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Analysis of biopharmaceutical proteins in biological matrices by LC-MS/MS II. LC-MS/MS analysis Ge´rard Hopfgartner, Antoine Lesur, Emmanuel Varesio The first section of Part II describes the current strategies for mass spectrometric (MS) detection in the selected reaction monitoring (SRM) mode which has become the method of choice to quantify peptides. We then discuss the selection of signature peptides, SRM transitions and labeled internal-standard peptides to obtain the best assay selectivity. We also present improved assay selectivity on triple-quadrupole linear ion trap using MS3 and differential mobility MS. We dedicate the final section to alternative approaches based on high-resolution data-independent acquisition. ª 2013 Elsevier Ltd. All rights reserved. Keywords: Biopharmaceuticals, Peptide; Protein, Quantitative analysis, Selected reaction monitoring (SRM), Assay selectivity; Biological matrix; Signature peptide; High resolution mass spectrometry, Ion mobility, MSn
1. Introduction Ge´rard Hopfgartner*, Antoine Lesur, Emmanuel Varesio Life Sciences Mass Spectrometry, School of Pharmaceutical Sciences, University of Geneva, Quai Ernest Ansermet 30, CH-1211 Geneva 4, Switzerland
*
Corresponding author. Tel.: +41 (0) 22 379 63 44; Fax: +41 (0) 22 379 33 32; E-mail: gerard.hopfgartner@ unige.ch
Biopharmaceuticals represent a significant portion of the pharmaceuticals market. In 2009, sales of biologics totaled $99 billion, 12% of the total market, including the $38 billion of the monoclonal-antibody (mAb)-related product (5% of the total market) [1]. The current gold standards for protein quantification are ligandbinding assays [e.g., enzyme-linked immunosorbent assay (ELISA)]. This analytical method is based on immuno-affinity and offers high sensitivity, but the dynamic range is often limited to one to two orders of magnitude. However, commercial assays are available for a limited number of proteins and the development of new antibodies is a time-consuming, costly process. ELISA may also suffer from selectivity issues and results can be significantly altered depending on the kit manufacturer [2]. Also, when multiplexed assays are designed, potential interferences from cross reactivity must be assessed. The alternative of protein quantification by LC-SRM/MS was recently applied to quantify therapeutic proteins (e.g., mAbs and recombinant proteins) [3–8]. The methodology took inspiration from the well-established quantification of small
molecules by LC-SRM/MS in the field of bioanalysis in the pharmaceutical industry, anti-doping, and forensics [9]. The assays tend to monitor only one protein in a large number of samples, so development and optimization of the analytical method, from sample preparation to MSdetection method, is focused on the development of a specific analytical method dedicated to the quantification of a particular target. Practically, quantification is based on the construction of calibration curves and needs to fulfill validation criteria {e.g., those of the Food and Drug Administration (FDA) guidelines [10,11]}. The use of isotopically-labeled synthetic peptides or proteins as internal standards (ISs) is necessary to balance the fluctuations inherent to the samplepreparation and mass-spectrometer response. The most predominant biological matrices for biopharmaceuticals are plasma and serum, which contain, in addition to the abundant proteins, informative proteins (e.g., hormones, cytokines, and proteins leaked from tissues). The protein concentrations are spread over 10 orders of magnitude (albumin represents 55% of the total plasmatic proteins) [12,13], so the analytical dynamic range represents a real challenge.
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This article is Part II of the review on detection and quantification of therapeutic proteins in complex biological matrices. While Part I [14] focuses on various sample-preparation steps, Part II addresses mass spectrometric (MS) and chromatographic aspects, in particular the selection of signature peptides, the selectivity of the selected reaction monitoring (SRM) mode and applications of high-resolution MS (HRMS).
2. SRM detection and signature-peptide selection In bioanalysis, proteins are not frequently quantified in their intact form (top-down) by LC-MS(/MS) because they display a broad range of size and chemical properties that require specific chromatographic and MS ionization conditions to be measured. In the bottom-up approach, the specific peptides resulting from an enzymatic digestion are analyzed as the surrogates of the targeted proteins. For quantitative purposes, the SRM
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mode of the triple quadrupole (QqQ), introduced by Enke and Yost in 1978 [15], has become the main asset of the QqQ design. Practically, the analysis by the SRM mode is provided by the selection at unit mass of a precursor ion on quadrupole Q1 and a fragment ion, produced by collision induced dissociation (CID) in the collision cell, on quadrupole Q3 of the mass spectrometer. While, for low-molecular-weight compounds, a single Q1-Q3 transition is used for quantification and a second one for confirmatory analysis, several transitions are generally recorded in the case of peptides. Another key aspect is that the quantification is performed at a peptide level and extrapolated to the protein. Selectivity is therefore becoming a key issue regarding the selection of the peptides and the analytical measurement. As illustrated in Fig. 1, several factors (e.g., selection of the SRM transitions, sample preparation or chromatography) can affect the analytical read-out. In peptides analysis, further specificity comes because these molecules are usually ionized in electrospray under a multi-charged form
Figure 1. The selectivity of an LC-SRM/MS method depends on the monitored fragment, the chromatographic separation and the sample preparation. (A) Plasma treated by selective precipitation (45% v/v, CH3CN) before digestion. SRM transition m/z 464.8 fi m/z 244.2. (B) Plasma treated by selective precipitation (45% v/v, CH3CN) before digestion. SRM transition m/z 464.8 fi m/z 557.3. (C) Plasma treated by selective precipitation (50% v/v, CH3CN) before digestion. SRM transition m/z 464.8 fi m/z 244.2.
