozzle Voltage 1500 V MS TOF (Expt) Fragmentor 175 V Skimmer 65 V Oct 1 RF Vpp 750 V
3 Result and discussion
The assign target of this report was to develop a method for LC-QTOFMS that was both simple and fast when it comes to preparation of samples. The method should also allow for simultaneous detection of the polar compound e.g. Gly and the semipolar compounds e.g., mycotoxins, by using a mixed mode column for the separation. A task that before has brought some problem thus the two groups of compounds requires different modes to be separated. In addition to developing the method a goal of this report was to identify what mycotoxins and if Gly was present in plasma sample from the L. Hakolans cohort study. As for QA/QC a pooled sample was done from all the samples to see the reparability of the run by calculating mean, standard diviation (STD) and relative standard relativity (RSD) for the run, also hexanoic acid was added as an internal standard. The hexanoic acid was added in a known concentration and could therefore indicate somewhat how large the amounts of found mycotoxins in the samples were. However, it needs to be stated that the exchange of the hexanoic acid and how it was affected by e.g. ion suppression is not known and therefor the indication of the amounts of mycotoxins are not exact or reliable. Blanks and extraction blanks were also analyzed to make sure the samples do not contaminate each other and that the extraction does not contaminate the samples. For the MS/MS the accurate mass was allowed an interval of ± 0.2 from the mass of the fragment reported in earlier studies that used mass resolution instrument.
3.1 Result from standard run
The data from the LC/Q-TOF analyses with standards was transferred into the MZmine software. The results from the run with mycotoxin standard was checked against the blanks to
make sure they had a signal higher than in the blanks. Also, all the blanks were compared to each other to make sure consistent analysis. (see appendix fig, 1.1, 1.2 and 1.3) After that the m/z of the mycotoxin standards was searched for to make sure they were visible and had been correctly separated. Peaks found with the right mass in the mode the mycotoxins could be expected to be found in can be seen in fig. 1, 2, 3. There were good peaks which indicated that the separation of the compounds by the LC worked. This applies for all the components except for the glyphosate (see fig.2).
A separate sample with only glyphosate (10 ppm) was analyzed and the chromatogram of this sample indicated that the method can visualize/separate the glyphosate (see fig 4). Why the glyphosate was separated better in the sample containing only the glyphosate could be that the solvent in the one only containing the glyphosate is a 1:1 mix of MeOH and H2O and thus has a stronger polarity then if the solvent would be 100% MeOH as in the mycotoxin mix [17]. Based on this observation the solvent for the plasma sample was changed to MeOH:H2O (1:1).
Fig 1. Chromatogram of A) HT-2 (425.2634 m/z) in positive mode, B) T2 (465.2784 m/z) in positive mode.
Fig 2. Chromatogram of C) ZEN (317.139 m/z) in negative mode, D) Gly (168.007 m/z) in negative mode.
Fig 3. Chromatogram of E) DON (341.1155 m/z) in negative mode. F) DON-3G (457.1638 m/z) in negative mode.
Fig 4. Chromatogram of Gly (168.007 m/z) in negative mode, from the sample with only Gly.
3.2 Result from plasma sample run
First a comparison of the extraction blanks (ExBlank) from the run was done (see appendix fig. 2.1 and 2.2). Due to an error in the file the extraction blank in positive mode and with an injection volume of 15 µL could not be seen. Instead fig 2.2. in appendix only shows the extraction blank with an injection volume of 5µL in positive mode. Two types of blanks were analyzed, extraction blank which is the ACN with 0.1 % formic acid (the same solvent that is added to the sample then the protein precipitation was done) that was prepared the same were as the samples, these ExBlank indicated if the preparation of the sample gave any contaminations. The solvent blank is a blank added to the instrument to ensure that the samples are not contaminated between each other during the analyze, ex. That they no not bleed over to other samples. The blanks in the negative mode is coherent as well as the positive mode, indicating that the run of the instrument has been stable. When the extraction blank is set up against the plasma sample with the same mode and injection volume it can be seen that also all the sample have a higher intensity then the blank, indicating that the extraction did not resulted in any detectable contaminations. (see appendix fig. 2.3-2.5) A comparison of the plasma
sample against the extraction blank positive mode with an injection volume of 15 µL could not be done due to the error.
3.2.1 Plasma volume
The result from the analyses with different volumes of plasma compared 30, 50, 70 and 100 µL of plasma. The data from the analyses was compared using the same injection volume. The result can be seen in appendix fig. 2.6-2.9.Due to a leakage during the run no data from sample of 100 µL and 15 µL injection volume in negative mode exist. Best results were obtained with the highest plasma volume, indicated by the higher intensity of the peaks and that the peaks still having a satisfactory shape. The conjecture that the concentration of mycotoxin in plasma is to be low are reinforced by this result. Thus, it can be said that the 100 µL plasma volume is the best of the tested volumes.
