Large-scale evaluation of quantitative reproducibility and proteome coverage using acid cleavable isotope coded affinity tag mass spectrometry for proteomic profiling

Comparative proteomics analysis of Tibetan hull-less barley under osmotic stress via data-independent acquisition mass spectrometry

Background

Tibetan hull-less barley (Hordeum vulgare L. var. nudum) is one of the primary crops cultivated in the mountains of Tibet and encounters low temperature, high salinity, and drought. Specifically, drought is one of the major abiotic stresses that affect and limit Tibetan barley growth. Osmotic stress is often simultaneously accompanied by drought conditions. Thus, to improve crop yield, it is critical to explore the molecular mechanism governing the responses of hull-less barley to osmotic/drought stress conditions.

Findings

In this study, we used quantitative proteomics by data-independent acquisition mass spectrometry to investigate protein abundance changes in tolerant (XL) and sensitive (DQ) cultivars. A total of 6,921 proteins were identified and quantified in all samples. Two distinct strategies based on pairwise and time-course comparisons were utilized in the comprehensive analysis of differentially abundant proteins. Further functional analysis of differentially abundant proteins revealed that some hormone metabolism–associated and phytohormone abscisic acid–induced genes are primarily affected by osmotic stress. Enhanced regulation of reactive oxygen species (may promote the tolerance of hull-less barley under osmotic stress. Moreover, we found that some regulators, such as GRF, PR10, MAPK, and AMPK, were centrally positioned in the gene regulatory network, suggesting that they may have a dominant role in the osmotic stress response of Tibetan barley.

Conclusions

Our findings highlight a subset of proteins and processes that are involved in the alleviation of osmotic stress. In addition, this study provides a large-scale and multidimensional proteomic data resource for the further investigation and improvement of osmotic/drought stress tolerance in hull-less barley or other plant species.

Omics in Systems Biology: Current Progress and Future Outlook

Biological research has undergone tremendous changes over the past three decades. Research used to almost exclusively focus on a single aspect of a single molecule per experiment. Modern technologies have enabled thousands of molecules to be simultaneously analyzed and the way that these molecules influence each other to be discerned. The change is so dramatic that it has given rise to a whole new descriptive suffix (i.e., omics) to describe these fields of study. While genomics was arguably the initial driver of this new trend, it quickly spread to other biological entities resulting in the creation of transcriptomics, proteomics, metabolomics, etc. The development of these "big four omics" created a wave of other omic fields, such as epigenomics, glycomics, lipidomics, microbiomics, and even foodomics; all with the purpose of comprehensively studying all the molecular entities or processes within their respective domain. The large number of omic fields that are invented even led to the term "panomics" as a way to classify them all under one category. Ultimately, all of these omic fields are setting the foundation for developing systems biology; in which the focus will be on determining the complex interactions that occur within biological systems.

Mass spectrometry-based proteome profile may be useful to differentiate adenoid cystic carcinoma from polymorphous adenocarcinoma of salivary glands

OBJECTIVE

The aim of this study was to determine the proteome of adenoid cystic carcinoma (AdCC) and polymorphous adenocarcinoma (PAc) and to identify a protein signature useful in distinguishing these two neoplasms.

STUDY DESIGN

Ten cases of AdCC and 10 cases of PAc were microdissected for enrichment of neoplastic tissue. The samples were submitted to liquid chromatography-tandem mass spectrometry (LC-MS/MS), and the proteomics data were analyzed by using the MaxQuant software. LC-MS/MS spectra were searched against the Human UniProt database, and statistical analyses were performed with Perseus software. Bioinformatic analyses were performed by using discovery-based proteomic data on both tumors.

RESULTS

LC-MS/MS analysis identified 1957 proteins. The tumors shared 1590 proteins, and 261 were exclusively identified in AdCC and 106 in PAc. Clustering analysis of the statistically significant proteins clearly separated AdCC from PAc. Protein expression 10 times higher in one group than in the other led to a signature of 16 proteins-6 upregulated in AdCC and 10 in PAc. A new clustering analysis showed reverse regulation and also differentiated both tumors.

CONCLUSIONS

Global proteomics may be useful in discriminating these two malignant salivary neoplasms that frequently show clinical and microscopic overlaps, but additional validation studies are still necessary to determine the diagnostic potential of the protein signature obtained.

Ribosomal proteomics: Strategies, approaches, and perspectives

Over the past few decades, proteomic research has seen unprecedented development due to technological advancement. However, whole-cell proteomics still has limitations with respect to sample complexity and the accuracy of determining protein locations. To deal with these limitations, several subcellular proteomic studies have been initiated. Nevertheless, compared to other subcellular proteomic fields, such as mitochondrial proteomics, ribosomal proteomics has lagged behind due to the long-held idea that the ribosome is just a translation machine. Recently, with the proposed ribosome filter hypothesis and subsequent studies of ribosome-specific regulatory capacity, ribosomal proteomics has become a promising chapter for both proteomic and ribosomal research. In this review, we discuss the current strategies and approaches in ribosomal proteomics and the efficacies as well as disadvantages of individual approaches for further improvement.

Quantitative proteomics in the field of microbiology

Quantitative proteomics has become an indispensable analytical tool for microbial research. Modern microbial proteomics covers a wide range of topics in basic and applied research from in vitro characterization of single organisms to unravel the physiological implications of stress/starvation to description of the proteome content of a cell at a given time. With the techniques available, ranging from classical gel-based procedures to modern MS-based quantitative techniques, including metabolic and chemical labeling, as well as label-free techniques, quantitative proteomics is today highly successful in sophisticated settings of high complexity such as host-pathogen interactions, mixed microbial communities, and microbial metaproteomics. In this review, we will focus on the vast range of techniques practically applied in current research with an introduction of the workflows used for quantitative comparisons, a description of the advantages/disadvantages of the various methods, reference to hallmark publications and presentation of applications in current microbial research.

