towards enhanced amine detection for plasma samples with ... · towards enhanced amine detection...

Universiteit van Amsterdam

Towards enhanced amine detection for plasma samples

with UPLC-MS/MS for metabolomic studies

Master Research Thesis by

W.F. Duvivier

Master of Science

Analytical Sciences

2010 – 2011

Master Research Thesis by

W.F. Duvivier

Daily Supervisor

Ing. S. Shi

Supervisors

Dr. W.Th. Kok

Dr. R.J. Vreeken

Second Reviewer

Prof. Dr. P.J. Schoenmakers



W.F. Duvivier

Table of contents

List of abbreviations 1

Abstract 2

Samenvatting 3

Preface 4

Chapter 1: Introduction 5

1.1 Metabolomics 5

1.2 Metabolites 6

1.3 Analytical approaches in metabolomics 7

1.4 Compound specific analysis: amino acids and amines 9

1.5 Aim of this project 11

Chapter 2: Synthesis of a new derivatization reagent 13

2.1 Introduction 13

2.2 Materials and methods 13

2.3 Results and discussion 15

2.4 Recommendations 18

Chapter 3: Analytical optimisation 20

3.1 Introduction 20

3.2 Materials and methods 20

3.3 Results and discussion 26

3.4 Recommendations and further research 35

Chapter 4: General conclusions 36

Acknowledgements 38

References 39

Attachments 41



W.F. Duvivier 1

List of abbreviations

ACN Acetonitrile

AMQ 6-aminoquinoline

ANOVA Analysis of Variance

AQC 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate

CSF Cerebrospinal Fluid

DCE Dichloroethane

DCM Dichloromethane

DMF Dimethylformamide

DSC di(N-succinimidyl)carbonate

EDTA Ethylenediaminetetraacetic acid

ESI Electrospray Ionization

FMOC 9-fluorenylmethylchloroformate

FT-MS Fourier Transform-Mass Spectrometry

GC Gas Chromatography

HILIC Hydrophilic Interaction Chromatography

HMDB Human Metabolome Database

HPLC High Performance Liquid Chromatography

IR Infrared

LC Liquid Chromatography

LOD Limit of Detection

LOQ Limit of Quantification

m/z Mass-to-charge ratio

MeOH Methanol

MRM Multiple Reaction Monitoring

MS Mass Spectrometry

NMR Nuclear Magnetic Resonance

OPA Ortho-phthalaldehyde

PITC Phenylisothiocyanate

RP Reversed Phase

RSD Relative Standard Deviation

SRM Selected Reaction Monitoring

SSA Sulfosalicylic Acid

t-BuOK Potassium-tert-butoxide

UPLC Ultra Performance Liquid Chromatography

UV Ultraviolet



W.F. Duvivier 2

Abstract

To acquire better understanding of diseases and their biomarkers, profiling methods are a

powerful tool to study a certain metabolic compound class. Recently, an amine profiling

method using AccQ·Tag (AQC) derivatization and UPLC-MS/MS is developed and validated

for CSF samples [1].

In the search for a new derivatization reagent with enhanced performance in negative ion-

mode MS-detection, 5-nitro-6-isocyanatoquinoline has been synthesized. This isocyanate

will, theoretically, result in AQC-like derivatized amines with an additional nitro functional

group. The applicability of this reagent has to be tested in future studies.

In addition, the established profiling method [1] has been optimised for application to

various kinds of plasma samples. Therefore, an adjustment has been made to the sample

preparation: the amount of methanol added to the sample for protein precipitation has been

raised to 150 µL. A full validation for mouse plasma has been performed, and two

comparisons have been made to gain more insight in the extendibility of this validation to

other types of plasma samples.

The method is successfully validated for almost 60 compounds in mouse plasma with a LOD

range of 7 ng/mL – 1.2 µg/mL. One important outcome of the validation is an observed day-

to-day batch effect.

The results of the comparisons show that there are no significant differences in the

performance of the method when analysing plasma samples of different species (human,

mouse or rat) or taken with different anti-coagulants (citrate, EDTA or heparin).

Overall can be concluded that the applicability of the amine profiling method is extended

and several leads to enhancing the method by using a new derivatization reagent are

proposed. Especially raising the yield and purity of the synthesized isocyanate requires high

priority for future projects. From an analytical point of view, the anomalies which came up

during the comparisons need more in-depth investigations. Next to this, validation of the

method for rat and human plasma samples has to be completed.



W.F. Duvivier 3

Samenvatting

Profiling methoden zijn een krachtig middel om meer begrip te krijgen van ziekten en hun

signaalstoffen. Met deze methoden is het mogelijk om een bepaalde groep metabolieten te

bestuderen. In de afgelopen jaren is een UPLC-MS/MS methode voor de profiling van aminen

opgezet en gevalideerd voor CSF monsters, hierbij wordt gebruik gemaakt van de AccQ·Tag

(AQC) derivatizering [1].

In de zoektocht naar een nieuw derivatizeringsreagens met verbeterde prestaties in negatieve

ion-mode bij MS-detectie, is 5-nitro-6-isocyanatoquinoline gesynthetiseerd. Dit isocyanaat

zal, theoretisch, resulteren in gederivatiseerde AQC-achtige aminen met een extra nitro-

functionele groep. De toepasbaarheid van dit reagens moet worden getest in toekomstige

studies.

Daarnaast is de gevestigde profiling methode [1] geoptimaliseerd voor toepassing op

verschillende soorten plasmamonsters. Hiervoor is een aanpassing gemaakt aan de

monstervoorbereiding: de toegevoegde hoeveelheid methanol voor denaturatie van het eiwit

in de monsters is verhoogd naar 150 µL. Een volledige validatie voor muisplasma is

uitgevoerd, en twee vergelijkingen zijn gemaakt om meer inzicht te verkrijgen in de

toepasbaarheid van deze validatie op andere plasmasoorten.

De methode is succesvol gevalideerd voor bijna 60 amine verbindingen in muisplasma met

een detectielimiet van 7 ng/ml tot 1.2 µg/ml. Een belangrijke uitkomst van de validatie is het

waargenomen dag-tot-dag batch effect.

Uit de resultaten van de vergelijkingen blijkt dat er geen significante verschillen zijn wat

betreft de werking van de methode bij de analyse van plasmamonsters afkomstig van

verschillende diersoorten (mens, muis of rat) of die zijn genomen met verschillende

antistollingsmiddelen (citraat, EDTA of heparine).

In het algemeen kan geconcludeerd worden dat de toepasbaarheid van de amine profiling

methode is vergroot en een aantal aanknopingspunten voor de synthese van een nieuw

derivatizeringsreagens zijn beschreven. Vooral het verhogen van de opbrengst en zuiverheid

van het gesynthetiseerde isocyanaat vereist hoge prioriteit voor toekomstige projecten.

Vanuit een analytisch oogpunt vereisen de afwijkingen die naar voren kwamen uit de

vergelijkingen meer onderzoek. Verder is volledige validatie van de methode voor rat en

humaan plasma gewenst.



W.F. Duvivier 4

Preface

The main goal of this master research project is to enhance amine profiling for metabolomic

studies. To acquire better understanding of diseases and their biomarkers, profiling methods

are a powerful tool to study a certain metabolic compound class. In the last few years, an

amine profiling method is compiled and validated for CSF samples [1]. This method is the

starting point of this thesis. Evaluation of the derivatization and analytical optimisation of the

method should provide us with more insight in possibilities to enhance the sensitivity and

applicability to other biological samples types.

Chapter 1 of this thesis is an introduction into metabolomics, analytical approaches and

amino acid analysis. Also, the objectives of this project are described in this chapter. The

reported study exists of two parts: an organic synthesis and an analytical part. The aim of the

first part, described in chapter 2, is to develop a new derivatization reagent, resulting in

derivatized amines with better characteristics for detection by mass spectrometry in negative

ion-mode. Chapter 3 describes the applicability of the amine profiling method to plasma

samples of different species. General conclusions are stated in the last chapter, chapter 4.

All the research described in the thesis is carried out at Leiden University in the Analytical

BioSciences group under supervision of ing. S. Shi and dr. R.J. Vreeken.



W.F. Duvivier 5

Chapter 1: Introduction

1.1 Metabolomics

Metabolomics, sometimes also referred to as metabonomics, studies small-molecule

metabolite profiles and provides us with information about the metabolic state of cellular

systems in different conditions (e.g. healthy and diseased) [2]. Metabolite profiles reflect the

combined effects of many influences, such as drugs, environment and nutrition, and result

into a better understanding of cellular biochemistry. Metabolomics is one of the newest

“omics” and is applicable for medical, diagnostic, food and industrial microbiology among

others [3].

Figure 1.1: Metabolomics as part of functional genomics [4].

In the search for a better view on the role of different biochemical processes and related

diseases, metabolomics is one of the key techniques. By studying the chemical profiles of

these processes, metabolic pathways and their workings can be unscrambled, hopefully

leading to better understanding of diseases and their causes. Especially the search for

biomarkers, which could contribute to the discovery of a certain disease in an early state, has

been a hot topic in metabolomics over the last few years.



W.F. Duvivier 6

Figure 1.2: Alanine, aspartate and glutamate metabolism in humans [5].

1.2 Metabolites

The metabolites which are studied in metabolomics belong to a wide range of different

compounds classes (figure 1.3). This study focuses on biogenic primary and secondary

amines, among which amino acids.

← More non-polar More polar →

Carotenoids

Steroids

Phenolics

Alcohols

Alkaloids

Organic acids

Organic amines

Sugars

Nucleotides

Flavenoids

Catecholamines

Polar organics

Nucleosides

Amino acids

Metals

Ionic compounds

Figure 1.3: Rough overview of metabolomic compound classes [6].

Amines are organic compounds which contain a basic nitrogen atom with a lone electron

pair. They can be distinguished in primary, secondary and tertiary amines based on the

number of substituents (respectively one, two and three) on the nitrogen atom. Amino acids



W.F. Duvivier 7

are vital as building blocks of proteins and have many functions in metabolism. Each amino

acid contains an amino group, a carboxylic functionality and a so-called “R” side chain, which

differs for each amino acid (e.g. –CH3 for Alanine). Humans must include 9 of the 20 standard

amino acids in their diet; these amino acids can not be metabolized or synthesized from

other compounds.

Amines play an important role as signal compounds and parts of metabolomic pathways

which are influenced by diseases such as Parkinson and other central nervous system

diseases. They may have multiple roles in mechanisms that among others can affect body

temperature, psychomotor functioning and pain. In the case of Parkinson, disorders of amine

metabolisms comprise a wide spectrum of symptoms, with motor dysfunction being the most

prominent clinical feature [7].

This project focuses on the analysis of amines in different matrices, mostly blood plasma and

cerebrospinal fluid (CSF). Blood plasma is the whole blood minus the blood cells and contains

dissolved proteins, glucose, clotting factors, mineral ions, hormones and carbon dioxide. On

the other hand, CSF is a clear body fluid that is taken from around the spinal cord. CSF

contains less plasma proteins and is produced at a rate of 500 ml/day. The concentration of

most biogenic amines is lower in CSF than in blood plasma [8].

1.3 Analytical approaches in metabolomics

In most cases, sample preparation depends much on the targeted group of metabolic

compounds. The extraction type and procedure, for example, are matched with the chemical

properties of the investigated compound group [4]. Due to this focusing, metabolomics

might seem to be a little less challenging from an analytical point of view. Nevertheless, the

high chemical complexity within a specific group of compounds, the wide dynamic range and

the large biological variance make metabolomics an analytical challenging exercise.

