Highly multiplexed and reproducible ion-current-based strategy for large-scale quantitative proteomics and the application to protein expression dynamics induced by methylprednisolone in 60 rats

High-quality and robust protein quantification in large clinical/pharmaceutical cohorts with IonStar proteomics investigation

Robust, reliable quantification of large sample cohorts is often essential for meaningful clinical or pharmaceutical proteomics investigations, but it is technically challenging. When analyzing very large numbers of samples, isotope labeling approaches may suffer from substantial batch effects, and even with label-free methods, it becomes evident that low-abundance proteins are not reliably measured owing to unsufficient reproducibility for quantification. The MS1-based quantitative proteomics pipeline IonStar was designed to address these challenges. IonStar is a label-free approach that takes advantage of the high sensitivity/selectivity attainable by ultrahigh-resolution (UHR)-MS1 acquisition (e.g., 120-240k full width at half maximum at m/z = 200) which is now widely available on ultrahigh-field Orbitrap instruments. By selectively and accurately procuring quantitative features of peptides within precisely defined, very narrow m/z windows corresponding to the UHR-MS1 resolution, the method minimizes co-eluted interferences and substantially enhances signal-to-noise ratio of low-abundance species by decreasing noise level. This feature results in high sensitivity, selectivity, accuracy and precision for quantification of low-abundance proteins, as well as fewer missing data and fewer false positives. This protocol also emphasizes the importance of well-controlled, robust experimental procedures to achieve high-quality quantification across a large cohort. It includes a surfactant cocktail-aided sample preparation procedure that achieves high/reproducible protein/peptide recoveries among many samples, and a trapping nano-liquid chromatography-mass spectrometry strategy for sensitive and reproducible acquisition of UHR-MS1 peptide signal robustly across a large cohort. Data processing and quality evaluation are illustrated using an example dataset ( http://proteomecentral.proteomexchange.org ), and example results from pharmaceutical project and one clinical project (patients with acute respiratory distress syndrome) are shown. The complete IonStar pipeline takes ~1-2 weeks for a sample cohort containing ~50-100 samples.

Ultra-High-Resolution IonStar Strategy Enhancing Accuracy and Precision of MS1-Based Proteomics and an Extensive Comparison with State-of-the-Art SWATH-MS in Large-Cohort Quantification

Quantitative proteomics in large cohorts is highly valuable for clinical/pharmaceutical investigations but often suffers from severely compromised reliability, accuracy, and reproducibility. Here, we describe an ultra-high-resolution IonStar method achieving reproducible protein measurement in large cohorts while minimizing the ratio compression problem, by taking advantage of the exceptional selectivity of ultra-high-resolution (UHR)-MS1 detection (240k_FWHM@m/z = 200). Using mixed-proteome benchmark sets reflecting large-cohort analysis with technical or biological replicates (N = 56), we comprehensively compared the quantitative performances of UHR-IonStar vs a state-of-the-art SWATH-MS method, each with their own optimal analytical platforms. We confirmed a cutting-edge micro-liquid chromatography (LC)/Triple-TOF with Spectronaut outperforms nano-LC/Orbitrap for SWATH-MS, which was then meticulously developed/optimized to maximize sensitivity, reproducibility, and proteome coverage. While the two methods with distinct principles (i.e., MS1- vs MS2-based) showed similar depth-of-analysis (∼6700-7000 missing-data-free proteins quantified, 1% protein-false discovery rate (FDR) for entire set, 2 unique peptides/protein) and good accuracy/precision in quantifying high-abundance proteins, UHR-IonStar achieved substantially superior quantitative accuracy, precision, and reproducibility for lower-abundance proteins (a category that includes most regulatory proteins), as well as much-improved sensitivity/selectivity for discovering significantly altered proteins. Furthermore, compared to SWATH-MS, UHR-IonStar showed markedly higher accuracy for a single analysis of each sample across a large set, which is an inadequately investigated albeit critical parameter for large-cohort analysis. Finally, we compared UHR-IonStar vs SWATH-MS in measuring the time courses of altered proteins in paclitaxel-treated cells (N = 36), where dysregulated biological pathways have been very well established. UHR-IonStar discovered substantially more well-recognized biological processes/pathways induced by paclitaxel. Additionally, UHR-IonStar showed markedly superior ability than SWATH-MS in accurately depicting the time courses of well known to be paclitaxel-induced biomarkers. In summary, UHR-IonStar represents a reliable, robust, and cost-effective solution for large-cohort proteomic quantification with excellent accuracy and precision.

A Novel PDE4D Inhibitor BPN14770 Reverses Scopolamine-Induced Cognitive Deficits via cAMP/SIRT1/Akt/Bcl-2 Pathway

A global, quantitative proteomics/systems-biology analysis of the selective pharmacological inhibition of phosphodiesterase-4D (PDE4D) revealed the differential regulation of pathways associated with neuroplasticity in memory-associated brain regions. Subtype selective inhibitors of PDE4D bind in an allosteric site that differs between mice and humans in a single amino acid (tyrosine vs. phenylalanine, respectively). Therefore to study selective inhibition of PDE4D by BPN14770, a subtype selective allosteric inhibitor of PDE4D, we utilized a line of mice in which the PDE4D gene had been humanized by mutating the critical tyrosine to phenylalanine. Relatively low doses of BPN14770 were effective at reversing scopolamine-induced memory and cognitive deficits in humanized PDE4D mice. Inhibition of PDE4D alters the expression of protein kinase A (PKA), Sirt1, Akt, and Bcl-2/Bax which are components of signaling pathways for regulating endocrine response, stress resistance, neuronal autophagy, and apoptosis. Treatment with a series of antagonists, such as H89, sirtinol, and MK-2206, reversed the effect of BPN14770 as shown by behavioral tests and immunoblot analysis. These findings suggest that inhibition of PDE4D enhances signaling through the cAMP-PKA-SIRT1-Akt -Bcl-2/Bax pathway and thereby may provide therapeutic benefit in neurocognitive disorders.

