Quantitative Proteomics of the Cancer Cell Line Encyclopedia.

Proteins are essential agents of biological processes. To date, large-scale profiling of cell line collections including the Cancer Cell Line Encyclopedia (CCLE) has focused primarily on genetic information whereas deep interrogation of the proteome has remained out of reach. Here, we expand the CCLE through quantitative profiling of thousands of proteins by mass spectrometry across 375 cell lines from diverse lineages to reveal information undiscovered by DNA and RNA methods. We observe unexpected correlations within and between pathways that are largely absent from RNA. An analysis of microsatellite instable (MSI) cell lines reveals the dysregulation of specific protein complexes associated with surveillance of mutation and translation. These and other protein complexes were associated with sensitivity to knockdown of several different genes. These data in conjunction with the wider CCLE are a broad resource to explore cellular behavior and facilitate cancer research.

A creatine-driven substrate cycle enhances energy expenditure and thermogenesis in beige fat.

Thermogenic brown and beige adipose tissues dissipate chemical energy as heat, and their thermogenic activities can combat obesity and diabetes. Herein the functional adaptations to cold of brown and beige adipose depots are examined using quantitative mitochondrial proteomics. We identify arginine/creatine metabolism as a beige adipose signature and demonstrate that creatine enhances respiration in beige-fat mitochondria when ADP is limiting. In murine beige fat, cold exposure stimulates mitochondrial creatine kinase activity and induces coordinated expression of genes associated with creatine metabolism. Pharmacological reduction of creatine levels decreases whole-body energy expenditure after administration of a ß3-agonist and reduces beige and brown adipose metabolic rate. Genes of creatine metabolism are compensatorily induced when UCP1-dependent thermogenesis is ablated, and creatine reduction in Ucp1-deficient mice reduces core body temperature. These findings link a futile cycle of creatine metabolism to adipose tissue energy expenditure and thermal homeostasis. PAPERCLIP.

The BioPlex Network: A Systematic Exploration of the Human Interactome.

Protein interactions form a network whose structure drives cellular function and whose organization informs biological inquiry. Using high-throughput affinity-purification mass spectrometry, we identify interacting partners for 2,594 human proteins in HEK293T cells. The resulting network (BioPlex) contains 23,744 interactions among 7,668 proteins with 86% previously undocumented. BioPlex accurately depicts known complexes, attaining 80%-100% coverage for most CORUM complexes. The network readily subdivides into communities that correspond to complexes or clusters of functionally related proteins. More generally, network architecture reflects cellular localization, biological process, and molecular function, enabling functional characterization of thousands of proteins. Network structure also reveals associations among thousands of protein domains, suggesting a basis for examining structurally related proteins. Finally, BioPlex, in combination with other approaches, can be used to reveal interactions of biological or clinical significance. For example, mutations in the membrane protein VAPB implicated in familial amyotrophic lateral sclerosis perturb a defined community of interactors.

A Strategy to Combine Sample Multiplexing with Targeted Proteomics Assays for High-Throughput Protein Signature Characterization.

Targeted mass spectrometry assays for protein quantitation monitor peptide surrogates, which are easily multiplexed to target many peptides in a single assay. However, these assays have generally not taken advantage of sample multiplexing, which allows up to ten analyses to occur in parallel. We present a two-dimensional multiplexing workflow that utilizes synthetic peptides for each protein to prompt the simultaneous quantification of >100 peptides from up to ten mixed sample conditions. We demonstrate that targeted analysis of unfractionated lysates (2 hr) accurately reproduces the quantification of fractionated lysates (72 hr analysis) while obviating the need for peptide detection prior to quantification. We targeted 131 peptides corresponding to 69 proteins across all 60 National Cancer Institute cell lines in biological triplicate, analyzing 180 samples in only 48 hr (the equivalent of 16 min/sample). These data further elucidated a correlation between the expression of key proteins and their cellular response to drug treatment.

Simulated Attack Reveals How Lesions Affect Network Properties in Poststroke Aphasia.

