Evaluation of shotgun sequencing for proteomic analysis of human plasma using HPLC coupled with either ion trap or Fourier transform mass spectrometry

Abundant plasma protein depletion using ammonium sulfate precipitation and Protein A affinity chromatography

Plasma is a highly valuable resource for biomarker research since it is easy obtainable and contains a high amount of information on patient health status. Although advancements in the field of proteomics enabled analysis of the plasma proteome, identification of low abundant proteins remains challenging due to high complexity and large dynamic range. In order to reduce the dynamic range of protein concentrations, a tandem depletion technique consisting of ammonium sulfate precipitation and Protein A affinity chromatography was developed. Using this method, 50% of albumin, together with other high abundant proteins such as alpha-1-antitrypsin, was depleted from the plasma sample at 20% to 40% ammonium sulfate saturation levels. In combination with immunoglobulin removal using a Protein A column, this technique delivered up to 40 new low- to medium abundance protein identifications when performing a shotgun mass spectrometry analysis. Compared to non-depleted plasma, 270 additional protein spots were observed during 2D-PAGE analysis. These results illustrate that this tandem depletion method is equivalent to commercial kits which are based on immune-affinity chromatography. Moreover, this method using Protein A immunoglobulin depletion was shown to be highly reproducible and a minimal amount of non-target proteins was depleted. The combination of ammonium sulfate precipitation and Protein A affinity chromatography offers a low cost, efficient, straightforward and reproducible alternative to commercial kits, with proteins remaining in native conformation, allowing protein activity and protein interaction studies.

A standardized kit for automated quantitative assessment of candidate protein biomarkers in human plasma

Background: An increasingly popular mass spectrometry-based quantitative approach for health-related research in the biomedical field involves the use of stable isotope-labeled standards (SIS) and multiple/selected reaction monitoring (MRM/SRM). To improve inter-laboratory precision and enable more widespread use of this ‘absolute’ quantitative technique in disease-biomarker assessment studies, methods must be standardized. Results/methodology: Using this MRM-with-SIS-peptide approach, we developed an automated method (encompassing sample preparation, processing and analysis) for quantifying 76 candidate protein markers (spanning >4 orders of magnitude in concentration) in neat human plasma. Discussion/conclusion: The assembled biomarker assessment kit – the ‘BAK-76’ – contains the essential materials (SIS mixes), methods (for acquisition and analysis), and tools (Qualis-SIS software) for performing biomarker discovery or verification studies in a rapid and standardized manner.

Depletion and fractionation technologies in plasma proteomic analysis

This review intends to survey the traditional and current technologies in the depletion and subfractionation of plasma proteins for further analyses. The value of depletion aims to enrich low-abundant proteins by removing highly abundant proteins, such as albumin or immunoglobulin G, from plasma. With this approach, one can examine both the resulting high- and low-abundant protein fractions. The depleted protein population can be further subfractionated based on their isoelectric point ranges, creating a more discrete pool of proteins for detailed post-translational modification studies by methods such as 2D gel electrophoresis and mass spectrometry. The concept of divide to conquer will greatly enhance our ability to identify and characterize low-abundant proteins and cleaved peptides from plasma as important diagnostic markers or potential drug targets. This can potentially reverse the decline in the development of new plasma diagnostic tests.

High-throughput proteomics using antibody microarrays

Antibody-based microarrays are a novel technology that hold great promise in proteomics. Microarrays can be printed with thousands of recombinant antibodies carrying the desired specificities, the biologic sample (e.g., an entire proteome) and any specifically bound analytes detected. The microarray patterns that are generated can then be converted into proteomic maps, or molecular fingerprints, revealing the composition of the proteome. Using this tool, global proteome analysis and protein expression profiling will thus provide new opportunities for biomarker discovery, drug target identification and disease diagnostics, as well as providing insights into disease biology. Intense work is currently underway to develop this novel technology platform into the high-throughput proteomic tool required by the research community.

Developing liquid chromatography ion mobility mass spectometry techniques

When a packet of ions in a buffer gas is exposed to a weak electric field, the ions will separate according to differences in their mobilities through the gas. This separation forms the basis of the analytical method known as ion mobility spectroscopy and is highly efficient, in that it can be carried out in a very short time frame (micro- to milliseconds). Recently, efforts have been made to couple the approach with liquid-phase separations and mass spectrometry in order to create a high-throughput and high-coverage approach for analyzing complex mixtures. This article reviews recent work to develop this approach for proteomics analyses. The instrumentation is described briefly. Several multidimensional data sets obtained upon analyzing complex mixtures are shown in order to illustrate the approach as well as provide a view of the limitations and required future work.