Peptide profiling of cerebrospinal fluid by mass spectrometry

The search for biomarkers is driven by the increasing clinical importance of early diagnosis. Reliable biomarkers can also assist in directing therapy, monitoring disease activity and the efficacy of treatment. In addition, the discovery of novel biomarkers might provide clues to the pathogenesis of a disease. The dynamic range of protein concentrations in body fluids exceeds 10 orders of magnitude. These huge differences in concentrations complicate the detection of proteins with low expression levels. Since all classical biomarkers have low expression levels (e.g., prostate-specific antigen: 2-4 microg/l; and CA125: 20-35 U/ml), new developments with respect to identification and validation techniques of the low-abundance proteins are required. This review will discuss the current status of profiling cerebrospinal fluid using mass spectrometry-based techniques, and new developments in this area.

Proteomics analysis of tumor microenvironment: Implications of metabolic and oxidative stresses in tumorigenesis

Tumorigenesis is always concomitant with microenvironmental alterations. The tumor microenvironment is a heterogeneous and complex milieu, which exerts a variety of stresses on tumor cells for proliferation, survival, or death. Recently, accumulated evidence revealed that metabolic and oxidative stresses both play significant roles in tumor development and progression that converge on a common autophagic pathway. Tumor cells display increased metabolic autonomy, and the hallmark is the exploitation of aerobic glycolysis (termed Warburg effect), which increased glucose consumption and decreased oxidative phosphorylation to support growth and proliferation. This characteristic renders cancer cells more aggressive; they devour tremendous amounts of nutrients from microenvironment to result in an ever-growing appetite for new tumor vessel formation and the release of more "waste," including key determinants of cell fate like lactate and reactive oxygen species (ROS). The intracellular ROS level of cancer cells can also be modulated by a variety of stimuli in the tumor microenvironment, such as pro-growth and pro-inflammatory factors. The intracellular redox state serves as a double-edged sword in tumor development and progression: ROS overproduction results in cytotoxic effects and might lead to apoptotic cell death, whereas certain level of ROS can act as a second-messenger for regulation of such cellular processes as cell survival, proliferation, and metastasis. The molecular mechanisms for cancer cell responses to metabolic and oxidative stresses are complex and are likely to involve multiple molecules or signaling pathways. In addition, the expression and modification of these proteins after metabolic or oxidative stress challenge are diverse in different cancer cells and endow them with different functions. Therefore, MS-based high-throughput platforms, such as proteomics, are indispensable in the global analysis of cancer cell responses to metabolic and oxidative stress. Herein, we highlight recent advances in the understanding of the metabolic and oxidative stresses associated with tumor progression with proteomics-based systems biology approaches.

Alteration of the serum N-glycome of mice locally exposed to high doses of ionizing radiation

Exposure of the skin to ionizing radiation leads to characteristic reactions that will often turn into a pathophysiological process called the cutaneous radiation syndrome. The study of this disorder is crucial to finding diagnostic and prognostic bioindicators of local radiation exposure or radiation effects. It is known that irradiation alters the serum proteome content and potentially post-translationally modifies serum proteins. In this study, we investigated whether localized irradiation of the skin alters the serum glycome. Two-dimensional differential in-gel electrophoresis of serum proteins from a man and from mice exposed to ionizing radiation showed that potential post-translational modification changes occurred following irradiation. Using a large-scale quantitative mass-spectrometry-based glycomic approach, we performed a global analysis of glycan structures of serum proteins from non-irradiated and locally irradiated mice exposed to high doses of γ-rays (20, 40, and 80 Gy). Non-supervised descriptive statistical analyses (principal component analysis) using quantitative glycan structure data allowed us to discriminate between uninjured/slightly injured animals and animals that developed severe lesions. Decisional statistics showed that several glycan families were down-regulated whereas others increased, and that particular structures were statistically significantly changed in the serum of locally irradiated mice. The observed increases in multiantennary N-glycans and in outer branch fucosylation and sialylation were associated with the up-regulation of genes involved in glycosylation in the liver, which is the main producer of serum proteins, and with an increase in the key proinflammatory serum cytokines IL-1β, IL-6, and TNFα, which can regulate the expression of glycosylation genes. Our results suggest for the first time a role of serum protein glycosylation in response to irradiation. These protein-associated glycan structure changes might signal radiation exposure or effects.

The methylazoxymethanol acetate (MAM-E17) rat model: molecular and functional effects in the hippocampus

Administration of the DNA-alkylating agent methylazoxymethanol acetate (MAM) on embryonic day 17 (E17) produces behavioral and anatomical brain abnormalities, which model some aspects of schizophrenia. This has lead to the premise that MAM rats are a neurodevelopmental model for schizophrenia. However, the underlying molecular pathways affected in this model have not been elucidated. In this study, we investigated the molecular phenotype of adult MAM rats by focusing on the frontal cortex and hippocampal areas, as these are known to be affected in schizophrenia. Proteomic and metabonomic analyses showed that the MAM treatment on E17 resulted primarily in deficits in hippocampal glutamatergic neurotransmission, as seen in some schizophrenia patients. Most importantly, these results were consistent with our finding of functional deficits in glutamatergic neurotransmission, as identified using electrophysiological recordings. Thus, this study provides the first molecular evidence, combined with functional validation, that the MAM-E17 rat model reproduces hippocampal deficits relevant to the pathology of schizophrenia.

