TECHNICAL REVIEW Quantitative A biologist’s guide to modern techniques in

Introduction Traditional vs. new methods for quantitation Biology is the study of the dynamic changes that living Traditionally, a large majority of quantitative protein measure- things undergo over time and in response to external stimuli. ments were done by western blotting. However, western play a crucial role in structure and function of blotting almost always requires a priori knowledge of the biological systems, from being involved in cellular develop- system, the expected changes and the proteins involved to ment, differentiation, responding to therapeutic intervention, obtain the appropriate antibodies that target the protein, transporting molecules within a cell and catalyzing metabolic or proteins of interest. Antibodies are often not available, reactions. To understand the functions of individual proteins not specific, or cost prohibitive to screen large quantity of and their place in complex biological systems, it is often nec- relevant targets. Antibodies for site-specific modifications can essary to measure changes in protein abundance relative to be even more difficult to obtain with high specificity. In addi- changes in the state of the system. As such, modern tion, western blotting is sample intensive, semi-quantitative, proteomics has evolved from an exclusively qualitative has limited linear dynamic range, and typically only a single technique into one that spans a continuum of qualitative and target is quantified in each western blot. Alternatively, quantitative. Confident protein identification is a necessary liquid chromatography coupled to foundation for proteomics, and with protein identifications, (LC-MS) has emerged as a powerful technology for system- high quality quantitative data is also needed (Figure 1). wide identification and quantitation of proteins. It can be Currently, proteomics researchers are striving to close the used for both discovery-based (untargeted) and targeted gap and ensure all identified proteins are quantified with high determination of changes in protein abundance. It can also precision and accuracy to gain real, significant biological be used to measure changes in the abundance of protein- insights. specific posttranslational modifications (PTMs) and facilitate identifying the location of the modified residue. Quantitative

Modern proteomics requires exceptional mass spectrometry (MS) analyses require less sample than sensitivity to comprehensively ID western blotting, does not require the use of antibodies and proteome profiles can detect and quantify thousands of proteins in a single experiment across multiple conditions.

Identi ed proteins must be quantified in various applications with high precision and accuracy in sample

Number of Proteins identified

quantified

Protein Concentration

Figure 1. Paradigm shift in proteomics Discovery vs. targeted proteomics Coverage, throughput, method development, MS-based proteomics is divided into two parts: discovery reproducibility and precision – dilemma proteomics and targeted proteomics. Discovery proteomics Quantitative proteomics relies on balancing proteome experiments are intended to identify as many proteins as coverage, sample throughput, method development, possible across a broad dynamic range, while at the same reproducibility and precision. There are tradeoffs between time measuring the relative protein abundance changes of these analytical criteria and unfortunately, there is no one- these proteins across multiple set of samples. Discovery size fits all approach. Therefore, depending on the biological proteomics focuses on optimizing protein identification by question and the specifics of the experimental objectives, an spending more time and effort per sample and reducing appropriate workflow can be chosen to ensure analytical the number of samples analyzed. This can result in errors criteria are met that are of higher importance to the experi- in quantitative precision and accuracy, but these errors are ment. There are multiple workflows currently available for well within the acceptable range for researchers. In contrast, discovery proteomics. In general they can be split into targeted proteomics strategies limit the number of proteins isotopic labeling or label-free methods. There are tradeoffs that will be monitored and optimizes the instrument method for each technique, and proteomics researchers need to for throughput of hundreds or thousands of samples. This choose the one that best fits the question at hand. translates to high quantitative precision and accuracy with very little errors in the estimation of the protein abundances. Proteomics pipeline Typically, discovery proteomics requires longer time on analy- Discovery-based analyses – identify and quantify sis (~2 hours), while targeted proteomics make use of shorter With discovery-based quantitative analyses, the goal is MS analysis (~10-20 mins). Discovery proteomics analysis is to both identify proteins and measure their relative abun- most often used to inventory proteins in a sample or detect dance changes across multiple sample sets, usually on a differences in the abundance of proteins between multiple proteome-wide level. The multiple sample sets here could samples; targeted quantitative proteomic experiments often potentially represent different time points in a biological follow discovery proteomics to quantitate specific proteins pathway, responses to different stimulus or different cellular found during fundamental biology or drug discovery location. Several discovery based techniques have been screening (Figure 2). developed, including stable isotope labeling by amino acids in cell culture (SILAC), chemical labeling with isobaric mass tags, and label-free quantitation (LFQ).1, 2, 3

Discovery

Data High Dependent Resolution TMT 1000s Acquisition DIA Quantitation (DDA) (HR-DIA)

500 SureQuant

Scale

Quality # of Targets 100 SRM/PRM

SRM/PRM 10 Targeted

Identification Quantitative Performance (Accuracy, Precision, Dynamic Range, Reproducibility) Figure 2. The proteomics continuum LC-MS techniques for quantitative proteomics LFQ – data-dependent acquisition LFQ enables exploration of the proteome in In this approach, the ions for a given m/z range are individually greater depth isolated and fragmented. The quantitation involves extracting LFQ has gained popularity for discovery-based quantitative peptide chromatograms (MS1 precursor ion) from LC-MS runs proteomics. It does not require specific sample preparation and integrating peak areas over the chromatographic time and accommodates large numbers of diverse samples. scale or using the intensity at the highest point of the chro- There are two types of LFQ approaches differentiated by matographic peak. The resulting areas or intensities are com- how the identification (MS2) data is acquired. This is done by pared across a sample set (i.e. control vs experimental) for either data-dependent acquisition (DDA) or data-independent quantitation. LFQ DDA has demonstrated high reproducibility acquisition (DIA). and linearity at both peptide and protein levels.4 The samples that are part of the comparison study are run individually. Therefore, meticulous sample handling, sample preparation, reproducible chromatography between technical and biolog- ical replicates, and sensitive, high-resolution, accurate-mass MS are all essential (Figure 3).

Table 1. Discovery-based quantitation techniques all have specific applications and advantages

Number Precision Method Technique Type of samples Accuracy Reproducibility Coverage Benefits Drawbacks (%CV) Development per LC-MS

• Applicable to • Each sample any sample type runs individually • Cost-efficient (low throughput) sample • Requires very LFQ Relative 1 <15-20 Good Very Good Medium Low preparation reproducible (DDA) • Minimal sample LC separations handling • Requires multiple technical replicates

• Applicable to • Each sample any sample type runs individually • Cost-efficient (low throughput) sample • Requires very preparation reproducible LFQ LC separations Relative 1 <10-15 Good Very Good Medium Low • Minimal sample (DIA) handling • Requires multiple technical replicates • Spectral libraries need to be generated

• Least • Only readily susceptible to applicable to inter-sample cell cultures variations in • Increases SILAC Relative 1-3 <10-15 Good Very Good High Low sample handling MS spectral and preparation complexity • Multiplexing increases MS throughput

• Applicable to • Requires any sample type extensive fractionation or TMT Relative 1-16 <5-10 Very Good Very Good High Low • Multiplexing long chromato- increases MS graphic gradients throughput LABEL-FREE WORKFLOW (DDA) In traditional data-dependent acquisition workflows, con- Cell Culture or Tissue sistent pre-cursor and thereby protein quantitation can be Unlimited number of samples challenging to achieve due to the stochastic sampling nature of the mass spectrometer. Innovations in software algorithms Extract proteins have addressed these limitations. These algorithms extract LC-MS peaks in the raw data files and maps them to iden- tified spectra. The algorithm then detects these features across LC-MS data files using retention-time alignment and feature linking. This minimizes ‘missing data points’ and maximizes quantitative insights.

Denature, reduce alkylate and digest down-regulated up-regulated

15

LC-MS2 Each sample run indivdually 10 Reproducible e chromatography and high-resolution MS are required -Log10 P-valu 5

Automated data analysis using software MS Quantitation is performed at the MS-level by comparing 0 chromatographic peak areas for -6 -4 -2 0 2 4 6 precursor ions between indivdual Log2 Ratio raw les Application example: LFQ (DDA) analysis of pre-classified prostate MS2 cancer tissue compared to matched control (tumor free) tissue. Protein identication is performed using the accurate-mass Data shows up-regulation of 334 proteins and down-regulation of precursor information and the 430 proteins compared to healthy tissue. 6,438 proteins were fragmentation data identified across 44 samples in 3 technical replicate analysis (22 healthy vs. 22 prostate cancer tissues) in 120 minutes analysis time.

