Journal of Experimental Botany, Vol. 56, No. 410,
Making Sense of the Metabolome Special Issue, pp. 219–243, January 2005
doi:10.1093/jxb/eri069 Advance Access publication 23 December, 2004
Chemical derivatization and mass spectral libraries
in metabolic profiling by GC/MS and LC/MS/MS
John M. Halket1,2,*, Daniel Waterman1, Anna M. Przyborowska2, Raj K. P. Patel1,2, Paul D. Fraser1 and
Peter M. Bramley1
1
Bourne Laboratory, Centre for Chemical and Bioanalytical Sciences, Royal Holloway,
University of London, Egham, Surrey TW20 0EX, UK
2
Specialist Bioanalytical Services Limited, Royal Holloway, University of London, Egham,
Surrey TW20 0EX, UK
Received 28 June 2004; Accepted 29 October 2004
Abstract
Introduction
An overview is presented of gas chromatography/mass
spectrometry (GC/MS) and liquid chromatography/mass
spectrometry (LC/MS), the two major hyphenated techniques employed in metabolic profiling that complement
direct ‘fingerprinting’ methods such as atmospheric
pressure ionization (API) quadrupole time-of-flight MS,
API Fourier transform MS, and NMR. In GC/MS, the
analytes are normally derivatized prior to analysis in
order to reduce their polarity and facilitate chromatographic separation. The electron ionization mass spectra obtained are reproducible and suitable for library
matching, mass spectral collections being readily available. In LC/MS, derivatization and library matching are at
an early stage of development and mini-reviews are
provided. Chemical derivatization can dramatically increase the sensitivity and specificity of LC/MS methods
for less polar compounds and provides additional structural information. The potential of derivatization for
metabolic profiling in LC/MS is demonstrated by the
enhanced analysis of plant extracts, including the potential to measure volatile acids such as formic acid,
difficult to achieve by GC/MS. The important role of mass
spectral library creation and usage in these techniques
is discussed and illustrated by examples.
Metabolic profiling and ‘fingerprinting’
Key words: Derivatization, electrospray ionization, food analysis, gas-liquid chromatography-mass spectrometry, ion trap,
liquid chromatography-mass spectrometry, urine analysis,
mass spectral library, metabolic profiling, tandem mass spectrometry, time-of-flight.
The emerging field of metabolomics requires profiling and
fingerprinting methods (Fiehn et al., 2000a; Glassbrook
and Ryals, 2001; Harrigan and Goodacre, 2003; Sumner
et al., 2003) capable of measuring the absolute or relative
amounts of all metabolites (the metabolome). The great
diversity of chemical properties and wide concentration
ranges of these compounds pose a significant challenge as
the methods need to be robust and reproducible to enable
samples to be reliably compared (Glassbrook et al., 2000).
Profiling refers to the detailed analysis by hyphenated
techniques such as gas chromatography-mass spectrometry
(GC/MS), liquid chromatography-mass spectrometry (LC/
MS) or capillary electrophoresis-mass spectrometry (CE/
MS). Such techniques provide a detailed chromatographic
profile of the sample and consequently measurements of
the relative or absolute amounts of the components. The
number of components measured will depend on the
resolution of the chromatographic system and the specificity of the detection technique. A mass spectrometer can
function as a highly specific chromatographic detector and
a high resolution mass spectrometer even more so.
‘Fingerprinting’ refers to more rapid and general screening methods such as direct infusion atmospheric pressure
ionization (API) MS (particularly at high mass resolution),
NMR spectroscopy, and other methods such as Raman
spectroscopy and Fourier transform infra-red spectroscopy
(Fig. 1), all of which provide complementary information.
Such techniques can be configured as ‘high-throughput’
and are suitable for determining differences and classifying
* To whom correspondence should be addressed. E-mail: [email protected]
Journal of Experimental Botany, Vol. 56, No. 410, ª Society for Experimental Biology 2004; all rights reserved
220 Halket et al.
metabolic PROFILING:
GC/MS
LC/MS(/MS),CE/MS(MS)
metabolic FINGERPRINTING
direct MS (Q-TOF, FT-ICR, MALDI)
NMR, Raman, FT-IR, ...
Fig. 1. Major techniques for metabolic profiling: gas chromatographymass spectrometry (GC/MS), liquid chromatography-mass spectrometry
(LC/MS), liquid chromatography-tandem mass spectrometry (LC/MS/
MS), capillary electrophoresis-mass spectrometry (CE/MS), direct MS
techniques for metabolic ‘fingerprinting’: quadrupole-time of flight (QTOF), Fourier transform-ion cyclotron resonance (FT-ICR) and matrix
assisted laser desorption/ionization (MALDI) and direct spectroscopic
techniques: nuclear magnetic resonance (NMR), Raman and Fourier
transform infra-red (FT-IR).
samples. Generally, fingerprinting involves much larger
numbers of measurements than profiling.
Targeted analyses
In cases where a relatively small number of analytes can be
defined in advance, for example, 20 known amino acids, or
a specific set of organic acids, so-called targeted GC/MS
and LC/MS methods can be employed. Such methods can
achieve great accuracy and precision particularly where
stable isotope labelled internal standards are available. In
such targeted analyses, signals from all other components
are ignored. However, such targeted methods can only
touch a tiny fraction of the metabolome. In addition, stable
isotope-labelled standards are very expensive and are only
available commercially for a relatively small number of
common compounds.
Non-targeted analyses
GC/MS can also perform non-targeted analysis where all
chromatographic peaks, or all peaks above a certain intensity, can be characterized by their mass spectral patterns
and GC retention indices, thereby enabling their reliable
recognition in further samples. The number of measurements can be increased by deconvolution of the spectra
using numerical methods (Colby, 1992; Dromey et al.,
1976; Holland et al., 1997; Stein, 1999). Several software
programs are available for this purpose and have been
applied to metabolic profiling (Halket et al., 1999; Fiehn,
2003; Waterman et al., 2004; Weckwerth et al., 2004).
LC/MS with atmospheric pressure ionization (API) is also
being applied to metabolic profiling, but is again limited by
the relatively small numbers of analytes amenable to the
analysis. Of particular importance is the development of
suitable HPLC columns (Tolstikov and Fiehn, 2002), peak
detection software (Tolstikov et al., 2003), high mass
resolution (van der Greef et al., 2004), the potential of ultra
high resolution LC (Tolley et al., 2001; Legido-Quigley
et al., 2002) and chemical derivatization (Gröger et al.,
2003). The latter is covered in greater detail below and
demonstrates that the approach can dramatically alter the
ionization characteristics of different functional groups so
that they may be detected more readily in a single analysis.
Capillary electrophoresis and related techniques when
combined with mass spectrometry appear to have great
potential in metabolic profiling (Soga et al., 2002; Guillo
et al., 2004). However, robustness and sample loading
problems remain to be overcome.
Profiling methods are more suited to the investigation of
only small parts of the metabolome, perhaps the elucidation
of a simple pathway. It is estimated that there are maybe
200 000 metabolites, present in plants and, of these, 10 000
are known compounds (Fiehn et al., 2000a). Considering
that popular techniques such as GC/MS and LC/MS in their
present form can analyse only up to several hundred
components with structures assigned to fewer than a hundred (Fiehn, 2003), the so-called ‘fingerprinting’ techniques where the extract is spectroscopically analysed
without chromatography may prove to be more useful. In
this way, a much ‘bigger picture’ perhaps consisting of
thousands of signals can be obtained very quickly albeit at
the expense of specificity.
Fingerprinting
Fingerprinting techniques include nuclear magnetic resonance spectroscopy (NMR), Fourier transform infra-red
spectroscopy (FTIR), and direct infusion atmospheric
pressure ionization MS. The latter, particularly at high
mass resolution, has been employed with success to classify
a variety of samples (Vaidyanathan et al., 2001, 2002;
Goodacre et al., 2002; Kaderbhai et al., 2003; Castrillo
et al., 2003; Overy et al., 2004) and has potential for the
initial detection of putative biomarkers. The employment of
high mass resolution will provide possible molecular
formulae for such biomarkers and attempts can then be
made to elucidate their structures using more-specific
techniques involving chromatography. Fourier transform
mass spectrometry can provide even higher mass resolution
and has been used to measure the relative amounts of over
6000 metabolites in ripening strawberries using electrospray ionization (ESI) and atmospheric pressure chemical
ionization (APCI) with recording of both positively and
negatively-charged ions (Goodenowe, 2001; Aharoni et al.,
2002). The development and application of such ultra high
mass resolution instruments has a great role to play in the
future of metabolic profiling, assuming that current limitations on data processing and interpretation software can
be overcome.