Improvement of the quantification accuracy and throughput for phosphoproteome analysis by a pseudo triplex stable isotope dimethyl labeling approach

Accurately quantifying the changes of phosphorylation level on specific sites is crucial to understand the role of protein phosphorylation in physiological and pathological processes. Here, a pseudo triplex stable isotope dimethyl labeling approach was developed to improve the accuracy and the throughput of comprehensive quantitative phosphoproteome analyses. In this strategy, two identical samples are labeled with light and heavy isotopes, respectively, while another comparative sample is labeled with an intermediate isotope. Two replicated quantification results were achieved in just one experiment, and the relative standard deviation (RSD) criterion was used to control the quantification accuracy. Compared with the conventional duplex labeling approach, the number of quantified phosphopeptides increased nearly 50% and the experimental time was reduced by 50% under the same quantification accuracy. Combined with the automated online reversed phase-strong cation exchange-reversed phase (RP-SCX-RP) multidimensional separation system, a comparative phosphoproteome analysis of hepatocellular carcinoma (HCC) and normal human liver tissues was performed. Over 1800 phosphopeptides corresponding to ~2000 phosphorylation sites were quantified reliably in a 42 h multidimensional analysis. The pro-directed motifs, which were mainly associated with the extracellular signal-regulated kinases (ERKs), were observed as being overrepresented in the regulated phosphorylation sites, and some quantification results of phosphorylation sites were validated by the other studies. Therefore, this pseudo triplex labeling approach was demonstrated as a promising alternative for the comprehensive quantitative phosphoproteome analysis.

A self-validating quantitative mass spectrometry method for assessing the accuracy of high-content phosphoproteomic experiments

Protein kinase pathways play pivotal roles in cell signaling and biology. The phosphoproteome is a reflection of protein kinase pathway activation and therefore there is considerable interest in its quantification as a means to assess the wiring of signaling networks. Although different approaches for quantitative phosphoproteomics have been described, there is no data on how accurate these are for each quantified phosphorylated site. We report a liquid chromatography-MS approach to objectively assess data quality in high-content comparison of phosphoproteomes in which samples to be compared are mixed at different proportions. The experimental data is then used to derive a linear regression function that allows calculating correlation values, linearity, and accuracy. We applied the technique to investigate phosphorylation in P31/Fuj and Kasumi-1, two leukemia cells lines showing strikingly different sensitivities to scr and PI3K inhibitors. We found that phosphopeptides quantified with accuracy were not always quantified with precision because of low ion statistics contributing to variability. Thus our approach was complementary to standard methods for calculating the precision of replicate measurements based on the coefficient of variation and provided additional information on data quality for each quantified phosphopeptide. We quantified > 2250 phosphorylation sites across cell lines with different levels of sensitivity to kinase inhibitors, of which 1847 showed an accuracy variation of < 30% (with an overall mean of 22%). Hundreds of phosphorylation sites on proteins with diverse function (including kinases, transcription, and translation factors) showed significantly distinct intensities across sensitive and resistant cells lines, indicating that kinase pathways are differentially regulated in cancer cells of distinct sensitivity to signaling inhibitors.

Overview of quantitative LC-MS techniques for proteomics and activitomics

LC-MS is a useful technique for protein and peptide quantification. In addition, as a powerful tool for systems biology research, LC-MS can also be used to quantify post-translational modifications and metabolites that reflect biochemical pathway activity. This review discusses the different analytical techniques that use LC-MS for the quantification of proteins, their modifications and activities in a multiplex manner.

Nonionic detergent phase extraction for the proteomic analysis of heart membrane proteins using label-free LC-MS

Heart diseases resulting in heart failure are among the leading causes of morbidity and mortality in the Western world and can result from either systemic disease (e.g., hypertensive heart disease, ischemic heart disease) or specific heart muscle disease (e.g., dilated cardiomyopathy/DCM). Subproteome analysis of such disease subsets affords a reduction in sample complexity, potentially revealing biomarkers of cardiac failure that would otherwise remain undiscovered in proteome wide studies. Label-free nanoscale LC-MS has been applied in this study to validate a Triton X-114-based phase enrichment method for cardiac membrane proteins. Annotation of the subcellular location combined with GRAVY score analysis indicates a clear separation between soluble and membrane-bound proteins with an enrichment of over 62% for this protein subset. LC-MS allowed confident identification and annotation of hydrophobic proteins in this control sample pilot study and demonstrates the power of the proposed technique to extract integral membrane-bound proteins. This approach should be applicable to a wider scale study of disease-associated changes in the cardiac membrane subproteome.

Proteomic approaches to the analysis of multiprotein signaling complexes

Signal transduction is one of the most active fields in modern biomedical research. Increasing evidence has shown that signaling proteins associate with each other in characteristic ways to form large signaling complexes. These diverse structures operate to boost signaling efficiency, ensure specificity and increase sensitivity of the biochemical circuitry. Traditional methods of protein analysis are inadequate to fully characterize and understand these structures, which are intricate, contain many components and are highly dynamic. Instead, proteomics technologies are currently being applied to investigate the nature and composition of multimeric signaling complexes. This review presents commonly used and potential proteomic methods of analyzing diverse protein complexes along with a discussion and a brief evaluation of alternative approaches. Challenges associated with proteomic analysis of signaling complexes are also discussed.

