Reinspection of a Clinical Proteomics Tumor Analysis Consortium (CPTAC) Dataset with Cloud Computing Reveals Abundant Post-Translational Modifications and Protein Sequence Variants.

The Clinical Proteomic Tumor Analysis Consortium (CPTAC) has provided some of the most in-depth analyses of the phenotypes of human tumors ever constructed. Today, the majority of proteomic data analysis is still performed using software housed on desktop computers which limits the number of sequence variants and post-translational modifications that can be considered. The original CPTAC studies limited the search for PTMs to only samples that were chemically enriched for those modified peptides. Similarly, the only sequence variants considered were those with strong evidence at the exon or transcript level. In this multi-institutional collaborative reanalysis, we utilized unbiased protein databases containing millions of human sequence variants in conjunction with hundreds of common post-translational modifications. Using these tools, we identified tens of thousands of high-confidence PTMs and sequence variants. We identified 4132 phosphorylated peptides in nonenriched samples, 93% of which were confirmed in the samples which were chemically enriched for phosphopeptides. In addition, our results also cover 90% of the high-confidence variants reported by the original proteogenomics study, without the need for sample specific next-generation sequencing. Finally, we report fivefold more somatic and germline variants that have an independent evidence at the peptide level, including mutations in ERRB2 and BCAS1. In this reanalysis of CPTAC proteomic data with cloud computing, we present an openly available and searchable web resource of the highest-coverage proteomic profiling of human tumors described to date.

Cloud Computing Based Immunopeptidomics Utilizing Community Curated Variant Libraries Simplifies and Improves Neo-Antigen Discovery in Metastatic Melanoma.

Unique peptide neo-antigens presented on the cell surface are attractive targets for researchers in nearly all areas of personalized medicine. Cells presenting peptides with mutated or other non-canonical sequences can be utilized for both targeted therapies and diagnostics. Today's state-of-the-art pipelines utilize complementary proteogenomic approaches where RNA or ribosomal sequencing data helps to create libraries from which tandem mass spectrometry data can be compared. In this study, we present an alternative approach whereby cloud computing is utilized to power neo-antigen searches against community curated databases containing more than 7 million human sequence variants. Using these expansive databases of high-quality sequences as a reference, we reanalyze the original data from two previously reported studies to identify neo-antigen targets in metastatic melanoma. Using our approach, we identify 79 percent of the non-canonical peptides reported by previous genomic analyses of these files. Furthermore, we report 18-fold more non-canonical peptides than previously reported. The novel neo-antigens we report herein can be corroborated by secondary analyses such as high predicted binding affinity, when analyzed by well-established tools such as NetMHC. Finally, we report 738 non-canonical peptides shared by at least five patient samples, and 3258 shared across the two studies. This illustrates the depth of data that is present, but typically missed by lower statistical power proteogenomic approaches. This large list of shared peptides across the two studies, their annotation, non-canonical origin, as well as MS/MS spectra from the two studies are made available on a web portal for community analysis.

The utilization of the search engine, Bolt, to decrease search time and increase peptide identifications in hydroxyl radical protein footprinting-based workflows.

Hydroxyl radical protein footprinting (HRPF) utilizes hydroxyl radicals to covalently modify solvent exposed regions of proteins. When coupled with mass spectrometry, HRPF can provide insightful information on protein structural changes including inside cells. However, the complex mixture of proteins and modifications makes identification a complicated task. To search all of the HRPF-induced modification combinations across the full proteome, requires substantial computational power and still can take days to search. To drastically decrease processing time and improve identifications, a novel cloud-based search engine, Bolt, was used to search for HRPF modifications in comparison to a commonly used search engine, Sequest. A 35% increase in the identification of modified peptides was observed in Bolt compared to Sequest with a decrease in computation time.

Digging deeper into the immunopeptidome: characterization of post-translationally modified peptides presented by MHC I.