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but produce mainly singly-charged fragments. This property can be used to eliminate interferences from small molecules, which are often singly charged, by exclusively selecting SRM transitions with Q3 m/z values higher than the precursor-ion m/z value to exclude signals from singly-charged molecules. Due to the short time required to acquire a SRM transition (typically 5– 20 ms) several transitions can be monitored for a single analyte and several peptides can easily be measured for a single protein to enhance the selectivity of the assay. The concentration range of proteins in biological matrices, including serum and plasma, is a key challenge of analytical science. As, after digestion, the sample complexity increases, the risk of not discriminating analytes from interfering peptides becomes even more significant. Sample preparation, fractionation and chromatographic separation play important roles in mitigating these risks by reducing the chemical background before the MS acquisition. The choice of a representative proteotypic peptide, called signature and quantified as a surrogate of the protein, must fit several requirements, including: (1) detection within the ionization mode and the mass analyzer m/z range; (2) uniqueness of the amino-acid sequence in the studied proteome or sub-proteome; and, (3) to be a peptide representative of the native protein concentration that is free from post-translational modifications (PTMs), alternative splicing sites, or prone to chemical alterations. A signature peptide is characterized by an amino-acid sequence exclusively related to the targeted protein in a given proteome. The uniqueness can be verified in silico by a peptide-sequence alignment, using algorithms (e.g., BLAST-P) against the whole proteome of the studied
Q1 (z=1) Q3 (z=1)
AVSMEDQHR 1072.5 1001.4 902.4 815.3 684.3 555.3 440.2 312.2 258.1 389.2 518.2 633.3 761.3 898.4
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organism. This process implies that the investigated proteome sequences are extensively compiled in protein databases (e.g., those maintained by UniProtKB or NCBI). The selection of the signature peptides on the basis of the uniqueness of their amino-acid sequence does not address the fact that the MS system will separate peptide ions according to their m/z values and that the databases do not take into account the concentration level of the protein versus that of the biopharmaceutical. Despite a unique amino-acid sequence, some significant redundancy in the m/z values of peptide precursors and fragments exists. This is the consequence of the peptide structure, a linear polymer of 20 amino acids. For example, there are 83 isobaric and quasi-isobaric permutations between two pairs of amino acids (e.g., DQ = NE), 13 equivalent permutations between one amino acid and a pair, and 4276 permutations between a pair and a triplet [16]. Peptides that differ by such permutations will share isobaric SRM transitions except at the pair position (Fig. 2). This situation can be overcome because an orthogonal separation, such as liquid chromatography (LC) and ion mobility spectrometry (IMS), can provide additional selectivity. To assist in the selection of signature peptides, bioinformatics tools have been developed. These tools are designed to predict observable proteotypic peptides on the basis of their computed chemical properties using software (e.g., PeptideSieve) [17]. Once the sequences of signature-peptide candidates are listed for the quantification of a targeted group of proteins, their experimental detectability must be assessed. Theoretically, a complete tryptic digestion produces an equimolar mixture of peptides from a given protein. The MS responses are dramatically different, and some of the peptides are undetectable, because ionization
y8 y7 y6 y5 y4 y3 y2 b3 b4 b5 b6 b7 b8
AVSMEENHR 1072.5 1001.4 902.4 815.3 684.3 555.3 426.2 312.2 258.1 389.2 518.2 647.3 761.3 898.4
Figure 2. AVSMEDQHR and AVSMEENHR peptides. Despite their dissimilar amino-acid sequences, only two SRM transitions corresponding to y3 and b6 fragments are selective.
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efficiency, stability, and even digestion yield are peptide dependent [18]. Information on peptide detectability can be obtained from in-house unsupervised experiments (e.g., the shotgun approach) performed on representative biological samples. These experimental data tend to be shared in proteomic databases {e.g., PeptideAtlas [19], PRIDE [20] or GPM [21]}, and data can be managed by specialized software (e.g., Skyline) [22]. During the development of quantitative assays for biopharmaceutical-drug proteins, the complete SRM selection and optimization (i.e. selection of the fragments and the collision energy) are often directly performed on the purified form of the protein available from the production lines. Regarding human mAbs, the choice of signature peptides must be made within the complementary determining regions (CDRs) that contain amino-acid sequences less prone to be found in the other endogenous immunoglobulins, so, for each new mAb, a new assay has to be developed and validated. Furlong et al. [23] proposed a different approach to selecting signature peptides. Indeed, considering the assay development for human mAbs and human Fc-fusion proteins administrated to animals, amino-acid sequences between human and animal proteins are also expected to differ in the Fc region of mAbs. They have identified a universal IgG Fc region tryptic peptide common to a variety of human-protein drug candidates and not present in endogenous animal proteins. A single LC-MS/MS assay can therefore be used to support drug-discovery studies. In all cases, the ultimate confirmation of peptide-signature suitability is provided during the method-validation procedure performed according to the agency guidelines.
3. Quantification and selection of the internal standards Quantitative MS-based experiments mostly rely on the use of stable-isotope (i.e. 13C, 15N and 18O)-labeled peptides used as ISs to balance variability coming from: (1) sample preparation (e.g., reduction and alkylation, solid-phase extraction, derivatization, precipitation) and enzymatic digestion; (2) peptide separation (i.e. auto-sampler stability, injection volume and retention-time variability); (3) MS detection where suppression/enhancement effects during the ionization process can occur [24,25]. The isotopically-labeled peptides, often called heavy peptides, share the same amino-acid sequence and physico-chemical properties as their native counterparts, which are called light peptides. Consequently, the chromatographic retention times, the ionization efficiency and the CID-fragmentation patterns are equivalent for labeled and native peptide forms, and MS differentiates the heavy/light peptide pairs based on their mass shift. 4
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When a tryptic digestion of the biological sample is planned in the analytical workflow, the heavy version of lysine and arginine residues will be incorporated preferentially into the peptide sequences, since each tryptic peptide will include the labeled amino-acid residues with the exception of the protein C-terminal peptide. In quantification of endogenous proteins (biomarkers) that are generally present in all samples, therapeutic proteins are not present prior to administration and the same quantification and method validation approaches can be applied as for small molecules, based on calibration and quality-control samples. Several strategies are currently in use for introducing labeled standards in a quantitative experiment. These include use of synthetic labeled peptides, concatemers of recombinant peptides (QconCAT), fully-labeled proteins, metabolic incorporation, and labeled reagents (Fig. 3). 3.1. Isotopically-labeled synthetic peptides Barr et al. first used isotopically-labeled peptide analogs in 1996 for the quantification of apolipoprotein A-I [26]. In 2003, a similar approach was used by Gygi et al. for the absolute quantification of proteins and phosphoproteins in cell lysates leading to the term of AQUA peptides [27–29]. Nowadays, the costs of synthetic labeled peptides has significantly decreased and several providers offer a wide variety of products from relatively inexpensive bulk material to precisely dosed peptides primarily dedicated to isotopic dilution experiments. However, synthetic peptides are often provided under their lyophilized form, and stability during their storage and their solubility are not guaranteed and depend on their amino-acid sequence. It is common practice to spike peptide ISs before the enzymatic digestion to correct for the degradation of the native peptides. However, one of the key points of sample preparation in quantitative proteomics remains the tryptic digestion. Indeed, this step is not always comprehensive and the use of synthetic peptides will not balance the digestion inconsistencies between samples [30], but only the subsequent sample-preparation steps and the LC-MS/MS analysis. Therefore, the potential benefit of using synthetic peptides flanked by short amino-acid sequences from the native protein has been evaluated [31]. This strategy aims to reproduce the kinetics and the yields of native-protein digestion. Nevertheless, it appeared that no significant advantages were shown for the quantification of immuno-captured mAbs in plasma and serum [32]. Along the same line, Anderson et al. used stable-isotope peptide standards together with anti-peptide antibodies to quantitate signature peptides from several human-plasma proteins. This analytical approach is known as SISCAPA, where both the signature peptide and its labeled form are enriched by immunoaffinity chromatography prior to LC-SRM/MS analysis [33].
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Figure 3. Major internal standardization strategies using stable isotopes. SILAC and protein internal standards are based on fully isotope-labeled proteins and efficiently balance every step of the sample preparation and the tryptic digestion yield. QcontCAT and isotope-labeled synthetic peptides are often spiked before the digestion but poorly balance this step. Absolute quantification is possible with heavy protein standards, QcontCat, and isotope-labeled peptides where SILAC and isotope-labeled reagent are fitted for relative quantification. After LC-SRM/MS analysis, the chromatographic peaks are integrated and the quantification results are calculated from the light/heavy SRM peak area or height ratios. {Adapted from Brun et al. [24]}.