Prognostic markers of astrocytoma: how to predict the unpredictable?

Astrocytomas are the most frequent tumors originating in the human nervous system. They carry a dismal prognosis as high-grade astroctyoma patients (World Health Organization [WHO] grade III and IV) rarely live beyond 5 years. At present, these tumors are mainly diagnosed through the difficult task of histologic examination of tissue obtained through stereotactic biopsy or tumor resection. In addition to determining the malignancy grade through histologic studies, the only other prognostic factors used in clinical setting are patient age and performance status. To overcome current limitations, research is underway to develop molecular approaches for glioma classification. These include identification, characterization and expansion of clinical (patient characteristics and imaging variables), histologic (WHO classification criteria) and molecular (genetic and proteomic) factors with prognostic potential. In this review the established classification characteristics, along with recent advances that may lead to the addition of new parameters and thus improve patient management and survival, are discussed.

Protein profiling of sickle cell versus control RBC core membrane skeletons by ICAT technology and tandem mass spectrometry

A proteomic approach using a cleavable ICAT reagent and nano-LC ESI tandem mass spectrometry was used to perform protein profiling of core RBC membrane skeleton proteins between sickle cell patients (SS) and controls (AA), and determine the efficacy of this technology. The data was validated through Peptide/Protein Prophet and protein ratios were calculated through ASAPratio. Through an ANOVA test, it was determined that there is no significant difference in the mean ratios from control populations (AA1/AA2) and sickle cell versus control populations (AA/SS). The mean ratios were not significantly different from 1.0 in either comparison for the core skeleton proteins (alpha spectrin, beta spectrin, band 4.1 and actin). On the natural-log scale, the variation (standard deviation) of the method was determined to be 14.1% and the variation contributed by the samples was 13.8% which together give a total variation of 19.7% in the ratios.

The anatomy of microbial cell state transitions in response to oxygen

Adjustment of physiology in response to changes in oxygen availability is critical for the survival of all organisms. However, the chronology of events and the regulatory processes that determine how and when changes in environmental oxygen tension result in an appropriate cellular response is not well understood at a systems level. Therefore, transcriptome, proteome, ATP, and growth changes were analyzed in a halophilic archaeon to generate a temporal model that describes the cellular events that drive the transition between the organism's two opposing cell states of anoxic quiescence and aerobic growth. According to this model, upon oxygen influx, an initial burst of protein synthesis precedes ATP and transcription induction, rapidly driving the cell out of anoxic quiescence, culminating in the resumption of growth. This model also suggests that quiescent cells appear to remain actively poised for energy production from a variety of different sources. Dynamic temporal analysis of relationships between transcription and translation of key genes suggests several important mechanisms for cellular sustenance under anoxia as well as specific instances of post-transcriptional regulation.

Technology insight: the application of proteomics in gastrointestinal disease

Analysis of the human genome has increased our knowledge of the genes that are associated with disease. At the same time, however, it has become clear that having complete DNA sequences alone is not sufficient to elucidate the biological functions of the proteins that they encode. For this reason, proteomics-the analysis of proteins-has become increasingly attractive, because the proteome reflects both the intrinsic genetic programming of a cell and the impact of its immediate environment. The principal goals of clinical proteomics are to identify biomarkers for the early diagnosis of disease and potential targets for therapeutic intervention. Other goals include the identification of biomarkers for the early detection of disease recurrence (relapse) and how they might be combined with diagnostic imaging techniques to improve the sensitivity for detecting disease. This Review describes conventional proteomic technologies, their strengths and limitations, and demonstrates their application to clinical practice, with specific reference to their use in the gastroenterology field.

Assessing bias in experiment design for large scale mass spectrometry-based quantitative proteomics

Mass spectrometry-based proteomics holds great promise as a discovery tool for biomarker candidates in the early detection of diseases. Recently much emphasis has been placed upon producing highly reliable data for quantitative profiling for which highly reproducible methodologies are indispensable. The main problems that affect experimental reproducibility stem from variations introduced by sample collection, preparation, and storage protocols and LC-MS settings and conditions. On the basis of a formally precise and quantitative definition of similarity between LC-MS experiments, we have developed Chaorder, a fully automatic software tool that can assess experimental reproducibility of sets of large scale LC-MS experiments. By visualizing the similarity relationships within a set of experiments, this tool can form the basis of systematic quality control and thus help assess the comparability of mass spectrometry data over time, across different laboratories, and between instruments. Applying Chaorder to data from multiple laboratories and a range of instruments, experimental protocols, and sample complexities revealed biases introduced by the sample processing steps, experimental protocols, and instrument choices. Moreover we show that reducing bias by correcting for just a few steps, for example randomizing the run order, does not provide much gain in statistical power for biomarker discovery.

Reproducibility Assessment of Relative Quantitation Strategies for LC−MS Based Proteomics

The reproducibility of a given method for relative quantitation governs the reliability of liquid chromatography-mass spectrometry (LC-MS) based differential analysis in proteomic studies. Understanding the noise level introduced from biological, chemical, and instrumental sources not only helps to determine the experimental design but also aids in assessing the reliability of expression ratios used for quantitation. Here we present a reproducibility assessment method for relative quantitation based on the intensity ratio distribution of common features in LC-MS replicates. This method applies to both decoupled (label-free quantitation) and coupled (label-dependent quantitation) methods. Aligning the features of LC-MS maps directly for the decoupled method or by matching an LC-MS map and its virtual map for the coupled method results in a list of common features for replicate samples. We find that the ratio distribution of the common features successfully indicates the reproducibility of each experiment prior to MS/MS peptide sequencing in three different quantitation strategies: decoupled, coupled isotope-coded affinity tag, and coupled stable isotope labeling of amino acids in cell culture experiments.

