Evaluation of large scale quantitative proteomic assay development using peptide affinity-based mass spectrometry

Stable isotope standards and capture by antipeptide antibodies (SISCAPA) couples affinity enrichment of peptides with stable isotope dilution and detection by multiple reaction monitoring mass spectrometry to provide quantitative measurement of peptides as surrogates for their respective proteins. In this report, we describe a feasibility study to determine the success rate for production of suitable antibodies for SISCAPA assays in order to inform strategies for large-scale assay development. A workflow was designed that included a multiplex immunization strategy in which up to five proteotypic peptides from a single protein target were used to immunize individual rabbits. A total of 403 proteotypic tryptic peptides representing 89 protein targets were used as immunogens. Antipeptide antibody titers were measured by ELISA and 220 antipeptide antibodies representing 89 proteins were chosen for affinity purification. These antibodies were characterized with respect to their performance in SISCAPA-multiple reaction monitoring assays using trypsin-digested human plasma matrix. More than half of the assays generated were capable of detecting the target peptide at concentrations of less than 0.5 fmol/μl in human plasma, corresponding to protein concentrations of less than 100 ng/ml. The strategy of multiplexing five peptide immunogens was successful in generating a working assay for 100% of the targeted proteins in this evaluation study. These results indicate it is feasible for a single laboratory to develop hundreds of assays per year and allow planning for cost-effective generation of SISCAPA assays.     

Selected Reaction Monitoring Mass Spectrometry for Absolute Protein Quantification

Absolute quantification of target proteins within complex biological samples is critical to a wide range of research and clinical applications. This protocol provides step-by-step instructions for the development and application of quantitative assays using selected reaction monitoring (SRM) mass spectrometry (MS). First, likely quantotypic target peptides are identified based on numerous criteria. This includes identifying proteotypic peptides, avoiding sites of posttranslational modification, and analyzing the uniqueness of the target peptide to the target protein. Next, crude external peptide standards are synthesized and used to develop SRM assays, and the resulting assays are used to perform qualitative analyses of the biological samples. Finally, purified, quantified, heavy isotope labeled internal peptide standards are prepared and used to perform isotope dilution series SRM assays. Analysis of all of the resulting MS data is presented. This protocol was used to accurately assay the absolute abundance of proteins of the chemotaxis signaling pathway within RAW 264.7 cells (a mouse monocyte/macrophage cell line). The quantification of G_i2 (a heterotrimeric G-protein α-subunit) is described in detail.     

Rapid verification of candidate serological biomarkers using gel-based, label-free multiple reaction monitoring

Stable isotope dilution-multiple reaction monitoring-mass spectrometry (SID-MRM-MS) has emerged as a promising platform for verification of serological candidate biomarkers. However, cost and time needed to synthesize and evaluate stable isotope peptides, optimize spike-in assays, and generate standard curves quickly becomes unattractive when testing many candidate biomarkers. In this study, we demonstrate that label-free multiplexed MRM-MS coupled with major protein depletion and 1D gel separation is a time-efficient, cost-effective initial biomarker verification strategy requiring less than 100 μL of serum. Furthermore, SDS gel fractionation can resolve different molecular weight forms of targeted proteins with potential diagnostic value. Because fractionation is at the protein level, consistency of peptide quantitation profiles across fractions permits rapid detection of quantitation problems for specific peptides from a given protein. Despite the lack of internal standards, the entire workflow can be highly reproducible, and long-term reproducibility of relative protein abundance can be obtained using different mass spectrometers and LC methods with external reference standards. Quantitation down to ~200 pg/mL could be achieved using this workflow. Hence, the label-free GeLC-MRM workflow enables rapid, sensitive, and economical initial screening of large numbers of candidate biomarkers prior to setting up SID-MRM assays or immunoassays for the most promising candidate biomarkers.     

Multiple Reaction Monitoring-Mass Spectrometry Enables Robust Quantitation of Plasma Proteins Regardless of Whole Blood Processing Delays That May Occur in the Clinic

Plasma is an important biofluid for clinical research and diagnostics. In the clinic, unpredictable delays—from minutes to hours—between blood collection and plasma generation are often unavoidable. These delays can potentially lead to protein degradation and modification and might considerably affect intact protein measurement methods such as sandwich enzyme-linked immunosorbent assays that bind proteins on two epitopes to increase specificity, thus requiring largely intact protein structures. Here, we investigated, using multiple reaction monitoring mass spectrometry (MRM-MS), how delays in plasma processing affect peptide-centric “bottom-up” proteomics. We used validated assays for proteotypic peptide surrogates of 270 human proteins to analyze plasma generated after whole blood had been kept at room temperature from 0 to 40 h to mimic delays that occur in the clinic. Moreover, we evaluated the impact of different plasma-thawing conditions on MRM-based plasma protein quantitation. We demonstrate that >90% of protein concentration measurements were unaffected by the thawing procedure and by up to 40-h delayed plasma generation, reflected by relative standard deviations (RSDs) of <30%. Of the 159 MRM assays that yielded quantitative results in 60% of the measured time points, 139 enabled a stable protein quantitation (RSD <20%), 14 showed a slight variation (RSD 20–30%), and 6 appeared unstable/irreproducible (RSD > 30%). These results demonstrate the high robustness and thus the potential for MRM-based plasma-protein quantitation to be used in a clinical setting. In contrast to enzyme-linked immunosorbent assay, peptide-based MRM assays do not require intact three-dimensional protein structures for an accurate and precise quantitation of protein concentrations in the original sample.     