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3.2. QconCAT The QconCAT strategy depends on a concatemer of signature peptides expressed in a host organism as an artificial recombinant protein [34,35]. This technique provides the benefit of producing peptides that are not easily synthesized using chemistry. After production, these peptides must be released using tryptic digestion. As AQUA and QconCAT standards are generally added at late and different stages of the analytical process, there is potential bias between the two methods [36]. There is also less room for the adjustment of individual standard concentrations with the use of concatemers, because QconCAT produces an equimolar mixture of peptides after the tryptic digestion. Finally, the production costs of a recombinant protein limit this approach mainly to large-scale experiments. 3.3. Isotopically-labeled proteins Fully isotopically-labeled proteins are the golden IS for targeted quantitative proteomics [7,37,38]. Indeed, fully labeled proteins balance completely the different sources of analytical variability, including the tryptic digestion and the pre-fractionation steps based on molecular weight, size and immuno-affinity capture. In addition, the heavy form of each observable peptide that holds the labeled amino acid is produced, dramatically increasing the method-development flexibility when selectivity issues arise for the choice of the signature peptides. The chemical synthesis of proteins is almost impossible because of the specific folding and PTMs. Metabolic incorporation of stable isotopes is a much more convenient approach for the production of fully isotopicallylabeled proteins. This labeling strategy is often possible during the production of therapeutic recombinant proteins from genetically-modified cell lines. In practice, the production and purification processes of the non-labeled version are already developed. Thus, a straightforward metabolic incorporation of an essential amino acid, isotopically labeled with 13C and 15N, into the growth media can lead to the production of a heavy analog protein with limited extra costs. Because the protein IS will be purified and quantified, absolute quantification strategies can be considered. 3.4. Peptide and protein analogs Protein or peptide analogs can be a cost-effective solution as ISs because they do not require incorporation of stable isotopes. They consist of proteins or peptides with an amino-acid sequence similar to the quantified protein or peptide. Ideally, an analog should also have very similar physicochemical properties to the protein or peptide of interest to correct variations occurring during the sample preparation. Both analyte and IS peptides should preferably co-elute to balance the matrix effects. The selection of an IS protein from phylogenetically close 6
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species is often a good option. Indeed, a single aminoacid substitution, located on the sequence of the signature peptide, is a good choice [39]. Beside many options, chemical derivatization can also be considered to generate an adequate protein IS [3]. An interesting approach with sample preparation using affinity enrichment is to use a protein that binds to the same receptor. This was applied for the quantification of mAb Erbitux using an IS consisting of a commercial mouse mAb specific to human sEGFR, the target of Erbitux [40].
4. Enhanced MS selectivity at low resolution In quantitative bioanalysis, sample throughput is essential to be able to quantify hundreds of samples on a daily basis. Accurate measurement of biopharmaceuticals is also key, and relies strongly on the selectivity of the assays. There is always a trade-off regarding sample throughput and selectivity; for example, a selective sample preparation based on affinity can be achieved, but chromatographic performance, and therefore peak capacity, have to be compromised. Since proteins are quantified based on their signature peptides and considering multiply-charged precursor ions and broad isotopic distributions, the risk of interferences is much more important for peptides than for low-molecular-weight compounds [41]. Besides HRMS, two orthogonal MSbased approaches [i.e. SRM cubed (SRM3) and differential IMS (DMS)] recently became available and offer new possibilities to increase assay selectivity. 4.1. SRM cubed An option for enhancing selectivity involves adding a second stage of fragmentation (MS/MS/MS or MS3) and the observation of second-generation fragments. MS3, and MSn for that matter, can be performed in ionic traps using tandem-in-time MS/MS. However, the number of ions that can be accumulated in the ion trap must be limited to avoid space-charging effects. As a result, the overall sensitivity of MSn using ion traps is limited by the dilution of the precursor in the ionic background. This is particularly detrimental for biological samples, which generate a rich ionic background. Using a QqQLIT massspectrometer design, the fragment ions generated in Q2 are accumulated in Q3, which is operated as a linear ion trap (LIT) in this instance. After a cooling step, a firstgeneration fragment is isolated and fragmented in the linear ion trap by CID. Then, the second-generation fragments are scanned by an axial ejection. Because the first precursor is selected in Q1 and fragmented in the same manner as a regular SRM approach, the LIT accumulates only the fragments ions of the precursor ion and consequently the dilution effect of the ionic trap is circumvented [42]. Quantification by SRM3 using QqQLIT can reach limits of detection (LODs) equal to or
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lower than the regular SRM method, because of the accumulation capabilities of an ion trap and because multiple fragments can be summed. In addition, the selectivity gain reduces the need for extensive sample preparation or a long LC run. However, the cycle time of SRM3 transitions (around 250 ms) is significantly longer than conventional SRM transitions, so the SRM3acquisition mode is only able to monitor a limited number of peptides per run. 4.2. Differential IMS (DMS) Another approach to improve the selectivity of analyte quantification is to place a DMS device between the electrospray ionization source and the mass spectrometer. The separation is orthogonal to MS and the ions are differentiated based on their different ionic mobilities at high and low electric fields in an inert transport gas. Two different commercially available forms have been described: high-field asymmetric waveform IMS (FAIMS) [43] and DMS [44]. The FAIMS system employs two cylindrical electrodes for the ion separation, whereas the DMS system uses two planar electrodes. In DMS, a transport gas carries the ions and a radio frequency (RF) voltage is applied orthogonally to the ion path. This RF voltage, also called the separation voltage (SV), is an asymmetric periodic waveform that consists of a short duration high field and then an opposite low field applied so that the integrated voltage is equal to zero after one cycle. Because an ion possesses a different mobility under low and high fields, the resultant trajectory will tend toward an electrode unless a specific compensation voltage (CoV) corrects its trajectory. Finally, for a given gas-flow velocity, the CoV and SV are used to filter the trajectory of different ion species. DMS can be implemented in several modes: (1) a fixed CoV and SV adapted for particular ion species will result in the continuous mass filtering of this ion; or, (2) a fixed SV and a scanning CoV will result in a DMS spectrum with a distribution of the ion species over the CoV range. The main asset of DMS is to bring an orthogonal selectivity to the LC-SIM/SIM [45] or LC-SRM/MS [46] approaches, so co-eluting interferences can be filtered out, even in the case of isobaric precursors. However, because FAIMS and DMS are implemented after the ionization source, these methods do not prevent suppression effects that may occur during the ionization process. Moreover, the residence time of ions in FAIMS (100 ms) limits the number of compounds that can be analyzed per run. The planar geometry (DMS) allows a residence time of 20 ms, which is much closer to the typical SRM dwell time. In addition, the planar design (DMS) allows the introduction of a modifier, typically a solvent (e.g., water, methanol, acetonitrile, acetone, propanol, or butanol) in the transport-gas flow. This
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addition has been shown to change the selectivity and to enhance the separation power, depending on the modifier infused [47].