Phytoplasma proteomic analysis

Proteome analysis is becoming a powerful tool in the functional characterization of organisms, and takes a broad, comprehensive, systematic approach to understanding biology. Following the sequencing of the phytoplasma genomes, the next step is to characterize the expressed proteome of phytoplasmas to acquire the verification and functional annotation of all predicted genes and their protein products. Here, we describe the protocol of mulberry dwarf phytoplasma purification, phytoplasma protein extraction and separation by SDS-PAGE, in-gel tryptic digestion of the proteins, separation of the digested peptides by liquid chromatography, and identification of the peptides by mass spectrometry. The protocol described here is also applicable to the analysis of other phytoplasma proteomes.

Quantitative proteomic analysis reveals that lipopolysaccharide induces mitogen-activated protein kinase-dependent activation in human microglial cells

Microglial cells act as the first and main form of active immune defense in the central nervous system related to inflammation and neurodegenerative disease. Lipopolysaccharide (LPS) induces many genes encoding inflammatory mediators, including cytokines such as tumor necrosis factor-α, interleukin-1β, (IL-1β), and IL-6, chemokines, and prostaglandins in microglial cells. Quantitative proteomics methods with isobaric chemical labeling using tandem mass tags and 2D-nano LC-ESI-MS/MS were used to systematically analyze proteomic changes in microglia responding to LPS stimulation. As a result, we found that the expression level of 21 proteins in human microglial cells changed after activation. Among those, one of the strong mitogen-activated protein kinase (MAPK) regulator proteins, CMPK1 was highly upregulated after LPS stimulation in human microglial cells. We detected and validated upregulation of MAPK including ERK1/2, p38, and SAPK/JNK by immunohistochemistry and Western blotting. NFκB, strong transcription factor of CMPK1, was translocated to the nucleus from the cytosol by high contents screening after LPS stimulation. Taken together, we conclude that MAPK signaling plays an important role in LPS-induced human microglial activation related to inflammatory response.

Proteomics-based investigations of animal models of disease

Cells contain a large yet, constant genome, which contains all the coding information necessary to sustain cellular physiology. However, proteins are the end products of genes, and hence dictate the phenotype of cells and tissues. Therefore, proteomics can provide key information for the elucidation of physiological and pathophysiological mechanisms by identifying the protein profile from cells and tissues. The relatively novel techniques used for the study of proteomics thus have the potential to improve diagnostic, prognostic, as well as therapeutic avenues. In this review, we first discuss the benefits of animal models over the use of human samples for the proteomic analysis of human disease. Next, we aim to demonstrate the potential of proteomics in the elucidation of disease mechanisms that may not be possible by other conventional technologies. Following this, we describe the use of proteomics for the analysis of PTM and protein interactions in animal models and their relevance to the study of human disease. Finally, we discuss the development of clinical biomarkers for the early diagnosis of disease via proteomic analysis of animal models. We also discuss the development of standard proteomes and relate how this data will benefit future proteomic research. A comprehensive review of all animal models used in conjunction with proteomics is beyond the scope of this manuscript. Therefore, we aimed to cover a large breadth of topics, which together, demonstrate the potential of proteomics as a powerful tool in biomedical research.

Human myocardial protein pattern reveals cardiac diseases

Proteomic profiles of myocardial tissue in two different etiologies of heart failure were investigated using high performance liquid chromatography (HPLC)/Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Right atrial appendages from 10 patients with hemodynamically significant isolated aortic valve disease and from 10 patients with isolated symptomatic coronary heart disease were collected during elective cardiac surgery. As presented in an earlier study by our group (Baykut et al., 2006), both disease forms showed clearly different pattern distribution characteristics. Interesting enough, the classification patterns could be used for correctly sorting unknown test samples in their correct categories. However, in order to fully exploit and also validate these findings there is a definite need for unambiguous identification of the differences between different etiologies at molecular level. In this study, samples representative for the aortic valve disease and coronary heart disease were prepared, tryptically digested, and analyzed using an FT-ICR MS that allowed collision-induced dissociation (CID) of selected classifier masses. By using the fragment spectra, proteins were identified by database searches. For comparison and further validation, classifier masses were also fragmented and analyzed using HPLC-/Matrix-assisted laser desorption ionization (MALDI) time-of-flight/time-of-flight (TOF/TOF) mass spectrometry. Desmin and lumican precursor were examples of proteins found in aortic samples at higher abundances than in coronary samples. Similarly, adenylate kinase isoenzyme was found in coronary samples at a higher abundance. The described methodology could also be feasible in search for specific biomarkers in plasma or serum for diagnostic purposes.