Transitioning from Basic toward Systems Pharmacodynamic Models: Lessons from Corticosteroids

Technology in bioanalysis, -omics, and computation have evolved over the past half century to allow for comprehensive assessments of the molecular to whole body pharmacology of diverse corticosteroids. Such studies have advanced pharmacokinetic and pharmacodynamic (PK/PD) concepts and models that often generalize across various classes of drugs. These models encompass the "pillars" of pharmacology, namely PK and target drug exposure, the mass-law interactions of drugs with receptors/targets, and the consequent turnover and homeostatic control of genes, biomarkers, physiologic responses, and disease symptoms. Pharmacokinetic methodology utilizes noncompartmental, compartmental, reversible, physiologic [full physiologically based pharmacokinetic (PBPK) and minimal PBPK], and target-mediated drug disposition models using a growing array of pharmacometric considerations and software. Basic PK/PD models have emerged (simple direct, biophase, slow receptor binding, indirect response, irreversible, turnover with inactivation, and transduction models) that place emphasis on parsimony, are mechanistic in nature, and serve as highly useful "top-down" methods of quantitating the actions of diverse drugs. These are often components of more complex quantitative systems pharmacology (QSP) models that explain the array of responses to various drugs, including corticosteroids. Progressively deeper mechanistic appreciation of PBPK, drug-target interactions, and systems physiology from the molecular (genomic, proteomic, metabolomic) to cellular to whole body levels provides the foundation for enhanced PK/PD to comprehensive QSP models. Our research based on cell, animal, clinical, and theoretical studies with corticosteroids have provided ideas and quantitative methods that have broadly advanced the fields of PK/PD and QSP modeling and illustrates the transition toward a global, systems understanding of actions of diverse drugs. SIGNIFICANCE STATEMENT: Over the past half century, pharmacokinetics (PK) and pharmacokinetics/pharmacodynamics (PK/PD) have evolved to provide an array of mechanism-based models that help quantitate the disposition and actions of most drugs. We describe how many basic PK and PK/PD model components were identified and often applied to the diverse properties of corticosteroids (CS). The CS have complications in disposition and a wide array of simple receptor-to complex gene-mediated actions in multiple organs. Continued assessments of such complexities have offered opportunities to develop models ranging from simple PK to enhanced PK/PD to quantitative systems pharmacology (QSP) that help explain therapeutic and adverse CS effects. Concurrent development of state-of-the-art PK, PK/PD, and QSP models are described alongside experimental studies that revealed diverse CS actions.

MS1 ion current-based quantitative proteomics: A promising solution for reliable analysis of large biological cohorts

The rapidly-advancing field of pharmaceutical and clinical research calls for systematic, molecular-level characterization of complex biological systems. To this end, quantitative proteomics represents a powerful tool but an optimal solution for reliable large-cohort proteomics analysis, as frequently involved in pharmaceutical/clinical investigations, is urgently needed. Large-cohort analysis remains challenging owing to the deteriorating quantitative quality and snowballing missing data and false-positive discovery of altered proteins when sample size increases. MS1 ion current-based methods, which have become an important class of label-free quantification techniques during the past decade, show considerable potential to achieve reproducible protein measurements in large cohorts with high quantitative accuracy/precision. Nonetheless, in order to fully unleash this potential, several critical prerequisites should be met. Here we provide an overview of the rationale of MS1-based strategies and then important considerations for experimental and data processing techniques, with the emphasis on (i) efficient and reproducible sample preparation and LC separation; (ii) sensitive, selective and high-resolution MS detection; iii)accurate chromatographic alignment; (iv) sensitive and selective generation of quantitative features; and (v) optimal post-feature-generation data quality control. Prominent technical developments in these aspects are discussed. Finally, we reviewed applications of MS1-based strategy in disease mechanism studies, biomarker discovery, and pharmaceutical investigations.

Pathway-Based Analysis of the Liver Response to Intravenous Methylprednisolone Administration in Rats: Acute Versus Chronic Dosing

Pharmacological time-series data, from comparative dosing studies, are critical to characterizing drug effects. Reconciling the data from multiple studies is inevitably difficult; multiple in vivo high-throughput -omics studies are necessary to capture the global and temporal effects of the drug, but these experiments, though analogous, differ in (microarray or other) platforms, time-scales, and dosing regimens and thus cannot be directly combined or compared. This investigation addresses this reconciliation issue with a meta-analysis technique aimed at assessing the intrinsic activity at the pathway level. The purpose of this is to characterize the dosing effects of methylprednisolone (MPL), a widely used anti-inflammatory and immunosuppressive corticosteroid (CS), within the liver. A multivariate decomposition approach is applied to analyze acute and chronic MPL dosing in male adrenalectomized rats and characterize the dosing-dependent differences in the dynamic response of MPL-responsive signaling and metabolic pathways. We demonstrate how to deconstruct signaling and metabolic pathways into their constituent pathway activities, activities which are scored for intrinsic pathway activity. Dosing-induced changes in the dynamics of pathway activities are compared using a model-based assessment of pathway dynamics, extending the principles of pharmacokinetics/pharmacodynamics (PKPD) to describe pathway activities. The model-based approach enabled us to hypothesize on the likely emergence (or disappearance) of indirect dosing-dependent regulatory interactions, pointing to likely mechanistic implications of dosing of MPL transcriptional regulation. Both acute and chronic MPL administration induced a strong core of activity within pathway families including the following: lipid metabolism, amino acid metabolism, carbohydrate metabolism, metabolism of cofactors and vitamins, regulation of essential organelles, and xenobiotic metabolism pathway families. Pathway activities alter between acute and chronic dosing, indicating that MPL response is dosing dependent. Furthermore, because multiple pathway activities are dominant within a single pathway, we observe that pathways cannot be defined by a single response. Instead, pathways are defined by multiple, complex, and temporally related activities corresponding to different subgroups of genes within each pathway.