3.2.2 Injection volume
The LC-MS in screening approach have a higher LOD/LOQ than it would in the SIM mode. For this reason, a test of injection volumes was done to see what volume of injection that should need to be used to have a sufficient signal.
The different injection volumes were compared, the 2 injection volumes tested was 15µL or 5 µL. This comparison will indicate an optimal injection volume for the sample run. However as said due to a leakage in the LC/Q-TOF under the run the sample with 100 µL plasma sample and an injection volume of 15 µL in negative mode were not analyzed instead the data from the 70 µL plasma volume and the 15 µL injection volume negative mode were compared with the 70µL plasma volume 5 µL injection volume in negative mode. The comparison can be seen in fig 5 and for the comparison of the injection volume 15µL and 5µL with 100 µL plasma volume in positive mode in fig 6.
Fig 5. Chromatogram of plasma volume 70 µL and injection volume 5 µL and 15 µL. Both in negative
Fig 6. Chromatogram of plasma volume 100 µL with the injection volume of 5 µL and 15 µL. Both in
positive mode. Blue 100 µL and 5 µL. Red: 100 µL and 15 µL.
The expected concentration of the mycotoxins in the blood plasma is very low and therefore the higher injection volume is expected to give better peaks. When increasing the injection volume, the impact of ESI ion suppression does also increases. Therefor the optimal injection volume has to be a compromise between the desire to have a larger injection to be above the instruments LOD and the impact of the ion suppression. The injection volume of 15 µL seem to be a good compromise thus it gives satisfying intensity of the peaks meaning the ion suppression is not covering the signal. Increased injection volume does also increase the risk of band broadening thus the mixed mode column makes it hard to say how the extraction solvent should be composed to counter the potential band bordering of the compounds eluting first. Also, in this aspect the 15 µL injection volume seems to work. However, in fig 5 and 6 there seems to be some residues as amino acids and proteins from the protein precipitation as the extract was not filtrated after the protein precipitation. Therefore, the method with the alternations explained in section 2.1.5 was applied, adding a higher volume of organic solvent and sample filtration step, to a new 100 µL plasma volume and 15 µL injection volume in negative mode. The result from with sample can be seen in fig. 7.
Fig 7. Chromatogram of samples with 100 µL plasma and injection volumes of 5 µL and 15 µL. Both in negative mode.
The total ion chromatogram from the sample with the added filtration step showed that the peaks had lower intensity then the chromatogram from the unfiltered sample. This is however likely due to the filtration that also remove some of impurities that increased the total peak intensity. The 15 µL injection volume together with the 100 µL plasma volume is considered to be the optimal settings for the sample run.
3.3. Result from sample run
3.3.1. Processed data from MZmine and identified components
The samples that were to be analyzed were provided from L. Hakolas study et.al. mentioned above. The data was processed in the MZmine program and a list of the identified components can be found in the appendix table. 3.1 and 3.2. The list with the components identified with the MZmine software was based on accurate mass of both the target compounds for which standards were available and also a suspect screen list of those mycotoxins that may be present in the samples In the next step, compounds detected at these target masses were selected and analyzed again using a targeted MS/MS mode for identification based on the fragmentation patterns.
Because of the low intensity of the compounds an automatically fragmentation identification program could not be used, instead the fragmentation identification had to be done manually. This was done for all the identified compounds in the list created by the MZmine software. In the list the same compound were sometimes identified more than one time, ex. 5 Beauvericin was tentatively identified. The product ion was looked for in all these and as for Beauvericin the fragment that would validate the identity was only found in one. The identified compounds and their found fragmentation can be seen in table 2 and table 3. The found m/z of the fragment
was allowed to have a deviation of ± 0.2 m/z because of that the instrument is a high-resolution instrument and that that was the mass accuracy of the software.
Only one of the product ions of the compound was found, this is due to the low fragmentations energy that is not sufficient to fragment the compound to greater extent. Still one fragment is in this case enough to conform the identity of the compound.
Three peaks that had a m/z corresponding with ZEN were detected at different RT. When comparing with the standard mix of mycotoxins ZEN seems to have a RT closest to 8.73 of the identified ZEN therefor this can be considered the real compound and therefore the other can be excluded.
