the behaviour of deoxynivalenol and deoxynivalenol-3...
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GHENT UNIVERSITY
FACULTY OF PHARMACEUTICAL
SCIENCES
Department of Bioanalysis
Laboratory of Food Analysis
Master thesis performed at:
WAGENINGEN UNIVERSITY
RIKILT – Institute of Food Safety
BU – Contaminants and Toxins
Academic year 2012-2013
The behaviour of deoxynivalenol and
deoxynivalenol-3-glucoside during the
baking process
Merel WAEYAERT First Master in Pharmaceutical Sciences: Drug Development
Promotor
Prof. dr. S. De Saeger
Co-promotor
Dr. ir. M. De Nijs
Commissioners
Dr. C. Van Poucke
Dr. J. Diana Di Mavungu
COPYRIGHT
"The author and the promoters give the authorization to consult and to copy parts of this thesis
for personal use only. Any other use is limited by the laws of copyright, especially concerning
the obligation to refer to the source whenever results from this thesis are cited."
Promotor Author
Prof. dr. S. De Saeger Merel Waeyaert
Co-promotor
Dr. ir. M. De Nijs
SUMMARY
Fusarium species (fungi), which grow mainly on crops, cause plant diseases such as
Fusarium head blight (wheat) and Fusarium ear rot (maize). They are able to produce
mycotoxins, which are harmful for the host plant and the animals and humans which consume
these plants. One of these mycotoxins is deoxynivalenol, which causes vomiting, diarrhoea
and nausea when administrated once to animals. In long-term animal experiments, anorexia,
food refusal and immunosuppression was found. Deoxynivalenol has also been linked to
epidemic outbreaks of gastroenteritis-like symptoms among humans after the consumption of
mouldy cereals.
Infected plants have developed defence mechanisms against mycotoxins. One of these is
the metabolisation of the parent molecule to a less toxic derivative. Deoxynivalenol is mainly
converted to deoxynivalenol-3-glucoside and stored in the plant. This derivative is probably
less toxic than deoxynivalenol for the host and consequently for animals and humans. There
is, however, the possibility that deoxynivalenol-3-glucoside might be converted to
deoxynivalenol during processing of the cereals.
This study was elaborated to ascertain the fate of deoxynivalenol and deoxynivalenol-3-
glucoside during bread-making when present in flour. As deoxynivalenol or deoxynivalenol-
3-glucoside might be captured in the matrix during processing, where it would evade
detection, enzymes were used to destroy the matrix. Next liquid chromatography in
combination with tandem mass spectrometry was used to quantitatively determine the
mycotoxins.
The first part of the study was completed, namely to devise an extraction method and to
research the effect of enzymatic matrix digestion on flour. The extraction solvent with the
highest recoveries and least interference for both analytes was acetonitrile and water (50:50,
v:v) with a 1:1 (v:v) dilution with water before injection. Recovery for deoxynivalenol ranged
between 70% and 80%. The recovery of deoxynivalenol-3-glucoside fluctuated during the
study from 60%-70% to 120%. No satisfying cause for this phenomenon was discovered;
degradation of the analyte under these particular circumstances cannot be ruled out. For the
flour matrix, enzymatic matrix digestion did not heighten the recovery of either analyte.
Further research must discover if it might be of use in further steps of the bread-making
process.
SAMENVATTING
Fusarium species infecteren voornamelijk granen, zowel voor als na de oogst. Daar
veroorzaken ze verschillende plantenziektes zoals fusariumrot, zowel in tarwe als mais. Deze
fungi produceren ook mycotoxines, die gevaarlijk zijn voor de gastheerplant, dieren en
mensen. Een hiervan is deoxynivalenol. Als deze stof eenmalig wordt toegediend aan dieren,
veroorzaakt het nausea, braken en diarree. In lange termijnstudies vertoonden de dieren
verlaagde voedselopname, anorexia en waren meer vatbaar voor infecties. Verschillende
plotse epidemieën waarbij mensen gastro-intestinale symptomen vertoonden zijn gelinkt aan
het eten van beschimmeld graan dat deoxynivalenol bevatte.
Geïnfecteerde planten hebben een aantal verdedigingsmechanismen tegen mycotoxines.
Een mogelijkheid is de omzetting van de moedermolecule naar een minder toxisch derivaat.
deoxynivalenol wordt grotendeels omgezet naar deoxynivalenol-3-glucoside en vervolgens
opgeslagen in de plant. Deze afgeleide molecule is waarschijnlijk niet alleen minder giftig
voor de plant, maar ook voor dieren en mensen. Het is echter mogelijk dat door bewerking
van de granen deoxynivalenol-3-glucoside weer wordt afgebroken tot deoxynivalenol.
Het doel van deze studie was het vaststellen van het lot van deoxynivalenol en
deoxynivalenol-3-glucoside als bloem tot brood wordt verwerkt wanneer de mycotoxines in
het bloem aanwezig zijn. Het kan niet uitgesloten worden dat deoxynivalenol of
deoxynivalenol-3-glucoside gecapteerd wordt in de matrix gedurende dit proces. Daarom
werden enzymen toegevoegd om de matrix te verteren. Vervolgens werden de mycotoxines
gemeten met vloeistof chromatografie gekoppeld aan tandem massa spectrometrie.
De extractiemethode en de enzymatische matrixvertering op meel werden onderzocht. Het
extractiesolvent met de beste resultaten voor beide onderzochte stoffen, zowel op het vlak van
terugvinding als interferentie, was een mix van acetonitrile en bufferoplossing in een (50:50,
v:v) verhouding, die vervolgens met water 1:1 (v:v) verdund werd. De terugvinding voor
deoxynivalenol was tussen de 70% en 80%. De terugvinding van deoxynivalenol-3-glucoside
fluctueerde sterk gedurende de studie: er trad bijna een verdubbeling op van 60%-70% naar
ongeveer 120%. Geen duidelijke oorzaak kon gevonden worden, maar het is mogelijk dat de
stof onder deze omstandigheden langzaam werd afgebroken. Enzymatische matrixvertering
verhoogde de terugvinding niet in bloem. Verder onderzoek zal uitwijzen of deze methode
nuttig is in verdere stappen van het broodbereidingsproces.
Ik zou graag iedereen bedanken die mij heeft geholpen gedurende het maken van deze
masterproef.
Mijn begeleider Monique, die ondanks haar drukke schema erin slaagde tijd voor mij vrij te
maken en voor de verbeteringen aan het finale werk.
Hester Van den Top, voor haar dagelijkse begeleiding op het labo, haar vrolijkheid en goede
uitleg.
Mijn medestagiairs, voor de gezelligheid en ontspanning: Susannah, Pieter, Larissa, Tjeerd,
Sander, Robbert, Stéphanie, Marlène en Maarten.
Mijn ouders en zus, die, hoewel ze niet lichamelijk aanwezig waren, mentaal een grote steun
waren.
TABLE OF CONTENTS
COPYRIGHT
SUMMARY
SAMENVATTING
ACKNOWLEDGEMENTS
TABLE OF CONTENTS
LIST OF ABBREVIATIONS
1. INTRODUCTION ........................................................................................................... 1
1.1. MYCOTOXINS ........................................................................................................... 1
1.1.1. Deoxynivalenol ....................................................................................................... 1
1.1.2. Deoxynivalenol-3-glucoside ................................................................................... 3
1.2. INFLUENCES OF PROCESSING ............................................................................. 5
1.2.1. The chemistry behind the recipe .......................................................................... 6
1.2.2. The influence of secondary processing on DON and D3G ................................. 7
1.2.2.1. The influence of secondary processing on DON .............................................. 7
1.2.2.2. The influence of secondary processing on D3G ............................................. 10
1.3. ANALYSIS OF DON AND D3G IN THE BREAD MATRIX ................................ 11
1.3.1. Matrix digestion ................................................................................................... 11
1.3.1.1. Peptidase K ..................................................................................................... 12
1.3.1.2. α-Amylase ....................................................................................................... 12
1.3.1.3. Triacylglycerol lipase ..................................................................................... 13
1.3.2. Extraction and clean-up of DON and D3G ........................................................ 14
1.3.3. Analysis of DON and D3G .................................................................................. 15
2. OBJECTIVES ................................................................................................................ 17
3. MATERIALS AND METHODS .................................................................................. 19
3.1. REAGENTS .............................................................................................................. 19
3.1.1. Chemicals .............................................................................................................. 19
3.1.2. Standards .............................................................................................................. 19
3.1.3. Enzymes ................................................................................................................ 19
3.1.4. Buffer .................................................................................................................... 20
3.2. COLLECTION OF THE SAMPLES ........................................................................ 20
3.3. SAMPLE PREPARATION ....................................................................................... 20
3.3.1. Sample digestion ................................................................................................... 20
3.3.2. Extraction method ............................................................................................... 21
3.4.1. Standard series ..................................................................................................... 21
3.4.2. Mobile phases ....................................................................................................... 21
3.4.3. LC conditions ....................................................................................................... 22
3.4.4. Mass spectrometry ............................................................................................... 22
3.4.5. Calculations and estimation of the margins of error ........................................ 22
4. RESULTS ....................................................................................................................... 26
4.1. OPTIMISATION OF THE EXTRACTION METHOD ........................................... 26
4.2. OPTIMISATION OF THE MATRIX DIGESTION ................................................. 28
4.2.1. Recovery of DON ................................................................................................. 28
4.2.2. Recovery of D3G .................................................................................................. 29
5. DISCUSSION ................................................................................................................. 32
5.1. EXTRACTION METHOD ........................................................................................ 32
5.2. ENZYME MATRIX DIGESTION ........................................................................... 33
6. CONCLUSIONS ............................................................................................................ 35
7. LITERATURE LIST/REFERENCES ......................................................................... 37
LIST OF ABBREVIATIONS
15C13 DON Fully C13-labelled deoxynivalenol
3-ADON 3-acetyldeoxynivalenol
15-ADON 15-acetyldeoxynivalenol
ANOVA Analysis of Variance
AOAC Association of Analytical Communities
BRENDA Braunschweig Enzyme Database
D3G Deoxynivalenol-3-glucoside
DNA Deoxyribonucleic acid
DON Deoxynivalenol
DON-GlcA Deoxynivalenol-glucuronide
ECD Electron Capture Detection
EDTA Ethylenediaminetetraacetic Acid
ELISA Enzyme-Linked Immuno Sorbent Assay
ESI Electrospray Ionisation
FAO Food and Agriculture Organisation
GC Gas Chromatography
HPLC High Performance Liquid Chromatography
HSS High Strength Silica
IA(C) Immunoaffinity (Column)
IARC International Agency for Research on Cancer
IgA Immunoglobulin A
IUBMB International Union of Biochemistry and Molecular Biology
JECFA Joint FAO/WHO Expert Committee on Food Additives
LC Liquid Chromatography
LoD Limit of Detection
LoQ Limit of Quantification
LSC Liquid Solid Chromatography
MRM Multiple Reaction Monitoring
MS Mass Spectrometry
m/z Mass-to-charge ratio
PBS Phosphate Buffered Saline
PMTDI Provisional Maximum Tolerable Daily Intake
QuEChERS Quick, Easy, Cheap, Effective, Rugged, and Safe
RNA Ribonucleic Acid
SCOOP Scientific Cooperation
SD Standard Deviation
S/N Signal-to-Noise ratio
SPE Solid Phase Extraction
TIC Total Ion Chromatogram
UPLC Ultra-high Performance Liquid Chromatography
UV Ultraviolet Detection
WHO World Health Organisation
1
1. INTRODUCTION
1.1. MYCOTOXINS
All through history, there have been incidents of mycotoxicoses, diseases caused by
mycotoxins in humans and animals. Cases of ergotism have been recorded since the Middle
Ages, when it was referred to as ‘Saint Anthony’s fire’ or ‘holy fire’ and was believed to be a
punishment from God. Some even argued the Salem witch trials were caused by ergot
poisoning (Caporael, 1976). As early as 1891, it was proven in Japan that a beriberi-like
disease known as cardiac beriberi or shoshin kakke was caused by the consumption of
mouldy, yellow rice. Later it was discovered the rice contained a mycotoxin, namely
citreoviridin. In the first half of the twentieth century Russia was plagued by epidemics of
alimentary toxic leukemia, a mycotoxicosis caused by the consumption of overwintered,
mouldy wheat. The true scale of the mycotoxin problem, however, was only fully realised in
1960, when it was discovered that the death of thousands of turkeys was caused by the
ingestion of mycotoxins in their peanut-based feed (Feuell, 1966).