Figure 3. Schematic representation of the LFQ workflow using DDA. LFQ – data-independent acquisition DIA significantly increases coverage and reproducibility by In LFQ DIA experiments, a precursor mass range is select- acquiring MS2 data from all detected precursor ions. This ed, usually one that covers the masses of most enzymatic also makes possible retrospective data analysis. Because peptides. That range is then divided into a series of relatively no prior knowledge of expected precursors is required, wide isolation windows: for example, 25 m/z each. Chimeric DIA method development is very simple. Similar to LFQ DDA, MS2 data is acquired from all detected precursor ions in the LFQ DIA involves extracting peptide chromatograms first isolation window. That is repeated for each consecutive, (MS1 precursor ion or MS2 fragment ions) from LC-MS runs adjacent isolation window until the entire precursor mass and integrating peak areas over the chromatographic time range is covered. MS2 spectral libraries are used to identify scale. The resulting areas are compared across the sample peptides of interest from the acquired data. set for quantitation. The samples that are part of the compar- ison study are run individually (Figure 4).

LABEL-FREE WORKFLOW (DIA) Cell Culture or Tissue A Identified Protein Groups Unlimited number of samples 1800

1600 Extract proteins 1400

1200

1000

800

Protein Groups 600

400

200

0 Denature, reduce alkylate and digest Pain Control Group Constipation Ovarian Cyst Mesenteric Adenitis Urinary Tract Infection Gastroenteritis

B Significantly Changed Proteins

800

700

600 LC-MS2 Each sample run 500 indivdually 400 Reproducible chromatography 300 and high-resolution MS are required 200

100

Significantly Changed Proteins (Mann-Whitney-U-test p<0.05) 0 Ovarian Cyst Urinary Tract Constipation Mesenteric Gastroenteritis Infection Adenitis

Automated data analysis Application example: Comprehensive urinary proteome coverage using software MS by LFQ DIA workflow The workflow was applied to a urinary study comprised of Quantitation is performed at the 87 samples associated with six different differential diagnoses MS-level by comparing chromato- (abdominal pain controls, ovarian cyst, mesenteric adenitis, graphic peak areas for precursor ions between indivdual raw les constipation, urinary tract infection (UTI), gastritis, gastroenteritis). The samples were obtained from patients with abdominal pain in a pediatric emergency room. On average, 1,301 protein groups MS2 Protein identication is performed (848 -1720, A above) were detected. In total, the DIA approach using the accurate-mass precursor enabled the detection of 2,456 proteins. Compared to all other information and the fragmentation samples, 773 proteins were significantly changed in their amount 2 data searched against MS spectral in the UTI samples (non-parametric Mann-Whitney U test, p<0.05), libraries 502 in the ovarian cyst samples, 209 in the constipation samples, 111 in the mesenteric adenitis samples and 58 in the gastroenteritis Figure 4. Schematic representation of the LFQ workflow using DIA samples (B). Stable isotope labeled techniques SILAC WORKFLOW SILAC improves the throughput of discovery-based Cell Cultures 2-3 samples grown in light- and heavy-labeled amino acid media quantitative MS analyses and increases accuracy of results SILAC is a powerful and widely used method of identifying and quantifying relative changes in complex protein sam- ples. It can be applied to complex biomarker discovery and systems biology studies, as well as to isolated proteins and Combine cells protein complexes. As its name implies, the SILAC method uses in vivo metabolic incorporation of “heavy” 13C- or 15N-labeled amino acids in place of the naturally occurring isotopes for one set of samples (experimental), while another sample incorporates the “light” amino acids of natural isotope Extract proteins abundance (control). Equal amounts of protein from both cell populations are combined, digested, separated and identified by MS (Figure 5). Because peptides labeled with heavy and light amino acids are chemically and biologically identical, they behave similarly within the analytical stage, co-eluting at Denature, reduce alkylate and digest the same time during liquid chromatography (LC). However, they can easily be differentiated by a mass spectrometer owing to the mass differences of the two isotope labels.

The relative peak intensities of multiple isotopically distinct peptides from each protein are used to determine the aver- age change in protein abundance in the treated sample. The main advantage of SILAC is its early incorporation of the LC-MS2 isotope labels within the growth medium, which minimizes the number of manipulations, thus, allowing for the least amount of variation between the samples during the prepar- ative procedures. In addition, the mixing of samples permits a variety of enrichment techniques including immunopre- Automated data analysis using software cipitation. These can improve the detection of abundance MS changes for both low-abundance proteins and PTMs such as phosphorylation or glycosylation. Quantitation is performed at the MS-level by comparing the intensities of the light- and heavy-labeled precursor ions

MS2 Proteins are identified using the accurate-mass precursor information and fragmentation data

Figure 5. Schematic representation of the SILAC workflow However, achieving quantitative accuracy is highly depen- SEPT1 (known Aur substrate) dent on the purity of the precursor ion population selected ARGH2 (known Aur substrate) More in HIV 2 SLK (at mitotic spindle) for MS analysis. Innovations such as synchronous precursor KI67 (on chromosomes) selection (SPS)-based MS3 technology and Real-Time Search -infected HP1alpha (interacts w/Aur) data acquisition for SPS MS3 addresses these challenges Stathmin (known Aur substrate) providing the capability to accurately measure the most subtle changes in low-abundance proteins.9,10 Currently, up

Mitosis More in mock-infected to 16 different samples can be compared and quantified in a (Dephoure/Gygi et al, 2008) single LC-MS analysis (Figure 6). Mitosis (Olsen/Mann et al, 2010) WT

TMT WORKFLOW Cell Culture or Tissue 2-16 samples Correlation mock / HIV

MLN8054 AURK A inhib Extract proteins (Kettenbach/Gerber 2011)

Correlation HIV WT / mock

Application example: SILAC based quantitative proteomic analysis of cells infected by HIV by monitoring the changes in the global phosphorylation status of host protein.6 Aurora kinases are Denature, reduce activated by HIV infection. SILAC phosphorylation profiles comparing alkylate and digest HIV-infected to mock-infected Jurkat cells were compared to the PTMfunc database of posttranslational modification. PTMfunc identified a correlation with two independent mitosis React with TMT phosphoproteomics data sets, and an anti-correlation with an aurora isobaric chemical tags kinase inhibitor data set. Manual inspection of the most heavily phosphorylated peptides confirmed strong activation of aurora kinases in HIV-infected cells.

Combine digests

TMT labeling increases the number of samples analyzed, and peptides identified and quantified, in a single analysis Isobaric chemical tags are a more universal alternative to LC-MSn SILAC for simultaneous identification and quantitation of Up to 16 samples proteins in multiple sample sets. They can facilitate relative in a single run quantitation of a wide variety of samples including cells, tissues, and biological fluids. Thermo Scientific™ (TMT) reagents are isobaric mass tags consist- Automated data analysis ing of an MS/MS reporter group, a spacer arm, and an using software MS amine-reactive group. Amine-reactive groups covalently bind MS2 SPS MS3 to peptide N-termini or to lysine residues. After labeling, the peptides are introduced into the mass spectrometer where each tag fragments during MS2, producing unique reporter ions due to the incorporation of heavy carbon and nitrogen Peptide identification SPS MS3 acqusition Quantitation is performed at isotopes in the tag structure. Peptide quantitation is accom- using fragmentation in for only identified the MS3 level by comparing plished by comparing the intensities of the reporter ions. real time spectrum the intensities of the TMT reporter ions