Using ion mobility data to improve peptide identification: intrinsic amino acid size parameters

A new method for enhancing peptide ion identification in proteomics analyses using ion mobility data is presented. Ideally, direct comparisons of experimental drift times (t(D)) with a standard mobility database could be used to rank candidate peptide sequence assignments. Such a database would represent only a fraction of sequences in protein databases and significant difficulties associated with the verification of data for constituent peptide ions would exist. A method that employs intrinsic amino acid size parameters to obtain ion mobility predictions that can be used to rank candidate peptide ion assignments is proposed. Intrinsic amino acid size parameters have been determined for doubly charged peptide ions from an annotated yeast proteome. Predictions of ion mobilities using the intrinsic size parameters are more accurate than those obtained from a polynomial fit to t(D) versus molecular weight data. More than a 2-fold improvement in prediction accuracy has been observed for a group of arginine-terminated peptide ions 12 residues in length. The use of this predictive enhancement as a means to aid peptide ion identification is discussed, and a simple peptide ion scoring scheme is presented.

Shotgun proteomic analysis of mulberry dwarf phytoplasma

BACKGROUND

Mulberry dwarf (MD), which is caused by phytoplasma, is one of the most serious infectious diseases of mulberry. Phytoplasmas have been associated with diseases in several hundred plant species. The inability to culture phytoplasmas in vitro has hindered their characterization at the molecular level. Though the complete genomes of two phytoplasmas have been published, little information has been obtained about the proteome of phytoplasma. Therefore, the proteomic information of phytoplasmas would be useful to elucidate the functional mechanisms of phytoplasma in many biological processes.

RESULTS

MD phytoplasmas, which belong to the 16SrI-B subgroup based on the 16S DNA analysis, were purified from infected tissues using a combination of differential centrifugation and density gradient centrifugation. The expressed proteome of phytoplasma was surveyed by one-dimensional SDS-PAGE and nanocapillary liquid chromatography-tandem mass spectrometry. A total of 209 phytoplasma proteins were unambiguously assigned, including the proteins with the functions of amino acid biosynthesis, cell envelope, cellular processes, energy metabolism, nucleosides and nucleotide metabolism, replication, transcription, translation, transport and binding as well as the proteins with other functions. In addition to these known function proteins, 63 proteins were annotated as hypothetical or conserved hypothetical proteins.

CONCLUSIONS

Taken together, a total of 209 phytoplasma proteins have been experimentally verified, representing the most extensive survey of any phytoplasma proteome to date. This study provided a valuable dataset of phytoplasma proteins, and a better understanding of the energy metabolism and virulence mechanisms of MD phytoplasma.

Separation with zwitterionic hydrophilic interaction liquid chromatography improves protein identification by matrix-assisted laser desorption/ionization-based proteomic analysis

Comprehensive proteomic analyses necessitate efficient separation of peptide mixtures for the subsequent identification of proteins by mass spectrometry (MS). However, digestion of proteins extracted from cells and tissues often yields complex peptide mixtures that confound direct comprehensive MS analysis. This study investigated a zwitterionic hydrophilic interaction liquid chromatography (ZIC-HILIC) technique for the peptide separation step, which was verified by subsequent MS analysis. Human serum albumin (HSA) was the model protein used for this analysis. HSA was digested with trypsin and resolved by ZIC-HILIC or conventional strong cation exchange (SCX) prior to MS analysis for peptide identification. Separation with ZIC-HILIC significantly improved the identification of HSA peptides over SCX chromatography. Detailed analyses of the identified peptides revealed that the ZIC-HILIC has better peptide fractionation ability. We further demonstrated that ZIC-HILIC is useful for quantitatively surveying cell surface markers specifically expressed in undifferentiated embryonic stem cells. These results suggested the value of ZIC-HILIC as a novel and efficient separation method for comprehensive and quantitative proteomic analyses.

Proteomic contributions to personalized cancer care

Cancer impacts each patient and family differently. Our current understanding of the disease is primarily limited to clinical hallmarks of cancer, but many specific molecular mechanisms remain elusive. Genetic markers can be used to determine predisposition to tumor development, but molecularly targeted treatment strategies that improve patient prognosis are not widely available for most cancers. Individualized care plans, also described as personalized medicine, still must be developed by understanding and implementing basic science research into clinical treatment. Proteomics holds great promise in contributing to the prevention and cure of cancer because it provides unique tools for discovery of biomarkers and therapeutic targets. As such, proteomics can help translate basic science discoveries into the clinical practice of personalized medicine. Here we describe how biological mass spectrometry and proteome analysis interact with other major patient care and research initiatives and present vignettes illustrating efforts in discovery of diagnostic biomarkers for ovarian cancer, development of treatment strategies in lung cancer, and monitoring prognosis and relapse in multiple myeloma patients.