Mycotoxins are secondary metabolites produced by fungi and are toxic to humans and
animals. The fungi producing the most dangerous mycotoxins infect plants in the fields and
greenhouse, or when in storage. Among these, the most important fungal genera producing
mycotoxins are Alternaria, Aspergillus, Fusarium and Penicillium.
1.1.1. Deoxynivalenol
Deoxynivalenol (DON, 12,13-epoxy-3,4,15-trihydroxytrichothec-9-en-8-one, Figure 1.1)
is a mycotoxin produced by Fusarium species. It is most commonly produced by F.
graminearum (common in North and South America, Europe and Asia) and F. culmorum
(common in Europe and Canada), but it is also produced by F. equiseti and F. sambucinum.
These fungi primarily infect small cereals as wheat, maize and barley and cause plant diseases
such as Fusarium head blight (wheat) and Fusarium ear rot (in maize) in the field. Fusarium
head blight often causes weight and size loss of the kernel together with a discolouration
(Figure 1.2).
Apart from disastrous effects on the economy due to yield loss, they also present a major
public health danger (Miller, 1995; Turner, 2010). DON itself was identified in 1972, when
maize infected by F. graminearum caused feed refusal and emesis in pigs.
DON is a member of the trichothecenes, that all share a pyran group, a 9, 10-double bond
and a 12, 13-epoxide. Toxicity and effects differ, however, widely, depending on the various
substituents present. They are therefore classified in four groups: A, B, C and D. All of them
2
are capable of disturbing the translation of deoxynucleic acid (DNA) by binding ribosomes
and can cause apoptosis in eukaryotic cells (Pestka, 2010). An epidemic outbreak in the
Kashmir Valley in India (1987) was found to be caused by the ingestion of wheat products
which contained high concentrations of various trichothecenes (Bhat et al., 1989).
DON, part of the group B trichothecenes, is considered as one of the lesser toxic
trichothecenes. For example, the international agency for research on cancer (IARC) has
classified it under group 3: not classifiable as to their carcinogenicity to humans (IARC,
1993). Nevertheless it is considered as important, as it is commonly detected in infected
crops, and in processed food and feed, often in high concentrations compared to the other
mycotoxins. Another aspect is the geographic distribution of the toxin: it has been found on
nearly every continent (WHO, 1990; SCOOP, 2003).
The effects of DON, also known as vomitoxin, can be subdivided in two groups: acute
toxicity and chronic toxicity. In humans, it is suggested that DON causes gastroenteritis-like
symptoms with vomiting after a highly DON-contaminated meal. When animal experiments
were performed, the following symptoms were observed: abdominal pain, emesis, diarrhoea
and shock-like death. The latter happened only to mice and rats, animals that are not able to
vomit. When test animals (pigs, mice or rats) were given low doses for an extended period,
Figure 1.1: The molecular structure of deoxynivalenol (Tran and Smith, 2011).
Figure 1.2: Example of cereals infected with Fusarium head blight.
3
however, the animals stopped gaining weight and became anorexic. It should be noted that
pigs’ symptoms were more severe when they were given naturally contaminated feed and not
when the purified toxin was added to the feed. Another effect of DON is immunotoxicity: a
heightened sensitivity to infections (mice, chickens and pigs), immunoglobulin A (IgA)
nephropathy (mice) and leukocyte apoptosis causing immunosuppression (rodents) were
found in animal studies. DON was also proven to be haemolytic and cytotoxic (a.o. human
adenocarcinoma cells in vitro). Some studies report negative effects on reproduction and
intra-uterine development (Pestka, 2010; JEFCA, 2001).
It is difficult to estimate the chronic, low-dose exposure of humans to the toxin. As
indicated earlier, processed cereal-based foods nearly always contain DON in variable levels.
Aside from this, other aspects such as diet (e.g. vegetarianism), bioavailability and
susceptibility must be taken into account. The food and agriculture organisation and world
health organisation (FAO/WHO) has set the provisional maximum tolerable daily intake
(PMTDI) at 1.00 µg/kg for the sum of DON and its acetylated derivatives, 3- (3-ADON) and
15- acetyldeoxynivalenol (15-ADON) (JECFA, 2010). There have been various studies, most
using DON itself or the sum of DON and DON-glucuronides (DON-GlcAs) as biomarker in
urine, researching the exposure of humans to the toxin. Most found sub-PMTDI levels
(Turner et al., 2010; Turnera et al., 2011; Turnerb et al., 2011), but there was a small study in
Austria were one third of all those examined were above the PMTDI (Warth et al., 2012).
Apart from the rules set by the FAO/WHO, the European Commission has put down a
regulation on the acceptable limits of DON in the following products: unprocessed durum
wheat, oats and maize (1,750 µg/kg); other unprocessed cereals (1,250 µg/kg); cereals meant
for human consumption and uncooked pasta (750 µg/kg); processed cereal-based food (500
µg/kg); and processed cereal-based food targeted at infants and children (200 µg/kg)
(European Commission, Regulation 1881/2006).
1.1.2. Deoxynivalenol-3-glucoside
Generally, derivatives of mycotoxins are indicated with the term ‘masked mycotoxins’,
because they cannot be determined with the conventional methods used for the parent
mycotoxin. Within this group, there are further distinctions: extractable conjugated
mycotoxins, which can be measured if an appropriate standard is available, and bound
mycotoxins, which have to be freed from the matrix before determination (Berthiller et al.,
2013). The terms bound, hidden and masked mycotoxins are often used as synonyms or
confused in different studies, but in this thesis the following definition will be used:
4
“Bound mycotoxins are covalently or non-covalently attached to polymeric carbohydrate
or protein matrices. Extractable conjugated mycotoxins can be detected by appropriate
analytical methods when their structure is known and analytical standards are available.
Bound mycotoxins, however, are not directly accessible and have to be liberated from the
matrix [...] (Berthiller et al., 2013).”
M
More specifically on the subject of DON, again different types of derivatives can be
discerned. The infected plants can detoxify the mycotoxins, resulting in conjugates such as
deoxynivalenol-3-glucoside (D3G, Figure 1.3). This happens in two phases: in phase I the
mycotoxin is hydrolysed or oxidised, in phase II the resulting molecule is conjugated with a
more polar group. Afterwards, the conjugate is stored in the plant cell, e.g. in the vacuole. It is
assumed that DON can also be bound to a string of glucoside molecules in plants. These are
referred to as DON-oligoglucosides: they explain the rise in D3G that is observed when
brewing beer. A recent study confirmed the presence of DON-oligoglucosides in bread as
well as in beer (Zachariasova et al., 2012).
D3G is less toxic for the plant than its parent molecule. It is found nearly always when
DON is present, usually in lower concentrations. However, more research is devoted to the
possibility of D3G being converted to DON, either during processing or during animal
digestion and metabolism. Also the determination of the altered exposure is being studied.
There have been a few studies focussing on absorption and metabolism (Berthiller et al.,
2011; De Nijs et al., 2012; Nagl et al., 2012). Overall, no reversal to DON was found in the
small intestine and D3G absorption was minimal. Some bacteria species present in the large
bowel can convert D3G to DON (Berthiller et al., 2011); this has been confirmed in a recent
study (Dall’Erta et al., 2013). It should be noted DON absorption is non-existent in the large
intestines. As little is known about its toxicity, no acceptable limits have been established yet,
nor has there been any legislation concerning D3G.
Figure 1.3: The molecular structure of deoxynivalenol-3-glucoside (courtesy of M. De Boevre).
5
1.2. INFLUENCES OF PROCESSING
The manufacture of cereal-based products with uncleaned cereals as starting point, exists
of two parts: the primary processing and the secondary processing.