Most analytical methods in metabolomics are based on separation techniques like GC (gas

chromatography) and HPLC (high performance liquid chromatography) or UPLC (ultra

performance liquid chromatography) coupled to different mass spectrometry (MS)

techniques or nuclear magnetic resonance (NMR) spectroscopy. Generally, mass

spectrometers are more selective and more sensitive compared to other types of detectors.

However, as stated by Zhang et al. [9], NMR is in some cases very suitable for metabolomic

research: “NMR might be less sensitive, but the data from NMR experiments is often more

easily quantitated and highly reproducible. In particular, the same nuclei detected (i.e. all 1H)

in an NMR experiment have the same sensitivity, independent of the properties of metabolite

molecules. Therefore, the absolute quantities of different metabolites can be measured with a

single internal or external standard. In addition, NMR requires minimal or no sample

preparation or separation, and is non-destructive.” This research project focuses though on

the use of mass spectrometry based methods.

Before compounds can be detected using MS, they have to be ionized and, preferably,

separated. Ionization techniques may vary, especially for GC-MS and LC-MS couplings. Also

the separation mechanisms in LC are various: hydrophilic and small, charged molecules are

best suited for capillary electrophoresis [10], reversed-phase chromatography can be used for



W.F. Duvivier 8

hydrophobic compounds [11] and hydrophilic and neutral compounds are well separated by

hydrophilic interaction chromatography (HILIC) [3][12].

Metabolic MS-analysis can be roughly divided into two approaches: targeted and non-

targeted. The aim in non-targeted methods is to cover the metabolome as broadly as

possible while at the same time maintaining the ability to at least differentially quantify the

metabolites. This way, it is possible to detect changes in metabolomic profiles, but also allows

detection of previously unknown or poorly characterized metabolites [13].

The aim in targeted methods is to quantitatively analyse a specific, biologically relevant,

metabolite class. More and more common are methods which cover over 100 metabolites of

a specific category. In targeted strategies predefined metabolite-specific signals are often

used to precisely and accurate determine relative abundances and concentrations of a limited

number of pre-known and expected endogenous metabolites [14].

A common used MS/MS (or MS2) detection mode for targeted metabolomics is selective

reaction monitoring (SRM). As shown in figure 1.4a, ions with a selected m/z value are

isolated into the collision cell. After collision induced dissociation, only the fragments with a

certain, forehands chosen, m/z value are lead into the detector. No time is wasted on

acquiring non-relevant data, which leads to maximum sensitivity [15].

Figure 1.4: Selective reaction monitoring (a) and precursor-ion scan (b) in MS/MS [15].

When using chromatographic separation, SRMs can be time-programmed to avoid

measuring irrelevant m/z values during analyte elution and thereby maximizing the

sensitivity. This technique is known as multiple reaction monitoring (MRM) [14][15].

While studying a metabolite class for which all the different metabolites fragment into a

specific fragment, it is possible to use a precursor-ion scan to obtain an overview of the most

abundant compounds. In a precursor-ion scan, MS2 can be set to a m/z value characteristic

to the studied metabolite class, while MS1-detection is scanned. This way, only ions which

fragment into the predefined fragment will be detected (figure 1.4b). [14] An example of the

use of a precursor-ion scan is described by Rochfort et al. [16]. This study shows a wide range

of aliphatic, alkenyl and indole glucosinolates which all fragment into a fragment of m/z 259

(figure 1.5).



W.F. Duvivier 9

Figure 1.5: Breakdown of glucosinolates to produce the characteristic m/z 259 ion [16].

1.4 Compound specific analysis: amino acids and amines

For years, the reference method for quantitative amino acid analysis was ion-exchange

chromatography followed by post-column ninhydrin derivatization [17][18]. Due to the need

for analysis of lower concentrations, methods based on reversed-phase (RP) liquid

chromatography have been developed over the last decades. The combination of pre-column

derivatization and RP-LC results not only in faster analysis (<60 min), but also in a rise of

sensitivity.

Ortho-phthalaldehyde (OPA) [19], phenylisothiocyanate (PITC) [20] and 9-

fluorenylmethylchloroformate (FMOC) [21] are among the most frequently used

derivatization reagents for amino acid analysis, but have various disadvantages. OPA, PITC

and FMOC respectively fail to react with secondary amino acids [22], bring about the need to

remove excess reagent by drying [20] and yield multiple derivatives [21].

Cohen et al. [23] demonstrated the use of 6-aminoquinolyl-N-hydroxysuccinimidyl carbamate

(AQC) as an amine derivatization reagent. This reagent reacts with amino acids in a rapid one

step procedure (figure 1.6) to form stable urea derivatives which can be analyzed by RP-LC

with fluorescence detection. The derivatization shows excellent results concerning

derivatization efficiency and tolerance of common buffer salts and detergents. Supported by

the good chromatographic characteristics of AQC-derivates, this derivatization has been used

on a wide range of products [24][25][26].

Figure 1.6: One step procedure for amino acid derivatization using AQC [23].



W.F. Duvivier 10

Boogers et al. [27] described a changeover from the Pico·Tag HPLC method to the

AccQ·Tagultra UPLC method for amino acid analysis in protein hydrolysates. The Pico·Tag and

AccQ·Tag methods are commercially available derivatization kits, which, respectively, use PITC

and AQC for the derivatization of primary and secondary amino acids. Boogers et al. found

that the total chromatographic run time of the AccQ·Tagultra UPLC method was only 40% of

the time required for the Pico·Tag HPLC method, while the quantitative results for both

methods compared fairly well.

Another (commercially developed) method for amino acid analysis is EZ:faast (Phenomenex).

It involves solid phase extraction (SPE) and liquid/liquid extraction for sample clean-up, and

subsequent reaction of the amino acids with ethylchloroformate to produce N-

ethoxycarbonyl ethylesters. These derivatives can be separated and detected using GC(-MS)

or LC-MS [28].

Recently, hydrophilic interaction chromatography (HILIC) is an innovative separation

technique and can also be used for amino acid analysis. HILIC is developed for the separation

of hydrophilic and neutral compounds among which amino acids and amines [29]. However,

HILIC is still an upcoming technique and lacks, for the moment, good reproducibility.

The last few years, mass spectrometry has been more and more used as a detection method

for AQC-derivatized amino acids [30][31]. This development is especially promising for

selective measurement of compounds at low concentrations and in complex matrices. In

theory, it is unnecessary to, baseline, separate the compounds prior to MS detection,

although this has some bottlenecks concerning co-eluting compounds (which may cause ion

suppression) or compounds with the same m/z value. Good chromatography can, almost

completely, solve these difficulties and enhance the sensitivity of the method [31].

The use of precursor-ion scans and full scan analysis of a concentrated CSF sample on a FT-

MS, in combination with information in the HMDB (Human Metabolome Database), made it

possible to expand the AQC-method from amino acid analysis to the detection and

quantification of about 60 amine containing compounds. This expanded method is validated

for CSF samples [1].

Despite of the advantages mentioned above, the AQC derivatization method is not perfect.

One of its drawbacks, is good performance in negative ion-mode. Therefore, a compound

requires negative charge stabilisation after ionization.

Measuring in negative ion-mode can enhance the sensitivity of a method. Almost all neutral

substances are able to yield positive ions, while acidic groups or electronegative elements are

needed to produce negative ions. [32] Due to the lower chemical background signal, a

compound with good performance in negative ion-mode will have a higher signal-to-noise

ratio compared with positive ion-mode. Theoretically, the decreased noise will result in a

lower detection limit for compounds with good performance in negative ion-mode [33].



W.F. Duvivier 11

1.5 Aim of this project

The aim of this project is to develop an enhanced amine profiling method, which will be used

for the detection and identification of amines in biological samples such as CSF and blood

plasma. To achieve this, a two-sided approach has been chosen: a new, improved,

derivatization reagent will be synthesized and in addition, the existing amine profiling

method [1] for CSF samples will be evaluated and validated for application to various plasma

types.

1.5.1 Organic synthesis of a new derivatization reagent

Until now, the amine profiling method has been used with positive ion-mode mass

spectrometry. After AQC derivatization and electrospray ionisation, positive ions (mostly

[M+H]+ ions) are more stable and formed more efficiently then negative ions (mostly [M-H]-).

In this project, the derivatization reagent will be modified to enhance the use of negative ion

mode. In theory, this should improve the sensitivity of the method. Fewer molecules are

ionized in the negative mode, so considerably less chemical background is observed,

providing an increased linear range and lower limits of detection [33].

AQC is easily synthesized by the addition of 6-aminoquinoline (AMQ, in dry acetonitrile), to

di(N-succinimidyl)carbonate (DSC, in dry acetonitrile) which is heated to reflux (figure 1.7).

After about 30 minutes of continued refluxing, the reaction mixture can be concentrated by

rotary evaporation and cooled for 24 hours, resulting in AQC-crystals [23].

Figure 1.7: Synthesis of AQC [23].

AQC as derivatization reagent has many advantages; the derivative has good

chromatographic characteristics and the reaction is a fast, one-step procedure. Furthermore,

it reacts instantaneous with primary and secondary amines, which makes it very suitable as

derivatization reagent for the method used in this project.

Other established methods for amino acid and amine analysis, such as ninhydrine and dansyl

derivatization [34][35] or EZ:faast [36], could be considered as well. However, because of the

previous described benefits, AQC is used as starting position for the synthesis of a new

derivatization reagent suitable for LC-MS in negative ion mode.

1.5.2 Analytical optimisation of the amine profiling method

The analytical part of this project focuses on implementation of the extended method to be

used with plasma samples and afterwards, validation of the method for this sample type.

Plasma samples are more easily obtained and available in bigger amounts, which make them

more suitable for large screening projects than CSF samples.



W.F. Duvivier 12

Validation of the method is important to ensure that the method is robust related to the limit

of detection and quantification (LOD and LOQ), linearity and repeatability. Therefore, a

validation protocol developed within the Analytical BioSciences group of Leiden University is

used, which evaluates the performance of the used method. Since plasma samples can be

taken with support of different anti-coagulants, a possible effect of these agents on the

performance of the method has to be investigated as well.



W.F. Duvivier 13

Chapter 2: Synthesis of a new derivatization reagent

2.1 Introduction

As stated in chapter 1, the AQC-derivatization method suits very well for amino acid analysis,

both with UV- and MS-detection. AQC-derivatives are best detected using positive ion-mode;

the lack of negative charge stabilisation in the derivatives causes low sensitivity in negative

ion-mode. The amine profiling method used nowadays is not sensitive enough for the

quantification of compounds of low endogenous levels. Compared to positive ion-mode, the

signal-to-noise ratio in negative ion-mode of a compound with good characteristics for

negative ionization is higher due to the lower background signal.

Derivatives with a good performance in negative ion-mode, in combination with the benefit

of negative ion-mode mentioned above, could make the method more sensitive. As stated in

the introduction, the AQC-reagent is chosen as starting point as a result of its advantages

and experience gained before.

Better performance in negative ion mode requires negative charge stabilisation in the

derivative. This can be achieved by incorporating a nitro-group in the reagent and

subsequently in the derivative. The best possibility to realize this, is the modification of

6-aminoquinoline (AMQ) before reacting with DSC (figure 2.1). The synthesis of an

aminoquinoline with an ortho-placed nitro-group (6-amino-5-nitroquinoline) was found in

literature and therefore chosen as starting point [37].

6-amino-5-nitroquinoline

N

NH2

NOO

N

O

O

O

N

O

O

O

O

+

DSC

N

NH

NOO

O

ON

O

O

+ N

O

O

OH

New derivatizing reagent

NHS Figure 2.1: Theoretical reaction scheme of 6-amino-5-nitroquinoline with DSC (based on [23]).

2.2 Materials and methods

All reactions were monitored using thin layer chromatography (TLC) and various colouring

reagents (e.g. ninhydrin and potassium permanganate).