A novel pyrimidine-based stable-isotope labeling reagent and its application to quantitative analysis using matrix-assisted laser desorption/ionization mass spectrometry

As an extension of our previous work, a novel pyrimidine-based stable-isotope labeling reagent, [d(0)]-/[d(6)]-4,6-dimethoxy-2-(methylsulfonyl)pyrimidine (DMMSP), was developed for comparative quantification of proteins by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS). Our one-step labeling strategy combines several desirable properties such as cysteine-specific labeling, signal amplification and direct analysis with minimum sample handling. All these features not only allow easy interpretation for protein identification and quantification but also ensure rapid and sensitive progression to MS analysis. Using cysteine, Cys-containing peptide, and lysozyme digest as model samples, the labeling methodology was established and the following pilot application for quantitative analysis was accomplished with high confidence, accuracy, efficiency, and reproducibility. The application of DMMSP-labeling strategy is expected to provide a powerful new tool for comparative proteome research, especially for the analysis of low-abundance proteins.

Label-free LC-MS/MS quantitative proteomics for large-scale biomarker discovery in complex samples

Proteomic platforms that enable researchers to profile a high number of proteins across large sets of complex samples hold a great potential for biomarker discovery. LC-MS/MS-based methods can be used to analyse many samples without the need for protein labelling. As the analysis is a sequential process, the performance of the system has to be consistent throughout the entire experiment. In this study we used a set of spiked serum samples as well as a set of 55 clinical serum samples from schizophrenia patients and healthy volunteers to show that the label-free proteomic approach yields reproducible results across a large number of samples and can be used to accurately measure the relative protein abundance. Using this approach, we identified 1709 serum proteins covering a dynamic range of over three orders of magnitude. We believe that label-free quantitative proteomics is especially suited for biomarker discovery in large sample sets.

Mapping the human plasma proteome by SCX-LC-IMS-MS

The advent of on-line multidimensional liquid chromatography-mass spectrometry has significantly impacted proteomic analyses of complex biological fluids such as plasma. However, there is general agreement that additional advances to enhance the peak capacity of such platforms are required to enhance the accuracy and coverage of proteome maps of such fluids. Here, we describe the combination of strong-cation-exchange and reversed-phase liquid chromatographies with ion mobility and mass spectrometry as a means of characterizing the complex mixture of proteins associated with the human plasma proteome. The increase in separation capacity associated with inclusion of the ion mobility separation leads to generation of one of the most extensive proteome maps to date. The map is generated by analyzing plasma samples of five healthy humans; we report a preliminary identification of 9087 proteins from 37,842 unique peptide assignments. An analysis of expected false-positive rates leads to a high-confidence identification of 2928 proteins. The results are catalogued in a fashion that includes positions and intensities of assigned features observed in the datasets as well as pertinent identification information such as protein accession number, mass, and homology score/confidence indicators. Comparisons of the assigned features reported here with other datasets shows substantial agreement with respect to the first several hundred entries; there is far less agreement associated with detection of lower abundance components.

Toward plasma proteome profiling with ion mobility-mass spectrometry

Differential, functional, and mapping proteomic analyses of complex biological mixtures suffer from a lack of component resolution. Here we describe the application of ion mobility-mass spectrometry (IMS-MS) to this problem. With this approach, components that are separated by liquid chromatography are dispersed based on differences in their mobilities through a buffer gas prior to being analyzed by MS. The inclusion of the gas-phase dispersion provides more than an order of magnitude enhancement in component resolution at no cost to data acquisition time. Additionally, the mobility separation often removes high-abundance species from spectral regions containing low-abundance species, effectively increasing measurement sensitivity and dynamic range. Finally, collision-induced dissociation of all ions can be recorded in a single experimental sequence while conventional MS methods sequentially select precursors. The approach is demonstrated in a single, rapid (3.3 h) analysis of a plasma digest sample where abundant proteins have not been removed. Protein database searches have yielded 731 high confidence peptide assignments corresponding to 438 unique proteins. Results have been compiled into an initial analytical map to be used -after further augmentation and refinement- for comparative plasma profiling studies.

Proteomics and transfusion medicine: Future perspectives

Limited number of important discoveries have greatly contributed to the progresses achieved in the blood transfusion; ABO histo-blood groups, citrate as anticoagulant, fractionation of plasma proteins, plastic bags and apheresis machines. Three major types of blood products are transfused to patients: red cell concentrates, platelet concentrates and fresh frozen plasma. Several parameters of these products change during storage process and they have been well studied over the years. However, several aspects have completely been ignored; in particular those related to peptide and protein changes. This review presents what has been done using proteomic tools and the potentials of proteomics for transfusion medicine.