Peptides presented by MHC molecules on the cell surface, or the immunopeptidome, play an important role in the adaptive arm of the immune response. Antigen processing for MHC class I molecules is a ubiquitous pathway present in all nucleated cells which generates and presents peptides of both self and non-self-origin. Peptides with post-translational modifications represent one category of peptides presented by MHC class I molecules. However, owing to the complexity of self-peptides presented by cells, the diversity of peptides with post-translational modifications is not well-studied. In this study, we carried out MHC Class I immunopeptidomics analysis of Loucy T-cell leukemia and A375 malignant melanoma cell line to characterize the diversity of post-translational modifications of MHC class I-bound peptides. Using high resolution mass spectrometry, we identified 25,761 MHC-bound peptides across both cell lines using Bolt and Sequest search engines. The enrichment method was highly specific as ~ 90% of the peptides were of typical length (8-12 amino acids long) and the motifs were expected based on previously reported motifs for MHC I alleles. Among the MHC-bound peptides, we identified phosphorylation as a major post-translational modification followed by deamidation. We observed site-specific localization of these post-translational modifications, at position P4 for phosphorylated peptides and position P3 for deamidated peptides. We identified a smaller number of peptides with acetylated and methylated lysine, possibly due to very low stoichiometric levels of these PTMs compared to phosphorylation and deamidation. Using PEAKS de novo sequencing algorithm, we identified spliced peptides that accounted for ~ 5-7% of MHC-bound peptides that were otherwise similar in their features as normal MHC-bound peptides. We validated the identity of several post-translationally modified peptides and spliced peptides through mass spectrometric analysis of synthetic peptides. Our study confirms post-translationally modified peptides to be present at low stoichiometric levels along with unusual spliced peptides through unbiased identification using high resolution mass spectrometry. Supplementary Information: The online version contains supplementary material available at 10.1007/s42485-021-00066-x.

Quantitative assessment of successive carbohydrate additions to the clustered O-glycosylation sites of IgA1 by glycosyltransferases.

Mucin-type O-glycosylation occurs on many proteins that transit the Golgi apparatus. These glycans impact structure and function of many proteins and have important roles in cellular biosynthetic processes, signaling and differentiation. Although recent technological advances have enhanced our ability to profile glycosylation of glycoproteins, limitations in the understanding of the biosynthesis of these glycan structures remain. Some of these limitations stem from the difficulty to track the biosynthetic process of mucin-type O-glycosylation, especially when glycans occur in dense clusters in repeat regions of proteins, such as the mucins or immunoglobulin A1 (IgA1). Here, we describe a series of nano-liquid chromatography (LC)-mass spectrometry (MS) analyses that demonstrate the range of glycosyltransferase enzymatic activities involved in the biosynthesis of clustered O-glycans on IgA1. By utilizing nano-LC-MS relative quantitation of in vitro reaction products, our results provide unique insights into the biosynthesis of clustered IgA1 O-glycans. We have developed a workflow to determine glycoform-specific apparent rates of a human UDP-N-acetylgalactosamine:polypeptide N-acetylgalactosaminyltrasnfersase (GalNAc-T EC 2.4.1.41) and demonstrated how pre-existing glycans affect subsequent activity of glycosyltransferases, such as core 1 galactosyltransferase and α2,3- and α2,6-specific sialyltransferases, in successive additions in the biosynthesis of clustered O-glycans. In the context of IgA1, these results have potential to provide insight into the molecular mechanisms implicated in the pathogenesis of IgA nephropathy, an autoimmune renal disease involving aberrant IgA1 O-glycosylation. In a broader sense, these methods and workflows are applicable to the studies of the concerted and competing functions of other glycosyltransferases that initiate and extend mucin-type core 1 clustered O-glycosylation.

Bolt: a New Age Peptide Search Engine for Comprehensive MS/MS Sequencing Through Vast Protein Databases in Minutes.