In most parts of the world, cereal-based products are a staple food. In developing countries
it often is the main, if not the only part of the diet. Cereals are usually processed before
consumption, at least by such simple actions as cooking. In Western countries, wheat is the
number one cereal used: it is processed to bread, pasta, crackers etc. Therefore, it is not
surprising that, on the subject of DON, wheat is the best studied cereal. Some wheat-based
products such as pasta have the advantage of being cooked before consumption. DON is
water-soluble and therefore a large part, when present, will be discarded with the cooking
water. Unfortunately, this is not customary for every wheat-based product. As bread is in
large parts of the world still the most important staple food, scientific interest is mostly
pointed towards this area. The following section of this study will therefore be devoted to the
making of bread. This process can be divided into two parts, primary and secondary
processing.
The primary processing involves all processing steps used to manufacture flour. It
encompasses cleaning, scouring, segregating and milling of the cereal fractions. The first
three processes can lower the mycotoxin level of the end product, mainly because visibly
infected kernels can be removed. Unfortunately, these fractions often end up in animal feed,
e.g. bran. An effect of infection is often a lower weight and size of the kernel, which means
that selection based on these parameters can lower the DON levels significantly. Also, the
infection by the fungi is mostly localised in the outer parts of the kernel. As more of these
outer parts are removed (e.g. scouring), the amount of DON present is lowered. However, not
all kernels reflect infection in their appearance and a substantial amount of toxin will not be
removed.
The final stage of the primary processing is milling. This also contributes to the removal of
DON, but again not because of destruction of the molecule, but through fractionation. The
highest levels of DON are found in these fractions that are usually not meant for human
consumption, e.g. germ and bran fractions. Furthermore, the finer the flour (i.e. contains less
of the outer parts of the grain), the lesser the DON levels (Kushiro, 2008; Ryu et al., 2008).
The secondary processing, i.e. from flour to bread, includes the making of the dough,
kneading, fermenting, proofing and baking. This research area has been heavily focussed on
in literature, as conclusions on the change in DON and D3G levels vary greatly among
different research groups. Therefore this shall be discussed more in depth below.
6
1.2.1. The chemistry behind the recipe
Usually, the ingredients of the dough are flour, water, salt, yeast and butter or some form
of fat. These are combined at the start and kneaded. The starch in the flour absorbs the water
and enzymes turn the starch into free sugars. During kneading, more air gets trapped into the
dough and gluten, a product of gliadin and glutenin proteins, is formed. Gluten adds both
plasticity and elasticity, which means that the dough changes form when put under pressure,
but returns to its original shape when that pressure is removed. This allows the dough to rise
and the air bubbles to expand but stops the bubbles in growing when they reach breaking
point.
Yeasts are eukaryotic fungal microorganisms, most commonly of the Saccharomyces
cerevisiae species (also called baker’s or brewer’s yeast). They ferment the sugars formed by
enzymes and produce alcohol and carbon dioxide (CO2) as by-products. The CO2 gets trapped
in the air bubbles in the dough. These bubbles are stabilised by a network of starch and
proteins or by a liquid-lipid film. During fermentation, these bubbles grow and the dough
rises. Often the bread is knocked down and allowed to rise again, which improves flavour.
The final fermenting step is referred to as ‘proving’ and takes place after dividing the dough.
When in the oven, the alcohol and water vaporise and fill holes in the gluten network. This
causes a further rise of the bread, until the crust becomes firm enough to resist growth. The
yeast has died at this point and the gluten are cross-linked: the bread is formed.
Salt is mainly added for the taste. Nevertheless it must be treated with caution, as it can
stop the fermentation process when present in high amounts. In some industrial processes,
additives are added as bread improvers to shorten the fermentation process and improve
dough quality. For example, oxidation-reduction systems are important in the formation of
disulphide bonds in gluten. Therefore oxidising agents, e.g. ascorbic acid (is converted into
dehydroascorbic acid, the true oxidising agent in the dough) and reducing agents, e.g. L-
cysteine, are added. Sometimes enzymes are used as quickening agents, e.g. amylases to
quicken the release of free sugars.
It should be noted that fermenting by yeast is not the only possibility to leave dough,
though it is the most used one. Next to yeasted dough, there is also sourdough, which
incorporates Lactobacillus species besides yeasts. This is a more traditional way of making
bread and needs a long fermentation time. Both sourdough and yeasted dough are biological
ways of leavening. Leavening agents can also be chemical and are then usually a combination
of an acid (e.g. baking soda (sodium bicarbonate)) and an alkali (e.g. cream of tartar
(potassium bitartrate)). Breads produced with leavening agents are usually referred to as quick
7
breads. Next to biological and chemical leavening, mechanical means can be used to
incorporate air into the dough by beating egg whites (often used in patisserie) or steam-
leavening (as used in popovers). Leavening is not required: there are some unfermented types
of bread. Most types of flatbreads are unleavened, e.g. tortilla (Buehler, 2005; Connelly,
2009; Reuben and Coultate, 2009).
1.2.2. The influence of secondary processing on DON and D3G
There are many contradictory reports in literature regarding the influence of secondary
processing on DON and D3G levels. Some authors report a reduction during the baking step,
others found no change or even an inclination in DON or D3G levels. Comparing these
studies was difficult due to differences in end product (cookies, bread, crackers and type of
bread), ingredients, (traditional) recipe, duration of the steps, the identity of the yeast strain or
temperature. The next subsection will therefore discuss some of these studies more in depth.
1.2.2.1. The influence of secondary processing on DON
The effect of breakmaking on DON has been researched since the eighties. A variety of
studies have focussed on the effect of the different steps, e.g. kneading, fermenting, and not
only on the process as a whole. Some of these studies and their results are summarised in
Table 1.1 (spiked) and 1.2 (natural contamination).
Article Kneaded
dough
Fermented
dough
Proofed
dough Bread Margin of error
Suman et al.,
2012
n.d.c.t.a
flour
n.d.c.t.
previous
stages
n.d.c.t.
previous
stages
rise of 7% to
loss of 54%
no LoDc or LoQd
mentioned
Kostelanska et al.,
2011
5% rise
compared
to flour
n.d.c.t.
previous
stages
n.d.c.t.
previous
stages
13% loss
compared to
flour
LoQ ≤ 5 µg/kg1
Monaci et al.,
2011 -b -
spiking
step
20-30% loss
compared to
spiking
LoD = 0.9 ng/ml
LoQ = 2.8 ng/ml3
Valle-Algarra et al.,
2009 -
n.d.c.t.
flour -
nearly 50%
loss compared
to flour
LoD = 8 µg/kg2
El-Banna et al.,
1983 -
n.d.c.t.
flour -
n.d.c.t.
flour LoD = 0.02 µg/kg1
ano difference compared to; bstep was not researched; climit of detection; dlimit of quantification 1method of calculation not mentioned; 2calculated as 3*S/N (signal-to-noise ratio) and LoQ=3*LoD; 3calculated
as 3 resp. 10 * the SD of the the intercept of the calibration curve
Table 1.1: Literature overview concerning the fate of added DON during the making of bread. If no other
spiking step is named, the DON was added to the flour.
8
Some research groups focussed on the effect of various additives. Sometimes this was done
to simply find the effect of an additive as used in the industry, others sought purposefully for
a chemical that might lower the amount of DON present. The addition of sodium bisulphate,
L-cysteine and ammonium phosphate to naturally contaminated flour reduced the amount of
DON in the bread (Boyacioglu et al., 1993). The fact that aqueous sodium bisulphate could
lower the detected DON had been discovered before by Young et al. (1986). These authors
used it to lower the DON level during the milling of naturally contaminated flour. They found
however that during the baking, the level of DON rose again, though levels were still lower in
the end product than in untreated flour. The effect of the addition of baking improvers was
researched, but no effect on DON (natural contamination) was found (Kostelanska et al.,
2011). According to one study, yeast, gluten nor starch had any influence on the DON level in
bread baked of naturally-contaminated flour (Ragab et al., 2005).
The effect of certain variables have also been researched. When the stability of DON was
studied under different values for pH and temperature (Lauren and Smith, 2001), only very
harsh conditions (pH > 10, 80 ˚C, several days) brought about any effect. Then again, effect
of temperature on barley powder and roasted kernels showed, next to a protective matrix
effect, a linear reduction of DON in function of the temperature (Yumbe-Guevara et al.,
2003).
Other research groups focussed only on the way of baking as could be found in their own
country. Among others, Lešnik et al. (2008) compared traditional, organic bread-making in
Slovenia with industrial bread-making when naturally-contaminated flour was used and found
no differences in DON reduction. Pacin et al. (2010) used a different approach: instead of
baking themselves, they took samples of both flour and bread in Argentinean bakeries. Both
in Vienna and French bread a reduction of DON was found. The fermentation step in
Argentinean bread made of naturally-contaminated flour (again Vienna and French bread)
was found to significantly lower DON levels, with a maximum of 56% (Samar et al., 2001).
When different conditions (temperature and duration) in Spanish bread-baking were
researched, an overall reduction of 50% DON in comparison to the spiked flour was found
only during the baking step with no difference between the various used conditions (Valle-
Algarra et al., 2009).
Apart from the influence of regional ways of baking, one could also focus on a variety of
different cereals. For instance, the level of DON and D3G were measured in durum wheat in
Italy and the DON level was found to be above regulatory levels (Dall'Asta et al., 2012).
When bread was baked of durum wheat flour (naturally contaminated), an increase in DON
9
level was measured (de Angelis et al., 2013). In another study, the thermodegradation of
DON in the manufacturing of maize bread was studied (Numanoglu et al., 2012). The
naturally contaminated maize used to manufacture this bread was collected from the Black sea
and Mediterranean regions. One report even differed between naturally contaminated white
and wholemeal flour and absolute values (corrected for dry weight) and corrected (for dry
weight and amount of flour used) values (Scudamore et al., 2009). For white bread, the
absolute value for DON was a reduction, but corrected it gave a risen level. The wholemeal
flour gave a reduction for both the absolute and the corrected values.