Advances in multiplexed MRM-based protein biomarker quantitation toward clinical utility

Accurate and rapid protein quantitation is essential for screening biomarkers for disease stratification and monitoring, and to validate the hundreds of putative markers in human biofluids, including blood plasma. An analytical method that utilizes stable isotope-labeled standard (SIS) peptides and selected/multiple reaction monitoring-mass spectrometry (SRM/MRM-MS) has emerged as a promising technique for determining protein concentrations. This targeted approach has analytical merit, but its true potential (in terms of sensitivity and multiplexing) has yet to be realized. Described herein is a method that extends the multiplexing ability of the MRM method to enable the quantitation 142 high-to-moderate abundance proteins (from 31 mg/mL to 44 ng/mL) in undepleted and non-enriched human plasma in a single run. The proteins have been reported to be associated to a wide variety of non-communicable diseases (NCDs), from cardiovascular disease (CVD) to diabetes. The concentrations of these proteins in human plasma are inferred from interference-free peptides functioning as molecular surrogates (2 peptides per protein, on average). A revised data analysis strategy, involving the linear regression equation of normal control plasma, has been instituted to enable the facile application to patient samples, as demonstrated in separate nutrigenomics and CVD studies. The exceptional robustness of the LC/MS platform and the quantitative method, as well as its high throughput, makes the assay suitable for application to patient samples for the verification of a condensed or complete protein panel. This article is part of a Special Issue entitled: Biomarkers: A Proteomic Challenge.     

Mass spectrometry-based detection and quantification of plasma glycoproteins using selective reaction monitoring

Mass spectrometry-based targeted proteomics is a rapidly expanding method for quantifying proteins in complex clinical samples such as plasma. In conjunction with the stable isotope dilution method, selected reaction monitoring (SRM) assays provide unparalleled sensitivity and selectivity for detection and quantification. A crucial factor for robust SRM assays is the reduction of interference by lowering the background. This can be achieved by the selective isolation of a subproteome, such as N-glycosylated proteins, from the original sample. The present protocol includes the development and optimization of SRM assays associated with each peptide of interest and the qualification of assays in the biological matrix to establish the limits of detection and quantification. The protocol also describes the enrichment of formerly N-glycosylated peptides relying on periodate oxidation of glycan moieties attached to the proteins, their immobilization on solid supports through hydrazide chemistry, proteolysis and enzymatic release of the formerly N-glycosylated peptides.     

Using Data Independent Acquisition (DIA) to Model High-responding Peptides for Targeted Proteomics Experiments

Targeted mass spectrometry is an essential tool for detecting quantitative changes in low abundant proteins throughout the proteome. Although selected reaction monitoring (SRM) is the preferred method for quantifying peptides in complex samples, the process of designing SRM assays is laborious. Peptides have widely varying signal responses dictated by sequence-specific physiochemical properties; one major challenge is in selecting representative peptides to target as a proxy for protein abundance. Here we present PREGO, a software tool that predicts high-responding peptides for SRM experiments. PREGO predicts peptide responses with an artificial neural network trained using 11 minimally redundant, maximally relevant properties. Crucial to its success, PREGO is trained using fragment ion intensities of equimolar synthetic peptides extracted from data independent acquisition experiments. Because of similarities in instrumentation and the nature of data collection, relative peptide responses from data independent acquisition experiments are a suitable substitute for SRM experiments because they both make quantitative measurements from integrated fragment ion chromatograms. Using an SRM experiment containing 12,973 peptides from 724 synthetic proteins, PREGO exhibits a 40–85% improvement over previously published approaches at selecting high-responding peptides. These results also represent a dramatic improvement over the rules-based peptide selection approaches commonly used in the literature.Targeted proteomics using selected reaction monitoring (SRM)¹ and parallel reaction monitoring (PRM) is increasingly becoming the gold-standard method for peptide quantitation within complex biological matrices (1, 2). By focusing on monitoring only a handful of transitions (associated precursor and fragment ions) for targeted peptides, SRM experiments filter out background signals, which in turn increases the signal to noise ratio. SRM experiments are almost exclusively performed on triple-quadrupole instruments. These instruments can isolate single transitions as an ion beam and measure that beam with extremely sensitive ion-striking detectors. As a result, SRM experiments generally exhibit significantly more accurate quantitation when compared with similarly powered discovery based proteomics experiments, and frequently benefit from a much wider linear range of quantitation (3). SRM experiments often require less fractionation and can be run in shorter time on less expensive instrumentation. These factors allow researchers to greatly scale up the number of samples they can run, which in turn increases the power of their experiment.However, the process of developing an effective SRM assay is often cumbersome, as subtle differences in peptide sequence can have a profound impact on the physiochemical properties and subsquent SRM responses of a peptide. To successfully develop an SRM assay for a protein of interest, unique peptide sequences must be chosen that also produce a high SRM signal (e.g. high-responding peptides). Once identified, these high-responding peptides are often synthesized or purchased, and independently analyzed to determine the most sensitive transition pairs. Finally, the selected peptide and transition pairs must be tested in complex mixtures to screen for transitions with chemical noise interference and to validate the sensitivity of the assay within a particular sample matrix. Peptides and transitions that survive this lengthy screening process can then undergo absolute quantitation by calibrating the signal intensity against standards of known quantity.Although experimental methods have been developed to empirically determine a set of best responding peptides (4), these strategies can be time consuming and require analytical standards, which are currently unavailable for all proteins. More often than not, representative peptides are essentially chosen at random, using only a small number of criteria, such as having a reasonable length for detection in the mass spectrometer, a lack of methionine, and a preference for peptides containing proline (5). It is not uncommon for SRM assays to fail at the final validation steps simply because the peptides chosen in the first assay creation step happened to be unexpectedly poor responding peptides.In an effort to speed up the process of generating robust assays, several groups (6–9) have designed approaches to predict sets of proteotypic peptides using machine-learning algorithms. Proteotypic peptides are peptides commonly identified in shotgun proteomics experiments for a variety of reasons including high signal, low interference, and search engine compatible fragmentation. Enhanced Signature Peptide (ESP) Predictor (7) was the first successful modification of this prediction approach to use proteotypic peptides as a proxy for high-responding peptides for SRM-based quantitation. In brief, Fusaro et al. built a training data set from data-dependent acquired (DDA) yeast peptides and a proxy for their response was quantitated using extracted precursor ion chromatograms (XICs). The authors calculated 550 physiochemical properties for each peptide based on sequence alone and built a random forest classifier to differentiate between the high and low response groups. Other peptide prediction tools follow the same general methodology for developing training data sets. CONSeQuence (8) applies several machine learning strategies and a pared down list of 50 distinct peptide properties. Alternately, Peptide Prediction with Abundance (9) (PPA) uses a back-propagation neural network (10) trained with 15 distinct peptide properties selected from ESP Predictor''s 550. The authors of CONSeQuence and PPA found that their approaches outperformed the ESP Predictor on a variety of data sets.As with most machine learning-based tools, the generality of the training set to real-world data is key to the effectiveness of the resulting prediction tool. Although MS1 intensities extracted from DDA data can be useful for predicting high-responding peptides (11, 12), several factors make them less than ideal for generalizing to SRM and PRM experiments. In particular, DDA peptides must be identified before being quantified and key biochemical features beneficial for targeted analysis of transitions can reduce overall identification rates by producing fragment spectra that are difficult to interpret with typical search engines. By building training data sets on precursor intensities alone these tools ignore the fact that targeted assays actually use fragment ions for quantification. We propose that constructing training sets from DIA fragment intensities (13) will produce machine-learning tools that are more effective at modeling peptides that produce detectible transitions, rather than just proteotypic peptides.The use of digested proteins in training sets presents additional concerns. The observed variance in peptide intensities is confounded by variation in protein abundance. Converting peptide intensities to ranks can remove the dependence on varying protein levels at the cost of corrupting the training set with proteins that biochemically contain no high-responding peptides. PPA attempts to ease this concern by training with Intensity Based Absolute Quantitation values (14) for DDA peptides estimated from XICs. We hypothesize that constructing a training set from equimolar synthetic peptides removes most adverse effects of digestion from the training set, making it possible to construct a more generalizable tool.     