Figure 6. Schematic representation of the TMT workflow A Targeted analyses – fast and sensitive quantitation

reporter ion channels Mass spectrometry-based targeted quantitation is widely 11-plex sample sets 126 127N 127C 128N 128C 129N 129C 130N 130C 131N 131C Sample Set 1 normal_1 PH-HFpEF_1 normal_2 PH-HFpEF_2 normal_3 PH-HFpEF_3 normal_4 normal_pooled PH-HFpEF_pooled mixed_pooled bridge used to determine relative or absolute abundances of pep- Sample Set 2 PH-HFpEF_4 normal_5 PH-HFpEF_5 normal_6 PH-HFpEF_6 normal_7 PH-HFpEF_7 normal_pooled PH-HFpEF_pooled mixed pooled bridge Sample Set 3 normal_8 PH-HFpEF_8 normal_9 PH-HFpEF_9 normal_10 PH-HFpEF_10 normal_11 normal_pooled PH-HFpEF_pooled mixed_pooled bridge tides of interest. It provides a high degree of accuracy and Sample Set 4 PH-HFpEF_11 normal_12 PH-HFpEF_12 normal_13 PH-HFpEF_13 normal_14 PH-HFpEF_14 normal pooled PH-HFpEF_pooled mixed_pooled bridge Sample Set 5 normal_15 PH-HFpEF_15 mixed_pooled normal_16 PH-HFpEF_16 mixed_pooled normal_17 normal_pooled PH-HFpEF_pooled mixed_pooled bridge sensitivity, and allows the profiling of hundreds of targets in a single experiment. It is a powerful, more-flexible alternative B IGF-binding protein complex acid labile subunit (P35858) to time- and resource intensive, enzyme-linked immuno-

200 180 sorbent assays (ELISAs). Targeted quantitation is frequently 151 160 140 111 applied to large sample sets to validate putative biomarkers 120 91 100 100 80 71 identified in earlier discovery experiments or to analyze wide- Abundance 60 49 40 20 scale changes in biological systems. While target peptides 0 PH-HFpEF normal normal PH-HFpEF combined bridging pooled pooled pooled channel are often selected through analysis of data from previous

IGF-binding protein 3 (P17936) discovery experiments, hypotheses and a priori knowledge 160 of targeted systems can also be used to select proteotypic 140 117 120 100 peptide targets. 100 88 81 71 80

Abundance 60 42 40 Targeted analyses provide improved quantitation sensitivity 20

0 PH-HFpEF normal normal PH-HFpEF combined bridging and, combined with increased speed of analyses, enable pooled pooled pooled channel analysis of expanded sample sets to assess the validity IGF-II (P01344) 140 of the candidate proteins. Spiking biological samples with 108 120 100 90 87 proteotypic, isotopically labeled peptide standards makes 100 88

80 59 possible the absolute quantitation of each protein or PTM of 60 Abundance

40 interest. Choosing the most appropriate quantitative pro- 20 teomics technique depends on experimental demands and 0 PH-HFpEF normal normal PH-HFpEF combined bridging pooled pooled pooled channel instrumental capabilities. This review is intended to assist the decision-making process. Several targeted quantitative tech- Application example: A TMT quantitative study in which thirty-two plasma samples from healthy donors and individuals diagnosed with niques have been developed in the past and were viewed as pulmonary hypertension heart failure with preserved ejection fraction gold standards such as selected reaction monitoring (SRM). (PH HFpEF) were analyzed in five 11-plexed sets, each set consisting The advent of high-resolution MS has enabled techniques of pooled controls and bridging channels. Protein abundances were compared across all individuals as well as between the two pooled such as parallel reaction monitoring (PRM) and SureQuant cohorts to identify potential biomarker candidates and gain insight internal standard (IS) targeted protein quantitation into the mechanism of the development and progression of the workflow.12, 13 PH-HFpEF. Several proteins were shown to have differential abundance in the PHHFpEF patients’ samples relative to the normal controls.11 IGF-binding proteins showed the most significant difference, with the abundance changes of IGF binding protein Selected Reaction Parallel Reaction SureQuant complex acid labile subunit and the IGF-binding protein 3 having the Monitoring (SRM) Monitoring (PRM) largest fold change. These were also shown to be lower in the New Paradigm The Original High-Resolution PH-HFpEF cohort. IGF-II was also detected at lower abundance for Targeted Gold Standard Accurate-Mass levels, consistent with the relative abundance level of its binding Quantitation Quantitation proteins. Table 2. Targeted quantitation techniques all have specific applications and advantages

Number Precision Method Technique Type of samples Accuracy Reproducibility Benefits Drawbacks (%CV) Development per LC-MS

• High sensitivity • Time consuming • High dynamic range assay Relative development SRM or 1 <5-10 Very Good Very Good Medium Absolute • Limited sensitivity in complex matrices

• Uses the same MS • Requires system as discovery reproducible Relative quantitation LC separations SIM or 1 <5-10 Very Good Very Good Low Absolute • Increases sensitivity • Limited 5- to 50-fold compared sensitivity in to full-scan MS complex matrices

• High selectivity, elimi- • Requires nates most interferences, reproducible providing more accuracy LC separations and attomole-level • Limited number limits of detection and of targets quantification • High sensitivity • Enables confident Relative confirmation of the PRM or 1 <5-10 Very Good Very Good Low peptide identity with Absolute spectral library matching • Fast method setup, reduces assay develop- ment time since no target transitions need to be pre-selected • Suitable for complex matrices

• Highest target multi- • Higher up front plexing capabilities in a cost of labeled single targeted analysis peptides • Enhanced acquisition efficiency enables increased throughput Relative SureQuant or 1 <5-10 Very Good Very Good Low • Reduced assay devel- Absolute opment time – spiked in internal standards guide LC-MS acquisition • Internal standard acts as detection positive control and allows absolute quantitation Selected reaction monitoring for high-throughput chemical interferences can be reduced to increase both se- Historically, targeted quantitation has been performed using lectivity and sensitivity for transitions of interest. Quantitation SRM with a triple quadrupole mass spectrometer such is performed by integrating the peak area of the transitions as Thermo Scientific™ TSQ™ triple quadrupole mass spec- over the chromatographic time scale and comparing them trometers (Figure 7). In SRM, a peptide/peptides unique to over multiple samples. SRM quantitation is extremely sen- the protein of interest are selected for targeted quantitation. sitive, reliable, and suitable for analyzing large numbers of Specific fragment ions from the target peptide along with its samples. SRM can also be used to perform absolute quan- parent mass (referred to as transitions) and retention time are titation of targeted proteins by incorporation of appropriate used to monitor the peptide across multiple sample sets. By stable isotope-labeled peptides as internal standards. using very narrow isolation windows to select the fragments,

m/z Isolation of precursor Fragmentation Isolation of fragment ion Fragment ion XIC from transition with quadrupole 1 within quadrupole 2 with quadrupole 3 spectrum (fragment ion)

m/z Isolation of precursor Fragmentation Isolation of fragment ion Fragment ion XIC from transition with quadrupole 1 within quadrupole 2 with quadrupole 3 spectrum (fragment ion) m/z Isolation of precursor Fragmentation Isolation of fragment ion Fragment ion XIC from transition with quadrupole 1 within quadrupole 2 with quadrupole 3 spectrum (fragment ion)

m/z Isolation of precursor Fragmentation Isolation of fragment ion Fragment ion XIC from transition Quantification with quadrupole 1 within quadrupole 2 with quadrupole 3 spectrum (fragment ion) of XIC from transitions (fragment ions) m/z Isolation of precursor Fragmentation Isolation of fragment ion Fragment ion XIC from transition Quantification with quadrupole 1 within quadrupole 2 with quadrupole 3 spectrum (fragment ion) of XIC from transitions m/z (fragment ions) Isolation of precursor Fragmentation Isolation of fragment ion Fragment ion XIC from transition Quantification with quadrupole 1 within quadrupole 2 with quadrupole 3 spectrum (fragment ion) of XIC from transitions (fragment ions)

m/z Isolation of precursor Fragmentation Isolation of fragment ion Fragment ion XIC from transition with quadrupole 1 within quadrupole 2 with quadrupole 3 spectrum (fragment ion)

m/z FigureIsolation 7. Schematic of precursor representationFragmentation of SRM Isolation of fragment ion Fragment ion XIC from transition with quadrupole 1 within quadrupole 2 with quadrupole 3 spectrum (fragment ion) m/z Isolation of precursor Fragmentation Isolation of fragment ion Fragment ion XIC from transition with quadrupole 1 within quadrupole 2 with quadrupole 3 spectrum (fragment ion) 4000000 200000 Hemoglobin subunit alpha, 180000 3500000 VGAHAGEYGAEALER - 510.5829+++ 160000 3000000 Thrombospondin, GTLLALER - 436.7636++ 140000 2500000 120000

