High Resolution Mass Spectrometry * Feng Xian, Christopher L. Hendrickson,

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Review
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High Resolution Mass Spectrometry
Feng Xian,† Christopher L. Hendrickson,*,†,‡ and Alan G. Marshall*,†,‡
†
Department of Chemistry and Biochemistry, Florida State University, 95 Chieftain Way, Tallahassee, Florida 32310-4390,
United States
‡
Ion Cyclotron Resonance Program, National High Magnetic Field Laboratory, 1800 East Paul Dirac Drive, Tallahassee,
Florida 32310-4005, United States
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CONTENTS
Mass Resolution, Mass Resolving Power
Mass Resolution and Accuracy
Time-of-Flight Mass Analyzers
Orthogonal Acceleration (see ref 13)
Reflectron/Multipass TOF
Recent Advances in TOF Mass Analyzers
Selected Applications
Fourier Transform Mass Analyzers
Common Features of Fourier Transform Mass
Analyzers
Ion Accumulation and Detection
Advances in Fourier Transform Mass Analyzers
Selected Applications
Author Information
Corresponding Author
Biographies
Acknowledgments
References
resolving power is required to distinguish the same mass difference
for ions of higher mass. In practice, high resolution designates
a mass analyzer with resolving power m/Δm50% > 10 000,
thereby excluding quadrupole mass filter, triple quadrupole, and
quadrupole ion trap mass analyzers. Finally, mass measurement
accuracy is usually expressed as the rms difference (in ppm)
between measured and exact (based on elemental composition)
mass. In the absence of systematic error, mass accuracy is the
same as mass precision.
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MASS RESOLUTION AND ACCURACY
In a mass analyzer, the detected ion signal (in this case, voltage,
current, or time-of-flight) is digitized. Peak height and position
are then determined by some sort of interpolation or fitting
procedure.2−4 Mass measurement precision, namely, m/δm, in
which δm is the rms error from a large number of repeated
measurements, may in general be predicted from the product of
signal-to-noise ratio and the square root of the number of data
points per peak width,5 depending on the nature of the noise,6
from a single spectrum. Thus, for a given mass resolution, mass
measurement precision can be increased by sampling more data
points per peak width, accounting in a significant part for the
increase in TOF mass accuracy as faster digitizers became available.
Once the peak positions have been precisely established, the
spectrum is calibrated, on the basis of the exact masses of two
or more ions of known elemental composition. External
calibration (performed for a different sample than for analyte)
is typically 2−3× less accurate than internal calibration (based
on multiple ions of known m/z values in the analyte sample).
As the number of atoms increases, the number of possible
elemental compositions for a given experimental mass measurement increases.7 For proteins, the number of amino acid
compositions also increases.8,9 Moreover, high resolving power is
needed to resolve closely spaced mass doublets in complex
mixtures. For example, resolution of two equally abundant ions of
the same nominal mass but differing in elemental composition by
C3 vs SH4 (separated by ∼3.4 mDa) at m/z 700 requires a
resolving power of m/Δm50% higher than 200 000.
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MASS RESOLUTION, MASS RESOLVING POWER
This review focuses on recent advances in instrumentation,
techniques, and applications of the highest resolution mass
analyzers (multipass time of flight (TOF), orbitrap, and Fourier
transform ion cyclotron resonance (FTICR)) since a prior
similar Analytical Chemistry review in 2008.1 We begin with
a brief discussion of the need for high mass resolution, and
then proceed to mass analyzer types and their development
and applications for bio-analysis (e.g., proteomics, lipidomics,
drug discovery) and complex organic mixtures (environmental,
petroleum, metabolomics).
Mass resolution is the minimum mass difference, m2 − m1,
between two mass spectral peaks such that the valley between
their sum is a specified fraction (e.g., 50%) of the height of the
smaller individual peak. For two peaks of equal height,
m2 − m1 ≈ Δm50%, in which Δm50% is the full width at halfmaximum height of either peak alone. Mass resolving power is
m2/(m2 − m1), in which (m2 − m1) is mass resolution; for an
isolated peak of mass, m, mass resolving power is m/Δm50%,
and for two peaks of equal height, mass resolving power is
m2/Δm50%.1 For a multiply charged ion, m is replaced in the
above definitions by m/z, in which z is the ion charge in
multiples of the elementary charge. The ability to distinguish
ions of different elemental composition is determined by mass
resolution (e.g., m2 − m1 = 0.0034 Da for ions differing in
composition by C3 vs SH4). However, mass analyzer performance
is usually expressed in terms of mass resolving power. Thus, higher
© 2012 American Chemical Society
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TIME-OF-FLIGHT MASS ANALYZERS
The time-of-flight mass analyzer, initially proposed by Stephan
in 194610 and reduced to practice in 1948,11 has evolved
through several stages. Delayed ion extraction addressed the
Special Issue: Fundamental and Applied Reviews in Analytical
Chemistry
Published: January 17, 2012
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problem of kinetic energy spread among ions of the same
m/z.12 The advent of fast digitizers; matrix-assisted laser
desorption/ionization (MALDI), and MALDI imaging; orthogonal ion introduction; and kinetic energy focusing by use of a
reflectron brought TOF MS to its present level of popularity.
Orthogonal Acceleration (see ref 13). Ideally, a TOF
MS experiment should begin with all ions with the same initial
position and velocity. Orthogonal ion introduction, in which
ions are accelerated in a direction perpendicular to a collimated
ion beam, effectively achieves that condition and thus improves
mass resolving power. Another advantage of orthogonal
introduction is that ions can be accumulated in the acceleration
region while previously accumulated ions fly toward the detector,
thereby more efficiently enabling coupling of continuous ion
sources with TOF mass analysis. Further optimization of ion
guides and use of an ion funnel14 with automatic gain control
(AGC) improves the ion beam quality, for higher sensitivity
and mass accuracy.15
Reflectron/Multipass TOF. The resolving power for a
TOF mass analyzer is m/Δm50% = (T/2Δt), in which T is the
ion total flight time and Δt is the mass spectral peak width.
Increasing the flight time for improved resolving power is made
possible by the reflectron, introduced by Mamyrin in 1973.16
After an initial drift region, ions are subjected to a spatially
quadratic potential that acts as an ion mirror. When ions of a
given m/z but different kinetic energy fly through the reflectron
region, the faster ions penetrate farther into the reflectron (and
therefore travel a greater distance to reach the detector) than
slow ions, and ions of all speeds arrive at the detector at the
same time. The reflectron thus provides increased ion flight path,
without defocusing due to spread in initial velocity, thereby
increasing mass resolving power. Broadband mass resolving power
of 10 000 and rms mass error of 5−10 ppm may now be routinely
attained. With high field pusher and dual stage reflectrons,
commercial TOF mass analyzers can now reach mass resolving
power of 40 00017 (Figure 1, top). If the ion spatial focusing can
be maintained with minimal ion loss at each reflection, the ion
flight path may be extended by multiple reflections. Multipass
(Figure 1, middle)18 and spiral (Figure 1, bottom)19 TOF mass
analyzers now attain mass resolving power of 50 000 or higher.
Recently, an optimized multipass time-of-flight mass analyzer
has been combined with MALDI for imaging mass spectrometry. The multipass time-of-flight mass analyzer consists of four
electric sectors, with cylindrical side electrodes and Matsuda
configuration to generate a toroidal electric field, in which
focusing is maintained by quadrupole triplet lenses at the
entrance and exit of each toroidal segment. Mass resolving
power of 130 000 has been achieved for angiotensin II
[M + H]+ ions (m/z 1046.542) after 500 turns and 654.8 m
total flight path.20 In a typical multipass time-of-flight mass
analyzer, the power supply for ion injection/ejection is very
large and complicated in order to reduce instability of voltage
switching between ion injection and ejection events. A more
recent multipass TOF design adds two more sectors for ion
injection and ejection only, thereby minimizing the size of the
power supply.21
Although a cyclic multipass TOF mass analyzer offers
potentially high mass resolution, the observable mass range is
limited, because low-m/z ions eventually overtake higher-m/z
ions so that the effective m/z range is reduced by a factor of N
for N passes. An elliptical flight path composed of four toroidal
electric sectors works with a new segmentation method to
identify the number of laps transited by ions of a given m/z.22
Figure 1. High resolution time-of-flight mass analyzers. Top: Dual
stage reflectron. Reproduced with permission from Waters Corporation. Copyright 2009 Waters Corportation. Middle: Multipass
reflectron with linear segments. Reprinted with permission from
ref 223. Bottom: Multipass spiral configuration. Reproduced with
permission from JEOL USA. Copyright 2006−2011 JEOL Ltd.
The most recent multipass designs include doughnut-shaped
ion optics,23 a spiral path electric reflector24 and multiple angle
reflecting electrostatic ion mirrors25 (Figure 1, middle). The
latter two designs have achieved broadband mass resolving
power of 60 000.
Recent Advances in TOF Mass Analyzers. Detection. The
most commonly used TOF ion detector is the microchannel
plate (MCP) detector, which converts ions to secondary electrons,
with large active area and rapid response time. However,
secondary electron generation efficiency varies directly with
incident ion velocity, and ion velocity varies inversely with the
square root of accelerated ion mass, so that MCP detection
efficiency for high-mass ions is low. The mechanical nanomembrane detector can detect the time-varying field emission
of electrons from mechanical oscillation without mass discrimination and thus improve high-mass detection sensitivity.
For example, singly charged immunoglobulin G (150 kDa) has
been experimentally observed by TOF MS with nanomembrane
detection.26 A different nanomechanical resonator,27,28 whose
resonance frequency is perturbed by surface adsorption of ions,
was also recently reported as a sensitive mass sensor, but
further investigation for its practical use in TOF MS is needed.
When applied to TOF MS, cryogenic detectors measure lowenergy solid-state phonon excitation created by a particle
impact. The energy of the phonons is less than a few meV,
much smaller than the energy in the electronvolt range
needed to produce secondary electrons in a conventional
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in brain areas with ischemic injury.50 As for protein profiling, a
different lipid distribution between normal and cancer cells
could diagnose disease.51,52
In aerosol analysis, it is necessary to track changes in aerosol
size and chemistry with subsecond time resolution. A TOF
mass analyzer collects high resolution aerosol mass spectra at
rates exceeding 1 kHz for determination of both aerosol size
and mass.53 Alternatively, two-dimensional gas chromatography
(GCxGC) mass spectrometry requires fast scanning because
the final GC peak width is typically 20−200 ms,54 making TOF
the MS method of choice. GCxGC TOF MS applications include
identification of naphthentic acids in oil samples,55,56 high
throughput metabolic profiling,57,58 characterization of pathogen
bacteria,59 and analysis of organic nitrogen compounds in aerosol
samples.60 Moreover, fast transient temporal analysis of catalyst
kinetics targets TOF mass analysis for its sensitivity, detector
response, and time resolution.61
The TOF mass analyzer has also been applied to polymer analysis
by virtue of its high m/z range and MS/MS capability. Evaluation of
top-down TOF MS/MS for poly(α-peptoid)s synthesized by Nheterocyclic carbine (NHC)-mediated zwitterionic ring-opening
polymerization62 showed that electrospray ionization (ESI) enabled
detection of the intact molecular species, whereas MALDI resulted in
elimination of the NHC initiator in the presence of cationizing salts.