Article Kneaded
dough
Fermented
dough
Proofed
dough Bread Margin of error
Bergamini et al.,
2010 -a
only
difference for
low amounts
-
pilot plant:
increase,
industrial:
11% loss
no LoDc or LoQd
mentioned
Abbas et al.,
1985 - - -
16%-60% loss
compared to
flour
LoD = 0.5 ng (GC-
MSe); 10 ng
(HPLC-UVf); DON
as ng/g1
Scott et al.,
1984 - - -
6.7% and 8%
rise compared
to flour
LoD = 0.014 µg/g2
Simsek et al.,
2012 -
50% rise
compared to
flour
n.d.c.t.b
previous
stages
rise of 70%
compared to
flour
no LoD or LoQ
mentioned
El Banna et al.,
1983 - n.d.c.t. flour - n.d.c.t. flour LoD = 0.02 µg/kg1
Ragab et al.,
2005 -
45% loss (~
fermentation
time)
loss of nearly
50% LoD = 0.1 mg/kg1
Lancova et al.,
2008
21%-
40% rise
compared
to flour
38%-46% loss
compared to
flour
32%-
45% rise
compared
to flour
n.d.c.t. flour LoD = 0.5 µg/kg
LoQ = 5 µg/kg1
astep not researched; bno difference compared to; climit of detection; dlimit of quantification; egas
chromatography - mass spectrometry; fhigh performance liquid chromatography - ultraviolet detection 1method of calculation not mentioned; 2calculated as 3*S/N (signal-to-noise ratio)
Some studies took a variety of end products or opted to not research bread. Young et al.
(1986) found a reduction in DON levels (natural contamination) when cookies were made,
however a rise was observed when used for making muffins. Cake, biscuits and crackers were
tested and no effect of baking (only by dilution) was found (Scudamore et al., 2009). In
Table 1.2: Literature overview concerning the fate of DON, present by natural contamination in the flour. All
used naturally contaminated cereals for their research.
10
another study, the level of DON in cookies, doughnuts and cake was compared to the level in
the flour and the naturally contaminated cereal. All three end products showed a reduction
when compared to the cereal, but hardly any difference compared to the flour. In fact, in the
doughnuts a rise in DON concentration took place, that was masked by the heavy dilution of
the flour (compared to wheat; Young et al., 1984). Doughnuts, pretzels, cookies, bread and
crackers were compared in another report, but only a reduction in DON was found in crackers
and bread (Voss and Snook, 2010). One study focussed exclusively on crackers, to which a
part of the bran (higher DON levels) was added in the dough stage. It showed that when
baking time is lengthened, DON is reduced (Suman et al., 2012).
One research group made a discrimination between the absolute levels of DON, which
were measured with high performance liquid chromatography – ultraviolet detection (HPLC-
UV), and its cytotoxicity according to bioassays. The latter seemed lowered by about 10%
during the baking step in comparison to the naturally contaminated flour, even when the
former remained stable (Sugita-Konishi et al., 2006). This concurred partly with the results of
another study which focussed on degradation products of DON in simple food models: a
significant reduction (up to 50%) of DON was found and the degraded products all possessed
less toxicity (Bretz et al., 2006).
1.2.2.2. The influence of secondary processing on D3G
D3G has not been as widely researched as DON. Three studies that focussed on the effect
of the different bread-making steps have investigated both DON and D3G. Their results for
D3G have been summarised in Table 1.3.
Article Kneaded
dough
Fermented
dough
Proofed
dough Bread
Margin of
error
Suman et al.,
2012
n.d.c.t.a
flour
n.d.c.t.
previous
stages
n.d.c.t.
previous
stages
n.d.c.t. previous
stages
no LoDb or
LoQc
mentioned
Kostelanska et
al., 2011
13% loss
compared
to flour
8% rise
compared
to flour
n.d.c.t.
previous
stages
10% loss
compared to
flour dough
LoQ ≤ 5 µg/kg1
Simsek et al.,
20122 -d n.d.c.t.
flour
slight loss
compared
to flour
loss of 50%
compared to
flour; 42% to
proofed dough
no LoD or LoQ
mentioned
ano difference compared to; blimit of detection; climit of quantification; dstep not researched. 1Method of calculation not mentioned; 2In this study, naturally contaminated wheat was used.
Table 1.3: Literature overview concerning the fate of D3G during the making of bread. If no other
spiking step is named, the D3G was added to the flour.
11
Kostelanska et al. (2011), who investigated the effect of baking improvers, observed that
the level of D3G increased nearly 50% in proofed dough compared to the naturally
contaminated flour. There was however a subsequent 10% decrease during the baking. The
analysts postulated that the increase was caused by the hydrolysis of DON-oligoglucosides, as
the DON level was not influenced.
In durum wheat, it was found that the D3G concentration was linked to the DON
concentration present (Dall'Asta et al., 2012). De Angelis et al. (2013) found that bread
contained far less D3G than the naturally contaminated durum wheat flour. According to one
study, the lengthening of the baking time of crackers did not influence the D3G levels (Suman
et al., 2012).
1.3. ANALYSIS OF DON AND D3G IN THE BREAD MATRIX
In the next subsections, various methods to quantitatively establish the amount of DON and
D3G will be discussed. Those methods that were used in this study will be mostly focussed
on.
1.3.1. Matrix digestion
As mentioned before, a difference can be made between extractable and bound (non-
extractable) masked mycotoxins. It has been suggested, particularly in those studies where a
rise in DON or D3G was observed after processing, that the bound molecule was released
during processing. When this is reflected upon, it is possible that the reverse might hold true
as well: DON or D3G might be captured in the matrix of the processed food, become
unextractable and cannot be detected. This might be an explanation for those studies where in
an early processing step a loss in the mycotoxin levels was found.
Some studies researched the masked DON present by treating the samples with acid and
comparing the total amount of DON with the amount of free DON found in untreated sample.
Unfortunately, these studies did not take into account the difference between covalently
bound, non-covalently bound and extractable conjugates (Zhou et al., 2008; Tran and Smith,
2011; Tran et al., 2012). Therefore it is not known how much of these found conjugates
represent an actual danger to animal and human health, and how much of it could be found in
the matrix.
Apart from chemical destruction, enzymatic digestion of the matrix is also possible. For
example, the amount of added folic acid in cereal-based products was measured after
treatment of the sample with α-amylase (Osseyi et al., 1998). This was carried out since
hydrolysis of starch heightened the levels of folate detected. Urine was treated with enzymes
12
in a study that investigated urinary biomarkers and as a result, the levels of mycotoxins
detected rose (Solfrizzo et al., 2011). Nevertheless, most protocols using enzymatic digestion
can be found in bioanalysis of tissues. Such a sample preparation, using collagenase and
proteinase K, was designed to find ingested drugs (Yu et al., 2004). Usually, large molecules
such as DNA, prions or RNA are the target molecules.
The enzymes used in this study, will be discussed in the following subsections.
1.3.1.1. Peptidase K
Peptidase K, more commonly known as proteinase K, is produced by the fungus
Engyodontium album. The enzyme gained its name because of its ability to hydrolyse keratin.
It is a serine endopeptidase, i.e. its active site contains a serine amino acid. Usually,
proteinase K cleaves on the carboxy-side of aliphatic and aromatic amino acids. Both the
temperature and pH range in which the enzyme is stable vary: from 20 °C to 60 °C (maximum
at 37 °C) and from pH 7.5 to 12.0. In addition, its activity is not influenced by commonly
used protein-denaturating chemicals, such as urea or sodium dodecyl sulfate. Calcium is an
activator of the molecule and can be bound in two sites. Nevertheless, proteolytic activity is
preserved (but lowered) in the presence of ethylenediaminetetraacetic acid (EDTA), which
binds calcium. EDTA is often used to eliminate the activity of enzymes that require the
presence.
Because of its stability and broad ligand spectrum, proteinase K is often used to hydrolyse
other enzymes. In nucleic acid purification it hydrolyses nucleases and other enzymes that
might destroy the DNA or ribonucleic acid (RNA) present. Another use is the cleavage of
proteins into peptides that can then be analysed by liquid chromatography – mass
spectrometry (LC-MS) to determine their structure. Among others, prions are often treated
this way (IUBMB, 1992; Sweeney and Walker, 1993).
1.3.1.2. α-Amylase
This enzyme is widespread in animal, fungal and bacterial species. The enzyme hydrolyses
1,4-α-D-glycosidic bonds within oligo- or polysaccharides, producing mono- and
disaccharides. These can be used as carbon sources by the organism that produces the
enzyme. The “α” does not refer to the type of cleavage bond, but to the anomeric
configuration of its product.
Because it is a common enzyme, properties vary greatly. Temperature ranges of activity
can be narrow or broad, pH ranges of activity can be low or high depending on the source of
the enzyme. Because of its use in industrial processes with uncommon pH and temperature
13
ranges, there are many studies focussing on the search for α-amylases that retain their activity
in these circumstances. Consequently, the pH with the highest stability can be 1 (Bacillus
spp.) to 11 (Streptomyces gulbargensis), and the temperature for activity can vary between 4
°C (Anabaena spp.) to 120 °C (Bacillus spp.) (IUBMB, 1961; BRENDA, EC 3.2.1.1).
The applications of α-amylase in industry are many. It is mainly used in starch conversion
to produce glucose and fructose. This process involves heating and sometimes acid treatment.
The pH often needs to be heightened, however, as the enzymes used in these processes
usually are vulnerable to high temperatures and low pH at the same time. Also, they are often
calcium-dependent. α-Amylases are also used in detergents to remove stains, in ethanol-
biofuel production and in the paper industry. In baking, next to digesting the starch (see
1.2.2.1), it is sometimes added as an anti-staling agent (de Souza and e Magalhães, 2010; Van
Der Maarel et al., 2002). Adding the α-amylase increases the volume, reduces the hardness
and preserves sensory characteristics of the bread. This is probably caused by the enzyme
reducing the starch network and the immobilisation of water (Goesaert et al., 2009; Gomes-
Ruffi et al., 2012).
1.3.1.3. Triacylglycerol lipase
The systematic name of this enzyme is triacylglycerol acylhydrolase. In the presence of
water, triacylglycerols (mostly the outer ones) are converted to diacylglycerols and
carboxylates. The enzyme needs an ester-water interface for activity. Again, this enzyme is
wide-spread, occurring in various bacterial species and in animal species. In the latter, it is
necessary for digestion of lipids, which are an important energy source. Usually, it is
expressed in the adipose tissue, the liver and pancreas. From the latter organ, it is transported
to the gallbladder with other enzymes and then to the small intestine (IUBMB 1961 EC
3.1.1.3; BRENDA EC 3.1.1.3).