An overview of the approximate range of applications of
GC/MS (electron ionization) and LC/MS (ESI, APCI) for
the analysis of selected compound classes over a range of
polarity and relative molecular mass is given in Fig. 2. In
GC/MS, the analytes are normally derivatized prior to
Metabolic profiling
221
COMMON IONIZATION TECHNIQUES
RANGE OF APPLICATION
LC/ MS (E LE CTROSP RA Y, ESI, +/ - )
500,000
proteins, DNA
50,000
1,000
Mr
pe p ti d e s
LC/MS (APCI, +/- )
GC/MS (EI, +)
sterols, steroids
fatty acids
essential oils, esters
alkylsilyl derivatives
h yd r o c a rb o ns , p e r f u m e s
drugs
amino acids
organic acids
metal ions
10
LOW POLARITY
HIGH POLARITY
Fig. 2. An overview of the approximate range of application of the commonly used GC/MS and LC/MS techniques for selected compound classes. The
arrows show the effect of derivatization of the polar organic acids, bringing them into the GC/MS region and also into the electrospray region (positive)
as described in the text.
analysis in order to reduce their polarity and facilitate
chromatographic separation on a column of low polarity as
usually employed in metabolic profiling. For example, fatty
acids are commonly esterified by methylation before GC
separation. In the case of ESI, polar and pre-ionized
components are favoured making the technique highly
complementary to GC/MS. By comparison, the related
APCI technique covers lower polarity compounds and
therefore has great potential in metabolic profiling by LC/
MS. The harsher conditions employed in APCI prevents its
use for larger molecules, but smaller analytes (generally
<2000 Da) can be detected over a wider polarity range
(Ardrey, 2003). The technique is also more tolerant to
changes in experimental conditions and is commonly
employed in quantitative analysis. Although APCI has
a requirement for high flow rates, making it less compatible
with microbore column technology, a post-column ‘makeup’ flow of mobile phase can be added. A newer ionization
technique, atmospheric pressure photoionization (APPI;
Robb et al., 2000) is not indicated, but has potential for the
analysis of compounds of lower polarity and thus considerable potential for metabolic profiling by LC/MS. In
conventional GC/MS, the electron ionization technique is
employed and only the much more abundant positively
charged ions are measured. In addition, the energy supplied
to induce fragmentation of the parent ion in order to obtain
a fragmentation pattern (mass spectrum, or plot of ion
abundance versus mass-to-charge ratio) is kept constant (70
eV) thereby enabling reproducible mass spectra to be
obtained. In this way, libraries of such spectra can be
shared between investigators and several libraries are
commercially available (see below). The LC/MS situation
is more complex. The atmospheric pressure ionization
techniques generally produce pseudo-molecular ions
([M+H]+ or [M-H]ÿ) depending on a number of factors:
the chemical properties of the analyte, the polarity of the
electrospray voltage, the nature of the matrix and the
solvent composition. It is not always a simple matter to
predict whether positive or negative ions will be preferentially produced (Cech and Enkei, 2001). For example, the
production of negative ions from carboxylic acids can be
enhanced by the addition of weak acid, rather than the
expected base (Wu et al., 2004). Matrix effects (Matuszewski
et al., 2003) can include ionization suppression (King et al.,
2000; Choi et al., 2001) and ionization enhancement
(Mallet et al., 2004; Liang et al., 2003) caused by the
presence of salts and other components being ionized at the
same time. The probability of such effects is greater where
no chromatographic steps are employed as in fingerprinting
by direct infusion ESI (Goodacre et al., 2002) and the
analyst must always be aware of the dangers.
Thus, there is a much more complex situation in LC/MS as
many compounds in a plant extract will not ionize optimally,
or at all, under the conditions employed in a single analytical
run. Currently, metabolic profiling by LC/MS is more suited
to groups of compounds, such as alkaloids, which ionize
similarly under given conditions. In complex mixtures such
as plant extracts, some compounds will preferentially form
positive ions, others negative ions, and some will be difficult
to ionize under fixed conditions. Chemical derivatization
has the potential to alter the ionization properties of the
analyte molecules favourably, as indicated by the arrows in
222 Halket et al.
Fig. 2: the polarities of organic acids can be reduced by
esterification facilitating their analysis by GC/MS. Similarly, organic acids can be derivatized in such a way that their
polarity is increased (arrowed, Fig. 2) making them more
amenable to analysis by positive electrospray and examples
of such a transformation are described below.
In addition, energy supply to such parent ions in order to
induce fragmentation and obtain the product ion mass
spectra, which can be used for library searching, is not
standardized between instrument types and complicates the
analysis. This situation is covered in the LC/MS library
section, below.
GC/MS and LC/MS: peak tables
The data transformation required in profiling techniques
such as GC/MS and LC/MS is illustrated in Fig. 3.
Component peaks (a,b,c. . .n) located in the mass chromatograms are detected by the manufacturers’ software and
quantified by the integration of selected ion currents usually
relative to one or more internal standards. The integrated
values are entered into a peak table for each sample
chromatogram (1,2,3. . .z). Mass spectrometry data systems
are generally equipped for ‘target compound analysis’
where preselected components can be recognized by their
mass spectral patterns or pattern of qualifier ions (see
below) and chromatographic retention data (time, relative
retention time or retention index; see below). In this case,
the data matrix is easily constructed. The situation with
non-targeted analysis is more complex. Components appearing or disappearing in some samples, for example,
following genetic modification, or in a disease state, will
require manual adjustment of the matrix. Commercially
available software to assist with this step is only just
becoming available. A selection of programs, some of
which can read a variety of file formats and carry out mass
spectral deconvolution, are listed in Table 1.
In comprehensive metabolic profiling of plant extracts by
GC/MS, the majority of compounds measured have not yet
been formally identified. Over 400 components were detected in Cucurbita maxima phloem, using automated mass
spectral deconvolution GC/MS, but only 90 of them were
tentatively identified (Fiehn, 2003). However, the power of
mass spectrometry enables relative measurements of compounds to be reliably made, even though their chemical
structures are not known. When measuring the relative
amounts of such compounds, usually against one or more
stable isotope labelled internal standards, it is important to
be sure that one is comparing like with like across multiple
samples. Mass spectral libraries and GC retention data are,
therefore, of paramount importance in such work. Some
aspects of metabolic profiling by GC/MS and LC/MS will be
considered below, focusing on the development and application of mass spectral libraries, chemical derivatization and
chromatographic retention data, all important parameters
when carrying out both targeted and non-targeted analyses.
Fig. 3. The data transformation required in profiling techniques such as GC/MS and LC/MS. Areas of mass chromatographic peaks corresponding to
components (a,b,c. . .n) are entered into a peak table for each sample chromatogram (1,2,3. . .z).
Table 1. A selection of specialist software packages for peak detection and mass spectral deconvolution
Name
Publisher
Reference
AMDIS
AnalyzerPro/MatrixAnalyzer
CODA
MassFrontier
metAlign
Uppsala
NIST
Spectralworks
ACD
Thermo/HighChem
RIKILT
University of Uppsala
Stein, 1999 //chemdata.nist.gov/mass-spc/amdis/
Draper et al., 2004; Draper, 2004 //www.spectralworks.com
Windig et al., 1996 //www.acdlabs.com
Kovacik et al., 2002 //www.highchem.com
Tolstikov et al., 2003 //www.metalign.nl
Danielsson et al., 2002 [email protected]
Metabolic profiling
In addition, examples of chemical derivatization for LC/
MS are shown and potential for metabolic profiling briefly
discussed.
Gas chromatography-mass spectrometry
(GC/MS)
GC/MS is now a robust and very widely used technique and
combines high sensitivity and specificity for suitable analyte
classes (Fig. 2). Several introductory and advanced texts are
available (Halket et al., 1990; Kitson et al., 1996; McMaster
and McMaster, 1998; Gerhards et al., 1998; Niessen, 2001).
Prior to its application in the plant arena (Roessner et al.,
2000), GC/MS has had a fairly long history in metabolic
profiling (Horning and Hornung, 1971) through the detailed
study of metabolic disorders in humans. Indeed, the technique was instrumental in the identification of a large
number of hitherto unknown inborn errors (Witten et al.,
1973; Eldjarn et al., 1974; Goodman, 1980; Tanaka et al.,
1980; Chalmers et al., 1982). Such metabolite profiling
techniques have since been routinely applied to the analysis
of plant extracts (Roessner et al., 2000; Fiehn et al., 2000a;
Waterman et al., 2004; Shepherd et al., 2004).
Sample extraction
Analytes present in wet or freeze-dried plant tissue are
normally extracted with methanol or methanol-water prior
to derivatization. Lipophilic components may be partitioned using chloroform (Roessner et al., 2000). Liquid–
liquid extraction using ethyl acetate or ethyl acetate–diethyl
ether is commonly employed for organic acids in acidified
urine. Solid phase extraction (anion exchange) techniques
have also been employed (Verhaeghe et al., 1988; Chalmers
and Lawson, 1982). A more general profile of urine
samples (organic acids, amino acids, sugars) has been
carried out by the use of urease followed by trimethylsilylation of the residue after drying (Shoemaker and Elliott,
1991). The urease removes large amounts of urea which can
obscure other components and reduce the chromatographic
resolution.