Aphasia is a prevalent cognitive syndrome caused by stroke. The rarity of premorbid imaging and heterogeneity of lesion obscures the links between the local effects of the lesion, global anatomic network organization, and aphasia symptoms. We applied a simulated attack approach in humans to examine the effects of 39 stroke lesions (16 females) on anatomic network topology by simulating their effects in a control sample of 36 healthy (15 females) brain networks. We focused on measures of global network organization thought to support overall brain function and resilience in the whole brain and within the left hemisphere. After removing lesion volume from the network topology measures and behavioral scores [the Western Aphasia Battery Aphasia Quotient (WAB-AQ), four behavioral factor scores obtained from a neuropsychological battery, and a factor sum], we compared the behavioral variance accounted for by simulated poststroke connectomes to that observed in the randomly permuted data. Global measures of anatomic network topology in the whole brain and left hemisphere accounted for 10% variance or more of the WAB-AQ and the lexical factor score beyond lesion volume and null permutations. Streamline networks provided more reliable point estimates than FA networks. Edge weights and network efficiency were weighted most highly in predicting the WAB-AQ for FA networks. Overall, our results suggest that global network measures provide modest statistical value beyond lesion volume when predicting overall aphasia severity, but less value in predicting specific behaviors. Variability in estimates could be induced by premorbid ability, deafferentation and diaschisis, and neuroplasticity following stroke.SIGNIFICANCE STATEMENT Poststroke, the remaining neuroanatomy maintains cognition and supports recovery. However, studies often use small, cross-sectional samples that cannot fully model the interactions between lesions and other variables that affect networks in stroke. Alternate methods are required to account for these effects. "Simulated attack" models are computational approaches that apply virtual damage to the brain and measure their putative consequences. Using a simulated attack model, we estimated how simulated damage to anatomic networks could account for language performance. Overall, our results reveal that global network measures can provide modest statistical value predicting overall aphasia severity, but less value in predicting specific behaviors. These findings suggest that more theoretically precise network models could be necessary to robustly predict individual outcomes in aphasia.

Individual-level functional connectivity predicts cognitive control efficiency.

Cognitive control (CC) is essential for problem-solving in everyday life, and CC-related deficits occur alongside costly and debilitating disorders. The tri-partite model suggests that CC comprises multiple behaviors, including switching, inhibiting, and updating. Activity within the fronto-parietal control network B (FPCN-B), the dorsal attention network (DAN), the cingulo-opercular network (CON), and the lateral default-mode network (L-DMN) is related to switching and inhibiting behaviors. However, our understanding of how these brain regions interact to bring about cognitive switching and inhibiting in individuals is unclear. In the current study, subjects performed two in-scanner tasks that required switching and inhibiting. We used support vector regression (SVR) models containing individually-estimated functional connectivity between the FPCN-B, DAN, CON and L-DMN to predict switching and inhibiting behaviors. We observed that: inter-network connectivity can predict inhibiting and switching behaviors in individuals, and the L-DMN plays a role in switching and inhibiting behaviors. Therefore, individually estimated inter-network connections are markers of CC behaviors, and CC behaviors may arise due to interactions between a set of networks.

Architecture of the human interactome defines protein communities and disease networks.

The physiology of a cell can be viewed as the product of thousands of proteins acting in concert to shape the cellular response. Coordination is achieved in part through networks of protein-protein interactions that assemble functionally related proteins into complexes, organelles, and signal transduction pathways. Understanding the architecture of the human proteome has the potential to inform cellular, structural, and evolutionary mechanisms and is critical to elucidating how genome variation contributes to disease. Here we present BioPlex 2.0 (Biophysical Interactions of ORFeome-derived complexes), which uses robust affinity purification-mass spectrometry methodology to elucidate protein interaction networks and co-complexes nucleated by more than 25% of protein-coding genes from the human genome, and constitutes, to our knowledge, the largest such network so far. With more than 56,000 candidate interactions, BioPlex 2.0 contains more than 29,000 previously unknown co-associations and provides functional insights into hundreds of poorly characterized proteins while enhancing network-based analyses of domain associations, subcellular localization, and co-complex formation. Unsupervised Markov clustering of interacting proteins identified more than 1,300 protein communities representing diverse cellular activities. Genes essential for cell fitness are enriched within 53 communities representing central cellular functions. Moreover, we identified 442 communities associated with more than 2,000 disease annotations, placing numerous candidate disease genes into a cellular framework. BioPlex 2.0 exceeds previous experimentally derived interaction networks in depth and breadth, and will be a valuable resource for exploring the biology of incompletely characterized proteins and for elucidating larger-scale patterns of proteome organization.

Glutamate-Weighted Magnetic Resonance Imaging (GluCEST) Detects Effects of Transcranial Magnetic Stimulation to the Motor Cortex.

