Fundamentals and Advances of Orbitrap Spectrometry

Fundamentals and Advances of Orbitrap Mass Spectrometry

Michaela Scigelova and Alexander Makarov

Thermo Fisher Scientific (Bremen) GmbH, Bremen, Germany

1 Introduction 1

2 Fundamentals of the Orbitrap Mass Analyzer 2

2.1 Structure of the Trap 2 2.2 Motion of Trapped Ions 3 2.3 Ion capture in the Orbitrap Analyzer 4 2.4 Ion Detection 4 2.5 Formation of Coherent Ion Packets 6 2.6 Decay of Coherent Ion Packets 6 2.7 Space–Charge Effects in the Orbitrap

Analyzer 7 2.8 Fragmentation Inside the Orbitrap

Analyzer 8 2.9 Overview of the Main Analytical Parameters

of the Orbitrap Mass Analyzer 9 3 The Orbitrap Analyzer used as an Accurate Mass

Detector 9

3.1 An Overview of Orbitrap-based Instruments 9

3.2 Linear Trap/Orbitrap Hybrid Mass Spectrometer 9

3.3 Exactive: The First Benchtop Fourier Transform Mass Spectrometer 12

3.4 Quadrupole/Orbitrap Hybrid Mass Spectrometer 12

4 Orbitrap Instrumentation—Applications 13

4.1 Current Trends in Analysis 13 4.2 Elemental Composition from High-resolution

Mass Spectrometry Data 15 4.3 Food Safety and Environmental Analysis 15 4.4 Metabolite Analysis, Clinical Analysis, and

Bioanalysis 16 4.5 Illicit Drug Use and Doping 17 4.6 Small Molecule—Omics 18 4.7 Proteomics 20 4.8 Oligonucleotide Analysis 26

5 Future of the Orbitrap Technology 26

6 Conclusion 26

Acknowledgments 27

Abbreviations and Acronyms 27

Related Articles 27

References 27

Analytical chemistry has considerably benefited from the developments in the field of mass spectrometry. The high resolution, mass accuracy, and sensitivity offered by modern mass spectrometers have been essential in addressing analytical needs in numerous areas of research as well as in routine laboratory praxis. The most recent addition to the family of mass spectrometers has been the Orbitrap analyzer, making an ultrahigh-resolution mass spectrometry accessible to most life science laboratories. The Orbitrap-based instrumentation has established itself firmly in the field of proteomics, metabolomics, and metabolite analysis. Moreover, it is gaining increased popularity also in areas of bioanalysis, lipidomics, doping, as well as in drug and pesticide residue analysis. This article presents the principle of operation of the Orbitrap analyzer, its most recent technological developments, and outlook, and it reviews application areas where the Orbitrap analyzers represent the state-of-the-art solution to a multitude of analytical needs.

1 INTRODUCTION

Although the Orbitrap™ mass analyzer is rightfully considered to be one of the newest analyzers, its roots can be traced back to 1923 when the principle of orbital trapping was proposed by Kingdon.(1) In his work, ions were formed by discharge inside an enclosed cylindrical metal can and attracted toward a charged wire stretched along the axis of the can. Ions with too high tangential velocity were ‘‘missing’’ the wire and thus starting to orbit around it for prolonged periods of time.

Experiments over the next half a century have shown that charged particles could indeed be effectively trapped in electrostatic fields,(2) but they offered no hint of how to use this for mass analysis. Meanwhile, advances in charged particle optics steadily expanded the number of electrostatic fields available for experimentation.(3) One such field with a quadro-logarithmic potential distribution was applied for orbital trapping of laser-produced ions by Knight,(4) with crude mass analysis performed by applying axial resonant excitation to trapped ions and ejecting them to a detector near the axis outside of the trap. As this device was not capable of separating even the simplest mixtures, this attempt demonstrated that the quest for a new mass analyzer would require considerable

Encyclopedia of Analytical Chemistry, Online © 2006–2013 John Wiley & Sons, Ltd. This article is © 2013 John Wiley & Sons, Ltd. This article was published in the Encyclopedia of Analytical Chemistry in 2013 by John Wiley & Sons, Ltd. DOI: 10.1002/9780470027318.a9309

2 MASS SPECTROMETRY

improvements in all key areas, most notably a more accurate definition of the quadro-logarithmic field, ion injection from an external ion source, and ion detection that matches well with the structure of the trap.

These issues have been successfully addressed in the seminal work of Makarov.(5,6) Unlike previous attempts, central electrode was implemented not as a thin wire but rather as a massive metal electrode with maximum accuracy of machining. Outer electrodes were made identical to each other and matching the shape of the central electrode. Being electrically separated, they were employed not only for trapping but also as receiver plates for image current detection, with geometry of the trap optimized to improve sensitivity of such detection and reduce higher harmonics. A special machined slot with a compensation electrode (a ‘‘deflector’’) was implemented to allow injection of ion packets with minimum losses. The image current from coherently oscillating ions was detected on receiver plates as a time-domain signal, and Fourier transform of this signal then gave a mass spectrum. Under the newly coined name ‘‘Orbitrap,’’ this analyzer joined and extended the family of Fourier transform mass analyzers, which, before this, contained only one widely used analyzer: Fourier transform ion cyclotron resonance (FT ICR).(7)

Following the first proof of principle with a laser ion source, further very significant technological advances were needed to make the Orbitrap analyzer useable in practice, most importantly the development of pulsed injection from an external ion storage device.(8 –10)

Unique to the history of mass spectrometry, both proof of principle and development of a commercial product have been carried out entirely within industry, from the first scientific presentation in 1999 till the entry into mainstream mass spectrometry in 2005. Since then, several thousands of Orbitrap-based instruments were produced and became a common sight in analytical laboratories and facilities worldwide.

2 FUNDAMENTALS OF THE ORBITRAP MASS ANALYZER

2.1 Structure of the Trap

Orbitrap mass analyzer essentially consists of three electrodes, as shown in Figure 1. These cut-outs show both a standard trap as introduced in 2005(10) and the so-called high-field compact trap introduced in 2011.(11)

Outer electrodes have the shape of cups facing each other and separated by a hair-thin gap secured by a central ring made of dielectric. Spindlelike central electrode holds the trap together and aligns it via dielectric end-spacers. These electrodes are shaped in such a manner to produce

(a)

(b)

Figure 1 A cut-out of a standard (a) and a high-field (b) Orbitrap analyzer. (Reprinted with permission of Thermo Fisher Scientific © 2012.)

the quadro-logarithmic potential distribution

U(r, z) = k

2

(

z2 − r2

2

)

+ k

2 · (Rm)2 · ln

[ r

Rm

]

+ C (1)

where r, z are cylindrical coordinates (z = 0 being the plane of the symmetry of the field), C is a constant, k is the field curvature, and Rm is the characteristic radius. This potential distribution is shown in Figure 2, with the ‘‘ridge’’ of the saddle corresponding to r = Rm. Equipotential lines shown in this figure reveal the shape of

U (r, z)

r

Z

0

Figure 2 Three-dimensional representation of the quadro-logarithmic potential distribution. Potential goes abruptly down as r → 0. (Reprinted with permission of Thermo Fisher Scientific © 2012.)


FUNDAMENTALS AND ADVANCES OF ORBITRAP MASS SPECTROMETRY 3

Ueff (r, z)

r

z

0

Figure 3 Three-dimensional representation of the effective potential formed by the quadro-logarithmic potential distribu-tion and centrifugal potential. A local minimum at z = 0 and r = R is indicated by an arrow. (Reprinted with permission of Thermo Fisher Scientific © 2012.)

electrodes. This electrostatic potential has no minimum, and therefore, an ion that starts from a static condition would inevitably roll off either toward r = 0 or away toward r → ∞.

For moving ions, this potential combines with centrifugal potential formed as a result of the initial momentum of ions

Ueff(r, z) = U(r, z) + E0 · r2

0

r2 (2)

where E0 = mvϕ 2/2, vϕ is the initial tangential component

of velocity, and r0 is the initial radius. This results in a drastic change of potential distribution, as shown in Figure 3: a minimum is formed between r = 0 and r = Rm as marked by an arrow, and ions could be now safely trapped in this ‘‘ditch.’’ The ditch has a much steeper wall on the side of lower radii. At the same time, potential distribution along z-axis remains quadratic and completely unaffected by centrifugal potential.

2.2 Motion of Trapped Ions

When ions start their motion at the correct energy and radius, stable trajectories are formed, which combine three cyclic motions (see Figure 4):

• rotational motion around the central electrode with a frequency of rotation ωϕ;

rR m

z

ϕ

Figure 4 The diagram of the Orbitrap mass analyzer showing a stable spiral trajectory of an ion between the central electrode and the split outer electrodes. The value of Rm is indicated on the radial axis, r. (Reprinted with permission of Thermo Fisher Scientific © 2012.)

• radial motion with a frequency ωr (between maximum and minimum radii inside the ‘‘ditch’’);

• axial oscillations along the central electrode with a frequency ω.

Even though ion trajectory assumes the shape of a complicated spiral (see Figure 4), it is important to note that, slightly counter intuitively, axial motion remains completely independent of rotational motion.

In practice, it is preferable to have the resulting spiral motion as close to circular as possible, because this reduces the influence of field imperfections. To provide a circular trajectory, the tangential velocity of the ions needs to be adjusted to such a value that the centrifugal force compensates the force created by radial electric field. This corresponds to movement at the bottom of the ‘‘ditch,’’ marked by an arrow as shown in Figure 3. For a radius R of this spiral, the frequency of angular rotation ωϕ is

ωϕ = ω

√ √ √ √ (

Rm R

)2 − 1

2 (3)

and the frequency of radial oscillations ωr is

ωr = ω

√ ( Rm

R

)2

− 2 (4)

where the frequency of axial oscillations ω is

ω = √

e

(m/z) ·k (5)

where e is the elementary charge (1.602 × 10−19 C).


4 MASS SPECTROMETRY

Even in this simplest form, rotational and radial frequencies show dependence on the initial radius R. The axial frequency, on the other hand, is completely independent of all initial velocities and coordinates of the ions. Therefore, only the axial frequency can be used for the determination of mass-to-charge ratios, m/z.

The axial field strength is at zero in the equator plane of the trap, but increases uniformly in opposing directions along the z-axis as the two coaxial electrodes become progressively closer (see Figure 4). This means that the axial electric field directs the ions toward the equator of the trap with a force proportional to the projection of the electric field onto the z-axis. It accelerates ions toward the equator (zero point along z-axis in Figures 2 and 3) and then the ions continue to fly through the equator (point of zero force) along the z-axis, but decelerate as they continue toward the opposite end of the trap using up the axial velocity previously gained in traversing the electric field gradient from the starting point to the equator. Having ‘‘spent’’ their axial velocity, the ions stop and then are accelerated back toward the equator of the trap by the symmetric electric field along the z-axis. In this way, the ions oscillate naturally along the z-axis in a manner similar to pulling back a pendulum bob and then releasing it to oscillate. It is this property of the electric field that causes the mass-dependent harmonic oscillation of the ions along the z-axis.

Another peculiar consequence of the spiral motion is the increased requirement on radial field strength: rotation around the electrode will be stable only when ωϕ > 0 in Equation (3), which requires R < Rm/

√ 2, that

is, ions should reside deep inside the potential well in order not to fly over its ridge.

2.3 Ion capture in the Orbitrap Analyzer

As almost no ion source could produce stable ions directly within the trap, an ion source has to be located externally to the Orbitrap analyzer. Ions from such a source are then captured using the principle of ‘‘electrodynamic squeezing,’’(6) wherein ions experience a steady increase in electric field strength as they enter the trapping field. This process is illustrated in Figure 4(a)–(d), which depicts squeezing ions of different m/z just in the radial direction, with a short packet of higher m/z arriving later to the field from an external pulsed ion source. Outer electrodes remain at a fixed potential (in practice, virtual ground), while the potential on the central electrode is ramped down (for positive ions). Once ions enter the field, they cannot return back to the point of entry because by the time of return the trapping potential evolves to form a noticeable barrier between ions and the entrance point. The rise time of the field (typically 30–50 μs) is chosen to ensure the widest range of trapped m/z.

Squeezing is stopped when ions reach the desired radius R (typically, equidistant from both central and outer electrodes) and the voltage on the central electrode is then stabilized to prevent mass drift during detection. Because of the strong dependence of rotational and radial frequencies on ion energies, angles, and initial positions (see Equations 3 and 4), each ion packet soon spreads over the angular and radial coordinates; it forms a thin rotating ring. This is illustrated in Figure 5(d) by ions spreading over the entire well of effective potential. This has important ramifications: more ions can be present in the Orbitrap mass analyzer before the space charge effects start impacting the mass resolution and accuracy of the measurement.

2.4 Ion Detection

The axial oscillation frequencies can be detected directly by measuring the image current on the outer Orbitrap electrodes, as shown in Figure 6. As ion packets oscillate harmonically along the axis, the difference of image currents between electrodes is detected by a differential amplifier and amplified over a broad range of frequencies. Its output is digitized and subjected to a fast Fourier transform that converts the recorded time-domain signal into a mass-to-charge ratio spectrum.(7)

As the image current is amplified and processed exactly in the same way as in FT ICR, sensitivity and signal-to-noise ratios are similar to those in FT ICR. There is a minor but important distinction; however, the square-root dependence originating from the electrostatic nature of the field causes a much slower drop in resolving power observed for ions of increasing m/z value. As a result, the Orbitrap analyzer may provide higher resolving power than FT ICR over the same transient duration above a particular m/z (typically, above m/z 500–1000).

Generally, the signal on the output of differential amplifier is not strictly harmonic and therefore overtones 3ω, 5ω, 7ω, and so on might appear in spectrum. However, the geometry of the trap could be matched to the amplitude of oscillations in such a way that these harmonics are minimized. The radial or rotational frequencies never appear in the spectrum because, as shown earlier, ion packets spread in thin rings and therefore the signals from opposing angular sectors of the ring exactly cancel each other.

There could be an alternative way of detecting ions that follows the original proposal of Knight(4): to excite the ions axially using a voltage at a resonant frequency and to scan the mass range by sweeping this frequency. The main advantage of this approach over conventional traps would be the ability to eject any ions, including those of very high m/z-value, using only very low


5 FUNDAMENTALS AND ADVANCES OF ORBITRAP MASS SPECTROMETRY

Ueff (r ) Ueff (r )

(a) r0 r (b) r0 r

Ueff (r ) Ueff (r )

(c) r0 r (d) r0 r

Figure 5 Electrodynamic squeezing of ions of different m/z in the radial direction r as voltage on the central electrode increases from (a) to (d). A packet of light ions is shown by a small red circle, and a packet of heavier ions by a bigger blue circle. The final steady distribution of ions along r is shown in (d), with ions spreading over the entire well of effective potential. (Reprinted with permission of Thermo Fisher Scientific © 2012.)

I(t )

I(t )

Z (t )

t

t

Figure 6 Image current detection using outer electrodes and differential amplifier. (Reprinted with permission of Thermo Fisher Scientific © 2012.)


6 MASS SPECTROMETRY

radio frequency (RF) voltages.(6) However, such a trapwould not be able to carry out MSn experiments, whichseverely limits its appeal in comparison to a Paul trap.Compared to the image current detection, this methodwould provide significantly lower resolving power forthe same scan time and wide mass range; it is alsoexpected to suffer from higher susceptibility to spacecharge. Therefore, detecting image current remains themajor mode of operation for all practical Orbitrap massspectrometers.

Sensitivity of image current detection is determinedby internal and thermal noise of electronic componentsof image current preamplifier. For the best present-daysolutions, this corresponds to a limit of detection in theorder of 3–5 elementary charges for a 1-s acquisition.

2.5 Formation of Coherent Ion Packets

The most important prerequisite for the image currentdetection is the ability to concentrate all ions of the samem/z within a packet that is significantly smaller in the axialdirection than the amplitude of oscillations. This could beachieved in one of two ways:

• Broadband excitation of ions from the equatorialplane. Although traditional to FT ICR as well ascompatible with well-known types of external RFstorage devices, this approach demands substantialcomplexity of an ion introduction apparatus.(5)

• Excitation by off-axis injection of pulsed ion packets(‘‘excitation by injection’’). This approach minimizesperturbations of the quadro-logarithmic field butrequires a very fast ejection of large ion populationfrom an ion source or an external RF storage device.

Proof of principle for the first approach has beendemonstrated for ions already trapped in the Orbitrapanalyzer.(2) Excitation could be implemented by applyingresonant AC voltage to the same outer electrodes that arelater used for detection. Ultimately, the second approachhas proved to be more practical and robust. For a pulsedlaser source, it was implemented using just a set of staticlenses.(2,6)

For a continuous ion source, an additional challenge ofconverting a continuous stream of ions into a short pulsecould be met only by inserting an external accumulationdevice. Then injection is performed according to thefollowing sequence:

1. Ions are trapped in the external accumulation devicein the form of a gas-filled RF—only set of rods,preferably a curved linear ion trap (C-trap as shownin Figure 7). In principle, this device could be alsoused for various manipulations of the ions, includingisolation, fragmentation, MSn, etc.

2. Pulsed voltages are applied to the end electrodes(8,9)

or across the RF electrodes(10) of the device sothat the ions find themselves in a strong extractionfield. The probability of collisions and collision-induced dissociation (CID) during the ion extractionis minimized by storing ions near the exit orifice orslit. Additional lenses are used for the final spatialfocusing of the ion beam onto the entrance of theOrbitrap analyzer, as well as to provide differentialpumping to achieve the very high vacuum necessaryfor effective mass measurement.

3. Simultaneously with pulsing voltages on the externalaccumulation device, voltage on the central electrodeis ramped down (for positive ions). In practice,there is also a small ramping voltage applied to thedeflector electrode that directs ions into the injectionslot.

4. Ions of individual mass-to-charge ratios arrive at theinjection slot of the Orbitrap analyzer as a tightpacket with dimensions considerably smaller than theamplitude of their axial oscillations. When ion packetsare injected into the Orbitrap analyzer off-axis(see Figure 7), they start coherent axial oscillationswithout the need for any additional excitation.

5. After entering the trap, the ion packets are‘‘squeezed’’ by increasing the electric field to movethe ions toward the equator and the central electrode.Simultaneously with the radial motion illustratedin Figure 4, a similar process also takes placealong the axial direction, the only difference beingthe quadratic shape of the axial potential well(see Figure 8a–d).

6. While ions spread in angular and radial directions,potential in the axial direction remains quadratic allthe time, so that axial oscillations remain harmoniceven though the field is ramped up. It means thation packet remains thin in the axial direction, thoughsome spreading might occur already during injection(see Figure 8d).

Following the injection, the voltages on both the centralelectrode and deflector are stabilized so that no mass driftcan take place during detection.

2.6 Decay of Coherent Ion Packets

As mentioned earlier, under ideal conditions, the ionscould remain in the trap indefinitely. Unfortunately, thecollisions with residual gas cause ions to scatter and limitthe time a transient can be detected down to a fewseconds. There are two reasons for signal decay and bothwork indirectly, via loss of coherence rather than throughphysical loss of ions:

Encyclopedia of Analytical Chemistry, Online © 2006–2013 John Wiley & Sons, Ltd.This article is © 2013 John Wiley & Sons, Ltd.This article was published in the Encyclopedia of Analytical Chemistry in 2013 by John Wiley & Sons, Ltd.DOI: 10.1002/9780470027318.a9309


Orbitrapanalyzer

Ion packet

C-trap

Voltage ramp

Amplifier

Detected signal

Figure 7 Cross section of the C-trap and Orbitrap analyzer (ion optics and differential pumping not shown). Ion packets enterthe analyzer during the voltage ramp and form rings that induce current detected by the amplifier. (Reprinted with permission ofThermo Fisher Scientific © 2012.)