For FB1 the data processer identified FB1 two times, however the two identified compounds had almost exactly the same m/z, 722.39 and 722.40 and the same RT, 6.73 and 6.76.
Because a fragment that validated the identity of the compound also was found the two identified compounds can be considered to be one. Therefore, the values representing the intensity of the compounds was added together. The added values can be seen I fig. 3.1 in appendix.
Table 2. Shows the identified compounds in negative mode, their m/z and retention time. It also shows the product ions from the compounds in negative mode, their m/z and retention time in min. If no fragment was found the box is marked Not Found (NF)
Compound m/z RT Fragment
311.0 RT for the fragment
NIV 357.1 10.6 311.1 10.60
Compound m/z RT Fragment
317.0 RT for the fragment
Fragment
299 RT for the fragment
Zearalenone 317.1 8.43 316.9 8,39 NF NF
Zearalenone 317.1 8.15 317.0 8.18 299.0 8.18
Zearalenone 317.1 8.73 316.9 8.80 NF NF
Table 3. shows the identified compounds in positive mode, their m/z and retention time. It also shows the product ions from the compounds in positive mode, their m/z and retention time in min.
Compound m/z RT Fragment
352.2 RT for the fragment
FB1 722.3 6.76 352.2 6.70
FB1 722.3 6.73 352.2 6.70
Compound m/z RT Fragment
152.0 RT for the fragment
Glyphoshate 170.0 1.72 152.0 1.70
Compound m/z RT Fragment
285.1 RT for the fragment
HT-2 425.2 6.68 285.1 6.70
Compound m/z RT Fragment
523.3 RT for the fragment
Beauvericin 783.4 8.20 523.3 8.20
Compound m/z RT Fragment
279.1 RT for the fragment
Compound m/z RT Fragment 564.1 RT for the fragment
Ergotaminine/ergotamine 581.3 8.14 564.3 8.10
3.3.2. Identified compounds
The compounds that had their identify confirmed with a fragment of the product ion found was compared against the samples to see which samples contained which mycotoxins and glyphosate. The value representing the intensity of the compounds signal was compared with the mean of the extraction blanks to ensure that the signal was > 3 times higher than the background noise. The values and mean of the extraction blank can be found in appendix table 3.3 and the sample compared with the blanks in fig. 3.1 and 3.2 in the appendix. In positive mode when summarized, all the sample contain an amount of glyphosate that is higher than the blank. Almost all the samples contained ergotaminine/ergotamine. The more infrequent compounds are Beauvericin, FB1 and HT-2. Even though DON-3 was identified both by accurate mass and fragment from the product ions, it was found that the signal was in a similar level as in the blanks and thus it is considered to be background noise, see table 4.
The samples analyzed in negative mode are summarized in table 5, NIV was found like Gly to be present in all the samples and ZEN not having an intensity higher the background noise.
Table 4. The identified compounds that had a signal higher than blank and in how many of the 30 samples they were found. Positive mode.
Compounds Found in Beauvericin 1/30 DON-3G 0/30 Ergotaminine/ergotamine 25/30 FB1 10/30 Gly 30/30 HT-2 2/30
Table 5. The identified compounds that had a signal higher than blank and in how many of the 30 samples they were found. Negative mode.
Compound Found in
NIV 30/30
ZEN 0/30
It should be noted that a result that indicates that the compound is not present in the plasma sample does not prove that the compound is totally absent thus the concentration of the mycotoxins in the plasma is over all low. It can only be said that in those cases the presence of the mycotoxins is very low. To use a MS/MS in SIM mode could make the detection of these compounds possible thus the sensitivity of the instrument thus could increase.
3.3.3 Hexanoic acid as an internal standard.
Hexanoic acid was added to all the samples as QA/QC and a peak were identified with the approximately the right m/z and RT that correlates with hexanoic acid. To ensure that the suspected component is hexanoic acid a comparison of the same sample in negative mode and positive mode was done. (see appendix fig. 4.1) The fact that a clear peak can be seen in
negative mode and the peak in positive mode is absent correlates with earlier studies that shows that hexanoic acid will be found in negative mode. [24]
The component identified using the Mzmine program are present in all the samples (negative mode) however, the intensity of the signal of the compound in extraction blank is remarkably lower.
The identity of the identified mycotoxins is relatively low thus they are all have an intensity under 55 000. When looking at the mycotoxin standard that were analyzed they were added in the concentration of 5 ppm and gave intensity from 1500 to 110 000. However, this large span of the intensity indicates that there is some ion suppression decreasing the signal for some of the compounds. The levels of mycotoxins in the plasma samples are however to be considered relatively low.