Transcranial magnetic stimulation (TMS) is used in several FDA-approved treatments and, increasingly, to treat neurological disorders in off-label uses. However, the mechanism by which TMS causes physiological change is unclear, as are the origins of response variability in the general population. Ideally, objective in vivo biomarkers could shed light on these unknowns and eventually inform personalized interventions. Continuous theta-burst stimulation (cTBS) is a form of TMS observed to reduce motor evoked potentials (MEPs) for 60 min or longer post-stimulation, although the consistency of this effect and its mechanism continue to be under debate. Here, we use glutamate-weighted chemical exchange saturation transfer (gluCEST) magnetic resonance imaging (MRI) at ultra-high magnetic field (7T) to measure changes in glutamate concentration at the site of cTBS. We find that the gluCEST signal in the ipsilateral hemisphere of the brain generally decreases in response to cTBS, whereas consistent changes were not detected in the contralateral region of interest (ROI) or in subjects receiving sham stimulation.

Mitochondrial ROS regulate thermogenic energy expenditure and sulfenylation of UCP1.

Brown and beige adipose tissues can dissipate chemical energy as heat through thermogenic respiration, which requires uncoupling protein 1 (UCP1). Thermogenesis from these adipocytes can combat obesity and diabetes, encouraging investigation of factors that control UCP1-dependent respiration in vivo. Here we show that acutely activated thermogenesis in brown adipose tissue is defined by a substantial increase in levels of mitochondrial reactive oxygen species (ROS). Remarkably, this process supports in vivo thermogenesis, as pharmacological depletion of mitochondrial ROS results in hypothermia upon cold exposure, and inhibits UCP1-dependent increases in whole-body energy expenditure. We further establish that thermogenic ROS alter the redox status of cysteine thiols in brown adipose tissue to drive increased respiration, and that Cys253 of UCP1 is a key target. UCP1 Cys253 is sulfenylated during thermogenesis, while mutation of this site desensitizes the purine-nucleotide-inhibited state of the carrier to adrenergic activation and uncoupling. These studies identify mitochondrial ROS induction in brown adipose tissue as a mechanism that supports UCP1-dependent thermogenesis and whole-body energy expenditure, which opens the way to improved therapeutic strategies for combating metabolic disorders.

Parallel Notched Gas-Phase Enrichment for Improved Proteome Identification and Quantification with Fast Spectral Acquisition Rates.

Gas-phase fractionation enables better quantitative accuracy, improves signal-to-noise ratios, and increases sensitivity in proteomic analyses. However, traditional gas-phase enrichment, which relies upon a large continuous bin, results in suboptimal enrichment, as most chromatographic separations are not 100% orthogonal relative to the first MS dimension (MS1m/z). As such, ions with similar m/z values tend to elute at the same retention time, which prevents the partitioning of narrow precursor m/z distributions into a few large continuous gas-phase enrichment bins. To overcome this issue, we developed and tested the use of notched isolation waveforms, which simultaneously isolate multiple discrete m/z windows in parallel (e.g., 650-700 m/z and 800-850 m/z). By comparison to a canonical gas-phase fractionation method, notched waveforms do not require bin optimization via in silico digestion or wasteful sample injections to isolate multiple precursor windows. Importantly, the collection of all m/z bins simultaneously using the isolation waveform does not suffer from the sensitivity and duty cycle pitfalls inherent to sequential collection of multiple m/z bins. Applying a notched injection waveform provided consistent enrichment of precursor ions, which resulted in improved proteome depth with greater coverage of low-abundance proteins. Finally, using a reductive dimethyl labeling approach, we show that notched isolation waveforms increase the number of quantified peptides with improved accuracy and precision across a wider dynamic range.

Full-Featured, Real-Time Database Searching Platform Enables Fast and Accurate Multiplexed Quantitative Proteomics.