1. The loss of ion momentum in collisions causes thecoherent ion packet to ‘‘diffuse,’’ thus increasingaberrations and accelerating further ‘‘diffusion’’ asa result of other factors such as field imperfections.

2. Collisions can lead to prompt or metastable ionfragmentation, which could also lead to direct lossof ions if they hit an electrode.

Both processes are random in time and, therefore,transform the original coherent ion cloud into anincoherent one that cannot be detected by image currentdetection, even if ions are still moving within the trap. Thetime between collisions is inversely proportional to theresidual pressure inside the trap and to the cross sectionof an ion. For a pressure of 10−10 mbar, time intervalranges from several seconds for small molecules to <1 sfor small- and medium-size proteins. By improving theOrbitrap vacuum below this level, isotopic resolution ofprotein ions up to several tens of kilodaltons has beendemonstrated.(12)

The decay of transient and consequent limitation ofresolving power is further caused by a loss of coherenceas a result of unavoidable compromises of design (suchas an injection slot, a limited length of electrodes, and

a gap between detection electrodes), limited accuracyof the Orbitrap electrode manufacturing, and due tospace charge repulsion. Therefore, the transient andhence the ultimate resolving power could be furtherextended by improving the vacuum and optimizing theabove parameters.

2.7 Space–Charge Effects in the Orbitrap Analyzer

Space–charge effects are Achilles’ heel of any trappingdevice. In the Orbitrap analyzer, these effects appeartypically at much higher charge densities than in RFion traps, and are especially pronounced in traps witha strong dependence of the period of oscillation on ionenergy. These effects include the following(13):

• mass shifts caused by the dependence of the periodof oscillation on the total charge in the trap and theintensity of individual peaks. Unlike in other types oftraps, relative amplitudes of these shifts are typicallyindependent of m/z and therefore could be correctedusing a calibration procedure(10);

• coalescence, that is the mutual locking of ion packetswith very similar m/z at a certain phase difference.


8 MASS SPECTROMETRY

U (z ) U (z )

U (z )

0 0z

(a) (b)

(c) (d)

z0

U (z )

0 0zz0

z0

z0 z

z

Figure 8 Electrodynamic squeezing of ions of different m/z in the axial direction z during ‘‘excitation by injection.’’ Voltage onthe central electrode increases from (a) to (d). A packet of light ions is shown by a small red circle, and a packet of heavier ions by abigger blue circle. The final steady distribution of ions along r is shown in (d), with ions spreading slightly but preserving coherencyof the initial packets. (Reprinted with permission of Thermo Fisher Scientific © 2012.)

For image current detection, coalescence could makethese packets to appear as a single packet at weight-averaged m/z;

• diffusion, that is a slow and monotonous increase inpacket size by space–charge interactions, and henceresponsible for a progressive growth of aberrations;

• synchronization (self-bunching), that is, a decrease inpacket size when a certain space–charge density isexceeded in a nonlinear field. This counterintuitiveeffect results in an undesirable difference in packetdecay times for m/z values of different intensities (e.g.isotopes).

Similar effects have been observed in other traps, forexample, in FT ICR mass analyzers. In the Orbitrapanalyzer, all space charge effects are greatly reduced asa result of the shielding action of the central electrodethat screens ions on the one side of the ion ring frominfluencing ions on the other side. To reduce diffusionand self-bunching, a slight controlled distortion of theideal electrode shape is introduced to provide theappropriate dependence of the oscillations periods onion energy.

2.8 Fragmentation Inside the Orbitrap Analyzer

The ions trapped in the Orbitrap analyzer haveenergies in the kiloelectronvolt range. A high-energyfragmentation caused by collisions with residual gashappens automatically, and its extent could be regulatedby gas pressure. Pulsed lasers could be another wayto induce fragmentation of ions inside the Orbitrapanalyzer. Unfortunately, when an ion decays under thedynamic trapping conditions, its fragments will have thesame velocity. As their energy is proportional to theirindividual mass-to-charge ratios, the trajectories becomehighly elliptical. Therefore, low-mass fragments (with m/ztypically below 30–50% of that of the precursor ion) willfall onto the central electrode, while lower charge statefragments (with m/z typically above 50% of the precursorion) will hit the outer electrodes. This property seriouslylimits the utility of the analyzer for MSn, especially havingin mind the absence of collisional cooling, increased cycletime, inferior resolving power and sensitivity, cost, andcomplexity of such an apparatus.

This is why, in all practical applications, the Orbitrapanalyzer is used only as an accurate mass detector, rather



than as an MS/MS (tandem mass spectrometry) device inits own right.

2.9 Overview of the Main Analytical Parameters of theOrbitrap Mass Analyzer

Similar to other mass analyzers (e.g. a quadrupole),analytical parameters are determined to a large extentby the present status of manufacturing technology andelectronics. The current level of machining precisionenables the resolving power of the Orbitrap mass analyzerto reach several hundred thousand routinely and abovemillion for some selected traps.(12) Internal and thermalnoise of electronic components impacts the sensitivityof image current detection in the Orbitrap, although itslimit of detection reaches just several elementary chargesin 1-s acquisition. The mass error using external masscalibration is a few parts per million and remains stableover at least a 24-h period, being limited by drift of powersupplies. The internal mass accuracy is limited at a sub-part per million level principally by stability of electroniccomponents as well as by space charge effects.

The repetition rate of the trap is mainly defined bythe desired resolving power and potentially could reachseveral tens of hertz. For transient durations up to 1–2 s,this allows to provide resolving power higher than that inFT ICR mass analyzers for m/z above 400–1000.

Transmission from the external accumulation device tothe trap is very efficient and allows more than 30–50%of ions to contribute to the detected signal. This is oneor two orders of magnitude higher than typical for otheraccurate mass analyzers. Therefore, it allows reducingdrastically the number of ions (and hence sample) neededfor accurate mass measurement.

3 THE ORBITRAP ANALYZER USED ASAN ACCURATE MASS DETECTOR

3.1 An Overview of Orbitrap-based Instruments

The challenging nature of the technical issues relatedto performing MS/MS in the Orbitrap mass analyzerwas the main reason behind the concept of using it asan accurate mass detector for another mass analyzer,that is, linking two mass spectrometers into one hybridinstrument. With an ion storage device of the C-trap typeinserted between the first mass analyzer and the Orbitrapanalyzer as shown in Figure 7, the analyzers becomeeffectively decoupled from each other and, therefore, anymass analyzer capable of selecting precursor ions and anyfragmentation technique could be now interfaced to it.

The entry of the Orbitrap analyzer into mainstreammass spectrometry took place in 2005, with the introduc-tion of the LTQ Orbitrap instrument by Thermo Electron

(currently Thermo Fisher Scientific). It used a combina-tion with a linear trap mass analyzer. In 2011, combinationwith a quadrupole mass analyzer was launched under thename of Q Exactive™. Since 2008, there has also beena stand-alone Orbitrap mass spectrometer, Exactive™,wherein the first analyzer had been replaced by a simpletransfer multipole. This section reviews these majormembers of the Orbitrap instrument family.

3.2 Linear Trap/Orbitrap Hybrid Mass Spectrometer

3.2.1 Configuration and Operation

In the very first commercial Orbitrap-based instru-ment,(10) a linear ion trap with radial ejection was chosenas a ‘‘partner’’ for the Orbitrap mass analyzer owing to itsvery high sensitivity, superb control of the ion population,short cycle time, and MSn capability. Depending on therequirements for the analysis, the two analyzers can beused independently or in concert. Schematic of both theearliest and the latest instrument of this family are shownin Figure 9.

An important feature of the instrument is the procedureof automatic gain control (AGC), wherein a short prescanin the linear trap is used to determine the ion currentwithin the mass range of interest, hence enabling storageof a defined number of ions (‘‘AGC target value’’) inthe subsequent analytical scan. The AGC feature incombination with the precise determination of the ioninjection time allows the instrument to be used foraccurate quantitative analyses and ensures stability andaccuracy of m/z measured by the Orbitrap analyzer.

It is worth pointing out that the MS/MS spectragenerated in the linear ion trap and detected either inthe linear trap or the Orbitrap analyzer are very similar,the only major difference being the resolution and massaccuracy of the observed peaks.

A true parallel operation is achieved by using the initialpart of the transient still being measured in the Orbitrapanalyzer (alternatively, the previous full transient couldbe used). This defines the parent ion masses for the linearion trap to fragment, while the detection of the Orbitrapimage current continues until the specified final resolutionis reached. The mass error using external mass calibrationremains stable over a 24-h period and stays within a fewparts per million for peaks ranging in intensity fromthe limit of detection and up to the saturation of thelinear trap. Meanwhile, internal mass accuracy frequentlyreaches the sub-parts per million range. This built-inflexibility, together with the sheer analytical power ofmass resolution and accuracy, ensured a great commercialsuccess of the instrument.


10 MASS SPECTROMETRY

Electrosprayion source

Electrosprayion source

S-lens Octopole

Newhigh-field orbitrap

mass analyzer

Square quadrupolewith beam blocker

Squarequadrupole

Octopole

(a)

Orbitrapmass analyzer

Low pressurecell

Lowpressure

cellQuadrupolemass filter

HCDcollision cell

Transfermultipole

Reagention source

Reagent 1heated inlet

Reagent 2 heated inlet

C-trap

Highpressure

cell

Multipole C-trap

(b)

Figure 9 Schematic layout and picture of a linear trap/Orbitrap hybrid mass spectrometer: (a) the LTQ Orbitrap Classic and (b)the Orbitrap Elite with ETD option. (Reprinted with permission of Thermo Fisher Scientific © 2012.)

3.2.2 Evolution of the Instrument: Extensions Behindthe C-trap

Since its introduction in 2005, further developments havetaken place toward expanding the analytical capabilitiesof the LTQ Orbitrap. In addition to delivering the ionsinto the Orbitrap, the C-trap was used to enable severalnovel modes of operation. For example, because of itshigh space charge capacity, the C-trap can be used toaccept multiple fills. An injection of a fixed number ofions of a known compound (calibrant) can be followedby an injection of analyte ions. Both sets of ions arethen injected simultaneously into the Orbitrap analyzerand measured in a single spectrum. This allows for arobust internal calibration of each spectrum, with root-mean-square (rms) errors below 1 ppm.(14) Furthermore,multiple injections of ions fragmented or selected atdifferent conditions can be stored together and acquiredin a single Orbitrap spectrum.

The C-trap can be also considered as a useful T-piece that allows interfacing to additional devices. Thisversatility provided by the C-trap has been extensivelyused for later extensions of the LTQ Orbitrap instrument.For example, the addition of a collision cell after the C-trap has opened a route to using higher energy collisions(with energies higher than those achievable in the linearion trap) and, hence, the term higher collision energydissociation (HCD).(15) Ions are allowed to pass through

the C-trap, enter an acceleration gap, and then fragmentin an RF-only multipole collision cell in a way similarto the fragmentation in triple quadrupole or quadrupoletime-of-flight instruments. Fragmentation of ions in theHCD cell is achieved by adjusting the offset of the RFrods to provide the required collision energy. As longas this offset remains negative relative to the C-trapand the HCD exit lenses, all fragments remain trappedinside the HCD cell, even if the offset of the RF rods isvaried. Fragment ions are trapped and cooled insidethe multipole and then returned to the C-trap fromwhich they are injected into the Orbitrap analyzer fordetection in a usual manner. This allows the collectionof all fragments without any low-mass cutoff. Analysis ofimmonium ions, quantitation with iTRAQ™ or TMT™labels, de novo sequencing of peptides, and buildinghighly informative fragmentation spectra libraries are justa few application areas that benefit from this extensionwith the multipole collision cell. In future, the use ofthis collision cell for infrared multiphoton dissociation(IRMPD), ion–molecule reactions, and ion–ion reactionswill open new avenues of mass spectrometry analysis.

HCD collision cell allows to introduce multipleprecursor ions and to fragment them at their optimumcollision energy without compromising the storage ofpreceding injections. The summed ion population canthen be transferred back into the C-trap with the helpof the axial field in the HCD cell, ejected into the



Orbitrap analyzer, and analyzed in a single detectioncycle. This opens the possibility of fundamentally new,‘‘multiplexing’’ modes of operation. In practice, the usefulnumber of ion injections for a single Orbitrap detectionis limited by the sum of the individual inject times beinglower than the time for the Orbitrap detection. Up to thislimit, additional analytical information could be gainedwithout a decrease in spectral acquisition rate.

Further important development appeared to bethe addition of electron transfer dissociation (ETD)capabilities.(16) For ETD application, reagent anions(such as fluoranthene) are produced by a chemical ioniza-tion source behind the HCD collision cell and passthrough the HCD cell and the C-trap into the lineartrap, where ion–ion reactions with peptide cations takeplace (see Figure 9b). The resulting peptide fragmentscan be analyzed by the linear ion trap at single-ion sensi-tivity or transferred via the C-trap into the Orbitrapanalyzer for high mass accuracy and resolution analysis.The ETD technique allows analysis of a much greatervariety of post-translational modifications than CID orHCD, providing in many cases an unambiguous identifi-cation and localization of phosphorylations, methylations,acetylations, glycosylations, and other generally fragilemodifications within the peptide sequence. Thanks to thehigh resolving power and mass accuracy of the Orbitrapanalyzer, the ETD approach can be successfully appliednot only for peptides but also for small- and medium-sizeproteins. The resulting instrument configuration driven bypowerful data-dependent ‘‘decision tree’’ software allowsthe combination of CID, HCD, and ETD fragmentationtechniques within one single system.(17)

3.2.3 Evolution of the Instrument on the Front-End

The LTQ Orbitrap capabilities were extended not onlyby enhancing C-trap abilities but also on the front-end.One of most important extensions became a matrix-assisted laser desorption and ionization (MALDI) sourceoperating at reduced pressure. Trapping in gas minimizesissues related to unimolecular dissociations due to highlaser power used for desorption. As a consequence,a smaller number of laser shots produce greater ionpopulations.(18) This allows for a dynamic range of manythousands just in a single Orbitrap scan. At the sametime, high transmission to the trap allows for excellentsensitivity. Important applications include peptide massfingerprinting, tissue imaging, and liquid chromatography(LC)/MALDI.

A number of atmospheric-pressure ion (API) sourceshave been interfaced to this and later Orbitrap instru-ments, such as an atmospheric-pressure MALDI, laserdiode thermal desorption (LDTD), desorption electro-spray ionization (DESI), inductively coupled plasma

(ICP), direct analysis in real time (DART), and so on.Filtering devices were also successfully used, for example,high-field asymmetric waveform ion mobility spectrom-etry (FAIMS). These extensions enhanced utility of theinstrument.(19)

The next generation of the instrumentation is associ-ated with the introduction of the LTQ Orbitrap Velosin 2009, where a number of innovations were intro-duced to increase sensitivity and scan speed.(20) Insteadof a capillary-skimmer interface of the LTQ OrbitrapClassic, a stacked ring RF ion guide (the so-called S-lens)was employed, with transfer efficiency 10-fold higher inMS/MS mode and three- to five-fold higher in full scanspectra. The linear trap was upgraded to a dual pres-sure ion trap configuration with accelerated scanning andreduced overhead times between scans. In this device, thefirst ion trap efficiently captures and fragments ions at arelatively high pressure, whereas the second ion trap real-izes extremely fast scan speeds at reduced pressure. Ioninjection times for MS/MS are predicted from precedingfull scans, instead of performing AGC scans (predic-tive AGC). Altogether, these improvements routinelyenabled acquisition of up to ten fragmentation spectraper second.

On the Orbitrap side, modifications included animproved HCD cell with reduced ion losses and highertemperature bakeout of the Orbitrap analyzer forimproved top-down analysis. The gas-filled HCD cellwas also separated from the C-trap only by a singlediaphragm, allowing easy HCD tuning.

3.2.4 Generation Change of the Orbitrap Analyzer

New generation of the Orbitrap analyzer was introducedin 2011 as a part of the Orbitrap Elite instrument.(11)

The resolving power of the Orbitrap analyzer hasbeen increased almost four-fold for the same transientlength. By employing a compact, high-field Orbitrapanalyzer (see Figure 1b), the observed frequenciespractically double, while an enhanced Fourier transform(eFT) algorithm further doubles the resolving powerto 240 000 at m/z 400 for a 768 ms transient. Thisalgorithm incorporates information about phases of ionoscillations that are precisely defined as a result ofthe built-in ‘‘excitation-by-injection’’ mechanism (seeSection 2.5). Both of these innovations required rigorousimprovements in adjacent ion optics, preamplifier, andmachining accuracy of the Orbitrap electrodes. Inaddition, robustness of the ion transfer optics and MS/MSacquisition speed of the dual linear ion trap wereimproved in this instrument.

Proteomics became by far the most prominentapplication area that makes use of this instrumentation.For top-down experiments, a survey scan is combined



with a selected ion monitoring scan of the charge stateof the protein to be fragmented and with several HCDmicroscans. The total cycle time is significantly reducedand becomes compatible with LC MS/MS, even whenspectra are being acquired at a higher resolving power.For bottom-up proteomics, increased speed of analysisbrings about higher numbers of identified proteins incomplex mixtures as well as a broader utilization ofcomplementary dissociation modes.

3.3 Exactive: The First Benchtop Fourier TransformMass Spectrometer

Following the introduction of the LTQ Orbitrap, anonhybrid mass spectrometer, the Exactive, has beendeveloped, wherein a stand-alone Orbitrap mass analyzeris combined with an API source. Figure 10(a) shows theschematic layout of this benchtop instrument.(21)

Samples are introduced into the API source and theions formed are transferred from the source through fourstages of differential pumping using RF-only multipolesinto the C-trap, where the ions are accumulated and theirenergies dampened using a bath gas (nitrogen). Ions arethen injected through three further stages of differentialpumping using a curved lens system into the Orbitrapanalyzer, where mass spectra are acquired via imagecurrent detection. The vacuum inside the Orbitrap massanalyzer is maintained in the 10−10 mbar range.

The ability to control the ion population within thetrap is the conditio sine qua non of any trapping device.In the absence of any preceding mass analyzer, the AGCof the number of ions in the Orbitrap is achieved bymeasuring the total ion charge using a prescan and thenusing this quantity to calculate the ion injection time forthe subsequent analytical scan. For very high scan rates,the previous analytical scan is used as a prescan in order tooptimize the scan cycle time without compromising AGC.

Ion gating is performed using a fast split lens set-up thatensures the precise determination of the ion injectiontime. In later instruments, Orbitrap AGC is monitoredand corrected when necessary, using periodic detectionof ejected charges by a dedicated charge detector.

The acquisition speed of this relatively simple instru-ment matches that of ultrahigh-performance liquid chro-matography (UHPLC). In addition, compared to theion trap/Orbitrap hybrid systems, the mass range of thesystem has been extended (up to m/z 6000). High in-scandynamic range of signal intensity (four orders of magni-tude), together with the ability to perform fast polarityswitching (acquiring one positive and one negative high-resolution scan within 1 s), made this system suitablefor a broad range of applications be it discovery work,screening, quantitative analyses, or elemental composi-tion determinations. The instrument also allows for abroad-band fragmentation without mass selection (‘‘allions MS/MS’’) performed in an optional HCD collisioncell inserted after the C-trap. This provides the user witha tool for confirmation or for identification of analytes.