3.3.4 Quality control sample
The pooled sample analyzed in both negative and positive mode, however pooled sample 1 in positive mode was not injected correctly and the result from this sample has therefor been excluded. The chromatogram with all the 3 pooled sample in positive mode can be seen in fig 5.1 in appendix as well as the chromatogram with only pooled sample 2 and 3 in positive mode can be seen in fig 5.2 in appendix. The chromatogram of the two pooled sample in positive mode and the three samples in negative mode (see fig.5.3 in appendix) is an indication of how stable the instrument has been under the run thus the sample shall be the same and therefor also the result shall be similar. However, some variation does occur this is probably due to that only two replicates were used for the calculations of these means, STD and RSD and that the peak of glyphosate even after the change in solvent has some band broadening. This can add to the variation. After processing of the data from the pooled sample the average (mean), standard deviation (STD) and relative standard deviation (RSD) can be calculated (see table 7 for the pooled sample analyzed in positive mode and table 8 for the mycotoxin analyzed in the pooled sample in negative mode.)
Table 7. Values from pooled samples 2 and 3, their mean, STD and RSD for the mycotoxins analyzed in positive mode.
Pooled 2 Pooled 3 mean STD RSD (%) Beauvericin 339 E+02 387 E+02 363 E+02 242 E+01 6.7
DON-3G 165 E+01 298 E+01 231 E+01 666 28.8
Ergotaminine/ergotamine 451 E+01 244 E+01 347 E+01 104 E+01 29.9
FB1 197 E+02 149 E+02 173 E+02 241 E+01 13.9
Gly 189 E+02 118 E+01 100 E+02 887 E+01 88.3
HT-2 969 829 899 70.0 7.80
Table 8. Values from pooled sample 2 and 3, their mean, STD and RSD for the mycotoxins analyzed in negative mode.
Pooled 1 Pooled 2 Pooled 3 mean STD RSD (%) NIV 670 E+01 902 E+01 836 E+01 803 E+01 977 12.2
4. Conclusions
The developed method has the capacity to detect the tested mycotoxins in both negative and positive mode. The pooled samples show some variation in the results. Some of the mycotoxins having a satisfying RSD and some having an extremely large RSD. Of the mycotoxins that was tested with the standard (ZEN, DON, DON-3G, T-2, HT-2) only HT-2 has found and having an intensity higher than the background noise in the plasma samples. However, both ZEN and DON-3G were identified as being present also with the MS/MS, yet in low amounts. In addition to the mycotoxins, glyphosate was also found to have an intensity higher than the background noise. Glyphosate was also found in all the plasma samples, however the variation within pooled samples was quite large and therefor some samples may contain noteworthy amounts of glyphosate in contrast to other that were just above the background noise. Whether a large amount of glyphosate or the present of HT-2 in the blood has some impact of the progress of T1D and IA is still unknown and further studies has to be done in this field.
The mycotoxins identified in our analyses that is commonly found on cereals was also checked for in the plasma samples and among these NIV, Beauvericin, Ergotaminine and FB1 was identified. NIV and Ergotaminine had in the most samples a satisfying intensity, and FB1 and Beauvericin had an intensity higher than the background in some cases.
To conclude the report, the LC-QTOF method developed has a good capacity of separating mycotoxins in plasma. The MS/MS could identify some mycotoxins, overall the amount of the mycotoxins was low but some variation between the samples did occur. The RSD from the pooled sample did varied much for some compounds and for some other it was as low as 6.7 % Together with the study from L. Hakolas that found that a diet containing high amounts of oats, wheat, rye, gluten-containing cereals, gluten and dietary fiber increases the risk of IA, it is now also clear that the plasma from the studied children do contains above mentioned mycotoxins and glyphosate. The mechanism of how these mycotoxins and glyphosate work and can affect the progress of T1D 1 and IA in patients with genetic risk of T1D is still to be found out.
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Acknowledgment
I would like to thank everybody at the MTM department. I would like to address a special thanks to Daniel Duberg for the help and support during my lab work. I would also like to thanks my supervisor Tuulia Hyötyläinen who has advised me and helped my throw the hole work. Thanks to you both for making me more comfortable and confident with this report.
Appendix
Table 1.1. Shows the list of the parameters used for the MS/MS run with the L. Hakolas sample.