2.2.1 Synthesis of N-tetramethylethiocarbamoylsulfenamide

4 mL ammonia solution (28-30 wt%) was injected in a 50 mL round-bottom flask which was

standing in ice mixed with salt (NaCl; -15°C) to cool the reaction . Next sodium hypochlorite

was diluted with water (1:1) to achieve a concentration of 7% sodium hypochlorite (1N). 16.5

mL of this solution was added dropwise to the ammonia, slowly enough (± 30 minutes) to

maintain the temperature below 0°C.



W.F. Duvivier 14

Ammonium N,N-tetramethylenedithiocarbamate solution (2.5 g ; 17.1 mmol in 15 mL H2O)

was added dropwise to the flask in about 15 minutes. The mixture was stirred vigorously for

30 minutes after which about 1 gram of pure sulfenamide was filtered off [38].

NS

SH

N+

H

HH

H

NS

S NH2

N-tetramethylethiocarbamoylsulfenamideAmmonia

N,N-tetramethylenedithiocarbamate

+NH4OH

NaOCl

Figure 2.2: Synthesis of N-tetramethylethiocarbamoylsulfenamide [38].

The purity of the sulfenamide was checked by 1H and 13C NMR (see attachment 1 and 2).

2.2.2 Synthesis of 6-amino-5-nitroquinoline

1.12 g (1.00 mmol) potassium-tert-butoxide (t-BuOK) was dissolved in 6 mL

dimethylformamide (DMF) under argon. A solution of 0.66 g (3.80 mmol) 5-nitroquinoline

and 0.74 g (4.56 mmol) sulfenamide (N-tetramethylethiocarbamoyl-sulfenamide, synthesis

described in paragraph 2.2.1) in 2 mL DMF was added dropwise to the t-BuOK solution over a

period 5 minutes. After 50 minutes of continued stirring, the mixture was poured into 100 mL

cold water. Subsequent to extraction with three times 60 mL dichloroethane (DCE), the DCE-

fraction was washed with 200 mL water and dried with Na2SO4 [37].

+N

NO O

N

NO O

NH2

6-amino-5-nitroquinoline

NS

S NH2

5-nitroquinoline

t-BuOK

carbamoylsulfenamideN-tetramethylethio-

Figure 2.3: Synthesis of 6-amino-5-nitroquinoline [37].

After filtration, the filtrate is chromatographically purified and characterized using 1H NMR

and TLC-MS (see attachment 3 and 4). 0.21 g (1.11 mmol) 6-amino-5-nitroquinoline was

yielded (29% of crude product).

2.2.3 Synthesis of an AQC-based derivatization reagent

0.15 g (0.60 mmol) of DSC (di(N-succinimidyl) carbonate) was dissolved in 10 mL dry

acetonitrile and heated to reflux. 6-amino-5-nitroquinoline (0.1 mg ; 0.50 mmol), dissolved in

8 mL of dry acetonitrile, was added dropwise to the refluxing carbonate solution in 30

minutes. After an additional 30 minutes of reflux the reaction mixture was concentrated by

rotary evaporation to about half its volume. The solution was cooled for 24 hours and the

resulting crystals were filtered.



W.F. Duvivier 15

2.2.4 Synthesis proposal for 5-nitro-6-isocyanatoquinoline

0.19 g (1.00 mmol) 6-amino-5-nitroquinoline was dissolved in 10 mL dry dichloromethane

(DCM) at 0°C under argon. 0.6 mL (1.14 mmol) phosgene (20% in toluene) was added

dropwise. The solution was stirred for 15 minutes, and NEt3 (0.4 mL; 2.9 mmol) was added.

After an additional 15 minutes of stirring, the solution was concentrated using rotary

evaporation [39].

N

NO O

NH2

+O

Cl Cl N

NO O

N

O + ClH

ClH

N

NO O

N

O+ Cl

-

6-amino-5-nitroquinoline Phosgene

5-nitro-6-isocyantoquinoline

5-nitro-6-isocyantoquinoline

Et3H+-HNEt3

Figure 2.4: Reaction scheme of 6-amino-5-nitroquinoline with phosgene [39].

2.2.5 Modified synthesis proposal for 5-nitro-6-isocyanatoquinoline

0.050 g (0.26 mmol) 6-amino-5-nitroquinoline (dissolved in 10 mL DCM, under argon) was

added dropwise to 0.7 mL (1.33 mmol) phosgene (20% in toluene, under argon at 0°C). A

yellow, turbid solution is formed, which becomes clear and more orange after the addition of

three equivalents of NEt3 (0.15 mL ; 1.09 mmol). Also, a white gas is formed. After rotary

evaporation, the residue was analyzed again.

2.3 Results and discussion

The main goal of the first part of this project was to develop a new derivatization reagent for

amines which has good properties for negative ion mode. As noted in the introduction of this

chapter, the chosen route to achieve this goal was to modify the AQC reagent by adding a

nitro-group to the part of the reagent that will be attached to the target compound.

The first step involved the synthesis of N-tetramethylethiocarbamoylsulfenamide, which was

necessary to enable synthesis of the desired quinoline: 6-amino-5-nitroquinoline. Both the

sulfenamide as the amino-nitroquinoline were obtained with only minor contaminations as

shown by the NMR spectra in the attachments.

2.3.1 Synthesis of new, AQC-based, reagent

The reaction of 6-amino-5-nitroquinoline with DSC, as described above, did not result in the

desired product; a new AQC-based reagent. The formed crystals did not contain the product

aimed for, but consisted of pure 6-amino-5-nitroquinoline and DSC (the starting products).

Several new experiments with adjustments to the protocol were performed (e.g. longer

refluxing, etc.), but without any improvements concerning the resulting compounds.



W.F. Duvivier 16

There are a couple of possibilities, or combinations of these possibilities, why this synthesis

protocol did not result in the compounds aimed for. Theoretically, the amine-group of the

synthesized amino-nitroquinoline is less nucleophile as the amine-group of the original

quinoline, 6-aminoquinoline, which is not very nucleophile to begin with. The nitro-group

pulls electrons away from the amine-group, causing lower reactivity.

Another possibility is stabilization due to hydrogen bonding. By tautomeric structures, a

hydrogen bond could be formed between the nitro- and the amine-group. Besides that,

there could be a steric effect from the nitro-group, which is positioned next to the amine-

group.

It is not likely that a different modification of the quinoline would have given better results.

When the nitro-group is situated on the other side of the amine-group, but still ortho-placed,

it would have the same disadvantages as the used quinoline.

Meta-placed nitro-groups (figure 2.5a) are not easy, or not even possible, to synthesis. A

para-placed group would theoretical give a more reactive compound, but changes the

reaction mechanism by dislocating the amine-group (figure 2.5b).

N

NOO

NH2N

NH2

NO O

N

NOO

NH2

A B

Figure 2.5: Possible amino-nitroquinolines with a; meta-placed groups and b; para-placed groups

2.3.2 Second synthesis proposal

After the disappointing results of the first synthesis procedure, several different options were

considered. Instead of continuing with trying to synthesis an AQC-like reagent, another

pathway was chosen, in which the amine-group of the amino-nitroquinoline was replaced by

an isocyanate (figure 2.4). This isocyanate can theoretically react with amines, as shown in

figure 2.6, resulting in the same derivatized amine as previously aimed for.

N

NO O

N

O+ NH

R1

R2

N

NO O

NH

O

N

R1

R2

5-nitro-6-isocyanatoquinolineAmine or amino acid

Derivatized amine Figure 2.6: Theoretical reaction scheme of an isocyanate with an amine or amino acid



W.F. Duvivier 17

Direct-infusion mass spectrometry analysis of the reaction mixture showed a spectrum with

high abundant m/z-values of 102, 190, 203, 239 and 405 (figure 2.7). Interpretation of these

m/z-values implies that 6-amino-5-nitroquinoline was still present in the reaction mixture

(m/z 190) and dimerization of the amino-nitroquinoline with the isocyanate takes place (m/z

405). This implies that the isocyanate is formed, but reacts with the surplus of amino-

nitroquinoline. M/z 102, 203 and 239 are most likely by-products of the synthesis.

Figure 2.7: Mass spectrum after direct infusion of reaction mixture with a possible dimmer structure

A new synthesis protocol was composed to achieve better results (paragraph 2.2.5). In this

protocol, some changes were made to avoid dimerization: 6-amino-5-nitroquinoline was

dissolved in a larger volume and this time added dropwise to the phosgene to prevent the

formed isocyanate to react with a surplus of amino-nitroquinoline.



W.F. Duvivier 18

Figure 2.8: Mass spectrum after direct infusion of reaction mixture

The resulting reaction mixture was again analyzed by direct-infusion MS. The results of this

analysis (figure 2.8) show that the desired product is actually formed, indicated by an m/z-

value of 216. Also m/z-values 190, 239 and 405 are still relatively high abundant. Next to that,

a lot of other, lower, m/z-values are present, which most likely are by-products.

Different quick, tests were done to examine a possible derivatization reaction between the

synthesized isocyanate and several amino acids. The results did not show new products to be

formed, but the yield of the synthesis was too small to achieve significant and thorough

testing.

2.4 Recommendations

A few recommendations regarding the synthesis are already mentioned in the discussion

section. The taken synthesis pathway was chosen based on the complexity of the synthesis

steps and the availability of the required chemicals. There are more possibilities to synthesis

the same compounds, which could be investigated in future studies to study the yield and

purity. The use of a catalyst could be considered to achieve this goal.

Adding another functional group to the reagent should be considered as well. Theoretically,

good results could be expected when adding a carboxylic acid or Fluor group.

Also, looking into other possible derivatization reagents could pay off. Next to AQC, EZ:faast

is another frequently used method for amino acid analysis which includes sample clean up by

SPE and liquid/liquid extraction [36].



W.F. Duvivier 19

2.4.1 Synthesis of isocyanate

With more time, experience with and knowledge of organic chemistry, it should be possible

to optimize the synthesis of the isocyanate. After modification of the reaction conditions, the

difficulty of the dimerization of the isocyanate with 6-amino-5-nitroquinoline was partly

solved. Another, but harder, option is to cool the reaction with liquid nitrogen or an acetone

bath. This is a more time and work consuming option, but could be investigated to gain yield

and purity. With a higher yield and purity, more and better testing could be done regarding

its derivatization properties.

In the synthesis protocol used in this project, phosgene is used for the formation of an

isocyanate. The toxicity of phosgene could be a drawback for the production of larger

amounts of the reagent. There are other synthesis pathways that lead to the sought

isocyanate, one of them is described below:

The first step in this pathway is the conversion of the amino-group of 6-amino-5-

nitroquinoline into an urethane-group. This can be achieved by the addition of triethylamine

and methylchloroformate, after which the reaction mixture is extracted, washed, dried and

filtered as described by Wilson et al. [40]. The urethane-group synthesized compound can be

converted into an isocyanate by the addition of chlorocatecholborane and refluxing [41].

N

NO O

NH2

N

NOO

NH

O

OCH3

N

NO O

N

O

6-amino-5-nitroquinoline 5-nitro-6-urethanequinoline

5-nitro-6-isocyanatoquinoline Figure 2.9: Alternative synthesis pathway for 5-nitro-6-isocyanatoquinoline [40][41].

2.4.2 Reagent testing

Due to a shortage of time, it was not possible to test the product carefully. The tests that

have been done did not show any results, but more testing need to be done to get to a more

considered conclusion.

To gain more reagent, more 5-nitro-6-isocyananatoquinoline could be synthesized (possibly

in several batches) and chromatographically purified. This way more and more accurate

testing is possible.



