Biology Reference
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from biological samples with no requirement for
chemical modi
the MS acquisition parameters are also critical
steps for minimizing ion suppression.
cation such as derivatization.
The latest LC-MS technological advances allow
absolute quantitation of more than 200 metabo-
lites in rat plasma 30 and relative quantitation of
more than 250 metabolic species in bodily
Metabolite Quantitation Using LC-MS
A number of LC-MS approaches have been
proposed to compensate for the effect of ion
suppression and provide reliable metabolite
quantitation. The most common approaches in-
volve spiking biological specimens with stable
isotope ( 2 H, 13 C, or 15 N) e labeled internal stan-
dards (SILISs) or structural analogues as internal
standards. Because these materials can often be
purchased commercially and can be obtained
in high purity, they can serve as relatively reli-
able standards. Quantitation utilizing SILISs
represents a very reliable approach, as such stan-
dards possess nearly identical chemical and
physical characteristics as the analyte of interest.
Each SILIS compound is eluted and ionized
nearly identically to its corresponding metabo-
lite in the biological sample, and the increased
mass provides a peak offset by the mass differ-
ence between the two isotopic forms.
In practice, biological samples are spiked with
a standard solution of a single or multiple SILISs,
often prior to the sample preparation step to
compensate for any inaccuracies caused by
recovery loss. 30,33 Accurate concentrations of
metabolites are then determined by directly
comparing peak areas of metabolites and their
isotope-labeled internal standard. The peak
area comparison, however, is reliable only if
the peak areas for both the metabolite and its
internal standard are similar, which is often not
the case for all metabolites. Some metabolites
vary in concentration or may have unknown
concentrations. In such cases, calibration curves
need to be obtained using mixtures of standard
compounds (calibrants) of different concentra-
tions. All calibrant mixtures are spiked with SIL-
ISs at the same concentration as used in the
analysis of actual biological samples. The cali-
brants
fluids,
cells, and tissue. 31
LC-based MS methods commonly use
ionization techniques such as electrospray
ionization (ESI), as it ionizes a wide range of
metabolites without inducing metabolite frag-
mentation. Ion suppression is a major problem
associated with ESI, as it affects both the detec-
tion of metabolites as well as their reliable quan-
titation. 32 Ion suppression, in which analytes do
not become ef
soft
ciently ionized because of compe-
tition with other ionizable species, is caused by
numerous endogenous and exogenous factors
including the presence of salts, macromolecules,
or highly abundant interfering metabolites. The
addition of volatile buffers such as ammonium
acetate or ammonium formate in LC solvents
can help alleviate ion suppression due to the
salt effect. Ion suppression can also be reduced
by proper choice of sample preparation and LC
and MS parameters. Most biological samples
contain macromolecules such as proteins, which
need to be precipitated using organic solvents
such as methanol or acetonitrile. Further purifi-
-
cation by solid-phase extraction (SPE) can also
help reduce matrix effects. However, SPE is
more labor intensive and often requires
a recovery test for each metabolite. Therefore,
protein precipitation using an organic solvent
is typically a better choice for large-scale studies.
Another important step to alleviate ion suppres-
sion is optimization of chromatographic param-
eters for better peak resolution and minimization
of co-eluting metabolites. In order to improve the
separation, recently a number of researchers
used multiplexed LC methods on different
analytical columns. This approach allowed Wei
et al. to perform absolute quantitation of over
200 metabolites in biological samples. 30 Regular
cleaning of the ion source and optimization of
concentrations are chosen to cover the
whole linear dynamic range (LDR)
'
for each
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