In humans, pancreatic lipase needs some extra chemicals, namely bile salts, colipase and
calcium. Bile salts, without colipase present, only enhance the activity of the enzyme in low
concentrations. The bile salts’ function is to aid micelle formation, which facilitate the
digestion of fats. When they are added in high concentrations, they can inhibit this process.
However, this is prevented by the presence of colipase. Colipase also increases the stability of
the lipase. Calcium is also necessary for the activity of lipase, partly because it precipitates
free fatty acids. The latter can inhibit the enzyme (Lessinger et al., 1996; Zangenberg et al.,
2001).
14
1.3.2. Extraction and clean-up of DON and D3G
For the extraction of DON and D3G, mostly a mix of water and a water-mixable organic
solvent is used. The water present in the extraction solution is supposed to make the grains
swell and enhance extraction (Meneely et al., 2011). Sometimes the organic solvent is
methanol (Suman et al., 2013), but more often acetonitrile is chosen. The ratio is usually
80:20 (v:v) or 84:16 (v:v) acetonitrile:water. Sometimes ammonium acetate and/or acetic acid
is added (Desmarchelier and Seefelder, 2010). Vendl et al. (2009) found that acidic extraction
gave optimal results for a multi-toxin analysis. In some studies, a defatting step was added
(De Boevre et al., 2012).
After a crude extraction, a clean-up step can possibly be added to enhance detection. This
is usually performed with the aid of columns, either solid phase extraction (SPE), e.g.
MycoSep, (Lattanzio et al., 2011; Berthiller et al., 2005), or immunoaffinity columns (IAC;
Suman et al., 2013). SPE has the same basis as liquid solid chromatography (LSC). A liquid
solution containing the target molecule is brought on a column, the solid phase. Elution times
depend on the affinity of the components for the solid phase. IACs also work with a column,
but the solid phase contains antibodies that recognise a specific structure (MacDonald et al.,
2005; Neumann et al., 2009). The problem with the latter method is the often unknown cross-
reactivity. In this case, the antibody-recognised structure is not specific enough and related
structures, e.g. conjugates, also are withheld on the column.
It is possible to use detection systems for which this is not important, e.g. mass spectrometry
(MS), but other methods might not make the distinction between different derivatives.
Consequently, some studies have focussed on the differences and cross-reactivity of
commercially available IACs (e.g. Veršilovskis et al., 2011). In two multi-toxin studies, the
clean-up was investigated. However, because of the low recovery, this method was neglected
(De Boevre et al., 2012; Vendl et al., 2009).
Next to column-clean-up, the QuEChERS (“Quick, Easy, Cheap, Effective, Rugged, and
Safe”) method is a possibility (Desmarchelier and Seefelder, 2010). In this method, originally
developed for multi-pesticide research, salts are added to the extraction mix. These increase
the polarity of the water to such an extent, that phase separation takes place. In theory, the
apolar molecules will prefer the organic solvent and migrate from the water phase. This would
hold true for DON as well. The organic solvent can then easily be separated from the water
and salts. Nevertheless when this method was compared with a MycoSep column for the
detection of DON, T-2- and HT-2-toxins, an enhanced matrix effect was found for DON with
QuEChERS method (Monaci et al., 2011). It was also implied that recovery for D3G might be
15
low with this method due to its higher polarity (Cirlini et al., 2012). For the same reason,
Dall'Asta et al. (2012) used a methanol-acetonitrile (v:v) mix for their extraction solvent
instead of a acetonitrile-water (v:v) mix.
These extra clean-up steps are becoming less necessary in reference to the higher
sensitivity and quality of the detection systems. The ‘dilute-and-shoot’ approach, in which the
sample only is diluted before injection, gains more attention especially LC-MS/MS (see
under).
1.3.3. Analysis of DON and D3G
For the identification of mycotoxins, a myriad of methods can be chosen. Some of the
detection methods include ultraviolet detection (UV), electron capture detection (ECD) and
MS (Scudamore et al., 2009).
The UV method was investigated in combination with a immunoaffinity clean-up step by
two interlaboratory studies (MacDonald et al., 2005; Neumann et al., 2009) and with post-
column fluorescence derivatisation by another group (Sano et al., 1987).
Before detection, an extra separation step is included, liquid (LC) or gas chromatography
(GC). In GC the molecules are evaporated (mobile phase) and run over a solid or liquid phase
to separate them based on their affinity for the different phases. This used to be a popular
choice for the analysis of DON. However, though GC methods are sensitive and have great
accuracy, they need derivatisation of the components (Meneely et al., 2011). Furthermore,
D3G is far too polar for this technique (Cirlini et al., 2012). Nowadays the LC-MS method is
the more popular, needing very little clean-up and having no necessity for derivatisation
(Lattanzio et al., 2011).
In LC, components are separated by their different affinity for the apolar and polar phases.
One of these is attached to the column and stationary, the other is a liquid mobile phase that
holds the components and is run over the stationary phase. The components distribute
between the two phases depending on their affinity for the stationary phase and elute at
different times. With DON and derivatives, reversed phase LC is mostly used. The preferred
column used is a C18-column with a methanol:water (v:v) or acetonitrile:water (v:v) mobile
phase. As with the extraction mix, ammonium acetate and/or acetic acid can be added
(Suman et al., 2013). Four C18-columns were compared in a study and circumstances were
optimised (Abdel-Aal et al., 2007).
16
A mass spectrometer (MS) turns the eluting molecules to ions. These are consequently
detected based on their m/z (ratio of mass and ion value) value. The resulting chromatogram
represents the relative intensity of the peaks opposite their m/z value.
In this study, the system used was a tandem mass spectrometry (MS/MS), with a tandem
quadrupole and a collision cell (a third quadrupole) in-between (Figure 1.4). The mode was
multiple reaction monitoring (MRM) which means that after the first selection (of a precursor
ion) in the first quadrupole a fragmentation takes place in the collision cell. This results into
product ions, which can then also be selected in the second quadrupole.
The ionisation technique was electrospray (ESI, Figure 1.4). In this method, the eluent is
forced through a capillary as it comes off the column. At the end of the needle, an electrical
field is placed which nebulises the solution into smaller droplets that all carry multiple
charges. A heated gas is sent through this spray, evaporating part of the solution. The droplets
decrease in size, bringing the identical surface charges closer together. This process is
repeated until the electrical repulsion (known as Coulomb repulsion) between the identical
charges exceeds the surface tension. At this point the droplet explodes into individual,
charged molecules. The advantages of this technique are its ‘soft’ nature, which means
fragmentation is rare, and the fact that it allows the molecules to carry multiple charges.
Figure 1.4: representation of the ionisation technique ESI (left, adapted from Andreas Dahlin from
adorgraphics) and tandem mass spectrometry with a triple quadrupole (right, adapted from
www.broadinstitute.org).
17
2. OBJECTIVES
Mycotoxins are secondary metabolites produced by fungi. These fungi, mainly Aspergillus,
Fusarium, Alternaria and Penicillium, often grow on cereals in the field. If the infected plants
are insufficiently noticed and subsequently removed, the mycotoxins might end up in food
and feed. As the infection is not always reflected in the plant’s outlook, this happens more
often than suspected. Fusarium species are widespread and can grow in different climates,
occurring nearly all over the world. The fungus can infect a variety of crops, e.g. maize,
wheat.
One of the mycotoxins produced by the Fusarium species is deoxynivalenol (DON), often
in high amounts. This is a mycotoxin that causes abdominal pain, diarrhoea and vomiting in
animals. Epidemic outbreaks of similar symptoms in humans have been linked to the
consumption of grain-based products contaminated with DON. The presence of DON in
cereals seems to be unavoidable. Even when visibly infected kernels are removed, the
mycotoxin can often be detected in the remaining kernels. Although primary processing
(cleaning, scouring and milling of cereals) can remove a certain amount of DON, again the
mycotoxin will still be present in the end products. The highest amounts of DON can be found
in those products that usually are discarded or end up as animal feed, but this hypotheses
DON is also present in products meant for human consumption.
Further problems are caused by the so-called masked mycotoxins. These often originate
from the infected plant. As a detoxification mechanism, the crop forms conjugates of the
mycotoxin and stores it in the plant tissue. Both bound derivatives, which have to be freed
from the matrix before measurement, and extractable, conjugated derivatives may be present
but not detected. In the case of DON, deoxynivalenol-3-glucoside (D3G) is only one example;
the existence of DON-oligoglucosides has been suggested. Those few studies that investigated
the fate of D3G when ingested, found no true risk. Nevertheless there is still the possibility
that processing might convert D3G to DON. There is also the possibility that DON can be
captured in the matrix or be changed (e.g. by micro-organisms) during processing.
Primary processing, which converts the cereals to flour, has proven to lower the amount of
DON when comparing start and end products. However, studies concerning secondary
processing often contradict one another. Furthermore, they often differ in circumstances and
context, making it impossible to compare them. Sometimes values characterising statistical
uncertainty are not mentioned or different formulas are used. This makes it difficult to assess
these studies and their findings.
18
The goal of the present study is to establish the changes in DON and D3G concentrations
when flour is processed to bread. Several steps in this process are investigated. To ensure that
all DON would be detected and quantified, enzymes are used to digest the bread matrix. This
is performed so even the bound mycotoxin will be included. It also excludes the possibility
that the spiked DON might be captured in the matrix during the processing and not be
detected, though still be harmful to consumer’s health. After digestion, DON and D3G is
extracted from the matrix, using a mix of acetonitrile and water as extraction solvent. The
samples are measured with LC-MS/MS.