3.4 Quadrupole/Orbitrap Hybrid Mass Spectrometer

The combination of a quadrupole mass filter with anOrbitrap analyzer was introduced in 2011 under thename Q Exactive. It offers unique and complementaryadvantage to the hybrid mass spectrometers describedearlier (see Figure 10b).(22) In particular, such instrumentis able to select ions virtually instantaneously as a resultof the fast switching times of the quadrupole, and it isable to fragment them in HCD mode on a similarly fasttimescale. In combination with the ability to fill the HCDcell or the C-trap with ions while a previous Orbitrapdetection cycle is still ongoing, the system can achieve avery high duty cycle. By allocating most of analysis time(up to 70–95%) just for accumulating ions, the sensitivity

HCD cell C-trap

S-lens

(a) (b)

S-lens



Transfer multipole HCD cell C-trap Quadrupole mass filter

Figure 10 Schematic layout of (a) a stand-alone Orbitrap instrument, the Exactive Plus and (b) quadrupole-Orbitrap hybrid massspectrometer, the Q Exactive. (Reprinted with permission of Thermo Fisher Scientific © 2012.)



is maximized, allowing to pre-empt the negative impactthat low ion currents could have on acquisition speed andquality of spectra.

Furthermore, quadrupole mass filter enables efficientmultiplexed scan modes not currently used by trappinginstruments. For instance, in a multiplexed single-ion monitoring mode, the quadrupole rapidly switchesbetween different narrow mass ranges, allowing ions ofselected masses to pass into the C-trap, where they aresequentially accumulated. Once the mixed population ofdesired ions is built up, they are analyzed jointly in asingle Orbitrap detection event. Similarly, the instrumentallows fragmentation of different precursor m/z in rapidsuccession while capturing and retaining the resultingfragment populations all together in the HCD collisioncell, followed by their joint analysis in the Orbitrapanalyzer. In practice, the useful number of ion injectionsfor a single Orbitrap detection is limited by the sum ofthe individual inject times being lower than the time forthe Orbitrap detection.

The Q Exactive instrument has incorporated all thelatest technology developments such as the S-lens, eFT,extended mass range, and fast polarity switching. Lastbut not least, because of the small size and mature tech-nology of current quadrupole mass filters, this analyzercombination has a small footprint and high robustness.

4 ORBITRAP INSTRUMENTATION—APPLICATIONS

Thermo Scientific Orbitrap technology has become anestablished platform in many application areas. The highresolving power, mass accuracy, and dynamic range ofthe Orbitrap analyzer allow rigorous characterizationof complex mixtures. While multiple levels of frag-mentation (MSn) available on ion trap/Orbitrap hybridinstruments enable advanced experiments including verydetailed structural analysis, for example, when identi-fying unknowns or probing into details on intact proteins,a relatively simple and straightforward mass spectrom-eter comprising an API source and a standalone Orbitrapmass analyzer has performance characteristics well suitedfor application areas such as exact mass measurementsof organic compounds, early drug discovery metabolismand pharmacokinetics, general unknown screening, andmultiresidue analysis (pesticides, mycotoxins, and veteri-nary drugs).

This section provides an overview of the publishedliterature mentioning the Orbitrap technology in thecontext of various application areas. Because of theoverwhelming number of publications, it should be notedthat the references herein inevitably and regretfullyrepresent just a short selection.

4.1 Current Trends in Analysis

Currently, practitioners of mass analysis face a bigdilemma: should they employ a unit-resolution selectivereaction monitoring or a high-resolution accurate massassay?

Triple quadrupole instruments use MS/MS as part ofthe technique called selected reaction monitoring (SRM)to achieve a high degree of selectivity, even in complexbiological samples. On the downside, preoptimization isrequired to determine appropriate SRM parameters. Themeasured compounds are limited to those targeted bySRM events programmed in the method. In addition,the quantitative performance decreases with increasingnumber of SRM scan events per unit of time.

The high-resolution mass analyzers, on the other hand,detect ions relying on measuring their accurate mass.High resolution is critical to obtaining adequate analytespecificity in complex biological samples. A genericfull scan method can be used, looking for everythingwith in the appropriate scan range. The number ofcompounds that can be detected is virtually unlimited. Nopreoptimization of the method is required that translatesinto considerable time/resource savings for the analyst.While accurate mass alone is generally not sufficient toidentify an unknown compound, it is a critical first steptoward such a goal.

The accuracy of the mass measurement is highlydependent on the mass resolution used for analysis.When analyzing complex mixtures, co-eluting, nearlyisobaric compounds can interfere with the peak of interestskewing the value of the mass detected by the analyzer.Figure 11 shows the pesticide pirimicarb present in acomplex mixture of other pesticides and toxins in a horsefeed extract. LC/MS analysis acquired at inadequateresolving power (here, 15 000 FWHM (full width athalf maximum) was used) shows a mass deviation of 6.5ppm for the peak corresponding to pirimicarb. The massreading is inaccurate due to a shift in detecting the peakcentroid. Reanalyzing the same sample at appropriateresolution settings (here, 100 000 FWHM), pirimicarb wasdetected with mass deviation of 0.3 ppm. An interferencethat had been responsible for that relatively large massshift observed at lower resolution settings was clearlyrevealed.

Employed mass resolution must be fit-for-the-purpose,taking into consideration the complexity of the sample.Only then is the mass measurement reliable, and a narrowmass tolerance window can be used for extracting the ionsof interest from a complex background. Resolution is thuscritical for obtaining adequate assay selectivity.

The intensity of the background signal will ultimatelylimit the sensitivity of an assay. The ability to use anarrow extraction window has a profound impact on the



239.15

239.15181 6.5 ppm

239.15033 0.3 ppm

Pirimicarb

Pirimicarb

Resolvedinterference

R = 100 000

R = 15 000

m/z(a)

(b) m/z

239.20 239.25

239.15 239.20 239.25

Figure 11 High-resolution results in better mass accuracy.Pesticide pirimicarb was measured in a mixture of other 115pesticides and food toxins in a horse feed matrix. (a) Massspectrum taken at the time of the elution of pirimicarb acquiredat resolving power 15 000 FWHM. The peak corresponding topirimicarb showed a mass deviation of 6.5 ppm. (b) Switching toresolution 100 000 FWHM in the same analytical run detectedpirimicarb with mass deviation of 0.3 ppm. At the same time,it revealed the presence of an interference that had beenresponsible for the relatively large mass shift observed atlower resolution settings. (Reprinted with permission of ThermoFisher Scientific © 2012.)

presence/intensity of a background signal. Resolution is,therefore, also the key to sensitivity of the assay.

A word of caution should be expressed here. Usingextraction mass windows that are too narrow might leadto missing the ion peak altogether, for three main reasons.The first is the earlier-mentioned problem related to theshift of the peak centroid mass due to insufficientlyresolved interference. The extraction mass toleranceshould not be narrower than the range provided by theavailable mass resolution.(23)

The second reason is the incapability of certainanalyzers to obtain accurate mass reading across the entireelution peak of the compound, be it due to a detectorsaturation near the peak apex or due to insufficiention statistics at the leading/trailing edge of the peak.A careful evaluation of the performance characteristicof the analyzer is called for. Figure 12 shows the highfidelity of mass measurement by an Orbitrap analyzeracross the entire eluting chromatographic peak, a featurethat clearly sets these analyzers apart.

2.00

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0.840.84

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Figure 12 Fidelity of mass measurement accuracy. Massdeviation obtained in the Orbitrap analyzer at 50 000 resolution(FWHM at m/z 400) across a 5 s chromatographic peak.Mass deviation corresponds to 0.62 ppm rms. (Reprinted withpermission of Thermo Fisher Scientific © 2012.)

The third important figure of merit is the precision ofthe mass measurement. Precision of some instruments isclearly doubtful as they present high dispersion with stan-dard deviation introducing an uncertainty in the accuratemass measurement with errors at the third decimal.(24)

Careful evaluation of mass measurement precision, inaddition to the evaluation of mass measurement accu-racy, is thus indispensable when choosing an adequatehigh-resolution mass spectrometry (HRMS) platform.

The most attractive feature of HRMS-based analysis is,however, the fact that the comprehensive data set allowsfor retrospective analysis based on a posteriori hypothesis.A theoretically unlimited number of analytes can beextracted from the full scan data without compromisingsensitivity. Furthermore, HRMS permits the elucidationof elemental composition of analytes based on exactmasses and isotopic patterns. The presence of resolvedsulfur and carbon isotope peaks illustrates the usefulnessof information obtainable from highly resolved MSspectra (see Figure 13). Such information can be usedfor compound confirmation or for identifying unknowns.

To conclude this introductory section on the high-resolution-based mass spectrometric analysis, it wouldbe pertinent to mention the outcome of a studysystematically comparing the selectivity provided by SRMand HRMS coupled to LC.(25) The authors aimed atdetermining the HRMS resolution setting that wouldproduce selectivity corresponding to SRM (the so-calledcrossover point). Artificial ‘‘dummy transitions’’ and‘‘dummy exact masses’’ were randomly generated andwere used to monitor blank samples by a UHPLC coupledto either SRM or HRMS instruments. The correspondingdummy traces were ‘‘monitored’’ to provoke a number ofendogenous matrix compounds to produce measurable



1000000

Abu

ndan

ce

80000

524.2653 R = 71000

525.2689 R = 72700

526.2611 R = 71900

526.2722 R = 70900

526.2611 R = 71900

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0526.24 526.26

34S 13C2

m/z526.28

0524.2 524.4 524.6 524.8 525.0 525.2

m/z525.4 525.6 525.8 526.0 526.2 526.4

Figure 13 Observing fine isotopic structures. Isotope cluster of a peptide (sequence MRFA) analyzed at effective resolution∼70 000. As the peptide contains sulfur (‘‘M’’ in the sequence stands for amino acid methionine), the splitting of the peakcorresponding to [A + 2] isotopologue can be observed. The peak resolves into two peptide species containing either one isotope of34S or two isotopes of 13C. (Reprinted with permission of Thermo Fisher Scientific © 2012.)

chromatographic peaks. The outcome of the studyconfirmed HRMS as an attractive tool for trace-leveldetection and quantitation of compounds in challengingmatrices. The authors concluded that the Orbitrapresolution setting in excess of 50 000 (FWHM at m/z200) permits selectivity exceeding that provided bycurrently used unit-resolving SRM instruments withsimilar sensitivities.

4.2 Elemental Composition from High-resolution MassSpectrometry Data

HRMS is the key to obtaining elemental compositionof observed ions. While accurate mass alone is in manycases not sufficient (depending on the number of elementsconsidered and the MW of the analyte), and oftenadditional heuristic rules, such as isotope ratio infor-mation and short-listing possible constituent elements,need to be employed to restrict the number of potentiallyrelevant elemental compositions, the confirmation of acompound’s identity using HRMS analysis is a straight-forward application for both natural(26,27) and syntheticproducts(28,29) as well as for polymers such as fructans(30)

or oligomers(31) with a degree of polymerization up to100.

4.3 Food Safety and Environmental Analysis

In the context of food analysis, selectivity is thoughtto refer to the likelihood that a compliant sample(containing no exogenous compounds) is incorrectlyconsidered noncompliant (false positive). Analogously,such a definition should also include the likelihood

that a noncompliant sample (containing exogenouscompounds) is wrongly considered compliant (falsenegative). A wrong decision regarding the presence orabsence of an exogenous compound is influenced, or evendirectly caused, by the presence of matrix compounds thatnegatively affect the reliability of the detection process.As a consequence, the lower the required detection limitand the more difficult the matrix, the higher the requireddetection selectivity.

Ever increasing share of analyses of toxins and pesticideand veterinary drug residues rely on HRMS to ensurethe safety of foodstuffs.(22) Several benchmarking studiesinvestigated the sensitivity of the HRMS approach andconfirmed the importance of high resolution for assaysin complex matrices.(32–34) By operating the Orbitrap-based instrument at varying resolving power settings(10 000–100 000 FWHM at m/z 200), we found that for aconsistent and reliable mass assignment (mass deviationless than 2 ppm) of analytes at low levels in complexmatrices, a high resolving power (an effective resolutionin excess of 50 000) was required (see Figure 14). Atlower effective resolution, the error of mass assignmentincreased as a result of the co-elution of analytes withinterferences at the same nominal mass.

In the quest for ever increasing sample throughput andreduced analysis times, a turbulent flow chromatography(a technique that separates analytes from the matrixusing specific columns packed with large particles whereanalytes are retained while the large molecules—such asproteins or lipids—pass through the column) has beencoupled to an Orbitrap-based MS. A fully automatedsample preparation relying on this technique has



160 100k 50k 25k 10k149140

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nt

Figure 14 Resolution enables accurate mass measurement inmixtures. Mass resolving power and complexity of the sampleare major parameters affecting the accuracy of mass assignmentin multiresidue screening applications. Resolution setting 50 000(FWHM at m/z 200) or higher was required for accurate analytemeasurement when screening 151 pesticides, veterinary drugs,mycotoxins, and plant toxins spiked into horse feed matrix.(Reprinted with permission of Thermo Fisher Scientific © 2012.)

been validated,(35) and rapid screening and accuratemass confirmation of pesticides at concentration limitssignificantly lower than the strictest limits set by theEuropean Union and the Japanese government has beendemonstrated in fruit matrices.(36)

Other food contaminants analyzed using an Orbitrap-based instrumentation, mostly coupled to an UHPLC,included biogenic amines,(37) marine biotoxins,(38) andmycotoxins.(39,40) Acquiring in both positive and negativeion modes within a single run further increased the samplethroughput.

A recently developed ionization technique, DART,enables sampling directly from surface of the produceor from simple swabs. Coupled to the Orbitrap-baseddetection, it has been employed for rapid screeningof pesticide residues and provided results comparableto traditional (more lengthy and laborious) samplepreparation methods.(41–44)

When detecting a particular contaminant, various foodmatrices require different levels of sensitivity. Examplesfrom wine analysis illustrate this fact. Although natamycinis allowed for the surface treatment of semihard andsemisoft cheese and dry, cured sausage, it is not permittedfor use in wines. As the current ISO method (limitof quantification (LOQ) 0.5 mg kg−1) is not sensitiveenough for the determination of low levels of natamycinexpected in adulterated wines, a method adequate for thedetection of natamycin in wines had to be developedand validated.(45) A highly sensitive Orbitrap-basedassay (limit of detection (LOD) tens of micrograms permillileter) has also been developed for the detection ofvery low amounts of casein remaining in wines after thefining treatment.(46,47)

It is not just the production and processing of foodstuffsthat might be a source of contaminants. Benzophenoneis one of the compounds reported in foodstuffs as aresult of its migration from food packaging materials. Afast, sensitive, and selective Orbitrap-based methodologyhas been developed that has achieved unequivocalidentification of benzophenon in packaged foods.(48) Notethat the high resolving power enabled the detection andidentification of the alkaloid harman as the compoundimpeding the confirmation of benzophenon in previouslyreported SRM-based experiments.

While the majority of analyses focuses on detecting the‘‘bad’’ things in the foodstuffs, there is a growing interestin a more valid assessment of the nutritional value, too.Consumption of anthocyanins, responsible for the red,purple, and dark blue colors of many fruits and berries, hasbeen associated with improved cognitive function. BothSRM- and HRMS-based methods have been employedfor the detection of cyanidin-3-O-glucoside in tissueextracts.(49) Because of its high level of selectivity,HRMS using an Orbitrap analyzer was approximately200-fold more sensitive, able to distinguish betweencompounds differing in mass by as little as 21 mDa, andprovided a dynamic range of four orders of magnitude ofconcentrations. Moreover, no compound-specific tuningwas necessary for the development of HRMS methoddevelopment.

The emerging demand under European legislationfor screening more hydrophilic compounds has beentranslated into development of methods for theirmonitoring in aqueous environments. Detection ofhighly polar compounds at trace concentration levelsin aqueous samples represents a major challenge wherethe Orbitrap instrumentation satisfied the sensitivityrequirements.(50–52) At a resolution setting of 50 000(FWHM at m/z 200), accurate mass measurements witherrors less than 2 ppm were obtained for all tested analytesacross different water matrices.(53)

4.4 Metabolite Analysis, Clinical Analysis, andBioanalysis

Large amounts of endogenous components can mask thedrug and its metabolites in biological matrices such asplasma, urine, faeces, and bile. The narrow mass windowreduces, and sometimes entirely eliminates, backgroundchemical noise, significantly increasing the sensitivity ofconfirming the presence of metabolites.(54,55)

Having spectra with a very high degree of mass accuracyat sufficient mass resolution and scan rates opens thepossibility for combining targeted analysis and unbiasedmetabolite profiling. Because the theoretical masses canbe used for ion extraction, it becomes possible to querythe data with a list of theoretical candidate metabolites,



without the need for any prior experimental screening,results, or evidence. The post-acquisition availability ofaccurate mass information for any ion in the full scanspectrum, with a degree of specificity equal to mostSRM-based assays, becomes a hallmark and a principaladvantage of HRMS approach.(56)

The ability of a mass analyzer to clearly observe anisotopic pattern can be used to trigger data-dependentproduct ion scans. Implementation of this attributeprovides a broader detection capability compared toclassical approaches using product ion or neutral lossscans, as it is independent of the CID behavior of thecompounds. This feature proved very useful for theanalysis of metal-containing compounds,(57,58) as wellas compounds with other atoms showing a distinctiveisotopic pattern signature, such as sulfur or bromine.(59,60)

Discovery stage drug metabolism studies (pharma-cokinetics, microsomal stability, etc.) typically use triplequadrupole-based approaches for quantitative analysis.This requires the optimization of parameters includingQ1 and Q3 m/z values, collision energy, and interfacevoltages. Such studies, however, detect only the specifiedcompound; information about other components is lost.The use of HRMS approach offers the potential for afundamental shift in how routine bioanalysis is carriedout in drug discovery. The ability to perform full-scanacquisition for quantitative analysis eliminates the needfor compound optimization while enabling the detectionof metabolites and other nondrug-related endogenouscomponents. The recent advancements in Orbitrap tech-nology have resulted in detection sensitivity equivalentto that of triple quadrupole mass spectrometry operatingin SRM mode. In addition, the acquisition frequency hasreached the level that is well suited for narrow peaksgenerated from current UHPLC systems.(61–65)

Additional advantage of HRMS approach is thecapability of simultaneous quantitation of, theoretically,an unlimited number of compounds, which is not possiblewith SRM on a triple quadrupole mass spectrometer.This unique bioanalytical capability of HRMS was usedto develop a novel in vitro absorption, distribution,metabolism, and excretion (ADME) workflow of cassetteincubation of as many as 32 compounds, followed byquantitative bioanalysis using full-scan acquisition on anOrbitrap instrument.(66) The workflow was evaluatedfor a serum protein-binding assay and a parallelartificial membrane permeability assay (PAMPA), whichdisplayed acceptable sensitivity, selectivity, and linearityfor all compounds in the cassettes. The biological resultsobtained using the cassette incubation approach weresimilar to those from discrete incubation and analysis,demonstrating the feasibility of the workflow withadditional benefits including a saving of analysis timedue to the reduced sample numbers from the cassette

approach, as well as cost saving due to the reduction inthe required assay reagents.