GC/MS: chemical derivatization
Some plant metabolites such as those contained within
essential oils are highly suited to GC/MS analysis without
derivatization (Jennings and Shibamoto, 1980; Adams,
2001). However, chemical derivatization (Knapp, 1979;
Blau and King, 1977; Blau and Halket, 1993) is usually
required to reduce the polarities of the functional groups,
facilitate their separation by GC and can influence their
mass spectral properties (Halket, 1993). Organic acids were
commonly esterified by reaction with diazomethane, but
now silylation (Poole, 1977; Evershed, 1993; Halket and
Zaiken, 2003), predominantly trimethylsilylation or tertbutyldimethylsilylation, is more popular. In addition, keto(oxo-) groups are usually oximated in order to improve
223
their GC properties and prevent enolization reactions which
can introduce multiple products, thereby complicating the
chromatograms. During high resolution chromatography,
the syn- and anti- isomers of the oximes can sometimes
partially separate giving rise to recognizable shoulders
on the GC peaks. Table 2 shows the common silylation
and oximation reactions: trimethylsilyl (TMS) and tertbutyldimethylsilyl (TBDMS) from hydroxyl and primary
amine groups and methoximation (MO) of carbonyl groups,
together with a selection of mass increments in each case.
As the number of derivatized groups increases, there is
a danger that the molecular mass of the derivative will be
outside the mass range of the detector, typically m/z 650–
1000, or be too high that the derivative will not pass through
the GC column. In addition, the likelihood of sterically
hindered groups can lead to the formation of multiple
products, thereby complicating the chromatogram.
tert-Butyldimethylsilylation has been evaluated as being
the most comprehensive for metabolite profiling applications (Birkemeyer et al., 2003) and has a further advantage
that the derivatives are less sensitive to the hydrolytic
effects of moisture than the corresponding TMS derivatives. They often give mass spectra having abundant
fragment ions (m/z M-57, where M is the molecular mass
of the analyte) from facile loss of the tert-butyl moiety,
convenient for structural assignments of plant metabolites
(Fiehn et al., 2000b). A disadvantage of TBDMS derivatives lies in the significant increase in molecular mass
(Table 2), particularly where multiple derivatizable groups
are present in the molecule. In addition, problems of steric
hindrance might lead to mixtures of fully and partially
derivatized analytes.
The analyst should be aware of possible artefact formation during the trimethylsilylation process. A useful study
has been published (Little, 1999) with an internet reference for updates (Little; http://users.chartertn.net/slittle/).
Table 2. The major derivatization steps in metabolic profiling
by GC/MS
Derivatization reaction
Number of
groups
Mass
increment
TMS
1
2
3
4
5
6
72
144
216
288
360
432
1
2
3
4
5
6
114
228
342
456
570
684
1
2
3
4
29
58
87
116
R O H
R O Si
R N H
R N Si
H
H
TBDMS
R O H
R O Si
R N H
H
R N Si
H
MO
O
N
O
R
C
R1
R
C
R1
224 Halket et al.
In addition, treatment with silylation reagents, even under
the mild conditions generally employed in plant metabolite
profiling, can lead to conversion. For example, arginine is
converted to ornithine by reaction with BSTFA (Leimer
et al., 1977). Figure 4 illustrates the same conversion using
MSTFA under conditions commonly employed for metabolic profiling of plant extracts (37 8C, 20 min). When
studying metabolic processes in detail, particularly where
the intermediate compounds may be reactive, or unstable,
the analyst should always be aware of such possibilities
when interpreting the results. Where there is any doubt,
alternative derivatization procedures are generally available
for specific functional groups (Blau and King, 1977; Blau
and Halket, 1993; Knapp, 1979).
GC/MS: retention indices and mass spectral
deconvolution
The trimethylsilyl derivatives of many plant components,
including sugars such as glucose and fructose, have very
similar EI mass spectra. In order to distinguish them, GC
retention parameters are particularly important. Since retention times vary with the column length, type of stationary
phase and temperature, suitable parameters for comparison
include relative retention times and so-called retention
indices (RI). Relative retention times are simply the ratios
of analyte times to the time of a chosen standard compound.
A more universal solution is based upon so-called Kovats
indices (Kovats, 1958) which relate the retention times of
the components to the retention times of n-alkanes analysed
under the same conditions, even by co-injection. For
example, a sugar derivative having the same retention
time as the n-alkane C20 would be assigned an index of
2000 or a ‘methylene unit’ value of 20.00. One appearing
half-way between C20 and C21, would be assigned an index
of 2050, and so on. Most manufacturers’ data systems do
not handle RI values well, if at all. However, the Automated
Mass Spectral Deconvolution and Identification System
(AMDIS) (Stein, 1999) from the National Institute of
Standards and Technology (NIST) has excellent RI capabilities and is readily available for download (http://
chemdata.nist.gov/mass-spc/amdis/). The software can read
most manufacturers’ data files and perform mass spectral
deconvolution in order to ‘clean up’ the mass spectra prior to
library searching. In addition, user library creation is simple
and spectra can be searched against the NIST database
(Table 3, www.hdscience.com). The AMDIS software has
been applied to plant (Fiehn, 2003) and urinary metabolites
(Halket et al., 1999).
GC/MS: mass spectral integrity
In metabolic profiling, mass spectra are scanned during the
chromatographic peak elution. Modern quadrupole mass
Fig. 4. GC/MS analysis showing conversion of arginine to ornithine upon trimethylsilylation by treatment with MSTFA (37 8C, 20 min). The total ion
current chromatograms obtained from arginine and ornithine are shown in (A) and (C), resp., and both have peaks at retention time 23.9 min as well as
identical mass spectra (B) and (D) corresponding to N,N9O-tris(trimethylsilyl)ornithine. Instrumentation: Agilent 6890 gas chromatograph, injected 1 ll
(split 1:20, 2908) sample in MSTFA (N-methyl-N-trimethylsilyltrifluoroacetamide), column: 30 m30.25 mm30.25 lm film thickness (DB5MS),
temperature program: 70 8C (5 min)ÿ5 8C minÿ1ÿ310 8C (7 min), detection: Agilent 5973 Mass Selective Detector, scanned m/z 10-800.
Metabolic profiling
225
Table 3. A selection of major commercially available EI
libraries
Database
Class
Wiley
NIST02
Wiley/Hennerberg
Wiley/Yarkov
General
444 000 www.hdscience.com
General
123 434 www.hdscience.com
General
40 000 www.hdscience.com
Organic
37 055 www.hdscience.com
compounds
Food volatiles
1620 www.hdscience.com
Steroids
2500 www.hdscience.com
Designer drugs
1700 www.hdscience.com
Geochemical
1100 www.hdscience.com
Pesticides
1450 www.ehrenstorfer.com
Pesticides
300 www.chem.agilent.com
Drugs/toxicol.
6300 Instrument
manufacturers
Fragrances
1606 www.allured.com
Wiley/Zeist
Wiley/Makin
Wiley/Roesner
Wiley/de Leeuw
Ehrenstorfer
Stan
PMW
Adams
Spectra
www
spectrometers can normally record about 1–6 spectra/s. If
the scanning speed is too slow, peak ‘skewing’ can occur
where the amount of sample from the GC peak changes
significantly during the mass spectral scan. Software such
as AMDIS can correct for such skewing, but the analyst has
to exercise care and ensure that a sufficient number of scans
are recorded across the GC peak to secure a sufficient
number of samples, perhaps 10, to define the peak and
enable measurements of adequate quality to be made. Since
the quantitation depends on the areas or heights of selected
ion chromatograms, an insufficient sampling rate will
increase the error in measurement. Detectors based on
time-of-flight MS can operate at much higher scan speeds,
up to 500 scans sÿ1, so that skewing is effectively
eliminated (Veriotti and Sacks, 2003).
Qualifier ions: chromatographic peak integrity
In addition to a matching retention index between the
analyte and the known compound, positive assignment will
require a mass spectral library match, performed by some
manufacturers’ data systems (see section below), or at least
agreement with the ratios of one or two qualifier ions. Figure
5 shows the GC/MS analysis of cholesterol TMS with three
reconstructed ion chromatograms; (a) m/z 458, (b) m/z 443,
and (c) m/z 368, together with a part of the mass spectrum
recorded at the peak apex (28.0 min). The ratios of the peak
areas (a), (b) and (c) should correspond to the ratios of
abundances of the ions m/z 458, 443, and 368, respectively,
in the library spectrum. The software checks these ratios and
reports deviations outside a preset range. The operation is
analogous to the wavelength absorbance ratio method in
HPLC to detect impure peaks (Sievert and Drouen, 1993).