Multiplexed Quantitation of Endogenous Proteins in Dried Blood Spots by Multiple Reaction Monitoring - Mass Spectrometry

Dried blood spot (DBS) sampling, coupled with multiple reaction monitoring mass spectrometry (MRM-MS), is a well-established approach for quantifying a wide range of small molecule biomarkers and drugs. This sampling procedure is simpler and less-invasive than those required for traditional plasma or serum samples enabling collection by minimally trained personnel. Many analytes are stable in the DBS format without refrigeration, which reduces the cost and logistical challenges of sample collection in remote locations. These advantages make DBS sample collection desirable for advancing personalized medicine through population-wide biomarker screening. Here we expand this technology by demonstrating the first multiplexed method for the quantitation of endogenous proteins in DBS samples. A panel of 60 abundant proteins in human blood was targeted by monitoring proteotypic tryptic peptides and their stable isotope-labeled analogs by MRM. Linear calibration curves were obtained for 40 of the 65 peptide targets demonstrating multiple proteins can be quantitatively extracted from DBS collection cards. The method was also highly reproducible with a coefficient of variation of <15% for all 40 peptides. Overall, this assay quantified 37 proteins spanning a range of more than four orders of magnitude in concentration within a single 25 min LC/MRM-MS analysis. The protein abundances of the 33 proteins quantified in matching DBS and whole blood samples showed an excellent correlation, with a slope of 0.96 and an R² value of 0.97. Furthermore, the measured concentrations for 80% of the proteins were stable for at least 10 days when stored at −20 °C, 4 °C and 37 °C. This work represents an important first step in evaluating the integration of DBS sampling with highly-multiplexed MRM for quantitation of endogenous proteins.Dried Blood Spot (DBS)¹ samples have many advantages over blood serum or plasma and are the preferred clinical sample for newborn screening for metabolic diseases (1, 2). These samples are collected by pricking a newborn''s heel and spotting a drop of blood onto specially designed filter paper collection cards. Samples are then dried under ambient conditions and are usually stored with desiccant at room temperature until analysis. This sampling procedure is simpler and less invasive then intravenous blood draws, which require a trained phlebotomist. Not surprisingly, the majority of adult patients prefer the small lancet used in finger-prick blood sampling methods to the larger needles used in intravenous blood draws (3, 4). Unlike plasma or serum samples, which consume ≥250 μl of blood and must be centrifuged within an hour of collection, DBS samples can be prepared using a volume of only 10 μl, and do not require any specialized equipment at the collection site (5). The simplicity and reduced safety risks associated with DBS sampling enables collection by minimally trained staff or by the patients themselves. In addition, many analytes are stable in the DBS format at room temperature, reducing sample transportation and storage costs, as well as the impact on the environment. Finally, DBS samples are safer to transport and are considered exempt from dangerous goods regulations (6, 7). These advantages make DBS sampling very attractive for advancing personalized medicine and population-based biomarker research (8).Numerous biomolecular targets covering genomics, metabolomics, and proteomics applications have been quantified in DBS samples using a wide array of analytical techniques (9). The most common clinical application of DBS sampling is screening newborns for metabolomics disorders by targeting small molecule biomarkers. Early screening programs relied on bacterial inhibition assays and later immunoassays, both of which required a different assay for each target of interest (2). However, the time and cost required to perform each assay independently has limited the number of diseases that could be screened nationwide to only a handful. In addition, a single biomarker often lacked the specificity to produce a definitive diagnosis, requiring extensive secondary testing. Hemoglobin is the only protein that is commonly targeted in DBS samples, and primary screening is accomplished by high-performance liquid chromatography (HPLC) or isoelectric focusing (IEF) methods (2). Similar to small-molecule screening methods, these approaches are low-throughput and are not amendable to multiplexing with additional protein targets. In newborn screening programs, these challenges associated with small molecule analysis were overcome with the introduction of multiple reaction monitoring mass spectrometry (MRM-MS) into the clinical laboratories (1, 10). The specificity of MRM enables hundreds of analytes to be monitored during a single experiment to facilitate the development of highly multiplexed assays. The addition of stable isotope-labeled internal standards (SIS) enables the acquisition of highly reproducible results across a variety of instrumentation at different institutions. It is now common for 20–30 small molecule targets including amino acids, fatty acid acylcarnitines, and organic acid acylcarnitines to be analyzed by flow injection MRM-MS, at a cost of $10–20 USD per patient sample (11). Expansion of the screening panel to include additional small-molecule biomarkers on an existing platform may cost less than $1 each. In addition to newborn screening, DBS sampling combined with MS is also gaining acceptance in small-molecule drug development (12, 13). Here the collection of smaller blood volumes allows serial sampling from mice reducing the total number of animals required to generate preclinical toxicology and pharmacokinetic data (5).Despite the successful use of DBS samples in MS-based experiments for small molecule analysis, there have been few reports of using this technology for protein targets (13). Daniel and coworkers reported a screening method for identifying