2000000 100000 Thromospondin peptide 80000 1500000

Area for 60000

1000000 Area for Hemogloin suunit alpha peptide 40000 QQ Pea 500000 20000 QQ Pea

0 0 H2000 H800 K2000 K800 S1 S14 S24 S48 Sample Name

Application example: Thrombospondin and Hemoglobin subunit alpha both increase in abundance as clotting occurs in blood. Studies were conducted to examine the effect on these proteins during sample collection and preparation methods.14 These samples were either spun at 2000 RCF for 30 min or 800 RCF for 5 minutes (in Heparin or K2EDTA vacutainers). The serum samples (S1-S48) were left on the benchtop for 1, 14, 24 and 48 hours prior to sample prep, which increases the chance of clotting. This highly multiplexed targeted method on the triple quadrupole MS detected significant increases in the peak area for samples spun at lower RCF, and for serum sitting on the bench top. In addition, Heparin vacutainers appeared to minimize the incidence of clotting, with lower overall peak areas for these 2 proteins. Selected ion monitoring for flexibility MS to isolate the precursor of the target peptide ion. Only Selected ion monitoring (SIM) performed on high-resolution the selected target ion is transferred to the mass analyzer accurate-mass instruments such as a Thermo Scientific™ for detection. There is no fragmentation. SIM experiments Orbitrap™ mass spectrometer provides the simplest method can also be multiplexed (msxSIM). In such experiments up to set up and the most selective and sensitive quantification. ten targets can be isolated sequentially, accumulated, and It is most suitable for quantifying tens of proteins in samples then transferred to the mass analyzer for detection in a single of medium complexity. SIM also provides higher sensitivity spectrum (Figure 8). Confirmation of the targeted peptide is for quantification of labile peptides which do not fragment accomplished using accurate-mass measurements in combi- efficiently. The SIM methodology uses the quadrupole of the nation with elution-time information.

m/z Isolation No fragmentation Detection Identification is accomplished Quantification with the quadrupole within the HCD cell with the Orbitrap analyzer using accurate-mass of XIC with elution time Figure 8. Schematic representation of SIM

Application example: Proteomics software displaying the quantification of 86 low and high abundant yeast peptides using SIM.15 All of the targeted peptides had CVs below 20% and 86% of the targeted peptides had CVs below 15%. Parallel reaction monitoring for high selectivity a target precursor ion, fragments the targeted precursor ion in High Throughput Signaling Pathway Analysis Using PRM,Multiplex also performed on -high-resolutionImmunoprecipitation accurate-mass the collision cell, and and then Fast detects the LC resulting-PRM product ions instruments, provides high selectivity, high sensitivity, and in the mass analyzer (Figure 9). Quantification is carried out by Sebastien Gallien1,2, Aaron Gajadhar3, Bhavin Patel4, Tabiwang Arrey5, Dave Sarracino2, Sarah Trusiak2, Yue Xuan2,5high-throughput, Emily Chen2 quantification with confident targeted peptide extracting one or more fragment ions’ area with a 5–10 ppm 1 2 3 4 5 Thermo Fisher Scientific, Paris, France; Thermo Fisher Scientific, PMSC, Cambridge, MA; Thermo Fisher Scientific,confirmation. San Jose, It is CA; most Thermo suitable Fisherfor quantifying Scientific, tens toRockford, hun- IL;mass Thermo window Fisher and then Scientific, comparing Bremen, the information Germany across dreds of targeted proteins in complex matrices. PRM method- multiple sample sets. ology uses the quadrupole of the mass spectrometer to isolate PRM assays were developed by Figure 4. Characterization of conventional PRM assays for AKT/mTOR surrogate peptides. ABSTRACT measuring the dilution series of the 32 Purpose: High-throughput mass spectrometry-based protein assays were developed, based on multiplex-immunoprecipitation, fast LC separations, and SIL peptides in “low” and “high” advanced PRM acquisition schemes, to support signaling pathway analysis. They were applied to the monitoring of the main protein components of AKT/mTOR complexity matrices (6-protein mix and Dilution Amount SIL signaling pathway, under“total-” or “phosphorylated-” forms. HeLa digests, respectively) points peptides (fmol) supplemented with constant amount of CC1 200.00 Methods: The analyses were performed on a Thermo Scientific™ Q Exactive™ HF-X hybrid quadrupole-Orbitrap™ mass spectrometer and a Thermo corresponding synthetic unlabeled CC2 50.00 Scientific™ Q Exactive™ HF hybrid quadrupole-Orbitrap mass spectrometer operated with several PRM-based acquisition schemes (using instrument peptides (Figure 4, left panel). Peptide CC3 12.50 programming interface in some cases). Chromatographic separations were carried out using an Evosep One system and a Thermo Scientific™ UltiMate™ 3000 assays characteristics (i.e., LOD, LOQ, CC4 3.13 RSLC system equipped for capillary flow. Various gradient lengths and MS acquisition parameter settings were employed to analyze samples of high complexity, and linearity range) were determined, CC5 0.78 m/z e.g., digests of human cell lines, and samples of low complexity obtained through multiplexed immunoprecipitation targeting proteins of AKT/mTOR pathway. as illustrated with the LOQs in low CC6 0.20 Isolation Fragmentation Detection Identification Quantification complexity matrix presented in Figure 4 CC7 0.05 Results: The developed set-ups exhibited the ability to quantify with high sensitivity several dozens of endogenous peptides in one hundred samples within one (rightwithpanel) the quadrupole. with the HCD cell with the Orbitrap analyzer using MS/MS spectrum of XIC day under high efficiency acquisition modes. Advanced PRM methods allowed further increases in analytical throughput without compromising the quality of « Blank » 0.00 quantification data when combined with multiplexed immunoprecipitation, and minor sensitivity decrease without enrichment. Figure 9. Schematic representation of PRM

INTRODUCTION Figure 5. PRM analyses of the surrogate peptides of AKT/mTOR pathway “Phospho-” and “Total-” proteins

Signaling pathways play a central role in development and disease. Precise measurements of total form and post-translational modifications (PTM) of signaling 1.E+01 TIC HCT116 untreated HCT116 stimulated proteins (e.g., phosphorylation) are vital to gain insights into mechanisms of diseases as well as to monitor therapeutic responses. Currently, monitoring of E /SIL) signaling pathways still mainly rely on immunoassays, which provide exquisite sensitivity and analytical throughput. However, LC-MS based workflows have 2 10 1.E+00

significant advantages in terms of specificity, quantification accuracy, and multiplexing capability. Here, we propose to combine multiplex immuno-precipitation of Endo proteins from the AKT/mTOR pathway with fast LC-PRM analyses to measure aberrant activation of this critical signaling pathway in cancer cell line. 1.E-01