GC/MS: automatic interpretation
Since the start of GC/MS for the diagnosis of metabolic
disorders, software approaches to automated data interpretation have been made in individual laboratories (Jellum
et al., 1975; Mizuno et al., 1981; Halket et al., 1999;
Fig. 5. The use of ‘qualifier’ ions to check the integrity of the ion used for
quantitation. GC/MS analysis of cholesterol TMS with three reconstructed ion chromatograms (a) m/z 458, (b) m/z 443 and (c) m/z 368, together
with a part of the mass spectrum recorded at the peak apex (28.0 min).
The ratios of the peak areas (a), (b) and (c) should correspond to the ratios
of abundances of the ions m/z 458, 443, and 368, respectively, in the
library spectrum.
Yamaguchi et al., 1999), but much remains to be achieved
in this area.
GC/MS: mass spectral library searching
A useful introduction to library searching is given in
a recent text (Smith and Busch, 1999). In addition, detailed
studies of search algorithms have been carried out (Stein
and Scott, 1994; McLafferty et al., 1998).
Table 3 lists some common commercially available
libraries with an indication of the numbers of spectra
available in each case. The mass spectra contained within
the NIST library are studied in detail by professional
evaluators before inclusion (Ausloos et al., 1999) ensuring
high quality.
Of particular interest to metabolic profilers are the useful
libraries downloadable from the Max-Planck Institute for
Plant Physiology in Golm, Germany (http://www.mpimp-golm.
mpg.de/mms-library/). These include TMS and TBDMS
derivatives of known compounds and also an important
library of unassigned spectra (TMS). Compound listings
include retention times. Collaborations are invited for
structure elucidation ([email protected]).
226 Halket et al.
The computerized matching of an unknown spectrum
with a database is a very rapid and useful tool in metabolic
profiling. Despite the advances made in algorithms and
software, such automated matching cannot be entirely
relied upon (Sparkman, 1996) and data must be checked
by an experienced analyst in order to ensure the integrity
of the results: a daunting task when one considers the
amount of data produced in a short time by modern
hyphenated techniques. The additional application of retention indices (see above) can improve the situation when
trying to distinguish between compounds having similar
mass spectra.
GC/MS: identification of unknowns
There is currently a great need for new methods to speed up
the structural elucidation of metabolites. In addition to
a library search, a number of steps can be taken to
‘interpret’ the mass spectrum, including accurate mass
measurements by high resolution mass spectrometry, study
of isotope ratios, study of the neutral losses, MS/MS, etc.
Several texts are available outlining such procedures in
some detail (McLafferty and Turecek, 1993; Smith and
Busch, 1999). Progress has also been made by applying
knowledge of isotopic ratios after derivatization and accurate mass measurement (Fiehn et al., 2000b).
GC/MS: the future
Great potential is offered by the high throughput capabilities
of GC/TOF/MS. Currently, the available instruments are
designed for high scanning speeds (up to 500 scan sÿ1) or
high mass resolution. Higher scanning speeds are already
being used for metabolic profiling with mass spectral
deconvolution (Weckwerth et al., 2004; Waterman et al.,
2003; Shepherd et al., 2004) and has great potential to solve
the through-put problem in GC/MS. Also, the so-called
‘ultrafast’ GC, in which very high oven temperature programming rates are used for fast chromatographic separations, can be used with fast scanning TOF mass
spectrometers. An example of a 2 min metabolic profile is
given in Fig. 6: (a) shows the total ion current chromatograms of a C8–C28 hydrocarbon mixture used for retention
index assignments via AMDIS software, (b) a derivatized
tomato extract (Waterman et al., 2003), (c) the mass
spectrum of the GC peak at 0.94 min, and (d) the match
obtained by searching the NIST02 database (Table 3)
indicating the identity as phosphoric acid TMS. In this
case, a narrow bore (0.1 mm i.d.) column has been used. The
column is resistively heated at rates of up to 1200 8C minÿ1.
GC3GC: a revolutionary development
A very simple and revolutionary innovation in GC is socalled ‘GC3GC’ or ‘comprehensive 2-dimensional GC’ in
which a non-polar column can be coupled to a shorter polar
column. The temperature of the junction between the
columns is modulated by a moving heater (Kinghorn and
Marriott, 1998a) or jets of gas (Ledford and Billesbach,
2000; Beens et al., 2001) so that peaks from the first
column are continually ‘frozen’ (modulated) and transferred to the second, faster-running column. If the first
column can separate 300 peaks and the second column 15
peaks, the total resolving power of the system is
300315=4500 peaks, representing a staggering increase
in analytical power! In addition, the modulation focuses the
peaks leading to a significant increase in sensitivity
(Kinghorn and Marriott, 1998b). Such systems are available commercially: ([email protected]; www.zoex.com).
A desirable instrument would utilize fast GC3GC, high
dynamic range and accurate mass measurements and it
remains to be seen if such a combination becomes available. However, the data generated in a short time would be
overwhelming, considering current computing limitations,
except for targeted analyses of a set of analytes small
enough to allow review by the analyst.
Liquid chromatography/mass spectrometry (LC/MS)
Many excellent sources of background information on the
major ionization techniques, such as ESI and APCI, as well
as the powerful hyphenated techniques, LC/MS, LC/MS/
MS, and LC/MSn are readily available (Cole, 1997;
Niessen, 1999; Pramanik et al., 2002; Willoughby et al.,
2002; Ardrey, 2003).
LC/MS: chemical derivatization
Compared with GC/MS, a major advantage of LC/MS
(API) has been the avoidance of a requirement to derivatize
the samples and the combined technique is already seeing
applications in metabolic profiling (Huhman and Sumner,
2002; Tolstikov and Fiehn, 2002; Tolstikov et al., 2003;
Stobiecki et al., 2003) with appropriate choices of polarity
and mobile phase compositions. As derivatization by
definition induces chemical changes and is sometimes
performed under harsh conditions with a consequent danger
of artefact formation, it is best avoided if at all possible.
However, the literature now contains many examples where
derivatization can be advantageously employed to enhance
the signals obtained from soft ionization MS techniques,
Fig. 6. Ultrafast GC/time-of-flight (TOF) MS showing metabolic profiles in approximately 2 min: (a) total ion current (TIC) chromatogram of a mixture
of C8-C28 straight chain hydrocarbons used for retention index assignments via AMDIS software, (b) TIC chromatogram of a trimethylsilylated tomato
extract (Waterman et al., 2003), (c) mass spectrum of GC peak with retention time 0.94 min (arrowed), (d) matched spectrum of phosphoric acid TMS
from NIST 02 mass spectral library. GC/MS system: TRACE gas chromatograph and TEMPUS mass spectrometer (Thermo, San Jose), equipped
with a split injector (1:300) and 10 m30.1 mm (0.1 lm film thickness RTX-5) column, temperature program 70 8C (0.1 min)ÿ120 8C minÿ1ÿ350 8C
(0.5 min), full scan mode (m/z 30–600, 40 scan sÿ1).
Metabolic profiling
227
228 Halket et al.
such as fast atom bombardment (FAB), thermospray, ESI,
and matrix-assisted laser desorption-ionization (MALDI).
The rationale behind such attempts to alter the chemical
properties can be seen in Fig. 2. Analytes in the ESI region
containing different functional groups can have diverse
ionization properties, giving preferentially positive or
negative ions depending on the mobile phase composition.
For example, the ESI method in positive mode would work
particularly well with positively charged (or easily chargeable) species (highly polar) so that a derivatization scheme
which introduces such species to a wide variety of compounds would facilitate simultaneous measurement (profiling) of an increased number of compounds in one
analysis. The same would apply to negatively charged (or
easily chargeable) species.
The early introduction of soft ionization techniques such
as fast atom bombardment (Barber et al., 1981) allowed
peptides to be analysed directly without the need for the
chemical derivatization, hitherto essential for direct probe
EI mass spectrometry and GC/MS. Despite this, derivatives
have been reported to improve the MS/MS fragmentation
patterns and facilitate de novo sequencing (Vath and
Biemann, 1990; Stults et al., 1993; Zaia and Biemann,
1995; Huang et al., 1997; Brancia et al., 2000; Lindh et al.,
2000). Derivatives for FAB MS have been reviewed
(Spreen, 1993). Similarly, the FAB/MS analysis of acylcarnitines and amino acids was improved by n-butylation of
their carboxylic acid groups (Millington et al., 1991).
Urinary carboxylic acids have been analysed directly by
LC/MS when the thermospray technique (Blakley and
Vestal, 1983) was introduced, but the method was not
powerful enough to achieve routine application. Alkylaminoethyl derivatization of the carboxylic acid groups improved the thermospray detection limits of prostaglandins
and thromboxane B2 by an order of magnitude (Voyksner
et al., 1987).