Recent increases in mass spectrometry speed, sensitivity, and resolution now permit comprehensive proteomics coverage. However, the results are often hindered by sub-optimal data processing pipelines. In almost all MS/MS peptide search engines, users must limit their search space to a canonical database due to time constraints and q value considerations, but this typically does not reflect the individual genetic variations of the organism being studied. In addition, engines will nearly always assume the presence of only fully tryptic peptides and limit PTMs to a handful. Even on high-performance servers, these search engines are computationally expensive, and most users decide to dial back their search parameters. We present Bolt, a new cloud-based search engine that can search more than 900,000 protein sequences (canonical, isoform, mutations, and contaminants) with 41 post-translation modifications and N-terminal and C-terminal partial tryptic search in minutes on a standard configuration laptop. Along with increases in speed, Bolt provides an additional benefit of improvement in high-confidence identifications. Sixty-one percent of peptides uniquely identified by Bolt may be validated by strong fragmentation patterns, compared with 13% of peptides uniquely identified by SEQUEST and 6% of peptides uniquely identified by Mascot. Furthermore, 30% of unique Bolt identifications were verified by all three software on the longer gradient analysis, compared with only 20% and 27% for SEQUEST and Mascot identifications respectively. Bolt represents, to the best of our knowledge, the first fully scalable, cloud-based quantitative proteomic solution that can be operated within a user-friendly GUI interface. Data are available via ProteomeXchange with identifier PXD012700.

Detection and verification of 2.3 million cancer mutations in NCI60 cancer cell lines with a cloud search engine.

Today we have unprecedented access to human genomic and proteomic data that appear to be rapidly approaching our current understanding of comprehensive coverage. Combining genomic information with shotgun proteomics remains challenging due to the large increase in proteomics search space. However, making this connection between genomic and proteomic information is critical for cancer studies to vaccine development. Furthermore, as we progress towards personalized medicine, it will be essential for proteomics analysis to identify individual mutations and variants in order to fully understand protein networks and to develop personalized therapies. While these advantages are well-established, only a few studies have demonstrated the successful integration of proteomic data with large genomic input. We present and examine the abilities of Bolt, a new cloud-based proteomics search engine to search for the presence of over 2.3 million known cancer mutations in a matter of minutes while still performing a standard proteomics search that includes 31 post translational modifications. We use previously published proteomics data sets and identify mutations that are verified using genomic studies as well as previous proteomics efforts. Our results also emphasize the need to search for mutations in a comprehensive manner while still searching for both common and rare PTMs. SIGNIFICANCE: We present and examine the abilities of Bolt, a new cloud-based proteomics search engine to search for the presence of over 2.3 million known cancer mutations in a matter of minutes while still performing a standard proteomics search that includes 31 post translational modifications. No other proteomics search software can do so.

Defining HIV-1 Envelope N-Glycan Microdomains through Site-Specific Heterogeneity Profiles.

The HIV-1 envelope (Env) glycans shield the surface of Env from the immune system and form integral interactions important for a functional Env. To understand how individual N-glycosylation sites (NGS) coordinate to form a dynamic shield and evade the immune system through mutations, we tracked 20 NGS in Env from HIV-transmitted/founder (T/F) and immune escape variants and their mutants involving the N262 glycan. NGS were profiled in a site-specific manner using a high-resolution mass spectrometry (MS)-based workflow. Using this site-specific quantitative heterogeneity profiling, we empirically characterized the interdependent NGS of a microdomain in the high-mannose patch (HMP). The changes (shifts) in NGS heterogeneity between the T/F and immune escape variants defined a range of NGS that we further probed for exclusive combinations of sequons in the HMP microdomain using the Los Alamos National Laboratory HIV sequence database. The resultant sequon combinations, including the highly conserved NGS N262, N448, and N301, created an immune escape map of the conserved and variable sequons in the HMP microdomain. This report provides details on how some clustered NGS form microdomains that can be identified and tracked across Env variants. These microdomains have a limited number of N-glycan-sequon combinations that may allow the anticipation of immune escape variants.IMPORTANCE The Env protein of HIV is highly glycosylated, and the sites of glycosylation can change as the virus mutates during immune evasion. Due to these changes, the glycan location and heterogeneity of surrounding N-glycosylation sites can be altered, resulting in exposure of different glycan or proteoglycan surfaces while still producing a viable HIV variant. These changes present a need for vaccine developers to identify Env variants with epitopes most likely to induce durable protective responses. Here we describe a means of anticipating HIV-1 immune evasion by dividing Env into N-glycan microdomains that have a limited number of N-glycan sequon combinations.

Assessing the reproducibility of an O-glycopeptide enrichment method with a novel software, Pinnacle.