Negative
mode Prec. m/z Z Ret. Time (min) Delta Ret. Time (min) Iso. Width Collision Energy Acquisition Time (ms/spec) 319.1614 1 6.00 0.25 Narrow (~1.3 m/z) 20 200 383.1377 1 11.17 0.25 Narrow (~1.3 m/z) 20 200 383.1328 1 7.83 0.25 Narrow (~1.3 m/z) 20 200 383.132 1 8.00 0.25 Narrow (~1.3 m/z) 20 200 322.0133 1 0.70 0.25 Narrow (~1.3 m/z) 20 200 184.0578 1 2.18 0.25 Narrow (~1.3 m/z) 20 200 295.0135 1 7.78 0.25 Narrow (~1.3 m/z) 20 200 341.1258 1 6.13 0.25 Narrow (~1.3 m/z) 20 200 457.1707 1 6.06 0.25 Narrow (~1.3 m/z) 20 200 235.9827 1 2.55 0.25 Narrow (~1.3 m/z) 20 200 235.9821 1 2.64 0.25 Narrow (~1.3 m/z) 20 200 399.1337 1 10.61 0.25 Narrow (~1.3 m/z) 20 200 399.1232 1 6.37 0.25 Narrow (~1.3 m/z) 20 200 357.1208 1 10.47 0.25 Narrow (~1.3 m/z) 20 200 357.1197 1 10.60 0.25 Narrow (~1.3 m/z) 20 200 357.1197 1 10.59 0.25 Narrow (~1.3 m/z) 20 200 583.0974 1 7.35 0.25 Narrow (~1.3 m/z) 20 200 465.210349346826 1 6.13 0.25 Narrow (~1.3 m/z) 20 200 465.210004173596 1 7.82 0.25 Narrow (~1.3 m/z) 20 200 317.139580079199 1 8.43 0.25 Narrow (~1.3 m/z) 20 200 317.140266419617 1 8.35 0.25 Narrow (~1.3 m/z) 20 200 317.138529100573 1 8.15 0.25 Narrow (~1.3 m/z) 20 200 317.139322342348 1 8.73 0.25 Narrow (~1.3 m/z) 20 200 Positive mode
Prec. m/z Z Ret. Time (min) Delta Ret.
Time (min) Iso. Width Collision Energy Acquisition Time (ms/spec) 373.19898155408 1 8.37 0.25 Narrow (~1.3 m/z) 20 200 238.146606399073 1 6.00 0.25 Narrow (~1.3 m/z) 20 200 783.415839955163 1 8.48 0.25 Narrow (~1.3 m/z) 20 200 783.416030704766 1 8.20 0.25 Narrow (~1.3 m/z) 20 200 783.416974385515 1 8.54 0.25 Narrow (~1.3 m/z) 20 200 783.417867101538 1 8.25 0.25 Narrow (~1.3 m/z) 20 200 783.417959453713 1 8.39 0.25 Narrow (~1.3 m/z) 20 200 283.131591796875 1 8.64 0.25 Narrow (~1.3 m/z) 20 200
336.144253990652 1 7.34 0.25 Narrow (~1.3 m/z) 20 200 297.13343974174 1 8.78 0.25 Narrow (~1.3 m/z) 20 200 297.133360418793 1 8.97 0.25 Narrow (~1.3 m/z) 20 200 297.133588445212 1 6.96 0.25 Narrow (~1.3 m/z) 20 200 297.128125508626 1 5.95 0.25 Narrow (~1.3 m/z) 20 200 297.133230035955 1 6.22 0.25 Narrow (~1.3 m/z) 20 200 297.132233288823 1 6.76 0.25 Narrow (~1.3 m/z) 20 200 297.136726531721 1 10.68 0.25 Narrow (~1.3 m/z) 20 200 297.133357892306 1 8.99 0.25 Narrow (~1.3 m/z) 20 200 343.136493476123 1 7.03 0.25 Narrow (~1.3 m/z) 20 200 343.136473609853 1 7.61 0.25 Narrow (~1.3 m/z) 20 200 343.136661529541 1 6.11 0.25 Narrow (~1.3 m/z) 20 200 343.134989384242 1 6.54 0.25 Narrow (~1.3 m/z) 20 200 459.183581160319 1 7.40 0.25 Narrow (~1.3 m/z) 20 200 459.185729980468 1 6.09 0.25 Narrow (~1.3 m/z) 20 200 459.183185336632 1 6.98 0.25 Narrow (~1.3 m/z) 20 200 547.271614638232 1 6.98 0.25 Narrow (~1.3 m/z) 20 200 547.271909347539 1 6.80 0.25 Narrow (~1.3 m/z) 20 200 547.278074919339 1 9.06 0.25 