Surfactant Cocktail-Aided Extraction/Precipitation/On-Pellet Digestion Strategy Enables Efficient and Reproducible Sample Preparation for Large-Scale Quantitative Proteomics

For quantitative proteomics, efficient, robust, and reproducible sample preparation with high throughput is critical yet challenging, especially when large cohorts are involved, as is often required by clinical/pharmaceutical studies. We describe a rapid and straightforward surfactant cocktail-aided extraction/precipitation/on-pellet digestion (SEPOD) strategy to address this need. Prior to organic solvent precipitation and on-pellet digestion, SEPOD treats samples with a surfactant cocktail (SC) containing multiple nonionic/anionic surfactants, which achieves (i) exhaustive/reproducible protein extraction, including membrane-bound proteins; (ii) effective removal of detrimental nonprotein matrix components (e.g., >94% of phospholipids); (iii) rapid/efficient proteolytic digestion owing to dual (surfactants + precipitation) denaturation. The optimal SC composition and concentrations were determined by Orthogonal-Array-Design investigation of their collective/individuals effects on protein extraction/denaturation. Key parameters for cleanup and digestion were experimentally identified as well. The optimized SEPOD procedures allowed a rapid 6 h digestion providing a clean digest with high peptide yields and excellent quantitative reproducibility (especially low-abundance proteins). Compared with filter-assisted sample preparation (FASP) and in-solution digestion, SEPOD showed superior performance by recovering substantially more peptide/proteins (including integral membrane proteins), yielding significantly higher peptide intensities and improving quantification for peptides with extreme physicochemical properties. SEPOD was further applied in a large-cohort temporal investigation of 44 IAV-infected mouse lungs, providing efficient and reproducible peptide yields (77.9 ± 4.6%) across all samples. With the IonStar pipeline, >6 400 unique protein groups were quantified (≥2 peptide/protein, peptide-FDR < 0.05%), ∼99% without missing data in any sample with <7% technical median-intragroup CV. Altered proteome patterns revealed interesting novel insights into pathophysiological changes by IAV infection. In summary, SEPOD offers a feasible solution for rapid, efficient, and reproducible preparation of biological samples, facilitating high-quality proteomic quantification of large sample cohorts.

Modeling Corticosteroid Pharmacogenomics and Proteomics in Rat Liver

Corticosteroids (CS) regulate the expression of numerous genes at the mRNA and protein levels. The time course of CS pharmacogenomics and proteomics were examined in livers obtained from adrenalectomized rats given a 50-mg/kg bolus dose of methylprednisolone. Microarrays and mass spectrometry-based proteomics were employed to quantify hepatic transcript and protein dynamics. One-hundred, sixty-three differentially expressed mRNA and their corresponding proteins (163 genes) were clustered into two dominant groups. The temporal profiles of most proteins were delayed compared with their mRNA, attributable to synthesis delays and slower degradation kinetics. On the basis of our fifth-generation model of CS, mathematical models were developed to simultaneously describe the emergent time patterns for an array of steroid-responsive mRNA and proteins. The majority of genes showed time-dependent increases in mRNA and protein expression before returning to baseline. A model assuming direct, steroid-mediated stimulation of mRNA synthesis was applied. Some mRNAs and their proteins displayed down-regulation following CS. A model assuming receptor-mediated inhibition of mRNA synthesis was used. More complex patterns were observed for other genes (e.g., biphasic behaviors and opposite directionality in mRNA and protein). Models assuming either stimulation or inhibition of mRNA synthesis coupled with dual secondarily induced regulatory mechanisms affecting mRNA or protein turnover were derived. These findings indicate that CS-regulated gene expression manifested at the mRNA and protein levels are controlled via mechanisms affecting key turnover processes. Our quantitative models of CS pharmacogenomics were expanded from mRNA to proteins and provide extended hypotheses for understanding the direct, secondary, and downstream mechanisms of CS actions.

IonStar enables high-precision, low-missing-data proteomics quantification in large biological cohorts

Reproducible quantification of large biological cohorts is critical for clinical/pharmaceutical proteomics yet remains challenging because most prevalent methods suffer from drastically declined commonly quantified proteins and substantially deteriorated quantitative quality as cohort size expands. MS2-based data-independent acquisition approaches represent tremendous advancements in reproducible protein measurement, but often with limited depth. We developed IonStar, an MS1-based quantitative approach enabling in-depth, high-quality quantification of large cohorts by combining efficient/reproducible experimental procedures with unique data-processing components, such as efficient 3D chromatographic alignment, sensitive and selective direct ion current extraction, and stringent postfeature generation quality control. Compared with several popular label-free methods, IonStar exhibited far lower missing data (0.1%), superior quantitative accuracy/precision [∼5% intragroup coefficient of variation (CV)], the widest protein abundance range, and the highest sensitivity/specificity for identifying protein changes (<5% false altered-protein discovery) in a benchmark sample set (n = 20). We demonstrated the usage of IonStar by a large-scale investigation of traumatic injuries and pharmacological treatments in rat brains (n = 100), quantifying >7,000 unique protein groups (>99.8% without missing data across the 100 samples) with a low false discovery rate (FDR), two or more unique peptides per protein, and high quantitative precision. IonStar represents a reliable and robust solution for precise and reproducible protein measurement in large cohorts.

Receptor/gene/protein-mediated signaling connects methylprednisolone exposure to metabolic and immune-related pharmacodynamic actions in liver

A multiscale pharmacodynamic model was developed to characterize the receptor-mediated, transcriptomic, and proteomic determinants of corticosteroid (CS) effects on clinically relevant hepatic processes following a single dose of methylprednisolone (MPL) given to adrenalectomized (ADX) rats. The enhancement of tyrosine aminotransferase (TAT) mRNA, protein, and enzyme activity were simultaneously described. Mechanisms related to the effects of MPL on glucose homeostasis, including the regulation of CCAAT-enhancer binding protein-beta (C/EBPβ) and phosphoenolpyruvate carboxykinase (PEPCK) as well as insulin dynamics were evaluated. The MPL-induced suppression of circulating lymphocytes was modeled by coupling its effect on cell trafficking with pharmacogenomic effects on cell apoptosis via the hepatic (STAT3-regulated) acute phase response. Transcriptomic and proteomic time-course profiles measured in steroid-treated rat liver were utilized to model the dynamics of mechanistically relevant gene products, which were linked to associated systemic end-points. While time-courses of TAT mRNA, protein, and activity were well described by transcription-mediated changes, additional post-transcriptional processes were included to explain the lack of correlation between PEPCK mRNA and protein. The immune response model quantitatively discerned the relative roles of cell trafficking versus gene-mediated lymphocyte apoptosis by MPL. This systems pharmacodynamic model provides insights into the contributions of selected molecular events occurring in liver and explores mechanistic hypotheses for the multi-factorial control of clinically relevant pharmacodynamic outcomes.