5. High-resolution mass spectrometry The quantification performed by HRMS with resolving power generally above 30,000, relies on narrow-width extracted ion chromatograms (nwXICs) in single MS or tandem MS/MS mode, typically below 0.05 Da. Compared to unit XICs, nwXICs dramatically improve the signal-to-noise ratio (S/N) and therefore the lower limit of quantification (LLOQ) due to the reduction of chemical noise and/or the increased selectivity. Several designs of high-resolution analyzers are commercially available, including the time-of-flight hybrid instruments (QqTOF, TOF/TOF) and the Fourier-Transform MS (Orbitrap and FTICR). Until recently these instruments were not commonly involved in bioanalysis, due to a restricted dynamic range and a relatively slow acquisition rate compared to a triple quadrupole operating in the SRM mode. The MS cycle time is indeed critical when the width of a chromatographic peak at half height is narrowed to few seconds with analytical column packed with sub-2 lm particles. The stability of the mass accuracy, which is below 5 ppm on most recent instruments, is also an important aspect to consider for data consistency when nwXIC quantification methods are employed. The latest QqTOF instruments benefit from high mass accuracies and higher acquisition speed (up to 100 Hz) in addition to an intra-run or inter-run automated calibration system that makes this platform more suited to quantification [48]. Recent designs of the Orbitrap can acquire data at 12 Hz and adapt in real-time the accumulation of ions in the C-trap to avoid space-charging effects and optimize sensitivity [49]. The addition of a quadrupole to this instrumental design goes a step further by filtering the flux of precursor ions (Q Exactive) [50]. HRMS potentially discriminates peptides on the fullscan spectra and thus the quantification by nwXICs is directly possible without a CID-fragmentation step. The feasibility of this approach was demonstrated for peptide quantification on both QqTOF and Orbitrap platforms [49,51,52]. In this instance, several windows of the most abundant isotopic peaks from several charge states of the same peptide can be summed for enhancing the signalto-noise ratio and improving the LLOQ. Unlike SRM acquisition performed on triple-quadrupole instruments, the high-resolution full scan makes possible the retrospective analysis of untargeted compounds at the time of the acquisition. Furthermore, the HR-SRM approach relies on acquiring full-scan MS/MS spectra at high resolution [53]. This technique advantageously captures http://www.elsevier.com/locate/trac
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Q1
Mass Spectrometer Geometry
Acquisition Mode
Triple Quadrupole Linear Ion Trap
Low Resolution MS
q2
Q3/LIT
Quadrupole –Time-of-Flight
TOF
Quadrupole-Orbitrap
Selected Ion Monitoring (SIM) Selected Reaction Monitoring (SRM) Scheduled or Windowed Selected Reaction Monitoring (sSRM) Selected Reaction Monitoring Cubed (SRM3)
High Resolution MS narrow window Extracted Ion Current (nwXIC) High Resolution SRM (HRSRM) or Parallel SRM MS Everything (MSE) or MSALL Sequential Windowed acquisition of All THeoretical ions (SWATH)
High Resolution MS narrow window Extracted Ion Current (nwXIC) High Resolution SRM (HRSRM) or Parallel SRM Single or Multiple Q1 isolation Window
Orbitrap Figure 4. Various MS geometries and acquisition modes for quantitative analysis.
complete information on precursor-ion fragmentation with minimal MS/MS optimization and consequently provides a more confident identification, but is limited to defined precursor ions. Several fragment signals can be summed to increase the signal intensity and to improve the peak integration. With HRMS instruments, slightly lower quantitative performances were reported compared to QqQ but significantly less method development was required and data analysis was straightforward [54]. Recently, alternative approaches were based on a data-independent acquisition (DIA) scheme that aims to collect all data in a single analysis. While targeted approaches based on triple quadrupoles still provide the best accuracy, precision, sensitivity, and throughput, they suffer from a lack of flexibility regarding the post8
acquisition selection of alternative precursor or fragment ions and still require quite extensive method development. High-resolution data-dependent acquisition allows simultaneous qualitative and quantitative analyses but quantification is limited to the survey MS mode only. An alternative acquisition scheme, enabling all data to be acquired in a single analysis, was developed based on the DIA strategy where mass isolation of the precursor ion is not performed or is performed with single or multiple Q1 isolation windows of 10–100 m/z units. The fragment ions are measured by ion trap [55], time-of-flight [56] or Orbitrap mass analyzer [57]. While these approaches are mainly developed for proteomic analyses based on accurate mass, the Sequential Windowed acquisition of All THeoretical ions (SWATH) has also been used on a QqTOF instrument for QUAL/QUAN bioanalysis of
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low-molecular-weight compounds. The main advantage of this approach, which could also be used for biopharmaceuticals, is the reduced time for MS-method development and the ability of post-acquisition quantification and identification in the MS/MS mode. DIA approaches can be performed on QqTOF and Orbitrap platforms, but, when coupling with ultra-high performance LC (UHPLC), one has to consider the different MS cycle time of both instrumental platforms [58].
6. Perspectives Quantification of biopharmaceuticals in biological matrices remains challenging for two major reasons: (1) protein quantification is based on signature peptides used as surrogates of the protein of interest; and, (2) peptides present in those matrices can interfere with the selectivity of the measurement and affect the assay accuracy. As for bioanalysis of low-molecular-weight compounds, triple quadrupole and triple quadrupole linear ion trap are instruments well suited to this task, regarding sensitivity, dynamic range, precision and accuracy. Selectivity can be further improved using an additional fragmentation step (e.g., SRM cubed). The recent commercialization of ion-mobility devices will also allow assay selectivity to be improved. While QqQ may be used more for routine assays, high-resolution approaches may find their place in drug-discovery type bioanalysis. A summary of the different instruments use for quantitative analysis is given in Fig. 4. DIA modes (e.g., SWATH) will certainly play an important role in future, particularly for drug-discovery type of work, but still require software development for efficient, straightforward data processing. In bioanalysis, sample volume is generally not a limitation and most of the assays are based on 2-mm i.d. columns for their robustness and ease of use, while proteomics assays are generally performed with nanoLC. Capillary columns or micro-columns (0.3–1.0 mm i.d.) could be a good compromise regarding sample throughput and improved sensitivity. Finally, electrospray ionization is currently ionization technique the most used with LC-MS, but matrix-assisted laser desorption ionization (MALDI) performs well for peptide analysis and may be very well suited to highthroughput methods with or without chromatography [59]. References [1] G. Walsh, Nat. Biotechnol. 28 (2010) 917. [2] D. Vordermark, H.M. Said, A. Katzer, T. Kuhnt, G. Hansgen, J. Dunst, M. Flentje, M. Bache, BMC Cancer 6 (2006) 207. [3] E. Ezan, M. Dubois, F. Becher, Analyst (Cambridge, UK) 134 (2009) 825.