A novel software, Pinnacle was used to reassess the reproducibility of a 2-step lectin-based O-glycopeptide enrichment method. A publicly available dataset consisting of 12 data files representing 3 technical replicates of enriched glycopeptides from human serum was investigated. Previously, an attempt for reproducibility assessment was made utilizing an MS/MS scan (MS2)-based method. However, the stochastic nature of precursor ion selection strongly biased this approach leading to underestimated rate of reproducibility. To bypass this problem, our present method follows the general path to confidently identify O-glycopeptides (database search with MS/MS data) supplemented with full scan/survey scan (MS1)/extracted ion chromatogram (XIC) mining in all files using two software packages, Pinnacle and Skyline. Confident MS/MS identifications were delivered by Protein Prospector. With this input Skyline indicated a 70% reproducibility for our workflow. However, Pinnacle performed better, indicating the presence of 90% of the confidently assigned glycopeptides in all the three replicates. Pinnacle, just like Skyline, performs ion extraction using the high accuracy, high resolution mass measurement data but it also utilizes all the available MS/MS spectra, even from different activation methods, within the same file to make mass spectrometric data evaluation for glycopeptides more reliable.

Biopsy Based Proteomic Assay Predicts Risk of Biochemical Recurrence after Radical Prostatectomy.

PURPOSE: Current clinicopathological parameters are insufficient to predict the likelihood of biochemical recurrence in patients with prostate cancer after radical prostatectomy. Such information may help identify patients who would likely benefit from adjuvant radiotherapy rather than active surveillance. A multiplex proteomic assay, previously tested on biopsies and found to be predictive of favorable or unfavorable pathology at radical prostatectomy, was assessed for its predictive value to identify patients at higher risk for biochemical relapse. MATERIALS AND METHODS: Proteomic assays from core needle biopsies of 288 men who subsequently underwent radical prostatectomy at CHUM (Centre hospitalier de l'Université de Montréal) were evaluated for the prediction of subsequent biochemical recurrence. RESULTS: Of the 288 men, biochemical relapse was observed in 47 (16.3%) and metastases were found in 5 (1.7%). Median followup was 68.5 months. The proteomic assay clearly separated patients into 3 categories, including those at low, intermediate and high risk for biochemical relapse (p = 0.0007). Assay scores predicted biochemical relapse on univariate analysis (HR 1.724, p = 0.0002 per 20% change in score), significantly better than other preoperative prognostic parameters. Additionally, the assay score had a significantly higher p value when combined with clinical National Comprehensive Cancer Network® stage compared to stage alone (HR 1.579, p = 0.0017 per 20% change in score). CONCLUSIONS: A protein based assay score derived from diagnostic needle biopsy has strong predictive ability for biochemical relapse after surgery. These results suggest that this assay score can be used at the diagnostic stage to identify patients in whom prostate cancer is potentially more biologically aggressive and active treatment should be considered.

Proteomic signatures of serum albumin-bound proteins from stroke patients with and without endovascular closure of PFO are significantly different and suggest a novel mechanism for cholesterol efflux.

BACKGROUND: The anatomy of PFO suggests that it can allow thrombi and potentially harmful circulatory factors to travel directly from the venous to the arterial circulation - altering circulatory phenotype. Our previous publication using high-resolution LC-MS/MS to profile protein and peptide expression patterns in plasma showed that albumin was relatively increased in donor samples from PFO-related than other types of ischemic strokes. Since albumin binds a host of molecules and acts as a carrier for lipoproteins, small molecules and drugs, we decided to investigate the albumin-bound proteins (in a similar sample cohort) in an effort to unravel biological changes and potentially discover biomarkers related to PFO-related stroke and PFO endovascular closure. METHODS: The method used in this study combined albumin immuno-enrichment with high resolution LC-MS in order to specifically capture and quantify the albumin-bound proteins. Subsequently, we measured cholesterol and HDL in a larger, separate cohort of PFO stroke patients, pre and post closure. RESULTS: The results demonstrated that a number of proteins were specifically associated with albumin in samples with and without endovascular closure of the PFO, and that the protein profiles were very different. Eight proteins, typically associated with HDL were common to both sample sets and quantitatively differently abundant. Pathway analysis of the MS results suggested that enhanced cholesterol efflux and reduced lipid oxidation were associated with PFO closure. Measurement of total cholesterol and HDL in a larger cohort of PFO closure samples using a colorimetric assay was consistent with the proteomic predictions. CONCLUSIONS: The collective data presented in this study demonstrate that analysis of albumin-bound proteins could provide a valuable tool for biomarker discovery on the effects of PFO endovascular closure. In addition, the results suggest that PFO endovascular closure can potentially have effects on HDL, cholesterol and albumin-bound ApoA-I abundance, therefore possibly providing benefits in cardioprotective functions.