Coupled with MALDI, TOF MS can address the mechanism of
polymer backbone degradation via free radical chemistry63 and
quantify residual polyethylene glycol (PEG) in ethoxylated surfactants.64 Cation adducts generated more informative fragment
ions under CID,65 and TOF MS has characterized various polymers
with ammonium adducts generated by ESI.66 Miscellaneous
other applications include characterization of C4 explosives by
TOF secondary ion mass spectrometry (SIMS),67 qualitative and
quantitative analysis of herbal medicines (HMs) by LC/TOF
MS,68 and identification of different contaminants in the human
body by GC/TOF MS.69
ionization detector. The cryodetector is capable of detecting
high m/z, slow-moving ions.29 For example, a strong signal at
510 kDa from a disulfide-linked dimer has been experimentally
observed in a MALDI TOF mass spectrometer coupled with a
cryodetector.30
TOF/TOF. Two time-of-flight (TOF) mass analyzers in
succession enable MS2 experiments.31,32 Usually, the first TOF
mass analyzer selects the precursor ion for injection into a high
energy collision cell for collision induced dissociation (CID). The
second TOF mass analyzer then records the fragment ions. The
most common TOF/TOF configuration is a linear TOF mass
analyzer followed by a reflectron TOF mass analyzer.33,34 However,
low resolution in MS1 can render product ion identification
difficult.
Multipass TOF/TOF has been achieved with a MALDI ion
source, a multiturn TOF mass analyzer (TOF1), a collision cell,
and a quadratic-field ion mirror,35,36 providing resolving power
of 5000 for precursor ion selection and 1000 resolving power
for product ions throughout the mass range. The identification
of lyso-phosphatidylcholine (LPC) and phosphorylation37 has
been demonstrated. Recently, a spiral ion optical TOF mass
analyzer for MS1 was combined with an offset parabolic ion
reflectron TOF as MS2, providing high resolution MS1
precursor monoisotopic ions up to m/z 2500.38
Selected Applications. Although TOF mass analyzers
have lower mass resolution than FT mass analyzers (FTICR
and orbitrap), they have no upper m/z limit in principle and are
thus particularly useful for identifying singly charged ions of
high molecular weight (as from MALDI). Fast response/scan
rate is also advantageous for applications requiring short acquisition period, e.g., analysis by liquid or gas chromatography mass
spectrometry.
A method for screening doping agents in human urine
consists of solid-phase extraction followed by HPLC-TOFMS.
Coupled with orthogonal electrospray ionization, 124 substances, including stimulants, narcotics, agonists, diuretics, etc.,
are identified in less than 30 min.39 Further development of the
extraction method enabled identification of 40 more doping
compounds.40 The utility of the LC-TOF method was assessed
by parallel analysis of 30 authentic urine samples by use of rapid
emergency drug identification and led to identification of twice
as many drugs.41 Compared to prior methods, the author
concluded that UPLC-TOFMS offers an attractive alternative
toxicological screening technique. Because the mass accuracy
tolerance for broad toxicology screening has historically been
quite wide (20 ppm or more),42 TOF mass accuracy less than
5 ppm provided substantial improvement in the number and
confidence of identifications.43,44
Mass spectrometry imaging (MSI) provides rapid detection,
localization, and identification of organic components of
complex biological mixtures,45 to establish chemical correlations with biological function or morphology. MSI experiments
are typically performed with a TOF mass analyzer, due to its
good sensitivity and speed. Localization of peptides by MALDI
TOF imaging reveals the distribution of their respective
proteins.46 Comparison of protein profiles from normal and
tumor tissue can lead to biomarker candidates.47,48 The
profiling and imaging of proteins involved in proliferation,
differentiation, and apoptosis by MALDI TOF MS generates
unique and differential proteomic blueprints for implantation
and interimplantation sites.49 Lipid imaging in rat brain tissues
during focal cerebral ischemia reveals dynamic conversion from
phosphatidylcholine (PC) to lyso-phosphatidylcholine (LPC)
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FOURIER TRANSFORM MASS ANALYZERS
The FTICR mass analyzer, introduced in 1974,70 has the
highest mass resolving power71,72 and best mass measurement
accuracy71 among current mass analyzers. The orbitrap, another
Fourier transform mass analyzer, invented in 1999,73 has been
widely distributed since its commercial introduction in 2004.74
Common Features of Fourier Transform Mass
Analyzers. The ion cyclotron and orbitrap each produce a
spatially coherent packet of ions of a given m/z. Coherence in
FTICR is achieved by rf excitation at the ion cyclotron
frequency, whereas coherence in the orbitrap is achieved by
injecting ions of a given m/z into the mass analyzer in a time
short compared to the ion oscillation frequency. In both
devices, the periodic motion (rotation in ICR, oscillation in
orbitrap) is detected from the oscillating current induced in
opposed detection electrodes, as ions pass near each electrode.
The signal from ions of a given m/z is linearly proportional to
the number of those ions and to the radius75,76 or amplitude of
the ion motion. Linearity is especially important for FTICR,
because ions of different m/z may be selected/excited in any
desired combination by a time-domain excitation waveform
produced by inverse Fourier transformation of the desired
frequency-domain excitation profile (“stored waveform inverse
Fourier transform” (SWIFT) excitation).77−79 Both devices
inherently detect ions of a wide m/z range simultaneously. The
time-domain signal is then digitized, apodized, zero-filled80,81
(to improve digital resolution), and subjected to discrete Fourier
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transformation to yield mathematically “real” and “imaginary”
frequency-domain spectra, Re(ω) and Im(ω), which are typically
combined to yield a “magnitude” spectrum, M(ω) (see below).76
Spectral frequency is then converted to m/z by an appropriate
calibration equation (see below).
FTMS resolving power is ultimately limited by the acquisition
period, T, for the time-domain transient. However, the time-domain
transient duration is in turn limited by magnetic and electric field
imperfection, ion-neutral collisions, and ion−ion interactions.81−84
Apodization functions85 help to detect small peaks near large peaks
by reducing the magnitude of auxiliary maxima and by narrowing
the peak width near the peak base (at the cost of broadening the
peak width at half-maximum peak height).
Ion Accumulation and Detection. Both ICR and
orbitrap mass analyzers are pulsed detectors. Because ion introduction is often temporally continuous (e.g., ESI and APPI), ions
are typically accumulated externally during detection of ions
from the preceding accumulation period.86 In FTICR, ions are
externally accumulated in a multipole electric ion trap and
simultaneously ejected toward the ICR cell, whereas in the orbitrap,
ions are collected in a “C” trap,87 and injected simultaneously
toward the orbitrap. In ICR, ion spatial coherence is maintained
by the confining magnetic and electrostatic fields and by ion−
ion interactions,84 whereas in the orbitrap, ion axial coherence
is achieved by short pulsed injection from the C trap and radial
coherence is lost as ions spread out to form a rotating ring
(actually, an advantage, by reducing space charge repulsions
and enabling increased dynamic range), and the ring for ions of
a given m/z oscillates axially to produce an image current on
the detection electrodes. The cyclotron frequency in ICR signal
varies as (m/z)−1,75 whereas the orbitrap axial frequency (like
the ICR “trapping” oscillation) varies as (m/z)−1/2.87 As a result,
ICR mass resolving power varies as (m/z)−1 vs (m/z)−1/2 for
the orbitrap.
Advances in Fourier Transform Mass Analyzers. High
Field Strength. The simplest way to improve FTMS performance is to operate at higher magnetic field, B (ICR) or higher
electric field (orbitrap). ICR mass resolving power or scan rate
increases proportional to B, whereas mass accuracy, dynamic range,
and upper m/z limit increases as B2.88,89 The highest field FTICR
instrument is currently 15 T, and 21 T systems are under construction at the USA National High Magnetic Field Laboratory and
Pacific Northwest National Laboratory.
The orbitrap axial oscillation frequency can be expressed
as:90
ω=
e
·
(m / z )
2Ur
⎛
⎞
R
1
R m 2 ln⎜ 2 ⎟ − [R2 2 − R12]
⎝ R1 ⎠ 2
resolved an isotopic distribution at a resolving power in excess
of 600 000 at m/z 195.90
Electric Field Optimization. The orbitrap mass analyzer is
composed of a spindle-like central electrode and a barrel-like
outer electrode (Figure 2). Application of a dc voltage to the
Figure 2. Standard orbitrap (left) and compact high field orbitrap
(right) mass analyzers. Reproduced with permission of ThermoFisher
Scientific, ref 90. Copyright 2009 ThermoFisher Scientific.
two axial electrodes produces an electrostatic potential that
ideally is the sum of a quadrupole ion trap potential and a
logarithmic potential of a cylindrical capacitor. For ICR, a
strong homogeneous static magnetic field confines ion motion
transverse to the magnetic field, and an ideally three-dimensional
quadrupolar electrostatic potential confines ion motion parallel
to the magnetic field.
In practice, the potentials in both mass analyzers deviate
from ideal, because the electrodes are truncated, imperfect in
shape and alignment, and must have apertures to admit ions
(both) and electrons or photons (ICR). In ICR, an imperfect
(anharmonic) quadrupolar electrostatic potential produces an
axially dependent, nonlinear radial electric field (Er) that makes
the observed cyclotron frequencies depend on ion radius and
axial amplitude. Different approaches to the cell anharmonicity
problem have been investigated since the 1980s.91−99 One
approach is to insert compensation rings into an open cylindrical
cell100−104 (e.g., Figure 3, top). Another idea relies on ion
cyclotron motion to average the electric potential from curved
segmented electrodes105 (Figure 3, bottom). Both cell designs in
Figure 3 have achieved baseline unit mass resolution for proteins
up to 150 kDa.106 Moreover, a coaxial multielectrode cell
(O-trap),107 with separate compartments for ICR excitation
and detection, has been experimentally demonstrated. The
potential benefit from that design is enhancement of resolving
power equal to detected frequency multiple order that could
alternatively yield a shorter detection period for correspondingly higher throughput. (e.g., for LC/MS).