1.E-02

MATERIALS AND METHODS 2 5 8 11 14 17 [min]20 Area ratio ( 1.E-03 Sample Preparation PHOSPHO-proteins Multiplex immunoprecipitation IRS1_1 IRS1_2 INSR_1 INSR_2 INSR_3 TSC2_1 TSC2_2 TSC2_3 AKT1_1 AKT1_2 AKT2_1 AKT2_2 AKT3_1 AKT3_2 PTEN_1 PTEN_2 IGF1R_1 IGF1R_2 IGF1R_3 MTOR_1 MTOR_2 MTOR_3 MTOR_4 GSK3B_1 GSK3B_2 GSK3B_3 Cell Culture: HCT116 cells were grown in McCoy’s 5A Media with 10% FBS/1xPenStrep to ~70-80% confluency. HCT116 cells were serum starved in 0.1% GSK3A_1 GSK3A_2 AKT1S1_1 AKT1S1_2 charcoal stripped FBS for 24 hours prior to the following treatments: untreated, stimulated (15 min hIGF-1 (100ng/mL; Cell Signaling Technology PN#8917SF)). RPS6KB1_1 RPS6KB1_2 Subsequent to treatments, cells were lysed with IP-Lysis buffer (Thermo Fisher Scientific PN#87788) supplemented with 1X HALT Protease and Phosphatase 1.E+01 TIC HCT116 untreated HCT116 stimulated inhibitor cocktail (Thermo Fisher Scientific PN#78440). Protein concentration of lysates was determined with BCA assay. /SIL) E 1.E+00 Multiplex Immunoprecipitation (mIP): The Thermo Scientific™ Pierce™ MS-Compatible Magnetic IP Kit, Protein A/G (Thermo Fisher Scientific PN#90409) was 2 10 used to screen and validate antibodies for 13 total and 12 phosphorylated AKT/mTOR pathway targets from 500μg cell lysate. Validated antibodies were Endo 1.E-01 biotinylated with the Thermo Scientific™ Pierce™ Antibody Biotinylation Kit for IP (Thermo Fisher Scientific PN#90407). The Thermo Scientific™ Pierce™ MS- 1.E-02 Compatible Magnetic IP Kit, Streptavidin (Thermo Fisher Scientific PN#90408) was used to multiplex IPs for target enrichment. IP samples were processed by an in-solution digestion method in which IP eluates were reconstituted with 6M Urea, 50mM TEAB (pH 8.5) followed by reduction, alkylation and trypsin (Thermo 1.E-03

Fisher Scientific PN#90057) digestion overnight at 37oC. The digested samples were acidified with TFA. Area ratio ( 1.E-04 MS sample preparation: A set of 32 high-purity Pierce™ stable isotopically labeled (SIL) peptides corresponding to 13 proteins from AKT/mTOR pathway was 2 5 8 11 14 17 [min]20 spiked at 20 fmol in 500 ng of HCT116, i) after mIP, or ii) with no enrichment. TOTAL-proteins Multiplex immunoprecipitation IRS1_1 IRS1_2 INSR_1 INSR_2 INSR_3 TSC2_1 TSC2_2 TSC2_3 AKT1_1 AKT1_2 AKT2_1 AKT2_2 AKT3_1 AKT3_2 PTEN_1 PTEN_2 IGF1R_1 IGF1R_2 IGF1R_3

For the preparation of the dilution series solutions in “low complexity” matrix, the set of 32 SIL peptides was spiked in various calibrated amounts (7 points from MTOR_1 MTOR_2 MTOR_3 MTOR_4 GSK3B_1 GSK3B_2 GSK3B_3 GSK3A_1 GSK3A_2 AKT1S1_1 AKT1S1_2

50 amol to 200 fmol, and one matrix blank) in 1 pmol of a 6-protein mix digest (Thermo Fisher Scientific PN#88342) supplemented with 20 fmol of synthetic RPS6KB1_1 RPS6KB1_2 unlabeled forms of the peptides. For the preparation of the dilution series solutions in “high” complexity matrix, the set of 32 SIL peptides was spiked in various 1.E+01 TIC calibrated amounts (7 points from 50 amol to 200 fmol, and one matrix blank) in 500 ng of a HeLa digest (Thermo Fisher Scientific PN#88329) supplemented /SIL) HCT116 untreated HCT116 stimulated 2E10 1.E+00 with 20 fmol of synthetic unlabeled forms of the peptides. All samples were supplemented with 30 fmol of a mixture of PRTC peptides (Thermo Fisher Scientific, PN#88321). Endo 1.E-01 1.E-02

LC-MS/MS Analysis 1.E-03

For single-signaling pathway monitoring experiments, chromatographic separations were performed on an Evosep One system (Evosep, Odense, Denmark) Area ratio ( 2 5 8 11 14 17 [min]20 1.E-04 equipped with Evosep C18 EvoTips and C18 analytical columns (3 μm, 0.1 x 80 mm operated at 1 or 1.2 µL/min, or 3 μm, 0.15 x 50 mm operated at 1.5 µL/min). For the multi-pathway monitoring experiment, chromatographic separations were performed on an UltiMate 3000 RSLC system in capillary flow mode equipped

TOTAL-proteins No immunoprecipitation IRS1_1 IRS1_2 INSR_1 INSR_2 INSR_3 TSC2_1 TSC2_2 TSC2_3 AKT1_1 AKT1_2 AKT2_1 AKT2_2 AKT3_1 AKT3_2 PTEN_1 PTEN_2 with C trap cartridges (5 µm, 0.3 x 5 mm operated at 100 µL/min) and analytical column (2 μm,, 0.15 x 150 mm operated at 3 µL/min). The various gradient IGF1R_1 IGF1R_2 IGF1R_3

18 MTOR_1 MTOR_2 MTOR_3 MTOR_4 GSK3B_1 GSK3B_2 GSK3B_3 GSK3A_1 GSK3A_2 AKT1S1_1 AKT1S1_2 lengths used are detailed in relevant figures. Evosep One and Ultimate 3000 RSLC systems were coupled to Q Exactive HF-X MS and Q Exactive HF RPS6KB1_1 RPS6KB1_2 quadrupole-Orbitrap MS instruments, respectively. The PRM assays developed for the quantification of AKT/mTOR surrogate peptides were applied to untreated and hIGF-1 stimulated HCT116 digest prepared i) Mass spectrometers were operated with several PRM-based acquisition schemes including dRT-PRM2, IS-PRM1 (using the instrument application programming Applicationby multiplex example:immunoprecipitattion Multiplex immuno-precipitationtargeting phosphoproteins ofof proteinsthe pathway from(Figure the AKT/mTOR5, upper panel), pathwayii) by multiplex with PRMimmunoprecipitation analyses to measuretargeting aberrant“total”proteins interface, iAPI). Under its main implementation (“sequential”), the IS-PRM technique alternated between i) a “watch mode”, in which internal standards (IS) were activationof the pathway of this (Figurecritical 5signaling, middle panel), pathwayand iniii) HCT116without enrichmentcancer cell(Figure line. PRM5, lower assaypanel) for. The the overallquantificationprotein digest of amountAKT/mTORinjected surrogateon the LCpeptidescolumn forwas continuously measured in their (dynamically corrected) elution time monitoring windows at fast scanning rates, and ii) a “quantitative mode” (triggered by the real- conventional PRM analyses was 0.5 µg for non-enriched samples and samples prepared by multiplex immunoprecipitation, as illustrated with the total ion time detection of the IS by means of spectral matching), which measured the corresponding pairs of IS and endogenous peptides serially over their elution applied to untreated and hIGF-1 stimulated HCT116 digest prepared i) by multiplex immunoprecipitation targeting phosphoproteins of the chromatograms displayed in left panels of Figure 5. Peptide surrogates were quantified based on the measurements of pairs of SIL and endogenous in triplicated profile, using optimized acquisition parameters (Figures 1). For all PRM, dRT-PRM, and IS-PRM (Quant. mode) experiments on Q Exactive HF-X instrument, pathway (upper panel), ii) by multiplex immunoprecipitation targeting “total” proteins of the pathway (middle panel), and iii) without enrichment LC-PRM analyses. While hIFG-1 stimulation did not induce changes in total proteins abundances, it modified the activation status of most of them, as illustrated PRM scans employed an Orbitrap resolution of 60,000 (at m/z 200) and maximum fill times of 116 ms. The watch mode of IS-PRM employed an Orbitrap (lowerby the panel).significant Peptideincrease surrogatesin the peptide wereabundance quantifiedof phosphoproteinsbased on the (especiallymeasurementsIGF1R, ofINSR, pairsand of AKTSIL andproteins) endogenous. The multiplexed in triplicateimmunoprecipitation PRM analyses.steps resolution of 7,500 (at m/z 200) and maximum fill times of 10 ms. Whileallowed hIFG-1differentiated stimulationquantification did not induceof phospho changes- and intotal total-proteins proteinsbut abundances,also quantification it modifiedof additional the peptides,phosphorylationbenefiting statusfrom theof mostdecrease of them,in sample as illustratedcomplexity and by the enrichmentsignificantof increasetargets in the peptide abundance of phosphoproteins (especially IGF1R, INSR, and AKT proteins). Figure 1. Peptide monitoring strategies in PRM and advanced PRM methods. The multiplexed immunoprecipitation steps allowed differentiated quantification of phospho- and total-proteins but also quantification of Figure 6. RNA expression of AKT/mTOR pathway components. 16 1E6 additional peptides, benefiting from the decrease in sample complexity and the enrichment of targets. 160 SIL ENDO For each IGF treatment condition, total RNA was isolated from three HCT116 pellets containing one million cells each using the Purelink RNA Mini Kit from Invitrogen. The 120 total RNA was DNase treated with Turbo DNase from Invitrogen and 10ng of the