Temporal Effects of Combined Birinapant and Paclitaxel on Pancreatic Cancer Cells Investigated via Large-Scale, Ion-Current-Based Quantitative Proteomics (IonStar)

Despite decades of effort, pancreatic adenocarcinoma (PDAC) remains an intractable clinical challenge. An insufficient understanding of mechanisms underlying tumor cell responses to chemotherapy contributes significantly to the lack of effective treatment regimens. Here, paclitaxel, a first-line chemotherapeutic agent, was observed to interact synergistically with birinapant, a second mitochondrial-derived activator of caspases mimetic. Therefore, we investigated molecular-level drug interaction mechanisms using comprehensive, reproducible, and well-controlled ion-current-based MS1 quantification (IonStar). By analyzing 40 biological samples in a single batch, we compared temporal proteomic responses of PDAC cells treated with birinapant and paclitaxel, alone and combined. Using stringent criteria (e.g. strict false-discovery-rate (FDR) control, two peptides/protein), we quantified 4069 unique proteins confidently (99.8% without any missing data), and 541 proteins were significantly altered in the three treatment groups, with an FDR of <1%. Interestingly, most of these proteins were altered only by combined birinapant/paclitaxel, and these predominantly represented three biological processes: mitochondrial function, cell growth and apoptosis, and cell cycle arrest. Proteins responsible for activation of oxidative phosphorylation, fatty acid β-oxidation, and inactivation of aerobic glycolysis were altered largely by combined birinapant/paclitaxel compared with single drugs, suggesting the Warburg effect, which is critical for survival and proliferation of cancer cells, was alleviated by the combination treatment. Metabolic profiling was performed to confirm substantially greater suppression of the Warburg effect by the combined agents compared with either drug alone. Immunoassays confirmed proteomic data revealing changes in apoptosis/survival signaling pathways, such as inhibition of PI3K/AKT, JAK/STAT, and MAPK/ERK signal transduction, as well as induction of G2/M arrest, and showed the drug combination induced much more apoptosis than did single agents. Overall, this in-depth, large-scale proteomics study provided novel insights into molecular mechanisms underlying synergy of combined birinapant/paclitaxel and describes a proteomics/informatics pipeline that can be applied broadly to the development of cancer drug combination regimens.

Proteomic Analysis of Combined Gemcitabine and Birinapant in Pancreatic Cancer Cells

Pancreatic cancer is characterized by mutated signaling pathways and a high incidence of drug resistance. Comprehensive, large-scale proteomic analysis can provide a system-wide view of signaling networks, assist in understanding drug mechanisms of action and interactions, and serve as a useful tool for pancreatic cancer research. In this study, liquid chromatography-mass spectrometry-based proteomic analysis was applied to characterize the combination of gemcitabine and birinapant in pancreatic cancer cells, which was shown previously to be synergistic. A total of 4069 drug-responsive proteins were identified and quantified in a time-series proteome analysis. This rich dataset provides broad views and accurate quantification of signaling pathways. Pathways relating to DNA damage response regulations, DNA repair, anti-apoptosis, pro-migration/invasion were implicated as underlying mechanisms for gemcitabine resistance and for the beneficial effects of the drug combination. Promising drug targets were identified for future investigation. This study also provides a database for systems mathematical modeling to relate drug effects and interactions in various signaling pathways in pancreatic cancer cells.

Sensitive, High-Throughput, and Robust Trapping-Micro-LC-MS Strategy for the Quantification of Biomarkers and Antibody Biotherapeutics

For LC-MS-based targeted quantification of biotherapeutics and biomarkers in clinical and pharmaceutical environments, high sensitivity, high throughput, and excellent robustness are all essential but remain challenging. For example, though nano-LC-MS has been employed to enhance analytical sensitivity, it falls short because of its low loading capacity, poor throughput, and low operational robustness. Furthermore, high chemical noise in protein bioanalysis typically limits the sensitivity. Here we describe a novel trapping-micro-LC-MS (T-μLC-MS) strategy for targeted protein bioanalysis, which achieves high sensitivity with exceptional robustness and high throughput. A rapid, high-capacity trapping of biological samples is followed by μLC-MS analysis; dynamic sample trapping and cleanup are performed using pH, column chemistry, and fluid mechanics separate from the μLC-MS analysis, enabling orthogonality, which contributes to the reduction of chemical noise and thus results in improved sensitivity. Typically, the selective-trapping and -delivery approach strategically removes >85% of the matrix peptides and detrimental components, markedly enhancing sensitivity, throughput, and operational robustness, and narrow-window-isolation selected-reaction monitoring further improves the signal-to-noise ratio. In addition, unique LC-hardware setups and flow approaches eliminate gradient shock and achieve effective peak compression, enabling highly sensitive analyses of plasma or tissue samples without band broadening. In this study, the quantification of 10 biotherapeutics and biomarkers in plasma and tissues was employed for method development. As observed, a significant sensitivity gain (up to 25-fold) compared with that of conventional LC-MS was achieved, although the average run time was only 8 min/sample. No appreciable peak deterioration or loss of sensitivity was observed after >1500 injections of tissue and plasma samples. The developed method enabled, for the first time, ultrasensitive LC-MS quantification of low levels of a monoclonal antibody and antigen in a tumor and cardiac troponin I in plasma after brief cardiac ischemia. This strategy is valuable when highly sensitive protein quantification in large sample sets is required, as is often the case in typical biomarker validation and pharmaceutical investigations of antibody therapeutics.