Multiplexed quantitative analyses of complex proteomes enable deep biological insight. While a multitude of workflows have been developed for multiplexed analyses, the most quantitatively accurate method (SPS-MS3) suffers from long acquisition duty cycles. We built a new, real-time database search (RTS) platform, Orbiter, to combat the SPS-MS3 method's longer duty cycles. RTS with Orbiter eliminates SPS-MS3 scans if no peptide matches to a given spectrum. With Orbiter's online proteomic analytical pipeline, which includes RTS and false discovery rate analysis, it was possible to process a single spectrum database search in less than 10 ms. The result is a fast, functional means to identify peptide spectral matches using Comet, filter these matches, and more efficiently quantify proteins of interest. Importantly, the use of Comet for peptide spectral matching allowed for a fully featured search, including analysis of post-translational modifications, with well-known and extensively validated scoring. These data could then be used to trigger subsequent scans in an adaptive and flexible manner. In this work we tested the utility of this adaptive data acquisition platform to improve the efficiency and accuracy of multiplexed quantitative experiments. We found that RTS enabled a 2-fold increase in mass spectrometric data acquisition efficiency. Orbiter's RTS quantified more than 8000 proteins across 10 proteomes in half the time of an SPS-MS3 analysis (18 h for RTS, 36 h for SPS-MS3).

An insight-related neural reward signal.

Moments of insight, a phenomenon of creative cognition in which an idea suddenly emerges into awareness as an "Aha!" are often reported to be affectively positive experiences. We tested the hypothesis that problem-solving by insight is accompanied by neural reward processing. We recorded high-density EEGs while participants solved a series of anagrams. For each solution, they reported whether the answer had occurred to them as a sudden insight or whether they had derived it deliberately and incrementally (i.e., "analytically'). Afterwards, they filled out a questionnaire that measures general dispositional reward sensitivity. We computed the time-frequency representations of the EEGs for trials with insight (I) solutions and trials with analytic (A) solutions and subtracted them to obtain an I-A time-frequency representation for each electrode. Statistical Parametric Mapping (SPM) analyses tested for significant I-A and reward-sensitivity effects. SPM revealed the time, frequency, and scalp locations of several I â€‹> â€‹A effects. No A â€‹> â€‹I effect was observed. The primary neural correlate of insight was a burst of (I â€‹> â€‹A) gamma-band oscillatory activity over prefrontal cortex approximately 500 â€‹ms before participants pressed a button to indicate that they had solved the problem. We correlated the I-A time-frequency representation with reward sensitivity to discover insight-related effects that were modulated by reward sensitivity. This revealed a separate anterior prefrontal burst of gamma-band activity, approximately 100 â€‹ms after the primary I-A insight effect, which we interpreted to be an insight-related reward signal. This interpretation was supported by source reconstruction showing that this signal was generated in part by orbitofrontal cortex, a region associated with reward learning and hedonically pleasurable experiences such as food, positive social experiences, addictive drugs, and orgasm. These findings support the notion that for many people insight is rewarding. Additionally, these results may explain why many people choose to engage in insight-generating recreational and vocational activities such as solving puzzles, reading murder mysteries, creating inventions, or doing research. This insight-related reward signal may be a manifestation of an evolutionarily adaptive mechanism for the reinforcement of exploration, problem solving, and creative cognition.

Dual-process contributions to creativity in jazz improvisations: An SPM-EEG study.

Conflicting theories identify creativity either with frontal-lobe mediated (Type-2) executive control processes or (Type-1) associative processes that are disinhibited when executive control is relaxed. Musical (jazz) improvisation is an ecologically valid test-case to distinguish between these views because relatively slow, deliberate, executive-control processes should not dominate during high-quality, real-time improvisation. In the present study, jazz guitarists (n â€‹= â€‹32) improvised to novel chord sequences while 64-channel EEGs were recorded. Jazz experts rated each improvisation for creativity, technical proficiency and aesthetic appeal. Surface-Laplacian-transformed EEGs recorded during the performances were analyzed in the scalp-frequency domain using SPM12. Significant clusters of high-frequency (beta-band and gamma-band) activity were observed when higher-quality versus lower-quality improvisations were compared. Higher-quality improvisations were associated with predominantly posterior left-hemisphere activity; lower-quality improvisations were associated with right temporo-parietal and fronto-polar activity. However, after statistically controlling for experience (defined as the number of public performances previously given), performance quality was a function of right-hemisphere, largely right-frontal, activity. These results support the notion that superior creative production is associated with hypofrontality and right-hemisphere activity thereby supporting a dual-process model of creativity in which experience influences the balance between executive and associative processes. This study also highlights the idea that the functional neuroanatomy of creative production depends on whether creativity is defined in terms of the quality of products or the type of cognitive processes involved.

UCP1 deficiency causes brown fat respiratory chain depletion and sensitizes mitochondria to calcium overload-induced dysfunction.