PRM DNased treated total RNA was converted to cDNA with SuperScript IV VILO per million 80 Mastermix from Invitrogen. Ampliseq-on-Chef libraries were made with a custom [min] designed AKT pathway RNA panel and the Ion Ampliseq Kit for Chef DL8. Libraries 30 31 32 33 30 31 32 33 40 were 540 templated on the Ion Chef and sequenced on the Ion 540 chip with the Ion GeneStudio Prime. Within a dataset, total reads for each pathway gene were Kiloreads 1E6 0 normalized for sequencing coverage by converting to reads per million (rpm) and then, SIL ENDO across the datasets, the rpm counts were further normalized with a conversion factor AKT1 AKT2 IRS1 PTEN TSC2 GSK3A GSK3B IGF1R mTOR based on the average total housekeeping gene rpm. RPS6KB1 dRT-PRM

30 31 32 33 30 31 32 [min]33 Throughput Capabilities of Advanced PRM Methods

E 1 6 Figure 7. Analyses of the 32 pairs of SIL and endo. peptides surrogate of the 13 AKT/mTOR proteins. SIL SIL ENDO IS-PRM A) dRT-PRM - “100 samples/day” LC method. B) IS-PRM - “200 samples/day” LC method. WATCH Mode QUANT Mode AKT/mTOR pathway monitoring Low Res/Fill time High Res/Fill time experiments were repeated using advanced [s] [data points / peak] [s] [data points / peak] PRM methods. The higher efficiency of 3 8 3 8 dRT-PRM and IS-PRM acquisition 30 31 32 33 30 31 30 31 schemes enabled the selection of faster 2 2 Cycle time Evosep LC methods (Table 1), allowing Cycle time Sampling rate*** 100- and 200-samples/day analytical Sampling rate** 4 4 throughput, respectively, while keeping 1 1 same PRM scans settings (quant. mode for Considerations for High-Throughput LC-PRM Analysis IS-PRM). The analyses exhibited sampling rates similar to those of conventional PRM 0 0 0 0 analyses using “60 samples/day” LC 0 3 6 9 12 [min] 0 2.5 5 [min] Figure 2. Determination of the chromatographic properties of Evosep system operated at throughputs of 60- 100-, and 200-samples analyzed/day, method (Figure 7). ** For a peak width of 7s *** For a peak width of 5s based on LC-MS analysis of 15 PRTC peptides Figure 8. Limits of detection of peptides in “low” and “high” complexity matrices. PRTC Peptides 8 ELGQSGVDTYLQTK Duty Gradient Elution Avg peak Throughput A) PRM - “60 samples/day” LC method. B) dRT-PRM - “100 samples/day” LC method. 1 SSAAPPPPPR 9 GLILVGGYGTR cycle (min) length (min) window (min) width (s) The compressed gradients used with 2 GISNEGQNASIK 10 GILFVGSGVSGGEEGAR 60 samples/day 35 35 24 21 12.39 11 advanced PRM methods did not affect the Low Background High Background Low Background High Background 8 cm x 100 µm ID 3 HVLTSIGEK 11 SFANQPLEVVYSK sensitivity of measurements in low 30 30 4 DIPVPKPK 12 LTILEELR 100 samples/day complexity matrix (e.g., multiplexed 14.4 12 5.73 7 25 25 5 IGDYAGIK 13 NGFILDGFPR 8 cm x 100 µm ID immunoprecipitated samples) and only 200 samples/day moderately compromised it in a more 6 TASEFDSAIAQDK 14 ELASGLSFPVGFK 7.2 5 2.6 5 20 20 5 cm x 150 µm ID complex matrix (Figures 8 and 9). 7 SAAGAFGPELSR 15 LSSEAPALFQFDLK 15 15 # Peptides > LOD # Peptides > LOD 10 10 0.2 0.78 [fmol] 0.2 0.78 [fmol] The chromatographic properties of the Evosep system were determined from LC-MS analyses of 15 PRTC peptides, covering the typical elution range of tryptic ≤ 0.05 ≥ 1 ≤ 0.05 ≥ 1 peptides (Figure 2). Three gradient lengths (from 5 to 21 min) were evaluated on two different column formats, enabling throughputs of 60-, 100-, and 200- samples analyzed per day, owing to minimized overhead in duty cycle (≤ 3 min). Based on the total elution window and peptide chromatographic peak widths associated with each set-up, the number of peptides that can be included in conventional PRM, dRT-PRM and IS-PRM experiments were predicted (Table 1). Figure 9. Success rate and reproducibility of quantification of the 32 endogenous peptides surrogate of the 13 AKT/mTOR proteins by conventional Predictions were performed for both ideal situation under which the elution times of the peptides are evenly distributed over the LC separation, and more PRM, dRT-PRM, and IS-PRM analyses across mIP / no IP experiments. common situation under which peptide elution times are compressed into chromatographic sub-ranges. As compared with conventional PRM, the higher [%] acquisition efficiency of dRT-PRM, and especially IS-PRM, enabled significant increase in experiment scale at constant analytical throughput. 100 PRM - « 60 samples/day » throughput dRT-PRM - « 100 samples/day » throughput Table 1. Estimation of the scale achievable by PRM, dRT-PRM and IS-PRM analyses. 75 IS-PRM - « 200 samples/day » throughput