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Analysis of biopharmaceutical proteins in biological matrices by LC-MS/MS II. LC-MS/MS analysis Ge´rard Hopfgartner, Antoine Lesur, Emmanuel Varesio The first section of Part II describes the current strategies for mass spectrometric (MS) detection in the selected reaction monitoring (SRM) mode which has become the method of choice to quantify peptides. We then discuss the selection of signature peptides, SRM transitions and labeled internal-standard peptides to obtain the best assay selectivity. We also present improved assay selectivity on triple-quadrupole linear ion trap using MS3 and differential mobility MS. We dedicate the final section to alternative approaches based on high-resolution data-independent acquisition. ª 2013 Elsevier Ltd. All rights reserved. Keywords: Biopharmaceuticals, Peptide; Protein, Quantitative analysis, Selected reaction monitoring (SRM), Assay selectivity; Biological matrix; Signature peptide; High resolution mass spectrometry, Ion mobility, MSn
1. Introduction Ge´rard Hopfgartner*, Antoine Lesur, Emmanuel Varesio Life Sciences Mass Spectrometry, School of Pharmaceutical Sciences, University of Geneva, Quai Ernest Ansermet 30, CH-1211 Geneva 4, Switzerland
*
Corresponding author. Tel.: +41 (0) 22 379 63 44; Fax: +41 (0) 22 379 33 32; E-mail: gerard.hopfgartner@ unige.ch
Biopharmaceuticals represent a significant portion of the pharmaceuticals market. In 2009, sales of biologics totaled $99 billion, 12% of the total market, including the $38 billion of the monoclonal-antibody (mAb)-related product (5% of the total market) [1]. The current gold standards for protein quantification are ligandbinding assays [e.g., enzyme-linked immunosorbent assay (ELISA)]. This analytical method is based on immuno-affinity and offers high sensitivity, but the dynamic range is often limited to one to two orders of magnitude. However, commercial assays are available for a limited number of proteins and the development of new antibodies is a time-consuming, costly process. ELISA may also suffer from selectivity issues and results can be significantly altered depending on the kit manufacturer [2]. Also, when multiplexed assays are designed, potential interferences from cross reactivity must be assessed. The alternative of protein quantification by LC-SRM/MS was recently applied to quantify therapeutic proteins (e.g., mAbs and recombinant proteins) [3–8]. The methodology took inspiration from the well-established quantification of small
molecules by LC-SRM/MS in the field of bioanalysis in the pharmaceutical industry, anti-doping, and forensics [9]. The assays tend to monitor only one protein in a large number of samples, so development and optimization of the analytical method, from sample preparation to MSdetection method, is focused on the development of a specific analytical method dedicated to the quantification of a particular target. Practically, quantification is based on the construction of calibration curves and needs to fulfill validation criteria {e.g., those of the Food and Drug Administration (FDA) guidelines [10,11]}. The use of isotopically-labeled synthetic peptides or proteins as internal standards (ISs) is necessary to balance the fluctuations inherent to the samplepreparation and mass-spectrometer response. The most predominant biological matrices for biopharmaceuticals are plasma and serum, which contain, in addition to the abundant proteins, informative proteins (e.g., hormones, cytokines, and proteins leaked from tissues). The protein concentrations are spread over 10 orders of magnitude (albumin represents 55% of the total plasmatic proteins) [12,13], so the analytical dynamic range represents a real challenge.
0165-9936/$ - see front matter ª 2013 Elsevier Ltd. All rights reserved. doi:http://dx.doi.org/10.1016/j.trac.2013.03.008
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This article is Part II of the review on detection and quantification of therapeutic proteins in complex biological matrices. While Part I [14] focuses on various sample-preparation steps, Part II addresses mass spectrometric (MS) and chromatographic aspects, in particular the selection of signature peptides, the selectivity of the selected reaction monitoring (SRM) mode and applications of high-resolution MS (HRMS).
2. SRM detection and signature-peptide selection In bioanalysis, proteins are not frequently quantified in their intact form (top-down) by LC-MS(/MS) because they display a broad range of size and chemical properties that require specific chromatographic and MS ionization conditions to be measured. In the bottom-up approach, the specific peptides resulting from an enzymatic digestion are analyzed as the surrogates of the targeted proteins. For quantitative purposes, the SRM
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mode of the triple quadrupole (QqQ), introduced by Enke and Yost in 1978 [15], has become the main asset of the QqQ design. Practically, the analysis by the SRM mode is provided by the selection at unit mass of a precursor ion on quadrupole Q1 and a fragment ion, produced by collision induced dissociation (CID) in the collision cell, on quadrupole Q3 of the mass spectrometer. While, for low-molecular-weight compounds, a single Q1-Q3 transition is used for quantification and a second one for confirmatory analysis, several transitions are generally recorded in the case of peptides. Another key aspect is that the quantification is performed at a peptide level and extrapolated to the protein. Selectivity is therefore becoming a key issue regarding the selection of the peptides and the analytical measurement. As illustrated in Fig. 1, several factors (e.g., selection of the SRM transitions, sample preparation or chromatography) can affect the analytical read-out. In peptides analysis, further specificity comes because these molecules are usually ionized in electrospray under a multi-charged form
Figure 1. The selectivity of an LC-SRM/MS method depends on the monitored fragment, the chromatographic separation and the sample preparation. (A) Plasma treated by selective precipitation (45% v/v, CH3CN) before digestion. SRM transition m/z 464.8 fi m/z 244.2. (B) Plasma treated by selective precipitation (45% v/v, CH3CN) before digestion. SRM transition m/z 464.8 fi m/z 557.3. (C) Plasma treated by selective precipitation (50% v/v, CH3CN) before digestion. SRM transition m/z 464.8 fi m/z 244.2.