Hybrid data acquisition and processing strategies with increased throughput and selectivity: pSMART analysis for global qualitative and quantitative analysis.

Data-dependent acquisition (DDA) and data-independent acquisition strategies (DIA) have both resulted in improved understanding of proteomics samples. Both strategies have advantages and disadvantages that are well-published, where DDA is typically applied for deep discovery and DIA may be used to create sample records. In this paper, we present a hybrid data acquisition and processing strategy (pSMART) that combines the strengths of both techniques and provides significant benefits for qualitative and quantitative peptide analysis. The performance of pSMART is compared to published DIA strategies in an experiment that allows the objective assessment of DIA performance with respect to interrogation of previously acquired MS data. The results of this experiment demonstrate that pSMART creates fewer decoy hits than a standard DIA strategy. Moreover, we show that pSMART is more selective, sensitive, and reproducible than either standard DIA or DDA strategies alone.

An automated, high-throughput method for targeted quantification of intact insulin and its therapeutic analogs in human serum or plasma coupling mass spectrometric immunoassay with high resolution and accurate mass detection (MSIA-HR/AM).

The detection and quantification of insulin and its therapeutic analogs is important for medical, sports doping, and forensic applications. Synthetic variants contain slight sequence variations to affect bioavailability. To reduce sample handling bias, a universal extraction method is required for simultaneous extraction of endogenous and variant insulins with subsequent targeted quantification by LC-MS. A mass spectrometric immunoassay (MSIA), a multiplexed assay for intact insulin and its analogues that couples immunoenrichment with high resolution and accurate mass (HR/AM) spectrometric detection across the clinical range is presented in this report. The assay is sensitive, selective, semi-automated and can potentially be applied to detect new insulin isoforms allowing their further incorporation into second or third generation assays.

Targeted selected reaction monitoring mass spectrometric immunoassay for insulin-like growth factor 1.

Insulin-like growth factor 1 (IGF1) is an important biomarker of human growth disorders that is routinely analyzed in clinical laboratories. Mass spectrometry-based workflows offer a viable alternative to standard IGF1 immunoassays, which utilize various pre-analytical preparation strategies. In this work we developed an assay that incorporates a novel sample preparation method for dissociating IGF1 from its binding proteins. The workflow also includes an immunoaffinity step using antibody-derivatized pipette tips, followed by elution, trypsin digestion, and LC-MS/MS separation and detection of the signature peptides in a selected reaction monitoring (SRM) mode. The resulting quantitative mass spectrometric immunoassay (MSIA) exhibited good linearity in the range of 1 to 1,500 ng/mL IGF1, intra- and inter-assay precision with CVs of less than 10%, and lowest limits of detection of 1 ng/mL. The linearity and recovery characteristics of the assay were also established, and the new method compared to a commercially available immunoassay using a large cohort of human serum samples. The IGF1 SRM MSIA is well suited for use in clinical laboratories.

Rapid development of sensitive, high-throughput, quantitative and highly selective mass spectrometric targeted immunoassays for clinically important proteins in human plasma and serum.