Although atmospheric pressure LC/MS/MS is eminently
suited to the profiling of polar compounds without such
derivatization (Tolstikov and Fiehn, 2002), applications of
derivatization are increasing, usually for specific applications. For example, the clinically important group of
acylcarnitines (Rashed et al., 1994) and amino acids (Casetta
et al., 2000) are commonly n-butylated prior to direct ESI
MS/MS analysis. The ion trap MS/MS spectra of the butyl
esters of acylcarnitines yield more fragment ions than the
underivatized compounds giving more detailed mass spectral ‘fingerprints’ and thereby increasing their utility for
identification (Baumann et al., 2000). Interesting derivatives
based on electrochemically-generated ions (Van Berkel et al.,
1992) can enhance detection characteristics. Ferrocenebased electrochemically ionizable derivatives facilitate
analysis of simple alcohols, sterols and phenols (Van Berkel
et al., 1998; Diehl and Karst, 2002) and provide further
structural information. Alcohols could be selectively
detected by ESI at low levels in a complex fruit extract
(Quirke et al., 2000). Fatty acids have been analysed by ESI
using alkyldimethylaminoethyl derivatives (Johnson, 2000).
Polar derivatives have been applied to steroids (Nakagawa
and Hashimoto, 2002; Griffiths et al., 2003), fatty alcohols
and alcohol ethoxylate surfactants in wastewater (Dunphy
et al., 2001), carbonyl compounds (Brombacher et al.,
2002), and drug impurities (Barry et al., 2003b) with
improved detection. In MALDI MS, charged tris(2,4,6trimethoxyphenyl)phosphonium (TMPP) derivatives were
used for the derivatization of peptide amino groups (Huang
et al., 1997), yielding improved sequence information.
Such derivatives have since been applied to amines and
carboxylic acids (Leavens et al., 2002), alcohols, aldehydes,
and ketones (Barry et al., 2003a), oligosaccharides (Naven
et al., 1996), and carboxylic acids (Gröger et al., 2003;
Cartwright et al., 2004; Waterman et al., 2004; J Halket
et al., unpublished data). The chromatographic properties of
the TMPP derivatives of amines have also been investigated
(Spikmans et al., 2002) and a preliminary study has been
carried out on the utility of TMPP derivatives for metabolic
profiling (Gröger et al., 2003; J Halket et al., unpublished
data). Also, electron-capturing derivatives have been shown
to facilitate greatly the analysis of small molecules at
attomole levels (Singh et al., 2000) with application to
lipidomics (Lee et al., 2003).
The application of stable-isotope-labelled derivatives
(Gygi et al., 1999) is having an enormous impact on
protein analysis (isotope coded affinity tags, ICAT), a clear
indication of the potential utility of chemical derivatization
(tagging) in API MS.
LC/MS: chromatographic retention data
The use of retention parameters in HPLC is complicated by
the variety of column stationary phases available and the
infinite number of mobile phase combinations which can be
used to provide suitable separations. Despite such difficulties, retention parameters have been described and this area
will have increasing importance in metabolic profiling by
LC/MS. One study used the co-injection of a series of
nitroalkanes (Bogusz and Wu, 1991) and another study
involved the assignment of hydrophobicity indices to the
analytes, based upon separation of a series of compounds of
known indices across a water–acetonitrile gradient (Valko
et al., 1997). It may be that a calculation approach will find
application in this area (Palmblad et al., 2002).
The creation of peak tables (metabolomic data matrices)
as illustrated in Fig. 3, and comparison of LC/MS data
between laboratories would be greatly facilitated by the
availability of a universal index. It is hoped that further
research will be carried out in this important area.
LC/MS: can we use mass spectral libraries?
Computerized library searching of electron ionization (EI)
mass spectra has revolutionalized the application of GC/
MS, and much was expected of LC/MS using the particle
Metabolic profiling
mass spectral patterns are less reproducible than electron
impact ionization (EI) mass spectra between instruments
from different manufacturers. The fragmentation patterns
depend on a large number of factors, many of which are not
properly understood: ion source designs, ion source potentials, mobile phase effects, etc. However, efforts are being
made and several API/MS/MS libraries have been created
and applied successfully.
Three common types of product ion mass spectra will be
considered here: (i) source-CID or transport region CID in
a single quadrupole mass spectrometer; (ii) CID in a triple
quadrupole mass spectrometer; and (iii) CID in a quadrupole ion trap mass spectrometer
beam interface (Willoughby and Browner, 1984) which
gives conventional EI spectra. However, the technique was
found to lack the sensitivity required for many applications
(Wolff et al., 2001). Softer ionization techniques, including
atmospheric pressure ionization (API), are much more
sensitive than particle beam, but generally produce much
simpler spectra than EI.
The EI mass spectrum of the turmeric pigment curcumin
(Curcuma longa L.) is shown in Fig. 7A together with the
ESI spectrum (Fig. 7B), consisting almost entirely of
a simple ‘pseudo’ or ‘quasi’ molecular ion signal
([M+H]+). Such simple mass spectra are less suitable as
mass spectral fingerprints for library searching. However,
further fragmentation of the pseudo-molecular ion by
a process known as collisionally induced dissociation
(CID) or collisionally activated dissociation (CAD) usually
produces a more detailed product ion mass spectrum, such
as that shown in Fig. 7C.
Although API/MS/MS techniques have been used for
many years, workers have been reluctant to create and
search libraries of product ion mass spectra because the
Source-CID or transport region CID in a single
quadrupole mass spectrometer
In single quadrupole instruments, the ions can be energized
in the transport region between the ion source and mass
spectrometer by increasing the cone voltage and thereby
promoting collisions with solvent and gas molecules. There
is no ion selection as in tandem mass spectrometry (see
177
100
O
O
(A)
O
50
190
137
89
51 65 77
O
HO
OH
217 232
159
50
80
(curc) CURCUMIN EI
110
140
298
170
200
350 368
272
0
230
260
290
320
320
350
O
O
(B)
O
O
50
HO
74
0
122
143
167 183
50
80
110
140
(curc) CURCUMIN ELECTROSPRAY
170
OH
235 256
208
200
230
260
279
309
290
340
320
350
380
245
100
50
380
369
100
(C)
229
O
O O
O
285
OH 175
HO
151
203 219
259
200
260
299
369
325
351
0
50
80
110
(curc) CURCUMIN MS/MS 30
140
NCE
170
230
290
320
350
380
Fig. 7. (A) EI spectrum of the turmeric (Curcuma longa L.) pigment curcumin (Mr=368) taken from the NIST02 database, (B) the ESI mass spectrum
showing [M+H]+=369, (C) the product ion mass spectrum obtained by collisionally induced dissociation (CID) using an LCQ DECA quadrupole ion
trap mass spectrometer (Thermo, San Jose), ESI, positive, 4.5 kV, capillary 200 8C, normalized collision energy 30%, isolation width 1.5 Th. A 1 lg
mlÿ1 standard solution of curcumin in acetonitrile-water (50:50, v/v) was infused at 5 ll minÿ1.
230 Halket et al.
below) so that this so-called ‘source CID’ or ‘transport
region CID’ is applied to all molecules present in the
system. Other names for the technique include orifice or
nozzle-skimmer voltage CID. As in EI, the mass spectra
produced will be overlapped so that chromatographic
separation is desirable (as in GC/MS).
Such transport region CID spectral patterns have been
shown to vary greatly with instrumental conditions (Bogusz
et al., 1999). Corresponding libraries have only become
available following the introduction of tuning compounds,
enabling fairly reproducible spectra to be obtained, albeit
on instrument types from the same manufacturer (Marquet
et al., 2003; Hough et al., 2000; Weinmann et al., 2001).
The equipment is relatively inexpensive.
Several libraries have been created and successfully
applied, mainly in the forensic toxicology arena (Table 4).
MS/MS: CID in a triple quadrupole mass spectrometer
This sophisticated technique represents true tandem mass
spectrometry where the different stages of the process are
separated in space. Parent ions are selected in the first
quadrupole, subjected to CID by collision with gas molecules (argon, nitrogen, air) in a second quadrupole, which
functions as a collision cell, and the product ion mass
spectrum scanned in the third. The instrumentation is still
relatively expensive. Some libraries are listed in Table 5.
MS/MS: CID in a quadrupole ion trap mass
spectrometer
In the quadrupole ion trap, different stages of MS are
carried out in time (Bier and Schwartz, 1997). In addition to
an inherent high sensitivity, multiple levels of MS (MSn)
can be carried out by sequentially isolating and fragmenting
selected ions in the trap. The ability automatically to switch
triggering of MS/MS according to parent ion intensities
(data-dependent scanning, (Tiller et al., 1997)) and further
automation facilities (Drexler et al., 1998) are powerful
features. Longer residence times in the ion trap can lead to
more rearrangement ions than with the other techniques
described above. The instrumentation is very compact and
relatively inexpensive. A selection of ion trap MS/MS
libraries is listed in Table 6.
The library references made here are by no means
complete. Many libraries are proprietary and details are
not made public. In addition, the accuracy of the information given in Tables 4–6 could not be verified in each case
prior to publication, library creation is hopefully not static!