An IonStar Experimental Strategy for MS1 Ion Current-Based Quantification Using Ultrahigh-Field Orbitrap: Reproducible, In-Depth, and Accurate Protein Measurement in Large Cohorts

In-depth and reproducible protein measurement in many biological samples is often critical for pharmaceutical/biomedical proteomics but remains challenging. MS1-based quantification using quadrupole/ultrahigh-field Orbitrap (Q/UHF-Orbitrap) holds great promise, but the critically important experimental approaches enabling reliable large-cohort analysis have long been overlooked. Here we described an IonStar experimental strategy achieving excellent quantitative quality of MS1 quantification. Key features include: (i) an optimized, surfactant-aided sample preparation approach provides highly efficient (>75% recovery) and reproducible (<15% CV) peptide recovery across large cell/tissue cohorts; (ii) a long column with modest gradient length (2.5 h) yields the optimal balance of depth/throughput on a Q/UHF-Orbitrap; (iii) a large-ID trap not only enables highly reproducible gradient delivery as for the first time observed via real-time conductivity monitoring, but also increases quantitative loading capacity by >8-fold and quantified >25% more proteins; (iv) an optimized HCD-OT markedly outperforms HCD-IT when analyzing large cohorts with high loading amounts; (v) selective removal of hydrophobic/hydrophilic matrix components using a novel selective trapping/delivery approach enables reproducible, robust LC-MS analysis of >100 biological samples in a single set, eliminating batch effect; (vi) MS1 acquired at higher resolution (fwhm = 120 k) provides enhanced S/N and quantitative accuracy/precision for low-abundance species. We examined this pipeline by analyzing a 5 group, 20 samples biological benchmark sample set, and quantified 6273 unique proteins (≥2 peptides/protein) under stringent cutoffs without fractionation, 6234 (>99.4%) without missing data in any of the 20 samples. The strategy achieved high quantitative accuracy (3-6% media error), low intragroup variation (6-9% media intragroup CV) and low false-positive biomarker discovery rates (3-8%) across the five groups, with quantified protein abundances spanning >6.5 orders of magnitude. Finally, this strategy is straightforward, robust, and broadly applicable in pharmaceutical/biomedical investigations.

Quantitative proteomic profiling of paired cancerous and normal colon epithelial cells isolated freshly from colorectal cancer patients

PURPOSE

The heterogeneous structure in tumor tissues from colorectal cancer (CRC) patients excludes an informative comparison between tumors and adjacent normal tissues. Here, we develop and apply a strategy to compare paired cancerous (CEC) versus normal (NEC) epithelial cells enriched from patients and discover potential biomarkers and therapeutic targets for CRC.

EXPERIMENTAL DESIGN

CEC and NEC cells are respectively isolated from five different tumor and normal locations in the resected colon tissue from each patient (N = 12 patients) using an optimized epithelial cell adhesion molecule (EpCAM)-based enrichment approach. An ion current-based quantitative method is employed to perform comparative proteomic analysis for each patient.

RESULTS

A total of 458 altered proteins that are common among >75% of patients are observed and selected for further investigation. Besides known findings such as deregulation of mitochondrial function, tricarboxylic acid cycle, and RNA post-transcriptional modification, functional analysis further revealed RAN signaling pathway, small nucleolar ribonucleoproteins (snoRNPs), and infection by RNA viruses are altered in CEC cells. A selection of the altered proteins of interest is validated by immunohistochemistry analyses.

CONCLUSION AND CLINICAL RELEVANCE

The informative comparison between matched CEC and NEC enhances our understanding of molecular mechanisms of CRC development and provides biomarker candidates and new pathways for therapeutic intervention.

Functional proteomic analysis of corticosteroid pharmacodynamics in rat liver: Relationship to hepatic stress, signaling, energy regulation, and drug metabolism

Corticosteroids (CS) are anti-inflammatory agents that cause extensive pharmacogenomic and proteomic changes in multiple tissues. An understanding of the proteome-wide effects of CS in liver and its relationships to altered hepatic and systemic physiology remains incomplete. Here, we report the application of a functional pharmacoproteomic approach to gain integrated insight into the complex nature of CS responses in liver in vivo. An in-depth functional analysis was performed using rich pharmacodynamic (temporal-based) proteomic data measured over 66h in rat liver following a single dose of methylprednisolone (MPL). Data mining identified 451 differentially regulated proteins. These proteins were analyzed on the basis of temporal regulation, cellular localization, and literature-mined functional information. Of the 451 proteins, 378 were clustered into six functional groups based on major clinically-relevant effects of CS in liver. MPL-responsive proteins were highly localized in the mitochondria (20%) and cytosol (24%). Interestingly, several proteins were related to hepatic stress and signaling processes, which appear to be involved in secondary signaling cascades and in protecting the liver from CS-induced oxidative damage. Consistent with known adverse metabolic effects of CS, several rate-controlling enzymes involved in amino acid metabolism, gluconeogenesis, and fatty-acid metabolism were altered by MPL. In addition, proteins involved in the metabolism of endogenous compounds, xenobiotics, and therapeutic drugs including cytochrome P450 and Phase-II enzymes were differentially regulated. Proteins related to the inflammatory acute-phase response were up-regulated in response to MPL. Functionally-similar proteins showed large diversity in their temporal profiles, indicating complex mechanisms of regulation by CS.

SIGNIFICANCE

Clinical use of corticosteroid (CS) therapy is frequent and chronic. However, current knowledge on the proteome-level effects of CS in liver and other tissues is sparse. While transcriptomic regulation following methylprednisolone (MPL) dosing has been temporally examined in rat liver, proteomic assessments are needed to better characterize the tissue-specific functional aspects of MPL actions. This study describes a functional pharmacoproteomic analysis of dynamic changes in MPL-regulated proteins in liver and provides biological insight into how steroid-induced perturbations on a molecular level may relate to both adverse and therapeutic responses presented clinically.