OBJECTIVES: The aim of this study was to develop high-throughput, quantitative and highly selective mass spectrometric, targeted immunoassays for clinically important proteins in human plasma or serum. DESIGN AND METHODS: The described method coupled mass spectrometric immunoassay (MSIA), a previously developed technique for immunoenrichment on a monolithic microcolumn activated with an anti-protein antibody and fixed in a pipette tip, to selected reaction monitoring (SRM) detection and accurate quantification of targeted peptides, including clinically relevant sequence or truncated variants. RESULTS: In this report, we demonstrate the rapid development of MSIA-SRM assays for sixteen different target proteins spanning seven different clinically important areas (including neurological, Alzheimer's, cardiovascular, endocrine function, cancer and other diseases) and ranging in concentration from pg/mL to mg/mL. The reported MSIA-SRM assays demonstrated high sensitivity (within published clinical ranges), precision, robustness and high-throughput as well as specific detection of clinically relevant isoforms for many of the target proteins. Most of the assays were tested with bona-fide clinical samples. In addition, positive correlations, (R2 0.67-0.87, depending on the target peptide), were demonstrated for MSIA-SRM assay data with clinical analyzer measurements of parathyroid hormone (PTH) and insulin growth factor 1 (IGF1) in clinical sample cohorts. CONCLUSIONS: We have presented a practical and scalable method for rapid development and deployment of MS-based SRM assays for clinically relevant proteins and measured levels of the target analytes in bona fide clinical samples. The method permits the specific quantification of individual protein isoforms and addresses the difficult problem of protein heterogeneity in clinical proteomics applications.

Depletion of nuclear histone H2A variants is associated with chronic DNA damage signaling upon drug-evoked senescence of human somatic cells.

Cellular senescence is associated with global chromatin changes, altered gene expression, and activation of chronic DNA damage signaling. These events ultimately lead to morphological and physiological transformations in primary cells. In this study, we show that chronic DNA damage signals caused by genotoxic stress impact the expression of histones H2A family members and lead to their depletion in the nuclei of senescent human fibroblasts. Our data reinforce the hypothesis that progressive chromatin destabilization may lead to the loss of epigenetic information and impaired cellular function associated with chronic DNA damage upon drug-evoked senescence. We propose that changes in the histone biosynthesis and chromatin assembly may directly contribute to cellular aging. In addition, we also outline the method that allows for quantitative and unbiased measurement of these changes.

Heart-brain signaling in patent foramen ovale-related stroke: differential plasma proteomic expression patterns revealed with a 2-pass liquid chromatography-tandem mass spectrometry discovery workflow.

Patent foramen ovale (PFO) is highly prevalent and associated with more than 150,000 strokes per year. Traditionally, it is thought that PFOs facilitate strokes by allowing venous clots to travel directly to the brain. However, only a small portion of PFO stroke patients have a known tendency to form blood clots, and the optimal treatment for this multiorgan disease is unclear. Therefore, mapping the changes in systemic circulation of PFO-related stroke is crucial in understanding the pathophysiology to individualize the best clinical treatment for each patient. We initiated a study using a novel quantitative, 2-pass discovery workflow using high-resolution liquid chromatography-mass spectrometry/mass spectrometry coupled with label-free analysis to track protein expression in PFO patients before and after endovascular closure of the PFO. Using this approach, we were able to demonstrate quantitative differences in protein expression between both PFO-related and non-PFO-related ischemic stroke groups as well as before and after PFO closure. As an initial step in understanding the molecular landscape of PFO-related physiology, our methods have yielded biologically relevant information on the synergistic and functional redundancy of various cell-signaling molecules with respect to PFO circulatory physiology. The resulting protein expression patterns were related to canonical pathways including prothrombin activation, atherosclerosis signaling, acute-phase response, LXR/RXR activation, and coagulation system. In particular, after PFO closure, numerous proteins demonstrated reduced expression in stroke-related canonical pathways such as acute inflammatory response and coagulation signaling. These findings demonstrate the feasibility and robustness of using a proteomic approach for biomarker discovery to help gauge therapeutic efficacy in stroke.

Biochemical fractionation and stable isotope dilution liquid chromatography-mass spectrometry for targeted and microdomain-specific protein quantification in human postmortem brain tissue.