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but produce mainly singly-charged fragments. This property can be used to eliminate interferences from small molecules, which are often singly charged, by exclusively selecting SRM transitions with Q3 m/z values higher than the precursor-ion m/z value to exclude signals from singly-charged molecules. Due to the short time required to acquire a SRM transition (typically 5– 20 ms) several transitions can be monitored for a single analyte and several peptides can easily be measured for a single protein to enhance the selectivity of the assay. The concentration range of proteins in biological matrices, including serum and plasma, is a key challenge of analytical science. As, after digestion, the sample complexity increases, the risk of not discriminating analytes from interfering peptides becomes even more significant. Sample preparation, fractionation and chromatographic separation play important roles in mitigating these risks by reducing the chemical background before the MS acquisition. The choice of a representative proteotypic peptide, called signature and quantified as a surrogate of the protein, must fit several requirements, including: (1) detection within the ionization mode and the mass analyzer m/z range; (2) uniqueness of the amino-acid sequence in the studied proteome or sub-proteome; and, (3) to be a peptide representative of the native protein concentration that is free from post-translational modifications (PTMs), alternative splicing sites, or prone to chemical alterations. A signature peptide is characterized by an amino-acid sequence exclusively related to the targeted protein in a given proteome. The uniqueness can be verified in silico by a peptide-sequence alignment, using algorithms (e.g., BLAST-P) against the whole proteome of the studied
Q1 (z=1) Q3 (z=1)
AVSMEDQHR 1072.5 1001.4 902.4 815.3 684.3 555.3 440.2 312.2 258.1 389.2 518.2 633.3 761.3 898.4
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organism. This process implies that the investigated proteome sequences are extensively compiled in protein databases (e.g., those maintained by UniProtKB or NCBI). The selection of the signature peptides on the basis of the uniqueness of their amino-acid sequence does not address the fact that the MS system will separate peptide ions according to their m/z values and that the databases do not take into account the concentration level of the protein versus that of the biopharmaceutical. Despite a unique amino-acid sequence, some significant redundancy in the m/z values of peptide precursors and fragments exists. This is the consequence of the peptide structure, a linear polymer of 20 amino acids. For example, there are 83 isobaric and quasi-isobaric permutations between two pairs of amino acids (e.g., DQ = NE), 13 equivalent permutations between one amino acid and a pair, and 4276 permutations between a pair and a triplet [16]. Peptides that differ by such permutations will share isobaric SRM transitions except at the pair position (Fig. 2). This situation can be overcome because an orthogonal separation, such as liquid chromatography (LC) and ion mobility spectrometry (IMS), can provide additional selectivity. To assist in the selection of signature peptides, bioinformatics tools have been developed. These tools are designed to predict observable proteotypic peptides on the basis of their computed chemical properties using software (e.g., PeptideSieve) [17]. Once the sequences of signature-peptide candidates are listed for the quantification of a targeted group of proteins, their experimental detectability must be assessed. Theoretically, a complete tryptic digestion produces an equimolar mixture of peptides from a given protein. The MS responses are dramatically different, and some of the peptides are undetectable, because ionization
y8 y7 y6 y5 y4 y3 y2 b3 b4 b5 b6 b7 b8
AVSMEENHR 1072.5 1001.4 902.4 815.3 684.3 555.3 426.2 312.2 258.1 389.2 518.2 647.3 761.3 898.4
Figure 2. AVSMEDQHR and AVSMEENHR peptides. Despite their dissimilar amino-acid sequences, only two SRM transitions corresponding to y3 and b6 fragments are selective.
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efficiency, stability, and even digestion yield are peptide dependent [18]. Information on peptide detectability can be obtained from in-house unsupervised experiments (e.g., the shotgun approach) performed on representative biological samples. These experimental data tend to be shared in proteomic databases {e.g., PeptideAtlas [19], PRIDE [20] or GPM [21]}, and data can be managed by specialized software (e.g., Skyline) [22]. During the development of quantitative assays for biopharmaceutical-drug proteins, the complete SRM selection and optimization (i.e. selection of the fragments and the collision energy) are often directly performed on the purified form of the protein available from the production lines. Regarding human mAbs, the choice of signature peptides must be made within the complementary determining regions (CDRs) that contain amino-acid sequences less prone to be found in the other endogenous immunoglobulins, so, for each new mAb, a new assay has to be developed and validated. Furlong et al. [23] proposed a different approach to selecting signature peptides. Indeed, considering the assay development for human mAbs and human Fc-fusion proteins administrated to animals, amino-acid sequences between human and animal proteins are also expected to differ in the Fc region of mAbs. They have identified a universal IgG Fc region tryptic peptide common to a variety of human-protein drug candidates and not present in endogenous animal proteins. A single LC-MS/MS assay can therefore be used to support drug-discovery studies. In all cases, the ultimate confirmation of peptide-signature suitability is provided during the method-validation procedure performed according to the agency guidelines.
3. Quantification and selection of the internal standards Quantitative MS-based experiments mostly rely on the use of stable-isotope (i.e. 13C, 15N and 18O)-labeled peptides used as ISs to balance variability coming from: (1) sample preparation (e.g., reduction and alkylation, solid-phase extraction, derivatization, precipitation) and enzymatic digestion; (2) peptide separation (i.e. auto-sampler stability, injection volume and retention-time variability); (3) MS detection where suppression/enhancement effects during the ionization process can occur [24,25]. The isotopically-labeled peptides, often called heavy peptides, share the same amino-acid sequence and physico-chemical properties as their native counterparts, which are called light peptides. Consequently, the chromatographic retention times, the ionization efficiency and the CID-fragmentation patterns are equivalent for labeled and native peptide forms, and MS differentiates the heavy/light peptide pairs based on their mass shift. 4
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When a tryptic digestion of the biological sample is planned in the analytical workflow, the heavy version of lysine and arginine residues will be incorporated preferentially into the peptide sequences, since each tryptic peptide will include the labeled amino-acid residues with the exception of the protein C-terminal peptide. In quantification of endogenous proteins (biomarkers) that are generally present in all samples, therapeutic proteins are not present prior to administration and the same quantification and method validation approaches can be applied as for small molecules, based on calibration and quality-control samples. Several strategies are currently in use for introducing labeled standards in a quantitative experiment. These include use of synthetic labeled peptides, concatemers of recombinant peptides (QconCAT), fully-labeled proteins, metabolic incorporation, and labeled reagents (Fig. 3). 3.1. Isotopically-labeled synthetic peptides Barr et al. first used isotopically-labeled peptide analogs in 1996 for the quantification of apolipoprotein A-I [26]. In 2003, a similar approach was used by Gygi et al. for the absolute quantification of proteins and phosphoproteins in cell lysates leading to the term of AQUA peptides [27–29]. Nowadays, the costs of synthetic labeled peptides has significantly decreased and several providers offer a wide variety of products from relatively inexpensive bulk material to precisely dosed peptides primarily dedicated to isotopic dilution experiments. However, synthetic peptides are often provided under their lyophilized form, and stability during their storage and their solubility are not guaranteed and depend on their amino-acid sequence. It is common practice to spike peptide ISs before the enzymatic digestion to correct for the degradation of the native peptides. However, one of the key points of sample preparation in quantitative proteomics remains the tryptic digestion. Indeed, this step is not always comprehensive and the use of synthetic peptides will not balance the digestion inconsistencies between samples [30], but only the subsequent sample-preparation steps and the LC-MS/MS analysis. Therefore, the potential benefit of using synthetic peptides flanked by short amino-acid sequences from the native protein has been evaluated [31]. This strategy aims to reproduce the kinetics and the yields of native-protein digestion. Nevertheless, it appeared that no significant advantages were shown for the quantification of immuno-captured mAbs in plasma and serum [32]. Along the same line, Anderson et al. used stable-isotope peptide standards together with anti-peptide antibodies to quantitate signature peptides from several human-plasma proteins. This analytical approach is known as SISCAPA, where both the signature peptide and its labeled form are enriched by immunoaffinity chromatography prior to LC-SRM/MS analysis [33].
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Figure 3. Major internal standardization strategies using stable isotopes. SILAC and protein internal standards are based on fully isotope-labeled proteins and efficiently balance every step of the sample preparation and the tryptic digestion yield. QcontCAT and isotope-labeled synthetic peptides are often spiked before the digestion but poorly balance this step. Absolute quantification is possible with heavy protein standards, QcontCat, and isotope-labeled peptides where SILAC and isotope-labeled reagent are fitted for relative quantification. After LC-SRM/MS analysis, the chromatographic peaks are integrated and the quantification results are calculated from the light/heavy SRM peak area or height ratios. {Adapted from Brun et al. [24]}.