Brown adipose tissue (BAT) mitochondria exhibit high oxidative capacity and abundant expression of both electron transport chain components and uncoupling protein 1 (UCP1). UCP1 dissipates the mitochondrial proton motive force (Δp) generated by the respiratory chain and increases thermogenesis. Here we find that in mice genetically lacking UCP1, cold-induced activation of metabolism triggers innate immune signaling and markers of cell death in BAT. Moreover, global proteomic analysis reveals that this cascade induced by UCP1 deletion is associated with a dramatic reduction in electron transport chain abundance. UCP1-deficient BAT mitochondria exhibit reduced mitochondrial calcium buffering capacity and are highly sensitive to mitochondrial permeability transition induced by reactive oxygen species (ROS) and calcium overload. This dysfunction depends on ROS production by reverse electron transport through mitochondrial complex I, and can be rescued by inhibition of electron transfer through complex I or pharmacologic depletion of ROS levels. Our findings indicate that the interscapular BAT of Ucp1 knockout mice exhibits mitochondrial disruptions that extend well beyond the deletion of UCP1 itself. This finding should be carefully considered when using this mouse model to examine the role of UCP1 in physiology.

Active Instrument Engagement Combined with a Real-Time Database Search for Improved Performance of Sample Multiplexing Workflows.

Quantitative proteomics employing isobaric reagents has been established as a powerful tool for biological discovery. Current workflows often utilize a dedicated quantitative spectrum to improve quantitative accuracy and precision. A consequence of this approach is a dramatic reduction in the spectral acquisition rate, which necessitates the use of additional instrument time to achieve comprehensive proteomic depth. This work assesses the performance and benefits of online and real-time spectral identification in quantitative multiplexed workflows. A Real-Time Search (RTS) algorithm was implemented to identify fragment spectra within milliseconds as they are acquired using a probabilistic score and to trigger quantitative spectra only upon confident peptide identification. The RTS-MS3 was benchmarked against standard workflows using a complex two-proteome model of interference and a targeted 10-plex comparison of kinase abundance profiles. Applying the RTS-MS3 method provided the comprehensive characterization of a 10-plex proteome in 50% less acquisition time. These data indicate that the RTS-MS3 approach provides dramatic performance improvements for quantitative multiplexed experiments.

TomahaqCompanion: A Tool for the Creation and Analysis of Isobaric Label Based Multiplexed Targeted Assays.

Triggered by Offset, Multiplexed, Accurate mass, High resolution, and Absolute Quantitation (TOMAHAQ) is a recently introduced targeted proteomics method that combines peptide and sample multiplexing. TOMAHAQ assays enable sensitive and accurate multiplexed quantification by implementing an intricate data collection scheme that comprises multiple MSn scans, mass inclusion lists, and data-driven filters. Consequently, manual creation of TOMAHAQ methods can be time-consuming and error prone, while the resulting TOMAHAQ data may not be compatible with common mass spectrometry analysis pipelines. To address these concerns we introduce TomahaqCompanion, an open-source desktop application that enables rapid creation of TOMAHAQ methods and analysis of TOMAHAQ data. Starting from a list of peptide sequences, a user can perform each step of TOMAHAQ assay development including (1) generation of priming run target list, (2) analysis of priming run data, (3) generation of TOMAHAQ method file, and (4) analysis and export of quantitative TOMAHAQ data. We demonstrate the flexibility of TomahaqCompanion by creating a variety of methods testing TOMAHAQ parameters (e.g., number of SPS notches, run length, etc.). Lastly, we analyze an interference sample comprising heavy yeast peptides, a standard human peptide mixture, TMT11-plex, and super heavy TMT (shTMT) isobaric labels to demonstrate ∼10-200 attomol limit of quantification within a complex background using TOMAHAQ.

Medical Cannabis: Effects on Opioid and Benzodiazepine Requirements for Pain Control.