MS parametersa Monitoring Nb targets (pairs HL Nb targets (pairs HL Throughput Method MS (Res.-Fill Time) windowb peptides) – Theoreticalc,d peptides) - Typical (/2-3)d 50 60 samples/day PRM 60k - 116ms 0.9 98 32-48 60 samples/day dRT-PRM 60k - 116ms 0.45 188 62-93 25 60 samples/day IS-PRM 60k - 116mse 0.45 391 130-195 Untreated Stimulated Untreated Stimulated Untreated Stimulated 100 samples/day PRM 60k - 116ms 0.66 37 12-18 3 4 4 5 7 4 4 4 3 4 4 3 3 5 8 6 3 6 Median CV (%) 100 samples/day dRT-PRM 60k - 116ms 0.33 70 23-34 mIP Phospho-Protein mIP Total-Protein No IP Total-Protein 100 samples/day IS-PRM 60k - 116mse 0.33 149 49-74 200 samples/day PRM 60k - 116ms 0.5 15 5-7 200 samples/day dRT-PRM 60k - 116ms 0.25 28 9-13 200 samples/day IS-PRM 60k - 116mse 0.25 62 20-30 a For Q Exactive HF-X MS; b Estimated as 5-6 and 2-3 x peak width in conventional PRM and dRT-PRM/IS-PRM analyses; c For an even distribution of peptide elution times over CONCLUSIONS the LC separation; d For a sampling rate of 6 data points/peak; e In QUANT mode § The developed fast LC-PRM set-ups exhibited the ability to quantify with high sensitivity several dozens of endogenous peptides in one hundred samples within one day under high efficiency acquisition modes. § AKT/mTOR Pathway Monitoring by Fast LC-PRM Advanced PRM methods combined with multiplexed immunoprecipitation increased the throughput of pathway monitoring without compromising data quality. REFERENCES Fast LC-PRM methods were applied to Figure 3. Establishment of conventional PRM assays for AKT/mTOR surrogate peptides. the monitoring of a single signaling 1. Gallien S, Kim SY, and Domon B; Mol. Cell. Proteomics, 2015 pathway. A total of 13 proteins were [data points / peak] [s] 2. Thoeing S, Gallien S, Arrey T, Xuan Y, Lange O, Strupat K ,and Kellmann M, PO-64997, Thermo Fisher Scientific, 2017 defined as main components of 3 8 Proteins Pep. Nb Proteins Pep. Nb AKT/mTOR pathway (Figure 3, right AKT1 2 INSR 3 panel). Two to four peptides were Cycle time AKT1S1 2 IRS1 2 Sampling rate* selected as surrogate of each protein. 2 AKT2 2 MTOR 4 TRADEMARKS/LICENSING The Evosep LC method, allowing 60 4 AKT3 2 PTEN 2 samples/day analytical throughput, was GSK3A 2 RPS6KB1 2 © 2016 Thermo Fisher Scientific Inc. All rights reserved. All trademarks are the property of Thermo Fisher Scientific and its subsidiaries. Evosep and EvoTips are 1 trademarks of Evosep. All other trademarks are the property of Thermo Fisher Scientific and its subsidiaries. This information is not intended to encourage use of selected as suited to PRM analysis of GSK3B 3 TSC2 3 these products in any manner that might infringe the intellectual property rights of others. the 32 pairs of SIL and endogenous IGF1R 3 peptides corresponding to the target 0 0 proteins (Table 1 and Figure 3, left 0 3 6 9 12 15 18 21[min] # n.a., LOD > 0.78 fmol, <5 points to determine linearity panel). range, hydrophobic peptides; * For a peak width of 11s ## Carry-over in blank matrix PRM offers several advantages for targeted quantitation. This is followed by the SureQuant analysis, targeting the It eliminates most interferences, providing high accuracy and peptides of interest. Here, using the SureQuant method, attomole-level limits of detection and quantification. Since the mass spectrometer is programmed to monitor the refer- PRM generates a fragmentation spectrum for the target ence internal standard in the sample using low fill times and peptide, confident confirmation of the peptide identity can be resolution. As soon as the internal standard is detected, the obtained with spectral library matching. Furthermore, it re- instrument switches to using longer fill times and higher res- duces assay development time since target transitions don’t olution to acquire PRM data for the internal standard and the need to be preselected. endogenous peptide. The real-time management of acquisi- tion time maximizes the time devoted to analyte quantitation SureQuant IS targeted protein quantitation workflow – allowing a greater number of targets to be reliably detected a new paradigm and quantified for targeted proteomics experiments. Further- SureQuant IS targeted protein quantitation workflow builds more, the constant on-the-fly monitoring of the internal stan- upon the PRM approach by using spiked-in internal stan- dard removes the need for retention time scheduling, allowing dards to dynamically control MS acquisition parameters for a far more robust and reproducible analytical method and optimize instrument duty cycle, thereby maximizing the (Figure 10). number of productive MS scans and improving sensitivity of target detection. This enhanced efficiency enables targeted The built-in positive internal standard control provides a quantitation of far more targets than PRM while still main- definitive limit of detection (LOD) measure for the presence or taining high quantitative performance. The overall SureQuant absence of proteins in the sample addressing the common IS targeted protein quantitation workflow is comprised of need to assess protein copy number expression in many two steps. First, a survey is run to verify the detectability of molecular biology experiments. Validated instrument method the reference internal standards. The internal standards are templates for both Survey Run and SureQuant IS targeted standards of the peptides that the user of the SureQuant protein quantitation workflow analysis are provided, preset method wants to target and quantify. The survey run analy- for various Thermo Scientific™ SureQuant™ targeted assay sis only needs to be run one time at the onset of the study, kits, like the AKT/mTOR pathway kit. Generic SureQuant on a user’s preferred LC-MS configuration, and no further method templates are also available to simplify the develop- adjustment is required over time. This analysis verifies the ment of custom protein panel assays. optimal precursor ion of each internal standard peptide and the optimal associated fragment ions that can be detected. The signal intensity of the internal standard and correspond- ing triggering intensity threshold is also determined from the survey run.

1

Determine protein panel Spike SIL-labeled internal standard (IS) Select proteotypic 2 3 4 5 peptides with good peptides into sample LC-MS behavior 3.0E+05 ✓✓✓✓ ✓✓ 2.0E+05

1.0E+05 Intensit y

0.0E+05 m/z m/z MS: Watch Mode monitors for If trigger peptide detected, perform fast, If matched, Quantification Mode the presence of the SIL-labeled low resolution MS/MS (MS2); match to optimizes high quality data collection IS trigger peptides internal standard peptide library for the endogenous peptides

Figure 10. Schematic representation of SureQuant IS targeted protein quantitation workflow A key cancer biology pathway Peptide PRM SureQuant Method Method PRM SureQuant Method AENGPGPGVLVLR 1 15 IGF AQEALDFYGEVR 10 11 SIL ENDO SIL ENDO DGFYPAPDFR 0 1 1.2e7 4e4 1.2e7 4e4 ✓ ETSFNQAYGR 2 6 ≈ EGFR IR/IGFR FEI SETSVNR 0 9 * * P1P2 * GALAEAAR 5 13 * GNNLQDTLR 0 6 P1P3 * PI3K Glycogen GQPEGPLPSSSPR 0 8 synthesis GYTI SDSAPSR 0 5 16.6 16.7 16.8 16.6 16.7 16.8 16.6 16.7 16.8 16.6 16.7 16.8 mTORC2 [min] [min] [min] [min] * IDIHSC[ Carbamidomet hyl] NHEAEK 1 12 * IYNLC[ Carbamidomet hyl] AER 0 15 β SIL ENDO SIL ENDO * LC[ Carbamidomet hyl] DSGELVAIK 5 15 6e6 6e3 6e6 6e3 * LFDAPEAPLPSR 11 11 ✗ ✓ * Translation LLEYTPTAR 0 15 initiation LPFYNQDHER 0 17 Cytoskeletal LVPPFKPQVTSETDTR 0 0 rearrangement

Rapamycin NDGTFI GYK 0 13 mTORC1 NNI DDVVR 0 4 16.2 16.35 16.5 16.2 16.35 16.5 16.2 16.35 16.5 16.2 16.35 16.5 SDGSFI GYK 0 13 [min] [min] [min] [min] β * SNPTDI YPSK 0 9 * SQEVAYTDI K 1 9 Number of specta including ≥ 5 ref. fragments SSDEENGPPSSPDLDR 0 8 Growth factor 0 1–2 ≥ 3 Cell growth Receptor SVSAPQQI I NPI R 0 0 ≤ LOD Detection Quantification Kinases *Targeted MS Assay Phosphatase TFHVDTPEER 0 0 GTPAse TGI AAEEVSLPR 0 0 GAP/GEF TLDQSPELR 2 10 Translation factors Remaining proteins TPPEAIALC[ Carbamidomet hyl] SR 1 20 TTINNEYNYR 0 7 VTTVVATLGQGPER 6 15 YSFQTHDR 0 10 • Easy method set-up • Sensitive, accurate, precise • More complete quantitation

Application example: Comparison of the analytical performance of PRM and the SureQuant method. The SureQuant method was applied to the monitoring of AKT/mTOR signaling pathway in HeLa digest. The improved sensitivity afforded by the SureQuant method enabled 26 of the 30 targeted endogenous peptides to be detected and quantified compared to 11 by PRM even in the absence of target immunoprecipitation enrichment.13