W.F. Duvivier 20

Chapter 3: Analytical optimisation

3.1 Introduction

This part of this research project focuses on the further development and optimisation of the

amine profiling method described by Shi et al. [1]. With this UPLC-MS/MS method based on

Waters’ AccQ·Tag method, around 60 amine containing compounds can be detected and

quantified using the benefits of UPLC and multiple reaction monitoring (MRM). UPLC results

in a higher chromatographic resolution and enables sufficient separation of the compounds

within a short run time. Besides that, MRM-mode provides us with a adequate sensitivity.

This expanded method is validated for CSF samples; validation for plasma samples of

different species is an important objective to achieve. This project was focused at human,

mouse and rat plasma samples, based on the need out of the field. Many studies are

performed on test animals before application on humans. Mice and rats are most frequently

used for these kind of studies, causing the need for an amine profiling method to be

applicable for these matrices.

Subsequently, the effect of different anti-coagulants on the method will be evaluated. Plasma

samples can be taken with support of different anti-coagulants, which may affect the

performance of the method. To ensure a wide application range, this method should be

applicable to plasma samples, irrespective of the used anti-coagulant.

3.2 Materials and methods

3.2.1 Chemicals

The acetonitrile (ACN), methanol (MeOH) and water (H2O) used for these experiments are all

Ultra LC-MS grade from Biosolve (Valkenswaard, The Netherlands). AccQ·Tag Ultra eluent A

and B concentrate and the AccQ·Tag Ultra derivatization kit are from Waters (Etten-Leur, The

Netherlands).

3.2.2 Standard mixes for validation and protein precipitation test

For the validation of the method and the protein precipitation test, a set of standard mixtures

is used. The composition of these mixes can be found in attachment 5.



W.F. Duvivier 21

3.2.3 Internal standards

The following labelled compounds are used as internal standards in the experiments

described below.

Labelled “Cell free” amino acid mix (U-13C, 98%; U-15N, 98%) from Cambridge Isotope

Laboratories, Inc. (Andover, USA):

Table 3.1: Content of labelled amino acid mix

Amino Acid Molar % Weight %

Aspartic Acid 5.8 6.0

Glutamic Acid 8.1 9.3

Asparagine 5.7 5.9

Serine 3.0 2.5

Glutamine 3.6 4.1

Histidine 0.6 0.7

Glycine 7.9 4.6

Threonine 5.5 5.1

Alanine 10.7 7.5

Arginine 2.8 3.9

Tyrosine 2.5 3.6

Alanine 6.8 6.2

Methionine 1.5 1.8

Tryptophan 2.5 4.0

Phenylalanine 5.5 7.1

Isoleucine 5.2 5.4

Leucine 9.1 9.3

Lysine 1.8 2.1

Proline 2.1 1.9

Cysteine 9.6 9.1

Deuterated compounds:

- β-alanine-2,2,3,3-D4

- (±)-Epinephrine-D3

- Histamine-α,α,β,β-D4-2HCl

- L-2-Aminobutyric-D6 Acid

- L-NT-methyl-D3-l-hisditine

- L-3-(4-Hydroxy-3-methoxy-D3-phenyl)alanine

- 2-(4-Hydroxy-3-methoxyphenyl)ethyl-1,1,2,2-D4-amine HCl

- (±)-Norepinephrine-2,5,6,α,β,β-D6 HCl, L-Ornithine-3,3,4,4,5,5-D6 HCl



W.F. Duvivier 22

3.2.4 Standard solutions

The above mentioned (internal) standards were dissolved in Ultra LC-MS-grade water in the

concentrations noted in table 3.2. From these stock solutions, the other concentration levels

are prepared by dilution factors of 2 between each concentration level.

Table 3.2: (Internal) Standard stock solutions

Mix Stock Solution

1 1 mg/mL

2 0.2 mg/mL

3 0.01 mg/mL

4 0.4 mg/mL

Labelled amino acids 0.1 mg/mL

Deuterated compounds 1 mg/mL*

*Already dissolved (1 mg/mL): 20 µL of each compound, 4820 µL water added (5 mL in total)

3.2.5 Plasma samples

For these experiments, pooled human (female), rat and mouse plasma samples were used,

taken from healthy populations (with heparin as anti-coagulant).

The samples used for the anti-coagulant comparison were taken from one person (female) at

one moment with different anti-coagulants: EDTA, heparin and citrate.

3.2.6 Sample pre-treatment

For biological fluids a simple protein precipitation was applied as sample pre-treatment. 10

µL of each (internal) standard dilution was added to 5 µL biological sample followed by the

addition of 150 µL* of MeOH for protein precipitation. The mixture was vortexed for 10s and

centrifuged at 10.000 rpm (9408 g) for 10 minutes at 10 °C. The supernatant was pipetted

into a sample vail and dried under N2.

The residue was dissolved in 80 µL borate buffer (Waters AccQ·Tag Ultra derivatization kit, pH

8.8), after 10s vortexing, 20 µL of AccQ·Tag reagent (dissolved in 500 µL AccQ·Tag Ultra

Reagent Diluent) was added and the mixture was vortexed immediately. This step was carried

out one by one.

The sample was heated 10 minutes at 55 °C. The heating converts a minor side product of

tyrosine to a major mono-derivatized compound.

1 µL of the derivatized mixture was injected into the UPLC-MS/MS system.

* Amount of MeOH added varied for some experiments



W.F. Duvivier 23

3.2.7 LC method

An Acquity UPLC system with autosampler (Waters) in combination with a Xevo TQ Tandem

Quadrupole mass spectrometer (Waters) was used for the experiments described below. The

column used was a AccQ·Tag Ultra 2.1x100mm (1.7 µm particle size) column (Waters), used

with mobile phase A (AccQ·Tag eluent A concentrate diluted 10 times with water) and mobile

phase B (AccQ·Tag eluent B). The LC-gradient used is shown in table 3.3.

Table 3.3: LC-gradient used for separation of the targeted compounds

Time Flow (mL/min) %A %B Curve

1 Initial 0.700 99.9 0.1 Initial

2 0.54 0.700 99.9 0.1 6

3 5.74 0.700 90.9 9.1 7

4 7.74 0.700 78.8 21.2 6

5 8.04 0.700 40.4 59.6 6

6 8.05 0.700 10.0 90.0 6

7 8.64 0.700 10.0 90.0 6

8 8.73 0.700 99.9 0.1 6

9 9.50 0.700 99.9 0.1 6

3.2.8 Mass spectrometry

MS/MS detection of the targeted amines was achieved by using selective reaction monitoring

(SRM) for each of the compounds. The SRM parameters were time-programmed to avoid

measuring irrelevant m/z values during analyte elution and thereby maximizing the

sensitivity. This technique is also known as multiple reaction monitoring (MRM). The used

SRM transitions can be found in attachment 6.

The MS/MS source and analyzer parameters used for the analysis of the derivatized amines

and internal standard are shown in attachment 7.

3.2.9 Calculations

The used calculations are described in attachment 8.



W.F. Duvivier 24

3.2.10 Experimental design

3.2.10.1 Method validation

Validation of the method is performed using a 3-day procedure which is shown in table 3.4.

To determine the recovery, plasma-containing samples are spiked after sample preparation.

The same goes for ion suppression samples, which are academic samples with no sample

pre-treatment. To calculate the recovery, ion suppression and matrix effect, the labelled

standards are used as calibrants and 4 labelled compounds (asparagine, glutamine, lysine

and valine) are used as internal standards. This way, the endogenous level of the compounds

is not interfering with the results of the measurement.

Academic samples did not contain plasma. The plasma added to FreezThaw+1 and +2

samples is thawed and frozen, respectively, one and two times more compared to the plasma

used for the other samples. Every sample is prepared in triplo and injected three times.

Table 3.4: Experimental design of method validation (total number of samples = 96)

Cal Academic Recovery Ion Suppr. Cal Recovery Cal Recovery FreezThaw+1 FreezThaw+2 C0 3 3 C1 3 3 C2 3 3 C3 3 3 3 3 3 3 3 3 C4 3 3 C5 3 3 3 3 3 3 3 3 3 3 C6 3 3 C7 3 3 3 3 3 3 3 3 C8 3 3 27 27 9 9 9 3 9 3 9 9

All samples consisted of 10 µL of each standard mix dilution (4 in total), 10 µL of both labelled internal

standard dilutions and 5 µL plasma. Except for the academic samples, those did not contain plasma.

Every sample is injected three times.

3.2.10.2 Protein precipitation test

For testing the protein precipitation, samples with three standard concentration levels and

three different amounts of methanol are prepared in duplo (table 3.5). Each sample is

injected three times.

Table 3.5: Experimental design of a protein precipitation test (total number of samples = 36)

100 µL MeOH 150 µL MeOH 500 µL MeOH

C3 2 2 2

C5 2 2 2

C7 2 2 2

All samples consisted of 10 µL of each standard mix dilution (4 in total), 10 µL of both labelled internal

standard dilutions and 5 µL human plasma. Every sample is injected three times.



W.F. Duvivier 25

3.2.10.3 Comparison between mouse, rat and human plasma

The comparison between plasma from different species is carried out by using the labelled

standards as calibrants and 4 labelled compounds (asparagine, glutamine, lysine and valine)

as internal standards. This way, the endogenous level of the compounds, which may vary

between the species, is not interfering with the results of the measurement. The used

samples are described in table 3.6, samples are spiked with calibrants both before (“Before”-

samples) and after (“After”-samples) protein precipitation. Each sample is prepared in triplo

and injected three times.

Table 3.6: Experimental design of comparison between mouse, rat and human plasma

(total number of samples = 72)

Conc. - Spiked Mouse Rat Human Academic

C3 - Before 3 3 3 3

- After 3 3 3 3

C5 - Before 3 3 3 3

- After 3 3 3 3

C7 - Before 3 3 3 3

- After 3 3 3 3

All samples consisted of 10 µL of both labelled internal standard dilutions and 5 µL plasma of the

relevant species. The academic samples did not contain plasma. Every sample is injected three times.

3.2.10.4 Comparison between different anti-coagulants

The comparison between EDTA, heparin and citrate as anti-coagulant is carried out the same

way as the comparison between plasma from different species, the experimental design is

described in table 3.7. Each sample is prepared in triplo and injected three times.

Table 3.7: Experimental design of comparison between EDTA, heparin and citrate

(total number of samples = 72)

Conc. - Spiked EDTA Heparin Citrate Academic

C3 - Before 3 3 3 3

- After 3 3 3 3

C5 - Before 3 3 3 3

- After 3 3 3 3

C7 - Before 3 3 3 3

- After 3 3 3 3

All samples consisted of 10 µL of both labelled internal standard dilutions and 5 µL human plasma

contain the relevant anti-coagulant. The academic samples did not contain plasma. Every sample is

injected three times.



W.F. Duvivier 26

3.3 Results and discussion

3.3.1 General chromatography

The samples are analysed using 99 different MRM windows which, in total, measure 57

compounds and 28 labelled internal standards using 99 transitions (figure 3.1). The

robustness of the used chromatography is demonstrated below.

Figure 3.1: MRM windows and number of transitions used for the analysis of the compounds

Figure 3.2 shows the chromatograms of two different injections; one of the first injections of

day one (run 13) compared to one of the last of day three (run 97). No changes in retention

times are observed, which indicates the robustness of this method.

Figure 3.2: Chromatography: day 1 run 13 (above) vs. day 3 run 97 (below)



W.F. Duvivier 27

The separation between isoleucine and leucine is a good indication for the suitability of the

chromatography for this purpose, because these isomeric amino acids are hard to separate.

Below, the chromatographic separation of isoleucine and leucine is shown for two samples

measured on different days (figure 3.3).

Figure 3.3: Separation of isoleucine and leucine (R=1)

during day 1 run 37 on the left and day 3 run 97 on the right

The resolution is 1 for all samples, which implies an acceptable separation of these isomers.

