A human proteome detection and quantitation project

Quantitative mass spectrometry evaluation of human retinol binding protein 4 and related variants

Background

Retinol Binding Protein 4 (RBP4) is an exciting new biomarker for the determination of insulin resistance and type 2 diabetes. It is known that circulating RBP4 resides in multiple variants which may provide enhanced clinical utility, but conventional immunoassay methods are blind to such differences. A Mass Spectrometric immunoassay (MSIA) technology that can quantitate total RBP4 as well as individual isoforms may provide an enhanced analysis for this biomarker.

Methods

RBP4 was isolated and detected from 0.5 uL of human plasma using MSIA technology, for the simultaneous quantification and differentiation of endogenous human RBP4 and its variants.

Results

The linear range of the assay was 7.81–500 ug/mL, and the limit of detection and limit of quantification were 3.36 ug/mL and 6.52 ug/mL, respectively. The intra-assay CVs were determined to be 5.1% and the inter-assay CVs were 9.6%. The percent recovery of the RBP4-MSIA ranged from 95 – 105%. Method comparison of the RBP4 MSIA vs the Immun Diagnostik ELISA yielded a Passing & Bablok fit of MSIA  = 1.05× ELISA – 3.09, while the Cusum linearity p-value was >0.1 and the mean bias determined by the Altman Bland test was 1.2%.

Conclusion

The novel RBP4 MSIA provided a fast, accurate and precise quantitative protein measurement as compared to the standard commercially available ELISA. Moreover, this method also allowed for the detection of RBP4 variants that are present in each sample, which may in the future provide a new dimension in the clinical utility of this biomarker.

ATAQS: A computational software tool for high throughput transition optimization and validation for selected reaction monitoring mass spectrometry

BACKGROUND

Since its inception, proteomics has essentially operated in a discovery mode with the goal of identifying and quantifying the maximal number of proteins in a sample. Increasingly, proteomic measurements are also supporting hypothesis-driven studies, in which a predetermined set of proteins is consistently detected and quantified in multiple samples. Selected reaction monitoring (SRM) is a targeted mass spectrometric technique that supports the detection and quantification of specific proteins in complex samples at high sensitivity and reproducibility. Here, we describe ATAQS, an integrated software platform that supports all stages of targeted, SRM-based proteomics experiments including target selection, transition optimization and post acquisition data analysis. This software will significantly facilitate the use of targeted proteomic techniques and contribute to the generation of highly sensitive, reproducible and complete datasets that are particularly critical for the discovery and validation of targets in hypothesis-driven studies in systems biology.

RESULT

We introduce a new open source software pipeline, ATAQS (Automated and Targeted Analysis with Quantitative SRM), which consists of a number of modules that collectively support the SRM assay development workflow for targeted proteomic experiments (project management and generation of protein, peptide and transitions and the validation of peptide detection by SRM). ATAQS provides a flexible pipeline for end-users by allowing the workflow to start or end at any point of the pipeline, and for computational biologists, by enabling the easy extension of java algorithm classes for their own algorithm plug-in or connection via an external web site.This integrated system supports all steps in a SRM-based experiment and provides a user-friendly GUI that can be run by any operating system that allows the installation of the Mozilla Firefox web browser.

CONCLUSIONS

Targeted proteomics via SRM is a powerful new technique that enables the reproducible and accurate identification and quantification of sets of proteins of interest. ATAQS is the first open-source software that supports all steps of the targeted proteomics workflow. ATAQS also provides software API (Application Program Interface) documentation that enables the addition of new algorithms to each of the workflow steps. The software, installation guide and sample dataset can be found in http://tools.proteomecenter.org/ATAQS/ATAQS.html.