Choosing the appropriate quantitative technique between technical and biological replicates, and sensitive, The selection of the appropriate quantitative proteomics high-resolution, accurate-mass mass spectrometers are all technique can be challenging due to the plethora of quanti- essential. Offline fractionation is not recommended with LFQ tative approaches currently available. The decision-making due to the negative effect on quantitation accuracy result- process must consider a number of factors, including the ing from slight variations in sample handling. The latter can experimental question at hand, complexity of the sample, the affect sample depth of analysis and limit the dynamic range resources available to the researcher such as the types of of proteins studied. mass spectrometers, instrument time, reagents and the over- all cost of the experiment. Tables 1 and 2 summarize some If instrument time and access to mass spectrometer is of the major advantages and disadvantages typically consid- limited and precise data is a requirement, then multiplexing ered when choosing a technique for quantitative proteomics. workflows using TMT are desirable. In a single analysis, mul- tiplexing TMT workflows can be used to identify and quantify Currently, LFQ is one of the more popular quantitative relative changes in complex protein samples across multiple approaches because unlimited numbers of samples can be experimental conditions (up to 16 currently). Since samples compared, samples can originate from any source, does are quantified in the same scan, coefficients of variation tend not require extensive sample preparation (e.g., labeling) and to be quite low. The mixing of the samples following digestion identification of the peptides is not restricted by the fragmen- and labeling permits a variety of fractionation and enrichment tation technique. If the researcher has access to their own techniques. These techniques can improve the detection of mass spectrometer then factors such as instrument time abundance changes for both low-abundance peptides and and labor costs can be negated, enabling such experiments PTMs such as phosphorylation and glycosylation. A wide to be performed relatively cheaply. In LFQ, where each selection of TMT kits are commercially available. These kits sample is analyzed individually and samples are extremely contain all of the reagents necessary for comparing two sam- complex, all conditions up to, and including LC analysis, ples in small profiling studies to sixteen samples in complex must be highly reproducible. Therefore, meticulous sample analyses with multiple conditions (e.g. time courses, dose handling, sample preparation, reproducible chromatography responses, replicates, and multiple-sample comparisons). If the objective of protein quantitation experiments is to References determine the protein and/or peptide expression levels of 1. Thompson, A.; Schafer, J.; Kuhn, K.; Kienle, S.; Schwarz, J.; Schmidt, G.; Neumann, T.; Johnstone, R.; Mohammed, A. K.; Hamon, C., Tandem Mass Tags: A Novel Quantifi- known targets in biological systems, then discovery based cation Strategy for Comparative Analysis of Complex Protein Mixtures by MS/MS. Anal relative quantitation experiments can be bypassed for a more Chem, 2003, 75, (8), 1895-904. focused targeted quantitation strategy. 2. Ong, S. E.; Blagoev, B.; Kratchmarova, I.; Kristensen, D. B.; Steen, H.; Pandey, A.; Mann, M., Stable Isotope Labeling by Amino Acids in Cell Culture, SILAC, as a Simple and Accurate Approach to Expression Proteomics. Mol Cell Proteomics, 2002, 1, (5), The experiments may be designed to determine either the 376-86. relative levels of the target peptide/protein or the absolute 3. Bantscheff, M.; Schirle, M.; Sweetman, G.; Rick, J.; Kuster, B., Quantitative Mass Spec- trometry in Proteomics: A Critical Review. Anal Bioanal Chem, 2007, 389, (4), 1017-31. levels. The scope of these experiments can range from the 4. Kiyonami, R.; Prakash, A.; Hart, B.; Cunniff, J.; Zabrouskov, V., Quantifying Peptides in analysis of individual samples in a research environment to Complex Mixtures with High Sensitivity and Precision Using a Targeted Approach with a the assessment of thousands of samples in a clinical research Hybrid Linear Ion Trap Orbitrap Mass Spectrometer, Thermo Scientific Application Note #500, 2010. setting. MS-based targeted quantitation requires a priori 5. Dufresne, C.; Semba, R.; Zhang, P.; Zhu, M.; Qian, J.; Gao, T.; AlJadaan, I.; AlShahwan, knowledge of the molecular targets, as well as of the general S.; Owaidha, O.; Craven, R.; Edward, D.; Mahale, A., Identifying Quantitative Protein properties of the samples in which they are contained. At a Changes in Iris Biopsies of Glaucoma Patients Using Label Free Proteomics, ASMS 2019 Poster. minimum, the scientist must know the molecular weight of 6. Eliuk, S.; Johnson, J.; Zabrouskov, V.; Krogan, N., Global In-depth Quantitative Pro- the targeted species. Knowledge of additional properties of teomic Analysis of HIV Infected Cells Using a Novel Q-OT-qIT Mass Spectrometer, ASMS the targets, such as their LC elution times, expected range of 2013 Poster. expression levels, dynamic range, as well as knowledge of the 7. Hebert, A.S.; Merrill, A.E.; Bailey, D.J.; Still, A.J.; Westphall, M.S.; Strieter, E.R.; Pagliarini, D.J.; Coon, J.J., Neutron-encoded Mass Signatures for Multiplexed Proteome characteristics of the background matrix, will all help greatly in Quantification, Nature Methods, 2013, 10, 332–4. designing a successful targeted quantitation experiment. 8. Bomgarden, R.D.; Singhal, K.; Patel, B.; Viner, R.I.; Sharma, S.; Coon, J.J.; Cox, J.H.; Rogers, J.J., Multiplex Quantitative Analysis Using NeuCode SILAC Metabolic Labeling of Signaling Protein Targets, ASMS 2017 Poster. The recently introduced SureQuant IS targeted protein quan- 9. McAlister, G.C.; Nusinow, D.P.; Jedrychowski, M.P.; Wühr, M,; Huttlin, E.L.; Erickson, titation workflow has demonstrated acquisition efficiency and B.K.; Rad, R.; Haas, W.; Gygi, S.P., MultiNotch MS3 Enables Accurate, Sensitive, and robustness, translating into a highly sensitive quantification Multiplexed Detection of Differential Expression across Cancer Cell Line Proteomes, Anal Chem. 2014, 86(14), 7150-8. workflow for large number of peptide targets (hundreds to 10. Erickson, B.K.; Mintseris, J.; Schweppe, D.K.; Navarrete-Perea, J.; Erickson, A.R.; thousands) in a wide range of samples. Its ‘load-and-play’ Nusinow, D.P.; Paulo, J.A.; Gygi, S.P., Active Instrument Engagement Combined with a execution, especially for embedded application specific kits, Real-Time Database Search for Improved Performance of Sample Multiplexing Work- flows, J Proteome Res, 2019, 18, 3, 1299-1306. significantly simplifies the user experience for non-mass 11. Snovida, S.I.; Lai,Y-C.; Flora, A.; Bomgarden, R.; Rogers, J.C. Proteomic Analysis of spectrometry experts. Plasma – Sample Preparation and Multiplexing Workflows for Relative Quantitation, ASMS 2019 Poster. Summary 12. Peterson A.C.; Russell J.D.; Bailey D.J.; Westphall M.S.; Coon J.J., Parallel reaction monitoring for high resolution and high mass accuracy quantitative, targeted proteomics. Irrespective of the method chosen, quantitative proteomics Mol. Cell. Proteom. 2012, 11, 1475–1488. provides a powerful tool that complements genetic ap- 13. Gallien, S.; Gajadhar, A.S.; Patel, B.; Kellmann, M.; Arrey, T.N.; Thoeing, C.; Harder, A.; proaches to allow for direct insight in the molecular mech- Huguet, R.; McAlister, G.; Bailey, D.; Eliuk, S.; Chen, E.L.; Xuan, Y.; Huhmer, A., Towards Turnkey Targeted Proteomics Solutions Using Internal Standard Triggered Acquisitions on anisms regulating biological processes. In recent years, a Modified Orbitrap MS, ASMS 2019 Poster steady stream of studies illuminating specific areas of biology 14. Sarracino, D.; Abbatiello, S.; Peterman, S.; Prakash, A.; Luan, S.; Martins, C.; Black- have marked the successful transition of these approaches burn, M., A Highly Effective Workflow for the Targeted Detection of Peptides in Complex Biological Sample Matrices, ASMS 2017 Poster. from proof-of-concept applications to essential components 15. Kiyonami, R.; Prakash, A.; Zabrouskov, V., Targeted Protein Quantitation of Low-Abun- of a molecular biologist’s toolkit. While the approaches will dance Yeast Proteins Using High Resolution, Accurate Mass Selected Ion Monitoring, undoubtedly improve in sensitivity, precision, and ease of ASMS 2011 Poster. use, the current landscape of techniques and technologies 16. Gallien, S.; Gajadhar, A.; Patel, B.; Arrey, T.; Sarracino, D.; Trusiak, S.; Xuan, Y.; Chen, E., High Throughput Signaling Pathway Analysis Using Multiplex-Immunoprecipitation allows one to gain rich knowledge about the molecular basis and Fast LC-PRM, Hupo 2018 Poster. of biology and disease.

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