Profiling human brain proteome by multi-dimensional separations coupled with MS

In our initial attempt to analyze the human brain proteome, we applied multi-dimensional protein separation and identification techniques using a combination of sample fractionation, 1-D SDS-PAGE, and MS analysis. The complexity of human brain proteome requires multiple fractionation strategies to extend the range and total number of proteins identified. According to the method of Klose (Methods Mol. Biol. 1999, 112, 67), proteins of the temporal lobe of human brain were fractionated into (i) cytoplasmic and nucleoplasmic, (ii) membrane and other structural, and (iii) DNA-binding proteins. Each fraction was then separated by SDS-PAGE, and the resulting gel line was cut into approximately 50 bands. After trypsin digestion, the resulting peptides from each band were analyzed by RP-LC/ESI-MS/MS using an LTQ spectrometer. The SEQUEST search program, which searched against the IPI database, was used for peptide sequence identification, and peptide sequences were validated by reversed sequence database search and filtered by the Protein Hit Score. Ultimately, 1533 proteins could be detected from the human brain. We classified the identified proteins according to their distribution on cellular components. Among these proteins, 24% were membrane proteins. Our results show that the multiple separation strategy is effective for high-throughput characterization of proteins from complex proteomic mixtures.

Relative quantification in proteomics: new approaches for biochemistry

Recent developments in mass spectrometry and protein arrays provide opportunities to derive systematically proteomic information from small samples of cellular material. Relative quantification among samples can be achieved with either gel-based or gel-free approaches. Furthermore, the adaptation of specific techniques facilitates absolute quantification. Here, relative quantification in two-dimensional gel electrophoresis is contrasted with that in non-gel-based approaches such as isobaric tagging of peptides, pre-labelling of living cells with isotopomeric forms of essential amino acids and protein array platforms. In addition, novel flow-cytometry-based approaches are considered. These technologies can all be used to determine accurately the levels of proteins or biomarkers in a wide range of samples.

Rarity gives a charm: evaluation of trace proteins in plasma and serum

Since plasma potentially contacts every cell as it circulates through the body, it may carry clues both to diagnosis and treatment of disease. It is commonly expected that the growing ability to detect and characterize trace proteins will result in discovery of novel therapeutics and biomarkers; however, the familiar, super-abundant plasma proteins remain a fundamental stumbling block. Furthermore, robust validation of proteomic data is a sometimes overlooked but always necessary component for the eventual development of clinical reagents. This review surveys some of the uses of typical and atypical low-abundance proteins, current analytical methods, existing impediments to discovery, and some innovations that are overcoming the challenges to evaluation of trace proteins in plasma and serum.

1-DE MS and 2-D LC-MS analysis of the mouse bronchoalveolar lavage proteome

Bronchoalveolar lavage fluid (BALF) is a complex mixture of proteins, which represents a unique clinically useful sampling of the lower respiratory tract. Many proteomic technologies can be used to characterize complex biological mixtures; however, it is not yet clear which technology(s) provide more information regarding the number of proteins identified and sequence coverage. In this study, we initially compared two common proteomic approaches, 2-D LC microESI MS/MS and 1-DE followed by gel slice digestion, peptide extraction and peptide identification by MS in characterization of the mouse BALF proteome; secondly, we identified 297 unique proteins from the mouse BALF proteome, greatly expanded the BALF proteome by about threefold regardless of species.

Rapid proteome analysis of bronchoalveolar lavage samples of lifelong smokers and never-smokers by micro-scale liquid chromatography and mass spectrometry

BACKGROUND

The aim of this study was to determine whether relative qualitative and quantitative differences in protein expression could be related to smoke exposure or smoke-induced airway inflammation. We therefore explored and characterized the protein components found in bronchoalveolar lavage (BAL) fluid sampled from either lifelong smokers or never-smokers.

METHODS

BAL fluid samples obtained by bronchoscopy from 60-year-old healthy never-smokers (n = 18) and asymptomatic smokers (n = 30) were analyzed in either pooled or individual form. Initial global proteomic analysis used shotgun digestion approaches on unfractionated BAL fluid samples (after minimal sample preparation) and separation of peptides by gradient (90-min) liquid chromatography (LC) coupled with on-line linear ion trap quadropole mass spectrometry (LTQ MS) for identification and analysis.

RESULTS

LTQ MS identified 481 high- to low-abundance proteins. Relative differences in patterns of BAL fluid proteins in smokers compared with never-smokers were observed in pooled and individual samples as well as by 2-dimensional gel analysis. Gene ontology categorization of all annotated proteins showed a wide spectrum of molecular functions and biological processes.