β-thalassemia using the well-known biomarker HbA₂, a hemoglobin variant composed of two alpha- and two delta-globin subunits (14). Proteins were extracted in an aqueous solution, digested with trypsin in 30 min and infused for MRM-MS analysis. Multiple hemoglobin peptides were targeted to measure the abundance of the delta-globin chain, using peptides from the beta-globin chain as an internal standard. This ratio correlated well with the abundance of intact HbA₂ as determined by a well-established HPLC method. The shorter acquisition time and the increased specificity of the MS-based method showed promise for improving population-wide screening. Boemer et al. used a similar flow injection MRM-MS strategy to screen newborns for hemoglobin variants associated with sickle cell disease (15). They analyzed more than 2000 DBS samples by targeting tryptic peptides that were unique to four different beta-globin mutations and compared their results with a standard IEF method that measured the intact proteins obtained from corresponding whole blood samples. Their flow injection MRM approach was able to identify the correct phenotype for all targeted variants. Recently, deWilde et al. reported a method for screening newborn DBS samples for ceruloplasmin, a protein linked to Wilson''s disease (16). Their method combined SIS peptides with LC/MRM-MS and produced results similar to those from an immunoassay for the analysis of seven patient samples. The monitoring of a therapeutic protein in rat blood was demonstrated with Kehler et al. to evaluate the suitability of this approach for supporting preclinical trials (17). Finally, a multiplexed approach was presented by Sleczka et al. for the simultaneous quantitation of two therapeutic proteins in spiked DBS samples collected from several animal models (18).In all previous methods, only one to two proteins were targeted in DBS samples and therefore the true multiplexing capabilities of MRM were not realized. MRM-based methods using SIS peptides have already proven proficient at highly multiplexed quantitation of proteins in plasma and serum samples (19–21). Our current work demonstrates the potential for integrating DBS sampling with LC/MRM-MS for highly multiplexed quantitation of endogenous proteins. Many of the 60 proteins that we have targeted have been cleared or approved by FDA, and are already being analyzed one at a time in clinical laboratories. The assay developed in this study includes a highly reproducible method for extracting multiple proteins from DBS samples followed by trypsin digestion and surrogate peptides, along with their SIS analogs, were analyzed by a standard-flow LC/MRM-MS platform that has previously been shown to give accurate, sensitive, and robust analysis of proteotypic peptides in human plasma (21, 22). The quantitative results from whole blood and the corresponding DBS samples were compared, and the integrity of DBS samples stored under various temperatures has been evaluated.     

How specific is my SRM?: The issue of precursor and product ion redundancy

Selected reaction monitoring (SRM) MS is proving to be a popular approach for targeted quantitative proteomics. The use of proteotypic peptides as candidates for SRM analysis is a wise first step in SRM method design. The obvious reason for this is the need to avoid redundancy at the sequence level, however this is incidental. The true reason is that homologous peptides result in redundancy in the mass‐to‐charge domain. This may seem like a trivial subtlety, however, we believe this is an issue of far greater significance than the proteomic community is aware. This VIEWPOINT article serves to highlight the complexity associated with designing SRM assays in light of potential ion redundancy.     

Precision of heavy-light peptide ratios measured by maldi-tof mass spectrometry

We have investigated the precision of peptide quantitation by MALDI-TOF mass spectrometry (MS) using six pairs of proteotypic peptides (light) and same-sequence stable isotope labeled synthetic internal standards (heavy). These were combined in two types of dilution curves spanning 100-fold and 2000-fold ratios. Coefficients of variation (CV; standard deviation divided by mean value) were examined across replicate MALDI spots using a reflector acquisition method requiring 100?000 counts for the most intense peak in each summed spectrum. The CV of light/heavy peptide centroid peak area ratios determined on four replicate spots per sample, averaged across 11 points of a 100-fold dilution curve and over all six peptides, was 2.2% (ranging from 1.5 to 3.7% among peptides) at 55 fmol total (light + heavy) of each peptide applied per spot, and 2.5% at 11 fmol applied. The average CV of measurements at near-equivalence (light = heavy, the center of the dilution curve) for the six peptides was 1.0%, about 17-fold lower CV than that observed when five peptides were ratioed to a sixth peptide (i.e., a different-sequence internal standard). Response curves across the 100-fold range were not completely linear but could be closely modeled by a power law fit giving R(2) values >0.998 for all peptides. The MALDI-TOF MS method was used to determine the endogenous level of a proteotypic peptide (EDQYHYLLDR) of human protein C inhibitor (PCI) in a plasma digest after enrichment by capture on a high affinity antipeptide antibody, a technique called stable isotope standards and capture by anti-peptide antibodies (SISCAPA). The level of PCI was determined to be 770 ng/mL with a replicate measurement CV of 1.5% and a >14?000-fold target enrichment via SISCAPA-MALDI-TOF. These results indicate that MALDI-TOF technology can provide precise quantitation of high-to-medium abundance peptide biomarkers over a 100-fold dynamic range when ratioed to same-sequence labeled internal standards and enriched to near purity by specific antibody capture. The robustness and throughput of MALDI-TOF in comparison to conventional nano-LC-MS technology could enable currently impractical large-scale verification studies of protein biomarkers.     