Mascot file parsing and quantification (MFPaQ), a new software to parse, validate, and quantify proteomics data generated by ICAT and SILAC mass spectrometric analyses: application to the proteomics study of membrane proteins from primary human endothelial cells

Proteomics strategies based on nanoflow (nano-) LC-MS/MS allow the identification of hundreds to thousands of proteins in complex mixtures. When combined with protein isotopic labeling, quantitative comparison of the proteome from different samples can be achieved using these approaches. However, bioinformatics analysis of the data remains a bottleneck in large scale quantitative proteomics studies. Here we present a new software named Mascot File Parsing and Quantification (MFPaQ) that easily processes the results of the Mascot search engine and performs protein quantification in the case of isotopic labeling experiments using either the ICAT or SILAC (stable isotope labeling with amino acids in cell culture) method. This new tool provides a convenient interface to retrieve Mascot protein lists; sort them according to Mascot scoring or to user-defined criteria based on the number, the score, and the rank of identified peptides; and to validate the results. Moreover the software extracts quantitative data from raw files obtained by nano-LC-MS/MS, calculates peptide ratios, and generates a non-redundant list of proteins identified in a multisearch experiment with their calculated averaged and normalized ratio. Here we apply this software to the proteomics analysis of membrane proteins from primary human endothelial cells (ECs), a cell type involved in many physiological and pathological processes including chronic inflammatory diseases such as rheumatoid arthritis. We analyzed the EC membrane proteome and set up methods for quantitative analysis of this proteome by ICAT labeling. EC microsomal proteins were fractionated and analyzed by nano-LC-MS/MS, and database searches were performed with Mascot. Data validation and clustering of proteins were performed with MFPaQ, which allowed identification of more than 600 unique proteins. The software was also successfully used in a quantitative differential proteomics analysis of the EC membrane proteome after stimulation with a combination of proinflammatory mediators (tumor necrosis factor-alpha, interferon-gamma, and lymphotoxin alpha/beta) that resulted in the identification of a full spectrum of EC membrane proteins regulated by inflammation.

Quantification of cysteine oxidation in human estrogen receptor by mass spectrometry

Redox-dependent modifications of sulfhydryl groups within the two Cys4 zinc fingers of the estrogen receptor DNA-binding domain (ER-DBD) result in structural damage and loss of ER DNA-binding function, which parallels the situation observed in many ER-positive breast cancers. Quantitation of the redox status of cysteinyl thiols within ER-DBD employed cysteine-specific oxidants to induce varying degrees of oxidation in recombinant ER, followed by differential alkylation with the stable isotopic labeling reagents [12C2]-iodoacetic acid and [13C2]-bromoacetic acid. Subsequent proteolysis with LysC/Asp-N generated diagnostic peptides of which the C-terminal peptide of the second zinc finger is most strongly detected by mass spectrometry (MS) and serves as a suitable marker of ER-DBD redox status. Data were collected from two different MALDI-MS instruments: a time-of-flight and a linear ion trap (vMALDI-LIT). An analogous but larger synthetic peptide treated with three isotopic variants of the alkylating reagent modeled isotopic overlaps that might complicate the relative quantitation of cysteine oxidation. Despite the isotopic overlaps, excellent relative quantitation was achieved from MS data obtained from both instruments. This was also true of tandem MS/MS data from the vMALDI-LIT, which should facilitate selected reaction monitoring. Relative quantitation by MS also closely matched data from immunochemical methods.

Quantitative analysis of acrylamide labeled serum proteins by LC-MS/MS

Isotopic labeling of cysteine residues with acrylamide was previously utilized for relative quantitation of proteins by MALDI-TOF. Here, we explored and compared the application of deuterated and (13)C isotopes of acrylamide for quantitative proteomic analysis using LC-MS/MS and high-resolution FTICR mass spectrometry. The method was applied to human serum samples that were immunodepleted of abundant proteins. Our results show reliable quantitation of proteins across an abundance range that spans 5 orders of magnitude based on ion intensities and known protein concentration in plasma. The use of (13)C isotope of acrylamide had a slightly greater advantage relative to deuterated acrylamide, because of shifts in elution of deuterated acrylamide relative to its corresponding nondeuterated compound by reversed-phase chromatography. Overall, the use of acrylamide for differentially labeling intact proteins in complex mixtures, in combination with LC-MS/MS provides a robust method for quantitative analysis of complex proteomes.

Systematic uncovering of multiple pathways underlying the pathology of Huntington disease by an acid-cleavable isotope-coded affinity tag approach

Huntington disease (HD) is an autosomal dominant neurodegenerative disease that results from a CAG (glutamine) trinucleotide expansion in exon 1 of huntingtin (Htt). The aggregation of mutant Htt has been implicated in the progression of HD. The earliest degeneration occurs in the striatum. To identify proteins critical for the progression of HD, we applied acid-cleavable ICAT technology to quantitatively determine changes in protein expressions in the striatum of a transgenic HD mouse model (R6/2). The cysteine residues of striatal proteins from HD and wild-type mice were labeled, respectively, with the heavy and light forms of the ICAT reagents. Samples were trypsinized, uncovered by avidin affinity chromatography, and analyzed by nano-LC-MS/MS. Western blot analyses were used to confirm and to calibrate the ICAT ratios. Linear regression was used to uncover a group of proteins that exhibited consistent changes. In two independent ICAT experiments, we identified 427 cysteine-containing striatal proteins among which approximately 66% (203 proteins) were detected in both ICAT experiments. Approximately two-thirds of proteins identified in each ICAT experiment were detected in both ICAT experiments. In total, 68 proteins with altered expressions in HD mice were identified. Elevated expressions of two down-regulated proteins (14-3-3sigma and FKBP12) effectively reduced Htt aggregates in a striatal cell line, supporting the functional relevance of the above findings. Collectively by using a well defined protocol for data analysis, large scale comparisons of protein expressions by ICAT can be reliable and can provide valuable clues for identifying proteins critical for pathophysiological functions.