Engaging one of several fragmentation techniquesavailable on the Orbitrap systems opens the route tostructural elucidation and identification of analytes.(67,68)

Fragments detected with high mass accuracy can be moreeasily assigned and correctly annotated (see Figure 15).The Orbitrap-based HRMS systems can thus be usedfor nontargeted metabolite and biomarker identificationwhile performing targeted bioanalytical quantitation in asingle data acquisition.(21)

The ability of hybrid ion trap/Orbitrap spectrometersto provide multiple levels of fragmentation (MSn) withaccurate mass detection generates valuable structuralinformation. The approach proves in many cases tobe superior to trying to interrogate a complex production spectrum typically generated on other types of massanalyzers. The analysis of an impurity in Fondaparinuxpreparation was the first example of using MS10 spectragenerated in negative ion electrospray ionization (ESI)mode reported in the literature.(69)

The results from several clinical application studiesdemonstrated that UHPLC coupled to the Orbitrap massspectrometer delivered results comparable to those oftriple quadrupole-based assays in routine quantitativedrug analyses.(70–72) An affordable and fast (2.5 min)method for accurate and precise determination ofglobal DNA methylation levels in peripheral blood wasdeveloped and validated on the Orbitrap system.(73) Theauthors highlighted the advantages of retrospective dataanalysis for other components, for example, when RNAdata were also needed.

The first publication of intact protein bioanalysisby HRMS has appeared recently.(74) Albeit the quan-titative analysis of intact proteins might not be thepreferred method, the routine quantitation/bioanalysis oflarge molecules in dystrophia myotonica protein kinase(DMPK) setting is rapidly growing and of tremendousinterest.

4.5 Illicit Drug Use and Doping

Metabolite identification and quantitation in the area ofdoping control is benefiting considerably from accuratemass determination. The identification of compoundsof interest can be achieved using the exact mass inalternating positive/negative ionization mode at theexpected retention times. The stability of mass accuracydelivered by the Orbitrap instrumentation is essential forthe success of screening methods.(75–78) The quantitativeperformance of the Orbitrap-based assays was, in general,similar to that of the SRM-based ones. Remarks suchas that 300 analyses could be carried out without any



O

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304.21033 455.29102

303.20703C9H10O2+;Δ = 1.76 ppm

C10H13O2+;Δ = 0.91 ppm

C18H27N2O2+;Δ = 1.08 ppm

C27H39N2O4+;Δ = 1.28 ppm

C16H22NO2+;Δ = 1.46 ppm

Figure 15 Structural information contained in MS/MS spectrum. Fragmentation of verapamil (C27H39N2O4 [M+H]+ m/z455.29102) was performed in the HCD cell with collision energy settings 35 eV. Mass deviation in parts per million is given foreach identified fragment. Mass Frontier software was used for spectrum processing and annotation. (Reprinted with permission ofThermo Fisher Scientific © 2012.)

routine maintenance testify about the robustness of theOrbitrap-based systems.(56)

Even though not used in doping practice at present,there are compounds that have a distinct doping‘‘potential,’’ such as small interfering ribonucleic acid(siRNA)(79) or hypoxia-inducible factor stabilizers.(80)

HRMS also helps elucidating dissociation pathways tocharacteristic product ions.(81) Such data can be includedin a novel multitargeted detection assay used for routinedoping control, which is based on direct injection ofhuman urine and simultaneous LC/ESI/MS/MS determi-nation of protonated and deprotonated compounds withscan-to-scan polarity switching.(82)

4.6 Small Molecule—Omics

The huge complexity of samples is a common theme for all-omics applications. Most analytical methods in the -omicsarea are based on one of the following two strategies. Thefirst strategy is aimed at specifically analyzing a limitednumber of known compound classes. The second strategyuses an unbiased approach for profiling as many featuresas possible in a given complex mixture without priorknowledge of the identity of these features.

The Orbitrap-based HRMS can address both of theseareas. The ability of benchtop Orbitrap-based systems toperform a fast polarity switching provides the option toacquire both positive and negative ionization spectra in

a single LC/MS run. Information obtained from experi-ments using multiple available fragmentation techniquesfurther supports the identification/quantification of theanalyzed species.

4.6.1 Metabolomics

Implementation of a high-resolution mass analyzerwithin the metabolomic workflow offers considerablesimplification of the entire process. The widest range andmost secure identification of metabolites can be made oninstruments operated at a high resolution, making use ofexact mass measurement of both precursor and fragmentions.(83)

Instruments with sufficiently high resolving powerallow for a direct introduction of some biologicalsamples, thus eliminating the need for chromatographicseparation.(84) Such an approach was validated bystudying the matrix effect, linearity, and intra-assayprecision of quantitation. Further, MSn fragmentationdata confirmed the structures proposed based on accuratemass measurement of the precursor ions. SRM-basedapproaches often proved cumbersome, especially formetabolites that can be partially labeled in many differentways, as each partially labeled form requires its own SRMscan.(85)

As global metabolite extracts can be quite complexand include many classes of compounds, the focus of



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Figure 16 Orbitrap data acquisition rate is UHPLC compat-ible. Eleven data points at effective resolution 45,000 werecollected over a 3-s wide elution peak of loperamide(C29H33ClN2O2, MW 476.2231 g mol−1) with the Q Exactivesystem. (Reprinted with permission of Thermo Fisher Scientific© 2012.)

LC/MS-based metabolomic profiling studies has been,among others, on the development of efficient and robustLC/MS methods.(86) UHPLC embodies current trend inimproving the effectiveness of analysis. Modern Orbitrapsystems with fast acquisition rates provide sufficient datapoints across narrow UHPLC peaks (see Figure 16),as well as a linear response to the concentration ofmetabolites over 3.5 orders of magnitude with limitsof detection less than 1 μmol l−1. As polar compoundstend to elute in the void volume from C18 reversed-phase columns, hydrophilic interaction chromatography(HILIC) can be of high utility as it retains hydrophiliccompounds while allowing hydrophobic species to flowthrough rapidly.(87) Analysis of selenized species carriedout with HILIC coupled to a time of flight and OrbitrapMS highlighted the importance of the higher intrascandynamic range of the Orbitrap analyzer. Another distinctadvantage of the Orbitrap system was the ability tomaintain both sub-parts per million mass accuracyand the selenium isotopic pattern (up to MS4) forall species with a minimum intrascan abundance ofat least 0.005, thus providing indisputable structuralconfirmation.(36)

Metabolomic approaches supported by the Orbitrap-based analysis contributed to elucidating the architectureof metabolic pathways,(88,89) in some cases using isotopetracers and quantitative flux modeling.(90) These studiesdemonstrate the importance of complementing genomeannotation with isotope tracer studies for determiningmetabolic pathways of diverse microbes.

4.6.2 Lipidomics

Lipidomics is a branch of -omics techniques that aims atquantifying a full complement of lipid molecules in cells,

tissues, or organisms. Because of rapid acquisition ofMS/MS spectra, very high mass resolution, and optionalMSn fragmentation, hybrid linear ion trap/Orbitraptandem mass spectrometers have developed into animportant lipidomics tool.

High-resolution survey spectra enable us to directlyprofile total lipid extracts.(91–94) Lipids of major classescould be recognized by accurately determined precursormasses with no recourse to MS/MS. Absolute quantifica-tion of molecular lipid species can also be performed. This‘‘top-down’’ workflow provides the ability to decipherglobal lipidome perturbations in a rapid and unbiasedmanner. Reliable mass accuracy and very high resolutionare a prerequisite for such studies.

‘‘Bottom-up’’ lipidomics relies on tandem mass spec-trometric experiments providing structural information.Experiments are either performed on-line with liquidchromatography or by infusion of total lipid extractsdirectly into a spectrometer. The latter approach, alsocalled shotgun lipidomics, has demonstrated potentialfor high-throughput screens to complement ongoingfunctional genomics efforts. High resolution and frag-mentation capabilities of Orbitrap systems allow for rapid,comprehensive, and structure-specific profiling of variouslipid classes.(95)

Modern Orbitrap-based instrumentation enables us toconduct both ‘‘bottom-up’’ (structural information usingfragmentation data) and ‘‘top-down’’ (profiling using fullscan data) lipid analysis within a single acquisition methodon a single platform.(96) A large study (240 UHPLC/MSruns, 10 min each) combined targeted analyses andgeneral metabolic profiling approaches for the analysisof phospholipids.(56) Very high mass accuracies enabledto extract ion chromatograms based on a narrow ±2.5ppm mass window. While increasing that window did notincrease the area under the curve, confirming the stabilityof mass accuracy measurement across entire elution peakof the compounds of interest, it can harbor an increasedrisk of interferences due to the incorporation of otherspecies (see Figure 17).

While some lipids ionize well in both positive andnegative modes, lipid ionization efficiency and detec-tion specificity of most species strongly depend onthe acquisition polarity. It is therefore beneficial toanalyze lipid mixtures in both positive and negativemodes.(97–100) There being no trade-off between reso-lution and sensitivity on the Orbitrap detector, suchassays allow for high sensitivity. This often leadsto the identification of novel compounds, with theability of the ion trap portion of the hybrid Orbi-trap system to perform MSn experiments often provingindispensable.(101)



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Figure 17 High resolution ensuring selectivity in phospholipid analysis. Extracted ion chromatograms for m/z 496.3398 and m/z518.3241. (a) The traces are shown for 2.5 ppm windows and (b) the traces for 7.5 ppm. Only using the 2.5 ppm windows (a), theextracted ion chromatogram for m/z 518.3241 is specific for GPCho (18:3/0:0). Increasing the uncertainty allowance yielded theincorporation of other masses. After increasing the ppm window to values >2.5 ppm, it was no longer possible to distinguish twoimportant M+22 species, generated by either sodiation or the addition of two carbons and a further unsaturation site. (Reprintedwith permission of Thermo Fisher Scientific © 2012.)

4.7 Proteomics

Judging from the publication activity since 2006, theOrbitrap-based systems have literally revolutionized thearea of mass spectrometry-based proteomics. The Orbi-trap instrumentation is capable of very fast data acquisi-tion while maintaining high resolution so important forcomplex mixture analyses. Moreover, the availability ofmultiple fragmentation techniques—an ion trap CID,a quadrupole-like HCD, and ETD—on a single plat-form has created a powerful and versatile proteomicsmachine.

The major area of development in near future could beexpected in automated data acquisition methods engagingan autonomous instrument-based decision making.Advanced instrument-based decisions beyond simpleData Dependent Acquisition™ and Dynamic Exclusion™are already employed in the ion trap/Orbitrap hybrids

with ETD capability.(17) The instrument decides aboutthe use of the most appropriate fragmentation techniquebased on criteria (in this particular case, the peptidecharge density) predefined in the acquisition method.Combining this with the ability of on-the-fly real-time database searching (e.g. the search result for agiven MS/MS spectrum is available to an on-boardcomputer before the decision about the type/settings ofthe following scan is taken) opens hitherto unimagin-able possibilities for intelligent data-directed acquisitionroutines.(102)

It would be pointless trying to collate literature reportsmentioning the use of the Orbitrap instruments forprotein identification and quantitation; they are far toonumerous and any such attempt would unavoidably beincomplete. Proteomics applications on Orbitrap systemshave been reviewed recently elsewhere.(103–105) Here,we simply cherry-picked publications highlighting the



capabilities of various Orbitrap platforms for a widerange of proteomics applications.

4.7.1 Protein Identification Studies

Protein identification has been the bread and butterof proteomics research. When using hybrid iontrap/Orbitrap instruments, most researchers took theadvantage of highly resolved/accurate measurements ofparent ions in the Orbitrap analyzer and complementedit with tandem mass spectra detected with high speed andsensitivity in a linear ion trap.(14,20) A systematic investi-gation of various MS settings on an LTQ Orbitrap massspectrometer empirically evaluated their influence andsignificance on peptide and protein identification ratesfor improving proteome analysis, providing a good guidefor optimized data acquisition settings.(106)

As the sensitivity and speed of acquisition increasedon more modern Orbitrap instruments, reports haveproliferated on using high-resolution detection also forMS/MS spectra.(11,22) Detecting product ions at higherresolution enables more efficient data base search,especially for modified peptides.(107)

Proteomes being so complex, methods of separatingintact proteins and/or peptides, combined with enzy-matic digestion, are usually included in the proteomicsworkflow.(108) Several separation techniques can belinked together providing a so-called multidimensionalLC approach.(109)

Even with the powerful arsenal of separation tech-niques at hand, the mass spectrometric analysis of anentire eukaryotic proteome has been, until recently,considered beyond reach. An effort capturing thecomplete yeast proteome demonstrated the feasibility ofsuch an undertaking.(110) The detected proteins spannedfour orders of magnitude in abundance and represented89% overlap with fused tandem affinity protein (TAP) orgreen fluorescent protein (GFP) tag genome-wide experi-ments. The authors later reanalyzed the same sample withmore recent Orbitrap systems and demonstrated that anear complete proteome analysis could be achieved in asingle LC/MS run.(111,112)

4.7.2 Peptidomics

Analysis of endogenous peptides complements the clas-sical proteomics approach. A combined study of thepeptidome and proteome of cerebrospinal fluid showedthe benefit of highly accurate mass measurements in bothMS and MS/MS modes, allowing unambiguous iden-tification of neuropeptides.(113) Other studies profiledendogenous peptides in human synovial fluid,(114) bioac-tive peptides arising from the proteolytic processing ofprecursor proteins in human neurons and endocrine

cells,(115) and neuropeptides from other species, suchas frogs, toads, and insects.(116) Sequences of nonribo-somal antibiotic peptides from Trichoderma atroviridewere derived from the reliable accuracy of mass measure-ment in MS/MS mode, where it was possible to excludethe presence of hydroxyproline residues (their mass beingvery close to that of isoleucine/leucine).(117)

4.7.3 Top-down Proteomics

High-resolution mass spectrometers are a powerful toolfor the characterization and monitoring of posttrans-lational modifications on intact proteins, the so-calledtop-down proteomics. A detailed evaluation of thetop-down capabilities of the most modern hybrid iontrap/Orbitrap system appeared recently.(11,118) The sameinstrument was also used for mapping intact proteinisofoms.(119)

Biotherapeutics (e.g. recombinant therapeuticproteins) have a growing importance within the pharma-ceutical industry. Recombinant monoclonal antibodiescan be heterogeneous as a result of modifications thatcan occur during expression, purification, or storage.Characterizing sites of modifications on these large multi-chain proteins can be very challenging. The OrbitrapMS has been used to obtain accurate average massesof individual glycoforms and to identify the site-specificmodification of methionines caused by oxidation.(120)

Orbitrap-based techniques for characterization of IgGdisulfide isoforms, glutamine and pyro-glutamate variantsof a heavy chain, and the glycosylation profile are nowwell described.(121,122)

Several points are worth noting about the Orbitrapperformance: glycoforms can be distinguished withbaseline resolution in the mass spectrum (see Figure 18)and for the light chain (approximate MW 23 kDa)an isotopic resolution can be obtained, enabling exactmonoisotopic mass determination of the species (seeFigure 19). Moreover, such analyses could be carried outin a true high-throughput manner with reversed-phaseLC coupled to the mass spectrometer.

In-source fragmentation enables a rapid characteriza-tion of variable regions of monoclonal antibodies.(123)

As no isolation of a precursor ion takes place in thesource, all charge states of a protein are being frag-mented at the same time, greatly improving the sensitivityof fragment ion detection over a true MS/MS experi-ment. Another strategy uses suitable enzymatic digestionprotocol to generate relatively large fragments of theoriginal protein and perform the so-called middle-downproteomics approach.(124)

Data interpretation is a complex issue as it has toaccommodate a multitude of modifications, mutations,insertions, and deletions characteristic of individual



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protein forms. A well-developed suite of tools forthe interpretation of high-resolution MS and MS/MSspectra relies on shotgun annotated peptide database(i.e. a peptide database incorporating all known protein-modifying events).(125) The software takes full advantageof the increased capabilities of the current generation ofthe Orbitrap-based mass spectrometers, requiring peptidefragmentation data with better than 5 ppm mass accuracy.

4.7.4 Posttranslational Modifications

Large-scale proteomics-based research is fundamentallychanging our understanding of signaling networks. MStechnology is now capable of delivering accurate andunbiased information about the quantitative changesof thousands of proteins and their modifications inresponse to any perturbation. Many studies so farfocused on phosphorylation, but acetylation, methylation,



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glycosylation, and ubiquitylation are also amenable tohigh throughput investigation.(126)

Phosphorylation is a key regulator of many eventsin eukaryotic cells. The relatively low abundanceof phosphopeptides calls for enrichment step(s) toimprove chances for their detection and characterization.Many thousands of phosphorylation sites can thenbe analyzed in a single experiment using hybrid iontrap-Orbitrap mass spectrometers after phosphopeptideenrichment.(127) These comprehensive data sets allow topinpoint conserved regulatory inputs or reveal kinase-substrate relationships.

Adding a quantitative dimension to the phospho-peptide identification experiments allows for studyingphosphorylation dynamics in the system. The dynamicphosphoproteome provides a missing link in a global, inte-grative view of cellular regulation.(128) The major advan-tage of following the temporal dynamics of phospho-sitesinstead of whole proteins is that signaling outcomescan be more directly connected to responsible upstreamor downstream events. These events are separated intime and were easily resolved in analysis. Probing

mitotic phosphorylation and phosphorylation events ofthe complete cell cycle in human cells were the nextanswered challenges.(129,130) Details capturing cascadesof multisite phosphorylation occurring at the onset of Sphase were reported recently.(131)

Kinase research, namely, their substrate specificity,activation state, and effect of specific kinase inhibitors,relies on assessing the impact of treating cells with specifickinase inhibitor.(132) A multiplexed, mass-spectrometry-based in vitro kinase assay has been devised to measurethe activation state of many kinases from the same celllysate.(133) This approach concurrently measured up to90 site-specific peptide phosphorylation rates, reportinga diagnostic fingerprint for activated kinase pathways ina variety of cellular settings. Further refinement of thisapproach and its adaptation to a 96-well plate format withan end-point detection on the benchtop Orbitrap systemhas been reported recently.(134)

To pinpoint phosphotyrosine-containing peptides,several studies made use of a diagnostic phosphotyrosine(Tyr(p)) immonium ion (m/z 216.0426).(15,135)



The exact localization of the phosphate moietywithin the peptide can be challenging, and severaladvanced software tools have been developed for thatpurpose.(136–138) Nevertheless, manual interpretation ofthe fragmentation spectra is often called for to gain therequired confidence of assignment.

The situation complicates considerably when otherconcurrent modifications such as acetylation, methyla-tion, ubiquitination, or formylated lysine residues appearwithin the same protein, as in the case of histones. Distin-guishing between these modifications is not a trivial task.For instance, a peptide modification with a nominal massincrement of +28 u could be assigned to either dimethyl-lysine (+28.031300 u), formyl-lysine (+27.994915 u), ora mutation of lysine to arginine (+28.00615 u). Reliablemass measurement on the Orbitrap system with sub-partsper million accuracy proved extremely useful for suchchallenging situations, in this particular case assigning anovel N,N-ε-dimethyl-lysine modification in the receptormolecule.(139)

Proteome-wide studies that used the Orbitrap-based instrumentation also focused on acetylation,(140)

palmitoylation,(141) or determination of the extent ofarginine methylation on peptides in relatively complexmixtures.(142) Other modifications studied in the contextof particular proteins of interest include, for instance,S-nitrosylation.(143)

Glycosylation represents another large subset ofposttranslational modification that plays crucial roles invarious biochemical processes, ranging from mediation ofinteractions between cells to defining cellular identitieswithin complex tissues.(144,145) However, because of thecomplex nature of glycans, structural characterization ofglycopeptides remains analytically challenging. CID, theworkhorse for conventional proteomics, has proved tobe very limiting when targeting intact glycopeptides.(146)

This is primarily because of the preference for glycosidicbond cleavages over peptidic bonds during fragmentation.Additionally, CID cleaves the peptide–glycan bondresulting in the loss of information regarding theglycosylation site.