MRMaid 2.0: Mining PRIDE for Evidence-Based SRM Transitions

Abstract Selected reaction monitoring (SRM) is becoming the tool of choice for targeted quantitative proteomics. The fundamental principle of proteomic SRM is that, for a given protein of interest, there is a set of peptides that are unique to that protein. The characteristic retention time (RT), and intact peptide m/z of these so-called proteotypic peptides are then programmed into the mass spectrometer, along with the m/z of high-intensity product ions for targeted quantitation. The particular combination of RT, peptide m/z, and product m/z for a given peptide is referred to as a transition. Selection of the most appropriate set of transitions for a given set of proteins is crucial to any SRM experiment. We previously developed the web-based MRMaid tool, which suggested the optimal transitions for a given human protein by mining spectral evidence from a small in-house database. In this article we present a completely new implementation of MRMaid, which offers substantial improvements over the original. The new version, MRMaid 2.0, uses spectra from the EBI's PRIDE database, which massively increases the coverage and quality of transitions. Transition lists can now be generated for multiple proteins simultaneously, edited within the web browser, and exported for laboratory use.     

Computational prediction of proteotypic peptides

Evaluation of: Mallick P, Schirle M, Chen SS et al. Computational prediction of proteotypic peptides for quantitative proteomics. Nat. Biotechnol. 25(1), 125–131 (2007).

Mass spectrometry, the driving analytical force behind proteomics, is primarily used to identify and quantify as many proteins in a complex biological mixture as possible. While there are many ways to prepare samples, one aspect that is common to a vast majority of bottom-up proteomic studies is the digestion of proteins into tryptic peptides prior to their analysis by mass spectrometry. As correctly highlighted by Mallick and colleagues, only a few peptides are repeatedly and consistently identified for any given protein within a complex mixture. While the existence of these proteotypic peptides (to borrow the authors’ terminology) is well known in the proteomics community, there has never been an empirical method to recognize which peptides may be proteotypic for a given protein. In this study, the investigators discovered over 16,000 proteotypic peptides from a collection of over 600,000 peptide identifications obtained from four different analytical platforms. The study examined a number of physicochemical parameters of these peptides to determine which properties were most relevant in defining a proteotypic peptide. These characteristic properties were then used to develop computational tools to predict proteotypic peptides for any given protein within an organism.     

Quantification of Cardiovascular Biomarkers in Patient Plasma by Targeted Mass Spectrometry and Stable Isotope Dilution

Verification of candidate biomarkers requires specific assays to selectively detect and quantify target proteins in accessible biofluids. The primary objective of verification is to screen potential biomarkers to ensure that only the highest quality candidates from the discovery phase are taken forward into preclinical validation. Because antibody reagents for a clinical grade immunoassay often exist for a small number of candidates, alternative methodologies are required to credential new and unproven candidates in a statistically viable number of serum or plasma samples. Using multiple reaction monitoring coupled with stable isotope dilution MS, we developed quantitative, multiplexed assays in plasma for six proteins of clinical relevance to cardiac injury. The process described does not require antibodies for immunoaffinity enrichment of either proteins or peptides. Limits of detection and quantitation for each signature peptide used as surrogates for the target proteins were determined by the method of standard addition using synthetic peptides and plasma from a healthy donor. Limits of quantitation ranged from 2 to 15 ng/ml for most of the target proteins. Quantitative measurements were obtained for one to two signature peptides derived from each target protein, including low abundance protein markers of cardiac injury in the nanogram/milliliter range such as the cardiac troponins. Intra- and interassay coefficients of variation were predominantly <10 and 25%, respectively. The configured multiplex assay was then used to measure levels of these proteins across three time points in six patients undergoing alcohol septal ablation for hypertrophic obstructive cardiomyopathy. These results are the first demonstration of a multiplexed, MS-based assay for detection and quantification of changes in concentration of proteins associated with cardiac injury in the low nanogram/milliliter range. Our results also demonstrate that these assays retain the necessary precision, reproducibility, and sensitivity to be applied to novel and uncharacterized candidate biomarkers for verification of proteins in blood.Discovery of disease-specific biomarkers with diagnostic and prognostic utility has become an important challenge in clinical proteomics. In general, unbiased discovery experiments often result in the confident identification of thousands of proteins, hundreds of which may vary significantly between case and control samples in small discovery studies. However, because of the stochastic sampling of proteomes in discovery “omics” experiments, a large fraction of the protein biomarkers “discovered” in these experiments are false positives arising from biological or technical variability. Clearly discovery omics experiments do not lead to biomarkers of immediate clinical utility but rather produce candidates that must be qualified and verified in larger sample sets than were used for discovery (1).Traditional, clinical validation of biomarkers has relied primarily on immunoassays because of their specificity and sensitivity for the target analyte and high throughput capability. However, antibody reagents for a clinical grade immunoassay often only exist for a short list of candidates. The development of a reliable sandwich immunoassay for one target protein is expensive, has a long development time, and is dependent upon the generation of high quality protein antibodies. For the large majority of new, unproven candidate biomarkers, an intermediate verification technology is required that has shorter assay development time lines, lower assay cost, and effective multiplexing of dozens of candidates in low sample volumes. Ideally the approach should be capable of analyzing hundreds of samples of serum or plasma with good precision. The desired outcome of verification is a small number of highly credentialed candidates suitable for traditional preclinical and clinical validation studies.Multiple reaction monitoring (MRM)¹ coupled with stable isotope dilution (SID) MS has recently been shown to be well suited for direct quantification of proteins in plasma (2–4) and has emerged as the core technology for candidate biomarker verification. MRM assays can be highly multiplexed such that a moderate number of candidate proteins (in the range of 10–50) can be simultaneously targeted and measured in the statistically viable number of patient samples required for verification (hundreds of serum samples). However, sensitivity for unambiguous detection and quantification of proteins by MS-based assays is often constrained by sample complexity, particularly when the measurements are being made in complex fluids such as plasma.Many biomarkers of current clinical importance, such as prostate-specific antigen and the cardiac troponins, reside in the low nanogram/milliliter range in plasma and, until recently, have been inaccessible by non-antibody approaches. Our laboratory has recently shown for the first time that a combination of abundant protein depletion with limited fractionation at the peptide level prior to SID-MRM-MS provides robust limits of quantitation (LOQs) in the 1–20 ng/ml range with coefficient of variation (CV) of 10–20% at the LOQ for proteins in plasma (3).Here we demonstrate that this work flow can be extended to configure assays for a number of known markers of cardiovascular disease and, more importantly, can be deployed to measure their concentrations in clinical samples. We modeled a verification study comprising six patients undergoing alcohol septal ablation treatment for hypertrophic obstructive cardiomyopathy, a human model of “planned” myocardial infarction (PMI), and obtained targeted, quantitative measurements for moderate to low concentrations of cardiac biomarkers in plasma. This work provides additional evidence that MS-based assays can be configured and applied to verification of new protein targets for which high quality antibody reagents are not available.     