19
3. MATERIALS AND METHODS
3.1. REAGENTS
3.1.1. Chemicals
Acetonitrile ultra LC-MS/MS was obtained from Biosolve BV (Valkenswaard, the
Netherlands) and Actu-All chemicals (Randmeer, the Netherlands). Sodium chloride (NaCl),
potassium chloride (KCl), calcium chloride (CaCl2), disodium hydrogen phosphate dihydrate
(Na2HPO4.2H2O), potassium dihydrogen phosphate (NaH2PO4) and hydrochloric acid (HCl)
were purchased from Merck (Darmstadt, Germany). Magnesium sulfate (MgSO4) and
ammonium acetate (NH4CH3COO) originated from Sigma-Aldrich (Steinheim, Germany).
The water used was purified by a MilliQ© system (Merck Millipore, Massachussets).
3.1.2. Standards
All standards DON, D3G and 15C13-DON were obtained from Biopure (Tulln, Austria).
The D3G stock solution (50.2 µg/mL) and the DON stock solution (100.2 µg/mL) had
acetonitrile as solvent. The internal standard was 15C13-DON (2.51 µg/mL, acetonitrile).
A working solution of DON and D3G was prepared at a concentration of 10 µg/mL as a
spiking solution. This working solution contained 20% D3G stock standard, 10% DON stock
standard and 70% acetonitrile (v:v:v). When necessary, this was replenished by mixing the
same stock solutions in the same ratios. Later in the study this working solution was adjusted
to 5 µg/mL. All solutions were kept in the dark at 2 °C to 8 °C.
3.1.3. Enzymes
All enzymes were purchased from Sigma-Aldrich (Steinheim, Germany). Lipase from
porcine pancreas type II, α-amylase from Bacillus spp., proteinase K from Tritirachium album
(now reclassified as Engyodontium album) and laminarinase from Trichoderma spp. in
powdered form were used. Between use, the enzymes were kept in the dark at -20 °C. The
enzymes were dissolved in the buffer solution (see 3.1.4). Except for laminarinase,
intermediate solutions of these enzymes contained 5 mg/mL, based on an intra-institute
research program. Later in the study, the enzyme concentrations were lowered to 1 mg/mL
without loss of effect. Solutions of enzymes were prepared fresh before use. Laminarinase, a
deconjugation enzyme that can split D3G into a glucose and DON, was made into a 2 mg/mL
solution.
20
3.1.4. Buffer
The recipe for a phosphate-buffered saline (PBS) with pH 7.4 and calcium was adapted
from Cold Spring Harbor Protocols (June, 2006). The amounts of salts mentioned in Table
3.1 were dissolved in 400 mL water, after which the pH was adjusted to 7.4. The solution was
then diluted to 500 mL. Each time before use, the solution was equilibrated at 37 °C.
For the experiment regarding optimisation of the laminarinase activity, HCl was used to
adjust the pH of the PBS buffer to 5 and 6. Of each pH, 20 mL was prepared.
Chemical Amount (µg)
NaCl 4,000.0
KCl 106.0
Na2HPO4.2H2O 902.1
KH2PO4 119.6
CaCl2 55.1
3.2. COLLECTION OF THE SAMPLES
A variety of flours were purchased in Dutch supermarkets and biological farms in the years
2012 and 2013. These were kept at room temperature in the dark. They were tested for the
presence of DON and D3G and a suitable blank flour was chosen for the rest of the study. In
the rest of this thesis, ‘flour’ will refer to these samples containing this flour. Those samples
that do not contain it, are referred to as ‘blank’.
3.3. SAMPLE PREPARATION
This section implies sample preparation and is most important in studies. It often controls
the recovery of the researched chemical and as such the quality of the entire investigation. In
this study the optimisation of the extraction method gained most attention.
3.3.1. Sample digestion
Enzyme solutions (2 mL) were added separately or together to the samples of 200 mg flour
(‘flour samples’) or empty vials (‘blanks’). After mixing, the samples were incubated for 16
hours at 37 °C on a shaking water bath. Laminarinase was added after this process to several
specific samples that already were digested by the enzymes and allowed to incubate for 30
minutes in a water bath at 37 °C. Different optimal pHs were investigated for laminarinase; in
this part of the study, no other enzymes were added to the mix. These samples were then
again kept in a water bath at 37 °C for half an hour, as described above.
Table 3.1: Amount of chemicals in 0.500 L water for
the manufacture of PBS.
21
3.3.2. Extraction method
Three possible extraction methods were investigated for flour spiked with DON and D3G.
After spiking, the flour was dried to the air for 30 minutes. The samples were extracted with
buffer, buffer and acetonitrile (20:80, v:v) or buffer and acetonitrile (20:80, v:v) with
QuEChERS (addition of 1.5 g magnesium sulphate and 0.25 g sodium acetate).
The buffer-acetonitrile combination was further optimised. Four concentrations were
tested: 80:20 (v:v) extraction, 50:50 (v:v) extraction, 50:50 (v:v) extraction with afterwards
dilution to 25% acetonitrile with water, and 50:50 (v:v) extraction with evaporation and
redissolvation in eluent A. Evaporation was performed on a Turbovap LV (Biotage, Sweden).
The enzyme samples already contained 2 mL buffer solution; to other samples 2 mL buffer
was added.
After addition of the acetonitrile (2 mL), samples were shaken on a shaking machine SM30
control (Edmund Bühler GmbH, Hechingen, Germany) for 90 minutes at 170 rpm to 200 rpm.
Then the samples were centrifuged at 3,000 rpm for 10 minutes (centrifuge Z513, HERMLE
Labortechnik GmbH, Wehingen, Germany). A small volume (600 µL or 700 µL) of each
sample was placed in a filter vial and placed for 30 minutes at 2 °C to 8 °C before being
filtered. 500 µL was transferred to an HPLC vial and kept by 2 °C to 8 °C until analysis.
3.4. DETECTION: LC AND MS CONDITIONS
3.4.1. Standard series
Standard series in both eluent A and buffer solution were made to accompany sample
injection and to enable the calculation of the concentrations. The standard solutions
mentioned before (3.1.1.) were used. An intermediate solution was made of the DON and
D3G standards with a concentration of 5 µg/mL. This intermediate was used to prepare six
standard levels. The final DON and D3G concentrations in these were 5, 10, 25, 50, 75 and
100 ng/mL. The internal standard 15C13-DON was added to the standard series in eluent A to
become a final concentration of 50 ng/mL.
3.4.2. Mobile phases
For HPLC analysis, two eluents, A and B, were prepared. Eluent A consisted of 5 %
acetonitrile and 95 % water, eluent B of 95 % acetonitrile and 5 % water. Both mobile phases
also contained 1mM of ammonium acetate. The obtained solutions were replenished every
two weeks by mixing of the proper ratios of reagents.
22
3.4.3. LC conditions
To separate the toxins, the Acquity UPLC© system (Waters, Dublin, Ireland) was used.
The instrument included a sample manager and a binary solvent manager. The column used
was an Acquity HSS (high strength silica) T3 UPLC column (1.8 µm, 2.1 x 100mm) with a
maximum pressure of 1,000 bar (Waters, Dublin, Ireland). This type of column is useful for
the separation of polar components and can tolerate pure water as a mobile phase. The HSS
silica particles can withstand the high pressures that are typical for UPLC.
The column temperature was kept at 50 °C ± 2 °C, the sample temperature was kept at 12
°C ± 5 °C. The flow rate was kept at 0.300 mL/min. Both injection volumes 10 µL as 5 µL
were considered and run time took 13 minutes. The gradient used is described in Table 3.2.
The retention time was 2.55 minutes for D3G and 2.76 for DON.
Time (min) Eluent A (%) Eluent B (%)
0.0 95.0 5.0
1.0 95.0 5.0
7.0 0.0 100.0
11.0 0.0 100.0
11.5 95.0 5.0
13.0 95.0 5.0
3.4.4. Mass spectrometry
The Mass spectrometer (MS) for all experiments was the Micromass Quattro Ultima PT
(Waters, Dublin, Ireland) with MassLynx NTTM Software. The ESI was used in the negative
ionisation mode.
In the ion source, adduct ions may be formed: a combination of an ion and a molecule
which are both present in the solution. In this study, acetate adducts (M + CH3COO-) gave the
best precursor results: 355.10 Da for DON, 370.40 Da for 15C13-DON and 517.30 Da for
D3G. The product ions that were focussed upon were the whole molecules (M-H+):
respectively 295.10, 310.20 and 457.10 Da. The collision energy was 11.00 eV, the cone
voltage was 40.00 V.
3.4.5. Calculations and estimation of the margins of error
When measuring a certain value or concentration, there is always an uncertainty related to
the measured value. The value depends on the circumstances: the used equipment, the
operator and the procedure. Each action has its own uncertainty and adds to the total
uncertainty of the method and eventually to the measured value.
Table 3.2: The gradient used in UPLC.
23
There are several ways to estimate this uncertainty. The variation in a collection of data
can be described by the standard deviation (variation from the mean in the collection). The
ratio of the standard deviation to the mean is called the relative standard deviation (expressed
as a percentage) and can be used as a representation for the uncertainty of the method.
Further uncertainty can be established by calculating the statistical significance of
differences between values. When two or more flours are analysed for the presence of
mycotoxins, the found values can be compared to find the significant differences between the
samples. The samples can also be compared to a blank sample. Usually a t-test (pair of
samples) or ANOVA (more than a pair of samples) test is used to express uncertainty. When
using these tests, a H0 hypothesis is set forth and challenged (e.g. “all these flours do not
contain mycotoxin, or do not differ from the blank”). When the found values turn out to be
statistically significantly different, the H0 hypothesis is proven wrong (e.g. “these flours differ
from the blank”). In other words, it is highly unlikely that the measurements could occur by
chance. It should be noted that, when using these tests, the formulation of the H0 hypothesis is
of great importance.
Concentrations in samples are often determined by using standard series. This allows
known quantities of the chemical to be linked to a certain response, often pictured in a graph
or in an equation. On this standard series not only the measured values depend, but also the
limit of detection (LoD) and the limit of quantification (LoQ). The LoD is the lowest
concentration that can be discerned from the blank. The LoQ is the lowest concentration that
can be determined. Both can be calculated by multiplying the signal-to-noise ratio (S/N;
response) by three (LoD) or ten (LoQ) and linked to a concentration through the standard
series equation. Other possible calculations are based on multiplication of the standard
deviation of the intercept of the calibration curve or of the calibration curve itself. The latter
method is used by our research institute (RIKILT). This means that the higher the uncertainty
on the standard series equation is, the less reliable the LoD, the LoQ and the determined value
become. The chances of deviations are the highest for the extreme values of the calibration
curve. For this reason it is important that all samples contain amounts of the analyte(s) above
the LoQ and within the concentration range of the standard series.