There is some change in retention time, but the difference is negligible (~0.02 minute) and

possibly caused by renewing the mobile phases in between days. This is another example of

the consistent chromatography of this method, even during large sample runs covering

multiple days.

3.3.2 Validation for human plasma samples

The starting point for this part of this project was validation of the extended amine profiling

method for human plasma samples. The 3-day procedure was carried out as described above

in section 3.2.10.1. The results, however, were not satisfying: the linearity (R2) was poor and

the relative standard deviation (RSD) of the (internal) standards was very high (>45%).

After evaluation of the (raw) data, a presumption was that the protein precipitation was not

sufficient or consistent enough. This can be caused by the high protein concentration in

plasma samples compared to CSF samples. Another approach was chosen to adjust for this

difficulty. The first step of this renewed approach was testing the protein precipitation to

make sure this was complete and consistent by using different volumes of methanol.



W.F. Duvivier 28

Leftover protein can interfere in the ionisation process and on the other hand, there could

also be an amount of compound lost in the precipitate. Both phenomena can cause a higher

RSD, which is screened for in this experiment.

3.3.3 Protein precipitation test

The relative standard deviations of around 20 compounds (both amino acids and amines) are

averaged and plotted with their deviation into figure 3.4.

Clearly, a decrease in the RSD is observed when using 150 µL MeOH for protein precipitation

instead of 100 µL. Also a lower deviation of the RSD is found. When using 500 µL, the RSD is

higher than for 150 µL, but lower compared to 100 µL. From this trend, it can be assumed

that the precipitation is not complete when using 100 µL MeOH, possibly causing

interference during sample preparation and analysis.

The high RSD values for 100 and 500 µL imply that the protein precipitation was not

consistent for these volumes. For 100 µL of added MeOH, this phenomenon is probably

caused by the interference of leftover protein.

By adding 500 µL of MeOH, another cause of the elevated RSD is more likely. A high volume

of MeOH, such as 500 µL, is not easy to handle in this sample pre-treatment protocol. The

sample vails were filled up to such an extend that, during the drying under N2, sample can

spatter out of the vail more easily than when handling lower volumes. This might explain the

higher RSD.

Protein precipitation test

0%

2%

4%

6%

8%

10%

12%

14%

16%

100 150 500

µL MeOH

Ave

rag

e R

SD

of

~20

com

po

un

ds

Figure 3.4: Relative standard deviation for samples deproteinated with different volumes of methanol

Based on these results, the unsatisfactory results of the human plasma validation can be

explained and consequently, 150 µL was used in the follow-up experiments discussed below.

After evaluation of the experiments thus far, this adjusted MeOH-volume was applied on

validation of the method for mouse plasma samples (which was already in preparation). Due

to a shortage of time, no new validation for human plasma samples was done. Instead, a

comparison between mouse, rat and human plasma based on recovery, matrix effect and ion

suppression was composed. The same experiment was applied to human plasma samples

taken with different anti-coagulants. The outcome of these comparisons provides us with a

indication of the applicability of the method on other plasma types.



W.F. Duvivier 29

3.3.4 Validation for mouse plasma

The same 3-day validation procedure as discussed in paragraph 3.3.2 was carried out for

mouse plasma samples. The resulting data is processed using a validation protocol used for

all the validations of the Analytical BioSciences group of Leiden University. This protocol

evaluates the performance of the method for compounds mentioned in paragraph 3.2.2,

regarding linearity, limit of detection and quantification (LOD/Q), recovery, matrix effect, ion

suppression and batch and freeze thaw effect.

A full overview of the results can be found in attachment 9, a brief overall impression and a

more detailed look into the results of one compound (citrulline) is given in this part of this

thesis.

The most important conclusions of the validation for mouse plasma samples are:

- Good linearity is achieved (average R2 of 0.974; range 0.875-0.999)

- General limit of quantification between 7 ng/mL and 1.2 µg/mL, which is comparable

to the results achieved during validation for CSF samples

- Average ion suppression, matrix effect and recovery of, respectively, 96.6 % (66.8 –

111.0), 92.3 % (58.9 – 108.4) and 86.9 % (range 57.2 – 96.0)

- A batch effect is observed for all compounds

- No freeze thaw effect is observed

- Robust chromatography is achieved (see attachment 9 for plotted retention times of

all injections; n>350)

Figure 3.5 shows the calibration curve for citrulline in sample matrix, with A, B and C as code

for the triplicate sample preparation and I, II and III indicating the injection. The R2 of the

curve (0.998), is a sign of adequate linearity for this compound.

Figure 3.5: Citrulline calibration curve in sample matrix, 8 concentration levels



W.F. Duvivier 30

For all compounds, a batch effect is observed (figure 3.6A for citrulline). The RSD within a day

is 3.54% (average for three concentration levels; n=9), the RSD between different days 6.34%

(average for three concentration levels; n=9). ANOVA shows that this difference is significant

and thus a batch effect is determined.

Figure 3.6: Batch (A) and freeze thaw (B) effect for three concentration levels (n=9)

No substantial difference is found between plasma samples with different amounts of freeze

and thaw cycles, respectively 0, 1 and 2 (figure 3.6B). The RSD of samples within a cycle (3.0%,

average for three concentration levels; n=9) is very similar to the RSD between samples with

different freeze and thaw cycles (2.9%, average for three concentration levels; n=9). ANOVA

shows that no significant difference is observed; freeze thaw cycles do not influence the

analysis.

Overall, it can be concluded that validation of the method for mouse plasma samples was

completed for all 57 compounds and difficulties described in paragraph 3.3.2 are solved by

the adjusted sample preparation. One important remark has to be taken into account; a day-

to-day batch effect occurs.

Due to a lack of time, a new validation for human plasma samples could not be completed.

To get more insight about the applicability of this validation to other types of plasma

samples, two comparisons are made: a first between mouse, rat and human plasma, another

between human plasma samples taken with different anti-coagulants. For these comparisons,

only labelled standards are used to rule out the variation in endogenous levels between the

different plasma samples. The recovery, ion suppression and matrix effect calculated from the

results of these analysis will be discussed below.

3.3.5 Comparison between mouse, rat and human plasma

For experimental observations, there appears to be a difference between the amount of

proteins in the different plasma samples. Human plasma seems to contain the highest

amount of proteins, based on the amount of precipitate after protein precipitation and

centrifugation.

The first thing to look at in this comparison is the recovery. Figure 3.7 shows the average

recoveries for the three different types of plasma. The average RSD of the experimental

observations is 7.5% (range 2.4 – 15.5%), histidine and norepinephrine have higher RSD-

values; respectively 22.7 and 19.2%.



W.F. Duvivier 31

It should be noted that the found recoveries are in general around 80%. This is caused by a

flaw in the experimental design; the internal standards are, for all samples, added before

sample preparation, causing a higher values for the ‘after’-samples and thus artificial lower

recoveries (see attachment 10 for a calculated explanation).

Recovery

0%

20%

40%

60%

80%

100%

120%

His

tidin

e

As p

a ra g

ine

1-m

e th

ylh i

s tid

ine

Se r

i ne

Glu

t am

ine

His

t am

ine

Arg

inin

e

Gly

cin

e

As p

a rt ic

Ac i

d

Gl u

tam

ic A

cid

Be

ta-a

lan

ine

Thr

eo

nine

Ala

nin

e

Nor

epin

eph r

ine

Pr o

li ne

L -a l

ph a

-am

i no b

u ty r

ica

c id

Orn

i thin

e

Lys

ine

Tyr

os i

ne

Me t

hio

n in e

Va

line

3-m

eth

ox y

tyro

sine

3- m

eth

ox y

t yr a

min

e

Isol

eu c

ine

Leu

cine

Ph

e nyl

a la

nin e

Try

pto

p ha

n

Mouse

Rat

Human

Figure 3.7: (Average) Recovery of samples with mouse, rat and human plasma (n=9)

A few irregularities can be found in the data presented in figure 3.7. Norepinephrine shows

the most different results for the recovery. The low recovery and elevated RSD imply that this

compound is instable during protein precipitation. More research is needed to confirm this

phenomenon.

Ornithine and lysine also have lower recoveries compared to the other compounds. Both

compounds contain two amine-groups and are double derivatized by the AccQ·Tag reagent.

The double derivatization might not be complete, or double charged ions could be formed

resulting in a lower recovery of these compounds. The elevated relative standard deviation

for these compounds is a plausible result of this phenomenon.

When focusing on the ion suppression, very similar results are found for all species (figure

3.8). Only three compounds have irregular results: norepinephrine and thryptophan, and

histidine to a lower extend. The first is already discussed above, thryptophan shows

unaccountable numbers for academic samples which cause abnormally high ion suppression.

No direct explanation for this occurring is found within the experiments of this research

project.

Histidine has a 2-3 times higher RSD, which is caused by the irregular shapes peaks that are

hard to integrate. Those irregular peaks are most likely caused by the short retention time of

this compound (tR = 1.68 ; tm = 1.12). This could possibly be prevented by using a higher

concentration level for this compound or adjustment of the gradient to achieve a longer

elution time.



W.F. Duvivier 32

Ion suppression

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%H

istid

ine

Asp

a rag

ine

1-m

e th

ylh

i sti d

i ne

Se r

ine

Glu

tam

i ne

Hi s

t am

ine

Arg

inin

e

Gly

cin

e

As p

a rt ic

Ac i

d

Glu

tam

i c A

c id

Bet

a -a l

ani

ne

Th

reon

ine

Ala

nin

e

No r

e pin

ep h

r ine

Pro

li ne

L-a

l ph

a-am

ino

buty

ricac

id

Orn

ithin

e

L ys i

n e

Tyr

osin

e

Met

h io n

i ne

Val

ine

3-m

eth

o xy t

y ro s

ine

3 -m

e th

oxyt

yram

ine

Iso l

eu c

ine

Leu c

ine

Ph e

n yl a

lan i

ne

Try

pto

p ha n

Mouse

Rat

Human

Figure 3.8: (Average) Ion suppression of samples with mouse, rat and human plasma (n=9)

Results similar to the recovery and ion suppression can be found for the matrix effect

(attachment 11). The matrix effect figures show somewhat more fluctuations due to the fact

that the samples used for these calculations are spiked before sample pre-treatment and thus

put through more steps causing higher variation.

The last step in this comparison is a t-test between the different sample groups concerning

recovery, ion suppression and matrix effect. Concluding from these calculations, there are no

structural significant differences for this method when used with mouse, rat or human plasma

samples regarding these parameters (attachment 11). This observation is consistent with

figures 3.7 and 3.8, which both do not show big differences between application on the

different plasma types.

Exception on this conclusion is methionine, which has a relatively low recovery in human

plasma. This is strengthened by the results from the t-test: the t-value from the t-test

between mouse and rat plasma is distinctively below the critical value of 2.78 (two-sided, 95%

confidence)[42], the t-values between mouse/rat and human plasma are far above this critical

value (table 3.8). This implies a difference in the performance of the method concerning

methionine in human plasma samples.

Table 3.8: T-values for the recovery

t-value

Mouse <-> Rat 1.54

Mouse <-> Human 10.22

Rat <-> Human 6.94

3.3.6 Comparison between different anti-coagulants

The recovery of the samples with different anti-coagulants is very consistent through almost

all compounds. The average RSD of the experimental observations is 12.2% (3.3 – 25.2%),

histidine has a much higher RSD; 42.1% (a possible explanation for this trend is explained

above in paragraph 3.3.5).



W.F. Duvivier 33

Norepinephrine, again, is a major abnormality, something already explained above

(paragraph 3.3.5). The same goes for histidine, which also has some differences compared to

the other compounds. 1-methylhistidine and histamine have somewhat higher recoveries,

without a direct biological explanation. They do have a elevated RSD compared to the other

compounds (2 times the average) which causes less accurate results.