Researchers have been content with obtaining partialinformation about the peptide sequence and site ofglycosylation, and foregoing any information about theattached glycans to circumvent this issue. For example,when dealing with N-linked glycopeptides, glycansare released with the enzyme peptide-N-glucosidaseF (PNGaseF), converting asparagine at the site ofglycosylation to aspartic acid. The conversion processcan then be monitored by high-resolution, accurate massinstruments, such as Orbitraps, to identify the site ofglycosylation and sequence the peptide. The glycanrelease by PNGasF could be performed in the presenceof H2

18O, resulting in a much larger mass shift of 2.9898

Da on the asparagine residues. The potential pitfall ofsuch approach is that a spontaneous deamidation canoccur during sample preparation, which can emulatethe site of glycosylation.(147) To date, a number oflarge-scale proteome-wide studies have been reportedfor N-linked glycopeptides using the earlier-describedapproach.(148–151)

The issue of spontaneous deamidation mentionedearlier underlines the importance of intact glycopeptidesstructural analysis. With the introduction of ETD, theglycopeptide research could make use of a remarkableproperty of this nonergodic fragmentation process,namely the retention of fragile glycan moiety on thepeptide backbone. This provides the ultimate proof forconfident site localization of the modification within thepeptide sequence.(152) Furthermore, ETD fragmentationhas benefitted O-linked glycopeptides tremendously asa result of the lack of enzymes similar to PNGaseF. Anumber of studies have reportedly shown the benefit ofETD fragmentation available on the ion trap-orbitraphybrid instruments.(153–159)

More recently, strategies for analyzing glycopeptidesmake use of an interplay of different fragmentationtechniques (CID, HCD, and ETD) available onhybrid ion trap/Orbitrap systems. Although HCDand CID are limited in terms of peptide information,they do provide informative fragmentation used toascertain glycan composition. Combining either ofthese fragmentations with ETD enables compre-hensive structural elucidation.(160,161) In the mostrecent approach to analyzing complex glycoproteomedigests, an advanced acquisition control engagingHCD and ETD has been implemented on the iontrap/Orbitrap instruments. This novel acquisitionstrategy termed ‘‘higher energy collisional dissociation-accurate mass product-dependent–electron transferdissociation’’ (HCD-PD-ETD) enables on the flyidentification of glycopeptides and acquires data only forglycopeptides precursors.(162–164) The HCD-PD-ETDapproach taps into the ability of HCD fragmentationto generate diagnostic glycan oxonium ions fromglycopeptides, and the subsequent ETD spectra beingtriggered for the same precursor only when thesediagnostic ions are seen in the HCD spectrum. Suchan approach streamlines data analysis while simultane-ously improving dynamic range and duty cycle of theanalysis.

High-field asymmetric waveform ion mobility spec-trometry has provided a powerful orthogonal separationmethod to chromatography and mass spectrometry.The usefulness of coupling FAIMS to Orbitrap-basedinstruments has been shown by a number of groups,maximizing peptide identification.(165–167) Recent studies



have focused on applications of FAIMS to separation andidentification of isomeric glycopeptides.(168)

Because of the complexity of glycan structures, struc-tural elucidation is performed on their release froma protein. Typically, derivatization is undertaken toovercome the weak acidity/basicity of most N- andO-linked glycans before MS analysis. Strategies employedto obtain detailed structural information about glycansrely heavily on the capability of an ion trap portion of thehybrid Orbitrap instruments to perform multiple levels offragmentation.(169–171) Workflows focusing on combiningpermethylation and multistage fragmentation (MSn) havebeen developed for glycan analysis. This strategy enablesdetailed determination of glycan linkage and branchinginformation important for structural isomer differenti-ation. Stumpo et al.(172) have employed this approachto perform global analysis of N-glycome in humanplasma.

Methods coupling HPLC to Orbitrap/MS have alsoinvolved fluorescence labeling at the reducing ends byreductive amination, as shown for analysis of recombinantproteins used as biopharmaceuticals.(173)

The Orbitrap-based instrumentation was used toaddress a host of biological questions relying on itsability to perform a thorough glycan analysis.(174–180)

Incorporating stable isotopes, either during the growth ofcultured cells (metabolic labeling) or in a reaction withstable-isotope reagents, opens the possibility to performrelative quantitation of glycans.(181,182)

4.7.5 Quantitative Analysis of Proteomes

Quantitative analysis has become an integral part ofmost proteomic studies. There are many choices ofmethods involving isotope labels for relative proteinand peptide quantitation. Methods relying on precursorion quantitation (detection in full scan MS) include avery popular stable isotope labeling by amino acids inculture (SILAC)(183) method and its refinements (super-SILAC),(184) incorporation of heavy oxygen during anenzymatic digestion step (18O labeling),(185) and a hostof approaches relying on incorporation of an isotopiclabel via a reaction with a chemical agents (e.g.dimethylation).(186)

Another very popular set of methods for relativepeptide quantitation is using isobaric labeling tags andrelies on the detection of reporter ions in low m/z rangeof the mass spectrum.(187,188) Very good resolution atlow mass range is required to eliminate any poten-tial interferences. Moreover, the coisolation of otherpeptides with the peptide of interest in the processof MS/MS spectrum generation leads to decreasedquantitative accuracy of these techniques. This partic-ular problem can be only partly circumvented by

narrowing down the precursor isolation width, partiallytrading off the sensitivity of the assay. Two Orbitrap-based methods appeared recently addressing thisproblem.(189,190)

Improvements in mass spectrometry and chromato-graphic techniques underlie the practicality of a label-freequantitation approach. The credibility of this approachdepends largely on a proper experimental design incor-porating controls at multiple steps during the samplecollection, preparation, and analysis processes.(191) Quan-titative comparisons become feasible and economicallyattractive on the scales of whole proteomes.(192)

Targeted absolute quantitation of peptides is afast developing field. Triple quadrupole instrumentsoperated in SRM mode have been traditionally usedfor this purpose. MS/MS data from hybrid Orbitrapmass analyzers represent a useful starting point toconfigure SRM assays on triple quadrupoles, thusgreatly expediting the development of downstream, high-throughput targeted SRM assays.(193,194)

Two major challenges are, however, associated withthe SRM-based approach. First, the number of peptidesto be included in one survey experiment needs tobe increased to routinely reach several hundreds, andsecondly, the degree of selectivity should be improvedto reliably discriminate the targeted analytes frombackground interferences. High resolution and accuratemass analysis on the recently developed quadrupole-Orbitrap mass spectrometer seems to address theseissues.

A new targeted proteomics paradigm, parallel reactionmonitoring (PRM), is centered on the use of next-generation, quadrupole-equipped HRMS instruments. InPRM, the third quadrupole of a QqQ is substituted witha high-resolution mass analyzer to permit the paralleldetection of all target product ions in one, concertedhigh-resolution mass analysis. The analytical performanceof the PRM method performed on a quadrupole-equipped benchtop Orbitrap MS was compared toSRM.(195) In addition to requiring minimal upfrontmethod development and facilitating automated dataanalysis, PRM yielded quantitative data over a widerdynamic range than SRM in the presence of a yeastbackground matrix as a result of PRM’s high selectivity inthe mass-to-charge domain and detection of all fragmentsin parallel. Achievable linearity over the quantifiabledynamic range was found to be statistically equal betweenthe two methods.

Similar results were reported when applying thesame quadrupole-Orbitrap platform to targeted proteinquantification in urine samples.(196) The instrumentexhibited comparable or better performances in termsof selectivity, dynamic range, and sensitivity. Themultiplexing capability of the instrument enables to



design novel acquisition methods and apply them to largetargeted proteomic studies, as demonstrated in a proof-of-concept study monitoring 770 peptides within a 60-minexperiment.

4.8 Oligonucleotide Analysis

Employing ESI for mass spectrometric analysis ofoligonucleotides allows for an easy coupling betweenLC and MS. Using LC before mass spectrometricdetection has multiple benefits; it effectively removessalts (Na+ and K+), minimizes heterogeneous adducts(with alkali metals), separates oligonucleotides accordingto their chain length, and causes a relative increasein concentration, thus boosting the assay sensitivity.Analysis is usually performed in negative ionizationmode where superior signal intensity is observed foroligonucleotides. Often, ion-pairing reagents such ashexylammonium acetate (HAA), 1,1,1,3,3,3-hexafluoro-2-propanol (HFIP), or triethylamine (TEA) are used,which are volatile and do not suppress the ion signal inMS.

High-resolution analysis of oligonucleotides withthe Orbitrap instrumentation provides accurate massmeasurement of monoisotopic species, calculated withthe same tolerance limits normally associated with smallmolecules.(197) Adequately high resolution can distinguishtwo possible metabolite sequences.(198) Fragmentationvia CID yields sequence of the oligonucleotides enablingunambiguous reliable metabolite identification in a moreautomated manner.

Using sequential MS3 experiments, analysis of DNAand RNA on a hybrid ion trap-Orbitrap mass spec-trometer afforded extensive information on adductsformed by the reaction of active metabolites of hete-rocyclic aromatic amines with deoxynucleosides, andon oligonucleotide analogs (2’-O-Me; phosphorothioate;20-mer).(199,200) Base losses could be assigned in suchhigh-resolution fragmentation spectra. Applying a lowvoltage just after the source region efficiently removesunwanted adducts (HAA).

5 FUTURE OF THE ORBITRAPTECHNOLOGY

As versatility and power of Orbitrap instruments grows,the analyzer remains their heart and still determinesbasic analytical performance. Therefore, it is importantto exemplify some potential improvements of thetechnology:

• Analyzer Design: Multielectrode (or overtone) trapwould allow to increase resolving power over the same

time, for example, 3× when two pairs of detectionelectrodes are used instead of the current one pair.However, such detection at third harmonic doescome at the expense of sensitivity (about threefoldreduction). With appropriate layout, it is possibleto combine several Orbitrap analyzers into a singleintegrated analyzer with several traps operating inparallel in an overlapping manner and providingproportional increase in speed and dynamic range.Further improvement of manufacturing accuracyopens potential of routinely achieving ultrahighresolving power in excess of 106 for applications inpetroleomics and analysis of fine isotopic structure.

• Data-processing Methods: New processing methods,such as filter diagonalization method (FDM), couldpotentially be used to circumvent the Nyquist limitof Fourier transform, thus yielding higher resolvingpower over the same transient length.(201) However,notorious numerical artifacts of this or other non-FT methods still remain an obstacle to realizing thispotential.

• Methods of Operation: The presence of a beam-type mass filter(22) allows us to accumulate ionsintelligently by enhancing certain m/z ranges by‘‘focused investment’’ and/or selecting peaks ofinterest in any desired combination. All selected peakscould then be acquired in a single Orbitrap spectrum(the so-called spectrum multiplexing). This approachis particularly promising for targeted mass analysis,with multiple SIM or MRM acquired in a singleOrbitrap spectrum. Besides, it could be also usedto combine multiple fragmentation techniques and/orconditions in one spectrum (e.g. HCD energy scan).For example, the selection of multiple charge statesof the same precursor, each fragmented at optimumconditions, could be used to increase sequencecoverage. Data-independent as well as multisegmentwide mass range acquisition could also be developedon the basis of this method.

6 CONCLUSION

The Orbitrap mass analyzer has become a powerfuladdition to the arsenal of mass spectrometric techniquesfor probing biological systems as well as for increasingselectivity and confidence of routine analyses. TheOrbitrap analytical performance can support a wide rangeof applications from routine compound identificationto the analysis of trace-level components in complexmixtures, be it in proteomics, drug metabolism, dopingcontrol, or detection of contaminants in food and feed.



The Orbitrap technology will continue to evolvetoward increased acquisition speed, higher resolvingpower, mass accuracy, and sensitivity. This evolution willundoubtedly give rise to exciting new applications as theOrbitrap instruments are becoming more widespread andpenetrate into new areas of research.

ACKNOWLEDGMENTS

The authors thank scientists from Thermo FisherScientific, namely Patrick Bennett, Eugen Damoc,Markus Kellmann, Olaf Scheibner, Julian Saba, and GaryWoffendin, who provided data, spectra, and graphics usedin many figures throughout this article. This work wassupported by the European Commission’s 7th FrameworkProgram PROteomics SPECification in Time and Space(PROSPECTS, HEALTH–F4–2008–021,648).

ABBREVIATIONS AND ACRONYMS

ADME Absorption, Distribution,Metabolism, and Excretion

AGC Automatic Gain ControlAPI Atmospheric-Pressure IonCID Collision-Induced DissociationDART Direct Analysis In Real TimeDESI Desorption Electrospray IonizationDMPK Dystrophia Myotonica Protein KinaseeFT Enhanced Fourier TransformESI Electrospray IonizationETD Electron Transfer DissociationFAIMS High-Field Asymmetric Waveform

Ion Mobility SpectrometryFT ICR Fourier Transform Ion Cyclotron

ResonanceFWHM Full Width at Half MaximumGFP Green Fluorescent ProteinHAA Hexylammonium AcetateHCD-PD-ETD Higher Energy Collisional

Dissociation-Accurate MassProduct-Dependent–ElectronTransfer Dissociation

HCD Higher Collision Energy DissociationHFIP 1,1,1,3,3,3-Hexafluoro-2-PropanolHILIC Hydrophilic Interaction

ChromatographyHRMS High-Resolution Mass SpectrometryICP Inductively Coupled PlasmaIRMPD Infrared Multiphoton Dissociation

LC Liquid ChromatographyLDTD Laser Diode Thermal DesorptionLOD Limit Of DetectionLOQ Limit Of QuantificationMALDI Matrix-Assisted Laser Desorption

And IonizationMS/MS Tandem Mass SpectrometryPAMPA Parallel Artificial Membrane

Permeability AssayPNGaseF Peptide-N-Glucosidase FPRM Parallel Reaction MonitoringRF Radio Frequencyrms Root-Mean-SquareSILAC Stable Isotope Labeling by Amino

Acids in CulturesiRNA Small Interfering Ribonucleic AcidSRM Selected Reaction MonitoringTAP Tandem Affinity ProteinTEA TriethylamineUHPLC Ultrahigh-Performance Liquid

Chromatography

RELATED ARTICLES

Desorption Electrospray Ionization Mass Spectrometry

Direct Analysis in Real-time Ion Source

Mass Spectrometry (Volume 13)Fourier Transform Ion Cyclotron Resonance MassSpectrometry • High-resolution Mass Spectrometry andits Applications • Time-of-flight Mass Spectrometry

REFERENCES

1. K.H. Kingdon, ‘A Method for the Neutralization ofElectron Space Charge by Positive Ionization at VeryLow Gas Pressures’, Phys. Rev., 21, 408–418 (1923).

2. R.H. Perry, R.G. Cooks, R.J. Noll, ‘Orbitrap Mass Spec-trometry: Instrumentation, Ion Motion and Applications’,Mass Spectrom. Rev., 27, 661– 699 (2008).

3. M.I. Korsunskii, V.A. Basakutsa, ‘A Study of the Ion-optical Properties of a Sector-shaped Electrostatic Fieldof the Difference Type’, Soviet Physics-Tech. Phys., 3,1396 (1958).

4. R.D. Knight, ‘Storage of Ions from Laser-producedPlasmas’, Appl. Phys. Lett., 38, 221–222 (1981).

5. A.A. Makarov, ‘Mass Spectrometer’ US Pat. 5,886,346,1999.



6. A.A. Makarov, ‘Electrostatic Axially Harmonic OrbitalTrapping: A High-performance Technique of MassAnalysis’, Anal. Chem., 72, 1156–1162 (2000).

7. A.G. Marshall, F.R. Verdun, Fourier transforms in NMR,optical, and mass spectrometry: A user’s handbook;Elsevier: Amsterdam, 1990.

8. M. Hardman, A.A. Makarov, ‘Interfacing the OrbitrapMass Analyzer to an Electrospray Ion Source’, Anal.Chem., 75, 1699–1705 (2003).

9. Q. Hu, R.J. Noll, H. Li, A. Makarov, M. Hardman, R.G,Cooks, ‘The Orbitrap: A New Mass Spectrometer’, J.Mass Spectrom.., 40, 430–443 (2005).

10. A. Makarov, E. Denisov, A. Kholomeev, W. Balschun,O. Lange, K. Strupat, S. Horning, ‘Performance Eval-uation of a Hybrid Linear ion Trap/Orbitrap MassSpectrometer’, Anal. Chem., 78, 2113–2120 (2006).

11. A. Michalski, E. Damoc, O. Lange, E. Denisov, D.Nolting, M. Mueller, R. Viner, J. Schwartz, P. Remes,M. Belford, J.J. Dunyach, J. Cox, S. Horning, M. Mann,A. Makarov, ‘Ultra High Resolution Linear ion TrapOrbitrap Mass Spectrometer (Orbitrap Elite) Facili-tates Top Down LC MS/MS and Versatile PeptideFragmentation Modes’, Mol. Cell. Proteomics, 11,doi:10.1074/mcp.O111.013698 (2012).

12. E. Denisov, E. Damoc, O. Lange, A. Makarov, ‘OrbitrapMass Spectrometry with Resolving Powers Above1,000,000’, Int. J. Mass Spectrom., 325–327, 80–85 (2012).

13. A. Makarov, Theory and Practice of the OrbitrapMass Analyzer. Practical Aspects of Trapped Ion MassSpectrometry. Chapter 3, Vol. IV, Eds. R.E. March, J.F.J.Todd, CRC Press., 2010, pp. 249–270.

14. J.V. Olsen, L.M. de Godoy, G. Li, B. Macek,P. Mortensen, R. Pesch, A.A. Makarov, O. Lange,S. Horning, M. Mann, ‘Parts Per Million Mass Accuracyon an Orbitrap Mass Spectrometer via Lock Mass Injec-tion into a C-trap’, Mol. Cell. Proteomics, 4, 2010–2021(2005).

15. J.V. Olsen, B. Macek, O. Lange, A. Makarov, S. Horning,M. Mann, ‘Higher-energy C-trap Dissociation for PeptideModification Analysis’, Nat. Methods, 4, 709–712 (2007).

16. G. McAlister, W. Berggren, J. Griep-Raming, S. Horning,A. Makarov, D. Phanstiel, G. Stafford, D. Swaney,J. Syka, V. Zabrouskov, J. Coon, ‘A Proteomics GradeElectron Transfer Dissociation-enabled Hybrid LinearIon Trap-Orbitrap Mass Spectrometer’, J. Proteome Res.,7, 3127–3136 (2008).

17. D.L. Swaney, G.C. McAlister, J.J. Coon, ‘DecisionTree-driven Tandem Mass Spectrometry for ShotgunProteomics’, Nat. Methods, 5, 959–964 (2008).

18. K. Strupat; V. Kovtoun, H. Bui, R. Viner, G. Stafford,S. Horning, ‘MALDI Produced Ions Inspected with aLinear Ion Trap—Orbitrap Hybrid Mass Analyzer’, J.Am. Soc. Mass Spectrom., 20, 1451–1463 (2009).

19. M. Scigelova, A. Makarov, ‘Advances in BioanalyticalLC-MS Using the Orbitrap Mass Spectrometer’, Bioanal-ysis, 1, 741–754 (2009).