The references are given as a guide or starting point for the
reader.
Some examples are now given of the ion trap library
being created in the authors’ laboratory (Baumann et al.,
2000; Eichler et al., 2000; Cintora et al., 2001). The
MS/MS library has been compiled using the powerful
Table 4. Some single quadrupole (in-source, transport region) CID libraries
Instrument
Class
Spectra
Compounds
Polarity
Reference/contact
Sciex
Sciex
Sciex
Sciex
Sciex
Micromass
Agilent
Agilent
Drugs/toxicity
Drugs/toxicity
Drugs/toxicity
Pesticides
Explosives
Chemicals
Pesticides
Drugs/toxicity
1200
1200
1293
90
50
559
100
41
400
1200
431
90
50
559
100
41
+/ÿ
+/ÿ
+/ÿ
+/ÿ
+/ÿ
+/ÿ
+/ÿ
+/ÿ
Gergov et al., 2000 [email protected]
Marquet et al., 2000 [email protected]
Weinmann et al., 2001 www.chemicalsoft.de
Schreiber et al., 2000 www.chemicalsoft.de
Schreiber et al., 2000 www.chemicalsoft.de
J Little, personal communication [email protected]
Hough et al., 2000
Lips et al.,2001
Table 5. Some triple quadrupole MS/MS libraries
Instrument
ClassS
Spectra
Compounds
Polarity
Reference/contact
Sciex
Sciex
Micromass
Thermo
Thermo
Drugs/toxicity
Drugs/toxicity
Pesticides
Drugs
Pesticides
1200
2151
60
70
193a
400
717
60
70
150a
+/ÿ
+/ÿ
+
+
+/ÿ
Weinmann et al., 2000 [email protected]
Weinmann, 2003 www.chemicalsoft.de
Slobodnik et al., 1996
Josephs, 1995
Kienhuis et al., 2002
a
General library with GC-MS/MS, LC/MS and LC/MS/MS data (www.riza.nl/cicid)
Metabolic profiling
231
Table 6. Some quadrupole ion trap MS/MS libraries
Instrument
Class
Spectra
Compounds
Polarity
Reference/contact
Thermo
Thermo
Thermo
Thermo
Thermo
Thermo
Thermo
Thermo
Bruker
Agilent
Miscellaneous
Drugs
Drugs
Drugs/natural products
Natural products
Natural products
Natural products
Pesticides
Misc.
Pesticides
1200
80
75
43 000
200
200
100
100
700
3000
1200
80
75
29 000
100
100
40
60
210
1000
+
+
+
+/ÿ
+/ÿ
+/ÿ
+/ÿ
+/ÿ
+/ÿ
+
Baumann et al., 2000; [email protected]
[email protected]
Fitzgerald et al., 1999
Josephs et al., 2004; [email protected]
G Kite, personal communication
[email protected]
E Messens, personal communication [email protected]
H-J Stan, personal communication
P Sander, personal communication
[email protected]
technique of normalized collision energy (Lopez et al.,
1999), which automatically compensates for the massdependent energy deposition characteristics typical of ion
trap instruments and makes the MS/MS spectra remarkably
reproducible and relatively insensitive to instrumental
settings.
Rapid confirmation of curcumin in turmeric (Curcuma
longa L.) powder
A simple extract of turmeric (Curcuma longa L.) powder
(approximately 0.5 mg mixed with 1 ml methanol–water,
1:1, v:v) was infused into an ion trap mass spectrometer at 5
ll minÿ1. A clear signal was obtained at m/z 369 (data not
shown) which could correspond to the [M+H]+ ion of
curcumin. The product ion mass spectrum obtained for m/z
369 is shown in Fig. 8A, together with the NIST library
match for curcumin (B), a substance exhibiting beneficial
antioxidant properties and approved as a colouring material
in foodstuffs. The library spectrum had been made several
years beforehand on a different LCQ instrument. The whole
analysis took only a few minutes.
MSn spectra
A great advantage of ion trap mass spectrometers is the
ability to carry out multiple levels of MS. In cases where the
MS/MS spectrum is dominated by a single ion, this ion can
be selected and fragmented further to give an MS/MS/MS
(MS3) spectrum.
A simple example is shown in Fig. 9. A solution of the
tomato alkaloid tomatine (5 lg mlÿ1 in methanol–water,
1:1, v:v, containing 0.1% formic acid, 5 ll minÿ1) was
infused into the LCQ XP. The mass spectrum gave a single
ion at m/z 1037.5 (data not shown). The MS/MS spectrum
obtained by fragmentation of this ion (50% collision energy
(Lopez et al., 1999) is shown in Fig. 9A in NIST user library
format. In addition to the major fragment ion at m/z 1017,
a smaller fragment ion at m/z 416, corresponding to the
molecular mass of tomatidine, was selected for a further
fragmentation step. The product ion mass spectrum (MS3)
obtained is shown in Fig. 9B together with the best library
match showing tomatidine contained in a 1000 compound
ion trap library (Baumann et al., 2000). The spectra are not
identical, giving a NIST match factor (Stein, 1994) of only
625, a consequence of the different energies used to obtain
them. However, they are similar enough to indicate the
usefulness of the procedure for rapid chemical analysis. An
advantage of relatively low cost ion trap mass spectrometers
is the capability of carrying out MSn experiments, useful in
structure elucidation (Tolstikov and Fiehn, 2002). The m/z
selection and ionization steps can be automated to give
fragmentation maps and can be repeated up to 10 times,
although the sensitivity of the technique reduces after each
step. In many cases, MS4 or MS5 will be achievable with
biological samples, depending on the analyte concentration.
Development of an ion trap library
Recently, spectra are being acquired with a variety of
conditions and contributions of spectra are being received
from collaborators. The library now contains approximately
1200 spectra, about half of which are drug-related. The
library will be distributed free of charge to contributors and
other Thermo LCQ users. The spectra will also be included
in a large MS/MS library to be distributed by NIST
([email protected]).
LC/MS/MS: towards a universal library?
Further to early work on the reproducibility of triple
quadrupole CID spectra (Martinez, 1991), the factors
affecting the API product ion mass spectra originating
from a number of instruments are being actively studied
(SE Stein, personal communication). Mass spectra from
different instrument types and manufacturers are being
232 Halket et al.
Fig. 8. Ion trap electrospray MS/MS spectrum of a turmeric (Curcuma longa L.) powder extract. NIST user library search on MS/MS spectrum (A)
obtained by infusion into an LCQ DECA XP quadrupole ion trap mass spectrometer (Thermo, San Jose), ESI, positive, 4.5 kV, capillary temperature
260 8C, nitrogen sheath gas 10 (arbitrary units), normalized collision energy 50% (wideband OFF), collisionally induced dissociation on [M+H]+ ion (m/
z 369) revealing a good match with curcumin standard MS/MS spectrum in ion trap library (B). Mass spectral searching utilized the National Institute of
Standards and Technology (NIST, Gaithersburg, USA) algorithm as implemented in the Xcalibur data system (version 1.2). Sample preparation:
approximately 0.5 mg powder mixed with 1 ml methanol–water (1:1) and centrifuged before infusion at 5 ll minÿ1.
compared. Although perfectly matchable spectra from
different instruments seems unlikely, early indications are
that useful universal libraries may be created (Bristow
et al., 2002, 2004; Gergov et al., 2004).
LC/MS/MS of derivatized organic acids
As previously demonstrated, charged tris(2,4,6-trimethoxyphenyl)phosphonium (TMPP) derivatives of organic acids
can be prepared using a TMPP propylamine reagent
following activation of the carboxylic acid group with 2chloro-1-methylpyridinium iodide (Leavens et al., 2002; J
Halket et al., unpublished data).
In the first part of a comprehensive LC/MS/MS derivatization study, MS/MS spectra of a wide range of
organic acid TMPP derivatives have been recorded and
stored in a NIST format user library. The derivatization
improves the detection characteristics of the carboxylic
acids and femtogram sensitivity has been achieved with
standards (J Halket et al., unpublished data). Utility of the
derivative is illustrated by preliminary examples of metabolic profiling in extracts of tomato tissue. The work
represents the first stage in the development of a sequential
derivatization and multi-component analysis procedure
applicable in the field of metabolic profiling.
The TMPP derivatization step is shown in Fig. 10A for
gibberellic acid (Cat+=m/z 918) together with the corresponding MS/MS spectrum (NIST user library format) of the
product in Fig. 10B. The mass spectrum has several high
molecular mass fragment ions eminently suitable for the
recognition and also for the quantitation of this compound.
Reconstructed mass chromatograms (C1–C6) for a mixture of volatile carboxylic acids following separation on
a short HPLC column are shown in Fig. 11A together with
the MS/MS spectrum of the formic acid TMPP derivative
(NIST user library format) in Fig. 11B. Using this procedure,
compounds covering a wide range of molecular mass can be
determined in a single analysis. The determination of low
molecular weight acids is difficult to carry out by GC/MS,
particularly in the same separation as compounds having
much greater molecular mass, such as oleic acid.