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3.2. QconCAT The QconCAT strategy depends on a concatemer of signature peptides expressed in a host organism as an artificial recombinant protein [34,35]. This technique provides the benefit of producing peptides that are not easily synthesized using chemistry. After production, these peptides must be released using tryptic digestion. As AQUA and QconCAT standards are generally added at late and different stages of the analytical process, there is potential bias between the two methods [36]. There is also less room for the adjustment of individual standard concentrations with the use of concatemers, because QconCAT produces an equimolar mixture of peptides after the tryptic digestion. Finally, the production costs of a recombinant protein limit this approach mainly to large-scale experiments. 3.3. Isotopically-labeled proteins Fully isotopically-labeled proteins are the golden IS for targeted quantitative proteomics [7,37,38]. Indeed, fully labeled proteins balance completely the different sources of analytical variability, including the tryptic digestion and the pre-fractionation steps based on molecular weight, size and immuno-affinity capture. In addition, the heavy form of each observable peptide that holds the labeled amino acid is produced, dramatically increasing the method-development flexibility when selectivity issues arise for the choice of the signature peptides. The chemical synthesis of proteins is almost impossible because of the specific folding and PTMs. Metabolic incorporation of stable isotopes is a much more convenient approach for the production of fully isotopicallylabeled proteins. This labeling strategy is often possible during the production of therapeutic recombinant proteins from genetically-modified cell lines. In practice, the production and purification processes of the non-labeled version are already developed. Thus, a straightforward metabolic incorporation of an essential amino acid, isotopically labeled with 13C and 15N, into the growth media can lead to the production of a heavy analog protein with limited extra costs. Because the protein IS will be purified and quantified, absolute quantification strategies can be considered. 3.4. Peptide and protein analogs Protein or peptide analogs can be a cost-effective solution as ISs because they do not require incorporation of stable isotopes. They consist of proteins or peptides with an amino-acid sequence similar to the quantified protein or peptide. Ideally, an analog should also have very similar physicochemical properties to the protein or peptide of interest to correct variations occurring during the sample preparation. Both analyte and IS peptides should preferably co-elute to balance the matrix effects. The selection of an IS protein from phylogenetically close 6
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species is often a good option. Indeed, a single aminoacid substitution, located on the sequence of the signature peptide, is a good choice [39]. Beside many options, chemical derivatization can also be considered to generate an adequate protein IS [3]. An interesting approach with sample preparation using affinity enrichment is to use a protein that binds to the same receptor. This was applied for the quantification of mAb Erbitux using an IS consisting of a commercial mouse mAb specific to human sEGFR, the target of Erbitux [40].
4. Enhanced MS selectivity at low resolution In quantitative bioanalysis, sample throughput is essential to be able to quantify hundreds of samples on a daily basis. Accurate measurement of biopharmaceuticals is also key, and relies strongly on the selectivity of the assays. There is always a trade-off regarding sample throughput and selectivity; for example, a selective sample preparation based on affinity can be achieved, but chromatographic performance, and therefore peak capacity, have to be compromised. Since proteins are quantified based on their signature peptides and considering multiply-charged precursor ions and broad isotopic distributions, the risk of interferences is much more important for peptides than for low-molecular-weight compounds [41]. Besides HRMS, two orthogonal MSbased approaches [i.e. SRM cubed (SRM3) and differential IMS (DMS)] recently became available and offer new possibilities to increase assay selectivity. 4.1. SRM cubed An option for enhancing selectivity involves adding a second stage of fragmentation (MS/MS/MS or MS3) and the observation of second-generation fragments. MS3, and MSn for that matter, can be performed in ionic traps using tandem-in-time MS/MS. However, the number of ions that can be accumulated in the ion trap must be limited to avoid space-charging effects. As a result, the overall sensitivity of MSn using ion traps is limited by the dilution of the precursor in the ionic background. This is particularly detrimental for biological samples, which generate a rich ionic background. Using a QqQLIT massspectrometer design, the fragment ions generated in Q2 are accumulated in Q3, which is operated as a linear ion trap (LIT) in this instance. After a cooling step, a firstgeneration fragment is isolated and fragmented in the linear ion trap by CID. Then, the second-generation fragments are scanned by an axial ejection. Because the first precursor is selected in Q1 and fragmented in the same manner as a regular SRM approach, the LIT accumulates only the fragments ions of the precursor ion and consequently the dilution effect of the ionic trap is circumvented [42]. Quantification by SRM3 using QqQLIT can reach limits of detection (LODs) equal to or
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lower than the regular SRM method, because of the accumulation capabilities of an ion trap and because multiple fragments can be summed. In addition, the selectivity gain reduces the need for extensive sample preparation or a long LC run. However, the cycle time of SRM3 transitions (around 250 ms) is significantly longer than conventional SRM transitions, so the SRM3acquisition mode is only able to monitor a limited number of peptides per run. 4.2. Differential IMS (DMS) Another approach to improve the selectivity of analyte quantification is to place a DMS device between the electrospray ionization source and the mass spectrometer. The separation is orthogonal to MS and the ions are differentiated based on their different ionic mobilities at high and low electric fields in an inert transport gas. Two different commercially available forms have been described: high-field asymmetric waveform IMS (FAIMS) [43] and DMS [44]. The FAIMS system employs two cylindrical electrodes for the ion separation, whereas the DMS system uses two planar electrodes. In DMS, a transport gas carries the ions and a radio frequency (RF) voltage is applied orthogonally to the ion path. This RF voltage, also called the separation voltage (SV), is an asymmetric periodic waveform that consists of a short duration high field and then an opposite low field applied so that the integrated voltage is equal to zero after one cycle. Because an ion possesses a different mobility under low and high fields, the resultant trajectory will tend toward an electrode unless a specific compensation voltage (CoV) corrects its trajectory. Finally, for a given gas-flow velocity, the CoV and SV are used to filter the trajectory of different ion species. DMS can be implemented in several modes: (1) a fixed CoV and SV adapted for particular ion species will result in the continuous mass filtering of this ion; or, (2) a fixed SV and a scanning CoV will result in a DMS spectrum with a distribution of the ion species over the CoV range. The main asset of DMS is to bring an orthogonal selectivity to the LC-SIM/SIM [45] or LC-SRM/MS [46] approaches, so co-eluting interferences can be filtered out, even in the case of isobaric precursors. However, because FAIMS and DMS are implemented after the ionization source, these methods do not prevent suppression effects that may occur during the ionization process. Moreover, the residence time of ions in FAIMS (100 ms) limits the number of compounds that can be analyzed per run. The planar geometry (DMS) allows a residence time of 20 ms, which is much closer to the typical SRM dwell time. In addition, the planar design (DMS) allows the introduction of a modifier, typically a solvent (e.g., water, methanol, acetonitrile, acetone, propanol, or butanol) in the transport-gas flow. This
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addition has been shown to change the selectivity and to enhance the separation power, depending on the modifier infused [47].