Understanding Physiology in the Continuum: Integration of Information from Multiple -Omics Levels

In this paper, we discuss approaches for integrating biological information reflecting diverse physiologic levels. In particular, we explore statistical and model-based methods for integrating transcriptomic, proteomic and metabolomics data. Our case studies reflect responses to a systemic inflammatory stimulus and in response to an anti-inflammatory treatment. Our paper serves partly as a review of existing methods and partly as a means to demonstrate, using case studies related to human endotoxemia and response to methylprednisolone (MPL) treatment, how specific questions may require specific methods, thus emphasizing the non-uniqueness of the approaches. Finally, we explore novel ways for integrating -omics information with PKPD models, toward the development of more integrated pharmacology models.

Phosphorylation of Tyr188 in the WW domain of YAP1 plays an essential role in YAP1-induced cellular transformation

The Hippo signaling pathway regulates cellular proliferation and survival, thus exerting profound effects on normal cell fate and tumorigenesis. The pivotal effector of this pathway is YAP1, a transcriptional co-activator amplified in mouse and human cancers where it promotes epithelial-to-mesenchymal transition (EMT) and malignant transformation. The Hippo tumor suppressor pathway has been suggested to inhibit the YAP1 function through serine phosphorylation-induced cytoplasmic retention and degradation. Here we report that the tyrosine188 (Y188) site of YAP1 isoform with 2 WW domains (known as YAP1-2) plays an important role in YAP1-induced cellular transformation. IP-Mass Spectrometry analysis of YAP1 identified the phosphorylation of Y188 but not other tyrosine residues. In contrast to the aberrant 3D acinus formation observed in YAP1-WT transduced cells, overexpression of YAP1-Y188F (non-phosphorylated mimic) displayed normal 3D structures. In addition, knockdown of the endogenous YAP1 in MDA-MB231 breast cancer cells inhibited cell proliferation and migration, which were then successfully rescued by the exogenous YAP1-WT and YAP1-Y188E but not Y188F. Mechanistically, we also demonstrated that YAP1-Y188F had a higher affinity to the upstream negative regulator PTPN14 and was extensively localized in the cytoplasm. Since the Y188 is located in the conserved aromatic core of the WW domain of YAP1, our finding has a wide implication for WW domain signaling in general, where Y phosphorylation may act as a common positive regulator of the complex formation via WW domains. In summary, our results indicate that tyrosine 188 plays an important role in the YAP1-induced cellular transformation and its phosphorylation may intriguingly serve as a positive indicator of YAP1 activation.

Large-Scale, Ion-Current-Based Proteomic Investigation of the Rat Striatal Proteome in a Model of Short- and Long-Term Cocaine Withdrawal

Given the tremendous detriments of cocaine dependence, effective diagnosis and patient stratification are critical for successful intervention yet difficult to achieve due to the largely unknown molecular mechanisms involved. To obtain new insights into cocaine dependence and withdrawal, we employed a reproducible, reliable, and large-scale proteomics approach to investigate the striatal proteomes of rats (n = 40, 10 per group) subjected to chronic cocaine exposure, followed by either short- (WD1) or long- (WD22) term withdrawal. By implementing a surfactant-aided precipitation/on-pellet digestion procedure, a reproducible and sensitive nanoLC-Orbitrap MS analysis, and an optimized ion-current-based MS1 quantification pipeline, >2000 nonredundant proteins were quantified confidently without missing data in any replicate. Although cocaine was cleared from the body, 129/37 altered proteins were observed in WD1/WD22 that are implicated in several biological processes related closely to drug-induced neuroplasticity. Although many of these changes recapitulate the findings from independent studies reported over the last two decades, some novel insights were obtained and further validated by immunoassays. For example, significantly elevated striatal protein kinase C activity persisted over the 22 day cocaine withdrawal. Cofilin-1 activity was up-regulated in WD1 and down-regulated in WD22. These discoveries suggest potentially distinct structural plasticity after short- and long-term cocaine withdrawal. In addition, this study provides compelling evidence that blood vessel narrowing, a long-known effect of cocaine use, occurred after long-term but not short-term withdrawal. In summary, this work developed a well-optimized paradigm for ion-current-based quantitative proteomics in brain tissues and obtained novel insights into molecular alterations in the striatum following cocaine exposure and withdrawal.

Ion-Current-Based Temporal Proteomic Profiling of Influenza-A-Virus-Infected Mouse Lungs Revealed Underlying Mechanisms of Altered Integrity of the Lung Microvascular Barrier

Investigation of influenza-A-virus (IAV)-infected lung proteomes will greatly promote our understanding on the virus-host crosstalk. Using a detergent-cocktail extraction and digestion procedure and a reproducible ion-current-based method, we performed the first comprehensive temporal analysis of mouse IAV infection. Mouse lung tissues at three time points post-inoculation were compared with controls (n = 4/group), and >1600 proteins were quantified without missing value in any animal. Significantly changed proteins were identified at 4 days (n = 144), 7 days (n = 695), and 10 days (n = 396) after infection, with low false altered protein rates (1.73-8.39%). Functional annotation revealed several key biological processes involved in the systemic host responses. Intriguingly, decreased levels of several cell junction proteins as well as increased levels of tissue metalloproteinase MMP9 were observed, reflecting the IAV-induced structural breakdown of lung epithelial barrier. Supporting evidence of MMP9 activation came from immunoassays examining the abundance and phosphorylation states of all MAPKs and several relevant molecules. Importantly, IAV-induced MMP gelatinase expression was suggested to be specific to MMP9, and p38 MAPK may contribute predominantly to MMP9 elevation. These findings help to resolve the long-lasting debate regarding the signaling pathways of IAV-induced MMP9 expression and shed light on the molecular mechanisms underlying pulmonary capillary-alveolar leak syndrome that can occur during influenza infection.