CONCLUSIONS

The described method provides comprehensive qualitative proteomic analysis of BAL fluid protein expression from never-smokers and from smokers at risk of developing chronic obstructive pulmonary disease. Many of the proteins identified had not been detected in previous studies of BAL fluid; thus, the use of LC-tandem MS with LTQ may provide new information regarding potentially important patterns of protein expression associated with lifelong smoking.

A proteomic study of the HUPO Plasma Proteome Project's pilot samples using an accurate mass and time tag strategy

Characterization of the human blood plasma proteome is critical to the discovery of routinely useful clinical biomarkers. We used an accurate mass and time (AMT) tag strategy with high-resolution mass accuracy cLC-FT-ICR MS to perform a global proteomic analysis of pilot study samples as part of the HUPO Plasma Proteome Project. HUPO reference serum and citrated plasma samples from African Americans, Asian Americans, and Caucasian Americans were analyzed, in addition to a Pacific Northwest National Laboratory reference serum and plasma. The AMT tag strategy allowed us to leverage two previously published "shotgun" proteomics experiments to perform global analyses on these samples in triplicate in less than 4 days total analysis time. A total of 722 (22% with multiple peptide identifications) International Protein Index redundant proteins, or 377 protein families by ProteinProphet, were identified over the six individual HUPO serum and plasma samples. The samples yielded a similar number of identified redundant proteins in the plasma samples (average 446 +/- 23) as found in the serum samples (average 440 +/- 20). These proteins were identified by an average of 956 +/- 35 unique peptides in plasma and 930 +/- 11 unique peptides in serum. In addition to this high-throughput analysis, the AMT tag approach was used with a Z-score normalization to compare relative protein abundances. This analysis highlighted both known differences in serum and citrated plasma such as fibrinogens, and reproducible differences in peptide abundances from proteins such as soluble activin receptor-like kinase 7b and glycoprotein m6b. The AMT tag strategy not only improved our sample throughput but also provided a basis for estimated quantitation.

The human plasma proteome: analysis of Chinese serum using shotgun strategy

We have investigated the serum proteome of Han-nationality Chinese by using shotgun strategy. A complete proteomics analysis was performed on two reference specimens from a total of 20 healthy donors, in which each sample was made from ten-pooled male or female serum, respectively. The methodology used encompassed (1) removal of six high-abundant proteins; (2) tryptic digestion of low- and high-abundant proteins of serum; (3) separation of peptide mixture by RP-HPLC followed by ESI-MS/MS identification. A total of 944 nonredundant proteins were identified under a stringent filter condition (X(corr) > or = 1.9, > or = 2.2, and > or = 3.75, < or = C(n) > or = 0.1, and R(sp) > or = 4.0) in both pooled male and female samples, in which 594 and 622 entire proteins were found, respectively. Compared with the total 3020 protein identifications confirmed by more than one laboratory or more than one specimen in HUPO Plasma Proteome Project (PPP) participating laboratories recently, 206 proteins were identified with at least two distinct peptides per protein and 185 proteins were considered as high-confidence identification. Moreover, some lower abundance serum proteins (ng/mL range) were detected, such as complement C5 and CA125, routinely used as an ovarian cancer marker in plasma and serum. The resulting nonredundant list of serum proteins would add significant information to the knowledge base of human plasma proteome and facilitate disease markers discovery.

Standardization in laboratory medicine: new challenges

The primary goal of Laboratory Medicine is to provide information that is useful to assist medical decision-making and permits optimal health care. This type of information should be independently obtained of the measurement test kits and instruments, and also of the laboratory where the procedure is carried out. It is therefore important to achieve a level of comparability of laboratory results among the many measurement procedures available so that results are harmonized and interchangeable over space and time. The standardization of measurements is therefore of high priority. In recent years, numerous efforts have been made at the international level under the auspices of the IFCC and other organizations to standardize measurement results for many important analytes, e.g. enzymes, cardiac proteins, etc. The aim of this review is to discuss some concepts related to the achievement of standardization by the implementation of a metrologically correct measurement system, providing some examples on how these concepts can be applied in Laboratory Medicine.