Narrow (~1.3 m/z) 20 200 547.273504676848 1 6.80 0.25 Narrow (~1.3 m/z) 20 200 581.256867893928 1 7.68 0.25 Narrow (~1.3 m/z) 20 200 581.260287437909 1 6.75 0.25 Narrow (~1.3 m/z) 20 200 581.256182789962 1 8.14 0.25 Narrow (~1.3 m/z) 20 200 581.256855132291 1 7.65 0.25 Narrow (~1.3 m/z) 20 200 722.399762471517 1 7.91 0.25 Narrow (~1.3 m/z) 20 200 722.400706869348 1 7.54 0.25 Narrow (~1.3 m/z) 20 200 722.401097105929 1 9.00 0.25 Narrow (~1.3 m/z) 20 200 722.399660323813 1 9.02 0.25 Narrow (~1.3 m/z) 20 200 722.396796005491 1 6.76 0.25 Narrow (~1.3 m/z) 20 200 722.403599765568 1 8.74 0.25 Narrow (~1.3 m/z) 20 200 722.40525606726 1 8.43 0.25 Narrow (~1.3 m/z) 20 200 722.401965421822 1 8.83 0.25 Narrow (~1.3 m/z) 20 200 722.403109805809 1 8.54 0.25 Narrow (~1.3 m/z) 20 200 722.402861159896 1 7.56 0.25 Narrow (~1.3 m/z) 20 200 722.38598306776 1 6.73 0.25 Narrow (~1.3 m/z) 20 200 706.399666756079 1 8.41 0.25 Narrow (~1.3 m/z) 20 200 706.398891023088 1 8.57 0.25 Narrow (~1.3 m/z) 20 200 706.398836371625 1 8.71 0.25 Narrow (~1.3 m/z) 20 200 706.398117693026 1 8.80 0.25 Narrow (~1.3 m/z) 20 200
706.404543970276 1 7.81 0.25 Narrow (~1.3 m/z) 20 200 706.403832621618 1 7.65 0.25 Narrow (~1.3 m/z) 20 200 706.396599301424 1 8.90 0.25 Narrow (~1.3 m/z) 20 200 706.407883839469 1 7.66 0.25 Narrow (~1.3 m/z) 20 200 706.410632424787 1 8.19 0.25 Narrow (~1.3 m/z) 20 200 706.403562966124 1 8.14 0.25 Narrow (~1.3 m/z) 20 200 706.39970560978 1 8.42 0.25 Narrow (~1.3 m/z) 20 200 721.397925676618 1 7.55 0.25 Narrow (~1.3 m/z) 20 200 721.395575055256 1 7.53 0.25 Narrow (~1.3 m/z) 20 200 721.397368316294 1 9.03 0.25 Narrow (~1.3 m/z) 20 200 721.39281198007 1 9.33 0.25 Narrow (~1.3 m/z) 20 200 721.389189212985 1 9.14 0.25 Narrow (~1.3 m/z) 20 200 721.385107446095 1 9.30 0.25 Narrow (~1.3 m/z) 20 200 705.39743166558 1 8.41 0.25 Narrow (~1.3 m/z) 20 200 705.396920590624 1 8.58 0.25 Narrow (~1.3 m/z) 20 200 705.402172660189 1 7.76 0.25 Narrow (~1.3 m/z) 20 200 705.398417089594 1 8.74 0.25 Narrow (~1.3 m/z) 20 200 705.403947475009 1 8.25 0.25 Narrow (~1.3 m/z) 20 200 705.395082718355 1 8.41 0.25 Narrow (~1.3 m/z) 20 200 705.394853963236 1 8.72 0.25 Narrow (~1.3 m/z) 20 200 705.404549195323 1 8.22 0.25 Narrow (~1.3 m/z) 20 200 705.395058993078 1 8.38 0.25 Narrow (~1.3 m/z) 20 200 705.395211830016 1 7.76 0.25 Narrow (~1.3 m/z) 20 200 705.397180453968 1 7.51 0.25 Narrow (~1.3 m/z) 20 200 705.396700301071 1 8.48 0.25 Narrow (~1.3 m/z) 20 200 705.388411510138 1 8.99 0.25 Narrow (~1.3 m/z) 20 200 170.012314681107 1 1.65 0.25 Narrow (~1.3 m/z) 20 200 170.012396057837 1 1.56 0.25 Narrow (~1.3 m/z) 20 200 170.018688548694 1 2.51 0.25 Narrow (~1.3 m/z) 20 200 170.01234242119 1 1.72 0.25 Narrow (~1.3 m/z) 20 200 170.012329796412 1 1.66 0.25 Narrow (~1.3 m/z) 20 200 170.012328467522 