Compared to a standard orbitrap geometry, the outer electrode
dimensions of the compact high-field orbitrap analyzer are scaled
down by a factor of 1.5, whereas the central electrode dimensions
are scaled down by a factor of 1.2 (Figure 2). The entrance
aperture cross-section is reduced by more than a factor of 2; thus, to
avoid a corresponding loss in sensitivity, a new miniature lens system
focuses ions to a much smaller spot. The capacitance of the orbitrap
drops in proportion to size, which results in improved image current
detection sensitivity. New transistors in the preamplifier further
increase sensitivity. In spite of higher ion density, the relatively thicker
central electrode results in smaller space charge shifts than for the
standard orbitrap.
(1)
−19
in which e is the elementary charge (1.602 × 10 C), R2 is the
maximum radius of the outer barrel-like electrode, R1 is the
radius of the central spindle-like electrode, Ur is the voltage
applied to the central electrode, and Rm is the “characteristic”
radius at which dU(r,z)/drz=0 = 0. From eq 1, it is clear that
orbitrap resolving power may be increased by increasing the
central electrode voltage or decreasing the R2/R1 ratio. The
newest orbitrap exhibits increased Ur and optimized R2/R1 ratio
to provide ∼2-fold improvement in resolving power (for a
given data acquisition period) or similar reduction in data
acquisition period (for faster online LC sampling, for a given
mass resolving power). With careful balancing of construction
tolerances and experimental parameters, the new orbitrap
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A(ω) = cos[ϕ(ω)]Re(ω) − sin[ϕ(ω)]Im(ω)
(3a)
D(ω) = sin[ϕ(ω)]Re(ω) + cos[ϕ(ω)]Im(ω)
(3b)
An absorption-mode spectral peak is inherently narrower
than its corresponding magnitude-mode spectral peak (Figure 4,
Figure 3. Top: Seven segment compensated ICR cell. Reproduced with permission from ref 102. Copyright 2011 American
Chemical Society. Bottom: Dynamically harmonized ICR cell
(bottom). Adapted with permission from ref 105. Copyright 2010
John Wiley & Sons, Inc.
Software Development. Calibration. FTMS mass accuracy
is determined by signal-to-noise ratio and number of data
points per peak width 5 and by “calibration”, namely, the
conversion of a frequency-domain spectrum to an m/z
spectrum. For FTICR, calibration typically relies on a twoterm equation based on a perfectly homogeneous magnetic
field and a purely quadrupolar electrostatic field.108,109 Other
equations incorporating variation in ion abundance110 and spacecharge effects111,112 have also been evaluated. External calibration (performed for a different sample than for analyte) is
typically 2−3× less accurate than internal calibration (based on
multiple ions of known m/z values in the analyte sample).
Systematic error has been reduced by a factor of up to 3 (and
the number of assigned peaks increased by ∼25%) by separate
calibration for each of up to ∼30 individual mass spectral
segments.113,71 Addition of an ion abundance-dependent term
to the calibration equation can reduce systematic error by
another factor of ∼2−3.71,103 For a high vacuum gas oil sample
with ∼5200 peaks, FTICR rms mass error for an absorptionmode spectrum (see below) drops from 107 to 27 ppb by
essentially eliminating systematic error. For the orbitrap, m/z is
first-order proportional to (ω)−1/2, leading to a one term
calibration equation. As for ICR, orbitrap mass calibration may
be improved by considering the effect of space charge, leading
to a mass measurement error as low as ∼80 ppb over an m/z
range of 100−2000.114
Phase Correction. Fourier transformation of a time-domain
signal produces mathematically real and imaginary frequencydomain spectra, Re(ω) and Im(ω), which may be combined to
yield magnitude-mode (also known as absolute-value) and phase
spectra, M(ω) and φ(ω), related according to eqs 2a and 2b.76
M(ω) = [[Re(ω)]2 + [Im(ω)]2 ]1/2
(2a)
ϕ(ω) = arc tan[Im(ω)/Re(ω)]
(2b)
Figure 4. (a) Magnitude-mode and absorption-mode Lorentzian
spectra, corresponding to Fourier transformation of an infinite duration
time-domain signal, f(t) = A cos(ω0t) exp(−t/τ). (b) Magnitude (upper)
and absorption-mode (lower) electrospray ionization 9.4 T
FTICR mass spectra from the same bitumen time-domain data.
The absorption display clearly resolves a mass doublet (compositions differing by C3 vs SH4, 0.0034 Da) unresolved in magnitude
mode.
top) by a factor that depends on the presence and mechanism of
signal damping,81−84 for an improvement in mass resolving power
by a factor of up to 2. In FTICR, temporally dispersed excitation
and the delay between excitation and detection result in complex
variation of phase with frequency. For that reason, magnitude
mode has been the conventional display for FTICR mass spectra.
The advantage of absorption-mode display was recognized from
the outset.115 Efforts to achieve broadband-phase correction116,117
culminated in a phase correction algorithm that can automatically
account for first- and second-order-phase accumulation from
excitation parameters and iterates the zero-order term.118 An
experimental FTICR absorption-mode mass spectrum with 40%
higher resolving power (and thus an increased number of resolved
peaks) as well as higher mass accuracy relative to its corresponding
magnitude mode spectrum is shown in Figure 4, bottom. Another
approach for phase correction is to assume a quadratic relation
between phase and frequency and iteratively solve for zero-, first-,
and second-order coefficients.119
ICR phase “wrapping” (i.e., phase variation by more than 2π
across the frequency spectrum) for the orbitrap is less severe
due to the short ion injection period from the C trap but
If the “phase spectrum”, φ(ω), is known, absorption- and
dispersion-mode spectra, A(ω) and D(ω), may in turn be
obtained as linear combinations of Re(ω) and Im(ω).
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post-translational modification according to its characteristic additional mass relative to an unmodified amino acid residue. The topdown approach can in principle locate all post-translational modifications, even when several are present at the same time. High
resolution and high mass accuracy are essential to resolve isotopic
distributions from peptides of different charge state as well as to
assign isobaric peptide compositions (e.g., lysine vs glutamine,
differing in mass by 0.0364 Da).129 Examples of top-down posttranslational identifications include: rhesus monkey cardiac
troponin,130 integral membrane proteins,131 and human histones.132,133 Further, 99 proteins have been identified by top-down
tandem mass spectrometry in Methanosarcina acetivorans,134
and capillary liquid chromatography coupled with FTICR
identified with high confidence 102 endogenous peptides in the
suprachiasmatic nucleus. Robust two-dimensional liquid
chromatography combined with top down mass spectrometry
increases efficiency for improved quantification and characterization.135,136 Further automated data processing can increase
top-down throughput.137 In addition to conventional ESI, IRMALDESI has been coupled with an FTICR mass analyzer to
perform top-down analysis of equine myoglobin (17 kDa).138
Discovery and characterization of endogenous peptide139 and
candidate pharmacodynamic markers140 has been demonstrated.
Recently, FTICR MS achieved unit mass baseline resolution for
an intact 148 kDa therapeutic monoclonal antibody, the highest
mass protein isotopically resolved to date.106
In the “bottom-up” approach, proteins are typically separated
by HPLC and/or electrophoresis, proteolytically digested into
peptides, and then subjected to online LC/MS, and the most
abundant peptides are subjected to MS/MS.141,142 Any of
several algorithms143,144 then compare precursor ion mass and
MS/MS peak spacing to an appropriate database for protein
identification.145−147 Identification reliability may be improved
by incorporating LC elution time.148 Alternatively, “shotgun”
proteomics also relies on online LC/MS and MS/MS but
without prior gel separation of the proteins.149 Shotgun
proteomics has been applied to microorganisms,150 histones
(especially post-translational modifications),151,152 and discovery of biosynthetic pathways,153 etc. For proteins too large for
efficient gas-phase fragmentation, “middle-down” proteomics
denotes LC/MS and MS/MS for large proteolyic fragments of
the original protein and has identified 7454 peptides from 2 to
20 kDa after 23 LC MS/MS injections of Lys-C digests of
HeLa-S3 nuclear proteins.154 Post-translationally modified
histone H3 variants have also been characterized by that
approach.155
Quantitative proteomics typically requires isotopic labeling,
either before (SILAC)156 or after peptide isolation.142 Quantification of human monkeypox virus and vaccinia virus confirmed the
level required for pathogenesis with the accurate mass and time tag
(AMT) method after peptide isolation.157 With stable isotope
labeling of amino acids in cell culture (SILAC), it is possible to
quantitatively evaluate phosphorylation changes in stable cell
lines.158 Quantitative proteomics depends on fragmentation
energy.159,160 When isotopic labeling is not applicable, label-free
methods can provide a measure of quantitation.161
Metabolomics. High throughput screening of chemical
toxicity in Daphnia magna has been reported.162 Metabolic
profiling facilitates biochemical phenotyping of normal and
neoplastic colon tissue at high significance levels163 and
annotates the ions originating from identical metabolites by
fragmentation pattern and database searching analysis.164 Coupled
with different chromatography platforms,165−167 higher dynamic
complicated by the change in central electrode voltage (and
therefore resonant frequency) during ion injection. A “pseudo”phase correction for the orbitrap combines absorption-mode
display for the top part of the peak with an increasing magnitudemode component for the bottom part. Although the peak width
at half peak height is thus narrower,120 improvement vanishes
for low abundance peaks that are near the base of a high
abundance peak, and the mass measurement accuracy does
not improve.
Improved Data Station. Continued improvement in FTz
mass analyzers requires optimized control of multiple
experimental events, precisely timed data acquisition, and efficient
data analysis to accommodate new hardware modifications and
ion optics configurations. A recent Predator data station121
exploits improved PC bus speed to transfer data to and from
the control PC in real time. Conditional data acquisition can
evaluate data in real time and apply user-defined conditions to
average and store data. This capability is primarily used to eliminate
low quality data so as to improve the data S/N ratio and
minimize the computer memory required to store data. Tool
command language (Tcl) scripting has been applied for 17
voltages and 18 triggers and provides a fast and easy way to
control the Predator data station and associated peripherals,
e.g., LC, autosampler, laser source, and electron emitter.121 Another
improved data control system combines PXI hardware with a
workflow-based acquisition and control software to allow unique
types of data-dependent experiments.122 Dynamic switching
between different dissociation technologies may be achieved due
to fast and precise hardware response.123
Selected Applications. Tandem Mass Spectrometry.