Effects of chromatography conditions on intact protein separations for top-down proteomics

For top-down proteomics, nano-reversed phase liquid chromatography (RPLC) plays a major role in both single and multidimensional protein separations in an effort to increase the overall peak capacity for the resolution of complex protein mixtures prior to mass spectrometry analysis. Effects of various chromatography conditions, including alkyl chain length in the stationary phase, capillary column temperature, and ion-pairing agent, on the resolution of intact proteins are studied using nano-RPLC-electrospray ionization-mass spectrometry. Optimal chromatography conditions include the use of C18 column heated at 60 degrees C and the addition of trifluoroacetic acid instead of heptafluorobutyric acid as the ion-paring agent in the mobile phase. Under optimized chromatography conditions, there are no significant differences in the separation performance of yeast cell lysates present in the native versus denatured states. Denatured yeast proteins resolved and eluted from nano-RPLC can be subjected to proteolytic digestion in an on- or off-line approach to provide improved protein sequence coverage toward protein identification in a combined top-down/bottom-up proteome platform.

Workshop on Cancer Biometrics: Identifying Biomarkers and Surrogates of Cancer in Patients

The current excitement about molecular targeted therapies has driven much of the recent dialog in cancer diagnosis and treatment. Particularly in the biologic therapy of cancer, identifiable antigenic T-cell targets restricted by MHC molecules and the related novel stress molecules such as MICA/B and Letal allow a degree of precision previously unknown in cancer therapy. We have previously held workshops on immunologic monitoring and angiogenesis monitoring. This workshop was designed to discuss the state of the art in identification of biomarkers and surrogates of tumor in patients with cancer, with particular emphasis on assays within the blood and tumor. We distinguish this from immunologic monitoring in the sense that it is primarily a measure of the tumor burden as opposed to the immune response to it. Recommendations for intensive investigation and targeted funding to enable such strategies were developed in seven areas: genomic analysis; detection of molecular markers in peripheral blood and lymph node by tumor capture and RT-PCR; serum, plasma, and tumor proteomics; immune polymorphisms; high content screening using flow and imaging cytometry; immunohistochemistry and tissue microarrays; and assessment of immune infiltrate and necrosis in tumors. Concrete recommendations for current application and enabling further development in cancer biometrics are summarized. This will allow a more informed, rapid, and accurate assessment of novel cancer therapies.

Comparative proteome analyses of human plasma following in vivo lipopolysaccharide administration using multidimensional separations coupled with tandem mass spectrometry

There is significant interest in characterization of the human plasma proteome due to its potential for providing biomarkers applicable to clinical diagnosis and treatment and for gaining a better understanding of human diseases. We describe here a strategy for comparative proteome analyses of human plasma, which is applicable to biomarker identifications for various disease states. Multidimensional liquid chromatography-mass spectrometry (LC-MS/MS) has been applied to make comparative proteome analyses of plasma samples from an individual prior to and 9 h after lipopolysaccharide (LPS) administration. Peptide peak areas and the number of peptide identifications for each protein were used to evaluate the reproducibility of LC-MS/MS and to compare relative changes in protein concentration between the samples following LPS treatment. A total of 804 distinct plasma proteins (not including immunoglobulins) were confidently identified with 32 proteins observed to be significantly increased in concentration following LPS administration, including several known inflammatory response or acute-phase mediators such as C-reactive protein, serum amyloid A and A2, LPS-binding protein, LPS-responsive and beige-like anchor protein, hepatocyte growth factor activator, and von Willebrand factor, and thus, constituting potential biomarkers for inflammatory response.

Integrated Capillary Isoelectric Focusing/Nano-reversed Phase Liquid Chromatography Coupled with ESI−MS for Characterization of Intact Yeast Proteins

An integrated protein concentration/separation platform, combining capillary isoelectric focusing (CIEF) with nano-reversed phase liquid chromatography (nano-RPLC), is developed to provide significant protein concentration and high resolving power for the analysis of complex protein mixtures. Upon completion of protein focusing, the proteins are sequentially and hydrodynamically loaded into individual trap columns using a group of microinjection and microselection valves. Repeated pro-tein loadings and injections into trap columns are carried out automatically until the entire CIEF cap-illary content is sampled and fractionated. Each CIEF fraction "parked" in separate trap columns is further resolved using nano-RPLC, and the eluants are analyzed using electrospray ionization-mass spectrometry.

Pathway Proteomics

Biological pathways represent the relationships (reactions and interactions) between biological molecules in the context of normal cellular functions and disease mechanisms. Understanding the roles of proteins and signaling pathways expressed within disease, and their link to drug discovery and drug development are central in today's target-driven pharmaceutical processes. This article gives an overview of proteomics strategies, including global expression analysis as well as focused approaches using multidimensional separation by both gel- and liquid-phase techniques linked to mass spectrometry, as applied to two of the pathways involved in inflammatory diseases. In primary human cell studies, our group has annotated and identified thousands of proteins using both electrospray ionization and matrix-assisted laser desorption ionization (MALDI)-sequencing technology. Annotations made from gel images and chromatography fractionation, interfaced to high-end mass spectrometry sequence and structure identity, are cornerstones in cutting-edge protein expression profiling. Regarding phosphorylation mechanisms of kinases, the quantitative stoichiometry can be determined using affinity probe isolations. Another strategy involves micro-preparative sample processing, which has been used to analyze single-target phosphoproteins and their relative phospho-stoichiometry.