1 1.62 0.25 Narrow (~1.3 m/z) 20 200 170.012434917961 1 1.58 0.25 Narrow (~1.3 m/z) 20 200 425.212501846872 1 8.13 0.25 Narrow (~1.3 m/z) 20 200 425.213846451196 1 9.83 0.25 Narrow (~1.3 m/z) 20 200 425.224475839066 1 6.68 0.25 Narrow (~1.3 m/z) 20 200 424.217834886101 1 6.68 0.25 Narrow (~1.3 m/z) 20 200 424.217899300923 1 6.89 0.25 Narrow (~1.3 m/z) 20 200 424.217498695607 1 8.42 0.25 Narrow (~1.3 m/z) 20 200
312.130321813851 1 5.96 0.25 Narrow (~1.3 m/z) 20 200 493.26206926142 1 6.92 0.25 Narrow (~1.3 m/z) 20 200 493.262758597823 1 8.71 0.25 Narrow (~1.3 m/z) 20 200 493.247330983479 1 5.98 0.25 Narrow (~1.3 m/z) 20 200 389.180808058518 1 6.12 0.25 Narrow (~1.3 m/z) 20 200 389.179136518998 1 7.70 0.25 Narrow (~1.3 m/z) 20 200 389.17846579544 1 6.53 0.25 Narrow (~1.3 m/z) 20 200 389.178573787851 1 6.98 0.25 Narrow (~1.3 m/z) 20 200 467.226225211876 1 7.86 0.25 Narrow (~1.3 m/z) 20 200 467.226358740802 1 7.86 0.25 Narrow (~1.3 m/z) 20 200 467.225534934318 1 8.23 0.25 Narrow (~1.3 m/z) 20 200 467.225823708736 1 6.52 0.25 Narrow (~1.3 m/z) 20 200 467.225695424065 1 6.91 0.25 Narrow (~1.3 m/z) 20 200 467.228129917856 1 9.34 0.25 Narrow (~1.3 m/z) 20 200 484.257094214062 1 8.37 0.25 Narrow (~1.3 m/z) 20 200 484.254256450309 1 9.34 0.25 Narrow (~1.3 m/z) 20 200
Fig 1.2. Chromatogram of mycotoxin mix std. and blank in negative mode. Blue: blank. Red: mycotoxin
Fig 2.1. Chromatogram of the two extraction blanks with the injection volume 5 µL and 15µL in negative
mode. Blue: 5 µL. Red: 15 µL
Fig 2.3. Chromatogram of extraction blank for injection volume 5 µL and all the plasma sample with
injection volume of 5 µL in negative mode. Blue: extraction blank. Red: 30 µL. Green: 50 µL. Pink: 70
µL. Turquoise: 100 µL.
Fig 2.4. Chromatogram of extraction blank for injection volume 15 µL and all the plasma sample with
injection volume of 15 µL in negative mode. Blue: 30 µL. Red: 50 µL. Green: 70 µL. Pink: extraction
Fig 2.5. Chromatogram of extraction blank for injection volume 5 µL and all the plasma sample with
injection volume of 5 µL in positive mode. Blue: Extraction blank. Red: 30 µL. Green: 50 µL. Pink: 70
Fig 2.6. Chromatogram of sample with injection volume 5 µL and the plasma volume of 30, 50, 70 and
100 µL. All in negative mode. Blue: 30 µL. Red: 50 µL. Green: 70 µL Pink: 100 µL
Fig 2.7. Chromatogram of sample with injection volume 15 µL and the plasma volume of 30, 50, 70 µL.
Fig 2.8. Chromatogram of sample with injection volume 5 µL and the plasma volume of 30, 50, 70 and
100 µL. All in positive mode. Blue: 30 µL. Red: 50 µL. Green: 70 µL. Pink 100 µL.
Fig 2.9. Chromatogram of sample with injection volume 15 µL and the plasma volume of 30, 50, 70 and
100 µL. All in positive mode. Blue:30 µL. Red: 50 µL. Green: 70 µL. Pink: 100 µL.