Usually the uncertainty on the equation and graph is limited by demanding that the
regression coefficient of the standard series equation is higher than 0.9800. This should ensure
that every measurement can only deviate about 20% of the value according to the equation.
Because of the importance of uncertainty on the totality of the study, all parameters
influencing this factor should be controlled as much as possible. It is also important to report
24
uncertainty values and how they were established in studies so others can assess the
importance and correctness of it. This is however not always remembered when a study is
written down. When taking the eleven studies, previously described in Tables 1.1 to 1.3, three
studies did not mention an LoD or LoQ. Three studies mentioned both, four mentioned only
the LoD and one only the LoQ. Only three out of eleven studies specified the calculation
method; only one of these used the multiplication of the standard deviation of the intercept of
the calibration curve. The other two used the multiplication of S/N.
The goal of this master thesis was not method development, nor validation. Therefore, the
LoD and LoQ was recalculated for every standard series that was injected and never formally
established. To obtain the LoQ, the standard error of the standard series graph was multiplied
by three. The intercept was subtracted from this value and the result was divided by the slope
(see Calculation 3.1 below). The LoQ was divided by three to give the LoD (Calculation
3.2).
𝐿𝑜𝑄 =3∗𝑆𝐸−𝑏
𝑎 (3.1)
with: LoQ = limit of quantification;
SE = standard error of the standard series equation;
b = intercept of the standard series equation;
a = slope of the standard series equation.
𝐿𝑜𝐷 = 𝐿𝑜𝑄
3 (3.2)
with: LoD = limit of detection.
Often in studies, the LoD and LoQ concentration is converted to w:w values (mass of
analyte compared to mass of flour). A generic example of such a calculation would be:
𝐿𝑜𝑋 (𝑤/𝑤) =𝐿𝑜𝑋∗𝑑𝑓∗𝑉𝑒𝑥𝑡𝑟𝑎𝑐𝑡𝑖𝑜𝑛
𝑤𝑓𝑙𝑜𝑢𝑟 (3.3)
with: LoX = LoD or LoQ (e.g. ng/mL);
df = dilution factor;
Vextraction = volume extraction solvent added (e.g. mL);
wflour = weight flour used (e.g. g).
In this particular study, Calculation (3.3) becomes:
25
𝐿𝑜𝑋 (µ𝑔/𝑔) = 𝐿𝑜𝑋 (𝑛𝑔/𝑚𝐿)∗2∗4 (𝑚𝐿)
200 (𝑚𝑔) (3.4)
The recovery of the samples was calculated based on the standard series equation of the
entire experiment if possible (i.e. a regression coefficient above 0.9800). If the regression
coefficient (R2) did not exceed this value, bracketing was used: the equation used was based
only on the two standard series injected in time closest to the sample. For all calculations,
MassLynx NTTM (Waters, Dublin, Ireland) and Microsoft Excel (Microsoft, Reading, UK)
were used.
26
4. RESULTS
4.1. OPTIMISATION OF THE EXTRACTION METHOD
The following extraction methods were investigated on spiked flour (see Figure 4.1):
Buffer;
Acetonitrile and buffer (80:20, v:v);
Acetonitrile and buffer (80:20, v:v) with QuEChERS;
Acetonitrile and buffer (80:20, v:v) with QuEChERS with subsequent evaporation and
redissolution in eluent A;
Acetonitrile and buffer (50:50, v:v);
Acetonitrile and buffer (50:50, v:v) with subsequent evaporation and redissolution in
eluent A;
Acetonitrile and buffer (50:50, v:v) with 1:1 (v:v) dilution with water before injection.
The use of buffer only gave low recoveries and was discarded. The buffer-acetonitrile
combination gave good results, but showed fronting. The same was observed with the
QuEChERS method, which did not show good phase separation in the solutions. An attempt
was made to heighten the recovery and lower the fronting of peaks in the latter method by
evaporating and redissolving in eluent A. This indeed helped for DON, however not for D3G.
Therefore, this method was also not continued.
0
20
40
60
80
100
120
Buffer QuEChERS QuEChERS
with
evaporation
ACN:buffer
(80:20)
ACN:buffer
(50:50)
ACN:buffer
(50:50) with
dilution
ACN:buffer
(50:50) with
evaporation
Rec
ov
ery
(%
)
DON D3G
Figure 4.1: Summary of researched possible extraction methods used on spiked flour. The amount of
D3G recovered in both QuEChERS methods was under the LoD.
27
The decision to use the extraction method acetonitrile and buffer (50:50, v:v) with 1:1 (v:v)
dilution before injection with water was based both on the recovery of DON and D3G and the
shape of the peaks. The 1:1 (v:v) dilution gave far less fronting in their peaks than the
undiluted samples and the recovery of D3G was better. In Figure 4.2 an MRM-chromatogram
is illustrated.
Figure 4.2: Total ion chromatogram (TIC) of two flour samples (no enzymes), one spiked with
DON (above) and one spiked with D3G (below).
28
4.2. OPTIMISATION OF THE MATRIX DIGESTION
Several flour samples and blanks were spiked with DON, D3G, both or none. To these
samples proteinase K, α-amylase, lipase, all enzymes or none were added. To some of the
samples, digested with all the enzymes, laminarinase was added after digestion.
With the acetonitrile-buffer (50:50, v:v) extraction with 1:1 (v:v) dilution before injection,
it became clear traces of DON was present in the flour used, even without spiking, possibly
due to natural contamination of the flour. The exact amount could not be measured, as it was
below to the LoQ. If any D3G was present, it was below the LoD. It should also be noted that
the D3G reference standard contained a small amount of DON, though again below the LoQ
at the normal spiking level.
4.2.1. Recovery of DON
The results of the effect of the matrix digestion on the recovery of DON is summarised in
Figure 4.3.
The presence of the enzymes seems to lower the DON detected instead of increasing it.
The LoD en LoQ for DON were relatively stable throughout the experiments. The LoD
0
10
20
30
40
50
60
70
80
90
no enzymes proteinase K α-amylase lipase all enzymes
Rec
ov
ery
(%
)
DON spike in flour DON spike in blank
DON and D3G spike in flour DON and D3G spike in blank
Figure 4.3: Summary of the DON recovery after spiking. DON was either spiked alone or with D3G.
All tests were performed in double. The term ‘blank’ means no flour was present in the sample.
29
fluctuated around 3 ng/mL and the LoQ about 10 ng/mL. The samples to which proteinase K
and all enzymes were added gave comparable results.
In the samples where only D3G was present as standard and enzymes were added, amounts
of DON were found (Figure 4.4). They were all above the LoQ, though still close to this
value. The recovery of D3G was not influenced in these instances.
4.2.2. Recovery of D3G
The effect of enzyme matrix digestion on the recovery of D3G for separate and all
enzymes together is summarised in Figure 4.5. The recovery in the spiked sample not
containing enzymes was below the LoQ. A part of the samples (no enzymes and all enzymes)
was therefore remade in a smaller experiment and now the recovery was much higher (Figure
4.6). LoD and LoQ were relatively stable: the LoD was approximately 5 ng/mL and the LoQ
13 ng/mL.
Though D3G could be detected when the standard series in buffer solution was injected
within two days of manufacture, the series showed no D3G presence when injected about a
week after manufacture. This happened twice in the course of the investigation. Several MS
0
0,1
0,2
0,3
0,4
0,5
0,6
0,7
blank proteinase K α-amylase lipase all enzymes all enzymes +
laminarinase
ab
solu
te a
mo
un
t (n
mo
l)
DON D3G
Figure 4.4: Summary of the absolute amount of DON and D3G found in samples that were spiked
with only D3G. In the blank the amount of DON was under the LoD. All tests were performed in
double.
30
fragment ion scans and a parent ion scan was performed to research this problem, but no other
adduct ions or different parent ions were found.
0
10
20
30
40
50
60
70
80
no enzymes proteinase K α-amylase lipase all enzymes
Rec
over
y (
%)
D3G spike in flour D3G spike in blank DON/D3G spike in flour DON/D3G spike in blank
0
20
40
60
80
100
120
140
160
180
flour without enzymes blank without enzymes flour with all enzymes blank with all enzymes
Rec
ov
ery
(%
)
first experiment second experiment
Figure 4.5: Summary of D3G recovery after spiking. D3G was either added alone or with DON. All
experiments were performed in double. The recovery for D3G alone in flour with no enzymes added
was below the LoD.
Figure 4.6: Comparison of two experiments to establish the recovery for D3G. D3G was spiked
alone. All experiments were performed in double. The recovery for D3G in flour with no enzymes
added in the first experiment was below the LoD.
31
The laminarinase did not seem to work when added after digestion under the circumstances
described earlier (see 3.3.1. and Figure 4.7). Even though a smaller amount of D3G was
found when laminarinase was added to flour spiked with DON and D3G, this was not
accompanied by a rise in DON as expected. Therefore a small experiment was set up to
optimise the experiment circumstances. The pH of a small volume buffer was lowered to 6
and 5. The laminarinase was incubated with for 30 minutes at 37 °C at either pH 5, 6 or 7.4
and no other enzymes were added. Samples either contained flour or no matrix (blanks). No
effect was found. The recovery for D3G was comparable to the samples without laminarinase
(see Table 4.1): This amount was estimated between 120% to 140% for both flour and blank
samples.
D3G in flour (%) D3G in blank (%)
pH 5 108.0 ± 10.1 115.9 ± 4.3
pH 6 115.6 ± 4.6 115.6 ± 11.4
pH 7.4 117.2 ± 6.4 114.7 ± 7.4
0
10
20
30
40
50
60
70
80
90
DON spiked D3G spiked DON in DON/D3G
spiked
D3G in DON/D3G
spiked
Rec
ov
ery
(%
)
all enzymes in blank all enzymes and laminarinase in blank
all enzymes in flour all enzymes and laminarinase in flour
Table 4.1: Comparison of the recovery for D3G when laminarinase was added at different pH values.