Multiple Reaction Monitoring-based, Multiplexed, Absolute Quantitation of 45 Proteins in Human Plasma

Mass spectrometry-based multiple reaction monitoring (MRM) quantitation of proteins can dramatically impact the discovery and quantitation of biomarkers via rapid, targeted, multiplexed protein expression profiling of clinical samples. A mixture of 45 peptide standards, easily adaptable to common plasma proteomics work flows, was created to permit absolute quantitation of 45 endogenous proteins in human plasma trypsin digests. All experiments were performed on simple tryptic digests of human EDTA-plasma without prior affinity depletion or enrichment. Stable isotope-labeled standard peptides were added immediately following tryptic digestion because addition of stable isotope-labeled standard peptides prior to trypsin digestion was found to generate elevated and unpredictable results. Proteotypic tryptic peptides containing isotopically coded amino acids ([¹³C₆]Arg or [¹³C₆]Lys) were synthesized for all 45 proteins. Peptide purity was assessed by capillary zone electrophoresis, and the peptide quantity was determined by amino acid analysis. For maximum sensitivity and specificity, instrumental parameters were empirically determined to generate the most abundant precursor ions and y ion fragments. Concentrations of individual peptide standards in the mixture were optimized to approximate endogenous concentrations of analytes and to ensure the maximum linear dynamic range of the MRM assays. Excellent linear responses (r > 0.99) were obtained for 43 of the 45 proteins with attomole level limits of quantitation (<20% coefficient of variation) for 27 of the 45 proteins. Analytical precision for 44 of the 45 assays varied by <10%. LC-MRM/MS analyses performed on 3 different days on different batches of plasma trypsin digests resulted in coefficients of variation of <20% for 42 of the 45 assays. Concentrations for 39 of the 45 proteins are within a factor of 2 of reported literature values. This mixture of internal standards has many uses and can be applied to the characterization of trypsin digestion kinetics and plasma protein expression profiling because 31 of the 45 proteins are putative biomarkers of cardiovascular disease.MS is capable of sensitive and accurate protein quantitation based on the quantitation of proteolytic peptides as surrogates for the corresponding intact proteins. Over the past 10 years, MS-based protein quantitation based on the analysis of peptides (in other words, based on “bottom-up” proteomics) has had a profound impact on how biological problems can be addressed (1, 2). Although advances in MS instrumentation have contributed to the improvement of MS-based protein quantitation, the use of stable isotopes in quantitative work flows has arguably had the greatest impact in improving the quality and reproducibility of MS-based protein quantitation (3–5).The ongoing development of untargeted MS-based quantitation work flows has focused on increasingly exhaustive sample prefractionation methods, at both the protein and peptide levels, with the goal of detecting and quantifying entire proteomes (6). Although untargeted MS-based quantitation work flows have their utility, they are costly in terms of lengthy MS data acquisition and analysis times, and as a result, they are often limited to quantifying differences between small sample sets (n < 10). To facilitate rapid quantitation of larger, clinically relevant sample sets (n > 100) there is a need to both simplify sample preparation and reduce MS analysis time.Multiple reaction monitoring (MRM)¹ is a tandem MS (MS/MS) scan mode unique to triple quadrupole MS instrumentation that is capable of rapid, sensitive, and specific quantitation of analytes in highly complex sample matrices (7). MRM is a targeted approach that requires knowledge of the molecular weight of an analyte and its fragmentation behavior under CID. MRM is capable of highly reproducible concentration determination when stable isotope-labeled internal standards are included in work flows and has been used for decades for the quantitation of low molecular mass analytes (<1000 Da) in pharmaceutical, clinical, and environmental applications (7, 8).The combination of triple quadrupole MS instrumentation with nanoliter flow rate high performance LC and nanoelectrospray ionization provides the necessary sensitivity for detection and quantitation of biological molecules such as peptides in complex samples such as plasma by MRM. When combined with the use of isotopically labeled synthetic peptide standards, MRM analysis is capable of sensitive (attomole level) and absolute determination of peptide concentrations across a wide concentration scale spanning a dynamic range of 10³–10⁴ (1, 9–13).Several recent studies involving MRM-based analysis of plasma proteins have focused on increasing MRM detection sensitivity by fractionating plasma using either multidimensional liquid chromatography, affinity depletion of high abundance proteins (11, 14, 15), or affinity enrichment of low abundance peptides (16, 17). Anderson and Hunter (14) have shown that LC-MRM/MS analysis is capable of detecting 47 moderate to high abundance proteins in plasma without depletion even though ∼90% of the total protein by weight in trypsin-digested plasma can be attributed to 10 high abundance proteins (18).Relative abundance of a protein does not preclude its involvement in disease. In fact, 32 of the 47 plasma proteins detected by Anderson and Hunter (14) have been implicated as putative markers for cardiovascular disease. The ability to rapidly quantify proteins in a highly multiplexed manner using MRM and internal standard peptides expands the potential application of MRM quantitation beyond biomarker validation and into the field of biomarker discovery. Targeted, simultaneous quantitation of hundreds of proteins in a single analysis will enable rapid protein expression profiling of large (n > 100) clinically relevant sample sets in a manner similar to DNA microarray expression profiling. By allowing researchers to look at patterns of expression levels of a large number of proteins in a large number of samples (as opposed to looking at the expression levels of only a single protein), multiplexed MRM-based quantitation will allow the correlation of expression patterns with particular diseases. Once these characteristic patterns have been established, physicians will be able to use these protein expression patterns to diagnose diseases in the same way they currently use blood chemistry panels or comprehensive metabolic panels.When considering the clinical utility of MS-based assays, direct comparisons are often made to ELISA, which is considered the “gold standard” for protein quantitation in clinical samples. Attributes of ELISAs, such as “time to first result” (1–2 h (19)) and the ability to quantify 96 or 384 samples in parallel because of their microtiter plate-based format, are currently difficult to match with MS-based protein assays. However, MRM protein assays may surpass ELISA in the rapid development of clinically useful, multiplexed protein assays. The impact of multiplexed assays in the field of genomics has increased interest in multiplexed quantitation of many proteins in individual clinical samples (19). Development and characterization of MRM-based protein assays using isotopically labeled peptides is rapid and inexpensive compared with the time and cost associated with the generation and characterization of antibodies for ELISA development.In this study, we describe the creation of a customizable mixture of concentration-balanced stable isotope-labeled standard (SIS) peptides representing an initial panel of 45 human plasma proteins. We used this mixture of SIS peptides to develop a suite of multiplexed, rapid, and reproducible MRM-based assays for expression profiling of these 45 proteins in simple tryptic digests of whole plasma. Additionally we characterized the analytical performance of these MRM peptide assays with respect to their reproducibility, and we demonstrated their utility for absolute protein concentration determination.Multiplexed MRM quantitation of peptides for protein quantitation has the potential to replace iTRAQ or other isotope label and label-free quantitative proteomics approaches because the approach is much faster than these other methods (30–60 min per analysis compared with 4 days for LC-MALDI-based iTRAQ), has greater reproducibility (CV <5% versus iTRAQ CV >20%), and enables absolute quantitation (concentration and copy number versus only x-fold up- or down-regulated). Additionally MRM-based quantitation with SIS peptides does not “miss” peptides because the SIS peptide must be detected in every sample: this means that if an endogenous peptide is not observed then it is below the limit of detection.     