20. J.V. Olsen, J.C. Schwartz, J. Griep-Raming, M.L. Nielsen,E. Damoc, E. Denisov, O. Lange, P. Remes, D. Taylor,M. Splendore, E.R. Wouters, M. Senko, A. Makarov,M. Mann, S. Horning, ‘A Dual Pressure Linear ion TrapOrbitrap Instrument with very High Sequencing Speed’,Mol. Cell. Proteomics, 8, 2759–2769 (2009).

21. K.P. Bateman, M. Kellmann, H. Muenster, R. Papp,L. Taylor, ‘Quantitative–Qualitative Data AcquisitionUsing a Benchtop Orbitrap Mass Spectrometer’, J. Am.Soc. Mass Spectrom., 20, 1441–1450 (2009).

22. A. Michalski, E. Damoc, J.P. Hauschild, O. Lange, A.Wieghaus, A. Makarov, N. Nagaraj, J. Cox, M. Mann,S. Horning, ‘Mass Spectrometry-based Proteomics UsingQ Exactive, a High-performance Benchtop QuadrupoleOrbitrap Mass Spectrometer’, Mol. Cell. Proteomics, 10,M111.011015 (2011).

23. A. Kaufmann, P. Butcher, K. Maden, S. Walker,M. Widmer, ‘Semi-targeted Residue Screening inComplex Matrices with Liquid Chromatography Coupledto High Resolution Mass Spectrometry: Current Possibil-ities and Limitations’, Analyst, 136, 1898–1909 (2011).

24. N. Cortes-Francisco, C. Flores, E. Moyano, J. Caixach,‘Accurate Mass Measurements and Ultrahigh-resolution:Evaluation of Different Mass Spectrometers for DailyRoutine Analysis of Small Molecules in NegativeElectrospray Ionization Mode’, Anal. Bioanal. Chem.,400, 3595–3606 (2011).

25. A. Kaufmann, P. Butcher, K. Maden, S. Walker,M. Widmer, ‘Comprehensive Comparison of LiquidChromatography Selectivity as Provided by Two Typesof Liquid Chromatography Detectors (High ResolutionMass Spectrometry and Tandem Mass Spectrometry):’Where is the Crossover Point?’ Anal. Chim. Acta, 673,60–72 (2010).

26. R. Alkhatib, T. Hennebelle, S. Joha, V. Roumy, Y. Guzel,M. Biabiany, T. Idziorek, C. Preudhomme, B. Quesnel,S. Sahpaz, F. Bailleul, ‘Humulane and GermacraneSesquiterpenes from Ferula lycia’, J. Nat. Prod., 73,780–783 (2010).

27. M.-L. Pesch, I. Christl, K. Barmettler, S.M. Kraemer,R. Kretzschmar, ‘Isolation and Purification of Cu-freeMethanobactin from Methylosinus trichosporium OB3b’,Geochem. Trans., 12, 2–9 (2011).

28. S. Yokojima, T. Kobayashi, K. Shinoda, K. Matsuda,K. Higashiguchi, S. Nakamura, ‘π-Conjugation of TwoNitronyl Nitroxides-attached Diarylethenes’, J. Phys.Chem., 115, 5685–5692 (2011).

29. X. Yan, T.O. Akinnusi, A.T. Larsen, K. Auclair,‘Synthesis of 4′-aminopantetheine and derivatives toprobe aminoglycoside N-6′-acetyltransferase’, Org.Biomol. Chem., 9, 1538–1546 (2011).



30. S. Harrison, K. Fraser, G. Lane, D. Hughes, S. Villas-Boas, S. Rasmussen, ‘Analysis of High-molecular-weightFructan Polymers in Crude Plant Extracts by High-resolution LC-MS’, Anal. Bioanal. Chem. 401, 2955–2963(2011).

31. Y. Wang, N. Kumar, L.A. Solt, T.I. Richardson, L.M.Helvering, C. Crumbley, R.D. Garcia-Ordonez, K.R.Stayrook, X. Zhang, S. Novick, M.J. Chalmers, P.R.Griffin, T.P. Burris, ‘Modulation of Retinoic AcidReceptor-related Orphan Receptor α and γ Activityby 7-oxygenated Sterol Ligands’, J. Biol. Chem. 285,5013–5025 (2011).

32. L. Alder, A. Steinborn, S. Bergelt, ‘Suitability ofan Orbitrap Mass Spectrometer for the Screening ofPesticide Residues in Extract of Fruits and Vegetables’,J. AOAC Intl. 94, 1–13 (2011).

33. M. Kellmann, H. Muenster, P. Zomer, H. Mol, ‘FullScan MS in Comprehensive Qualitative and QuantitativeResidue Analysis in Food and Feed Matrices: Howmuch Resolving Power is Required?’ J. Am. Soc. MassSpectrom., 20, 1464–1476 (2009).

34. H.G.J. Mol, R.C.J. Van Dam, P. Zomer, P.P.J. Mulder,‘Screening of Plant Toxins in Food, Feed and BotanicalsUsing Full-scan High-resolution (Orbitrap) Mass Spec-trometry’, Food Addit. Contam., 28, 1405–1423 (2011).

35. T. Bernsmann, P. Fuerst, M. Godula, ‘Quick Screeningof Priority β-agonists in Urine Using AutomatedTurboFlowTM-LC/Exactive Mass Spectrometry’, FoodAddit. Contam., 28, 1352–1363 (2011).

36. Y. Shi, J.S. Chang, C.L. Esposito, C. Lafontaine,M.J. Berube, J.A. Fink, F.A. Espourteille, ‘RapidScreening for Pesticides Using Automated Online SamplePreparation with a High-resolution Benchtop OrbitrapMass Spectrometer’, Food Addit. Contam., 28, 1383–1392(2011).

37. R. Self, W.-H. Wu, H.S. Marks, ‘Simultaneous Quan-tification of Eight Biogenic Amine Compounds in Tunaby Matrix Solid-phase Dispersion Followed by HPLC-Orbitrap Mass Spectrometry’, J. Agric. Food Chem., 59,5906–5913 (2011).

38. P. Blay, J.P.M. Hui, J. Chang, J.E. Melanson, ‘Screeningfor Multiple Classes of Marine Biotoxins by LiquidChromatography-high-resolution Mass Spectrometry’,Anal. Bioanal. Chem., 400, 577–585 (2011).

39. M. Zachariasova, T. Cajka, M. Godula, A. Malachova,Z. Veprikova, J. Hajslova, ‘Analysis of Multiple Myco-toxins in Beer Employing (ultra)-high-resolution MassSpectrometry’, Rapid Commun. Mass Spectrom., 24,3357–3367 (2010).

40. H. Nakagawa, K. Ohmichi, S. Sakamoto, Y. Sago,M. Kushiro, H. Nagashima, M. Yoshida, T. Nakajima,‘Detection of a New Fusarium Masked Mycotoxin inWheat Grain by High-resolution LC-Orbitrap MS’, FoodAddit. Contam., 28, 1447–1456 (2011).

41. S.E. Edison, L.A. Lin, B.M. Gamble, J. Wong, K. Zhang,‘Surface Swabbing Technique for the Rapid Screeningfor Pesticides Using Ambient Pressure DesorptionIonization with High-resolution Mass Spectrometry’,Rapid Commun. Mass Spectrom., 25, 127–139 (2011).

42. S.E. Edison, L.A. Lin, L. Parrales, ‘Practical Consid-erations for the Rapid Screening for Pesticides UsingAmbient Pressure Desorption Ionization with High-resolution Mass Spectrometry’, Food Addit. Contam.,28, 1393–1404 (2011).

43. L. Vaclavik, M. Zachariasova, V. Hrbek, J. Hajslova,‘Analysis of Multiple Mycotoxins in Cereals UnderAmbient Conditions Using Direct Analysis in Real Time(DART) Ionization Coupled to High Resolution MassSpectrometry’, Talanta, 82, 1950–1957 (2010).

44. T. Cajka, K. Riddellova, P. Zomer, H. Mol, J. Hajslova,‘Direct Analysis of Dithiocarbamate Fungicides in Fruitby Ambient Mass Spectrometry’, Food Addit. Contam.,28, 1372–1382 (2011).

45. D.P.T. Roberts, M.J. Scotter, M. Godula, M. Dickinson,A.J. Charlton, ‘Development and Validation of a RapidMethod for the Determination of Natamycin in Wine byHigh-performance Liquid Chromatography Coupled toHigh Resolution Mass Spectrometry’, Anal. Methods, 3,937-943(2011).

46. L. Monaci, I. Losito, F. Palmisano, M. Godula,A. Visconti, ‘Towards the Quantification of Residual MilkAllergens in Caseinate-fined White Wines Using HPLCCoupled with Single-stage Orbitrap Mass Spectrometry’,Food Addit. Contam., 28, 1304–1314 (2011).

47. L. Monaci, I. Losito, F. Palmisano, A. Visconti, ‘ReliableDetection of Milk Allergens in Food Using a High-resolution, Stand-alone Mass Spectrometer’, J. Assoc.Off. Anal. Chem. Int., 94, 1–9 (2011).

48. H. Gallart-Ayala, O. Nunez, E. Moyano, M.T. Galceran,C.P.B. Martins, ‘Preventing False Negatives with High-resolution Mass Spectrometry: The Benzophenone Case’,Rapid Commun. Mass Spectrom., 25, 3161–3166 (2011).

49. W. Mullen, S. Larcombe, K. Arnold, H. Welchman,A. Crozier, ‘Use of Accurate Mass Full Scan MassSpectrometry for the Analysis of Anthocyanins in Berriesand Berry-fed Tissues’, J. Agric. Food Chem., 58,3910–3915 (2010).

50. A.C. Hogenboom, J.A. van Leerdam, P. de Voogt,‘Accurate Mass Screening and Identification of EmergingContaminants in Environmental Samples by LiquidChromatography–Hybrid Linear Ion Trap Orbitrap MassSpectrometry’, J Chrom. A, 1216, 510–519 (2009).

51. J.A. van Leerdam, A.C. Hogenboom, M.M.E. vander Kooi, P. De Voogt, ‘Determination of Polar 1H-benzotriazoles and Benzothiazoles in Water by Solid-phase Extraction and Liquid Chromatography LTQ FTOrbitrap Mass Spectrometry’, Int. J. Mass Spectrom., 282,99–107 (2009).



52. M. Krauss, J. Hollender, ‘Analysis of Nitrosamines inWastewater: Exploring the Trace Level QuantificationCapabilities of a Hybrid Linear Ion Trap/Orbitrap MassSpectrometer’, Anal. Chem., 80, 834–842 (2008).

53. Z.H. Rivera, E. Oosterink, L. Rietveld, F. Schoutsen,L. Stolker, ‘Influence of Natural Organic Matter on theScreening of Pharmaceuticals in Water by Using LiquidChromatography with Full Scan Mass Spectrometry’,Anal. Chim. Acta, 700, 114–125 (2011).

54. S.M. Peterman, N. Duczak, A.S. Kalgutkar, M.E. Lame,J.R. Soglia, ‘Application of a Linear Ion Trap/OrbitrapMass Spectrometer in Metabolite CharacterizationStudies: Examination of the Human Liver MicrosomalMetabolism of the Non-tricyclic Anti-depressant Nefa-zodone Using Data-dependent Accurate Mass Measure-ments’, J. Am. Soc. Mass Spectrom., 17, 363–375 (2006).

55. J. Xing, Z. Yang, B. Lv, L. Xiang, ‘Rapid Screeningfor Cyclo-dopa and Diketopiperazine Alkaloids inCrude Extracts of Portulaca oleracea L. Using LiquidChromatography/Tandem Mass Spectrometry’, RapidCommun. Mass Spectrom., 22, 1415–1422 (2008).

56. A. Koulman, G. Woffendin, V.K. Narayana,H. Welchman, C. Crone, D.A. Volmer, ‘High-resolution Extracted Ion Chromatography, A NewTool for Metabolomics and Lipidomics Using aSecond-generation Orbitrap Mass Spectrometer’, RapidCommun. Mass Spectrom. 23, 1411–1418 (2009).

57. K. Bluemlein, A. Raab, A.A. Meharg, J.M. Charnock,J. Fledmann, ‘Can We Trust Mass Spectrometry forDetermination of Arsenic Peptides in Plants: Compar-ison of LC-ICP-MS and LC-ES-MS/ICP-MS withXANES/EXAFS in Analysis of Thunbergia alata’, Anal.Bioanal. Chem. 390, 1739–1751 (2008).

58. M. Dernovics, R. Lobinski, ‘Speciation Analysis ofSelenium Metabolites in Yeast-based food Supple-ments by ICPMS-assisted Hydrophilic Interaction HPLCHybrid Linear Ion Trap/Orbitrap MSn’, Anal. Chem., 80,3975–3984 (2008).

59. H.K. Lim, J. Chen, K. Cook, C. Sensenhauser, J. Silva,D.C. Evans, ‘A Generic Method to Detect ElectrophilicIntermediates Using Isotopic Pattern Triggered Data-dependent High-resolution Accurate Mass Spectrom-etry’, Rapid Commun. Mass Spectrom., 22, 1295–1311(2008).

60. F. Cuyckens, L.I.L. Balcaen, K. De Wolf, B. De Samber,C. Van Looveren, R. Hurkmans, F. Vanhaecke, ‘Use ofthe Bromine Isotope Ratio in HPLC-ICP-MS and HPLC-ESIMS Analysis of a New Drug in Development’, Anal.Bioanal. Chem., 390, 1717–1729 (2008).

61. W. Korfmacher, ‘High-Resolution Mass Spectrometrywill Dramatically Change our Drug-discovery BioanalysisProcedures’, Bioanalysis 3, 1169–1171 (2011).

62. R.L. Wong, X. Baomin, T. Olah, ‘Optimization of Exac-tive Orbitrap Acquisition Parameters for QuantitativeBioanalysis’, Bioanalysis, 3, 863–871 (2011).

63. K.P. Bateman, M. Kellmann, H. Muenster, R. Papp,L. Taylor, ‘Quantitative–Qualitative Data AcquisitionUsing a Benchtop Orbitrap Mass Spectrometer’, J. Am.Soc. Mass Spectrom., 20, 1441–1450 (2009).

64. B. Rochat, ‘Quantitative/Qualitative Analysis UsingLC–HRMS: The Fundamental Step Forward for Clin-ical Laboratories and Clinical Practice’, Bioanalysis 4,1709–1711 (2012).

65. N.R. Zhang, S. Yu, P. Tiller, S. Yeh, E. Mahan, W.B.Emary, ‘Quantitation of Small Molecules Using High-resolution Accurate Mass Spectrometers—A DifferentApproach for Analysis of Biological Samples’, RapidCommun. Mass Spectrom., 23, 1085–1094 (2009).

66. J. Zhang, J. Maloney, D.M. Drexler, X. Cai, J. Stewart, C.Mayer,J. Herbst, H. Weller, W.Z. Shou, ‘Cassette Incu-bation Followed by Bioanalysis Using High-resolutionMS for in vitro ADME Screening Assays’, Bioanalysis,4, 581–593 (2012).

67. E. Werner, V. Croixmarie, T. Umbdenstock, E. Ezan,P. Chaminade, J.C. Tabet, C. Junot, ‘Mass Spectrometry-based Metabolomics: Accelerating the Characterizationof Discriminating Signals by Combining StatisticalCorrelations and Ultrahigh Resolution’, Anal. Chem.,80, 4918–4932 (2008).

68. H.K. Lim, J. Chen, C. Sensenhauser, K. Cook, V. Subra-manyam, ‘Metabolite Identification by Data-dependentAccurate Mass Spectrometric Analysis at ResolvingPower of 60,000 in External Calibration Mode Usingan LTQ/Orbitrap’, Rapid Comm. Mass Spectrom., 21,1821–1832 (2007).

69. M. Smith, C. Thickitt, ‘The Benefit of Sample Pretreat-ment and Use of MS10 on the Orbitrap for the Analysis ofPentasaccharides’, Rapid Commun. Mass Spectrom., 23,3018–3022 (2009).

70. H. Henry, H.R. Sobhi, O. Scheibner, M. Bromirski,S.B. Nimkar, B. Rochat, ‘Comparison between a High-resolution Single-stage Orbitrap and a Triple QuadrupoleMass Spectrometer for Quantitative Analyses of Drugs’,Rapid Commun. Mass Spectrom., 26, 499–509 (2012).

71. A.A. Franke, L.J. Custer, Y. Morimoto, F.J. Nordt,G. Maskarinec, ‘Analysis of Urinary Estrogens, theirOxidized Metabolites, and other Endogenous Steroidsby Benchtop Orbitrap LCMS versus TraditionalQuadrupole GCMS’, Anal. Bioanal. Chem., 401,1319–1330 (2011).

72. X. Li, A.A. Franke, ‘Improved LC-MS Method for theDetermination of Fatty Acids in Red Blood Cells byLC-Orbitrap MS’, Anal. Chem., 83, 3192–3198 (2011).



73. X. Li, A.A. Franke, ‘High-throughput and Cost-effective Global DNA Methylation Assay by LiquidChromatography-Mass Spectrometry’, Anal. Chim. Acta,703, 58–63 (2011).

74. Q. Ruan, Q.C. Ji, M.E. Arnold, W.G. Humphreys,M. Zhu, ‘Strategy and its Implications of ProteinBioanalysis Utilizing High-resolution Mass SpectrometricDetection of Intact Protein’, Anal. Chem. 83, 8937–8944(2011).

75. Y. Moulard, L. Bailly-Chouriberry, S. Boyer, P. Garcia,M.-A. Popot, Y. Bonnaire, ‘Use of benchtop ExactiveHigh Resolution and High Mass Accuracy Orbitrap MassSpectrometer for Screening in Horse Doping Control’,Anal. Chim. Acta, 700, 126–136 (2011).

76. M. Thevis, W. Schanzer, ‘Mass Spectrometry of SelectiveAndrogen Receptor Modulators’, J. Mass Spectrom., 43,865–876 (2008).

77. M. Thevis, A. Thomas, W. Schanzer, ‘Mass SpectrometricDetermination of Insulins and their Degradation Prod-ucts in Sports Drug Testing’, Mass Spectrom. Rev., 27,35–50 (2008).

78. E.D. Virus, T.G. Sobolevsky, G.M. Rodchenkov, ‘Intro-duction of HPLC/Orbitrap Mass Spectrometry asScreening Method for Doping Control’, J. Mass Spec-trom., 43, 949–957 (2008).

79. M. Kohler, A. Thomas, K. Walpurgis, W. Schanzer,M. Thevis, ‘Mass Spectrometric Detection of siRNA inPlasma Samples for Doping Control Purposes’, Anal.Bioanal. Chem., 398, 1305–1312 (2010).

80. S. Beuck, W. Bornatsch, A. Lagojda, W. Schanzer,M. Thevis, ‘Development of Liquid Chromatography-Tandem Mass Spectrometry-based analytical Assays forthe Determination of HIF Stabilizers in PreventiveDoping Research’, Drug Test. Analysis, 3, 756–770(2011).

81. E. van der Heeft, Y.J.C. Bolck, B. Beumer, A.W.J.M.Nijrolder, A.A.M. Stolker, M.W.F. Nielen, ‘Full-scanAccurate Mass Selectivity of Ultra-performance LiquidChromatography with Time-of-flight and Orbitrap MassSpectrometry in Hormone and Veterinary Drug ResidueAnalysis’, J. Am. Soc. Mass Spectrom., 20, 451–463 (2009).