Evaluation of large scale quantitative proteomic assay development using peptide affinity-based mass spectrometry

Stable isotope standards and capture by antipeptide antibodies (SISCAPA) couples affinity enrichment of peptides with stable isotope dilution and detection by multiple reaction monitoring mass spectrometry to provide quantitative measurement of peptides as surrogates for their respective proteins. In this report, we describe a feasibility study to determine the success rate for production of suitable antibodies for SISCAPA assays in order to inform strategies for large-scale assay development. A workflow was designed that included a multiplex immunization strategy in which up to five proteotypic peptides from a single protein target were used to immunize individual rabbits. A total of 403 proteotypic tryptic peptides representing 89 protein targets were used as immunogens. Antipeptide antibody titers were measured by ELISA and 220 antipeptide antibodies representing 89 proteins were chosen for affinity purification. These antibodies were characterized with respect to their performance in SISCAPA-multiple reaction monitoring assays using trypsin-digested human plasma matrix. More than half of the assays generated were capable of detecting the target peptide at concentrations of less than 0.5 fmol/μl in human plasma, corresponding to protein concentrations of less than 100 ng/ml. The strategy of multiplexing five peptide immunogens was successful in generating a working assay for 100% of the targeted proteins in this evaluation study. These results indicate it is feasible for a single laboratory to develop hundreds of assays per year and allow planning for cost-effective generation of SISCAPA assays.

Cardiovascular proteomics: translational studies to develop novel biomarkers in heart failure and left ventricular remodeling

Heart failure (HF) remains a severe disease with a poor prognosis. HF biomarkers may include demographic features, cardiac imaging, or genetic polymorphisms but this term is commonly applied to circulating serum or plasma analytes. Biomarkers may have at least three clinical uses in the context of HF: diagnosis, risk stratification, and guidance in the selection of therapy. Proteomic studies on HF biomarkers can be designed as case/control using clinical endpoints; alternatively, left ventricular remodeling can be used as a surrogate endpoint. The type of samples (tissue, cells, serum or plasma) used for proteomic analysis is a key factor in the research of biomarkers. Since the final aim is the discovery of circulating biomarkers, and since plasma and serum samples are easily accessible, proteomic analysis is frequently used for blood samples. However, standardization of sampling and access to low-abundance proteins remains problematic. Although, proteomics is playing a major role in the discovery phase of biomarkers, validation in independent populations is necessary by using more specific methods. The knowledge of new HF biomarkers may allow a more personalized medicine in the future.

Development of serum glycoproteomic profiling technique; simultaneous identification of glycosylation sites and site-specific quantification of glycan structure changes

Characterization and interpretation of disease-associated alterations of protein glycosylation are the central aims of the emerging glycoproteomics projects, which are expected to lead to more sensitive and specific diagnosis and improve therapeutic outcomes for various diseases. Here we report a new approach to identify carbohydrate-targeting serum biomarkers, termed isotopic glycosidase elution and labeling on lectin-column chromatography (IGEL). This technology is based on glycan structure-specific enrichment of glycopeptides by lectin-column chromatography and site-directed tagging of N-glycosylation sites by (18)O during the elution with N-glycosidase. The combination of IGEL with 8-plex isobaric tag for relative and absolute quantitation (iTRAQ) stable isotope labeling enabled us not only to identify N-glycosylation sites effectively but also to compare glycan structures on each glycosylation site quantitatively in a single LC/MS/MS analysis. We applied this method to eight sera from lung cancer patients and controls, and finally identified 107 glycopeptides in their sera, including A2GL_Asn151, A2GL_Asn290, CD14_Asn132, CO8A_Asn417, C163A_Asn64, TIMP1_Asn30, and TSP1_Asn1049 which showed the significant change of the affinity to Concanavalin A (ConA) lectin between the lung cancer samples and the controls (p < 0.05 and more than twofold change). These screening results were further confirmed by the conventional lectin-column chromatography and immunoblot analysis using additional serum samples. Our novel methodology, which should be valuable for diverse biomarker discoveries, can provide high-throughput and quantitative profiling of glycan structure alterations.

Bioinformatics challenges in the proteomic analysis of human plasma

Mass spectrometry has become the method of choice for studying proteins in complex mixtures in a qualitative and quantitative fashion. The application of mass spectrometry-based proteomics analyses on plasma has correspondingly been established as an important method for disease-associated biomarker discovery and validation. Yet despite being a readily available human sample, plasma poses several important challenges to the proteomics researcher. With a focus on bioinformatics aspects, this chapter will discuss the problems involved in analyzing plasma proteomics data, along with the scope of solutions available through specialised tools and sophisticated analysis methods.

Is a gene-centric human proteome project the best way for proteomics to serve biology?