Recovery

0%

20%

40%

60%

80%

100%

120%

His

tidin

e

Asp

a ra g

i ne

1-m

eth y

lhis

t idin

e

Se r

ine

Gl u

t am

ine

Hi s

t am

ine

Ar g

i ni n

e

Gly

cin e

Asp

a rti c

Ac i

d

Glu

tam

ic A

cid

Be t

a-al

anin

e

Th r

e on i

n e

Ala

n in e

Nor

epin

e ph r

ine

Pro

line

L -a l

pha -

a min

obut

yric

a cid

Or n

i thi n

e

L ysi

n e

Ty r

o si n

e

Met

hio n

ine

Val

i ne

3 -m

e th o

xyty

r os i

n e

3 -m

e th o

xyty

ram

ine

Iso l

e uc i

n e

L euc

ine

Phe

nyla

lani

ne

Tr y

p to p

h an

Citrate

EDTA

Heparin

Figure 3.9: (Average) Recovery of samples with different anti-coagulants (n=9)

One other thing that should be mentioned is the low value for methionine concerning

heparin plasma. This was also noticed in the comparison between mouse, rat and human

plasma, but concluding from the results of this experiment, has to be a phenomenon limited

to analysis of heparin plasma samples.

The ion suppression is very similar for all compounds, expect the previously discussed

exceptions norepinephrine, tryptophan and, at a lower extend, histidine. There are only small

differences in the performance of the method between the sample groups (figure 3.10). The

same thing goes for the matrix effect (attachment 12), although it has some more

fluctuations because the samples used for these calculations are spiked before sample pre-

treatment.



W.F. Duvivier 34

Ion Suppression

0%

20%

40%

60%

80%

100%

120%

140%

160%

180%H

ist id

ine

Asp

ar a

gin

e

1-m

eth

ylhi

s tid

ine

Se r

ine

Glu

tam

ine

His

t am

ine

Arg

inin

e

Gly

cin e

Asp

art

i c A

c id

Glu

t am

ic A

cid

Bet

a-a l

ani

ne

Thr

eoni

ne

Ala

nine

No

repi

ne p

h rin

e

Pro

l ine

L-al

pha-

amin

obu

tyr ic

acid

Orn

ithin

e

L ys i

n e

Ty r

o si n

e

Met

hio n

ine

Val

i ne

3 -m

eth

oxyt

yro s

ine

3-m

eth

oxyt

yram

ine

Isol

eu c

ine

Leu c

ine

Phe

nyla

lani

ne

Try

ptop

han

Citrate

EDTA

Heparin

Figure 3.10: (Average) Ion suppression of samples with different anti-coagulants (n=9)

The results of the t-tests from this dataset show, in most cases, no significant difference of

the method performance when used with human plasma taken with different anti-coagulants

(attachment 12). One anomaly has been observed; for a few compounds (beta-alanine, L-

alpha-aminobutyric acid, isoleucine and leucine), a significant difference in matrix effect has

been observed between citrate on one hand and heparin and EDTA on the other. The same

effect is not observed in the ion suppression results. This implies that citrate has an effect on

these compounds only during sample preparation and not during MS-analysis.



W.F. Duvivier 35

3.4 Recommendations and further research

Below are suggestions for further research, based on the outcomes of this project;

- The use of another protein precipitant should be studied. Acetonitrile and SSA (sulfosalicylic

acid) are much described in the literature and especially acetonitrile might be a good

alternative, while SSA is not favourable when using MS-detection.

- Possibly, the ESI-source is disturbed on the retention times of the compounds with irregular

results described in the results section of this chapter. By performing a full scan in MS-mode,

these disturbances in the ESI-source, for instance caused by left-over protein or co-eluting

compounds, might be detected.

- A MS-scan for multiple charged compounds could be done. Ornithine and lysine are

suspected of gaining multiple charges during electrospray ionization because of their double

derivatization. This presumption can be confirmed by scanning for m/z-values for multiple

charged compounds.

- Norepinephrine should be investigated more intensively to determine what happens during

protein precipitation. A more detailed literature study and/or focused experiments should be

considered.

- The low values for thryptophan in academic samples (which do not contain plasma) are

another anomaly found during this research project: this does not seem to be an anomaly

(the same trend is observed during different experiments), more research on this subject is

needed.

- For some compounds (beta-alanine, L-alpha-aminobutyric acid, isoleucine and leucine) a

significant difference between citrate on one hand and heparin and EDTA on the other is

observed concerning the matrix effect. This trend is not observed in the ion suppression

results, implying an effect of citrate on these compounds during sample preparation. More

experiments to confirm or reject this conclusion are needed.

- Alike, the effect of heparin on the recovery of methionine is another focus point. Lower

recoveries are found for heparin human plasma samples compared to EDTA or citrate as anti-

coagulant. To fully understand this phenomenon, literature should be consulted or new

experiments could be done.

In addition, several general research focus points can be noted. First of all validation of the

method for human and rat plasma samples should be completed using the adjusted MeOH

volume for protein precipitation, including validation for different anti-coagulants. Expanding

the method to monitor even more compounds is the next step in enhancing amine profiling

for metabolomic studies.



W.F. Duvivier 36

Chapter 4: General conclusions

The main aim of this thesis was to develop an enhanced amine profiling method suitable for

biological samples. The first approach to reach this goal was the development of a new

derivatization reagent to be used with, the more sensitive, negative ion-mode. Several

synthesis protocols were applied and eventually 5-nitro-6-isocyanatoquinoline was

synthesized.

N

NO O

N

O+ NH

R1

R2

N

NO O

NH

O

N

R1

R2

5-nitro-6-isocyanatoquinolineAmine or amino acid

Derivatized amine Figure 4.1: Amine derivatization with 5-nitro-6-isocyanatoquinoline

This isocyanate should theoretically form AQC-like derivatized amines with an additional

NO2-functional group (figure 4.1) to gain negative charge stabilisation for better performance

in negative ion-mode. The reagent has to be synthesized and purified in higher quantities

before significant testing can be done. Due to a lack of time, this was not possible during this

research project.

Furthermore, the already established amine profiling method for CSF samples [1] has been

optimised for application to various kinds of plasma samples. Therefore, an adjustment has

been made to the sample preparation: the amount of methanol added to the sample for

protein precipitation has been raised to 150 µL. Afterwards, the method is successfully

validated for 57 compounds (attachment 9) in mouse plasma with a LOD range of 7 ng/mL –

1.2 µg/mL. One important outcome of the validation has to be taken into account; a day-to-

day batch effect is observed for all compounds.

To gain more insight in the extendibility of the validation to other types of plasma samples,

two comparisons have been made. The results of these comparisons show that there are no

significant differences in the performance of the method when analysing plasma samples

from different species or samples taken with different anti-coagulants. These findings are

graphically presented in figure 4.2. Two exceptions on the stated conclusions are observed;

the performance regarding recovery for methionine in heparin human plasma, and regarding

matrix effect for four compounds in citrate human plasma differ compared to the other

samples.

Figure 4.2: Graphical representation of the applicability of the method



W.F. Duvivier 37

Overall can be concluded that the applicability of the method is extended. In addition, several

leads to enhancing the method by using a new derivatization reagent are proposed.

Especially raising the yield and purity of the synthesized isocyanate requires high priority.

Supplementary, the anomalies which came up during the analytical part of this thesis need

more research, next to validation of the method for rat and human plasma samples.

Ideally, this project is continued in a collaboration between a student with high affinity for

organic synthesis and a student with an analytical chemistry background. The synergy in such

a duo-project might lead to new steps towards enhanced amine profiling.



W.F. Duvivier 38

Acknowledgements

In the first place, I want to thank Shanna Shi for her role as my daily supervisor. Thank you for

all the time you invested in my project and all the questions you answered. Your contribution

to my thesis even involved giving your blood for my experiments!

Secondly, I would like to thank Rob Vreeken for keeping track of my project during my time

in Leiden and correcting my thesis. Next to that, thank you for your help with my questions

about future jobs and applying at DSM.

Richard van den Berg was very important during the organic synthesis part of my project;

thank you for all your suggestions, instructions and showing me there is more than just

analytical chemistry.

I also want to thank everyone in the Analytical BioSciences and Bio-organic Synthesis groups

of Leiden University for their direct and indirect influence on this thesis. Adrie Dane is

gratefully acknowledged for his calculations on the experimental results. Finally, I have to

thank Wim Kok for being my study coordinator and his supervision out of the University of

Amsterdam.



W.F. Duvivier 39

References

[1] Shi, S., manuscript in preparation

[2] Nicholson, J.K., Xenobiotica, 1999, 29 (11), 1181-1189

[3] Krastanov, A., Biotechnology & Biotechnological Equipment, 2010, 24 (1), 1537-1543

[4] Fukusaki, E., Journal of Bioscience and Bioengineering, 2005, 100 (4), 347-354

[5] KEGG PATHWAY Database, 21-10-2010, http://www.genome.jp/kegg/pathway.html

[6] Introduction to metabolomics, Dave Barrett

http://www.docstoc.com/docs/2699139/Introduction-to-Metabolomics

[7] Pons, R., Journal of Inherited Metabolic Disease, 2009, 32 (3), 321-332

[8] Human Metabolome Database, 21-10-2010, http://www.hmdb.ca/

[9] Zhang, S., Analyst, 2010, 135 (7), 1490-1498

[10] Soga, T., Journal of Proteome Research, 2003, 2 (5), 488-494

[11] Tolstikov, V.V., Analytical Chemistry, 2003, 75 (23), 6737-6740

[12] Tolstikov, V.V., Analytical Biochemistry, 2002, 301 (2), 298-307

[13] Orešič, M., Nutrition, Metabolism and Cardiovascular diseases, 2009, 19 (11), 816-824

[14] Griffiths, W.J., Angewandte Chemie-International Edition, 2010, 49 (32), 5426-5445

[15] Griffiths, W.J., Chemical Society Reviews, 2009, 38 (7), 1882-1896

[16] Rochfort, S.J., Phytochemistry, 2008, 69 (8), 1671-1679

[17] Moore, S., Journal of Biological Chemistry, 1948, 176 (1), 367-388

[18] Moore, S., Analytical Chemistry, 1958, 30 (7), 1185-1190

[19] Turnell, D.C., Clinical Chemistry, 1982, 28 (3), 527-531

[20] Bidlingmeyer, B.A., Journal of the Association of Official Analytical Chemists, 1987, 70 (2),

241-247

[21] Einarsson, S., Journal of Chromatography A, 1983, 282 (Dec), 609-618

[22] Bidlingmeyer, B.A., Journal of Chromatography B, 1984, 336 (1), 93-104



W.F. Duvivier 40

[23] Cohen, S.A., Analytical Biochemistry, 1993, 211 (2), 279-287

[24] Bosch, L., Journal of Chromatography B, 2006, 831 (1-2), 176-183

[25] Callejon, R.M., European Food Research and Technology, 2008, 227 (1), 93-102

[26] Kabelova, I., Journal of Food Composition and Analysis, 2008, 21 (8), 736-741

[27] Boogers, I., Journal of Chromatography A, 2008, 1189 (1-2), 406-409

[28] Phenomenex Application Note TN-110: EZ:faast

[29] Langrock, T., Amino Acids, 2006, 30 (3), 291-297

[30] Mayer, H.K., Journal of Chromatography A, 2010, 1217 (19), 3251-3257

[31] Hou, S.M., Talanta, 2009, 80 (2), 440-447

[32] Mass Spectrometry; Principles and Applications (Third Edition); Edmond de Hoffman and

Vincent Stroobant

[33] Bigwarfe Jr., P.M., Rapid Communications in Mass Spectrometry, 2002, 16 (24), 2266-