Quantitative Microbial Ecology through Stable Isotope Probing

Bacteria grow and transform elements at different rates, and as yet, quantifying this variation in the environment is difficult. Determining isotope enrichment with fine taxonomic resolution after exposure to isotope tracers could help, but there are few suitable techniques. We propose a modification to stable isotope probing (SIP) that enables the isotopic composition of DNA from individual bacterial taxa after exposure to isotope tracers to be determined. In our modification, after isopycnic centrifugation, DNA is collected in multiple density fractions, and each fraction is sequenced separately. Taxon-specific density curves are produced for labeled and nonlabeled treatments, from which the shift in density for each individual taxon in response to isotope labeling is calculated. Expressing each taxon''s density shift relative to that taxon''s density measured without isotope enrichment accounts for the influence of nucleic acid composition on density and isolates the influence of isotope tracer assimilation. The shift in density translates quantitatively to isotopic enrichment. Because this revision to SIP allows quantitative measurements of isotope enrichment, we propose to call it quantitative stable isotope probing (qSIP). We demonstrated qSIP using soil incubations, in which soil bacteria exhibited strong taxonomic variations in ¹⁸O and ¹³C composition after exposure to [¹⁸O]water or [¹³C]glucose. The addition of glucose increased the assimilation of ¹⁸O into DNA from [¹⁸O]water. However, the increase in ¹⁸O assimilation was greater than expected based on utilization of glucose-derived carbon alone, because the addition of glucose indirectly stimulated bacteria to utilize other substrates for growth. This example illustrates the benefit of a quantitative approach to stable isotope probing.     

A direct introduction of <Superscript>18</Superscript>O isotopes into peptides and proteins for quantitative mass spectroscopy analysis

A method for direct introduction of ¹⁸O isotopes into carboxyl groups of peptides and proteins via the exchange with H₂ ¹⁸O in the presence of TFA is described. The isotope label is sufficiently stable in a wide pH range. Since the compounds labeled by this method retain their physicochemical characteristics, they can be used as an internal standard in quantitative assay of authentic compounds in the analyzed objects by means of mass spectrometry. This method is applicable to quantitative analysis of peptides and proteins in biological environments, as well as for quantitative kinetic studies of metabolism and enzyme activity. The quantitative analysis of polypeptides and proteins is combined with trypsinolysis. When necessary, the isotope label can be simultaneously introduced into all peptides and proteins in a control biosample, making it applicable as a standard for comparative analysis of experimental biosamples.     