New Insights into the Disease Progression Control Mechanisms by Comparing Long-Term-Nonprogressors versus Normal-Progressors among HIV-1-Positive Patients Using an Ion Current-Based MS1 Proteomic Profiling

For decades, epidemiological studies have found significant differences in the susceptibility to disease progression among HIV-carrying patients. One unique group of HIV-1-positive patients, the long-term-nonprogressors (LTNP), exhibits far superior ability in virus control compared with normal-progressors (NP), which proceed to Acquired Immune Deficiency Syndrome (AIDS) much more rapidly. Nonetheless, elucidation of the underlying mechanisms of virus control in LTNP is highly valuable in disease management and treatment but remains poorly understood. Peripheral blood mononuclear cells (PBMC) have been known to play important roles in innate immune responses and thereby would be of great interest for the investigation of the mechanisms of virus defense in LTNP. Here, we described the first comparative proteome analysis of PBMC from LTNP (n = 10) and NP (n = 10) patients using a reproducible ion-current-based MS1 approach, which includes efficient and reproducible sample preparation and chromatographic separation followed by an optimized pipeline for protein identification and quantification. This strategy enables analysis of many biological samples in one set with high quantitative precision and extremely low missing data. In total, 925 unique proteins were quantified under stringent criteria without missing value in any of the 20 subjects, and 87 proteins showed altered expressions between the two patient groups. These proteins are implicated in key processes such as cytoskeleton organization, defense response, apoptosis regulation, intracellular transport, etc., which provided novel insights into the control of disease progressions in LTNP versus NP, and the expression and phosphorylation states of key regulators were further validated by immunoassay. For instance, (1) SAMH1, a potent and "hot" molecule facilitating HIV-1 defense, was for the first time found elevated in LTNP compared with NP or healthy controls; elevated proteins from IFN-α response pathway may also contribute to viral control in LTNP; (2) decreased proapoptotic protein ASC along with the elevation of antiapoptotic proteins may contribute to the less apoptotic profile in PBMC of LTNP; and (3) elevated actin polymerization and less microtubule assembly that impede viral protein transport were first observed in LTNP. These results not only enhanced the understanding of the mechanisms for nonprogression of LTNP, but also may afford highly valuable clues to direct therapeutic efforts. Moreover, this work also demonstrated the ion-current-based MS1 approach as a reliable tool for large-scale clinical research.

Experimental Null Method to Guide the Development of Technical Procedures and to Control False-Positive Discovery in Quantitative Proteomics

Comprehensive and accurate evaluation of data quality and false-positive biomarker discovery is critical to direct the method development/optimization for quantitative proteomics, which nonetheless remains challenging largely due to the high complexity and unique features of proteomic data. Here we describe an experimental null (EN) method to address this need. Because the method experimentally measures the null distribution (either technical or biological replicates) using the same proteomic samples, the same procedures and the same batch as the case-vs-contol experiment, it correctly reflects the collective effects of technical variability (e.g., variation/bias in sample preparation, LC-MS analysis, and data processing) and project-specific features (e.g., characteristics of the proteome and biological variation) on the performances of quantitative analysis. To show a proof of concept, we employed the EN method to assess the quantitative accuracy and precision and the ability to quantify subtle ratio changes between groups using different experimental and data-processing approaches and in various cellular and tissue proteomes. It was found that choices of quantitative features, sample size, experimental design, data-processing strategies, and quality of chromatographic separation can profoundly affect quantitative precision and accuracy of label-free quantification. The EN method was also demonstrated as a practical tool to determine the optimal experimental parameters and rational ratio cutoff for reliable protein quantification in specific proteomic experiments, for example, to identify the necessary number of technical/biological replicates per group that affords sufficient power for discovery. Furthermore, we assessed the ability of EN method to estimate levels of false-positives in the discovery of altered proteins, using two concocted sample sets mimicking proteomic profiling using technical and biological replicates, respectively, where the true-positives/negatives are known and span a wide concentration range. It was observed that the EN method correctly reflects the null distribution in a proteomic system and accurately measures false altered proteins discovery rate (FADR). In summary, the EN method provides a straightforward, practical, and accurate alternative to statistics-based approaches for the development and evaluation of proteomic experiments and can be universally adapted to various types of quantitative techniques.

Analytical strategies used to identify the readers of histone modifications: A review

The so-called "readers" of histone post-translational modifications (HPTMs) refer to proteins or complexes that are recruited to HPTMs thus eventually regulate gene transcription. To identify these "readers", mass spectrometry plays an essential role following various enriching strategies. These enriching methods include the use of modified histone peptides/proteins or chemically synthesized histones/nucleosomes containing desired HPTMs to enrich the readers of HPTMs. Despite the peptide- or protein-based assay is straightforward and easy to perform for most labs, this strategy has limited applications for those weak or combinational interactions among various HPTMs and false-positive results are a potential big problem. While the results derived from synthesized histone proteins/nucleosomes is more reliable as it mimics the real chromatic conditions thus is able to analyze the binders of those cross-talked HPTMs, usually the synthesis is so difficult that their applications are impeded for high throughput analysis. In this review, an overview of these analytical techniques is provided and their advantages and disadvantages are discussed.

Nano-LC in proteomics: recent advances and approaches

In proteomics, nano-LC is arguably the most common tool for separating peptides/proteins prior to MS. The main advantage of nano-LC is enhanced sensitivity, as compounds enter the MS in more concentrated bands. This is particularly relevant for determining low abundant compounds in limited samples. Nano-LC columns can produce peak capacities of 1000 or more, and very narrow columns can be used to perform proteomics of 1000 cells or less. Also, nano-LC can be coupled with online add-ons such as selective trap columns or enzymatic reactors, for faster and more automated analysis. Nano-LC is today an established tool for research laboratories; but can nano-LC-based systems soon be ready for more routine settings, such as in clinics?