2272

[34] Spackman, D.H., Analytical Chemistry, 1958, 30 (7), 1190-1206

[35] Loukou, Z., Journal of Chromatography A, 2003, 996 (1-2), 103-113

[36] U.S. Patent 6, 770, 246, 2004

[37] Mąkosza, M., Journal of Organic Chemistry, 1998, 63 (15), 4878-4888

[38] Smith, G.E.P. Jr., Journal of Organic Chemistry, 1949, 14 (6), 935-945

[39] Soulier, J.L., Journal of Medicinal Chemistry, 1997, 40 (11), 1755-1761

[40] Wilson, A.A., Organic & Biomolecular Chemistry, 2010, 8 (2), 428-432

[41] Valli, V.L.K., Journal of Organic Chemistry, 1995, 60 (1), 257-258

[42] Miller, J.N. & Miller J.C., Statistics and Chemometrics for Analytical Chemistry (Fifth

edition) 2005



W.F. Duvivier 41

Attachments



W.F. Duvivier 42

Attachment 1

1H NMR spectrum of N-tetramethylethiocarbamoylsulfenamide



W.F. Duvivier 43

Attachment 2

13C NMR spectrum of N-tetramethylethiocarbamoylsulfenamide



W.F. Duvivier 44

Attachment 3

1H NMR spectrum of 6-amino-5-nitroquinoline



W.F. Duvivier 45

Attachment 4

TLC-MS scan of 6-amino-5-nitroquinoline ([M+H]+ = 190.1)



W.F. Duvivier 46

Attachment 5

Composition of standard mixes for validation and protein precipitation test

Mix 1 Mix 3

Weight % Weight %

Aspartic acid 1,0 Beta-Alanine 19,8

Glutamic acid 1,5 Norepinephrine 13,7

Asparagine 1,8 S-adenosylhomocysteine 11,1

Serine 3,1 dopamine 12,5

Glutamine 24,9 Epinephrine 29,8

Histidine 2,6 serotonin 7,9

Glycine 4,3 3-methoxytyramine 5,2

Threonine 4,0 Total 100

Alanine 6,7

Arginine 4,9 Mix 4

Tyrosine 3,1 Weight %

Valine 7,4 DL-5-hydroxy-lysine 4,1

Methionine 1,2 gamma-L-glutamyl-L-alanine 4,5

Tryptophan 2,5 L-4-hydroxy-proline 3,9

Phenylalanine 2,7 Sarcosine 4,2

Isoleucine 2,2 Hydroxylamine 4,6

Leucine 4,5 L-2-aminoadipic acid 4,0

Lysine 5,0 5-hydroxy-L-tryptophan 4,3

Proline 4,0 L-carnosine 4,6

Cystine 4,6 methyldopa 4,3

Taurine 2,2 L-homoserine 4,1

Citrulline 2,0 S-(5)-adenosyl-L-homocysteine 3,3

L-alpha-aminobutyric acid 1,1 phosphoserine 4,0

Ornithine 1,9 Nε,Nε,Nε-trimethyllysine 4,0

Homocysteine 1,1 homocystine 4,3

Total 100 DL-3-aminoisobutyric acid 3,8

5-aminolevulinic 4,2

Mix 2 Glycylglycine 4,3

Weight % ethanolamine 4,3

O-Phosphoethanolamine 15,1 o-acetyl-L-serine 4,5

3-Methyl-L-Histidine 12,6 s-methyl-L-cysteine 4,3

Taurine 26,4 L-methionine sulfoxide 4,0

1-Methyl-L-Histidine 1,5 L-pipecolic acid 4,1

Histamine 0,7 gamma-aminobutyric acid 4,3

Citrulline 16,5 L-alpha-aminobutyric acid 3,9

Ornithine 16,2 Total 100

Putrescine 2,0

L-Kynurenine 1,1

Homo-L-arginine 7,8

Total 100



W.F. Duvivier 47

Attachment 6

Used SRM transitions for MS/MS detection (tm = 1.12 minutes)

Compound Mass Transition tR

L-Histidine 326 171 1,68

L-4-hydroxy-proline 302 171 1,69

O-Phosphoethanolamine 312 171 1,86

L-Asparagine 303 171 1,94

L-Asparagine_C13N15 309 171 1,94

3-Methylhistidine 340 171 2,08

Taurine 296 171 2,22

1-Methylhistidine 340 171 2,36

1-Methylhistidine_d3 343 171 2,36

Glycylglycine 303 171 2,52

L-Serine 276 171 2,54

L-Glutamine 317 171 2,74

L-Glutamine_C13N15 324 171 2,74

N6,N6,N6-Trimethyl-L-lysine 359 171 2,69

L-Arginine 345 171 2,81

L-Arginine_C13N15 355 171 2,81

Histamine 282 171 2,82

Histamine_d4 286 171 2,82

Glycine 246 171 2,91

Glycine_C13_N15 249 171 2,91

L-carnosine 397 171 3,01

L-homoserine 290 171 3,25

L-Aspartic acid 304 171 3,26

L-Aspartic acid_C13N15 309 171 3,26

ethanolamine 232 171 3,29

L-methionine sulfoxide 336 171 3,4

L-Glutamic acid 318 171 3,86

L-Glutamic acid_C13N15 324 171 3,86

Sarcosine 260 171 3,87

Citrulline 346 171 3,88

Homo-L-arginine 359 171 4,05

Beta-Alanine 260 171 4,09

Beta-Alanine_d4 264 171 4,09

L-Threonine 290 171 4,33

L-Threonine_C13N15 295 171 4,33

gamma-L-glutamyl-L-alanine 389 171 4,54

5-aminolevulinic 302 171 4,68

L-Alanine 260 171 4,77

L-Alanine_C13N15 264 171 4,77

gamma-aminobutyric acid 274 171 4,95

L-2-aminoadipic acid 332 171 5,14

o-acetyl-L-serine 318 171 5,14

Norepinephrine 340 171 5,22

Norepinephrine_d6 346 171 5,22

DL-3-aminoisobutyric acid 274 171 5,41



W.F. Duvivier 48

L-Proline 286 171 5,45

L-Proline_C13N15 292 171 5,45

Epinephrine 354 171 5,84

Epinephrine_d3 357 171 5,84

S-(5)-adenosyl-L-homocysteine 555 171 5,85

L-Alpha-aminobutyric acid 274 171 6,04

L-Alpha-aminobutyric acid_d6 280 171 6,04

Ornithine 473 171 6,14

Ornithine_d6 479 171 6,14

5-hydroxy-L-tryptophan 391 171 6,44

L-Lysine 487 171 6,54

L-Lysine_C13N15 495 171 6,54

Dopamine 324 171 6,56

L-Tyrosine 352 171 6,61

L-Tyrosine_C13N15 362 171 6,61

methyldopa 382 171 6,66

Putrescine 429 171 6,68

L-Methionine 320 171 6,76

L-Methionine_C13N15 326 171 6,76

L-pipecolic acid 300 171 6,85

Serotonine 347 171 6,85

L-Valine 288 171 6,9

L-Valine_C13N15 294 171 6,9

3-Methoxytyrosine 382 171 6,92

3-Methoxytyrosine_d3 385 171 6,92

3-Methoxytyramine 338 171 7,33

3-Methoxytyramine_d4 342 171 7,28

homocystine 609 171 7,49

s-methyl-L-cysteine 306 171 7,5

L-Kynurenine 379 171 7,59

L-Isoleucine 302 171 7,65

L-Isoleucine_C13N15 309 171 7,65

L-Leucine 302 171 7,73

L-Leucine_C13N15 309 171 7,72

L-Phenylalanine 336 171 7,83

L-Phenylalanine_C13N15 346 171 7,82

L-Tryptophan 375 171 7,92

L-Tryptophan_C13N15 388 171 7,91



W.F. Duvivier 49

Attachment 7

MS/MS source and analyzer parameters used for analysis of the derivatized amines and internal

standards

Source parameters Analyzer parameters

Polarity ES+ Low Mass 1 Resolution 3.0

Capillary (kV) 3.20 High Mass 1 Resolution 3.0

Cone (V) 52.00 Ion Energy 1 0.5

Extractor (V) 3.00 MS Mode Collision Energy 4.00

Source Temperature (°C) 140 MSMS Mode Collision Energy 20.00

Desolvation Temperature (°C) 450 MS Mode Entrance 0.50

Cone Gas Flow (L/Hr) 50 MS Mode Exit 0.50

Desolvation Gas Flow (L/Hr) 1000 Low Mass 2 Resolution 3.0

Collision Gas Flow (mL/min) 0.10 High Mass 2 Resolution 3.0

Ion energy 2 1.0

Multiplier 509.16



W.F. Duvivier 50

Attachment 8

• Calculation of recovery, matrix effect and ion suppression

Sample classes:

Recovery: ∗1100%

2 Matrix effect: ∗1

100%3

Ion suppression: ∗2100%

4

• t-test

−=

+

1 2

1 2

( )

1 1

x xt

sn n

where − + −

=+ −

2 22 1 1 2 2

1 2

( 1) ( 1)

( 2)

n s n ss

n n

• ANOVA

21 1

( )( )

n m

iji j

total total

XTotal of all observations

CMN N

= == =∑ ∑

2

1 1

n m

total iji j

SS X CM= =

= −∑ ∑

2

1

ni

i i

TSST CM

n== −∑

totalSSE SS SST= −

1

SSTMST

k=

−

SSEMSE

N k=

−

MSTF

MSE=

4

No sample prep.

3

Spiked before

sample prep.

Academic

2

Spiked after

sample prep.

1

Spiked before

sample prep.

Matrix



W.F. Duvivier 51

Attachment 9

Overview of the validation results for mouse plasma samples

Validation characteristics for each compound

Component Slope Intercept R2

LOQ

[ug/ml]