Chemistry meets proteomics: the use of chemical tagging reactions for MS-based proteomics

As proteomics matures from a purely descriptive to a function-oriented discipline of the life sciences, there is strong demand for novel methodologies that increase the depth of information that can be obtained from proteomic studies. MS has long played a central role for protein identification and characterization, often in combination with dedicated chemical modification reactions. Today, chemistry is helping to advance the field of proteomics in numerous ways. In this review, we focus on those methodologies that have a significant impact for the large-scale study of proteins and peptides. This includes approaches that allow the introduction of affinity tags for the enrichment of subclasses of peptides or proteins and strategies for in vitro stable isotope labeling for quantification purposes, among others. Particular attention is given to the study of PTMs where recent advancements have been promising, but many interesting targets are not yet being addressed.

A study of reproducibility of guanidination-dimethylation labeling and liquid chromatography matrix-assisted laser desorption ionization mass spectrometry for relative proteome quantification

The combination of dimethylation after guanidination (2MEGA) isotope labeling with microbore liquid chromatography (LC)-matrix-assisted laser desorption ionization (MALDI) MS and MS/MS [C. Ji, N. Guo, L. Li, J. Proteome Res. 4 (2005) 2099] has been reported as a promising strategy for abundance ratio-dependent quantitative proteome analysis. A critical step in using this integrated strategy is to set up the abundance ratio threshold of peptide pairs, above which the peptide pairs are used for quantifying and identifying the protein that is considered to be differentially expressed between two different samples. The threshold is determined by technical variation (i.e., the overall abundance ratio variation caused by the experimental process including sample workup, MS analysis and data processing) as well as biological variation (i.e., the abundance ratio variation caused by the biological process including cell growth), which can be defined and assessed by a coefficient of variation (CV). We have designed experiments and measured three different levels of variations, starting with the same membrane protein preparation, the same batch of cells and three batches of cells from the same cell line grown under the same conditions, respectively. It is shown that technical variation from the experimental processes involved in 2MEGA labeling LC-MALDI MS has a CV of <15%. In addition, the measured biological variation from cell growth was much smaller than the measured technical variation. From the studies of the occurrence rate of outliers in the distribution of the abundance ratio data within a comparative dataset of peptide pairs, it is concluded that, to compare the proteome changes between two sets of cultured cells without the use of replicate experiments, a relative abundance ratio of greater than 2X or less than 0.5X (X is the average abundance ratio of the dataset) on peptide pairs can be used as a stringent threshold to quantify and identify differentially expressed proteins with high confidence.

Proteolytic 18O-labeling strategies for quantitative proteomics

A number of proteomic techniques have been developed to quantify proteins in biological systems. This review focuses on the quantitative proteomic technique known as "proteolytic 18O-labeling." This technique utilizes a protease and H(2)18O to produce labeled peptides, with subsequent chromatographic and mass spectrometric analysis to identify and quantify (relative) the proteins from which the peptides originated. The technique determines the ratio of individual protein's expression level between two samples relative to each other, and can be used to quantitatively examine protein expression (comparative proteomics) and post-translational modifications, and to study protein-protein interactions. The present review discusses various aspects of the 18O-labeling technique, including: its history, the advantages and disadvantages of the proteolytic 18O-labeling technique compared to other techniques, enzymatic considerations, the problem of variable incorporation of 18O atoms into peptides with a discussion on recent advancements of the technique to overcome it, computational tools to interpret the data, and a review of the biological applications.

Antibody-based enrichment of peptides on magnetic beads for mass-spectrometry-based quantification of serum biomarkers

A major bottleneck for validation of new clinical diagnostics is the development of highly sensitive and specific assays for quantifying proteins. We previously described a method, stable isotope standards with capture by antipeptide antibodies, wherein a specific tryptic peptide is selected as a stoichiometric representative of the protein from which it is cleaved, is enriched from biological samples using immobilized antibodies, and is quantitated using mass spectrometry against a spiked internal standard to yield a measure of protein concentration. In this study, we optimized a magnetic-bead-based platform amenable to high-throughput peptide capture and demonstrated that antibody capture followed by mass spectrometry can achieve ion signal enhancements on the order of 10(3), with precision (CVs <10%) and accuracy (relative error approximately 20%) sufficient for quantifying biomarkers in the physiologically relevant ng/mL range. These methods are generally applicable to any protein or biological fluid of interest and hold great potential for providing a desperately needed bridging technology between biomarker discovery and clinical application.