Results are given as recovery ± standard deviation. All tests were performed in triple.
Figure 4.7: Comparison of the recoveries for DON and D3G when laminarinase is or is not present
after matrix digestion. All experiments were performed in double.
32
5. DISCUSSION
5.1. EXTRACTION METHOD
Research was mainly focussed on the optimisation of the extraction method and several
possibilities were taken into account. Most of them were based on a mix of acetonitrile and
buffer solution as basis, as literature showed a preference for mixes of acetonitrile and water.
Though QuEChERS was attempted, it was not used as the final extraction method, as
recovery was low for DON to non-existent for D3G. The latter might be too polar to move to
the acetonitrile separate phase that ought to arise, as literature has suggested (Cirlini et al.,
2012, Dall'Asta et al., 2012).
The recovery of D3G changed overtime. During the first experiments, it was estimated on
60% to 70% at best. When some experiments were repeated, however, the recovery rose to
approximately 120%. No explanation for this phenomenon was found, though it might be
linked to another strange occurrence: the apparent destruction of D3G in the standard series
prepared in buffer solution. Several MS scans were performed on the standard with the
highest level to find possible degradation or fragment ions, but none were found. Also, a
parent ion scan was performed to observe possible different parent ions (normally mainly the
acetate adducts were focussed upon) with again no results. It might be possible that these
were present but not detected. The Micromass Quattro Ultima PT is more suited as a
quantification instrument than as an identification instrument. A possible cause is an
interaction with a chemical in the buffer solution, but since the standard series had been
prepared before in buffer solution without apparent problems, it seems unlikely that this was
the only cause. Another possibility is the HPLC vials used, as these were changed to another
type a few days before the standard series that first showed this problem were prepared.
Again, it seems unlikely that this was the only cause. It might be that these two possibilities
enhanced one another, however, speeding the process up. Possibly, the same process was
responsible for the change in recovery during the study. No suggested cause could be pointed
as the only possibility however. This could either be researched further, or it must be
attempted to measure samples containing D3G as soon as possible after preparation.
As explained under 3.4.5, several calculations for the LoD and LoQ can be used. When the
LoDs and LoQs found in this study are converted to w:w values (see Calculation 3.4), as can
be found in literature, the following values can be found: 0.12 µg/g and 0.40 µg/g resp. for
DON and 0.20 µg/g and 0.52 µg/g resp. for D3G. In comparison to the values found in
literature (for examples see Tables 1.1 to 1.3), these are rather high: most values in literature
can be found in the µg/kg order of magnitude. The calculation used in this study is much more
33
conservative than the more common signal-to-noise ratio however. Thus, the values found in
this study and those found in literature are not truly comparable. Additionally, the original
sample was diluted several times. While the amounts measured in the standard series are
rather low, when they are converted to w:w values, they seem much higher. Also, most
studies use, as mentioned above, a mix of acetonitrile and water as their extraction solvent,
while here a buffer solution was used instead of water. When the response of the standard
series in eluent A was compared to the response in buffer solution, it was clear that the latter’s
response was lower than the former’s. The ions present in the buffer solution seem to lower
the response of the analytes, which made determination of low amounts difficult. It must also
be stressed that no method validation was performed and the LoD and LoQ varied dependent
of the exact standard series injection.
5.2. ENZYME MATRIX DIGESTION
The enzyme digestion step was added to the sample preparation to extract and quantify
bound mycotoxins, either already present in the flour or captured there during processing.
Though no conclusions could be drawn regarding other matrices, e.g. dough or bread,
enzymatic matrix digestion did not seem fit for flour. DON and D3G recoveries were the
highest when no enzymes are present and the presence of proteinase K in particular seemed to
heighten the interference, which complicated the integration of the peak surfaces.
When looking at the differences between the enzymes, it could be noted that the recovery
when the proteinase K was used was comparable to the recovery of those samples where all
enzymes were used. This suggested that proteinase K might hydrolyse the other enzymes in
the mix. This suggestion was backed up by the fact that proteinase K is often used to
hydrolyse other enzymes and might destroy both α-amylase and lipase. It would perhaps be
useful to in future therefore use only the individual enzymes and to never add them all
together in future experiments.
Laminarinase was an enzyme that was discovered to be able to hydrolyse D3G to DON
and a glucose molecule in an unpublished study undertaken at Wageningen University. The
goal of its use in this study was to establish the sum of DON and D3G present so that if the
recovery of D3G was lower than the recovery of DON, this could perhaps be corrected.
Unfortunately, laminarinase did not seem to work under the given circumstances, though an
attempt to optimise the pH was made. Originally the enzyme was only used at pH 7.4, but in
the unpublished study the pH was 5. Therefore the pH was lowered to 6 and 5 and the
experiment was repeated. This did not activate the enzyme. The temperature (37 °C) was the
34
same as in the unpublished study and the time of incubation as well. Glucose was an inhibitor
of laminarinase and this could explain its lack of activity in samples containing flour.
However, no activity was found in the blank samples which did not contain flour. It was thus
unlikely that glucose inhibited the enzyme. There might be another chemical present in the
buffer solution that caused the inhibition of activity. The buffer used in the unpublished study
was less complex than the solution we used and, except for glucose, no other information
about possible inhibitors was given. It is possible that one of the salts contained an ion that
inhibited the enzyme.
A small amount of DON, below the LoQ, could be detected in the unspiked flour. This
amount seemed slightly higher when only D3G was spiked, which suggested the presence of a
small amount of DON present in the D3G standard. Again the amount of DON seemed higher
when enzymes were present: it could now be actually measured, as it exceeded the LoQ. As
the recovery of D3G remained stable, a possible explanation is the undetected presence of a
bound form of DON in the matrix, which is freed by the enzymes. One must be careful
however to draw this conclusion. Though the amount exceeded the LoQ, it was still very near
to it and the value has therefore a high uncertainty. Plus, the DON detected in the flour when
no enzymes were present did not seem to differ from the amount of DON found when all
enzymes were present: both were below the LoQ. It might be possible that the presence of
DON in both the flour and the D3G standard, together with fluctuations in the mass
spectrometer, caused the exceeding of the LoQ.
35
6. CONCLUSIONS
The goal of this study was to ascertain the fate of DON and D3G when present in flour that
is made into bread. To make certain that all forms of DON, whether they were free, bound or
conjugated and extractable, would be detected, the possibility of enzymatic matrix digestion
was researched. Because several preparation steps took longer than was previously assumed,
only the extraction method and enzyme matrix digestion were researched. The rest of the
study would have to be continued later.
The extraction method with the highest recoveries for both DON and D3G as well as the
least interference was chosen. This was a mix of acetonitrile and buffer solution in a 50:50
(v:v) relationship with a 1:1 (v:v) dilution with water before injection. Recovery was 70% to
80% for DON.
The recovery for D3G nearly doubled in the course of this study. At the same time, it was
discovered that D3G seemed to get destroyed in the standard series prepared in buffer solution
when it was kept for more than a couple of days. A possibility is the enhancement of a buffer
solution effect by a new type of glassware, but this was not further investigated due to a lack
of time. It might be advisable to measure samples containing D3G as close as possible to
preparation.
A small amount of DON was present in the flour used as matrix. It was below the LoQ and
thus could not be measured. It is not certain if the presence of enzymes might release DON
from the matrix.
Laminarinase, an enzyme that ought to convert D3G to DON and glucose, did not work
under the circumstances used in this part of the study. An unknown inhibitor in the buffer
solution might be the cause.
The enzyme matrix digestion did not result in higher recoveries when used on flour
matrices. More than that, interference was higher when proteinase K was present. It was also
suspected that this enzyme might destroy the other enzymes present. Thus, it might be more
economical to no longer add all enzymes together to samples, as this gives no further
information.
In the next part of the study, several stadia in the breadmaking process will be examined,
e.g. dough, kneaded dough, proofed dough and bread itself. It might be necessary to adapt the
sample preparation to each of these stadia, as the matrix will have changed after every step.
Likewise, it might be feasible to use enzymatic matrix digestion on one of these steps, even if
it does not add to the results of the starting product, i.e. the flour. If it turns out enzymatic
matrix digestion is not suited for this kind of research at all, it might be considered to change
36
the buffer solution used in the extraction solvent to water. This will make the response on the
mass spectrometer rise and might have a positive effect on the conservation of samples
containing D3G. It might be advisable nevertheless to measure those samples containing D3G
as soon as possible after preparation.
37
7. LITERATURE LIST/REFERENCES
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Abdel-Aal, E.-S. M., K. Miah, J. Christopher Young and I. Rabalski (2007). "Comparison of
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Berthiller, F., C. Dall'Asta, R. Schuhmacher, M. Lemmens, G. Adam and R. Krska (2005).
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of Agricultural and Food Chemistry 53(9): 3421-3425.
Berthiller, F., R. Krska, K. J. Domig, W. Kneifel, N. Juge, R. Schuhmacher and G. Adam
(2011). "Hydrolytic fate of deoxynivalenol-3-glucoside during digestion." Toxicology Letters
206(3): 264-267.
Bhat, R., Y. Ramakrishna, S. R. Beedu and K. L. Miunshi (1989). "Outbreak of trichothecene
mycotoxicosis associated with consumption of mould-damaged wheat products in Kashmir
Valley, India." Lancet 1(8628): 35-37.
Boyacioglu, D., N. S. Hettiarachchy and B. L. D'Appolonia (1993). "Additives Affect
Deoxynivalenol (Vomitoxin) Flour during Breadbaking." Journal of Food Science 58(2): 416-
418.
BRENDA - The Comprehensive Enzyme Information System. EC 3.1.1.3 - triacylglycerol
lipase, Technische Universität Braunschweig. url: http://www.brenda-enzymes.org/
(consulted on 20-02-2013)
BRENDA - The Comprehensive Enzyme Information System. EC 3.2.1.1 - alpha-amylase,
Technische Universität Braunschweig. url: http://www.brenda-enzymes.org/ (consulted on 20-
02-2013)
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