With the recent developments in proteomic technologies, a complete human proteome project (HPP) appears feasible for the first time. However, there is still debate as to how it should be designed and what it should encompass. In "proteomics speak", the debate revolves around the central question as to whether a gene-centric or a protein-centric proteomics approach is the most appropriate way forward. In this paper, we try to shed light on what these definitions mean, how large-scale proteomics such as a HPP can insert into the larger omics chorus, and what we can reasonably expect from a HPP in the way it has been proposed so far.

Innovative proteomics for the discovery of systemically accessible cancer biomarkers suitable for imaging and targeted therapies

The discovery of biomarkers that are readily accessible through the circulating blood and are selectively overexpressed in pathological tissues has become a major research objective, particularly in the field of oncology. Indisputably, this group of molecules has a high potential to serve as an innovative tool for effective imaging and targeted cancer therapy approaches. In this attractive therapeutic concept, specific cancer proteins are reached by intravenously administered ligands that are coupled to cytotoxic drugs. Such compounds are able to induce cancer destruction while sparing normal tissues. Owing to the performance of mass spectrometry technology, current high-throughput proteomic analysis allows for the identification of a high number of proteins that are differentially expressed in the cancerous tissues. However, such approaches provide no information regarding the effective accessibility of the >biomarkers and, therefore, the possibility for these discovered proteins to be targeted. To bypass this major limitation, which clearly slows the discovery of such biomarkers, innovative methodological strategies have been developed to enrich the clinical specimens before the mass spectrometry analysis. The focus is laid on the group of proteins that are necessarily located either at the exterior face of the plasma membrane or in the extracellular matrix. The present review addresses the current technologies meant for the discovery and analysis of accessible antigens from clinically relevant samples.

Plasma proteome analysis in diet-induced obesity-prone and obesity-resistant rats

One of the major issues in the field of obesity is why some humans become obese and others resist development of obesity when exposed to high-calorie diets. Despite the same genetic background, namely obesity-prone (OP) and -resistant (OR) rats, differing responses have been demonstrated in a high fat diet-induced rodent model. The aim of the present study was to discover novel obesity-related biomarkers for susceptibility and/or resistance to obesity by proteomic analysis of OP and OR rat plasma. After feeding of high fat diet, OP rats gained approximately 25% more body weight than OR rats and were used for proteomic analysis using 2-DE combined with MALDI-TOF-MS. We categorized identified proteins into three groups by analysis of both average spot density in each group and individual spot density of six rats as a function of body weight. Consequently, category (1) included inter-α-inhibitor H4 heavy chain and fetuin B precursor, which can be used as novel plasma biomarkers for risk of obesity. Nine proteins of category (2) and (3) can also be plausible plasma markers in the study of obesity. This proteomic study is an important advancement over the previous steps needed for identification of OP and OR rats.

Biomarker analysis of stored blood products: emphasis on pre-analytical issues

Millions of blood products are transfused every year; many lives are thus directly concerned by transfusion. The three main labile blood products used in transfusion are erythrocyte concentrates, platelet concentrates and fresh frozen plasma. Each of these products has to be stored according to its particular components. However, during storage, modifications or degradation of those components may occur, and are known as storage lesions. Thus, biomarker discovery of in vivo blood aging as well as in vitro labile blood products storage lesions is of high interest for the transfusion medicine community. Pre-analytical issues are of major importance in analyzing the various blood products during storage conditions as well as according to various protocols that are currently used in blood banks for their preparations. This paper will review key elements that have to be taken into account in the context of proteomic-based biomarker discovery applied to blood banking.

Combinatorial peptide ligand library plasma treatment: Advantages for accessing low-abundance proteins

Depletion of major blood proteins is one of the most promising approaches to accessing low-abundance biomarkers. This study compared the use of combinatorial peptide ligand library (CPLL) and albumin and immunoglobulins (IgGs) depletion technology for accessing these low-abundance proteins in plasma using 2-DE in an acidic restricted pH range (4-7). Compared with native plasma, both techniques enlarge the visibility of other proteins than albumin and IgG, but there were marked differences in their composition. An increase of the number of spots was detected compared with native plasma (157 spots) with 427 and 557 spots, respectively, detected with albumin and IgG depletion, and CPLL treatment. We selected 70 spots to be identified by MALDI-TOF related to their absence in the 2-D gels from native or albumin and IgG-depleted plasma. The 42 spots identified corresponded to 24 different proteins, with more than half of the proteins which did not belong to the major plasma proteins. CPLL treatment allowed the accessibility to proteolytic fragments obtained from major plasma proteins. We found a large superiority of the CPLL approach over the albumin and IgG depletion process. These findings show the utility of depleting major blood proteins to be able to access low-abundance proteins and the potential of CPLL to select and identify candidate biomarkers in clinical studies.