Tabel 3.1. Showing identified compounds in negative mode in the LC-QTOF run with the samples from the L. Hakola study.
m/z Ret. Time (min) ID
383 11.2 3-ADON 383 7.83 3-ADON 383 8.00 3-ADON 322 0.70 Chloramphenicol 184 2.18 Chlorothymol 295 7.78 Diclofenac 341 6.13 DON 457 6.06 DON-3G 236 2.55 Ferpiconil 236 2.64 Ferpiconil 399 10.6 FUS-X 399 6.37 FUS-X 357 10.5 NIV 357 10.6 NIV 357 10.6 NIV 583 7.35 Skyrin 465 6.13 T-2 465 7.82 T-2
317 8.43 Zeaealeone
317 8.35 Zeaealeone
317 8.15 Zeaealeone
317 8.73 Zeaealeone
Table 3.2. Showing identified compounds in positive mode in the LC-QTOF run with the samples from the L. Hakola study.
m/z Rent.Time (min) ID 373 8.37 16-keto-aspergillimide 238 6.00 Agroclavine 783 8.48 Beauvericin 783 8.20 Beauvericin 783 8.54 Beauvericin 783 8.25 Beauvericin 783 8.39 Beauvericin 283 8.64 Brevianamid F 336 7.34 Cyclopiazonic acid 297 8.78 Deoxynivalenol 297 8.97 Deoxynivalenol 297 6.96 Deoxynivalenol 297 5.95 Deoxynivalenol 297 6.22 Deoxynivalenol 297 6.76 Deoxynivalenol 297 10.68 Deoxynivalenol 297 8.99 Deoxynivalenol 343 7.03 DON 343 7.61 DON 343 6.11 DON 343 6.54 DON 459 7.40 DON-3G 459 6.09 DON-3G 459 6.98 DON-3G 547 6.98 Ergosine 547 6.80 Ergosine 547 9.06 Ergosine 547 6.80 Ergosine 581 7.68 Ergotaminine/ergotamine 581 6.75 Ergotaminine/ergotamine 581 8.14 Ergotaminine/ergotamine 581 7.65 Ergotaminine/ergotamine 722 7.91 FB1 722 7.54 FB1 722 9.00 FB1 722 9.02 FB1
722 6.76 FB1 722 8.74 FB1 722 8.43 FB1 722 8.83 FB1 722 8.54 FB1 722 7.56 FB1 722 6.73 FB1 706 8.41 FB2 706 8.57 FB2 706 8.71 FB2 706 8.80 FB2 706 7.81 FB2 706 7.65 FB2 706 8.90 FB2 706 7.66 FB2 706 8,19 FB2 706 8.14 FB2 706 8.42 FB2 170 1.65 glyphoshate 170 1.56 glyphoshate 170 2.51 glyphoshate 170 1.72 glyphoshate 170 1.66 glyphoshate 170 1.62 glyphoshate 170 1.58 glyphoshate 425 8.13 HT-2 425 9.83 HT-2 425 6.68 HT-2 312 5.96 Nivalenol 493 6.92 Paraherquamide A 493 8.71 Paraherquamide A 493 5.98 Paraherquamide A 389 6.12 Roquefortine C 389 7.70 Roquefortine C 389 6.53 Roquefortine C 389 6.98 Roquefortine C 467 7.86 T-2 467 7.86 T-2 467 8.23 T-2 467 6.52 T-2 467 6.91 T-2 467 9.34 T-2 484 8.37 T-2 ammonium adduct 484 9.34 T-2 ammonium adduct
Fig 3.1. Showing the table over which sample containing which compounds in positive mode. The sample having a more intense signal of the mycotoxins, HT-2, FB1, Ergotamini, Beauvericin and Gly then the extraction blank mean is marked with green.
Table 3.3. Values representing the intensity of the extraction blanks and the mean of the blank. In positive mode.
Identified compounds ExBlank1 ExBlank2 ExBlank3 Mean of blanks
Beauvericin 880 E+02 690 E+02 393 E+02 654 E+02
DON-3G 529 E+01 524 E+01 399 E+01 484 E+01
Ergotaminine/ergotamine 163 E+01 170 E+01 440 126 E+01
FB1 265 E+01 270 E+01 636 E+01 390 E+01
FB1 303 E+02 250 E+02 175 E+02 243 E+02
glyphoshate 0,00 108 0,00 36,1
Fig 3.2. Showing the table over which sample containing which compounds in negative mode. The sample having a more intense signal of the mycotoxins, NIV, ZEN then the extraction blank mean is marked with green.
Fig.4.1. Chromatogram of the m/z for what probably Hexanoic acid in both positive and negative mode. Blue:negative mode. Red: positive mode
Fig 5.1. Chromatogram of pooled sample 1,2 and 3 in positive mode. Blue: pooled sample 3. Red: pooled sample 2. Green: pooled sample 1.
Fig 5.2. Chromatogram of pooled sample 2 and 3 in positive mode. Blue: pooled sample 3. Red: pooled sample 2.
Fig,5.3. Chromatogram of the three pooled sample 1,2 and 3. All in negative mode. Blue: pooled sample 3. Red: pooled sample 2. Green: pooled sample 1.