Protein Markers of Ischemic Insult in Brain Endothelial Cells Identified Using 2D Gel Electrophoresis and ICAT-Based Quantitative Proteomics

The blood-brain barrier (BBB) is formed by endothelial cells of cerebral microvessels sealed by tight junctions. Ischemic brain injury is known to initiate a series of biochemical and molecular processes that lead to the disruption of the BBB, development of vascular inflammation, and subsequent neurovascular remodeling including angiogenesis. Molecular effectors of these changes are multiple and are regulated in a dynamic fashion. The current study was designed to analyze changes in cellular and secreted proteins in rat brain endothelial cells (BEC) exposed to ischemic insult in vitro using two complementary quantitative proteomic approaches: two-dimensional gel electrophoresis (2DE) and isotope-coded affinity tag (ICAT)-based proteomics. We show a comprehensive qualitative and quantitative comparison between the two proteomic methods applied to the same experimental system with respect to their reproducibility, specificity, and the type of proteins identified. In total, >160 proteins showed differential expression in response to the ischemic insult, with 38 identified by 2DE and 138 by ICAT. Only 15 proteins were commonly identified. ICAT showed superior reproducibility over 2DE and was more suitable for detecting small, large, basic, hydrophobic, and secreted proteins than 2DE. However, positive identification of proteins by MS/MS was more reliably done using a 2DE-based method compared to ICAT. Changes in proteins involved in nucleic acid, protein, and carbohydrate metabolism, signal transduction, cell structure, adhesion and motility, immunity and defense, cell cycle, and apoptosis were observed. The functional significance of observed protein changes was evaluated through a multifaceted protein classification and validation process, which included literature mining and comparative evaluation of protein changes in analogous in vitro and in vivo ischemia models. The comparative analyses of protein changes between the in vitro and in vivo models demonstrated a significant correlative relationship, emphasizing the 'translational' value of in vitro endothelial models in neurovascular research.

Quantitative profiling of drug-associated proteomic alterations by combined 2-nitrobenzenesulfenyl chloride (NBS) isotope labeling and 2DE/MS identification

The identification of drug-responsive biomarkers in complex protein mixtures is an important goal of quantitative proteomics. Here, we describe a novel approach for identifying such drug-induced protein alterations, which combines 2-nitrobenzenesulfenyl chloride (NBS) tryptophan labeling with two-dimensional gel electrophoresis (2DE)/mass spectrometry (MS). Lysates from drug-treated and control samples are labeled with light or heavy NBS moiety and separated on a common 2DE gel, and protein alterations are identified by MS through the differential intensity of paired NBS peptide peaks. Using NBS/2DE/MS, we profiled the proteomic alterations induced by tamoxifen (TAM) in the estrogen receptor (ER) positive MCF-7 breast cancer cell line. Of 88 protein spots that significantly changed upon TAM treatment, 44 spots representing 23 distinct protein species were successfully identified with NBS-paired peptides. Of these 23 TAM-altered proteins, 16 (70%) have not been previously associated with TAM or ER activity. We found the NBS labeling procedure to be both technically and biologically reproducible, and the NBS/2DE/MS alterations exhibited good concordance with conventional 2DE differential protein quantitation, with discrepancies largely due to the comigration of distinct proteins in the regular 2DE gels. To validate the NBS/2DE/MS results, we used immunoblotting to confirm GRP78, CK19, and PA2G4 as bona fide TAM-regulated proteins. Furthermore, we demonstrate that PA2G4 expression can serve as a novel prognostic factor for disease-free survival in two independent breast cancer patient cohorts. To our knowledge, this is the first report describing the proteomic changes in breast cancer cells induced by TAM, the most commonly used selective estrogen receptor modulator (SERM). Our results indicate that NBS/2DE/MS may represent a more reliable approach for cellular protein quantitation than conventional 2DE approaches.

A Standard Operating Procedure (SOP) for the preparation of intra- and extracellular proteins of Clostridium acetobutylicum for proteome analysis

We report on the development of a Standard Operating Procedure (SOP) for extraction and handling of intra- and extracellular protein fractions of Clostridium acetobutylicum ATCC 824 for reproducible high quality two-dimensional gel electrophoresis (2-DE) analyses. Standardized cells from a phosphate-limited chemostat were used to evaluate different protein preparation methods. For the preparation of the secretome, a dialysis/ultrafiltration procedure resulted in higher protein yields and proved to be more reliable compared to different precipitation methods using TCA, DOC-TCA, acetone, and PEG 6000. Sonication was found to be the most efficient method among different tested techniques of cell disruption for the analysis of the intracellular proteome. Furthermore, the effect of protease inhibitors and sample storage conditions were tested for both intra- and extracellular protein samples. Significant changes in the protein pattern were observed depending on the addition of protease inhibitors. 2-DE gels with a pH gradient from 4 to 7 prepared according to the developed SOP contained at least 736 intracellular and 324 extracellular protein spots.

Analytical characteristics of cleavable isotope-coded affinity tag-LC-tandem mass spectrometry for quantitative proteomic studies

Quantitative proteomic studies using cleavable isotope-coded affinity tags (cICAT) in concert with tandem mass spectrometry (MS/MS) permit unbiased comparisons between biologically distinct samples. We sought to determine the analytical characteristics of cICAT-based studies by examining the cumulative results of multiple, separate cICAT-based experiments involving human lymphoma-derived cells. We found that the number of identified proteins increased with larger numbers of fractions analyzed. The majority of proteins were identified by single peptides. Only 24 to 41% of the peptides contained cysteine residues, but 85% of the cysteine-containing peptides yielded quantification data. Approximately 28% of all identified proteins yielded quantification data, with 57% of these being differentially expressed by at least 1.5-fold. The quantification ratios of peptides for proteins with multiple quantified peptides were concordant in trend in 87% of instances. cICAT-labeled peptides identified proteins in all subcellular compartments without significant bias. Analysis of the flow-through fraction did not increase the number of peptides identified per protein. Our studies indicate that cICAT-LC-MS/MS yields quantifications primarily based on single peptides, and analysis of flow-through peptides does not contribute signifi-cantly to the results. Nevertheless, identifications based on single cICAT-labeled peptides with tryptic ends provide sufficiently reliable protein identifications and quantification information in cICAT-LC-MS/MS-based proteomic studies.