82. S. Guddat, E. Solymos, A. Orlovius, A. Thomas,G. Sigmund, M. Geyer, M. Thevis, W. Schanzer,‘High-throughput Screening for Various Classes ofDoping Agents Using a New ‘dilute-and-shoot’ LiquidChromatography / Tandem Mass Spectrometry Multi-targeted Approach’, Drug Test. Analysis, 3, 836–850(2011).

83. W.J. Griffiths, M. Hornshaw, G. Woffendin, S.F. Baker,A. Lockhart, S. Heidelberger, M. Gustafsson, J. Sjorvall,Y. Wang, ‘Discovering Oxysterols in Plasma: a Windowon the Metabolome’, J. Proteome Res., 7, 3602–3612(2008).

84. G. Madalinski, E. Godat, S. Alves, D. Lesage, E. Genin,P. Levi, J. Labarre, J.C. Tabet, E. Ezan, C. Junot, ‘DirectIntroduction of Biological Samples into a LTQ-OrbitrapHybrid Mass Spectrometer as a Tool for Fast MetabolomeAnalysis’, Anal. Chem., 80, 3291–3303 (2008).

85. W. Lu, M.F. Clasquin, E. Melamud, D. Amador-Noguez,A.A. Caudy, J.D. Rabinowitz, ‘Metabolomics Analysisvia Reversed-phase ion-pairing Liquid ChromatographyCoupled to a Standalone Orbitrap Mass Spectrometer’,Anal. Chem., 82, 3212–3221 (2010).

86. J. Ding, C.M. Sorensen, Q. Zhang, H. Jiang, N. Jaitly, E.A.Livesay, Y. Shen, R.D. Smith, T.O. Metz, ‘Capillary LCCoupled with High-mass Measurement Accuracy MassSpectrometry for Metabolic Profiling’, Anal. Chem., 79,6081–6093 (2007).

87. A. Kamleh, M.P. Barrett, D. Wildridge, R.J.S. Burch-more, R.A. Scheltema, D.G. Watson, ‘MetabolomicProfiling Using Orbitrap Fourier Transform Mass Spec-trometry with Hydrophilic Interation Chromatography:A Method with Wide Applicability to Analysis ofBiomolecules’, Rapid Commun. Mass Spectrom., 22,1912–1918 (2008).

88. K.L. Olszewski, M.W. Mather, J.M. Morrisey, B.A.Garcia, A.B. Vaidya, J.D. Rabinowitz, M. Llinas,‘Branched Tricarboxylic Acid Metabolism in Plas-modium falciparum’, Nat. Lett., 466, 774–778 (2010).

89. J. Storm, J. Perner, I. Aparicio, E.-M. Patzewitz,K. Olszewski, M. Llinas, P.C. Engel, S. Muller, ‘Plas-modium falciparum Glutamate Dehydrogenase a isDispensable and not a Drug Target During ErythrocyticDevelopment’, Malaria J., 10:193 1–12 (2011).

90. D. Amador-Noguez, X.-J. Feng, J. Fan, N. Roquet,H. Rabitz, J.D. Rabinowitz, ‘Systems-level MetabolicFlux Profiling Elucidates a Complete Bifurcated Tricar-boxylic Acid Cycle in Clostridium acetobutylicum’, J.Bacteriol., 192, 4452–4461 (2010).

91. D. Schwudke, G. Lieblisch, R. Herzog, G. Schmitz,A. Shevchenko, ‘Shotgun Lipidomics by TandemMass Spectrometry Under Data-dependent AcquisitionControl’, Meth. Enzymol., 433, 175–191 (2007).

92. C.S. Ejsing, J.L. Sampaio, V. Surendranath, E. Duchoslav,K. Ekroos, R.W. Klemm, K. Simons, A. Shevchenko,‘Global Analysis of the Yeast Lipidome by QuantitativeShotgun Mass Spectrometry’, Proc. Natl. Acad. Sci. USA,106, 2136–2141 (2009).

93. B. Davis, G. Koster, L.J. Douet, M. Scigelova,G. Woffendin, J.M. Ward, A. Smith, J. Humphries,K.G. Burnand, C.H. Macphee, A.D. Postle, ‘ElectrosprayIonization Mass Spectrometry Identifies Substrates andProducts of Lipoprotein-associated Phospholipase A(2)in Oxidized Human Low Density Lipoprotein’, J. Biol.Chem., 283, 6428–6437 (2008).

94. J. Graessler, D. Schwudke, P.E.H. Schwarz, R. Herzog,A. Shevchenko, S.R. Bornstein, ‘Top-Down Lipidomics



Reveals Ether Lipid Deficiency in Blood Plasma ofHypertensive Patients’, PLoS One, 4, e6261 (2009).

95. D. Schwudke, J.T. Hannich, V. Surendranath,V. Grimard, T. Moehring, L. Burton, T. Kurzchalia,A. Shevchenko, ‘Top-down Lipidomic Screens byMultivariate Analysis of High-resolution Survey MassSpectra’, Anal. Chem., 79, 4083–4093 (2007).

96. K. Schuhmann, R. Herzog, D. Schwudke, W. Metelmann-Strupat, S.R. Bornstein, A. Shevchenko, ‘Bottom-upShotgun Lipidomics by Higher Energy CollisionalDissociation on LTQ Orbitrap Mass Spectrometers’,Anal. Chem., 83, 5480–5487 (2011).

97. K. Schuhmann, R. Almeida, M. Baumert, R. Herzog,S.R. Bornstein, A. Shevchenko, ‘Shotgun Lipidomicson a LTQ Orbitrap Mass Spectrometer by SuccessiveSwitching Between Acquisition Polarity Modes’, J. MassSpectrom. 47, 96–104 (2012).

98. S.S. Bird, V.R. Marur, M.J. Sniatynski, H.K. Greenberg,B.S. Kristal, ‘Serum Lipidomics Profiling Using LC-MSand High Energy Collisional Dissociation Fragmentation:Focus on Triglyceride Detection and Characterization’,Anal. Chem. 83, 6648–6657 (2011).

99. S.S. Bird, V.R. Marur, I.G. Stavrovskaya, B.S. Kristal,‘Qualitative Characterization of the Rat Liver Mitochon-drial Lipidome Using LC–MS Profiling and High EnergyCollisional Dissociation (HCD) all Ion Fragmentation’,Metabolomics 8, doi 10.1007/s11306-012-0400-1 (2012).

100. S.S. Bird, V.R. Marur, M.J. Sniatynski, H.K. Greenberg,B.S. Kristal, ‘Lipidomics Profiling by High-resolutionLC-MS and High-energy Collisional Dissociation Frag-mentation: Focus on Characterization of MitochondrialCardiolipins and Monolysocardiolipins’, Anal. Chem., 83,940–949 (2011).

101. K. Karu, M. Hornshaw, G. Woffendin, K. Bodin,M. Hamberg, G. Alvelius, J. Sjovall, J. Turton,Y. Wang, W.J. Griffiths, ‘Liquid Chromatography-MassSpectrometry Utilizing Multi-stage Fragmentation for theIdentification of Oxysterols’, J. Lipid Res., 48, 976–987(2007).

102. D.J. Bailey, C.M. Rose, G.C. McAlister, J. Brumbaugh,P. Yu, C.D. Wenger, M.S. Westphall, J.A. Thomson,J.J. Coon, ‘Instant Spectral Assignment for AdvancedDecision tree-driven Mass Spectrometry’, Proc. Natl.Acad. Sci. USA, 109, 8411–8416 (2012).

103. X. Han, A. Aslanian, J.R. Yates 3rd, ‘Mass Spectrometryfor Proteomics’, Curr. Opin. Chem. Biol., 12, 483–490(2008).

104. M. Mann, N.L. Kelleher, ‘Precision Proteomics: The Casefor High Resolution and High Mass Accuracy’, Proc. Natl.Acad. Sci. USA, 105, 18132–18138 (2008).

105. R.H. Perry, R.G. Cooks, R.J. Noll, ‘Orbitrap Mass Spec-trometry: Instrumentation, Ion Motion and Applications’,Mass Spectrom. Rev., 27, 661–669 (2008).

106. A. Kalli, S. Hess, ‘Effect of Mass SpectrometricParameters on Peptide and Protein Identification Ratesfor Shotgun Proteomic Experiments on an LTQ-orbitrapMass Analyzer’, Proteomics, 12, 1–11 (2011).

107. A. Scherl, S.A. Shaffer, G.K. Taylor, P. Hernandez, R.D.Appel, P.A. Binz, D.R. Goodlett, ‘On the Benefits ofAcquiring Peptide Fragment Ions at High MeasuredMass Accuracy’, J. Am. Soc. Mass Spectrom., 19, 891–901(2008).

108. J.R. Wisnievski, A. Zougman, N. Nagaraj, M. Mann,‘Universal Sample Preparation Method for ProteomeAnalysis’, Nat. Methods, 6, 359–362 (2009).

109. A. Makarov, M. Scigelova, ‘Coupling Liquid Chromatog-raphy to Orbitrap Mass Spectrometry’, J. Chrom. A, 1217,3938–3945 (2010).

110. L.M.F. de Godoy, J.V. Olsen, J. Cox, M.L. Nielsen, N.C.Hubner, F. Frohlich, T.C. Walther, M. Mann, ‘Compre-hensive Mass-spectrometry-based Proteome Quantifica-tion of Haploid Versus Diploid Yeast’, Nature, 455,1251–1254 (2008).

111. S.S. Thakur, T. Geiger, B. Chatterjee, P. Bandilla,F. Frohlich, J. Cox, M. Mann, ‘Deep and HighlySensitive Proteome Coverage by LC-MS/MS WithoutPre-fractionation’, Mol. Cell. Proteomics, 10, 1–9doi:10.1074/mcp.M110.003699 (2011).

112. N. Nagaraj, N.A. Kulak, J. Cox, N. Neuhauser,K. Mayr, O. Hoerning, O. Vorm, M. Mann, ‘Systems-widePerturbation Analysis with Near Complete Coverage ofthe Yeast Proteome by Single-shot UHPLC Runs ona Bench-top Orbitrap’, Mol. Cell. Proteomics, 11, 1–11doi:10.1074/mcp.M111.013722 (2012).

113. A. Zougman, B. Pilch, M. Kiehntopf, C. Schnabel,C. Kumar, M. Mann, ‘Integrated Analysis of the Cere-brospinal Fluid Peptidome and Proteome’, J. ProteomeRes., 7, 386–399 (2008).

114. J.J. Kamphorst, R. van der Heijden, J. DeGroot, F.P.J.G.Lafeber, T.H. Reijmers, B. van Ei, U.R. Tjaden, J. van derGreef, T. Hankemeier, ‘Profiling of Endogenous Peptidesin Human Synovial Fluid by NanoLC-MS: MethodValidation and Peptide Identification’, J. Proteome Res.,6, 4388–4396 (2007).

115. K. Sasaki, Y. Satomi, T. Takao, N. Minamino, ‘SnapshotPeptidomics of the Regulated Secretory Pathway’, Mol.Cell. Proteomics, 8, 1638–1647 (2008).

116. P.D.E.M. Verhaert, M.W.H. Pinkse, M. Prieto-Conaway, M. Kellmann, ‘A Short History of Insect(neuro)peptidomics—A Personal Story of the Birth andYouth of an Excellent Model for Studying PeptidomeBiology’, in Peptidomics Methods and Applications, eds.M. Soloviev, P. Andren, C. Shaw, John Wiley & Sons,Inc.,Hoboken N.J. 2008, p. 25–54.



117. N. Stoppacher, S. Zeilinger, M. Omann, LP.G. Lassahn,A. Roitinger, R. Krska, R. Schuhmacher, ‘Characterisa-tion of the Peptaibiome of the Biocontrol Fungus Tricho-derma atroviride by Liquid Chromatography/TandemMass Spectrometry’, Rapid Commun. Mass Spectrom.,22, 1889–1898 (2008).

118. D.R. Ahlf, P.D. Compton, J.C. Tran, B.P. Early, P.M.Thomas, N.L. Kelleher, ‘Evaluation of the Compact High-field Orbitrap for Top-down Proteomics of Human Cells’,J. Proteome Res., 11, 4308–4314 (2012).

119. J.C. Tran, L. Zamdborg, D.R. Ahlf, J.E. Lee, A.D.Catherman, K.R. Durbin, J.D. Tipton, A. Vellaichamy,J.F. Kellie, M. Li, C. Wu, S.M. M. Sweet, B.P. Early,N. Siuti, R.D. LeDuc, P.D. Compton, P.M. Thomas, N.L.Kelleher, ‘Mapping Intact Protein Isoforms in DiscoveryMode Using Top-down Proteomics’, Nature, 480, 254–258(2011).

120. J. Zhang, H. Liu, V. Katta, ‘Structural Characterization ofIntact Antibodies by High-resolution LTQ Orbitrap MassSpectrometry’, J. Mass Spectrom., 45, 112–120 (2010).

121. P.V. Bondarenko, T.P. Second, V. Zabrouskov, A.A.Makarov, Z. Zhang, ‘Mass Measurement and Top-downHPLC/MS Analysis of Intact Monoclonal Antibodies ona Hybrid Linear Quadrupole Ion Trap–Orbitrap MassSpectrometer’, J. Am. Mass Spectrom. Soc., 20, 1415–1424(2009).

122. S. Nallet, L. Fornelli, S. Schmitt, J. Parra, L. Baldi,Y.O. Tsybin, F.M. Wurm, ‘Glycan Variability on aRecombinant IgG Antibody Transiently Produced inHEK-293E Cells’, New Biotechnol., 29, 471–476 (2012).

123. Z.Q. Zhang, B. Shah, ‘Characterization of VariableRegions of Monoclonal Antibodies by Top-down MassSpectrometry’, Anal. Chem., 79, 5723–5729 (2007).

124. C. Wu, J.C. Tran, L. Zamdborg, K.R. Durbin, M. Li,D.R. Ahlf, B.P. Early, P.M. Thomas, J.V. Sweedler, N.L.Kelleher, ‘A Protease for ‘Middle-down’ Proteomics’,Nat. Methods, 9, 822–824 (2012).

125. G.K. Taylor, Y.B. Kim, A.J. Forbes, F. Meng,R. McCarthy, N.L. Kelleher, ‘Web and Database Soft-ware for Identification of Intact Proteins Using ‘‘TopDown’’ Mass Spectrometry’, Anal. Chem., 75, 4081–4086(2003).

126. C. Choudhary, M. Mann, ‘Decoding Signalling Networksby Mass Spectrometry-based Proteomics’, Nat. Rev. Mol.Cell Biol., 11, 427–439 (2010).

127. J. Villen, S.P. Gygi, ‘The SCX/IMAC EnrichmentApproach for Global Phosphorylation Analysis by MassSpectrometry’, Nat. Protocols, 3, 1630–1638 (2008).

128. J.V. Olsen, B. Blagoev, F. Gnad, B. Macek, C. Kumar,P. Mortensen, M. Mann, ‘Global, In Vivo, andSite-specific Phosphorylation Dynamics in SignalingNetworks’, Cell, 127, 635–648 (2006).

129. N. Dephoure, C. Zhou, J. Villen, S.A. Beausoleil, C.E.Bakalarski, S.J. Elledge, S.P. Gygi, ‘A Quantitative Atlasof Mitotic Phosphorylation’, Proc. Natl. Acad. Sci. USA,105, 10762–10767 (2008).

130. J. V. Olsen, M. Vermeulen, A. Santamaria,C. Kumar,M.L.Miller, L. J. Jensen, F. Gnad, J. Cox, T. S. Jensen, E.A. Nigg, S. Brunak, M. Mann, Quantitative Phosphopro-teomics Reveals Widespread Full Phosphorylation SiteOccupancy During Mitosis’, Sci. Signal. 3, ra3 (2010).

131. M. Koivomagi, E. Valk, R. Venta, A. Iofik, M. Lepiku,E.R.M. Balog, S.M. Rubin, D.O. Morgan, M. Loog,‘Cascades of Multisite Phosphorylation Control Sic1Destruction at the Onset of S Phase’, Nature, 480, 128–131(2011).

132. M. Franz-Wachtel, S.A. Eisler, K. Krug, S. Wahl,A. Carpy, A. Nordheim, K. Pfizenmaier, A. Hausser,B. Macek, ‘Global Detection of Protein Kinase D-Dependent Phosphorylation Events in NocodazoleTreated Human Cells’, Mol. Cell. Proteomics, 11, 160–170(2012).

133. Y. Yu, R. Anjum, K. Kubota, J. Rush, J. Villen,S.P. Gygi, ‘A Site-specific, Multiplexed Kinase ActivityAssay Using Stable-isotope Dilution and high-resolutionMass Spectrometry’, Proc. Natl. Acad. Sci. USA, 106,11606–11611 (2009).

134. R.C. Kunz, F.E. McAllister, J. Rush, S.P. Gygi, ‘A High-throughput, Multiplexed Kinase Assay Using a BenchtopOrbitrap Mass Spectrometer to Investigate the Effect ofKinase Inhibitors on Kinase Signaling Pathways’, Anal.Chem., 84, 6233–6239 (2012).

135. Y. Zhang, S.B. Ficarro, S. Li, J.A. Marto, ‘OptimizedOrbitrap HCD for Quantitative Analysis of Phospho-peptides’, J. Am. Soc. Mass Spectrom., 20, 1425–1434(2009).

136. S.A. Beausoleil, J. Villen, S.A. Gerber, J. Rush, S.P. Gygi,‘A Probability-based Approach for High-throughputProtein Phosphorylation Analysis and Site Localization’,Nat. Biotech., 24, 1285–1292 (2008).

137. M. M. Savitski, S. Lemeer, M. Boesche, M. Lang, T. Math-ieson, M. Bantscheff, B. Kuster, ‘Confident Phosphory-lation Site Localization Using the Mascot Delta Score’,Mol. Cell. Proteomics, 10, doi:10.1074/mcp.M110.003830,1–12 (2011).

138. T. Taus, T. Kocher, P. Pichler, C. Paschke, A. Schmidt,C. Henrich, K. Mechtler, ‘Universal and ConfidentPhosphorylation Site Localization Using Phosphors’, J.Proteome Res. 10, 5354–5362 (2011).

139. K.A. Dave, B.R. Hamilton, T.P. Wallis, S.G.B. Furness,M.L. Whitelaw, J.J. Gorman, ‘Identification of N,Nε-dimethyl-lysine in the Murine Dioxin Receptor UsingMALDI-TOF/TOF- and ESI-LTQ-Orbitrap-FT-MS’,Intl. J. Mass Spectrom., 268, 168–180 (2007).



140. C. Choudhary, C. Kumar, F. Gnad, M.L. Nielsen,M. Rehman, T.C. Walther, J.V. Olsen, M. Mann, ‘LysineAcetylation Targets Protein Complexes and Co-regulatesMajor Cellular Functions’, Science, 325, 834–840 (2009).

141. B.R. Martin, C. Wang, A. Adibekian, S.E. Tully,B.F. Cravatt, ‘Global Profiling of Dynamic ProteinPalmitoylation’, Nat. Methods, 9, 84–89 (2012).

142. H. Wang, R.M. Straubinger, J.M. Aletta, J. Cao,X. Duan, H. Yu, J. Qu, ‘Accurate Localization andRelative Quantification of Arginine Methylation UsingNanoflow Liquid Chromatography Coupled to ElectronTransfer Dissociation and Orbitrap Mass Spectrometry’,J. Am. Soc. Mass Spectrom., 20, 507–519 (2009).