The main difference between ICR and orbitrap for MS/MS is
that precursor ion dissociation can be performed in a Penning
trap but not in an orbitrap. In principle, fragment ions can be
brought to coherence in an orbitrap for subsequent excitation
and detection,124 but MS/MS is typically performed externally
(CID or ETD) for orbitrap detection.125,126 MS/MS can be
performed in an ICR cell by collision-induced dissociation
(CID), infrared multiphoton dissociation (IRMPD), and
electron capture dissociation (ECD). However, high resolution
requires low pressure in the ICR cell, so introduction of collision
gas into the cell requires subsequent pumpdown before
excitation/detection; ergo, CID FTICR experiments are now
typically conducted with an external electric multipole ion trap.
Because ECD (or ETD) can fragment a peptide but not dissociate
the noncovalently bound fragments, infrared irradiation is
commonly used to release the product ion. CID and IRMPD
heat an ion and typically break the weakest bond to produce
predominantly b- and z-type peptide fragment ions. However,
post-translational linkages (e.g., phosphorylation, glycosylation)
are often lost before peptide backbone cleavage, thereby eliminating knowledge of their location. In contrast, ECD (or ETD)
produces mainly c- and z-type backbone cleavage fragment ions by
breaking the backbone N−Cα bond without loss of phosphate or
glycan. Thus, ECD or ETD is much preferred for locating posttranslational modifications.127,128
Proteomics. Proteomics encompasses identification and
structural characterization of proteins and their complexes,
determination of post-translational modifications, and quantitation
of protein expression under different treatments. In “top-down”
proteomics, a single gas-phase protein is isolated and subjected to
fragmentation (e.g., CID, IRMPD, ECD, ETD, etc.) to generate
fragment masses for comparison to an appropriate database for
protein identification, as well as identity and location of each
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ligands,184 enable characterization of polypurine tract-containing
RNA−DNA hybrids and show that the common structural
features of lentiviral and retrotransposon polypurine tracts
facilitate the interaction with their cognate reverse transcriptase.
Structural elucidation of the HIV-1 virus has also been achieved
by the combination of footprinting and cross-linking techniques
with high resolution MS detection.184,185
Synthetic Polymer Analysis. The most obvious advantage of
mass spectrometry for synthetic polymer analysis is the generation
of the full molecular weight distribution, rather than simply
number-average or weight-average molecular weight.186,187 High
resolution MS can also reveal pathways of polymer synthesis, as
for a sterically hindered alkoxyamine initiator for the nitroxidemediated copolymerization (NMP) of methyl methacrylate
(MMA);188 the styrene monomer was added as polymerization
terminator, and the progress was monitored from the product
oligomer distributions. Synthetic polymer structure has been
probed by various fragmentation techniques, including electron
capture dissociation (ECD), collision induced dissociation (CID),
and electron detachment dissociation (EDD),189−194 e.g.,
polyamidoamine dendrimer characterization by ECD and EDD.
Petroleomics. From sufficiently complete characterization
of the organic composition of petroleum and its products, it is
becoming possible to correlate (and ultimately predict) their
properties and behavior.195,196 FTICR MS is the preferred
identification technique for petroleum analysis because of the
need to resolve mass splits down to 3.4 mDa (32S1H4 vs 12C3) or
∼0.5 mDa (for nickel-containing porphyrins) (Figure 6). Removal
range and identification of more metabolites can be achieved.
Autocorrelation of retention and ionization leads to more
exhaustive metabolic fingerprints.168
Lipidomics. Characterization of nonpolar lipids and selected
steroids by high resolution mass analysis has emerged as a
powerful tool for lipidomics.169,170 Online LC separation can
quickly narrow down the possible phospholipid and glycosphingolipid compositions and facilitate their identification.171,172 Unequivocal lipid elemental composition from
isotopic fine structure has been used to validate the
identification of sulfur-containing lipids in algae extracts
(Figure 5).173 Direct infusion high resolution mass analysis with
Figure 5. Positive electrospray ionization 14.5 T FTICR mass
spectrum for Nannochloropsis oculata species lipid extract. Inset: Two
peaks differing by 2.37 mDa are resolved and assigned. (Figure kindly
provided by Huan He.)
computer-assisted assignment is able to profile the
13
C-isotopologues of glycerophospholipids (GPL) directly in
crude cell extracts.174 High resolution MS/MS enabled
identification of triacylglycerols archeological extracts175 and
neutral lipids.176 Matrix-assisted laser desorption ionization
combined with high-resolution MS enables confident identification and spatial localization of lipids in tissue sections.177,178
RNA/DNA Analysis. Most high resolution MS analyses of
oligonucleotides have focused on synthetic DNA, RNA,
aptamers, etc. Double-stranded small interfering RNA (siRNA)
presents numerous fragment ions and multiple chemical
modifications. The different metabolite patterns for synthetic
siRNA in different biomatrixes (rat and human serum) provide
insight into the stability and pharmacokinetic properties of
therapeutic siRNA compounds.179 A method for sequencing
single and double stranded RNA oligonucleotides by acid
hydrolysis has been presented. From the mass differences
between adjacent members of a mass ladder, the complete
sequences of different siRNA 21-mer single and double strands
could be verified. This simple and fast method can be applied to
controlling sequences of synthetic oligomers, as well as for de
novo sequencing.180 A high resolution mass spectrometry-based
analytical platform for RNA, employing direct nanoflow
reversed-phase liquid chromatography with a spray tip column
predicted the nucleotide composition of a 21-nucleotide small
interfering RNA, detected yeast tRNA post-transcriptional
modifications, and analyzed the nucleolytic fragments of RNA
at a subfemtomole level.181 Various other approaches, e.g.,
combing chemical modification of RNA with mass spectrometry,182 based on neomycin B+183 or classical nucleic acid
Figure 6. Positive ion atmospheric pressure photoionization (APPI)
9.4 T Fourier transform ion cyclotron resonance (FTICR) mass
spectrum of a petroleum crude oil. Upper inset: Mass scale expansion
revealing 90 singly charged ions within a mass range of 0.32 Da. Lower
inset: Baseline resolution of ions differing in mass by 1.1 mDa, made
possible by ultrahigh mass resolving power of 1 000 000 at m/z 428.
(Data kindly provided by Amy McKenna.)
of contaminants in asphaltenes during the crude oil processing is
necessary to avoid catalyst fouling and hence lower liquid yield.
Also, asphaltenes can precipitate during production and refining.
Thus, asphaltenes are one of the most discussed topics in
petroleomics.198−202 Ion mobility mass spectrometry and FTICR
MS have been combined to confirm the presence of asphaltene
nanoaggregates in toluene at concentrations (10−4 mass fraction)
below those in crude oils.197 Subsequently, in situ analysis of a
3000 ft vertical column of crude oil by downhole fluid analysis
indicated that the asphaltenes in a black crude oil exhibit
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gravitational sedimentation according to the Boltzmann distribution and that the asphaltene colloidal size is ∼2 nm.203 The
detailed characterization of a Middle Eastern heavy crude oil
distillation series fully validated the Boduszynski model, namely,
that petroleum is a continuum with regard to composition,
molecular weight, aromaticity, and heteroatom content and that
boiling point can be predicted from aromaticity and heteroatom
content.204,205 Naphthenic acids (i.e., species containing nonaromatic hydrocarbon rings) can form harmful deposits and may
be identified in crude oil before the deposits form206−208 as well as
in oil sands processed water.209−211 Ultrahigh mass resolution also
enables identification of biomarkers, such as nickel and vanadyl
petroporphyrins.212,213
Environmental Analysis. Applications of high resolution
MS technology in the fields of food safety214 and environmental
analysis have recently been reviewed.215 High resolution helps to
trace contaminants, as well as to identify analogs for which
standards are not available. High-resolution full scan MS analysis
with simultaneous targeted CID MS/MS has been applied to
analysis of polyether toxin azaspiracid food contaminants in
shellfish.214 High resolution is also useful in the high-throughput
screening of micropollutants in wastewater treatment. Both
targeted and nontargeted screening have identified a variety of
unreported and previously reported pesticide transformation
products.216 Characteristic polar oil sand components (naphthenic
acids and other related acid fraction components) spiked into plant
tissue prior to extraction can be differentiated from coextracted
endogenous plant components by high resolution MS.210 LC/high
resolution MS showed that the industrial chemical, perfluorooctanoic acid, is microbiologically inert and hence environmentally
persistent.217 The high production volume chemicals, benzotriazoles and benzothiazoles, have been extracted from environmental
water by solid-phase extraction and identified by LC/high
resolution MS.218 Induced metabolite changes in myriophyllum
spicatum, an aquatic vascular plant, have been monitored by high
resolution MS.219 The method has also provided molecular
characterization as the level of elemental composition, for dissolved
organic matter (DOM), e.g., from pore water,220 secondary-treated
wastewater,221 and the Greenland ice sheet,222 because it is capable
of resolving complex molecular mixtures and providing information
about the exact elemental composition.
development, and applications of analytical Fourier transform ion
cyclotron resonance mass spectrometry.
Feng Xian is a PhD candidate in the Ion Cyclotron Resonance
program at the National High Magnetic Field Laboratory at Florida
State University in Tallahassee, Florida. He received his Bachelor of
Science in Chemical Engineering from the Xi’an Jiaotong University in
1996, and he anticipates his Ph.D. in Analytical Chemistry from Florida
State University in 2012. His research focuses on Fourier Transform
Ion Cyclotron Resonance (FTICR) mass spectrometry instrumentation development.
■
ACKNOWLEDGMENTS
■
REFERENCES
The authors are not aware of any biases that might be perceived
as affecting the objectivity of this Review. We thank Amy
McKenna and Huan He for providing the data for Figures 5
and 6, and Alexander Makarov for providing images for Figure 2.
This work was supported by NSF Division of Materials
Research through DMR-0654118 and the State of Florida.
(1) Marshall, A. G.; Hendrickson, C. L. Ann. Rev. Anal. Chem. 2008,
1, 579−599.
(2) Giancaspro, C.; Comisarow, M. B. Appl. Spectrosc. 1983, 37, 153−
166.
(3) Keefe, C. D.; Comisarow, M. B. Appl. Spectrosc. 1989, 43, 605−
607.
(4) Verdun, F. R.; Giancaspro, C.; Marshall, A. G. Appl. Spectrosc.
1988, 42, 715−721.
(5) Chen, L.; Cottrell, C. E.; Marshall, A. G. Chemom. Intell. Lab. Syst.
1986, 1, 51−58.
(6) Liang, Z.; Marshall, A. G. Appl. Spectrosc. 1990, 44, 766−775.
(7) Kim, S.; Rodgers, R. P.; Marshall, A. G. Int. J. Mass Spectrom.
2006, 251, 260−265.