Systematic quantification of peptides/proteins in urine using selected reaction monitoring

The evaluation of biomarkers in bodily fluids necessitates the development of robust methods to quantify proteins in a complex background, using large sets of samples. The ability to multiplex numerous analytes in a single assay expedites the process. Liquid chromatography-mass spectrometry (LC-MS) analyses performed in selected reaction monitoring (SRM) in conjunction with stable isotope dilution MS present an effective way to detect and quantify biomarker candidates in bodily fluids. The strategy presented involves an initial qualification of predefined sets of proteins in urine. The technique was applied to detect and quantify peptides in urine samples as surrogates for a few endogenous proteins. Multiplexed assays were developed to analyze proteins associated with bladder cancer; a few exogenous proteins were added as internal standards. The sample preparation and the analytical protocols were optimized to ensure reproducibility, analytical precision, and quantification limits in the low nanogram per milliliter range. Analyses were performed using known amounts of isotopically labeled peptides. Systematic replication of the measurements indicated intra-assay and inter-assay variability, with CVs in the range of 10%. The differences measured for two targeted proteins were correlated with their level of expression in the corresponding tumors using immunohistochemistry.     

Quantitative, multiplexed assays for low abundance proteins in plasma by targeted mass spectrometry and stable isotope dilution

Biomarker discovery produces lists of candidate markers whose presence and level must be subsequently verified in serum or plasma. Verification represents a paradigm shift from unbiased discovery approaches to targeted, hypothesis-driven methods and relies upon specific, quantitative assays optimized for the selective detection of target proteins. Many protein biomarkers of clinical currency are present at or below the nanogram/milliliter range in plasma and have been inaccessible to date by MS-based methods. Using multiple reaction monitoring coupled with stable isotope dilution mass spectrometry, we describe here the development of quantitative, multiplexed assays for six proteins in plasma that achieve limits of quantitation in the 1-10 ng/ml range with percent coefficients of variation from 3 to 15% without immunoaffinity enrichment of either proteins or peptides. Sample processing methods with sufficient throughput, recovery, and reproducibility to enable robust detection and quantitation of candidate biomarker proteins were developed and optimized by addition of exogenous proteins to immunoaffinity depleted plasma from a healthy donor. Quantitative multiple reaction monitoring assays were designed and optimized for signature peptides derived from the test proteins. Based upon calibration curves using known concentrations of spiked protein in plasma, we determined that each target protein had at least one signature peptide with a limit of quantitation in the 1-10 ng/ml range and linearity typically over 2 orders of magnitude in the measurement range of interest. Limits of detection were frequently in the high picogram/milliliter range. These levels of assay performance represent up to a 1000-fold improvement compared with direct analysis of proteins in plasma by MS and were achieved by simple, robust sample processing involving abundant protein depletion and minimal fractionation by strong cation exchange chromatography at the peptide level prior to LC-multiple reaction monitoring/MS. The methods presented here provide a solid basis for developing quantitative MS-based assays of low level proteins in blood.     

Platform for establishing interlaboratory reproducibility of selected reaction monitoring-based mass spectrometry peptide assays

Mass spectrometry (MS) is an attractive alternative to quantification of proteins by immunoassays, particularly for protein biomarkers of clinical relevance. Reliable quantification requires that the MS-based assays are robust, selective, and reproducible. Thus, the development of standardized protocols is essential to introduce MS into clinical research laboratories. The aim of this study was to establish a complete workflow for assessing the transferability and reproducibility of selected reaction monitoring (SRM) assays between clinical research laboratories. Four independent laboratories in North America, using identical triple-quadrupole mass spectrometers (Quantum Ultra, Thermo), were provided with standard protocols and instrumentation settings to analyze unknown samples and internal standards in a digested plasma matrix to quantify 51 peptides from 39 human proteins using a multiplexed SRM assay. The interlaboratory coefficient of variation (CV) was less than 10% for 25 of 39 peptides quantified (12 peptides were not quantified based upon hydrophobicity) and exhibited CVs less than 20% for the remaining peptides. In this report, we demonstrate that previously developed research platforms for SRM assays can be improved and optimized for deployment in clinical research environments.     

Interlaboratory evaluation of automated, multiplexed peptide immunoaffinity enrichment coupled to multiple reaction monitoring mass spectrometry for quantifying proteins in plasma

The inability to quantify large numbers of proteins in tissues and biofluids with high precision, sensitivity, and throughput is a major bottleneck in biomarker studies. We previously demonstrated that coupling immunoaffinity enrichment using anti-peptide antibodies (SISCAPA) to multiple reaction monitoring mass spectrometry (MRM-MS) produces Immunoprecipitation MRM-MS (immuno-MRM-MS) assays that can be multiplexed to quantify proteins in plasma with high sensitivity, specificity, and precision. Here we report the first systematic evaluation of the interlaboratory performance of multiplexed (8-plex) immuno-MRM-MS in three independent labs. A staged study was carried out in which the effect of each processing and analysis step on assay coefficient of variance, limit of detection, limit of quantification, and recovery was evaluated. Limits of detection were at or below 1 ng/ml for the assayed proteins in 30 μl of plasma. Assay reproducibility was acceptable for verification studies, with median intra- and interlaboratory coefficients of variance above the limit of quantification of 11% and <14%, respectively, for the entire immuno-MRM-MS assay process, including enzymatic digestion of plasma. Trypsin digestion and its requisite sample handling contributed the most to assay variability and reduced the recovery of target peptides from digested proteins. Using a stable isotope-labeled protein as an internal standard instead of stable isotope-labeled peptides to account for losses in the digestion process nearly doubled assay accuracy for this while improving assay precision 5%. Our results demonstrate that multiplexed immuno-MRM-MS can be made reproducible across independent laboratories and has the potential to be adopted widely for assaying proteins in matrices as complex as plasma.