Vaccines and the future of human immunology

In this issue of Immunity, a collection of detailed reviews summarizes needs, opportunities, and roadblocks to the development of new vaccines, all in the context of our current knowledge and understanding of key aspects of immune function and microbial interactions with the host. This Perspective is designed to provide a broad overview that discusses our present limitations in designing effective novel vaccines for diseases that do not typically induce robust resistance in infected individuals and how the addition of a systems-level, multiplexed approach to the analysis of the human immune system can complement traditional highly focused research efforts to accelerate our progress toward this goal and the improvement of human health.

MALDI immunoscreening (MiSCREEN): a method for selection of anti-peptide monoclonal antibodies for use in immunoproteomics

A scalable method for screening and selection of peptide-specific monoclonal antibodies (mAbs) is described. To identify high affinity anti-peptide mAbs in hybridoma supernatants, antibodies were captured by magnetic affinity beads followed by binding of specific peptides from solution. After timed washing steps, the remaining bound peptides were eluted from the beads and detected by matrix-assisted laser desorption/ionization time-of-flight (MALDI-TOF) mass spectrometry (MS). This allowed measurement of monovalent interactions of peptides with single antigen binding sites on the antibodies, thus reflecting antibody affinity rather than avidity. Antibodies that were able to bind target peptides from solution phase and retain them during washing for a minimum of 10 min were identified by the strength of the appropriate m/z peptide MS signals obtained. This wash time reflects the minimum peptide dissociation time required for use of these antibodies in several current immuno-mass spectrometry assays. Kinetic analysis of antibody-peptide binding by surface plasmon resonance (SPR) showed that the selected antibodies were of high affinity and, most importantly, had low dissociation constants. This method, called MALDI immunoscreening (MiSCREEN), thus enables rapid screening and selection of high affinity anti-peptide antibodies that are useful for a variety of immunoproteomics applications. To demonstrate their functional utility in immuno-mass spectrometry assays, we used the selected, purified RabMAbs to enrich natural (tryptic) peptides from digested human plasma.

Proteomics database in chronic kidney disease

Databases which are useful for proteomic analysis of human kidney tissue and urine have been discussed in this article. Integration of the gene-centric and protein-centric general databases with those of human kidney tissue and urine proteomes may open a new window for research in nephrology. Proteins present in the kidney and urine provide basic tools for investigation of kidney function and disease. By comparing such databases between the healthy and diseased populations, we may be able to identify the following: proteins involved in the development of renal disease, proteins involved in progression of CKD, or new biomarker candidate proteins for either the development of renal disease or the progression of CKD.

Targeting peptide termini, a novel immunoaffinity approach to reduce complexity in mass spectrometric protein identification

Mass spectrometry and peptide-centric approaches are powerful techniques for the identification of differentially expressed proteins. Despite enormous improvements in MS technologies, sample preparation and efficient fractionation of target analytes are still major bottlenecks in MS-based protein analysis. The complexity of tryptically digested whole proteomes needs to be considerably reduced before low abundance proteins can be effectively analyzed using MS/MS. Sample preparation strategies that use peptide-specific antibodies are able to reduce the complexity of tryptic digests and lead to a substantial increase in throughput and sensitivity; however, the number of peptide-specific capture reagents is low, and consequently immunoaffinity-based approaches are only capable of detecting small sets of protein-derived peptides. In this proof-of-principle study, special anti-peptide antibodies were used to enrich peptides from a complex mixture. These antibodies recognize short amino acid sequences that are found directly at the termini of the peptides. The recognized epitopes consist of three or four amino acids only and include the terminally charged group of the peptide. Because of its limited length, antibodies recognizing the epitope will enrich not only one peptide but a whole class of peptides that share this terminal epitope. In this study, β-catenin-derived peptides were used to demonstrate that it is possible (i) to effectively generate antibodies that recognize short C-terminal peptide epitopes and (ii) to enrich and identify peptide classes from a complex mixture using these antibodies in an immunoaffinity MS approach. The expected β-catenin peptides and a set of 38 epitope-containing peptides were identified from trypsin-digested cell lysates. This might be a first step in the development of proteomics applications that are based on the use of peptide class-specific antibodies.