Precision

RSD

Batch

Effect

L-histidine 0,332 0,134 0,988 0,235 < 6% Yes

L-4-hydroxyproline 2,696 0,441 0,997 0,005 < 10% Yes

o-phosphoethanolamine 0,955 0,035 0,993 0,008 < 10% Yes

L-asparagine 3,140 1,451 0,998 0,040 < 10% Yes

3-methylhistidine 1,773 0,212 0,992 0,019 < 10% Yes

taurine 1,826 5,364 0,978 0,691 < 6% Yes

L-serine 6,644 5,552 0,998 0,168 < 6% Yes

N-methylhistidine 2,586 0,178 0,977 0,008 < 10% Yes

Histamine 5,373 -0,006 0,987 0,003 < 10% Yes

L-arginine 4,525 3,998 0,992 0,227 < 6% Yes

L-glutamine 9,508 36,064 0,996 0,641 < 6% Yes

glycine 4,113 6,050 0,994 0,373 < 6% Yes

glycylglycine 25,450 0,052 0,991 0,002 < 10% Yes

L-carnosine 1,271 0,005 0,982 0,045 < 10% Yes

L-homoserine 22,616 0,074 0,979 0,010 < 10% Yes

N6,N6,N6-trimethyllysine 1,798 0,019 0,954 0,043 < 10% Yes

L-aspartic acid 2,892 0,094 0,998 0,021 < 10% Yes

L-glutamic acid 1,809 0,458 0,999 0,038 < 10% Yes

sarcosine 4,317 0,039 0,995 0,008 < 10% Yes

citrulline 0,977 0,491 0,998 0,197 < 6% Yes

Beta-alanine 3,880 0,056 0,984 0,003 < 10% Yes

ethanolamine 22,133 1,767 0,958 0,076 < 10% Yes

L-methioninesulfoxide 3,584 0,117 0,996 0,011 < 10% Yes

gamma-aminobutyricacid 5,043 0,005 0,995 0,001 < 10% Yes

L-threonine 3,567 4,697 0,998 0,202 < 6% Yes

L-alanine 1,803 6,977 0,947 4,743 < 6% Yes

5-aminolevulinic 0,157 0,004 0,949 0,071 < 10% Yes

DL-3-aminoisobutyricacid 2,411 0,001 0,997 0,000 < 10% Yes

homo-L-arginine 0,026 0,003 0,965 0,225 < 6% Yes

gamma-L-glutamyl-L-alanine 0,175 0,004 0,984 0,083 < 10% Yes

epinephrine 0,920 0,001 0,905 0,010 < 10% Yes

L-2-aminoadipicacid 3,895 0,548 0,996 0,070 < 10% Yes

S-(5)-adenosyl-L-

homocysteine 0,173 0,000 0,987 0,001 < 10% Yes

o-acetyl-L-serine 0,752 -0,001 0,962 0,016 < 10% Yes

Norepinephrine 9,174 0,001 0,965 0,001 < 10% Yes

putrescine 0,089 0,000 0,904 0,019 < 10% Yes

3-methoxytyrosine 3,230 0,006 0,988 0,002 < 10% Yes

L-alpha-aminobutyricacid 2,462 0,090 0,997 0,011 < 10% Yes

3-methoxytyramine 3,738 0,000 0,993 0,000 < 10% Yes

ornithine 3,325 1,652 0,991 0,116 < 6% Yes

dopamine 8,396 0,034 0,979 0,003 < 10% Yes

methionine 7,706 3,998 0,996 0,065 < 10% Yes

L-lysine 7,751 16,706 0,992 0,475 < 6% Yes



W.F. Duvivier 52

L-tyrosine 3,490 3,611 0,995 0,267 < 6% Yes

L-valine 1,994 4,192 0,915 2,340 < 6% Yes

L-proline 8,830 8,448 0,997 0,246 < 6% Yes

L-kynurenine 0,404 0,005 0,988 0,023 < 10% Yes

L-tryptophan 4,840 3,660 0,998 0,149 < 6% Yes

L-isoleucine 2,391 2,002 0,998 0,136 < 6% Yes

L-leucine 1,227 1,661 0,934 1,601 < 6% Yes

L-phenylalanine 7,940 4,579 0,996 0,068 < 10% Yes

cystine 1,413 0,000 0,911 2,999 < 6% Yes

5-hydroxy-L-tryptophan 4,559 -0,016 0,972 0,024 < 10% Yes

methyldopa 0,929 -0,003 0,982 0,011 < 10% Yes

homocystine 0,014 0,000 0,904 0,008 < 10% Yes

s-methyl-L-cysteine 0,248 0,000 0,890 0,006 < 10% Yes

L-pipecolicacid 0,076 0,003 0,875 0,014 < 10% Yes

serotonine 2,322 0,029 0,952 0,006 < 10% Yes

Plotted retention times for all injections (n>350)



W.F. Duvivier 53

Attachment 10

Example calculations of the low recovery

“Before” samples: internal standards added before, calibrants added before

“After” samples: internal standards added before, calibrants added after

If a loss of compound during sample preparation is assumed, the following effect on the

relative area will be observed:

Area Internal standards Area Calibrants Relative area

Before Decreased Decreased No change (e.g. 100)

After Decreased No change Increased (e.g. 120)

Relative area = Area Calibrants / Area internal standards

Example of resulting recovery:

Recovery = ∗100%Before

After

= ∗ =100100% 83%

120



W.F. Duvivier 54

Attachment 11

Additional figures and tables for the comparison of mouse, rat and human plasma

Matrix effect

0%

20%

40%

60%

80%

100%

120%

140%

His

tidin

e

Asp

arag

ine

1-m

eth

y lh

ist id

i ne

Ser

ine

Glu

tam

i ne

His

t am

ine

Ar g

inin

e

Gl y

c in

e

As p

a rt ic

Ac i

d

Glu

tam

ic A

cid

Be t

a-al

an i

ne

Th

reo n

ine

Ala

nin

e

Nor

epin

ep h

rin e

Pro

line

L-a

lph

a-am

ino

b uty

r icac

id

Orn

ithin

e

Lysi

ne

Ty r

o si n

e

Me t

h io n

i ne

Va l

ine

3 -m

e th

oxyt

yros

ine

3 -m

e th

oxyt

yra m

ine

Iso l

eu c

ine

L eu c

i ne

Phe

nyla

lani

ne

Try

p to

p ha n

Mouse

Rat

Human

Matrix effect for the comparison of mouse, rat and human plasma (n=9)

t-test results compared to critical value 2.78 (two-sided, 95% confidence)[42]:

green=no significant difference, red=significant difference

Recovery Ion suppression Matrix effect

Histidine Mouse<->Human 0,94 1,39 0,95

Rat<->Human 0,44 0,82 3,50

Mouse<->Rat 1,39 0,25 1,29

Asparagine etc. 2,41 1,10 0,07

3,00 0,63 0,51

0,48 0,68 0,51

1-methylhistidine 0,54 1,01 0,31

0,23 0,18 0,10

0,28 0,77 0,38

Serine 0,67 4,11 1,43

0,09 1,67 1,19

0,66 0,78 0,70

Glutamine 0,12 0,48 0,94

0,55 0,94 0,77

0,24 1,21 1,30

Histamine 2,31 1,07 7,00

1,08 1,29 4,41

1,07 0,57 0,89

Arginine 1,72 0,43 1,35

0,61 0,01 0,64

2,95 0,54 4,82

Glycine 0,18 0,77 0,86

0,25 0,12 0,05

0,73 0,68 1,19

Aspartic Acid 1,35 0,10 0,54

0,04 0,12 0,34

1,10 0,00 0,70

Glutamic Acid 3,48 0,02 2,23



W.F. Duvivier 55

0,43 0,06 0,04

1,89 0,05 1,07

Beta-alanine 2,86 0,24 4,44

0,97 0,02 1,19

1,17 0,24 2,97

Threonine 1,80 0,73 3,82

0,49 0,29 1,52

0,66 0,36 1,62

Alanine 1,01 0,79 2,85

0,38 0,45 0,41

1,73 0,39 1,68

Norepinephrine 2,77 0,21 1,36

1,56 0,34 0,73

0,35 0,45 0,25

Proline 0,69 0,72 0,96

0,15 0,22 0,06

0,31 0,90 0,70

L-alpha-aminobutyricacid 0,85 0,42 6,49

0,15 0,14 0,30

0,75 0,28 2,55

Ornithine 1,14 0,00 0,84

0,62 0,05 0,93

0,07 0,05 0,34

Lysine 1,93 0,74 1,61

1,18 0,02 1,43

1,17 0,79 0,09

Tyrosine 2,31 0,27 2,56

0,32 0,04 0,18

2,79 0,33 1,58

Methionine 10,22 0,97 1,99

6,94 0,65 0,94

1,53 2,16 2,38

Valine 4,38 0,79 2,19

0,56 0,26 0,32

2,33 0,52 1,01

3-methoxytyrosine 2,10 1,23 8,98

0,12 0,45 0,64

1,26 0,82 1,97

3-methoxytyramine 2,23 0,75 2,94

0,82 0,73 1,57

1,64 0,02 3,70

Isoleucine 2,93 0,19 1,27

0,43 0,53 0,24

1,81 0,33 0,91

Leucine 1,31 0,35 1,02

0,12 0,14 0,08

1,72 0,56 0,68

Phenylalanine 1,37 0,33 1,31

0,10 0,21 0,17

0,91 0,19 0,74

Tryptophan 2,74 0,02 1,27

0,34 0,06 0,08

3,27 0,04 1,02



W.F. Duvivier 56

Attachment 12

Additional figures and tables for the comparison of EDTA, heparin and citrate

Matrix Effect

0%

20%

40%

60%

80%

100%

120%

140%H

isti d

ine

As p

ara

gin

e

1 -m

eth

y lhi

sti d

ine

Ser

ine

Glu

t am

ine

Hi s

tam

ine

Ar g

inin

e

Gly

cine

Asp

ar t

ic A

c id

Glu

t am

ic A

cid

Be t

a -a l

an i

n e

Th r

eoni

ne

Ala

nin e

No

r ep i

nep

hri n

e

Pro

l ine

L-a l

p ha -

amin

o bu

tyr ic

a cid

Or n

it hin

e

L ys i

n e

Tyr

o si n

e

Met

h io n

ine

Va l

ine

3 -m

eth

o xy t

y ros

ine

3 -m

et h

o xy t

yram

ine

Isol

eu c

ine

Leuc

ine

Ph e

n yl a

lani

ne

Try

ptop

han

Citrate

EDTA

Heparin

Matrix effect for the comparison of EDTA, heparin and citrate as anti-coagulant (n=9)

t-test results compared to critical value 2.78 (two-sided, 95% confidence)[42]:

green=no significant difference, red=significant difference

Recovery Ion suppression Matrix effect

Histidine Citrate<->Heparin 0,74 0,14 0,70

Citrate<->EDTA 1,11 0,15 0,85

EDTA<->Heparin 1,16 0,29 0,96

Asparagine etc. 0,02 0,46 0,64

etc. 0,30 0,74 0,90

etc. 0,22 0,35 0,25

1-methylhistidine 1,26 0,42 1,15

0,83 0,80 0,85

0,10 0,73 0,01

Serine 0,21 0,15 0,26

0,70 0,78 0,80

0,34 0,08 0,76

Glutamine 0,26 0,05 0,34

0,29 0,10 0,42

0,04 0,06 0,03

Histamine 0,10 0,13 0,36

0,60 0,03 1,08

0,47 0,17 1,77

Arginine 0,40 0,37 0,09

1,44 0,01 1,39

0,96 0,33 0,76

Glycine 0,22 0,33 0,20

0,65 0,39 0,15

0,67 0,66 0,11

Aspartic Acid 4,60 1,15 1,01

0,58 0,92 0,13

2,49 1,75 0,72

Glutamic Acid 1,23 0,42 1,20

0,56 1,70 0,36



W.F. Duvivier 57

2,20 1,05 1,86

Beta-alanine 2,86 0,24 4,44

1,17 0,24 2,97

0,97 0,02 1,19

Threonine 0,67 0,74 0,11

0,19 0,14 0,26

0,53 0,79 0,38

Alanine 1,39 0,11 1,57

0,36 1,85 0,77

1,29 0,48 0,69

Norepinephrine 3,11 0,02 0,91

1,19 0,44 0,89

5,66 0,49 3,36

Proline 0,74 1,32 2,67

0,99 6,25 2,66

0,64 0,18 0,92

L-alpha-aminobutyricacid 2,01 0,22 2,87

1,14 1,50 3,18

1,08 0,32 0,69

Ornithine 0,28 0,50 0,23

0,10 0,52 0,32

0,41 0,92 0,54

Lysine 0,06 0,52 0,65

0,83 1,18 0,20

0,77 1,57 0,82

Tyrosine 0,38 0,87 0,15

0,19 2,25 1,18

0,89 1,52 2,26

Methionine 1,03 0,71 0,95

2,34 1,53 1,94

1,55 3,13 1,61

Valine 1,03 0,28 1,66

1,14 1,37 2,14

0,29 0,47 1,01

3-methoxytyrosine 0,07 0,41 0,13

1,07 0,58 2,51

1,47 0,64 2,95

3-methoxytyramine 0,17 0,44 0,26

0,47 0,46 4,10

1,44 0,05 1,73

Isoleucine 2,40 0,33 4,98

1,70 2,47 5,32

0,02 1,35 2,03

Leucine 1,46 0,56 3,56

1,20 2,97 4,34

0,07 1,46 2,15

Phenylalanine 0,07 1,08 0,65

0,77 1,41 2,88

1,16 0,76 2,52

Tryptophan 0,07 0,67 0,91

0,93 1,37 3,31

1,14 0,75 2,82

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