(8) He, F.; Emmett, M. R.; Hakansson, K.; Hendrickson, C. L.;
Marshall, A. G. J. Proteome Res. 2004, 3, 61−67.
(9) Mao, Y.; Tipton, J. D.; Blakney, G. T.; Hendrickson, C. L.;
Marshall, A. G. Anal. Chem. 2011, 83, 8024−8028.
(10) Mirsaleh-Kohan, N.; Robertson, W. D.; Compton, R. N. Mass
Spectrom. Rev. 2008, 27, 237−285.
(11) Cameron, A. E.; Eggers, D. F. Rev. Sci. Instrum. 1948, 19, 605−
607.
(12) Wiley, W. C.; McLaren, I. H. Rev. Sci. Instrum. 1955, 26, 1150−
1157.
(13) Verentchikov, A. N.; Ens, W.; Standing, K. G. Anal. Chem. 1994,
66, 126−133.
(14) Kelly, R. T.; Tolmachev, A. V.; Page, J. S.; Tang, K.; Smith, R. D.
Mass Spectrom. Rev. 2010, 29, 294−312.
(15) Ibrahim, Y. M.; Belov, M. E.; Liyu, A. V.; Smith, R. D. Anal.
Chem. 2008, 80, 5367−5376.
(16) Mamyrin, B. A. Int. J. Mass Spectrom. 2000, 206, 251−266.
(17) Pringle, S. D.; Giles, K.; Wildgoose, J. L.; Williams, J. P.; Slade,
S. E.; Thalassinos, K.; Bateman, R. H.; Bowers, M. T.; Scrivens, J. H.
Int. J. Mass Spectrom. 2007, 261, 1−12.
(18) Toyoda, M.; Okumura, D.; Ishihara, M.; Katakuse, I. J. Mass
Spectrom. 2003, 38, 1125−1142.
(19) Satoh, T.; Sato, T.; Tamura, J. J. Am. Soc. Mass Spectrom. 2007,
18, 1318−1323.
(20) Hazama, H.; Aoki, J.; Nagao, H.; Suzuki, R.; Tashima, T.; Fujii,
K.-i.; Masuda, K.; Awazu, K.; Toyoda, M.; Naito, Y. Appl. Surf. Sci.
2008, 255, 1257−1263.
(21) Shimma, S.; Nagao, H.; Aoki, J.; Takahashi, K.; Miki, S.;
Toyoda, M. Anal. Chem. 2010, 82, 8456−8463.
(22) Nishiguchi, M.; Ueno, Y.; Toyoda, M.; Setou, M. J. Mass
Spectrom. 2008, 44, 594−604.
■
AUTHOR INFORMATION
Corresponding Author
*E-mail: marshall@magnet.fsu.edu (A.G.M.); hendrick@
magnet.fsu.edu (C.L.H.).
Biographies
Alan G. Marshall completed his B.A. degree with Honors in
Chemistry at Northwestern University in 1965 and his Ph.D. in
Physical Chemistry from Stanford University in 1970. He is Robert O.
Lawton Professor of Chemistry and Biochemistry at Florida State
University and Director of the Ion Cyclotron Resonance (ICR)
Program, an NSF national user facility for mass spectrometry. His
current reseach spans FTICR instrumentation development, fossil
fuels and environmental analysis, and mapping the primary and higherorder structures of biological macromolecules and their complexes.
Christopher L. Hendrickson, Associate Director of the Ion Cyclotron
Resonance Program at the National High Magnetic Field Laboratory
and Courtesy Professor of Chemistry at Florida State University,
received his B.A. degree in chemistry from the University of Northern
Iowa and his Ph.D. in analytical chemistry from the University of Texas
at Austin. His research interests are in instrumentation, technique
715
dx.doi.org/10.1021/ac203191t | Anal. Chem. 2012, 84, 708−719
Analytical Chemistry
Review
(23) Shchepunov, V.; Berdnikov, A.; Lzumi, H.; Giles, R.; Gall, N.
Proceedings of the 58th ASMS Conference on Mass Spectrometry & Allied
Topics, Salt Lake City, UT, May 23−27, 2010.
(24) Ioanoviciu, D. Int. J. Mass Spectrom. 2010, 290, 145−147.
(25) Verentchikov, A. N.; Yavor, M. I. Quasi-Planar Multi-Reflecting
Time-of-Flight Mass Spectrometer. United States Patent, US 2011/
01086729 A1, 2011
(26) Park, J.; Qin, H.; Scalf, M.; Hilger, R. T.; Westphall, M. S.;
Smith, L. M.; Blick, R. H. Nano Lett. 2011, 11, 3681−3684.
(27) Chiu, H.-Y.; Hung, P.; Postma, H. W. C.; Bockrath, M. Nano
Lett. 2008, 8, 4342−4346.
(28) Lassagne, B.; Garcia-Sanchez, D.; Aguasca, A.; Bachtold, A.
Nano Lett. 2008, 8, 3735−3738.
(29) Frank, M.; Labov, S. E.; Westmacott, G.; Benner, W. H. Mass
Spectrom. Rev. 1999, 18, 155−186.
(30) Wenzel, R. J.; Matter, U.; Schultheis, L.; Zenobi, R. Anal. Chem.
2005, 77, 4329−4337.
(31) Cotter, R. J.; Gardner, B. D.; Iltchenko, S.; English, R. D. Anal.
Chem. 2004, 76, 1976−1981.
(32) Iltchenko, S.; Cotter, R. J. Int. J. Mass Spectrom. 2007, 265, 372−
381.
(33) Pittenauer, E.; Allmaier, G. J. Am. Soc. Mass Spectrom. 2009, 20,
1037−1047.
(34) Pittenauer, E.; Allmaier, G. Comb. Chem. High Throughput
Screening 2009, 12, 137−155.
(35) Toyoda, M. Eur. J. Mass Spectrom. 2010, 16, 397−406.
(36) Toyoda, M.; Giannakopulos, A.; Colburn, A.; Derrick, P. Rev.
Sci. Instrum. 2007, 78, 074101−074109.
(37) Shimma, S.; Nagao, H.; Giannakopulos, A.; Hayakawa, S.;
Awazu, K.; Toyoda, M. J. Mass Spectrom. 2008, 43, 535−537.
(38) Satoh, T.; Sato, T.; Kubo, A.; Tamura, J. J. Am. Soc. Mass
Spectrom. 2011, 22, 797−803.
(39) Kolmonen, M.; Leinonen, A.; Pelander, A.; Ojanpera, I. Anal.
Chim. Acta 2007, 585, 94−102.
(40) Kolmonen, M.; Leinonen, A.; Pelander, A.; Ojanpera, I. Drug
Test. Anal. 2009, 1, 250−266.
(41) Lee, H. K.; Ho, C. S.; Iu, Y. P. H; Lai, P. S. J.; Shek, C. C.; Lo,
Y.-C.; Klinke, H. B.; Wood, M. Anal. Chim. Acta 2009, 649, 80−90.
(42) Williamson, L. N.; Zhang, G. D.; Terry, A. V.; Bartlett, M. G.
J. Liq. Chromatogr. Relat. Technol. 2008, 31, 2737−2751.
(43) Badoud, F.; Grate, E.; Perrenoud, L.; Avois, L.; Saugy, M.;
Rudaz, S.; Venthey, J.-L. J. Chromatogr., A 2009, 1216, 4423−4433.
(44) van der Heeft, E.; Bolck, Y. J. C.; Beurner, B.; Nijrolder, A. W. J. M.;
Stolker, A. A. M.; Nielen, M. W. F. J. Am. Soc. Mass Spectrom. 2009, 20,
451−463.
(45) Chughtai, K.; Heeren, R. M. A. Chem. Rev. 2010, 110, 3237−
3277.
(46) Tucker, K. R.; Serebryannyy, L. A.; Zimmerman, T. A.; Rubakhin,
S. S.; Sweedler, J. V. Chem. Sci. 2011, 2, 785−795.
(47) Kang, S.; Shim, H. S.; Lee, J. S.; Kim, D. S.; Kim, H. Y.; Hong,
S. H.; Kim, P. S.; Yoon, J. H.; Cho, N. H. J. Proteome Res. 2010, 9,
1157−1164.
(48) Sanders, M. E.; Dias, E. C.; Xu, B. J.; Mobley, J. A.; Billheimer,
D.; Roder, H.; Grigorieva, J.; Dowsett, M.; Arteaga, C. L.; Caprioli, R. M.
J. Proteome Res. 2008, 7, 1500−1506.
(49) Burnum, K. E.; Tranguch, S.; Mi, D.; Daikoku, T.; Dey, S. K.;
Caprioli, R. M. Endocrinology 2008, 147, 3274−3278.
(50) Koizumi, S.; Yamamoto, S.; Hayasaka, T.; Konishi, Y.;
Yamaguchi-Okada, M.; Goto-Inoue, N.; Sugiura, Y.; Setou, M.;
Namba, H. Neuroscience 2010, 168, 219−225.
(51) Dill, A. L.; Ifa, D. R.; Manicke, N. E.; Costa, A. B.; Ramos-Vara,
J. A.; Knapp, D. W.; Cooks, R. G. Anal. Chem. 2009, 81, 8758−8764.
(52) Girod, M.; Shi, Y.; Cheng, J.-X.; Cooks, R. G. J. Am. Soc. Mass
Spectrom. 2010, 21, 1177−1189.
(53) Kimmel, J. R.; Farmer, D. K.; Cubison, M. J.; Sueper, D.;
Tanner, C.; Nemitz, E.; Worsnop, D. R.; Gonin, M.; Jimenez, J. L. Int.
J. Mass Spectrom. 2011, 303, 15−26.
(54) Shellie, R.; Marriott, P. J. Flavour and Fragrance J. 2003, 18,
179−191.
(55) Rowland, S. J.; Scarlett, A. G.; Jones, D.; West, C. E.; Frank, R. A.
Environ. Sci. Technol. 2011, 45, 3154−3159.
(56) Rowland, S. J.; West, C. E.; Scarlett, A. G.; Jones, D.; Frank, R. A.
Rapid Commun. Mass Spectrom. 2011, 25, 1198−1204.
(57) Li, X.; Xu, Z.; Lu, X.; Ying, B.; Kong, H.; Yu, Y.; Xu, G. Anal.
Chim. Acta 2009, 633, 257−262.
(58) Wojtowicz, P.; Zrostlikova, J.; Kovalczuk, T.; Schurek, J.; Adam, T.
J. Chromatogr., A 2010, 1217, 8054−8061.
(59) Gardner, J. Y.; Brillhart, D. E.; Benjamin, M. M.; Dixon, L. G.;
Mitchell, L. M.; Dimandja, J.-M. D. J. Sep. Sci. 2011, 34, 176−185.