Proteomic profile of zebrafish brain based on two-dimensional gel electrophoresis matrix-assisted laser desorption/ionization MS/MS analysis

Zebrafish is one of the most widely studied model organisms for understanding the neurodevelopment and neurological disorders of humans because of its similar brain structure, genome, and proteome. Understanding the zebrafish brain proteome is particularly useful as no data of zebrafish brain proteome are available despite its wide use as an alternative neurological animal model. We have determined the proteome profile of the zebrafish brain based on two-dimensional gel electrophoresis covering 161 proteins including 96 protein identities reported to the Swiss-Prot database. The proteins identified in this study were found to be associated with various pathways such as cell death, free radical scavenging, cell signaling, nervous system development, and cell cycle. The identified proteins were also observed to play important roles in various brain-related diseases and genetic disorders, such as Huntington's disease, Parkinson's disease, and schizophrenia. This article provides the zebrafish brain two-dimensional gel electrophoresis proteome map and the details of the 161 brain tissue-specific proteins. Also we have established the roles of the identified proteins in various neurological functions and diseases based on pathway analysis.

Simultaneous quantification of apolipoprotein A-I and apolipoprotein B by liquid-chromatography-multiple- reaction-monitoring mass spectrometry

BACKGROUND

If liquid-chromatography-multiple-reaction-monitoring mass spectrometry (LC-MRM/MS) could be used in the large-scale preclinical verification of putative biomarkers, it would obviate the need for the development of expensive immunoassays. In addition, the translation of novel biomarkers to clinical use would be accelerated if the assays used in preclinical studies were the same as those used in the clinical laboratory. To validate this approach, we developed a multiplexed assay for the quantification of 2 clinically well-known biomarkers in human plasma, apolipoprotein A-I and apolipoprotein B (apoA-I and apoB).

METHODS

We used PeptideAtlas to identify candidate peptides. Human samples were denatured with urea or trifluoroethanol, reduced and alkylated, and digested with trypsin. We compared reversed-phase chromatographic separation of peptides with normal flow and microflow, and we normalized endogenous peptide peak areas to internal standard peptides. We evaluated different methods of calibration and compared the final method with a nephelometric immunoassay.

RESULTS

We developed a final method using trifluoroethanol denaturation, 21-h digestion, normal flow chromatography-electrospray ionization, and calibration with a single normal human plasma sample. For samples injected in duplicate, the method had intraassay CVs <6% and interassay CVs <12% for both proteins, and compared well with immunoassay (n = 47; Deming regression, LC-MRM/MS = 1.17 × immunoassay - 36.6; S(x|y) = 10.3 for apoA-I and LC-MRM/MS = 1.21 × immunoassay + 7.0; S(x|y) = 7.9 for apoB).

CONCLUSIONS

Multiplexed quantification of proteins in human plasma/serum by LC-MRM/MS is possible and compares well with clinically useful immunoassays. The potential application of single-point calibration to large clinical studies could simplify efforts to reduce day-to-day digestion variability.

Toward point-of-care microchip profiling of proteins

Profiling of protein biomarkers is powerful for the analysis of complex proteomes altered during the progression of diseases. Lab-on-a-chip technologies can potentially provide the throughput and efficiency required for point-of-care and clinical applications. While initial studies utilized 1D microchip separation techniques, researchers have recently developed novel 2D microchip separation platforms with the ability to profile thousands of proteins more effectively. Despite advancements in lab-on-a-chip technologies, very few reports have demonstrated a point-of-care microchip-based profiling of proteins. In this review, recent progress in 1D and 2D microchip profiling of protein mixtures of a biological sample with potential point-of-care applications are discussed. A selection of recent microchip immunoassay-based techniques is also highlighted.

Mass-spectrometry-based clinical proteomics--a review and prospective

This review reports on the current and emerging technologies for the use of mass-spectrometry-based proteomics in clinical applications.