Optimized proteomic analysis of a mouse model of cerebellar dysfunction using amine-specific isobaric tags

Recent proteomic applications have demonstrated their potential for revealing the molecular mechanisms underlying neurodegeneration. The present study quantifies cerebellar protein changes in mice that are deficient in plasma membrane calcium ATPase 2 (PMCA2), an essential neuronal pump that extrudes calcium from cells and is abundantly expressed in Purkinje neurons. PMCA2-null mice display motor dyscoordination and unsteady gait deficits observed in neurological diseases such as multiple sclerosis and ataxia. We optimized an amine-specific isobaric tags (iTRAQ)-based shotgun proteomics workflow for this study. This workflow took consideration of analytical variance as a function of ion signal intensity and employed biological repeats to aid noise reduction. Even with stringent protein identification criteria, we could reliably quantify nearly 1000 proteins, including many neuronal proteins that are important for synaptic function. We identified 21 proteins that were differentially expressed in PMCA2-null mice. These proteins are involved in calcium homeostasis, cell structure and chromosome organization. Our findings shed light on the molecular changes that underlie the neurological deficits observed in PMCA2-null mice. The optimized workflow presented here will be valuable for others who plan to implement the iTRAQ method.

The Escherichia coli proteome: past, present, and future prospects

Proteomics has emerged as an indispensable methodology for large-scale protein analysis in functional genomics. The Escherichia coli proteome has been extensively studied and is well defined in terms of biochemical, biological, and biotechnological data. Even before the entire E. coli proteome was fully elucidated, the largest available data set had been integrated to decipher regulatory circuits and metabolic pathways, providing valuable insights into global cellular physiology and the development of metabolic and cellular engineering strategies. With the recent advent of advanced proteomic technologies, the E. coli proteome has been used for the validation of new technologies and methodologies such as sample prefractionation, protein enrichment, two-dimensional gel electrophoresis, protein detection, mass spectrometry (MS), combinatorial assays with n-dimensional chromatographies and MS, and image analysis software. These important technologies will not only provide a great amount of additional information on the E. coli proteome but also synergistically contribute to other proteomic studies. Here, we review the past development and current status of E. coli proteome research in terms of its biological, biotechnological, and methodological significance and suggest future prospects.

Isobaric Tags for Relative and Absolute Quantitation (iTRAQ) Reproducibility: Implication of Multiple Injections

We analyzed 10 isobaric tags for relative and absolute quantitation (iTRAQ) experiments using three different model organisms across the domains of life: Saccharomyces cerevisiae KAY446, Sulfolobussolfataricus P2, and Synechocystis sp. PCC6803. A double database search strategy was employed to minimize the rate of false positives to less than 3% for all organisms. The reliability of proteins with single-peptide identification was also assessed using the search strategy, coupled with multiple analyses of samples into LC-MS/MS. The outcomes of the three LC-MS/MS analyses provided higher proteome coverage with an average increment in total proteins identified of 6%, 33%, and 50% found in S. cerevisiae, S. solfataricus, and Synechocystis sp., respectively. The iTRAQ quantification values were found to be highly reproducible across the injections, with an average coefficient of variation (CV) of 0.09 (scattering from 0.14 to 0.04) calculated based on log mean average ratio for all three organisms. Hence, we recommend multiple analyses of iTRAQ samples for greater proteome coverage and precise quantification.

Comparison of label-free methods for quantifying human proteins by shotgun proteomics

Measurements of mass spectral peak intensities and spectral counts are promising methods for quantifying protein abundance changes in shotgun proteomic analyses. We describe Serac, software developed to evaluate the ability of each method to quantify relative changes in protein abundance. Dynamic range and linearity using a three-dimensional ion trap were tested using standard proteins spiked into a complex sample. Linearity and good agreement between observed versus expected protein ratios were obtained after normalization and background subtraction of peak area intensity measurements and correction of spectral counts to eliminate discontinuity in ratio estimates. Peak intensity values useful for protein quantitation ranged from 10(7) to 10(11) counts with no obvious saturation effect, and proteins in replicate samples showed variations of less than 2-fold within the 95% range (+/-2sigma) when >or=3 peptides/protein were shared between samples. Protein ratios were determined with high confidence from spectral counts when maximum spectral counts were >or=4 spectra/protein, and replicates showed equivalent measurements well within 95% confidence limits. In further tests, complex samples were separated by gel exclusion chromatography, quantifying changes in protein abundance between different fractions. Linear behavior of peak area intensity measurements was obtained for peptides from proteins in different fractions. Protein ratios determined by spectral counting agreed well with those determined from peak area intensity measurements, and both agreed with independent measurements based on gel staining intensities. Overall spectral counting proved to be a more sensitive method for detecting proteins that undergo changes in abundance, whereas peak area intensity measurements yielded more accurate estimates of protein ratios. Finally these methods were used to analyze differential changes in protein expression in human erythroleukemia K562 cells stimulated under conditions that promote cell differentiation by mitogen-activated protein kinase pathway activation. Protein changes identified with p<0.1 showed good correlations with parallel measurements of changes in mRNA expression.