(60) Ozel, M. Z.; Ward, M. W.; Hamilton, J. F.; Lewis, A. C.;
Raventos-Duran, T.; Harrison, R. M. Aerosol Sci. Technol. 2009, 44,
109−116.
(61) Goguet, A.; Hardacre, C.; Maguire, N.; Morgan, K.; Shekhtman,
S. O.; Thompson, S. P. Analyst 2011, 136, 155−163.
(62) Li, X.; Casiano-Maldonado, M.; Zhang, D.; Wesdemiotis, C.
Macromolecules 2011, 44, 4555−4564.
(63) Polce, M. J.; Ocampo, M.; Quirk, R. P.; Wesdemiotis, C. Anal.
Chem. 2008, 80, 347−354.
(64) Szyszke, R.; Hanton, S. D.; Henning, D.; Owens, K. G. J. Am.
Soc. Mass Spectrom. 2011, 22, 633−640.
(65) Nasioudis, A.; van Velde, J. W.; Heeren, R. M. A.; van den Brink,
O. F. Int. J. Mass Spectrom. 2011, 303, 63−68.
(66) Fouquet, T.; Humbel, S.; Charles, L. J. Am. Soc. Mass Spectrom.
2011, 22, 649−658.
(67) Mahoney, C. M.; Fahey, A. J.; Steffens, K. L.; Benner, B. A.;
Lareau, R. T. Anal. Chem. 2010, 82, 7237−7248.
(68) Zhou, J.-L.; Qi, L.-W.; Li, P. J. Chromatogr., A 2009, 1216,
7582−7594.
(69) Hernandez, F.; Portoles, T.; Pitarch, E.; Lopez, F. J. J. Mass
Spectrom. 2008, 44, 1−11.
(70) Comisarow, M. B.; Marshall, A. G. Chem. Phys. Lett. 1974, 25,
282−283.
(71) Savory, J. J.; Kaiser, N. K.; McKenna, A. M.; Xian, F.; Blakney,
G. T.; Rodgers, R. P.; Hendrickson, C. L.; Marshall, A. G. Anal. Chem.
2011, 83, 1732−1736.
(72) Shi, S. D.-H.; Hendrickson, C. L.; Marshall, A. G. Proc. Natl.
Acad. Sci. U.S.A. 1998, 95, 11532−11537.
(73) Makarov, A. Anal. Chem. 2000, 72, 1156−1162.
(74) Hu, Q.; Noll, R. J.; Li, H.; Makarov, A.; Hardman, M.; Cooks, R. G.
J. Mass Spectrom. 2005, 40, 430−443.
(75) Marshall, A. G.; Hendrickson, C. L.; Jackson, G. S. Mass Spectrom.
Rev. 1998, 17, 1−35.
(76) Marshall, A. G.; Verdun, F. R.Fourier Transforms in NMR, Optical,
and Mass Spectrometry: A User’s Handbook; Elsevier: Amsterdam, 1990;
pp 460.
(77) Chen, L.; Wang, T.-C. L.; Ricca, T. L.; Marshall, A. G. Anal.
Chem. 1987, 59, 449−454.
(78) Guan, S.; Marshall, A. G. Int. J. Mass Spectrom. Ion Processes
1996, 157/158, 5−37.
(79) Marshall, A. G.; Wang, T.-C. L.; Ricca, T. L. J. Am. Chem. Soc.
1985, 107, 7893−7897.
(80) Bartholdi, E.; Ernst, R. R. J. Magn. Reson. 1969, 1973 (11), 9−19.
(81) Comisarow, M. B.; Marshall, A. G. J. Chem. Phys. 1976, 64,
110−119.
(82) Guan, S.; Li, G.-Z.; Marshall, A. G. Int. J. Mass Spectrom. Ion
Processes 1997, 167/168, 185−194.
(83) Mitchell, D. W. J. Am. Soc. Mass Spectrom. 1999, 10, 136−152.
(84) Nikolaev, E. N.; Heeren, R. M. A.; Popov, A. M.; Pozdneev,
A. V.; Chingin, K. S. Rapid Commun. Mass Spectrom. 2007, 21, 3527−
3546.
(85) Aarstol, M.; Comisarow, M. B. Int. J. Mass Spectrom. Ion Processes
1987, 76, 287−297.
(86) Senko, M. W.; Hendrickson, C. L.; Emmett, M. R.; Shi, S. D.-H.;
Marshall, A. G. J. Am. Soc. Mass Spectrom. 1997, 8, 970−976.
(87) Perry, R. H.; Cooks, R. G.; Noll, R. J. Mass Spectrom. Rev. 2008,
27, 661−699.
(88) Marshall, A. G.; Guan, S. Rapid Commun. Mass Spectrom. 1996,
10, 1819−1823.
716
dx.doi.org/10.1021/ac203191t | Anal. Chem. 2012, 84, 708−719
Analytical Chemistry
Review
(89) Schaub, T. M.; Hendrickson, C. L.; Horning, S.; Quinn, J. P.;
Senko, M. W.; Marshall, A. G. Anal. Chem. 2008, 80, 3985−3990.
(90) Makarov, A.; Denisov, E.; Lange, O. J. Am. Soc. Mass Spectrom.
2009, 20, 1391−1396.
(91) Bruce, J. E.; Anderson, G. A.; Lin, C. Y.; Gorshkov, M.;
Rockwood, A. L.; Smith, R. D. J. Mass Spectrom. 2000, 35, 85−94.
(92) Gabrielse, G.; Haarsma, L.; Rolston, S. L. Int. J. Mass Spectrom.
1989, 88, 319−332.
(93) Gabrielse, G.; MacKintosh, F. Int. J. Mass Spectrom. Ion Processes
1984, 57, 1−17.
(94) Gooden, J. K.; Rempel, D. L.; Gross, M. L. J. Am. Soc. Mass
Spectrom. 2004, 15, 1109−1115.
(95) Guan, S.; Marshall, A. G. Int. J. Mass Spectrom. Ion Processes
1995, 146, 261−296.
(96) Jackson, G. S.; White, F. M.; Guan, S.; Marshall, A. G. J. Am. Soc.
Mass Spectrom. 1999, 10, 759−769.
(97) Naito, Y.; Fujiwara, M.; Inoue, M. Int. J. Mass Spectrom. Ion
Processes 1992, 120, 179−192.
(98) Vartanian, V. H.; Hadjarab, F.; Laude, D. A. Int. J. Mass
Spectrom. 1995, 151, 175−187.
(99) Weisbrod, C. R.; Kaiser, N. K.; Skulason, G. E.; Bruce, J. E. Anal.
Chem. 2008, 80, 6545−6553.
(100) Brustkern, A. M.; Rempel, D. L.; Gross, M. L. J. Am. Soc. Mass
Spectrom. 2008, 19, 1281−1285.
(101) Brustkern, A. M.; Rempel, D. L.; Gross, M. L. J. Am. Soc. Mass
Spectrom. 2010, 21, 451−454.
(102) Kaiser, N. K.; Savory, J. J.; McKenna, A. M.; Quinn, J. P.;
Hendrickson, C. L.; Marshall, A. G. Anal. Chem. 2011, 83, 6907−6910.
(103) Tolmachev, A. V.; Robinson, E. W.; Smith, R. D.; Pasa-Tolic, L.
J. Am. Soc. Mass Spectrom. 2011, 22, 1334−1342.
(104) Tolmachev, A. V.; Robinson, E. W.; Wu, S.; Kang, H.;
Lourette, N. M.; Pasa-Tolic, L.; Smith, R. D. J. Am. Soc. Mass Spectrom.
2008, 19, 586−597.
(105) Boldin, I. A.; Nikolaev, E. N. Rapid Commun. Mass Spectrom.
2010, 25, 122−126.
(106) Valeja, S. G.; Kaiser, N. K.; Xian, F.; Hendrickson, C. L.;
Rouse, J. C.; Marshall, A. G. Anal. Chem. 2011, 83, 8391−8395.
(107) Misharin, A. S.; Zubarev, R. A.; Doroshenko, V. M. Rapid
Commun. Mass Spectrom. 2010, 24, 1931−1940.
(108) Ledford, E. B.; Rempel, D. L.; Gross, M. L. Anal. Chem. 1984,
56, 2744−2748.
(109) Shi, S. D.-H.; Drader, J. J.; Freitas, M. A.; Hendrickson, C. L.;
Marshall, A. G. Int. J. Mass Spectrom. 1999, 195/196, 591−598.
(110) Jefferies, J. B.; Barlow, S. E.; Dunn, G. H. Int. J. Mass Spectrom.
Ion Processes 1983, 34, 169−187.
(111) Easterling, M. L.; Mize, T. H.; Amster, I. J. Anal. Chem. 1999,
71, 624−632.
(112) Muddiman, D. C.; Oberg, A. L. Anal. Chem. 2005, 77, 2406−
2414.
(113) Rodgers, R. P.; White, F. M.; Hendrickson, C. L.; Marshall,
A. G.; Andersen, K. V. Anal. Chem. 1998, 70, 4734−4750.
(114) Gorshkov, M.; Good, D. M.; Lyutvinshiy, Y.; Yang, H.;
Zubarev, R. A. J. Am. Soc. Mass Spectrom. 2010, 21, 1846−1851.
(115) Comisarow, M. B.; Marshall, A. G. Can. J. Chem. 1974, 52,
1997−1999.
(116) Beu, S. C.; Blakney, G. T.; Quinn, J. P.; Hendrickson, C. L.;
Marshall, A. G. Anal. Chem. 2004, 76, 5756−5761.
(117) Vining, B. A.; Bossio, R. E.; Marshall, A. G. Anal. Chem. 1999,
71, 460−467.
(118) Xian, F.; Hendrickson, C. L.; Blakney, G. T.; Beu, S. C.;
Marshall, A. G. Anal. Chem. 2010, 82, 8807−8812.
(119) Qi, Y.; Thompson, C. J.; Van Ordan, S. L.; O’Connor, P. B.
J. Am. Soc. Mass Spectrom. 2011, 22, 138−147.
(120) Lange, O.; Damoc, E.; Wieghaus, A.; Makarov, A. Proceedings of
the 59th ASMS Conference on Mass Spectrometry & Allied Topics,
Denver, CO, June 5−9, 2011.
(121) Blakney, G. T.; Hendrickson, C. L.; Marshall, A. G. Int. J. Mass
Spectrom. 2011, 306, 246−252.
(122) Mize, T. H.; Taban, I. M.; Duursma, M.; Seynen, M.;
Konijnenburg, M.; Vijftigschild, A.; Doornik, C. V.; Rooij, G. V.;
Heeren, R. M. A. Int. J. Mass Spectrom. 2004, 235, 243−253.