The degree of separation of the acid TMPP derivatives
obtained using such a short HPLC column is remarkable.
Metabolic profiling
233
Fig. 9. Positive electrospray MS/MS and MS3 spectra of the tomato alkaloid tomatine (5 lg mlÿ1 in 1:1 methanol-water, containing 0.1% formic acid)
infused into the ion trap mass spectrometer at 5 ll minÿ1: (A) product ion mass spectrum of m/z 1037.5 (M+H]+) shown in NIST library format and (B)
library search report on product ion mass spectrum of m/z 416 (MS3, indicated by arrow) together with best library match (C, tomatidine). LCQ DECA
XP quadrupole ion trap mass spectrometer (Thermo, San Jose), ESI, positive 4.5 kV, heated capillary 260 8C, nitrogen sheath gas 40 (arbitrary units),
normalized collision energy 50%, isolation width 3 Th. Mass spectral searching utilized the National Institute of Standards and Technology (NIST,
Gaithersburg, USA) algorithm as implemented in the Xcalibur data system (version 1.3).
Formic and acetic acids are nearly resolved and acetic and
propionic acids are resolved completely within about 8 min.
The new technique should prove to be useful for the
qualitative and quantitative analysis of acidic compounds
present at very low levels in plant tissues. The ion trap TMPP
derivative library now contains nearly 100 product ion mass
spectra, including some MS/MS/MS (MS3) spectra.
Metabolic profiling of tomato extracts
A selection of the ion chromatograms present in a total ion
current profile of TMPP derivatized tomato extract is
shown in Fig. 12 and illustrates how relative integrated
peak areas could be utilized in statistical comparisons of
biological samples, such as the comparison of GM versus
non-GM foodstuffs (Gröger et al., 2003; Waterman et al.,
2004). The boxed peak indicated in Fig. 12A for m/z 764 is
shown in expanded form in Fig. 12B. The product ion mass
spectrum recorded for the small peak with a retention time
of 16.2 min is shown in Fig. 12C together with the best
library match, indicating that the compound is derived from
the TMPP derivative of quinic acid. The larger chromatographic peak at 16.81 min in Fig. 12B was found to
correspond to citric acid TMPP (data not shown). The lack
of chemical noise in the reconstructed ion chromatograms
in Fig. 12A is notable and a result of the relatively high m/z
ratios of the derivatives.
234 Halket et al.
O
O
O
HO
O
O
O
Br
O
O
GA
O
NH2
P
CMPI / TEA
O
O
O
O
O
HN
P
(A)
O
O
O
O
OH
O
C49H61NO14P
O
918.382969
O
874
100
O
O HO
O
O
P+
NH
O
O
O
533
320
4 40
280
360
400
(g02 tmp p) GIBBERELIC ACID TMPP
48 0
520
560
600
846
856
OH
O
O
590 616
0
(B)
O
O
50
O
828
640
680
720
760
8 00
840
880
920
Fig. 10. (A) Reaction scheme for the TMPP derivatization of gibberellic acid (CMPI=2-chloro-1-methylpyridinium iodide, TEA=triethylamine) and (B)
resulting ion trap MS/MS spectrum (product ions of m/z 918) in NIST user library. Derivatization was carried out as previously described (Leavens et al.,
2002; J Halket et al., unpublished data).
Statistical analysis
The principal components analysis (PCA) score plot of a set
of electrospray LC/MS (ion trap) obtained from derivatized
tomato extracts (Waterman et al., 2004; J Halket et al.,
unpublished data) is shown in Fig. 13. A matrix (16315,
compound abundance versus sample) representing the
relative amounts of 16 unidentified analytes corresponding
to TMPP-derivatized components from five tomato types in
triplicate was extracted from the data. Chromatograms of
the m/z values (Cat+) for the selected components were
automatically integrated from each chromatogram, using
a quantitation method in the Xcalibur software and the
peak areas (abundances) input into the table.
Of the ten principal components generated, the first two
components accounted for 67% of the total variance in the
data.
Proper treatment of data using PCA should involve more
data points than shown in this example. However, the
diagram does serve to illustrate the potential of the method
for metabolic profiling. Although there is a degree of
overlap for the five types of tomato samples, the data are
seen to cluster relative to tomato type. In order to evaluate
the route of the distribution along the two principal
component axes, a weightings plot for each variable can
be produced indicating components corresponding to each
area of the PCA scores plot (data not shown). In this case
components are not identified and the PCA methodology
simply illustrates the potential of the derivatization technique in this field. An exhaustive study using a large
number of samples is currently being carried out and
includes the identification of key metabolites.
LC/MS: structure elucidation of unknowns
As in GC/MS, library searching and mass spectral interpretation steps (see GC/MS section) may assist in
structure elucidation, although fragmentation mechanisms
can be quite different. The application of ion trap or Fourier
transform mass spectrometers with multiple levels of MS
(MSn) to elucidate fragmentation pathways, together with
NMR and high resolution MS (Tolstikov and Fiehn, 2002)
is encouraging. The power of LC/UV/NMR/MS for the
structural elucidation of plant metabolites has been well
demonstrated (Wolfender et al., 2003). Recent developments in cryoprobe NMR on-line with MS (Spraul et al.,
Metabolic profiling
235
Fig. 11. Reconstructed mass chromatograms (C1–C6) for a mixture of volatile carboxylic acids together with the MS/MS library spectrum of formic
acid TMPP (Cat+=m/z 618). HPLC: Thermo Separation Products AS3000 autosampler, P4000 gradient pump, 50 mm32.1 mm i.d. (5 lm Zorbax SBC18), gradient: % water:% methanol: 60:40 (0 min); 60:40 (6.5 min); 90:10 (15 min); 90:10 (30 min); MS: ion trap mass spectrometer (LCQ DECA,
Thermo, San Jose), ESI, positive mode, 4.5 kV, heated capillary 200 8C, nitrogen sheath gas 60 (arbitrary units), normalized collision energy 40%,
wideband activation OFF, two scan events: (1) full scan m/z 250–1000, (2) full data dependent scan to automatically trigger MS/MS data acquisition, (B)
MS/MS spectrum (40% normalized collision energy) of formic acid TMPP from NIST user library.
2003; Exarchou et al., 2003) will surely assist with this
important task.
Discussion
Physico-chemical limitations of GC/MS and LC/MS
An obvious limitation of these combined techniques is that
the columns are also acting as filters and not all components
injected will necessarily pass through, a consequence of the
different physico-chemical properties of the analytes and
matrix components (polarity, molecular mass, etc). Components will therefore remain in the injector, column and
detector areas and the whole system will be inherently
different after each injection. This is in stark contrast to
a non-destructive spectroscopic technique such as NMR.
The analyst must therefore be aware of subsequent degradation in both column and detector performance and appropriate controls must be incorporated in any such analytical
system (regular injection of quality assurance samples and
maintenance of control charts).
It is clear that the current speed limitations on the
analytical power of GC/MS and LC/MS are quite severe
considering the large numbers of samples to be analysed in
metabolomics. However, the introduction of faster devices
such as TOF/MS perhaps combined with multi-dimensional
chromatographic separation techniques and more ‘intelligent’ software, both for peak recognition and data interpretation, will help to ensure the future of the profiling
methods. The LC/MS technique particularly requires faster
separations. Although important developments are being
made in LC column technology (Tolstikov and Fiehn,
2002) and in ultra-high pressure gradient l-HPLC (Tolley
et al., 2001; Legido-Quigley et al., 2002) with corresponding increases in resolving power, such methods are not yet
fast enough for high throughput profiling.
Data exchange limitations on GC/MS and LC/MS
Serious problems still exist with compatibilities between
mass spectrometer manufacturers’ data files, so there is
a strong need for universal data processing. AMDIS
software can read and process most data files and although
it has been designed for GC/MS applications, it should also
find applications in LC/MS. Further specialized software is
being developed with metabolic profiling in mind (Table 1)
and the development should benefit from user feedback on
requirements.