Arginine methylation of DRBD18 differentially impacts its opposing effects on the trypanosome transcriptome

Arginine methylation is a posttranslational modification that impacts wide-ranging cellular functions, including transcription, mRNA splicing and translation. RNA binding proteins (RBPs) represent one of the largest classes of arginine methylated proteins in both mammals and the early diverging parasitic protozoan, Trypanosoma brucei. Here, we report the effects of arginine methylation on the functions of the essential and previously uncharacterized T. brucei RBP, DRBD18. RNAseq analysis shows that DRBD18 depletion causes extensive rearrangement of the T. brucei transcriptome, with increases and decreases in hundreds of mRNAs. DRBD18 contains three methylated arginines, and we used complementation of DRBD18 knockdown cells with methylmimic or hypomethylated DRBD18 to assess the functions of these methylmarks. Methylmimic and hypomethylated DRBD18 associate with different ribonucleoprotein complexes. These altered macromolecular interactions translate into differential impacts on the T. brucei transcriptome. Methylmimic DRBD18 preferentially stabilizes target RNAs, while hypomethylated DRBD18 is more efficient at destabilizing RNA. The protein arginine methyltransferase, TbPRMT1, interacts with DRBD18 and knockdown of TbPRMT1 recapitulates the effects of hypomethylated DRBD18 on mRNA levels. Together, these data support a model in which arginine methylation acts as a switch that regulates T. brucei gene expression.

Proteomic profiling of the retinas in a neonatal rat model of oxygen-induced retinopathy with a reproducible ion-current-based MS1 approach

Investigation of the retina proteome during hypoxia-induced retinal neovascularization is valuable for understanding pathogenesis of retinopathy of prematurity (ROP). Here we employed a reproducible ion-current-based MS1 quantification approach (ICB) to explore the retinal proteomic changes in early stage of ROP in a rat model of oxygen-induced retinopathy (OIR). Retina proteins, which are rich in membrane proteins, were efficiently extracted by a detergent-cocktail and subjected to precipitation/on-pellet-digestion, followed by nano-LC-MS analysis on a 75-cm column with a 7-h gradient. The high reproducibility of sample preparation and chromatography separation enabled excellent peak alignment and contributed to the superior performance of ICB over parallel label-free approaches. In this study, sum-of-intensity with rejection was incorporated to determine the protein ratios. In total, 1325 unique protein groups were quantified from rat retinas (n = 4/group) with at least two distinct peptides at a protein FDR of 1%. Thirty-two significantly altered proteins were observed with confidence, and the elevated glial fibrillary acidic protein and decreased crystalline proteins in OIR retinas agree well with previous studies. Selected key alterations were further validated by Western blot analysis. Interestingly, Rab21/RhoA/ROCK2/moesin signaling pathway was found to be involved in retinal neovascularization of OIR. Moreover, highly elevated annexin A3, a potential angiogenic mediator, was observed in OIR retinas and may serve as a potential therapeutic target. In conclusion, reproducible ICB profiling enabled reliable discovery of many altered mediators and pathways in OIR retinas, thereby providing new insights into molecular mechanisms involved in pathogenesis of ROP.

Surfactant-aided precipitation/on-pellet-digestion (SOD) procedure provides robust and rapid sample preparation for reproducible, accurate and sensitive LC/MS quantification of therapeutic protein in plasma and tissues

For targeted protein quantification by liquid chromatography mass spectrometry (LC/MS), an optimal approach for efficient, robust and hi-throughput sample preparation is critical, but often remains elusive. Here we describe a straightforward surfactant-aided-precipitation/on-pellet-digestion (SOD) strategy that provides effective sample cleanup and enables high and constant peptide yields in various matrices, allowing reproducible, accurate and sensitive protein quantification. This strategy was developed using quantification of monocolnocal antibody in tissues and plasma as the model system. Surfactant treatment before precipitation substantially increased peptide recovery and reproducibility from plasma/tissue, likely because surfactant permits extensive denaturation/reduction/alkylation of proteins and inactivation of endogenous protease inhibitors, and facilitates removal of matrix components. The subsequent precipitation procedure effectively eliminates the surfactant and nonprotein matrix components, and the thorough denaturation by both surfactant and precipitation enabled very rapid on-pellet-digestion (45 min at 37 °C) with high peptide recovery. The performance of SOD was systematically compared against in-solution-digestion, in-gel-digestion and filter-aided-sample-preparation (FASP) in plasma/tissues, and then examined in a full pharmacokinetic study in rats. SOD achieved the best peptide recovery (∼21.0-700% higher than the other three methods across various matrices), reproducibility (3.75-10.9%) and sensitivity (28-30 ng/g across plasma and tissue matrices), and its performance was independent of matrix types. Finally, in validation and pharmacokinetic studies in rats, SOD outperformed other methods and provided highly accurate and precise quantification in all plasma samples without using stable isotope labeled (SIL)-protein internal standard (I.S.). In summary, the SOD method has proven to be highly robust, efficient and rapid, making it readily adaptable to large-scale clinical and pharmaceutical quantification of biomarkers or biotherapeutics.

Tandem analysis of transcriptome and proteome changes after a single dose of corticosteroid: a systems approach to liver function in pharmacogenomics

Corticosteroids (CS) such as methylprednisolone (MPL) affect almost all liver functions through multiple mechanisms of action, and long-term use results in dysregulation causing diverse side effects. The complexity of involved molecular mechanisms necessitates a systems approach. Integration of information from the transcriptomic and proteomic responses has potential to provide deeper insights into CS actions. The present report describes the tandem analysis of rich time-series transcriptomic and proteomic data in rat liver after a single dose of MPL. Hierarchical clustering of the common genes represented in both mRNA and protein datasets displayed two dominant patterns. One of these patterns exhibited complementary mRNA and protein expression profiles indicating that MPL affected the regulation of these genes at the transcriptional level. Some of the classic pharmacodynamic markers for CS actions, including tyrosine aminotransferase (TAT), were among this group, together with genes encoding urea cycle enzymes and ribosomal proteins. The other pattern was rather unexpected. For this group of genes, MPL had distinctly observable effects at the protein expression level, although a change in the reverse direction occurred at the transcriptional level. These genes were functionally associated with metabolic processes that might be essential to elucidate side effects of MPL on liver, most importantly including modulation of oxidative stress, fatty acid oxidation, and bile acid biosynthesis. Furthermore, profiling of gene and protein expression data was also done independently of one another by a two-way sequential approach. Prominent temporal shifts in expression and relevant cellular functions were described together with the assessment of changes in the complementary side.