(123) Taban, I. M.; van der Burgt, Y. E. M.; Duursma, M.; Takats, Z.;
Seynen, M.; Konijnenburg, M.; Vijftigschild, A.; Attema, I.; Heeren, R.
M. A. Rapid Commun. Mass Spectrom. 2008, 22, 1245−1256.
(124) Perry, R. H.; Hu, Q.; Salazar, G. A.; Cooks, R. G.; Noll, R. J.
J. Am. Soc. Mass Spectrom. 2009, 20, 1397−1404.
(125) Frese, C. K.; Altelaar, A. F. M.; Hennrich, M. L.; Nolting, D.;
Zeller, M.; Griep-Raming, J.; Heck, A. J. R.; Mohammed, S. J. Proteome
Res. 2011, 10, 2377−2388.
(126) Macek, B.; Waanders, L. F.; Olsen, J. V.; Mann, M. Mol. Cell.
Proteomics 2006, 5, 949−958.
(127) Hakansson, K.; Cooper, H. J.; Emmett, M. R.; Costello, C. E.;
Marshall, A. G.; Nilsson, C. L. Anal. Chem. 2001, 73, 4530−4536.
(128) McAlister, G. C.; Phanstiel, D.; Good, D. M.; Berggren, T.;
Coon, J. J. Anal. Chem. 2007, 79, 3525−3534.
(129) Mann, M.; Kelleher, N. L. Proc. Natl. Acad. Sci. 2008, 105,
18132−18138.
(130) Xu, F.; Xu, Q.; Dong, X.; Guy, M.; Guner, H.; Hacker, T.; Ge, Y.
Int. J. Mass Spectrom. 2011, 305, 95−102.
(131) Ryan, C. M.; Souda, P.; Bassilian, S.; Ujwal, R.; Zhang, J.;
Abramson, J.; Ping, P.; Durazo, A.; Bowie, J. U.; Hasan, S. S.; Baniulis,
D.; Cramer, W. A.; Faull, K. F.; Whitelegge, J. P. Mol. Cell. Proteomics
2010, 791−803.
(132) Li, M.; Jiang, L.; Kelleher, N. L. J. Chromatogr., B 2009, 877,
3885−3892.
(133) Pesavento, J. J.; Yang, H.; Kelleher, N. L.; Mizzen, C. A. Mol.
Cell. Biol. 2008, 28, 468−486.
(134) Ferguson, J. T.; Wenger, C. D.; Metcalf, W. W.; Kelleher, N. L.
J. Am. Soc. Mass Spectrom. 2009, 20, 1743−1750.
(135) Lee, J. E.; Kellie, J. F.; Tran, J. C.; Tipton, J. D.; Catherman,
A. D.; Thomas, H. M.; Ahlf, D. R.; Durbin, K. R.; Vellaichamy, A.;
Ntai, I.; Marshall, A. G.; Kelleher, N. L. J. Am. Soc. Mass Spectrom.
2009, 20, 2183−2191.
(136) Pesavento, J. J.; Bullock, C. R.; LeDuc, R. D.; Mizzen, C. A.;
Kelleher, N. L. J. Proteome Res. 2008, 283, 14927−14937.
(137) Durbin, K. R.; Tran, J. C.; Zamdborg, L.; Sweet, S. M. M.;
Catherman, A. D.; Lee, J. E.; Li, M.; Kellie, J. F.; Kelleher, N. L.
Proteomics 2010, 10, 3589−3597.
(138) Sampson, J. S.; Murray, K. K.; Muddiman, D. C. J. Am. Soc.
Mass Spectrom. 2009, 20, 667−673.
(139) Lee, J. E.; Atkins, N.; Hatcher, N. G.; Zamdborg, L.; Gillette,
M. U.; Sweedler, J. V.; Kelleher, N. L. Mol. Cell. Proteomics 2010, 9,
285−297.
(140) Warder, S. E.; Tucker, L. A.; McLoughlin, S. M.; Strelitzer, T. J.;
Meuth, J. L.; Zhang, Q.; Sheppard, G. S.; Richardson, P. L.;
Lesniewski, R.; Davidsen, S. K.; Bell, R. L.; Rogers, J. C.; Wang, J.
J. Proteome Res. 2008, 7, 4807−4820.
(141) Armirotti, A. Curr. Anal. Chem. 2009, 5, 116−130.
(142) Han, X.; Aslanian, A.; Yates, J. R. III Curr. Opin. Chem. Biol.
2008, 12, 483−490.
(143) Perkins, D. N.; Pappin, D. J. C.; Creasy, D. M.; Cottrell, J. S.
Electrophoresis 1999, 20, 3551−3567.
(144) Eng, J. K.; McCormack, A. L.; Yates III, J. R. J. Am. Soc. Mass
Spectrom. 1994, 5, 976−989.
(145) Brosch, M.; Swamy, S.; Hubbard, T.; Choudhary, J. Mol. Cell.
Proteomics 2008, 962−970.
(146) Sweet, S. M. M.; Jones, A. W.; Cunningham, D. L.; Heath,
J. K.; Creese, A. J.; Cooper, H. J. J. Proteome Res. 2009, 8, 5475−5484.
(147) Tolmachev, A. V.; Monroe, M. E.; Purvine, S. O.; Moore, R. J.;
Jaitly, N.; Adkins, J. N.; Anderson, G. A.; Smith, R. D. Anal. Chem.
2008, 80, 8514−8525.
(148) Karpievitch, Y.; Stanley, J.; Taverner, T.; Huang, J.; Adkins,
J. N.; Ansong, C.; Heffron, F.; Metz, T. O.; Qian, W.-J.; Yoon, H.;
Smith, R. D.; Dabney, A. R. Bioinformatics 2009, 25, 2028−2034.
(149) Bereman, M. S.; Egertson, J. D.; MacCoss, M. J. Proteomics
2011, 11, 2931−2935.
717
dx.doi.org/10.1021/ac203191t | Anal. Chem. 2012, 84, 708−719
Analytical Chemistry
Review
(179) Zou, Y.; Tiller, P.; Chen, I.-W.; Beverly, M.; Hochman, J. Rapid
Commun. Mass Spectrom. 2008, 22, 1871−1881.
(180) Bahr, U.; Aygun, H.; Karas, M. Anal. Chem. 2009, 81, 3173−
3179.
(181) Taoka, M.; Yamauchi, Y.; Nobe, Y.; Masaki, S.; Nakayama, H.;
Ishikawa, H.; Takahashi, N.; Isobe, T. Nucleic Acids Res. 2009, 37,
1−14.
(182) Turner, K. B.; Brinson, R. G.; Yi-Brunozzi, H. Y.; Rausch, J. W.;
Miller, J. T.; Le Grice, S. F. J.; Marino, J. P.; Fabris, D. Nucleic Acids
Res. 2008, 36, 2799−2810.
(183) Turner, K. B.; Young, Y.-B.; Hye.; Brinson, R. G.; Marino, J. P.;
Fabris, D.; Le Grice, S. F. J. RNA 2009, 15, 1605−1613.
(184) Turner, K. B.; Kohlway, A. S.; Hagan, N. A.; Fabris, D.
Biopolymers 2008, 91, 283−295.
(185) Yu, E. T.; Hawkins, A.; Eaton, J.; Fabris, D. Proc. Natl. Acad.
Sci. 2008, 105, 12248−12253.
(186) Weidner, S. M.; Trimpin, S. Anal. Chem. 2010, 82, 4811−4829.
(187) Pernot, P.; Carrasco, N.; Thissen, R.; Schmitz-Afonso, I. Anal.
Chem. 2010, 82, 1371−1380.
(188) Wienhofer, I. C.; Luftmann, H.; Studer, A. Macromolecules
2011, 44, 2510−2523.
(189) Kaczorowska, M.; Cooper, H. J. J. Am. Soc. Mass Spectrom.
2008, 19, 1312−1319.
(190) Kaczorowska, M.; Cooper, H. J. J. Am. Soc. Mass Spectrom.
2009, 20, 2238−2247.
(191) Kaczorowska, M.; Cooper, H. J. J. Am. Soc. Mass Spectrom.
2009, 20, 674−681.
(192) Miladinovic, S. M.; Kaeser, C. J.; Knust, M. M.; Wilkins, C. L.
Int. J. Mass Spectrom. 2011, 301, 184−194.
(193) Nasioudis, A.; Heeren, R. M. A.; van Doormalen, I.; de WijsRot, N.; Van den Brink, O. F. J. Am. Soc. Mass Spectrom. 2011, 22,
837−844.
(194) Song, J.; van Velde, J. W.; Vertommen, L. L. T.; van der Ven,
L. G. J.; Heeren, R. M. A.; Van den Brink, O. F. Macromolecules 2010,
43, 7082−7089.
(195) Marshall, A. G.; Rodgers, R. P. Proc. Natl. Acad. Sci. U.S.A.
2008, 105, 18090−18095.
(196) Rodgers, R. P.; McKenna, A. M. Anal. Chem. 2011, 83, 4665−
4687.
(197) Fernandez-Lima, F. A.; Becker, C.; McKenna, A. M.; Rodgers,
R. P.; Marshall, A. G.; Russell, D. H. Anal. Chem. 2009, 81, 9941−
9947.
(198) Betancourt, S. S.; Ventura, G. T.; Pomerantz, A. E.; Viloria, O.;
Dubost, F. X.; Zuo, J.; Monson, G.; Bustamante, D.; Purcell, J. M.;
Nelson, R. K.; Rodgers, R. P.; Reddy, C. M.; Marshall, A. G.; Mullins,
O. C. Energy Fuels 2009, 23, 1178−1188.
(199) McKenna, A. M.; Purcell, J. M.; Rodgers, R. P.; Marshall, A. G.
Energy Fuels 2009, 23, 2122−2128.
(200) Pinkston, D. S.; Duan, P.; Gallardo, V. A.; Habicht, S. C.; Tan,
X.; Qian, K.; Gray, M.; Mullen, K.; Kenttamaa, H. I. Energy Fuels 2009,
23, 5564−5570.
(201) Purcell, J. M.; Merdrignac, I.; Rodgers, R. P.; Marshall, A. G.;
Gauthier, T.; Guibard, I. Energy Fuels 2010, 24, 2257−2265.
(202) Smith, D. F.; Rodgers, R. P.; Rahimi, P.; Teclemariam, A.;
Marshall, A. G. Energy Fuels 2009, 23, 314−319.
(203) Mullins, O. C.; Sheu, E. Y.; Hammami, A.; Marshall, A. G., Eds.