143. B.-W. Yun, A. Feechan, M. Yin, N.B.B. Saidi, T. LeBihan, M. Yu, J.W. Moore, J.-G. Kang, E. Kwon,S.H. Spoel, J.A. Pallas, G.J. Loake, ‘S-Nitrosylationof NADPH Oxidase Regulates Cell Death in PlantImmunity’, Nature, 478, 264–268 (2011).

144. Z. Shriver, S. Raguram, R. Sasisekharan, ‘Glycomics: APathway to a Class of New and Improved Therapeutics’,Nat. Rev. Drug Discovery, 3, 863–873 (2004).

145. R.K.T. Kam, T.C.W. Poon, ‘The Potentials of Glycomicsin Biomarker Discovery’, Clin. Proteomics, 4, 67–79(2008).

146. M. Wuhrer, M.I. Catalina, A.M. Deelder, C.H. Hokke,‘Glycoproteomics Based on Tandem Mass Spectrometryof Glycopeptides’, J. Chrom. B, 849, 115–128 (2007).

147. G. Palmisano, M.N. Melo-Braga, K. Engholm-Keller,B.L. Parker, M.R. Larsen, ‘Chemical Deamidation: ACommon Pitfall in Large-scale Nlinked glycoproteomicMass Spectrometry-based Analyses’, J. Proteome Res.,11, 1949–1957 (2012).

148. D.F. Zielinska, F. Gnad, K. Schropp, J.R. Wisniewski,M. Mann, ‘Mapping N-glycosylation Sites AcrossSeven Evolutionarily Distant Species Reveals a Diver-gent Substrate Proteome Despite a Common CoreMachinery’, Mol. Cell, 46, 542–548 (2012).

149. B.L. Parker, G. Palmisano, A.V.G. Edwards, M.Y.White, K. Engholm-Keller, A. Lee, N.E. Scott,D. Kolarich, B.D. Hambly, N.H. Packer, M.R. Larsen,S.J. Cordwell, ‘Quantitative N-linked Glycoproteomicsof Myocardial Ischemia and Reperfusion Injury RevealsEarly Remodeling in the Extracellular Environment’,Mol. Cell. Proteomics, 10, doi:10.1074/mcp.M110.006833(2011).

150. C. Danzer, K. Eckhardt, A. Schmidt, N. Fankhauser,S. Ribrioux, B. Wollscheid, L. Muller, R. Schiess,R. Zullig, R. Lehmann, G. Spinas, R. Aebersold, W. Krek,‘Comprehensive Description of the N-Glycoproteome ofMouse Pancreatic β-cells and Human Islets’, J. ProteomeRes., 11, 1598–1608 (2002).

151. X. Qiao, D. Tao, Y. Qu, L. Sun, L. Gao,X. Zhang, Z. Liang, L. Zhang, Y. Zhang, ‘Large-scale N-Glycoproteome Map of Rat Brain Tissue:Simultaneous Characterization of Insoluble and SolubleProtein Fractions’, Proteomics, 11, 4274–4278 (2011).

152. J.E. Syka, J.J. Coon, M.J. Schroeder, J. Shabanowitz, D.F.Hunt, ‘Peptide and Protein Sequence Analysis by Elec-tron Transfer Dissociation Mass Spectrometry’, Proc.Natl. Acad. Sci. USA, 101, 9528–9533 (2004).

153. J.F. Alfaro, C.-X. Gong, M.E. Monroe, J.T. Aldrich,T.R.W. Clauss, S.O. Purvine, Z. Wang, D.G. Camp II,, J.Shabanowitz, P. Stanley, G.W. Hart, D.F. Hunt, F. Yang,R.D. Smith, ‘Tandem Mass Spectrometry Identifies ManyMouse Brain O-GlcNAcylated Proteins Including EGFDomain-specific O-GlcNAc Transferase Targets’, Proc.Natl. Acad. Sci. USA, 109, 7280–7285 (2012).

154. Z. Darula, J. Sherman, K.F. Medzihradszky, ‘How toDig Deeper? Improved Enrichment Methods for Mucincore-1 Type Glycopeptides’, Mol. Cell. Proteomics, 11,doi:10.1074/mcp.O111.016774 (2012).

155. P. Zhao, R. Viner, C.F. Teo, G.-J. Boons, D. Horn,L. Wells, Combining High-energy C-trap Dissociationand Electron Transfer Dissociation for Protein O-GlcNAc Modification Site Assignment, J. Proteome Res.,10, 4088–4104 (2011).

156. H. Hahne, B. Kuster, ‘A Novel Two-stage Tandem MassSpectrometry Approach and Scoring Scheme for theIdentification of O-GlcNAc Modified Peptides’, J. Am.Soc. Mass Spectrom., 22, 931–942 (2011).

157. C. Steentoft, S.Y. Vakhrushev, M.B. Vester-Christensen, K. Schjoldager, Y. Kong, E.P. Bennett,U. Mandel, H. Wandall, S.B. Levery, H. Clausen,‘Mining the O-Glycoproteome Using Zinc-fingerNuclease–glycoengineered SimpleCell Lines’, Nat.Methods 8, 977–984 (2011).

158. K.T.G. Schjoldager, M.B Vester-Christensen, C.K. Goth,T.N. Petersen, S. Brunak, E.P. Bennett, S.B. Levery, H.Clausen, ‘A Systematic Study of Site-specific GalNAc-type O-glycosylation Modulating Proprotein ConvertaseProcessing’, J. Biol. Chem., 286, 40122–40132 (2011).

159. R.I. Viner, T. Zhang, T. Second, V. Zabrouskov,‘Quantification of Post-translationally Modified Peptidesof Bovine α-crystallin Using Tandem Mass Tags andElectron Transfer Dissociation’, J. Proteomics, 72,874–885 (2009).

160. S. I. Snovida, E. D. Bodnar, R. Viner, J. Saba,H. Perreault, ‘A Simple Cellulose Column Procedurefor Selective Enrichment of Glycopeptides and Charac-terization by Nano LC Coupled with Electron-transferand High-energy Collisional-dissociation Tandem MassSpectrometry’, Carbohyd. Res., 345, 792–801 (2010).

161. T. Zhang, R. Viner, Z. Hao, V. Zabrouskov, Analysis ofGlycopeptides Using Porous Graphite Chromatographyand LTQ Orbitrap XL ETD Hybrid MS, Sample



Preparation in Biological Mass Spectrometry 26, 535–546(2011).

162. J. Saba, S. Dutta, E. Hemenway, R. Viner, ‘Increasingthe Productivity of Glycopeptides Analysis by UsingHigher-energy Collision Dissociation-accurate Mass-product-dependent Electron Transfer Dissociation’, Int.J. Proteomics, 2012, doi:10.1155/2012/560391 (2012).

163. K. Schjoldager, S.Y. Vakhrushev, Y. Kong, C. Steentoft,A.S. Nudelman, N.B. Pedersen, H.H. Wandall,U. Mandel, E.P. Bennett, S.B. Levery, H. Clausen,‘Probing Isoform-specific Functions of PolypeptideGalNAc-transferases Using Zinc Finger NucleaseGlycoengineered Simple Cells’, Proc. Natl. Acad. Sci.USA, 109, 9893–9898 (2012).

164. C. Singh, C. Zampronio, A. Creese, H.J. Cooper, ‘HigherEnergy Collision Dissociation (HCD) Product Ion Trig-gered Electron Transfer Dissociation (ETD) Mass Spec-trometry for the Analysis of N-linked Glycoproteins’, J.Proteome Res., 11, 4517–4525 (2012).

165. J. Saba, E. Bonneil, C. Pomies, K. Eng, P. Thibault,‘Enhanced Sensitivity in Proteomics ExperimentsUsing FAIMS Coupled with a Hybrid Linear IonTrap/Orbitrap Mass Spectrometer’, J. Proteome Res., 8,3355–3366 (2009).

166. G. Bridon, E.Bonneil, T. Muratore-Schroeder, O. Caron-Lizotte, P. Thibault, ‘Improvement of PhosphoproteomeAnalyses Using FAIMS and Decision Tree Fragmenta-tion. Application to the Insulin Signaling Pathway inDrosophila melanogaster S2 Cells’, J. Proteome Res., 11,927–940 (2012).

167. K.E. Swearingen, M.R. Hoopmann, R.S. Johnson, S.A.Saleem, J.D. Aitchison, R.L. Moritz, ‘NanosprayFAIMS Fractionation Provides Significant Increases inProteome Coverage of Unfractionated Complex ProteinDigests’, Mol. Cell. Proteomics,11, M111.014985 (2012).

168. A.J. Creese, H.J. Cooper, ‘Separation and Identificationof Isomeric Glycopeptides by High Field AsymmetricWaveform Ion Mobility Spectrometry’, Anal. Chem., 84,2597–2601 (2012).

169. C. Bleckmann, H. Geyer, R. Geyer, ‘Nanoelectrospray-MSn of Native and Permethylated Glycans’, Meth. Mol.Biol., 790, 71–85 (2011).

170. J. Jiao, H. Zhang, V.N. Reinhold, ‘High PerformanceIT-MSn Sequencing of Glycans (Spatial Resolutionof Ovalbumin Isomers)’, Int. J. Mass Spectrom., 303,109–117 (2011).

171. N. Suzuki, T.-H. Su, S.-W. Wu, K. Yamamoto,K.-H. Khoo, Y.C. Lee, ‘Structural Analysis of N-glycansfrom Gull Egg White Glycoproteins and Egg Yolk IgG’,Glycobiology, 19, 693–706 (2009).

172. K.A. Stumpo, V.N. Reinhold, ‘The N-glycome of HumanPlasma’, J. Proteome Res., 9, 4823–4830 (2010).

173. M. Melmer, T. Stangler, M. Schiefermeier, W. Brunner,H. Toll, A. Rupprechter, W. Lindner, A. Premstaller,‘HILIC Analysis of Fluorescence-labeled N-glycansfrom Recombinant Biopharmaceuticals’, Anal. Bioanal.Chem., 398, 905–914 (2010).

174. M.C. Reilly, K. Aoki, Z.A. Wang, M.L. Skowyra,M. Williams, M. Tiemeyer, T.L. Doering, ‘A Xylo-sylphosphotransferase of Cryptococcus neoformans Actsin Protein O-glycan Synthesis’, J. Biol. Chem., 286,26888–26899 (2011).

175. A.Moen, T.T. Hafte, H. Tveit, W. Egge-Jacobsen,K. Prydz, ‘N-Glycan Synthesis in the Apical andBasolateral Secretory Pathway of Epithelial MDCK Cellsand the Influence of a Glycosaminoglycan Domain’,Glycobiology, 21, 1416–1425 (2011).

176. A.K. Bergfeld, O.M.T. Pearce, S.L. Diaz,R. Lawrence, D.J. Vocadlo, B. Choudhury, J.D.Esko, A. Varki, ‘Metabolism of Vertebrate AminoSugars with N-glycolyl groups: Incorporation ofN-Glycolylhexosamines into Mammalian Glycans byFeeding N-glycolylgalactosamine’, J. Biol. Chem., 287,28898–28916 (2012).

177. A.K. Bergfeld, O.M.T. Pearce, S.L. Diaz, T. Pham,A. Varki, ‘Metabolism of Vertebrate Amino Sugars withN-glycolyl Groups: Elucidating the Intracellular Fate ofthe Non-human Sialic Acid N-glycolylneuraminic Acid’,J. Biol. Chem., 287, 28865–28881 (2012).

178. P.V. Cabrera, M. Pang, J.L. Marshall, R. Kung, S.F.Nelson, S.H. Stalnaker, L. Wells, R.H. Crosbie-Watson,L.G. Baum, ‘High Throughput Screening for Compoundsthat Alter Muscle Cell Glycosylation Identifies a NewRole for N-glycans in Regulating Sarcolemmal ProteinAbundance and Laminin Binding’, J. Biol. Chem., 287,22759–22770 (2012).

179. R. Lawrence, J.R. Brown, K. Al-Mafraji, W.C. Lamanna,J.R. Beitel, G.-J. Boons, J.D. Esko, B.E. Craw-ford, ‘Disease-specific Non-reducing End CarbohydrateBiomarkers for Mucopolysaccharidoses’, Nat. Chem.Biol., 8, 197–204 (2012).

180. S.-Y. Yu, L.-Y. Chang, C.-W. Cheng, C.-C. Chou,M. N. Fukuda, K.-H. Khoo, ‘Priming Mass Spectrometry-based Sulfoglycomic Mapping for Identification ofTerminal Sulfated lacdiNAc Glycotope’, GlycoconjugateJ., doi:10.1007/s10719-012-9396-7 (2012).

181. R. Orlando, J.-M. Lim, J.A. Atwood III, P.M. Angel,M. Fang, K. Aoki, G. Alvarez-Manilla, K.W. Moremen,W.S. York, M. Tiemeyer, M. Pierce, S. Dalton, L. Wells,‘IDAWG: Metabolic Incorporation of Stable IsotopeLabels for Quantitative Glycomics of Cultured Cells’,J. Proteome Res., 8, 3816–3823 (2009).

182. S.H. Walker, J. Budhathoki-Uprety, B.M. Novak,D.C. Muddiman, ‘Stable-Isotope Labeled HydrophobicHydrazide Reagents for the Relative Quantification of



N-linked Glycans by Electrospray Ionization Mass Spec-trometry’, Anal. Chem., 83, 6738–6745 (2011).

183. S.E. Ong, B. Blagoev, I. Kratchmarova, D.B. Kristensen,H. Steen, A. Pandey, M. Mann, ‘Stable Isotope Labelingby Amino Acids in Cell Culture, SILAC, as a Simpleand Accurate Approach to Expression Proteomics’, Mol.Cell. Proteomics, 1, 376–386 (2002).

184. T. Geiger, J. Cox, P. Ostasiewicz, J.R. Wisniewski,M. Mann, ‘Super-SILAC Mix for QuantitativeProteomics of Human Tumor Tissue’, Nat. Methods 7,383–385 (2010).

185. X. Yao, A. Freas, J. Ramirez, P.A. Demirev, C. Fenselau,‘Proteolytic 18O Labeling for Comparative Proteomics:Model Studies with Two Serotypes of Adenovirus’, Anal.Chem., 73, 2836–2842 (2001).

186. P.J. Boersema, R. Raijmakers, S. Lemeer, S. Mohammed,A.J.R. Heck, ‘Multiplex Peptide Stable Isotope DimethylLabeling for Quantitative Proteomics’, Nat. Protocols, 4,484–494 (2009).

187. A. Thompson, J. Schafer, K. Kuhn, S. Kienle, J. Schwarz,G. Schmidt, T. Neumann, C. Hamon, ‘Tandem MassTags: A Novel Quantification Strategy for ComparativeAnalysis of Complex Protein Mixtures by MS/MS’, Anal.Chem., 75, 1895–1904 (2003).

188. P.L. Ross, Y.N. Huang, J.N. Marchese, B. Williamson,K. Parker, S. Hattan, N. Khainovski, S. Pillai, S. Dey,S. Daniels, S. Purkayastha, P. Juhasz, S. Martin, M.Bartlet-Jones, F. He, A. Jacobson, D.J. Pappin, ‘Multi-plexed Protein Quantitation in Saccharomyces cerevisiaeUsing Amine-reactive Isobaric Tagging Reagents’, Mol.Cell. Proteomics, 3, 1154–1169 (2004).

189. L. Ting, R. Rad, S.P. Gygi, W. Haas, ‘MS3 EliminatesRatio Distortion in Isobaric Multiplexed QuantitativeProteomics’, Nat. Methods 8, 937–940 (2011).

190. C.D. Wenger, M.V. Lee, A.S. Herbert, G.C. McAlister,D.H. Phanstiel, M.S. Westphall, J.J. Coon, ‘Gas-phasePurification Enables Accurate, Multiplexed ProteomeQuantification with Isobaric Tagging’, Nat. Methods, 8,933–935 (2011).

191. J. Sutton, T. Richmond, X. Shi, M. Athanas, C. Ptak,R. Gerszten, L. Bonilla, ‘Performance Characteristics ofan FT MS-based Workflow for Label-free Differential MSAnalysis of Human Plasma: Standards, Reproducibility,Targeted Feature Investigation, and Application to aModel of Controlled Myocardial Infarction’, ProteomicsClin. Appl., 2, 862–881 (2008).

192. N.P. Manes, R.D. Estep, H.M. Mottaz, R.J. Moore,T.R.W. Clauss, M.E. Monroe, X. Du, J.N. Adkins,

S.W. Wong, R.D. Smith, ‘Comparative Proteomics ofHuman Monkeypox and Vaccinia Intracellular Matureand Extracellular Enveloped Virions’, J. Proteome Res.,7, 960–968 (2008).

193. J.D. Jaffe, H. Keshishian, B. Chang, T.A. Addona, M.A.Gillette, S.A. Carr, ‘Accurate Inclusion Mass Screening’,Mol. Cell. Proteomics, 7, 1952–1962 (2008).

194. A. Prakash, D. Tomazela, B. Frewen, G. Merrihew,B. MacLean, S. Peterman, M.J. MacCoss, ‘Expediting theDevelopment of Targeted SRM Assays: Using Data fromShotgun Proteomics to Automate Method Development’,J. Proteome Res., 8, 2733–2739 (2009).

195. A.C. Peterson, J.D. Russell, D.J. Bailey, M.S. West-phall, J.J. Coon, ‘Parallel Reaction Monitoring forHigh Resolution and High Mass Accuracy Quantita-tive, Targeted Proteomics’, Mol. Cell. Proteomics, 11,doi:10.1074/mcp.O112.020131 (2012).

196. S. Gallien, E. Duriez, C. Crone, M. Kellmann,T. Moehring, B. Domon, ‘Targeted Proteomic Quan-tification on Quadrupole-Orbitrap Mass Spectrometer’,Mol. Cell. Proteomics, 11, doi:10.1074/mcp.O112.019802(2012).

197. H. Manduzio, A. Martelet, E. Ezan, F. Fenaille, ‘Compar-ison of Approaches for Purifying and Desalting Poly-merase Chain Reaction Products Prior to ElectrosprayIonization Mass Spectrometry’, Anal. Biochem., 398,272–274 (2010).

198. Y. Zou, P. Tiller, I.W. Chen, M. Beverly, J. Hochman,‘Metabolite Identification of Small Interfering RNADuplex by high-resolution Accurate Mass Spectrometry’,Rapid Commun. Mass Spectrom., 22, 1871–1881 (2008).

199. E.L. Jamin, D. Arquier, C. Canlet, E. Rathahao, J. Tulliez,L. Debrauwer, ‘New Insights in Deoxynucleoside theFormation of Adducts with the Heterocyclic AromaticAmines PhIP and IQ by Means of Ion Trap MSn andAccurate Mass Measurement of Fragment Ions’, J. Am.Soc. Mass Spectrom., 18, 2107–2118 (2007).

200. M. Smith, ‘Characterisation of a Modified Oligonu-cleotide Together with its Synthetic Impurities UsingAccurate Mass Measurements’, Rapid Commun. MassSpectrom., 25, 511–525 (2011).

201. K. Aizikov, P. B. O’Connor. ‘Use of the FilterDiagonalization Method in the Study of Space ChargeRelated Frequency Modulation in Fourier TransformIon Cyclotron Resonance Mass Spectrometry’, J. Am.Soc. Mass Spectrom., Vol. 17(6), 836–843 (2006).


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Fundamentals and Advances of Orbitrap Spectrometry