Diagnostic protein discovery using liquid chromatography/mass spectrometry for proteolytic peptide targeting

A peptide targeting method has been developed for diagnostic protein discovery, which combines proteolytic digestion of fractionated plasma proteins and liquid chromatography coupled to electrospray time-of-flight mass spectrometry (LC/ESI-TOFMS) profiling. Proteolysis prior to profiling overcomes molecular weight limitations and compensates for the poor sensitivity of matrix-assisted laser desorption/ionization (MALDI) protein profiling. LC/MS increases the peak capacity compared to crude fractionation techniques or single sample MALDI analysis. Differentially expressed peptides are targeted in the mass chromatograms using bioinformatic techniques and subsequently sequenced with MALDI tandem MS. In a model study comparing pancreatic cancer patients to controls, 74% of the peptide targets were successfully sequenced. This profiling method was superior to previous experiments using single sample MALDI analysis for protein profiling or proteolytic peptide profiling, because more potential protein markers were identified.

Cerebrospinal fluid protein patterns in neurodegenerative disease revealed by liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry

This study demonstrates the power of a novel proteomic approach developed for the detection and identification of biological markers in body fluids. The goal was to observe alterations in the protein patterns of cerebrospinal fluid (CSF) related to amyotrophic lateral sclerosis (ALS), a neurodegenerative disorder with unknown etiology. In the experiments, tryptic digests of CSF from patients and healthy controls were analyzed by on-line capillary liquid chromatography-Fourier transform ion cyclotron resonance mass spectrometry. (FT-ICR MS) Typically, around 4000 peptides were detected in one such experiment, and a pattern recognition program was constructed for the data analysis to distinguish mass chromatograms from patients and controls. This strategy was evaluated comparing the peptide patterns of CSF spiked in vitro with a biomarker, with control CSF. The patterns were clearly separated and the tryptic peptides of the biomarker were successfully selected as characteristic peaks. Hence, the method was applied to compare mass chromatograms of CSF from 12 ALS-patients and 10 matched healthy controls. While no biomarker alone could be identified from the characteristic peaks, we were able to assign 4 out of 5 unknown samples correctly (i.e., 80% correctly diagnosed, 20% false-negative), and it would be 100% if we reject a possible outlier believed to be caused by an occlusion in the spinal CSF compartment. These findings are very promising, although the clinical relevance is not fully established due to the low number of unknown samples analyzed. In addition to the diagnostic potential, these results may be important steps towards understanding the neurodegenerative process.

A new and sensitive on-line liquid chromatography/mass spectrometric approach for top-down protein analysis: the comprehensive analysis of human growth hormone in an E. coli lysate using a hybrid linear ion trap/Fourier transform ion cyclotron resonance mass spectrometer

A sensitive, integrated top-down liquid chromatography/mass spectrometry (LC/MS) approach, suitable for the near complete characterization of specific proteins in complex protein mixtures, such as inclusion bodies of an E. coli lysate, has been successfully developed using a hybrid linear ion trap/Fourier transform ion cyclotron resonance (FTICR) mass spectrometer. In particular, human growth hormone (hGH) (200 fmol) was analyzed with high sequence coverage (>95%), including the sites of disulfide linkages. The high mass accuracy and resolution of the FTICR mass spectrometer was used to reveal high charge state ions of hGH (22 kDa). The highly charged intact protein ions (such as the 17+ species) were captured and fragmented in the linear ion trap cell. The fragment ions from MS/MS spectra were then successfully analyzed in the FTICR cell in an on-line LC/MS run. Peptide fragments from the N-terminal and C-terminal regions, as well as large interior fragments, were captured and identified. The results allowed the unambiguous assignment of disulfide bonds Cys53-Cys165 and Cys182-Cys189, indicative of proper folding of hGH. The disulfide bond assignments were also confirmed by analysis of the tryptic digest of a sample of hGH purified from inclusion bodies. On-line LC/MS with the linear ion trap/FTICR yields high mass accuracy in both the MS and MS/MS modes (within 2 ppm with external calibration). The approach should prove useful in biotechnology applications to characterize correctly folded proteins, both in the early protein expression and the later processed stages, using only a single automated on-line LC/MS top-down method.