Asphaltenes, Heavy Oils, and Petroleomics; Springer: New York, 2007.
(204) McKenna, A. M.; Blakney, G. T.; Xian, F.; Glaser, P. B.;
Rodgers, R. P.; Marshall, A. G. Energy Fuels 2010, 24, 2939−2946.
(205) McKenna, A. M.; Purcell, J. M.; Rodgers, R. P.; Marshall, A. G.
Energy Fuels 2010, 24, 2929−2938.
(206) Hughey, C. A.; Minardi, C. S.; Galasso-Roth, S. A.; Paspalof,
G. B.; Mapolelo, M. M.; Rodgers, R. P.; Marshall, A. G.; Ruderman,
D. L. Rapid Commun. Mass Spectrom. 2008, 22, 3968−3976.
(207) Mapolelo, M. M.; Rodgers, R. P.; Blakney, G. T.; Yen, A. T.;
Asomaning, S.; Marshall, A. G. Int. J. Mass Spectrom. 2011, 300, 149−
157.
(150) Porteus, B.; Kocharunchitt, C.; Nilsson, R. E.; Ross, T.;
Bowman, J. P. Appl. Microbiol. Biotechnol. 2011, 90, 407−416.
(151) Plazas-Mayorca, M. D.; Zee, B. M.; Young, N. L.; Fingerman,
I. M.; LeRoy, G.; Briggs, S. D.; Garcia, B. A. J. Proteome Res. 2009, 8,
5367−5374.
(152) Sweet, S. M. M.; Li, M.; Thomas, P. M.; Durbin, K. R.;
Kelleher, N. L. J. Biol. Chem. 2010, 285, 32778−32786.
(153) Bumpus, S. B.; Evans, B. S.; Thomas, P. M.; Ntai, I.; Kelleher,
N. L. Nat. Biotechnol. 2009, 27, 951−955.
(154) Boyne, M. T. II; Garcia, B. A.; Li, M.; Zamdborg, L.; Wenger,
C. D.; Babal, S.; Kelleher, N. L. J. Proteome Res. 2009, 8, 374−379.
(155) Garcia, B. A.; Thomas, C. E.; Kelleher, N. L.; Mizzen, C. A.
J. Proteome Res. 2008, 7, 4225−4236.
(156) Ong, S.-E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D. B.;
Steen, H.; Pandey, A.; Mann, M. Mol. Cell. Proteomics 2002, 1, 376−
586.
(157) Manes, N. P.; Estep, R. D.; Mottaz, H. M.; Moore, R. J.;
Clauss, T. R.; Monroe, M. E.; Du, X.; Adkins, J. N.; Wong, S. W.;
Smith, R. D. J. Proteome Res. 2008, 7, 960−968.
(158) Wu, J.; Warren, P.; Shakey, Q.; Sousa, E.; Hill, A.; Ryan, T.;
He, T. Proteomics 2010, 10, 2224−2234.
(159) Dayon, L.; Pasquarello, C.; Hoogland, C.; Sanchez, J.-C.;
Scherl, A. J. Proteomics 2010, 73, 769−777.
(160) Zhang, Y.; Ficarro, S. B.; Li, S.; Marto, J. A. J. Am. Soc. Mass
Spectrom. 2009, 20, 1425−1434.
(161) Zybailov, B.; Coleman, M. K.; Florens, L.; Washburn, M. P.
Anal. Chem. 2005, 77, 6218−6224.
(162) Taylor, N. S.; Weber, R. J. M.; Southam, A. D.; Payne, T. G.;
Hrydziuszko, O.; Arvanitis, T. N.; Viant, M. R. Metabolomics 2009, 5,
44−58.
(163) Denkert, C.; Budczies, J.; Weichert, W.; Wohlgemuth, G.;
Scholz, M.; Kind, T.; Niesporek, S.; Noske, A.; Buckendahl, A.; Dietel,
M.; Fiehn, O. Mol. Cancer 2008, 7, 72.
(164) Takahashi, H.; Kai, K.; Shinbo, Y.; Tanaka, K.; Ohta, D.;
Oshima, T.; Altaf-UI-Amin, M.; Kurokawa, K.; Ogasawara, N.; Kanaya, S.
Anal. Bioanal. Chem. 2008, 391, 2769−2782.
(165) Baidoo, E. E. K.; Benke, P. I.; Neususs, C.; Pelzing, M.;
Kruppa, G.; Leary, J. A.; Keasling, J. D. Anal. Chem. 2008, 80, 3112−
3122.
(166) Dunn, W. B.; Broadhurst, D.; Brown, M.; Baker, P. N.;
Redman, C. W. G.; Kenny, L. C.; Kell, D. B. J. Chromatogr., B 2008,
871, 288−298.
(167) Kamleh, M. A.; Hobani, Y.; Dow, J. A. T.; Watson, D. G. FEBS
Lett. 2008, 582, 2916−2922.
(168) Werner, E.; Croixmarie, V.; Umbdenstock, T.; Ezan, E.;
Chaminade, P.; Tabet, J.-C.; Junot, C. Anal. Chem. 2008, 80, 4918−
4932.
(169) Jin, Z.; Daiya, S.; Kenttamaa, H. I. Int. J. Mass Spectrom. 2011,
301, 234−239.
(170) Murphy, R. C.; Gaskell, S. J. J. Biol. Chem. 2011, 286, 25427−
25433.
(171) Huan, H.; Emmett, M. R.; Nilsson, C. L.; Conrad, C. A.;
Marshall, A. G. Int. J. Mass Spectrom. 2010, 305, 116−119.
(172) Huan, H.; Nilsson, C. L.; Emmett, M. R.; Ji, Y.; Marshall, A. G.;
Kroes, R. A.; Moskai, J. R.; Colman, H.; Lang, F. F.; Conrad, C. A.
Glycoconjugate J. 2010, 27, 27−38.
(173) Huan, H.; Rodger, R. P.; Marshall, A. G.; Hsu, C. S. Energy
Fuels 2011, 26, 4770−4775.
(174) Lane, A. N.; Fan, T. W.-M.; Xie, Z.; Moseley, H. N. B.; Higashi,
R. M. Anal. Chim. Acta 2009, 651, 201−208.
(175) Garnier, N.; Rolando, C.; Hotje, J. M.; Tokarski, C. Int. J. Mass
Spectrom. 2009, 284, 47−56.
(176) Komaniecka, I.; Choma, A.; Lindner, B.; Holst, O. Chem.
Eur. J. 2009, 16, 2922−2929.
(177) Pol, J.; Vidova, V.; Hyotylainen, T.; Volny, M.; Novak, P.;
Strohalm, M.; Kostiainen, R.; Havlicek, V.; Wiedmer, S.; Holopainen,
J. M. Plos ONE 2011, 6, 1−9.
(178) Vidova, V.; Pol, J.; Volny, M.; Novak, P.; Havlicek, V.;
Wiedmer, S.; Holopainen, J. M. J. Lipid Res. 2010, 51, 2295−2299.
718
dx.doi.org/10.1021/ac203191t | Anal. Chem. 2012, 84, 708−719
Analytical Chemistry
Review
(208) Mapolelo, M. M.; Stanford, L. A.; Rodgers, R. P.; Yen, A. T.;
Debord, J. D.; Asomaning, S.; Marshall, A. G. Energy Fuels 2009, 23,
349−355.
(209) Headley, J. V.; Barrow, M. P.; Peru, K. M.; Derrick, P. J.
J. Environ. Sci. Health, Part A 2011, 46, 844−854.
(210) Headley, J. V.; Peru, K. M.; Janfada, A.; Fahlman, B.; Gu, C.;
Hassan, S. Rapid Commun. Mass Spectrom. 2011, 25, 459−462.
(211) Headley, J. V.; Peru, K. M.; Mishra, S.; Meda, V.; Dalai, A. K.;
McMartin, D. W.; Mapolelo, M. M.; Rodgers, R. P.; Marshall, A. G.
Rapid Commun. Mass Spectrom. 2010, 24, 3121−3126.
(212) Juyal, P.; McKenna, A. M.; Yen, A. T.; Rodgers, R. P.; Reddy,
C. M.; Nelson, R. K.; Andrews, A. B.; Atolia, E.; Allenson, S. J.;
Mullins, O. C.; Marshall, A. G. Energy Fuels 2011, 25, 172−182.
(213) Pomerantz, A. E.; Ventura, G. T.; McKenna, A. M.; Canas,
J. A.; Auman, J.; Koerner, K.; Curry, D.; Nelson, R. K.; Reddy, C. M.;
Rodgers, R. P.; Marshall, A. G.; Peters, K. E.; Mullins, O. C. Org.
Geochem. 2010, 41, 812−821.
(214) Kellmann, M.; Muenster, H.; Zomer, P.; Mol, H. J. Am. Soc.
Mass Spectrom. 2009, 20, 1464−1476.
(215) Krauss, M.; Singer, H.; Hollender, J. Anal. Bioanal. Chem. 2010,
397, 943−951.
(216) Helbling, D. E.; Hollender, J.; Kohler, H.-P. E.; Singer, H.;
Fenner, K. Environ. Sci. Technol. 2010, 44, 6621−6627.
(217) Liou, J. S.-C.; Szostek, B.; DeRito, C. M.; Madsen, E. L.
Chemosphere 2010, 80, 176−183.
(218) van Leerdam, J. A.; Hogenboom, A. C.; van der Kooi, M. M. E.;
de Voogt, P. Int. J. Mass Spectrom. 2009, 282, 99−107.
(219) Nam, S.; Joo, S.; Kim, S.; Baek, N.-I.; Choi, H.-K.; Park, S.
J. Plant Biol. 2008, 51, 373−378.
(220) Schmidt, F.; Elvert, M.; Koch, B. P.; Witt, M.; Hinrichs, K.-U.
Geochim. Cosmochim. Acta 2009, 73, 3337−3358.
(221) Gonsior, M.; Zwartjes, M.; Cooper, W. J.; Song, W.; Ishida,
K. P.; Tseng, L. Y.; Jeung, M. K.; Rosso, D.; Hertkorn, N.; SchmittKopplin, P. Water Res. 2011, 45, 2943−2953.
(222) Bhatia, M. P.; Das, S. B.; Longnecker, K.; Charette, M. A.;
Kujawinski, E. B. Geochim. Cosmochim. Acta 2010, 74, 3768−3784.
(223) Giardina, M.; Siek, K.; Kowalski, J. In Proceedings of the 58th
ASMS Conference on Mass Spectrometry & Allied Topics, Salt Lake City,
Utah, May 23−27, 2010.
719
dx.doi.org/10.1021/ac203191t | Anal. Chem. 2012, 84, 708−719
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