GC/MS and LC/MS: inter-laboratory comparison of
data sets
Library matching and retention parameter comparisons are
important for inter-laboratory comparisons of data sets, i.e.
is the unknown ‘x’ in laboratory A the same ‘x’ measured in
laboratory B and so on. A useful step would be the creation
of standard data sets for individual species (Overy et al.,
2004). A further aid to recognition of compounds between
laboratories could be the universal adoption of an identifier
236 Halket et al.
Fig. 12. Data-dependent LC/MS/MS analysis of a TMPP derivatized methanolic extract of tomato tissue (J Halket et al., unpublished data) showing (a)
selected ion chromatograms, (b) detail of m/z 764 peak and (c) NIST library match for quinic acid on corresponding MS/MS spectrum recorded for m/z
764 at 16.2 min. HPLC: Thermo Separation Products AS3000 autosampler, P4000 gradient pump (Thermo Separation), 10 cm32.1 mm i.d. (5 lm
HyPURITY C18), gradient: % water:% acetonitrile both with 0.05% formic acid (time min), 0.5 ml minÿ1: 70:30 (0 min); 70:30 (3 min); 10:90 (10
min); 10:90 (20 min); 70:30 (20.5 min); 70:30 (37 min), MS: Thermo LCQ DECA, ESI, positive mode, 4.5 kV, heated capillary 200 8C, nitrogen
sheath gas 60 (arbitrary units), normalized collision energy 40%, wideband activation OFF.
for chemical entities such as the CAS (Chemical Abstracts
Service) Registry Number: The Chemical Abstracts Service
(a Division of the American Chemical Society) administers
a scheme whereby chemical entities can be assigned unique
numerical identifier numbers (http://www.cas.org/). Considering the variety of naming schemes available for
chemicals (common names, IUPAC names, etc), the use
of such unique identifiers can enable workers throughout
the world to avoid confusion.
The numbers themselves have no chemical significance
and can contain up to nine digits divided by hyphens into three
parts. Examples of CAS numbers taken from the NIST02
Metabolic profiling
237
Scores Plot of TMPP Profiling Data
8.E+09
Tomato Line 2
PC2
Tomato Line 1
0.E+00
Tomato Line 3
Tomato Line 4
TomatoLine 5
-2.E+10
0.E+00
2.E+10
-8.E+09
4.E+10
PC1
Fig. 13. Principal components analysis (PCA) scores plot of electrospray LC/MS data from TMPP derivatized tomato extracts (three samples of each of
five tomato types and the selected ion abundances of 16 components) (J Halket et al., unpublished data). By plotting PC1 versus PC2 a degree of
clustering of the data by tomato type is apparent showing the potential of the technique to distinguish between tomato types. Chromatograms of the m/z
values (Cat+) were automatically extracted and integrated from each chromatogram using a quantitation method in the Xcalibur software and the peak
areas (abundances) input into the table.
mass spectral library (http://www.nist.gov/srd/nist1a.htm/)
are: citric acid: [77-92-9]; citric acid tetra-TMS derivative:
[14330-97-3]; L-serine: [56-45-1]; D-serine: [312-84-5]; DLserine: [302-84-1]; serine di-TMS derivative [70125-39-2]
(O,O9-bis(trimethylsilyl)serine); serine tri-TMS drivative
[64625-17-8] (N,O,O9 tris(trimethylsilyl)serine).
The right digit in each case is a check digit used to verify
the validity and uniqueness of the entire number (http://
www.cas.org/EO/checkdig.html/).
Approximately 4000 new numbers are created every day
and there are now more than 23 million organic and
inorganic substances represented as well as over 43 million
sequences. The adoption of such CAS Numbers in metabolic profiling would facilitate data set comparisons for
compounds with assigned structures between laboratories.
Considering that many analytes in metabolic profiling have
still not been formally identified, a similar numerical
system, perhaps based on mass spectral and GC retention
parameters, could probably be developed for inter-laboratory
comparison.
*note added in proof: a system for naming unknown
compounds has just been proposed by the International
Committee on Plant Metabolomics (http://www.metabolomics.
nl). (Bino et al., 2004). Important plans to distribute
lyophilized standard reference materials are also described.
LC/MS libraries, retention data and unknowns
LC/MS libraries: Metabolic profiling by LC/MS requires the
creation and the application of mass spectral libraries, areas
being actively investigated by a number of research groups.
Until fairly recently, their creation has been ignored by mass
spectrometer manufacturers and software incompatibilities
between data files of major manufacturers still exist. These
issues will hopefully be addressed as more users undertake
profiling. NIST user libraries are being constructed in the
authors’ laboratory by the addition of product-ion (MS/MS)
and MSn mass spectra of metabolites and derivatives
obtained from an ion trap mass spectrometer. These MS/
MS spectra are reproducible and suitable for library searching. In cases where the MS2 spectrum is very simple, MS3
and further levels can be easily investigated. Such library
searching in LC/MS is now a routine operation (Baumann
et al., 2000). The libraries are being constantly updated with
the spectra of unknowns from biological material as well as
those of authentic standards. The NIST format libraries can
be accessed directly by the Xcalibur data system to perform
library matching including spectra acquired during datadependent scanning experiments, i.e. where the software
triggers MS/MS on a chosen set of precursor ions or those
ions above a preset abundance threshold.
LC retention parameters: Development and standardization
of LC retention parameters is lacking. Hopefully, powerful
concepts such as the ‘hydrophobicity index’ (Valko et al.,
1997) will provide a solution.
Derivatives for LC/MS: Although chemical derivatization
is often not necessary in LC/MS, it is clear that derivatives
238 Halket et al.
can provide advantages in many cases. This follows the
widespread and highly successful application of derivatization in HPLC with UV and fluorescence detection (Lunn
and Hellig, 1998; Toyo’oka, 1999). Increasing numbers of
MS applications are being described.
Organic acids: The ESI mass spectra of the organic acid
TMPP derivatives show strong Cat+ ions with little fragmentation, as previously observed in a quadrupole instrument (Leavens et al., 2002). The ion trap MS/MS spectra
obtained at 30–50% normalized collision energy (LCQ)
appear to be useful mass spectral ‘fingerprints’ and are not
generally dominated by the expected m/z 533 ion resulting
from cleavage of the phosphonium moiety.
Derivatization of extracts with TMPP reagent greatly
improves the sensitivity of detection of carboxylic acids in
positive ESI LCMS over negative ion measurements. An
increase of approximately 1000 times has been found for
adipic acid (J Halket et al., unpublished data) using an ion
trap mass spectrometer, and about 30 times for sorbic
acid using a triple quadrupole instrument (Cartwright et al.,
2004).
Although the TMPP derivatization has not been studied
fully with regard to the reaction yield and formation of
multiple-charged ions, the examples clearly demonstrate
the potential of this method and encourages further investigation. For many analyses, a quantitative yield is not
essential where the method is reproducible and stable
isotope-labelled internal standards are employed for representative components.
The method provides a great improvement in signal/
noise ratio by virtue of the high mass derivatization. This
should enable the small volatile organic acids to be
measured in the same chromatographic run as much larger
analyte molecules. The improvement in sensitivity will
have consequences for trace analysis, for example, the
detection of very low levels of metabolites, plant hormones,
and signalling compounds as TMPP derivatizing reagents
are also available for other functional groups (Barry et al.,
2003a). TMPP derivatives are also suitable for inductivelycoupled plasma (ICP) MS detection and such an application
has also been described (Cartwright et al., 2004).
Charge derivatization may be useful in compensating for
ionization suppression effects by virtue of the sensitivity
increases obtained by the precharged species and such
a study is ongoing.
Examples have been given here of the charge derivatization of carboxylic acids as part of a larger study to design
a generic multi-reagent derivatization procedure in order to
maximize the number of compounds which can be detected
and possibly quantified in a single polarity direct infusion
MS or LC/MS(/MS) experiment. It remains to be seen
whether derivatization procedures will significantly contribute to metabolic profiling by LC/MS and related soft
ionization MS techniques.
GC/MS and LC/MS: the compromises on quality
GC/MS and LC/MS for metabolic profiling are by their
nature compromises. The majority of measurements are
relative rather than absolute and are of unknowns, although
in some cases the compound class can be recognized from
the mass spectral features. The techniques have to supply
sufficient reproducibility to enable meaningful comparisons
of samples (Glassbrook et al., 2000). Stable isotope-labelled
internal standards can only be employed for a few representative members of the different analyte classes, but the
relatively large numbers of analytes in a metabolic profile
means that optimal methods cannot be applied.
The analyst should be aware of deficiencies in the
methodology used, particularly artefact formation, and
care should be exercized when interpreting the findings as
transformations can occur during sample processing (for
example, Fig. 4). Such deficiencies do not necessarily
invalidate the methods for metabolic profiling but ‘analyst
beware’. It should be understood that satisfaction of
conventional validation criteria, as used in the pharmaceutical industry (Krull and Swartz, 1999; Wood, 1999; Rosing
et al., 2000) for small and highly defined analyte groups,
cannot be met in such circumstances.
Online material
The figures in colour can be accessed at JXB online.
Acknowledgements
The authors wish to thank the Food Standards Agency (London,
UK) for funding part of this work (G02005), Bill Leavens of Glaxo
SmithKline (Stevenage, UK) for supplying the TMPP propylamine
reagent and Dr Yong Min (King’s College London) for synthesizing
a later batch, Lin Lu of Thermo Electron Corporation, Runcorn, for
assistance with the ultra-fast GC analyses and both Thermo Electron
Corporation (San Jose, CA) and Specialist Bioanalytical Services
Limited (Egham, UK) for support.
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