Background: There is currently little evidence regarding the use of medical cannabis for the treatment of intractable pain. Literature published on the subject to date has yielded mixed results concerning the efficacy of medical cannabis and has been limited by study design and regulatory issues. Objective: The objective of this study was to determine if the use of medical cannabis affects the amount of opioids and benzodiazepines used by patients on a daily basis. Methods: This single-center, retrospective cohort study evaluated opioid and benzodiazepine doses over a 6-month time period for patients certified to use medical cannabis for intractable pain. All available daily milligram morphine equivalents (MMEs) and daily diazepam equivalents (DEs) were calculated at baseline and at 3 and 6 months. Results: A total of 77 patients were included in the final analysis. There was a statistically significant decrease in median MME from baseline to 3 months (-32.5 mg; P = 0.013) and 6 months (-39.1 mg; P = 0.001). Additionally, there was a non-statistically significant decrease in median DE at 3 months (-3.75 mg; P = 0.285) and no change in median DE from baseline to 6 months (-0 mg; P = 0.833). Conclusion and Relevance: Over the course of this 6-month retrospective study, patients using medical cannabis for intractable pain experienced a significant reduction in the number of MMEs available to use for pain control. No significant difference was noted in DE from baseline. Further prospective studies are warranted to confirm or deny the opioid-sparing effects of medical cannabis when used to treat intractable pain.

Identification and quantification of protein S-nitrosation by nitrite in the mouse heart during ischemia.

Nitrate (NO3-) and nitrite (NO2-) are known to be cardioprotective and to alter energy metabolism in vivo NO3- action results from its conversion to NO2- by salivary bacteria, but the mechanism(s) by which NO2- affects metabolism remains obscure. NO2- may act by S-nitrosating protein thiols, thereby altering protein activity. But how this occurs, and the functional importance of S-nitrosation sites across the mammalian proteome, remain largely uncharacterized. Here we analyzed protein thiols within mouse hearts in vivo using quantitative proteomics to determine S-nitrosation site occupancy. We extended the thiol-redox proteomic technique, isotope-coded affinity tag labeling, to quantify the extent of NO2--dependent S-nitrosation of proteins thiols in vivo Using this approach, called SNOxICAT (S-nitrosothiol redox isotope-coded affinity tag), we found that exposure to NO2- under normoxic conditions or exposure to ischemia alone results in minimal S-nitrosation of protein thiols. However, exposure to NO2- in conjunction with ischemia led to extensive S-nitrosation of protein thiols across all cellular compartments. Several mitochondrial protein thiols exposed to the mitochondrial matrix were selectively S-nitrosated under these conditions, potentially contributing to the beneficial effects of NO2- on mitochondrial metabolism. The permeability of the mitochondrial inner membrane to HNO2, but not to NO2-, combined with the lack of S-nitrosation during anoxia alone or by NO2- during normoxia places constraints on how S-nitrosation occurs in vivo and on its mechanisms of cardioprotection and modulation of energy metabolism. Quantifying S-nitrosated protein thiols now allows determination of modified cysteines across the proteome and identification of those most likely responsible for the functional consequences of NO2- exposure.

Comparison of Proteomic Quantification Approaches for Hepatic Drug Transporters: Multiplexed Global Quantitation Correlates with Targeted Proteomic Quantitation.

Targeted protein quantification using liquid chromatography-tandem mass spectrometry with stable isotope-labeled standards is recognized as the gold standard of practice for protein quantification. Such assays, however, can only cover a limited number of proteins, and developing targeted methods for larger numbers of proteins requires substantial investment. Alternatively, large-scale global proteomic experiments along with computational methods such as the "total protein approach" (TPA) have the potential to provide extensive protein quantification. In this study, we compared the TPA-based quantitation of seven major hepatic uptake transporters in four human liver tissue samples using global proteomic data obtained from two multiplexed tandem mass tag experiments (performed in two independent laboratories) to the quantitative data from targeted proteomic assays. The TPA-based quantitation of these hepatic transporters [sodium-taurocholate cotransporting polypeptide (NTCP/SLC10A1), organic anion transporter 2 (OAT2/SLC22A7), OAT7/SLC22A9, organic anion-transporting polypeptide 1B1 (OATP1B1/SLCO1B1), OATP1B3/SLCO1B3, OATP2B1/SLCO2B1, and organic cation transporter (OCT1/SLC22A1)] showed good-to-excellent correlations (Pearson r = 0.74-1.00) to the targeted data. In addition, the values were similar to those measured by targeted proteomics with 71% and 86% of the data sets falling within 3-fold of the targeted data. A comparison of the TPA-based quantifications of enzyme abundances to available literature data showed that the majority of the enzyme quantifications fell within the reference data intervals. In conclusion, these results demonstrate the capability of multiplexed global proteomic experiments to detect differences in protein expression between samples and provide reasonable estimations of protein expression levels.