Optimal selection of epitopes for TXP-immunoaffinity mass spectrometry

Background

Mass spectrometry (MS) based protein profiling has become one of the key technologies in biomedical research and biomarker discovery. One bottleneck in MS-based protein analysis is sample preparation and an efficient fractionation step to reduce the complexity of the biological samples, which are too complex to be analyzed directly with MS. Sample preparation strategies that reduce the complexity of tryptic digests by using immunoaffinity based methods have shown to lead to a substantial increase in throughput and sensitivity in the proteomic mass spectrometry approach. The limitation of using such immunoaffinity-based approaches is the availability of the appropriate peptide specific capture antibodies. Recent developments in these approaches, where subsets of peptides with short identical terminal sequences can be enriched using antibodies directed against short terminal epitopes, promise a significant gain in efficiency.

Results

We show that the minimal set of terminal epitopes for the coverage of a target protein list can be found by the formulation as a set cover problem, preceded by a filtering pipeline for the exclusion of peptides and target epitopes with undesirable properties.

Conclusions

For small datasets (a few hundred proteins) it is possible to solve the problem to optimality with moderate computational effort using commercial or free solvers. Larger datasets, like full proteomes require the use of heuristics.

Proteomics of plant pathogenic fungi

Plant pathogenic fungi cause important yield losses in crops. In order to develop efficient and environmental friendly crop protection strategies, molecular studies of the fungal biological cycle, virulence factors, and interaction with its host are necessary. For that reason, several approaches have been performed using both classical genetic, cell biology, and biochemistry and the modern, holistic, and high-throughput, omic techniques. This work briefly overviews the tools available for studying Plant Pathogenic Fungi and is amply focused on MS-based Proteomics analysis, based on original papers published up to December 2009. At a methodological level, different steps in a proteomic workflow experiment are discussed. Separate sections are devoted to fungal descriptive (intracellular, subcellular, extracellular) and differential expression proteomics and interactomics. From the work published we can conclude that Proteomics, in combination with other techniques, constitutes a powerful tool for providing important information about pathogenicity and virulence factors, thus opening up new possibilities for crop disease diagnosis and crop protection.

Synthetic peptide arrays for pathway-level protein monitoring by liquid chromatography-tandem mass spectrometry

Effective methods to detect and quantify functionally linked regulatory proteins in complex biological samples are essential for investigating mammalian signaling pathways. Traditional immunoassays depend on proprietary reagents that are difficult to generate and multiplex, whereas global proteomic profiling can be tedious and can miss low abundance proteins. Here, we report a target-driven liquid chromatography-tandem mass spectrometry (LC-MS/MS) strategy for selectively examining the levels of multiple low abundance components of signaling pathways which are refractory to standard shotgun screening procedures and hence appear limited in current MS/MS repositories. Our stepwise approach consists of: (i) synthesizing microscale peptide arrays, including heavy isotope-labeled internal standards, for use as high quality references to (ii) build empirically validated high density LC-MS/MS detection assays with a retention time scheduling system that can be used to (iii) identify and quantify endogenous low abundance protein targets in complex biological mixtures with high accuracy by correlation to a spectral database using new software tools. The method offers a flexible, rapid, and cost-effective means for routine proteomic exploration of biological systems including "label-free" quantification, while minimizing spurious interferences. As proof-of-concept, we have examined the abundance of transcription factors and protein kinases mediating pluripotency and self-renewal in embryonic stem cell populations.

Towards proteome standards: the use of absolute quantitation in high-throughput biomarker discovery

The use of proteomics to profile biological fluids and identify therein biomarkers for cancer and other diseases was initially received with considerable excitement. However, results have fallen short of the expectations. Traditionally, protein biomarkers have been identified by measurement of relative expression changes between case and control samples from which differentially expressed proteins are then considered to represent biomarker candidates. We argue that current individual proteomics-based biomarker discovery studies lack the statistical strength for the identification of high-confidence biomarkers. Instead, multi-group efforts are necessary to facilitate the generation of sufficient sample sizes. This is contingent on the ability to collate and cross-compare data from different studies, which will require the use of a common metric or standards. Though profound, the technical challenges for absolute protein quantification can be overcome. The use of matrix specific, shared standards for absolute quantitation presents an opportunity to facilitate the much needed, but currently impossible, comparisons of different studies. In addition to community-wide approaches to standardize pre-analytical biomarker research studies, it is also important to establish means to integrate experimental data from different studies in order to assess the usefulness of proposed biomarkers with sufficient statistical certainty.