Synaptic architecture and its adaptive changes require numerous molecular events that are both highly ordered and complex. A majority of neuropsychiatric illnesses are complex trait disorders, in which multiple etiologic factors converge at the synapse via many signaling pathways. Investigating the protein composition of synaptic microdomains from human patient brain tissues will yield valuable insights into the interactions of risk genes in many disorders. These types of studies in postmortem tissues have been limited by the lack of proper study paradigms. Thus, it is necessary not only to develop strategies to quantify protein and post-translational modifications at the synapse, but also to rigorously validate them for use in postmortem human brain tissues. In this study we describe the development of a liquid chromatography-selected reaction monitoring method, using a stable isotope-labeled neuronal proteome standard prepared from the brain tissue of a stable isotope-labeled mouse, for the multiplexed quantification of target synaptic proteins in mammalian samples. Additionally, we report the use of this method to validate a biochemical approach for the preparation of synaptic microdomain enrichments from human postmortem prefrontal cortex. Our data demonstrate that a targeted mass spectrometry approach with a true neuronal proteome standard facilitates accurate and precise quantification of over 100 synaptic proteins in mammalian samples, with the potential to quantify over 1000 proteins. Using this method, we found that protein enrichments in subcellular fractions prepared from human postmortem brain tissue were strikingly similar to those prepared from fresh mouse brain tissue. These findings demonstrate that biochemical fractionation methods paired with targeted proteomic strategies can be used in human brain tissues, with important implications for the study of neuropsychiatric disease.

Interlaboratory reproducibility of selective reaction monitoring assays using multiple upfront analyte enrichment strategies.

Over the past few years, mass spectrometry has emerged as a technology to complement and potentially replace standard immunoassays in routine clinical core laboratories. Application of mass spectrometry to protein and peptide measurement can provide advantages including high sensitivity, the ability to multiplex analytes, and high specificity at the amino acid sequence level. In our previous study, we demonstrated excellent reproducibility of mass spectrometry-selective reaction monitoring (MS-SRM) assays when applying standardized standard operating procedures (SOPs) to measure synthetic peptides in a complex sample, as lack of reproducibility has been a frequent criticism leveled at the use of mass spectrometers in the clinical laboratory compared to immunoassays. Furthermore, an important caveat of SRM-based assays for proteins is that many low-abundance analytes require some type of enrichment before detection with MS. This adds a level of complexity to the procedure and the potential for irreproducibility increases, especially across different laboratories with different operators. The purpose of this study was to test the interlaboratory reproducibility of SRM assays with various upfront enrichment strategies and different types of clinical samples (representing real-world body fluids commonly encountered in routine clinical laboratories). Three different, previously published enrichment strategies for low-abundance analytes and a no-enrichment strategy for high-abundance analytes were tested across four different laboratories using different liquid chromatography-SRM (LC-SRM) platforms and previously developed SOPs. The results demonstrated that these assays were indeed reproducible with coefficients of variation of less than 30% for the measurement of important clinical proteins across all four laboratories in real world samples.

Discrimination of ischemic and hemorrhagic strokes using a multiplexed, mass spectrometry-based assay for serum apolipoproteins coupled to multi-marker ROC algorithm.

PURPOSE: Typically, apolipoproteins are individually measured in blood by immunoassay. In this report, we describe the development of a multiplexed selected reaction monitoring (SRM) based assay for a panel of apolipoproteins and its application to a clinical cohort of samples derived from acute stroke patients. EXPERIMENTAL DESIGN: An SRM assay for a panel of nine apolipoproteins was developed on a triple quadrupole mass spectrometer. Quantitative data for each apolipoprotein were analyzed to determine expression ratio and receiver operating characteristic (ROC) values for ischemic versus hemorrhagic stroke. RESULTS: The optimized SRM assay was used to interrogate a small cohort of well-characterized plasma samples obtained from patients with acute ischemic and hemorrhagic strokes. The ROC analyses demonstrated good classification power for several single apolipoproteins, most notably apoC-III and apoC-I. When a novel multi-marker ROC algorithm was applied, the ischemic versus hemorrhagic groups were best differentiated by a combination of apoC-III and apoA-I with an area under the curve (AUC) value of 0.92. CONCLUSIONS AND CLINICAL RELEVANCE: This proof-of-concept study provides interesting and provocative data for distinguishing ischemic versus hemorrhage within first week of symptom onset. However, the observations are based on one cohort of patient samples and further confirmation will be required.