5. High-resolution mass spectrometry The quantification performed by HRMS with resolving power generally above 30,000, relies on narrow-width extracted ion chromatograms (nwXICs) in single MS or tandem MS/MS mode, typically below 0.05 Da. Compared to unit XICs, nwXICs dramatically improve the signal-to-noise ratio (S/N) and therefore the lower limit of quantification (LLOQ) due to the reduction of chemical noise and/or the increased selectivity. Several designs of high-resolution analyzers are commercially available, including the time-of-flight hybrid instruments (QqTOF, TOF/TOF) and the Fourier-Transform MS (Orbitrap and FTICR). Until recently these instruments were not commonly involved in bioanalysis, due to a restricted dynamic range and a relatively slow acquisition rate compared to a triple quadrupole operating in the SRM mode. The MS cycle time is indeed critical when the width of a chromatographic peak at half height is narrowed to few seconds with analytical column packed with sub-2 lm particles. The stability of the mass accuracy, which is below 5 ppm on most recent instruments, is also an important aspect to consider for data consistency when nwXIC quantification methods are employed. The latest QqTOF instruments benefit from high mass accuracies and higher acquisition speed (up to 100 Hz) in addition to an intra-run or inter-run automated calibration system that makes this platform more suited to quantification [48]. Recent designs of the Orbitrap can acquire data at 12 Hz and adapt in real-time the accumulation of ions in the C-trap to avoid space-charging effects and optimize sensitivity [49]. The addition of a quadrupole to this instrumental design goes a step further by filtering the flux of precursor ions (Q Exactive) [50]. HRMS potentially discriminates peptides on the fullscan spectra and thus the quantification by nwXICs is directly possible without a CID-fragmentation step. The feasibility of this approach was demonstrated for peptide quantification on both QqTOF and Orbitrap platforms [49,51,52]. In this instance, several windows of the most abundant isotopic peaks from several charge states of the same peptide can be summed for enhancing the signalto-noise ratio and improving the LLOQ. Unlike SRM acquisition performed on triple-quadrupole instruments, the high-resolution full scan makes possible the retrospective analysis of untargeted compounds at the time of the acquisition. Furthermore, the HR-SRM approach relies on acquiring full-scan MS/MS spectra at high resolution [53]. This technique advantageously captures http://www.elsevier.com/locate/trac
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Q1
Mass Spectrometer Geometry
Acquisition Mode
Triple Quadrupole Linear Ion Trap
Low Resolution MS
q2
Q3/LIT
Quadrupole –Time-of-Flight
TOF
Quadrupole-Orbitrap
Selected Ion Monitoring (SIM) Selected Reaction Monitoring (SRM) Scheduled or Windowed Selected Reaction Monitoring (sSRM) Selected Reaction Monitoring Cubed (SRM3)
High Resolution MS narrow window Extracted Ion Current (nwXIC) High Resolution SRM (HRSRM) or Parallel SRM MS Everything (MSE) or MSALL Sequential Windowed acquisition of All THeoretical ions (SWATH)
High Resolution MS narrow window Extracted Ion Current (nwXIC) High Resolution SRM (HRSRM) or Parallel SRM Single or Multiple Q1 isolation Window
Orbitrap Figure 4. Various MS geometries and acquisition modes for quantitative analysis.
complete information on precursor-ion fragmentation with minimal MS/MS optimization and consequently provides a more confident identification, but is limited to defined precursor ions. Several fragment signals can be summed to increase the signal intensity and to improve the peak integration. With HRMS instruments, slightly lower quantitative performances were reported compared to QqQ but significantly less method development was required and data analysis was straightforward [54]. Recently, alternative approaches were based on a data-independent acquisition (DIA) scheme that aims to collect all data in a single analysis. While targeted approaches based on triple quadrupoles still provide the best accuracy, precision, sensitivity, and throughput, they suffer from a lack of flexibility regarding the post8
acquisition selection of alternative precursor or fragment ions and still require quite extensive method development. High-resolution data-dependent acquisition allows simultaneous qualitative and quantitative analyses but quantification is limited to the survey MS mode only. An alternative acquisition scheme, enabling all data to be acquired in a single analysis, was developed based on the DIA strategy where mass isolation of the precursor ion is not performed or is performed with single or multiple Q1 isolation windows of 10–100 m/z units. The fragment ions are measured by ion trap [55], time-of-flight [56] or Orbitrap mass analyzer [57]. While these approaches are mainly developed for proteomic analyses based on accurate mass, the Sequential Windowed acquisition of All THeoretical ions (SWATH) has also been used on a QqTOF instrument for QUAL/QUAN bioanalysis of
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low-molecular-weight compounds. The main advantage of this approach, which could also be used for biopharmaceuticals, is the reduced time for MS-method development and the ability of post-acquisition quantification and identification in the MS/MS mode. DIA approaches can be performed on QqTOF and Orbitrap platforms, but, when coupling with ultra-high performance LC (UHPLC), one has to consider the different MS cycle time of both instrumental platforms [58].
6. Perspectives Quantification of biopharmaceuticals in biological matrices remains challenging for two major reasons: (1) protein quantification is based on signature peptides used as surrogates of the protein of interest; and, (2) peptides present in those matrices can interfere with the selectivity of the measurement and affect the assay accuracy. As for bioanalysis of low-molecular-weight compounds, triple quadrupole and triple quadrupole linear ion trap are instruments well suited to this task, regarding sensitivity, dynamic range, precision and accuracy. Selectivity can be further improved using an additional fragmentation step (e.g., SRM cubed). The recent commercialization of ion-mobility devices will also allow assay selectivity to be improved. While QqQ may be used more for routine assays, high-resolution approaches may find their place in drug-discovery type bioanalysis. A summary of the different instruments use for quantitative analysis is given in Fig. 4. DIA modes (e.g., SWATH) will certainly play an important role in future, particularly for drug-discovery type of work, but still require software development for efficient, straightforward data processing. In bioanalysis, sample volume is generally not a limitation and most of the assays are based on 2-mm i.d. columns for their robustness and ease of use, while proteomics assays are generally performed with nanoLC. Capillary columns or micro-columns (0.3–1.0 mm i.d.) could be a good compromise regarding sample throughput and improved sensitivity. Finally, electrospray ionization is currently ionization technique the most used with LC-MS, but matrix-assisted laser desorption ionization (MALDI) performs well for peptide analysis and may be very well suited to highthroughput methods with or without chromatography [59]. References [1] G. Walsh, Nat. Biotechnol. 28 (2010) 917. [2] D. Vordermark, H.M. Said, A. Katzer, T. Kuhnt, G. Hansgen, J. Dunst, M. Flentje, M. Bache, BMC Cancer 6 (2006) 207. [3] E. Ezan, M. Dubois, F. Becher, Analyst (Cambridge, UK) 134 (2009) 825.
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