Urine collection and processing for protein biomarker discovery and quantification

BACKGROUND

Urine is a useful source of protein for biomarker discovery and assessment because it is readily available, can be obtained by noninvasive collection methods, and enables monitoring of a wide range of physiologic processes and diseases. Urine aliquots provide enough protein for multiple analyses, combining current protocols with new techniques.

CONCLUSIONS

Standardized collection and processing protocols are now being established and new methods for protein detection and quantification are emerging to complement traditional immunoassays. The current state of urine collection, specimen processing, and storage is reviewed with regard to discovery and quantification of protein biomarkers for cancer.

Yeast expression proteomics by high-resolution mass spectrometry

Comprehensive analysis of yeast as a model system requires to reliably determine its composition. Systematic approaches to globally determine the abundance of RNAs have existed for more than a decade and measurements of mRNAs are widely used as proxies for detecting changes in protein abundance. In contrast, methodologies to globally quantitate proteins are only recently becoming available. Such experiments are essential as proteins mediate the majority of biological processes and their abundance does not always correlate well with changes in gene expression. Particularly translational and post-translational controls contribute majorly to regulation of protein abundance, for example in heat shock stress response. The development of new sample preparation methods, high-resolution mass spectrometry and novel bioinfomatic tools close this gap and allow the global quantitation of the yeast proteome under different conditions. Here, we provide background information on proteomics by mass-spectrometry and describe the practice of a comprehensive yeast proteome analysis.

Stable-isotope dilution LC–MS for quantitative biomarker analysis

The ability to conduct validated analyses of biomarkers is critically important in order to establish the sensitivity and selectivity of the biomarker in identifying a particular disease. The use of stable-isotope dilution (SID) methodology in combination with LC–MS/MS provides the highest possible analytical specificity for quantitative determinations. This methodology is now widely used in the discovery and validation of putative exposure and disease biomarkers. This review will describe the application of SID LC–MS methodology for the analysis of small-molecule and protein biomarkers. It will also discuss potential future directions for the use of this methodology for rigorous biomarker analysis.

Full-Length Characterization of Proteins in Human Populations

Background: Diversity in human proteins often gives rise to pluralities of structurally similar but functionally distinct proteins. Such microheterogeneity generally escapes proteomics discovery technologies, as well as conventional immunometric assays. As an intermediate between these 2 technological approaches, targeted, full-length characterization of proteins using mass spectrometry is a suitable means of defining microheterogeneity evident in human populations.

Content: We describe and explore the implications of microheterogeneity using the exemplar of human vitamin D binding protein (Gc-Globulin) as observed in cohorts of 400 individuals. Our investigations yielded: (a) population frequency data comparable to genotyping; (b) population frequency data for protein variants, with and without genotype linkage; (c) reference values for the different protein variants per cohort and genotype; and (d) associations between variant, frequency, relative abundance, and diseases.

Summary: With the exception of the genotype frequency, such population data are unique and illustrate a need to more fully understand the exact full-length qualitative and quantitative idiosyncrasies of individual proteins in relation to health and disease as part of the standardized biomarker development and clinical proteomic investigation of human proteins.

Multiplex assays for biomarker research and clinical application: translational science coming of age

Over the last decade, translational science has come into the focus of academic medicine, and significant intellectual and financial efforts have been made to initiate a multitude of bench-to-bedside projects. The quest for suitable biomarkers that will significantly change clinical practice has become one of the biggest challenges in translational medicine. Quantitative measurement of proteins is a critical step in biomarker discovery. Assessing a large number of potential protein biomarkers in a statistically significant number of samples and controls still constitutes a major technical hurdle. Multiplexed analysis offers significant advantages regarding time, reagent cost, sample requirements and the amount of data that can be generated. The two contemporary approaches in multiplexed and quantitative biomarker validation, antibody-based immunoassays and MS-based multiple (or selected) reaction monitoring, are based on different assay principles and instrument requirements. Both approaches have their own advantages and disadvantages and therefore have complementary roles in the multi-staged biomarker verification and validation process. In this review, we discuss quantitative immunoassay and multiple reaction monitoring/selected reaction monitoring assay principles and development. We also discuss choosing an appropriate platform, judging the performance of assays, obtaining reliable, quantitative results for translational research and clinical applications in the biomarker field.

The bottleneck in the cancer biomarker pipeline and protein quantification through mass spectrometry-based approaches: current strategies for candidate verification

BACKGROUND

Although robust discovery-phase platforms have resulted in the generation of large numbers of candidate cancer biomarkers, a comparable system for subsequent quantitative assessment and verification of all candidates is lacking. Established immunoassays and available antibodies permit analysis of small subsets of candidates; however, the lack of commercially available reagents, coupled with high costs and lengthy production and purification times, have rendered the large majority of candidates untestable.

CONTENT

Mass spectrometry (MS), and in particular multiple reaction monitoring (MRM)-MS, has emerged as an alternative technology to immunoassays for quantification of target proteins. Novel biomarkers are expected to be present in serum in the low (microg/L-ng/L) range, but analysis of complex serum or plasma digests by MS has yielded milligram per liter limits of detection at best. The coupling of prior sample purification strategies such as enrichment of target analytes, depletion of high-abundance proteins, and prefractionation, has enabled reliable penetration into the low microgram per liter range. This review highlights prospects for candidate verification through MS-based methods. We first outline the biomarker discovery pipeline and its existing bottleneck; we then discuss various MRM-based strategies for targeted protein quantification, the applicability of such methods for candidate verification, and points of concern.

SUMMARY

Although it is unlikely that MS-based protein quantification will replace immunoassays in the near future, with the expected improvements in limits of detection and specificity in instrumentation, MRM-based approaches show great promise for alleviating the existing bottleneck to discovery.

Perspectives of targeted mass spectrometry for protein biomarker verification

The identification of specific biomarkers will improve the early diagnosis of disease, facilitate the development of targeted therapies, and provide an accurate method to monitor treatment response. A major challenge in the process of verifying biomarker candidates in blood plasma is the complexity and high dynamic range of proteins. This article reviews the current, targeted proteomic strategies that are capable of quantifying biomarker candidates at concentration ranges where biomarkers are expected in plasma (i.e. at the ng/ml level). In addition, a workflow is presented that allows the fast and definitive generation of targeted mass spectrometry-based assays for most biomarker candidate proteins. These assays are stored in publicly accessible databases and have the potential to greatly impact the throughput of biomarker verification studies.

Up-regulated proteins in the fluid bathing the tumour cell microenvironment as potential serological markers for early detection of cancer of the breast

Breast cancer is by far the most common diagnosed form of cancer and the leading cause of cancer death in women today. Clinically useful biomarkers for early detection of breast cancer could lead to a significant reduction in mortality. Here we describe a detailed analysis using gel-based proteomics in combination with mass spectrometry and immunohistochemistry (IHC) of the tumour interstitial fluids (TIF) and normal interstitial fluids (NIF) collected from 69 prospective breast cancer patients. The goal of this study was to identify abundant cancer up-regulated proteins that are externalised by cells in the tumour microenvironment of most if not all these lesions. To this end, we applied a phased biomarker discovery research strategy to the analysis of these samples rather than comparing all samples among each other, with inherent inter and intra-sample variability problems. To this end, we chose to use samples derived from a single tumour/benign tissue pair (patient 46, triple negative tumour), for which we had well-matched samples in terms of epithelial cell numbers, to generate the initial dataset. In this first phase we found 110 proteins that were up-regulated by a factor of 2 or more in the TIF, some of which were confirmed by IHC. In the second phase, we carried out a systematic computer assisted analysis of the 2D gels of the remaining 68 TIF samples in order to identify TIF 46 up-regulated proteins that were deregulated in 90% or more of all the available TIFs, thus representing common breast cancer markers. This second phase singled out a set of 26 breast cancer markers, most of which were also identified by a complementary analysis using LC-MS/MS. The expression of calreticulin, cellular retinoic acid-binding protein II, chloride intracellular channel protein 1, EF-1-beta, galectin 1, peroxiredoxin-2, platelet-derived endothelial cell growth factor, protein disulfide isomerase and ubiquitin carboxyl-terminal hydrolase 5 were further validated using a tissue microarray containing 70 malignant breast carcinomas of various grades of atypia. A significant number of these proteins have already been detected in the blood/plasma/secretome by others. The next steps, which include biomarker prioritization based on the hierarchal evaluation of these markers, antibody and antigen development, assay development, analytical validation, and preliminary testing in the blood of healthy and breast cancer patients, are discussed.